Overall Survival In Breast Cancer Research Articles

Suppression of Breast Cancer Progression by FBXL16 Via Oxygen-Independent Regulation of HIF1α Stability

Summary Triple-negative breast cancers (TNBCs) are characterized by high rates of recurrence and aggressiveness, and poor clinical outcomes. Deregulated E3 ligases are involved in breast cancer pathogenesis and progression, but the underlying mechanisms are unclear. Here, we found that F-box and leucine-rich repeat protein 16 (FBXL16) acts as a tumor suppressor in TNBC. Specifically, FBXL16 directly binds to HIF1α and induces its ubiquitination and degradation, regardless of the tumor microenvironment, resulting in blockade of the HIF1α-mediated epithelial-mesenchymal transition (EMT) and angiogenesis features of breast cancer. In TNBC, FBXL16 expression is downregulated by the p38/miR-135b-3p axis, and loss of FBXL16 expression restores HIF1α-mediated metastatic features of breast cancer. Low expression of FBXL16 is associated with high-grade and lymph node-positive tumors and poor overall survival of breast cancer. Together, these findings reveal a novel suppressive role of FBXL16 in regulating breast cancer progression and suggest that modulation of FBXL16 expression may offer a favorable strategy for treatment of patients with metastatic breast cancer, including TNBCs.

CD8+ T Lymphocyte Coexpression Genes Correlate with Immune Microenvironment and Overall Survival in Breast Cancer.

Purpose To identify CD8+ T lymphocyte-related coexpressed genes that increase CD8+ T lymphocyte proportions in breast cancer and to elucidate the underlying mechanisms among relevant genes in the tumor microenvironment. Method We obtained breast cancer expression matrix data and patient phenotype following information from TCGA–BRCA FPKM. Tumor purity, immune score, stromal score, and estimate score were calculated using the estimate package in R. The CD8+ T lymphocyte proportions in each breast carcinoma sample were estimated using the CIBERSORT algorithm. The samples with p < 0.05 were considered to be significant and were taken into the weighted gene coexpression network analysis. Based on the CD8+ T lymphocyte proportion and tumor purity, we generated CD8+ T lymphocyte coexpression networks and selected the most CD8+ T lymphocyte-related module as our interested coexpression modules. We constructed a CD8+ T cell model based on the least absolute shrinkage and selection operator method (LASSO) regression model and robust model and evaluate the prediction ability in different subgroups. Results A breast carcinoma CD8+ T lymphocyte proportion coexpression yellow module was determined. The coexpression genes in the yellow module were determined to increase the CD8+ T lymphocyte proportion levels in breast cancer patients. The yellow module was significantly enriched in the antigen presentation process, cellular response to interferon-gamma, and leukocyte proliferation. Subsequently, we generated CD8+ T cell-related genes lasso regression risk model and robust model, and eight genes were taken into the risk model. The risk score showed significant prognostic ability in various subgroups. Expression levels of proteins, encoded by CD74, were lower in the breast carcinoma samples than in normal tissue, suggesting expression differences at both the mRNA and the protein levels. Conclusion These eight CD8+ T lymphocyte proportion coexpression genes increase CD8+ T lymphocyte in breast cancer by an antigen presentation process. The mechanism might suggest new pathways to improve outcomes in patients who do not benefit from immune therapy.

A novel metabolic gene signature-based nomogram to predict overall survival in breast cancer.

BackgroundBreast cancer risk prediction is often based on clinicopathological characteristics despite the high heterogeneity derived from gene expression. Metabolic alteration is a hallmark of cancer, and thus, the integration of a metabolic signature with clinical parameters is necessary to predict disease outcomes in breast cancers.MethodsMetabolic genes were downloaded from the Gene Set Enrichment Analysis (GSEA) dataset. Genes with statistical significance in the univariate analysis were applied in the least absolute shrinkage and selection operator (LASSO) analysis to build a gene signature in the GSE20685 dataset. Clinicopathological characteristics and risk scores with prognostic significance were incorporated into the nomogram to predict the overall survival (OS) of patients. The Cancer Genome Atlas (TCGA) and GSE866166 datasets were used as the validation datasets. Time-dependent receiver operating characteristic (tROC) curves and calibration plots were used to assess the accuracy and discrimination of the model.ResultsA 55-gene metabolic gene signature (MGS) was constructed, and was significantly related to OS both in the discovery (P<0.001) and validation (P<0.001) datasets. The MGS was an independent prognostic factor and could divide patients into high- and low-risk groups regardless of their different prediction analysis of microarray 50 (PAM50) subtypes. Time-dependent ROC curves indicated that the risk scores based on the MGS [area under the ROC curve (AUC): 0.931] were superior to the those based on the American Joint Committee on Cancer (AJCC) stage (AUC: 0.781) and PAM50 (AUC: 0.675). A nomogram based on the AJCC stage and risk score could predict OS, and the calibration curves showed good agreement to the actual outcome, indicating that the nomogram may have practical utility. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis indicated that this MGS was primarily enriched in amino acid pathways.ConclusionsOur results demonstrated that the MGS was superior to existing risk predictors such as PAM50 and AJCC stage. By combining clinical factors (AJCC stage) and the MGS, a nomogram was constructed and showed good predictive ability for OS in breast cancer.

