Abstract PO-150: Comparison of RUNX1, RUNX2, RUNX3 and CBFβ gene expression in breast tumors Indicate ethnic differences and similarities by receptor status

2022 ◽  
Author(s):  
Uzoamaka A. Okoli
Keyword(s):  
Gene Expression ◽  
Ethnic Differences ◽  
Breast Tumors ◽  
Receptor Status

scholarly journals The prognostic potential of alternative transcript isoforms across human tumors

2016 ◽  
Author(s):  
Juan L. Trincado ◽  
E. Sebestyén ◽  
A. Pagés ◽  
E. Eyras
Keyword(s):  
Gene Expression ◽  
Estrogen Receptor ◽  
Lymph Node ◽  
Cancer Progression ◽  
Estrogen Receptor Status ◽  
Breast Tumors ◽  
The Cancer Genome Atlas ◽  
Alternative Transcript ◽  
Transcript Isoforms ◽  
Receptor Status

AbstractBackgroundPhenotypic changes during cancer progression are associated to alterations in gene expression, which can be exploited to build molecular signatures for tumor stage identification and prognosis. However, it is not yet known whether the relative abundance of transcript isoforms may be informative for clinical stage and survival.MethodsUsing information theory and machine learning methods, we integrated RNA sequencing and clinical data from The Cancer Genome Atlas project to perform the first systematic analysis of the prognostic potential of transcript isoforms in 12 solid tumors to build new predictive signatures for stage and prognosis. This study was also performed in breast tumors according to estrogen receptor status and melanoma tumors with proliferative and invasive phenotypes.ResultsTranscript isoform signatures accurately separate early from late stage and metastatic from non-metastatic tumors, and are predictive of the survival of patients with undetermined lymph node invasion or metastatic status. These signatures show similar, and sometimes better, accuracies compared with known gene expression signatures, and are largely independent of gene expression changes. Furthermore, we show frequent transcript isoform changes in breast tumors according to estrogen receptor status, and in melanoma tumors according to the invasive or proliferative phenotype, and derive accurate predictive models of stage and survival within each patient subgroup.ConclusionsOur analyses reveal new signatures based on transcript isoform abundances that characterize tumor phenotypes and their progression independently of gene expression. Transcript isoform signatures appear especially relevant to determine lymph node invasion and metastasis, and may potentially contribute towards current strategies of precision cancer medicine.

scholarly journals Decision theory for precision therapy of breast cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Michael Kenn ◽  
Dan Cacsire Castillo-Tong ◽  
Christian F. Singer ◽  
Rudolf Karch ◽  
Michael Cibena ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Decision Theory ◽  
Data Science ◽  
Gene Expression Omnibus ◽  
Hormone Receptor Status ◽  
Breast Cancer Patients ◽  
Receptor Status ◽  
Kaplan Meier ◽  
Precision Therapy

AbstractCorrectly estimating the hormone receptor status for estrogen (ER) and progesterone (PGR) is crucial for precision therapy of breast cancer. It is known that conventional diagnostics (immunohistochemistry, IHC) yields a significant rate of wrongly diagnosed receptor status. Here we demonstrate how Dempster Shafer decision Theory (DST) enhances diagnostic precision by adding information from gene expression. We downloaded data of 3753 breast cancer patients from Gene Expression Omnibus. Information from IHC and gene expression was fused according to DST, and the clinical criterion for receptor positivity was re-modelled along DST. Receptor status predicted according to DST was compared with conventional assessment via IHC and gene-expression, and deviations were flagged as questionable. The survival of questionable cases turned out significantly worse (Kaplan Meier p < 1%) than for patients with receptor status confirmed by DST, indicating a substantial enhancement of diagnostic precision via DST. This study is not only relevant for precision medicine but also paves the way for introducing decision theory into OMICS data science.

