Hypoxia-induced proteasomal degradation of DBC1 by SIAH2 in breast cancer progression

  1. Qiangqiang Liu
  2. Qian Luo
  3. Jianyu Feng
  4. Yanping Zhao
  5. Biao Ma
  6. Hongcheng Cheng
  7. Tian Zhao
  8. Hong Lei
  9. Chenglong Mu
  10. Linbo Chen
  11. Yuanyuan Meng
  12. Jiaojiao Zhang
  13. Yijia Long
  14. Jingyi Su
  15. Guo Chen
  16. Yanjun Li
  17. Gang Hu
  18. Xudong Liao
  19. Quan Chen
  20. Yushan Zhu  Is a corresponding author
  1. State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, Tianjin Key Laboratory of Protein Science, College of Life Sciences, Haihe Laboratory of Cell Ecosystem, Nankai University, China
  2. School of Statistics and Data Science, LPMC and KLMDASR, Nankai University, China

Abstract

DBC1 has been characterized as a key regulator of physiological and pathophysiological activities, such as DNA damage, senescence, and tumorigenesis. However, the mechanism by which the functional stability of DBC1 is regulated has yet to be elucidated. Here, we report that the ubiquitination-mediated degradation of DBC1 is regulated by the E3 ubiquitin ligase SIAH2 and deubiquitinase OTUD5 under hypoxic stress. Mechanistically, hypoxia promoted DBC1 to interact with SIAH2 but not OTUD5, resulting in the ubiquitination and subsequent degradation of DBC1 through the ubiquitin–proteasome pathway. SIAH2 knockout inhibited tumor cell proliferation and migration, which could be rescued by double knockout of SIAH2/CCAR2. Human tissue microarray analysis further revealed that the SIAH2/DBC1 axis was responsible for tumor progression under hypoxic stress. These findings define a key role of the hypoxia-mediated SIAH2-DBC1 pathway in the progression of human breast cancer and provide novel insights into the metastatic mechanism of breast cancer.

Editor's evaluation

This is a study with relatively convincing data on examining the dynamic regulation of hypoxia regulating SIAH2/OTUD5 interaction with DBC1 by regulating DBC1 stability. Therefore, DBC1, by regulating p53 signaling, would affect breast cancer phenotype in vivo.

https://doi.org/10.7554/eLife.81247.sa0

Introduction

The occurrence and development of tumors are modulated by the dual regulation of genetic instability and the tumor microenvironment (Singleton et al., 2021). Hypoxic stress or low oxygen tension, a major hallmark of the tumor microenvironment, plays an essential role in the progression and metastasis of many solid tumors (Cheng et al., 2020; Lee et al., 2019). Moreover, our previous studies have documented that hypoxic stress attenuates tumorigenesis and progression by modulating the Hippo signaling pathway and mitochondrial biogenesis (Ma et al., 2015; Ma et al., 2019). To extensively understand the critical roles of hypoxic stress in tumorigenesis or tumor development, more precise mechanisms need to be further explored.

Deleted in breast cancer 1 (DBC1; also known as CCAR2) is a nuclear protein containing multifunctional domains and plays a critical role in a variety of cancers. Importantly, DBC1 cooperates with lots of epigenetic and transcriptional factors to regulate cell activities. DBC1 mediates p53 function not only by inhibiting the deacetylase activity of SIRT1, but also by inhibition of p53 ubiquitination and degradation (Qin et al., 2015; Akande et al., 2019; Kim et al., 2008; Zhao et al., 2008). In addition, DBC1 can specifically inhibit deacetylase HDAC3 activity and alter its subcellular distribution, resulting in cell senescence (Chini et al., 2010). Most importantly, mice with a genetic deletion of CCAR2 exhibited more likely to spontaneously develop lung tumors, liver tumors, lymphomas, and teratomas and showed poor overall survival (Qin et al., 2015). Recently, the downregulation of DBC1 highly correlates with poor prognosis and distant metastatic relapse in breast, colon, and prostate cancer patients, and low levels of DBC1 determine tumor grade and metastasis (Won et al., 2015; Noguchi et al., 2014; Yu et al., 2013). Accumulating evidence has shown that DBC1 activity and quality of control play key roles in tumorigenicity, while the mechanisms by which DBC1 stability is regulated remain elusive.

Protein ubiquitination is one of the most-studied post-translational modifications and is critical and essential for protein stability, activity, localization, and biological function. Here, we delineated that the ubiquitination and stability of DBC1 were orchestrated by the E3 ubiquitin ligase SIAH2 and deubiquitinase OTUD5 under normoxic or hypoxic stress. Mechanistically, hypoxic stress promoted the interaction between DBC1 and SIAH2 and enhanced the disassociation of DBC1 from OTUD5, resulting in an increase in DBC1 ubiquitination and degradation, contributing to tumor cell proliferation and migration. Human tissue microarray analysis further revealed that the SIAH2/DBC1 axis was responsible for regulating tumor progression under hypoxic stress. Our findings provide novel insights into the metastatic mechanism of breast cancer and a promising therapeutic target for breast cancer.

Results

Hypoxic stress triggers the degradation of DBC1

Hypoxia is a common hallmark of solid tumors and contributes to the development and progression of many cancers (Lee et al., 2019). To investigate the effects of hypoxia on breast cancer cells, we first performed RNA-seq analysis of MDA-MB-231 cells in response to hypoxic stress. Differential expression analysis showed that 1151 genes were significantly upregulated and 310 genes were downregulated (adjusted p<0.05) under hypoxic stress (Figure 1A). Enrichment analysis of differentially expressed genes by Metascape suggested that the upregulated genes were related to the pathways of cell proliferation and cancer; in contrast, the downregulated genes were implicated in the DNA damage repair, senescence, SIRT1, and p53 signaling pathways (Figure 1B). To further investigate the mechanism by which hypoxia regulates the p53 signaling pathway, we examined p53 pathway activity by Western blotting and found that the stabilities of SIRT1 and p53 protein were not changed under hypoxia, but the acetylation of p53 was decreased (Figure 1C). Interestingly, we observed that the protein level of DBC1 gradually decreased with the duration of hypoxia (Figure 1D). In order to verify whether DBC1 protein level is involved in the HIF1α signaling pathway, we further analyzed DBC1 protein levels with HIF1α inhibitor under hypoxic conditions. The results showed that hypoxia-induced decrease in DBC1 protein level and p53 signaling pathway activity was not blocked by HIF1α inhibitor (Figure 1—figure supplement 1A). These results prove that HIF1α signaling pathway is not involved in hypoxia-induced decrease in DBC1. Under hypoxic conditions, the decrease in DBC1 protein level could be inhibited by the proteasome inhibitor MG132 (Figure 1E), but not the lysosomal inhibitor BA1 (Figure 1—figure supplement 1B and C), suggesting that hypoxia induced DBC1 degradation through the ubiquitin–proteasome system. In most cell lines derived from different subtypes of breast cancer or other cancers, DBC1 protein was degraded under hypoxia, suggesting the reduced stability of DBC1 was a general rule in hypoxic conditions (Figure 1F and Supplementary file 1), while the mRNA level of CCAR2 was not changed under hypoxia (Figure 1G and Supplementary file 1). Similarly, the RNA-seq datasets of CCAR2 knockout MDA-MB-231 cells showed that genes related to cell proliferation and migration were also upregulated, and genes associated with DNA repair and apoptosis were downregulated (Figure 1H and I, Figure 1—figure supplement 1D and E). Collectively, these results suggest that hypoxia and DBC1 degradation contribute to tumor progression, which suggests that hypoxia may regulate tumor progression by mediating DBC1 protein degradation.

Figure 1 with 1 supplement see all
Hypoxia induces DBC1 degradation.

(A) MDA-MB-231 cells were cultured under normoxia or hypoxia for 24 hr and then the total RNA was extracted from cells using a total RNA extraction kit. RNA-sequence analysis of gene expression and heatmap shows the differential transcriptomic expression. (B) Highlights of the enriched pathways from transcriptomic expression by Metascape. (C) MDA-MB-231 cells were exposed to hypoxia for the indicated time and then Western blotting analysis of the protein levels using the indicated antibodies. (D) MDA-MB-231 cells were exposed to hypoxia for the indicated time and then protein levels of DBC1 were detected by Western blotting. (E) MDA-MB-231 cells were exposed to normoxia or hypoxia for 24 hr, with or without MG132 (10 μM), and then the protein levels of DBC1 were detected by Western blotting. (F) The indicated cell lines were cultured under normoxia or hypoxia for 24 hr and then the protein level of DBC1 was detected by Western blotting. Mean ± SEM from three independent experiments, Student’s t-test, ns, not significant, **p<0.01, ***p<0.001. (G) MDA-MB-231 cells were cultured under normoxia or hypoxia for 24 hr. Cells were collected and lysed with RNA lysis buffer. The mRNA level of DBC1 was quantified by quantitative real-time PCR assay (data are the mean ± SEM of three experiments, Student’s t-test, ns, not significant). (H) Venn diagram showing the numbers of DBC1-regulated genes common to hypoxia target genes. (I) Heatmap showing the representatives of differentially regulated transcripts associated with tumor initiation and progression.

SIAH2 interacts with DBC1 and regulates its stability

To identify the E3 ligases that potentially ubiquitinates DBC1 to contribute to its degradation, several ubiquitin E3 ligases previously reported to be involved in the hypoxia response were screened (Figure 2A, Figure 2—figure supplement 1A), and SIAH2 was finally identified to be responsible for the stability of DBC1 (Figure 2B). To confirm our hypothesis, LC-MS/MS analysis of proteins bound to SIAH2RM (an SIAH2 enzyme-inactive mutant) was performed. DBC1 was validated as one of the substrates of SIAH2 (Supplementary file 1). To further explore the relationship between SIAH2 and DBC1, we carried out a co-immunoprecipitation (Co-IP) assay and found that exogenously expressed Flag-SIAH2RM and Myc-DBC1 were reciprocally co-immunoprecipitated (Figure 2C). Meanwhile, we validated the interaction between endogenous SIAH2 and DBC1 (Figure 2D, Figure 2—figure supplement 1B and C), and purified glutathione S-transferase (GST) SIAH2 was able to pull down His-DBC1 in vitro (Figure 2E), suggesting that DBC1 could directly interact with SIAH2. To identify the necessary domain of DBC1 responsible for interaction with SIAH2, we constructed several truncations of DBC1 and SIAH2 (Figure 2—figure supplement 1D and E), and the Co-IP assay showed that the 1–230 amino acids at the N-terminus of DBC1 were necessary for binding to SIAH2 (Figure 2F), and the full-length SIAH2 was required for their interaction (Figure 2G). Importantly, the N-terminus (1–461) of the DBC1 protein rather than the C-terminus (462–923) was pulled down by SIAH2 in vitro (Figure 2H and I). These results suggest that the N-terminus of DBC1 is crucial for its interaction with SIAH2. In line with the fact that SIAH2 acts as an E3 ligase, mediating substrate degradation by the ubiquitin–proteasome pathway, we found that SIAH2, rather than SIAH2RM, reduced the protein level of endogenous DBC1 in a dose-dependent manner (Figure 2J and M) and had no effect on the transcriptional level of DBC1 (Figure 2—figure supplement 1F and Supplementary file 1). The CHX chase assay showed that ectopic expression of wildtype SIAH2, but not SIAH2RM, promoted DBC1 degradation over time (Figure 2K and L and Supplementary file 1). Furthermore, the proteasome inhibitor MG132 completely reversed DBC1 destabilization (Figure 2N), whereas the lysosomal inhibitor bafilomycin A1 (BA1) had no such function (Figure 2—figure supplement 1G), suggesting that SIAH2 mediated DBC1 degradation through the proteasome pathway rather than lysosomes. These results reveal that SIAH2 promotes DBC1 degradation by directly interacting with DBC1.

Figure 2 with 1 supplement see all
SIAH2 interacts with DBC1 and regulates its stability.

