Understanding and targeting anoikis in metastasis for cancer therapies

Digoxin promotes anoikis of circulating cancer cells by targeting Na+/K+-ATPase α3-isoform

Circulating cancer cells (CCCs) are closely related to the process of distant metastasis. In early step of the metastasis cascade, CCCs must evade the detachment-induced cell death (anoikis) for their survival. Here, we examined whether Na+/K+-ATPase α3-isoform (α3NaK) in CCCs contributes to avoidance of anoikis. In CCCs isolated from gastric cancer patients, α3NaK was predominantly localized in the plasma membrane (PM), but it moved to the cytoplasm when the CCCs were attached to culture dishes. The CCCs showed significant expression of integrin α5 but not fibronectin, one of components of the extracellular matrix (ECM). In human gastric cancer MKN45 cells, digoxin (20 and 50 nM), a cardiac glycoside, significantly inhibited the enzyme activity and translocation (from cytoplasm to PM) of α3NaK, while they had no significant effect on ubiquitous Na+/K+-ATPase α1-isoform (α1NaK) in the PM. The translocation of α3NaK required the loss of ECM components from the cells. Additionally, digoxin significantly enhanced caspase 3/7 activity, as well as the expression of cleaved caspase 3, while reducing the viability of detached (floating) cells. In the MKN45 xenograft mouse model, intraperitoneal administration of digoxin (2 mg/kg/day) significantly decreased the number of CCCs and suppressed their liver metastasis. Our results suggest that α3NaK plays an essential role in the survival of CCCs in gastric cancer, and that digoxin enhances anoikis in detached (metastatic) gastric cancer cells by inhibiting the α3NaK translocation from cytoplasm to PM, thereby reducing CCCs. Targeting α3NaK may be a promising therapeutic strategy against CCC survival.

TIMP1 Overexpression in Ovarian Cancer Spheroids: Implications for Prognosis, Resistance, and Metastatic Potential

Background: High dissemination potential and resistance to standard therapy significantly contribute to high mortality associated with ovarian cancer. Cancer stem cells (CSCs) drive tumor progression, metastasis, and recurrence after treatments' failure. Here, we provide the first evidence of TIMP1 overexpression in ovarian CSCs, suggesting its potential role as a prognostic biomarker. Methods: Different ovarian cancer cell models were used to explore the potential link between TIMP1 and stem-like phenotypes. Experiments included spheroid formation, drug treatments, gene expression, functional assays, and zebrafish xenograft models to assess cell behavior and molecular changes. Results: TIMP1 was overexpressed in CSCs, and its expression was also upregulated in chemoresistant and anoikis-resistant cells. Our database analysis revealed a correlation between TIMP1 expression levels and poor patient prognosis. Overexpression of TIMP1 in ovarian cancer cell lines was able to recapitulate several features of the ovarian cancer stem cell phenotype, including treatment resistance, expression of stem cell markers, and anoikis resistance. TIMP1-overexpressing cells also exhibited enhanced migration potential in vitro and increased metastatic potential in vivo. Moreover, TIMP1 overexpression significantly altered the transcriptome landscape of cells, highlighting its role in modulating critical pathways associated with cell migration and inflammation. Conclusions: This study identifies the pivotal role of TIMP1 in ovarian CSCs and its contribution to therapy resistance, recurrence, and metastasis.

Multi-cohort validation based on a novel prognostic signature of anoikis for predicting prognosis and immunotherapy response of esophageal squamous cell carcinoma

Immunotherapy is recognized as an effective and promising treatment modality that offers a new approach to cancer treatment. However, identifying responsive patients remains challenging. Anoikis, a distinct form of programmed cell death, plays a crucial role in cancer progression and metastasis. Thus, we aimed to investigate prognostic biomarkers based on anoikis and their role in guiding immunotherapy decisions for esophageal squamous cell carcinoma (ESCC). By consensus clustering, the GSE53624 cohort of ESCC patients was divided into two subgroups based on prognostic anoikis-related genes (ARGs), with significant differences in survival outcomes between the two subgroups. Subsequently, we constructed an ARGs signature with four genes, and its reliability and accuracy were validated both internally and externally. Additional, different risk groups showed notable variances in terms of immunotherapy response, tumor infiltration, functional enrichment, immune function, and tumor mutation burden. Notably, the effectiveness of the signature in predicting immunotherapy response was confirmed across multiple cohorts, including GSE53624, GSE53625, TCGA-ESCC, and IMvigor210, highlighting its potential utility in predicting immunotherapy response. In conclusion, the ARGs signature has the potential to serve as an innovative and dependable prognostic biomarker for ESCC, facilitating personalized treatment strategies in this field, and may represent a valuable new tool for guiding ESCC immunotherapy decision-making.

Upregulated FSP1 by GPD1/1L mediated lipid droplet accumulation enhances ferroptosis resistance and peritoneal metastasis in gastric cancer

To successfully metastasize, cancer cells must evade detachment induced cell death, known as anoikis. Unraveling the mechanisms that gastric cancer (GC) circumvent anoikis and achieve peritoneal metastasis especially during unanchored growth, could significantly improve patient outcomes. Our study reveals that GC cells exhibit increased lipid peroxidation, MDA production, and cell death during suspension culture, which can be mitigated by the intervention with liproxstatin-1 and ferrostatin-1. We discovered that oleic acid (OA) or adipocytes stimulate lipid accumulation in GC cells, thereby inhibiting lipid peroxidation and cell death. Lipid mass spectrometry confirmed an upregulation of triglyceride synthesis, indicating that the accumulation of lipid droplet may confer resistance to ferroptosis during suspension growth. In vitro assays demonstrated that OA not only induces lipid droplet accumulation but also upregulates the expression of ferroptosis suppressor protein 1 (FSP1), a process that can be abrogated by the double knockout of GPD1/1L genes. Additionally, we have demonstrated that a decrease in the ubiquitination of FSP1 in GC cells upon lipid droplet accumulation, as well as silencing or pharmacological targeting FSP1, promotes ferroptosis and disrupts the peritoneal metastatic potential of GC cells. Collectively, our findings highlight the potential of FSP1 as a promising therapeutic target for metastatic gastric cancer.

