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High-grade serous carcinoma (HGSC) is the most lethal gynecological malignancy in the United States. Late diagnosis and the emergence of chemoresistance have prompted studies into how the tumor microenvironment, and more recently tumor innervation, may be leveraged for HGSC prevention and interception. In addition to stess-induced sources, concentrations of the sympathetic neurotransmitter norepinephrine (NE) in the ovary increase during ovulation and after menopause. Importantly, NE exacerbates advanced HGSC progression. However, little is known about the role of NE in early disease pathogenesis. Here, we investigated the role of NE in instigating anchorage independence and micrometastasis of preneoplastic lesions from the fallopian tube epithelium (FTE) to the ovary, an essential step in HGSC onset. We found that in the presence of NE, FTE cell lines were able to survive in ultra-low-attachment (ULA) culture in a β-adrenergic receptor-dependent (β-AR-dependent) manner. Importantly, spheroid formation and cell viability conferred by treatment with physiological sources of NE were abrogated using the β-AR blocker propranolol. We have also identified that NE-mediated anoikis resistance may be attributable to downregulation of colony-stimulating factor 2. These findings provide mechanistic insight and identify targets that may be regulated by ovary-derived NE in early HGSC.

Spinal cord injury (SCI) is a serious disease without effective therapeutic strategies. To identify the potential treatments for SCI, it is extremely important to explore the underlying mechanism. Current studies demonstrate that anoikis might play an important role in SCI. In this study, we aimed to identify the key anoikis-related genes (ARGs) providing therapeutic targets for SCI. The mRNA expression matrix of GSE45006 was downloaded from the Gene Expression Omnibus (GEO) database, and the ARGs were downloaded from the Molecular Signatures Database (MSigDB database). Then, the potential differentially expressed ARGs were identified. Next, correlation analysis, gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein–protein interaction (PPI) analysis were employed for the differentially expressed ARGs. Moreover, miRNA-gene networks were constructed by the hub ARGs. Finally, RNA expression of the top ten hub ARGs was validated in the SCI cell model and rat SCI model. A total of 27 common differentially expressed ARGs were identified at different time points (1, 3, 7, and 14 days) following SCI. The GO and KEGG enrichment analysis of these ARGs indicated several enriched terms related to proliferation, cell cycle, and apoptotic process. The PPI results revealed that most of the ARGs interacted with each other. Ten hub ARGs were further screened, and all the 10 genes were validated in the SCI cell model. In the rat model, only seven genes were validated eventually. We identified 27 differentially expressed ARGs of the SCI through bioinformatic analysis. Seven real hub ARGs (CCND1, FN1, IGF1, MYC, STAT3, TGFB1, and TP53) were identified eventually. These results may expand our understanding of SCI and contribute to the exploration of potential SCI targets. [ABSTRACT FROM AUTHOR]

Background: Hepatocellular carcinoma (HCC) poses a significant global health challenge due to its poor prognosis and limited therapeutic modalities. Anoikis and ErbB signaling pathways are pivotal in cancer cell proliferation and metastasis, but their relevance in HCC remains insufficiently explored. Methods: This study evaluates the prognostic significance of anoikis and ErbB signaling pathways in HCC by utilizing data from The Cancer Genome Atlas (TCGA), the International Cancer Genome Consortium (ICGC), three additional independent validation cohorts, and an in-house cohort. Advanced bioinformatics analyses and 167 machine learning models based on leave-oneout cross-validation (LOOCV) were used to predict HCC prognosis and assess outcomes of immune-targeted therapies. Additionally, key biological processes of the anoikis and ErbB signaling pathways in HCC were further investigated. Results: The single sample Gene Set Enrichment Analysis revealed a strong correlation between upregulated ErbB signaling in high anoikis-expressing tumors and poor clinical outcomes. The development of the Anoikis-ErbB Related Signature (AERS) using the LASSO + RSF model demonstrated robust predictive capabilities, as validated across multiple patient cohorts, and proved effective in predicting responses to immune-targeted therapies. Further investigation highlighted activated NOTCH signaling pathways and decreased macrophage infiltration was associated with resistance to sorafenib and immune checkpoint inhibitors, as evidenced by bulk and single-cell RNA sequencing (scRNA-seq). Conclusion: AERS provides a novel tool for clinical prognosis and paves the way for immune-targeted therapeutic approaches, underscoring the potential of integrated molecular profiling in enhancing treatment strategies for HCC. [ABSTRACT FROM AUTHOR]

Metastatic lung cancer is a highly prevalent cancer with a very low chance of long‐term survival. Metastasis at secondary sites requires that cancer cells develop anoikis resistance to survive during circulation. High levels of bone sialoprotein (BSP), a member of the small integrin‐binding ligand N‐linked glycoproteins (SIBLINGs), have been shown to promote the spread of lung cancer cells; however, the effects of BSP in anoikis resistance are largely unknown. In this study, we determined that BSP promotes anoikis resistance in lung cancer cells. BSP was also shown to promote the expression of E‐cadherin and vimentin (epithelial‐to‐mesenchymal transition markers, which have been utilized as indicators of anoikis resistance). It appears that BSP facilitates MMP‐14‐dependent anoikis resistance by inhibiting the synthesis of miR‐150‐5p and activating the ERK signalling pathway. Knockdown of BSP expression was shown to block lung cancer metastasis by lowering anoikis resistance in vivo. These results indicate that BSP is a promising target to deal with anoikis resistance and metastasis in human lung cancers. [ABSTRACT FROM AUTHOR]

Background: Bone metastasis from prostate cancer severely impacts patient outcomes and quality of life. Anoikis, a form of programmed cell death triggered by the loss of cell-matrix interactions, plays a critical role in cancer progression. However, its precise relationship with prostate cancer-induced bone metastasis remains unclear. This study aims to elucidate this relationship, focusing on anoikis-related gene signatures, molecular pathways, and therapeutic implications. Methods: We used the TCGA-PRAD dataset for training, with MSKCC and GSE70769 as validation cohorts. To evaluate immunotherapy efficacy, we examined IMvigor 210 and GSE91016 datasets, and GSE137829 provided single-cell insights into prostate cancer. Specific anoikis-related genes (ARGs) were identified, and Random Survival Forest analysis and multivariate Cox regression were employed to develop anoikis-linked features. The ‘clustanoikisProfilanoikis’ and ‘GSEA’ packages were used to explore potential ARG-related pathways. Results: Analyzing 553 samples from TCGA, 231 from MSKCC, 94 from GSE70769, and single-cell data from 6 prostate cancer patients (GSE137829), we constructed a prognostic model based on 9 ARGs. GSVA revealed upregulation of carcinogenic pathways, including epithelial-mesenchymal transition, E2F targets, and angiogenesis, with downregulation of metabolic pathways. Significant differences in somatic mutations were observed between cohorts, with a positive correlation between anoikis scores and tumor mutational burden (TMB). Immune landscape analysis suggested high-risk patients might benefit more from chemotherapy than immunotherapy based on their risk score. Single-cell analysis indicated overactivation of carcinogenic pathways in the high anoikis score group. Conclusion: This study elucidates the complex interplay between anoikis and bone metastasis in prostate cancer. Our findings highlight the critical role of anoikis in metastatic progression, enhancing the understanding of key biomarkers and molecular dynamics. The identified anoikis-related gene signatures and disrupted pathways offer promising avenues for predictive and therapeutic strategies in prostate cancer management. [ABSTRACT FROM AUTHOR]

