ZEB family is a prognostic biomarker and correlates with anoikis and immune infiltration in kidney renal clear cell carcinoma.

BACKGROUND: Zinc finger E-box binding homEeobox 1 (ZEB1) and ZEB2 are two anoikis-related transcription factors. The mRNA expressions of these two genes are significantly increased in kidney renal clear cell carcinoma (KIRC), which are associated with poor survival. Meanwhile, the mechanisms and clinical significance of ZEB1 and ZEB2 upregulation in KIRC remain unknown. METHODS: Through the Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database, expression profiles, prognostic value and receiver operating characteristic curves (ROCs) of ZEB1 and ZEB2 were evaluated. The correlations of ZEB1 and ZEB2 with anoikis were further assessed in TCGA-KIRC database. Next, miRTarBase, miRDB, and TargetScan were used to predict microRNAs targeting ZEB1 and ZEB2, and TCGA-KIRC database was utilized to discern differences in microRNAs and establish the association between microRNAs and ZEBs. TCGA, TIMER, TISIDB, and TISCH were used to analyze tumor immune infiltration. RESULTS: It was found that ZEB1 and ZEB2 expression were related with histologic grade in KIRC patient. Kaplan-Meier survival analyses showed that KIRC patients with low ZEB1 or ZEB2 levels had a significantly lower survival rate. Meanwhile, ZEB1 and ZEB2 are closely related to anoikis and are regulated by microRNAs. We constructed a risk model using univariate Cox and LASSO regression analyses to identify two microRNAs (hsa-miR-130b-3p and hsa-miR-138-5p). Furthermore, ZEB1 and ZEB2 regulate immune cell invasion in KIRC tumor microenvironments. CONCLUSIONS: Anoikis, cytotoxic immune cell infiltration, and patient survival outcomes were correlated with ZEB1 and ZEB2 mRNA upregulation in KIRC. ZEB1 and ZEB2 are regulated by microRNAs.

System analysis based on Anoikis-related genes identifies MAPK1 as a novel therapy target for osteosarcoma with neoadjuvant chemotherapy.

BACKGROUND: Osteosarcoma (OS) is the most common bone malignant tumor in children, and its prognosis is often poor. Anoikis is a unique mode of cell death.However, the effects of Anoikis in OS remain unexplored. METHOD: Differential analysis of Anoikis-related genes was performed based on the metastatic and non-metastatic groups. Then LASSO logistic regression and SVM-RFE algorithms were applied to screen out the characteristic genes. Later, Univariate and multivariate Cox regression was conducted to identify prognostic genes and further develop the Anoikis-based risk score. In addition, correlation analysis was performed to analyze the relationship between tumor microenvironment, drug sensitivity, and prognostic models. RESULTS: We established novel Anoikis-related subgroups and developed a prognostic model based on three Anoikis-related genes (MAPK1, MYC, and EDIL3). The survival and ROC analysis results showed that the prognostic model was reliable. Besides, the results of single-cell sequencing analysis suggested that the three prognostic genes were closely related to immune cell infiltration. Subsequently, aberrant expression of two prognostic genes was identified in osteosarcoma cells. Nilotinib can promote the apoptosis of osteosarcoma cells and down-regulate the expression of MAPK1. CONCLUSIONS: We developed a novel Anoikis-related risk score model, which can assist clinicians in evaluating the prognosis of osteosarcoma patients in clinical practice. Analysis of the tumor immune microenvironment and chemotherapeutic drug sensitivity can provide necessary insights into subsequent mechanisms. MAPK1 may be a valuable therapeutic target for neoadjuvant chemotherapy in osteosarcoma.

ANXA5: A Key Regulator of Immune Cell Infiltration in Hepatocellular Carcinoma.

