Non-canonical phosphorylation of Bmf by p38 MAPK promotes its apoptotic activity in anoikis

Anoikis resistance in Cancer: Mechanisms, therapeutic strategies, potential targets, and models for enhanced understanding

Anoikis, defined as programmed cell death triggered by the loss of cell-extracellular matrix (ECM) and cell-cell interactions, is crucial for maintaining tissue homeostasis and preventing aberrant cell migration. Cancer cells, however, display anoikis resistance (AR) which in turn enables cancer metastasis. AR results from alterations in apoptotic signaling, metabolic reprogramming, autophagy modulation, and epigenetic changes, allowing cancer cells to survive in detached conditions. In this review we describe the mechanisms underlying both anoikis and AR, focusing on intrinsic and extrinsic pathways, disrupted cell-ECM interactions, and autophagy in cancer. Recent findings (i.e., between 2014 and 2024) on epigenetic regulation of AR and its role in metastasis are discussed. Therapeutic strategies targeting AR, including chemical inhibitors, are highlighted alongside a network analysis of 122 proteins reported to be associated with AR which identifies 53 hub proteins as potential targets. We also evaluate in vitro and in vivo models for studying AR, emphasizing their role in advancing metastasis research. Our overall goal is to guide future studies and therapeutic developments to counter cancer metastasis.

Pressure loading regulates the stemness of liver cancer stem cells via YAP/BMF signaling axis

Cancer stem cells (CSCs) are considered the major cause of the occurrence, progression, chemoresistance/radioresistance, recurrence, and metastasis of cancer. Increased interstitial fluid pressure (IFP) is a key feature of solid tumors. Our previous study showed that the distribution of liver cancer stem cells (LCSCs) correlated with the mechanical heterogeneity within liver cancer tissues. However, the regulation of liver cancer's mechanical microenvironment on the LCSC stemness is not fully understood. Here, we employed a cellular pressure-loading device to investigate the effects of normal IFP (5 mmHg), as well as increased IFP (40 and 200 mmHg) on the stemness of LCSCs. Compared to the control LCSCs (exposure to 5 mmHg pressure loading), the LCSCs exposed to 40 mmHg pressure loading exhibited significantly upregulated expression of CSC markers (CD44, EpCAM, Nanog), enhanced sphere and colony formation capacities, and tumorigenic potential, whereas continuously increased pressure to 200 mmHg suppressed the LCSC characteristics. Mechanistically, pressure loading regulated Yes-associated protein (YAP) activity and Bcl-2 modifying factor (BMF) expression. YAP transcriptionally regulated BMF expression to affect the stemness of LCSCs. Knockdown of YAP and overexpression of BMF attenuated pressure-mediated stemness and tumorgenicity, while YAP-deficient and BMF-deletion recused pressure-dependent stemness on LCSCs, suggesting the involvement of YAP/BMF signaling axis in this process. Together, our findings provide a potential target for overcoming the stemness of CSCs and elucidate the significance of increased IFP in cancer progression.

An anoikis-related gene signature predicts prognosis in patients with acute myeloid leukemia and immunotherapy

Acute myeloid leukemia (AML) is a malignant blood disorder and the most common type of acute leukemia in adults. Notwithstanding the plethora of therapeutic modalities, a significant cohort of patients fail to respond to treatment and experience relapse. Anoikis, a distinct modality of programmed cell death, has been linked to cancer progression. However, the prognostic significance of anoikis in AML remains unclear. In this study, a non-negative matrix factorization algorithm was utilized to efficiently reduce the dimensions of merged datasets. We used differential analysis, weighted gene co-expression network analysis (WGCNA), univariate Cox regression, and least absolute shrinkage and selection operator (LASSO) regression to identify genes associated with prognosis and develop a risk scoring model. Immunohistochemistry was conducted to assess the expression levels of key genes in clinical samples. The association between risk score and the tumor microenvironment (TME), stemness, clinical characteristics, and immunotherapy was evaluated. We identified 41 AML anoikis-related genes (ANRGs) related to survival, and seven genes were chosen to develop prognostic models. The prognostic risk score combined with the clinical and pathological features of AML was used to develop a nomogram, and decision curve analysis demonstrated the net clinical benefit of the model. Furthermore, analysis of ANRGs revealed that PDGFRB inhibition significantly reduced the proliferation of AML cells, promoted apoptosis, and inhibited AML progression both in vitro and in vivo, indicating that PDGFRB plays a crucial role in AML development.

