scholarly journals APOBEC3B expression in breast cancer reflects cellular proliferation, while a deletion polymorphism is associated with immune activation

2015 ◽  
Vol 112 (9) ◽  
pp. 2841-2846 ◽  
Author(s):  
David W. Cescon ◽  
Benjamin Haibe-Kains ◽  
Tak W. Mak
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Immune Activation ◽  
Cellular Proliferation ◽  
Molecular Taxonomy ◽  
Adverse Outcomes ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Breast Cancers ◽  
Deletion Polymorphism

Genomic sequencing studies of breast and other cancers have identified patterns of mutations that have been attributed to the endogenous mutator activity of APOBEC3B (A3B), a member of the AID/APOBEC family of cytidine deaminases. A3B gene expression is increased in many cancers, but its upstream drivers remain undefined. Furthermore, there exists a common germ-line deletion polymorphism (A3Bdel), which has been associated with a paradoxical increase in breast cancer risk. To examine causes and consequences of A3B expression and its constitutive absence in breast cancer, we analyzed two large clinically annotated genomic datasets [The Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC)]. We confirmed that A3B expression is associated with aggressive clinicopathologic characteristics and adverse outcomes and show that A3B expression is highly correlated with proliferative features (mitosis and cell cycle-related gene expression) in breast and 15 of 16 other solid tumor types. However, breast cancers arising in homozygous A3Bdel individuals with A3B absent did not differ in these features, indicating that A3B expression is a reflection rather than a direct cause of increased proliferation. Using gene set enrichment analysis (GSEA), we detected a pattern of immune activation in A3Bdel breast cancers, which seems to be related to hypermutation arising in A3Bdel carriers. Together, these results provide an explanation for A3B overexpression and its prognostic effect, giving context to additional study of this mutator as a cancer biomarker or putative drug target. In addition, although immune features of A3Bdel require additional study, these findings nominate the A3Bdel polymorphism as a potential predictor for cancer immunotherapy.

scholarly journals MUC1-C integrates activation of the IFN-γ pathway with suppression of the tumor immune microenvironment in triple-negative breast cancer

2021 ◽  
Vol 9 (1) ◽  
pp. e002115
Author(s):  
Nami Yamashita ◽  
Mark Long ◽  
Atsushi Fushimi ◽  
Masaaki Yamamoto ◽  
Tsuyoshi Hata ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
T Cells ◽  
Cd8 T Cells ◽  
Triple Negative ◽  
Checkpoint Inhibitors ◽  
Molecular Taxonomy ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Ifn Γ

BackgroundImmune checkpoint inhibitors (ICIs) have had a profound impact on the treatment of many tumors; however, their effectiveness against triple-negative breast cancers (TNBCs) has been limited. One factor limiting responsiveness of TNBCs to ICIs is a lack of functional tumor-infiltrating lymphocytes (TILs) in ‘non-inflamed’ or ‘cold’ tumor immune microenvironments (TIMEs), although by unknown mechanisms. Targeting MUC1-C in a mouse transgenic TNBC tumor model increases cytotoxic tumor-infiltrating CD8+ T cells (CTLs), supporting a role for MUC1-C in immune evasion. The basis for these findings and whether they extend to human TNBCs are not known.MethodsHuman TNBC cells silenced for MUC1-C using short hairpin RNAs (shRNAs) were analyzed for the effects of MUC1-C on global transcriptional profiles. Differential expression and rank order analysis was used for gene set enrichment analysis (GSEA). Gene expression was confirmed by quantitative reverse-transcription PCR and immunoblotting. The The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) datasets were analyzed for effects of MUC1 on GSEA, cell-type enrichment, and tumor immune dysfunction and exclusion. Single-cell scRNA-seq datasets of TNBC samples were analyzed for normalized expression associations between MUC1 and selected genes within tumor cells.ResultsOur results demonstrate that MUC1-C is a master regulator of the TNBC transcriptome and that MUC1-C-induced gene expression is driven by STAT1 and IRF1. We found that MUC1-C activates the inflammatory interferon (IFN)-γ-driven JAK1→STAT1→IRF1 pathway and induces the IDO1 and COX2/PTGS2 effectors, which play key roles in immunosuppression. Involvement of MUC1-C in activating the immunosuppressive IFN-γ pathway was extended by analysis of human bulk and scRNA-seq datasets. We further demonstrate that MUC1 associates with the depletion and dysfunction of CD8+ T cells in the TNBC TIME.ConclusionsThese findings demonstrate that MUC1-C integrates activation of the immunosuppressive IFN-γ pathway with depletion of TILs in the TNBC TIME and provide support for MUC1-C as a potential target for improving TNBC treatment alone and in combination with ICIs. Of translational significance, MUC1-C is a druggable target with chimeric antigen receptor (CAR) T cells, antibody-drug conjugates (ADCs) and a functional inhibitor that are under clinical development.