(A) HeLa cells were transfected with Myc-DBC1 and several hypoxia-relative E3 ligases and cultured under normoxic conditions for 24 hr. The protein level of DBC1 was detected by Western blotting. (B) HeLa cells were transfected with several hypoxia-relative E3 ligases and cultured under hypoxic conditions for 24 hr. The protein level of DBC1 was detected by Western blotting. (C) HEK293T cells were transfected with Myc-DBC1 and Flag-SIAH2RM for 24 hr. Cells were collected for immunoprecipitation with anti-Flag or anti-Myc antibody. (D) MDA-MB-231 cells were cultured under hypoxia for 18 hr, then treated with 10 μM MG132 and incubated under normoxia or hypoxia for another 6 hr. Endogenous interactions between DBC1 and SIAH2 were analyzed by co-immunoprecipitation (Co-IP). (E) Purified GST and GST-tagged SIAH2 proteins were used for GST affinity isolation of His-DBC1 in vitro and blotted with an anti-DBC1 antibody. (F) HEK293T cells were co-transfected with full-length or truncated forms of Myc-DBC1 and Flag-SIAH2RM, and immunoprecipitation was performed with an anti-Flag antibody. Co-immunoprecipitated DBC1 and SIAH2 were detected by Western blotting with anti-Myc and anti-Flag antibodies, respectively. (G) Myc-DBC1 was co-transfected with full-length or truncated forms of Flag-SIAH2RM, and immunoprecipitation was performed with an anti-Myc antibody. Co-immunoprecipitated SIAH2 and DBC1 were detected by Western blotting with anti-Flag and anti-Myc antibodies, respectively. (H, I) GST pull-down analysis showing the direct interaction between bacterially expressed GST-SIAH2 and the N- or C-terminal half of His-DBC1 in vitro. (J) HeLa cells were transfected with Flag-SIAH2, Flag-SIAH2RM, or the empty Flag-vector for 24 hr and the cell lysates were subjected to Western blotting analysis of DBC1. (K) HeLa cells were transfected with Flag-SIAH2, Flag-SIAH2RM, or the empty Flag-vector for 24 hr. CHX (10 μM) was added for the indicated time, and the cell lysates were subjected to Western blotting analysis of DBC1. (L) Quantification of DBC1 protein level in (K) (mean ± SEM from three independent experiments, two-way ANOVA, ns, not significant, ***p<0.001). (M) HeLa cells were transfected with Flag-SIAH2 by quantitative gradient and then protein level of DBC1 was detected by Western blotting. (N) HeLa cells were transfected with Flag-SIAH2 for 24 hr and then treated with or without MG132 (10 μM) for 6 hr. The cell lysates were subjected to Western blotting analysis of DBC1.

SIAH2 is responsible for DBC1 ubiquitination and degradation under hypoxic stress

Next, we checked whether SIAH2 ubiquitinated DBC1, and the results showed that ectopic expression of SIAH2, but not SIAH2RM, dramatically increased the ubiquitination level of DBC1 (Figure 3A and B). Additionally, immunoprecipitation analysis proved that SIAH2 induced the polyubiquitination of DBC1 in the form of K48 conjugation (Figure 3—figure supplement 1A and B). In vitro ubiquitination assay further revealed that DBC1 was directly ubiquitinated by SIAH2 rather than the E3 ligase-dead mutant SIAH2RM (Figure 3C). To identify the sites of DBC1 ubiquitinated by SIAH2, we performed MS analysis, and the results showed that K287 of DBC1 was the potential site ubiquitinated by SIAH2 (Figure 3D). Next, we found that ectopic expression of SIAH2 did not increase the ubiquitination level of the K287R mutant of DBC1, and the mutant did not degrade (Figure 3E, Figure 3—figure supplement 1C and D). In conclusion, these results demonstrate that SIAH2 ubiquitinates DBC1 to mediate its degradation. To further understand the mechanism underlying hypoxia-induced DBC1 degradation, we examined whether SIAH2 was responsible for DBC1 ubiquitination and degradation in response to hypoxia. Our results showed that under hypoxic stress both SIAH2 deletion and K287R mutation of DBC1 failed to increase DBC1 ubiquitination (Figure 3F and G), and DBC1 degradation was also inhibited (Figure 3H–J, Figure 3—figure supplement 1E and F, and Supplementary file 1). Consistently, knockout of SIAH2 prolonged the half-life of DBC1 under hypoxia (Figure 3K and L, Figure 3—figure supplement 1F–H, and Supplementary file 1). It has been reported that under hypoxic conditions the regulation of SIAH2 was regulated by several mechanisms including induction of gene expression, interference translation, and formation of dimeric complexes. SIAH2 could be phosphorylated by kinases such as p38 and Src under hypoxic conditions, increasing its ubiquitin ligase activity and protein stability (Khurana et al., 2006). When cells were treated with doramapimod, an inhibitor of p38, under hypoxic conditions, we found that the degradation of DBC1 was partially blocked (Figure 3—figure supplement 1I). Moreover, we found that inhibition of p38 partially decreased SIAH2 protein level and inhibited the interaction between SIAH2 and DBC1 under hypoxia (Figure 3—figure supplement 1J). Therefore, hypoxia activates SIAH2 to interact with DBC1, which induces DBC1 degradation by ubiquitin–proteasome system to regulate DBC1 stability. Under hypoxic conditions, SIAH2 acts as an E3 ligase-related hypoxia to target substrate degradation. Taken together, these results demonstrate that hypoxia-induced DBC1 degradation is dependent on SIAH2-mediated DBC1 ubiquitination.

Figure 3 with 1 supplement see all
SIAH2 promotes DBC1 polyubiquitination and degradation under hypoxia.

(A) HEK293T cells were transfected with Myc-DBC1, HA-Ub, and Flag-SIAH2 or Flag-SIAH2RM for 24 hr and then treated with MG132 (10 μM) for 6 hr. Ubiquitylation assays were performed and the ubiquitylation level of DBC1 was detected using an anti-HA antibody. (B) The HEK293T cells with or without Flag-SIAH2 transfection were treated with MG132 (10 μM) for 6 hr; then the cell lysates were subjected to anti-HA immunoprecipitation, and the immunoprecipitated were analyzed by Western blot using anti-DBC1. (C) Ubiquitination of bacterially expressed His-DBC1 by purified SIAH2 but not by SIAH2RM in vitro. The reactions were performed either with purified ubiquitin, UBA1 (E1), UBCH7 (E2), and SIAH2 or its inactive mutant or in the absence of UBA1, UBCH7, or ubiquitin. (D) Mass spectrometry analysis identifies K287 of DBC1 as the site for SIAH2-induced ubiquitination. Ubiquitinated DBC1 was trypsin digested and analyzed by LC-MS/MS. The MS/MS mass spectrum of a ubiquitinated peptide is shown for peptide DBC1 279–291 containing ubiquitinated Lys-287. (E) HeLa cells were transfected with Myc-DBC1 or the Myc-DBC1 (K287R) mutant and Flag-SIAH2 or the empty Flag-vector for 24 hr. The protein level of DBC1 was detected using an anti-Myc antibody. (F) WT and SIAH2 knockout MDA-MB-231 cells were cultured under normoxia or hypoxia for 24 hr and then treated with MG132 (10 μM) for 6 hr. Cells were harvested, denatured, and lysed for immunoprecipitation with anti-DBC1 antibody. The ubiquitination level of DBC1 was assessed by immunoblotting with an anti-Ub antibody. (G) HeLa cells were transfected with Myc-DBC1 or the Myc-DBC1 (K287R) mutant and cultured under normoxia or hypoxia for 24 hr. Cells were harvested, denatured, and lysed for immunoprecipitation with anti-Myc antibody. The ubiquitination level of DBC1 was assessed by immunoblotting with an anti-Ub antibody. (H) WT and SIAH2 knockout MDA-MB-231 cells were exposed to hypoxia for the indicated time and then protein level of DBC1 was detected by Western blotting. (I) Quantification of DBC1 protein as indicated in (H) (mean ± SEM from three independent experiments, Student’s t-test, **p<0.01, ***p<0.001). (J) HeLa cells were transfected with Myc-DBC1 or the Myc-DBC1 (K287R) mutant and cultured under normoxia or hypoxia for 24 hr and then protein level of DBC1 was detected by Western blotting. (K) WT and SIAH2 knockout MDA-MB-231 cells was exposed to hypoxia for 24 hr, CHX (10 μM) was added for the indicated time, and the cell lysates were subjected to Western blotting analysis of DBC1. (L) Quantification of DBC1 protein levels in (K) (mean ± SEM from three independent experiments, Student’s t-test, *p<0.05, **p<0.01).

Figure 3—source data 1

SIAH2 promotes DBC1 polyubiquitination and degradation.

https://cdn.elifesciences.org/articles/81247/elife-81247-fig3-data1-v2.zip

OTUD5 regulates the deubiquitination and stability of DBC1

Strikingly, we also observed that the ubiquitination level of DBC1 was sharply decreased when returned to normal conditions after hypoxic stress (Figure 4A). Therefore, we screened the deubiquitinating enzymes (DUBs) plasmids library to identify the candidate responsible for deubiquitination of DBC1 (Figure 4—figure supplement 1A). Lots of interaction assays suggested that the potential DUB OTUD5 might interact with DBC1 (Figure 4—figure supplement 1A and B) and regulate its ubiquitination (Figure 4—figure supplement 1C). Co-IP analysis demonstrated the exogenous interaction between OTUD5 and DBC1 (Figure 4—figure supplement 1D and E). Furthermore, we confirmed that endogenous DBC1 could directly interact with OTUD5 (Figure 4B, Figure 4—figure supplement 1F), which was further verified by an in vitro pull-down assay using purified His-tagged DBC1 to pull down OTUD5 from cell lysates (Figure 4C, Figure 4—figure supplement 1G). We next tested whether DBC1 deubiquitination was dependent on OTUD5 enzyme activity. The ubiquitination assay showed that only ectopic expression of wildtype OTUD5 but not inactive mutant C224S led to DBC1 ubiquitination level decrease under hypoxia (Figure 4D). Consistently, hypoxia-induced endogenous DBC1 degradation was specifically inhibited by expression of wildtype OTUD5 rather than the inactive mutant (Figure 4E). Moreover, the CHX assay also confirmed that ectopic expression of wildtype OTUD5 obviously prolonged the half-life of DBC1 (Figure 4F and G and Supplementary file 1), indicating that deubiquitination of DBC1 was beneficial for its stability. Domain mapping analysis further revealed that the N-terminal region (amino acid residues 1–230) of DBC1, which binds with SIAH2, was also necessary for its interaction with OTUD5 (Figure 4H). Interestingly, we found that either hypoxia treatment or overexpression of SIAH2 promoted the interaction between DBC1 and SIAH2, but inhibited the interaction of DBC1 with OTUD5 (Figure 4I, Figure 4—figure supplement 1H). Overall, our results suggest that SIAH2 and OTUD5 substitutionally interact with DBC1 in response to changes in oxygen concentration (Figure 4J), cooperatively regulating reversible DBC1 ubiquitination and stability to orchestrate DBC1 function.

Figure 4 with 1 supplement see all
OTUD5 interacts with DBC1 and regulates its stability.

(A) MDA-MB-231 cells were cultured under normoxia or hypoxia for indicated time, then one group was recovered to normoxia for 6 hr, and then treated with MG132 (10 μM) for 6 hr. Cells were harvested, denatured, and lysed for immunoprecipitation with anti-DBC1 antibody. The ubiquitination level of DBC1 was assessed by immunoblotting with anti-Ub antibody. (B) MDA-MB-231 cells were collected for immunoprecipitation with anti-DBC1 antibody, and co-immunoprecipitated endogenous OTUD5 was detected by Western blotting with an anti-OTUD5 antibody. (C) Purified His-tagged DBC1 proteins were used for His affinity isolation of endogenous OTUD5 of MCF7 cells and blotted with an anti-OTUD5 antibody. (D) HeLa cells were transfected with Flag-OTUD5 or the Flag-OTUD5 (C224S) mutant and cultured under normoxia or hypoxia for 24 hr and then treated with MG132 (10 μM) for 6 hr. Cells were harvested, denatured, and lysed for immunoprecipitation with anti-DBC1 antibody. The ubiquitination level of DBC1 was assessed by immunoblotting with anti-Ub antibody. (E) HeLa cells were transfected with Flag-OTUD5 or the Flag-OTUD5 (C224S) mutant and cultured under normoxia or hypoxia for 24 hr and then protein level of DBC1 was detected by Western blotting. (F) HeLa cells were transfected with Flag-OTUD5 or the Flag-OTUD5 (C224S) mutant and exposed to hypoxia for 24 hr, CHX (10 μM) was added for the indicated time, and the cell lysates were subjected to Western blotting analysis of DBC1. (G) Quantification of DBC1 protein levels in (F) (mean ± SEM from three independent experiments, two-way ANOVA, *p<0.05, ***p<0.001). (H) HEK293T cells were co-transfected with full-length or truncated forms of Myc-DBC1 and Flag-OTUD5, and immunoprecipitation was performed with an anti-Flag antibody. Co-immunoprecipitated DBC1 and OTUD5 were detected by Western blotting with anti-Myc and anti-Flag antibodies, respectively. (I) The WT and SIAH2 knockout MDA-MB-231 cells were exposed to normoxia or hypoxia for 24 hr and then treated with MG132 (10 μM) for 6 hr. Immunoprecipitation was performed with an anti-DBC1 antibody. Co-immunoprecipitated endogenous SIAH2 and OTUD5 were detected by Western blotting with anti-SIAH2 and anti-OTUD5 antibodies, respectively. (J) Schematic model presenting the substitution interaction of SIAH2 and OTUD5 with DBC1 under hypoxia.

