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Proteomes Jan 2024Billions of cells die in us every hour, and our tissues do not shrink because there is a natural regulation where Cell Death (CD) is balanced with cell division. The... (Review)
Review
Billions of cells die in us every hour, and our tissues do not shrink because there is a natural regulation where Cell Death (CD) is balanced with cell division. The process in which cells eliminate themselves in a controlled manner is called Programmed Cell Death (PCD). The PCD plays an important role during embryonic development, in maintaining homeostasis of the body's tissues, and in the elimination of damaged cells, under a wide range of physiological and developmental stimuli. A multitude of protein mediators of PCD have been identified and signals have been found to utilize common pathways elucidating the proteins involved. This narrative review focuses on caspase-dependent and caspase-independent PCD pathways. Included are studies of caspase-dependent PCD such as Anoikis, Catastrophe Mitotic, Pyroptosis, Emperitosis, Parthanatos and Cornification, and Caspase-Independent PCD as Wallerian Degeneration, Ferroptosis, Paraptosis, Entosis, Methuosis, and Extracellular Trap Abnormal Condition (ETosis), as well as neutrophil extracellular trap abnormal condition (NETosis) and Eosinophil Extracellular Trap Abnormal Condition (EETosis). Understanding PCD from those reported in this review could shed substantial light on the processes of biological homeostasis. In addition, identifying specific proteins involved in these processes is mandatory to identify molecular biomarkers, as well as therapeutic targets. This knowledge could provide the ability to modulate the PCD response and could lead to new therapeutic interventions in a wide range of diseases.
PubMed: 38250814
DOI: 10.3390/proteomes12010003 -
International Journal of Oncology Mar 2024Carcinoembryonic antigen (CEA)‑related cell adhesion molecule 6 (CEACAM6) is a cell adhesion protein of the CEA family of glycosyl phosphatidyl inositol anchored cell... (Review)
Review
Carcinoembryonic antigen (CEA)‑related cell adhesion molecule 6 (CEACAM6) is a cell adhesion protein of the CEA family of glycosyl phosphatidyl inositol anchored cell surface glycoproteins. A wealth of research has demonstrated that CEACAM6 is generally upregulated in pancreatic adenocarcinoma, breast cancer, non‑small cell lung cancer, gastric cancer, colon cancer and other cancers and promotes tumor progression, invasion and metastasis. The transcriptional expression of CEACAM6 is regulated by various factors, including the CD151/TGF‑β1/Smad3 axis, microRNA (miR)‑146, miR‑26a, miR‑29a/b/c, miR‑128, miR‑1256 and DNA methylation. In addition, the N‑glycosylation of CEACAM6 protein at Asn256 is mediated by α‑1,6‑mannosylglycoptotein 6‑β‑N‑acetylglucosaminyltransferase. In terms of downstream signaling pathways, CEACAM6 promotes tumor proliferation by increasing levels of cyclin D1 and cyclin‑dependent kinase 4 proteins. CEACAM6 can activate the ERK1/2/MAPK or SRC/focal adhesion kinase/PI3K/AKT pathways directly or through EGFR, leading to stimulation of tumor proliferation, invasion, migration, resistance to anoikis and chemotherapy, as well as angiogenesis. This article provides a review of the expression pattern, biological function and relationship with prognosis of CEACAM6 in cancer. In summary, CEACAM6 may be a valuable diagnostic biomarker and potential therapeutic target for human cancers exhibiting overexpression of CEACAM6.
Topics: Humans; Cell Adhesion; Carcinoembryonic Antigen; Adenocarcinoma; Carcinoma, Non-Small-Cell Lung; Phosphatidylinositol 3-Kinases; Pancreatic Neoplasms; Lung Neoplasms; Cell Adhesion Molecules; GPI-Linked Proteins; MicroRNAs; Cell Line, Tumor; Antigens, CD
PubMed: 38240103
DOI: 10.3892/ijo.2024.5615 -
Scientific Reports Jan 2024The aim of this study was to determine the prognostic significance of anoikis related genes (ARGs) in ovarian cancer (OC) and to develop a prognostic signature based on...
