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Breast Cancer Research : BCR May 2024Despite progress understanding the mechanisms underlying tumor spread, metastasis remains a clinical challenge. We identified the choline-producing...
BACKGROUND
Despite progress understanding the mechanisms underlying tumor spread, metastasis remains a clinical challenge. We identified the choline-producing glycerophosphodiesterase, EDI3 and reported its association with metastasis-free survival in endometrial cancer. We also observed that silencing EDI3 slowed cell migration and other cancer-relevant phenotypes in vitro. Recent work demonstrated high EDI3 expression in ER-HER2+ breast cancer compared to the other molecular subtypes. Silencing EDI3 in ER-HER2+ cells significantly reduced cell survival in vitro and decreased tumor growth in vivo. However, a role for EDI3 in tumor metastasis in this breast cancer subtype was not explored. Therefore, in the present work we investigate whether silencing EDI3 in ER-HER2+ breast cancer cell lines alters phenotypes linked to metastasis in vitro, and metastasis formation in vivo using mouse models of experimental metastasis.
METHODS
To inducibly silence EDI3, luciferase-expressing HCC1954 cells were transduced with lentiviral particles containing shRNA oligos targeting EDI3 under the control of doxycycline. The effect on cell migration, adhesion, colony formation and anoikis was determined in vitro, and significant findings were confirmed in a second ER-HER2+ cell line, SUM190PT. Doxycycline-induced HCC1954-luc shEDI3 cells were injected into the tail vein or peritoneum of immunodeficient mice to generate lung and peritoneal metastases, respectively and monitored using non-invasive bioluminescence imaging. Metabolite levels in cells and tumor tissue were analyzed using targeted mass spectrometry and MALDI mass spectrometry imaging (MALDI-MSI), respectively.
RESULTS
Inducibly silencing EDI3 reduced cell adhesion and colony formation, as well as increased susceptibility to anoikis in HCC1954-luc cells, which was confirmed in SUM190PT cells. No influence on cell migration was observed. Reduced luminescence was seen in lungs and peritoneum of mice injected with cells expressing less EDI3 after tail vein and intraperitoneal injection, respectively, indicative of reduced metastasis. Importantly, mice injected with EDI3-silenced cells survived longer. Closer analysis of the peritoneal organs revealed that silencing EDI3 had no effect on metastatic organotropism but instead reduced metastatic burden. Finally, metabolic analyses revealed significant changes in choline and glycerophospholipid metabolites in cells and in pancreatic metastases in vivo.
CONCLUSIONS
Reduced metastasis upon silencing supports EDI3's potential as a treatment target in metastasizing ER-HER2+ breast cancer.
Topics: Animals; Female; Humans; Mice; Cell Line, Tumor; Receptor, ErbB-2; Breast Neoplasms; Receptors, Estrogen; Disease Models, Animal; Cell Movement; Gene Knockdown Techniques; Tumor Burden; Neoplasm Metastasis; Lung Neoplasms; Cell Proliferation
PubMed: 38816770
DOI: 10.1186/s13058-024-01849-y -
Heliyon May 2024Esophageal cancer (EC) is a prevalent malignancy with heterogeneous outcomes. This study explores the significance of anoikis-related long non-coding RNAs (lncRNAs) in...
BACKGROUND
Esophageal cancer (EC) is a prevalent malignancy with heterogeneous outcomes. This study explores the significance of anoikis-related long non-coding RNAs (lncRNAs) in EC, aiming to unravel their molecular roles and clinical implications.
METHODS
Transcriptome and clinical data were obtained from TCGA database for EC samples. We identified anoikis-related genes and lncRNAs by Pearson correlation analysis. The risk score model hinged on prognostic lncRNAs filtered from multiple steps. Risk scores were calculated using the derived formula, and categorized patients into low- and high-risk groups. Model robustness was assessed through Kaplan-Meier (KM) survival analysis and Receiver Operating Characteristic (ROC) curve, with clinical utility achieved via a constructed nomogram. We also explored the interplay between the risk score and immune cell infiltration, and investigated drug sensitivity.