Abstract PS7-91: Influence of physician’s lifestyle on the prescription of healthy habits to breast cancer patients (LACOG 1218)

Abstract BACKGROUND Healthy lifestyle has been shown to have a positive impact on quality of life, risk of recurrence, and overall survival in breast cancer (BC). Physicians play an important role in encouraging their patients to lifestyle modification. Nonetheless, little is known whether physician lifestyle can impact on healthy habits recommendations to BC patients. We aimed to evaluate how physician’s lifestyle influences the prescription of healthy habits to BC patients. METHODSLACOG 1218 was an observational, cross-sectional study. An online questionnaire composed of 14 objective questions to evaluate physician lifestyle and prescription of healthy habits to BC patients was developed and circulated by e-mail to breast surgeons, clinical and radiation oncologists who were members of the Brazilian Society of Clinical Oncology (SBOC) and Latin American Cooperative Oncology Group (LACOG) and dedicated to the treatment of BC patients. The primary objective of the study was to evaluate the correlation between the physician lifestyle and the prescription of healthy habits to BC patients. A multivariate Poisson regression analysis was used to assess which factors of physician lifestyle could influence prescription of healthy habits.RESULTSA total of 267 physicians answered the questionnaire from October to November 2018. Of these, 142 (53.2%) were clinical oncologists, 116 (43.5%) were breast surgeons, and 9 (3.4%) were radiation oncologists. Female were 58.4%, 51.8% were older than 50 years and the majority 71.5% worked in private health insurance practice. In terms of physician lifestyle, 228 (85.4%) had healthy eating habits, 236 (88.4%) practiced physical activity and 93 (34.9%) were self-reported with overweight or obese. A total of 143 (46.1%) did not drink alcohol or drunk less than once a month and did not consume more than 5 doses and only 8 (3%) of them were current smoker. Overall, 84.3% of the physicians advised their BC patients on the importance of lifestyle modification. Physicians who did not exercise regularly have a higher chance of not advising for health lifestyle (HR 2.48; 95% CI 1.28 to 4.82, p=0.0265) as opposite to physicians older than 50 years (RR 0.37; CI 95% 0.15 - 0.92; p=0.0118).Obesity treatment and management was performed by 121 (45.3%) of physicians. Being a breast surgeon (RR 1.29; 95% CI 1.02 to 1.63, p=0.0025) or radiation oncologists (RR 1.82; 95% CI 1.43 to 2.31, p=0.0025) were the only factors associated with not performing obesity treatment and management. About 53.4% of physicians referred overweight or obese patients to a dietician and/or endocrinologist. Male gender (RR 1.35; CI 95% 1.03-1.76; p=0.0296), breast surgeons (RR 1.99; CI 95% 1.50-2.64; p=0.0001) and clinical practice in public health system (RR 1.53; CI 95% 1.20-1.96; p=0.0012) were factors associated with not referring patients to dietician and/or endocrinologist as opposed to physicians older than 50 years (RR 0.46; CI 95% 0.28-0.75; p=0.0005).CONCLUSIONIn general physicians treating BC patients have a healthy lifestyle. Physicians who practice physical activity regularly or older than 50 years had more chance to advise lifestyle modification. Only half of BC patients’ physicians treat obesity or refer these patients to specialist which in this case may impact BC patient’s outcome. Citation Format: Renata Cangussú, Eldsamira Mascarenhas, Taiane F Rebelatto, Paulo R Nunes, Rafaela G de Jesus, Facundo Zaffaroni, Gustavo Werutsky. Influence of physician’s lifestyle on the prescription of healthy habits to breast cancer patients (LACOG 1218) [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS7-91.

