Unveiling an anoikis-related risk model and the role of RAD9A in colon cancer.

OBJECTIVE: Colorectal cancer (CRC), specifically colon adenocarcinoma, is the third most prevalent and the second most lethal form of cancer. Anoikis is found to be specialized form of programmed cell death (PCD), which plays a pivotal role in tumor progression. This study aimed to investigate the role of the anoikis related genes (ARGs) in colon cancer. METHODS: Consensus unsupervised clustering, differential expression analysis, tumor mutational burden analysis, and analysis of immune cell infiltration were utilized in the study. For the analysis of RNA sequences and clinical data of COAD patients, data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were obtained. A prognostic scoring system for overall survival (OS) prediction was developed using Cox regression and LASSO regression analysis. Furthermore, loss-of-function assay was utilized to explore the role of RAD9A played in the progression of colon cancer. RESULTS: The prognostic value of a risk score composed of NTRK2, EPHA2, RAD9A, CDC25C, and SNAI1 genes was significant. Furthermore, these findings suggested potential mechanisms that may influence prognosis, supporting the development of individualized treatment plans and management of patient outcomes. Further experiments confirmed that RAD9A could promote proliferation and metastasis of colon cancer cells. These effects may be achieved by affecting the phosphorylation of AKT. CONCLUSION: Differences in survival time and the tumor immune microenvironment (TIME) were observed between two gene clusters associated with ARGs. In addition, a prognostic risk model was established and confirmed as an independent risk factor. Furthermore, our data indicated that RAD9A promoted tumorigenicityby activating AKT in colon cancer.

FASN promotes anoikis resistance in colorectal liver metastases through the ERK1/2 pathway.

PURPOSE: Colorectal cancer (CRC) is recognized as the third most common form of malignancy, with the liver frequently serving as the main site for metastasis. Anoikis resistance (AR) is critical in colorectal cancer liver metastases (CRLM). Fatty acid synthase (FASN), essential in lipid synthesis, mediates AR in many cancers. The present research examines the function of FASN in ERK1/2-mediated AR in CRLM and evaluates its therapeutic potential. METHODS: We performed scratch and migration experiment to evaluate the migration capacity of the LoVo cells. Flow cytometry was employed to identify cell apoptosis. The levels of FASN, p-ERK1/2, and proteins related to apoptosis was analyzed by Western blot. The mRNA level of FASN was determined by q-PCR after FASN silencing. In addition, we used an intrasplenic liver metastasis model of nude to assess the effect of FASN on CRLM. RESULTS: In vitro experiments showed that after FASN silencing, the cell apoptosis rate was increased, migration capability was notably decreased, the expression of p-ERK1/2, the proteins related to anti-apoptotic were significantly decreased, and the proteins related to apoptosis were significantly increased. In vivo experiments showed that AR significantly increased the number of liver metastatic foci, whereas FASN silencing significantly inhibited CRLM. CONCLUSION: These results suggest that FASN silencing suppressed AR through the ERK 1/2 pathway, which in turn suppressed CRLM.

Pokemon inhibits Bim transcription to promote the proliferation, anti-anoikis, invasion, histological grade, and dukes stage of colorectal neoplasms.

PURPOSE: This study aims to determine whether Pokemon regulates Bim activity in colorectal carcinoma (CRC) carcinogenesis. METHODS: Clinical tissue samples were analyzed to detect the expression and clinicopathological significance of Pokemon and Bim in CRC. Proliferation, apoptosis, and invasion assays were conducted to identify the regulatory effect of Pokemon on Bim. The combined treatment effects of Pokemon knockdown and diamminedichloroplatinum (DDP) were also examined. RESULTS: Immunohistochemical analysis of 80 samples of colorectal epithelia (CRE), 80 cases of colorectal adenoma (CRA), and 160 of CRC samples revealed protein expression rates of 23.8%, 38.8%, and 70.6% for Pokemon, and 88.8%, 73.8%, and 31.9% for Bim, respectively. A significant negative correlation was observed between Pokemon and Bim expression across the CRE, CRA, and CRC lesion stages. In CRC, higher Pokemon and lower Bim expression correlated with higher histological grades, advanced Dukes stages, and increased cancer invasion. In both LoVo and HCT116 cells, overexpression of Pokemon significantly reduced Bim expression, leading to increased proliferation, resistance to anoikis, and cell invasion. Additionally, Pokemon overexpression significantly decreased DDP-induced Bim expression, reduction of anti-apoptosis and invasion, whereas Pokemon knockdown resulted in the opposite effects. CONCLUSION: These findings suggest that Pokemon inhibits Bim transcription, thereby promoting CRC proliferation, resistance to apoptosis, invasion, and advancing histological grade and Dukes staging. Pokemon knockdown enhances the therapeutic efficacy of DDP in the treatment of CRC.