RESULTS
We identified 2365 anoikis-related lncRNAs through co-expression analysis, including 1415 significant lncRNAs differentially expressed between normal and tumor samples. A risk score model was constructed from ten prognostic lncRNAs. The risk score model effectively stratified patients based on the median score, and its predictive capacity was validated through KM survival, ROC curve analyses, and the external GSE53622 dataset. The nomogram provided a practical tool for individualized prognosis evaluation. We unveiled significant correlations between specific immune cell subsets and the risk score. Eosinophils and common lymphoid progenitors exhibited positive associations, while endothelial cells and myeloid dendritic cells showed negative correlations. Drug sensitivity analysis revealed potential sensitive drugs for EC treatment that aligned with the risk subgroups.
CONCLUSION
This study established an anoikis-related lncRNAs risk score model that may predict the prognosis, immune infiltration, and drug sensitivity in EC, in hope of facilitating tailored patient management.
PubMed: 38803953
DOI: 10.1016/j.heliyon.2024.e31202 -
Cell Stress 2024Anoikis is a common programmed death for most of detached cells, but cancer cells can obtain anoikis resistance to facilitate their distant metastasis through the...
Anoikis is a common programmed death for most of detached cells, but cancer cells can obtain anoikis resistance to facilitate their distant metastasis through the circulation system. Researches have indicated that enhanced autophagic flux accounts for the survival of many cancer cells under detached conditions. Targeting ATG4B, the key factor of autophagy progress, can inhibit cancer metastasis , but ATG4B-deficient mice are susceptible to many serious diseases, which indicates the potential uncontrolled side effects of direct targeting of ATG4B. In our recent research, we confirmed that ATG4B is a novel RNA binding protein in the gastric cancer (GC) cell. It interacts with SPECC1 which consequently facilitates the liquid-liquid phase separation and ubiquitination of ATG4B. Additionally, the mA reader ELAVL1 inhibits the expression of SPECC1 to enhance the expression of ATG4B and anoikis resistance of GC cells. Further, we screened out an FDA-approved compound, lopinavir, to restore SPECC1 abundance and suppress GC metastasis. In conclusion, our research identified a novel signal pathway (ELAVL1-SPECC1-ATG4B-autophagy) to facilitate anoikis resistance and metastasis of GC cells and screened out a compound with clinical application potential to block this pathway, providing a novel strategy for the prevention of GC metastasis.
PubMed: 38803355
DOI: 10.15698/cst2024.05.296 -
Scientific Reports May 2024This study tackles the persistent prognostic and management challenges of clear cell renal cell carcinoma (ccRCC), despite advancements in multimodal therapies. Focusing...
This study tackles the persistent prognostic and management challenges of clear cell renal cell carcinoma (ccRCC), despite advancements in multimodal therapies. Focusing on anoikis, a critical form of programmed cell death in tumor progression and metastasis, we investigated its resistance in cancer evolution. Using single-cell RNA sequencing from seven ccRCC patients, we assessed the impact of anoikis-related genes (ARGs) and identified differentially expressed genes (DEGs) in Anoikis-related epithelial subclusters (ARESs). Additionally, six ccRCC RNA microarray datasets from the GEO database were analyzed for robust DEGs. A novel risk prognostic model was developed through LASSO and multivariate Cox regression, validated using BEST, ULCAN, and RT-PCR. The study included functional enrichment, immune infiltration analysis in the tumor microenvironment (TME), and drug sensitivity assessments, leading to a predictive nomogram integrating clinical parameters. Results highlighted dynamic ARG expression patterns and enhanced intercellular interactions in ARESs, with significant KEGG pathway enrichment in MYC + Epithelial subclusters indicating enhanced anoikis resistance. Additionally, all ARESs were identified in the spatial context, and their locational relationships were explored. Three key prognostic genes-TIMP1, PECAM1, and CDKN1A-were identified, with the high-risk group showing greater immune infiltration and anoikis resistance, linked to poorer prognosis. This study offers a novel ccRCC risk signature, providing innovative approaches for patient management, prognosis, and personalized treatment.