Abstract PS6-21: High expression of MicroRNA-223 indicates better prognosis in triple negative breast cancer

Abstract Background: MicroRNAs (miRNAs) can influence many biological processes and also show promise as biomarkers for cancer. Few researches have focused on the expression of microRNA-223 (miR-223) and its precise role in breast cancer (BC). We aimed to examine the expression level of miR-223 and further explored the prognostic value in BC.Methods: Tissue microarray-based miRNA detection in situ hybridization with LNA probe was used to detect miR-223 expression in 450 BC tissue. Overall survival (OS) and disease-free survival (DFS) were compared between two groups using the Kaplan-Meier method and Cox regression model.Results: Better OS and DFS were observed in the high-miR-223 expression patients compared to those of low expression patients (P &amp;lt; 0.0001 and P = 0.017, respectively), especially in the triple-negative breast cancer (TNBC) subtype (P = 0.046and P &amp;lt; 0.001, respectively). Combined with the univariate and multivariate Cox regression analysis, TNM stage (p = 0.008), molecular subtype (p =0.049) and miR-223 (p &amp;lt; 0.001) were independently linked to OS and DFS. External validation was performed in METABRIC and TCGA database via online webtool and consistent with the data above.Conclusions: This study provided evidence that high-miR-223 expression at diagnosis was associated with better DFS and OS for BC, especially for the TNBC subtype. miR-223 is a valid and independent prognostic biomarker in BC. Table Univariate and multivariate survival analysis for disease-free survivalUnivariate MultivariateVariableHR95% CIP valueHR95% CIP valueAge0.594≤40 vs &amp;gt;601.3510.626-2.9140.44440-60 vs &amp;gt;600.9940.548-1.8030.984Menopausal statuspre vs post0.7370.487-1.1130.147DifferentiationII vs III0.7300.457-1.1640.186TNM stage0.0080.008II vs I1.4210.860-2.3460.1701.4850.887-2.4850.132III vs I2.7581.446-5.2590.0022.8581.469-5.5630.002Molecular subtype0.1940.049Luminal B vs Luminal A1.1060.580-2.1070.7600.8130.415-1.5930.546HER2+ vs Luminal A0.9860.497-1.9560.9670.7010.337-1.4580.342Triple-negative vs Luminal A1.6260.930-2.8430.0881.4930.849-2.6260.164MicroRNA-223low vs high3.9602.201-7.126&amp;lt;0.0013.7892.098-6.843&amp;lt;0.001Abbreviations: CI, confidence interval; HR, hazard ratio.The covariates in the Cox model were all categorical variables, and the adjusted p value and HR were derived from the model. Citation Format: Li Chen, Xiuzhi Zhu, Ling Yao, Zonghua Wang. High expression of MicroRNA-223 indicates better prognosis in triple negative breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS6-21.

ADAM10 is involved in the oncogenic process and chemo-resistance of triple-negative breast cancer via regulating Notch1 signaling pathway, CD44 and PrPc

BackgroundTriple-negative breast cancer (TNBC) is the most challenging breast cancer subtype to treat, because it is so aggressive with shorter survival. Chemotherapy remains the standard treatment due to the lack of specific and effective molecular targets. The aim of the present study is to investigate the potential roles of A Disintegrin and Metalloproteinase 10 (ADAM10) on TNBC cells and the effects of combining ADAM10 expression and neoadjuvant chemotherapy treatment (NACT) to improve the overall survival in breast cancer patients.MethodsUsing a series of breast cancer cell lines, we measured the expression of ADAM10 and its substrates by quantitative real-time PCR assay (qRT-PCR) and western blot analysis. Cell migration and invasion, cell proliferation, drug sensitivity assay, cell cycle and apoptosis were conducted in MDA-MB-231 cells cultured with ADAM10 siRNA. The effect of ADAM10 down-regulation by siRNA on its substrates was assessed by western blot analysis. We performed immunohistochemical staining for ADAM10 in clinical breast cancer tissues in 94 patients receiving NACT.ResultsThe active form of ADAM10 was highly expressed in TNBC cell lines. Knockdown of ADAM10 in MDA-MB-231 cells led to a significant decrease in cell proliferation, migration, invasion and the IC50 value of paclitaxel and adriamycin, while induced cell cycle arrest and apoptosis. And these changes were correlated with down-regulation of Notch signaling, CD44 and cellular prion protein (PrPc). In clinical breast cancer cases, a high ADAM10 expression in pre-NACT samples was strongly associated with poorer response to NACT and shorter overall survival.ConclusionsThese data suggest the previously unrecognized roles of ADAM10 in contributing to the progression and chemo-resistance of TNBC.

