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Lung Cancer (Amsterdam, Netherlands) Jun 2024We aimed to reveal the clinicopathological differences between epidermal growth factor receptor (EGFR)-mutated and wild-type (WT) lung adenocarcinoma (LUAD) focusing on...
OBJECTIVES
We aimed to reveal the clinicopathological differences between epidermal growth factor receptor (EGFR)-mutated and wild-type (WT) lung adenocarcinoma (LUAD) focusing on the predominant subtype.
METHODS
This study included 352 with EGFR mutation and 370 with WT patients in consecutive stage I LUAD classified by the predominant subtype, and their clinicopathological characteristics and prognosis were analyzed. Using the Cancer Genome Atlas Program (TCGA) cohort, we analyzed differences in gene expression between EGFR mutation and WT groups. Furthermore, we performed immunohistochemical evaluations for 46 with EGFR mutation and 47 with WT patients in consecutive stage I papillary predominant adenocarcinoma (PPA).
RESULTS
Compared to the PPA with WT [n = 115], those with EGFR mutation [n = 99] exhibited smaller invasive size (p = 0.03) and less frequent vessel invasion (p < 0.01). However, PPA with EGFR mutation showed significantly worse 5-ys recurrence-free survival (RFS) rates compared to those with WT (70.6 % versus 83.3 %, p = 0.03). Contrarily, no significant differences were observed in other predominant subtypes. In the TCGA cohort, PPA with EGFR mutation tended to show higher expression of galectin-3, which is associated with tumor metastasis and resistance to anoikis, compared to those with WT (p = 0.06). Immunohistochemical evaluation revealed that galectin-3 expression was significantly higher in PPA with EGFR mutation than in those with WT (p < 0.01).
CONCLUSIONS
The prognosis of PPA with EGFR mutation proved to be less favorable compared to that with WT, and galectin-3 is highly expressed in EGFR-mutated PPA.
Topics: Humans; ErbB Receptors; Male; Female; Mutation; Lung Neoplasms; Adenocarcinoma of Lung; Aged; Middle Aged; Prognosis; Neoplasm Staging; Biomarkers, Tumor; Galectin 3; Aged, 80 and over; Adult; Adenocarcinoma, Papillary
PubMed: 38805901
DOI: 10.1016/j.lungcan.2024.107830 -
Heliyon May 2024Esophageal cancer (EC) is a prevalent malignancy with heterogeneous outcomes. This study explores the significance of anoikis-related long non-coding RNAs (lncRNAs) in...
BACKGROUND
Esophageal cancer (EC) is a prevalent malignancy with heterogeneous outcomes. This study explores the significance of anoikis-related long non-coding RNAs (lncRNAs) in EC, aiming to unravel their molecular roles and clinical implications.
METHODS
Transcriptome and clinical data were obtained from TCGA database for EC samples. We identified anoikis-related genes and lncRNAs by Pearson correlation analysis. The risk score model hinged on prognostic lncRNAs filtered from multiple steps. Risk scores were calculated using the derived formula, and categorized patients into low- and high-risk groups. Model robustness was assessed through Kaplan-Meier (KM) survival analysis and Receiver Operating Characteristic (ROC) curve, with clinical utility achieved via a constructed nomogram. We also explored the interplay between the risk score and immune cell infiltration, and investigated drug sensitivity.
RESULTS
We identified 2365 anoikis-related lncRNAs through co-expression analysis, including 1415 significant lncRNAs differentially expressed between normal and tumor samples. A risk score model was constructed from ten prognostic lncRNAs. The risk score model effectively stratified patients based on the median score, and its predictive capacity was validated through KM survival, ROC curve analyses, and the external GSE53622 dataset. The nomogram provided a practical tool for individualized prognosis evaluation. We unveiled significant correlations between specific immune cell subsets and the risk score. Eosinophils and common lymphoid progenitors exhibited positive associations, while endothelial cells and myeloid dendritic cells showed negative correlations. Drug sensitivity analysis revealed potential sensitive drugs for EC treatment that aligned with the risk subgroups.
CONCLUSION
This study established an anoikis-related lncRNAs risk score model that may predict the prognosis, immune infiltration, and drug sensitivity in EC, in hope of facilitating tailored patient management.