Identification and Validation of Molecular Features of the Anoikis Gene-Related Hub Genes in Nasopharyngeal Carcinoma

Nasopharyngeal carcinoma (NPC) is a malignant tumor originating from nasopharyngeal mucosa. Anoikis, a form of programmed cell death induced by detachment from the extracellular matrix, normally prevents metastasis. Resistance to anoikis in cancer cells can enhance their metastatic potential. This study identifies anoikis-related genes (ARGs) associated with NPC to elucidate tumorigenesis mechanisms. Analysis of the GSE12452 dataset from GEO revealed 77 differentially expressed ARGs in NPC tissues. GO and KEGG analyses highlighted significant enrichment in apoptosis-related pathways. A PPI network identified MYC, FN1, BRCA1, and FGF2 as Hub genes. Correlation analysis showed MYC positively correlated with activated dendritic cells (p < 0.01) but negatively with naive CD4 T cells (p < 0.001). FN1 was positively correlated with activated dendritic cells (p < 0.01) and negatively with M1 macrophages (p < 0.05). FGF2 negatively correlated with naive CD4 T cells (p < 0.001), while BRCA1 was positively correlated with eosinophils (p < 0.01). GSVA and GSEA indicated that MYC, FN1, BRCA1, and FGF2 were significantly enriched in cell cycle and DNA replication pathways. Immunohistochemistry and qPCR of 50 NPC samples confirmed the overexpression of these genes. Knockdown of MYC, FN1, BRCA1, and FGF2 led to increased tumor cell malignancy, with statistical significance (p < 0.05). This study identifies MYC, FN1, BRCA1, and FGF2 as anoikis-related genes (ARGs) with significant regulatory roles in nasopharyngeal carcinoma (NPC). These ARGs are found to be involved in the development and progression of NPC, suggesting their potential as therapeutic targets for this cancer.

An anoikis-related signature predicts prognosis and immunotherapy response in gastrointestinal cancers

Background

Gastrointestinal (GI) cancers have high incidence rates and mortality rates. Anoikis is a special type of cell apoptosis, and anoikis resistance has been reported to be associated with tumor malignancy. We aimed to explore the roles of anoikis-related genes (ARGs) in the GI cancer prognosis.

Methods

We extracted RNA sequencing and clinical data from The Cancer Genome Atlas and Gene Expression Omnibu databases for patients with esophageal cancer, gastric cancer, colon cancer and rectal cancer and identified ARGs from GeneCards and Harmonizome. Anoikis-related patterns were identified via unsupervised clustering analysis. We constructed a prognostic signature (Anoscore) based on prognostic ARGs through univariate, LASSO, and multivariate Cox regression analyses. The model was validated and evaluated using Kaplan-Meier analysis, receiver operating characteristic curves, univariate Cox regression analysis, multivariate Cox regression analysis, column charts, and calibration curves. We also performed a single-cell sequencing analysis of candidate genes via TISCH2. A correlation analysis between the Anoscore, the tumor microenvironment and drug sensitivity was conducted in GI cancers. The expression and function of some candidate genes were validated in vitro.

Results

In terms of prognostic ARGs, two anoikis-related patterns, ARG clusters A and B, were identified. ARG cluster B had a worse prognosis than did ARG cluster A. Subsequently, the Anoscore was developed as an independent prognostic factor. It demonstrated the robust predictive capability for the prognosis of patients with GI cancers. Notably, patients with high Anoscores exhibited poor outcomes. In addition, we established a nomogram (Ano-nomogram) based on the Anoscore and clinicopathological factors of patients to predict the 3-year and 5-year survival probabilities. Moreover, patients with high Anoscores had higher levels of immune cell infiltration and higher immune checkpoint expression. The drug sensitivity analysis revealed that patients with high or low Anoscores were sensitive to different chemotherapies and targeted drugs. S100A11 and TLR3, representative candidate genes, exhibited different expression patterns and biological functions.

Conclusion

This study highlighted the significant potential of the Anoscore in predicting prognosis and guiding the selection of personalized therapeutic regimens for patients with GI cancers.

Emerging roles of angiopoietin‑like 4 in human tumors (Review)

Angiopoietin‑like 4 (ANGPTL4), a member of the angiopoietin family, plays critical roles in angiogenesis, lipid metabolism and inflammation. It has been demonstrated that ANGPTL4 has significant influence on various diseases. Accumulating evidence has highlighted the impacts of ANGPTL4 on human malignancies. ANGPTL4 is commonly overexpressed in various types of cancer, such as breast, non‑small cell lung, gastric and colorectal cancer. Its upregulation promotes tumor growth, invasion, metastasis and angiogenesis, as well as metabolic reprogramming and resistance to programmed cell death, radiotherapy and chemotherapy. However, ANGPTL4 has also exhibited antitumor effects under certain conditions, indicating its complex roles in tumor biology. The transcriptional regulation of ANGPTL4 is influenced by multiple factors, such as HIF‑1, PPARs, TGF‑β and long non‑coding RNAs. In terms of signaling pathways, STATs, PI3K/AKT and COX-2/PGE2 are important in regulating cellular processes. The present review summarizes the biological functions of ANGPTL4 in tumors and its association with patient prognosis. Furthermore, the key molecular mechanisms and potential reasons for its dual roles in cancer are also discussed. In conclusion, ANGPTL4 is a valuable diagnostic biomarker and a potential therapeutic target for human cancers.

Anoikis-related genes linked with patient outcome in pancreatic cancer

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

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

OBJECTIVE

Colorectal cancer (CRC), specifically colon adenocarcinoma, is the third most prevalent and the second most lethal form of cancer. Anoikis is found to be specialized form of programmed cell death (PCD), which plays a pivotal role in tumor progression. This study aimed to investigate the role of the anoikis related genes (ARGs) in colon cancer.

