Breast cancer heterogeneity is a challenge in clinical practice and calls for extensive patient stratification. Similarly, the underlying tumor biology needs evaluation in stratified patient populations. Breast cancers classify into five molecular subtypes (normal-like, luminal A and B, HER2-enriched, basal-like) that differ in metabolic and proliferative activity, metastatic potential, therapeutic responsiveness, and prognosis (Dai et al., 2015). Whereas radical surgery can cure most patients with localized breast cancer, disseminated disease requires additional systemic therapy. Available successful therapies target the receptor tyrosine-protein kinase HER2 (ErbB2/neu) and estrogen receptors. However, patients with basal-like/triple-negative breast cancer lack targeted treatment options and currently receive classical chemotherapy (e.g., anthracycline and taxane in combination) with considerable adverse effects (Ávalos-Moreno et al., 2020).

Accelerated intermediary metabolism in breast cancer tissue (Voss et al., 2020) burdens the molecular pathways for acidic waste product elimination. In solid cancer tissue, extracellular pH (pH_o) can reach as low as 6.5 (Voss et al., 2020; Vaupel et al., 1989), which is distinct from corresponding normal tissue with pH_o around 7.3–7.4. The acidity of the extracellular tumor microenvironment challenges intracellular pH (pH_i) homeostasis as it inhibits cellular net acid extrusion (Bonde and Boedtkjer, 2017). The changes in metabolic profile and proliferative rate of cancer cells contribute to the acidity of the tumor microenvironment, are important determinants of the malignant phenotype, and shape breast cancer progression (Parks et al., 2017; Persi et al., 2021; Boedtkjer and Pedersen, 2020).

Cells generally eliminate their metabolic acid load via membrane proteins that mediate H⁺ extrusion (e.g., Na⁺/H⁺ exchange, H⁺-ATPase activity) or HCO₃^– uptake (e.g., Na⁺,HCO₃^– cotransport) (Aalkjaer et al., 2014; Xu et al., 2018; Stransky et al., 2016; see Figure 1B). Tissue relying partly on fermentative glycolysis can also eliminate acidic waste products from metabolism through coupled transport of H⁺ and lactate via monocarboxylate transporters (Pérez-Escuredo et al., 2016). In human and murine breast cancer tissue analyzed without stratification by molecular subtype, Na⁺,HCO₃^– cotransport activity is elevated and protein expression of the Na⁺,HCO₃^– cotransporter NBCn1 (SLC4A7) and monocarboxylate transporters MCT1 (SLC16A1) and MCT4 (SLC16A3) are upregulated compared to normal breast tissue (Boedtkjer, 2019; Boedtkjer et al., 2013; Lee et al., 2016; Lee et al., 2018; Lee et al., 2015). Protein expression of the Na⁺/H⁺ exchanger NHE1 (SLC9A1) is more variable in primary breast cancer tissue showing unchanged or only moderately elevated levels (Lee et al., 2016; Lee et al., 2015) when compared to normal breast tissue as one unstratified group.

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Figure 1—source data 1

Data file containing NBCn1 and NHE1 protein expression levels, steady-state intracellular pH (pH_i) values, and net acid extrusion capacities linked to de-identified clinical and pathological patient characteristics.

Note that this source data file pertains to Figure 1 but it also contains the clinicopathological information used for stratification in Figures 2–5, 7, and 8, and Figure 2—figure supplement 1; for the multiple linear and logistic regression analyses in Figure 6; and for the plots in Figure 6—figure supplement 1.

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Net acid extrusion from cancer cells elevates the cytosolic pH and acidifies the outer cell surface and interstitial space. In various model systems, acid-base transporters can modify carcinogenesis and the behavior of cancer cells including cancer cell proliferation, migration, and invasion (Boedtkjer and Pedersen, 2020; Amith and Fliegel, 2017; Stock and Pedersen, 2017). Although detailed molecular mechanisms are not yet established, elevated pH_i maintains metabolic activity (Parks et al., 2013), increases DNA and protein synthesis (Pedersen, 2006), and accelerates cell cycle progression (Flinck et al., 2018) in cultured cell lines. In accordance, mice with disrupted expression of NBCn1 show delayed tumor development and decelerated tumor growth when tested using models of carcinogen- and ErbB2-induced breast cancer (Lee et al., 2016; Lee et al., 2018).

Acidification at the outer cell surface depends on the rate of net acid transfer across the cell membrane and on diffusion hindrances that limit exchange with the bulk interstitial solution and the blood stream. Cell surface pH can modify cell-cell and cell-matrix interactions (Stock et al., 2005; Riemann et al., 2019), pH gradients from the leading to the rear end of cells can promote directional migration (Stock et al., 2007; Boedtkjer et al., 2016), and interstitial acidification of the tumor microenvironment has potential for modifying anti-cancer immune responses (Cassim and Pouyssegur, 2019). Indeed, cancer progression through metastasis and development of treatment resistance have been reported sensitive to inhibition of Na⁺/H⁺ exchangers (Amith and Fliegel, 2017; Stock and Pedersen, 2017); however, several anti-cancer effects of pharmacologically inhibiting Na⁺/H⁺ exchange appear only partly pH-dependent (Boedtkjer et al., 2012; Loo et al., 2012; Schwab et al., 2012) and can be caused by NHE1-independent toxicity due to intracellular drug accumulation (Rolver et al., 2020).

Despite the molecular and mechanistic insights from human cultured cell lines and inbred mouse models, the consequences of pH deregulation in human cancer tissue remain unclear. In particular, mechanisms of pH control in breast cancer tissue and their consequences for disease progression were previously explored in models that do not reflect the heterogeneity of human breast cancer. In the current study, we investigated an extensive cohort of human breast cancer patients, sufficiently large to reflect the heterogeneity of acid-base conditions and the variation in cellular handling of metabolic waste products. We tested the hypotheses that (a) specific clinical and pathological characteristics accelerate cellular net acid extrusion and determine the underlying molecular mechanisms of pH regulation in human breast cancer tissue; and (b) the capacity for cellular net acid extrusion, the steady-state pH_i level, and the expression of acid-base transporters in human breast cancer tissue predict the severity of disease.

We sampled human tissue biopsies from an extensive cohort of 110 women with breast cancer (Table 1) and evaluated pH_i dynamics based on organoids freshly isolated from the breast cancer tissue and corresponding normal breast tissue (Figure 1). Within this patient population, we stratified the pH_i dynamics and the NHE1 and NBCn1 expression levels by histopathology (Figure 2 and Figure 2—figure supplement 1), malignancy grade (Figure 3), estrogen receptor status (Figure 4), and HER2 status (Figure 5); and adjusted for variation in other clinical and pathological characteristics (Figure 6). We then explored how the pH_i dynamics and the NHE1 and NBCn1 protein expression levels relate to cancer cell proliferation (Figure 7) and lymph node metastasis (Figure 8). Finally, we evaluated how variation in expression levels for acid-base transporters influence patient survival within individual breast cancer molecular subtypes (Figures 9 and 10, and Figure 10—figure supplements 1 and 2).

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Figure 9—source data 1

The mRNA expression for SLC9A1 correlates with that of ESR1 and ERBB2.

When adjusted for expression of ESR1, PGR, and ERBB2, the mRNA expression of SLC9A1 does not correlate with that of SLC4A7, SLC16A1, and SLC16A3 (n=409–1162).

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The mRNA expression for SLC4A7 correlates with that of ESR1, PGR, and ERBB2.

When adjusted for expression of ESR1, PGR, and ERBB2, the mRNA expression of SLC4A7 does not correlate with that of SLC9A1, SLC16A1, and SLC16A3 (n=409–1162).

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We report here on the first large-scale study of pH_i dynamics in human cancer samples. We demonstrate that acid-base transporters play key pathophysiological roles by counteracting intracellular acidification and setting the steady-state pH_i in human breast cancer tissue (Figure 1). Furthermore, the level of cellular acidity and the capacity for net acid extrusion in human primary breast carcinomas can account for variation in proliferative activity (Figure 7) and are predictive for the occurrence of lymph node metastasis (Figure 8). The functional recordings of pH_i dynamics carry predictive value that is complementary to and independent from information based on protein expression analyses (Figures 7G and 8G).

We detect substantial inter-patient heterogeneity in acid-base conditions of breast carcinomas and explore the underlying modifiers and biological consequences. As illustrated in Figure 11, we show that (a) Na⁺,HCO₃^– cotransport raises pH_i more in invasive lobular than ductal breast carcinomas and particularly in breast cancer tissue of high malignancy grade (Figures 2, 3 and 6); (b) Na⁺/H⁺ exchange raises pH_i more in estrogen receptor-negative breast carcinomas (Figures 4 and 6); (c) protein expression of NBCn1 and NHE1 is elevated by HER2 overexpression or gene amplification (Figures 5 and 6); (d) elevated steady-state pH_i particularly due to Na⁺,HCO₃^– cotransport predicts high proliferative activity in primary breast carcinomas (Figure 7); (e) elevated capacity for Na⁺,HCO₃^– cotransport, high NBCn1 protein expression, and low NHE1 protein expression predict lymph node metastasis (Figure 8); and (f) high SLC4A7 and/or low SLC9A1 mRNA expression are associated with shorter survival in patients with luminal A and basal-like/triple-negative breast cancer (Figures 9 and 10).

Figure 11

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Supporting the validity of our study, the findings are based on two distinct patient populations evaluated by separate experimental approaches: (a) the links between pH_i dynamics, protein expression of acid-base transporters, and clinical and pathological patient characteristics (Figures 1–8) come from a cohort of 110 breast cancer patients with information derived from medical records, pH_i recordings, and immunohistochemical staining; and (b) the prognostic evidence linking transcriptomics data to patient survival (Figures 9 and 10) comes from a separate cohort of 1457 breast cancer patients.

As depicted schematically in Figure 1B, HCO₃^– uptake via NBCn1 is functionally equivalent to H⁺ extrusion via NHE1 when the CO₂/HCO₃^– buffer is in equilibrium (Boedtkjer et al., 2012). However, as summarized in Figure 11, it is clear from our analyses that NBCn1 and NHE1 have very different consequences in human breast cancer tissue: Na⁺,HCO₃^– cotransport sets the steady-state pH_i associated with proliferative activity (Figure 7G); and the capacity for Na⁺,HCO₃^– cotransport and protein expression of NBCn1 predict lymph node metastasis (Figure 8G). In contrast, steady-state pH_i in absence of CO₂/HCO₃^– and the capacity for Na⁺/H⁺ exchange show no relation to proliferation (Figure 7G) or metastasis (Figure 8G); and the protein expression of NHE1 is even negatively related to axillary lymph node metastasis (Figure 8G). Accordingly, high SLC4A7 but low SLC9A1 mRNA expression is associated with poor survival in select breast cancer molecular subtypes (Figures 9 and 10). Although the reason for these marked differences between NBCn1 and NHE1 is not yet entirely clear, distinct cellular and subcellular expression patterns (Boedtkjer et al., 2013; Lauritzen et al., 2012), allosteric regulation by pH_i and pH_o (Bonde and Boedtkjer, 2017; Boedtkjer et al., 2013; Hulikova et al., 2011), molecular interacting partners, and responses to auto-, para-, and endocrine signals (Boedtkjer et al., 2012; Boedtkjer and Aalkjaer, 2009; Danielsen et al., 2013) likely play important roles.

The impact of global steady-state pH_i on cell proliferation (Figure 7G) is consistent with earlier observations from cultured cell lines that cell cycle progression requires a permissive pH_i in the slightly alkaline range (Flinck et al., 2018). Low pH_i inhibits the enhanced DNA and protein synthesis preceding cell division although the exact molecular mechanisms have not yet been conclusively identified (Boedtkjer, 2019; Boedtkjer and Aalkjaer, 2013; Pouysségur et al., 1985; Ober and Pardee, 1987). We previously found that knockout of NBCn1 inhibits cell proliferation in murine breast cancer tissue, particularly in deep tumor regions and larger-sized tumors where fermentative glycolysis dominates and the cellular metabolic acid load is elevated (Lee et al., 2016; Lee et al., 2018).