The extracellular matrix (ECM) governs a wide spectrum of cellular fate processes, with a particular emphasis on anoikis, an integrin‐dependent form of cell death. Currently, anoikis is defined as an intrinsic apoptosis. In contrast to traditional apoptosis and necroptosis, integrin correlates ECM signaling with intracellular signaling cascades, describing the full process of anoikis. However, anoikis is frequently overlooked in physiological and pathological processes as well as traditional in vitro research models. In this review, we summarized the role of anoikis in physiological and pathological processes, spanning embryonic development, organ development, tissue repair, inflammatory responses, cardiovascular diseases, tumor metastasis, and so on. Similarly, in the realm of stem cell research focused on the functional evolution of cells, anoikis offers a potential solution to various challenges, including in vitro cell culture models, stem cell therapy, cell transplantation, and engineering applications, which are largely based on the regulation of cell fate by anoikis. More importantly, the regulatory mechanisms of anoikis based on molecular processes and ECM signaling will provide new strategies for therapeutic interventions (drug therapy and cell‐based therapy) in disease. In summary, this review provides a systematic elaboration of anoikis, thus shedding light on its future research. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Metastasis, the leading cause of renal cell carcinoma (RCC) mortality, involves cancer cells resisting anoikis and invading. Until now, the role of the matrix metalloproteinase (MMP)-related enzyme, A disintegrin and metalloprotease with thrombospondin motifs 1 (ADAMTS1), in RCC anoikis regulation remains unclear. Methods: The clinical significance of ADAMTS1 and its associated molecules in patients with RCC was investigated using data from the Gene Expression Omnibus (GEO) and TCGA datasets. Human phosphoreceptor tyrosine kinase (RTK) array, luciferase reporter assays, immunoprecipitation (IP) assays, western blotting, and real-time reverse-transcription quantitative polymerase chain reaction (RT–qPCR) were used to elucidate the underlying mechanisms of ADAMTS1. Functional assays, including anoikis resistance assays, invasion assays, and a Zebrafish xenotransplantation model, were conducted to assess the roles of ADAMTS1 in conferring resistance to anoikis in RCC. Results: This study found elevated ADAMTS1 transcripts in RCC tissues that were correlated with a poor prognosis. ADAMTS1 manipulation significantly affected cell anoikis through the mitochondrial pathway in RCC cells. Human receptor tyrosine kinase (RTK) array screening identified that epidermal growth factor receptor (EGFR) activation was responsible for ADAMTS1-induced anoikis resistance and invasion. Further investigations revealed that enzymatically active ADAMTS1-induced versican V1 (VCAN V1) proteolysis led to EGFR transactivation, which in turn, through positive feedback, regulated ADAMTS1. Additionally, ADAMTS1 can form a complex with p53 to influence EGFR signaling. In vivo, VCAN or EGFR knockdown reversed ADAMTS1-induced prometastatic characteristics of RCC. A clinical analysis revealed a positive correlation between ADAMTS1 and VCAN or the EGFR and patients with RCC with high ADAMTS1 and VCAN expression had the worst prognoses. Conclusions: Our results collectively uncover a novel cyclic axis involving ADAMTS1–VCAN–EGFR, which significantly contributes to RCC invasion and resistance to anoikis, thus presenting a promising therapeutic target for RCC metastasis. [ABSTRACT FROM AUTHOR]

Background: Breast cancer (BC) is the most common cancer in women, and its progression is closely related to the phenomenon of anoikis. Anoikis, the specific programmed death resulting from a lack of contact between cells and the extracellular matrix, has recently been recognized as playing a critical role in tumor initiation, maintenance, and treatment. The ability of cancer cells to resist anoikis leads to cancer progression and metastatic colonization. However, the impact of anoikis on the prognosis of BC patients remains unclear. Method: This study utilized data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to collect transcriptome and clinical data of BC patients. Anoikis-related genes (ARGs) were classified into subtypes A and B through consensus clustering. Subsequently, survival prognosis analysis, immune cell infiltration analysis, and functional enrichment analysis were performed for both subtypes. Using the Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, a set of 10 ARGs related to prognosis was identified. Immune cell infiltration and tumor microenvironment analyses were conducted on these 10 ARGs to develop a prognostic model. Furthermore, single-cell data analysis and real-time polymerase chain reaction (RT-PCR) analysis were employed to study the expression of the 10 identified prognostic ARGs in BC cells. Results: One hundred thirty-five ARGs were identified as differentially expressed genes in the TCGA and GEO databases, with 42 of them associated with the survival prognosis of BC patients. Analyses involving Principal Component Analysis (PCA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Uniform Manifold Approximation and Projection (UMAP) revealed distinct expression patterns of ARGs between types A and B. Patients in type A exhibited worse survival prognosis and lower immune cell infiltration compared to type B. Subsequent analyses identified 10 key ARGs (YAP1, PIK3R1, BAK1, PHLDA2, EDA2R, LAMB3, CD24, SLC2A1, CDC25C, and SLC39A6) relevant to BC prognosis. Kaplan–Meier analysis indicated that high-risk patients based on these ARGs had a poorer BC prognosis. Additionally, Cox regression analysis established gender, age, T (tumor), N (nodes), and risk score as predictive factors in a nomogram model for BC. The model demonstrated diagnostic value for BC patients at 1, 3, and 5 years. Decision curve analysis (DCA) verified the risk score as a reliable predictor of BC patient survival rates. Moreover, RT-PCR results confirmed differential expressions of YAP1, PIK3R1, BAK1, PHLDA2, CD24, SLC2A1, and CDC25C in BC cells, with SLC39A6, EDA2R, and LAMB3 showing low expression levels. Conclusion: ARGs markers can be used as BC biomarkers for risk stratification and survival prediction in BC patients. Besides, ARGs can be used as stratification factors for individualized and precise treatment of BC patients. [ABSTRACT FROM AUTHOR]

Background: Anoikis and epithelial-mesenchymal transition (EMT) are pivotal in the distant metastasis of lung adenocarcinoma (LUAD). A detailed understanding of their interplay and the identification of key genes is vital for effective therapeutic strategies against LUAD metastasis. Methods: Key prognostic genes related to anoikis and EMT were identified through univariate Cox regression analysis. We utilized ten machine learning algorithms to develop the Anoikis and EMT-Related Optimal Model (AEOM). The TCGA-LUAD dataset served as the training cohort, while six additional international multicenter LUAD datasets were employed as validation cohorts. The average concordance index (c-index) was used to evaluate model performance and identify the most effective model. Subsequent multi-omics analyses were conducted to explore differences in pathway enrichment, immune infiltration, and mutation landscapes between high and low AEOM groups. Experimental validation demonstrated that RHPN2, a key biomarker within the model, acts as an oncogene facilitating LUAD progression. Results: The AEOM displayed superior prognostic predictive performance for LUAD patients, outperforming numerous previously published LUAD signatures. Biologically, the AEOM was notably associated with immune features; the high AEOM group exhibited decreased immune activity and a tendency towards immune-cold tumors, as well as a higher tumor mutational burden (TMB). Subgroup analysis revealed that the low AEOM + high TMB group had the most favorable prognosis. The high AEOM group was primarily enriched in cell cycle-related pathways, promoting cancer cell proliferation. RHPN2, a crucial gene within the AEOM (correlation = 0.85, P < 0.05), was linked to poorer prognosis in LUAD patients with elevated RHPN2 expression. Further in vitro experiments showed that RHPN2 modulates LUAD cell proliferation and invasion. Conclusion: The AEOM provides a robust prognostic model for LUAD, uncovering critical immune and biological pathways, with RHPN2 identified as a key oncogenic driver. These findings offer valuable insights for targeted therapies and enhanced patient outcomes. [ABSTRACT FROM AUTHOR]