Topics: Humans; Carcinoma, Renal Cell; Anoikis; Kidney Neoplasms; Prognosis; Biomarkers, Tumor; Tumor Microenvironment; Gene Expression Regulation, Neoplastic; Epithelial Cells; Male; Female; Gene Expression Profiling; Nomograms
PubMed: 38802480
DOI: 10.1038/s41598-024-62978-0 -
Cancer Medicine May 2024Tumors that resist anoikis, a programmed cell death triggered by detachment from the extracellular matrix, promote metastasis; however, the role of anoikis-related genes...
Identification of the molecular subtypes and signatures to predict the prognosis, biological functions, and therapeutic response based on the anoikis-related genes in colorectal cancer.
BACKGROUND
Tumors that resist anoikis, a programmed cell death triggered by detachment from the extracellular matrix, promote metastasis; however, the role of anoikis-related genes (ARGs) in colorectal cancer (CRC) stratification, prognosis, and biological functions remains unclear.
METHODS
We obtained transcriptomic profiles of CRC and 27 ARGs from The Cancer Genome Atlas, the Gene Expression Omnibus, and MSigDB databases, respectively. CRC tissue samples were classified into two clusters based on the expression pattern of ARGs, and their functional differences were explored. Hub genes were screened using weighted gene co-expression network analysis, univariate analysis, and least absolute selection and shrinkage operator analysis, and validated in cell lines, tissues, or the Human Protein Atlas database. We constructed an ARG-risk model and nomogram to predict prognosis in patients with CRC, which was validated using an external cohort. Multifaceted landscapes, including stemness, tumor microenvironment (TME), immune landscape, and drug sensitivity, between high- and low-risk groups were examined.
RESULTS
Patients with CRC were divided into C1 and C2 clusters. Cluster C1 exhibited higher TME scores, whereas cluster C2 had favorable outcomes and a higher stemness index. Eight upregulated hub ARGs (TIMP1, P3H1, SPP1, HAMP, IFI30, ADAM8, ITGAX, and APOC1) were utilized to construct the risk model. The qRT-PCR, Western blotting, and immunohistochemistry results were consistent with those of the bioinformatics analysis. Patients with high risk exhibited worse overall survival (p < 0.01), increased stemness, TME, immune checkpoint expression, immune infiltration, tumor mutation burden, and drug susceptibility compared with the patients with low risk.
CONCLUSION
Our results offer a novel CRC stratification based on ARGs and a risk-scoring system that could predict the prognosis, stemness, TME, immunophenotypes, and drug susceptibility of patients with CRC, thereby improving their prognosis. This stratification may facilitate personalized therapies.
Topics: Humans; Colorectal Neoplasms; Anoikis; Prognosis; Tumor Microenvironment; Gene Expression Regulation, Neoplastic; Male; Biomarkers, Tumor; Nomograms; Female; Transcriptome; Gene Expression Profiling
PubMed: 38785271
DOI: 10.1002/cam4.7315 -
Frontiers in Immunology 2024The effect of anoikis-related genes (ARGs) on clinicopathological characteristics and tumor microenvironment remains unclear. We comprehensively analyzed...
