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PeerJ 2023Breast cancer (BRCA) is the most diagnosed cancer worldwide and is responsible for the highest cancer-associated mortality among women. It is evident that anoikis...
Breast cancer (BRCA) is the most diagnosed cancer worldwide and is responsible for the highest cancer-associated mortality among women. It is evident that anoikis resistance contributes to tumour cell metastasis, and this is the primary cause of treatment failure for BRCA. However, anoikis-related gene (ARG) expression profiles and their prognostic value in BRCA remain unclear. In this study, a prognostic model of ARGs based on The Cancer Genome Atlas (TCGA) database was established using a least absolute shrinkage and selection operator analysis to evaluate the prognostic value of ARGs in BRCA. The risk factor graph demonstrated that the low-risk group had longer survival than the high-risk group, implying that the prognostic model had a good performance. We identified 11 ARGs that exhibited differential expression between the two risk groups in TCGA and Gene Expression Omnibus databases. Through Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes enrichment analyses, we revealed that the screened ARGs were associated with tumour progression and metastasis. In addition, a protein-protein interaction network showed potential interactions among these ARGs. Furthermore, gene set enrichment analysis suggested that the Notch and Wnt signalling pathways were overexpressed in the high-risk group, and gene set variation analysis revealed that 38 hallmark genes differed between the two groups. Moreover, Kaplan-Meier survival curves and receiver operating characteristic curves were used to identify five ARGs (CD24, KRT15, MIA, NDRG1, TP63), and quantitative polymerase chain reaction was employed to assess the differential expression of these ARGs. Univariate and multivariate Cox regression analyses were then performed for the key ARGs, with the best prediction of 3 year survival. In conclusion, ARGs might play a crucial role in tumour progression and serve as indicators of prognosis in BRCA.
Topics: Female; Humans; Breast Neoplasms; Prognosis; Anoikis; Genes, Regulator; Databases, Factual
PubMed: 37842046
DOI: 10.7717/peerj.15475 -
Drug Resistance Updates : Reviews and... Jul 2024Anoikis, known as matrix detachment-induced apoptosis or detachment-induced cell death, is crucial for tissue development and homeostasis. Cancer cells develop means to... (Review)
Review
Anoikis, known as matrix detachment-induced apoptosis or detachment-induced cell death, is crucial for tissue development and homeostasis. Cancer cells develop means to evade anoikis, e.g. anoikis resistance, thereby allowing for cells to survive under anchorage-independent conditions. Uncovering the mechanisms of anoikis resistance will provide details about cancer metastasis, and potential strategies against cancer cell dissemination and metastasis. Here, we summarize the principal elements and core molecular mechanisms of anoikis and anoikis resistance. We discuss the latest progress of how anoikis and anoikis resistance are regulated in cancers. Furthermore, we summarize emerging data on selective compounds and nanomedicines, explaining how inhibiting anoikis resistance can serve as a meaningful treatment modality against cancers. Finally, we discuss the key limitations of this therapeutic paradigm and possible strategies to overcome them. In this review, we suggest that pharmacological modulation of anoikis and anoikis resistance by bioactive compounds could surmount anoikis resistance, highlighting a promising therapeutic regimen that could be used to overcome anoikis resistance in cancers.
Topics: Anoikis; Humans; Neoplasms; Antineoplastic Agents; Animals; Drug Resistance, Neoplasm; Neoplasm Metastasis
PubMed: 38850692
DOI: 10.1016/j.drup.2024.101099 -
Frontiers in Genetics 2023Polycythemia Vera (PV) is a type of typical Myeloproliferative Neoplasms (MPNs) characterized with excessive erythropoiesis and thrombosis. Anoikis is a special...