BACKGROUND Hepatocellular carcinoma (HCC) poses a significant threat to human life and is the most prevalent form of liver cancer. The intricate interplay between apoptosis, a common form of programmed cell death, and its role in immune regulation stands as a crucial mechanism influencing tumor metastasis. MATERIAL AND METHODS Utilizing HCC samples from the TCGA database and 61 anoikis-related genes (ARGs) sourced from GeneCards, we analyzed the relationship between ARGs and immune cell infiltration in HCC. Subsequently, we identified long non-coding RNAs (lncRNAs) associated with ARGs, using the least absolute shrinkage and selection operator (LASSO) regression analysis to construct a robust prognostic model. The predictive capabilities of the model were then validated through examination in a single-cell dataset. RESULTS Our constructed prognostic model, derived from lncRNAs linked to ARGs, comprised 11 significant lncRNAs: NRAV, MCM3AP-AS1, OTUD6B-AS1, AC026356.1, AC009133.1, DDX11-AS1, AC108463.2, MIR4435-2HG, WARS2-AS1, LINC01094, and HCG18. The risk score assigned to HCC samples demonstrated associations with immune indicators and the infiltration of immune cells. Further, we identified Annexin A5 (ANXA5) as the pivotal gene among ARGs, with it exerting a prominent role in regulating the lncRNA gene signature. Our validation in a single-cell database elucidated the involvement of ANXA5 in immune cell infiltration, specifically in the regulation of mononuclear cells. CONCLUSIONS This study delves into the intricate correlation between ARGs and immune cell infiltration in HCC, culminating in the development of a novel prognostic model reliant on 11 ARGs-associated lncRNAs. Furthermore, our findings highlight ANXA5 as a promising target for immune regulation in HCC, offering new perspectives for immune therapy in the context of HCC.

Identification and validation of a prognostic anoikis-related gene signature in papillary thyroid carcinoma by integrated analysis of single-cell and bulk RNA-sequencing.

Papillary thyroid carcinoma (PTC) prognosis may be deteriorated due to the metastases, and anoikis palys an essential role in the tumor metastasis. However, the potential effect of anoikis-related genes on the prognosis of PTC was unclear. The mRNA and clinical information were obtained from the cancer genome atlas database. Hub genes were identified and risk model was constructed using Cox regression analysis. Kaplan-Meier (K-M) curve was applied for the survival analysis. Immune infiltration and immune therapy response were calculated using CIBERSORT and TIDE. The identification of cell types and cell interaction was performed by Seurat, SingleR and CellChat packages. GO, KEGG, and GSVA were applied for the enrichment analysis. Protein-protein interaction network was constructed in STRING and Cytoscape. Drug sensitivity was assessed in GSCA. Based on bulk RNA data, we identified 4 anoikis-related risk signatures, which were oncogenes, and constructed a risk model. The enrichment analysis found high risk group was enriched in some immune-related pathways. High risk group had higher infiltration of Tregs, higher TIDE score and lower levels of monocytes and CD8 T cells. Based on scRNA data, we found that 4 hub genes were mainly expressed in monocytes and macrophages, and they interacted with T cells. Hub genes were significantly related to immune escape-related genes. Drug sensitivity analysis suggested that cyclin dependent kinase inhibitor 2A may be a better chemotherapy target. We constructed a risk model which could effectively and steadily predict the prognosis of PTC. We inferred that the immune escape may be involved in the development of PTC.

Development of an anoikis-related gene signature and prognostic model for predicting the tumor microenvironment and response to immunotherapy in colorectal cancer.

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 in vitro and in vivo. 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.

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.

Development of a biomarker signature associated with anoikis to predict prognosis and immunotherapy response in melanoma.

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.

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.

Anchorage Dependence and Cancer Metastasis.

The process of cancer metastasis is dependent on the cancer cells' capacity to detach from the primary tumor, endure in a suspended state, and establish colonies in other locations. Anchorage dependence, which refers to the cells' reliance on attachment to the extracellular matrix (ECM), is a critical determinant of cellular shape, dynamics, behavior, and, ultimately, cell fate in nonmalignant and cancer cells. Anchorage-independent growth is a characteristic feature of cells resistant to anoikis, a programmed cell death process triggered by detachment from the ECM. This ability to grow and survive without attachment to a substrate is a crucial stage in the progression of metastasis. The recently discovered phenomenon named "adherent-to-suspension transition (AST)" alters the requirement for anchoring and enhances survival in a suspended state. AST is controlled by four transcription factors (IKAROS family zinc finger 1, nuclear factor erythroid 2, BTG anti-proliferation factor 2, and interferon regulatory factor 8) and can detach cells without undergoing the typical epithelial-mesenchymal transition. Notably, AST factors are highly expressed in circulating tumor cells compared to their attached counterparts, indicating their crucial role in the spread of cancer. Crucially, the suppression of AST substantially reduces metastasis while sparing primary tumors. These findings open up possibilities for developing targeted therapies that inhibit metastasis and emphasize the importance of AST, leading to a fundamental change in our comprehension of how cancer spreads.