Exploring the prognostic value of BRMS1 + microglia based on single-cell anoikis regulator patterns in the immunologic microenvironment of GBM.

BACKGROUND: Anoikis is a specialized form of programmed cell death induced by the loss of cell adhesion to the extracellular matrix (ECM). Acquisition of anoikis resistance is a significant marker for cancer cell invasion, metastasis, therapy resistance, and recurrence. Although current research has identified multiple factors that regulate anoikis resistance, the pathological mechanisms of anoikis-mediated tumor microenvironment (TME) in glioblastoma (GBM) remain largely unexplored. METHODS: Utilizing single-cell RNA sequencing (scRNA-seq) data and employing non-negative matrix factorization (NMF), we identified and characterized TME cell clusters with distinct anoikis-associated gene signatures. Prognostic and therapeutic response analyses were conducted using TCGA and CGGA datasets to assess the clinical significance of different TME cell clusters. The spatial relationship between BRMS1 + microglia and tumor cells was inferred from spatial transcriptome RNA sequencing (stRNA-seq) data. To simulate the tumor immune microenvironment, co-culture experiments were performed with microglia (HMC3) and GBM cells (U118/U251), and microglia were transfected with a BRMS1 overexpression lentivirus. Western blot or ELISA were used to detect BRMS1, M2 macrophage-specific markers, PI3K/AKT signaling proteins, and apoptosis-related proteins. The proliferation and apoptosis capabilities of tumor cells were evaluated using CCK-8, colony formation, and apoptosis assays, while the invasive and migratory abilities of tumor cells were assessed using Transwell assays. RESULTS: NMF-based analysis successfully identified CD8 + T cell and microglia cell clusters with distinct gene signature characteristics. Trajectory analysis, cell communication, and gene regulatory network analyses collectively indicated that anoikis-mediated TME cell clusters can influence tumor cell development through various mechanisms. Notably, BRMS1 + AP-Mic exhibited an M2 macrophage phenotype and had significant cell communication with malignant cells. Moreover, high expression of BRMS1 + AP-Mic in TCGA and CGGA datasets was associated with poorer survival outcomes, indicating its detrimental impact on immunotherapy. Upregulation of BRMS1 in microglia may lead to M2 macrophage polarization, activate the PI3K/AKT signaling pathway through SPP1/CD44-mediated cell interactions, inhibit tumor cell apoptosis, and promote tumor proliferation and invasion. CONCLUSION: This pioneering study used NMF-based analysis to reveal the important predictive value of anoikis-regulated TME in GBM for prognosis and immunotherapeutic response. BRMS1 + microglial cells provide a new perspective for a deeper understanding of the immunosuppressive microenvironment of GBM and could serve as a potential therapeutic target in the future.

Prognositic value of anoikis and tumor immune microenvironment-related gene in the treatment of osteosarcoma. / Anoikiså’Œè‚¿ç˜¤å ç–«å¾®çŽ¯å¢ƒç›¸å ³åŸºå› åœ¨éª¨è‚‰ç˜¤æ²»ç–—ä¸­çš„é¢„åŽä»·å€¼ï¼ˆè‹±æ–‡ï¼‰.