Polycythemia Vera (PV) is a type of typical Myeloproliferative Neoplasms (MPNs) characterized with excessive erythropoiesis and thrombosis. Anoikis is a special programmed cell death mode induced by the adhesion disorder between cells and extracellular matrix (ECM) or adjacent cells facilitating cancer metastasis. However, few studies have focused on the role of anoikis in PV, especially on the development of PV. The microarray and RNA-seq results were screened from the Gene Expression Omnibus (GEO) database and the anoikis-related genes (ARGs) were downloaded from Genecards. The functional enrichment analysis of intersecting differentially expressed genes (DEGs) and protein-protein interaction (PPI) network analysis were performed to discover hub genes. The hub genes expression was tested in the training (GSE136335) and validation cohort (GSE145802), and RT-qPCR was performed to verify the gene expression in PV mice. In the training GSE136335, a total of 1,195 DEGs was obtained from Myeloproliferative Neoplasm (MPN) patients compared with controls, among which 58 were anoikis-related DEGs. The significant enrichment of the apoptosis and cell adhesion pathways (i.e., cadherin binding) were shown in functional enrichment analysis. The PPI network was conducted to identify top five hub genes (CASP3, CYCS, HIF1A, IL1B, MCL1). The expression of CASP3 and IL1B were significantly upregulated both in validation cohort and PV mice and downregulated after treatment, suggesting that CASP3 and IL1B could be important indicators for disease surveillance. Our research revealed a relationship between anoikis and PV for the first time by combined analysis of gene level, protein interaction and functional enrichment, allowing novel insights into mechanisms of PV. Moreover, CASP3 and IL1B may become promising indicators of PV development and treatment.
PubMed: 36873934
DOI: 10.3389/fgene.2023.1139351 -
Frontiers in Immunology 2023Anoikis resistance is recognized as a crucial step in the metastasis of cancer cells. Most epithelial tumors are distinguished by the ability of epithelial cells to...
BACKGROUND
Anoikis resistance is recognized as a crucial step in the metastasis of cancer cells. Most epithelial tumors are distinguished by the ability of epithelial cells to abscond anoikis when detached from the extracellular matrix. However, no study has investigated the involvement of anoikis in the small airway epithelium (SAE) of chronic obstructive pulmonary disease (COPD).
METHODS
Anoikis-related genes (ANRGs) exhibiting differential expression in COPD were identified using microarray datasets obtained from the Gene Expression Omnibus (GEO) database. Unsupervised clustering was performed to classify COPD patients into anoikis-related subtypes. Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA) were used to annotate the functions between different subtypes. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were leveraged to identify key molecules. The relative proportion of infiltrating immune cells in the SAE was quantified using the CIBERSORT and ssGSEA computational algorithms, and the correlation between key molecules and immune cell abundance was analyzed. The expression of key molecules in BEAS-2B cells exposed to cigarette smoke extract (CSE) was validated using qRT-PCR.
RESULTS
A total of 25 ANRGs exhibited differential expression in the SAE of COPD patients, based on which two subtypes of COPD patients with distinct anoikis patterns were identified. COPD patients with anoikis resistance had more advanced GOLD stages and cigarette consumption. Functional annotations revealed a different immune status between COPD patients with pro-anoikis and anoikis resistance. Tenomodulin (TNMD) and long intergenic non-protein coding RNA 656 (LINC00656) were subsequently identified as key molecules involved in this process, and a close correlation between TNMD and the infiltrating immune cells was observed, such as activated CD4 memory T cells, M1 macrophages, and activated NK cells. Further enrichment analyses clarified the relationship between TNMD and the inflammatory and apoptotic signaling pathway as the potential mechanism for regulating anoikis. experiments showed a dramatic upregulation of TNMD and LINC00656 in BEAS-2B cells when exposed to 3% CSE for 48 hours.
CONCLUSION
TNMD contributes to the progression of COPD by inducing anoikis resistance in SAE, which is intimately associated with the immune microenvironment.
Topics: Humans; Anoikis; Pulmonary Disease, Chronic Obstructive; Epithelium; Epithelial Cells; Signal Transduction
PubMed: 37090717
DOI: 10.3389/fimmu.2023.1155478 -
Frontiers in Oncology 2023Hepatocellular carcinoma (HCC) is a global health burden with poor prognosis. Anoikis, a novel programmed cell death, has a close interaction with metastasis and...