Variation in the rate of acidic metabolic waste production and in the capacity for net acid extrusion shapes the local chemical environment and thereby influences the cancer cell phenotype important for disease progression. There is evidence that local pH_i induces cytoskeletal rearrangements (Bernstein et al., 2000; Pope et al., 2004) and that cell surface pH modifies cell-cell and cell-matrix interactions (Riemann et al., 2019; Stock et al., 2007), which in combination with acid-induced degradation of the extracellular matrix (Rofstad et al., 2006) can promote directional migration and metastasis. Differences in cell surface pH along the axis of migration have been reported for various migrating cells in culture based on differences in expression and activity of acid-base transporters between leading and rear ends (Schwab et al., 2012). We have previously found that migrating vascular smooth muscle cells generate NBCn1-dependent spatial pH gradients that are critical for directional migration (Boedtkjer et al., 2016), and the role of NBCn1 was subsequently supported by a study on a lung adenocarcinoma cell line (Hwang et al., 2020). Our current findings (Figure 8G) suggest that NBCn1-mediated Na⁺,HCO₃^– cotransport plays a similar role for the invasiveness of human breast cancer cells. Interestingly, the cellular capacity for net acid extrusion was not associated with other of the tested clinicopathological characteristics (Figure 6C,D), which supports that NBCn1 independently impact the metastatic potential of breast cancer cells (Figure 8G).

Based on the negative relationship between NHE1 expression and lymph node metastasis (Figure 8G) and considering the improved survival of luminal A breast cancer patients with high SLC9A1 expression (Figure 9D), we propose that NHE1 is a metastasis suppressor in human breast cancer. Metastasis suppressor proteins are frequently upregulated in early cancer disease, as their expression is lost during cancer progression rather than malignant transformation (Smith and Theodorescu, 2009; Guo et al., 1996). The spatiotemporal regulation of NHE1 expression during breast cancer development has not been investigated in detail. In studies of murine carcinogen-induced breast cancer, NHE1 protein levels were unchanged in the primary cancer tissue compared to normal breast tissue and showed a tendency to decline with increasing tumor size (Lee et al., 2016). In previous studies on human breast cancer tissue, NHE1 protein expression was very high in ductal carcinoma in situ lesions and elevated in early primary breast carcinomas, yet showed a tendency to decrease during metastatic progression (Boedtkjer et al., 2013; Lee et al., 2015). In the same human biopsy material, NBCn1 showed a continuous trend for progressively increasing protein levels from normal breast tissue, over primary breast carcinomas, to metastatic lesions (Boedtkjer et al., 2013). Previous investigations in MCF7 human breast cancer cells support the functional consequences of NHE1 observed in our human breast cancer cohort: NHE1 protein expression in the MCF7 cells markedly increased during heterologous overexpression of an amino-truncated ErbB2 receptor (Lauritzen et al., 2010), yet pharmacological inhibition of NHE1 under these conditions stimulated cell migration (Lauritzen et al., 2012).

Acid-base transporters play a key role for eliminating metabolic acidic waste, and hence their pathophysiological impact depends on the metabolic activity in the specific cancer tissue. This is particularly evident in triple-negative breast cancer that shows an overall low expression of SLC4A7 mRNA (Figure 10A). Nonetheless, the survival of triple-negative breast cancer patients is sensitive to variation in SLC4A7 transcript levels (Figure 10G) most likely due to high proliferative and metabolic activities (Figure 9—figure supplement 1) that challenge pH_i homeostasis. This observation supports that selectivity of anti-cancer therapies targeting acid-base transporters can be conferred not only by dramatic overexpression in cancer tissue relative to other tissues in the body but also by a greater functional dependency on net acid extrusion capacity in the cancer tissue. Pharmacological inhibitors of acid-base transporters have not yet reached clinical use. Previously described small molecule inhibitors of NBCn1 (e.g., S0859) do not provide the selectivity or pharmacokinetic properties necessary for systemic therapy (Boedtkjer et al., 2012; Larsen et al., 2012; Steinkamp et al., 2015); and whereas NHE1 inhibitors (e.g., cariporide, eniporide) reached phase 3 clinical studies for ischemic heart disease (Mentzer et al., 2008; Zeymer et al., 2001), they have not been sufficiently explored for cancer therapy. Recently developed inhibitors of monocarboxylate transporters show initial experimental promise as anti-cancer drugs (Beloueche-Babari et al., 2017).

Most current diagnostic procedures and selection of patients for targeted therapy (e.g., based on HER2 or estrogen receptors) rely on analysis of protein expression in fixed tissue. The current study validates that quantitative protein activity measurements and evaluation of functional contribution from specific molecular targets in viable tissue preparations provide additional clinically and prognostically important information. The independent information carried by RNA expression, protein expression, and acid-base transport activity suggests that considerable regulation occurs at translational and post-translational levels. The pH_i dynamics in the tumor tissue can therefore not be directly deduced from data on protein or gene expression. It is especially noticeable that the protein expression levels of NBCn1 and NHE1 (Figures 5E,F and 6E,F) are elevated in breast cancer tissue with HER2 overexpression or gene amplification despite low SLC4A7 and intermediate SLC9A1 mRNA levels (Figures 9A and 10A). For NBCn1, this inverse relationship between mRNA and protein expression is in congruence with previous reports from murine breast cancer tissue where ErbB2 overexpression is associated with significantly elevated NBCn1 protein levels despite a drastically decreased Slc4a7 mRNA level compared to normal breast tissue (Lee et al., 2018). Thus, increased translational activity or protein stability must be responsible for the raised NBCn1 protein levels in HER2-enriched breast cancer tissue. Because the SLC4A7 mRNA level—based on the abovementioned considerations—does not reflect the NBCn1 protein level or functional capacity in HER2-enriched breast cancer, the survival analysis based on SLC4A7 mRNA expression (Figure 10F) should be interpreted with caution for this molecular subtype. Even without a link between SLC4A7 mRNA expression and survival, the NBCn1 protein expression level and functional capacity could influence patient prognosis.

In light of the widespread use of HER2-targeted breast cancer therapy, it is intriguing that HER2 signaling shows apparently opposing effects on breast cancer progression by concurrently upregulating the protein expression of NBCn1 and NHE1 (Figures 5E,F and 8G). Our findings indicate that (a) additional detailed analysis of downstream signaling effects (e.g., relative upregulation of NBCn1 vs. NHE1) may provide more accurate predictive value than simple evaluation of HER2 overexpression and gene amplification and (b) selective targeting of individual HER2-activated effectors—including acid-base transporters—could optimize the current therapeutic approach based on direct HER2 inhibition.

Luminal A breast cancer differs from other breast cancer molecular subtypes in the profile whereby expression of acid-base transporters influences mortality rates. Elevated mRNA expression of SLC4A7 impedes (Figure 10D), SLC9A1 improves (Figure 9D), whereas SLC16A1 and SLC16A3 show no influence on (Figure 10—figure supplements 1D and 2D) patient survival in luminal A breast cancer. The observation regarding SLC16A3 is notable because high expression worsens (or tends to worsen) patient prognosis in the other breast cancer molecular subtypes (Figure 10—figure supplement 2C and E–G). Luminal A breast cancer comprises 50–70% of breast cancer cases in the United States and Europe (Kulkarni et al., 2019; Acheampong et al., 2020; Valla et al., 2016) and is clinically interesting because distant metastasis occurs throughout follow-up for as long as 25 years after initial diagnosis (Yu et al., 2019). This is different from, for instance, luminal B breast cancer where the risk of metastasis is high the first 5 years after diagnosis but then markedly declines (Yu et al., 2019). Given the identified link between acid-base conditions and metastasis (Figure 8), the distinct prognostic dependency of luminal A breast cancer patients on expression of acid-base transporters could hold a key to the underlying pathophysiology resulting in protracted metastatic risk.

Invasive lobular carcinomas show diffusely infiltrative growth patterns that differ from the dominant masses typical for invasive ductal carcinomas (Thomas et al., 2019). Lost expression of the cell-cell adhesion molecule E-cadherin can explain the tendency for cancer cells from lobular carcinomas to invade in single file (Gamallo et al., 1993; Pai et al., 2013), which is more difficult to delineate by mammography, and thus account for the higher positive surgical margin rates following lumpectomy procedures (van Deurzen, 2016). More efficient net acid extrusion in lobular compared to ductal breast carcinomas is evident from the greater elevation of pH_i by Na⁺,HCO₃^– cotransport (Figures 2 and 6) and likely translates to enhanced extracellular acidification. Thus, based on the downregulation of E-cadherin expression in response to extracellular acidosis—previously identified in cultured cell lines (Riemann et al., 2019; Suzuki et al., 2014)—it is an intriguing possibility that cellular acid-base handling in human breast carcinomas shapes the histology characteristic growth patterns.

To our knowledge, the current study reports from the largest existing human cancer cohort (Table 1) with detailed cellular acid-base information. Still, the size of the cohort comes with some limitations. Mortality rates for breast cancer patients undergoing breast-conserving surgery are generally low (Onitilo et al., 2015). Therefore, at currently 2–5 years of follow-up, we are unable to perform meaningful survival analyses linking directly to measurements of pH or protein expression. However, our meta-analysis based on transcriptomics data from larger cohorts with longer follow-up partly compensates for this limitation (Figures 9 and 10, and Figure 10—figure supplements 1 and 2). In addition, despite the large overall cohort size, we are for the individual subgroup analyses limited by the natural incidence of specific clinicopathological characteristics. For some of the less frequent characteristics—e.g., rarer histological types (Table 1)—the subgroups are too small for statistical comparison.

Whereas the short delay from tissue isolation to functional evaluation is a unique strength of the current study—because it minimizes the risk of phenotypical changes and thereby strengthens the connection to the clinical condition—it limits the experimental possibilities for detailed mechanistic and molecular studies. The experimental setup allows for manipulation and precise control of the buffer compositions; but with half-lives of protein degradation of 76 and 48 hr for NBCn1 and NHE1, respectively (Olesen et al., 2018), we cannot realistically reduce overall cellular protein levels by interfering with their expression—e.g., by RNAi knockdown technologies (Boedtkjer et al., 2006)—in the human biopsy material. Also, the available pharmacological options are too unspecific and without selectivity for individual Na⁺,HCO₃^– cotransporters (Boedtkjer et al., 2016; Boedtkjer et al., 2012; Larsen et al., 2012). Still, our previous studies confirm that the Na⁺,HCO₃^– cotransport in human breast cancer tissue is of low 4,4′-diisothiocyano-2,2′-stilbenedisulfonic acid sensitivity (Boedtkjer et al., 2013), which is a pharmacological characteristic of NBCn1 relative to other Na⁺,HCO₃^– cotransporters (Boedtkjer et al., 2012; Choi et al., 2000; Romero et al., 2004). This pharmacological profile thus corroborates strong recent molecular evidence—based on gene knockout technology—that the upregulated Na⁺,HCO₃^– cotransport in two different murine breast cancer models completely depends on NBCn1 (Lee et al., 2016; Lee et al., 2018).

In conclusion, we identify distinct patterns of pH_i dynamics as well as mRNA and protein expression of acid-base transporters among breast cancer patients based on clinical and pathological characteristics and molecular subtypes. The mechanisms of acidic waste product elimination reflect the heterogeneity in human breast cancer tissue. Dependency on Na⁺,HCO₃^– cotransport for steady-state pH_i regulation independently predicts proliferative activity, whereas the capacity for Na⁺,HCO₃^– cotransport activity and the expression of NBCn1 predict lymph node metastasis and patient survival. In contrast, NHE1 expression negatively predicts lymph node metastasis and patient survival. Together, these findings underscore the important pathophysiological role of acid-base homeostasis in human breast cancer tissue and emphasize the potential of acid-base transporters as anti-cancer targets.