The aim of this study was to determine the prognostic significance of anoikis related genes (ARGs) in ovarian cancer (OC) and to develop a prognostic signature based on ARG expression. We analyzed cohorts of OC patients and used nonnegative matrix factorization (NMF) for clustering. Single-sample gene-set enrichment analysis (ssGSEA) was employed to quantify immune infiltration. Survival analyses were performed using the Kaplan-Meier method, and differences in survival were determined using the log-rank test. The extent of anoikis modification was quantified using a risk score generated from ARG expression. The analysis of single-cell sequencing data was performed by the Tumor Immune Single Cell Hub (TISCH). Our analyses revealed two distinct patterns of anoikis modification. The risk score was used to evaluate the anoikis modification patterns in individual tumors. Three hub-genes were screened using the LASSO (Least Absolute Shrinkage and Selection Operator) method and patients were classified into different risk groups based on their individual score and the median score. The low-risk subtype was characterized by decreased expression of hub-genes and better overall survival. The risk score, along with patient age and gender, were considered to identify the prognostic signature, which was visualized using a nomogram. Our findings suggest that ARGs may play a novel role in the prognosis of OC. Based on ARG expression, we have developed a prognostic signature for OC that can aid in patient stratification and treatment decision-making. Further studies are needed to validate these results and to explore the underlying mechanisms.
Topics: Humans; Female; Anoikis; Prognosis; Ovarian Neoplasms; Nomograms; Algorithms
PubMed: 38238592
DOI: 10.1038/s41598-024-52117-0 -
Aging Jan 2024Anoikis, a form of apoptotic cell death resulting from inadequate cell-matrix interactions, has been implicated in tumor progression by regulating tumor angiogenesis and...
Anoikis, a form of apoptotic cell death resulting from inadequate cell-matrix interactions, has been implicated in tumor progression by regulating tumor angiogenesis and metastasis. However, the potential roles of anoikis-related long non-coding RNAs (arlncRNAs) in the tumor microenvironment are not well understood. In this study, five candidate lncRNAs were screened through least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis based on differentially expressed lncRNAs associated with anoikis-related genes (ARGs) from TCGA and GSE40595 datasets. The prognostic accuracy of the risk model was evaluated using Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curves. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis (GSEA) analyses revealed significant differences in immune-related hallmarks and signal transduction pathways between the high-risk and low-risk groups. Additionally, immune infiltrate analysis showed significant differences in the distribution of macrophages M2, follicular T helper cells, plasma cells, and neutrophils between the two risk groups. Lastly, silencing the expression of PRR34_AS1 and SPAG5_AS1 significantly increased anoikis-induced cell death in ovarian cancer cells. In conclusion, our study constructed a risk model that can predict clinicopathological features, tumor microenvironment characteristics, and prognosis of ovarian cancer patients. The immune-related pathways identified in this study may offer new treatment strategies for ovarian cancer.
Topics: Humans; Female; Anoikis; Prognosis; RNA, Long Noncoding; Ovarian Neoplasms; Tumor Microenvironment; Cell Cycle Proteins
PubMed: 38226979
DOI: 10.18632/aging.205439 -
Aging Jan 2024Hepatocellular carcinoma (HCC) exhibits a high degree of invasiveness and is closely associated with rapid disease progression. Multiple lines of evidence indicate a...
BACKGROUND
Hepatocellular carcinoma (HCC) exhibits a high degree of invasiveness and is closely associated with rapid disease progression. Multiple lines of evidence indicate a strong correlation between anoikis resistance and tumor progression, invasion, and metastasis. Nevertheless, the classification of anoikis in HCC and the investigation of novel biological target mechanisms in this context continue to pose challenges, requiring further exploration.
METHODS
Combined with HCC samples from TCGA, GEO and ICGC databases, cluster analysis was conducted on anoikis genes, revealing novel patterns among different subtypes. Significant gene analysis of different gene subtypes was performed using WCGNA. The anoikis prognostic risk model was established by Lasso-Cox. Go, KEGG, and GSEA were applied to investigate pathway enrichment primarily observed in risk groups. We compared the disparities in immune infiltration, TMB, tumor microenvironment (TME), and drug sensitivity between the two risk groups. RT-qPCR and Western blotting were performed to validate the expression levels of SLCO4C1 in HCC. The biological functions of SLCO4C1 in HCC cells were assessed through various experiments, including CCK8 assay, colony formation assay, invasion migration assay, wound healing assay, and flow cytometry analysis.
RESULTS
HCC was divided into 2 anoikis subtypes, and the subtypeB had a better prognosis. An anoikis prognostic model based on 12 (COPZ2, ACTG2, IFI27, SPP1, EPO, SLCO4C1, RAB26, STC2, RAC3, NQO1, MYCN, HSPA1B) risk genes is important for survival and prognosis. Significant differences were observed in immune cell infiltration, TME, and drug sensitivity analysis between the risk groups. SLCO4C1 was downregulated in HCC. SLCO4C1 downregulation promoted the proliferation, invasion, migration, and apoptosis of HCC cells. The tumor-suppressive role of SLCO4C1 in HCC has been confirmed.