OBJECTIVES: Osteosarcoma is a highly aggressive primary malignant bone tumor commonly seen in children and adolescents, with a poor prognosis. Anchorage-dependent cell death (anoikis) has been proven to be indispensable in tumor metastasis, regulating the migration and adhesion of tumor cells at the primary site. However, as a type of programmed cell death, anoikis is rarely studied in osteosarcoma, especially in the tumor immune microenvironment. This study aims to clarify prognostic value of anoikis and tumor immune microenvironment-related gene in the treatment of osteosarcoma. METHODS: Anoikis-related genes (ANRGs) were obtained from GeneCards. Clinical information and ANRGs expression profiles of osteosarcoma patients were sourced from the therapeutically applicable research to generate effective therapies and Gene Expression Omnibus (GEO) databases. ANRGs highly associated with tumor immune microenvironment were identified by the estimate package and the weighted gene coexpression network analysis (WGCNA) algorithm. Machine learning algorithms were performed to construct long-term survival predictive strategy, each sample was divided into high-risk and low-risk subgroups, which was further verified in the GEO cohort. Finally, based on single-cell RNA-seq from the GEO database, analysis was done on the function of signature genes in the osteosarcoma tumor microenvironment. RESULTS: A total of 51 hub ANRGs closely associated with the tumor microenvironment were identified, from which 3 genes (MERTK, BNIP3, S100A8) were selected to construct the prognostic model. Significant differences in immune cell activation and immune-related signaling pathways were observed between the high-risk and low-risk groups based on tumor microenvironment analysis (all P<0.05). Additionally, characteristic genes within the osteosarcoma microenvironment were identified in regulation of intercellular crosstalk through the GAS6-MERTK signaling pathway. CONCLUSIONS: The prognostic model based on ANRGs and tumor microenvironment demonstrate good predictive power and provide more personalized treatment options for patients with osteosarcoma.

The critical role of glutamine and fatty acids in the metabolic reprogramming of anoikis-resistant melanoma cells.

Introduction: Circulating tumor cells (CTCs) represent the sub-population of cells shed into the vasculature and able to survive in the bloodstream, adhere to target vascular endothelial cells, and re-growth into the distant organ. CTCs have been found in the blood of most solid tumor-bearing patients and are used as a diagnostic marker. Although a complex genotypic and phenotypic signature characterizes CTCs, the ability to survive in suspension constitutes the most critical property, known as resistance to anoikis, e.g., the ability to resist apoptosis resulting from a loss of substrate adhesion. Here, we selected melanoma cells resistant to anoikis, and we studied their metabolic reprogramming, with the aim of identifying new metabolic targets of CTCs. Methods: Subpopulations of melanoma cells expressing a high anoikis-resistant phenotype were selected by three consecutive rocking exposures in suspension and studied for their phenotypic and metabolic characteristics. Moreover, we tested the efficacy of different metabolic inhibitors targeting glycolysis (2DG), LDHA (LDHA-in-3), the mitochondrial electron transport chain complex I (rotenone), glutaminase (BPTES), fatty acid transporter (SSO), fatty acid synthase (denifanstat), CPT1 (etomoxir), to inhibit cell survival and colony formation ability after 24 h of rocking condition. Results: Anoikis-resistant cells displayed higher ability to grow in suspension on agarose-covered dishes respect to control cells, and higher cell viability and colony formation capability after a further step in rocking condition. They showed also an epithelial-to-mesenchymal transition associated with high invasiveness and a stemness-like phenotype. Anoikis-resistant melanoma cells in suspension showed a metabolic reprogramming from a characteristic glycolytic metabolism toward a more oxidative metabolism based on the use of glutamine and fatty acids, while re-adhesion on the dishes reversed the metabolism to glycolysis. The treatment with metabolic inhibitors highlighted the effectiveness of rotenone, BPTES, SSO, and etomoxir in reducing the viability and the colony formation ability of cells capable of surviving in suspension, confirming the dependence of their metabolism on oxidative phosphorylation, using glutamine and fatty acids as the most important fuels. Discussion: This finding opens up new therapeutic strategies based on metabolic inhibitors of glutaminase and fatty acid oxidation for the treatment of CTCs and melanoma metastases.

A thermo-sensitive hydrogel with prominent hemostatic effect prevents tumor recurrence via anti-anoikis-resistance.