Hypoxia regulates tumor progression via the SIAH2-DBC1 axis

As suggested in Figure 1, hypoxia-induced DBC1 degradation might regulate pathways associated with tumor cell growth, such as SIRT1 and p53 signaling pathways. Therefore, we examined whether SIAH2-mediated DBC1 ubiquitination was responsible for tumor progression. Our results showed that knockdown of SIAH2, in different breast cancer cell lines, attenuated the reduction of p53 pathway activity under hypoxia (Figure 5A). In addition, deletion of SIAH2 promoted etoposide triggering cell apoptosis under hypoxia, which could be rescued by simultaneous knockout of CCAR2 (Figure 5B, Figure 5—figure supplement 1A). The clone formation assay further revealed that cell growth was suppressed when SIAH2 was deleted under hypoxia, whereas double knockout of SIAH2 and CCAR2 almost did not inhibit cell growth (Figure 5C, Figure 5—figure supplement 1B). Transwell and scratch assays also revealed that knockout of SIAH2 inhibited cell migration under hypoxia rather than double knockout of SIAH2 and CCAR2 (Figure 5D and E, Figure 5—figure supplement 1C and D). These results suggest that SIAH2 promotes cell growth, proliferation, and migration in response to hypoxia by ubiquitinating DBC1 to induce DBC1 degradation.

Figure 5 with 1 supplement see all
Hypoxia regulates tumor progression via the SIAH2-DBC1 axis.

(A) SIAH2 siRNA was transfected into indicated cell lines. The cells were cultured under normoxia or hypoxia for 24 hr and then cell lysates were analyzed by immunoblotting using the indicated antibodies. (B) Apoptosis assay analysis of wildtype, SIAH2 knockout, and SIAH2/CCAR2 double-knockout MDA-MB-231 cells under normoxia or hypoxia. (C) Colony formation analysis of wildtype, SIAH2 knockout, and SIAH2/CCAR2 double-knockout MDA-MB-231 cells under normoxia or hypoxia. Colony numbers were quantified. (D) Transwell analysis of wildtype, SIAH2 knockout, and SIAH2/CCAR2 double-knockout MDA-MB-231 cells under normoxia or hypoxia. (E) Scratching analysis of wildtype, SIAH2 knockout, and SIAH2/CCAR2 double-knockout MDA-MB-231 cells under normoxia or hypoxia. (F–H) Tumor images (F), tumor growth curves (G), and tumor weight (H) from mice subcutaneously injected with SIAH2 knockout or SIAH2/CCAR2 double-knockout MDA-MB-231 cells. (I) Immunohistochemical analysis of SIAH2 knockout and SIAH2/CCAR2 double-knockout xenograft tumor tissues with the indicated antibodies. Scale bars, 100 μm. (J) EdU proliferation analysis of different tumor cells isolated from SIAH2 knockout or SIAH2/CCAR2 double-knockout xenografts. Scale bars, 200 μm. (K) The percentage of EdU-positive cells from (J) was quantified. Data shown are representative of at least three independent experiments. Similar results were found in each experiment. All data are mean ± SEM; *p<0.05, **p<0.01, ***p<0.001. Statistical significance was analyzed by using the two-tailed unpaired Student’s t-test.

Figure 5—source data 1

Source data of Hypoxia regulates tumor progression via the SIAH2-DBC1 axis.

https://cdn.elifesciences.org/articles/81247/elife-81247-fig5-data1-v2.zip

To validate the effects of SIAH2-mediated DBC1 stability on tumorigenesis and tumor progression in vivo, we implanted SIAH2 knockout and SIAH2/CCAR2 double-knockout MDA-MB-231 cells into the mammary fat pads of BALB/c nude mice and then monitored tumor growth. The results showed that both tumor volume and tumor weight in the nude mice transplanted with SIAH2 knockout cells were decreased, whereas concurrent deficiency of SIAH2 and DBC1 restored tumor growth to a certain extent (Figure 5F–H). Immunohistochemical analysis revealed that the number of Ki67-positive proliferative cells in SIAH2 knockout-implanted tumors was decreased compared with that in both wildtype and SIAH2/CCAR2 double-knockout xenografts (Figure 5I). Furthermore, the results of EdU assay to detect the proliferation rate of tumor cells of different genotypes were consistent with immunohistochemical analysis. (Figure 5J and K). Collectively, these results demonstrate the critical role of the SIAH2-DBC1 axis in promoting tumor progression.

Correlation of SIAH2 and DBC1 expression with tumor progression in breast cancer

To evaluate whether the mechanism by which the SIAH2-DBC1 axis regulates tumor progression is relevant to human tumorigenesis and tumor progression. We analyzed RNA-sequencing data in TCGA (Cancer Genome Atlas) using TIMER, and the results demonstrated that the expression level of SIAH2 was significantly higher in most tumors than in adjacent normal tissues (Figure 6A). In particular, the expression of SIAH2 in breast cancers was higher than that in normal samples (Figure 6B). Analyzing the data from TCGA, we found that SIAH2 was positively correlated with tumor stage and number of lymph nodes, indicative of tumor malignancy (Figure 6C and D). To further explore the clinical relevance of SIAH2-mediated DBC1 degradation, we analyzed the expression of SIAH2 and DBC1 in breast cancer tissue microarrays of patients. The immunohistochemistry results showed that DBC1 and SIAH2 were negatively correlated in this cohort (Figure 6E and F, Figure 6—figure supplement 1A), coincident with our finding that DBC1 was the substrate of SIAH2. We also found that in human breast cancer tissue DBC1 expression was reduced in hypoxic regions (Figure 6G), and the downregulation of DBC1 was found to be negatively correlated with clinical stage and the percentage of the Ki67-positive cell population (Figure 6H and I and Supplementary file 2), further indicating that under pathological conditions SIAH2-mediated DBC1 ubiquitination and degradation are beneficial for tumor progression.

Figure 6 with 1 supplement see all
Correlation of SIAH2 and DBC1 expression with tumor progression in BRCA.

(A) SIAH2 expression level in different human cancers from TCGA data in TIMER. *p<0.05, **p<0.01, ***p<0.001. (B) Volcano plot analysis of SIAH2 DBC1 and OTUD5 expression levels in breast cancer. (C) Relative expression level of SIAH2 in tumor stage (stages 1, 2, 3, 4, or 5) from BRCA patients. (D) Relative expression level of SIAH2 in nodal metastasis status (normal, N0, or N1) from BRCA patients. (E) Immunohistochemistry staining analysis of the expression levels of SIAH2 and DBC1 in a series of breast cancer patient tissue microarrays. Scale bars, (left) 200 μm; (right) 100 μm. (F) Heatmap of the expression levels of SIAH2 and DBC1 in human normal breast tissues and breast tumor tissues. (G) Human breast cancer tissues were stained with DAPI (blue) together with anti-CAIX (green) and anti-DBC1 (red) antibodies. Scale bars, 50 μm. (H) Statistical analysis of correlations between DBC1 expression level and clinical T stage. (I) Statistical analysis of correlations between DBC1 expression level and Ki67-positive stage.

Discussion

It has been documented that DBC1, a specific nuclear protein containing multifunctional domains, participates in the positive and negative regulation of multiple signaling pathways. Several findings have suggested that DBC1 acts as a natural and endogenous inhibitor of SIRT1, and DBC1 deletion increases the SIRT1-p53 interaction and represses p53 transcriptional activity to inhibit apoptosis and promote tumorigenesis (Kim et al., 2008; Zhao et al., 2008; Noh et al., 2013; Qin et al., 2015; Akande et al., 2019). Given the importance of DBC1 function, the regulatory mechanisms by which DBC1 protein stability is regulated remain unclear. Here, we showed that the protein level of DBC1 was degraded under hypoxic stress, which was regulated by the E3 ubiquitin ligase SIAH2 and deubiquitinase OTUD5. Additionally, knockout of SIAH2 promoted apoptosis and reduced cell migration and tumor proliferation, whereas double knockout of CCAR2 and SIAH2 partially rescued cell proliferation and tumorigenesis. Importantly, DBC1 is negatively correlated with SIAH2 expression levels in human breast tumors, suggesting that the SIAH2–DBC1 axis pathway may play a key role in human breast cancer. These results provide novel insights into the metastatic mechanisms of human breast cancer.

An abundance of evidence has shown that SIAH2 mediates the ubiquitination and degradation of substrates, including PI3K, LATS2, Spry2, ACK1, and TYK2 (Chan et al., 2017; Ma et al., 2016; Buchwald et al., 2013; Nadeau et al., 2007; Müller et al., 2014), in response to hypoxic stress to modulate multiple signaling pathways, such as the Hippo pathway, Ras signaling pathway, and STAT3 pathway. In general, DBC1 activity is regulated by multiple post-translational modifications, including phosphorylation (Magni et al., 2015; Zannini et al., 2012), acetylation (Zheng et al., 2013; Rajendran et al., 2019) and sumoylation (Park et al., 2014). However, it remains unclear whether DBC1 function can be regulated by ubiquitination modification. Our group demonstrated for the first time that SIAH2 can also ubiquitinate DBC1 at Lys287 by binding to the N-terminus of DBC1, resulting in DBC1 degradation by the ubiquitin–proteasome pathway, and that deletion of SIAH2 will block DBC1 degradation in response to hypoxic stress. Collectively, we identify a novel mechanism by which SIAH2 regulates DBC1 protein stability in response to hypoxic stress, contributing to tumorigenesis and tumor progression.

It has been reported that DBC1 cooperates with SIRT1 to mediate different physiological functions within mammalian cells. For example, stimulation of DBC1 transcription inhibits SIRT1 activity, contributing to TGF-β-induced epithelial–mesenchymal transition (Chen et al., 2021). Additionally, SIRT7 represses DBC1 transcription to promote thyroid tumorigenesis by binding to the promoter of DBC1 (Li et al., 2019). Recently, DBC1 was found to play a role in upregulating glucose homeostasis-related genes, which are implicated in type 2 diabetes pathogenesis (Basu et al., 2020). Strikingly, our findings reveal that SIAH2-mediated DBC1 ubiquitination under hypoxia regulates cell proliferation and tumorigenesis. We also found that the decrease in p53 acetylation was accompanied by DBC1 degradation in hypoxia zone of breast tumor.

In general, ubiquitination is a dynamic and reversible process cooperatively regulated by E3 ligases and DUBs (Li and Reverter, 2021). In this study, we identified that the deubiquitinase OTUD5 could specifically cleave the polyubiquitin chains of DBC1 once hypoxic stress was removed. If OTUD5 was overexpressed under hypoxia, the ubiquitination and degradation of DBC1 would be inhibited. Interestingly, we further confirmed that SIAH2 and OTUD5 competitively bind to DBC1 at the same N-terminal region, and hypoxia promotes the interaction of DBC1 with SIAH2 rather than OTUD5, resulting in ubiquitination and degradation of DBC1 to promote tumor progression. It is well known that OTUD5 controls cell survival and cell proliferation by deubiquitinating substrates (Zhang et al., 2021; Guo et al., 2021; Cho et al., 2021; Li et al., 2020; de Vivo et al., 2019; Park et al., 2015; Luo et al., 2013; Kayagaki et al., 2007). Based on our findings and others’, we speculate that the activation of OTUD5-mediated DBC1 deubiquitination may suppress tumor growth, which may provide a novel target for clinical tumor therapy. Moreover, we still need to further investigate the details of how the OTUD5-DBC1 complex dissociates under hypoxia to modulate DBC1 stability. There are also some limitations in the study; as we have shown that DBC1 reduction only takes place in the hypoxic regions in a tumor, the tumor microenvironment could have more factors besides hypoxia stress. However, the tumor microenvironment could have more factors besides hypoxia stress. In addition, the expression changes of SIAH2 and OTUD5 under hypoxia require more studies to explain.

Taken together, our study revealed that hypoxia stimulates SIAH2 to ubiquitinate DBC1 and inhibit OTUD5-mediated DBC1 deubiquitination, resulting in DBC1 degradation through the ubiquitin–proteasome pathway. Our results further address the importance of the SIAH2-DBC1 axis in promoting tumor cell survival and migration. In conclusion, we uncovered a complete and detailed dynamic regulatory mechanism by which DBC1 protein ubiquitination and stability are regulated. It is of great significance to deeply understand the function of SIAH2 and DBC1 and the role of hypoxia in regulating tumorigenesis and tumor progression, which provides a solid theoretical basis for cancer treatment.

Materials and methods

Construction of plasmids

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The expression plasmids for human SIAH2, DBC1, OTUD5, and ubiquitin were generated by amplifying the corresponding cDNA by PCR and cloning it into pcDNA4-TO-Myc-His-B, pCMV-3xFLAG, pEGFP-C1, pRK5-HA, pGEX4T1, or PET28a expression vectors. Site-specific mutants and special domain deletion mutants were generated using TransStart FastPfu DNA Polymerase (Transgene, Cat# AP221-11) according to the manufacturer’s protocols.

Cell culture and transfection

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HEK293T cells, HeLa cells, MDA-MB-231 cells, MCF7 cells, SH-SY5Y cells, U2OS cells, SW480 cells, HCT116 cells, PC3 cells, and HepG2 cells were sourced from ATCC, maintained Mycoplasma-negative culture, and cells were regularly tested for Mycoplasma contamination. Cells were cultured in GIBCO Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% fetal bovine serum (FBS, Lanzhou Bailing) and 100 units/mL penicillin and 100 mg/mL streptomycin in a 5% CO2 incubator at 37°C. All cells were cultured in an atmosphere of 5% CO2 at 37°C, and hypoxia was induced by culturing cells in a hypoxia chamber (Billups-Rothenberg) flushed with a mixed gas of 1% O2, 5% CO2, and 94% N2. For HeLa and HEK293T cells, plasmids were transfected with polyethyleneimine (PEI; Polysciences, Cat# 23966) according to the manufacturer’s protocols. For MDA-MB-231 and MCF7 cells, plasmids were transfected with Lipofectamine 3000 (Invitrogen, Cat# L3000015) according to the manufacturer’s instructions.