Simple Summary: Drugs work by binding to a specific 3D structure on a protein. Drug discovery has historically been driven by prior knowledge of function, either of a protein or chemical. This knowledge of function then drives investigations to probe chemical/protein interactions. We undertook a different approach. We first identified unique 3D structures, agnostic of function, and investigated whether they could lead us to innovative therapeutics. Using a synchrotron-based X-ray source, we first determined high-resolution structures of hundreds of proteins. With a supercomputer running analytical programs created by us, we identified novel 3D structures and screened for chemicals binding them. We then tested their ability to inhibit cancer growth without damaging normal cells. We identified a potent inhibitor of a deadly cancer, melanoma. It was not toxic to normal cells even at 2100-fold higher doses. It worked by inducing anoikis, a fundamental process of known importance for cancer. Therapeutics that selectively induce anoikis are needed. In summary, we demonstrate the power of using a 3D protein structure as the starting point to discover new biology and drugs. Drug discovery historically starts with an established function, either that of compounds or proteins. This can hamper discovery of novel therapeutics. As structure determines function, we hypothesized that unique 3D protein structures constitute primary data that can inform novel discovery. Using a computationally intensive physics-based analytical platform operating at supercomputing speeds, we probed a high-resolution protein X-ray crystallographic library developed by us. For each of the eight identified novel 3D structures, we analyzed binding of sixty million compounds. Top-ranking compounds were acquired and screened for efficacy against breast, prostate, colon, or lung cancer, and for toxicity on normal human bone marrow stem cells, both using eight-day colony formation assays. Effective and non-toxic compounds segregated to two pockets. One compound, Dxr2-017, exhibited selective anti-melanoma activity in the NCI-60 cell line screen. In eight-day assays, Dxr2-017 had an IC50 of 12 nM against melanoma cells, while concentrations over 2100-fold higher had minimal stem cell toxicity. Dxr2-017 induced anoikis, a unique form of programmed cell death in need of targeted therapeutics. Our findings demonstrate proof-of-concept that protein structures represent high-value primary data to support the discovery of novel acting therapeutics. This approach is widely applicable. [ABSTRACT FROM AUTHOR]

Hypothermic preservation (HP) is highly desired for the maintenance of the viability of living cell specimens, e.g. rare cells in whole-blood samples or therapeutic cells, in an unfrozen state. However, the extension of the viable preservation time is a challenge because of the multiple injuries suffered by hypothermically preserved cells. Here, based on a dynamic bond crosslinked zwitterionic hydrogel, we established a sensing preservation system that could monitor the levels of reactive oxygen species (ROS) via real-time electronic signals and intelligent control of antioxidant addition, to completely prevent an excess of ROS in the whole-cell specimen. Furthermore, the hydrogel-based system can counter the extracellular-matrix-loss-induced anoikis of living cells. Based on the design aimed at affording protection against two primary HP injuries (i.e. ROS overproduction and anoikis) to cells, this system extended the preservation time of cell specimens under refrigerated conditions to 24 days. After preservation, the use of a mild cell retrieval process guaranteed the activity of the preserved living cells. This work not only possesses the potential to facilitate intelligent cell-based clinical applications, but also paves the way for the preparation of living materials that can host programmed cells with long-term survival. An intelligent system based on a zwitterionic sensing hydrogel is established, which can afford ultra-long hypothermic cell-preservation times of up to 24 days. The system enables the real-time monitoring of ROS overproduction and intelligent antioxidant addition, because of the merging of the smart hydrogel with a computer intelligent detection and control system. Furthermore, the automatic addition of an antioxidant according to the ROS-signal changes produced by the ZBA hydrogel effectively prevented HP lesions, including ROS over-production and ECM loss, in the preserved living cells. Subsequently, the system could also be gently dissociated, to retrieve the preserved cells. This work provides a solution for the real-time monitoring and long-term HP of living specimens, which holds the promise of benefiting cell-based medicine and the development of genetically programmed cell-based living materials. [Display omitted] [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is the most common neurodegenerative disease. Anoikis is a new type of programmed cell death that can lead to the development of many diseases. The purpose of this study is to investigate the role of anoikis-related genes (ANRGs) in AD and establish a prediction model. Based on GSE33000, 1 666 differentially expressed genes are screened, and 10 genes are obtained by intersection with 53 ANRGs. Using the above genes, 310 patients with AD are classified into three subtypes by unsupervised clustering, and the differences of immune microenvironment among different subtypes are further analyzed. After that, WGCNA algorithm is used to screen the characteristic genes associated with AD, and combined with four machine learning models (RF, GLM, SVM and XGB), the AD risk prediction model is constructed and verified in three external cohorts (GSE5281, GSE29378 and GSE122063). Finally, we successfully construct a nomogram based on five AD characteristic genes (TM6SF1, SMYD3, OXCT1, MAP1B and ITPKB) of the XGB model to provide reference for clinical prediction of AD. [ABSTRACT FROM AUTHOR]

Anoikis is a distinct type of programmed cell death and a unique mechanism for tumor progress. However, its exact function in gastric cancer (GC) remains unknown. This study aims to investigate the function of anoikis-related lncRNA (ar-lncRNA) in the prognosis of GC and its immunological infiltration. The ar-lncRNAs were derived from RNA sequencing data and associated clinical information obtained from The Cancer Genome Atlas. Pearson correlation analysis, differential screening, LASSO and Cox regression were utilized to identify the typical ar-lncRNAs with prognostic significance, and the corresponding risk model was constructed, respectively. Comprehensive methods were employed to assess the clinical characteristics of the prediction model, ensuring the accuracy of the prediction results. Further analysis was conducted on the relationship between immune microenvironment and risk features, and sensitivity predictions were made about anticancer medicines. A risk model was built according to seven selected ar-lncRNAs. The model was validated and the calibration plots were highly consistent in validating nomogram predictions. Further analyses revealed the great accuracy of the model and its ability to serve as a stand-alone GC prognostic factor. We subsequently disclosed that high-risk groups display significant enrichment in pathways related to tumors and the immune system. Additionally, in tumor immunoassays, notable variations in immune infiltrates and checkpoints were noted between different risk groups. This study proposes, for the first time, that prognostic signatures of ar-lncRNA can be established in GC. These signatures accurately predict the prognosis of GC and offer potential biomarkers, suggesting new avenues for basic research, prognosis prediction and personalized diagnosis and treatment of GC. [ABSTRACT FROM AUTHOR]

Background/Aim: Patients diagnosed with advanced metastatic colorectal cancer (CRC) confront a bleak prognosis characterized by low survival rates. Anoikis, the programmed apoptosis resistance exhibited by metastatic cancer cells, is a crucial factor in this scenario. Materials and Methods: We employed bulk flow cytometry and RT-qPCR assays, conducted in vivo experiments with mice and zebrafish, and analyzed patient tissues to examine the effects of the B cell-specific Moloney murine leukemia virus insertion site 1 (Bmi1)-midkine (MDK) axis on the cellular response to anoikis. Bmi1 is pivotal in tumorigenesis. This study elucidated the involvement of Bmi1 in conferring anoikis resistance in CRC and explored its downstream targets associated with metastasis. Results: Elevated levels of Bmi1 expression correlated with distant metastasis in CRC. Suppression of Bmi1 significantly diminished the metastatic potential of CRC cells. Inhibition of Bmi1 led to an increase in the proportion of apoptotic SW620 cells detached from the matrix. This effect was further enhanced by the addition of irinotecan, a topoisomerase I inhibitor. Furthermore, Bmi1 was found to synergize with MDK in modulating CRC viability, with consistent expression patterns observed in in vivo models and clinical tissue specimens. In summary, Bmi1 acted as a regulator of CRC metastatic capability by conferring anoikis resistance. Additionally, it collaborated with MDK to facilitate invasion and distant metastasis. Conclusion: Targeting Bmi1 may offer a promising adjunctive therapeutic strategy when administering traditional chemotherapy regimens to patients with advanced CRC. [ABSTRACT FROM AUTHOR]

Metastasis remains the principal trigger for relapse and mortality across diverse cancer types. Circulating tumor cells (CTCs), which originate from the primary tumor or its metastatic sites, traverse the vascular system, serving as precursors in cancer recurrence and metastasis. Nevertheless, before CTCs can establish themselves in the distant parenchyma, they must overcome significant challenges present within the circulatory system, including hydrodynamic shear stress (HSS), oxidative damage, anoikis, and immune surveillance. Recently, there has been a growing body of compelling evidence suggesting that a specific subset of CTCs can persist within the bloodstream, but the precise mechanisms of their survival remain largely elusive. This review aims to present an outline of the survival challenges encountered by CTCs and to summarize the recent advancements in understanding the underlying survival mechanisms, suggesting their implications for cancer treatment. [ABSTRACT FROM AUTHOR]

