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eTumorMetastasis:A Network-based Algorithm Predicts Clinical Outcomes Using Whole-exome Sequencing Data of Cancer Patients

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Genomics, Proteomics & Bioinformatics 2021年第6期19卷 973-985页

作者： Jean-Sébastien Milanese Chabane Tibiche Naif Zaman Jinfeng Zou Pengyong Han Zhigang Meng Andre Nantel arnaud droit Edwin Wang Human Health Therapeutics National Research Council CanadaMontreal H4P 2R2Canada Genomics Center Centre Hospitalier Universitaire de Québec-UniversitéLaval Research CenterQuebec G1V 4G2Canada Department of Biochemistry&Molecular Biology Medical Geneticsand OncologyUniversity of CalgaryCalgary T2N 4N1Canada Alberta Children’s Hospital Research Institute and Arnie Charbonneau Cancer Research Institute University of CalgaryCalgary T2N 4N1Canada Institute of Biotechnology Chinese Academy of Agricultural SciencesBeijing 100086China Department of Medicine McGill UniversityMontreal H3G 2M1Canada

Continual reduction in sequencing cost is expanding the accessibility of genome sequencing data for routine clinical ***,the lack of methods to construct machine learning-based predictive models using these datasets has become a crucial bottleneck for the application of sequencing technology in ***,we develop a new algorithm,eTumorMetastasis,which transforms tumor functional mutations into network-based profiles and identifies network operational gene(NOG)*** signatures model the tipping point at which a tumor cell shifts from a state that doesn’t favor recurrence to one that *** show that NOG signatures derived from genomic mutations of tumor founding clones(i.e.,the‘most recent common ancestor’of the cells within a tumor)significantly distinguish the recurred and non-recurred breast tumors as well as outperform the most popular genomic test(i.e.,Oncotype DX).These results imply that mutations of the tumor founding clones are associated with tumor recurrence and can be used to predict clinical *** such,predictive tools could be used in clinics to guide treatment ***,the concepts underlying the eTumorMetastasis pave the way for the application of genome sequencing in predictions for other complex genetic *** pseudocode and related data used in this study are available at https://***/WangEdwinLab/eTumorMetastasis.

关键词： Breast cancer Sequencing data Predictive model Systems biology Machine learning

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Association between genome-wide epigenetic and genetic alterations in breast cancer tissue and response to HER2-targeted therapies in HER2- positive breast cancer patients: new findings and a systematic review

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Cancer Drug Resistance 2022年第4期5卷 995-1015页

作者： Daniela Furrer Dzevka Dragic Sue-Ling Chang Frédéric Fournier arnaud droit Simon Jacob Caroline Diorio Centre de Recherche sur le cancer de l’UniversitéLaval 1050 Avenue de la MédecineQuébecQC G1V 0A6Canada Axe Oncologie Centre de Recherche du CHU de Québec-UniversitéLavalQuébecQC G1S 4L8Canada Département de médecine sociale et préventive Facultéde MédecineUniversitéLavalQuébecQC G1V 0A6Canada UniversitéParis-Saclay UVSQInsermCESP U1018Exposome and Heredity TeamGustave RoussyVillejuif 94807France Département de médecine moléculaire Facultéde MédecineUniversitéLavalQuébecQC G1V 0A6Canada Département de biologie moléculaire de biochimie médicale et de pathologieFacultéde MédecineUniversitéLavalQuébecQC G1V 0A6Canada Centre des Maladies du Sein Hôpital du Saint-SacrementQuébecQC G1S 4L8Canada

Recent evidence suggests that genetic and epigenetic mechanisms might be associated with acquired resistance to cancer *** aim of this study was to assess the association of genome-wide genetic and epigenetic alterations with the response to anti-HER2 agents in HER2-positive breast cancer *** was screened for articles published until March 2021 on observational studies investigating the association of genome-wide genetic and epigenetic alterations,measured in breast cancer tissues or blood,with the response to targeted treatment in HER2-positive breast cancer *** studies were included in the review along with ours,in which we compared the genome-wide DNA methylation pattern in breast tumor tissues of patients who acquired resistance to treatment (case group, n = 6) to that of patients who did not develop resistance (control group, n =6). Among genes identified as differentially methylated between the breast cancer tissue of cases and controls, oneof them, PRKACA, was also reported as differentially expressed in two studies included in the review. Althoughincluded studies were heterogeneous in terms of methodology and study population, our review suggests thatgenes of the PI3K pathway may play an important role in developing resistance to anti-HER2 agents in breastcancer patients. Genome-wide genetic and epigenetic alterations measured in breast cancer tissue or blood mightbe promising markers of resistance to anti-HER2 agents in HER2-positive breast cancer patients. Further studiesare needed to confirm these data.

关键词： Breast neoplasms epigenetics genetics HER2 inhibitors treatment response biomarkers

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