CRISPR/Cas9-mediated gene knockout

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To generate SIAH2- and DBC1- knockout MDA-MB-231 and MCF7 cells, oligonucleotides were cloned into LentiCRISPR. The backbone plasmid was co-transfected with lentiviral packaging plasmids psPAX2 and pMD2.G for lentivirus production. The oligonucleotide pair used was as follows:

SIAH2 (F: 5′-CACCGGCTGCAGGGTTTATTAGCGC-3′ and R: 5′-AAAC GCGCTAATAAACCCTGCAGC C-3′), CCAR2 (F: 5′-CACCG TGGTTTGCTCACTCCTCCTG-3′ and R: 5′-AAAC CAGGAGGAGTGAGCAAACCA C-3′). Knockout of the respective genes was further confirmed by sequencing the edited genomic regions after PCR. The loss of the protein was verified by Western blotting.

Co-immunoprecipitation and pull-down assay

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After the described treatment, cells were collected and lysed in 0.8 mL IP lysis buffer (150 mM NaCl, 20 mM Tris, pH 7.4, 1 mM EGTA, 1 mM EDTA, 1% NP-40, 10% glycerol) containing protease inhibitors (1:100, Roche) for 45 min on a rotor at 4°C. After centrifugation at 12,000 × g for 10 min, the supernatant was immunoprecipitated with 1.5 µg of specific antibodies overnight at 4°C. Protein A/G agarose beads (15–30 µL, Santa Cruz) were washed and then added for another 2 hr. The precipitants were washed seven times with wash buffer, and the immune complexes were boiled with loading buffer and analyzed. GST-SIAH2 and His-DBC1 proteins were generated in Escherichia coli and incubated in vitro overnight. Then, 25 µL GST beads (GE Healthcare) were added to the system for 2 hr on a rotor at 4°C.

Immunoprecipitation and mass spectrometric analysis of SIAH2-associated proteins

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Twelve 10 cm dishes of HEK293T cells were transiently transfected with Flag–SIAH2RM. Then, 24 hr later, cells were collected and lysed in lysis buffer followed by immunoprecipitation with anti-Flag antibody overnight at 4°C. The precipitants were extensively washed with lysis buffer and then boiled with SDS loading buffer and subjected to SDS–PAGE. Gels with total proteins were excised, followed by in-gel digestion and analysis by LC-MS/MS.

Ubiquitination assay

In vivo ubiquitination assays

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Cells were transiently transfected with plasmids expressing HA-ubiquitin or special site mutations and Myc-DBC1 together with Flag-SIAH2 or Flag-SIAH2RM 24 hr after transfection. Cells were treated with 10 µM MG132 (Selleck, S2619) for 6 hr before collection. Cells were washed with cold PBS and then lysed in 200 µL of denaturing buffer (150 mM Tris-HCl, pH 7.4, 1% SDS) by sonication and boiling for 15 min. Lysates were made up to 1 mL with regular lysis buffer and immunoprecipitated with 2 µg anti-c-Myc antibody at 4°C overnight, washed three times with cold lysis buffer, and then analyzed by SDS–PAGE. For the DBC1 endogenous ubiquitination assay, cells were treated with 10 µM MG132 for 6 hr before collection. Lysates were immunoprecipitated using 2 µg anti-Ub antibody or anti-DBC1 antibody and subjected to ubiquitination analysis by Western blotting with anti-DBC1 or anti-ubiquitin antibody. In vitro ubiquitination assays were carried out in ubiquitination buffer (50 mM Tris, pH 7.4, 5 mM MgCl2, 2 mM dithiothreitol) with human recombinant E1 (100 ng, Upstate), human recombinant E2 UbcH5c (200 ng, Upstate), and His-tagged ubiquitin (10 µg, Upstate). GST-SIAH2, GST-SIAH2RM, and His-DBC1 were expressed and purified from E. coli BL21 cells. Also, 2 µg of GST, GST-SIAH2, or GST-SIAH2RM protein was used in the corresponding ubiquitination reactions. Reactions (total volume 30 µL) were incubated at 37°C for 2 hr and subjected to ubiquitination analysis by Western blotting using anti-DBC1 antibody.

Western blotting

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Cells were collected and washed with PBS and then lysed in 1% SDS lysis buffer or NP-40 lysis buffer (150 mM NaCl, 20 mM Tris, pH 7.4, 1 mM EGTA, 1 mM EDTA, 1% NP-40, 10% glycerol) containing protease inhibitors (1:100, Roche) for 45 min on a rotor at 4°C. After centrifugation at 12,000 × g for 10 min, the supernatant was boiled with loading buffer. Cell lysates containing equivalent protein quantities were subjected to 6 or 10% SDS–PAGE, transferred to nitrocellulose membranes, and then incubated with 5% milk for 2 hr at room temperature. Then, the membranes were probed with related primary antibodies at 4°C, followed by the appropriate HRP-conjugated secondary antibodies (KPL). Immunoreactive bands were checked with a chemiluminescence kit (En-green Biosystem) and visualized with a chemiluminescence imager (JUNYI). The following antibodies were used: Flag-M2 (1:2000, Sigma), Myc (1:1000, Santa Cruz Biotechnology), HA (1:1000, Santa Cruz Biotechnology), GFP (1:1000, Santa Cruz Biotechnology), His (1:1000, Santa Cruz Biotechnology), GST (1:1000, Santa Cruz Biotechnology), anti-ACTIN (1:10,000, Sigma), anti-mono- and polyubiquitinated conjugate monoclonal antibodies (FK2) (1:1000, Enzo Life Sciences), SIAH2 (1:500 Proteintech), OTUD5 (1:1000 Proteintech and CST), DBC1 (1:1000 Proteintech, CST, and Abcam), SIRT1 (1:1000 Abcam), p53 (1:1000 Abcam), acetylated-K382-p53 (1:1000 Abcam), HIF1α (1:1000 Proteintech), and GSK3β (1:1000 Proteintech).

Immunofluorescence microscopy

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Cells were fixed with 4% paraformaldehyde (Dingguo Changsheng Biotechnology) at 37°C for 30 min, then permeabilized with 0.2% Triton X-100 (Shanghai Sangon Biotech, TB0198) at 4°C for 10 min. After blocking in goat serum for 2 hr, cells were incubated with the indicated antibodies for 2 hr at room temperature or overnight at 4°C, washed with 0.05% Triton X-100, and stained with FITC- or CY5-conjugated secondary antibodies (Invitrogen) for 1 hr at room temperature. Cell images were captured with TCS SP5 Leica confocal microscope. The following antibodies were used: CAIX (1:100, Proteintech, 66243-1-Ig); DBC1 (1:1000, CST, 5693); and DAPI (300 nM, Invitrogen, D21490).

Flow cytometry

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After the described treatment, cells were collected and washed twice with prewarmed FBS-free DMEM and then stained with PI and Annexin V (Thermo Fisher) for 20 min at 37°C. After staining, cells were washed twice with prewarmed PBS for analysis with a flow cytometer (BD Calibur).

RNA extraction and quantitative real-time PCR assay

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RNA samples were extracted with TRIzol reagent (Sigma T9424), reverse transcription PCR was performed with a Reverse Transcriptase kit (Promega A3803), and real-time PCR was performed using Powerup SYBR Green PCR master mix (A25743) and a Step-One Plus real-time PCR machine (Applied Biosystems). Human actin expression was used for normalization. Quantitative real-time PCR assay (data are the mean ± SEM of three experiments, ns means not significant, *p<0.05, **p<0.01, ***p<0.001).

RNA-sequencing analysis

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RNA was extracted in biological triplicates using the miRNeasy Mini kit (QIAGEN) according to the manufacturer’s instructions. RNA degradation and contamination were monitored on 1% agarose gels. RNA purity was checked using a NanoPhotometer spectrophotometer (Implen, CA). RNA integrity was assessed using the RNA Nano 6000 Assay Kit of the Bioanalyzer 2100 system (Agilent Technologies, CA). RNA quality control was performed using a fragment analyzer and standard or high-sensitivity RNA analysis kits (Labgene; DNF-471-0500 or DNF-472-0500). RNA concentrations were measured using the Quanti-iTTM RiboGreen RNA assay Kit (Life Technologies/Thermo Fisher Scientific). A total of 1000 ng of RNA was utilized for library preparation with the NEBNext Ultra RNA Library Prep Kit for Illumina (NEB, USA) following the manufacturer’s recommendations, and index codes were added to attribute sequences to each sample. Poly-A + RNA was sequenced with a HiSeq SBS Kit v4 (Illumina) on an Illumina HiSeq 2500 using protocols defined by the manufacturer.

Raw data (raw reads) in fastq format were first processed through in-house Perl scripts. In this step, clean data (clean reads) were obtained by removing reads containing adapters, reads containing poly-N and low-quality reads from raw data. At the same time, the Q20, Q30, and GC contents of the clean data were calculated. All downstream analyses were based on clean data with high quality. Reference genome and gene model annotation files were downloaded from the genome website directly. The index of the reference genome was built using Hisat2 v2.2.1, and paired-end clean reads were aligned to the reference genome using Hisat2 v2.2.1. We selected Hisat2 as the mapping tool because Hisat2 can generate a database of splice junctions based on the gene model annotation file and thus a better mapping result than other nonsplice mapping tools. The mapped reads of each sample were assembled by StringTie (v2.1.4) (Mihaela Pertea et al. 2015) in a reference-based approach. StringTie uses a novel network flow algorithm as well as an optional de novo assembly step to assemble and quantitate full-length transcripts representing multiple splice variants for each gene locus. Differential expression analysis of two conditions/groups (two biological replicates per condition) was performed using the DESeq2 R package (1.30.1). DESeq2 provides statistical routines for determining differential expression in digital gene expression data using a model based on the negative binomial distribution. The resulting p-values were adjusted using Benjamini–Hochberg’s approach for controlling the false discovery rate. Genes with an adjusted p-value of 0.05 and absolute log2FoldChange of 0.5 were set as the threshold for significantly differential expression. Sequencing data have been deposited in GEO under accession codes GSE193133.

Colony formation assay

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MDA-MB-231 and MCF7 cells were serum-starved for 24 hr, and 500 cells/well were seeded on 6-well plate in triplicate. Cells were cultured under normoxia or hypoxia and incubated until formatted 50 cells by colony (approximately 10–15 days). Then, colonies were also dyed using crystal violet and the number of colonies was counted by using the software ImageJ.

Transwell assay

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MDA-MB-231 and MCF7 cells were serum-starved for 24 hr, and 5 × 104 cells were seeded on 24-well plate of 8.0 μm pore-size diameter polycarbonate (PC) membrane transwell inserts (Corning, Cat#3422, USA). After 24 hr, the non-migrated cells were removed from the insert with a cotton swab. The migrated cells were fixed for 10 min in 3.7% (v/v) formaldehyde in PBS before staining with 0.1% crystal violet for 15 min, followed by washing with PBS. Images were taken and the crystal violet-stained cells were counted.

Scratch/wound healing assay

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MDA-MB-231 and MCF7 cells were plated to confluence in 6-well culture plates containing DMEM medium (with 1% FBS and 1% penicillin/streptomycin). Using a 10 μL pipette tip, three horizontal scratches were made across the diameter of the well. In addition, on the bottom/back of each well, a line perpendicular to the scratches was drawn with a permanent marker. The monolayer was washed one time with PBS to remove any floating cells generated by the scratching process and fresh media applied. Using an inverted microscope, photo at the intersection of each cell scratch and the line on the bottom of the plate were captured immediately (six images per well) and used as a reference point for the 24 hr time point to determine percentage scratch coverage.

Xenograft tumorigenesis study

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All mouse experiments were approved by the Institutional Animal Care and Use Committee (2022-SYDWLL-000353) at the College of Life Sciences at Nankai University. MDA-MB-231 breast cancer cells (1 × 106 in 200 μL PBS) were injected subcutaneously into the armpit of 6- to 8-week-old female BALB/c nude mice. Tumor size was measured every 3–5 days 1 week after the implantation, and tumor volume was also analyzed by using the formula V = 0.5 × L × W2 (V, volume; L, length; W, width). The mice were then sacrificed, and the subcutaneous tumors were surgically removed, weighed, and photographed. No statistical method was used to predetermine the sample size for each group. The experiments were not randomized.