Abstract Background Breast cancer (BC) is the most common cancer in women, and its progression is closely related to the phenomenon of anoikis. Anoikis, the specific programmed death resulting from a lack of contact between cells and the extracellular matrix, has recently been recognized as playing a critical role in tumor initiation, maintenance, and treatment. The ability of cancer cells to resist anoikis leads to cancer progression and metastatic colonization. However, the impact of anoikis on the prognosis of BC patients remains unclear. Method This study utilized data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to collect transcriptome and clinical data of BC patients. Anoikis-related genes (ARGs) were classified into subtypes A and B through consensus clustering. Subsequently, survival prognosis analysis, immune cell infiltration analysis, and functional enrichment analysis were performed for both subtypes. Using the Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, a set of 10 ARGs related to prognosis was identified. Immune cell infiltration and tumor microenvironment analyses were conducted on these 10 ARGs to develop a prognostic model. Furthermore, single-cell data analysis and real-time polymerase chain reaction (RT-PCR) analysis were employed to study the expression of the 10 identified prognostic ARGs in BC cells. Results One hundred thirty-five ARGs were identified as differentially expressed genes in the TCGA and GEO databases, with 42 of them associated with the survival prognosis of BC patients. Analyses involving Principal Component Analysis (PCA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Uniform Manifold Approximation and Projection (UMAP) revealed distinct expression patterns of ARGs between types A and B. Patients in type A exhibited worse survival prognosis and lower immune cell infiltration compared to type B. Subsequent analyses identified 10 key ARGs (YAP1, PIK3R1, BAK1, PHLDA2, EDA2R, LAMB3, CD24, SLC2A1, CDC25C, and SLC39A6) relevant to BC prognosis. Kaplan–Meier analysis indicated that high-risk patients based on these ARGs had a poorer BC prognosis. Additionally, Cox regression analysis established gender, age, T (tumor), N (nodes), and risk score as predictive factors in a nomogram model for BC. The model demonstrated diagnostic value for BC patients at 1, 3, and 5 years. Decision curve analysis (DCA) verified the risk score as a reliable predictor of BC patient survival rates. Moreover, RT-PCR results confirmed differential expressions of YAP1, PIK3R1, BAK1, PHLDA2, CD24, SLC2A1, and CDC25C in BC cells, with SLC39A6, EDA2R, and LAMB3 showing low expression levels. Conclusion ARGs markers can be used as BC biomarkers for risk stratification and survival prediction in BC patients. Besides, ARGs can be used as stratification factors for individualized and precise treatment of BC patients.

Abstract Background Anoikis and epithelial-mesenchymal transition (EMT) are pivotal in the distant metastasis of lung adenocarcinoma (LUAD). A detailed understanding of their interplay and the identification of key genes is vital for effective therapeutic strategies against LUAD metastasis. Methods Key prognostic genes related to anoikis and EMT were identified through univariate Cox regression analysis. We utilized ten machine learning algorithms to develop the Anoikis and EMT-Related Optimal Model (AEOM). The TCGA-LUAD dataset served as the training cohort, while six additional international multicenter LUAD datasets were employed as validation cohorts. The average concordance index (c-index) was used to evaluate model performance and identify the most effective model. Subsequent multi-omics analyses were conducted to explore differences in pathway enrichment, immune infiltration, and mutation landscapes between high and low AEOM groups. Experimental validation demonstrated that RHPN2, a key biomarker within the model, acts as an oncogene facilitating LUAD progression. Results The AEOM displayed superior prognostic predictive performance for LUAD patients, outperforming numerous previously published LUAD signatures. Biologically, the AEOM was notably associated with immune features; the high AEOM group exhibited decreased immune activity and a tendency towards immune-cold tumors, as well as a higher tumor mutational burden (TMB). Subgroup analysis revealed that the low AEOM + high TMB group had the most favorable prognosis. The high AEOM group was primarily enriched in cell cycle-related pathways, promoting cancer cell proliferation. RHPN2, a crucial gene within the AEOM (correlation = 0.85, P

Abstract Background Metastasis, the leading cause of renal cell carcinoma (RCC) mortality, involves cancer cells resisting anoikis and invading. Until now, the role of the matrix metalloproteinase (MMP)-related enzyme, A disintegrin and metalloprotease with thrombospondin motifs 1 (ADAMTS1), in RCC anoikis regulation remains unclear. Methods The clinical significance of ADAMTS1 and its associated molecules in patients with RCC was investigated using data from the Gene Expression Omnibus (GEO) and TCGA datasets. Human phosphoreceptor tyrosine kinase (RTK) array, luciferase reporter assays, immunoprecipitation (IP) assays, western blotting, and real-time reverse-transcription quantitative polymerase chain reaction (RT–qPCR) were used to elucidate the underlying mechanisms of ADAMTS1. Functional assays, including anoikis resistance assays, invasion assays, and a Zebrafish xenotransplantation model, were conducted to assess the roles of ADAMTS1 in conferring resistance to anoikis in RCC. Results This study found elevated ADAMTS1 transcripts in RCC tissues that were correlated with a poor prognosis. ADAMTS1 manipulation significantly affected cell anoikis through the mitochondrial pathway in RCC cells. Human receptor tyrosine kinase (RTK) array screening identified that epidermal growth factor receptor (EGFR) activation was responsible for ADAMTS1-induced anoikis resistance and invasion. Further investigations revealed that enzymatically active ADAMTS1-induced versican V1 (VCAN V1) proteolysis led to EGFR transactivation, which in turn, through positive feedback, regulated ADAMTS1. Additionally, ADAMTS1 can form a complex with p53 to influence EGFR signaling. In vivo, VCAN or EGFR knockdown reversed ADAMTS1-induced prometastatic characteristics of RCC. A clinical analysis revealed a positive correlation between ADAMTS1 and VCAN or the EGFR and patients with RCC with high ADAMTS1 and VCAN expression had the worst prognoses. Conclusions Our results collectively uncover a novel cyclic axis involving ADAMTS1–VCAN–EGFR, which significantly contributes to RCC invasion and resistance to anoikis, thus presenting a promising therapeutic target for RCC metastasis.

AbstractOsteoarthritis (OA) is a degenerative disease closely associated with Anoikis. The objective of this work was to discover novel transcriptome-based anoikis-related biomarkers and pathways for OA progression.The microarray datasets GSE114007 and GSE89408 were downloaded using the Gene Expression Omnibus (GEO) database. A collection of genes linked to anoikis has been collected from the GeneCards database. The intersection genes of the differential anoikis-related genes (DEARGs) were identified using a Venn diagram. Infiltration analyses were used to identify and study the differentially expressed genes (DEGs). Anoikis clustering was used to identify the DEGs. By using gene clustering, two OA subgroups were formed using the DEGs. GSE152805 was used to analyse OA cartilage on a single cell level. 10 DEARGs were identified by lasso analysis, and two Anoikis subtypes were constructed. MEgreen module was found in disease WGCNA analysis, and MEturquoise module was most significant in gene clusters WGCNA. The XGB, SVM, RF, and GLM models identified five hub genes (CDH2, SHCBP1, SCG2, C10orf10, P FKFB3), and the diagnostic model built using these five genes performed well in the training and validation cohorts. analysing single-cell RNA sequencing data from GSE152805, including 25,852 cells of 6 OA cartilage.