Tumor cells can survive when detached from the extracellular matrix (ECM) or lose cell-cell connections, a phenomenon known as anoikis-resistance (AR). AR is closely associated with tumor cell metastasis and recurrence, enabling tumor cells to disseminate, migrate, and invade after detachment. To address this issue, a novel intervention method combining intraoperative hemostasis with multifunctional nanozyme driven-enhanced chemodynamic therapy (ECDT) has been proposed, which holds the potential to weaken the AR capability of tumor cells and suppress tumor recurrence. Here, a nanocomposite containing a dendritic mesoporous nanoframework with Cu2+ was developed using an anion-assisted approach after surface PEG grafting and glucose oxidase (GOx) anchoring (DMSN-Cu@GOx/PEG). DMSN-Cu@GOx/PEG was further encapsulated in a thermal-sensitive hydrogel (H@DMSN-Cu@GOx/PEG). DMSN-Cu@GOx/PEG utilizes its high peroxidase (POD) activity to elevate intracellular ROS levels, thereby weakening the AR capability of bladder cancer cells. Additionally, through its excellent catalase (CAT) activity, DMSN-Cu@GOx/PEG converts the high level of hydrogen peroxide (H2O2) catalyzed by intracellular GOx into oxygen (O2), effectively alleviating tumor hypoxia, downregulating hypoxia-inducible factor-1α (HIF-1α) expression, inhibiting epithelial-mesenchymal transition (EMT) processes, and ultimately suppressing the migration and invasion of bladder cancer cells. Interestingly, in vivo results showed that the thermosensitive hydrogel H@DMSN-Cu@GOx/PEG could rapidly gel at body temperature, forming a gel film on wounds to eliminate residual tumor tissue after tumor resection surgery. Importantly, H@DMSN-Cu@GOx/PEG exhibited excellent hemostatic capabilities, effectively enhancing tissue coagulation during post-tumor resection surgery and mitigating the risk of cancer cell dissemination and recurrence due to surgical bleeding. Such hydrogels undoubtedly possess strong surgical application. Our developed novel nanosystem and hydrogel can inhibit the AR capability of tumor cells and prevent recurrence post-surgery. This study represents the first report of using dendritic mesoporous silica-based nanoreactors for inhibiting the AR capability of bladder cancer cells and suppressing tumor recurrence post-surgery, providing a new avenue for developing strategies to impede tumor recurrence after surgery.

Unraveling the relationship between anoikis-related genes and cancer-associated fibroblasts in liver hepatocellular carcinoma.

This study intended to determine the molecular subtypes of liver hepatocellular carcinoma (LIHC) on the strength of anoikis-related genes (ARGs) and to assess their prognostic value and prospective relationship with immune cell infiltration and cancer-associated fibroblasts (CAFs). Univariate Cox regression analysis yielded 66 prognosis-related ARGs and classified LIHC into two distinct subtypes, with subtype A demonstrating overexpression of most prognosis-related ARGs and a significant survival disadvantage. Furthermore, a reliable prediction model was developed using ARGs to evaluate the risk of LIHC patients. This model served as an independent prognostic indicator and a quantitative tool for clinical prognostic prediction. Additionally, subtype-specific differences in immune cell infiltration were observed, and the risk score was potentially linked to immune-related characteristics. Moreover, the study identified a significant association between CAF score and LIHC prognosis, with a low CAF score indicating a favorable patient prognosis. In conclusion, this study reveals the molecular mechanisms underlying the development and progression of LIHC and identifies potential therapeutic targets for the disease.

ANXA5 predicts prognosis and immune response and mediates proliferation and migration in head and neck squamous cell carcinoma.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is a common malignancy that often develops unnoticed. Typically, these tumors are identified at advanced stages, resulting in a relatively low chance of successful treatment. Anoikis serves as a natural defense against the spread of tumor cells, meaning circumventing anoikis can effectively inhibit tumor metastasis. Nonetheless, studies focusing on anoikis in the context of HNSCC remain scarce. METHODS: Anoikis-related genes (ARGs) were identified by using the GeneCards and Harmonizome databases. Expression data of these genes and relevant clinical features were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A LASSO regression and a prognostic risk score model were developed to determine their prognostic significance. The analysis included the use of the CIBERSORT algorithm to quantify immune and stromal cell presence. Furthermore, in vitro and in vivo, we confirmed the expression and functional roles of proteins and mRNA of genes independently predictive of prognosis. RESULTS: The study identified eight genes linked to prognosis (ANXA5, BAK1, CDKN2A, PPARG, CCR7, MAPK11, CRYAB, CRYBA1) and developed a prognostic model that effectively forecasts the survival outcomes for patients with HNSCC. A higher survival likelihood is associated with lower risk scores. In addition, a significant relationship was found between immune and risk score, and ANXA5 deletion promoted the killing of HNSCC cells by activated T cells. During the screening process, 65 different chemotherapeutic drugs were found to have significant differences in IC50 values when comparing high- and low-risk categories. ANXA5 emerged as a gene with independent prognostic significance, exhibiting notably elevated protein and mRNA levels in HNSCC tissue compared to non-tumorous tissue. The suppression of ANXA5 gene activity resulted in a substantial decrease in both the growth and mobility of HNSCC cells. Animal model experiments demonstrated that inhibiting ANXA5 suppressed HNSCC growth and migration in vivo. CONCLUSION: Through bioinformatics, a prognostic risk model of high precision was developed, offering valuable insights into the survival rates and immune responses in patients with HNSCC. ANXA5 is highlighted as a significant prognostic factor among the identified genes, indicating its promise as a potential therapeutic target for those with HNSCC.