METHODS

Consensus unsupervised clustering, differential expression analysis, tumor mutational burden analysis, and analysis of immune cell infiltration were utilized in the study. For the analysis of RNA sequences and clinical data of COAD patients, data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were obtained. A prognostic scoring system for overall survival (OS) prediction was developed using Cox regression and LASSO regression analysis. Furthermore, loss-of-function assay was utilized to explore the role of RAD9A played in the progression of colon cancer.

RESULTS

The prognostic value of a risk score composed of NTRK2, EPHA2, RAD9A, CDC25C, and SNAI1 genes was significant. Furthermore, these findings suggested potential mechanisms that may influence prognosis, supporting the development of individualized treatment plans and management of patient outcomes. Further experiments confirmed that RAD9A could promote proliferation and metastasis of colon cancer cells. These effects may be achieved by affecting the phosphorylation of AKT.

CONCLUSION

Differences in survival time and the tumor immune microenvironment (TIME) were observed between two gene clusters associated with ARGs. In addition, a prognostic risk model was established and confirmed as an independent risk factor. Furthermore, our data indicated that RAD9A promoted tumorigenicityby activating AKT in colon cancer.

Combating anoikis resistance: bioactive compounds transforming prostate cancer therapy

The study aims to discuss the challenges associated with treating prostate cancer (PCa), which is known for its complexity and drug resistance. It attempts to find differentially expressed genes (DEGs), such as those linked to anoikis resistance and circulating tumor cells, in PCa samples. This study involves analyzing the functional roles of these DEGs using gene enrichment analysis, and then screening of 102 bioactive compounds to identify a combination that can control the expression of the identified DEGs. In this study, 53 DEGs were identified from PCa samples including anoikis-resistant PCa cells and circulating tumor cells in PCa. Gene enrichment analysis with regards to functional enrichment of DEGs was performed. An inclusive screening process was carried out among 102 bioactive compounds to identify a combination capable of affecting and regulating the expression of selected DEGs. Eventually, gastrodin, nitidine chloride, chenodeoxycholic acid, and bilobalide were selected, as their combination demonstrated ability to modulate expression of 50 out of the 53 genes targeted. The subsequent analysis focused on investigating the biological pathways and processes influenced by this combination. The findings revealed a multifaceted and multidimensional approach to tumor regression. The combination of bioactive compounds exhibited effects on various genes including those related to production of inflammatory cytokines, cell proliferation, autophagy, apoptosis, angiogenesis, and metastasis. The current study has made a valuable contribution to the development of a combination of bioactive natural compounds that can significantly impede the development of treatment resistance in prostate tumor while countering the tumors' evasion of the immune system. The implications of this study are highly significant as it suggests the creation of an enhanced immunotherapeutic, natural therapeutic concoction with combinatorial potential.

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

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

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

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

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

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

Targeting anoikis resistance as a strategy for cancer therapy

Anoikis, known as matrix detachment-induced apoptosis or detachment-induced cell death, is crucial for tissue development and homeostasis. Cancer cells develop means to evade anoikis, e.g. anoikis resistance, thereby allowing for cells to survive under anchorage-independent conditions. Uncovering the mechanisms of anoikis resistance will provide details about cancer metastasis, and potential strategies against cancer cell dissemination and metastasis. Here, we summarize the principal elements and core molecular mechanisms of anoikis and anoikis resistance. We discuss the latest progress of how anoikis and anoikis resistance are regulated in cancers. Furthermore, we summarize emerging data on selective compounds and nanomedicines, explaining how inhibiting anoikis resistance can serve as a meaningful treatment modality against cancers. Finally, we discuss the key limitations of this therapeutic paradigm and possible strategies to overcome them. In this review, we suggest that pharmacological modulation of anoikis and anoikis resistance by bioactive compounds could surmount anoikis resistance, highlighting a promising therapeutic regimen that could be used to overcome anoikis resistance in cancers.

Pharmacologically inducing anoikis offers novel therapeutic opportunities in hepatocellular carcinoma

Tumor metastasis occurs in hepatocellular carcinoma (HCC), leading to tumor progression and therapeutic failure. Anoikis is a matrix detachment-induced apoptosis, also known as detachment-induced cell death, and mechanistically prevents tumor cells from escaping their native extracellular matrix to metastasize to new organs. Deciphering the regulators and mechanisms of anoikis in cancer metastasis is urgently needed to treat HCC. Several natural and synthetic products induce anoikis in HCC cells and in vivo models. Here, we first briefly summarize the current understanding of the molecular mechanisms of anoikis regulation and relevant regulators involved in HCC metastasis. Then we discuss the therapeutic potential of pharmacological induction of anoikis as a potential treatment against HCC. Finally, we discuss the key limitations of this therapeutic paradigm and propose possible strategies to overcome them. Cumulatively this review suggests that the pharmacological induction of anoikis can be used a promising therapeutic modality against HCC.

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

Background

One of the primary reasons for tumor invasion and metastasis is anoikis resistance. Biochemical recurrence (BCR) of prostate cancer (PCa) serves as a harbinger of its distant metastasis. However, the role of anoikis in PCa biochemical recurrence has not been fully elucidated.

Methods

Differential expression analysis was used to identify anoikis-related genes based on the TCGA and GeneCards databases. Prognostic models were constructed utilizing LASSO regression, univariate and multivariate Cox regression analyses. Moreover, Gene Expression Omnibus datasets (GSE70770 and GSE46602) were applied as validation cohorts. Gene Ontology, KEGG and GSVA were utilized to explore biological pathways and molecular mechanisms. Further, immune profiles were assessed using CIBERSORT, ssGSEA, and TIDE, while anti-cancer drugs sensitivity was analyzed by GDSC database. In addition, gene expressions in the model were examined using online databases (Human Protein Atlas and Tumor Immune Single-Cell Hub).