Identification and Validation of a Novel 16-Gene Prognostic Signature for Patients with Breast Cancer

2021 ◽  
Author(s):  
Zhenhua Zhong ◽  
Wenqiang Jiang ◽  
Jing Zhang ◽  
Zhanwen Li ◽  
Fengfeng Fan
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cox Regression ◽  
Molecular Taxonomy ◽  
Rna Degradation ◽  
The Cancer Genome Atlas ◽  
Gene Score ◽  
Disease Heterogeneity ◽  
Cox Regression Analysis ◽  
Risk Of Death

Abstract Background: Despite increased early diagnosis and improved treatment in breast cancer (BRCA) patients, prognosis prediction is still a challenging task due to the disease heterogeneity. This study was to identify a novel gene signature that can accurately evaluate BRCA patient survival. Methods: The gene expression and clinical data of BRCA patients were collected from The Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of BRCA International Consortium (METABRIC) databases. Genes associated with prognosis were determined by Kaplan–Meier survival analysis and multivariate Cox regression analysis. A prognostic 16-gene score was established with linear combination of 16 genes. The prognostic value of the signature was validated in the METABRIC dataset. Gene expression analysis was performed to investigate the diagnostic values of 16 genes. Results: The 16-gene score was associated with shortened overall survival in BRCA patients independently of clinicopathological characteristics. The signalling pathways of cell cycle, oocyte meiosis, RNA degradation, progesterone mediated oocyte maturation and DNA replication were the top five most enriched pathways in the high 16-gene score group. The 16-gene nomogram incorporating the survival‐related clinical factors showed improved prediction accuracies for 1-year, 3-year and 5‐year survival (area under curve [AUC] = 0.91, 0.79 and 0.77 respectively). MORN3, IGJ, DERL1 exhibited high accuracy in differentiating BRCA tissues from normal breast tissues (AUC > 0.80 for all cases). Conclusions: The 16-gene profile provides novel insights into the identification of BRCA with a high risk of death, which eventually guides treatment decision making.

scholarly journals High expression of JAM2 indicates better prognosis and immunotherapy response in breast cancer

2020 ◽  
Author(s):  
Yang Peng ◽  
Chi Qu ◽  
Yingzi Zhang ◽  
Beige Zong ◽  
Yong Fu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Molecular Mechanisms ◽  
Potential Role ◽  
Molecular Taxonomy ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Cancer Tissue ◽  
Mesenchymal Transition ◽  
Chemotherapy Drugs

In our study, multiple databases were used to explore the potential role and underlying mechanism of junctional adhesion molecule B (JAM2) in breast cancer (BRCA). The data of JAM2 were downloaded from The Cancer Cell Line Encyclopedia (CCLE), the Genotype-Tissue Expression (GTEx), The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) databases. Receiver operating characteristic (ROC) curve analysis was performed to analyze the area under the curve (AUC) of JAM2 expression correlated with normal breast tissue and breast cancer tissue. Gene set enrichment analysis (GSEA) was used to identify the potential biological mechanisms of the JAM2. The expression of JAM2 mRNA was downregulated in most tumors, including BRCA, which may be due to the hypermethylated status. The AUCs, which were 0.929 and 0.887 by the logistic regression and random forest algorithms, indicated that JAM2 mRNA expression has good diagnostic value in BRCA. Univariate and multivariate analyses indicated JAM2 as an independent prognostic factor for the overall survival of BRCA patients in both the TCGA cohort (HR = 0.62, P = 0.034) and METABRIC cohort (HR = 0.77, P = 0.001). GSEA showed that multiple tumor pathways were suppressed in the JAM2 high expression group. The expression of JAM2 was most positively related to the epithelial-mesenchymal transition (EMT) score (r = 0.38; P <0.01) by the reverse-phase protein array (RPPA) analysis. Patients with high JAM2 expression may be more sensitive to immunotherapy. 18 chemotherapy drugs that patients in the JAM2 low expression group were more sensitive to being identified. Our results demonstrated the diagnostic and prognostic value of JAM2. Analysis of the molecular mechanisms indicates the potential role of JAM2 as a tumor suppressor, and high JAM2 expression may predict a better immunotherapy response in BRCA.

scholarly journals Germline APOBEC3B deletion in Asian women increases somatic hypermutation in breast cancer that is associated with Her2 subtype, PIK3CA mutations, immune activation, and increased survival