Anoikis-related genes linked with patient outcome in pancreatic cancer.

Anoikis is programmed cell death occurring upon cell detachment from the extracellular matrix. Cancer cells need to evade anoikis to be able to metastasize to distant sites. However, the molecular features and prognostic value of anoikis-related genes (ARGs) in pancreatic cancer remain unclear. In this study, we utilized transcriptome data from the TCGA and GSE102238 databases to identify 64 ARGs significantly associated with prognosis. We used the "ConsensusClusterPlus" R package to stratify patients into high and low-risk prognostic subgroups. The KEGG and GSEA analyses revealed that the clusters with poor prognosis were enriched for the ECM receptor interaction pathway, the TP53 signaling pathway, and the galactose metabolism pathway, and that the cell cycle pathway was upregulated. A prognostic model consisting of seven ARGs (SERPINE1, EGF, E2F1, MSLN, RAB27B, ETV7, MST1) was constructed using LASSO regression and when combined with clinicopathological parameters using Cox regression, a prognostic Nomogram was created, which demonstrated high prognostic utility. Among the biomarker candidates, we report ETV7 as a novel, independent prognostic marker in pancreatic cancer. ETV7 was highly expressed in KRAS and TP53 co-occurrent mutant TCGA patients, indicating that it may be regulated by the two major driver genes of pancreatic cancer. Therefore, targeting ETV7 could be a potential focus for future therapeutic studies.

Anoikis-Related Genes Impact Prognosis and Tumor Microenvironment in Bladder Cancer.

Anoikis tolerance is an important biological process of tumor colonization and metastasis outside the primary tumor. Recent research has progressively elucidated the function and underlying mechanisms of anoikis in the metastasis of various solid tumors. Nevertheless, the specific mechanisms of anoikis in bladder cancer and its consequent effects on the tumor immune microenvironment remain ambiguous. In this study, we developed an anoikis score based on five genes (ETV7, NGF, SCD, LAMC1, and CASP6) and categorized subjects into high and low-risk groups using the median score from the TCGA database. Our findings indicate that SCD enhances the proliferation of bladder cancer cells in vitro. Furthermore, integrating the anoikis score with clinicopathological features to construct a prognostic nomogram demonstrated precision in assessing patient outcomes. Immune cell analysis revealed elevated infiltration levels of Treg cells and M2 macrophages in the high anoikis score group, whereas CD8+ T cell levels were reduced. This study highlights the importance of anoikis score in predicting patient prognosis, immune cell infiltration, and drug response, which may provide a treatment modality worth exploring in depth for the study of bladder cancer.

Integrative analysis of Anoikis-related genes reveals that FASN is a novel prognostic biomarker and promotes the malignancy of bladder cancer via Wnt/ß-catenin pathway.

Bladder cancer (BC) exhibits diversity in clinical outcomes and is characterized by heterogeneity. Anoikis, a form of programmed cell death, plays a crucial role in facilitating tumor invasion and metastasis. This study comprehensively investigated the genetic landscape of BC progression, identifying 300 differentially expressed Anoikis-related genes (DE-ARGs) through in-depth analysis of the GSE13507 datasets. Functional enrichment analysis revealed associations with diverse diseases and biological processes. Employing machine learning algorithms, a logistic regression model based on nine marker genes demonstrated superior accuracy in distinguishing BC from normal samples. Validation in TCGA datasets highlighted the prognostic significance of LRP1, FASN, and SIRT6, suggesting their potential as cancer biomarkers. Particularly, FASN emerged as an independent prognostic indicator, regulating BC cell proliferation and metastasis through the Wnt/ß-catenin pathway. The study provides crucial insights into altered genetic landscapes and potential therapeutic strategies for BC, emphasizing the significance of FASN in BC prognosis and progression.

The resistance to anoikis, mediated by Spp1, and the evasion of immune surveillance facilitate the invasion and metastasis of hepatocellular carcinoma.