PubMed: 38803953
DOI: 10.1016/j.heliyon.2024.e31202 -
Cell Stress 2024Anoikis is a common programmed death for most of detached cells, but cancer cells can obtain anoikis resistance to facilitate their distant metastasis through the...
Anoikis is a common programmed death for most of detached cells, but cancer cells can obtain anoikis resistance to facilitate their distant metastasis through the circulation system. Researches have indicated that enhanced autophagic flux accounts for the survival of many cancer cells under detached conditions. Targeting ATG4B, the key factor of autophagy progress, can inhibit cancer metastasis , but ATG4B-deficient mice are susceptible to many serious diseases, which indicates the potential uncontrolled side effects of direct targeting of ATG4B. In our recent research, we confirmed that ATG4B is a novel RNA binding protein in the gastric cancer (GC) cell. It interacts with SPECC1 which consequently facilitates the liquid-liquid phase separation and ubiquitination of ATG4B. Additionally, the mA reader ELAVL1 inhibits the expression of SPECC1 to enhance the expression of ATG4B and anoikis resistance of GC cells. Further, we screened out an FDA-approved compound, lopinavir, to restore SPECC1 abundance and suppress GC metastasis. In conclusion, our research identified a novel signal pathway (ELAVL1-SPECC1-ATG4B-autophagy) to facilitate anoikis resistance and metastasis of GC cells and screened out a compound with clinical application potential to block this pathway, providing a novel strategy for the prevention of GC metastasis.
PubMed: 38803355
DOI: 10.15698/cst2024.05.296 -
Scientific Reports May 2024This study tackles the persistent prognostic and management challenges of clear cell renal cell carcinoma (ccRCC), despite advancements in multimodal therapies. Focusing...
This study tackles the persistent prognostic and management challenges of clear cell renal cell carcinoma (ccRCC), despite advancements in multimodal therapies. Focusing on anoikis, a critical form of programmed cell death in tumor progression and metastasis, we investigated its resistance in cancer evolution. Using single-cell RNA sequencing from seven ccRCC patients, we assessed the impact of anoikis-related genes (ARGs) and identified differentially expressed genes (DEGs) in Anoikis-related epithelial subclusters (ARESs). Additionally, six ccRCC RNA microarray datasets from the GEO database were analyzed for robust DEGs. A novel risk prognostic model was developed through LASSO and multivariate Cox regression, validated using BEST, ULCAN, and RT-PCR. The study included functional enrichment, immune infiltration analysis in the tumor microenvironment (TME), and drug sensitivity assessments, leading to a predictive nomogram integrating clinical parameters. Results highlighted dynamic ARG expression patterns and enhanced intercellular interactions in ARESs, with significant KEGG pathway enrichment in MYC + Epithelial subclusters indicating enhanced anoikis resistance. Additionally, all ARESs were identified in the spatial context, and their locational relationships were explored. Three key prognostic genes-TIMP1, PECAM1, and CDKN1A-were identified, with the high-risk group showing greater immune infiltration and anoikis resistance, linked to poorer prognosis. This study offers a novel ccRCC risk signature, providing innovative approaches for patient management, prognosis, and personalized treatment.
Topics: Humans; Carcinoma, Renal Cell; Anoikis; Kidney Neoplasms; Prognosis; Biomarkers, Tumor; Tumor Microenvironment; Gene Expression Regulation, Neoplastic; Epithelial Cells; Male; Female; Gene Expression Profiling; Nomograms
PubMed: 38802480
DOI: 10.1038/s41598-024-62978-0 -
Gene Oct 2024Pancreatic adenocarcinoma (PAAD) is one of the most malignant cancers. After escaping death, cancer cells are made more metastatic, aggressive, and also drug-resistant...