BACKGROUND
Hepatocellular carcinoma (HCC) is a global health burden with poor prognosis. Anoikis, a novel programmed cell death, has a close interaction with metastasis and progression of cancer. In this study, we aimed to construct a novel bioinformatics model for evaluating the prognosis of HCC based on anoikis-related gene signatures as well as exploring the potential mechanisms.
MATERIALS AND METHODS
We downloaded the RNA expression profiles and clinical data of liver hepatocellular carcinoma from TCGA database, ICGC database and GEO database. DEG analysis was performed using TCGA and verified in the GEO database. The anoikis-related risk score was developed univariate Cox regression, LASSO Cox regression and multivariate Cox regression, which was then used to categorize patients into high- and low-risk groups. Then GO and KEGG enrichment analyses were performed to investigate the function between the two groups. CIBERSORT was used for determining the fractions of 22 immune cell types, while the ssGSEA analyses was used to estimate the differential immune cell infiltrations and related pathways. The "pRRophetic" R package was applied to predict the sensitivity of administering chemotherapeutic and targeted drugs.
RESULTS
A total of 49 anoikis-related DEGs in HCC were detected and 3 genes (EZH2, KIF18A and NQO1) were selected out to build a prognostic model. Furthermore, GO and KEGG functional enrichment analyses indicated that the difference in overall survival between risk groups was closely related to cell cycle pathway. Notably, further analyses found the frequency of tumor mutations, immune infiltration level and expression of immune checkpoints were significantly different between the two risk groups, and the results of the immunotherapy cohort showed that patients in the high-risk group have a better immune response. Additionally, the high-risk group was found to have higher sensitivity to 5-fluorouracil, doxorubicin and gemcitabine.
CONCLUSION
The novel signature of 3 anoikis-related genes (EZH2, KIF18A and NQO1) can predict the prognosis of patients with HCC, and provide a revealing insight into personalized treatments in HCC.
PubMed: 37182175
DOI: 10.3389/fonc.2023.1158605 -
Medicine Nov 2022Colorectal cancer (CRC) is second most commonly diagnosed cancer with high morbidity and mortality. The heterogeneity of CRC makes clinical treatment tremendously...
Colorectal cancer (CRC) is second most commonly diagnosed cancer with high morbidity and mortality. The heterogeneity of CRC makes clinical treatment tremendously challenging. Here, we aimed to comprehensively analyze the prognosis of CRC patients based on ANOIKIS- and immune-related genes. ANOIKIS-related genes were identified by differentially analysis of high anoikis score group (ANOIKIS_high group) and low anoikis score group (ANOIKIS_low group) divided by the cutoff value of anoikis score. Immune-related genes were screened by differentially analysis of high immune score group (ImmuneScore_high group) and low immune score group (ImmuneScore_low group) classified by the cutoff value of ImmuneScore. Prognostic ANOIKIS- and immune-related genes were identified by univariate Cox regression analysis. Multivariate Cox regression analysis were used for prognostic model construction. Ferroptosis expression profiles, the infiltration of immune cells, and the somatic mutation status were analyzed and compared. Univariate and multivariate Cox-regression analyses were performed to identify independent prognostic factors for CRC patient. Nomogram that contained the independent prognostic factors was established to predict 1-, 3-, and 5-year OS probability of CRC patients. Three ANOIKIS- and immune-related signatures were applied to construct a prognostic model, which divided the CRC patients into high-risk and low-risk groups. The patients with high-risk scores had obviously shorter OSs than those with low-risk scores. The time dependent ROC curve indicated that the risk score model had a stable performance to predict survival rates. Notably, the age, pathologic T, and risk score could be used independent indicators for CRC prognosis prediction. A nomogram containing the independent prognostic factors showed that the nomogram accurately predicted 1-, 3-, and 5-year survival rates of CRC patients. In our research, a novel prognostic model was developed based on ANOIKIS- and immune-related genes in CRC, which could be used for prognostic prediction of CRC patients.
Topics: Humans; Prognosis; Anoikis; Gene Expression Regulation, Neoplastic; Colorectal Neoplasms; Nomograms
PubMed: 36401385
DOI: 10.1097/MD.0000000000031127 -
Translational Oncology Feb 2024Thyroid carcinoma (THCA) is a tumor commonly occurring in the endocrine system, and its incidence rate is increasing yearly. Anoikis is a type of cell death involved in...
