Breast cancer heterogeneity in histology and molecular subtype influences metabolic and proliferative activity and hence the acid load on cancer cells. We hypothesized that acid-base transporters and intracellular pH (pHi) dynamics contribute inter-individual variability in breast cancer aggressiveness and prognosis. We show that Na+,HCO3--cotransport and Na+/H+-exchange dominate cellular net acid extrusion in human breast carcinomas. Na+/H+-exchange elevates pHi preferentially in estrogen receptor-negative breast carcinomas, whereas Na+,HCO3--cotransport raises pHi more in invasive lobular than ductal breast carcinomas and in higher malignancy grade breast cancer. HER2-positive breast carcinomas have elevated protein expression of Na+/H+-exchanger NHE1/SLC9A1 and Na+,HCO3--cotransporter NBCn1/SLC4A7. Increased dependency on Na+,HCO3--cotransport associates with severe breast cancer: enlarged CO2/HCO3--dependent rises in pHi predict accelerated cell proliferation; whereas enhanced CO2/HCO3--dependent net acid extrusion, elevated NBCn1 protein expression, and reduced NHE1 protein expression predict lymph node metastasis. Accordingly, we observe reduced survival for patients suffering from Luminal A or Basal-like/triple-negative breast cancer with high SLC4A7 and/or low SLC9A1 mRNA expression. We conclude that the molecular mechanisms of acid-base regulation depend on clinicopathological characteristics of breast cancer patients. NBCn1 expression and dependency on Na+,HCO3--cotransport for pHi regulation, measured in biopsies of human primary breast carcinomas, independently predict proliferative activity, lymph node metastasis, and patient survival.
- 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 (references 28-34), as detailed in the manuscript and the dataset list.
A gene-expression signature as a predictor of survival in breast cancerBudczies J, Kosztyla D (2020). cancerdata: Development and validation of diagnostic tests from high-dimensional molecular data: Datasets. R package version 1.28.0.; data(Vijver).
Intrinsic molecular signature of breast cancer in a population-based cohort of 412 patientsYudi Pawitan uploads; Intrinsic_signature.
The molecular portraits of breast tumors are conserved across microarray platformsNCBI Gene Expression Omnibus, GSE1992.
Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancerNCBI Gene Expression Omnibus, GSE2034.
The humoral immune system has a key prognostic impact in node-negative breast cancerNCBI Gene Expression Omnibus, GSE11121.
Oncogenic pathway signatures in human cancers as a guide to targeted therapiesNCBI Gene Expression Omnibus, GSE3143.
- Ebbe Boedtkjer
- Ebbe Boedtkjer
- Nicolai J Toft
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Human subjects: All participants gave written informed consent. The Mid-Jutland regional division of the Danish Committee on Health Research Ethics (M-20100288) and the Danish Data Protection Agency (1-16-02-191-16) approved the procedures for tissue sampling and data handling, respectively.
- Caigang Liu, Shengjing Hospital of China Medical University, China
© 2021, Toft et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Late advances in genome sequencing expanded the space of known cancer driver genes several-fold. However, most of this surge was based on computational analysis of somatic mutation frequencies and/or their impact on the protein function. On the contrary, experimental research necessarily accounted for functional context of mutations interacting with other genes and conferring cancer phenotypes. Eventually, just such results become ‘hard currency’ of cancer biology. The new method, NEAdriver employs knowledge accumulated thus far in the form of global interaction network and functionally annotated pathways in order to recover known and predict novel driver genes. The driver discovery was individualized by accounting for mutations’ co-occurrence in each tumour genome – as an alternative to summarizing information over the whole cancer patient cohorts. For each somatic genome change, probabilistic estimates from two lanes of network analysis were combined into joint likelihoods of being a driver. Thus, ability to detect previously unnoticed candidate driver events emerged from combining individual genomic context with network perspective. The procedure was applied to 10 largest cancer cohorts followed by evaluating error rates against previous cancer gene sets. The discovered driver combinations were shown to be informative on cancer outcome. This revealed driver genes with individually sparse mutation patterns that would not be detectable by other computational methods and related to cancer biology domains poorly covered by previous analyses. In particular, recurrent mutations of collagen, laminin, and integrin genes were observed in the adenocarcinoma and glioblastoma cancers. Considering constellation patterns of candidate drivers in individual cancer genomes opens a novel avenue for personalized cancer medicine.
Cancer stem cells (CSCs) alone can initiate and maintain tumors, but the function of non-cancer stem cells (non-CSCs) that form the tumor bulk remains poorly understood. Proteomic analysis showed a higher abundance of the extracellular matrix small leucine-rich proteoglycan Fibromodulin (FMOD) in the conditioned medium of differentiated glioma cells (DGCs), the equivalent of glioma non-CSCs, compared to that of glioma stem-like cells (GSCs). DGCs silenced for FMOD fail to cooperate with co-implanted GSCs to promote tumor growth. FMOD downregulation neither affects GSC growth and differentiation nor DGC growth and reprogramming in vitro. DGC-secreted FMOD promotes angiogenesis by activating Integrin-dependent Notch signaling in endothelial cells. Furthermore, conditional silencing of FMOD in newly generated DGCs in vivo inhibits the growth of GSC-initiated tumors due to poorly developed vasculature and increases mouse survival. Collectively, these findings demonstrate that DGC-secreted FMOD promotes glioma tumor angiogenesis and growth through paracrine signaling in endothelial cells and identifies a DGC-produced protein as a potential therapeutic target in glioma.