Uncovering the Role of Anoikis-Related Genes in Modulating Immune Infiltration and Pathogenesis of Diabetic Kidney Disease

Background

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.

Construction and validation of a prognostic signature based on anoikis-related lncRNAs in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common type of lung cancer and is characterized by a high death rate and a poor prospect for survival. Anoikis, which is a kind of programmed cell apoptosis, is an important factor in the advancement of tumors. Nonetheless, the function of anoikis-related lncRNAs (ARLRs) in LUAD is still not well understood. The TCGA database was queried for genomic and clinical information. A prognostic signature for ARLRs was established via the use of coexpression analysis and Cox regression. Validation of the model's accuracy was conducted utilizing K-M curves and receiver operating characteristic (ROC) curves, and the signature was utilized to develop a nomogram. LncRNAs were implicated in the progression of tumors, as determined by functional enrichment analysis. There was an improvement in prognosis, increased immune cell infiltration, and higher immune scores among the low-risk patients. Additionally, we found that the two groups had varied anticancer drug sensitivities, which could help guide treatment. The impact of one ARLR, AC026355.2, on migration and invasion was validated by in vitro experiments in LUAD cells. Herein, a new lncRNA signature associated with anoikis was identified and estimated, potentially serving as a prognostic indicator for LUAD patients.

Deciphering anoikis resistance and identifying prognostic biomarkers in clear cell renal cell carcinoma epithelial cells

This study tackles the persistent prognostic and management challenges of clear cell renal cell carcinoma (ccRCC), despite advancements in multimodal therapies. Focusing on anoikis, a critical form of programmed cell death in tumor progression and metastasis, we investigated its resistance in cancer evolution. Using single-cell RNA sequencing from seven ccRCC patients, we assessed the impact of anoikis-related genes (ARGs) and identified differentially expressed genes (DEGs) in Anoikis-related epithelial subclusters (ARESs). Additionally, six ccRCC RNA microarray datasets from the GEO database were analyzed for robust DEGs. A novel risk prognostic model was developed through LASSO and multivariate Cox regression, validated using BEST, ULCAN, and RT-PCR. The study included functional enrichment, immune infiltration analysis in the tumor microenvironment (TME), and drug sensitivity assessments, leading to a predictive nomogram integrating clinical parameters. Results highlighted dynamic ARG expression patterns and enhanced intercellular interactions in ARESs, with significant KEGG pathway enrichment in MYC + Epithelial subclusters indicating enhanced anoikis resistance. Additionally, all ARESs were identified in the spatial context, and their locational relationships were explored. Three key prognostic genes-TIMP1, PECAM1, and CDKN1A-were identified, with the high-risk group showing greater immune infiltration and anoikis resistance, linked to poorer prognosis. This study offers a novel ccRCC risk signature, providing innovative approaches for patient management, prognosis, and personalized treatment.

Anoikis related genes may be novel markers associated with prognosis for ovarian cancer