2020 ◽  
Author(s):  
Jia-Wern Pan ◽  
Muhammad Mamduh Ahmad Zabidi ◽  
Boon-Keat Chong ◽  
Mei-Yee Meng ◽  
Pei-Sze Ng ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Immune Activation ◽  
Somatic Hypermutation ◽  
Molecular Subtype ◽  
Significant Proportion ◽  
Asian Women ◽  
Breast Cancers ◽  
Coding Region ◽  
Deletion Polymorphism ◽  
Increased Risk

AbstractA 30-kb deletion that eliminates the coding region of APOBEC3B (A3B) is >5 times more common in women of Asian compared to European descent. This polymorphism creates a chimera with the APOBEC3A (A3A) coding region and A3B 3’UTR, and is associated with an increased risk for breast cancer in Asian women. Here, we explored the relationship between the A3B deletion polymorphism with tumour characteristics in Asian women. Using whole exome and whole transcriptome sequencing data of 527 breast tumours, we report that germline A3B deletion polymorphism leads to expression of the A3A-B hybrid isoform and increased APOBEC-associated somatic hypermutation. Hypermutated tumours, regardless of A3B germline status, were associated with the Her2 molecular subtype and PIK3CA mutations. Compared to non-hypermutated tumours, hypermutated tumours also had higher neoantigen burden, tumour heterogeneity and immune activation. Taken together, our results suggest that the germline A3B deletion polymorphism, via the A3A-B hybrid isoform, contributes to APOBEC-mutagenesis in a significant proportion of Asian breast cancers. In addition, APOBEC somatic hypermutation, regardless of A3B background, may be an important clinical biomarker for Asian breast cancers.Graphical Abstract

scholarly journals Both EZH2 and JMJD6 regulate cell cycle genes in breast cancer

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Antara Biswas ◽  
Geetashree Mukherjee ◽  
Paturu Kondaiah ◽  
Kartiki V. Desai
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cell Cycle ◽  
Single Molecule ◽  
Critical Role ◽  
Therapeutic Targets ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Clinical Samples ◽  
Pcr Analysis

Abstract Background Strong evidences support the critical role of Jumonji domain containing 6 (JMJD6) in progression of breast cancer. Here we explore potential partners that coregulate gene expression, to understand additional pathways that are activated by higher amounts of JMJD6. Methods We used Gene Set Enrichment Analysis (GSEA) data to identify factors that display gene expression similar to cells treated with JMJD6 siRNA. Using chromatin immunoprecipitations (ChIP) against genomic regions that bind JMJD6 identified by in house and public database Encyclopaedia of DNA Elements (ENCODE), we confirmed JMJD6 occupancy by ChIP PCR. We tested the association of co-regulated genes with patient prognosis using The Cancer Genome Atlas (TCGA) datasets. Results JMJD6 profiles overlapped with those of Enhancer of Zeste homolog 2 (EZH2) and together they appear to co-regulate a unique cassette of genes in both ER+ and ER- cells. 496 genes including aurora kinases, which are currently being tested as novel therapeutic targets in breast cancer were co-regulated in MDA MB 231 cells. JMJD6 and EZH2 neither inter-regulated nor physically interacted with one another. Since both proteins are chromatin modulators, we performed ChIP linked PCR analysis and show that JMJD6 bound in the neighbourhood of co-regulated genes, though EZH2 data did not show any peaks within 100 kb of these sites. Alignment of binding site sequences suggested that atleast two types of binding partners could offer their DNA binding properties to enrich JMJD6 at regulatory sites. In clinical samples, JMJD6 and EZH2 expression significantly correlated in both normal and tumor samples, however the strongest correlation was observed in triple-negative breast cancer (TNBC) subtype. Co-expression of JMJD6 and EZH2 imposed poorer prognosis in breast cancer. Conclusions JMJD6 and EZH2 regulate the same crucial cell cycle regulatory and therapeutic targets but their mechanisms appear to be independent of each other. Blocking of a single molecule may not axe cell proliferation completely and blocking both JMJD6 and EZH2 simultaneously may be more effective in breast cancer patients.

scholarly journals Developing ZNF Gene Signatures Predicting Radiosensitivity of Patients with Breast Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Derui Yan ◽  
Mingjing Shen ◽  
Zixuan Du ◽  
Jianping Cao ◽  
Ye Tian ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Patients ◽  
Cox Regression ◽  
Molecular Taxonomy ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Breast Cancer Patients ◽  
Expression Levels ◽  
The Relationship

