In 2013, The Cancer Genome Atlas (TCGA) Research Network found four novel prognostic subgroups of endometrial carcinoma: POLE/ultramutated (POLE), microsatellite-instable/hypermutated (MSI), copy-number-low/TP53-wild-type (CNL), and copy-number-highTP53-mutant (CNH). However, poor is known regarding uncommon histotypes of endometrial cancer. We aimed to assess the genetic profile of uterine carcinosarcoma (UCS) on the light of these findings. A systematic review and meta-analysis was performed through electronic databases searching (up to July 2019). All studies assessing UCS series for the TCGA classification were included. For each TCGA subgroup, pooled prevalence on the total UCS number was calculated. Four studies with 231 patients were included. Pooled prevalence of the TCGA subgroups were: 5.3% for the POLE subgroup, 7.3% for the MSI subgroup, 73.9% for the CNH subgroup, 13.5% for the CNL subgroup. The CNH subgroup predominates in UCS, while subgroups with high mutational load (POLE and MSI) are less common. UCS appears as a preferential evolution of CNH carcinomas.
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http://dx.doi.org/10.1007/s12253-020-00829-9 | DOI Listing |
Comput Methods Programs Biomed
January 2025
Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China; Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, 300070, China. Electronic address:
Background And Objective: Colorectal cancer (CRC) represents a heterogeneous malignancy that has concerned global burden of incidence and mortality. The traditional tumor-node-metastasis staging system has exhibited certain limitations. With the advancement of omics technologies, researchers are directing their focus on developing a more precise multi-omics molecular classification.
View Article and Find Full Text PDFCancer Cell Int
January 2025
Department of Infectious Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197, Ruijin 2nd Road, Shanghai, 20025, China.
Background: Methyltransferase-like (METTL) family protein plays a crucial role in the progression of malignancies. However, the function of METTL17 across pan-cancers, especially in hepatocellular carcinoma (HCC) is still poorly understood.
Methods: All original data were downloaded from TCGA, GTEx, HPA, UCSC databases and various data portals.
Cancer Med
January 2025
Department of Respiratory Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, People's Republic of China.
Background: Lung adenocarcinoma (LUAD) exhibits molecular heterogeneity, with mitochondrial damage affecting progression. The relationship between mitochondrial damage and immune infiltration, and Weighted Gene Co-expression Network Analysis (WGCNA)-derived biomarkers for LUAD classification and prognosis, remains unexplored.
Aims: The objective of our research is to identify gene modules closely related to the clinical stages of LUAD using the WGCNA method.
Bioinformatics
January 2025
Geneis Beijing Co., Ltd, Beijing 100102, China.
Motivation: The classification task based on whole-slide images (WSIs) is a classic problem in computational pathology. Multiple Instance Learning (MIL) provides a robust framework for analyzing whole slide images with slide-level labels at gigapixel resolution. However, existing MIL models typically focus on modeling the relationships between instances while neglecting the variability across the channel dimensions of instances, which prevents the model from fully capturing critical information in the channel dimension.
View Article and Find Full Text PDFCurr Res Transl Med
January 2025
Department of Hematology and Blood Banking, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran; Hematology-Oncology and Stem Cell Transplantation Research Center, Tehran University of Medical Sciences, Tehran, Iran. Electronic address:
Background: Stromal cells play a pivotal role in the tumor microenvironment (TME), significantly impacting the progression of acute myeloid leukemia (AML). This study sought to develop a stromal-related prognostic model for AML, aiming to uncover novel prognostic markers and therapeutic targets.
Methods: RNA expression data and clinical profiles of AML patients were retrieved from the Cancer Genome Atlas (TCGA).
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