scholarly journals Expressing Status and Correlation of ARID1A and Histone H2B on Breast Cancer

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Yan Wu ◽  
Yan Gu ◽  
Shanyu Guo ◽  
Qiancheng Dai ◽  
Wei Zhang
Keyword(s):  
Breast Cancer ◽  
Ductal Carcinoma ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Mucinous Carcinoma ◽  
Cancer Gene ◽  
Breast Cancers ◽  
Histone H2b ◽  
Oncomine Database ◽  
Breast Cancer Gene

ARID1A is one of the important cancer-related genes and regulates transcription of certain genes by altering chromatin structure. Inactivated mutations and decreased expression of ARID1A gene have been reported in several kinds of cancer. Histone H2B is a major component of chromatin and encoded by HIST1H2BE. The goal of the study is to evaluate expressing status of ARID1A and H2B as well as their correlation on breast cancer. Gene expression profiles of ARID1A and H2B on Oncomine database are analyzed. Tissue microarray of breast cancer was used for examination of ARID1A and H2B expression by immunohistochemistry. As a result, the disagreement of ARID1A expression was found, while HIST1H2BE expression is elevated in 4 out of 5 datasets on Oncomine database. There were 15 cases (20%) of breast cancers that were positive for ARID1A. Fifty-eight out of 75 cases of breast cancer (77.3%) were highly expressed for H2B protein and 17 cases (22.7%) were low expressed for H2B protein. All cases with ARID1A expression are overlapped with H2B high expression. Among 15 cases with ARID1A and H2B coexpression, 13 are invasive ductal carcinoma and 2 are mucinous carcinoma. Our results indicate that ARID1A gene may be involved in carcinogenesis of some subtypes of breast cancer.

Epigenetic Reprogramming and Landscape of Transcriptomic Interactions: Impending Therapeutic Interference of Triple-Negative Breast Cancer in Molecular Medicine

2021 ◽  
Vol 21 ◽  
Author(s):  
Suman Kumar Ray ◽  
Sukhes Mukherjee
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Treatment Decision ◽  
Copy Number Variations ◽  
Molecular Medicine ◽  
Breast Cancers ◽  
Breast Carcinogenesis

: The mechanisms governing the development and progression of cancers are believed to be the consequence of hereditary deformities and epigenetic modifications. Accordingly, epigenetics has become an incredible and progressively explored field of research to discover better prevention and therapy for neoplasia, especially triple-negative breast cancer (TNBC). It represents 15–20% of all invasive breast cancers and will, in general, have bellicose histological highlights and poor clinical outcomes. In the early phases of triple-negative breast carcinogenesis, epigenetic deregulation modifies chromatin structure and influences the plasticity of cells. It up-keeps the oncogenic reprogramming of malignant progenitor cells with the acquisition of unrestrained selfrenewal capacities. Genomic impulsiveness in TNBC prompts mutations, copy number variations, as well as genetic rearrangements, while epigenetic remodeling includes an amendment by DNA methylation, histone modification, and noncoding RNAs of gene expression profiles. It is currently evident that epigenetic mechanisms assume a significant part in the pathogenesis, maintenance, and therapeutic resistance of TNBC. Although TNBC is a heterogeneous malaise that is perplexing to describe and treat, the ongoing explosion of genetic and epigenetic research will help to expand these endeavors. Latest developments in transcriptome analysis have reformed our understanding of human diseases, including TNBC at the molecular medicine level. It is appealing to envision transcriptomic biomarkers to comprehend tumor behavior more readily regarding its cellular microenvironment. Understanding these essential biomarkers and molecular changes will propel our capability to treat TNBC adequately. This review will depict the different aspects of epigenetics and the landscape of transcriptomics in triple-negative breast carcinogenesis and their impending application for diagnosis, prognosis, and treatment decision with the view of molecular medicine.

scholarly journals A novel immune subtype classification of ER-positive, PR-negative and HER2-negative breast cancer based on the genomic and transcriptomic landscape

