Integrative analysis of anoikis-related genes prognostic signature with immunotherapy and identification of CDKN3 as a key oncogene in lung adenocarcinoma.

Anoikis, a form of programmed cell death induced by loss of cell contact, is closely associated with tumor invasion and metastasis, making it highly significant in lung cancer research. We examined the expression patterns and prognostic relevance of Anoikis-related genes (ARGs) in lung adenocarcinoma (LUAD) using the TCGA-LUAD database. This study identified molecular subtypes associated with Anoikis in LUAD and conducted functional enrichment analyses. We constructed an ARG risk score using univariate least absolute shrinkage and selection operator (LASSO) Cox regression, validated externally with GEO datasets and clinical samples. The clinical applicability of the prognostic model was evaluated using nomograms, calibration curves, decision curve analysis (DCA), and time-dependent AUC assessments. We identified four prognostically significant genes (PLK1, SLC2A1, CDKN3, PHLDA2) and two ARG-related molecular subtypes. ARGs were generally upregulated in LUAD and correlated with multiple pathways including the cell cycle and DNA replication. The prognostic model indicated that the low-risk group had better outcomes and significant correlations with clinicopathological features, tumor microenvironment, immune therapy responses, drug sensitivity, and pan-RNA epigenetic modification-related genes. Patients with low-risk LUAD were potential beneficiaries of immune checkpoint inhibitor (ICI) therapy. Prognostic ARGs' distribution and expression across various immune cell types were further analyzed using single-cell RNA sequencing. The pivotal role of CDKN3 in LUAD was confirmed through qRT-PCR and gene knockout experiments, demonstrating that CDKN3 knockdown inhibits tumor cell proliferation, migration, and invasion. Additionally, we constructed a ceRNA network involving CDKN3/hsa-miR-26a-5p/SNHG6, LINC00665, DUXAP8, and SLC2A1/hsa-miR-218-5p/RNASEH1-AS1, providing new insights for personalized and immune therapy decisions in LUAD patients.

Qin H ，Wang Q ，Xu J ，Zeng H ，Liu J ，Yu F ，Yang J ... -  《-》

Integrated single-cell and bulk RNA-Seq analysis enhances prognostic accuracy of PD-1/PD-L1 immunotherapy response in lung adenocarcinoma through necroptotic anoikis gene signatures.

In addition to presenting significant diagnostic and treatment challenges, lung adenocarcinoma (LUAD) is the most common form of lung cancer. Using scRNA-Seq and bulk RNA-Seq data, we identify three genes referred to as HMR, FAM83A, and KRT6A these genes are related to necroptotic anoikis-related gene expression. Initial validation, conducted on the GSE50081 dataset, demonstrated the model's ability to categorize LUAD patients into high-risk and low-risk groups with significant survival differences. This model was further applied to predict responses to PD-1/PD-L1 blockade therapies, utilizing the IMvigor210 and GSE78220 cohorts, and showed strong correlation with patient outcomes, highlighting its potential in personalized immunotherapy. Further, LUAD cell lines were analyzed using quantitative PCR (qPCR) and Western blot analysis to confirm their expression levels, further corroborating the model's relevance in LUAD pathophysiology. The mutation landscape of these genes was also explored, revealing their broad implication in various cancer types through a pan-cancer analysis. The study also delved into molecular subclustering, revealing distinct expression profiles and associations with different survival outcomes, emphasizing the model's utility in precision oncology. Moreover, the diversity of immune cell infiltration, analyzed in relation to the necroptotic anoikis signature, suggested significant implications for immune evasion mechanisms in LUAD. While the findings present a promising stride towards personalized LUAD treatment, especially in immunotherapy, limitations such as the retrospective nature of the datasets and the need for larger sample sizes are acknowledged. Prospective clinical trials and further experimental research are essential to validate these findings and enhance the clinical applicability of our prognostic model.

Sui P ，Liu X ，Zhong C ，Sha Z ... -  《Scientific Reports》

Anoikis-related gene signatures can aid prognosis of lung adenocarcinoma.

Mo G ，Long X ，Hu Z ，Tang Y ，Zhou Z ... -  《Advances in Clinical and Experimental Medicine》

Development of the prognostic value in lung adenocarcinoma based on anoikis-related genes and initial experimental validation.

Lung adenocarcinoma (LUAD) is a highly aggressive cancer in advanced stages and has the highest cancer-related death across the world. Anoikis has emerged as a specific form of apoptotic cell death that may play a vital role in the formation and development of tumors. Based on The Cancer Genome Atlas dataset, we developed a novel anoikis-related genes (ARGs) signature in LUAD and evaluated the differences between low and high-risk groups in clinical characteristics, expression patterns, immune cell infiltration, and drug sensitivity, etc. According to multivariate Cox regression analysis, the risk score was identified as a significant independent prognostic factor. The possible biological pathways of ARGs' were assessed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. The immune infiltration landscape and risk score of ARGs were analyzed by ESTIMATE and CIBERSORT analysis. A nomogram grounded on six key ARGs and clinicopathological features was provided. Moreover, experiment validation of the expression patterns of six hub ARGs in lung cancer cell lines was conducted. We identified 53 survival-related LUAD anoikis-related differentially expressed genes and finally six hub anoikis genes (LDHA, SLC2A1, SERPINB5, ITGB4, BRCA2, and PIK3R1) were selected to construct an ARG model. The risk model could efficiently cluster the patients into low- and high-risk groups which could accurately predict clinical outcomes for LUAD patients. There is evidence that the prognostic risk score is a remarkable prognostic factor in determining overall survival. Different immune statuses and drug sensitivity between low- and high-risk groups were explored according to functional analysis. On the basis of risk scores and LUAD clinicopathological features, a novel nomogram was developed. Ultimately, all six key genes except for PIK3R1 were proved to be upregulated in LUAD tissues and cell lines by bioinformatics analysis and experimental validation. The result of the present study suggest that ARGs could be carcinogenic to LUAD and could be used as an effective stratification factor to customize therapies and forecast the survival rate in LUAD patients.

Guo W ，Zhao G ，Liu S ，Deng T ，Zhang G ，Zhang B ... -  《-》

Identification of crucial anoikis-related genes as novel biomarkers and potential therapeutic targets for lung adenocarcinoma via bioinformatic analysis and experimental verification.

Wu J ，Zhang Y ，You G ，Guo W ，Wang Y ，Li J ，Tan R ，Fu X ，Tang Y ，Zan J ，Su J ... -  《Aging-US》