An immune-related risk gene signature predicts the prognosis of breast cancer.

Accurate prediction of the outcome of breast cancer remains as a challenge due to its heterogeneous nature. We aimed to construct an immune-related risk signature to predict the overall outcome of breast cancer using bioinformatic approaches. In this study, transcriptome and survival data obtained from The Cancer Genome Atlas database and the Gene Expression Omnibus database were used to identify differentially expressed genes between breast cancer and normal samples. A regulatory network was constructed based on the immune-related prognostic genes and transcription factors screened from the differently expressed genes. The immune-related risk gene signature was obtained using the least absolute shrinkage and selection operator (LASSO) method and Cox regression model. The immune-related prognostic scores of breast cancer (IPSBC) calculated from the risk signature were used to group breast cancer patients by risk levels. The accuracy of IPSBC was evaluated by survival analysis and receiver operating characteristic curve analysis. The independency and the relationship of IPSBC with clinicopathological characteristics and abundance of tumor-infiltrated immune cells were also investigated. A total of 4296 differentially expressed genes between breast cancer and normal samples were identified, and a total of 13 prognostic immune-related genes were eventually selected as the risk gene signature, which was an independent prognostic factor of the overall survival of breast cancer. The IPSBC stratified breast cancer patients into low- and high-risk groups. Breast cancer patients in the high-risk group were associated with worse overall outcomes, more advanced stage and less abundance of tumor-infiltrated immune cells, including B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells compared to low-risk group. In this study, an immune-related gene signature of breast cancer was identified, which could be used as potential prognostic and therapeutic targets of breast cancer.

Evaluation des facteurs pronostiques dans le cancer du sein chez la femme au Sénégal : à propos de 288 cas

INTRODUCTION : Au Sénégal le cancer du sein représente le deuxième cancer féminin et pose un problème de santé public majeur. Le but de ce travail était d’évaluer les facteurs pronostiques dans l’évolution du cancer du sein chez la femme. PATIENTS ET METHODES : Il s'agit d'une étude rétrospective réalisée sur une période sur un an allant du 1er janvier 2008 au 31 Décembre 2008 portant sur l'ensemble des femmes suivies pour cancer du sein au service de cancérologie à l'Institut Joliot Curie. Ainsi, 288 patientes atteintes de cancer du sein ont été colligés. RESULTATS : La moyenne d’âge de nos malades était de 47,32 ans. La parité moyenne était de 4,9 enfants par femme. Vingt-deux soit 7% des patientes avaient un antécédent de cancer. Cliniquement, la taille tumorale était classée T4 chez 180 patientes soit 81%. Une atteinte ganglionnaire chez 188 patientes (65,2%). Le type histologique le plus fréquent était le carcinome canalaire infiltrant avec 90,3% des cas. Une prédominance des grades SBRII et SBRIII a été observé (respectivement 41% et 46%). Les récepteurs hormonaux (RH) étaient positifs dans huit cas (24%). La surexpression du gène HER2 était retrouvée chez seulement quatre patientes sur 30. Les limites de la chirurgie étaient précisées chez 48 patientes avec des marges envahies chez sept patientes (14,5%). La présence d'emboles vasculaires était notée chez 18 patientes parmi les 29 dont la recherche a été effectuée chez 179 patientes soit 62%. Au moment du diagnostic initial, 45 patientes soit 19,7% des malades présentaient au moins une métastase distance. La majorité des patientes étaient reçues à un stade avancé (89%, classées entre stade III et IV). Une seule patiente était reçue au stade I. La survie globale pour les cancers du sein était à 72% à 3 ans et 30% à 5 ans. La survie globale à 5 ans des patientes au stade localisé de la maladie était de 85% contre 5% pour les patientes au stade avancé. CONCLUSION : Les facteurs pronostiques sont multiples et souvent péjoratifs chez nos patients avec une prédominance des femmes jeunes, des cancers localement avancés et des formes biologiques agressifs.

Breast cancer overall-survival can be predicted with a 19 lncRNA tissue signature

Breast cancer overall-survival can be predicted with a 19 lncRNA tissue signature

Chemical features of blood-borne TRG CDR3s associated with an increased overall survival in breast cancer.

