Author:
Hu Gunchu,Li Jian,Zeng Yi,Liu Lixin,Yu Zhuowen,Qi Xiaoyan,Liu Kuijie,Yao Hongliang
Abstract
AbstractColon adenocarcinoma (COAD) is a serious public health problem, the third most common cancer and the second most deadly cancer in the world. About 9.4% of cancer-related deaths in 2020 were due to COAD. Anoikis is a specialized form of programmed cell death that plays an important role in tumor invasion and metastasis. The presence of anti-anoikis factors is associated with tumor aggressiveness and drug resistance. Various bioinformatic methods, such as differential expression analysis, and functional annotation analysis, machine learning, were used in this study. RNA-sequencing and clinical data from COAD patients were obtained from the Gene expression omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Construction of a prognostic nomogram for predicting overall survival (OS) using multivariate analysis and Lasso-Cox regression. Immunohistochemistry (IHC) was our method of validating the expression of seven genes that are linked to anoikis in COAD. We identified seven anoikis-related genes as predictors of COAD survival and prognosis, and confirmed their accuracy in predicting colon adenocarcinoma prognosis by KM survival curves and ROC curves. A seven-gene risk score consisting of NAT1, CDC25C, ATP2A3, MMP3, EEF1A2, PBK, and TIMP1 showed strong prognostic value. Meanwhile, we made a nomogram to predict the survival rate of COAD patients. The immune infiltration assay showed T cells. CD4 memory. Rest and macrophages. M0 has a higher proportion in COAD, and 11 genes related to tumor immunity are important. GDSC2-based drug susceptibility analysis showed that 6 out of 198 drugs were significant in COAD. Anoikis-related genes have potential value in predicting the prognosis of COAD and provide clues for developing new therapeutic strategies for COAD. Immune infiltration and drug susceptibility results provide important clues for finding new personalized treatment options for COAD. These findings also suggest possible mechanisms that may affect prognosis. These results are the starting point for planning individualized treatment and managing patient outcomes.
Publisher
Springer Science and Business Media LLC
Reference59 articles.
1. Feng, R. M., Zong, Y. N., Cao, S. M. & Xu, R. H. Current cancer situation in China: Good or bad news from the 2018 Global Cancer Statistics?. Cancer Commun. (Lond). 39(1), 22 (2019).
2. Hossain, M. S. et al. Colorectal cancer: A review of carcinogenesis, global epidemiology, current challenges, risk factors, preventive and treatment strategies. Cancers (Basel) 14(7), 1732 (2022).
3. Chen, W. et al. Cancer statistics in China, 2015. CA Cancer J. Clin. 66(2), 115–132 (2016).
4. Van Cutsem, E. et al. ESMO consensus guidelines for the management of patients with metastatic colorectal cancer. Ann. Oncol. 27(8), 1386–1422 (2016).
5. Han, H. J. et al. Fibronectin regulates anoikis resistance via cell aggregate formation. Cancer Lett. 508, 59–72 (2021).
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