In order to comply with the ethical approval, we share the human data presented in Figure 1–8 and corresponding figure supplements (data on acid-base transport activity, intracellular pH, and protein expression of transporters linked to clinicopathological information) in de-identified form. Following consultation with the legal team at the Regional Committee on Health Research Ethics, we have generated dataset files where restricted information is grouped in intervals each consisting of no less than five individuals. To provide the reader with the best possible data insight, we also show figure supplements with more detailed and advanced plots of the data and include the corresponding de-identified dataset. The meta analyses presented in Figure 9, 10, and corresponding figure supplements (data on RNA expression linked to patient survival) are based on data that have previously been published by other investigators, as detailed in the manuscript and the dataset list.

1. 1. van de Vijver MJ
   2. He YD
   3. van't Veer LJ
   4. Dai H
   5. Hart AA
   6. Voskuil DW
   7. Schreiber GJ
   8. Peterse JL
   9. Roberts C
   10. Marton MJ
   11. Parrish M
   12. Atsma D
   13. Witteveen A
   14. Glas A
   15. Delahaye L
   16. van der Velde T
   17. Bartelink H
   18. Rodenhuis S
   19. Rutgers ET
   20. Friend SH
   21. Bernards R

   (2002) Budczies J

   ID cancerdata. A gene-expression signature as a predictor of survival in breast cancer.

   http://bioconductor.org/packages/release/data/experiment/html/cancerdata.html
2. 1. Calza S
   2. Hall P
   3. Auer G
   4. Bjöhle J
   5. Klaar S
   6. Kronenwett U
   7. Liu ET
   8. Miller L
   9. Ploner A
   10. Smeds J
   11. Bergh J
   12. Pawitan Y

   (2006) Karolinska Institutet

   ID Intrinsic_Signature.zip. Intrinsic molecular signature of breast cancer in a population-based cohort of 412 patients.

   https://www.meb.ki.se/sites/yudpaw/wp-content/uploads/sites/5/papers/Intrinsic_Signature.zip
3. 1. Wang Y
   2. Klijn JGM
   3. Zhang Y
   4. Sieuwerts AM
   5. Look MP
   6. Yang F
   7. Talantov D
   8. Timmermans M
   9. van Gelder MEM
   10. Yu J
   11. Jatkoe T
   12. Berns EMJJ
   13. Atkins D
   14. Foekens JA

   (2006) NCBI Gene Expression Omnibus

   ID GSE1992. The molecular portraits of breast tumors are conserved across microarray platforms.

   https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE1992
4. 1. Wang Y
   2. Klijn JGM
   3. Zhang Y
   4. Sieuwerts AM
   5. Look MP
   6. Yang F
   7. Talantov D
   8. Timmermans M
   9. van Gelder MEM
   10. Yu J
   11. Jatkoe T
   12. Berns EMJJ
   13. Atkins D
   14. Foekens JA

   (2005) NCBI Gene Expression Omnibus

   ID GSE2034. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer.

   https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE2034
5. 1. Schmidt M
   2. Böhm D
   3. von Törne C
   4. Steiner E
   5. Puhl A
   6. Pilch H
   7. Lehr H-A
   8. Hengstler JG
   9. Kölbl H
   10. Gehrmann M

   (2008) NCBI Gene Expression Omnibus

   ID GSE11121. The humoral immune system has a key prognostic impact in node-negative breast cancer.

   https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE11121
6. 1. Bild AH
   2. Yao G
   3. Chang JT
   4. Wang Q
   5. Potti A
   6. Chasse D
   7. Joshi MB
   8. Harpole D
   9. Lancaster JM
   10. Berchuck A
   11. Olson Jr JA
   12. Marks JR
   13. Dressman HK
   14. West M
   15. Nevins JR

   (2006) NCBI Gene Expression Omnibus

   ID GSE3143. Oncogenic pathway signatures in human cancers as a guide to targeted therapies.

   https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE3143

1. 1. Aalkjaer C
   2. Boedtkjer E
   3. Choi I
   4. Lee S

   (2014) Cation-coupled bicarbonate transporters

   Comprehensive Physiology 4:1605–1637.

   https://doi.org/10.1002/cphy.c130005

   • PubMed
   • Google Scholar
2. 1. Acheampong T
   2. Kehm RD
   3. Terry MB
   4. Argov EL
   5. Tehranifar P

   (2020) Incidence trends of breast cancer molecular subtypes by age and race/ethnicity in the US from 2010 to 2016

   JAMA Network Open 3:e2013226.

   https://doi.org/10.1001/jamanetworkopen.2020.13226

   • PubMed
   • Google Scholar
3. 1. Amith SR
   2. Fliegel L

   (2017) Na⁺/H⁺ exchanger-mediated hydrogen ion extrusion as a carcinogenic signal in triple-negative breast cancer etiopathogenesis and prospects for its inhibition in therapeutics

   Seminars in Cancer Biology 43:35–41.

   https://doi.org/10.1016/j.semcancer.2017.01.004

   • PubMed
   • Google Scholar
4. 1. Ávalos-Moreno M
   2. López-Tejada A
   3. Blaya-Cánovas JL
   4. Cara-Lupiañez FE
   5. González-González A
   6. Lorente JA
   7. Sánchez-Rovira P
   8. Granados-Principal S

   (2020) Drug repurposing for triple-negative breast cancer

   Journal of Personalized Medicine 10:200.

   https://doi.org/10.3390/jpm10040200

   • Google Scholar
5. 1. Beloueche-Babari M
   2. Wantuch S
   3. Casals Galobart T
   4. Koniordou M
   5. Parkes HG
   6. Arunan V
   7. Chung YL
   8. Eykyn TR
   9. Smith PD
   10. Leach MO

   (2017) MCT1 inhibitor AZD3965 increases mitochondrial metabolism, facilitating combination therapy and noninvasive magnetic resonance spectroscopy

   Cancer Research 77:5913–5924.

   https://doi.org/10.1158/0008-5472.CAN-16-2686

   • PubMed
   • Google Scholar
6. 1. Bernstein BW
   2. Painter WB
   3. Chen H
   4. Minamide LS
   5. Abe H
   6. Bamburg JR

   (2000) Intracellular pH modulation of ADF/cofilin proteins

   Cell Motility and the Cytoskeleton 47:319–336.

   https://doi.org/10.1002/1097-0169(200012)47:4<319::AID-CM6>3.0.CO;2-I

   • PubMed
   • Google Scholar
7. 1. Bild AH
   2. Yao G
   3. Chang JT
   4. Wang Q
   5. Potti A
   6. Chasse D
   7. Joshi MB
   8. Harpole D
   9. Lancaster JM
   10. Berchuck A
   11. Olson JA
   12. Marks JR
   13. Dressman HK
   14. West M
   15. Nevins JR

   (2006) Oncogenic pathway signatures in human cancers as a guide to targeted therapies

   Nature 439:353–357.

   https://doi.org/10.1038/nature04296

   • PubMed
   • Google Scholar
8. 1. Boedtkjer E
   2. Praetorius J
   3. Aalkjaer C

   (2006) NBCn1 (slc4a7) mediates the Na⁺-dependent bicarbonate transport important for regulation of intracellular pH in mouse vascular smooth muscle cells

   Circulation Research 98:515–523.

   https://doi.org/10.1161/01.RES.0000204750.04971.76

   • PubMed
   • Google Scholar
9. 1. Boedtkjer E
   2. Bunch L
   3. Pedersen SF

   (2012) Physiology, pharmacology and pathophysiology of the pH regulatory transport proteins NHE1 and NBCn1: similarities, differences, and implications for cancer therapy

   Current Pharmaceutical Design 18:1345–1371.

   https://doi.org/10.2174/138161212799504830

   • PubMed
   • Google Scholar
10. 1. Boedtkjer E
    2. Moreira JM
    3. Mele M
    4. Vahl P
    5. Wielenga VT
    6. Christiansen PM
    7. Jensen VE
    8. Pedersen SF
    9. Aalkjaer C

    (2013) Contribution of Na⁺,HCO₃^–-cotransport to cellular pH control in human breast cancer: a role for the breast cancer susceptibility locus NBCn1 (SLC4A7)

    International Journal of Cancer 132:1288–1299.

    https://doi.org/10.1002/ijc.27782

    • PubMed
    • Google Scholar
11. 1. Boedtkjer E
    2. Bentzon JF
    3. Dam VS
    4. Aalkjaer C

    (2016) Na⁺, HCO₃^–-cotransporter NBCn1 increases pH_i gradients, filopodia, and migration of smooth muscle cells and promotes arterial remodelling

    Cardiovascular Research 111:227–239.

    https://doi.org/10.1093/cvr/cvw079

    • PubMed
    • Google Scholar
12. 1. Boedtkjer E

    (2019) Na⁺,HCO₃⁻ cotransporter NBCn1 accelerates breast carcinogenesis

    Cancer and Metastasis Reviews 38:165–178.

    https://doi.org/10.1007/s10555-019-09784-7

    • Google Scholar
13. 1. Boedtkjer E
    2. Aalkjaer C

    (2009) Insulin inhibits Na⁺/H⁺ exchange in vascular smooth muscle and endothelial cells in situ: involvement of H₂O₂ and tyrosine phosphatase SHP-2

    American Journal of Physiology. Heart and Circulatory Physiology 296:H247–H255.

    https://doi.org/10.1152/ajpheart.00725.2008

    • PubMed
    • Google Scholar
14. 1. Boedtkjer E
    2. Aalkjaer C

    (2012) Intracellular pH in the resistance vasculature: regulation and functional implications

    Journal of Vascular Research 49:479–496.

    https://doi.org/10.1159/000341235

    • PubMed
    • Google Scholar
15. 1. Boedtkjer E
    2. Aalkjaer C

    (2013) Acid-base transporters modulate cell migration, growth and proliferation: implications for structure development and remodeling of resistance arteries?

    Trends in Cardiovascular Medicine 23:59–65.

    https://doi.org/10.1016/j.tcm.2012.09.001

    • PubMed
    • Google Scholar
16. 1. Boedtkjer E
    2. Pedersen SF

    (2020) The acidic tumor microenvironment as a driver of cancer

    Annual Review of Physiology 82:103–126.

    https://doi.org/10.1146/annurev-physiol-021119-034627

    • PubMed
    • Google Scholar
17. 1. Bonde L
    2. Boedtkjer E

    (2017) Extracellular acidosis and very low [Na⁺] inhibit NBCn1- and NHE1-mediated net acid extrusion from mouse vascular smooth muscle cells

    Acta Physiologica 221:129–141.

    https://doi.org/10.1111/apha.12877

    • Google Scholar
18. 1. Boron WF
    2. De Weer P

    (1976) Intracellular pH transients in squid giant axons caused by CO₂, NH₃, and metabolic inhibitors

    Journal of General Physiology 67:91–112.

    https://doi.org/10.1085/jgp.67.1.91

    • PubMed
    • Google Scholar
19. 1. Calza S
    2. Hall P
    3. Auer G
    4. Bjöhle J
    5. Klaar S
    6. Kronenwett U
    7. Liu ET
    8. Miller L
    9. Ploner A
    10. Smeds J
    11. Bergh J
    12. Pawitan Y

    (2006) Intrinsic molecular signature of breast cancer in a population-based cohort of 412 patients

    Breast Cancer Research 8:R34.

    https://doi.org/10.1186/bcr1517

    • PubMed
    • Google Scholar
20. 1. Cassim S
    2. Pouyssegur J

    (2019) Tumor microenvironment: a metabolic player that shapes the immune response

    International Journal of Molecular Sciences 21:157.

    https://doi.org/10.3390/ijms21010157

    • PubMed
    • Google Scholar
21. 1. Choi I
    2. Aalkjaer C
    3. Boulpaep EL
    4. Boron WF

    (2000) An electroneutral sodium/bicarbonate cotransporter NBCn1 and associated sodium channel

    Nature 405:571–575.

    https://doi.org/10.1038/35014615

    • PubMed
    • Google Scholar
22. 1. Coates AS
    2. Winer EP
    3. Goldhirsch A
    4. Gelber RD
    5. Gnant M
    6. Piccart-Gebhart M
    7. Thürlimann B
    8. Senn HJ
    9. Panel Members

    (2015) Tailoring therapies--improving the management of early breast cancer: St Gallen international expert consensus on the primary therapy of early breast cancer 2015

    Annals of Oncology 26:1533–1546.

    https://doi.org/10.1093/annonc/mdv221

    • PubMed
    • Google Scholar
23. 1. Connell CM
    2. Doherty GJ

    (2017) Activating HER2 mutations as emerging targets in multiple solid cancers

    ESMO Open 2:e000279.

    https://doi.org/10.1136/esmoopen-2017-000279

    • PubMed
    • Google Scholar
24. 1. Dai X
    2. Li T
    3. Bai Z
    4. Yang Y
    5. Liu X
    6. Zhan J
    7. Shi B

    (2015)

    Breast cancer intrinsic subtype classification, clinical use and future trends

    American Journal of Cancer Research 5:2929–2943.