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Peiling Xie ◽  
Rui An ◽  
Shibo Yu ◽  
Jianjun He ◽  
Huimin Zhang
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Clinical Outcomes ◽  
Immune Escape ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Molecular Characteristics ◽  
Consensus Clustering ◽  
Breast Cancers ◽  
Her2 Breast Cancer

Abstract Background The diversity and plasticity behind ER+/PR−/HER2− breast cancer have not been widely explored. It is essential to identify heterogeneous microenvironment phenotypes and investigate specific genomic events driving the formation of these phenotypes. Methods Based on the immune-related gene expression profiles of 411 ER+/PR−/HER2− breast cancers in the METABRIC cohort, we used consensus clustering to identify heterogeneous immune subtypes and assessed their reproducibility in an independent meta-cohort including 135 patients collected from GEO database. We further analyzed the differences of cellular and molecular characteristics, and potential immune escape mechanism among immune subtypes. In addition, we constructed a transcriptional trajectory to visualize the distribution of individual patient. Results Our analysis identified and validated five reproducible immune subtypes with distinct cellular and molecular characteristics, potential immune escape mechanisms, genomic drivers, as well as clinical outcomes. An immune-cold subtype, with the least amount of lymphocyte infiltration, had a poorer prognosis. By contrast, an immune-hot subtype, which demonstrated the highest infiltration of CD8+ T cells, DCs and NK cells, and elevated IFN-γ response, had a comparatively favorable prognosis. Other subtypes showed more diverse gene expression and immune infiltration patterns with distinct clinical outcomes. Finally, our analysis revealed a complex immune landscape consisting of both discrete cluster and continuous spectrum. Conclusion Overall, this study revealed five heterogeneous immune subtypes among ER+/PR–/HER2− breast cancer, also provided important implications for clinical translations.

scholarly journals Classification models for Invasive Ductal Carcinoma Progression, based on gene expression data-trained supervised machine learning

2019 ◽  
Author(s):  
Shikha Roy ◽  
Rakesh Kumar ◽  
Vaibhav Mittal ◽  
Dinesh Gupta
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Machine Learning ◽  
Invasive Ductal Carcinoma ◽  
Ductal Carcinoma ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Classification Models ◽  
Rna Seq ◽  
Late Stages

AbstractEarly detection of breast cancer and its correct stage determination are important for prognosis and rendering appropriate personalized clinical treatment to breast cancer patients. However, despite considerable efforts and progress, there is a need to identify the specific genomic factors responsible for, or accompanying Invasive Ductal Carcinoma (IDC) progression stages, which can aid the determination of the correct cancer stages. We have developed two-class machine-learning classification models to differentiate the early and late stages of invasive ductal carcinoma. The prediction models are trained with RNA-seq gene expression profiles representing different IDC stages of 610 patients, obtained from The Cancer Genome Atlas (TCGA). Different supervised learning algorithms were trained and evaluated with an enriched model learning, facilitated by different feature selection methods. We also developed a machine-learning classifier trained on the same datasets with training sets reduced data corresponding to IDC driver genes. Based on these two classifiers, we have developed a web-server Duct-BRCA-CSP to predict early stage from late stages of IDC based on input RNA-seq gene expression profiles. The analysis conducted by us also enables deeper insights into the stage-dependent molecular events accompanying breast ductal carcinoma progression. The server is publicly available at http://bioinfo.icgeb.res.in/duct-BRCA-CSP.