ObjectiveTo construct a prognostic risk scoring model for gastric cancer (GC) anoikis-related genes (ARGs) based on least absolute shrinkage and selection operator (LASSO) regression, and analyze the relationship between anoikis and prognosis of gastric cancer as well as the significance of the model in immunotherapy and chemotherapy of gastric cancer patients. MethodsDifferentially expressed prognostic anoikis-related genes (ARGs) in gastric cancer and adjacent tissues were screened through The Cancer Genome Atlas (TCGA) database and the Molecular Signatures Database (MSigDB); key anoikis genes were selected based on LASSO regression analysis to construct a prognostic risk scoring model, and patients were divided into high-risk and low-risk groups with the median risk score as the cutoff point. Gene expression levels in gastric cancer clinical samples and cells were detected by real-time quantitative PCR (RT-qPCR); Kaplan-Meier (KM) survival curves, univariate and multivariate Cox regression analyses were used to verify the predictive efficiency of the prognostic risk scoring model for the prognosis of gastric cancer patients; CIBERSORT and ESTIMATE algorithms were used to analyze the immune cell infiltration levels in patients with different risk groups; the correlation between risk scores and immune checkpoint expression levels in gastric cancer patients was analyzed using the R package "ggplot2" and "ggExtra", and the correlation between tumor mutation burden (TMB) and risk scores was assessed; chemotherapy drug sensitivity analysis was used to evaluate the value of the constructed prognostic risk scoring model in gastric cancer chemotherapy. ResultsSix key ARGs (VCAN, FEN1, BRIP1, CNTN1, P3H2, DUSP1) were screened out based on LASSO regression analysis, and a prognostic risk scoring model was constructed. RT-qPCR detection showed that VCAN, FEN1, and BRIP1 genes were highly expressed in gastric cancer tissues and cells (P < 0.05), while CNTN1, P3H2, and DUSP1 genes were lowly expressed (P < 0.05); Kaplan-Meier survival curve analysis found that the survival rate of patients in the high-risk group was significantly lower than that in the low-risk group (P < 0.001), and there were statistically significant differences in survival rate and TMB levels between high- and low-risk group patients (P < 0.05); univariate and multivariate analyses showed that tumor stage, age, and risk score were significantly associated with survival in gastric cancer patients (P < 0.05); immune cell infiltration analysis showed that the tumor immune matrix score was significantly higher in the high-risk group than in the low-risk group (P < 0.05), and the constructed prognostic risk scoring model can be used as an indicator of the tumor immune microenvironment (TIME) status; analysis using the R package "ggplot2" and "ggExtra" showed that the risk score of the constructed model was positively correlated with the upregulated expression of immune checkpoints TIM3, VISTA, TIGIT, BTLA, and B7-H3 (r = 0.26, 0.40, 0.16, 0.26, 0.21, P < 0.05), and TMB level was negatively correlated with risk score (R = – 0.4, P < 0.05); the constructed prognostic risk scoring model can be used to guide chemotherapy for gastric cancer patients. ConclusionThe prognostic risk scoring model constructed based on anoikis-related genes can be used to predict the prognosis of gastric cancer patients; the risk genes in the model can serve as potential targets for gastric cancer treatment, providing a reference for individualized treatment of gastric cancer.

Tumor metastasis, the apex of cancer progression, poses a formidable challenge in therapeutic endeavors. Circulating tumor cells (CTCs), resilient entities originating from primary tumors or their metastases, significantly contribute to this process by demonstrating remarkable adaptability. They survive shear stress, resist anoikis, evade immune surveillance, and thwart chemotherapy. This comprehensive review aims to elucidate the intricate landscape of CTC formation, metastatic mechanisms, and the myriad factors influencing their behavior. Integral signaling pathways, such as integrin-related signaling, cellular autophagy, epithelial-mesenchymal transition, and interactions with platelets, are examined in detail. Furthermore, we explore the realm of precision nanomedicine design, with a specific emphasis on the anoikis‒platelet interface. This innovative approach strategically targets CTC survival mechanisms, offering promising avenues for combatting metastatic cancer with unprecedented precision and efficacy. The review underscores the indispensable role of the rational design of platelet-based nanomedicine in the pursuit of restraining CTC-driven metastasis.

Jiaqiong Lin,1,2 Yan Lin,3 Xiaoyong Li,4 Fei He,5 Qinyuan Gao,3 Yuanjun Wang,3 Zena Huang,3 Fu Xiong5,6 1Microbiome Medicine Center, Department of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, 510282, People’s Republic of China; 2Dongguan Maternal and Child Health Care Hospital, Postdoctoral Innovation Practice Base of Southern Medical University, Dongguan, People’s Republic of China; 3Yunkang School of Medicine and Health, Nanfang College, Guangzhou, People’s Republic of China; 4General Surgery Department; Guangdong Provincial Key Laboratory of Major Obstetric Diseases; Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology; The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of China; 5Department of Medical Genetics/Experimental Education/Administration Center, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, People’s Republic of China; 6Department of Fetal Medicine and Prenatal Diagnosis, Zhujiang Hospital, Southern Medical University, Guangzhou, People’s Republic of ChinaCorrespondence: Fu Xiong, Department of Medical Genetics/Experimental Education/Administration Center, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, People’s Republic of China, Email xiongfu@smu.edu.cn Zena Huang, Yunkang School of Medicine and Health, Nanfang College, Guangzhou, 510970, People’s Republic of China, Email 506647168@qq.comBackground: Diabetic kidney disease (DKD) is an intricate complication of diabetes with limited treatment options. Anoikis, a programmed cell death activated by loss of cell anchorage to the extracellular matrix, participated in various physiological and pathological processes. Our study aimed to elucidate the role of anoikis-related genes in DKD pathogenesis.Methods: Differentially expressed genes (DEGs) associated with anoikis in DKD were identified. Weighted gene co-expression network analysis (WGCNA) was conducted to identify DKD-correlated modules and assess their functional implications. A diagnostic model for DKD was developed using LASSO regression and Gene set variation analysis (GSVA) was performed for enrichment analysis. Experimental validation was employed to validate the significance of selected genes in the progression of DKD.Results: We identified 10 anoikis-related DEGs involved in key signaling pathways impacting DKD progression. WGCNA highlighted the yellow module’s significant enrichment in immune response and regulatory pathways. Correlation analysis further revealed the association between immune infiltration and anoikis-related DEGs. Our LASSO regression-based diagnostic model demonstrated a well-predictive efficacy with seven identified genes. GSVA indicated that gene function in the high-risk group was primarily associated with immune regulation. Further experimental validation using diabetic mouse models and data analysis in the single-cell dataset confirmed the significance of PYCARD and SFN in DKD progression. High glucose stimulation in RAW264.7 and TCMK-1 cells showed significantly increased expression levels of both Pycard and Sfn. Co-expression analysis demonstrated distinct functions of PYCARD and SFN, with KEGG pathway analysis showing significant enrichment in immune regulation and cell proliferation pathway.Conclusion: In conclusion, our study provides valuable insights into the molecular mechanisms involved in DKD pathogenesis, specifically highlighting the role of anoikis-related genes in modulating immune infiltration. These findings suggest that targeting these genes may hold promise for future diagnostic and therapeutic approaches in DKD management.Keywords: diabetic kidney disease, anoikis, immune infiltration, biomarker, PYCARD, SFN

Abstract 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.

Abstract Background The intermediate filament protein vimentin is widely recognized as a molecular marker of epithelial-to-mesenchymal transition. Although vimentin expression is strongly associated with cancer metastatic potential, the exact role of vimentin in cancer metastasis and the underlying mechanism of its pro-metastatic functions remain unclear. Results This study revealed that vimentin can enhance integrin β1 surface expression and induce integrin-dependent clustering of cells, shielding them against anoikis cell death. The increased integrin β1 surface expression in suspended cells was caused by vimentin-mediated protection of the internal integrin β1 pool against lysosomal degradation. Additionally, cell detachment was found to induce vimentin Ser38 phosphorylation, allowing the translocation of internal integrin β1 to the plasma membrane. Furthermore, the use of an inhibitor of p21-activated kinase PAK1, one of the kinases responsible for vimentin Ser38 phosphorylation, significantly reduced cancer metastasis in animal models. Conclusions These findings suggest that vimentin can act as an integrin buffer, storing internalized integrin β1 and releasing it when needed. Overall, this study provides insights regarding the strong correlation between vimentin expression and cancer metastasis and a basis for blocking metastasis using this novel therapeutic mechanism.