The effect of anoikis-related genes (ARGs) on clinicopathological characteristics and tumor microenvironment remains unclear. We comprehensively analyzed anoikis-associated gene signatures of 1057 colorectal cancer (CRC) samples based on 18 ARGs. Anoikis-related molecular subtypes and gene features were identified through consensus clustering analysis. The biological functions and immune cell infiltration were assessed using the GSVA and ssGSEA algorithms. Prognostic risk score was constructed using multivariate Cox regression analysis. The immunological features of high-risk and low-risk groups were compared. Finally, DAPK2-overexpressing plasmid was transfected to measure its effect on tumor proliferation and metastasis and . We identified 18 prognostic ARGs. Three different subtypes of anoikis were identified and demonstrated to be linked to distinct biological processes and prognosis. Then, a risk score model was constructed and identified as an independent prognostic factor. Compared to the high-risk group, patients in the low-risk group exhibited longer survival, higher enrichment of checkpoint function, increased expression of CTLA4 and PD-L1, higher IPS scores, and a higher proportion of MSI-H. The results of RT-PCR indicated that the expression of DAPK2 mRNA was significantly downregulated in CRC tissues compared to normal tissues. Increased DAPK2 expression significantly suppressed cell proliferation, promoted apoptosis, and inhibited migration and invasion. The nude mice xenograft tumor model confirmed that high expression of DAPK2 inhibited tumor growth. Collectively, we discovered an innovative anoikis-related gene signature associated with prognosis and TME. Besides, our study indicated that DAPK2 can serve as a promising therapeutic target for inhibiting the growth and metastasis of CRC.
Topics: Humans; Colorectal Neoplasms; Tumor Microenvironment; Anoikis; Animals; Prognosis; Mice; Immunotherapy; Female; Male; Gene Expression Regulation, Neoplastic; Death-Associated Protein Kinases; Cell Line, Tumor; Biomarkers, Tumor; Mice, Nude; Transcriptome; Gene Expression Profiling; Xenograft Model Antitumor Assays; Middle Aged; Cell Proliferation; Mice, Inbred BALB C
PubMed: 38779664
DOI: 10.3389/fimmu.2024.1378305 -
Scientific Reports May 2024Colorectal cancer (CRC) is a malignant tumor originating from epithelial cells of the colon or rectum, and its invasion and metastasis could be regulated by anoikis....
Colorectal cancer (CRC) is a malignant tumor originating from epithelial cells of the colon or rectum, and its invasion and metastasis could be regulated by anoikis. However, the key genes and pathways regulating anoikis in CRC are still unclear and require further research. The single cell transcriptome dataset GSE221575 of GEO database was downloaded and applied to cell subpopulation type identification, intercellular communication, pseudo time cell trajectory analysis, and receptor ligand expression analysis of CRC. Meanwhile, the RNA transcriptome dataset of TCGA, the GSE39582, GSE17536, and GSE17537 datasets of GEO were downloaded and merged into one bulk transcriptome dataset. The differentially expressed genes (DEGs) related to anoikis were extracted from these data sets, and key marker genes were obtained after feature selection. A clinical prognosis prediction model was constructed based on the marker genes and the predictive effect was analyzed. Subsequently, gene pathway analysis, immune infiltration analysis, immunosuppressive point analysis, drug sensitivity analysis, and immunotherapy efficacy based on the key marker genes were conducted for the model. In this study, we used single cell datasets to determine the anoikis activity of cells and analyzed the DEGs of cells based on the score to identify the genes involved in anoikis and extracted DEGs related to the disease from the transcriptome dataset. After dimensionality reduction selection, 7 marker genes were obtained, including TIMP1, VEGFA, MYC, MSLN, EPHA2, ABHD2, and CD24. The prognostic risk model scoring system built by these 7 genes, along with patient clinical data (age, tumor stage, grade), were incorporated to create a nomogram, which predicted the 1-, 3-, and 5-years survival of CRC with accuracy of 0.818, 0.821, and 0.824. By using the scoring system, the CRC samples were divided into high/low anoikis-related prognosis risk groups, there are significant differences in immune infiltration, distribution of immune checkpoints, sensitivity to chemotherapy drugs, and efficacy of immunotherapy between these two risk groups. Anoikis genes participate in the differentiation of colorectal cancer tumor cells, promote tumor development, and could predict the prognosis of colorectal cancer.
