Identification of Anoikis-Related Subgroups and Prognosis Model in Liver Hepatocellular Carcinoma

Abstract

Resistance to anoikis is a key characteristic of many cancer cells, promoting cell survival. However, the mechanism of anoikis in hepatocellular carcinoma (HCC) remains unknown. In this study, we applied differentially expressed overlapping anoikis-related genes to classify The Cancer Genome Atlas (TCGA) samples using an unsupervised cluster algorithm. Then, we employed weighted gene coexpression network analysis (WGCNA) to identify highly correlated genes and constructed a prognostic risk model based on univariate Cox proportional hazards regression. This model was validated using external datasets from the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO). Finally, we used a CIBERSORT algorithm to investigate the correlation between risk score and immune infiltration. Our results showed that the TCGA cohorts could be divided into two subgroups, with subgroup A having a lower survival probability. Five genes (BAK1, SPP1, BSG, PBK and DAP3) were identified as anoikis-related prognostic genes. Moreover, the prognostic risk model effectively predicted overall survival, which was validated using ICGC and GEO datasets. In addition, there was a strong correlation between infiltrating immune cells and prognostic genes and risk score. In conclusion, we identified anoikis-related subgroups and prognostic genes in HCC, which could be significant for understanding the molecular mechanisms and treatment of HCC.

Comprehensive analysis of anoikis‐related lncRNAs for predicting prognosis and response of immunotherapy in hepatocellular carcinoma

“…For instance, Chen et al developed an innovative signature consisting of three anoikis-related genes (EZH2, KIF18A and NQO1), which demonstrated the ability to predict prognosis and provide valuable insights into personalised treatment strategies for HCC patients [39]. Furthermore, another study identified a prognostic signature based on anoikis-related genes that exhibited significant efficacy in predicting OS and may contribute to a better understanding of the molecular mechanisms and treatment options for HCC [28]. However, it is important to note that there is currently limited research on the development of prognostic models utilising anoikis-related lncRNAs specifically in the context of HCC.…”

Comprehensive analysis of diverse programmed cell death patterns in the prognosis, tumor microenvironment and drug sensitivity in hepatocellular carcinoma

“…Most of these genes, except for DEDD and IL33, had also been included in different prognostic models of LIHC in previous studies. [35][36][37][38][39][40][41][42][43] The protein DEDD (death effector domain-containing protein) has been implicated in numerous physiological processes, including apoptosis. [44] Recent studies have suggested that DEDD could potentially serve as a valuable prognostic marker and therapeutic target for the treatment of cancer metastasis.…”

Unveiling Anoikis‐related genes: A breakthrough in the prognosis of bladder cancer

“…Anoikis occurs when the cell detaches from the correct extracellular matrix, interrupting integrin ligation 9 . Many cancer cells are resistant to Anoikis, which promotes survival 10 . Recent researches indicated that Anoikis resistance played crucial role in the metastasis and progression of bladder cancer 11 .…”

“…9 Many cancer cells are resistant to Anoikis, which promotes survival. 10 Recent researches indicated that Anoikis resistance played crucial role in the metastasis and progression of bladder cancer. 11 However, the molecular mechanism of Anoikis-associated genes remains unclear in BLCA.…”