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

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

Triple‐negative breast cancer (TNBC) poses a challenging prognosis due to early metastasis driven by anoikis resistance. Identifying crucial regulators to overcome this resistance is vital for improving patient outcomes. In this study, a genome‐wide CRISPR/Cas9 knockout screen in TNBC cells has identified tyrosine‐protein phosphatase nonreceptor type 14 (PTPN14) as a key regulator of anoikis resistance. PTPN14 expression has shown a progressive decrease from normal breast tissue to metastatic tumors. Overexpressing PTPN14 has induced anoikis and inhibited cell proliferation in TNBC cells, while normal human breast cells are unaffected. Mechanistically, PTPN14 is identified as a key factor in dephosphorylating breast cancer antiestrogen resistance 3, a novel substrate, leading to the subsequent inhibition of PI3K/AKT and ERK signaling pathways. Local delivery of in vitro transcribed PTPN14 mRNA encapsulated by lipid nanoparticles in a TNBC mouse model has effectively inhibited tumor growth and metastasis, prolonging survival. The study underscores PTPN14 as a potential therapeutic target for metastatic TNBC, with the therapeutic strategy based on mRNA expression of PTPN14 demonstrating clinical application prospects in alleviating the burden of both primary tumors and metastatic disease. [ABSTRACT FROM AUTHOR]

Skin cutaneous melanoma (SKCM) is malignant cancer known for its high aggressiveness and unfavorable prognosis, particularly in advanced tumors. Anoikis is a specific pattern of programmed cell death associated with tumor regeneration, migration, and metastasis. Nevertheless, limited research has been conducted to investigate the function of anoikis in SKCM. Anoikis-related genes (ARGs) were extracted from Genecards to identify SKCM subtypes and to explore the immune microenvironment between the different subtypes. Prognostic models of SKCM were developed by LASSO COX regression analysis. Subsequently, the predictive value of risk scores in SKCM and the association with immunotherapy were further explored. Finally, the expression of 6 ARGs involved in the model construction was detected by immunohistochemistry and PCR. This study identified 20 ARGs significantly associated with SKCM prognosis and performed disease subtype analysis of samples based on these genes, different subtypes exhibited significantly different clinical features and tumor immune microenvironment (TIME) landscapes. The risk score prognostic model was generated by further screening and identification of the six ARGs. The model exhibited a high degree of sensitivity and specificity to predict the prognosis of individuals with SKCM. These high- and low-risk populations showed different immune statuses and drug sensitivity. Further immunohistochemical and PCR experiments identified significant differential expression of the six ARGs in tumor and normal samples. Anoikis-based features may serve as novel prognostic biomarkers for SKCM and may provide important new insights for survival prediction and individualized treatment development. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Tumor metastasis, the apex of cancer progression, poses a formidable challenge in therapeutic endeavors. Circulating tumor cells (CTCs), resilient entities originating from primary tumors or their metastases, significantly contribute to this process by demonstrating remarkable adaptability. They survive shear stress, resist anoikis, evade immune surveillance, and thwart chemotherapy. This comprehensive review aims to elucidate the intricate landscape of CTC formation, metastatic mechanisms, and the myriad factors influencing their behavior. Integral signaling pathways, such as integrin-related signaling, cellular autophagy, epithelial-mesenchymal transition, and interactions with platelets, are examined in detail. Furthermore, we explore the realm of precision nanomedicine design, with a specific emphasis on the anoikis‒platelet interface. This innovative approach strategically targets CTC survival mechanisms, offering promising avenues for combatting metastatic cancer with unprecedented precision and efficacy. The review underscores the indispensable role of the rational design of platelet-based nanomedicine in the pursuit of restraining CTC-driven metastasis. This review emphasizes the vital role of platelet-based nanomedicine design aiming to target the anoikis–platelet interface in restraining circulating tumor-cell metastasis. [Display omitted] [ABSTRACT FROM AUTHOR]

Objective: Anoikis is a programmed cell death process that plays a crucial role in tumor metastasis. Lung adenocarcinoma frequently results in multi-organ metastasis, which significantly impacts patient prognosis. This study aims to identify new anoikis-related gene signature to predict metastasis and prognosis of lung adenocarcinoma. Methods: The study obtained gene expression profiles and clinical data of patients with metastatic and non-metastatic lung adenocarcinoma from the TCGA and GEO databases. Additionally, 293 genes related to anoikis were downloaded from the GeneCard database. Unsupervised cluster analysis was used to divide patients with metastatic lung adenocarcinoma into two tumor subtypes. The study assessed immunoinfiltration and immune cell function in two groups using the TIMER database and single sample gene set enrichment analysis (ssGSEA). A prognostic model of genes related to anoikis was constructed using the minimum absolute contraction and selection algorithm (LASSO) and Cox regression model, which was then validated using external data sets. The predictive power of the model was further evaluated using ROC curves and a nomogram. The study evaluated the differences in immunotherapy and drug therapy between high-risk and low-risk groups. Selective gene expression was verified using real-time quantitative fluorescent PCR (qRT-PCR), and immune cell infiltration was verified using multiple immunofluorescence histochemistry. Results: The two molecular subtypes exhibited significant differences in clinicopathological features, prognosis, and immune cell infiltration. Lasso and multivariate Cox regression identified three prognostic genes related to anoikis (TLE1, EIF2AK3 and BIRC3), and a risk model was constructed using these genes. The patients were categorized into high- and low-risk groups based on their median risk scores. The low-risk group exhibited higher overall survival (OS) time, immune activity, tumor mutation burden (TMB), and PD1/ PD-L1 expression, which is consistent with a better response to immune checkpoint inhibitors. The nomogram demonstrates the model's superior predictive value. The expression of three prognostic genes was higher in lung adenocarcinoma cell lines and tissue, as determined by qRT-PCR. Furthermore, this expression was positively correlated with the degree of immune cell infiltration. Conclusion: This study has established a prognostic risk model characterized by anoikis-related genes. The model has good prognostic value in patients with lung adenocarcinoma and can be used as a potential diagnostic marker and therapeutic target for evaluating patient prognosis. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Recent advances in tumor molecular subtyping have revolutionized precision oncology, offering novel avenues for patient-specific treatment strategies. However, a comprehensive and independent comparison of these subtyping methodologies remains unexplored. This study introduces 'Themis' (Tumor HEterogeneity analysis on Molecular subtypIng System), an evaluation platform that encapsulates a few representative tumor molecular subtyping methods, including Stemness, Anoikis, Metabolism, and pathway-based classifications, utilizing 38 test datasets curated from The Cancer Genome Atlas (TCGA) and significant studies. Our self-designed quantitative analysis uncovers the relative strengths, limitations, and applicability of each method in different clinical contexts. Crucially, Themis serves as a vital tool in identifying the most appropriate subtyping methods for specific clinical scenarios. It also guides fine-tuning existing subtyping methods to achieve more accurate phenotype-associated results. To demonstrate the practical utility, we apply Themis to a breast cancer dataset, showcasing its efficacy in selecting the most suitable subtyping methods for personalized medicine in various clinical scenarios. This study bridges a crucial gap in cancer research and lays a foundation for future advancements in individualized cancer therapy and patient management. [ABSTRACT FROM AUTHOR]

Apoptosis, or programmed cell death, maintains tissue homeostasis by eliminating damaged or unnecessary cells. However, cells can evade this process, contributing to conditions such as cancer. Escape mechanisms include anoikis, mitochondrial DNA depletion, cellular FLICE inhibitory protein (c-FLIP), endosomal sorting complexes required for transport (ESCRT), mitotic slippage, anastasis, and blebbishield formation. Anoikis, triggered by cell detachment from the extracellular matrix, is pivotal in cancer research due to its role in cellular survival and metastasis. Mitochondrial DNA depletion, associated with cellular dysfunction and diseases such as breast and prostate cancer, links to apoptosis resistance. The c-FLIP protein family, notably CFLAR, regulates cell death processes as a truncated caspase-8 form. The ESCRT complex aids apoptosis evasion by repairing intracellular damage through increased Ca2+ levels. Antimitotic agents induce mitotic arrest in cancer treatment but can lead to mitotic slippage and tetraploid cell formation. Anastasis allows cells to resist apoptosis induced by various triggers. Blebbishield formation suppresses apoptosis indirectly in cancer stem cells by transforming apoptotic cells into blebbishields. In conclusion, the future of apoptosis research offers exciting possibilities for innovative therapeutic approaches, enhanced diagnostic tools, and a deeper understanding of the complex biological processes that govern cell fate. Collaborative efforts across disciplines, including molecular biology, genetics, immunology, and bioinformatics, will be essential to realize these prospects and improve patient outcomes in diverse disease contexts. [ABSTRACT FROM AUTHOR]

