High-throughput allelic expression imbalance analyses identify candidate breast cancer risk genes

Marjaneh, Mahdi Moradi; Sivakumaran, Haran; Hillman, Kristine M.; Kaufmann, Susanne; Hussein, Nehal; Lima, Luize Gonçalves; Ham, Sunyoung; Kar, Siddhartha; Beesley, Jonathan; Fachal, Laura; Easton, Douglas F.; Dunning, Alison M.; Möller, Andreas; Chenevix-Trench, Georgia; Edwards, Stacey L.; French, J. D.

doi:10.1101/521013

Cited by 3 publications

(2 citation statements)

References 33 publications

(32 reference statements)

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“…Interestingly, losses in the homologue human regions (located in HSA 11q) are associated with HBC-tumourigenesis and poor survival 95,96 . The deletion or down-regulation of genes BARX2, HEPACAM, and OPCML included in those regions is a potential biomarker and therapeutic target in different types of human malignancies [97][98][99][100][101] including HBCs [102][103][104] . OPCML and BARX2 downregulation is associated with EMT-elicitation and poor prognosis in different types of human cancer 97,99,105 .…”

Section: Discussionmentioning

confidence: 99%

Analysis of Copy-Number Variations and Feline Mammary Carcinoma Survival

Granados-Soler

Bornemann-Kolatzki²,

Beck³

et al. 2020

Sci Rep

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Feline mammary carcinomas (FMCs) are highly malignant. As the disease-free survival (DFS) and overall survival (OS) are short, prognostication is crucial. Copy-number variations (CNVs) analysis by nextgeneration sequencing serves to identify critical cancer-related genomic regions. Thirty-three female cats with FMCs were followed during two years after surgery. Tumours represented tubulopapillary and solid carcinomas encompassing six molecular subtypes. Regardless of the histopathological diagnosis, molecular subtypes showed important differences in survival. Luminal A tumours exhibited the highest DFS (p = 0.002) and cancer-specific OS (p = 0.001), and the lowest amount of CNVs (p = 0.0001). In contrast, basal-like triple-negative FMCs had the worst outcome (DFS, p < 0.0001; and OS, p < 0.00001) and were the most aberrant (p = 0.05). In the multivariate analysis, copy-number losses (CNLs) in chromosome B1 (1-23 Mb) harbouring several tumour-repressors (e.g. CSMD1, MTUS1, MSR1, DBC2, and TUSC3) negatively influenced DFS. Whereas, copy-number gains (CNGs) in B4 (1-29 Mb) and F2 (64-82.3 Mb) comprising epithelial to mesenchymal transition genes and metastasis-promoting transcription factors (e.g. GATA3, VIM, ZEB1, and MYC) negatively influenced DFS and cancer-specific OS. These data evidence an association between specific CNVs in chromosomes B1, B4 and F2, and poor prognosis in FMCs.

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Section: Discussionmentioning

confidence: 99%

Analysis of Copy-Number Variations and Feline Mammary Carcinoma Survival

Granados-Soler

Bornemann-Kolatzki²,

Beck³

et al. 2020

Sci Rep

View full text Add to dashboard Cite

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“…5D, left), a trait with highly sex-differentiated incidence and presentation (50). For breast cancer, we identified two additional female-driven (PP4 F > PP4 M ) colocalized sb-eGenes, NTN4 and CRLF3 (table S15), previously reported as breast cancer-relevant genes (51,52).…”

Section: Sex-aware Eqtl-gwas Colocalization Provides Insights Into the Genetic Basis Of Complex Traitsmentioning

confidence: 65%

The impact of sex on gene expression across human tissues

Oliva

Muñoz-Aguirre

Kim-Hellmuth

et al. 2020

Science

417

382

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Many complex human phenotypes exhibit sex-differentiated characteristics. However, the molecular mechanisms underlying these differences remain largely unknown. We generated a catalog of sex differences in gene expression and in the genetic regulation of gene expression across 44 human tissue sources surveyed by the Genotype-Tissue Expression project (GTEx, v8 release). We demonstrate that sex influences gene expression levels and cellular composition of tissue samples across the human body. A total of 37% of all genes exhibit sex-biased expression in at least one tissue. We identify cis expression quantitative trait loci (eQTLs) with sex-differentiated effects and characterize their cellular origin. By integrating sex-biased eQTLs with genome-wide association study data, we identify 58 gene-trait associations that are driven by genetic regulation of gene expression in a single sex. These findings provide an extensive characterization of sex differences in the human transcriptome and its genetic regulation.

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Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes

et al. 2020

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Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants (CCVs) in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium, and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:

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High-throughput allelic expression imbalance analyses identify candidate breast cancer risk genes

Cited by 3 publications

References 33 publications

Analysis of Copy-Number Variations and Feline Mammary Carcinoma Survival

Analysis of Copy-Number Variations and Feline Mammary Carcinoma Survival

The impact of sex on gene expression across human tissues

Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes

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