    • PubMed
    • Google Scholar
25. 1. Damkier HH
    2. Nielsen S
    3. Praetorius J

    (2006) An anti-NH₂-terminal antibody localizes NBCn1 to heart endothelia and skeletal and vascular smooth muscle cells

    American Journal of Physiology-Heart and Circulatory Physiology 290:H172–H180.

    https://doi.org/10.1152/ajpheart.00713.2005

    • PubMed
    • Google Scholar
26. 1. Danielsen AA
    2. Parker MD
    3. Lee S
    4. Boron WF
    5. Aalkjaer C
    6. Boedtkjer E

    (2013) Splice cassette II of Na⁺,HCO₃^– cotransporter NBCn1 (slc4a7) interacts with calcineurin A: implications for transporter activity and intracellular pH control during rat artery contractions

    The Journal of Biological Chemistry 288:8146–8155.

    https://doi.org/10.1074/jbc.M113.455386

    • PubMed
    • Google Scholar
27. 1. Flinck M
    2. Kramer SH
    3. Pedersen SF

    (2018) Roles of pH in control of cell proliferation

    Acta Physiologica 223:e13068.

    https://doi.org/10.1111/apha.13068

    • Google Scholar
28. 1. Gamallo C
    2. Palacios J
    3. Suarez A
    4. Pizarro A
    5. Navarro P
    6. Quintanilla M
    7. Cano A

    (1993)

    Correlation of E-cadherin expression with differentiation grade and histological type in breast carcinoma

    The American Journal of Pathology 142:987–993.

    • PubMed
    • Google Scholar
29. 1. Guo X
    2. Friess H
    3. Graber HU
    4. Kashiwagi M
    5. Zimmermann A
    6. Korc M
    7. Büchler MW

    (1996)

    KAI1 expression is up-regulated in early pancreatic cancer and decreased in the presence of metastases

    Cancer Research 56:4876–4880.

    • PubMed
    • Google Scholar
30. 1. Guo Z
    2. Zhang T
    3. Li X
    4. Wang Q
    5. Xu J
    6. Yu H
    7. Zhu J
    8. Wang H
    9. Wang C
    10. Topol EJ
    11. Wang Q
    12. Rao S

    (2005) Towards precise classification of cancers based on robust gene functional expression profiles

    BMC Bioinformatics 6:58.

    https://doi.org/10.1186/1471-2105-6-58

    • PubMed
    • Google Scholar
31. 1. Hu Z
    2. Fan C
    3. Oh DS
    4. Marron JS
    5. He X
    6. Qaqish BF
    7. Livasy C
    8. Carey LA
    9. Reynolds E
    10. Dressler L
    11. Nobel A
    12. Parker J
    13. Ewend MG
    14. Sawyer LR
    15. Wu J
    16. Liu Y
    17. Nanda R
    18. Tretiakova M
    19. Ruiz Orrico A
    20. Dreher D
    21. Palazzo JP
    22. Perreard L
    23. Nelson E
    24. Mone M
    25. Hansen H
    26. Mullins M
    27. Quackenbush JF
    28. Ellis MJ
    29. Olopade OI
    30. Bernard PS
    31. Perou CM

    (2006) The molecular portraits of breast tumors are conserved across microarray platforms

    BMC Genomics 7:96.

    https://doi.org/10.1186/1471-2164-7-96

    • PubMed
    • Google Scholar
32. 1. Hulikova A
    2. Vaughan-Jones RD
    3. Swietach P

    (2011) Dual role of CO₂/HCO₃^– buffer in the regulation of intracellular pH of three-dimensional tumor growths

    Journal of Biological Chemistry 286:13815–13826.

    https://doi.org/10.1074/jbc.M111.219899

    • PubMed
    • Google Scholar
33. 1. Hwang S
    2. Shin DM
    3. Hong JH

    (2020) Protective role of IRBIT on sodium bicarbonate cotransporter-n1 for migratory cancer cells

    Pharmaceutics 12:816.

    https://doi.org/10.3390/pharmaceutics12090816

    • Google Scholar
34. 1. Kulkarni A
    2. Stroup AM
    3. Paddock LE
    4. Hill SM
    5. Plascak JJ
    6. Llanos AAM

    (2019) Breast cancer incidence and mortality by molecular subtype: statewide age and racial/ethnic disparities in New Jersey

    Cancer Health Disparities 3:e1–e17.

    https://doi.org/10.9777/chd.2019.1012

    • PubMed
    • Google Scholar
35. 1. Larsen AM
    2. Krogsgaard-Larsen N
    3. Lauritzen G
    4. Olesen CW
    5. Honoré Hansen S
    6. Boedtkjer E
    7. Pedersen SF
    8. Bunch L

    (2012) Gram-scale solution-phase synthesis of selective sodium bicarbonate co-transport inhibitor S0859: in vitro efficacy studies in breast cancer cells

    ChemMedChem 7:1808–1814.

    https://doi.org/10.1002/cmdc.201200335

    • PubMed
    • Google Scholar
36. 1. Lauritzen G
    2. Jensen MB
    3. Boedtkjer E
    4. Dybboe R
    5. Aalkjaer C
    6. Nylandsted J
    7. Pedersen SF

    (2010) NBCn1 and NHE1 expression and activity in ΔNErbB2 receptor-expressing MCF-7 breast cancer cells: contributions to pH_i regulation and chemotherapy resistance

    Experimental Cell Research 316:2538–2553.

    https://doi.org/10.1016/j.yexcr.2010.06.005

    • PubMed
    • Google Scholar
37. 1. Lauritzen G
    2. Stock CM
    3. Lemaire J
    4. Lund SF
    5. Jensen MF
    6. Damsgaard B
    7. Petersen KS
    8. Wiwel M
    9. Rønnov-Jessen L
    10. Schwab A
    11. Pedersen SF

    (2012) The Na⁺/H⁺ exchanger NHE1, but not the Na⁺,HCO₃^– cotransporter NBCn1, regulates motility of MCF7 breast cancer cells expressing constitutively active ErbB2

    Cancer Letters 317:172–183.

    https://doi.org/10.1016/j.canlet.2011.11.023

    • PubMed
    • Google Scholar
38. 1. Lee S
    2. Mele M
    3. Vahl P
    4. Christiansen PM
    5. Jensen VE
    6. Boedtkjer E

    (2015) Na⁺,HCO₃^–-cotransport is functionally upregulated during human breast carcinogenesis and required for the inverted pH gradient across the plasma membrane

    Pflügers Archiv - European Journal of Physiology 467:367–377.

    https://doi.org/10.1007/s00424-014-1524-0

    • PubMed
    • Google Scholar
39. 1. Lee S
    2. Axelsen TV
    3. Andersen AP
    4. Vahl P
    5. Pedersen SF
    6. Boedtkjer E

    (2016) Disrupting Na⁺, HCO₃⁻-cotransporter NBCn1 (Slc4a7) delays murine breast cancer development

    Oncogene 35:2112–2122.

    https://doi.org/10.1038/onc.2015.273

    • PubMed
    • Google Scholar
40. 1. Lee S
    2. Axelsen TV
    3. Jessen N
    4. Pedersen SF
    5. Vahl P
    6. Boedtkjer E

    (2018) Na⁺,HCO₃^–-cotransporter NBCn1 (Slc4a7) accelerates ErbB2-induced breast cancer development and tumor growth in mice

    Oncogene 37:5569–5584.

    https://doi.org/10.1038/s41388-018-0353-6

    • PubMed
    • Google Scholar
41. 1. Loo SY
    2. Chang MK
    3. Chua CS
    4. Kumar AP
    5. Pervaiz S
    6. Clement MV

    (2012) NHE-1: a promising target for novel anti-cancer therapeutics

    Current Pharmaceutical Design 18:1372–1382.

    https://doi.org/10.2174/138161212799504885

    • PubMed
    • Google Scholar
42. 1. Mentzer RM
    2. Bartels C
    3. Bolli R
    4. Boyce S
    5. Buckberg GD
    6. Chaitman B
    7. Haverich A
    8. Knight J
    9. Menasché P
    10. Myers ML
    11. Nicolau J
    12. Simoons M
    13. Thulin L
    14. Weisel RD
    15. EXPEDITION Study Investigators

    (2008) Sodium-hydrogen exchange inhibition by cariporide to reduce the risk of ischemic cardiac events in patients undergoing coronary artery bypass grafting: results of the EXPEDITION study

    The Annals of Thoracic Surgery 85:1261–1270.

    https://doi.org/10.1016/j.athoracsur.2007.10.054

    • PubMed
    • Google Scholar
43. 1. Ober SS
    2. Pardee AB

    (1987) Intracellular pH is increased after transformation of chinese hamster embryo fibroblasts

    PNAS 84:2766–2770.

    https://doi.org/10.1073/pnas.84.9.2766

    • PubMed
    • Google Scholar
44. 1. Oh H
    2. Eliassen AH
    3. Beck AH
    4. Rosner B
    5. Schnitt SJ
    6. Collins LC
    7. Connolly JL
    8. Montaser-Kouhsari L
    9. Willett WC
    10. Tamimi RM

    (2017) Breast cancer risk factors in relation to estrogen receptor, progesterone receptor, insulin-like growth factor-1 receptor, and Ki67 expression in normal breast tissue

    Npj Breast Cancer 3:39.

    https://doi.org/10.1038/s41523-017-0041-7

    • PubMed
    • Google Scholar
45. 1. Olesen CW
    2. Vogensen J
    3. Axholm I
    4. Severin M
    5. Schnipper J
    6. Pedersen IS
    7. von Stemann JH
    8. Schrøder JM
    9. Christensen DP
    10. Pedersen SF

    (2018) Trafficking, localization and degradation of the Na⁺,HCO₃^– co-transporter NBCn1 in kidney and breast epithelial cells

    Scientific Reports 8:7435.

    https://doi.org/10.1038/s41598-018-25059-7

    • PubMed
    • Google Scholar
46. 1. Onitilo AA
    2. Engel JM
    3. Stankowski RV
    4. Doi SA

    (2015) Survival comparisons for breast conserving surgery and mastectomy revisited: community experience and the role of radiation therapy

    Clinical Medicine & Research 13:65–73.

    https://doi.org/10.3121/cmr.2014.1245

    • PubMed
    • Google Scholar
47. 1. Pai K
    2. Baliga P
    3. Shrestha BL

    (2013) E-cadherin expression: a diagnostic utility for differentiating breast carcinomas with ductal and lobular morphologies

    Journal of Clinical and Diagnostic Research 7:840–844.

    https://doi.org/10.7860/JCDR/2013/5755.2954

    • PubMed
    • Google Scholar
48. 1. Parker JS
    2. Mullins M
    3. Cheang MC
    4. Leung S
    5. Voduc D
    6. Vickery T
    7. Davies S
    8. Fauron C
    9. He X
    10. Hu Z
    11. Quackenbush JF
    12. Stijleman IJ
    13. Palazzo J
    14. Marron JS
    15. Nobel AB
    16. Mardis E
    17. Nielsen TO
    18. Ellis MJ
    19. Perou CM
    20. Bernard PS

    (2009) Supervised risk predictor of breast cancer based on intrinsic subtypes

    Journal of Clinical Oncology 27:1160–1167.