Gene expression profiling can predict pathological complete response (pCR) to anthracycline-based therapy in estrogen- receptor (ER) negative breast cancer (BC) patients

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 10564-10564
Author(s):  
C. Desmedt ◽  
F. André ◽  
E. Azambuja ◽  
B. Haibe-Kains ◽  
D. Larsimont ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Expression Profiles ◽  
Single Agent ◽  
Gene Expression Profiles ◽  
Molecular Transport ◽  
Complete Response ◽  
Dominant Factor ◽  
Breast Cancers ◽  
Two Samples

10564 Background: Breast cancers show variable sensitivity to anthracycline (A)-based therapy. Here we aimed to identify gene expression profiles associated with pCR to this treatment. As it has repeatedly and consistently been shown that ER is the most dominant factor influencing the molecular composition of breast cancer, defining different types of BC disease and because we wanted to eliminate the confounding effect of indirect ovarian suppression in ER+ BC, we focused in this study on ER-negative patients only. Methods: We analyzed Affymetrix gene expression profiles generated from 132 ER- pre-treatment samples, constituting the largest series of ER- preoperatively A-treated BC (n=132/35 pCR). Sixty-two samples derived from the prospective multicentric TOP trial (epirubicin single-agent), 41 from Institut G. Roussy (retrospective selection/ FEC) and 27 from MD Anderson (prospective study/ FAC). Results: A student t- test analysis on the combined population of A-treated pts was performed identifying 102 genes that were significantly associated with pCR (p<.01). These genes were mainly involved in cell death, DNA replication and recombination, molecular transport, cell cycle and morphology. Interestingly, 14 of these genes were located on the topoIIa amplicon. Of interest, none of these 14 genes seem to carry any prognostic value in untreated ER- pts (N=161). When we considered gene expression indices for specific A-targets such as topoIIa and helicase, we found that both were associated with pCR. However, subgroup analysis revealed that topoIIa index was predictive in ERBB2+ but not in ERBB2- subgroup. None of the genes from the adriamycin predictor (Potti et al.) or the p53 signature (Miller et al.) were significantly associated with pCR. Conclusions: This study suggests that a group of genes associated with topoIIa can identify ER-negative BC pts likely to respond to A-based therapy. These promising results are currently being validated in a larger series. No significant financial relationships to disclose.

scholarly journals EP.TH.3Male Breast Cancer: A Series of Three Extremely Rare Cases

2021 ◽  
Vol 108 (Supplement_7) ◽  
Author(s):  
Ahmed Latif ◽  
Amna Suliman ◽  
Anupama Nagarajakumar ◽  
Mihir Khan ◽  
Anna Metafa ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Papillary Carcinoma ◽  
Ductal Carcinoma ◽  
Case Series ◽  
Mucinous Carcinoma ◽  
Wall Thickening ◽  
Low Grade ◽  
Breast Cancers ◽  
History Of ◽  
One Year

Abstract Aims Male breast cancer (MBC) is rare and accounts for 1% of all breast cancers. We present a case series of three very rare histological subtype MBC within one year in a UK hospital. Methods We retrospectively identified all MBCs from the local breast cancer database. Their presentations, radiology and histopathology were analysed. Results Three MBCs were identified from 2019 to 2020. A healthy 28-year-old presented with a right breast lump. Ultrasound (USS) revealed a partially cystic 15mm U3 lesion. Mammography (MMG) was suggestive of gynaecomastia (M2). Biopsy was inconclusive. Diagnostic excision revealed Papillary Ductal Carcinoma in Situ (DCIS) with involved margin. Mastectomy and Sentinel Node Biopsy (SNB) confirmed low-grade Papillary DCIS. A 48-year-old with background of hyperlipidaemia presented with a 2-year history of left axillary lump. PET CT demonstrated an FDG-avid lesion. USS showed a superficial U3 28mm lesion. MMG showed a 34mm density (M4). Biopsy identified Mucinous Carcinoma. Wide Local Excision and SNB confirmed grade 2 Mucinous Carcinoma. A 75-year-old with history of cardiac disease, COPD and Type 2 Diabetes, presented with a right retro-areolar lump. MMG identified a 47mm mass (M4). USS showed a 41mm cystic lesion with wall thickening (U4). Cytology was inconclusive. Biopsy identified intra-cystic papillary carcinoma. Mastectomy and SNB confirmed intra-cystic papillary carcinoma. All three histological subtypes are extremely rare and account for less than 4% of all MBCs. Conclusions MBC is rare but increasing in incidence. More research and awareness are needed to minimise delays in diagnosis and treatment even in young men.

