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Aging Feb 2024Clear cell carcinoma (ccRCC) usually has a high metastasis rate and high mortality rate. To enable precise risk stratification, there is a need for novel biomarkers. As...
BACKGROUND
Clear cell carcinoma (ccRCC) usually has a high metastasis rate and high mortality rate. To enable precise risk stratification, there is a need for novel biomarkers. As one form of apoptosis, anoikis results from the disruption of cell-cell connection or cell-ECM attachment. However, the impact of anoikis-related lncRNAs on ccRCC has not yet received adequate attention.
METHODS
The study utilized univariate Cox regression analysis in order to identify the overall survival (OS) associated anoikis-related lncRNAs (ARLs), followed by the LASSO algorithm for selection. On this basis, a risk model was subsequently established using five anoikis-related lncRNAs. To dig the inner molecular mechanism, KEGG, GO, and GSVA analyses were conducted. Additionally, the immune infiltration landscape was estimated using the ESTIMATE, CIBERSORT, and ssGSEA algorithms.
RESULTS
The study constructed a novel risk model based on five ARLs (AC092611.2, AC027601.2, AC103809.1, AL133215.2, and AL162586.1). Patients categorized as low-risk exhibited significantly better OS. Notably, the study observed marked different immune infiltration landscapes and drug sensitivity by risk stratification. Additionally, the study preliminarily explored potential signal pathways associated with risk stratification.
CONCLUSION
The study exhibited the crucial role of ARLs in the carcinogenesis of ccRCC, potentially through differential immune infiltration. Furthermore, the established risk model could serve as a valuable stratification factor for predicting OS prognosis.
Topics: Humans; Carcinoma, Renal Cell; Anoikis; RNA, Long Noncoding; Prognosis; Carcinoma; Kidney Neoplasms
PubMed: 38385949
DOI: 10.18632/aging.205568 -
IET Systems Biology Apr 2024Gastric cancer (GC) is a frequent malignancy of the gastrointestinal tract. Exploring the potential anoikis mechanisms and pathways might facilitate GC research.
BACKGROUND
Gastric cancer (GC) is a frequent malignancy of the gastrointestinal tract. Exploring the potential anoikis mechanisms and pathways might facilitate GC research.
PURPOSE
The authors aim to determine the significance of anoikis-related genes (ARGs) in GC prognosis and explore the regulatory mechanisms in epigenetics.
METHODS
After describing the genetic and transcriptional alterations of ARGs, we searched differentially expressed genes (DEGs) from the cancer genome atlas and gene expression omnibus databases to identify major cancer marker pathways. The non-negative matrix factorisation algorithm, Lasso, and Cox regression analysis were used to construct a risk model, and we validated and assessed the nomogram. Based on multiple levels and online platforms, this research evaluated the regulatory relationship of ARGs with GC.
RESULTS
Overexpression of ARGs is associated with poor prognosis, which modulates immune signalling and promotes anti-anoikis. The consistency of the DEGs clustering with weighted gene co-expression network analysis results and the nomogram containing 10 variable genes improved the clinical applicability of ARGs. In anti-anoikis mode, cytology, histology, and epigenetics could facilitate the analysis of immunophenotypes, tumour immune microenvironment (TIME), and treatment prognosis.
CONCLUSION
A novel anoikis-related prognostic model for GC is constructed, and the significance of anoikis-related prognostic genes in the TIME and the metabolic pathways of tumours is initially explored.
Topics: Humans; Stomach Neoplasms; Prognosis; Anoikis; Algorithms; Biomarkers; Tumor Microenvironment
PubMed: 38377622
DOI: 10.1049/syb2.12088 -
Cancer Cell International Feb 2024Ferroptosis is a form of regulated cell death characterized by iron-dependent lipid peroxidation. Its role in cancer metastasis remains unclear. In this study, we aimed...
BACKGROUND AND PURPOSE
Ferroptosis is a form of regulated cell death characterized by iron-dependent lipid peroxidation. Its role in cancer metastasis remains unclear. In this study, we aimed to investigate the potential involvement of ferroptosis in gastric cancer (GC) metastasis.