The aim of this study was to determine the prognostic significance of anoikis related genes (ARGs) in ovarian cancer (OC) and to develop a prognostic signature based on ARG expression. We analyzed cohorts of OC patients and used nonnegative matrix factorization (NMF) for clustering. Single-sample gene-set enrichment analysis (ssGSEA) was employed to quantify immune infiltration. Survival analyses were performed using the Kaplan-Meier method, and differences in survival were determined using the log-rank test. The extent of anoikis modification was quantified using a risk score generated from ARG expression. The analysis of single-cell sequencing data was performed by the Tumor Immune Single Cell Hub (TISCH). Our analyses revealed two distinct patterns of anoikis modification. The risk score was used to evaluate the anoikis modification patterns in individual tumors. Three hub-genes were screened using the LASSO (Least Absolute Shrinkage and Selection Operator) method and patients were classified into different risk groups based on their individual score and the median score. The low-risk subtype was characterized by decreased expression of hub-genes and better overall survival. The risk score, along with patient age and gender, were considered to identify the prognostic signature, which was visualized using a nomogram. Our findings suggest that ARGs may play a novel role in the prognosis of OC. Based on ARG expression, we have developed a prognostic signature for OC that can aid in patient stratification and treatment decision-making. Further studies are needed to validate these results and to explore the underlying mechanisms.

Deciphering the significance of anoikis in bladder cancer and systematic analysis of S100A7 as a potential therapeutic target

BACKGROUND

Bladder cancer is an epidemic and life-threating urologic carcinoma. Anoikis is a unusual type of programmed cell death which plays a vital role in tumor survival, invasion and metastasis. Nevertheless, the relationship between anoikis and bladder cancer has not been understood thoroughly.

METHODS

We downloaded the transcriptome and clinical information of BLCA patients from TCGA and GEO databases. Then, we analyzed different expression of anoikis-related genes and established a prognostic model based on TCGA database by univariate Cox regression, lasso regression, and multivariate Cox regression. Then the Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curves were performed. GEO database was used for external validation. BLCA patients in TCGA database were divided into two subgroups by non-negative matrix factorization (NMF) classification. Survival analysis, different gene expression, immune cell infiltration and drug sensitivity were calculated. Finally, we verified the function of S100A7 in two BLCA cell lines.

RESULTS

We developed a prognostic risk model based on three anoikis-related genes including TPM1, RAC3 and S100A7. The overall survival of BLCA patients in low-risk groups was significantly better than high-risk groups in training sets, test sets and external validation sets. Subsequently, the checkpoint and immune cell infiltration had significant difference between two groups. Then we identified two subtypes (CA and CB) through NMF analysis and found CA had better OS and PFS than CB. Besides, the accuracy of risk model was verified by ROC analysis. Finally, we identified that knocking down S100A7 gene expression restrained the proliferation and invasion of bladder cancer cells.

CONCLUSION

We established and validated a bladder cancer prognostic model consisting of three genes, which can effectively evaluate the prognosis of bladder cancer patients. Additionally, through cellular experiments, we demonstrated the significant role of S100A7 in the metastasis and invasion of bladder cancer, suggesting its potential as a novel target for future treatments.

Development of a prognostic model to predict BLCA based on anoikis-related gene signature: preliminary findings

BACKGROUND

The prevalence of bladder urothelial carcinoma (BLCA) is significant on a global scale. Anoikis is a type of procedural cell death that has an important role in tumor invasion and metastasis. The advent of single-cell RNA sequencing (scRNA-seq) approaches has revolutionized the genomics field by providing unprecedented opportunities for elucidating cellular heterogeneity. Understanding the mechanisms associated with anoikis in BLCA is essential to improve its survival rate.

METHODS

Data on BLCA and clinical information were acquired from the databases of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). ARGs were obtained from Genecards and Harmonizome databases. According to univariate Cox regression analysis, the least absolute shrinkage and selection operator (LASSO) algorithm was utilized to select the ARGs associated with the overall rate (OS). A multivariate Cox regression analysis was carried out to identify eight prognostic ARGs, leading to the establishment of a risk model. The OS rate of BLCA patients was evaluated using Kaplan-Meier survival analysis. To explore the molecular mechanism in low- and high-risk groups, we employed Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSVA). Immune infiltration landscape estimation was performed using ESTIMATE, CIBERSOT, and single sample gene set enrichment analysis (ssGSEA) algorithms. Patients were categorized into different subgroups through consensus clustering analysis. We employed biological functional enrichment analysis and conducted immune infiltration analysis to examine the disparities in potential biological functions, infiltration of immune cells, immune activities, and responses to immunotherapy.

