Dataset Information

Discovery and validation of a transcriptional signature identifying homologous recombination-deficient breast, endometrial and ovarian cancers.

ABSTRACT:

Background

Molecular alterations leading to homologous recombination deficiency (HRD) are heterogeneous. We aimed to identify a transcriptional profile shared by endometrial (UCEC), breast (BRCA) and ovarian (OV) cancers with HRD.

Methods

Genes differentially expressed with HRD genomic score (continuous gHRD score) in UCEC/BRCA/OV were identified using edgeR, and used to train a RNAseq score (ridge-regression model) predictive of the gHRD score (PanCanAtlas, N = 1684 samples). The RNAseq score was applied in independent gynaecological datasets (CARPEM/CPTAC/SCAN/TCGA, N = 4038 samples). Validations used ROC curves, linear regressions and Pearson correlations. Overall survival (OS) analyses used Kaplan-Meier curves and Cox models.

Results

In total, 656 genes were commonly up/downregulated with gHRD score in UCEC/BRCA/OV. Upregulated genes were enriched for nuclear/chromatin/DNA-repair processes, while downregulated genes for cytoskeleton (gene ontologies). The RNAseq score correlated with gHRD score in independent gynaecological cancers (R² = 0.4-0.7, Pearson correlation = 0.64-0.86, all P < 10^-11), and was predictive of gHRD score >42 (RNAseq HRD profile; AUC = 0.95/0.92/0.78 in UCEC/BRCA/OV). RNAseq HRD profile was associated (i) with better OS in platinum-treated advanced TP53-mutated-UCEC (P < 0.001) and OV (P = 0.013), and (ii) with poorer OS (P < 0.001) and higher benefit of adjuvant chemotherapy in Stage I-III BRCA (interaction test, P < 0.001).

Conclusions

UCEC/BRCA/OV with HRD-associated genomic scars share a common transcriptional profile. RNAseq signatures might be relevant for identifying HRD-gynaecological cancers, for prognostication and for therapeutic decision.

SUBMITTER: Beinse G

PROVIDER: S-EPMC9470569 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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Publications

Discovery and validation of a transcriptional signature identifying homologous recombination-deficient breast, endometrial and ovarian cancers.

Beinse Guillaume G Just Pierre-Alexandre PA Le Frere Belda Marie-Aude MA Laurent-Puig Pierre P Jacques Sebastien S Koual Meriem M Garinet Simon S Leroy Karen K Delanoy Nicolas N Blons Helene H Gervais Claire C Durdux Catherine C Chapron Charles C Goldwasser François F Terris Benoit B Badoual Cecile C Taly Valerie V Bats Anne-Sophie AS Borghese Bruno B Alexandre Jérôme J

British journal of cancer 20220625 6

<h4>Background</h4>Molecular alterations leading to homologous recombination deficiency (HRD) are heterogeneous. We aimed to identify a transcriptional profile shared by endometrial (UCEC), breast (BRCA) and ovarian (OV) cancers with HRD.<h4>Methods</h4>Genes differentially expressed with HRD genomic score (continuous gHRD score) in UCEC/BRCA/OV were identified using edgeR, and used to train a RNAseq score (ridge-regression model) predictive of the gHRD score (PanCanAtlas, N = 1684 samples). The ...[more]

PMID: 35752712

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Project description:BackgroundGlioblastoma (GBM) is a frequent malignant tumor in neurosurgery characterized by a high degree of heterogeneity and genetic instability. DNA double-strand breaks generated by homologous recombination deficiency (HRD) are a well-known contributor to genomic instability, which can encourage tumor development. It is unknown, however, whether the molecular characteristics linked with HRD have a predictive role in GBM. The study aims to assess the extent of genomic instability in GBM using HRD score and investigate the prognostic significance of HRD-related molecular features in GBM.MethodsThe discovery cohort comprised 567 GBM patients from The Cancer Genome Atlas (TCGA) database. We established HRD scores using the single nucleotide polymorphism (SNP) array data and analyzed transcriptomic data from patients with different HRD scores to identify biomarkers associated with HRD. A prognostic model was built by using HRD-related differentially expressed genes (DEGs) and validated in a distinct cohort from the Chinese Glioma Genome Atlas (CGGA) database.ResultsBased on the SNP array data, the gene expression profile data, and the clinical characteristics of GBM patients, we found that patients with a high HRD score had a better prognosis than those with a low HRD score. The DNA damage repair (DDR) signaling pathways were notably enriched in the HRD-positive subgroup. The prognostic model was developed by including HRD-related DEGs that could evaluate the clinical prognosis of patients more efficiently than the HRD score. In addition, patients with a low-risk score had a considerably augmented signature of γδT cells. Finally, through univariate and multivariate Cox regression analyses, it was demonstrated that the prognostic model was superior to other prognostic markers.ConclusionsIn conclusion, our research has not only demonstrated that a high HRD score is a valid prognostic biomarker in GBM patients but also built a stable prognosis model [odds ratio (OR) 0.18, 95% confidence interval (CI): 0.11-0.23, P<0.001] that is more accurate than conventional prognostic markers such as O6-methylguanine-DNA methyltransferase (MGMT) methylation (OR 0.55, 95% CI: 0.33-0.91, P=0.02).

Dataset Information

Discovery and validation of a transcriptional signature identifying homologous recombination-deficient breast, endometrial and ovarian cancers.

Background

Methods

Results

Conclusions

Publications

Discovery and validation of a transcriptional signature identifying homologous recombination-deficient breast, endometrial and ovarian cancers.

Similar Datasets

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