Anoikis-Related Genes (ARGs) lead to the organism manifesting resistance to anoikis and are associated with unfavorable prognostic outcomes across various malignancies.Therefore, it is crucial to identify the pivotal target genes related to anoikis in HCC .We found that ARGs were significantly correlated with prognosis and immune responses in HCC. The core gene, SPP1, notably promoted anoikis resistance and metastasis in HCC through both in vivo and in vitro studies. The PI3K-Akt-mTOR pathway played a critical role in anoikis suppression within HCC contexts. Our research unveiled SPP1's role in enhancing PKCα phosphorylation, which in turn activated the PI3K-Akt-mTOR cascade. Additionally, SPP1 was identified as a key regulator of MDSCs and Tregs migration, directly affecting their immunosuppressive capabilities.These findings indicate that in HCC, SPP1 promoted anoikis resistance and facilitated immune evasion by modulating MDSCs and Tregs.

Knockdown of Anoikis-Associated Gene OCIAD2 Reduces Proliferation and Migration of Glioblastoma Cell Lines.

BACKGROUND: Glioblastoma (GBM) severely disrupts the quality of life of patients. Anoikis represents a significant mechanism in cancer invasion and metastasis. Our study focused on the prognostic relationship between the anoikis-associated gene and GBM and its effect on GBM cell progression. METHODS: We downloaded 656 and 979 GBM sample data from TCGA and CGGA cohort datasets, respectively. Fifteen anoikis-associated genes were obtained from the GeneCards database and were subsequently clustered to identify differential genes associated with them. After LAASO screening, the expression values of the 5 differential genes were the sum of LASSO regression coefficients. Survival analysis and ROC curve analysis of anoikis scores were performed using the TCGA training and CGGA validation sets. The prognostic factors were analyzed using Cox regression analysis in GBM. Moreover, CCK-8, colony formation, wound healing, and transwell assay were used to evaluate GBM cell proliferation and migration. RESULTS: Significant differences were observed in the 5-year survival of GBM patients between the two subgroups. Then, our analysis demonstrated that high OCIAD2, FTLP3, IGFBP2, and H19 levels were associated with lower 5-year GBM survival rates, whereas high SFRP2 levels were associated with higher survival rates. Univariate Cox analysis indicated that GBM risk was linked to both anoikis score and grade, while multivariate Cox analysis indicated that GBM risk was associated with both anoikis score and age. Additionally, OCIAD2 was highly expressed in U251MG and T98G cells. Moreover, OCIAD2 silencing inhibited GBM cell proliferation and migration. CONCLUSION: This study demonstrated the potential of the anoikis-associated gene OCIAD2 as a prognostic biomarker for GBM. Furthermore, we validated in vitro that OCIAD2 promoted GBM cell progression.

Integrative nomogram model based on anoikis-related genes enhances prognostic evaluation in colorectal cancer.

Background: Revealing the role of anoikis resistance plays in CRC is significant for CRC diagnosis and treatment. This study integrated the CRC anoikis-related key genes (CRC-AKGs) and established a novel model for improving the efficiency and accuracy of the prognostic evaluation of CRC. Methods: CRC-ARGs were screened out by performing differential expression and univariate Cox analysis. CRC-AKGs were obtained through the LASSO machine learning algorithm and the LASSO Risk-Score was constructed to build a nomogram clinical prediction model combined with the clinical predictors. In parallel, this work developed a web-based dynamic nomogram to facilitate the generalization and practical application of our model. Results: We identified 10 CRC-AKGs and a risk-related prognostic Risk-Score was calculated. Multivariate COX regression analysis indicated that the Risk-Score, TNM stage, and age were independent risk factors that significantly associated with the CRC prognosis(p < 0.05). A prognostic model was built to predict the outcome with satisfied accuracy (3-year AUC = 0.815) for CRC individuals. The web interactive nomogram (https://yuexiaozhang.shinyapps.io/anoikisCRC/) showed strong generalizability of our model. In parallel, a substantial correlation between tumor microenvironment and Risk-Score was discovered in the present work. Conclusion: This study reveals the potential role of anoikis in CRC and sets new insights into clinical decision-making in colorectal cancer based on both clinical and sequencing data. Also, the interactive tool provides researchers with a user-friendly interface to input relevant clinical variables and obtain personalized risk predictions or prognostic assessments based on our established model.

A prognostic model for anoikis-related genes in pancreatic cancer.

