TCGA Breast Cancer Research Articles

Identification of hub genes associated with EMT-induced chemoresistance in breast cancer using integrated bioinformatics analysis

Chemoresistance is one of the major challenges in the treatment of breast cancer. Recent evidence suggests that epithelial-to-mesenchymal transition (EMT) plays a critical role in not only metastasis but also in chemoresistance, hence causing tumor relapse. This study aimed to identify the hub genes associated with EMT and chemoresistance in breast cancer affecting patient/clinical survival. Commonly differentially expressed genes (DEGs) during EMT and chemoresistance in breast cancer cells were identified using publicly available datasets, GSE23655, GSE39359, GSE33146 and GSE76540. Hierarchical clustering analysis was utilized to determine the commonly DEGs expression pattern in chemoresistant (CR) breast cancer cells. GSEA revealed that EMT-related genes sets were enriched in the CR samples. Further, we found that EMT-induced breast cancer cells showed overexpression of drug efflux transporters along with resistance to chemotherapeutic drug. Pathway enrichment analysis revealed that the commonly DEGs were enriched in immunological pathways, early endosome, protein dimerization, and proteoglycans in cancer. Further, we identified eight hub genes from the protein-protein interaction (PPI) network. We validated the gene expression levels of the hub genes among TCGA breast cancer samples using UALCAN. Survival analysis for the hub genes was performed using KM plotter, which showed a worse relapse-free survival (RFS) of the hub genes among breast cancer patients. In conclusion, this study identified eight hub genes that play an important role in the pathways underlying EMT-induced chemoresistance in breast cancer and can be used as therapeutic targets after clinical validation.

Molecular analysis of TCGA breast cancer histologic types

Breast cancer is classified into multiple distinct histologic types, and many of the rarer types have limited characterization. Here, we extend The Cancer Genome Atlas Breast Cancer (TCGA-BRCA) dataset with additional histologic type annotations, in a total of 1063 breast cancers. We analyze this extended dataset to define transcriptomic and genomic profiles of six rare special histologic types: cribriform, micropapillary, mucinous, papillary, metaplastic, and invasive carcinoma with medullary pattern. We show the broader applicability of our constructed special histologic type gene signatures in the TCGA Pan-Cancer Atlas dataset with a predictive model that detects mucinous histologic type across cancers of other organ systems. Using a normal mammary cell differentiation score analysis, we order histologic types into a continuum from stem cell-like to luminal progenitor-like to mature luminal-like. Finally, we classify TCGA-BRCA into 12 consensus groups based on integrated genomic and histological features. We present a rich openly accessible resource of histologic and genomic characterization of TCGA-BRCA to enable studies of the range of breast cancers.

MYC dosage compensation is mediated by miRNA-transcription factor interactions in aneuploid cancer

SummaryWe hypothesize that dosage compensation of critical genes arises from systems-level properties for cancer cells to withstand the negative effects of aneuploidy. We identified several candidate genes in cancer multiomics data and developed a biocomputational platform to construct a mathematical model of their interaction network with micro-RNAs and transcription factors, where the property of dosage compensation emerged for MYC and was dependent on the kinetic parameters of its feedback interactions with three micro-RNAs. These circuits were experimentally validated using a genetic tug-of-war technique to overexpress an exogenous MYC, leading to overexpression of the three microRNAs involved and downregulation of endogenous MYC. In addition, MYC overexpression or inhibition of its compensating miRNAs led to dosage-dependent cytotoxicity in MYC-amplified colon cancer cells. Finally, we identified negative correlation of MYC dosage compensation with patient survival in TCGA breast cancer patients, highlighting the potential of this mechanism to prevent aneuploid cancer progression.

Identification of a novel cancer microbiome signature for predicting prognosis of human breast cancer patients.

Prognosis of breast cancer (BC) patients differs considerably and identifying reliable prognostic biomarker(s) is imperative. With evidence that the microbiome plays a critical role in the response to cancer therapies, we aimed to identify a cancer microbiome signature for predicting the prognosis of BC patients. The TCGA BC microbiome data (TCGA-BRCA-microbiome) was downloaded from cBioPortal. Univariate and multivariate Cox regression analyses were used to examine association of microbial abundance with overall survival (OS) and to identify a microbial signature for creating a prognostic scoring model. The performance of the scoring model was assessed by the area under the ROC curve (AUC). Nomograms using the microbial signature, clinical factors, and molecular subtypes were established to predict OS and progression-free survival (PFS). Among 1406 genera, the abundances of 94 genera were significantly associated with BC patient OS in TCGA-BRCA-microbiome dataset. From that set we identified a 15-microbe prognostic signature and developed a 15-microbial abundance prognostic scoring (MAPS) model. Patients in low-risk group significantly prolong OS and PFS as compared to those in high-risk group. The time-dependent ROC curves with MAPS showed good predictive efficacy both in OS and PFS. Moreover, MAPS is an independent prognostic factor for OS and PFS over clinical factors and PAM50-based molecular subtypes and superior to the previously published 12-gene signature. The integration of MAPS into nomograms significantly improved prognosis prediction. MAPS was successfully established to have independent prognostic value, and our study provides a new avenue for developing prognostic biomarkers by microbiome profiling.