Immunogenomics and earlier, pioneering studies, particularly by Whiteside and colleagues, have indicated a positive role for B-cells in breast cancer, as well as a positive role for gamma-delta T-cells. However, these studies have been completely limited to assessing breast cancer tumor tissue. Our analyses here has shown that blood-borne T-cell receptor gamma (TRG) chain sequences were associated with greater overall survival, of particular note due to the comparative longevity of primary breast cancer patients, whereby assessments of disease-free, but rarely overall survival parameters are possible. Additional immunogenomics approaches narrowed the overall survival correlations to specific, TRG complementarity determining region-3, amino acid (AA) sequence chemical features, independently of many common, confounding variables in the breast cancer setting, such as estrogen or progesterone receptor status. These results are discussed in the context of patient age and with regard to potential antigenic targets, based on the chemistry of the TRG CDR3 AA sequences associated with the higher survival rates.

Development of nomograms predicting overall survival of breast cancer based on indicators of nutritional status: An observational prospective study

Development of nomograms predicting overall survival of breast cancer based on indicators of nutritional status: An observational prospective study

Clinical impact of interruption in adjuvant Trastuzumab therapy in patients with operable HER-2 positive breast cancer

BackgroundTrastuzumab-induced cardiotoxicity (TIC) can lead to early discontinuation of adjuvant therapy, however there is limited evidence on long-term survival outcomes in patients with operable human epidermal growth factor receptor 2 (HER2)-positive breast cancer (BC) experiencing treatment interruption or discontinuation.MethodsThe primary objective of the study was to evaluate disease-free survival (DFS) in non-metastatic, HER2-positive, female BC patients who experienced treatment interruption or early discontinuation of trastuzumab therapy. Clinical and histopathological data were collected on 400 patients at The Ohio State University, an NCI-designated comprehensive cancer center between January 2005 and December 2015. Treatment interruption was defined as any delay of ≥2 weeks during trastuzumab therapy, including permanent cessation prior to completing planned therapy. TIC was defined as LVEF < 50% or > 15 points decline from baseline as evaluated by 2D echocardiogram after initiation of (neo) adjuvant therapy. DFS was defined as the time from diagnosis to first recurrence (loco-regional or distant recurrence) including second primary BC or death. Overall survival (OS) was defined as the time from diagnosis to death or last known follow up. OS/DFS estimates were generated using Kaplan-Meier methods and compared using Log-rank tests. Cox proportional hazard models were used to calculate adjusted hazard ratios (aHR) for OS/DFS.ResultsA total of 369 patients received trastuzumab therapy; 106 (29%) patients experienced treatment interruption at least once and 42 (11%) permanently discontinued trastuzumab prior to completing planned therapy. TIC was the most common reason for interruption (66 patients, 62%). The median duration of trastuzumab in patients with treatment interruption was 11.3 months (range: 0.5–16.9) with 24 (23%) patients receiving ≤6 months of therapy. This duration includes the time delay related to treatment interruption. Patients with any treatment interruption had worse DFS (aHR: 4.4, p = 0.001) and OS (aHR: 4.8, p < 0.001) after adjusting for age, stage, grade, ER, node status and TIC.ConclusionsTreatment interruption or early discontinuation of trastuzumab therapy in early HER2-positive BC, most often from TIC, is an independent prognostic marker for worse DFS and OS in operable HER2-positive BC. Future prospective studies should consider targeting at-risk populations and optimizing cardiac function to avoid interruption in trastuzumab therapy.

Systemic Analysis of the Prognosis-Associated Alternative Polyadenylation Events in Breast Cancer.

Alternative polyadenylation (APA) is a post-translational modification that occurs during mRNA maturation in humans. Studies suggested that abnormal APA events are associated with the genesis and progression of malignant tumors. Here, we aimed to comprehensively evaluate the prognostic value of APA events involved in breast cancer (BC). Both APA events and clinical information for BC patients were downloaded from The Cancer Genome Atlas (TCGA) database to identify prognosis-related APA events in BC. A total of 462 APA events and 374 APA events were shown to be significantly related to overall survival (OS) and relapse-free survival (RFS), respectively, of BC patients. The TCGA set was randomly divided into a training and a test set. Key prognosis-related APA events were selected by LASSO regression to build prediction signatures for OS and RFS by multivariate Cox regression analysis in the training, test, and whole set. BC patients were stratified into high-risk and low-risk groups based on median risk scores. Kaplan–Meier survival analysis demonstrated that low-risk groups had better OS and RFS than high-risk groups in all three sets. The time-dependent receiver operating characteristic (ROC) curves showed that our signatures had a good predictive ability for survival and recurrence for BC patients in all three sets. The independent prognostic indicators-based nomogram model had excellent performance and considerable net benefit for predicting the OS and RFS in BC. A PPI network was constructed between key prognosis and core regulators associated with APA, consisting of 48 nodes and 244 edges. Functional enrichment analysis also revealed their association with RNA processing and RNA synthesis. Collectively, our data indicate that prognostic signatures based on APA events may be powerful prognostic predictors for OS and RFS in BC.