Abstract SS1-07: Gene expression profiles of Ghanaian and Ethiopian triple-negative breast tumors

2021 ◽  
Author(s):  
Rachel Martini ◽  
Endale Gebregzabher ◽  
Princesca Dorsaint ◽  
Timothy Chu ◽  
Kanika Arora ◽  
...  
Keyword(s):  
Gene Expression ◽  
Triple Negative ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Breast Tumors

scholarly journals Gene expression profiling of triple-negative breast tumors with different expression of secreted protein acidic and cysteine rich (SPARC)

2018 ◽  
Vol 7 (2) ◽  
pp. BMT09
Author(s):  
Paulo R de Alcantara Filho ◽  
Flavia R Mangone ◽  
Ana C Pavanelli ◽  
Simone A de Bessa Garcia ◽  
Suely Nonogaki ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Triple Negative ◽  
Breast Tumors ◽  
Secreted Protein

scholarly journals MOSTWAS: Multi-Omic Strategies for Transcriptome-Wide Association Studies

2020 ◽  
Author(s):  
Arjun Bhattacharya ◽  
Yun Li ◽  
Michael I. Love
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Brain Tissue ◽  
Predictive Models ◽  
Association Studies ◽  
Genetic Regulation ◽  
Breast Tumors ◽  
Risk Genes ◽  
Complex Interactions ◽  
Trait Associations

ABSTRACTTraditional predictive models for transcriptome-wide association studies (TWAS) consider only single nucleotide polymorphisms (SNPs) local to genes of interest and perform parameter shrinkage with a regularization process. These approaches ignore the effect of distal-SNPs or other molecular effects underlying the SNP-gene association. Here, we outline multi-omics strategies for transcriptome imputation from germline genetics to allow more powerful testing of gene-trait associations by prioritizing distal-SNPs to the gene of interest. In one extension, we identify mediating biomarkers (CpG sites, microRNAs, and transcription factors) highly associated with gene expression and train predictive models for these mediators using their local SNPs. Imputed values for mediators are then incorporated into the final predictive model of gene expression, along with local SNPs. In the second extension, we assess distal-eQTLs (SNPs associated with genes not in a local window around it) for their mediation effect through mediating biomarkers local to these distal-eSNPs. Distal-eSNPs with large indirect mediation effects are then included in the transcriptomic prediction model with the local SNPs around the gene of interest. Using simulations and real data from ROS/MAP brain tissue and TCGA breast tumors, we show considerable gains of percent variance explained (1-2% additive increase) of gene expression and TWAS power to detect gene-trait associations. This integrative approach to transcriptome-wide imputation and association studies aids in identifying the complex interactions underlying genetic regulation within a tissue and important risk genes for various traits and disorders.AUTHOR SUMMARYTranscriptome-wide association studies (TWAS) are a powerful strategy to study gene-trait associations by integrating genome-wide association studies (GWAS) with gene expression datasets. TWAS increases study power and interpretability by mapping genetic variants to genes. However, traditional TWAS consider only variants that are close to a gene and thus ignores important variants far away from the gene that may be involved in complex regulatory mechanisms. Here, we present MOSTWAS (Multi-Omic Strategies for TWAS), a suite of tools that extends the TWAS framework to include these distal variants. MOSTWAS leverages multi-omic data of regulatory biomarkers (transcription factors, microRNAs, epigenetics) and borrows from techniques in mediation analysis to prioritize distal variants that are around these regulatory biomarkers. Using simulations and real public data from brain tissue and breast tumors, we show that MOSTWAS improves upon traditional TWAS in both predictive performance and power to detect gene-trait associations. MOSTWAS also aids in identifying possible mechanisms for gene regulation using a novel added-last test that assesses the added information gained from the distal variants beyond the local association. In conclusion, our method aids in detecting important risk genes for traits and disorders and the possible complex interactions underlying genetic regulation within a tissue.