Pancreatic adenocarcinoma (PAAD) is one of the most malignant cancers. After escaping death, cancer cells are made more metastatic, aggressive, and also drug-resistant through anoikis resistance. The aim of this study is to explore the molecular mechanisms of anoikis-related genes in PAAD and to identify potential key biomarkers. We integrated information about PAAD from The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) databases and identified anoikis-related gene BCL2L1 by survival analysis, univariate Cox regression analysis, and multifactorial Cox regression analysis. Various bioinformatics approaches showed that BCL2L1 was a valuable prognostic marker that might be involved in PAAD development and progression through different mechanisms, including cancer intervention, genomic heterogeneity, and RNA modifications. Our analysis showed that BCL2L1 expression also closely correlates with the expression of various immune checkpoint inhibitors. In particular, we found that long non-coding RNA MIR4435-2HG acted as ceRNA sponging miR-513a-5p to promote the expression of BCL2L1, thereby promoting pancreatic cancer cells proliferation. In conclusion, BCL2L1 expression regulated by the MIR4435-2HG-miR-513a-5p-BCL2L1 ceRNA axis might be used as a biomarker for cancer prognosis, treatment selection, and follow-up in PAAD patients.
Topics: Humans; Pancreatic Neoplasms; RNA, Long Noncoding; MicroRNAs; Biomarkers, Tumor; Prognosis; bcl-X Protein; Gene Expression Regulation, Neoplastic; Adenocarcinoma; Cell Line, Tumor; Cell Proliferation; Male; RNA, Competitive Endogenous
PubMed: 38788819
DOI: 10.1016/j.gene.2024.148615 -
Archives of Dermatological Research May 2024Skin cutaneous melanoma (SKCM) is malignant cancer known for its high aggressiveness and unfavorable prognosis, particularly in advanced tumors. Anoikis is a specific...
Skin cutaneous melanoma (SKCM) is malignant cancer known for its high aggressiveness and unfavorable prognosis, particularly in advanced tumors. Anoikis is a specific pattern of programmed cell death associated with tumor regeneration, migration, and metastasis. Nevertheless, limited research has been conducted to investigate the function of anoikis in SKCM. Anoikis-related genes (ARGs) were extracted from Genecards to identify SKCM subtypes and to explore the immune microenvironment between the different subtypes. Prognostic models of SKCM were developed by LASSO COX regression analysis. Subsequently, the predictive value of risk scores in SKCM and the association with immunotherapy were further explored. Finally, the expression of 6 ARGs involved in the model construction was detected by immunohistochemistry and PCR. This study identified 20 ARGs significantly associated with SKCM prognosis and performed disease subtype analysis of samples based on these genes, different subtypes exhibited significantly different clinical features and tumor immune microenvironment (TIME) landscapes. The risk score prognostic model was generated by further screening and identification of the six ARGs. The model exhibited a high degree of sensitivity and specificity to predict the prognosis of individuals with SKCM. These high- and low-risk populations showed different immune statuses and drug sensitivity. Further immunohistochemical and PCR experiments identified significant differential expression of the six ARGs in tumor and normal samples. Anoikis-based features may serve as novel prognostic biomarkers for SKCM and may provide important new insights for survival prediction and individualized treatment development.
Topics: Humans; Melanoma; Anoikis; Skin Neoplasms; Biomarkers, Tumor; Tumor Microenvironment; Prognosis; Immunotherapy; Female; Male; Melanoma, Cutaneous Malignant; Middle Aged; Gene Expression Regulation, Neoplastic
PubMed: 38787413
DOI: 10.1007/s00403-024-03085-y -
Cancer Medicine May 2024Tumors that resist anoikis, a programmed cell death triggered by detachment from the extracellular matrix, promote metastasis; however, the role of anoikis-related genes...
Identification of the molecular subtypes and signatures to predict the prognosis, biological functions, and therapeutic response based on the anoikis-related genes in colorectal cancer.
BACKGROUND
Tumors that resist anoikis, a programmed cell death triggered by detachment from the extracellular matrix, promote metastasis; however, the role of anoikis-related genes (ARGs) in colorectal cancer (CRC) stratification, prognosis, and biological functions remains unclear.