METHODS
GC cells (AGS, MKN45, HGC27) were used to explore the role of ferroptosis in single and clustered cells with extracellular matrix (ECM) detachment in vitro. We overexpressed glutathione peroxidase 4 (GPX4) to inhibit ferroptosis and assessed the changes in cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT). Then tumor tissues from 54 GC patients with and without lymphatic metastasis were collected for immunohistochemical staining to investigate the expression of ferroptosis and EMT markers. Finally, Kaplan-Meier survival curves were used to investigate the relationship between overall survival and expression of GPX4 in 178 GC patients.
RESULTS
Detached single cells had lower viability than adherent cells, but cell clustering improved their survival under matrix-detached conditions. Detached single cells exhibited an induction of iron-dependent reactive oxygen species (ROS) accumulation, glutathione (GSH) depletion, lipid peroxidation, upregulation of ACSL4, TFRC and HO-1, increased iron levels, and changes in mitochondrial morphology. Opposite effects were observed in detached clustered cells, including the upregulation of the ferroptosis suppressors GPX4 and SLC7A11. Overexpression of GPX4 inhibited ferroptosis and promoted GC cell proliferation, migration, invasion, and EMT. Immunohistochemical analysis of tumor tissues from GC patients indicated that lymphatic metastasis was associated with higher potential for ferroptosis inhibition and EMT induction. Finally, Kaplan-Meier survival curves demonstrated a significant decrease in overall survival among GC patients with high GPX4 expression.
CONCLUSIONS
Our study provides the first evidence that inhibition of ferroptosis is a crucial mechanism promoting GC metastasis. GPX4 may be a valuable prognostic factor for GC patients. These findings suggest that targeting ferroptosis inhibition may be a promising strategy for GC patients with metastatic potential. Trial registration The ethical approval code of this study in Institutional Review Board of Peking Union Medical College Hospital is No: K1447.
PubMed: 38369484
DOI: 10.1186/s12935-024-03260-1 -
Genomic and epigenomic basis of breast invasive lobular carcinomas lacking CDH1 genetic alterations.NPJ Precision Oncology Feb 2024CDH1 (E-cadherin) bi-allelic inactivation is the hallmark alteration of breast invasive lobular carcinoma (ILC), resulting in its discohesive phenotype. A subset of...
CDH1 (E-cadherin) bi-allelic inactivation is the hallmark alteration of breast invasive lobular carcinoma (ILC), resulting in its discohesive phenotype. A subset of ILCs, however, lack CDH1 genetic/epigenetic inactivation, and their genetic underpinning is unknown. Through clinical targeted sequencing data reanalysis of 364 primary ILCs, we identified 25 ILCs lacking CDH1 bi-allelic genetic alterations. CDH1 promoter methylation was frequent (63%) in these cases. Targeted sequencing reanalysis revealed 3 ILCs harboring AXIN2 deleterious fusions (n = 2) or loss-of-function mutation (n = 1). Whole-genome sequencing of 3 cases lacking bi-allelic CDH1 genetic/epigenetic inactivation confirmed the AXIN2 mutation and no other cell-cell adhesion genetic alterations but revealed a new CTNND1 (p120) deleterious fusion. AXIN2 knock-out in MCF7 cells resulted in lobular-like features, including increased cellular migration and resistance to anoikis. Taken together, ILCs lacking CDH1 genetic/epigenetic alterations are driven by inactivating alterations in other cell adhesion genes (CTNND1 or AXIN2), endorsing a convergent phenotype in ILC.
PubMed: 38347189
DOI: 10.1038/s41698-024-00508-x -
Aging Feb 2024Lung adenocarcinoma (LUAD) is a malignant tumor of the respiratory system that has a poor 5-year survival rate. Anoikis, a type of programmed cell death, contributes to...
Identification of crucial anoikis-related genes as novel biomarkers and potential therapeutic targets for lung adenocarcinoma via bioinformatic analysis and experimental verification.