Dual roles of AMAP1 in the transcriptional regulation and intracellular trafficking of carbonic anhydrase IX

BackgroundThe cell-surface enzyme carbonic anhydrase IX (CAIX/CA9) promotes tumor growth, survival, invasion, and metastasis, mainly via its pH-regulating functions. Owing to its tumor-specific expression, CAIX-targeting antibodies/chemicals are utilized for therapeutic and diagnostic purposes. However, mechanisms of CAIX trafficking, which affects such CAIX-targeting modalities remain unclear. In this study, roles of the AMAP1-PRKD2 pathway, which mediates integrin recycling of invasive cancer cells, in CAIX trafficking were investigated. MethodsUsing highly invasive MDA-MB-231 breast cancer cells, the physical association and colocalization of endogenous proteins were analyzed by immunoprecipitation and immunofluorescence, protein/mRNA levels were quantified by western blotting/qPCR, and cell-surface transport and intracellular/extracellular pH regulation were measured by biotin-labeling and fluorescent dye-based assays, respectively. The correlation between mRNA levels and patients’ prognoses was analyzed using a TCGA breast cancer dataset. ResultsAMAP1 associated with the CAIX protein complex, and they colocalized at the plasma membrane and tubulovesicular structures. AMAP1 knockdown reduced total/surface CAIX, induced its lysosomal accumulation and degradation, and affected intracellular/extracellular pH. PRKD2 knockdown excluded AMAP1 from the CAIX complex and reduced total CAIX in a lysosome-dependent manner. Unexpectedly, AMAP1 knockdown also reduced CAIX mRNA. AMAP1 interacted with PIAS3, which stabilizes HIF-1α, a transcriptional regulator of CA9. AMAP1 knockdown inhibited the PIAS3-HIF-1α interaction and destabilized the HIF-1α protein. High-ASAP1 (AMAP1-encoding gene) together with high-PIAS3 correlated with high-CA9 and an unfavorable prognosis in breast cancer. ConclusionThe AMAP1-PRKD2 pathway regulates CAIX trafficking, and modulates its total/surface expression. The AMAP1-PIAS3 interaction augments CA9 transcription by stabilizing HIF-1α, presumably contributing to an unfavorable prognosis.

Importance-Penalized Joint Graphical Lasso (IPJGL): differential network inference via GGMs.

MotivationDifferential network inference is a fundamental and challenging problem to reveal gene interactions and regulation relationships under different conditions. Many algorithms have been developed for this problem; however, they do not consider the differences between the importance of genes, which may not fit the real-world situation. Different genes have different mutation probabilities, and the vital genes associated with basic life activities have less fault tolerance to mutation. Equally treating all genes may bias the results of differential network inference. Thus, it is necessary to consider the importance of genes in the models of differential network inference.ResultsBased on the Gaussian graphical model with adaptive gene importance regularization, we develop a novel Importance-Penalized Joint Graphical Lasso method (IPJGL) for differential network inference. The presented method is validated by the simulation experiments as well as the real datasets. Furthermore, to precisely evaluate the results of differential network inference, we propose a new metric named APC2 for the differential levels of gene pairs. We apply IPJGL to analyze the TCGA colorectal and breast cancer datasets and find some candidate cancer genes with significant survival analysis results, including SOST for colorectal cancer and RBBP8 for breast cancer. We also conduct further analysis based on the interactions in the Reactome database and confirm the utility of our method.Availability and implementationR source code of Importance-Penalized Joint Graphical Lasso is freely available at https://github.com/Wu-Lab/IPJGL.Supplementary information Supplementary data are available at Bioinformatics online.

Cancer testis antigen PRAME: An anti-cancer target with immunomodulatory potential.