Tissue microarrays and immunohistochemistry

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The breast cancer tissue microarrays were purchased from US Biomax. These tissue microarrays consisted of 100 analyzable cases of invasive breast carcinoma and 10 analyzable cases of normal breast tissue. For antigen retrieval, the slides were rehydrated and then treated with 10 mM sodium citrate buffer (pH 6.0) heated for 3 min under pressure. The samples were treated with 3% H2O2 for 15 min to block endogenous peroxidase activity and then blocked with 5% goat serum for 1 hr at room temperature. Then, the tissues were incubated with the indicated antibodies at 4°C overnight, followed by incubation with HRP-conjugated secondary antibody for 1 hr at room temperature. Immunoreactive signals were visualized with a DAB Substrate Kit (MaiXin Bio). Protein expression levels in all the samples were scored on a scale of four grades (negative, +, ++, +++) according to the percentage of immunopositive cells and immunostaining intensity. The χ2 test was used for analysis of statistical significance. The following antibodies were used for immunohistochemistry: Ki67 (1:200, Abcam, Cat# ab16667, RRID:AB_302459), SIAH2 (1:40, Novus Biologicals, NB110-88113), and DBC1 (1:100, Proteintech, 22638-1-AP).

Quantification and statistical analysis

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For quantitative analyses of Western blots, real-time PCR results, flow cytometry data, or cell numbers, values were obtained from three independent experiments. The quantitative data are presented as the means ± SEM. Student’s t-test was performed to assess whether significant differences existed between groups. Multiple comparisons were performed with one-way ANOVA and Tukey’s post-hoc test. For correlations between DBC1 protein level and clinical T stage and Ki67 staining intensity in clinical samples, statistical significance was determined using the χ2 test. p-Values <0.05 were considered statistically significant. The significance level is presented as *p<0.05, **p<0.01, and ***p<0.001. ‘ns’ indicates that no significant difference was found. All analyses were performed using Prism 8.0 (GraphPad Software, Inc, La Jolla, CA).

Data availability

Sequencing data have been deposited in GEO under accession codes GSE193133. All data generated or analysed during this study are included in the manuscript and supporting file; Source Data files have been provided for Figures 1-6 and Figure S1-5.

The following data sets were generated
    1. Qiangqiang Liu
    2. Yanping Zhao
    (2022) NCBI Gene Expression Omnibus
    ID GSE193133. Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and CCAR2-/- MDA-MB-231 cells Transcriptomes: Liu Q, 2021.

References

    1. Won KY
    2. Cho H
    3. Kim GY
    4. Lim SJ
    5. Bae GE
    6. Lim JU
    7. Sung JY
    8. Park YK
    9. Kim YW
    10. Lee J
    (2015)
    High DBC1 (CCAR2) expression in gallbladder carcinoma is associated with favorable clinicopathological factors
    International Journal of Clinical and Experimental Pathology 8:11440–11445.

Decision letter

  1. Qing Zhang
    Reviewing Editor; University of Texas Southwestern Medical Center, United States
  2. Richard M White
    Senior Editor; Memorial Sloan Kettering Cancer Center, United States
  3. Qing Zhang
    Reviewer; University of Texas Southwestern Medical Center, United States
  4. Paul Grevitt
    Reviewer; Barts Cancer Institute, Queen Mary University of London, United Kingdom

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Decision letter after peer review:

[Editors’ note: the authors submitted for reconsideration following the decision after peer review. What follows is the decision letter after the first round of review.]

Thank you for submitting the paper "Hypoxia Dynamically Regulates DBC1 Ubiquitination and Stability by SIAH2 and OTUD5 in Breast Cancer Progression" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by a Senior Editor.

Unfortunately, numerous significant concerns were raised by each of the 3 reviewers. In considering the sum total of their comments, we are sorry to say that, after consultation with the reviewers, we have decided that this work will not be considered further for publication by eLife. The full details are provided below, but the reviewers raised significant concerns about the exact characterization of DBC1 signaling in breast cancer, the underlying mechanism by which hypoxia regulates this signaling axis and the physiological relevance of findings in breast cancer patients. Without a higher level of enthusiasm, we do not feel this paper would fare well during additional rounds of review at eLife. We hope these comments are useful to you as you consider your next steps for this manuscript.

Reviewer #1 (Recommendations for the authors):

This study, in general, provides the compelling biochemistry and functional data on examining how SIAH2/OTUD5 may regulate DBC1 protein stability in breast cancer under hypoxia. As a result of DBC1 downregulation of hypoxia, breast cancer may display more malignant phenotype. The study is well designed. However, there are a few things that need to be addressed as suggested below:

1. The functional role of DBC1 in breast cancer needs to be characterized in details. For example, the expression of DBC1 in different subtypes of breast cancer. The phenotype of DBC1 overexpression and KO in breast cancer needs to be characterized in details.

2. Throughout the study, two main cell lines are used Hela and MDA-MB-231. Hela cells may display diminished p53 protein due to HPV expression while MDA-MB-231 cells contain mutant p53. It is unclear whether Hypoxia, by downregulating DBC1 level, would lead to further decrease of p53 activity in these cells. This would need to be clarified and reconciled. In addition, some other breast cancer cell lines with WT p53 (at least from in vitro) would need to be added to further strengthen the conclusion.

3. The molecular mechanism by which hypoxia regulates SIAH2/OTUD5 interaction with DBC1 needs more detailed analysis and discussion. Is HIF involved in this process?

Reviewer #2 (Recommendations for the authors):

This study reports on the control of DCB1 by the ubiquitin ligase Siah2 under hypoxia growth conditions in breast cancer, while the deubiquitinating enzyme OTUD5 limits DCB1 ubiquitination and thereby prolongs its stability under normoxia.

The following are some of the key points raised for authors considerations:

It is unclear what underlies the control of DCB1 stability under hypoxia (and not under other conditions).

It would be important to determine what is the physiological significance of DCB1 loss under hypoxia for breast cancer cells.

This work focuses on breast cancer, and it is necessary to better establish relevance in numerous breast cancer (all types?) as opposed to other tumor types.

The authors claim for dynamic regulation of DCB1 stability, but it is unclear what determines the dynamics.

Experiments are performed largely under one condition and not another; complementing the assessment for hypoxia with normoxia conditions and vice versa is needed for number of studies shown.

In this study, Liu et al. report on post-translational regulation of DBC1 by the ubiquitin ligase Siah2 and the DUB OTUD5, which occurs during hypoxia. The separate roles of Siah2 and DBC1 in tumor progression have been shown in previous publications. Here the authors define the role of Siah2 in regulating DBC1 stability in breast cancer cells during hypoxia. While interesting, several points need to be experimentally addressed before further evaluation of this study as a candidate for publication in eLife should take place.

– Why is Siah2 more effective in degrading DBC1 under hypoxia? The title and elsewhere in this manuscript authors claims for dynamic regulation of DBC1 stability. What underlies this dynamic regulation?

– The work suggests that the Siah2 effect on DBC1 occurs in breast cancer cells, but most of the data is based on studies performed in either 293 or HeLa cells. Work on breast cancer lines is primarily limited to a single cell line.

– Are the effects reported here also seen in breast cancer patients?

– Much of the data relies on overexpression. Authors ought to demonstrate changes in endogenous proteins and their physiological relevance (when does it happen and why).

– OTUD5 is shown to regulate DBC1 under normoxic (and not hypoxic?) conditions. Why?

– All figure legends and Results sections lack details. It is not clear how the experiments were carried out.

Additional comments:

Figure 1: the authors assess the overlap of differentially expressed genes between hypoxia and DBC1 deletion (in normoxia). DEG needs to be compared under the same (hypoxic) conditions. Can overexpression of DBC1 rescue phenotypes be seen under hypoxia?

Figure 2A: the authors overexpress several E3 ubiquitin ligases to determine possible candidates responsible for DBC1 protein degradation. However, the level of expression of each E3 ligase (mRNA level) is missing, making it difficult to compare the efficiency of each E3 ligase in degrading DBC1. HUWE1 also seems to be as efficient as Siah2 in degrading DBC1, but it is not mentioned in the Results section. Why? The experiment is carried out in normoxia rather than hypoxia; why? Does any UBL tested exhibit different efficiency for DBC1 interaction and degradation under hypoxia?

Figure 3: The authors should demonstrate, experimentally, why Siah2 dependent degradation of DBC1 is primarily claimed to be under hypoxia.

Figure 3H: the authors compared DBC1 protein levels in WT and Siah2 KO cells using MDA-MB-231 cells. It would be informative to compare the level of DBC1 between WT and Siah2 KO in the same Western and demonstrate possible changes in the level of DBC1 under normoxia. Additional breast cancer cell lines (and non-transformed breast cultures) should be studied.

Figure 3K: It would be informative to perform CHX chase under normoxia, compared with CHX done under hypoxia. These assessments need to be extended to include additional breast cancer cell lines.

Figure 4: the authors should study OTUD5 binding to DBC1 under hypoxia compared with normoxia to substantiate the claim for preferred interaction under normoxia. Does OTUD5 expression change in breast cancer patients, compared to healthy donors or between cancerous and normal tissues? Does it correlate with patient survival? The screening of DUBS to identify the candidate responsible for deubiquitination of DBC1 is not clear. Sup Figure 4 A shows the level of expression of the different DUBS but does not reveal why the authors chose to focus on OTUD5.

Figure4I: the authors should add Siah2 KO cells to their analysis; it is important to determine whether OTUD5 and Siah2 compete for binding to DBC1.

Figure 5B, D, F: the authors should address whether Siah2 KO can promote apoptosis, colony formation assay, and invasion under normoxia, not only in hypoxia.

Figure 5M: the authors should check for possible changes in apoptosis, in addition to shown data for proliferation.

All figure legends and Results sections lack details. It is not clear how the experiments were carried out. (for example, Figure 1A: how long were the cells kept in hypoxia when RNAseq was performed? The authors should define the conditions used to reach hypoxia in the results and Figure legends. Condition of 1% O2 is briefly noted in the Methods section, but not in results or legends.

Reviewer #3 (Recommendations for the authors):

The authors sought to identify how the breast cancer tumour suppressor DBC1 (CCAR2) is post-translationally regulated. This came from transcriptomic analysis of MB231 cells in hypoxia revealed decreased SIRT1 activity, without changes in protein levels. Instead known regulator DBC1 displayed reduced protein expression in hypoxia with no changes in mRNA. Through targeted screen of hypoxia associated E3 ligases and IP-MS of SIAH2, the authors identify interaction between DBC1 and SIAH2. They comprehensively map the interaction between DBC1 and SIAH2 and identify the residue ubiquitinated. Upon 6h of reoxygenation the ubiquitination of DBC1 is decreased. OTUD5 was identified as the DUB that deubiquitinates DBC1. The authors propose that in normoxia, OTUD5 is bound to DBC1 which is displaced by SIAH2 upon activation by hypoxia, however despite the comprehensive study of the interaction between DBC1 this is not fully supported by the data. SIAH2 Knockout reduced colony formation, cell migration and growth in a xenograft tumour model which could all be partially rescued by knockout of DBC1. SIAH2 expression was elevated in breast cancer and correlated with cancer stage. Through staining of a TMA the authors suggest a negative correlation between DBC1 and SIAH2 protein expression however this is not immediately clear as the data is currently presented, furthermore this expression has been correlated with proliferation markers, whereas markers of hypoxia score would be more informative for the proposed mechanism.

The interaction studies are convincing and well performed. One particular strength of the manuscript is the use of enzymatic dead mutants as further negative controls. Furthermore, each interaction is interrogated in depth with exogenous mapping, direct binding assays and endogenous IPs. Some aspects of the manuscript lack detail, particularly the figure legends making interpretation of data difficult at times and would certainly aid readers looking to replicate this data if these are more detailed. Whilst the ubiquitination of DCB1 and subsequent deubiquitination by OTUD5 is clear, the hypothesis that hypoxia promotes SIAH2 binding to DBC1 instead of OTUD5 is somewhat addressed however lacks detail. Hypoxic activation of SIAH2 is not addressed (reported to be via p38 phosphorylation), nor is further detail of OTUD5 binding prior to SIAH2 ubiquitination as the graphical abstract suggests.

The role of this axis in patients and more physiological tumour models is yet to be tested in detail and therefore is a potential weakness of the work proposed. It is currently unclear how important this post-translational regulation of DBC1 is in tumours compared to epigenetic silencing, copy number alterations or other methods of DBC1 silencing. Despite these points, the identification of this axis and detailed characterization provides an important step in further understanding the regulation of this tumour suppressor.

1) The authors propose a hypothesis that OTUD5 is bound to DBC1 in normoxic conditions which is displaced upon activation of SIAH2. This is an interesting hypothesis but requires further experiments to fully support this.

a. Does OTUD5 bind to non-ubiquitinated DBC1? If so, this supports the hypothesis that it is bound in normoxia prior to SIAH2-mediated ubiquitination upon activation in hypoxia as is suggested in the schematic. Direct binding of recombinant DBC1 and OTUD5 could confirm this.

b. Does expression of SIAH2 or OTUD5 change in hypoxia?

c. SIAH2 is still binding in normoxia (Figure 4I), are there other factors still mediating this?