Media supplemented with sera from acutely exercised men has been shown to have 'anti‐cancer' effects on prostate and breast cancer cell lines. This study investigated whether media supplemented with plasma samples taken at rest (≥30 h since the most recent exercise session) from men who were endurance‐trained (END), strength‐trained (STR) or recreationally active controls (CON) impacted the results of four assays that mimic hallmarks of cancer (proliferation, migration, extracellular matrix invasion and anoikis resistance) in the BT‐549 breast cancer cell line. Compared to control conditions of either serum‐free media or fetal bovine serum as appropriate, BT‐549 cells cultured with plasma‐supplemented media regardless of group resulted in greater cell proliferation (∼20–50%) and cell migration (∼15–20%), and lower extracellular matrix invasion (∼10–20%) and anoikis resistance (∼15–20%). Supplementing media with plasma from END or STR did not impact any outcomes of these assays compared to plasma from CON. Media supplemented with human plasma can impact functional assays reflective of cancer hallmarks in BT‐549 cells, but effects of exercise on proliferation, migration, extracellular matrix invasion and anoikis resistance were not evident in resting blood samples of individuals with a prior history of exercise training. What is the central question of this study?Little is known regarding the effects of media supplemented with resting plasma from exercise‐trained individuals, despite the established bioactive effects of acutely exercised samples. Does media supplemented with resting plasma from endurance‐trained, strength‐trained or recreationally active controls impact hallmarks of cancer in BT‐549 cells?What is the main finding and its importance?Supplementing media with plasma from these trained athletes did not impact proliferation, migration, invasion or anoikis resistance compared to plasma from recreationally‐active controls. These findings suggest that 'anti‐cancer' effects of exercise are not present in resting blood samples of exercise‐trained individuals. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Macroautophagy/autophagy-mediated anoikis resistance is crucial for tumor metastasis. As a key autophagy-related protein, ATG4B has been demonstrated to be a prospective anti-tumor target. However, the existing ATG4B inhibitors are still far from clinical application, especially for tumor metastasis. In this study, we identified a novel circRNA, circSPECC1, that interacted with ATG4B. CircSPECC1 facilitated liquid-liquid phase separation of ATG4B, which boosted the ubiquitination and degradation of ATG4B in gastric cancer (GC) cells. Thus, pharmacological addition of circSPECC1 may serve as an innovative approach to suppress autophagy by targeting ATG4B. Specifically, the circSPECC1 underwent significant m6A modification in GC cells and was subsequently recognized and suppressed by the m6A reader protein ELAVL1/HuR. The activation of the ELAVL1-circSPECC1-ATG4B pathway was demonstrated to mediate anoikis resistance in GC cells. Moreover, we also verified that the above pathway was closely related to metastasis in tissues from GC patients. Furthermore, we determined that the FDA-approved compound lopinavir efficiently enhanced anoikis and prevented metastasis by eliminating repression of ELAVL1 on circSPECC1. In summary, this study provides novel insights into ATG4B-mediated autophagy and introduces a viable clinical inhibitor of autophagy, which may be beneficial for the treatment of GC with metastasis. [ABSTRACT FROM AUTHOR]

Background. Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer, and while advancements in diagnosis, surgery, radiotherapy, and molecular therapy have improved clinical prognosis, the long-term survival rate and quality of life of patients remain unsatisfactory. Therefore, identifying new prognostic biomarkers and potential therapeutic targets is crucial. Objectives. This study aimed to analyze the role of anoikis-related gene characteristics in LUAD. Materials and methods. The anoikis-related genes were obtained from the GeneCards database. Genetic expression data and clinical characteristic information were collected from The Cancer Genome Atlas (TCGA)-LUAD, and the Gene Expression Omnibus (GEO) GSE31210, GSE37745, and GSE68465 datasets. Random survival forest and least absolute shrinkage and selection operator (LASSO) models were applied to construct the risk model. An analysis of immune cell infiltration and function was performed with the scores. Results. Four prognosis-related genes (TLE1, GLI2, PLK1, and BAK1) were obtained and used to construct the anoikis score. We found that the patient survival rate was higher in the low-anoikis score (LAS) group. Moreover, both the stromal and immune scores were negatively correlated with the anoikis score. With the increase of the anoikis score, the levels of natural killer cells, regulatory T cells, CD4+ T cells, CD8+ T cells, B cells, and macrophages decreased. The anoikis score had a negative regulatory relationship with the immune response, natural killer cell activation and T cell activation. The TP53 mutation was significant in LUAD patients and was present in 56% of the high-anoikis score (HAS) group and in 40% of the LAS group. Conclusions. The anoikis score was associated with poor prognosis in LUAD patients. Anoikis-related genes were associated with tumor immune dysregulation and TP53 mutation in LUAD. This study opens a new perspective for LUAD therapy. [ABSTRACT FROM AUTHOR]

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Background: The intermediate filament protein vimentin is widely recognized as a molecular marker of epithelial-to-mesenchymal transition. Although vimentin expression is strongly associated with cancer metastatic potential, the exact role of vimentin in cancer metastasis and the underlying mechanism of its pro-metastatic functions remain unclear. Results: This study revealed that vimentin can enhance integrin β1 surface expression and induce integrin-dependent clustering of cells, shielding them against anoikis cell death. The increased integrin β1 surface expression in suspended cells was caused by vimentin-mediated protection of the internal integrin β1 pool against lysosomal degradation. Additionally, cell detachment was found to induce vimentin Ser38 phosphorylation, allowing the translocation of internal integrin β1 to the plasma membrane. Furthermore, the use of an inhibitor of p21-activated kinase PAK1, one of the kinases responsible for vimentin Ser38 phosphorylation, significantly reduced cancer metastasis in animal models. Conclusions: These findings suggest that vimentin can act as an integrin buffer, storing internalized integrin β1 and releasing it when needed. Overall, this study provides insights regarding the strong correlation between vimentin expression and cancer metastasis and a basis for blocking metastasis using this novel therapeutic mechanism. [ABSTRACT FROM AUTHOR]

Arsenic compounds have been used as therapeutic alternatives for several diseases including cancer. In the following work, we obtained arsenic nanoparticles (AsNPs) produced by an anaerobic bacterium from the Salar de Ascotán, in northern Chile, and evaluated their effects on the human oral squamous carcinoma cell line OECM-1. Resazurin reduction assays were carried out on these cells using 1–100 µM of AsNPs, finding a concentration-dependent reduction in cell viability that was not observed for the non-tumoral gastric mucosa-derived cell line GES-1. To establish if these effects were associated with apoptosis induction, markers like Bcl2, Bax, and cleaved caspase 3 were analyzed via Western blot, executor caspases 3/7 via luminometry, and DNA fragmentation was analyzed by TUNEL assay, using 100 µM cisplatin as a positive control. OECM-1 cells treated with AsNPs showed an induction of both extrinsic and intrinsic apoptotic pathways, which can be explained by a significant decrease in P-Akt/Akt and P-ERK/ERK relative protein ratios, and an increase in both PTEN and p53 mRNA levels and Bit-1 relative protein levels. These results suggest a prospective mechanism of action for AsNPs that involves a potential interaction with extracellular matrix (ECM) components that reduces cell attachment and subsequently triggers anoikis, an anchorage-dependent type of apoptosis. [ABSTRACT FROM AUTHOR]

