Breast cancer cell lines have been widely used for breast cancer modelling which encompasses a panel of diseases with distinct phenotypical associations. Though cell lines provide unlimited homogenous materials for tumor studies and are relatively easy to culture, they are known to accumulate mutations duringthe initial establishment and subsequent series of cultivations. Thus, whether breast cancer cell line heterogeneity reflects that of carcinoma remains an important issue to resolve before drawing any reliable conclusion at the tumor level using cell lines. Inconsistent nomenclatures used for breast cancer cell line subtyping and the different number of subtypes grouped for cell lines and tumors make their direct matching elusive. By analyzing the molecular features of 92 breast cancer cell lines as documented by different literatures, we categorize 84 cell lines into 5 groups to be consistent with breast tumor classification. After combing through these cell lines, we summarized the molecular features, genetically and epigenetically, of each subtype, and manually documented 10 cell lines lacking explicit information on subtyping. Nine cell lines, either found inconsistent on their primary molecular features from different studies or being contaminated at the origin, are not suggested as the first choice for experimental use. We conclude that breast tumor cell lines, though having a high mutational frequency with many uncertainties and could not fully capture breast cancer heterogeneity, are feasible but crude models for tumors of the same subtype. New cell lines with enriched interferon regulated genes need to be established to enlarge the coverage of cell lines on tumor heterogeneity.

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Background: Triple negative breast cancers are aggressive, enriched with cancer stem cells, and lack effective targeted therapies with little side effects.Methods: We isolated cancer stem cells from two triple negative breast cancer cell lines via cell sorting following transcriptome sequencing, bioinformatics analysis, experimental and clinical validations, as well as functional investigations to explore genes capturing triple negative breast cancer features for improved diagnosis and therapeutics in clinics.Results: We found that FA2H is under-expressed in triple negative breast cancers both in vitro and in clinics, and FA2H suppresses cancer stemness via inhibiting the STAT3/IL6 axis and NFkB signaling.Conclusions: This study reports the tumor suppressive roles of FA2H on breast cancer cells through cancer stemness control. FA2H and other candidates unveiled in this study that capture the features of cancer stem cells may contribute as diagnostic marker and/or effective therapeutic targets for improved triple negative breast cancer management.

Having markers feasible for breast cancer subtyping, especially for triple negative breast cancer identification is crucial for improving the treatment outcome of such cancers. Here we explore the role of FOXA1 in characterizing triple negative breast cancers and the driving mechanisms. Through in vitro examination of the expression pattern at both transcriptional and translational levels, patient relapse-free survival analysis, immunohistochemistry staining and prediction power assessment using clinical samples, as well as functional studies, we systematically compared the role of FOXA1 in identifying triple negative and luminal type of breast cancers and explored the mechanisms driving such functionalities. We report that FOXA1 under-expression can lead to increased malignancy and cancer stemness, and is a subtyping marker identifying triple negative breast cancers rather than the luminal subtype by transcriptionally suppressing the expression of SOD2 and IL6 . We are the first to systematically address the significance of FOXA1 in triple negative breast cancer identification as a biomarker and elucidate the mechanism at the molecular level, through a sequential bioinformatics analysis and experimental validations both in vitro and in clinics. Our discoveries compliment the current biomarker modalities once verified using larger clinical cohorts and improve the precision on characterizing breast cancer heterogeneity.