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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. [ABSTRACT FROM AUTHOR]

Despite recent advances in endometrial carcinoma (EC) molecular characterization, its prognostication remains challenging. We aimed to assess whether RNAseq could stratify EC patient prognosis beyond current classification systems. A prognostic signature was identified using a LASSO-penalized Cox model trained on TCGA (N = 543 patients). A clinically applicable polyA-RNAseq-based work-flow was developed for validation of the signature in a cohort of stage I-IV patients treated in two Hospitals [2010–2017]. Model performances were evaluated using time-dependent ROC curves (prediction of disease-specific-survival (DSS)). The additional value of the RNAseq signature was evaluated by multivariable Cox model, adjusted on high-risk prognostic group (2021 ESGO-ESTRO-ESP guidelines: non-endometrioid histology or stage III-IVA or TP53 -mutated molecular subgroup). Among 209 patients included in the external validation cohort, 61 (30%), 10 (5%), 52 (25%), and 82 (40%), had mismatch repair-deficient, POLE -mutated, TP53 -mutated tumors, and tumors with no specific molecular profile, respectively. The 38-genes signature accurately predicted DSS (AUC = 0.80). Most disease-related deaths occurred in high-risk patients (5-years DSS = 78% (95% CI = [68%–89%]) versus 99% [97%–100%] in patients without high-risk). A composite classifier accounting for the TP53- mutated subgroup and the RNAseq signature identified three classes independently associated with DSS: RNAseq-good prognosis (reference, 5-years DSS = 99%), non- TP53 tumors but with RNAseq-poor prognosis (adjusted-hazard ratio (aHR) = 5.75, 95% CI[1.14–29.0]), and TP53 -mutated subgroup (aHR = 5.64 [1.12–28.3]). The model accounting for the high-risk group and the composite classifier predicted DSS with AUC = 0.84, versus AUC = 0.76 without (p = 0.01). RNA-seq profiling can provide an additional prognostic information to established classification systems, and warrants validation for potential RNAseq-based therapeutic strategies in EC. • One out of 3 endometrial cancer (EC) are at high risk of relapse (2021 guidelines). • Histological and molecular features of this group are widely heterogeneous. • RNAseq prognostication is feasible & robust from routine practice FFPE EC samples. • Integrating RNAseq to current classification improves EC prognostic stratification. [ABSTRACT FROM AUTHOR]

Background: Patients with non-small cell lung cancer (NSCLC) receiving curative surgery have a risk of relapse, and adjuvant treatments only translate into a 5% increase in 5-year survival. We assessed the clinical significance of epithelial-mesenchymal transition (EMT) and explored its association with the [SNAIL/miR-34]:[ZEB/miR-200] regulation hub to refine prognostic information.Methods: We validated a 7-gene EMT score using a consecutive series of 176 resected NSCLC. We quantified EMT transcription factors, microRNAs (miRs) of the miR-200, miR-34 families and miR-200 promoter hypermethylation to identify outcome predictors.Results: Most tumours presented with an EMT-hybrid state and the EMT score was not predictive of outcome. Individually, all miR-200 were inversely associated with the EMT score, but only chromosome-1 miRs, miR-200a, b, 429, were associated with disease-free survival (p = 0.08, 0.05 and 0.025) and overall survival (p = 0.013, 0.003 and 0.006). We validated these associations on The Cancer Genome Atlas data. Tumour unsupervised clustering based on miR expression identified two good prognostic groups, unrelated to the EMT score, suggesting that miR profiling may have an important clinical value.Conclusion: miR-200 family members do not have similar predictive value. Core EMT-miR, regulators and not EMT itself, identify NSCLC patients with a low risk of relapse after surgery. [ABSTRACT FROM AUTHOR]