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pmid:39029056

Prognostic analysis of anoikis-related genes in bladder cancer: An observational study.

Fu Huang · Liquan Zhou · Junjie Sun · Xihua Ma · Yongfeng Pei · Qiuwen Zhang · Yanqing Yu · Guining He · Lirong Zhu · Haibin Li · Xiaoming Wang · Fuzhi Long · Haipeng Huang · Jiange Zhang · Xuyong Sun

Medicine · 2024 doi:10.1097/MD.0000000000038999

Paper

complete

Experiment

partial

Data

partial

Analysis

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Execution

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Prognostic analysis of anoikis-related genes in bladder cancer: An observational study.
doi
10.1097/MD.0000000000038999
pmid
39029056
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[0]
Fu Huang
[1]
Liquan Zhou
[2]
Junjie Sun
[3]
Xihua Ma
[4]
Yongfeng Pei
[5]
Qiuwen Zhang
[6]
Yanqing Yu
[7]
Guining He
[8]
Lirong Zhu
[9]
Haibin Li
[10]
Xiaoming Wang
[11]
Fuzhi Long
[12]
Haipeng Huang
[13]
Jiange Zhang
[14]
Xuyong Sun
journal
Medicine
year
2024
abstract
Anoikis is proved to play a crucial role in the development of cancers. However, the impact of anoikis on the prognosis of bladder cancer (BLCA) is currently unknown. Thus, this study aimed to find potential effect of anoikis in BLCA. The Cancer Genome Atlas (TCGA)-BLCA and GSE13507 cohorts were downloaded from TCGA and the Gene Expression Omnibus (GEO) databases, respectively. Differentially expressed genes (DEGs) were screened between BLCA and normal groups, which intersected with anoikis-related genes to yield anoikis-related DEGs (AR DEGs). Univariate COX, rbsurv, and multivariate COX analyses were adopted in order to build a prognostic risk model. The differences of risk score in the different clinical subgroups and the relevance between survival rate and clinical characteristics were explored as well. Finally, chemotherapy drug sensitivity in different risk groups was analyzed. In total, 78 AR DEGs were acquired and a prognostic signature was build based on the 6 characteristic genes (CALR, FASN, CSPG4, HGF, INHBB, SATB1), where the patients of low-risk group had longer survival time. The survival rate of BLCA patients was significantly differential in different groups of age, stage, smoking history, pathologic-T, and pathologic-N. The IC50 of 56 drugs showed significant differences between 2 risk groups, such as imatinib, docetaxel, and dasatinib. At last, the results of real time quantitative-polymerase chain reaction (RT-qPCR) demonstrated that the expression trend of CALR, HGF, and INHBB was consistent with the result obtained previously based on public databases. Taken together, this study identified 6 anoikis-related characteristic genes (CALR, FASN, CSPG4, HGF, INHBB, SATB1) for the prognosis of BLCA patients, providing a scientific reference for further research on BLCA.
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Additionally, we also analyzed DEGs 2 between BLCA and normal groups in TCGA-BLCA dataset via “DEseq2” R package (version 1.36.0) with |log2FC| > 1 and adj P < .05.[12]
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Additionally, we also analyzed DEGs 2 between BLCA and normal groups in TCGA-BLCA dataset via “DEseq2” R package (version 1.36.0) with |log2FC| > 1 and adj P < .05.[12]
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In total, 78 AR DEGs were acquired and a prognostic signature was build based on the 6 characteristic genes (CALR, FASN, CSPG4, HGF, INHBB, SATB1), where the patients of low-risk group had longer survival time.
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In total, 78 AR DEGs were acquired and a prognostic signature was build based on the 6 characteristic genes (CALR, FASN, CSPG4, HGF, INHBB, SATB1), where the patients of low-risk group had longer survival time.
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In total, 78 AR DEGs were acquired and a prognostic signature was build based on the 6 characteristic genes (CALR, FASN, CSPG4, HGF, INHBB, SATB1), where the patients of low-risk group had longer survival time.
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Additionally, we also analyzed DEGs 2 between BLCA and normal groups in TCGA-BLCA dataset via “DEseq2” R package (version 1.36.0) with |log2FC| > 1 and adj P < .05.[12]
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However, the impact of anoikis on the prognosis of bladder cancer (BLCA) is currently unknown. Thus, this study aimed to find potential effect of anoikis in BLCA. The Cancer Genome Atlas (TCGA)-BLCA and GSE13507 cohorts were downloaded from TCGA and the Gene Expression Omnibus (GEO) databases, respectively. Differentially expressed genes (DEGs) were screened between BLCA and normal groups, which intersected with anoikis-related genes to yield anoikis-related DEGs (AR DEGs). Univariate COX, rbsurv, and multivariate COX analyses were adopted in order to build a prognostic risk model. The differences of risk score in the different clinical subgroups and the relevance between survival rate and clinical characteristics were explored as well. Finally, chemotherapy drug sensitivity in different risk groups was analyzed. In total, 78 AR DEGs were acquired and a prognostic signature was build based on the 6 characteristic genes (CALR, FASN, CSPG4, HGF, INHBB, SATB1), where the patients of low-risk group had longer survival time. The survival rate of BLCA patients was significantly differential in different groups of age, stage, smoking history, pathologic-T, and pathologic-N. The IC50 of 56 drugs showed significant differences between 2 risk groups, such as imatinib, docetaxel, and dasatinib. At last, the results of real time quantitative-polymerase chain reaction (RT-qPCR) demonstrated that the expression trend of CALR, HGF, and INHBB was consistent with the result obtained previously based on public databases. Taken together, this study identified 6 anoikis-related characteristic genes (CALR, FASN, CSPG4, HGF, INHBB, SATB1) for the prognosis of BLCA patients, providing a scientific reference for further research on BLCA.", "claims": [{"id": "claim-method", "statement": "Additionally, we also analyzed DEGs 2 between BLCA and normal groups in TCGA-BLCA dataset via “DEseq2” R package (version 1.36.0) with |log2FC| > 1 and adj P < .05.[12]", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39029056", "locator": "sections[4] \"2.2. 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