RESULTS

We identified 647 ARGs and 37 survival-related genes. We further developed a risk scoring model to quantitatively assess the predictive capacity of ARGs. The high-risk score group exhibited an unfavorable prognosis, whereas the low-risk score group demonstrated a converse effect. We also found that the two groups of patients might respond differently to immune targets and anti-tumor drugs.

CONCLUSION

The nomogram with 8 ARGs may help guide treatment of BLCA. The systematic assessment of risk scores can help to design more individualized and precise treatment strategies for BLCA patients.

Cell aggregation activates small GTPase Rac1 and induces CD44 cleavage by maintaining lipid raft integrity

Lipid rafts are highly ordered membrane domains that are enriched in cholesterol and glycosphingolipids and serve as major platforms for signal transduction. Cell detachment from the extracellular matrix (ECM) triggers lipid raft disruption and anoikis, which is a barrier for cancer cells to metastasize. Compared to single circulating tumor cells (CTCs), our recent studies have demonstrated that CD44-mediatd cell aggregation enhances the stemness, survival and metastatic ability of aggregated cells. Here, we investigated whether and how lipid rafts are involved in CD44-mediated cell aggregation. We found that cell detachment, which mimics the condition when tumor cells detach from the ECM to metastasize, induced lipid raft disruption in single cells, but lipid raft integrity was maintained in aggregated cells. We further found that lipid raft integrity in aggregated cells was required for Rac1 activation to prevent anoikis. In addition, CD44 and γ-secretase coexisted at lipid rafts in aggregated cells, which promoted CD44 cleavage and generated CD44 intracellular domain (CD44 ICD) to enhance stemness of aggregated cells. Consequently, lipid raft disruption inhibited Rac1 activation, CD44 ICD generation, and metastasis. Our findings reveal two new pathways regulated by CD44-mediated cell aggregation via maintaining lipid raft integrity. These findings also suggest that targeting cell aggregation-mediated pathways could be a novel therapeutic strategy to prevent CTC cluster-initiated metastasis.

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.

Types of Cell Death from a Molecular Perspective

The former conventional belief was that cell death resulted from either apoptosis or necrosis; however, in recent years, different pathways through which a cell can undergo cell death have been discovered. Various types of cell death are distinguished by specific morphological alterations in the cell's structure, coupled with numerous biological activation processes. Various diseases, such as cancers, can occur due to the accumulation of damaged cells in the body caused by the dysregulation and failure of cell death. Thus, comprehending these cell death pathways is crucial for formulating effective therapeutic strategies. We focused on providing a comprehensive overview of the existing literature pertaining to various forms of cell death, encompassing apoptosis, anoikis, pyroptosis, NETosis, ferroptosis, autophagy, entosis, methuosis, paraptosis, mitoptosis, parthanatos, necroptosis, and necrosis.

Glioma Stem Cells Are Sensitized to BCL-2 Family Inhibition by Compromising Histone Deacetylases

Glioblastoma (GBM) remains an incurable disease with an extremely high five-year recurrence rate. We studied apoptosis in glioma stem cells (GSCs) in response to HDAC inhibition (HDACi) combined with MEK1/2 inhibition (MEKi) or BCL-2 family inhibitors. MEKi effectively combined with HDACi to suppress growth, induce cell cycle defects, and apoptosis, as well as to rescue the expression of the pro-apoptotic BH3-only proteins BIM and BMF. A RNAseq analysis of GSCs revealed that HDACi repressed the pro-survival BCL-2 family genes MCL1 and BCL-XL. We therefore replaced MEKi with BCL-2 family inhibitors and observed enhanced apoptosis. Conversely, a ligand for the cancer stem cell receptor CD44 led to reductions in BMF, BIM, and apoptosis. Our data strongly support further testing of HDACi in combination with MEKi or BCL-2 family inhibitors in glioma.