Adjuvant radiotherapy is one of the main treatment methods for breast cancer, but its clinical benefit depends largely on the characteristics of the patient. This study aimed to explore the relationship between the expression of zinc finger (ZNF) gene family proteins and the radiosensitivity of breast cancer patients. Clinical and gene expression data on a total of 976 breast cancer samples were obtained from The Cancer Genome Atlas (TCGA) database. ZNF gene expression was dichotomized into groups with a higher or lower level than the median level of expression. Univariate and multivariate Cox regression analyses were used to evaluate the relationship between ZNF gene expression levels and radiosensitivity. The Molecular Taxonomy Data of the International Federation of Breast Cancer (METABRIC) database was used for validation. The results revealed that 4 ZNF genes were possible radiosensitivity markers. High expression of ZNF644 and low expression levels of the other 3 genes (ZNF341, ZNF541, and ZNF653) were related to the radiosensitivity of breast cancer. Hierarchical cluster, Cox, and CoxBoost analysis based on these 4 ZNF genes indicated that patients with a favorable 4-gene signature had better overall survival on radiotherapy. Thus, this 4-gene signature may have value for selecting those patients most likely to benefit from radiotherapy. ZNF gene clusters could act as radiosensitivity signatures for breast cancer patients and may be involved in determining the radiosensitivity of cancer.

Utilizing Cancer - Functional Gene Set - Compound Networks to Identify Putative Drugs for Breast Cancer

2018 ◽  
Vol 21 (2) ◽  
pp. 74-83
Author(s):  
Tzu-Hung Hsiao ◽  
Yu-Chiao Chiu ◽  
Yu-Heng Chen ◽  
Yu-Ching Hsu ◽  
Hung-I Harry Chen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Therapy ◽  
Cancer Treatment ◽  
Cancer Survival ◽  
Expression Profiles ◽  
Functional Gene ◽  
Gene Set Enrichment Analysis ◽  
Gene Set ◽  
Gene Sets

Aim and Objective: The number of anticancer drugs available currently is limited, and some of them have low treatment response rates. Moreover, developing a new drug for cancer therapy is labor intensive and sometimes cost prohibitive. Therefore, “repositioning” of known cancer treatment compounds can speed up the development time and potentially increase the response rate of cancer therapy. This study proposes a systems biology method for identifying new compound candidates for cancer treatment in two separate procedures. Materials and Methods: First, a “gene set–compound” network was constructed by conducting gene set enrichment analysis on the expression profile of responses to a compound. Second, survival analyses were applied to gene expression profiles derived from four breast cancer patient cohorts to identify gene sets that are associated with cancer survival. A “cancer–functional gene set– compound” network was constructed, and candidate anticancer compounds were identified. Through the use of breast cancer as an example, 162 breast cancer survival-associated gene sets and 172 putative compounds were obtained. Results: We demonstrated how to utilize the clinical relevance of previous studies through gene sets and then connect it to candidate compounds by using gene expression data from the Connectivity Map. Specifically, we chose a gene set derived from a stem cell study to demonstrate its association with breast cancer prognosis and discussed six new compounds that can increase the expression of the gene set after the treatment. Conclusion: Our method can effectively identify compounds with a potential to be “repositioned” for cancer treatment according to their active mechanisms and their association with patients’ survival time.

scholarly journals The BIRC Family Genes Expression in Patients with Triple Negative Breast Cancer

2021 ◽  
Vol 22 (4) ◽  
pp. 1820
Author(s):  
Anna Makuch-Kocka ◽  
Janusz Kocki ◽  
Anna Brzozowska ◽  
Jacek Bogucki ◽  
Przemysław Kołodziej ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Clinical Data ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Lymphatic Vessels ◽  
The Cancer Genome Atlas ◽  
Expression Level ◽  
Cancer Tissue ◽  
Expression Levels

The BIRC (baculoviral IAP repeat-containing; BIRC) family genes encode for Inhibitor of Apoptosis (IAP) proteins. The dysregulation of the expression levels of the genes in question in cancer tissue as compared to normal tissue suggests that the apoptosis process in cancer cells was disturbed, which may be associated with the development and chemoresistance of triple negative breast cancer (TNBC). In our study, we determined the expression level of eight genes from the BIRC family using the Real-Time PCR method in patients with TNBC and compared the obtained results with clinical data. Additionally, using bioinformatics tools (Ualcan and The Breast Cancer Gene-Expression Miner v4.5 (bc-GenExMiner v4.5)), we compared our data with the data in the Cancer Genome Atlas (TCGA) database. We observed diverse expression pattern among the studied genes in breast cancer tissue. Comparing the expression level of the studied genes with the clinical data, we found that in patients diagnosed with breast cancer under the age of 50, the expression levels of all studied genes were higher compared to patients diagnosed after the age of 50. We observed that in patients with invasion of neoplastic cells into lymphatic vessels and fat tissue, the expression levels of BIRC family genes were lower compared to patients in whom these features were not noted. Statistically significant differences in gene expression were also noted in patients classified into three groups depending on the basis of the Scarff-Bloom and Richardson (SBR) Grading System.