    https://doi.org/10.1200/JCO.2008.18.1370

    • PubMed
    • Google Scholar
49. 1. Parks SK
    2. Chiche J
    3. Pouysségur J

    (2013) Disrupting proton dynamics and energy metabolism for cancer therapy

    Nature Reviews Cancer 13:611–623.

    https://doi.org/10.1038/nrc3579

    • PubMed
    • Google Scholar
50. 1. Parks SK
    2. Cormerais Y
    3. Pouysségur J

    (2017) Hypoxia and cellular metabolism in tumour pathophysiology

    The Journal of Physiology 595:2439–2450.

    https://doi.org/10.1113/JP273309

    • PubMed
    • Google Scholar
51. 1. Pedersen SF

    (2006) The Na⁺/H⁺ exchanger NHE1 in stress-induced signal transduction: implications for cell proliferation and cell death

    Pflügers Archiv - European Journal of Physiology 452:249–259.

    https://doi.org/10.1007/s00424-006-0044-y

    • PubMed
    • Google Scholar
52. 1. Pérez-Escuredo J
    2. Van Hée VF
    3. Sboarina M
    4. Falces J
    5. Payen VL
    6. Pellerin L
    7. Sonveaux P

    (2016) Monocarboxylate transporters in the brain and in cancer

    Biochimica et Biophysica Acta (BBA) - Molecular Cell Research 1863:2481–2497.

    https://doi.org/10.1016/j.bbamcr.2016.03.013

    • PubMed
    • Google Scholar
53. 1. Perou CM
    2. Sørlie T
    3. Eisen MB
    4. van de Rijn M
    5. Jeffrey SS
    6. Rees CA
    7. Pollack JR
    8. Ross DT
    9. Johnsen H
    10. Akslen LA
    11. Fluge O
    12. Pergamenschikov A
    13. Williams C
    14. Zhu SX
    15. Lønning PE
    16. Børresen-Dale AL
    17. Brown PO
    18. Botstein D

    (2000) Molecular portraits of human breast tumours

    Nature 406:747–752.

    https://doi.org/10.1038/35021093

    • PubMed
    • Google Scholar
54. 1. Persi E
    2. Wolf YI
    3. Horn D
    4. Ruppin E
    5. Demichelis F
    6. Gatenby RA
    7. Gillies RJ
    8. Koonin EV

    (2021) Mutation-selection balance and compensatory mechanisms in tumour evolution

    Nature Reviews Genetics 22:251–262.

    https://doi.org/10.1038/s41576-020-00299-4

    • PubMed
    • Google Scholar
55. 1. Pope BJ
    2. Zierler-Gould KM
    3. Kühne R
    4. Weeds AG
    5. Ball LJ

    (2004) Solution structure of human cofilin: actin binding, pH sensitivity, and relationship to actin-depolymerizing factor

    The Journal of Biological Chemistry 279:4840–4848.

    https://doi.org/10.1074/jbc.M310148200

    • PubMed
    • Google Scholar
56. 1. Pouysségur J
    2. Franchi A
    3. L'Allemain G
    4. Paris S

    (1985) Cytoplasmic pH, a key determinant of growth factor-induced DNA synthesis in quiescent fibroblasts

    FEBS Letters 190:115–119.

    https://doi.org/10.1016/0014-5793(85)80439-7

    • PubMed
    • Google Scholar
57. 1. Rakha EA
    2. Reis-Filho JS
    3. Baehner F
    4. Dabbs DJ
    5. Decker T
    6. Eusebi V
    7. Fox SB
    8. Ichihara S
    9. Jacquemier J
    10. Lakhani SR
    11. Palacios J
    12. Richardson AL
    13. Schnitt SJ
    14. Schmitt FC
    15. Tan PH
    16. Tse GM
    17. Badve S
    18. Ellis IO

    (2010) Breast cancer prognostic classification in the molecular era: the role of histological grade

    Breast Cancer Research 12:207.

    https://doi.org/10.1186/bcr2607

    • PubMed
    • Google Scholar
58. 1. Riemann A
    2. Rauschner M
    3. Gießelmann M
    4. Reime S
    5. Haupt V
    6. Thews O

    (2019) Extracellular acidosis modulates the expression of Epithelial-Mesenchymal transition (EMT) Markers and adhesion of epithelial and tumor cells

    Neoplasia 21:450–458.

    https://doi.org/10.1016/j.neo.2019.03.004

    • Google Scholar
59. 1. Rofstad EK
    2. Mathiesen B
    3. Kindem K
    4. Galappathi K

    (2006) Acidic extracellular pH promotes experimental metastasis of human melanoma cells in athymic nude mice

    Cancer Research 66:6699–6707.

    https://doi.org/10.1158/0008-5472.CAN-06-0983

    • PubMed
    • Google Scholar
60. 1. Rolver MG
    2. Elingaard-Larsen LO
    3. Andersen AP
    4. Counillon L
    5. Pedersen SF

    (2020) Pyrazine ring-based Na⁺/H⁺ exchanger (NHE) inhibitors potently inhibit cancer cell growth in 3D culture, independent of NHE1

    Scientific Reports 10:5800.

    https://doi.org/10.1038/s41598-020-62430-z

    • PubMed
    • Google Scholar
61. 1. Romero MF
    2. Fulton CM
    3. Boron WF

    (2004) The SLC4 family of HCO₃^– transporters

    Pflugers Archiv - European Journal of Physiology 447:495–509.

    https://doi.org/10.1007/s00424-003-1180-2

    • PubMed
    • Google Scholar
62. 1. Roos A
    2. Boron WF

    (1981) Intracellular pH

    Physiological Reviews 61:296–434.

    https://doi.org/10.1152/physrev.1981.61.2.296

    • PubMed
    • Google Scholar
63. 1. Schmidt M
    2. Böhm D
    3. von Törne C
    4. Steiner E
    5. Puhl A
    6. Pilch H
    7. Lehr HA
    8. Hengstler JG
    9. Kölbl H
    10. Gehrmann M

    (2008) The humoral immune system has a key prognostic impact in node-negative breast cancer

    Cancer Research 68:5405–5413.

    https://doi.org/10.1158/0008-5472.CAN-07-5206

    • PubMed
    • Google Scholar
64. 1. Schwab A
    2. Fabian A
    3. Hanley PJ
    4. Stock C

    (2012) Role of ion channels and transporters in cell migration

    Physiological Reviews 92:1865–1913.

    https://doi.org/10.1152/physrev.00018.2011

    • PubMed
    • Google Scholar
65. 1. Shyamala G

    (1997) Roles of estrogen and progesterone in normal mammary gland development insights from progesterone receptor null mutant mice and in situ localization of receptor

    Trends in Endocrinology and Metabolism: TEM 8:34–39.

    https://doi.org/10.1016/s1043-2760(96)00207-x

    • PubMed
    • Google Scholar
66. 1. Smith SC
    2. Theodorescu D

    (2009) Learning therapeutic lessons from metastasis suppressor proteins

    Nature Reviews Cancer 9:253–264.

    https://doi.org/10.1038/nrc2594

    • PubMed
    • Google Scholar
67. 1. Sørlie T
    2. Perou CM
    3. Tibshirani R
    4. Aas T
    5. Geisler S
    6. Johnsen H
    7. Hastie T
    8. Eisen MB
    9. van de Rijn M
    10. Jeffrey SS
    11. Thorsen T
    12. Quist H
    13. Matese JC
    14. Brown PO
    15. Botstein D
    16. Lønning PE
    17. Børresen-Dale AL

    (2001) Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications

    PNAS 98:10869–10874.

    https://doi.org/10.1073/pnas.191367098

    • PubMed
    • Google Scholar
68. 1. Steinkamp A-D
    2. Seling N
    3. Lee S
    4. Boedtkjer E
    5. Bolm C

    (2015) Synthesis of N-cyano-substituted sulfilimine and sulfoximine derivatives of S0859 and their biological evaluation as sodium bicarbonate co-transport inhibitors

    MedChemComm 6:2163–2169.

    https://doi.org/10.1039/C5MD00367A

    • Google Scholar
69. 1. Stock C
    2. Gassner B
    3. Hauck CR
    4. Arnold H
    5. Mally S
    6. Eble JA
    7. Dieterich P
    8. Schwab A

    (2005) Migration of human melanoma cells depends on extracellular pH and Na⁺/H⁺ exchange

    The Journal of Physiology 567:225–238.

    https://doi.org/10.1113/jphysiol.2005.088344

    • PubMed
    • Google Scholar
70. 1. Stock C
    2. Mueller M
    3. Kraehling H
    4. Mally S
    5. Noël J
    6. Eder C
    7. Schwab A

    (2007) pH nanoenvironment at the surface of single melanoma cells

    Cellular Physiology and Biochemistry 20:679–686.

    https://doi.org/10.1159/000107550

    • PubMed
    • Google Scholar
71. 1. Stock C
    2. Pedersen SF

    (2017) Roles of pH and the Na⁺/H⁺ exchanger NHE1 in cancer: from cell biology and animal models to an emerging translational perspective?

    Seminars in Cancer Biology 43:5–16.

    https://doi.org/10.1016/j.semcancer.2016.12.001

    • PubMed
    • Google Scholar
72. 1. Stransky L
    2. Cotter K
    3. Forgac M

    (2016) The function of V-ATPases in cancer

    Physiological Reviews 96:1071–1091.

    https://doi.org/10.1152/physrev.00035.2015

    • PubMed
    • Google Scholar
73. 1. Suzuki A
    2. Maeda T
    3. Baba Y
    4. Shimamura K
    5. Kato Y

    (2014) Acidic extracellular pH promotes epithelial mesenchymal transition in Lewis lung carcinoma model

    Cancer Cell International 14:129.

    https://doi.org/10.1186/s12935-014-0129-1

    • PubMed
    • Google Scholar
74. 1. Thomas JA
    2. Buchsbaum RN
    3. Zimniak A
    4. Racker E

    (1979) Intracellular pH measurements in Ehrlich ascites tumor cells utilizing spectroscopic probes generated in situ

    Biochemistry 18:2210–2218.

    https://doi.org/10.1021/bi00578a012

    • PubMed
    • Google Scholar
75. 1. Thomas M
    2. Kelly ED
    3. Abraham J
    4. Kruse M

    (2019) Invasive lobular breast cancer: a review of pathogenesis, diagnosis, management, and future directions of early stage disease

    Seminars in Oncology 46:121–132.

    https://doi.org/10.1053/j.seminoncol.2019.03.002

    • PubMed
    • Google Scholar
76. 1. Valla M
    2. Vatten LJ
    3. Engstrøm MJ
    4. Haugen OA
    5. Akslen LA
    6. Bjørngaard JH
    7. Hagen AI
    8. Ytterhus B
    9. Bofin AM
    10. Opdahl S

    (2016) Molecular subtypes of breast cancer: long-term incidence trends and prognostic differences

    Cancer Epidemiology Biomarkers & Prevention 25:1625–1634.

    https://doi.org/10.1158/1055-9965.EPI-16-0427

    • PubMed
    • Google Scholar
77. 1. van de Vijver MJ
    2. He YD
    3. van't Veer LJ
    4. Dai H
    5. Hart AA
    6. Voskuil DW
    7. Schreiber GJ
    8. Peterse JL
    9. Roberts C
    10. Marton MJ
    11. Parrish M
    12. Atsma D
    13. Witteveen A
    14. Glas A
    15. Delahaye L
    16. van der Velde T
    17. Bartelink H
    18. Rodenhuis S
    19. Rutgers ET
    20. Friend SH
    21. Bernards R

    (2002) A gene-expression signature as a predictor of survival in breast cancer

    New England Journal of Medicine 347:1999–2009.

    https://doi.org/10.1056/NEJMoa021967

    • PubMed
    • Google Scholar
78. 1. van Deurzen CH

    (2016) Predictors of surgical margin following breast-conserving surgery: a large population-based cohort study

    Annals of Surgical Oncology 23:627–633.

    https://doi.org/10.1245/s10434-016-5532-5

    • PubMed
    • Google Scholar
79. 1. Vaupel P
    2. Kallinowski F
    3. Okunieff P

    (1989)

    Blood flow, oxygen and nutrient supply, and metabolic microenvironment of human tumors: a review

    Cancer Research 49:6449–6465.