CONCLUSIONS
Our study presents a novel anoikis classification method for HCC that reveals the association between anoikis features and HCC. The anoikis feature is a critical biomarker bridging tumor cell death and tumor immunity. In this study, we provided the first evidence of SLCO4C1 functioning as a tumor suppressor in HCC.
Topics: Humans; Carcinoma, Hepatocellular; Anoikis; Liver Neoplasms; Biomarkers; Biological Assay; Tumor Microenvironment; Prognosis; Organic Anion Transporters
PubMed: 38226966
DOI: 10.18632/aging.205438 -
Aging Jan 2024Anoikis is essential for the progression of many malignant tumors. However, the understanding of anoikis' roles in osteosarcoma remains scarce. This study conducted an...
Anoikis is essential for the progression of many malignant tumors. However, the understanding of anoikis' roles in osteosarcoma remains scarce. This study conducted an extensive bioinformatics analysis to identify anoikis-related genes (ARGs), developed ARGs modeles for predicting OS and RFS, and evaluated the effect of these ARGs on osteosarcoma cell migration and invasion. The GSE16088 and GSE28425 datasets provided the differentially expressed genes (DEGs). The prognostic significance and functions of these DEGs were systematically investigated using several bioinformatics techniques. Transwell assays were conducted to determine the effect of OGT on osteosarcoma cell migration and invasion. Seven genes were identified as hub genes, including , and , while 71 ARGs were identified as DEGs. Four ARGs-, and -were used to develop an RFS-predicting model, whereas seven ARGs-, and -were used to develop an OS-predicting model in patients with osteosarcoma. In both the training and validation cohorts, high-risk group patients had significantly shorter OS and RFS duration than low-risk group patients. Furthermore, using the aforementioned ARGs, we developed clinically applicable nomograms for OS and RFS prediction. The proportion of tumor-infiltrating immune cells was significantly linked to risk scores. experiments revealed that knocking down OGT significantly inhibited the ability of MG63 and U2OS cells to invade and migrate. ARG-based gene signatures reliably predicted RFS and OS in osteosarcoma, and OGT showed promise as a potential biomarker. These findings contribute to a better understanding of ARGs' prognostic roles in osteosarcoma.
Topics: Humans; Anoikis; PPAR gamma; Osteosarcoma; Biological Assay; Bone Neoplasms; Prognosis; Phosphatidylinositol 3-Kinases
PubMed: 38217543
DOI: 10.18632/aging.205411 -
European Journal of Medical Research Jan 2024Bladder cancer is an epidemic and life-threating urologic carcinoma. Anoikis is a unusual type of programmed cell death which plays a vital role in tumor survival,...
BACKGROUND
Bladder cancer is an epidemic and life-threating urologic carcinoma. Anoikis is a unusual type of programmed cell death which plays a vital role in tumor survival, invasion and metastasis. Nevertheless, the relationship between anoikis and bladder cancer has not been understood thoroughly.
METHODS
We downloaded the transcriptome and clinical information of BLCA patients from TCGA and GEO databases. Then, we analyzed different expression of anoikis-related genes and established a prognostic model based on TCGA database by univariate Cox regression, lasso regression, and multivariate Cox regression. Then the Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curves were performed. GEO database was used for external validation. BLCA patients in TCGA database were divided into two subgroups by non-negative matrix factorization (NMF) classification. Survival analysis, different gene expression, immune cell infiltration and drug sensitivity were calculated. Finally, we verified the function of S100A7 in two BLCA cell lines.
RESULTS
We developed a prognostic risk model based on three anoikis-related genes including TPM1, RAC3 and S100A7. The overall survival of BLCA patients in low-risk groups was significantly better than high-risk groups in training sets, test sets and external validation sets. Subsequently, the checkpoint and immune cell infiltration had significant difference between two groups. Then we identified two subtypes (C and C) through NMF analysis and found CA had better OS and PFS than CB. Besides, the accuracy of risk model was verified by ROC analysis. Finally, we identified that knocking down S100A7 gene expression restrained the proliferation and invasion of bladder cancer cells.
CONCLUSION
We established and validated a bladder cancer prognostic model consisting of three genes, which can effectively evaluate the prognosis of bladder cancer patients. Additionally, through cellular experiments, we demonstrated the significant role of S100A7 in the metastasis and invasion of bladder cancer, suggesting its potential as a novel target for future treatments.
Topics: Humans; Anoikis; Urinary Bladder Neoplasms; Algorithms; Cell Line; Prognosis; S100 Calcium Binding Protein A7
PubMed: 38217031
DOI: 10.1186/s40001-024-01642-9 -
Journal of Cancer 2024Anoikis, a mechanism of programmed apoptosis, plays an important role in growth and metastasis of tumors. However, there are still few available comprehensive reports...