A novel anoikis-related signature predicts prognosis risk and treatment responsiveness in diffuse large B-cell lymphoma.

BACKGROUND: Although anoikis plays a role in cancer metastasis and aggressiveness, it has rarely been reported in diffuse large B cell lymphoma (DLBCL). METHODS: We obtained RNA sequencing data and matched clinical data from the GEO database. An anoikis-related genes (ARGs)-based risk signature was developed in GSE10846 training cohort and validated in three other cohorts. Additionally, we predicted half-maximal inhibitory concentration (IC50) of drugs based on bioinformatics method and obtained the actual IC50 to some chemotherapy drugs via cytotoxicity assay. RESULTS: The high-risk group, as determined by our signature, was associated with worse prognosis and an immunosuppressive environment in DLBCL. Meanwhile, the nomogram based on eight variables had more accurate ability in forecasting the prognosis than the international prognostic index in DLBCL. The prediction of IC50 indicated that DLBCL patients in the high-risk group were more sensitive to doxorubicin, IPA-3, lenalidomide, gemcitabine, and CEP.701, while patients in the low-risk group were sensitive to cisplatin and dasatinib. Consistent with the prediction, cytotoxicity assay suggested the higher sensitivity to doxorubicin and gemcitabine and the lower sensitivity to dasatinib in the high-risk group in DLBCL. CONCLUSION: The ARG-based signature may provide a promising direction for prognosis prediction and treatment optimization for DLBCL patients.

Functional Role of DUSP6 in the EGFR-mediated Progression of Head and Neck Squamous Cell Carcinoma.

BACKGROUND/AIM: Epidermal growth factor receptor (EGFR) over-expression is commonly observed in advanced head and neck squamous cell carcinoma (HNSCC) and is correlated with poor patient outcomes. However, the role of dual-specificity phosphatase 6 (DUSP6) in EGFR-associated HNSCC progression remains poorly understood. This study aimed to investigate the correlation between DUSP6 expression and EGFR signaling in malignant HNSCC tissues. MATERIALS AND METHODS: Data mining and in vitro assays were employed to assess DUSP6 expression levels in HNSCC tissues compared to normal tissues. Additionally, the correlation between DUSP6 and EGFR expression was examined. Functional assays were conducted to investigate the modulation of DUSP6 expression by EGFR signaling and its involvement in EGF-induced cell migration and anoikis resistance. RESULTS: Our analysis revealed a significant elevation in DUSP6 expression in HNSCC tissues compared to normal tissues and a strong correlation between DUSP6 and EGFR expression. EGFR signaling modulated DUSP6 expression in a dose- and time-dependent manner, primarily through the extracellular signal-regulated kinase (ERK) pathway. Knockdown experiments demonstrated the functional role of DUSP6 in EGF-induced cell migration and anoikis resistance. CONCLUSION: The findings of this study elucidate the intricate signaling networks governing DUSP6 expression and its interplay with EGFR signaling in HNSCC. Moreover, the results provide insights into the potential role of DUSP6 as a therapeutic target and highlight the importance of personalized treatment strategies in HNSCC management.

Empagliflozin drives ferroptosis in anoikis-resistant cells by activating miR-128-3p dependent pathway and inhibiting CD98hc in breast cancer.