Topics: Humans; Colorectal Neoplasms; Anoikis; Prognosis; Gene Expression Regulation, Neoplastic; Cell Differentiation; Transcriptome; Biomarkers, Tumor; Gene Expression Profiling; Female
PubMed: 38773226
DOI: 10.1038/s41598-024-62370-y -
Journal of Korean Medical Science May 2024The 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... (Review)
Review
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.
Topics: Humans; Neoplasm Metastasis; Neoplasms; Cell Adhesion; Extracellular Matrix; Epithelial-Mesenchymal Transition; Anoikis; Transcription Factors
PubMed: 38769921
DOI: 10.3346/jkms.2024.39.e156 -
Scientific Reports May 2024In addition to presenting significant diagnostic and treatment challenges, lung adenocarcinoma (LUAD) is the most common form of lung cancer. Using scRNA-Seq and bulk...
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.
Topics: Humans; Adenocarcinoma of Lung; Anoikis; Lung Neoplasms; Prognosis; Immunotherapy; Programmed Cell Death 1 Receptor; RNA-Seq; B7-H1 Antigen; Single-Cell Analysis; Gene Expression Regulation, Neoplastic; Cell Line, Tumor; Immune Checkpoint Inhibitors; Biomarkers, Tumor
PubMed: 38740918
DOI: 10.1038/s41598-024-61629-8 -
Translational Cancer Research Apr 2024Colorectal cancer (CRC) is characterized by a high metastasis rate, leading to poor prognosis and increased mortality. Anoikis, a physiological process, serves as a...
BACKGROUND
Colorectal cancer (CRC) is characterized by a high metastasis rate, leading to poor prognosis and increased mortality. Anoikis, a physiological process, serves as a crucial barrier against metastasis. The objective of this research is to construct a prognostic model for CRC based on genes associated with anoikis.
METHODS
The study involved differential analysis and univariate Cox analysis of anoikis-related genes (ARGs), resulting in the selection of 47 genes closely associated with prognosis. Subsequently, unsupervised k-means clustering analysis was conducted on all patients to identify distinct clusters. Survival analysis, principal component analysis (PCA), and t-distributed stochastic neighbor embedding (t-SNE) analysis were performed on the different clusters to investigate associations within the clusters. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were utilized to assess metabolic pathway enrichment between the identified clusters. Furthermore, single-sample GSEA (ssGSEA) was applied to explore variations in immune infiltration. Multivariable Cox regression and least absolute shrinkage and selection operator (LASSO) analyses were conducted to construct a risk model based on ten signatures, which enabled the grouping of all samples according to their risk scores. The prognostic value of the model was validated using receiver operating characteristic (ROC) curves, area under the curve (AUC) calculations, and survival curves. Additionally, the expression of candidate genes was validated using quantitative real-time polymerase chain reaction (qRT-PCR).
RESULTS
Forty-seven survival-related ARGs were screened out. Somatic mutation analysis showed that these genes revealed a high mutation rate. Based on their expression, two clusters were identified. Cluster B patients exhibited a shortened overall survival and higher immune infiltration. A risk scoring model including ten genes was subsequently developed, which exhibited excellent prognostic predictive ability for CRC, as evidenced by the survival curve, ROC curve, and AUC curve. In addition, a nomogram was developed for predicting 3- and 5-year survival probabilities. The qRT-PCR results indicated the dissimilarities among the ten signatures in the tumor tissues and adjacent tissues of patients with CRC were fundamentally consistent with the analytical findings.
CONCLUSIONS
This study comprehensively evaluated the prognostic significance of ARGs in CRC. It identified two distinct anoikis-related clusters and examined their respective immune microenvironments. Furthermore, an ARGs signature was developed to effectively predict the prognosis of CRC, thereby establishing a solid foundation for investigating the clinical prognostic role of anoikis in CRC.
PubMed: 38737694
DOI: 10.21037/tcr-23-1221