Su(var)3–9, Enhancer of Zeste, and Trithorax Domain-Containing 5 Facilitates Tumor Growth and Pulmonary Metastasis through Up-Regulation of AKT1 Signaling in Breast Cancer

Several studies have confirmed the function of Su(var)3-9, Enhancer of zeste, and Trithorax (SET) domain-containing 5 (SETD5) in post-translational modifications of nonhistone proteins. Mutation of the SETD5 gene has been implicated in the progression of many human cancers, such as breast cancer (BC), but its functional role in BC progression is still unknown. The current article investigates the clinical significance and the functional role of SETD5 in BC. Our studies show that SETD5 expression in BC was related to poor clinical outcomes, including lymph node metastasis and advanced clinical stage. SETD5 expression positively correlated with tumor-associated macrophages. SETD5 was an independent predictor of poor overall survival in BC. Furthermore, these studies show that down-regulation of SETD5 significantly decreased BC cell proliferation, metastasis, and angiogenesis, and increased apoptosis of BC cells. The mechanistic analysis showed that SETD5 contributes BC progression by interacting with AKT1 pathway. Also, invivo experiments show that blocking of SETD5 expression significantly inhibited tumor growth and pulmonary metastasis of BC cells. These findings indicate that SETD5 is a potential prognosis marker and facilitates tumor progression of BC.

Cyclin E2 Promotes Whole Genome Doubling in Breast Cancer

Genome doubling is an underlying cause of cancer cell aneuploidy and genomic instability, but few drivers have been identified for this process. Due to their physiological roles in the genome reduplication of normal cells, we hypothesised that the oncogenes cyclins E1 and E2 may be drivers of genome doubling in cancer. We show that both cyclin E1 (CCNE1) and cyclin E2 (CCNE2) mRNA are significantly associated with high genome ploidy in breast cancers. By live cell imaging and flow cytometry, we show that cyclin E2 overexpression promotes aberrant mitosis without causing mitotic slippage, and it increases ploidy with negative feedback on the replication licensing protein, Cdt1. We demonstrate that cyclin E2 localises with core preRC (pre-replication complex) proteins (MCM2, MCM7) on the chromatin of cancer cells. Low CCNE2 is associated with improved overall survival in breast cancers, and we demonstrate that low cyclin E2 protects from excess genome rereplication. This occurs regardless of p53 status, consistent with the association of high cyclin E2 with genome doubling in both p53 null/mutant and p53 wildtype cancers. In contrast, while cyclin E1 can localise to the preRC, its downregulation does not prevent rereplication, and overexpression promotes polyploidy via mitotic slippage. Thus, in breast cancer, cyclin E2 has a strong association with genome doubling, and likely contributes to highly proliferative and genomically unstable breast cancers.

Abstract 2603: Single cell RNA sequencing-based identification of molecular drivers in circulating tumor cell cluster formation and lung metastasis