Lung adenocarcinoma (LUAD) is a malignant tumor of the respiratory system that has a poor 5-year survival rate. Anoikis, a type of programmed cell death, contributes to tumor development and metastasis. The aim of this study was to develop an anoikis-based stratified model, and a multivariable-based nomogram for guiding clinical therapy for LUAD. Through differentially expressed analysis, univariate Cox, LASSO Cox regression, and random forest algorithm analysis, we established a 4 anoikis-related genes-based stratified model, and a multivariable-based nomogram, which could accurately predict the prognosis of LUAD patients in the TCGA and GEO databases, respectively. The low and high-risk score LUAD patients stratified by the model showed different tumor mutation burden, tumor microenvironment, gemcitabine sensitivity and immune checkpoint expressions. Through immunohistochemical analysis of clinical LUAD samples, we found that the 4 anoikis-related genes (PLK1, SLC2A1, ANGPTL4, CDKN3) were highly expressed in the tumor samples from clinical LUAD patients, and knockdown of these genes in LUAD cells by transfection with small interfering RNAs significantly inhibited LUAD cell proliferation and migration, and promoted anoikis. In conclusion, we developed an anoikis-based stratified model and a multivariable-based nomogram of LUAD, which could predict the survival of LUAD patients and guide clinical treatment.
Topics: Humans; Anoikis; Adenocarcinoma of Lung; Biomarkers; Computational Biology; Lung Neoplasms; Prognosis; Tumor Microenvironment
PubMed: 38345559
DOI: 10.18632/aging.205521 -
Molecular Cancer Feb 2024Bladder cancer ranks as the 10th most common cancer worldwide, with deteriorating prognosis as the disease advances. While immune checkpoint inhibitors (ICIs) have shown...
Bladder cancer ranks as the 10th most common cancer worldwide, with deteriorating prognosis as the disease advances. While immune checkpoint inhibitors (ICIs) have shown promise in clinical therapy in both operable and advanced bladder cancer, identifying patients who will respond is challenging. Anoikis, a specialized form of cell death that occurs when cells detach from the extracellular matrix, is closely linked to tumor progression. Here, we aimed to explore the anoikis-based biomarkers for bladder cancer prognosis and immunotherapeutic decisions. Through consensus clustering, we categorized patients from the TCGA-BLCA cohort into two clusters based on anoikis-related genes (ARGs). Significant differences in survival outcome, clinical features, tumor immune environment (TIME), and potential ICIs response were observed between clusters. We then formulated a four-gene signature, termed "Ascore", to encapsulate this gene expression pattern. The Ascore was found to be closely associated with survival outcome and served as an independent prognosticator in both the TCGA-BLCA cohort and the IMvigor210 cohort. It also demonstrated superior predictive capacity (AUC = 0.717) for bladder cancer immunotherapy response compared to biomarkers like TMB and PD-L1. Finally, we evaluated Ascore's independent prognostic performance as a non-invasive biomarker in our clinical cohort (Gulou-Cohort1) using circulating tumor cells detection, achieving an AUC of 0.803. Another clinical cohort (Gulou-Cohort2) consisted of 40 patients undergoing neoadjuvant anti-PD-1 treatment was also examined. Immunohistochemistry of Ascore in these patients revealed its correlation with the pathological response to bladder cancer immunotherapy (P = 0.004). Impressively, Ascore (AUC = 0.913) surpassed PD-L1 (AUC = 0.662) in forecasting immunotherapy response and indicated better net benefit. In conclusion, our study introduces Ascore as a novel, robust prognostic biomarker for bladder cancer, offering a new tool for enhancing immunotherapy decisions and contributing to the tailored treatment approaches in this field.
Topics: Humans; Prognosis; B7-H1 Antigen; Anoikis; Disease Progression; Urinary Bladder Neoplasms; Immunotherapy; Biomarkers; Tumor Microenvironment
PubMed: 38341586
DOI: 10.1186/s12943-024-01945-9 -
Journal of Cellular and Molecular... Feb 2024The resistance to anoikis plays a critical role in the metastatic progression of various types of malignancies, including gastric cancer (GC). Nevertheless, the precise...