scholarly journals Distinct gene expression profiles between primary breast cancers and brain metastases from pair-matched samples

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Takayuki Iwamoto ◽  
Naoki Niikura ◽  
Rin Ogiya ◽  
Hiroyuki Yasojima ◽  
Ken-ichi Watanabe ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Brain Metastases ◽  
Therapeutic Target ◽  
Target Genes ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Breast Cancers ◽  
Mesenchymal Transition ◽  
Matched Samples

Abstract Our objectives were to determine whether clinic-pathological markers and immune-related gene signatures in breast cancer exhibit any change upon brain metastasis and whether previously reported genes significantly associated with brain metastases and the epithelial-mesenchymal transition (EMT) were reproducible and consistent in our dataset. Sixteen pair-matched samples from primary breast cancers and brain metastases diagnosed were collected from the Japan Clinical Oncology Group Breast Cancer Study Group. Gene expression profiles for immune-, brain metastases-, and EMT-related genes were compared between primary breast cancers and brain metastases. Potential therapeutic target genes of 41 FDA-approved or under-investigation agents for brain metastases were explored. Immune-related signatures exhibited significantly lower gene expression in brain metastases than in primary breast cancers. No significant differences were detected for the majority of genes associated with brain metastases and EMT in the two groups. Among 41 therapeutic target candidates, VEGFA and DNMT3A demonstrated significantly higher gene expression in brain metastases. We found that distinct patterns of gene expression exist between primary breast cancers and brain metastases. Further studies are needed to explore whether these distinct expression profiles derive from or underlie disease status and compare these features between metastases to the brain and other sites.

Gene Expression Profiles Differentiating Between Breast Cancers Clinically Responsive or Resistant to Letrozole

2009 ◽  
Vol 27 (9) ◽  
pp. 1382-1387 ◽  
Author(s):  
William R. Miller ◽  
Alexey Larionov ◽  
Lorna Renshaw ◽  
Thomas J. Anderson ◽  
John R. Walker ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Neoadjuvant Treatment ◽  
Gene Expression Profiles ◽  
Bioinformatic Analysis ◽  
Breast Cancers ◽  
Before And After ◽  
Volume Measurements ◽  
Molecular Phenotypes

Purpose Endocrine agents, such as letrozole, are established in the treatment of hormone-dependent breast cancer. However, response rates are only 50% to 70% in the neoadjuvant setting and lower in advanced disease. Thus there is a need to identify novel markers predicting for response and to understand molecular mechanisms of resistance. Patients and Methods Sequential tumor biopsies were taken before and after 10 to 14 days of neoadjuvant treatment with letrozole in patients with estrogen receptor–rich breast cancer. Expression profiles on high-density microarray chips were then related to clinical responses as assessed from tumor volume measurements after 3 months of treatment. Results Of 52 patients, 37 (71%) were classified as having a clinical response to letrozole and 15 being clinically resistant. Bioinformatic analysis identified 205 covariables (69 baseline expression, 45 day 14 expression, and 91 change in expression with treatment) which differentiated between clinical responders and nonresponders. Hierarchical clustering using the variables separated responders and nonresponders into two distinct groups. Ontological assessment indicated that discriminating genes were enriched toward cellular biosynthetic processes. In particular, functional gene assessment showed ribosomal protein probes to have higher baseline expression in tumors responsive to letrozole and increased expression with treatment in nonresponding cases. Conclusion To our knowledge, this is the first study to describe genetic covariables and molecular processes discriminating between tumors clinically responsive and resistant to an aromatase inhibitor. The understanding of such molecular phenotypes will be important in optimizing the clinical use of aromatase inhibitors, both in terms of identifying responsive breast cancers and developing new agents to target resistance pathways.

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