Results

113 differentially expressed anoikis-related genes were found. Four genes (EEF1A2, RET, FOSL1, PCA3) were selected for constructing a prognostic model. Using the findings from the Cox regression analysis, we grouped patients into groups of high and low risk. The high-risk group exhibited a poorer prognosis, with a maximum AUC of 0.897. Moreover, larger percentage of immune infiltration of memory B cells, CD8 Tcells, neutrophils, and M1 macrophages were observed in the high-risk group than those in the low-risk group, whereas the percentage of activated mast cells and dendritic cells in the high-risk group were lower. An increased TIDE score was founded in the high-risk group, suggesting reduced effectiveness of ICI therapy. Additionally, the IC50 results for chemotherapy drugs indicated that the low-risk group was more sensitive to most of the drugs. Finally, the genes EEF1A2, RET, and FOSL1 were expressed in PCa cases based on HPA website. The TISCH database suggested that these four ARGs might contribute to the tumor microenvironment of PCa.

Conclusion

We created a risk model utilizing four ARGs that effectively predicts the risk of BCR in PCa patients. This study lays the groundwork for risk stratification and predicting survival outcomes in PCa patients with BCR.

HK2 promotes migration and invasion of intrahepatic cholangiocarcinoma via enhancing cancer stem-like cells' resistance to anoikis

Cancer stem-like cells (CSLCs) and anoikis resistance play crucial roles in the metastasis of cancers. However, it remains unclear whether CSLCs are related to anoikis resistance in intrahepatic cholangiocarcinoma (ICC). Here we identified a group of stemness-related anoikis genes (SRAGs) via bioinformatic analysis of public data. Accordingly, a novel anoikis-related classification was established and it divided ICC into C1 and C2 type. Different type ICC displayed distinct prognosis, molecular as well immune characteristics. Furthermore, we found one key SRAGs via several machine learning algorithms. HK2 was up-regulated in tumor-repopulating cells (TRCs) of ICC, a kind of CSLCs with a potent resistance to anoikis. Its up-regulation may be caused by the activation of MTORC1 signaling in ICC-TRCs. And inhibition of HK2 significantly increased anoikis and decreased migration as well invasion in ICC-TRCs. Our studies provide an insight into the molecular mechanism underlying the resistance of ICC-TRCs to anoikis and enhance the evidences for targeting HK2 in ICC.

P53/NANOG balance; the leading switch between poorly to well differentiated status in liver cancer cells

Enforcing a well-differentiated state on cells requires tumor suppressor p53 activation as a key player in apoptosis induction and well differentiation. In addition, recent investigations showed a significant correlation between poorly differentiated status and higher expression of NANOG. Inducing the expression of NANOG and decreasing p53 level switch the status of liver cancer cells from well differentiated to poorly status. In this review, we highlighted p53 and NANOG cross-talk in hepatocellular carcinoma (HCC) which is regulated through mitophagy and makes it a novel molecular target to attenuate cancerous phenotype in the management of this tumor.

Anoikis-related gene signatures in colorectal cancer: implications for cell differentiation, immune infiltration, and prognostic prediction

Colorectal cancer (CRC) is a malignant tumor originating from epithelial cells of the colon or rectum, and its invasion and metastasis could be regulated by anoikis. However, the key genes and pathways regulating anoikis in CRC are still unclear and require further research. The single cell transcriptome dataset GSE221575 of GEO database was downloaded and applied to cell subpopulation type identification, intercellular communication, pseudo time cell trajectory analysis, and receptor ligand expression analysis of CRC. Meanwhile, the RNA transcriptome dataset of TCGA, the GSE39582, GSE17536, and GSE17537 datasets of GEO were downloaded and merged into one bulk transcriptome dataset. The differentially expressed genes (DEGs) related to anoikis were extracted from these data sets, and key marker genes were obtained after feature selection. A clinical prognosis prediction model was constructed based on the marker genes and the predictive effect was analyzed. Subsequently, gene pathway analysis, immune infiltration analysis, immunosuppressive point analysis, drug sensitivity analysis, and immunotherapy efficacy based on the key marker genes were conducted for the model. In this study, we used single cell datasets to determine the anoikis activity of cells and analyzed the DEGs of cells based on the score to identify the genes involved in anoikis and extracted DEGs related to the disease from the transcriptome dataset. After dimensionality reduction selection, 7 marker genes were obtained, including TIMP1, VEGFA, MYC, MSLN, EPHA2, ABHD2, and CD24. The prognostic risk model scoring system built by these 7 genes, along with patient clinical data (age, tumor stage, grade), were incorporated to create a nomogram, which predicted the 1-, 3-, and 5-years survival of CRC with accuracy of 0.818, 0.821, and 0.824. By using the scoring system, the CRC samples were divided into high/low anoikis-related prognosis risk groups, there are significant differences in immune infiltration, distribution of immune checkpoints, sensitivity to chemotherapy drugs, and efficacy of immunotherapy between these two risk groups. Anoikis genes participate in the differentiation of colorectal cancer tumor cells, promote tumor development, and could predict the prognosis of colorectal cancer.

SIRT6 Inhibits Anoikis of Colorectal Cancer Cells by Down-Regulating NDRG1

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.

Apigenin: Molecular Mechanisms and Therapeutic Potential against Cancer Spreading

Due to its propensity to metastasize, cancer remains one of the leading causes of death worldwide. Thanks in part to their intrinsic low cytotoxicity, the effects of the flavonoid family in the prevention and treatment of various human cancers, both in vitro and in vivo, have received increasing attention in recent years. It is well documented that Apigenin (4',5,7-trihydroxyflavone), among other flavonoids, is able to modulate key signaling molecules involved in the initiation of cancer cell proliferation, invasion, and metastasis, including JAK/STAT, PI3K/Akt/mTOR, MAPK/ERK, NF-κB, and Wnt/β-catenin pathways, as well as the oncogenic non-coding RNA network. Based on these premises, the aim of this review is to emphasize some of the key events through which Apigenin suppresses cancer proliferation, focusing specifically on its ability to target key molecular pathways involved in angiogenesis, epithelial-to-mesenchymal transition (EMT), maintenance of cancer stem cells (CSCs), cell cycle arrest, and cancer cell death.

