Robotics & Machine Learning Daily News2024,Issue(Feb.14) :13-14.DOI:10.1002/jgm.3651

Jilin Cancer Hospital Reports Findings in Bladder Cancer (Unveiling Anoikis-related genes: A breakthrough in the prognosis of bladder cancer)

Robotics & Machine Learning Daily News2024,Issue(Feb.14) :13-14.DOI:10.1002/jgm.3651

Jilin Cancer Hospital Reports Findings in Bladder Cancer (Unveiling Anoikis-related genes: A breakthrough in the prognosis of bladder cancer)

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Abstract

New research on Oncology - Bladder Cancer is the subject of a report. According to news reporting originating in Jilin, People’s Republic of China, by NewsRx journalists, research stated, “Bladder cancer (BLCA) is a prevalent malignancy worldwide. Anoikis remains a new form of cell death.” The news reporters obtained a quote from the research from Jilin Cancer Hospital, “It is necessary to explore Anoikis-related genes in the prognosis of BLCA. We obtained RNA expression profiles from the The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases for dimensionality reduction analysis and isolated epithelial cells, T cells and fibroblasts for copy number variation analysis, pseudotime analysis and transcription factor analysis based on R package. We integrated machine-learning algorithms to develop the artificial intelligence-derived prognostic signature (AIDPS). The performance of AIDPS validation dataset compared to other models. Mendelian randomization analysis was conducted. Single nucleotide polymorphism (SNP) sites of rs3100578 (HK2) and rs66467677 (HSP90B1) exhibited significant correlation of bladder problem (not cancer) and bladder cancer, whereasSNP sites of rs3100578 (HK2) and rs947939 (BAD) had correlation between bladder stone and bladder cancer. The immune infiltration analysis of the TCGA-BLCA cohort was calculated via the ESTIMATE (i.e. Estimation of STromal and Immune cells in MAlignantTumours using Expression data) algorithm which contains stromal, immune and estimate scores. We also found significant differences in the IC values of Bortezomib_1191, Docetaxel_1007, Staurosporine_1034 and Rapamycin_1084 among the high- and low-risk groups.”

Key words

Jilin/People’s Republic of China/Asia/Bladder Cancer/Cancer/Cyborgs/Emerging Technologies/Gene Therapy/Genetics/Health and Medicine/Machine Learning/Oncology

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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