scholarly journals Relationship Between Plasma Estradiol Levels and Estrogen-Responsive Gene Expression in Estrogen Receptor–Positive Breast Cancer in Postmenopausal Women

2010 ◽  
Vol 28 (7) ◽  
pp. 1161-1167 ◽  
Author(s):  
Anita K. Dunbier ◽  
Helen Anderson ◽  
Zara Ghazoui ◽  
Elizabeth J. Folkerd ◽  
Roger A'Hern ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Estrogen Receptor ◽  
Postmenopausal Women ◽  
Multivariable Analysis ◽  
Independent Set ◽  
Breast Cancers ◽  
Plasma Estradiol ◽  
Er Positive ◽  
Positive Breast Cancer

Purpose To determine whether plasma estradiol (E2) levels are related to gene expression in estrogen receptor (ER)–positive breast cancers in postmenopausal women. Materials and Methods Genome-wide RNA profiles were obtained from pretreatment core-cut tumor biopsies from 104 postmenopausal patients with primary ER-positive breast cancer treated with neoadjuvant anastrozole. Pretreatment plasma E2 levels were determined by highly sensitive radioimmunoassay. Genes were identified for which expression was correlated with pretreatment plasma E2 levels. Validation was performed in an independent set of 73 ER-positive breast cancers. Results The expression of many known estrogen-responsive genes and gene sets was highly significantly associated with plasma E2 levels (eg, TFF1/pS2, GREB1, PDZK1 and PGR; P < .005). Plasma E2 explained 27% of the average expression of these four average estrogen-responsive genes (ie, AvERG; r = 0.51; P < .0001), and a standardized mean of plasma E2 levels and ER transcript levels explained 37% (r, 0.61). These observations were validated in an independent set of 73 ER-positive tumors. Exploratory analysis suggested that addition of the nuclear coregulators in a multivariable analysis with ER and E2 levels might additionally improve the relationship with the AvERG. Plasma E2 and the standardized mean of E2 and ER were both significantly correlated with 2-week Ki67, a surrogate marker of clinical outcome (r = −0.179; P = .05; and r = −0.389; P = .0005, respectively). Conclusion Plasma E2 levels are significantly associated with gene expression of ER-positive breast cancers and should be considered in future genomic studies of ER-positive breast cancer. The AvERG is a new experimental tool for the study of putative estrogenic stimuli of breast cancer.

scholarly journals Development of a Novel Prognostic Signature Based on Antigen Processing and Presentation in Patients with Breast Cancer

2021 ◽  
Vol 27 ◽  
Author(s):  
Aoshuang Qi ◽  
Mingyi Ju ◽  
Yinfeng Liu ◽  
Jia Bi ◽  
Qian Wei ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Antigen Processing ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Prognostic Indicators ◽  
Gene Set ◽  
Antigen Processing And Presentation

Background: Complex antigen processing and presentation processes are involved in the development and progression of breast cancer (BC). A single biomarker is unlikely to adequately reflect the complex interplay between immune cells and cancer; however, there have been few attempts to find a robust antigen processing and presentation-related signature to predict the survival outcome of BC patients with respect to tumor immunology. Therefore, we aimed to develop an accurate gene signature based on immune-related genes for prognosis prediction of BC.Methods: Information on BC patients was obtained from The Cancer Genome Atlas. Gene set enrichment analysis was used to confirm the gene set related to antigen processing and presentation that contributed to BC. Cox proportional regression, multivariate Cox regression, and stratified analysis were used to identify the prognostic power of the gene signature. Differentially expressed mRNAs between high- and low-risk groups were determined by KEGG analysis.Results: A three-gene signature comprising HSPA5 (heat shock protein family A member 5), PSME2 (proteasome activator subunit 2), and HLA-F (major histocompatibility complex, class I, F) was significantly associated with OS. HSPA5 and PSME2 were protective (hazard ratio (HR) &lt; 1), and HLA-F was risky (HR &gt; 1). Risk score, estrogen receptor (ER), progesterone receptor (PR) and PD-L1 were independent prognostic indicators. KIT and ACACB may have important roles in the mechanism by which the gene signature regulates prognosis of BC.Conclusion: The proposed three-gene signature is a promising biomarker for estimating survival outcomes in BC patients.

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