Construction of an Anoikis-Related Gene Prognostic Signature and Identification of ANGPTL4 as a Key Oncogene in Lung Adenocarcinoma

Anoikis plays an important role in cancer invasion and metastasis. However, the role of anoikis-related genes, AnRGs, in lung adenocarcinoma (LUAD) is not clear. First, anoikis-related genes (AnRGs) were obtained from the Genecard database. Second, the prognostic risk model of AnRGs was established by univariate Cox analysis, the Least Absolute Shrinkage and Selection Operator (LASSO) analysis, and multivariate Cox analysis. Finally, in vitro cell experiments were carried out to determine the expression and function of the key gene AnRGs. Three AnRGs (angiopoietin-like 4, ANGPTL4; Cyclin-Dependent Kinase Inhibitor 3, CDKN3; Solute Carrier Organic Anion Transporter Family Member 1B3, SLCO1B3) were screened for the construction of risk prediction model. Additionally, ANGPTL4 was significantly highly expressed in tumor cells, and the knockdown of ANGPTL4 expression on tumor cells could inhibit tumor cell migration and apoptosis. Constructing a risk model based on anoikis-related genes can effectively differentiate the prognosis of LUAD. ANGPTL4 can be used as a potential new target for LUAD treatment.

Multi-cohort validation of Ascore: an anoikis-based prognostic signature for predicting disease progression and immunotherapy response in bladder cancer

Bladder cancer ranks as the 10th most common cancer worldwide, with deteriorating prognosis as the disease advances. While immune checkpoint inhibitors (ICIs) have shown promise in clinical therapy in both operable and advanced bladder cancer, identifying patients who will respond is challenging. Anoikis, a specialized form of cell death that occurs when cells detach from the extracellular matrix, is closely linked to tumor progression. Here, we aimed to explore the anoikis-based biomarkers for bladder cancer prognosis and immunotherapeutic decisions. Through consensus clustering, we categorized patients from the TCGA-BLCA cohort into two clusters based on anoikis-related genes (ARGs). Significant differences in survival outcome, clinical features, tumor immune environment (TIME), and potential ICIs response were observed between clusters. We then formulated a four-gene signature, termed "Ascore", to encapsulate this gene expression pattern. The Ascore was found to be closely associated with survival outcome and served as an independent prognosticator in both the TCGA-BLCA cohort and the IMvigor210 cohort. It also demonstrated superior predictive capacity (AUC = 0.717) for bladder cancer immunotherapy response compared to biomarkers like TMB and PD-L1. Finally, we evaluated Ascore's independent prognostic performance as a non-invasive biomarker in our clinical cohort (Gulou-Cohort1) using circulating tumor cells detection, achieving an AUC of 0.803. Another clinical cohort (Gulou-Cohort2) consisted of 40 patients undergoing neoadjuvant anti-PD-1 treatment was also examined. Immunohistochemistry of Ascore in these patients revealed its correlation with the pathological response to bladder cancer immunotherapy (P = 0.004). Impressively, Ascore (AUC = 0.913) surpassed PD-L1 (AUC = 0.662) in forecasting immunotherapy response and indicated better net benefit. In conclusion, our study introduces Ascore as a novel, robust prognostic biomarker for bladder cancer, offering a new tool for enhancing immunotherapy decisions and contributing to the tailored treatment approaches in this field.

Identification of crucial anoikis-related genes as novel biomarkers and potential therapeutic targets for lung adenocarcinoma via bioinformatic analysis and experimental verification

Lung adenocarcinoma (LUAD) is a malignant tumor of the respiratory system that has a poor 5-year survival rate. Anoikis, a type of programmed cell death, contributes to tumor development and metastasis. The aim of this study was to develop an anoikis-based stratified model, and a multivariable-based nomogram for guiding clinical therapy for LUAD. Through differentially expressed analysis, univariate Cox, LASSO Cox regression, and random forest algorithm analysis, we established a 4 anoikis-related genes-based stratified model, and a multivariable-based nomogram, which could accurately predict the prognosis of LUAD patients in the TCGA and GEO databases, respectively. The low and high-risk score LUAD patients stratified by the model showed different tumor mutation burden, tumor microenvironment, gemcitabine sensitivity and immune checkpoint expressions. Through immunohistochemical analysis of clinical LUAD samples, we found that the 4 anoikis-related genes (PLK1, SLC2A1, ANGPTL4, CDKN3) were highly expressed in the tumor samples from clinical LUAD patients, and knockdown of these genes in LUAD cells by transfection with small interfering RNAs significantly inhibited LUAD cell proliferation and migration, and promoted anoikis. In conclusion, we developed an anoikis-based stratified model and a multivariable-based nomogram of LUAD, which could predict the survival of LUAD patients and guide clinical treatment.

Adhesion States Greatly Affect Cellular Susceptibility to Graphene Oxide: Therapeutic Implications for Cancer Metastasis

Graphene oxide (GO) has received increasing attention in the life sciences because of its potential for various applications. Although GO is generally considered biocompatible, it can negatively impact cell physiology under some circumstances. Here, we demonstrate that the cytotoxicity of GO greatly varies depending on the cell adhesion states. Human HCT-116 cells in a non-adhered state were more susceptible to GO than those in an adherent state. Apoptosis was partially induced by GO in both adhered and non-adhered cells to a similar extent, suggesting that apoptosis induction does not account for the selective effects of GO on non-adhered cells. GO treatment rapidly decreased intracellular ATP levels in non-adhered cells but not in adhered ones, suggesting ATP depletion as the primary cause of GO-induced cell death. Concurrently, autophagy induction, a cellular response for energy homeostasis, was more evident in non-adhered cells than in adhered cells. Collectively, our observations provide novel insights into GO's action with regard to cell adhesion states. Because the elimination of non-adhered cells is important in preventing cancer metastasis, the selective detrimental effects of GO on non-adhered cells suggest its therapeutic potential for use in cancer metastasis.

