A DNA damage repair gene-associated signature predicts responses of patients with advanced soft-tissue sarcoma to treatment with trabectedin

Signatura genètica; Biomarcadors predictius; TrabectedinaFirma genética; Biomarcadores predictivos; TrabectedinaGene signature; Predictive biomarkers; TrabectedinPredictive biomarkers of trabectedin represent an unmet need in advanced soft-tissue sarcomas (STS). DNA damage repair (DDR) genes, involved in homologous recombination or nucleotide excision repair, had been previously described as biomarkers of trabectedin resistance or sensitivity, respectively. The majority of these studies only focused on specific factors (ERCC1, ERCC5, and BRCA1) and did not evaluate several other DDR-related genes that could have a relevant role for trabectedin efficacy. In this retrospective translational study, 118 genes involved in DDR were evaluated to determine, by transcriptomics, a predictive gene signature of trabectedin efficacy. A six-gene predictive signature of trabectedin efficacy was built in a series of 139 tumor samples from patients with advanced STS. Patients in the high-risk gene signature group showed a significantly worse progression-free survival compared with patients in the low-risk group (2.1 vs 6.0 months, respectively). Differential gene expression analysis defined new potential predictive biomarkers of trabectedin sensitivity (PARP3 and CCNH) or resistance (DNAJB11 and PARP1). Our study identified a new gene signature that significantly predicts patients with higher probability to respond to treatment with trabectedin. Targeting some genes of this signature emerges as a potential strategy to enhance trabectedin efficacy.This study was funded by the Spanish Group for Research on Sarcoma (GEIS) and partially by PharmaMar. The authors would like to thank the GEIS data center for data management. The authors also thank the donors and the Hospital Universitario Virgen del Rocío—Instituto de Biomedicina de Sevilla Biobank (Andalusian Public Health System Biobank and ISCIII-Red de Biobancos PT17/0015/0041) for part of the human specimens used in this study. David S. Moura is recipient of a Sara Borrell postdoctoral fellowship funded by the National Institute of Health Carlos III (ISCIII) (CD20/00155)

Genetic polymorphisms in DNA repair and oxidative stress pathways associated with malignant melanoma susceptibility

Background: Base excision repair (BER) and nucleotide excision repair (NER) pathways eliminate a wide variety of DNA damage, including UV photoproducts. The ability of each individual to repair DNA damage following different causes might explain at least in part the variability in cancer susceptibility. Moreover, inflammatory response to UV exposure may further contribute to skin carcinogenesis by oxidative stress mechanisms. Single nucleotide polymorphisms in genes encoding various DNA-repair enzymes and oxidative stress factors may be candidate low-penetrance variants with a role in susceptibility to different cancers, particularly in those with aetiologies linked to environmental exposure, such as malignant melanoma (MM). Methods: In this case control study, 684 Spanish sporadic MM patients and 406 cancer-free control subjects were included and the role of 46 polymorphisms belonging to 16 BER and NER genes as well as 11 genes involved in oxidative stress processes were investigated. Results: One polymorphism was identified to be individually associated with MM in the Spanish population. The variant was found in the NOS1 oxidative stress gene (rs2682826; p-value = 0.01). These results suggest a putative role of oxidative stress processes in the genetic predisposition to melanoma. Conclusion: To the authors' knowledge, this is the largest DNA repair-related SNP study in melanoma risk conducted in the Spanish population up to now. Furthermore, it also represents a comprehensive genetic study of several oxidative stress polymorphisms tested in relation to MM susceptibility. (C) 2011 Elsevier Ltd. All rights reserved

A versatile and interoperable computational framework for the analysis and modeling of COVID-19 disease mechanisms

The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. Community-driven and highly interdisciplinary, the project is collaborative and supports community standards, open access, and the FAIR data principles. The coordination of community work allowed for an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework links key molecules highlighted from broad omics data analysis and computational modeling to dysregulated pathways in a cell-, tissue- or patient-specific manner. We also employ text mining and AI-assisted analysis to identify potential drugs and drug targets and use topological analysis to reveal interesting structural features of the map. The proposed framework is versatile and expandable, offering a significant upgrade in the arsenal used to understand virus-host interactions and other complex pathologies