The resistance to anoikis plays a critical role in the metastatic progression of various types of malignancies, including gastric cancer (GC). Nevertheless, the precise mechanism behind anoikis resistance is not fully understood. Here, our primary focus was to examine the function and underlying molecular mechanism of Integrin beta-like 1 (ITGBL1) in the modulation of anoikis resistance and metastasis in GC. The findings of our investigation have demonstrated that the overexpression of ITGBL1 significantly augmented the resistance of GC cells to anoikis and promoted their metastatic potential, while knockdown of ITGBL1 had a suppressive effect on both cellular processes in vitro and in vivo. Mechanistically, we proved that ITGBL1 has a role in enhancing the resistance of GC cells to anoikis and promoting metastasis through the AKT/Fibulin-2 (FBLN2) axis. The inhibition of AKT/FBLN2 signalling was able to reverse the impact of ITGBL1 on the resistance of GC cells to anoikis and their metastatic capability. Moreover, the expression levels of ITGBL1 were found to be significantly elevated in the cancerous tissues of patients diagnosed with GC, and there was a strong correlation observed between high expression levels of ITGBL1 and worse prognosis among individuals diagnosed with GC. Significantly, it was revealed that within our cohort of GC patients, individuals exhibiting elevated ITGBL1 expression and diminished FBLN2 expression experienced the worst prognosis. In conclusion, the findings of our study indicate that ITGBL1 may serve as a possible modulator of resistance to anoikis and the metastatic process in GC.
Topics: Humans; Anoikis; Stomach Neoplasms; Proto-Oncogene Proteins c-akt; Extracellular Matrix Proteins; Cell Line, Tumor; Neoplasm Metastasis; Integrin beta1; Calcium-Binding Proteins
PubMed: 38332530
DOI: 10.1111/jcmm.18113 -
Scientific Reports Feb 2024Bladder cancer (BLCA) is a malignant tumor associated with unfavorable outcomes. Studies suggest that anoikis plays a crucial role in tumor progression and cancer cell...
Bladder cancer (BLCA) is a malignant tumor associated with unfavorable outcomes. Studies suggest that anoikis plays a crucial role in tumor progression and cancer cell metastasis. However, its specific role in bladder cancer remains poorly understood. Our objective was to identify anoikis-related genes (ARGs) and subsequently construct a risk model to assess their potential for predicting the prognosis of bladder cancer.The transcriptome data and clinical data of BLCA patients were sourced from The Cancer Genome Atlas and GEO database. We then performed the differential expression analysis to screen differentially expressed ARGs. Subsequently, we conducted non-negative matrix factorization (NMF) clustering analysis to establish molecular subtypes based on the differentially expressed ARGs. The CIBERSORT algorithm was used to estimate the quantification of different cell infiltration in BLCA tumor microenviroment. A prognostic risk model containing 7 ARGs was established using Lasso-Cox regression analysis. The nomogram was built for predicting the survival probability of BLCA patients. To determine the drug sensitivity of each sample from the high- and low-risk groups, the R package "pRRophetic" was performed. Finally, the role of LYPD1 was explored in BLCA cell lines.We identified 90 differential expression ARGs and NMF clustering categorizated the BLCA patientss into two distinct groups (cluster A and B). Patients in cluster A had a better prognosis than those in cluster B. Then, we established a ARGs risk model including CALR, FASN, FOSL1, JUN, LYPD1, MST1R, and SATB1, which was validated in the train and test set. The results suggested overall survival rate was much higher in low risk group than high risk group. The cox regression analysis, ROC curve analysis, and nomogram collectively demonstrated that the risk model served as an independent prognostic factor. The high risk group had a higher level TME scores compared to the low risk group. Furthermore, LYPD1 was low expression in BLCA cells and overexpression of LYPD1 inhibits the prolifearation, migration and invasion.In the current study, we have identified differential expression ARGs and constructed a risk model with the promise for guiding prognostic predictions and provided a therapeutic target for patients with BLCA.