    • Google Scholar
80. 1. Voss NCS
    2. Dreyer T
    3. Henningsen MB
    4. Vahl P
    5. Honoré B
    6. Boedtkjer E

    (2020) Targeting the acidic tumor microenvironment: unexpected pro-neoplastic effects of oral NaHCO₃ therapy in murine breast tissue

    Cancers 12:891.

    https://doi.org/10.3390/cancers12040891

    • Google Scholar
81. 1. Wang Y
    2. Klijn JG
    3. Zhang Y
    4. Sieuwerts AM
    5. Look MP
    6. Yang F
    7. Talantov D
    8. Timmermans M
    9. Meijer-van Gelder ME
    10. Yu J
    11. Jatkoe T
    12. Berns EM
    13. Atkins D
    14. Foekens JA

    (2005) Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer

    The Lancet 365:671–679.

    https://doi.org/10.1016/S0140-6736(05)17947-1

    • PubMed
    • Google Scholar
82. 1. Xu H
    2. Ghishan FK
    3. Kiela PR

    (2018) SLC9 gene family: function, expression, and regulation

    Comprehensive Physiology 8:555–583.

    https://doi.org/10.1002/cphy.c170027

    • PubMed
    • Google Scholar
83. 1. Yu NY
    2. Iftimi A
    3. Yau C
    4. Tobin NP
    5. van 't Veer L
    6. Hoadley KA
    7. Benz CC
    8. Nordenskjöld B
    9. Fornander T
    10. Stål O
    11. Czene K
    12. Esserman LJ
    13. Lindström LS

    (2019) Assessment of long-term distant recurrence-free survival associated with tamoxifen therapy in postmenopausal patients with luminal A or luminal B breast cancer

    JAMA Oncology 5:1304–1309.

    https://doi.org/10.1001/jamaoncol.2019.1856

    • PubMed
    • Google Scholar
84. 1. Zeymer U
    2. Suryapranata H
    3. Monassier JP
    4. Opolski G
    5. Davies J
    6. Rasmanis G
    7. Linssen G
    8. Tebbe U
    9. Schröder R
    10. Tiemann R
    11. Machnig T
    12. Neuhaus KL
    13. ESCAMI Investigators

    (2001) The Na⁺/H⁺ exchange inhibitor eniporide as an adjunct to early reperfusion therapy for acute myocardial infarction. Results of the evaluation of the safety and cardioprotective effects of eniporide in acute myocardial infarction (ESCAMI) trial

    Journal of the American College of Cardiology 38:1644–1650.

    https://doi.org/10.1016/s0735-1097(01)01608-4

    • PubMed
    • Google Scholar

Acceptance summary:

Dysregulated acid-base microenvironment has been revealed to be associated with several adverse outcomes, such as drug resistance and enhanced aggression. In this research a large-scale cohort comprised of patient-derived organoids were employed mimicking exactly the condition under clinical setting to observe effect of dysregulated acid-base transporter on clinical parameters and survival. This work provides potential novel therapeutic avenue through targeting acid-base transporter regulating pH.

Decision letter after peer review:

Thank you for submitting your article "Acid-base transporters and pH dynamics in human breast carcinomas predict proliferative activity, metastasis, and survival" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, including Caigang Liu as the Reviewing Editor and Reviewer #1, and the evaluation has been overseen by Maureen Murphy as the Senior Editor.

The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.

Essential revisions:

1) Most of the conclusions could be well supported by clinical data statistics. However, there still exist some concerns expected to be explained, especially, detailed mechanism or therapeutic strategies description regarding pH dysregulation are deficient.

2) There are several contradictory and confusing conclusions in the manuscript remaining to be discussed. It would be better to reorganize the manuscript in a clearer and more convincing manner to present the data in the study.

Reviewer #1:

The authors launched an observational study on 110 breast cancer organoids, measured the cancer and normal cell net acid extrusion capacity to correlate different clinicopathological parameters with intracellular pH regulator (NHE1 and NBCn1) level, and unravel the relationship between them and tumor proliferation, lymph node metastasis together with the impact of cotransporter mRNA on patient's survival, thus highlighting the role of pH regulator in malignancy. This study was performed on a large-scale cohort based on tissue samples to comprehensively reflect the heterogeneity setting. However, there lacks detailed mechanism or therapeutic strategies description regarding pH dysregulation. The data has been sufficient to hold back the views proposed and the results will provide better understanding for the role of dysregulated pH in cancer progression and help future studies regarding targeting pH regulator in managing cancer.

1. In Figure 9 and 10, SLC9A1 and SLC4A7 mRNA level was analyzed for their correlation with survival outcome, it would be better to supplement survival analysis regarding the expression of SLC9A1 and SLC4A7 protein based on your study cohort.

2. Please specify the reasons for ER and Ki-67 cut-off value setting and include them in Method or insert supporting reference literature.

3. It is described in lines 320-321 that the protein expression level of NHE1 and NBCn1 was not significantly influenced by estrogen receptor status. And it is described in lines 333-335 that the protein expression levels of NHE1 as well as NBCn1 were elevated in breast carcinomas with HER2 overexpression or gene amplification both before and after adjustment for other clinicopathological characteristics. But the survival figures of Figure 9, 10 indicated that 'For patients with HER2-enriched breast cancer, we saw no association of SLC4A7 or SLC9A1 mRNA expression with survival; The high overall SLC4A7 expression level in Luminal A breast cancer suggests a prominent role of NBCn1 in this breast cancer molecular subtype. And patients with high SLC9A1 mRNA expression suffering from Luminal A breast cancer showed significantly improved survival (hazard ratio 0.552) compared to patients with low SLC9A1 mRNA expression'. The conclusions seem to be contradictory, please explain this.

4. In lines 75-81: 'In human and murine breast cancer tissue analyzed without stratification by molecular subtype, Na+, HCO₃^- cotransport activity is elevated and protein expression of the NBCn1 (SLC4A7) and MCT1 (SLC16A1) and MCT4 (SLC16A3) are upregulated compared to normal breast tissue. Protein expression of the NHE1 (SLC9A1) is either unchanged or moderately upregulated when breast cancer tissue as one unstratified group is compared to normal breast tissue.' However, worse prognosis was observed in patients suffering from Luminal A or Basal-like/triple-negative breast cancer with high SLC4A7 and/or low SLC9A1 mRNA expression. The expression level of NHE1 (SLC9A1) and the prognostic data are conflicting, please discuss it in detail.

5. The authors found that the expressions of NBCn1 and NHE1 were related to lymph node metastasis and cancer cell proliferation. However, lymph node metastasis and cancer cell proliferation are both key factors predicting worse prognosis. The existing data cannot indicate whether intratumor PH directly affects the patient's prognosis, or indirectly affects the prognosis through lymph nodes metastasis or cancer cell proliferation. Please add survival charts of patients in different subgroups to illustrate it.

6. The authors separately verified the effects of NBCn1 (SLC4A7), MCT1 (SLC16A1), MCT4 (SLC16A3) and NHE1 (SLC9A1) on the prognosis of patients, but whether there exist synergistic or antagonistic effect among the four genes, or whether there is mutual regulation relationship should be addressed.

7. This manuscript requires a more comprehensive summary regarding previous reported role of abnormal pH in promoting cancer in Introduction, and the same about mechanism description and future interfering strategies in Discussion to help readers comprehend this field more conveniently.

8. Breast cancer organoids are mainly composed of cytokeratin 19-positive epithelial cells while the authors only provide the microscopic pictures. It would be better to provide immunofluorescence or IHC staining pictures of cytokeratin 19-positive epithelial cells.

9. Several references date 20 years ago, new references supporting the authors' findings would strengthen the hypothesis. Meanwhile, please arrange it in accordance with the reference format required by eLife.

Reviewer #2:

In this extensive study, authors have shown that Na+,HCO₃^- cotransport and Na+/H⁺-exchange transporters predominantly mediate overall cellular acid extrusion in breast cancer microenvironment. In addition, authors demonstrate that higher activity of Na+,HCO₃^--cotransport correlates with increased growth and lymph node metastasis of breast cancer. The mechanistic insights gained from the study will help in the development of therapeutic strategies for breast cancers. The strengths of this study include the use of organoid culture system, and detailed cellular acid-base homeostasis analyses in an extensive cohort of breast cancer patients. Overall, this study is of interest to the peers working in the breast cancer field.

1. It would be interesting if the authors have used genetic knockdown or specific inhibitors against NBCn1 and NHE1 in breast cancer organoids to avoid the redundant functions of other ion exchangers.

2. Did the authors analyze the expression of angiogenic markers such as CD31 or CD34 in the patient samples?

3. For the ease of readers, in Figure 1B, authors should also highlight the observations on expression and correlation of NBCn1 and NHE1 with overall survival in different breast cancer subtypes.

4. Authors should discuss the possible limitations of their study in the Discussion part of the manuscript.

5. Please correct the spelling of Maier to Kaplan-Meier in methods.

6. In Figure 1 E, authors should use only one asterisk to show the statistical significance between the groups.

Reviewer #3:

Nicolai J. Toft et al. investigated the feature of acid-base metabolism in breast cancer tissue from several aspects, revealing the underlying mechanism of pH regulation according to the heterogeneity. Moreover, the acid-base transport and intracellular pH state were proved capable of predicting the proliferation ability and lymph node metastasis risk of breast cancer, and were associated with the survival in specific breast cancer subtypes. The conclusions of this paper are mostly well supported by data. However, it would have been clearer and more convincing to present the clinical significance combining all data in this study, especially in a more direct way (using tables or graphs).

1. An exposition for combined analysis of the results in figure 1-6 and figure 7-8 is expected to let the readers better understand the clinical significance (like prediction for proliferation and lymph node metastasis) of the various situations in breast cancer with different acid-base metabolism features.

2. There are some questions of how to select different indicators to evaluate the prognosis tendency. For example, data in figure 5E-F and 6E-F showed that Her2 receptor increased the expression of both NBCn1 and NHE1, which exert opposite predictive function in lymph node metastasis according to the data in figure 8G. In this condition, how to evaluate the risk of metastasis? What is the clinical significance of the data on Her2-enriched subtype?

3. How to confirm the statistical significance of the difference in the figures showing "traces of NH⁺4-prepulse-induced pHi dynamics" (like figure 2A-B)? Meanwhile, the p value is better to be marked in the figures.

4. The standard to define estrogen receptor-negative breast cancer and estrogen receptor-positive breast cancer should be pointed out. The results in figure 4 is confusing.

5. The information in figure 10A and 10F showed that the mRNA of SLC4A7, which encodes protein NBCn1, expressed in a very low level and could not predict the survival prognosis in HER2-riched breast cancer subtype. However, in figure 5F and figure 6F, the data indicated that HER2 expression level was positively associated with higher NBCn1 frequency. So, a further explanation is needed for the contradiction of these data and their clinical significance.

6. The authors should add more biological and molecular experiments to better support the conclusions.

Essential revisions:

1) Most of the conclusions could be well supported by clinical data statistics. However, there still exist some concerns expected to be explained, especially, detailed mechanism or therapeutic strategies description regarding pH dysregulation are deficient.

We have now very substantially expanded the introduction (l. 82-99), results (l. 380-387), and discussion (l. 452-469 and 486-565) sections in order to better explain how our findings relate to molecular mechanisms of breast carcinogenesis and further discuss the prognostic and possible therapeutic impact of pH dysregulation. Please also see the responses to the individual reviewer comments below.

2) There are several contradictory and confusing conclusions in the manuscript remaining to be discussed. It would be better to reorganize the manuscript in a clearer and more convincing manner to present the data in the study.

To better convey the methodological approach and conclusions of the study and avoid confusion, we have now improved the illustration in Figure 1B and included additional schematic illustrations as a new Figure 11.

Additionally, we have reorganized the supplementary material as figure supplements linked up to the regular figures in order to create a clearer structure.