Abstract Introduction: Circulating tumor cells (CTCs) mediate metastases, which account for 90% of solid tumor-related mortality. Compared to single cells, clustered CTCs mediate metastasis at a 20-100 times higher efficiency and are associated with lower overall survival in breast cancer (BC). We have recently identified a new mechanism of CTC cluster formation through cellular aggregation instead of cohesive shedding, and demonstrated that CTC clusters have enhanced stemness (Cancer Discovery, 2019). However, the cellular heterogeneity and molecular mechanisms underlying CTC cluster formation and polyclonal metastasis have yet to be fully elucidated. We hypothesize that molecular drivers of metastasis initiation enhance cancer stemness and CTC cluster formation, and serve as a novel therapeutic target for BC metastasis. Methods: Using single cell RNA sequencing, we compared tumor cells from the primary breast tumor site and lung metastases of BC patient-derived xenografts. We identified genes specifically expressed in the lung metastases and determined their functional importance in CTC clustering, cancer stemness, and lung colonization. We performed proteomic and transcriptomic analyses as well as machine learning to elucidate the downstream signaling pathways and protein structural basis involved in CTC cluster formation and lung metastasis. Finally, we explored therapeutic intervention options in blocking CTC cluster formation and lung metastasis. New results: Compared to the primary breast tumor cells, we identified a stemness gene signature enriched in a subpopulation of the CD44+ lung metastases, with 30-60 fold higher expression of CD34, CD36, ICAM1, VCAM1, ZEB1, ALDH1A1, TGFBR2 and TSPAN8. Analysis of patient blood samples (N=40) revealed that CD44 and many of these new candidate proteins were enriched in CTC clusters in comparison to single CTCs. We then examined the CSC-related properties of these tumor cells, such as tumorigenesis, sphere formation, and lung metastasis. Knockdown of selected surface molecules (e.g. ICAM1) significantly reduced the efficiency of lung metastasis of BC cells in vivo. A subset of ICAM1+/CD44+ tumor cells had increased stemness and tumor growth upon orthotopic implantation in vivo. Knockdown of ICAM1 dramatically reduced the self-renewal ability in mammosphere formation of breast tumor cells in vitro. In addition, our studies also revealed that these tumor cells cluster through CD44 and other surface protein-mediated homophilic binding between two neighboring tumor cells. Neutralizing antibodies significantly blocked tumor cluster formation and lung colonization. Conclusions: We identified new molecular mediators of CTC aggregation and lung metastasis in BC. We anticipate that specific blockade of tumor clustering could decrease cancer progression and improve survival of BC patients. Citation Format: Rokana Taftaf, Xia Liu, Salendra Singh, Yuzhi Jia, David Scholten, Youbin Zhang, Andrew Davis, Carolina Reduzzi, Yue Cao, Yang Shen, Massimo Cristofanilli, William A. Muller, Vinay Varadan, Huiping Liu. Single cell RNA sequencing-based identification of molecular drivers in circulating tumor cell cluster formation and lung metastasis [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2603.

A four-gene signature in the tumor microenvironment that significantly associates with the prognosis of patients with breast cancer.

Breast cancer (BRCA) is a highly heterogeneous disease due to the complicated microenvironment in the tumor, making the treatment benefits varied. Therefore, this study aims to identify a gene signature in the tumor microenvironment (TME) associated with the prognosis of BRCA patients. We downloaded the immune, stromal, and proliferation (ISP)-associated genes from the literature on BRCA. mRNA expression and clinical information obtained from The Cancer Genome Atlas (TCGA) were performed to identify the initial biomarker. Furthermore, we validated the robustness of the gene signature in the independent validation data set GSE20685. A four-gene signature in TME, including CD74, MMP9, RPA3, and SHCBP1, was constructed to predict the overall survival of BRCA. The survival time of the high-risk group was significantly worse than that of the low-risk group. Univariate and multivariate Cox regression analysis showed that our four-gene ISP signature was an independent prognostic factor in TCGA and GSE20685 data sets. The AUC suggested that our four-gene ISP signature was comparable to TNM classification at predicting the overall survival of BRCA patients. Interestingly, BRCA patients with high-risk scores were more likely to be associated with stromal and proliferation of cancer. In contrast, those with high-risk scores were more likely to be associated with tumor immunity-related pathway. We found an innovative biomarker in TME to predict the prognosis of BRCA. This signal might reflect the imbalance of TME and provide potential biomarkers for the individualized and precise treatment of BRCA.

Disruption of super-enhancer-driven tumor suppressor gene RCAN1.4 expression promotes the malignancy of breast carcinoma