Topics: Humans; Anoikis; Urinary Bladder Neoplasms; Genes, Homeobox; Urinary Bladder; Nomograms; Prognosis; Matrix Attachment Region Binding Proteins
PubMed: 38332160
DOI: 10.1038/s41598-024-53272-0 -
Aging Feb 2024Non-small cell lung cancer (NSCLC) is the most common histological type of lung cancer. With the in-depth exploration of cell death manners, numerous studies found that...
Non-small cell lung cancer (NSCLC) is the most common histological type of lung cancer. With the in-depth exploration of cell death manners, numerous studies found that anoikis is an important mechanism that associated with treatment. Therefore, we aimed to explore the prognostic value and treatment guidance of anoikis in NSCLC patients. In the current study, we first constructed a prognostic model based on the anoikis-related genes based on bulk RNA-sequencing and single-cell RNA-sequencing (scRNA-seq) dataset. Then, immuno-correlations of anoikis-related risk scores (ARGRS) were analyzed. In addition, HMGA1, a risky gene in ARGRS, was further explored to define its expression and immuno-correlation. Results showed that patients with higher ARGRS had worse clinical outcomes. Moreover, the five genes in the prognostic model were all highly expressed on tumor cells. Moreover, further analysis found that the ARGRS was negatively correlated with ImmuneScore, but positively with tumor purity. Besides, patients in the ARGRS-high group had lower levels of immunological characteristics, such as the immune-related signaling pathways and subpopulations. Additionally, in the immunotherapy cohorts, patients with the ARGRS-high phenotype were more resistant to immunotherapy and tended to not achieve remission after treatment. Last, HMGA1 was chosen as the representative biomarker, and analysis of the in-house cohort showed that HMGA1 was highly expressed in tumor tissues and correlated with decreased T cell infiltration. To sum up, ARGRS was correlated with a desert tumor microenvironment and identified immune-cold tumors, which can be a novel biomarker for the recognition of immunological characteristics and an immunotherapeutic response in NSCLC.
Topics: Humans; Carcinoma, Non-Small-Cell Lung; HMGA1a Protein; Lung Neoplasms; Anoikis; Prognosis; Biomarkers; RNA; Tumor Microenvironment
PubMed: 38329444
DOI: 10.18632/aging.205522 -
Aging Feb 2024Methods for predicting the outcome of lung adenocarcinoma (LUAD) in the clinic are limited. Anoikis is an important route to programmed cell death in LUAD, and the...
BACKGROUND
Methods for predicting the outcome of lung adenocarcinoma (LUAD) in the clinic are limited. Anoikis is an important route to programmed cell death in LUAD, and the prognostic value of a model constructed with anoikis-related lncRNAs (ARlncRNAs) in LUAD is unclear.
METHODS
Transcriptome and basic information for LUAD patients was obtained from the Cancer Genome Atlas. Coexpression and Cox regression analyses were utilized to identify prognostically significant ARlncRNAs and construct a prognostic signature. Furthermore, the signature was combined with clinical characteristics to create a nomogram. Finally, we performed principal component, enrichment, tumor mutation burden (TMB), tumor microenvironment (TME) and drug sensitivity analyses to evaluate the basic research and clinical merit of the signature.
RESULTS
The prognostic signature developed with eleven ARlncRNAs can accurately predict that high-risk group patients have a worse prognosis, as proven by the receiver operating characteristic (ROC) curve (AUC: 0.718). Independent prognostic analyses indicated that the risk score is a significant independent prognostic element for LUAD (P<0.001). In the high-risk group, enrichment analysis demonstrated that glucose metabolism and DNA replication were the main enrichment pathways. TMB analysis indicated that the high-risk group had a high TMB (P<0.05). Drug sensitivity analyses can recognize drugs that are sensitive to different risk groups. Finally, 11 ARlncRNAs of this signature were verified by RT-qPCR analysis.
CONCLUSIONS
A novel prognostic signature developed with 11 ARlncRNAs can accurately predict the OS of LUAD patients and offer clinical guidance value for immunotherapy and chemotherapy treatment.
Topics: Humans; Anoikis; Prognosis; RNA, Long Noncoding; Adenocarcinoma; Lung; Lung Neoplasms; Tumor Microenvironment
PubMed: 38319706
DOI: 10.18632/aging.205481