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Triple negative breast cancers (TNBCs) represent 15–20% of all breast cancers and are associated with higher recurrence and distant metastasis rate. Standard of care for early stage TNBC is anthracyclines combined with cyclophosphamide (AC) followed by taxanes, in the neo‐adjuvant or adjuvant setting. This work aimed to identify predictive biomarkers of AC response in patient‐derived xenograft (PDX) models of TNBC and to validate them in the clinical setting. By gene and protein expression analysis of 39 PDX with different responses to AC, we found that high expression of HORMAD1 was associated with better response to AC. Both gene and protein expression were associated with promoter hypomethylation. In a cohort of 526 breast cancer patients, HORMAD1 was overexpressed in 71% of TNBC. In a second cohort of 186 TNBC patients treated with AC, HORMAD1 expression was associated with longer metastasis‐free survival (MFS). In summary, HORMAD1 overexpression was predictive of an improved response to AC in PDX and is an independent prognostic factor in TNBC patients treated with AC.

Pathogenicity assessment of genetic variants is the cornerstone of genetic counselling. Copy gains of exons are challenging, as pathogenicity depends on the localization of the additional exons. Eight patients form six families carried copy gains of BRCA1 exons 8–20. For appropriate characterization, long-read sequencing aligned on three distinct reference genome assemblies, optical genomic mapping, short-read and long-read RNA sequencing were performed. All patients shared the same pathogenic structural variant, involving a large segment located downstream in the genome. One breakpoint occurred in a region incorrectly annotated in GRCh37/hg19 and GRCh38/hg38. Alignment to the T2T-CHM13/hs1 assembly was therefore necessary for accurate characterization. This rearrangement caused various BRCA1 transcriptomic abnormalities: back-splicing, forward genomic strand transcription by insertion of an ectopic promoter, fusion transcripts with the “Next to BRCA1 ” gene 1 ( NBR1 ). Our findings underscore the need to combine advanced technologies with the latest genome references to resolve complex rearrangements with significant medical implications.

Background The distinction between primary and secondary ovarian tumors may be challenging for pathologists. The purpose of the present work was to develop genomic and transcriptomic tools to further refine the pathological diagnosis of ovarian tumors after a previous history of breast cancer. Methods Sixteen paired breast-ovary tumors from patients with a former diagnosis of breast cancer were collected. The genomic profiles of paired tumors were analyzed using the Affymetrix GeneChip ® Mapping 50 K Xba Array or Genome-Wide Human SNP Array 6.0 (for one pair), and the data were normalized with ITALICS (ITerative and Alternative normaLIzation and Copy number calling for affymetrix Snp arrays) algorithm or Partek Genomic Suite, respectively. The transcriptome of paired samples was analyzed using Affymetrix GeneChip ® Human Genome U133 Plus 2.0 Arrays, and the data were normalized with gc-Robust Multi-array Average (gcRMA) algorithm. A hierarchical clustering of these samples was performed, combined with a dataset of well-identified primary and secondary ovarian tumors. Results In 12 of the 16 paired tumors analyzed, the comparison of genomic profiles confirmed the pathological diagnosis of primary ovarian tumor (n = 5) or metastasis of breast cancer (n = 7). Among four cases with uncertain pathological diagnosis, genomic profiles were clearly distinct between the ovarian and breast tumors in two pairs, thus indicating primary ovarian carcinomas, and showed common patterns in the two others, indicating metastases from breast cancer. In all pairs, the result of the transcriptomic analysis was concordant with that of the genomic analysis. Conclusions In patients with ovarian carcinoma and a previous history of breast cancer, SNP array analysis can be used to distinguish primary and secondary ovarian tumors. Transcriptomic analysis may be used when primary breast tissue specimen is not available.

A significant proportion of patients with oestrogen receptor (ER) positive breast cancers (BC) develop resistance to endocrine treatments (ET) and relapse with metastatic disease. Here we perform whole exome sequencing and gene expression analysis of matched primary breast tumours and bone metastasis-derived patient-derived xenografts (PDX). Tran-scriptomic analyses reveal enrichment of the G2/M checkpoint and up-regulation of Polo-like kinase 1 (PLK1) in PDX. PLK1 inhibition results in tumour shrinkage in highly proliferating CCND1-driven PDX, including different RB-positive PDX with acquired palbociclib resistance. Mechanistic studies in endocrine resistant cell lines, suggest an ER-independent function of PLK1 in regulating cell proliferation. Finally, in two independent clinical cohorts of ER positive BC, we find a strong association between high expression of PLK1 and a shorter metastases-free survival and poor response to anastrozole. In conclusion, our findings support clinical development of PLK1 inhibitors in patients with advanced CCND1-driven BC, including patients progressing on palbociclib treatment.