A tumour suppressor miRNA, miR-128-3p, is widely involved in various biological processes and has been found to get downregulated in breast cancer patients. We previously published that ectopically expressed miR-128-3p suppressed migration, invasion, cell cycle arrest, and breast cancer stem cells. In the present study, we explored the role of Empagliflozin (EMPA) as a miR-128-3p functionality-mimicking drug in inducing ferroptosis by inhibiting CD98hc. Given that CD98hc is one of the proteins critical in triggering ferroptosis, we confirmed that miR-128-3p and EMPA inhibited SP1, leading to inhibition of CD98hc expression. Further, transfection with siCD98hc, miR-128-3p mimics, and inhibitors was performed to assess their involvement in the ferroptosis of anoikis-resistant cells. We proved that anoikis-resistant cells possess high ROS and iron levels. Further, miR-128-3p and EMPA treatments induced ferroptosis by inhibiting GSH and enzymatic activity of GPX4 and also induced lipid peroxidation. Moreover, EMPA suppressed bioluminescence of 4T1-Red-FLuc induced thoracic cavity, peritoneal tumour burden and lung nodules in an in-vivo metastatic model of breast cancer. Collectively, we revealed that EMPA sensitized the ECM detached cells to ferroptosis by synergically activating miR-128-3p and lowering the levels of SP1 and CD98hc, making it a potential adjunct drug for breast cancer chemotherapy.

Deciphering anoikis resistance and identifying prognostic biomarkers in clear cell renal cell carcinoma epithelial cells.

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.

Muscone restores anoikis sensitivity in TMZ-resistant glioblastoma cells by suppressing TOP2A via the EGFR/Integrin ß1/FAK signaling pathway.

BACKGROUND: Temozolomide (TMZ) resistance is the main obstacle faced by glioblastoma multiforme (GBM) treatment. Muscone, one of the primary active pharmacological ingredients of Shexiang (Moschus), can cross the blood-brain barrier (BBB) and is being investigated as an antineoplastic medication. However, muscone treatment for GBM has received little research, and its possible mechanisms are still unclear. PURPOSE: This study aims to evaluate the effect and the potential molecular mechanism of muscone on TMZ-resistant GBM cells. METHODS: The differentially expressed genes (DEGs) between TMZ-resistant GBM cells and TMZ-sensitive GBM cells were screened using GEO2R. By progressively raising the TMZ concentration, a relatively stable TMZ-resistant human GBM cell line was established. The drug-resistance traits of U251-TR cells were assessed via the CCK-8 assay and Western Blot analysis of MGMT and TOP2A expression. Cell viability, cell proliferation, cell migration ability, and drug synergism were detected by the CCK-8 assay, colony formation assay, wound healing assay, and drug interaction relationship test, respectively. Anoikis was quantified by Calcein-AM/EthD-1 staining, MTT assay, and flow cytometry. Measurements of cell cycle arrest, apoptosis, mitochondrial membrane potential (MMP), and reactive oxygen species (ROS) were performed using cell cycle staining, Annexin V-FITC/PI labeling, JC-1 assay, and ROS assay, respectively. DNA damage was measured by TUNEL assay, alkaline comet assay, and γ-H2AX foci assay. GEPIA was used to investigate the link between the anoikis marker (FAK)/drug resistance gene and critical proteins in the EGFR/Integrin ß1 signaling pathway. Molecular docking was used to anticipate the probable targets of muscone. The intracellular co-localization and expression of EGFR and FAK were shown using immunofluorescence. The U251-TR cell line stably overexpressing EGFR was constructed using lentiviral transduction to assess the involvement of EGFR-related signaling in anoikis resistance. Western Blot was employed to detect the expression of migration-related proteins, cyclins, anoikis-related proteins, DNA damage/repair-related proteins, and associated pathway proteins. RESULTS: DEGs analysis identified 97 deregulated chemotherapy-resistant genes and 3779 upregulated genes in TMZ-resistant GBM cells. Subsequent experiments verified TMZ resistance and the hyper-expression of DNA repair-related genes (TOP2A and MGMT) in continuously low-dose TMZ-induced U251-TR cells. Muscone exhibited dose-dependent inhibition of U251-TR cell migration and proliferation, and its co-administration with TMZ showed the potential for enhanced therapeutic efficacy. By downregulating FAK, muscone reduced anoikis resistance in anchorage-independent U251-TR cells. It also caused cell cycle arrest in the G2/M phase by upregulating p21 and downregulating CDK1, CDK2, and Cyclin E1. Muscone-induced anoikis was accompanied by mitochondrial membrane potential collapse, ROS production, an increase in the BAX/Bcl-2 ratio, as well as elevated levels of Cytochrome c (Cyt c), cleaved caspase-9, and cleaved caspase-3. These findings indicated that muscone might trigger mitochondrial-dependent anoikis via ROS generation. Moreover, significant DNA damage, DNA double-strand breaks (DSBs), the formation of γ-H2AX foci, and a reduction in TOP2A expression are also associated with muscone-induced anoikis. Overexpression of EGFR in U251-TR cells boosted the expression of Integrin ß1, FAK, ß-Catenin, and TOP2A, whereas muscone suppressed the expression levels of EGFR, Integrin ß1, ß-Catenin, FAK, and TOP2A. Muscone may influence the expression of the key DNA repair enzyme, TOP2A, by suppressing the EGFR/Integrin ß1/FAK pathway. CONCLUSION: We first demonstrated that muscone suppressed TOP2A expression through the EGFR/Integrin ß1/FAK pathway, hence restoring anoikis sensitivity in TMZ-resistant GBM cells. These data suggest that muscone may be a promising co-therapeutic agent for enhancing GBM treatment, particularly in cases of TMZ-resistant GBM with elevated TOP2A expression.

