ArticleMolecular carcinogenesis2020
Comprehensive analysis of somatic copy number alterations in clear cell renal cell carcinoma.
Article in Molecular carcinogenesis, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 10 citations in OpenAlex.
- Genetic Testing and Counselling for Hereditary Renal Carcinoma: What Do Clinicians Need to Know?European urology open science · 2025Review
- Radiomics predicts the prognosis of patients with clear cell renal cell carcinoma by reflecting the tumor heterogeneity and microenvironment.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- Review
- Cribriform-type adenocarcinoma of the colorectum: comprehensive molecular analyses of a distinctive histologic subtype of colorectal cancer.Carcinogenesis · 2022Article
- Integrated Multi-Omics Analysis Identified PTPRG and CHL1 as Key Regulators of Immunophenotypes in Clear Cell Renal Cell Carcinoma(ccRCC).Frontiers in oncology · 2022Article
- Analysis of somatic copy number alterations in biliary tract carcinoma using a single nucleotide polymorphism array.Future science OA · 2022Article
- A genome-wide analysis of the molecular alterations occurring in the adenomatous and carcinomatous components of the same tumor based on the adenoma-carcinoma sequence.Pathology international · 2021Article
- A genome-wide study of the relationship between chromosomal abnormalities and gene expression in colorectal tumors.Genes, chromosomes & cancer · 2021Article
- Comprehensive analysis of somatic copy number alterations in clear cell renal cell carcinoma.Molecular carcinogenesis · 2020Article
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Somatic copy number alterations (SCNAs) are important biological characteristics that can identify genome-wide alterations in renal cell carcinoma (RCC). Recent studies have shown that SCNAs have potential value for determining the prognosis of RCC. We examined SCNAs using the Affymetrix platform to analyze samples from 59 patients with clear cell RCCs (ccRCCs) including first cohort (30 cases) and second cohort (validation cohort, 29 cases). We stratified SCNAs in the ccRCCs using a hierarchical cluster analysis based on SCNA types, including gain, loss of heterozygosity (LOH), copy neutral LOH, mosaic, and mixed types. In this way, the examined two cohorts were categorized into two subgroups (1 and 2). Although the frequency of mixed type was higher in subgroup 1 than in subgroup 2 in the two cohorts, the association did not reach statistical significance. There was a significant difference in the frequency of metachronous metastasis between subgroups 1 and 2 (subgroup 2 > 1). In addition, subgroup 2 was retained in multivariate analysis of both cohorts. We examined whether there were specific alleles differing between subgroups 1 and 2 in both cohorts. We found that there was indeed a statistically significant difference in the 3p mixed types. Among the 3p mixed type, we found that 3p24.3 mixed type was inversely correlated with the presence of metachronous metastasis in ccRCC. The association was also retained in multivariate analysis in second cohort. We suggest that the 3p24.3 mixed type may be a novel marker to predict a favorable prognosis in ccRCC.
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