Muscle-invasive bladder cancer (BLCA) is an aggressive disease. Consensus BLCA transcriptomic subtypes have been proposed, with two major Luminal and Basal subgroups, presenting distinct molecular and clinical characteristics. However, how these distinct subtypes are regulated remains unclear. We hypothesized that epigenetic activation of distinct super-enhancers could drive the transcriptional programs of BLCA subtypes. Through integrated RNA-sequencing and epigenomic profiling of histone marks in primary tumours, cancer cell lines, and normal human urothelia, we established the first integrated epigenetic map of BLCA and demonstrated the link between subtype and epigenetic control. We identified the repertoire of activated super-enhancers and highlighted Basal, Luminal and Normal-associated SEs. We revealed super-enhancer-regulated networks of candidate master transcription factors for Luminal and Basal subgroups including FOXA1 and ZBED2, respectively. FOXA1 CRISPR-Cas9 mutation triggered a shift from Luminal to Basal phenotype, confirming its role in Luminal identity regulation and induced ZBED2 overexpression. In parallel, we showed that both FOXA1 and ZBED2 play concordant roles in preventing inflammatory response in cancer cells through STAT2 inhibition. Our study furthers the understanding of epigenetic regulation of muscle-invasive BLCA and identifies a co-regulated network of super-enhancers and associated transcription factors providing potential targets for the treatment of this aggressive disease.

Bladder cancer is a common cancer; it is the tenth most common cancer in the world. Around one fourth of all diagnosed patients have muscle-invasive bladder cancer (MIBC), characterized by advanced tumors and which remains a lethal disease. The standard treatment for MIBC is the bladder removal by surgery. However, bladder-preserving alternatives are emerging by combining chemotherapy, radiotherapy and minimal surgery, aiming to increase the patient’s quality of life. The aim of the study was to improve these treatments by investigating a novel approach where in addition to radiotherapy, a receptor, TYRO3, a member of TAM receptor tyrosine kinase family known to be highly expressed on the bladder cancer cells and involved in the control of cell survival is targeted. For this, we evaluated the influence of TYRO3 expression levels on a colony or cell survival assays, DNA damage, γH2AX foci formation, gene expression profiling and cell cycle regulation, after radiation on different bladder cell models. We found that TYRO3 expression impacts the radiation response via the cell cycle dysregulation with noeffets on the DNA repair. Therefore, targeting TYRO3 is a promising sensitization marker that could be clinically employed in future treatments.

Purpose Investigate in what extent sperm transcriptome of infertile men is different from that of fertile individuals. Methods Semen samples were collected for determination of sperm parameters as well as for RNA isolation. Gene expression profile was investigated in spermatozoa of 8 infertile and 3 fertile men by microarray analysis using the Affymetrix Chip HG-U133 Plus 2.0. Result(s) We observed up to 33-fold reduction expression of genes involved in spermatogenesis and sperm motility. Furthermore, there is an important decrease in expression of genes involved in DNA repair as well as oxidative stress regulation. In this study, we also show a striking drop in expression of histone modification genes. Conclusion(s) We found that transcription profile in germ cells of men with idiopathic infertility is different from that of fertile individuals. Interestingly, about 15% of the regulated genes (Eddy Rev Reprod 4:23–30, 1999 ) play a role in spermatogenesis.

The use of RNA-sequencing technologies held a promise of improved diagnostic tools based on comprehensive transcript sets. However, mining human transcriptome data for disease biomarkers in clinical specimens are restricted by the limited power of conventional reference-based protocols relying on unique and annotated transcripts. Here, we implemented a blind reference-free computational protocol, DE-kupl, to infer yet unreferenced RNA variations from total stranded RNA-sequencing datasets of tissue origin. As a bench test, this protocol was powered for detection of RNA subsequences embedded into putative long noncoding (lnc)RNAs expressed in prostate cancer. Through filtering of 1,179 candidates, we defined 21 lncRNAs that were further validated by NanoString for robust tumor-specific expression in 144 tissue specimens. Predictive modeling yielded a restricted probe panel enabling more than 90% of true-positive detections of cancer in an independent The Cancer Genome Atlas cohort. Remarkably, this clinical signature made of only nine unannotated lncRNAs largely outperformed PCA3, the only used prostate cancer lncRNA biomarker, in detection of high-risk tumors. This modular workflow is highly sensitive and can be applied to any pathology or clinical application.