Anoikis-related gene signatures in colorectal cancer: implications for cell differentiation, immune infiltration, and prognostic prediction.

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.

Identification of an anoikis-related gene signature and characterization of immune infiltration in skin cutaneous melanoma.

Anoikis is considered strongly associated with a biological procession of tumors. Herein, we utilized anoikis-related genes (ARGs) to predict the prognosis and immunotherapeutic efficacy for skin cutaneous melanoma (SKCM). RNA-seq data were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. After dividing patients into novel subtypes based on the expression of prognostic ARGs, K-M survival was conducted to compare the survival status. Subsequently, differentially expressed ARGs were identified and the predictive model was established. The predictive effects were validated using the areas under the curve about the receiver operating characteristic. Moreover, tumor mutation burden, the enriched functional pathway, immune cells and functions, and the immunotherapeutic response were also analyzed and compared. The distribution of model genes at cell level was visualized by the single-cell seq with tumor immune single-cell hub database. Patients of The Cancer Genome Atlas-SKCM cohort were divided into 2 clusters, the cluster 1 performed a better prognosis. Cluster 2 was more enriched in metabolism-related pathways whereas cluster 1 was more associated with immune pathways. A predictive risk model was established with 6 ARGs, showing the areas under the curves of 1-year, 3-year, and 5-year ROC were 0.715, 0,720, and 0.731, respectively. Moreover, risk score was negatively associated with tumor mutation burden and immune-related pathways enrichment. In addition, patients with high-risk scores performed immunosuppressive status but the decreasing scores enhanced immune cell infiltration, immune function activation, and immunotherapeutic response. In this study, we established a novel signature in predicting prognosis and immunotherapy. It can be considered reliable to formulate the complex treatment for SKCM patients.

Identification and validation of anoikis-related genes to clarify the prognosis and immune mechanisms of patients with low-grade glioma.

BACKGROUND: Low-grade glioma (LGG) has an extremely poor prognosis, and the mechanism leading to malignant development has not been determined. The aim of our study was to clarify the function and mechanism of anoikis and TIMP1 in the malignant progression of LGG. METHODS: We screened 7 anoikis-related genes from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to construct a prognostic-predicting model. The study assessed the clinical prognosis, pathological characteristics, and immune cell infiltration in both high- and low-risk groups. Additionally, the potential modulatory effects of TIMP1 on proliferation, migration, and anoikis in LGG were investigated both in vivo and in vitro. RESULTS: In this study, we identified seven critical genes, namely, PTGS2, CCND1, TIMP1, PDK4, LGALS3, CDKN1A, and CDKN2A. Kaplan‒Meier (K‒M) curves demonstrated a significant correlation between clinical features and overall survival (OS), and single-cell analysis and mutation examination emphasized the heterogeneity and pivotal role of hub gene expression imbalances in LGG development. Immune cell infiltration and microenvironment analysis further elucidated the relationships between key genes and immune cells. In addition, TIMP1 promoted the malignant progression of LGG in both in vitro and in vivo models. CONCLUSIONS: This study confirmed that TIMP1 promoted the malignant progression of LGG by inhibiting anoikis, providing insights into LGG pathogenesis and potential therapeutic targets.