Anoikis, a distinct form of programmed cell death, is crucial for both organismal development and maintaining tissue equilibrium. Its role extends to the proliferation and progression of cancer cells. This study aimed to establish an anoikis-related prognostic model to predict the prognosis of pancreatic cancer (PC) patients. Gene expression data and patient clinical profiles were sourced from The Cancer Genome Atlas (TCGA-PAAD: Pancreatic Adenocarcinoma) and the International Cancer Genome Consortium (ICGC-PACA: Pancreatic Ductal Adenocarcinoma). Non-cancerous pancreatic tissue gene expression data were obtained from the Genotype-Tissue Expression (GTEx) project. The R package was used to construct anoikis-related PC prognostic models, which were later validated with the ICGC-PACA database. Survival analyses demonstrated a poorer prognosis for patients in the high-risk group, consistent across both TCGA-PAAD and ICGC-PACA datasets. A nomogram was designed as a predictive tool to estimate patient mortality. The study also analyzed tumor mutations and immune infiltration across various risk groups, uncovering notable differences in tumor mutation patterns and immune landscapes between high- and low-risk groups. In conclusion, this research successfully developed a prognostic model centered on anoikis-related genes, offering a novel tool for predicting the clinical trajectory of PC patients.

An anoikis-related gene signature predicts prognosis, drug sensitivity, and immune microenvironment in cholangiocarcinoma.

Background: Cholangiocarcinoma is a malignant invasive biliary tract carcinoma with a poor prognosis. Anoikis-related genes are prognostic features of a variety of cancers. However, the value of prognostication and therapeutic effect of anoikis-related genes in cholangiocarcinoma have not been reported. The aim of this research was developing an ARGs signature associated with cholangiocarcinoma patients. Methods: We introduced transcriptome data to discover genes that were differentially expressed in cholangiocarcinoma. Subsequently, WGCNA was utilized to screen critical module genes in reference to anoikis. The univariate Cox, Lasso regression and Kaplan-Meier survival were executed to build a prognostic signature. We further performed gene functional enrichment, immune microenvironment and immunotherapy analysis between two risk subgroups. Finally, the pRRophetic algorithm was applied to compare the half inhibitory concentration value of several drugs. Results: A grand total of 1844 genes with differential expression related to the cholangiocarcinoma patients were identified. Furthermore, we obtained 2678 key module genes related to anoikis. Then, a prognostic signature was developed using the 6 prognostic genes (FXYD2, PCBD1, C1RL, GMNN, LAMA4 and HACL1). Independent prognostic analysis showed that risk score and alcohol could function as separate prognostic variables. We found cetain distinction in the immune microenvironment between the two risk subgroups. Moreover, immunotherapy evaluation showed that the anoikis-related gene signature could be applied as a therapy predictor. Finally, Chemotherapeutic drug sensitivity results showed that the low-risk group responded better to bosutinib, gefitinib, gemcitabine, and paclitaxel, while the high-risk group responded better to axitinib, cisplatin, and imatinib. Conclusion: The prognostic signature comprised of FXYD2, PCBD1, C1RL, GMNN, LAMA4 and HACL1 based on anoikis-related genes was established, which provided theoretical basis and reference value for the research and treatment of cholangiocarcinoma.

Elucidating prognosis in cervical squamous cell carcinoma and endocervical adenocarcinoma: a novel anoikis-related gene signature model.

Background: Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) are among the most prevalent gynecologic malignancies globally. The prognosis is abysmal once cervical cancer progresses to lymphatic metastasis. Anoikis, a specialized form of apoptosis induced by loss of cell adhesion to the extracellular matrix, plays a critical role. The prediction model based on anoikis-related genes (ARGs) expression and clinical data could greatly aid clinical decision-making. However, the relationship between ARGs and CESC remains unclear. Methods: ARGs curated from the GeneCards and Harmonizome portals were instrumental in delineating CESC subtypes and in developing a prognostic framework for patients afflicted with this condition. We further delved into the intricacies of the immune microenvironment and pathway enrichment across the identified subtypes. Finally, our efforts culminated in the creation of an innovative nomogram that integrates ARGs. The utility of this prognostic tool was underscored by Decision Curve Analysis (DCA), which illuminate its prospective benefits in guiding clinical interventions. Results: In our study, We discerned a set of 17 survival-pertinent, anoikis-related differentially expressed genes (DEGs) in CESC, from which nine were meticulously selected for the construction of prognostic models. The derived prognostic risk score was subsequently validated as an autonomous prognostic determinant. Through comprehensive functional analyses, we observed distinct immune profiles and drug response patterns among divergent prognostic stratifications. Further, we integrated the risk scores with the clinicopathological characteristics of CESC to develop a robust nomogram. DCA corroborated the utility of our model, demonstrating its potential to enhance patient outcomes through tailored clinical treatment strategies. Conclusion: The predictive signature, encompassing nine pivotal genes, alongside the meticulously constructed nomogram developed in this research, furnishes clinicians with a sophisticated tool for tailoring treatment strategies to individual patients diagnosed with CESC.

