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Keywords = SKCM-TCGA Pan Cancer Atlas

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12 pages, 436 KiB  
Communication
Genetic Variants and Somatic Alterations Associated with MITF-E318K Germline Mutation in Melanoma Patients
by Elisabetta Vergani, Simona Frigerio, Matteo Dugo, Andrea Devecchi, Erika Feltrin, Loris De Cecco, Viviana Vallacchi, Mara Cossa, Lorenza Di Guardo, Siranoush Manoukian, Bernard Peissel, Andrea Ferrari, Gianfrancesco Gallino, Andrea Maurichi, Licia Rivoltini, Marialuisa Sensi and Monica Rodolfo
Genes 2021, 12(9), 1440; https://doi.org/10.3390/genes12091440 - 18 Sep 2021
Cited by 5 | Viewed by 3997
Abstract
The MITF-E318K variant has been implicated in genetic predisposition to cutaneous melanoma. We addressed the occurrence of MITF-E318K and its association with germline status of CDKN2A and MC1R genes in a hospital-based series of 248 melanoma patients including cohorts of multiple, familial, pediatric, [...] Read more.
The MITF-E318K variant has been implicated in genetic predisposition to cutaneous melanoma. We addressed the occurrence of MITF-E318K and its association with germline status of CDKN2A and MC1R genes in a hospital-based series of 248 melanoma patients including cohorts of multiple, familial, pediatric, sporadic and melanoma associated with other tumors. Seven MITF-E318K carriers were identified, spanning every group except the pediatric patients. Three carriers showed mutated CDKN2A, five displayed MC1R variants, while the sporadic carrier revealed no variants. Germline/tumor whole exome sequencing for this carrier revealed germline variants of unknown significance in ATM and FANCI genes and, in four BRAF-V600E metastases, somatic loss of the MITF wild-type allele, amplification of MITF-E318K and deletion of a 9p21.3 chromosomal region including CDKN2A and MTAP. In silico analysis of tumors from MITF-E318K melanoma carriers in the TCGA Pan-Cancer-Atlas dataset confirmed the association with BRAF mutation and 9p21.3 deletion revealing a common genetic pattern. MTAP was the gene deleted at homozygous level in the highest number of patients. These results support the utility of both germline and tumor genome analysis to define tumor groups providing enhanced information for clinical strategies and highlight the importance of melanoma prevention programs for MITF-E318K patients. Full article
(This article belongs to the Special Issue Genetics and Genomics of Melanoma)
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21 pages, 1212 KiB  
Article
The Expression Profiles of ADME Genes in Human Cancers and Their Associations with Clinical Outcomes
by Dong Gui Hu, Peter I. Mackenzie, Pramod C. Nair, Ross A. McKinnon and Robyn Meech
Cancers 2020, 12(11), 3369; https://doi.org/10.3390/cancers12113369 - 13 Nov 2020
Cited by 21 | Viewed by 4443
Abstract
ADME genes are a group of genes that are involved in drug absorption, distribution, metabolism, and excretion (ADME). The expression profiles of ADME genes within tumours is proposed to impact on cancer patient survival; however, this has not been systematically examined. In this [...] Read more.
ADME genes are a group of genes that are involved in drug absorption, distribution, metabolism, and excretion (ADME). The expression profiles of ADME genes within tumours is proposed to impact on cancer patient survival; however, this has not been systematically examined. In this study, our comprehensive analyses of pan-cancer datasets from the Cancer Genome Atlas (TCGA) revealed differential intratumoral expression profiles for ADME genes in 21 different cancer types. Most genes also showed high interindividual variability within cancer-specific patient cohorts. Using Kaplan-Meier plots and logrank tests, we showed that intratumoral expression levels of twenty of the thirty-two core ADME genes were associated with overall survival (OS) in these cancers. Of these genes, five showed significant association with unfavourable OS in three cancers, including SKCM (ABCC2, GSTP1), KIRC (CYP2D6, CYP2E1), PAAD (UGT2B7); sixteen showed significant associations with favourable OS in twelve cancers, including BLCA (UGT2B15), BRCA (CYP2D6), COAD (NAT1), HNSC (ABCB1), KIRC (ABCG2, CYP3A4, SLC22A2, SLC22A6), KIRP (SLC22A2), LIHC (CYP2C19, CYP2C8, CYP2C9, CYP3A5, SLC22A1), LUAD (SLC15A2), LUSC (UGT1A1), PAAD (ABCB1), SARC (ABCB1), and SKCM (ABCB1, DYPD). Overall, these data provide compelling evidence supporting ADME genes as prognostic biomarkers and potential therapeutic targets. We propose that intratumoral expression of ADME genes may impact cancer patient survival by multiple mechanisms that can include metabolizing/transporting anticancer drugs, activating anticancer drugs, and metabolizing/transporting a variety of endogenous molecules involved in metabolically fuelling cancer cells and/or controlling pro-growth signalling pathways. Full article
(This article belongs to the Section Cancer Biomarkers)
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12 pages, 2634 KiB  
Article
Observed Survival Interval: A Supplement to TCGA Pan-Cancer Clinical Data Resource
by Jie Xiong, Zhitong Bing and Shengyu Guo
Cancers 2019, 11(3), 280; https://doi.org/10.3390/cancers11030280 - 26 Feb 2019
Cited by 25 | Viewed by 8163
Abstract
To drive high-quality omics translational research using The Cancer Genome Atlas (TCGA) data, a TCGA Pan-Cancer Clinical Data Resource was proposed. However, there is an out-of-step issue between clinical outcomes and the omics data of TCGA for skin cutaneous melanoma (SKCM), due to [...] Read more.
To drive high-quality omics translational research using The Cancer Genome Atlas (TCGA) data, a TCGA Pan-Cancer Clinical Data Resource was proposed. However, there is an out-of-step issue between clinical outcomes and the omics data of TCGA for skin cutaneous melanoma (SKCM), due to the majority of metastatic samples. In clinical cases, the survival time started from the initial SKCM diagnosis, while the omics data were characterized at TCGA sampling. This study aimed to address this issue by proposing an observed survival interval (OBS), which was defined as the time interval from TCGA sampling to patient death or last follow-up. We compared the OBS with the usual recommended overall survival (OS) by associating them with both clinical data and microRNA sequencing data of TCGA-SKCM. We found that the OS of primary SKCM was significantly shorter than that of metastatic SKCM, while the opposite happened if OBS was compared. OS was associated with the pathological stage of both primary and metastatic SKCM, while OBS was associated with the pathological stage of primary SKCM but not that of metastatic SKCM. Five previously cross-validated survival-associated microRNAs were found to be associated with the OBS rather than OS in metastatic SKCM. Thus, the OBS was more appropriate for associating microRNA-omics data of TCGA-SKCM than OS, and it is a timely supplement to TCGA Pan-Cancer Clinical Data Resource. Full article
(This article belongs to the Special Issue Application of Bioinformatics in Cancers)
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