2) It is unclear how prevalent this mechanism is in breast cancer patients. It is difficult to determine how significant this is as is currently presented

a. It may be easier to observe this correlation by scoring staining by H-score and performing correlation from XandY scatter.

b. The authors have correlated staining of xenografts and TMAs with Ki67 positivity and shown clear differences in proliferation. Staining a hypoxic marker (such as CAIX) and observing correlations between DBC1 expression would be a way of validating this mechanism in vivo or in patients.

c. If the main point of regulation in DBC1 expression occurs at the post-translational stage then one would posit there is poor correlation between mRNA and protein levels for DBC1. Perhaps the authors could test this using CPTAC/TCGA data for breast cancer patients readily available on cbioportal.

3) Most experiments are performed in HEK293T, HeLa or MB231 cells. The CHX chase experiments with endogenous DBC1 and endogenous IPs should be repeated with an additional breast cancer line.

4) There is a significant lack of detail in the figure legends throughout. Length of hypoxic exposures are not stated, and it is unclear which cell line is used in Figure 1D. Furthermore, number of replicates and specific statistical tests would be useful in interpreting the data.

5) It would be great to see more detail how OTUD5 was identified as the DUB that deubiquitinates DBC1. Currently the text mentions 'Lots of interaction studies showed' and Figure S2 shows the overexpression of a panel of DUBs tested however there are no further details.

6) In Figure 5A the KO of SIAH2 reduces DBC1 protein levels compared to WT. One would expect that the levels would be equivalent or even slightly increased, could this authors comment on this please?

7) The phenotypic assays in 5B-I were performed in hypoxia. Were these assays also performed in 21% O2? If this data shows no difference, then this strengthens the necessity for this hypoxia dependent axis in the pro-tumorigenic effects. If there are differences observed, then perhaps alternative pathways regulated by SIAH2 or DBC1 are important for tumorigenesis.

8) Can the authors provide more details on Figure 6J? The legend states that patients were stratified by 'DBC1 high expression'. If this is mRNA expression then could the authors explain how this impacts the significance of DBC1 post-translational regulation in breast cancer?

https://doi.org/10.7554/eLife.81247.sa1

Author response

[Editors’ note: the authors resubmitted a revised version of the paper for consideration. What follows is the authors’ response to the first round of review.]

Unfortunately, numerous significant concerns were raised by each of the 3 reviewers. In considering the sum total of their comments, we are sorry to say that, after consultation with the reviewers, we have decided that this work will not be considered further for publication by eLife. The full details are provided below, but the reviewers raised significant concerns about the exact characterization of DBC1 signaling in breast cancer, the underlying mechanism by which hypoxia regulates this signaling axis and the physiological relevance of findings in breast cancer patients. Without a higher level of enthusiasm, we do not feel this paper would fare well during additional rounds of review at eLife. We hope these comments are useful to you as you consider your next steps for this manuscript.

Reviewer #1 (Recommendations for the authors):

This study, in general, provides the compelling biochemistry and functional data on examining how SIAH2/OTUD5 may regulate DBC1 protein stability in breast cancer under hypoxia. As a result of DBC1 downregulation of hypoxia, breast cancer may display more malignant phenotype. The study is well designed. However, there are a few things that need to be addressed as suggested below:

1. The functional role of DBC1 in breast cancer needs to be characterized in details. For example, the expression of DBC1 in different subtypes of breast cancer. The phenotype of DBC1 overexpression and KO in breast cancer needs to be characterized in details.

We thank the reviewer for positive comments and constructive suggestions. In our manuscript, we have checked the expression of DBC1 in different cell lines including breast cancer, colon cancer, hepatocarcinoma etc. The results showed that hypoxia could induced the degradation of DBC1 in many cell lines (Figure 1F).

In addition, tissue microarray analysis using antibodies against SIAH2 or DBC1 revealed significant negative correlations between the protein levels of DBC1 and SIAH2 in human breast cancer patients (Figure 6E-F), which further validated our results from the bioinformatics analysis. Furthermore, the DBC1 protein levels were negatively correlated with that of Ki67, a marker of cancer cell proliferation, and clinical stages (new Supplementary Table 2), indicating that the quality control of DBC1 under hypoxia play an important role in the breast tumor progression.

2. Throughout the study, two main cell lines are used Hela and MDA-MB-231. Hela cells may display diminished p53 protein due to HPV expression while MDA-MB-231 cells contain mutant p53. It is unclear whether Hypoxia, by downregulating DBC1 level, would lead to further decrease of p53 activity in these cells. This would need to be clarified and reconciled. In addition, some other breast cancer cell lines with WT p53 (at least from in vitro) would need to be added to further strengthen the conclusion.

R2. We agree with the reviewer’s comments. Several reports have shown that DBC1 acts as a native inhibitor of SIRT1 in human cells, and the repression of SIRT1 increases p53 acetylation leading to upregulated p53 function. We analyzed the levels of p53 acetylation and SIAH2-DBC1 signaling in five breast cell lines that have different P53 conditions (MCF10A and MCF7 cells with WT p53, MDA-MB-231, T47D and JIMT1 cells with mutant p53). The results showed that, regardless WT or mutant p53, the acetylation of p53 was decrease after 24-hour hypoxia, which was blocked by SIAH2 knockdown (new Figure 5A).

3. The molecular mechanism by which hypoxia regulates SIAH2/OTUD5 interaction with DBC1 needs more detailed analysis and discussion. Is HIF involved in this process?

R3. Many thanks for the reviewer’s comments. As shown in the new Figure 4I, we found that the deubiquitinase OTUD5 only interacted with DBC1 under normoxic conditions, and the interaction between SIAH2 and DBC1 was increased under hypoxia, which promoted the ubiquitination and degradation of DBC1. We further analyzed the interaction of OTUD5 with DBC1 in SIAH2 knockout cells, and showed that deletion of SIAH2 significantly increased the interaction of OTUD5 with DBC1 under hypoxic conditions (new Figure 4I).

We have also analyzed whether DBC1 protein levels were affected by a HIF1α inhibitor (CAS 934593-90-5-Calbiochem) in MDA-MB-231 cells under hypoxia. The results showed that hypoxia-induced decrease of DBC1 protein and p53 acetylation were not blocked by HIF1α inhibitor (Figure 1-figure supplement 1A), and suggested that HIF1α signaling pathway might not be involved in DBC1 stability regulation.

Reviewer #2 (Recommendations for the authors):

This study reports on the control of DCB1 by the ubiquitin ligase Siah2 under hypoxia growth conditions in breast cancer, while the deubiquitinating enzyme OTUD5 limits DCB1 ubiquitination and thereby prolongs its stability under normoxia.

The following are some of the key points raised for authors considerations:

It is unclear what underlies the control of DCB1 stability under hypoxia (and not under other conditions).

R4. We thank the reviewer’s comments and suggestions. We have demonstrated that under hypoxic conditions, DBC1 was ubiquitinated by the E3 ubiquitin ligase SIAH2 and degraded via the ubiquitin-proteasome pathway under hypoxia. In this study, we found that hypoxia could promote the interaction between SIAH2 and DBC1 (new Figure 4I). Furthermore, several studies have reported that the ubiquitin ligase activity and stability of SIAH2 were increased under hypoxic conditions, which is due to its phosphorylation mediated by several kinases including p38. Under hypoxic conditions, we found that hypoxia induced DBC1 degradation was partially blocked by Doramapimod, an inhibitor of p38 (new Figure 3-figure supplement 1I). Moreover, we found that inhibition of p38 partially decreased SIAH2 protein and inhibited the interaction between SIAH2 and DBC1 under hypoxia (new Figure 3-figure supplement 1J). Therefore, there results show that hypoxia activates SIAH2 to interact with DBC1, which induces DBC1 degradation by ubiquitin-proteasome system to regulate DBC1 stability.

It would be important to determine what is the physiological significance of DCB1 loss under hypoxia for breast cancer cells.

R5. We have shown that, under hypoxic conditions, the degradation of DBC1 could promote tumor cell proliferation and migration, and inhibit DNA damage-induced apoptosis (new Figures 5B-E). Consistent with this observation, we found that the protein levels of DBC1 in clinical breast cancer samples were closely related with the clinical stage and pathological grades (new Figures 6H, 6I and Supplementary Table 2). These results demonstrate that SIAH2-mediated loss of DBC1 under hypoxia plays an important role in the breast tumor progression.

This work focuses on breast cancer, and it is necessary to better establish relevance in numerous breast cancer (all types?) as opposed to other tumor types.

R6. As following the reviewer’s suggestion, we studied more cancer cell lines, including breast cancer cells (T47D, JIMT1, MCF7, MDA-MB-231, etc) and other type of tumor cells (HepG2, A549, etc). These results show that the degradation of DBC1 protein under hypoxic conditions is a common phenomenon in tumor cells (Figure 1F and new Figure 5A).

The authors claim for dynamic regulation of DCB1 stability, but it is unclear what determines the dynamics.

R7. Thanks for the reviewer’s suggestion. According to the result that SIAH2mediated DBC1 ubiquitination was reversible when restoring the oxygen concentration (Figure 4A). Combined with mapping and interaction results, we found that under hypoxia, SIAH2 replaced OTUD5 for binding to the 1-130 domain of DBC1 (Figures 2F, 4H, 4J and new Figure 4I), which mediated the ubiquitination and degradation of DBC1 protein. These results suggest that hypoxia induces DBC1 degradation via the ubiquitin-proteasome system was mediated by E3 ligase SIAH2. We agree with the reviewer that the word “dynamic” may be confusing and have revised the title to “hypoxia induces DBC1 proteasomal degradation by SIAH2 in breast cancer progression”.

Experiments are performed largely under one condition and not another; complementing the assessment for hypoxia with normoxia conditions and vice versa is needed for number of studies shown.

We are agreeing with the reviewer. Actually, these experiments in our manuscript were strictly carried out under normoxic and hypoxic conditions. Now, we included the normoxia data set (new Figures 5B-E and Figure 5-figure supplement 1).

In this study, Liu et al. report on post-translational regulation of DBC1 by the ubiquitin ligase Siah2 and the DUB OTUD5, which occurs during hypoxia. The separate roles of Siah2 and DBC1 in tumor progression have been shown in previous publications. Here the authors define the role of Siah2 in regulating DBC1 stability in breast cancer cells during hypoxia. While interesting, several points need to be experimentally addressed before further evaluation of this study as a candidate for publication in eLife should take place.

– Why is Siah2 more effective in degrading DBC1 under hypoxia? The title and elsewhere in this manuscript authors claims for dynamic regulation of DBC1 stability. What underlies this dynamic regulation?

R9. It has been reported that under hypoxic conditions, the regulation of SIAH2 was regulated by several mechanisms including gene transcription, post transcriptional modifications, and formation of dimeric complexes. SIAH2 could be phosphorylated by kinases such as p38 and Src under hypoxic conditions, increasing its ubiquitin ligase activity and protein stability[1, 2]. Combined with Co-IP, ubiquitination and degradation assays, we found that hypoxia activated SIAH2 to interact with DBC1 and promote its degradation by the ubiquitin-proteasome pathway (Figure 3H and new Figure 4I). We agree with the reviewer that the word “dynamic” may be confusing and have revised the title to “hypoxia induces DBC1 proteasomal degradation by SIAH2 in breast cancer progression”.

– The work suggests that the Siah2 effect on DBC1 occurs in breast cancer cells, but most of the data is based on studies performed in either 293 or HeLa cells. Work on breast cancer lines is primarily limited to a single cell line.

R10. We are agreeing with reviewer’s comments. Besides using 293T or HeLa cells, we have also performed experiments in normal and breast cancer cell lines (MCF10A, MCF7 and MDA-MB-231), including the Co-IP assay (Figures 2D, 4B and Figure 2-figure supplement 1B, Figure 2-figure supplement 1C, Figure 3-figure supplement 1J and Figure 4-figure supplement 1F), detecting the ubiquitination level of DBC1 (Figures 3F and Figure 4A) and the protein level of DBC1 (Figures 1C-F, Figures 3H-L, and Figure 1-figure supplement 1A-C, Figure 3-figure supplement 1F-I and Figure 5A). In addition, we analysis DBC1 protein expression levels and DBC1 downstream signaling pathway activities in various breast cancer tumor cell lines under hypoxic conditions (Figure 1F and new Figure 5A). These results showed that SIAH2-mediated degradation of DBC1 protein under hypoxic conditions generally occurred in many breast cancer cells.

– Are the effects reported here also seen in breast cancer patients?

R11. Following this suggestions, we analysis the protein expression database and tissue microarray samples of human breast cancer patients, and found that the protein expression levels of SIAH2 and DBC1 were significantly negatively correlated (Figure 6E and Figure 6-figure supplement 1A), and the protein level of DBC1 was significantly correlated with the clinical stage and pathological grade (new Figures 6H, 6I and new Supplementary Table 2). It is demonstrated that SIAH2-mediated ubiquitination and degradation of DBC1 plays an important role related in breast tumor progression in human.

– Much of the data relies on overexpression. Authors ought to demonstrate changes in endogenous proteins and their physiological relevance (when does it happen and why).