PReferentially expressed Antigen in Melanoma (PRAME) is a cancer testis antigen with restricted expression in somatic tissues and re‐expression in poor prognostic solid tumours. PRAME has been extensively investigated as a target for immunotherapy, however, its role in modulating the anti‐tumour immune response remains largely unknown. Here, we show that PRAME tumour expression is associated with worse survival in the TCGA breast cancer cohort, particularly in immune‐unfavourable tumours. Using direct and indirect co‐culture models, we found that PRAME overexpressing MDA‐MB‐468 breast cancer cells inhibit T cell activation and cytolytic potential, which could be partly restored by silencing of PRAME. Furthermore, silencing of PRAME reduced expression of several immune checkpoints and their ligands, including PD‐1, LAG3, PD‐L1, CD86, Gal‐9 and VISTA. Interestingly, silencing of PRAME induced cancer cell killing to levels similar to anti‐PD‐L1 atezolizumab treatment. Comprehensive analysis of soluble inflammatory mediators and cancer cell expression of immune‐related genes showed that PRAME tumour expression can suppress the expression and secretion of multiple pro‐inflammatory cytokines, and mediators of T cell activation, differentiation and cytolysis. Together, our data indicate that targeting of PRAME offers a potential, novel dual therapeutic approach to specifically target tumour cells and regulate immune activation in the tumour microenvironment.

Chemotherapy of HER2- and MDM2-Enriched Breast Cancer Subtypes Induces Homologous Recombination DNA Repair and Chemoresistance.

Simple SummaryMDM2 is a protein responsible for negative regulation of the p53 tumor suppressor. In addition, MDM2 exhibits chaperone-like properties similar to the HSP90 molecular chaperone. Multiple studies revealed that MDM2 is deeply involved in cancer development and progression. Some recently published results indicate that the role of MDM2 in DNA repair inhibition is more complex than previously thought. We show that MDM2 is directly involved in the homologous recombination DNA repair, and its chaperone-like activity is crucial for this function. The DNA repair inhibition is a result of inefficient MDM2 dissociation from the NBN protein complex. When cancer cells are treated with chemotherapy, MDM2 can be easily released from the interaction and degraded, resulting in effective homologous recombination DNA repair, which translates into the acquisition of a chemoresistant phenotype by the tumor. This knowledge may allow for identification of the patients that are at particular risk of tumor chemoresistance. Analyzing the TCGA breast cancer database, we discovered that patients with the HER2 cancer subtype and overexpression of MDM2 exhibited decreased post-treatment survival. Inhibition of MDM2 expression in the SKBR3 cell line (HER2 subtype) diminished the survival of cancer cells treated with doxorubicin, etoposide, and camptothecin. Moreover, we demonstrated that inhibition of MDM2 expression diminished DNA repair by homologous recombination (HR) and sensitized SKBR3 cells to a PARP inhibitor, olaparib. In H1299 (TP53−/−) cells treated with neocarzinostatin (NCS), overexpression of MDM2 WT or E3-dead MDM2 C478S variant stimulated the NCS-dependent phosphorylation of ATM, NBN, and BRCA1, proteins involved in HR DNA repair. However, overexpression of chaperone-dead MDM2 K454A variant diminished phosphorylation of these proteins as well as the HR DNA repair. Moreover, we demonstrated that, upon NCS treatment, MDM2 K454A interacted with NBN more efficiently than MDM2 WT and that MDM2 WT was degraded more efficiently than MDM2 K454A. Using a proliferation assay, we showed that overexpression of MDM2 WT, but not MDM2 K454A, led to acquisition of resistance to NCS. The presented results indicate that, following chemotherapy, MDM2 WT was released from MDM2-NBN complex and efficiently degraded, hence allowing extensive HR DNA repair leading to the acquisition of chemoresistance by cancer cells.

Establishment of a novel CNV-related prognostic signature predicting prognosis in patients with breast cancer

BackgroundCopy number variation (CNVs) is a key factor in breast cancer development. This study determined prognostic molecular characteristics to predict breast cancer through performing a comprehensive analysis of copy number and gene expression data.MethodsBreast cancer expression profiles, CNV and complete information from The Cancer Genome Atlas (TCGA) dataset were collected. Gene Expression Omnibus (GEO) chip data sets (GSE20685 and GSE31448) containing breast cancer samples were used as external validation sets. Univariate survival COX analysis, multivariate survival COX analysis, least absolute shrinkage and selection operator (LASSO), Chi square, Kaplan-Meier (KM) survival curve and receiver operating characteristic (ROC) analysis were applied to build a gene signature model and assess its performance.ResultsA total of 649 CNV related-differentially expressed gene obtained from TCGA-breast cancer dataset were related to several cancer pathways and functions. A prognostic gene sets with 9 genes were developed to stratify patients into high-risk and low-risk groups, and its prognostic performance was verified in two independent patient cohorts (n = 327, 246). The result uncovered that 9-gene signature could independently predict breast cancer prognosis. Lower mutation of PIK3CA and higher mutation of TP53 and CDH1 were found in samples with high-risk score compared with samples with low-risk score. Patients in the high-risk group showed higher immune score, malignant clinical features than those in the low-risk group. The 9-gene signature developed in this study achieved a higher AUC.ConclusionThe current research established a 5-CNV gene signature to evaluate prognosis of breast cancer patients, which may innovate clinical application of prognostic assessment.