Anoikis, a mechanism of programmed apoptosis, plays an important role in growth and metastasis of tumors. However, there are still few available comprehensive reports on the impact of anoikis on colorectal cancer. A clustering analysis was done on 133 anoikis-related genes in GSE39582, and we compared clinical features between clusters, the tumor microenvironment was analyzed with algorithms such as "Cibersort" and "ssGSEA". We investigated risk scores of clinical feature groups and anoikis-associated gene mutations after creating a predictive model. We incorporated clinical traits to build a nomogram. Additionally, the quantitative real-time PCR was employed to investigate the mRNA expression of selected anoikis-associated genes. We identified two anoikis-related clusters with distinct prognoses, clinical characteristics, and biological functions. One of the clusters was associated with anoikis resistance, which activated multiple pathways encouraging tumor metastasis. In our prognostic model, oxaliplatin may be a sensitive drug for low-risk patients. The nomogram showed good ability to predict survival time. And SIRT3, PIK3CA, ITGA3, DAPK1, and CASP3 increased in CRC group through the PCR assay. Our study identified two distinct modes of anoikis in colorectal cancer, with active metastasis-promoting pathways inducing an anti-anoikis subtype, which has a stronger propensity for metastasis and a worse prognosis than an anoikis-activated subtype. Massive immune cell infiltration may be an indicator of anoikis resistance. Anoikis' role in the colorectal cancer remains to be investigated.
PubMed: 38213716
DOI: 10.7150/jca.91627 -
Redox Biology Apr 2024Significant efforts have focused on identifying targetable genetic drivers that support the growth of solid tumors and/or increase metastatic ability. During tumor...
Significant efforts have focused on identifying targetable genetic drivers that support the growth of solid tumors and/or increase metastatic ability. During tumor development and progression to metastatic disease, physiological and pharmacological selective pressures influence parallel adaptive strategies within cancer cell sub-populations. Such adaptations allow cancer cells to withstand these stressful microenvironments. This Darwinian model of stress adaptation often prevents durable clinical responses and influences the emergence of aggressive cancers with increased metastatic fitness. However, the mechanisms contributing to such adaptive stress responses are poorly understood. We now demonstrate that the p66ShcA redox protein, itself a ROS inducer, is essential for survival in response to physiological stressors, including anchorage independence and nutrient deprivation, in the context of poor outcome breast cancers. Mechanistically, we show that p66ShcA promotes both glucose and glutamine metabolic reprogramming in breast cancer cells, to increase their capacity to engage catabolic metabolism and support glutathione synthesis. In doing so, chronic p66ShcA exposure contributes to adaptive stress responses, providing breast cancer cells with sufficient ATP and redox balance needed to withstand such transient stressed states. Our studies demonstrate that p66ShcA functionally contributes to the maintenance of aggressive phenotypes and the emergence of metastatic disease by forcing breast tumors to adapt to chronic and moderately elevated levels of oxidative stress.
Topics: Humans; Female; Shc Signaling Adaptor Proteins; Breast Neoplasms; Src Homology 2 Domain-Containing, Transforming Protein 1; Oxidative Stress; Phenotype; Cell Line, Tumor; Tumor Microenvironment
PubMed: 38211442
DOI: 10.1016/j.redox.2024.103028 -
Aging Jan 2024The global prevalence of breast cancer necessitates the development of innovative prognostic markers and therapeutic strategies. This study investigated the prognostic...
Deciphering the prognostic significance of anoikis-related lncRNAs in invasive breast cancer: from comprehensive bioinformatics analysis to functional experimental validation.
The global prevalence of breast cancer necessitates the development of innovative prognostic markers and therapeutic strategies. This study investigated the prognostic implications of anoikis-related long non-coding RNAs (ARLs) in invasive breast cancer (IBC), which is an area that has not been extensively explored. By integrating the RNA sequence transcriptome and clinical data from The Cancer Genome Atlas (TCGA) database and employing advanced regression analyses, we devised a novel prognostic model based on ARL scores. ARL scores correlated with diverse clinicopathological parameters, cellular pathways, distinct mutation patterns, and immune responses, thereby affecting both immune cell infiltration and anticipated responses to chemotherapy and immunotherapy. Additionally, the overexpression of a specific lncRNA, , significantly impeded the proliferation and migration, as well as possibly the anoikis resistance of breast cancer cells. These findings highlight the potential of the ARL signature as a robust prognostic tool and a promising basis for personalized IBC treatment strategies.
Topics: Anoikis; Prognosis; RNA, Long Noncoding; Computational Biology; Databases, Factual; Neoplasms
PubMed: 38189818
DOI: 10.18632/aging.