Thyroid carcinoma (THCA) is a tumor commonly occurring in the endocrine system, and its incidence rate is increasing yearly. Anoikis is a type of cell death involved in the carcinogenesis process. This study aimed to investigate the prognosis and immune correlations of anoikis in THCA. Our study used several bioinformatics algorithms (co-expression analysis, univariate and multivariate Cox analysis) to screen anoikis-related genes (ARGs) to construct risk models. Through receiver operating characteristic (ROC) curve, nomogram, and independent prognostic analysis found that the constructed model had ideal predictive value for THCA. The consensus clustering method was used to divide ARG patterns into three subgroups, and there were significant differences in survival among the three subgroups. The CIBERSORT algorithm demonstrated strong correlations among immune infiltrating cells, prognostic genes, and risk scores. Univariate and multivariate Cox analysis showed that CDKN2A is an independent prognostic gene. Basic experiments (immunohistochemistry, qRT-PCR, etc.) showed that the expression levels of CDKN2A mRNA and protein were highly expressed in THCA, which was consistent with the results of bioinformatics analysis. In vitro, the knockdown of CDKN2A significantly inhibited the proliferation and migration of THCA cells. In summary, our study utilized eight ARGs to construct an accurate risk model. ARGs, especially CDKN2A, play a crucial role in the occurrence and development of THCA and can become potential targets for treating THCA patients.
PubMed: 38141377
DOI: 10.1016/j.tranon.2023.101873 -
Translational Cancer Research Apr 2023Both metastasis and immune resistance are huge obstacle in lung adenocarcinoma (LUAD) treatment. Multiple studies have shown that the ability of tumor cells to resist...
BACKGROUND
Both metastasis and immune resistance are huge obstacle in lung adenocarcinoma (LUAD) treatment. Multiple studies have shown that the ability of tumor cells to resist anoikis is closely related to the metastasis of tumor cells.
METHODS
In this study, the risk prognosis signature related to anoikis and immune related genes (AIRGs) was constructed by cluster analysis and the least absolute shrinkage and selection operator (LASSO) regression by using The Cancer Genome Atlas (TCGA) Program and the Gene Expression Omnibus (GEO) database. Kaplan-Meier (K-M) curve described the prognosis in the different groups. Receiver operating characteristic (ROC) was applied to evaluate the sensitivity of this signature. Principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE), independent prognostic analysis, and nomogram were utilized to assess the validity of the signature. In addition, we used multiple bioinformatic tools to analyze the function between different groups. Finally, mRNA levels were analyzed by quantitative real-time PCR (qRT-PCR).
RESULTS
The K-M curve showed a worse prognosis for the high-risk group compared to that for the low-risk group. ROC, PCA, t-SNE, independent prognostic analysis and nomogram showed well predictive capabilities. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that differential genes were mainly enriched in immunity, metabolism, and cell cycle. In addition, multiple immune cells and targeted drugs differed in the two risk groups. Finally, we found that the mRNA levels of AIRGs were remarkably different in normal versus cancer cells.
CONCLUSIONS
In short, we established a new model about anoikis and immune, which can well predict prognosis and immune response.
PubMed: 37180666
DOI: 10.21037/tcr-22-2550 -
Scientific Reports Sep 2023Considering the high fatality of hepatocellular carcinoma (HCC), current prognostic systems are insufficient to accurately forecast HCC patients' outcomes. In our study,...