A unified framework for the integration of multiple hierarchical clusterings or networks from multi-source data

BackgroundIntegrating data from different sources is a recurring question in computational biology. Much effort has been devoted to the integration of data sets of the same type, typically multiple numerical data tables. However, data types are generally heterogeneous: it is a common place to gather data in the form of trees, networks or factorial maps, as these representations all have an appealing visual interpretation that helps to study grouping patterns and interactions between entities. The question we aim to answer in this paper is that of the integration of such representations.ResultsTo this end, we provide a simple procedure to compare data with various types, in particular trees or networks, that relies essentially on two steps: the first step projects the representations into a common coordinate system; the second step then uses a multi-table integration approach to compare the projected data. We rely on efficient and well-known methodologies for each step: the projection step is achieved by retrieving a distance matrix for each representation form and then applying multidimensional scaling to provide a new set of coordinates from all the pairwise distances. The integration step is then achieved by applying a multiple factor analysis to the multiple tables of the new coordinates. This procedure provides tools to integrate and compare data available, for instance, as tree or network structures. Our approach is complementary to kernel methods, traditionally used to answer the same question.ConclusionOur approach is evaluated on simulation and used to analyze two real-world data sets: first, we compare several clusterings for different cell-types obtained from a transcriptomics single-cell data set in mouse embryos; second, we use our procedure to aggregate a multi-table data set from the TCGA breast cancer database, in order to compare several protein networks inferred for different breast cancer subtypes.

O29 Aberrant expression of BMP8A and the BMPRs involves in the progression of breast cancer

Abstract Introduction Role of Bone morphogenetic protein 8A (BMP8A) and BMP receptors (BMPRs) in the tumourigenesis and progression of breast cancer remains elusive. Present study aims to investigate the expression of BMP8A and related BMPRs in breast cancer and their clinical implication. Method Expression of BMP8A and BMPRs was analysed using the RNA sequencing data of the TCGA breast cancer cohort. Findings were further validated in a meta gene array dataset (E-MDTA6703, n = 2302). STRING dataset was applied to explore the predicted receptors of BMP8A. Clinical relevance of deregulated BMP8A and BMPRs in breast cancer was assessed using both ANOVA and Kaplan-Meier tests. Correlation with markers of proliferation and invasion was evaluated using Spearman test. Result Analysis of datasets revealed that BMP8A and BMPR1B were highly expressed in breast cancer while ACVRL1, ACVR1, BMPR1A, ACVR1C, TGFBR2, TGFBR3, BMPR2 and ACVR2A were lower-expressed compared with normal controls. Expressions of BMPR1B, BMPR1A, BMPR2, ACVR2A and ACVR2B were highly correlated with BMP8A in the breast cancers. Overall survival in the group with higher BMP8A expression was shorter(median= 122.3 months), P = 0.012 compared with lower-expressed group(median = 215.2 months). No significant difference was observed in BMP8A and BMPRs in tumours according to their staging and lymph node involvement. Positive correlations were found between BMP8A and tumour proliferation, EMT, angiogenic markers. Conclusion BMP8A is increased in breast cancer and correlates with poor prognosis. The highly correlated BMPRs might be involved in the signal transduction of BMP8A to co-regulate BMP responsive genes and cellular functions which is yet to be investigated. Take-home Message BMP8A is increased in breast cancer and correlates with poor prognosis.

Risk Signature of Cancer-Associated Fibroblast-Secreted Cytokines Associates With Clinical Outcomes of Breast Cancer.

Cancer-associated fibroblasts (CAFs) are key components in tumor microenvironment (TME). The secreted products of CAFs play important roles in regulating tumor cells and further impacting clinical prognosis. This study aims to reveal the relationship between CAF-secreted cytokines and breast cancer (BC) by constructing the risk signature. We performed three algorithms to reveal CAF-related cytokines in the TCGA BC dataset and identified five prognosis-related cytokines. Then we used single-cell RNA sequencing (ScRNA-Seq) datasets of BC to confirm the expression level of these five cytokines in CAFs. METABRIC and other independent datasets were utilized to validate the findings in further analyses. Based on the identified five-cytokine signature derived from CAFs, BC patients with high-risk score (RS) had shorter overall survival than low-RS cases. Further analysis suggested that the high-RS level correlated with cell proliferation and mast cell infiltration in BCs of the Basal-like subtype. The results also indicated that the level of RS could discriminate the high-risk BC cases harboring driver mutations (i.e., PI3KCA, CDH1, and TP53). Additionally, the status of five-cytokine signature was associated with the frequency and molecular timing of whole genome duplication (WGD) events. Intratumor heterogeneity (ITH) analysis among BC samples indicated that the high-RS level was associated with the increase of tumor subclones. This work demonstrated that the prognostic signature based on CAF-secreted cytokines was associated with clinical outcome, tumor progression, and genetic alteration. Our findings may provide insights to develop novel strategies for early intervention and prognostic prediction of BC.