Identification and validation of an anoikis-related genes signature for prognostic implication in papillary thyroid cancer.

Thyroid cancer, notably papillary thyroid cancer (PTC), is a global health concern with increasing incidence. Anoikis, a regulator of programmed cell death, is pivotal in normal physiology and, when dysregulated, can drive cancer progression and metastasis. This study explored the impact of anoikis on PTC prognosis. Analyzing data from GEO, TCGA, and GeneCards, we identified a prognostic signature consisting of six anoikis-related genes (ARGs): EZH2, PRKCQ, CD36, INHBB, TDGF1, and MMP9. This signature independently predicted patient outcomes, with high-risk scores associated with worse prognoses. A robust predictive ability was confirmed via ROC analysis, and a nomogram achieved a C-index of 0.712. Differences in immune infiltration levels were observed between high- and low-risk groups. Importantly, the high-risk group displayed reduced drug sensitivity and poor responses to immunotherapy. This research provides insights into anoikis in PTC, offering a novel ARG signature for predicting patient prognosis and guiding personalized treatment strategies.

Synergistic effects of photodynamic therapy and chemotherapy: Activating the intrinsic/extrinsic apoptotic pathway of anoikis for triple-negative breast cancer treatment.

Triple-negative breast cancer (TNBC) is a highly invasive and metastatic subtype of breast cancer that often recurs after surgery. Herein, we developed a cyclodextrin-based tumor-targeted nano delivery system that incorporated the photosensitizer chlorin e6 (Ce6) and the chemotherapeutic agent lonidamine (LND) to form the R6RGD-CMßCD-se-se-Ce6/LND nanoparticles (RCC/LND NPS). This nanosystem could target cancer cells, avoid lysosomal degradation and further localize within the mitochondria. The RCC/LND NPS had pH and redox-responsive to control the release of Ce6 and LND. Consequently, the nanosystem had a synergistic effect by effectively alleviating hypoxia, enhancing the production of cytotoxic reactive oxygen species (ROS) and amplifying the efficacy of photodynamic therapy (PDT). Furthermore, the RCC/LND NPS + light weakened anoikis resistance, disrupted extracellular matrix (ECM), activated both the intrinsic apoptotic pathway (mitochondrial pathway) and extrinsic apoptotic pathway (receptor death pathway) of anoikis. In addition, the nanosystem showed significant anti-TNBC efficacy in vivo. These findings collectively demonstrated that RCC/LND NPS + light enhanced the anticancer effects, induced anoikis and inhibited tumor cell migration and invasion through a synergistic effect of chemotherapy and PDT. Overall, this study highlighted the promising potential of the RCC/LND NPS + light for the treatment of TNBC.

Identification and immunological characteristics of anoikis-associated molecular clusters in lung adenocarcinoma.

Anoikis plays a crucial role in the progression, prognosis, and immune response of lung adenocarcinoma (LUAD). However, its specific impact on LUAD remains unclear. In this study, we investigated the intricate interplay of nesting apoptotic factors in LUAD. By analyzing nine key nesting apoptotic factors, we categorized LUAD patients into two distinct clusters. Further examination of immune cell profiles revealed that Cluster A exhibited greater infiltration of innate immune cells than did Cluster B. Additionally, we identified two genes closely associated with prognosis and developed a predictive model to differentiate patients based on molecular clusters. Our findings suggest that the loss of specific anoikis-related genes could significantly influence the prognosis, tumor microenvironment, and clinical features of LUAD patients. Furthermore, we validated the expression and functional roles of two pivotal prognostic genes, solute carrier family 2 member 1 (SLC2A1) and sphingosine kinase 1 (SPHK1), in regulating tumor cell viability, migration, apoptosis, and anoikis. These results offer valuable insights for future mechanistic investigations. In conclusion, this study provides new avenues for advancing our understanding of LUAD, improving prognostic assessments, and developing more effective immunotherapy strategies.