| Literature DB >> 33568750 |
Andrew J Armstrong1, Xiaotong Li2, Matthew Tucker3, Shantao Li2, Xinmeng Jasmine Mu4, Kenneth Wha Eng5, Andrea Sboner6, Mark Rubin7,8,9, Mark Gerstein10,11.
Abstract
PURPOSE: Molecular profiling of cancer is increasingly common as part of routine care in oncology, and germline and somatic profiling may provide insights and actionable targets for men with metastatic prostate cancer. However, all reported cases are of deidentified individuals without full medical and genomic data available in the public domain. PATIENT AND METHODS: We present a case of whole-genome tumor and germline sequencing in a patient with advanced prostate cancer, who has agreed to make his genomic and clinical data publicly available.Entities:
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Year: 2021 PMID: 33568750 PMCID: PMC8384621 DOI: 10.1038/s41391-021-00324-5
Source DB: PubMed Journal: Prostate Cancer Prostatic Dis ISSN: 1365-7852 Impact factor: 5.554
Fig. 1Summary of the patient case and outcomes.
A Response of serum PSA to initial therapy with IMRT and 3 years of ADT, with ongoing response off therapy now for 2 years. B Staging CT at diagnosis demonstrating a left pelvic/ischia osteoblastic metastasis, confirmed on C bone scan at baseline/diagnosis in 2015 and D subsequent to therapy 3 months after treatment initiation, showing a favorable treatment effect. E Summary table of our patient’s case report.
Fig. 2Enrichment of GWAS risk alleles.
A The number of heterogenous states of risk alleles (i.e., carry one risk allele) in an individual. B The number of homogenous states of GWAS risk alleles (i.e., carry two risk alleles) in an individual. In both cases, our subject carries slightly higher risk alleles (z-score: +0.36 and +1.0 respectively).
Fig. 3Somatic mutatioal signatures and tumor heterogeneity.
A A dotchart showing the fractions of activities of signatures in the subject (blue) and average PCAWG individuals (red). The subject has higher signature 5. B The subject (red) when compared to the PCAWG individuals (gray), has slightly higher mutation load (y-axis) and higher MATH score (x-axis).
Fig. 4Cancer genes with copy number alterations.
Cancer genes reporting genomic alterations identified from the subject were listed based on their locations on chromosomes. Genes in red had copy number gain events. Genes in blue reported copy number loss events.