Abstract 3111: Notch3 functions as a tumor suppressor in ER-positive breast cancer

Abstract The Notch signaling pathway has been implicated in the development as well as tumorigenesis of the mammary gland. Notch3 promotes luminal cell specification and marks a highly clonogenic luminal progenitor population. Aberrant Notch3 activation has been shown to promote the growth of basal breast cancer as well as resistance to hormonal therapy in metastatic luminal breast cancer. Interestingly, recent studies also suggest a tumor-suppressive function of Notch3 in mammary epithelium through regulation of estrogen receptor α (ER). Here we report the expression and functional analysis of Notch3 in the mouse mammary gland. X-gal staining of the Notch3β-Geo/+ mammary gland showed that Notch3 was highly expressed in luminal cells throughout mammary development with exception at the initiation of post-lactational involution, when Notch3 expression was restricted to the basal cells. Deletion of Notch3 caused decreased Notch activation in the CD24HiCD49fLo subpopulation of the pubescent mammary gland, accompanied by a significant decrease in the number of CD24HiCD49fLoCD61+ luminal progenitor cells. Whole-mount preparation of the Notch3 knockout mammary glands showed normal development during puberty, pregnancy, lactation and involution. Surprisingly, parous Notch3 knockout mice developed mammary ductal hyperplasia by 10 months of age, some of which progressed to ductal carcinoma in situ, and ultimately to invasive and metastatic cancer. Parous Notch3 knockout mice exhibited an expansion of the CD24HiCD49fLo subpopulation, and mammary tumors from these mice were composed predominantly of CD24HiCD49fLo cells. The vast majority of these tumors were ER-positive and relatively well differentiated, with a papillary and/or glandular pattern. They expressed the luminal marker cytokeratin 8, and some of them co-expressed cytokeratin 14, a basal marker. All Notch3 knockout mammary tumors showed high level expression of Cyclin D1. These results suggest that Notch3 may prevent ER-positive breast cancer through suppression of CD24HiCD49fLo progenitor cell self-renewal in the postpartum mammary gland. In addition to its impact on mammary epithelium, deletion of Notch3 altered the mammary microenvironment, in particular, brown adipocyte differentiation in the mammary fat pad. Further experiments will be performed to define a potential role for Notch3-regulated brown adipose tissue in breast cancer initiation and progression. Finally, analysis of TCGA and METABRIC human breast cancer data sets revealed a negative correlation between expressions of NOTCH3 and ESR1 (encoding estrogen receptor α), and association of high NOTCH3 expression with enhanced survival of patients with luminal A and luminal B subtype breast tumors. Taken together, Notch3 can act as a tumor suppressor in the mammary epithelium, and possibly in the mammary microenvironment as well, to prevent development and metastasis of ER-positive breast cancer. Citation Format: Wen-Cheng Chung, Sean E. Egan, Keli Xu. Notch3 functions as a tumor suppressor in ER-positive breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3111.

Abstract 2411: CEACAM1 is a Critical SOX9-regulated gene that suppresses TNBC growth