We have also expanded the discussion very substantially (l. 452-469 and 500-565). Particularly, we have added more background and explanations in the areas highlighted as confusing or contradictory by the reviewers. With the included additional information, we hope the editors and reviewers agree that the findings and conclusions of the manuscript are now more convincingly presented.

For more details, see the responses to the individual reviewer comments below.

Reviewer #1:The authors launched an observational study on 110 breast cancer organoids, measured the cancer and normal cell net acid extrusion capacity to correlate different clinicopathological parameters with intracellular pH regulator (NHE1 and NBCn1) level, and unravel the relationship between them and tumor proliferation, lymph node metastasis together with the impact of cotransporter mRNA on patient's survival, thus highlighting the role of pH regulator in malignancy. This study was performed on a large-scale cohort based on tissue samples to comprehensively reflect the heterogeneity setting. However, there lacks detailed mechanism or therapeutic strategies description regarding pH dysregulation. The data has been sufficient to hold back the views proposed and the results will provide better understanding for the role of dysregulated pH in cancer progression and help future studies regarding targeting pH regulator in managing cancer.

1. In Figure 9 and 10, SLC9A1 and SLC4A7 mRNA level was analyzed for their correlation with survival outcome, it would be better to supplement survival analysis regarding the expression of SLC9A1 and SLC4A7 protein based on your study cohort.

We appreciate this suggestion. However, even though our cohort used for protein expression analyses and pH measurements – to our knowledge – is the largest existing with functional data on acid-base regulation for any type of human cancer, at this duration (2-5 years) of follow-up, it is not large enough for survival outcome analyses. The number of fatalities is too low to provide the statistical strength needed, and we have now included a comment regarding this limitation in the discussion (l. 540-546).

2. Please specify the reasons for ER and Ki-67 cut-off value setting and include them in Method or insert supporting reference literature.

This is an important point, which we now address on l. 651-661 and 206-212 of the revised manuscript:

Regarding ER (l. 652-656 and 206-212): “We observed a clear distinction between one group of patients with very high estrogen receptor expression (≥90% positive cells) and another group of patients with low estrogen receptor expression (≤15% positive cells) in the breast tumors. […] The absence of intermediate expression levels provided a clear and obvious cut-off value for separation between the two groups.”

Regarding Ki67 (l. 656-661): “As previously noted by others (reference 74), Ki67 expression displays a continuous distribution with no clear separation between groups of high and low expression. The median Ki67 index in our study cohort was 20%; and we therefore followed the guidelines of the 2015 St Gallen International Expert Consensus (reference 74) that in a similar population recommend a cut-off setting of 30% for identification of patients with a clearly high Ki67 index.”

3. It is described in lines 320-321 that the protein expression level of NHE1 and NBCn1 was not significantly influenced by estrogen receptor status. And it is described in lines 333-335 that the protein expression levels of NHE1 as well as NBCn1 were elevated in breast carcinomas with HER2 overexpression or gene amplification both before and after adjustment for other clinicopathological characteristics. But the survival figures of Figure 9, 10 indicated that 'For patients with HER2-enriched breast cancer, we saw no association of SLC4A7 or SLC9A1 mRNA expression with survival; The high overall SLC4A7 expression level in Luminal A breast cancer suggests a prominent role of NBCn1 in this breast cancer molecular subtype. And patients with high SLC9A1 mRNA expression suffering from Luminal A breast cancer showed significantly improved survival (hazard ratio 0.552) compared to patients with low SLC9A1 mRNA expression'. The conclusions seem to be contradictory, please explain this.

The point raised by the reviewer is important and underscores that there is not always straightforward proportionality between mRNA, protein, and function. This is particularly important, when making comparisons across molecular subtypes or clinicopathological characteristics driven by distinct carcinogenic mechanisms. The relationship between mRNA, protein, and function is likely much simpler when compared between individuals within the same molecular subtype; and therefore, we focus primarily on survival analyses performed following molecular subtype stratification (Figure 9, 10 and Figure 10—figure supplement 1 and 2). We now discuss this point on l. 317-324 of the revised manuscript.

The impact of estrogen and HER2 receptors on protein expression is described in Figure 4-6, and we have now included additional analyses to evaluate how ESR1, PGR, and ERBB2 expression affects SLC4A7 and SLC9A1 mRNA levels (Figure 9-Source Data 1 and Figure 10-Source Data 1). The lower SLC4A7 mRNA but higher NBCn1 protein level in HER2-enriched breast cancer imply that the HER2-dependent regulation occurs at post-transcriptional level (i.e., by an increased translational activity or higher protein stability). This relationship between mRNA and protein expression for NBCn1 is in line with previous findings in murine breast cancer tissue induced by HER2 overexpression (reference 16), where the SLC4A7 mRNA level was found low despite an elevated NBCn1 protein level. The predominant post-transcriptional regulation of NBCn1 expression by HER2 complicates the interpretation of the corresponding survival analysis (Figure 10F), and we have now included a comment regarding this point in the manuscript (l. 496-506).

The high SLC4A7 mRNA level in Luminal A breast cancer is consistent with a prominent regulation of NBCn1 expression at transcriptional level in this molecular subtype; and in congruence, the SLC4A7 mRNA level carries predictive prognostic value for patients with Luminal A breast cancer (Figure 10D). We have now clarified and expanded this point on l. 346-351 of the revised manuscript.

4. In lines 75-81：'In human and murine breast cancer tissue analyzed without stratification by molecular subtype, Na⁺, HCO₃^- cotransport activity is elevated and protein expression of the NBCn1 (SLC4A7) and MCT1 (SLC16A1) and MCT4 (SLC16A3) are upregulated compared to normal breast tissue. Protein expression of the NHE1 (SLC9A1) is either unchanged or moderately upregulated when breast cancer tissue as one unstratified group is compared to normal breast tissue.' However, worse prognosis was observed in patients suffering from Luminal A or Basal-like/triple-negative breast cancer with high SLC4A7 and/or low SLC9A1 mRNA expression. The expression level of NHE1 (SLC9A1) and the prognostic data are conflicting, please discuss it in detail.

We have now included a much more detailed discussion of NHE1 expression in breast cancer tissue on l. 452-469 of the revised manuscript. Our data establish NHE1 as a metastasis suppressor gene in human breast cancer. Although the spatio-temporal relationships for NHE1 expression need further examination in future studies, it is not unusual that metastasis-suppressor genes are upregulated during early cancer development but downregulated during cancer progression thereby promoting cancer cell metastasis to distant regions (references 49 and 50). We have now expanded the discussion of how NHE1 expression is influenced during breast carcinogenesis and included the existing knowledge regarding NHE1 expression changes during breast cancer progression (l. 452-465). With this additional information, we hope the reviewer agrees that the conclusions based on expression, function, and survival are clearer and more consistent.

We also now emphasize (l. 465-469) that our findings are in accordance with previous studies based on the human MCF7 cancer cell line where NHE1 is upregulated in response to HER2 overexpression (reference 51) but inhibits cell migration (reference 38).

5. The authors found that the expressions of NBCn1 and NHE1 were related to lymph node metastasis and cancer cell proliferation. However, lymph node metastasis and cancer cell proliferation are both key factors predicting worse prognosis. The existing data cannot indicate whether intratumor pH directly affects the patient's prognosis, or indirectly affects the prognosis through lymph nodes metastasis or cancer cell proliferation. Please add survival charts of patients in different subgroups to illustrate it.

We have now included a much more detailed discussion of NHE1 expression in breast cancer tissue on l. 452-469 of the revised manuscript. Our data establish NHE1 as a metastasis suppressor gene in human breast cancer. Although the spatio-temporal relationships for NHE1 expression need further examination in future studies, it is not unusual that metastasis-suppressor genes are upregulated during early cancer development but downregulated during cancer progression thereby promoting cancer cell metastasis to distant regions (references 49 and 50). We have now expanded the discussion of how NHE1 expression is influenced during breast carcinogenesis and included the existing knowledge regarding NHE1 expression changes during breast cancer progression (l. 452-465). With this additional information, we hope the reviewer agrees that the conclusions based on expression, function, and survival are clearer and more consistent.

We also now emphasize (l. 465-469) that our findings are in accordance with previous studies based on the human MCF7 cancer cell line where NHE1 is upregulated in response to HER2 overexpression (reference 51) but inhibits cell migration (reference 38).

6. The authors separately verified the effects of NBCn1 (SLC4A7), MCT1 (SLC16A1), MCT4 (SLC16A3) and NHE1 (SLC9A1) on the prognosis of patients, but whether there exist synergistic or antagonistic effect among the four genes, or whether there is mutual regulation relationship should be addressed.

Our meta-analysis covers data from seven different original studies. Because of variation in the genes covered by the different studies, the n-value drops drastically if only studies covering all four genes are included in a combined analysis of synergism/antagonism. Instead, as suggested by the reviewer, we now examine whether there is mutual regulation relationships between the four genes. This can be done in pair-wise correlation analyses that maintain the original high n-values. As shown in Figure 9-Source Data 1, Figure 10-Source Data 1, Figure 10—figure supplement 1-Source Data 1, and Figure 10—figure supplement 2-Source Data 1, the gene expression levels of the four acid-base transporters vary in response to differences in ERBB2, ESR1, and PGR expression – but when corrected for these effects, we find no independent correlation between the expression levels for any pair of transporters. These findings – described and discussed in the revised manuscript (l. 380-387) – support that the survival effects of the individual transporters are independent.

7. This manuscript requires a more comprehensive summary regarding previous reported role of abnormal pH in promoting cancer in Introduction, and the same about mechanism description and future interfering strategies in Discussion to help readers comprehend this field more conveniently.

Our meta-analysis covers data from seven different original studies. Because of variation in the genes covered by the different studies, the n-value drops drastically if only studies covering all four genes are included in a combined analysis of synergism/antagonism. Instead, as suggested by the reviewer, we now examine whether there is mutual regulation relationships between the four genes. This can be done in pair-wise correlation analyses that maintain the original high n-values. As shown in Figure 9-Source Data 1, Figure 10-Source Data 1, Figure 10—figure supplement 1-Source Data 1, and Figure 10—figure supplement 2-Source Data 1, the gene expression levels of the four acid-base transporters vary in response to differences in ERBB2, ESR1, and PGR expression – but when corrected for these effects, we find no independent correlation between the expression levels for any pair of transporters. These findings – described and discussed in the revised manuscript (l. 380-387) – support that the survival effects of the individual transporters are independent.

8. Breast cancer organoids are mainly composed of cytokeratin 19-positive epithelial cells while the authors only provide the microscopic pictures. It would be better to provide immunofluorescence or IHC staining pictures of cytokeratin 19-positive epithelial cells.

Our meta-analysis covers data from seven different original studies. Because of variation in the genes covered by the different studies, the n-value drops drastically if only studies covering all four genes are included in a combined analysis of synergism/antagonism. Instead, as suggested by the reviewer, we now examine whether there is mutual regulation relationships between the four genes. This can be done in pair-wise correlation analyses that maintain the original high n-values. As shown in Figure 9-Source Data 1, Figure 10-Source Data 1, Figure 10—figure supplement 1-Source Data 1, and Figure 10—figure supplement 2-Source Data 1, the gene expression levels of the four acid-base transporters vary in response to differences in ERBB2, ESR1, and PGR expression – but when corrected for these effects, we find no independent correlation between the expression levels for any pair of transporters. These findings – described and discussed in the revised manuscript (l. 380-387) – support that the survival effects of the individual transporters are independent.

9. Several references date 20 years ago, new references supporting the authors' findings would strengthen the hypothesis. Meanwhile, please arrange it in accordance with the reference format required by eLife.

We have now included additional, newer references. The references dating back more than 20 years now comprise less than 12% of the total number of references and are restricted to seminal papers that lay the theoretical or technical groundwork for the research field.

Our impression – based on the instructions to authors – was that no special reference format is required by eLife. We apologize if we have misunderstood this point and now use a reference format that specifies all authors on each paper. We would appreciate further instructions if a different reference format is more convenient – in which case, we will happily modify.