Anoikis-related signature predicts prognosis and characterizes immune landscape of ovarian cancer

Ovarian cancer (OV) is the most lethal gynecological malignancy worldwide, with high recurrence rates. Anoikis, a newly-acknowledged form of programmed cell death, plays an essential role in cancer progression, though studies focused on prognostic patterns of anoikis in OV are still lacking. We filtered 32 potential anoikis-related genes (ARGs) among the 6406 differentially expressed genes (DEGs) between the 180 normal controls and 376 TCGA-OV samples. Through the LASSO-Cox analysis, a 2-gene prognostic signature, namely AKT2, and DAPK1, was finally distinguished. We then demonstrated the promising prognostic value of the signature through the K-M survival analysis and time-dependent ROC curves (p-value < 0.05). Moreover, based on the signature and clinical features, we constructed and validated a nomogram model for 1-year, 3-year, and 5-year overall survival, with reliable prognostic values in both TCGA-OV training cohort (p-value < 0.001) and ICGC-OV validation cohort (p-value = 0.030). We evaluated the tumor immune landscape through the CIBERSORT algorithm, which indicated the upregulation of resting Myeloid Dendritic Cells (DCs), memory B cells, and naïve B cells and high expression of key immune checkpoint molecules (CD274 and PDCD1LG2) in the high-risk group. Interestingly, the high-risk group exhibited better sensitivity toward immunotherapy and less sensitivity toward chemotherapies, including Cisplatin and Bleomycin. Especially, based on the IHC of tissue microarrays among 125 OV patients at our institution, we reported that aberrant upregulation of DAPK1 was related to poor prognosis. Conclusively, the anoikis-related signature was a promising tool to evaluate prognosis and predict therapy responses, thus assisting decision-making in the realm of OV precision medicine.

ITGBL1 promotes anoikis resistance and metastasis in human gastric cancer via the AKT/FBLN2 axis

The resistance to anoikis plays a critical role in the metastatic progression of various types of malignancies, including gastric cancer (GC). Nevertheless, the precise mechanism behind anoikis resistance is not fully understood. Here, our primary focus was to examine the function and underlying molecular mechanism of Integrin beta-like 1 (ITGBL1) in the modulation of anoikis resistance and metastasis in GC. The findings of our investigation have demonstrated that the overexpression of ITGBL1 significantly augmented the resistance of GC cells to anoikis and promoted their metastatic potential, while knockdown of ITGBL1 had a suppressive effect on both cellular processes in vitro and in vivo. Mechanistically, we proved that ITGBL1 has a role in enhancing the resistance of GC cells to anoikis and promoting metastasis through the AKT/Fibulin-2 (FBLN2) axis. The inhibition of AKT/FBLN2 signalling was able to reverse the impact of ITGBL1 on the resistance of GC cells to anoikis and their metastatic capability. Moreover, the expression levels of ITGBL1 were found to be significantly elevated in the cancerous tissues of patients diagnosed with GC, and there was a strong correlation observed between high expression levels of ITGBL1 and worse prognosis among individuals diagnosed with GC. Significantly, it was revealed that within our cohort of GC patients, individuals exhibiting elevated ITGBL1 expression and diminished FBLN2 expression experienced the worst prognosis. In conclusion, the findings of our study indicate that ITGBL1 may serve as a possible modulator of resistance to anoikis and the metastatic process in GC.

Identification of Novel Anoikis-Related Gene Signatures to Predict the Prognosis, Immune Microenvironment, and Drug Sensitivity of Breast Cancer Patients

INTRODUCTION

Breast cancer is one of the most prevalent types of cancer and a leading cause of cancer-related death among females worldwide. Anoikis, a specific type of apoptosis that is triggered by the loss of anchoring between cells and the native extracellular matrix, plays a vital role in cancer invasion and metastasis. However, studies that focus on the prognostic values of anoikis-related genes (ARGs) in breast cancer are scarce.

METHODS

Gene expression data were obtained from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) databases. Five anoikis-related signatures (ARS) were selected from ARGs through univariate Cox regression analysis, LASSO regression analysis, and multivariate Cox regression analysis. Subsequently, an ARGs risk score model was established, and breast cancer patients were divided into high and low risk groups. The correlation between risk groups and overall survival (OS), tumor mutation burden (TMB), tumor microenvironment (TME), stemness, and drug sensitivity were analyzed. Moreover, RT-qPCR was performed to verify the gene expression levels of the five ARS in breast cancer tissues. Furthermore, a nomogram model was constructed based on ARGs risk score and clinicopathological factors.

RESULTS

A novel ARGs risk score model was constructed based on five ARS (CEMIP, LAMB3, CD24, PTK6, and PLK1), and breast cancer patients were divided into high and low risk groups. Correlation analysis showed that the high and low risk groups had different OS, TMB, TME, stemness, and drug sensitivity. Both the ARGs risk score model and the nomogram showed promising prognosis predictive value in breast cancer.

CONCLUSION

ARS could be used as promising biomarkers for breast cancer prognosis predication and treatment options selection.

The Prognosis of Cancer Depends on the Interplay of Autophagy, Apoptosis, and Anoikis within the Tumor Microenvironment

Within the tumor microenvironment, the fight between the immune system and cancer influences tumor transformation. Metastasis formation is an important stage in the progression of cancer. This process is aided by cellular detachment and resistance to anoikis, which are achieved by altering intercellular signaling. Autophagy, specifically pro-survival autophagy, aids cancer cells in developing treatment resistance. Numerous studies have shown that autophagy promotes tumor growth and resistance to anoikis. To regulate protective autophagy, cancer-related genes phosphorylate both pro- and anti-apoptotic proteins. Apoptosis, a type of controlled cell death, eliminates damaged or unwanted cells. Anoikis is a type of programmed cell death in which cells lose contact with the extracellular matrix. The dysregulation of these cellular pathways promotes tumor growth and spread. Apoptosis, anoikis, and autophagy interact meticulously and differently depending on the cellular circumstances. For instance, autophagy can protect cancer cells from apoptosis by removing cellular components that are damaged and might otherwise trigger apoptotic pathways. Similarly, anoikis dysregulation can trigger autophagy by causing cellular harm and metabolic stress. In order to prevent or treat metastatic disease, specifically, targeting these cellular mechanisms may present a promising prospect for cancer therapy. This review discourses the state of our understanding of the molecular and cellular mechanisms underlying tumor transformation and the establishment of metastatic tumors. To enhance the prognosis for cancer, we highlight and discuss potential therapeutic approaches that target these processes and genes involved in them.