Investigating survivin as a novel target in black women with breast cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 594-594
Author(s):  
Andrea Walens ◽  
Linnea T Olsson ◽  
Sarah Van Alsten ◽  
Lisa A. Carey ◽  
Melissa A. Troester ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Black Women ◽  
White Women ◽  
Tumor Biology ◽  
Survivin Expression ◽  
Breast Tumors ◽  
The Cancer Genome Atlas ◽  
Molecular Features ◽  
Apoptosis Protein

594 Background: Black women with breast cancer have higher mortality than White women. Differences in tumor biology contribute to racial disparities in breast cancer outcomes. BIRC5 gene encodes survivin, an inhibitor of apoptosis protein, and an independent marker of poor prognosis in breast cancer. Cancer patients have anti-survivin antibodies and circulating survivin-specific T cells, suggesting that survivin may be targetable. Several ongoing antibody-mediated, vaccine strategies that target survivin are being developed. Nevertheless, most survivin studies were conducted in cohorts of White women. To date, the prevalence and/or role of survivin expression in breast tumors from Black women has not been studied. Methods: Associations between BIRC5 expression, clinicopathological and molecular features were measured in the population-based Carolina Breast Cancer Study (CBCS) and The Cancer Genome Atlas (TCGA) breast cancer cohort. Gene expression was measured by Nanostring RNA counting and split into BIRC5 high (4th quartile) and low categories based on log2 gene expression values. Relative frequency differences (RFD) for the association between BIRC5 high and clinicopathologic features were estimated. RNA based p53 mutant status and homologous recombination deficiency (HRD) status were included in RFD analysis. Receiver operating characteristic (ROC) curves were used to illustrate the potential of BIRC5 expression to distinguish patients who achieved pathological complete response (pCR) after receiving neoadjuvant chemotherapy in CBCS (133 Black, 49 non-Black). Results: BIRC5 gene expression was significantly increased in tumors from 966 Black patients compared to 1,497 non-Black (p < 0.00001), adjusting for stage and subtype. BIRC5 high tumors were significantly more expressed in higher stage and basal-like breast cancer subtypes. BIRC5 high tumors were also significantly enriched for expression of genes involved in p53 loss and HRD. Furthermore, in an analysis of 182 CBCS patients, BIRC5 gene expression alone predicted pCR with similar overall AUC to ROR-PT multigene signatures (AUC 0.62 vs 0.64). Conclusions: Our study shows that survivin expression is particularly high in breast tumors from Black women. This was associated with more aggressive clinicopathological features in addition to p53 mutant and HRD status. Black women with breast cancer represent an area of unmet clinical need and could potentially benefit from anti-survivin targetable treatment strategies. Further studies are needed to help close this gap which constitutes the largest disparity among cancer-specific diseases.[Table: see text]

scholarly journals Stochastic changes in gene expression promote chaotic dysregulation of homeostasis in clonal breast tumors

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Sara J. Felts ◽  
Xiaojia Tang ◽  
Benjamin Willett ◽  
Virginia P. Van Keulen ◽  
Michael J. Hansen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Breast Tumors

Gene expression profiles of primary breast tumors maintained in lymph node- and distant metastases

2004 ◽  
Vol 2 (3) ◽  
pp. 125
Author(s):  
B Weigelt ◽  
A.M Glas ◽  
L.F Wessels ◽  
A.T Witteveen ◽  
A.J Bosma ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lymph Node ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Distant Metastases ◽  
Breast Tumors

Characteristic Genes in Luminal Subtype Breast Tumors with CD44+CD24–/Low Gene Expression Signature

Oncology ◽  
2011 ◽  
Vol 81 (5-6) ◽  
pp. 336-344 ◽  
Author(s):  
Y. Tsunoda ◽  
M. Sakamoto ◽  
T. Sawada ◽  
A. Sasaki ◽  
G. Yamamoto ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Signature ◽  
Breast Tumors ◽  
Luminal Subtype ◽  
Expression Signature
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