Fine mapping of RNA isoform diversity using an innovative targeted long-read RNA sequencing protocol with novel dedicated bioinformatics pipeline.

BACKGROUND: Solving the structure of mRNA transcripts is a major challenge for both research and molecular diagnostic purposes. Current approaches based on short-read RNA sequencing and RT-PCR techniques cannot fully explore the complexity of transcript structure. The emergence of third-generation long-read sequencing addresses this problem by solving this sequence directly. However, genes with low expression levels are difficult to study with the whole transcriptome sequencing approach. To fix this technical limitation, we propose a novel method to capture transcripts of a gene panel using a targeted enrichment approach suitable for Pacific Biosciences and Oxford Nanopore Technologies platforms. RESULTS: We designed a set of probes to capture transcripts of a panel of genes involved in hereditary breast and ovarian cancer syndrome. We present SOSTAR (iSofOrmS annoTAtoR), a versatile pipeline to assemble, quantify and annotate isoforms from long read sequencing using a new tool specially designed for this application. The significant enrichment of transcripts by our capture protocol, together with the SOSTAR annotation, allowed the identification of 1,231 unique transcripts within the gene panel from the eight patients sequenced. The structure of these transcripts was annotated with a resolution of one base relative to a reference transcript. All major alternative splicing events of the BRCA1 and BRCA2 genes described in the literature were found. Complex splicing events such as pseudoexons were correctly annotated. SOSTAR enabled the identification of abnormal transcripts in the positive controls. In addition, a case of unexplained inheritance in a family with a history of breast and ovarian cancer was solved by identifying an SVA retrotransposon in intron 13 of the BRCA1 gene. CONCLUSIONS: We have validated a new protocol for the enrichment of transcripts of interest using probes adapted to the ONT and PacBio platforms. This protocol allows a complete description of the alternative structures of transcripts, the estimation of their expression and the identification of aberrant transcripts in a single experiment. This proof-of-concept opens new possibilities for RNA structure exploration in both research and molecular diagnostics.

Classification of 101 BRCA1 and BRCA2 variants of uncertain significance by cosegregation study: A powerful approach.

Up to 80% of BRCA1 and BRCA2 genetic variants remain of uncertain clinical significance (VUSs). Only variants classified as pathogenic or likely pathogenic can guide breast and ovarian cancer prevention measures and treatment by PARP inhibitors. We report the first results of the ongoing French national COVAR (cosegregation variant) study, the aim of which is to classify BRCA1/2 VUSs. The classification method was a multifactorial model combining different associations between VUSs and cancer, including cosegregation data. At this time, among the 653 variants selected, 101 (15%) distinct variants shared by 1,624 families were classified as pathogenic/likely pathogenic or benign/likely benign by the COVAR study. Sixty-six of the 101 (65%) variants classified by COVAR would have remained VUSs without cosegregation data. Of note, among the 34 variants classified as pathogenic by COVAR, 16 remained VUSs or likely pathogenic when following the ACMG/AMP variant classification guidelines. Although the initiation and organization of cosegregation analyses require a considerable effort, the growing number of available genetic tests results in an increasing number of families sharing a particular variant, and thereby increases the power of such analyses. Here we demonstrate that variant cosegregation analyses are a powerful tool for the classification of variants in the BRCA1/2 breast-ovarian cancer predisposition genes.

SPiP: Splicing Prediction Pipeline, a machine learning tool for massive detection of exonic and intronic variant effects on mRNA splicing.

Modeling splicing is essential for tackling the challenge of variant interpretation as each nucleotide variation can be pathogenic by affecting pre-mRNA splicing via disruption/creation of splicing motifs such as 5'/3' splice sites, branch sites, or splicing regulatory elements. Unfortunately, most in silico tools focus on a specific type of splicing motif, which is why we developed the Splicing Prediction Pipeline (SPiP) to perform, in one single bioinformatic analysis based on a machine learning approach, a comprehensive assessment of the variant effect on different splicing motifs. We gathered a curated set of 4616 variants scattered all along the sequence of 227 genes, with their corresponding splicing studies. The Bayesian analysis provided us with the number of control variants, that is, variants without impact on splicing, to mimic the deluge of variants from high-throughput sequencing data. Results show that SPiP can deal with the diversity of splicing alterations, with 83.13% sensitivity and 99% specificity to detect spliceogenic variants. Overall performance as measured by area under the receiving operator curve was 0.986, better than SpliceAI and SQUIRLS (0.965 and 0.766) for the same data set. SPiP lends itself to a unique suite for comprehensive prediction of spliceogenicity in the genomic medicine era. SPiP is available at: https://sourceforge.net/projects/splicing-prediction-pipeline/.

Further delineation of the NTHL1 associated syndrome: A report from the French Oncogenetic Consortium.

Biallelic pathogenic variants in the NTHL1 (Nth like DNA glycosylase 1) gene cause a recently identified autosomal recessive hereditary cancer syndrome predisposing to adenomatous polyposis and colorectal cancer. Half of biallelic carriers also display multiple colonic or extra-colonic primary tumors, mainly breast, endometrium, urothelium, and brain tumors. Published data designate NTHL1 as an important contributor to hereditary cancers but also underline the scarcity of available informations. Thanks to the French oncogenetic consortium (Groupe Génétique et Cancer), we collected NTHL1 variants from 7765 patients attending for hereditary colorectal cancer or polyposis (n = 3936) or other hereditary cancers (n = 3829). Here, we describe 10 patients with pathogenic biallelic NTHL1 germline variants, that is, the second largest NTHL1 series. All carriers were from the "colorectal cancer or polyposis" series. All nine biallelic carriers who underwent colonoscopy presented adenomatous polyps. For digestive cancers, average age at diagnosis was 56.2 and we reported colorectal, duodenal, caecal, and pancreatic cancers. Extra-digestive malignancies included sarcoma, basal cell carcinoma, breast cancer, urothelial carcinoma, and melanoma. Although tumor risks remain to be precisely defined, these novel data support NTHL1 inclusion in diagnostic panel testing. Colonic surveillance should be conducted based on MUTYH recommendations while extra-colonic surveillance has to be defined.