R12. We thank the reviewer’s suggestion. In our manuscript, the ubiquitination level and protein stability of endogenous DBC1 were detected in both MCF7 cells and MDAMB-231 cells (Figures 3F and 4A, Figures 1C-F, Figures 3H-L, and Figure 1-figure supplement 1A-C, Figure 3-figure supplement 1F-I and Figure5A). Also, the endogenous interaction between SIAH2, DBC1 and OTUD5 were performed in MCF10A, MCF7 and MDA 231 cells (Figure 2D, Figures 4B and Figure 2-figure supplement 1B, C and Figure 4-figure supplement 1F). these results show that under normoxic conditions, endogenous protein of DBC1 binds to the deubiquitinase OTUD5 and maintains a non-ubiquitinated stable state. Under hypoxic conditions, DBC1 binds to the E3 ubiquitin ligase SIAH2, increases the level of ubiquitination modification, and is further degraded by the proteasome pathway. The detailed mechanisms underlying hypoxia-mediated OTUD5 and SIAH2 regulation are under active investigation in our lab.

– OTUD5 is shown to regulate DBC1 under normoxic (and not hypoxic?) conditions. Why?

R13. We showed that OTUD5 binds to and deubiquitinates DBC1 under normoxia, leading to enhanced protein stability of DBC1. However, such OTUD5-DBC1 interaction is attenuated under hypoxia by multiple mechanisms. First, SIAH2 could attenuate endogenous OTUD5-DBC1 interaction under hypoxic conditions, while deletion of SIAH2 significantly increased the interaction of OTUD5 with DBC1 under hypoxia (new Figure 4I). Therefore, these results suggest that OTUD5 is responsible for DBC1 deubiquitination and stabilization under normoxic conditions.

– All figure legends and Results sections lack details. It is not clear how the experiments were carried out.

R14. Thanks for the suggestions, we have carefully checked all of the legends and methods, and revised them with experimental technical details and experimental conditions. New and updated text is highlighted in red.

Additional comments:

Figure 1: the authors assess the overlap of differentially expressed genes between hypoxia and DBC1 deletion (in normoxia). DEG needs to be compared under the same (hypoxic) conditions. Can overexpression of DBC1 rescue phenotypes be seen under hypoxia?

R15. Thanks for reviewer’s suggestion. In order to identify the candidate genes that are both regulated by hypoxia and DBC1, we analyzed the DEGs of wild-type cells under normoxic and hypoxic conditions, and the DEGs of wild-type and DBC1 knockout cells under normoxic conditions, respectively. (Figures 1H and 1I). Since hypoxia also leads to DBC1 loss in WT cells, we will not be able to separate hypoxiaregulated genes from that regulated by DBC1 loss under hypoxia condition.

Figure 2A: the authors overexpress several E3 ubiquitin ligases to determine possible candidates responsible for DBC1 protein degradation. However, the level of expression of each E3 ligase (mRNA level) is missing, making it difficult to compare the efficiency of each E3 ligase in degrading DBC1. HUWE1 also seems to be as efficient as Siah2 in degrading DBC1, but it is not mentioned in the Results section. Why? The experiment is carried out in normoxia rather than hypoxia; why? Does any UBL tested exhibit different efficiency for DBC1 interaction and degradation under hypoxia?

R16. Thanks for suggestions. To screen the ubiquitin ligases of DBC1, we overexpressed a series of hypoxia-related ubiquitin ligases and found that both HUWE1 and SIAH2 might mediated DBC1 stability regulation (Figure 2A). In the revised Figure 2-figure supplement 1A, we have included Western blot results to show the protein levels of all E3s overexpressed. We agree with the reviewer that normoxia is not the perfect condition for E3 screening assay. Therefore, we performed the same assay under hypoxia and found that only SIAH2 was able to reduce DBC1 protein levels (new Figure 2B). These data clearly demonstrate that SIAH2 is the E3 ligase targeting DBC1 under hypoxia.

Figure 3: The authors should demonstrate, experimentally, why Siah2 dependent degradation of DBC1 is primarily claimed to be under hypoxia.

R17. We thank the reviewer’s suggestion. Please refer to the detail molecular mechanism of SIAH2 dependent degradation of DBC1 in R6 and R11.

Figure 3H: the authors compared DBC1 protein levels in WT and Siah2 KO cells using MDA-MB-231 cells. It would be informative to compare the level of DBC1 between WT and Siah2 KO in the same Western and demonstrate possible changes in the level of DBC1 under normoxia. Additional breast cancer cell lines (and non-transformed breast cultures) should be studied.

Figure 3K: It would be informative to perform CHX chase under normoxia, compared with CHX done under hypoxia. These assessments need to be extended to include additional breast cancer cell lines.

Figure 4: the authors should study OTUD5 binding to DBC1 under hypoxia compared with normoxia to substantiate the claim for preferred interaction under normoxia. Does OTUD5 expression change in breast cancer patients, compared to healthy donors or between cancerous and normal tissues? Does it correlate with patient survival? The screening of DUBS to identify the candidate responsible for deubiquitination of DBC1 is not clear. Sup Figure 4 A shows the level of expression of the different DUBS but does not reveal why the authors chose to focus on OTUD5.

R18. Thanks for good suggestions. We analyzed the interaction of endogenous OTUD5 and DBC1 under normoxia and hypoxia. The result showed that OTUD5 only interacted with DBC1 under normoxia in WT cells. However, such interaction in SIAH2-KO cells also took place under hypoxia (new Figure 4I). OTUD5 was also degraded via the ubiquitin-proteasome pathway under hypoxia. These results suggest that, under hypoxic conditions, the interaction between SIAH2 and DBC1 attenuates OTUD5 binding to DBC1, and the degradation of OTUD5 further reduces its interaction with DBC1.

Unfortunately, there is no good immunohistochemical antibodies for OTUD5 to check its expression levels in clinical samples (we have check the OTUD5 antibodies from Proteintech: 21002-1-AP, CST: OTUD5 (D8Y2U) Rabbit mAb #20087 and Abcam: ab254742 as same as the references, but those not work on breast cancer tissue). Data analysis using TCGA and CPTAC database revealed that the mRNA level of OTUD5 was not obvious changed (Figure 6B). We have included the detail of the DUBs screening. In order to screen and identify the DUB of DBC1, we constructed human DUBs plasmids and detected their overexpression level in cells. The interaction assays between DUBs and DBC1 were performed and found that OTUD5 and USP29 are potential deubiquitinases of DBC1 (Figure 4-figure supplement 1A and B). Further deubiquitination experiments results showed that only OTUD5 could specifically deubiquitinate DBC1 (Figure 4-figure supplement 1C). So, we identify OTUD5 as the deubiquitinating enzyme of DBC1.

Figure4I: the authors should add Siah2 KO cells to their analysis; it is important to determine whether OTUD5 and Siah2 compete for binding to DBC1.

R19. We thank the reviewer for good suggestion. We performed the study and found that deletion of SIAH2 significantly increased the interaction of OTUD5 with DBC1 under hypoxia (new Figure 4I). These results suggest that under hypoxic conditions the interaction between SIAH2 and DBC1 attenuates OTUD5 binding to DBC1.

Figure 5B, D, F: the authors should address whether Siah2 KO can promote apoptosis, colony formation assay, and invasion under normoxia, not only in hypoxia.

We are agreeing the reviewer, and have included new data for the control groups under normoxia and hypoxia (new Figures 5B-E and Figure 5-figure supplement 1).

Figure 5M: the authors should check for possible changes in apoptosis, in addition to shown data for proliferation.

R21. We have updated the results of apoptosis by detecting TUNEL staining on breast cancer tissue (new Figure 5I).

All figure legends and Results sections lack details. It is not clear how the experiments were carried out. (for example, Figure 1A: how long were the cells kept in hypoxia when RNAseq was performed? The authors should define the conditions used to reach hypoxia in the results and Figure legends. Condition of 1% O2 is briefly noted in the Methods section, but not in results or legends.

R22. Thanks for suggestions, we have carefully checked all of the legends and methods, and updated experimental technical details and experimental conditions.

Reviewer #3 (Recommendations for the authors):

The authors sought to identify how the breast cancer tumour suppressor DBC1 (CCAR2) is post-translationally regulated. This came from transcriptomic analysis of MB231 cells in hypoxia revealed decreased SIRT1 activity, without changes in protein levels. Instead known regulator DBC1 displayed reduced protein expression in hypoxia with no changes in mRNA. Through targeted screen of hypoxia associated E3 ligases and IP-MS of SIAH2, the authors identify interaction between DBC1 and SIAH2. They comprehensively map the interaction between DBC1 and SIAH2 and identify the residue ubiquitinated. Upon 6h of reoxygenation the ubiquitination of DBC1 is decreased. OTUD5 was identified as the DUB that deubiquitinates DBC1. The authors propose that in normoxia, OTUD5 is bound to DBC1 which is displaced by SIAH2 upon activation by hypoxia, however despite the comprehensive study of the interaction between DBC1 this is not fully supported by the data. SIAH2 Knockout reduced colony formation, cell migration and growth in a xenograft tumour model which could all be partially rescued by knockout of DBC1. SIAH2 expression was elevated in breast cancer and correlated with cancer stage. Through staining of a TMA the authors suggest a negative correlation between DBC1 and SIAH2 protein expression however this is not immediately clear as the data is currently presented, furthermore this expression has been correlated with proliferation markers, whereas markers of hypoxia score would be more informative for the proposed mechanism.

The interaction studies are convincing and well performed. One particular strength of the manuscript is the use of enzymatic dead mutants as further negative controls. Furthermore, each interaction is interrogated in depth with exogenous mapping, direct binding assays and endogenous IPs. Some aspects of the manuscript lack detail, particularly the figure legends making interpretation of data difficult at times and would certainly aid readers looking to replicate this data if these are more detailed. Whilst the ubiquitination of DCB1 and subsequent deubiquitination by OTUD5 is clear, the hypothesis that hypoxia promotes SIAH2 binding to DBC1 instead of OTUD5 is somewhat addressed however lacks detail. Hypoxic activation of SIAH2 is not addressed (reported to be via p38 phosphorylation), nor is further detail of OTUD5 binding prior to SIAH2 ubiquitination as the graphical abstract suggests.

The role of this axis in patients and more physiological tumour models is yet to be tested in detail and therefore is a potential weakness of the work proposed. It is currently unclear how important this post-translational regulation of DBC1 is in tumours compared to epigenetic silencing, copy number alterations or other methods of DBC1 silencing. Despite these points, the identification of this axis and detailed characterization provides an important step in further understanding the regulation of this tumour suppressor.

1) The authors propose a hypothesis that OTUD5 is bound to DBC1 in normoxic conditions which is displaced upon activation of SIAH2. This is an interesting hypothesis but requires further experiments to fully support this.

a. Does OTUD5 bind to non-ubiquitinated DBC1? If so, this supports the hypothesis that it is bound in normoxia prior to SIAH2-mediated ubiquitination upon activation in hypoxia as is suggested in the schematic. Direct binding of recombinant DBC1 and OTUD5 could confirm this.

R23. Many thanks for the reviewer’s suggestion and we have found OTUD5 could direct bind non-ubiquitinated DBC1. in vitro, pull-down experiments were performed using purified His-DBC1 protein after co-incubation with cell lysates under normoxic conditions (Figure 4C). This result showed that OTUD5 had a direct interaction with DBC1. And as shown in the new Figure 4I, OTUD5 interacted with DBC1 under normoxic conditions. In order to further address this concern, we have performed new Co-IP experiments, and showed OTUD5 could bind to non-ubiquitinated DBC1 (Author response image 1).

Author response image 1
HEK293T cells were transfected with Myc-DBC1 (K287R) mutant and Flag-OTUD5 for 24 h.Cells were collected for immunoprecipitation with anti-Flag antibody.

b. Does expression of SIAH2 or OTUD5 change in hypoxia?

R24. It has been reported that under hypoxic conditions, the regulation of SIAH2 was regulated by several mechanisms including gene transcription, post transcriptional modifications, and formation of dimeric complexes.The detailed mechanisms underlying hypoxiamediated OTUD5 and SIAH2 regulation are under active investigation in our lab.

c. SIAH2 is still binding in normoxia (Figure 4I), are there other factors still mediating this?

R25. In our manuscript, the endogenous interaction assay between SIAH2 and DBC1 was performed in MDA-MB-231 cells supplemented with the proteasomal inhibitor MG132 (10 μM) before cells were harvest. Because MG132 could inhibit SIAH2 degradation and promote its stability, so that there was weak interaction of SIAH2 and DBC1 could be detected under normxia. The direct interaction between SIAH2 and DBC1 was confirmed by pull-down experiments using purified proteins in vitro (Figures 2D, G and H). This has been clarified in the updated figure legend.

2) It is unclear how prevalent this mechanism is in breast cancer patients. It is difficult to determine how significant this is as is currently presented

a. It may be easier to observe this correlation by scoring staining by H-score and performing correlation from XandY scatter.