Oncoviruses: Induction of cancer development and metastasis by increasing anoikis resistance

The phenomenon of cell death is a vital aspect in the regulation of aberrant cells such as cancer cells. Anoikis is a kind of cell death that occurs when cells get separated from the extracellular matrix. Some cancer cells can inhibit anoikis in order to progress metastasis. One of the key variables that might be implicated in anoikis resistance (AR) is viral infections. The most important viruses involved in this process are Epstein-Barr virus, human papillomavirus, hepatitis B virus, human herpes virus 8, human T-cell lymphotropic virus type 1, and hepatitis C virus. A better understanding of how carcinogenic viruses suppress anoikis might be helpful in developing an effective treatment for virus-associated cancers. In the current study, we review the role of the mentioned viruses and their gene products in anoikis inhibition.

Predicting the prognosis, immune response, and immunotherapy in head and neck squamous cell carcinoma using a novel risk model based on anoikis-related lncRNAs

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is an extremely heterogeneous and metastatic disease. Anoikis, which is a specific type of programmed apoptosis, is involved in tumor metastasis, tissue homeostasis, and development. Herein, we constructed an anoikis-related long non-coding RNA (lncRNA) signature to predict the prognosis, immune responses, and therapeutic effects in HNSCC patients.

METHODS

A total of 501 HNSCC samples were acquired from the TCGA database and randomly classified into the training and validation groups (1:1 ratio). Thereafter, the results derived from the training set were analyzed with the LASSO regression analysis, and a novel anoikis-related lncRNA risk model was constructed. Time-dependent ROC curves and Kaplan-Meier analysis were carried out to assess the diagnostic value and survival outcomes. A nomogram was utilized to predict the prognostic accuracy. Furthermore, we studied the tumor microenvironment, tumor mutation burden, enrichment pathways, and the response to chemotherapy and immunotherapy.

RESULTS

Seven anoikis-related lncRNAs (AC015878.1, CYTOR, EMSLR, LINC01503, LINC02084, RAB11B-AS1, Z97200.1) were screened to design a novel risk model, which was recognized as the independent prognostic factor for HNSCC patients. The findings implied that low-risk patients showed significantly longer OS, PFS, and DSS compared to those high-risk patients. The two groups that were classified using the risk model showed significant differences in their immune landscape. The risk model also predicted that low-risk HNSCC patients could attain a better response to immunotherapy, while high-risk patients would be more sensitive to gemcitabine, docetaxel, and cisplatin.

CONCLUSIONS

We constructed a novel risk model that could be employed for effectively predicting patient prognosis with a good independent prognostic value for HNSCC patients. Furthermore, this model could be used for designing new immunotherapeutic and chemotherapeutic strategies, and it helps clinicians establish personalized and detailed strategies for HNSCC patients.

A novel stratification framework based on anoikis-related genes for predicting the prognosis in patients with osteosarcoma

Background

Anoikis resistance is a prerequisite for the successful development of osteosarcoma (OS) metastases, whether the expression of anoikis-related genes (ARGs) correlates with OS prognosis remains unclear. This study aimed to investigate the feasibility of using ARGs as prognostic tools for the risk stratification of OS.

Methods

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases provided transcriptome information relevant to OS. The GeneCards database was used to identify ARGs. Differentially expressed ARGs (DEARGs) were identified by overlapping ARGs with common differentially expressed genes (DEGs) between OS and normal samples from the GSE16088, GSE19276, and GSE99671 datasets. Anoikis-related clusters of patients were obtained by consistent clustering, and gene set variation analysis (GSVA) of the different clusters was completed. Next, a risk model was created using Cox regression analyses. Risk scores and clinical features were assessed for independent prognostic values, and a nomogram model was constructed. Subsequently, a functional enrichment analysis of the high- and low-risk groups was performed. In addition, the immunological characteristics of OS samples were compared between the high- and low-risk groups, and their sensitivity to therapeutic agents was explored.

Results

Seven DEARGs between OS and normal samples were obtained by intersecting 501 ARGs with 68 common DEGs. BNIP3 and CXCL12 were significantly differentially expressed between both clusters (P<0.05) and were identified as prognosis-related genes. The risk model showed that the risk score and tumor metastasis were independent prognostic factors of patients with OS. A nomogram combining risk score and tumor metastasis effectively predicted the prognosis. In addition, patients in the high-risk group had low immune scores and high tumor purity. The levels of immune cell infiltration, expression of human leukocyte antigen (HLA) genes, immune response gene sets, and immune checkpoints were lower in the high-risk group than those in the low-risk group. The low-risk group was sensitive to the immune checkpoint PD-1 inhibitor, and the high-risk group exhibited lower inhibitory concentration values by 50% for 24 drugs, including AG.014699, AMG.706, and AZD6482.

Conclusion

The prognostic stratification framework of patients with OS based on ARGs, such as BNIP3 and CXCL12, may lead to more efficient clinical management.

Prognostic model for hepatocellular carcinoma based on anoikis-related genes: immune landscape analysis and prediction of drug sensitivity

Background

Hepatocellular carcinoma (HCC) represents a complex ailment characterized by an unfavorable prognosis in advanced stages. The involvement of immune cells in HCC progression is of significant importance. Moreover, metastasis poses a substantial impediment to enhanced prognostication for HCC patients, with anoikis playing an indispensable role in facilitating the distant metastasis of tumor cells. Nevertheless, limited investigations have been conducted regarding the utilization of anoikis factors for predicting HCC prognosis and assessing immune infiltration. This present study aims to identify hepatocellular carcinoma-associated anoikis-related genes (ANRGs), establish a robust prognostic model for HCC, and delineate distinct immune characteristics based on the anoikis signature. Cell migration and cytotoxicity experiments were performed to validate the accuracy of the ANRGs model.