Reviewer #2:

In this extensive study, authors have shown that Na⁺,HCO₃^- cotransport and Na⁺/H⁺-exchange transporters predominantly mediate overall cellular acid extrusion in breast cancer microenvironment. In addition, authors demonstrate that higher activity of Na+,HCO₃^--cotransport correlates with increased growth and lymph node metastasis of breast cancer. The mechanistic insights gained from the study will help in the development of therapeutic strategies for breast cancers. The strengths of this study include the use of organoid culture system, and detailed cellular acid-base homeostasis analyses in an extensive cohort of breast cancer patients. Overall, this study is of interest to the peers working in the breast cancer field.

1. It would be interesting if the authors have used genetic knockdown or specific inhibitors against NBCn1 and NHE1 in breast cancer organoids to avoid the redundant functions of other ion exchangers.

It is important to note that the current study is based on freshly isolated organoids that are studied after only the delay (hours) needed for enzymatic digestion of the human tissue biopsies. Since the half-lives of protein degradation for NBCn1 and NHE1 in MCF7 human breast cancer cells are around 76 and 48 hours (reference 67), respectively, genetic knockdown techniques would not be possible within the time available. This is now described on l. 551-558 of the revised manuscript. We apologize if the freshly isolated organoids used in this manuscript and their difference from organoid cultures used in other studies were inadequately described. The organoids in our studies were investigated directly after enzymatic isolation without tissue culture because it is well known that culture processes dramatically influence acid-base transporter expression and function. Had the tissue been cultured, it is very likely that it would no longer resemble the human clinical condition. To further emphasize this important point, we have now expanded Figure 1B to include an ultra-brief illustration of the methodological approach and expanded the description on l. 602-603, 125-127, and 551-554 of the revised manuscript.

Regarding specific inhibitors, no such compounds currently exist for NBCn1, which we now mention on l. 558-559 of the revised manuscript. We have previously shown that the Na⁺,HCO₃^–-cotransport in human breast cancer tissue has low sensitivity to 4,4′-diisothiocyano-2,2′-stilbenedisulfonic acid (DIDS), which is a pharmacological characteristic of NBCn1 compared to other Na⁺,HCO₃^–-cotransporters. A comment and reference to this information has been included on l. 559-565 of the revised manuscript.

2. Did the authors analyze the expression of angiogenic markers such as CD31 or CD34 in the patient samples?

For our cohort evaluated with pH dynamics and protein expression levels for NBCn1 and NHE1, we did not analyze the expression of angiogenic markers. In addition to the protein expression analyses for NBCn1 and NHE1, the pathological information stems from the standard diagnostic pathology evaluation, which did not include CD31/PECAM or CD34. However, to accommodate the request from the reviewer, we have now assessed how CD31 and CD34 mRNA expression relates to the different breast cancer molecular subtypes evaluated in the meta-analysis. These data are now included in Figure 9—figure supplement 1 and mentioned on l. 331-333 of the revised manuscript.

3. For the ease of readers, in Figure 1B, authors should also highlight the observations on expression and correlation of NBCn1 and NHE1 with overall survival in different breast cancer subtypes.

This is a point well taken. Instead of expanding Figure 1B – which has already been expanded with methodological details, see point 1 above – we have included new summary schematics of our conclusions regarding NHE1 and NBCn1 in a new Figure 11 in order to best maintain the natural progression of the manuscript.

4. Authors should discuss the possible limitations of their study in the Discussion part of the manuscript.

We now discuss limitations of the study on l. 540-550 of the revised manuscript. These include considerations regarding n-values and follow-up time in our cohort. We also discussion that the sizes of individual subgroups are determined by the natural incidence of the various clinicopathological characteristics, which results in a less balanced distribution for some breast cancer characteristics.

On l. 551-565, we also emphasize that the current approach based on freshly isolated organoids provides the closest possible evaluation of in vivo characteristics under conditions where experimental buffer compositions can be modified and controlled. In order to study detailed molecular mechanisms and their influence on the cellular biology, future studies in model systems will be important.

5. Please correct the spelling of Maier to Kaplan-Meier in methods.

Thank you for pointing this out – corrected twice in the methods section (l. 678 and 700).

6. In Figure 1 E, authors should use only one asterisk to show the statistical significance between the groups.

The asterisks were meant to indicate the statistical difference relating to two different comparisons between the cancer tissue and the normal breast tissue: one in the presence of CO₂/HCO₃^–, the other in the absence of CO₂/HCO₃^–. We apologize if this was not clear and have now changed the layout of the figure panel to avoid confusion.

Reviewer #3:

Nicolai J. Toft et al. investigated the feature of acid-base metabolism in breast cancer tissue from several aspects, revealing the underlying mechanism of pH regulation according to the heterogeneity. Moreover, the acid-base transport and intracellular pH state were proved capable of predicting the proliferation ability and lymph node metastasis risk of breast cancer, and were associated with the survival in specific breast cancer subtypes. The conclusions of this paper are mostly well supported by data. However, it would have been clearer and more convincing to present the clinical significance combining all data in this study, especially in a more direct way (using tables or graphs).

1. An exposition for combined analysis of the results in figure 1-6 and figure 7-8 is expected to let the readers better understand the clinical significance (like prediction for proliferation and lymph node metastasis) of the various situations in breast cancer with different acid-base metabolism features.

As suggested, we have now markedly expanded the explanation and discussion of the analyses on l. 452-469, and 507-565 of the revised manuscript. The additional discussion highlights the clinical significance and several pathological characteristics in breast cancer that based on our findings are likely to be at least partly due to the acid-base features of the individual molecular subtypes.

2. There are some questions of how to select different indicators to evaluate the prognosis tendency. For example, data in figure 5E-F and 6E-F showed that Her2 receptor increased the expression of both NBCn1 and NHE1, which exert opposite predictive function in lymph node metastasis according to the data in figure 8G. In this condition, how to evaluate the risk of metastasis? What is the clinical significance of the data on Her2-enriched subtype?

This is an excellent point, which we now discuss in greater detail on l. 507-514 of the revised manuscript. The dual effect of HER2 on expression of NBCn1 and NHE1 is intriguing as it suggests that more detailed analyses (e.g., relative regulation of NBCn1 vs NHE1) may provide more accurate predictive value than simple evaluation of HER2 overexpression/gene amplification. Our findings furthermore suggest that selective targeting of individual HER2-activated downstream signaling pathways (including individual acid-base transporters) could optimize the current therapeutic approach based on direct HER2 inhibition.

3. How to confirm the statistical significance of the difference in the figures showing "traces of NH₄⁺-prepulse-induced pH_i dynamics" (like figure 2A-B)? Meanwhile, the p value is better to be marked in the figures.

We have now included a paragraph (l. 151-155) that explains the relationship between the different panels, i.e., how data extracted from the pH_i traces (like Figure 2A,B) were summarized and statistically compared in the associated panels (like Figure 2C,D and Figure 2—figure supplement 2). The statistical analyses compared the net acid extrusion capacities (Figure 2C) and steady-state pH_i levels (Figure 2D) derived from the pH_i traces. We include the traces in order to give the reader a better feel for the recordings underlying our analyses, which is in line with the recommendation in the eLife instructions to authors that traces should be included whenever possible.

4. The standard to define estrogen receptor-negative breast cancer and estrogen receptor-positive breast cancer should be pointed out. The results in figure 4 is confusing.

We apologize if the description of the nomenclature was inadequate and confusing. We have now described in detail how we distinguished between breast cancer samples with highly elevated estrogen receptor expression (ER-positive breast cancer: ≥90% ER⁺ cells) and samples where the estrogen receptor expression was in a range similar to that previously reported for normal breast tissue (ER-normal breast cancer: ≤15% ER⁺ cells) on l. 206-212 and 652-656 of the revised manuscript.

5. The information in figure 10A and 10F showed that the mRNA of SLC4A7, which encodes protein NBCn1, expressed in a very low level and could not predict the survival prognosis in HER2-riched breast cancer subtype. However, in figure 5F and figure 6F, the data indicated that HER2 expression level was positively associated with higher NBCn1 frequency. So, a further explanation is needed for the contradiction of these data and their clinical significance.

This is a very good point. The lower SLC4A7 mRNA but higher NBCn1 protein level in HER2-enriched breast cancer imply that the HER2-dependent regulation occurs at post-transcriptional level (i.e., by an increased translational activity or higher protein stability). This relationship between mRNA and protein expression for NBCn1 is in line with previous findings in murine breast cancer tissue induced by HER2 overexpression (reference 16), where the SLC4A7 mRNA level was found low despite an elevated NBCn1 protein level. The predominant post-transcriptional regulation of NBCn1 expression by HER2 complicates the interpretation of the corresponding survival analysis (Figure 10F), and we have now included a comment regarding this point in the manuscript (l. 496-506).

6. The authors should add more biological and molecular experiments to better support the conclusions.

The unique strength of the current study is the clinically relevant functional data on pH dynamics from a human cohort of previously unparalleled size. The data set is unique because it so clearly links up to the human clinical condition and embraces its heterogeneity and complexity, thereby allowing us to establish relationships between pH dynamics and clinical and pathological characteristics, which has not been possible before. To establish this link convincingly, we performed the functional recordings immediately after organoid isolation from the sampled tissue biopsies in order to avoid culture-induced phenotypical changes. The short time period between tissue sampling and the functional experiments, however, makes the approach unsuited for molecular interventions as the half-lives of protein degradation is ~76 hours for NBCn1 and ~48 hours for NHE1 (reference 81). We now discuss these points in the revised manuscript (l. 551-565).

Although beyond the scope of the current study, the results from the current study has already prompted new biological and molecular investigations in our group based on murine breast cancer models that are further away from the human clinical condition but much better suited for molecular intervention. Undoubtedly, the current study will also stimulate new molecular studies from colleagues in the field.

Author details

1. Nicolai J Toft

   Department of Biomedicine, Aarhus University, Aarhus, Denmark

   Contribution

   Data curation, Formal analysis, Investigation, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

2. Trine V Axelsen

   Department of Biomedicine, Aarhus University, Aarhus, Denmark

   Contribution

   Data curation, Formal analysis, Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

3. Helene L Pedersen

   Department of Pathology, Regionshospitalet Randers, Randers, Denmark

   Contribution

   Data curation, Formal analysis, Writing - review and editing

   Competing interests

   No competing interests declared

4. Marco Mele

   Department of Surgery, Regionshospitalet Randers, Randers, Denmark

   Contribution

   Data curation, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-8156-7804

5. Mark Burton

   1. Department of Clinical Genetics, University of Southern Denmark, Odense, Denmark
   2. Clinical Genome Center, University and Region of Southern Denmark, Odense, Denmark

   Contribution

   Data curation, Formal analysis, Writing - review and editing

   Competing interests

   No competing interests declared

6. Eva Balling

   Department of Surgery, Regionshospitalet Randers, Randers, Denmark

   Contribution

   Data curation, Writing - review and editing

   Competing interests

   No competing interests declared

7. Tonje Johansen

   Department of Pathology, Regionshospitalet Randers, Randers, Denmark

   Contribution

   Data curation

   Competing interests

   No competing interests declared

8. Mads Thomassen

   1. Department of Clinical Genetics, University of Southern Denmark, Odense, Denmark
   2. Clinical Genome Center, University and Region of Southern Denmark, Odense, Denmark

   Contribution

   Data curation, Formal analysis, Writing - review and editing

   Competing interests

   No competing interests declared

9. Peer M Christiansen

   1. Department of Surgery, Regionshospitalet Randers, Randers, Denmark
   2. Department of Plastic and Breast Surgery, Department of Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark

   Contribution

   Data curation, Writing - review and editing

   Competing interests

   No competing interests declared

10. Ebbe Boedtkjer

    Department of Biomedicine, Aarhus University, Aarhus, Denmark

    Contribution

    Conceptualization, Formal analysis, Supervision, Funding acquisition, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing

    For correspondence

    eb@biomed.au.dk

    Competing interests

    is an inventor on patents covering NBCn1 as target for cancer therapy (EP 3271402)

    "This ORCID iD identifies the author of this article:" 0000-0002-5078-9279

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