METHODS
We obtained transcriptomic profiles of CRC and 27 ARGs from The Cancer Genome Atlas, the Gene Expression Omnibus, and MSigDB databases, respectively. CRC tissue samples were classified into two clusters based on the expression pattern of ARGs, and their functional differences were explored. Hub genes were screened using weighted gene co-expression network analysis, univariate analysis, and least absolute selection and shrinkage operator analysis, and validated in cell lines, tissues, or the Human Protein Atlas database. We constructed an ARG-risk model and nomogram to predict prognosis in patients with CRC, which was validated using an external cohort. Multifaceted landscapes, including stemness, tumor microenvironment (TME), immune landscape, and drug sensitivity, between high- and low-risk groups were examined.
RESULTS
Patients with CRC were divided into C1 and C2 clusters. Cluster C1 exhibited higher TME scores, whereas cluster C2 had favorable outcomes and a higher stemness index. Eight upregulated hub ARGs (TIMP1, P3H1, SPP1, HAMP, IFI30, ADAM8, ITGAX, and APOC1) were utilized to construct the risk model. The qRT-PCR, Western blotting, and immunohistochemistry results were consistent with those of the bioinformatics analysis. Patients with high risk exhibited worse overall survival (p < 0.01), increased stemness, TME, immune checkpoint expression, immune infiltration, tumor mutation burden, and drug susceptibility compared with the patients with low risk.
CONCLUSION
Our results offer a novel CRC stratification based on ARGs and a risk-scoring system that could predict the prognosis, stemness, TME, immunophenotypes, and drug susceptibility of patients with CRC, thereby improving their prognosis. This stratification may facilitate personalized therapies.
Topics: Humans; Colorectal Neoplasms; Anoikis; Prognosis; Tumor Microenvironment; Gene Expression Regulation, Neoplastic; Male; Biomarkers, Tumor; Nomograms; Female; Transcriptome; Gene Expression Profiling
PubMed: 38785271
DOI: 10.1002/cam4.7315 -
Frontiers in Immunology 2024The effect of anoikis-related genes (ARGs) on clinicopathological characteristics and tumor microenvironment remains unclear. We comprehensively analyzed...
The effect of anoikis-related genes (ARGs) on clinicopathological characteristics and tumor microenvironment remains unclear. We comprehensively analyzed anoikis-associated gene signatures of 1057 colorectal cancer (CRC) samples based on 18 ARGs. Anoikis-related molecular subtypes and gene features were identified through consensus clustering analysis. The biological functions and immune cell infiltration were assessed using the GSVA and ssGSEA algorithms. Prognostic risk score was constructed using multivariate Cox regression analysis. The immunological features of high-risk and low-risk groups were compared. Finally, DAPK2-overexpressing plasmid was transfected to measure its effect on tumor proliferation and metastasis and . We identified 18 prognostic ARGs. Three different subtypes of anoikis were identified and demonstrated to be linked to distinct biological processes and prognosis. Then, a risk score model was constructed and identified as an independent prognostic factor. Compared to the high-risk group, patients in the low-risk group exhibited longer survival, higher enrichment of checkpoint function, increased expression of CTLA4 and PD-L1, higher IPS scores, and a higher proportion of MSI-H. The results of RT-PCR indicated that the expression of DAPK2 mRNA was significantly downregulated in CRC tissues compared to normal tissues. Increased DAPK2 expression significantly suppressed cell proliferation, promoted apoptosis, and inhibited migration and invasion. The nude mice xenograft tumor model confirmed that high expression of DAPK2 inhibited tumor growth. Collectively, we discovered an innovative anoikis-related gene signature associated with prognosis and TME. Besides, our study indicated that DAPK2 can serve as a promising therapeutic target for inhibiting the growth and metastasis of CRC.
Topics: Humans; Colorectal Neoplasms; Tumor Microenvironment; Anoikis; Animals; Prognosis; Mice; Immunotherapy; Female; Male; Gene Expression Regulation, Neoplastic; Death-Associated Protein Kinases; Cell Line, Tumor; Biomarkers, Tumor; Mice, Nude; Transcriptome; Gene Expression Profiling; Xenograft Model Antitumor Assays; Middle Aged; Cell Proliferation; Mice, Inbred BALB C
PubMed: 38779664
DOI: 10.3389/fimmu.2024.1378305 -
Advances in Wound Care May 2024Anoikis, a kind of programmed cell death that is triggered when cells lose contact with each other or with the matrix. However, the potential value of anoikis-related...