R26. Many thanks for the suggestion. Tissue microarray analysis using antibodies against the SIAH2 or DBC1 revealed that the expression of DBC1 was significantly negatively correlated with that of SIAH2 in clinical breast cancer samples (Figures 6E, 6F). Furthermore, we found that the expression of DBC1 was negatively correlated with clinical stage and the percentage of the Ki67-positive cell population (new Figures 6H, 6I and new Supplementary Table 2).

b. The authors have correlated staining of xenografts and TMAs with Ki67 positivity and shown clear differences in proliferation. Staining a hypoxic marker (such as CAIX) and observing correlations between DBC1 expression would be a way of validating this mechanism in vivo or in patients.

R27. These are very helpful suggestions. We have performed immunofluorescence assay using a CAIX monoclonal antibody (Proteintech, 66243-1-Ig) to analyze DBC1 expression levels in the hypoxic zone in clinical breast cancer samples. The result showed that the DBC1 expression is dramatically reduced in the CAIX+ hypoxic zone (new Figure 6G), demonstrating the DBC1 loss due to hypoxia is clinically significant.

c. If the main point of regulation in DBC1 expression occurs at the post-translational stage then one would posit there is poor correlation between mRNA and protein levels for DBC1. Perhaps the authors could test this using CPTAC/TCGA data for breast cancer patients readily available on cbioportal.

R28. We analyzed the correlation between mRNA and protein levels for DBC1 on cbioportal for breast cancer patient samples, generated by CPTAC. Surprisingly, there was a positive correlation between mRNA and protein levels of DBC1. We think there are two possible explanations. (1) As we have shown that DBC1 reduction only takes place in the hypoxic regions in a tumor (new Figure 6G), the DBC1 expression data from cbioportal may not be limited to the hypoxic regions. (2) The tumor microenvironment could have more factors besides hypoxia stress.

3) Most experiments are performed in HEK293T, HeLa or MB231 cells. The CHX chase experiments with endogenous DBC1 and endogenous IPs should be repeated with an additional breast cancer line.

R29. We agree with the reviewer. We have examined the endogenous protein interaction, ubiquitination level and protein level of DBC1 in breast cancer cell lines. The results of CHX chase experiments with endogenous DBC1 and endogenous CoIPs in breast cancer cells were shown in Figures 2D, 3K, 4B and new Figures Figure 2-figure supplement 1B and C, Figure 3-figure supplement 1F-J and 4I.

4) There is a significant lack of detail in the figure legends throughout. Length of hypoxic exposures are not stated, and it is unclear which cell line is used in Figure 1D. Furthermore, number of replicates and specific statistical tests would be useful in interpreting the data.

R30. Thanks for suggestions, we have carefully checked all of the legends and methods, and updated experimental technical details, experimental conditions and detail protocol information.

5) It would be great to see more detail how OTUD5 was identified as the DUB that deubiquitinates DBC1. Currently the text mentions 'Lots of interaction studies showed' and Figure S2 shows the overexpression of a panel of DUBs tested however there are no further details.

R31. Thanks for suggestions. We have included the detail of the DUBs screening. In order to screen and identify the DUB of DBC1, we constructed human DUBs plasmids and detected their overexpression level in cells. The interaction assays between DUBs and DBC1 were performed and found that OTUD5 and USP29 are potential deubiquitinases of DBC1 (new Figures S4A and S4B). Further deubiquitination experiments results showed that only OTUD5 could specifically deubiquitinate DBC1 (new Figure S4C). So, we identify OTUD5 as the deubiquitinating enzyme of DBC1.

6) In Figure 5A the KO of SIAH2 reduces DBC1 protein levels compared to WT. One would expect that the levels would be equivalent or even slightly increased, could this authors comment on this please?

In order to address this concern and confirm the effect of SIAH2 deletion on DBC1 protein level, we detected the levels of DBC1 under hypoxia in several breast cancer cell lines with or without siRNA of SIAH2, such as MCF10A, MCF7, T47D and JIMT1 cells (new Figure 5A). The results show that DBC1 was degraded under hypoxic conditions in breast cancer cells, which was dependent on SIAH2.

7) The phenotypic assays in 5B-I were performed in hypoxia. Were these assays also performed in 21% O2? If this data shows no difference, then this strengthens the necessity for this hypoxia dependent axis in the pro-tumorigenic effects. If there are differences observed, then perhaps alternative pathways regulated by SIAH2 or DBC1 are important for tumorigenesis.

Thanks, we agree with the reviewer. We included normoxia data as shown in revised Figure S5. Under normoxic conditions (21% O2), SIAH2 knock out did not affect tumor cell proliferation and DNA damage-induced apoptosis. However, the deletion of SIAH2 and DBC1 significantly increased cell proliferation and reduced Etoposide-mediated apoptosis (new Figures 5B-E and Figure S5).

8) Can the authors provide more details on Figure 6J? The legend states that patients were stratified by 'DBC1 high expression'. If this is mRNA expression then could the authors explain how this impacts the significance of DBC1 post-translational regulation in breast cancer?

R34. Thanks for the suggestion. The “High or low levels” represents mRNA expression of DBC1. As we have shown that DBC1 reduction only takes place in the hypoxic regions in a tumor (new Figure 6G) and the total mRNA levels of DBC1 might not accurately characterize protein levels, so we removed these data.

References

1. Sarkar, T.R., et al., Identification of a Src tyrosine kinase/SIAH2 E3 ubiquitin ligase pathway that regulates C/EBPdelta expression and contributes to transformation of breast tumor cells. Mol Cell Biol, 2012. 32(2): p. 320-32.

2. Khurana, A., et al., Regulation of the ring finger E3 ligase Siah2 by p38 MAPK. J Biol Chem, 2006. 281(46): p. 35316-26.

https://doi.org/10.7554/eLife.81247.sa2

Article and author information

Author details

  1. Qiangqiang Liu

    State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, Tianjin Key Laboratory of Protein Science, College of Life Sciences, Haihe Laboratory of Cell Ecosystem, Nankai University, Tianjin, China
    Contribution
    Conceptualization, Resources, Data curation, Investigation, Writing – original draft
    Competing interests
    No competing interests declared
  2. Qian Luo

    State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, Tianjin Key Laboratory of Protein Science, College of Life Sciences, Haihe Laboratory of Cell Ecosystem, Nankai University, Tianjin, China
    Contribution
    Investigation, Methodology, Writing – original draft
    Competing interests
    No competing interests declared
  3. Jianyu Feng

    State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, Tianjin Key Laboratory of Protein Science, College of Life Sciences, Haihe Laboratory of Cell Ecosystem, Nankai University, Tianjin, China
    Contribution
    Methodology
    Competing interests
    No competing interests declared
  4. Yanping Zhao

    School of Statistics and Data Science, LPMC and KLMDASR, Nankai University, Tianjin, China
    Contribution
    Software, Methodology
    Competing interests
    No competing interests declared
  5. Biao Ma

    State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, Tianjin Key Laboratory of Protein Science, College of Life Sciences, Haihe Laboratory of Cell Ecosystem, Nankai University, Tianjin, China
    Contribution
    Methodology
    Competing interests
    No competing interests declared
  6. Hongcheng Cheng

    State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, Tianjin Key Laboratory of Protein Science, College of Life Sciences, Haihe Laboratory of Cell Ecosystem, Nankai University, Tianjin, China
    Contribution
    Methodology
    Competing interests
    No competing interests declared
  7. Tian Zhao

    State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, Tianjin Key Laboratory of Protein Science, College of Life Sciences, Haihe Laboratory of Cell Ecosystem, Nankai University, Tianjin, China
    Contribution
    Methodology
    Competing interests
    No competing interests declared
  8. Hong Lei

    State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, Tianjin Key Laboratory of Protein Science, College of Life Sciences, Haihe Laboratory of Cell Ecosystem, Nankai University, Tianjin, China
    Contribution
    Methodology
    Competing interests
    No competing interests declared
  9. Chenglong Mu

    State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, Tianjin Key Laboratory of Protein Science, College of Life Sciences, Haihe Laboratory of Cell Ecosystem, Nankai University, Tianjin, China
    Contribution
    Methodology
    Competing interests
    No competing interests declared
  10. Linbo Chen

    State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, Tianjin Key Laboratory of Protein Science, College of Life Sciences, Haihe Laboratory of Cell Ecosystem, Nankai University, Tianjin, China
    Contribution
    Methodology
    Competing interests
    No competing interests declared
  11. Yuanyuan Meng

    State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, Tianjin Key Laboratory of Protein Science, College of Life Sciences, Haihe Laboratory of Cell Ecosystem, Nankai University, Tianjin, China
    Contribution
    Methodology
    Competing interests
    No competing interests declared
  12. Jiaojiao Zhang

    State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, Tianjin Key Laboratory of Protein Science, College of Life Sciences, Haihe Laboratory of Cell Ecosystem, Nankai University, Tianjin, China
    Contribution
    Methodology
    Competing interests
    No competing interests declared
  13. Yijia Long

    State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, Tianjin Key Laboratory of Protein Science, College of Life Sciences, Haihe Laboratory of Cell Ecosystem, Nankai University, Tianjin, China
    Contribution
    Methodology
    Competing interests
    No competing interests declared
  14. Jingyi Su

    State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, Tianjin Key Laboratory of Protein Science, College of Life Sciences, Haihe Laboratory of Cell Ecosystem, Nankai University, Tianjin, China
    Contribution
    Methodology
    Competing interests
    No competing interests declared
  15. Guo Chen

    State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, Tianjin Key Laboratory of Protein Science, College of Life Sciences, Haihe Laboratory of Cell Ecosystem, Nankai University, Tianjin, China
    Contribution
    Methodology
    Competing interests
    No competing interests declared
  16. Yanjun Li

    State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, Tianjin Key Laboratory of Protein Science, College of Life Sciences, Haihe Laboratory of Cell Ecosystem, Nankai University, Tianjin, China
    Contribution
    Methodology
    Competing interests
    No competing interests declared
  17. Gang Hu

    School of Statistics and Data Science, LPMC and KLMDASR, Nankai University, Tianjin, China
    Contribution
    Methodology
    Competing interests
    No competing interests declared
  18. Xudong Liao

    State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, Tianjin Key Laboratory of Protein Science, College of Life Sciences, Haihe Laboratory of Cell Ecosystem, Nankai University, Tianjin, China
    Contribution
    Methodology
    Competing interests
    No competing interests declared
  19. Quan Chen

    State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, Tianjin Key Laboratory of Protein Science, College of Life Sciences, Haihe Laboratory of Cell Ecosystem, Nankai University, Tianjin, China
    Contribution
    Funding acquisition, Investigation, Methodology
    Competing interests
    No competing interests declared
  20. Yushan Zhu

    State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, Tianjin Key Laboratory of Protein Science, College of Life Sciences, Haihe Laboratory of Cell Ecosystem, Nankai University, Tianjin, China
    Contribution
    Conceptualization, Supervision, Funding acquisition, Writing – original draft, Project administration, Writing – review and editing, Validation, Visualization
    For correspondence
    zhuys@nankai.edu.cn
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5648-0416

Funding

National Key Research and Development Program of China (2019YFA0508603)

  • Yushan Zhu

National Natural Science Foundation of China (32030026)

  • Yushan Zhu

National Natural Science Foundation of China (91849201)

  • Quan Chen

National Natural Science Foundation of China (91754114)

  • Yushan Zhu

National Natural Science Foundation of China (31790404)

  • Quan Chen

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We are grateful to Dr. Wenhui Zhao for providing us the OTUD5 plasmids at the Center for Peking University Health Science Center. We are also grateful to Dr. Changhai Tian from the University of Kentucky College of Medicine for critical reading of the manuscript.

Ethics

Mice were maintained in the animal core facility of College of Life Sciences, Nankai University, Tianjin, China. All experiments involving animals were reviewed and approved by the Animal Care and Use Committee of Nankai University and were performed in accordance with the university guidelines (no. 2022-SYDWLL-000353).

Senior Editor

  1. Richard M White, Memorial Sloan Kettering Cancer Center, United States

Reviewing Editor

  1. Qing Zhang, University of Texas Southwestern Medical Center, United States

Reviewers

  1. Qing Zhang, University of Texas Southwestern Medical Center, United States
  2. Paul Grevitt, Barts Cancer Institute, Queen Mary University of London, United Kingdom

Publication history

  1. Preprint posted: January 11, 2022 (view preprint)
  2. Received: June 20, 2022
  3. Accepted: July 19, 2022
  4. Accepted Manuscript published: August 1, 2022 (version 1)
  5. Version of Record published: August 15, 2022 (version 2)

Copyright

© 2022, Liu et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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  1. Qiangqiang Liu
  2. Qian Luo
  3. Jianyu Feng
  4. Yanping Zhao
  5. Biao Ma
  6. Hongcheng Cheng
  7. Tian Zhao
  8. Hong Lei
  9. Chenglong Mu
  10. Linbo Chen
  11. Yuanyuan Meng
  12. Jiaojiao Zhang
  13. Yijia Long
  14. Jingyi Su
  15. Guo Chen
  16. Yanjun Li
  17. Gang Hu
  18. Xudong Liao
  19. Quan Chen
  20. Yushan Zhu
(2022)
Hypoxia-induced proteasomal degradation of DBC1 by SIAH2 in breast cancer progression
eLife 11:e81247.
https://doi.org/10.7554/eLife.81247

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