Abstract Background: Triple-negative breast cancers (TNBCs), which lack expression of the estrogen and progesterone receptors and the HER2 protein, are typically treated with chemotherapy and have a poor prognosis. Our previous studies have demonstrated that the SOX9 transcription factor is highly expressed in TNBC and is essential for survival and metastasis of these aggressive breast cancers. Hypothesis: CEACAM1 is a SOX9 regulated gene that regulates TNBC growth and metastasis. Material and Methods: RNA-Seq analysis was used to identify SOX9 downstream targets in MDA MB-231, MDA MB-468 or MCF-7 cells, with support from MD Anderson's genomic biostatistics core. Cells were treated with or without siRNAs or overexpression plasmids to knock down or over-express target genes. Cell growth was measured using an automated cell counting assay. Protein and mRNA levels were examined by western blotting and qRT-PCR assays. CHIP assay was used to examine direct binding of SOX9 protein on promoter of CEACAM1 gene. Several breast cancer datasets were used to analyze CEACAM1 expression in TNBCs and non-TNBCs, and the association between SOX9 and CEACAM1 expression. Significant genes are defined by using a false discovery rate (FDR) cut-off of 0.01 and log2 fold change of 2. Significant common genes are defined by using a FDR cut-off of 0.05 and log2 fold change of 1 among the cell lines. Data are presented as mean values ± SD. Statistical significance (p-values) was calculated using the Student's t-test unless otherwise indicated. Results: Upon SOX9 knockdown, 340 genes and 843 genes levels were significantly changed in MDA MB-231 and MDA MB-468 respectively. Upon SOX9 overexpression, 250 genes were regulated in MCF-7 cells. There were 38 common genes regulated by SOX9 in MDA MBA-231, MDA MB-468 cells and MCF-7 cells. Among 38 common genes, 5 genes showed positive correlation with SOX9 level (MIOX, LAMB2P1, SLCO4C1, RGCC, and PRTN3 genes). The most highly up-regulated genes upon SOX9 knockdown in TNBC cells were CEACAM1, PRSS35, CALB1, and SLC6A19. We then investigated how these SOX9 downstream genes affected TNBC cell growth in vitro. Knockdown of RGCC, PRTN3, or SLCO4C1 by siRNA reduced cell growth in TNBC cells, but had minimal effect on the growth of MCF-7 cells. Loss of CEACAM1 promoted the growth of MDA MBA-231 and MDA MB-468 cells, while overexpression of CEACAM1 decreased cell growth in TNBC cells. Bioinformatic analysis of the Curtis dataset demonstrated that TNBCs had lower CEACAM1 expression as compared to non-TNBCs. CEACAM1 was inversely correlated with SOX9 expression in the Curtis and TCGA breast cancer datasets. CHIP assays were then performed that showed that the CEACAM1 gene promoter is bound by the SOX9 transcript factor in MDA MD-231 cells. Conclusion: Our results demonstrate that CEACAM1 is a SOX9-regulated gene and is a suppressor of TNBC growth. Grant Support: These studies were supported by a Breast Cancer Research Foundation (BCRF) grant (PB). Citation Format: Yanxia Ma, William M. Tahaney, Ganiraju C. Manyam, Wenyi Wang, Abhijit Mazumdar, Powel H. Brown. CEACAM1 is a Critical SOX9-regulated gene that suppresses TNBC growth [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2411.

Abstract LB207: Glutamine transporter SLC38A3 promotes breast cancer migration via GSK3beta/beta-catenin/EMT pathway

Abstract Breast cancer is one of the most commonly diagnosed cancers and the leading cause of cancer-related death among women. Triple negative breast cancer (TNBC) is a subtype of breast cancer characterized by the absence of estrogen receptor, progesterone receptor and HER2 expression. TNBC shows a high capacity for early metastasis and leads to worse clinical outcomes than other breast cancer subtypes due to the lack of specific therapeutic targets. We are looking to develop cancer-specific therapeutic targets for TNBC. Many types of cancer cells including TNBC cells rely on glutamine as carbon and nitrogen source to fuel unchecked growth. We screened for key genes in regulating glutamine metabolism in a panel of breast cancer cell lines. This screen identified the mRNA and protein levels of solute carrier family 38 member 3 (SLC38A3), a glutamine transporter, to be upregulated in human breast cancer cell lines, especially in TNBC cell lines. The TCGA breast cancer patient database also showed that SLC38A3 mRNA is overexpressed in invasive ductal breast carcinoma tissues, and it is even higher in TNBC relative to other breast cancer subtypes. To test the biological role of SLC38A3 protein in TNBC cells, we performed loss-of-function experiments in multiple TNBC cell lines. Silencing of SLC38A3 decreased cellular glutamate, glutamine and alanine levels. Silencing of SLC38A3 also activated apoptosis, and suppressed cell viability, migration and invasion in several TNBC cell lines. Interestingly, silencing of SLC38A3 increased the activity of glycogen synthase kinase 3-β (GSK3β) which promoted the degradation of β-catenin, leading to the decrease of the mRNA levels of epithelial-to-mesenchymal-transition (EMT)-associated transcription factors in TNBC cell lines. In summary, we showed that SLC38A3 is overexpressed in TNBC and promotes breast cancer migration and invasion via GSK3β/β-catenin/EMT pathway, which could be a novel therapeutic target for breast cancer. Citation Format: Zheqiong Tan, Caitlin M. Tressler, Kanchan Sonkar, Kristine Glunde. Glutamine transporter SLC38A3 promotes breast cancer migration via GSK3beta/beta-catenin/EMT pathway [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB207.