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

Anoikis, a form of apoptosis resulting from the loss of cell–extracellular matrix interaction, is a significant barrier to cancer cell metastasis. However, the epigenetic regulation of this process remains to be explored. Here, we demonstrate that the histone deacetylase sirtuin 6 (SIRT6) plays a pivotal role in conferring anoikis resistance to colorectal cancer (CRC) cells. The protein level of SIRT6 is negatively correlated with anoikis in CRC cells. The overexpression of SIRT6 decreases while the knockdown of SIRT6 increases detachment-induced anoikis. Mechanistically, SIRT6 inhibits the transcription of N-myc downstream-regulated gene 1 (NDRG1), a negative regulator of the AKT signaling pathway. We observed the up-regulation of SIRT6 in advanced-stage CRC samples. Together, our findings unveil a novel epigenetic program regulating the anoikis of CRC cells. [ABSTRACT FROM AUTHOR]

Anoikis is a process of programmed cell death induced by the loss of cell/matrix interactions. In previous work, we have shown that the acquisition of anoikis resistance upregulates syndecan‐4 (SDC4) expression in endothelial cells. In addition, SDC4 gene silencing by microRNA interference reverses the transformed phenotype of anoikis‐resistant endothelial cells. Due to this role of SDC4 in regulating the behavior of anoikis‐resistant endothelial cells, we have evaluated that the functional consequences of SDC4 silencing in the extracellular matrix (ECM) remodeling in anoikis‐resistant rabbit aortic endothelial cells submitted to SDC4 gene silencing (miR‐Syn4‐Adh‐1‐EC). For this, we evaluated the expression of adhesive proteins, ECM receptors, nonreceptor protein‐tyrosine kinases, and ECM‐degrading enzymes and their inhibitors. Altered cell behavior was monitored by adhesion, migration, and tube formation assays. We found that SDC4 silencing led to a decrease in migration and angiogenic capacity of anoikis‐resistant endothelial cells; this was accompanied by an increase in adhesion to fibronectin. Furthermore, after SDC4 silencing, we observed an increase in the expression of fibronectin, collagen IV, and vitronectin, and a decrease in the expression of integrin α5β1 and αvβ3, besides that, silenced cells show an increase in Src and FAK expression. Quantitative polymerase chain reaction and Western blot analysis demonstrated that SDC4 silencing leads to altered gene and protein expression of MMP2, MMP9, and HSPE. Compared with parental cells, SDC4 silenced cells showed a decrease in nitric oxide production and eNOS expression. In conclusion, these data demonstrate that SDC4 plays an important role in ECM remodeling. In addition, our findings represent an important step toward understanding the mechanism by which SDC4 can reverse the transformed phenotype of anoikis‐resistant endothelial cells. [ABSTRACT FROM AUTHOR]

This study aims to explore the relevance of anoikis in idiopathic pulmonary fibrosis (IPF) and identify associated biomarkers and signaling pathways. Unsupervised consensus cluster analysis was employed to categorize IPF patients into subtypes. We utilized Weighted Gene Co-Expression Network Analysis (WGCNA) and Protein-Protein Interaction network construction to identify anoikis-related modules and key genes. A prognostic signature was developed using Lasso and multivariate Cox regression analysis. Single-cell sequencing assessed hub gene expression in various cell types, and both cell and animal experiments confirmed IPF-related pathways. We identified two distinct anoikis-associated subtypes with differing prognoses. WGCNA revealed essential hub genes, with SPP1 being prominent in the anoikis-related signature. The anoikis-related signature is effective in determining the prognosis of patients with IPF. Single-cell sequencing highlighted significant differences in SPP1 expression, notably elevated in fibroblasts derived from IPF patients. In vivo and in vitro experiments demonstrated that SPP1 enhances fibrosis in mouse lung fibroblasts by regulating p27 through the PI3K/Akt pathway. Our research demonstrates a robust prognostic signature associated with anoikis and highlights SPP1 as a pivotal regulator of the PI3K/AKT signaling pathway in pulmonary fibrosis. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) is the second most prevalent neurodegenerative disease, and its pathological mechanisms are thought to be closely linked to apoptosis. Anoikis, a specific type of apoptosis, has recently been suggested to play a role in the progression of Parkinson's disease; however, the underlying mechanisms are not well understood. To explore the potential mechanisms involved in PD, we selected genes from the GSE28894 dataset and compared their expression in PD patients and healthy controls to identify differentially expressed genes (DEGs), and selected anoikis-related genes (ANRGs) from the DEGs. Furthermore, the least absolute shrinkage and selection operator (LASSO) regression approach and multivariate logistic regression highlighted five key genes—GSK3B, PCNA, CDC42, DAPK2, and SRC—as biomarker candidates. Subsequently, we developed a nomogram model incorporating these 5 genes along with age and sex to predict and diagnose PD. To evaluate the model's coherence, clinical applicability, and distinguishability, we utilized receiver operating characteristic (ROC) curves, the C-index, and calibration curves and validated it in both the GSE20295 dataset and our center's external clinical data. In addition, we confirmed the differential expression of the 5 model genes in human blood samples through qRT-PCR and Western blotting. Our constructed anoikis-related PD diagnostic model exhibits satisfactory predictive accuracy and offers novel insights into both diagnosis and treatment strategies for Parkinson's disease while facilitating its implementation in clinical practice. [ABSTRACT FROM AUTHOR]

Cell survival in metazoans depends on cell attachment to the extracellular matrix (ECM) or to neighboring cells. Loss of such attachment triggers a type of programmed cell death known as anoikis, the acquisition of resistance to which is a key step in cancer development. The mechanisms underlying anoikis resistance remain unclear, however. The intracellular F-actin cytoskeleton plays a key role in sensing the loss of cell–ECM attachment, but how its disruption affects cell fate during such stress is not well understood. Here, we reveal a cell survival strategy characterized by the formation of a giant unilocular vacuole (GUVac) in the cytoplasm of the cells whose actin cytoskeleton is disrupted during loss of matrix attachment. Time-lapse imaging and electron microscopy showed that large vacuoles with a diameter of >500 nm accumulated early after inhibition of actin polymerization in cells in suspension culture, and that these vacuoles subsequently coalesced to form a GUVac. GUVac formation was found to result from a variation of a macropinocytosis-like process, characterized by the presence of inwardly curved membrane invaginations. This phenomenon relies on both F-actin depolymerization and the recruitment of septin proteins for micron-sized plasma membrane invagination. The vacuole fusion step during GUVac formation requires PI(3)P produced by VPS34 and PI3K-C2α on the surface of vacuoles. Furthermore, its induction after loss of matrix attachment conferred anoikis resistance. Our results thus show that the formation of a previously unrecognized organelle promotes cell survival in the face of altered actin and matrix environments.

BackgroundAnoikis is intricately associated with the malignant progression of cancer. Thyroid cancer (THCA) is the most common endocrine tumor, metastasis is closely related to treatment response and prognosis of THCA. Hence, it is imperative to comprehensively identify predictive prognostic genes and novel molecular targets for effective THCA therapy.MethodsDifferential expression analysis and weighted gene co-expression network analysis (WGCNA) were utilized to mine differentially expressed anoikis-related (DE-ARGs). Then, the prognostic genes were identified and a risk signature was constructed for THCA using univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) method. Furthermore, the associations between risk signature and immune infiltration, immunotherapy, as well as potential mechanisms of action were determined using multiple R packages and Wilcoxon test. Finally, Mendelian randomized (MR) analysis was conducted to investigate the causal relationship between the prognostic genes and THCA.ResultsIn total, six prognostic genes (LRRC75A, METTL7B, ADRA1B, TPD52L1, TNFRSF10C, and CXCL8) related to anoikis were identified, and the corresponding risk signature were constructed to assess the survival time of THCA patients. Immunocorrelation analysis demonstrated the anoikis-relevant risk signature could be used to evaluate immunotherapy effects in THCA patients, and the infiltration of immune cells was correlated with the degree of risk in THCA patients. According to two-sample MR analysis, there was the significant causal relationship between CXCL8 and THCA (odds ratio [OR] > 1 & p< 0.05), and the increase of its gene expression would lead to an increased risk of THCA. Furthermore, real-time quantitative polymerase chain reaction (RT-qPCR) confirmed the upregulated expression patterns of these prognostic genes in THCA tissues.ConclusionIn conclusion, we constructed the risk signature related to anoikis for THCA, which might have important clinical significance for improving the quality of life and treatment effect of THCA patients.