Methods

Consensus clustering based on ANRGs was employed in this investigation to categorize HCC samples obtained from both TCGA and Gene Expression Omnibus (GEO) cohorts. To assess the differentially expressed genes, Cox regression analysis was conducted, and subsequently, prognostic gene signatures were constructed using LASSO-Cox methodology. External validation was performed at the International Cancer Genome Conference. The tumor microenvironment (TME) was characterized utilizing ESTIMATE and CIBERSORT algorithms, while machine learning techniques facilitated the identification of potential target drugs. The wound healing assay and CCK-8 assay were employed to evaluate the migratory capacity and drug sensitivity of HCC cell lines, respectively.

Results

Utilizing the TCGA-LIHC dataset, we devised a nomogram integrating a ten-gene signature with diverse clinicopathological features. Furthermore, the discriminative potential and clinical utility of the ten-gene signature and nomogram were substantiated through ROC analysis and DCA. Subsequently, we devised a prognostic framework leveraging gene expression data from distinct risk cohorts to predict the drug responsiveness of HCC subtypes.

Conclusion

In this study, we have established a promising HCC prognostic ANRGs model, which can serve as a valuable tool for clinicians in selecting targeted therapeutic drugs, thereby improving overall patient survival rates. Additionally, this model has also revealed a strong connection between anoikis and immune cells, providing a potential avenue for elucidating the mechanisms underlying immune cell infiltration regulated by anoikis.

MCL1 Inhibition Overcomes the Aggressiveness Features of Triple-Negative Breast Cancer MDA-MB-231 Cells

Triple-Negative Breast Cancer (TNBC) is a particularly aggressive subtype among breast cancers (BCs), characterized by anoikis resistance, high invasiveness, and metastatic potential as well as Epithelial-Mesenchymal Transition (EMT) and stemness features. In the last few years, our research focused on the function of MCL1, an antiapoptotic protein frequently deregulated in TNBC. Here, we demonstrate that MCL1 inhibition by A-1210477, a specific BH3-mimetic, promotes anoikis/apoptosis in the MDA-MB-231 cell line, as shown via an increase in proapoptotic markers and caspase activation. Our evidence also shows A-1210477 effects on Focal Adhesions (FAs) impairing the integrin trim and survival signaling pathways, such as FAK, AKT, ERK, NF-κB, and GSK3β-inducing anoikis, thus suggesting a putative role of MCL1 in regulation of FA dynamics. Interestingly, in accordance with these results, we observed a reduction in migratory and invasiveness capabilities as confirmed by a decrease in metalloproteinases (MMPs) levels following A-1210477 treatment. Moreover, MCL1 inhibition promotes a reduction in EMT characteristics as demonstrated by the downregulation of Vimentin, MUC1, DNMT1, and a surprising re-expression of E-Cadherin, suggesting a possible mesenchymal-like phenotype reversion. In addition, we also observed the downregulation of stemness makers such as OCT3/4, SOX2, NANOG, as well as CD133, EpCAM, and CD49f. Our findings support the idea that MCL1 inhibition in MDA-MB-231 could be crucial to reduce anoikis resistance, aggressiveness, and metastatic potential and to minimize EMT and stemness features that distinguish TNBC.

V. J, Pal S, Nair BG, Kar R, Mishra N. Paraptosis: a unique cell death mode for targeting cancer

Programmed cell death (PCD) is the universal process that maintains cellular homeostasis and regulates all living systems' development, health and disease. Out of all, apoptosis is one of the major PCDs that was found to play a crucial role in many disease conditions, including cancer. The cancer cells acquire the ability to escape apoptotic cell death, thereby increasing their resistance towards current therapies. This issue has led to the need to search for alternate forms of programmed cell death mechanisms. Paraptosis is an alternative cell death pathway characterized by vacuolation and damage to the endoplasmic reticulum and mitochondria. Many natural compounds and metallic complexes have been reported to induce paraptosis in cancer cell lines. Since the morphological and biochemical features of paraptosis are much different from apoptosis and other alternate PCDs, it is crucial to understand the different modulators governing it. In this review, we have highlighted the factors that trigger paraptosis and the role of specific modulators in mediating this alternative cell death pathway. Recent findings include the role of paraptosis in inducing anti-tumour T-cell immunity and other immunogenic responses against cancer. A significant role played by paraptosis in cancer has also scaled its importance in knowing its mechanism. The study of paraptosis in xenograft mice, zebrafish model, 3D cultures, and novel paraptosis-based prognostic model for low-grade glioma patients have led to the broad aspect and its potential involvement in the field of cancer therapy. The co-occurrence of different modes of cell death with photodynamic therapy and other combinatorial treatments in the tumour microenvironment are also summarized here. Finally, the growth, challenges, and future perspectives of paraptosis research in cancer are discussed in this review. Understanding this unique PCD pathway would help to develop potential therapy and combat chemo-resistance in various cancer.

Therapeutic targeting of anoikis resistance in cutaneous melanoma metastasis

The acquisition of resistance to anoikis, the cell death induced by loss of adhesion to the extracellular matrix, is an absolute requirement for the survival of disseminating and circulating tumour cells (CTCs), and for the seeding of metastatic lesions. In melanoma, a range of intracellular signalling cascades have been identified as potential drivers of anoikis resistance, however a full understanding of the process is yet to be attained. Mechanisms of anoikis resistance pose an attractive target for the therapeutic treatment of disseminating and circulating melanoma cells. This review explores the range of small molecule, peptide and antibody inhibitors targeting molecules involved in anoikis resistance in melanoma, and may be repurposed to prevent metastatic melanoma prior to its initiation, potentially improving the prognosis for patients.