Identification of anoikis-related gene signatures and construction of the prognosis model in prostate cancer.

Background: One of the primary reasons for tumor invasion and metastasis is anoikis resistance. Biochemical recurrence (BCR) of prostate cancer (PCa) serves as a harbinger of its distant metastasis. However, the role of anoikis in PCa biochemical recurrence has not been fully elucidated. Methods: Differential expression analysis was used to identify anoikis-related genes based on the TCGA and GeneCards databases. Prognostic models were constructed utilizing LASSO regression, univariate and multivariate Cox regression analyses. Moreover, Gene Expression Omnibus datasets (GSE70770 and GSE46602) were applied as validation cohorts. Gene Ontology, KEGG and GSVA were utilized to explore biological pathways and molecular mechanisms. Further, immune profiles were assessed using CIBERSORT, ssGSEA, and TIDE, while anti-cancer drugs sensitivity was analyzed by GDSC database. In addition, gene expressions in the model were examined using online databases (Human Protein Atlas and Tumor Immune Single-Cell Hub). Results: 113 differentially expressed anoikis-related genes were found. Four genes (EEF1A2, RET, FOSL1, PCA3) were selected for constructing a prognostic model. Using the findings from the Cox regression analysis, we grouped patients into groups of high and low risk. The high-risk group exhibited a poorer prognosis, with a maximum AUC of 0.897. Moreover, larger percentage of immune infiltration of memory B cells, CD8 Tcells, neutrophils, and M1 macrophages were observed in the high-risk group than those in the low-risk group, whereas the percentage of activated mast cells and dendritic cells in the high-risk group were lower. An increased TIDE score was founded in the high-risk group, suggesting reduced effectiveness of ICI therapy. Additionally, the IC50 results for chemotherapy drugs indicated that the low-risk group was more sensitive to most of the drugs. Finally, the genes EEF1A2, RET, and FOSL1 were expressed in PCa cases based on HPA website. The TISCH database suggested that these four ARGs might contribute to the tumor microenvironment of PCa. Conclusion: We created a risk model utilizing four ARGs that effectively predicts the risk of BCR in PCa patients. This study lays the groundwork for risk stratification and predicting survival outcomes in PCa patients with BCR.

Anoikis resistance regulates immune infiltration and drug sensitivity in clear-cell renal cell carcinoma: insights from multi omics, single cell analysis and in vitro experiment.

Background: Anoikis is a form of programmed cell death essential for preventing cancer metastasis. In some solid cancer, anoikis resistance can facilitate tumor progression. However, this phenomenon is underexplored in clear-cell renal cell carcinoma (ccRCC). Methods: Using SVM machine learning, we identified core anoikis-related genes (ARGs) from ccRCC patient transcriptomic data. A LASSO Cox regression model stratified patients into risk groups, informing a prognostic model. GSVA and ssGSEA assessed immune infiltration, and single-cell analysis examined ARG expression across immune cells. Quantitative PCR and immunohistochemistry validated ARG expression differences between immune therapy responders and non-responders in ccRCC. Results: ARGs such as CCND1, CDKN3, PLK1, and BID were key in predicting ccRCC outcomes, linking higher risk with increased Treg infiltration and reduced M1 macrophage presence, indicating an immunosuppressive environment facilitated by anoikis resistance. Single-cell insights showed ARG enrichment in Tregs and dendritic cells, affecting immune checkpoints. Immunohistochemical analysis reveals that ARGs protein expression is markedly elevated in ccRCC tissues responsive to immunotherapy. Conclusion: This study establishes a novel anoikis resistance gene signature that predicts survival and immunotherapy response in ccRCC, suggesting that manipulating the immune environment through these ARGs could improve therapeutic strategies and prognostication in ccRCC.