BackgroundSuper-enhancers (SEs) play a crucial role in cancer, which is often associate with activated oncogenes. However, little is known about how SEs facilitate tumour suppression. Individuals with Down syndrome exhibit a remarkably reduced incidence of breast cancer (BC), moving the search for tumor suppressor genes on human chromosome 21 (HSA21). In this study, we aim to identify and explore potential mechanisms by which SEs are established for tumor suppressor RCAN1.4 on HSA21 in BC.MethodsIn silico analysis and immunohistochemical staining were used to assess the expression and clinical relevance of RCAN1.4 and RUNX3 in BC. Function experiments were performed to evaluate the effects of RCAN1.4 on the malignancy of breast carcinoma in vitro and in vivo. ChIP-seq data analysis, ChIP-qPCR, double-CRISPR genome editing, and luciferase reporter assay were utilized to confirm RUNX3 was involved in regulating RCAN1.4-associated SE in BC. The clinical value of co-expression of RCAN1.4 and RUNX3 was evaluated in BC patients.ResultsHere, we characterized RCAN1.4 as a potential tumour suppressor in BC. RCAN1.4 loss promoted tumour metastasis to bone and brain, and its overexpression inhibited tumour growth by blocking the calcineurin-NFATc1 pathway. Unexpectedly, we found RCAN1.4 expression was driven by a ~ 23 kb-long SE. RCAN1.4-SEdistal was sensitive to BRD4 inhibition, and its deletion decreased RCAN1.4 expression by over 90% and induced the malignant phenotype of BC cells. We also discovered that the binding sites in the SE region of RCAN1.4 were enriched for consensus sequences of transcription factor RUNX3. Knockdown of RUNX3 repressed the luciferase activity and also decreased H3K27ac enrichment binding at the SE region of RCAN1.4. Furthermore, abnormal SE-driven RCAN1.4 expression mediated by RUNX3 loss could be physiologically significant and clinically relevant in BC patients. Notably, we established a prognostic model based on RCAN1.4 and RUNX3 co-expression that effectively predicted the overall survival in BC patients.ConclusionsThese findings reveal an important role of SEs in facilitating tumour suppression in BC. Considering that the combination of low RCAN1.4 and low RUNX3 expression has worse prognosis, RUNX3-RCAN1.4 axis maybe a novel prognostic biomarker and therapeutic target for BC patients.

Integrating multi-omics data by learning modality invariant representations for improved prediction of overall survival of cancer.

Breast and ovarian cancers are the second and the fifth leading causes of cancer death among women. Predicting the overall survival of breast and ovarian cancer patients can facilitate the therapeutics evaluation and treatment decision making. Multi-scale multi-omics data such as gene expression, DNA methylation, miRNA expression, and copy number variations can provide insights on personalized survival. However, how to effectively integrate multi-omics data remains a challenging task. In this paper, we develop multi-omics integration methods to improve the prediction of overall survival for breast cancer and ovarian cancer patients. Because multi-omics data for the same patient jointly impact the survival of cancer patients, features from different -omics modality are related and can be modeled by either association or causal relationship (e.g., pathways). By extracting these relationships among modalities, we can get rid of the irrelevant information from high-throughput multi-omics data. However, it is infeasible to use the Brute Force method to capture all possible multi-omics interactions. Thus, we use deep neural networks with novel divergence-based consensus regularization to capture multi-omics interactions implicitly by extracting modality-invariant representations. In comparing the concatenation-based integration networks with our new divergence-based consensus networks, the breast cancer overall survival C-index is improved from 0.655±0.062 to 0.671±0.046 when combing DNA methylation and miRNA expression, and from 0.627±0.062 to 0.667±0.073 when combing miRNA expression and copy number variations. In summary, our novel deep consensus neural network has successfully improved the prediction of overall survival for breast cancer and ovarian cancer patients by implicitly learning the multi-omics interactions.

Comprehensive analysis of autophagy-related prognostic genes in breast cancer.

Accumulating evidence revealed that autophagy played vital roles in breast cancer (BC) progression. Thus, the aim of this study was to investigate the prognostic value of autophagy‐related genes (ARGs) and develop a ARG‐based model to evaluate 5‐year overall survival (OS) in BC patients. We acquired ARG expression profiling in a large BC cohort (N = 1007) from The Cancer Genome Atlas (TCGA) database. The correlation between ARGs and OS was confirmed by the LASSO and Cox regression analyses. A predictive model was established based on independent prognostic variables. Thus, time‐dependent receiver operating curve (ROC), calibration plot, decision curve and subgroup analysis were conducted to determine the predictive performance of ARG‐based model. Four ARGs (ATG4A, IFNG, NRG1 and SERPINA1) were identified using the LASSO and multivariate Cox regression analyses. A ARG‐based model was constructed based on the four ARGs and two clinicopathological risk factors (age and TNM stage), dividing patients into high‐risk and low‐risk groups. The 5‐year OS of patients in the low‐risk group was higher than that in the high‐risk group (P < 0.0001). Time‐dependent ROC at 5 years indicated that the four ARG–based tool had better prognostic accuracy than TNM stage in the training cohort (AUC: 0.731 vs 0.640, P < 0.01) and validation cohort (AUC: 0.804 vs 0.671, P < 0.01). The mutation frequencies of the four ARGs (ATG4A, IFNG, NRG1 and SERPINA1) were 0.9%, 2.8%, 8% and 1.3%, respectively. We built and verified a novel four ARG–based nomogram, a credible approach to predict 5‐year OS in BC, which can assist oncologists in determining effective therapeutic strategies.