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Caloto R, Lorenzo-Martín LF, Quesada V, Carracedo A, Bustelo XR. CiberAMP: An R Package to Identify Differential mRNA Expression Linked to Somatic Copy Number Variations in Cancer Datasets. BIOLOGY 2022; 11:biology11101411. [PMID: 36290315 PMCID: PMC9598370 DOI: 10.3390/biology11101411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 09/05/2022] [Accepted: 09/26/2022] [Indexed: 11/27/2022]
Abstract
Simple Summary The ability to establish accurate correlations between the number of copies of genes and the expression levels of their encoded transcripts remains a challenge despite the extensive progress made in the understanding of the genome of cancer cells. Here, we describe a new algorithm that does so by integrating both genomics and transcriptomics data from the Cancer Genome Atlas. In addition to explaining the step-by-step basis of this new method, we provide examples of how this new algorithm can help identify functionally meaningful gene copy alterations that are recurrently detected in cancer patients. Abstract Somatic copy number variations (SCNVs) are genetic alterations frequently found in cancer cells. These genetic alterations can lead to concomitant perturbations in the expression of the genes included in them and, as a result, promote a selective advantage to cancer cells. However, this is not always the case. Due to this, it is important to develop in silico tools to facilitate the accurate identification and functional cataloging of gene expression changes associated with SCNVs from pan-cancer data. Here, we present a new R-coded tool, designated as CiberAMP, which utilizes genomic and transcriptomic data contained in the Cancer Genome Atlas (TCGA) to identify such events. It also includes information on the genomic context in which such SCNVs take place. By doing so, CiberAMP provides clues about the potential functional relevance of each of the SCNV-associated gene expression changes found in the interrogated tumor samples. The main features and advantages of this new algorithm are illustrated using glioblastoma data from the TCGA database.
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Affiliation(s)
- Rubén Caloto
- Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, 37007 Salamanca, Spain
- Instituto de Biología Molecular y Celular del Cáncer de Salamanca, CSIC-University of Salamanca, 37007 Salamanca, Spain
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, 37007 Salamanca, Spain
| | - L. Francisco Lorenzo-Martín
- Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, 37007 Salamanca, Spain
- Instituto de Biología Molecular y Celular del Cáncer de Salamanca, CSIC-University of Salamanca, 37007 Salamanca, Spain
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, 37007 Salamanca, Spain
| | - Víctor Quesada
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, 37007 Salamanca, Spain
- Departamento de Bioquímica y Biología Molecular, Universidad de Oviedo, 33006 Oviedo, Spain
| | - Arkaitz Carracedo
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, 37007 Salamanca, Spain
- Center for Cooperative Research in Biosciences (CIC-bioGUNE), Basque Research and Technology Alliance (BRTA), Bizkaia Technology Park, 48160 Derio, Spain
- Ikerbasque, Basque Foundation for Science, 48013 Bilbao, Spain
- Traslational Prostate Cancer Research Lab, CIC-bioGUNE, Biocruces Bizkaia Health Research Institute, 48903 Barakaldo, Spain
| | - Xosé R. Bustelo
- Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, 37007 Salamanca, Spain
- Instituto de Biología Molecular y Celular del Cáncer de Salamanca, CSIC-University of Salamanca, 37007 Salamanca, Spain
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, 37007 Salamanca, Spain
- Correspondence:
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Hu W, Shi Y, Han T, Liu C, Cao X, Shi G, Zhu W. A Panel of E2F Target Gene Signature Predicting the Prognosis of Hepatocellular Carcinoma. Front Genet 2022; 13:879299. [PMID: 35591857 PMCID: PMC9110819 DOI: 10.3389/fgene.2022.879299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Accepted: 04/18/2022] [Indexed: 11/21/2022] Open
Abstract
Hepatocellular carcinoma is one of the most malignant tumors, and the therapeutic effects of traditional treatments are poor. It is urgent to explore and identify new biomarkers and therapeutic targets to develop novel treatments which are individualized and effective. Three hallmarks, including E2F targets, G2M checkpoint and DNA repair, were collected by GSEA analysis. The panel of E2F-related gene signature consisted of five genes: HN1, KIF4A, CDCA3, CDCA8 and SSRP1. They had various mutation rates ranging from 0.8 to 5% in hepatocellular carcinoma, and patients with gene mutation had poorer prognosis. Among these genes, HN1 has the greatest mutation rate, and SSRP1 has the greatest impact on the model with a B (COX) value of 0.8842. Patients with higher expression of these genes had poorer prognosis. Kaplan-Meier curves in stratified survival analysis confirmed that patients with high risk scores had poor prognosis (p < 0.05). The results of univariate and multivariate COX survival analysis showed that risk score was closely related to the overall survival of patients with hepatocellular carcinoma. For clinical validation, we found that all the genes in the model were upregulated in hepatocellular carcinoma tissues compared to normal liver tissues, which was consistent with the previous results we obtained. Our study demonstrated that a panel of E2F target genes signature including five genes could predict the prognosis of hepatocellular carcinoma. This panel gene signature can facilitate the development of individualized and effective treatment for hepatocellular carcinoma.
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Affiliation(s)
- Wenmin Hu
- School of Medicine and Pharmacy, Ocean University of China, Department of Pulmonary and Critical Care Medicine, Qingdao Municipal Hospital, Qingdao, China
| | - Yongmei Shi
- Department of Gynecology, Qingdao Municipal Hospital, School of Medicine, Qingdao University, Qingdao, China
| | - Tongqin Han
- Department of General Practice, Qingdao Municipal Hospital, School of Medicine, Qingdao University, Qingdao, China
| | - Caiyun Liu
- Department of Hepatobiliary Surgery, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Xipeng Cao
- Clinical Research Center, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Guangjun Shi
- Department of Hepatobiliary Surgery, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
- *Correspondence: Guangjun Shi, ; Wenjing Zhu,
| | - Wenjing Zhu
- Clinical Research Center, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
- Respiratory Disease Key Laboratory of Qingdao, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
- *Correspondence: Guangjun Shi, ; Wenjing Zhu,
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