Abstract 245: A comprehensive characterization of hyper-morph, hypo-morph, and neo-morph mutations in cancer

Abstract Although annotation of genomic mutations is a highly relevant and complex segment of the analysis of sequence-based genomic analyses, currently more than ten million variants lack functional annotation. While computational predictions of variant function are usually integrated into gene-based analyses of rare-variants, there is limited information for assessing variant function in the context of a particular disease. The goal of this study is to assess the mechanistic characterization of context-dependent hyper-, hypo-, and neomorph mutations in cancers. We developed a computational approach to characterize these mutations and assess the functional effects of mutations occurring in the same or different protein domains, and differentiate mutations in terms of their hyper-morph (gain-of-function), hypo-morph (loss-of-function), neutral, or neo-morph (establishing a novel function) potential. To elucidate the functional consequence of such mutations, we based our computational pipeline on inferring the activity of regulatory proteins such as transcription factors (TFs) and co-factors (co-TFs) using the VIPER algorithm. Our analytical pipeline integrates structural and functional information encompassing six topics : 1) structural domains affected by the mutation, 2) the overlap between mutation-specific TF/co-TFs, 3) differential activity signatures and signatures induced by established hyper-morph, hypo-morph and neutral or neo-morph mutations, 4) in vitro data generated by reporter assays, 5) the VIPER-inferred activity of each protein relative to a validated control, and 6) the fraction of proteins in a sample that are not affected by established hyper-morphs and hypo-morphs (candidate neo-morphs).The current repertoire considers 25 TCGA cohorts for 3830 proteins (oncoproteins/tumor suppressors). As an example, we validated our method on the TCGA Breast Cancer dataset (TCGA-BRCA) by predicting with very high confidence several neo-morphic phenotypes, including the previously-described PIK3CAE545, PIK3CAE542, PIK3CAH1047, PIK3CAQ546K and PIK3CAG1049R. Interestingly, PIK3CAE545K, classified previously as a gain-of-function mutation (in one TCGA-BRCA sample) or a loss-of-function mutation (in two other TCGA-BRCA samples), is predicted to be a neo-morph based on our approach. Further validation of these mutations using PIK3CA reporter assays led to the identification of several significant hypo-morphic signals in TP53 mutant samples. We defined this phenomenon as mutational mimicry (i.e. mutations in proteins mimicking those in established oncogenes) and we propose it as a tool for predicting tumor sensitivity/resistance to drugs. Citation Format: Somnath Tagore, Andrea Califano. A comprehensive characterization of hyper-morph, hypo-morph, and neo-morph mutations in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 245.

NEFM DNA methylation correlates with immune infiltration and survival in breast cancer

BackgroundThis study aims to determine whether NEFM (neurofilament medium) DNA methylation correlates with immune infiltration and prognosis in breast cancer (BRCA) and to explore NEFM-connected immune gene signature.MethodsNEFM transcriptional expression was analyzed in BRCA and normal breast tissues using Oncomine and Tumor Immune Estimation Resource (TIMER) databases. The relationship between NEFM DNA methylation and NEFM transcriptional expression was investigated in TCGA. Potential influence of NEFM DNA methylation/expression on clinical outcome was evaluated using TCGA BRCA, The Human Protein Atlas and Kaplan–Meier plotter databases. Association of NEFM transcriptional expression/DNA methylation with cancer immune infiltration was investigated using TIMER and TISIDB databases.ResultsHigh expression of NEFM correlated with better overall survival (OS) and recurrence-free survival (RFS) in TCGA BRCA and Kaplan–Meier plotter, whereas NEFM DNA methylation with worse OS in TCGA BRCA. NEFM transcriptional expression negatively correlated with DNA methylation. NEFM DNA methylation significantly negatively correlated with infiltrating levels of B, CD8+ T/CD4+ T cells, macrophages, neutrophils and dendritic cells in TIMER and TISIDB. NEFM expression positively correlated with macrophage infiltration in TIMER and TISIDB. After adjusted with tumor purity, NEFM expression weekly negatively correlated with infiltration level of B cells, whereas positively correlated with CD8+ T cell infiltration in TIMER gene modules. NEFM expression/DNA methylation correlated with diverse immune markers in TCGA and TISIDB.ConclusionsNEFM low-expression/DNA methylation correlates with poor prognosis. NEFM expression positively correlates with macrophage infiltration. NEFM DNA methylation strongly negatively correlates with immune infiltration in BRCA. Our study highlights novel potential functions of NEFM expression/DNA methylation in regulation of tumor immune microenvironment.