Considering the high fatality of hepatocellular carcinoma (HCC), current prognostic systems are insufficient to accurately forecast HCC patients' outcomes. In our study, nine anoikis‑related genes (PTRH2, ITGAV, ANXA5, BIRC5, BDNF, BSG, DAP3, SKP2, and EGF) were determined to establish a risk scoring model using LASSO regression, which could be validated in ICGC dataset. Kaplan-Meier curves and time-dependent receiver operating characteristic (ROC) curve analysis confirmed the risk score possessed an accurate predictive value for the prognosis of HCC patients. The high-risk group showed a higher infiltration of aDCs, macrophages, T-follicular helper cells, and Th2 cells. Besides, PD-L1 was significantly higher in the high-risk group compared to the low-risk group. Several anoikis‑related genes, such as ANX5, ITGAV, BDNF and SKP2, were associated with drug sensitivity in HCC. Finally, we identified BIRC5 and SKP2 as hub genes among the nine model genes using WGCNA analysis. BIRC5 and SKP2 were over-expressed in HCC tissues, and their over-expression was associated with poor prognosis, no matter in our cohort by immunohistochemical staining or in the TCGA cohort by mRNA-Seq. In our cohort, BIRC5 expression was highly associated with the T stage, pathologic stage, histologic grade and AFP of HCC patients. In general, our anoikis-related risk model can enhance the ability to predict the survival outcomes of HCC patients and provide a feasible therapeutic strategy for immunotherapy and drug resistance in HCC. BIRC5 and SKP2 are hub genes of anoikis‑related genes in HCC.
Topics: Humans; Prognosis; Carcinoma, Hepatocellular; Anoikis; Brain-Derived Neurotrophic Factor; Liver Neoplasms
PubMed: 37679418
DOI: 10.1038/s41598-023-41139-9 -
Cancer Letters Jun 2021The loss of cell-matrix interactions induces apoptosis, known as anoikis. For successful distant metastasis, circulating tumor cells (CTCs) that have lost matrix...
The loss of cell-matrix interactions induces apoptosis, known as anoikis. For successful distant metastasis, circulating tumor cells (CTCs) that have lost matrix attachment need to acquire anoikis resistance in order to survive. Cell aggregate formation confers anoikis resistance, and CTC clusters are more highly metastatic compared to single cells; however, the molecular mechanisms underlying this aggregation are not well understood. In this study, we demonstrated that cell detachment increased cell aggregation and upregulated fibronectin (FN) levels in lung and breast cancer cells, but not in their normal counterparts. FN knockdown decreased cell aggregation and increased anoikis. In addition, cell detachment induced cell-cell adhesion proteins, including E-cadherin, desmoglein-2, desmocollin-2/3, and plakoglobin. Interestingly, FN knockdown decreased the levels of desmoglein-2, desmocollin-2/3, and plakoglobin, but not E-cadherin, suggesting the involvement of desmosomal junction in cell aggregation. Accordingly, knockdown of desmoglein-2, desmocollin-2, or plakoglobin reduced cell aggregation and increased cell sensitivity to anoikis. Previously, we reported that NADPH oxidase 4 (Nox4) upregulation is important for anoikis resistance. Nox4 inhibition by siRNA or apocynin decreased cell aggregation and increased anoikis with the downregulation of FN, and, consequently, decreased desmoglein-2, desmocollin-2/3, or plakoglobin. The coexpression of Nox4 and FN was found to be significant in lung and breast cancer patients, based on cBioPortal data. In vivo mouse lung metastasis model showed that FN knockdown suppressed lung metastasis and thus enhanced survival. FN staining of micro tissue array revealed that FN expression was positive for human lung cancer (61%) and breast cancer (58%) patients. Furthermore, the expression levels of FN, desmoglein-2, desmocollin-2, and plakoglobin were significantly correlated with the poor survival of lung and breast cancer patients, as per the Kaplan-Meier plotter analysis. Altogether, our data suggest that FN upregulation and enhanced desmosomal interactions are critical for cell aggregation and anoikis resistance upon cell detachment.
Topics: A549 Cells; Animals; Anoikis; Breast Neoplasms; Carcinoma, Non-Small-Cell Lung; Cell Aggregation; Cell Line, Tumor; Fibronectins; Heterografts; Humans; Immunohistochemistry; Lung Neoplasms; Mice; Mice, Nude; NADPH Oxidase 4; Neoplasm Metastasis; RNA, Messenger; Tissue Array Analysis; Up-Regulation
PubMed: 33771684
DOI: 10.1016/j.canlet.2021.03.011