MiR-4270 acts as a tumor suppressor by directly targeting Bcl-xL in human osteosarcoma cells.

Chondrosarcomas and osteosarcomas are malignant bone tumors with a poor prognosis when unresectable or metastasized. Moreover, radiotherapy and chemotherapy could be ineffective. MiRNAs represent an alternative therapeutic approach. Based on high-throughput functional screening, we identified four miRNAs with a potential antiproliferative effect on SW1353 chondrosarcoma cells. Individual functional validations were then performed in SW1353 cells, as well as in three osteosarcoma cell lines. The antiproliferative and cytotoxic effects of miRNAs were evaluated in comparison with a positive control, miR-342-5p. The cytotoxic effect of four selected miRNAs was not confirmed on SW1353 cells, but we unambiguously revealed that miR-4270 had a potent cytotoxic effect on HOS and MG-63 osteosarcoma cell lines, but not on SaOS-2 cell line. Furthermore, like miR-342-5p, miR-4270 induced apoptosis in these two cell lines. In addition, we provided the first report of Bcl-xL as a direct target of miR-4270. MiR-4270 also decreased the expression of the anti-apoptotic protein Mcl-1, and increased the expression of the pro-apoptotic protein Bak. Our findings demonstrated that miR-4270 has tumor suppressive activity in osteosarcoma cells, particularly through Bcl-xL downregulation.

Validation of the Clinical Use of GIScar, an Academic-developed Genomic Instability Score Predicting Sensitivity to Maintenance Olaparib for Ovarian Cancer.

PURPOSE: The optimal application of maintenance PARP inhibitor therapy for ovarian cancer requires accessible, robust, and rapid testing of homologous recombination deficiency (HRD). However, in many countries, access to HRD testing is problematic and the failure rate is high. We developed an academic HRD test to support treatment decision-making. EXPERIMENTAL DESIGN: Genomic Instability Scar (GIScar) was developed through targeted sequencing of a 127-gene panel to determine HRD status. GIScar was trained from a noninterventional study with 250 prospectively collected ovarian tumor samples. GIScar was validated on 469 DNA tumor samples from the PAOLA-1 trial evaluating maintenance olaparib for newly diagnosed ovarian cancer, and its predictive value was compared with Myriad Genetics MyChoice (MGMC). RESULTS: GIScar showed significant correlation with MGMC HRD classification (kappa statistics: 0.780). From PAOLA-1 samples, more HRD-positive tumors were identified by GIScar (258) than MGMC (242), with a lower proportion of inconclusive results (1% vs. 9%, respectively). The HRs for progression-free survival (PFS) with olaparib versus placebo were 0.45 [95% confidence interval (CI), 0.33-0.62] in GIScar-identified HRD-positive BRCA-mutated tumors, 0.50 (95% CI, 0.31-0.80) in HRD-positive BRCA-wild-type tumors, and 1.02 (95% CI, 0.74-1.40) in HRD-negative tumors. Tumors identified as HRD positive by GIScar but HRD negative by MGMC had better PFS with olaparib (HR, 0.23; 95% CI, 0.07-0.72). CONCLUSIONS: GIScar is a valuable diagnostic tool, reliably detecting HRD and predicting sensitivity to olaparib for ovarian cancer. GIScar showed high analytic concordance with MGMC test and fewer inconclusive results. GIScar is easily implemented into diagnostic laboratories with a rapid turnaround.

Outcomes of Patients with Metastatic Castration-Resistant Prostate Cancer According to Somatic Damage DNA Repair Gene Alterations.

(1) Background: In literature, approximately 20% of mCRPC present somatic DNA damage repair (DDR) gene mutations, and their relationship with response to standard therapies in mCRPC is not well understood. The objective was to evaluate outcomes of mCRPC patients treated with standard therapies according to somatic DDR status. (2) Methods: Eighty-three patients were recruited at Caen Cancer Center (France). Progression-free survival (PFS) after first-line treatment was analyzed according to somatic DDR mutation as primary endpoint. PFS according to first exposure to taxane chemotherapy and PFS2 (time to second event of disease progression) depending on therapeutic sequences were also analyzed. (3) Results: Median first-line PFS was 9.7 months in 33 mutated patients and 8.4 months in 50 non-mutated patients (p = 0.9). PFS of first exposure to taxanes was 8.1 months in mutated patients and 5.7 months in non-mutated patients (p = 0.32) and significantly longer among patients with ATM/BRCA1/BRCA2 mutations compared to the others (10.6 months vs. 5.5 months, p = 0.04). PFS2 was 16.5 months in mutated patients, whatever the sequence, and 11.7 months in non-mutated patients (p = 0.07). The mutated patients treated with chemotherapy followed by NHT had a long median PFS2 (49.8 months). (4) Conclusions: mCRPC patients with BRCA1/2 and ATM benefit from standard therapies, with a long response to taxanes.