OBJECTIVE
Anoikis, a kind of programmed cell death that is triggered when cells lose contact with each other or with the matrix. However, the potential value of anoikis-related genes (ARGs) in keloid (KD) has not been investigated.
APPROACH
We downloaded three keloid fibroblast (KF) RNA-seq datasets from the GEO and obtained 338 ARGs from a search of the GeneCards database and PubMed articles. WGCNA was used to construct the coexpression network, and obtain the KF-related ARGs. The LASSO-Cox method was used to screen the hub ARGs and construct the best prediction model. Then, GEO single cell sequencing datasets were used to verify the expression of hub genes. We used whole RNA sequencing for gene-level validation, and the correlation between KD immune infiltration and anoikis.
RESULTS
Our study comprehensively analyzed the role of ARGs in KD for the first time. LASSO regression analysis identified six hub ARGs (HIF1A, SEMA7A, SESN1, CASP3, LAMA3 and SIK2). A large number of miRNAs participate in the regulation of hub ARGs. In addition, correlation analysis revealed that ARGs were significantly correlated with the infiltration levels of multiple immune cells in KD patients. Innovation We explored the expression characteristics of ARGs in KD, which is extremely important for determining the molecular pathways and mechanisms underlying KD.
CONCLUSIONS
This study provides a useful reference for revealing the characteristics of ARGs in the pathogenesis of KD. The identified hub genes may provide potential therapeutic targets for patients. This study provides new ideas for individualized therapy and immunotherapy.
PubMed: 38775414
DOI: 10.1089/wound.2024.0027 -
Scientific Reports May 2024Colorectal cancer (CRC) is a malignant tumor originating from epithelial cells of the colon or rectum, and its invasion and metastasis could be regulated by anoikis....
Colorectal cancer (CRC) is a malignant tumor originating from epithelial cells of the colon or rectum, and its invasion and metastasis could be regulated by anoikis. However, the key genes and pathways regulating anoikis in CRC are still unclear and require further research. The single cell transcriptome dataset GSE221575 of GEO database was downloaded and applied to cell subpopulation type identification, intercellular communication, pseudo time cell trajectory analysis, and receptor ligand expression analysis of CRC. Meanwhile, the RNA transcriptome dataset of TCGA, the GSE39582, GSE17536, and GSE17537 datasets of GEO were downloaded and merged into one bulk transcriptome dataset. The differentially expressed genes (DEGs) related to anoikis were extracted from these data sets, and key marker genes were obtained after feature selection. A clinical prognosis prediction model was constructed based on the marker genes and the predictive effect was analyzed. Subsequently, gene pathway analysis, immune infiltration analysis, immunosuppressive point analysis, drug sensitivity analysis, and immunotherapy efficacy based on the key marker genes were conducted for the model. In this study, we used single cell datasets to determine the anoikis activity of cells and analyzed the DEGs of cells based on the score to identify the genes involved in anoikis and extracted DEGs related to the disease from the transcriptome dataset. After dimensionality reduction selection, 7 marker genes were obtained, including TIMP1, VEGFA, MYC, MSLN, EPHA2, ABHD2, and CD24. The prognostic risk model scoring system built by these 7 genes, along with patient clinical data (age, tumor stage, grade), were incorporated to create a nomogram, which predicted the 1-, 3-, and 5-years survival of CRC with accuracy of 0.818, 0.821, and 0.824. By using the scoring system, the CRC samples were divided into high/low anoikis-related prognosis risk groups, there are significant differences in immune infiltration, distribution of immune checkpoints, sensitivity to chemotherapy drugs, and efficacy of immunotherapy between these two risk groups. Anoikis genes participate in the differentiation of colorectal cancer tumor cells, promote tumor development, and could predict the prognosis of colorectal cancer.
Topics: Humans; Colorectal Neoplasms; Anoikis; Prognosis; Gene Expression Regulation, Neoplastic; Cell Differentiation; Transcriptome; Biomarkers, Tumor; Gene Expression Profiling; Female
PubMed: 38773226
DOI: 10.1038/s41598-024-62370-y