Splicing factor SRSF1 promotes breast cancer progression via oncogenic splice switching of PTPMT1

BackgroundIntensive evidence has highlighted the effect of aberrant alternative splicing (AS) events on cancer progression when triggered by dysregulation of the SR protein family. Nonetheless, the underlying mechanism in breast cancer (BRCA) remains elusive. Here we sought to explore the molecular function of SRSF1 and identify the key AS events regulated by SRSF1 in BRCA.MethodsWe conducted a comprehensive analysis of the expression and clinical correlation of SRSF1 in BRCA based on the TCGA dataset, Metabric database and clinical tissue samples. Functional analysis of SRSF1 in BRCA was conducted in vitro and in vivo. SRSF1-mediated AS events and their binding motifs were identified by RNA-seq, RNA immunoprecipitation-PCR (RIP-PCR) and in vivo crosslinking followed by immunoprecipitation (CLIP), which was further validated by the minigene reporter assay. PTPMT1 exon 3 (E3) AS was identified to partially mediate the oncogenic role of SRSF1 by the P-AKT/C-MYC axis. Finally, the expression and clinical significance of these AS events were validated in clinical samples and using the TCGA database.ResultsSRSF1 expression was consistently upregulated in BRCA samples, positively associated with tumor grade and the Ki-67 index, and correlated with poor prognosis in a hormone receptor-positive (HR+) cohort, which facilitated proliferation, cell migration and inhibited apoptosis in vitro and in vivo. We identified SRSF1-mediated AS events and discovered the SRSF1 binding motif in the regulation of splice switching of PTPMT1. Furthermore, PTPMT1 splice switching was regulated by SRSF1 by binding directly to its motif in E3 which partially mediated the oncogenic role of SRSF1 by the AKT/C-MYC axis. Additionally, PTPMT1 splice switching was validated in tissue samples of BRCA patients and using the TCGA database. The high-risk group, identified by AS of PTPMT1 and expression of SRSF1, possessed poorer prognosis in the stage I/II TCGA BRCA cohort.ConclusionsSRSF1 exerts oncogenic roles in BRCA partially by regulating the AS of PTPMT1, which could be a therapeutic target candidate in BRCA and a prognostic factor in HR+ BRCA patient.

Comparative analysis of triple-negative breast cancer transcriptomics of Kenyan, African American and Caucasian Women

Purpose: Triple-negative breast cancer (TNBC) patients of various ethnic groups often have discrete clinical presentations and outcomes. Women of African descent have a disproportionately higher chance of developing TNBCs. The aim of the current study was to establish the transcriptome of TNBCs from Kenyan (KE) women of Bantu origin and compare it to those TNBCs of African-Americans (AA) and Caucasians (CA) for identifying KE TNBC-specific molecular determinants of cancer progression and potential biomarkers of clinical outcomes. Patients and Methods: Pathology-confirmed TNBC tissues from Kenyan women of Bantu origin (n = 15) and age and stage range matched AA (n = 19) and CA (n = 23) TNBCs of patients from Alabama were included in this study. RNA was isolated from paraffin-embedded tissues, and expression was analyzed by RNA sequencing. Results: At clinical presentation, young KE TNBC patients have tumors of higher stages. Differential expression analysis identified 160 up-regulated and 178 down-regulated genes in KE TNBCs compared to AA and CA TNBCs. Validation analyses of the TCGA breast cancer data identified 45 KE TNBC-specific genes that are involved in the apoptosis (ACTC1, ERCC6 and CD14), cell proliferation (UHRF2, KDM4C, UHMK1, KCNH5, KRT18, CSF1R and S100A13), and Wnt signaling (BCL9L) pathways. Conclusions: In this study, we identified biomarkers that are specific for KE TNBC patients of Bantu origin. Further study with a larger sample size of matched tumors could confirm our findings. If biologically confirmed, these molecular determinants could have clinical and biological implications and serve as targets for development of personalized therapeutics for KE TNBC patients.

Novel lncRNAs Co-Expression Networks Identifies LINC00504 with Oncogenic Role in Luminal A Breast Cancer Cells.

Long non-coding RNAs (lncRNAs) are functional transcripts with more than 200 nucleotides. These molecules exhibit great regulatory capacity and may act at different levels of gene expression regulation. Despite this regulatory versatility, the biology of these molecules is still poorly understood. Computational approaches are being increasingly used to elucidate biological mechanisms in which these lncRNAs may be involved. Co-expression networks can serve as great allies in elucidating the possible regulatory contexts in which these molecules are involved. Herein, we propose the use of the pipeline deposited in the RTN package to build lncRNAs co-expression networks using TCGA breast cancer (BC) cohort data. Worldwide, BC is the most common cancer in women and has great molecular heterogeneity. We identified an enriched co-expression network for the validation of relevant cell processes in the context of BC, including LINC00504. This lncRNA has increased expression in luminal subtype A samples, and is associated with prognosis in basal-like subtype. Silencing this lncRNA in luminal A cell lines resulted in decreased cell viability and colony formation. These results highlight the relevance of the proposed method for the identification of lncRNAs in specific biological contexts.