The anoikis-related gene signature predicts survival accurately in colon adenocarcinoma

Colon adenocarcinoma (COAD) is a serious public health problem, the third most common cancer and the second most deadly cancer in the world. About 9.4% of cancer-related deaths in 2020 were due to COAD. Anoikis is a specialized form of programmed cell death that plays an important role in tumor invasion and metastasis. The presence of anti-anoikis factors is associated with tumor aggressiveness and drug resistance. Various bioinformatic methods, such as differential expression analysis, and functional annotation analysis, machine learning, were used in this study. RNA-sequencing and clinical data from COAD patients were obtained from the Gene expression omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Construction of a prognostic nomogram for predicting overall survival (OS) using multivariate analysis and Lasso-Cox regression. Immunohistochemistry (IHC) was our method of validating the expression of seven genes that are linked to anoikis in COAD. We identified seven anoikis-related genes as predictors of COAD survival and prognosis, and confirmed their accuracy in predicting colon adenocarcinoma prognosis by KM survival curves and ROC curves. A seven-gene risk score consisting of NAT1, CDC25C, ATP2A3, MMP3, EEF1A2, PBK, and TIMP1 showed strong prognostic value. Meanwhile, we made a nomogram to predict the survival rate of COAD patients. The immune infiltration assay showed T cells. CD4 memory. Rest and macrophages. M0 has a higher proportion in COAD, and 11 genes related to tumor immunity are important. GDSC2-based drug susceptibility analysis showed that 6 out of 198 drugs were significant in COAD. Anoikis-related genes have potential value in predicting the prognosis of COAD and provide clues for developing new therapeutic strategies for COAD. Immune infiltration and drug susceptibility results provide important clues for finding new personalized treatment options for COAD. These findings also suggest possible mechanisms that may affect prognosis. These results are the starting point for planning individualized treatment and managing patient outcomes.

Structural basis of the specificity and interaction mechanism of Bmf binding to pro-survival Bcl-2 family proteins

The apoptotic pathway is regulated by protein-protein interactions between members of the Bcl-2 family. Pro-survival Bcl-2 family proteins act as cell guardians and protect cells against death. Selective binding and neutralization of BH3-only proteins with pro-survival Bcl-2 family proteins is critical for initiating apoptosis. In this study, the binding assay shows that the BH3 peptide derived from the BH3-only protein Bmf has a high affinity for the pro-survival proteins Bcl-2 and Bcl-xL, but a much lower affinity for Mcl-1. The complex structures of Bmf BH3 with Bcl-2, Bcl-xL and Mcl-1 reveal that the α-helical Bmf BH3 accommodates into the canonical groove of these pro-survival proteins, but the conformational changes and some interactions are different among the three complexes. Bmf BH3 forms conserved hydrophobic and salt bridge interactions with Bcl-2 and Bcl-xL, and also establishes several hydrogen bonds to support their binding. However, the highly conserved Asp-Arg salt bridge is not formed in the Mcl-1/Bmf BH3 complex, and few hydrogen bonds are observed. Furthermore, mutational analysis shows that substitutions of less-conserved residues in the α2-α3 region of these pro-survival Bcl-2 family proteins, as well as the highly conserved Arg, lead to significant changes in their binding affinity to Bmf BH3, while substitutions of less-conserved residues in Bmf BH3 have a more dramatic effect on its affinity to Mcl-1. This study provides structural insight into the specificity and interaction mechanism of Bmf BH3 binding to pro-survival Bcl-2 family proteins, and helps guide the design of BH3 mimics targeting pro-survival Bcl-2 family proteins.

Cell aggregation prevents anoikis and induces CD44 cleavage by maintaining lipid raft integrity to promote triple negative breast cancer metastasis

Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype, and metastasis is the major cause of cancer morbidity and mortality. Therefore, it is urgent to discover novel therapeutic targets and develop effective treatments for this lethal disease. Circulating tumor cells (CTCs) are considered "seeds of metastasis". Compared to single CTCs, our previous studies have demonstrated that CD44 homophilic interaction mediates CTC aggregation to enhance the stemness, survival and metastatic ability of aggregated cells. Importantly, the presence of CD44+ CTC clusters correlates with a poor prognosis in breast cancer patients. Here, we further investigated the underlying mechanism of how CD44-mediated cell aggregation promotes TNBC metastasis. We found that cell detachment, which mimics the condition when tumor cells detach from the extracellular matrix (ECM) to metastasize, induces lipid raft disruption in single cells, but lipid rafts integrity is maintained in aggregated cells. We further found that lipid rafts integrity in aggregated cells is required for Rac1 activation to prevent anoikis. In addition, CD44 and γ-secretase coexisted at lipid rafts in aggregated cells, which promotes CD44 cleavage and generates CD44 intracellular domain (CD44 ICD) to enhance stemness. Consequently, lipid rafts disruption inhibited Rac1 activation, CD44 ICD generation and metastasis. These data reveal a new mechanism of cell aggregation-mediated TNBC metastasis via maintaining lipid raft integrity after cell detachment. The finding provides a potential therapeutic strategy to prevent CTC cluster-initiated metastasis by disrupting lipid raft integrity and its-mediated downstream pathways.

Identification and validation of an anoikis-related lncRNA signature to predict prognosis and immune landscape in osteosarcoma

Background

Anoikis is a specialized form of programmed apoptosis that occurs in two model epithelial cell lines and plays an important role in tumors. However, the prognostic value of anoikis-related lncRNA (ARLncs) in osteosarcoma (OS) has not been reported.

Methods

Based on GTEx and TARGET RNA sequencing data, we carried out a thorough bioinformatics analysis. The 27 anoikis-related genes were obtained from the Gene Set Enrichment Analysis (GSEA). Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analysis were successively used to screen for prognostic-related ARLncs. To create the prognostic signature of ARLncs, we performed multivariate Cox regression analysis. We calculated the risk score based on the risk coefficient, dividing OS patients into high- and low-risk subgroups. Additionally, the relationship between the OS immune microenvironment and risk prognostic models was investigated using function enrichment, including Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), single-sample gene set enrichment analysis (ssGSEA), and GSEA analysis. Finally, the potential effective drugs in OS were found by immune checkpoint and drug sensitivity screening.

Results

A prognostic signature consisting of four ARLncs (AC079612.1, MEF2C-AS1, SNHG6, and TBX2-AS1) was constructed. To assess the regulation patterns of anoikis-related lncRNA genes, we created a risk score model. According to a survival analysis, high-risk patients have a poor prognosis as they progress. By using immune functional analysis, the lower-risk group demonstrated the opposite effects compared with the higher-risk group. GO and KEGG analysis showed that the ARLncs pathways and immune-related pathways were enriched. Immune checkpoints and drug sensitivity analysis might be used to determine the better effects of the higher group.

Conclusion

We identified a novel prognostic model based on a four-ARLncs signature that might serve as potential prognostic indicators that can be used to predict the prognosis of OS patients, and immunotherapy and drugs that may contribute to improving the overall survival of OS patients and advance our understanding of OS.

Exploration and identification of anoikis-related genes in polycythemia vera

Background: Polycythemia Vera (PV) is a type of typical Myeloproliferative Neoplasms (MPNs) characterized with excessive erythropoiesis and thrombosis. Anoikis is a special programmed cell death mode induced by the adhesion disorder between cells and extracellular matrix (ECM) or adjacent cells facilitating cancer metastasis. However, few studies have focused on the role of anoikis in PV, especially on the development of PV. Methods: The microarray and RNA-seq results were screened from the Gene Expression Omnibus (GEO) database and the anoikis-related genes (ARGs) were downloaded from Genecards. The functional enrichment analysis of intersecting differentially expressed genes (DEGs) and protein-protein interaction (PPI) network analysis were performed to discover hub genes. The hub genes expression was tested in the training (GSE136335) and validation cohort (GSE145802), and RT-qPCR was performed to verify the gene expression in PV mice. Results: In the training GSE136335, a total of 1,195 DEGs was obtained from Myeloproliferative Neoplasm (MPN) patients compared with controls, among which 58 were anoikis-related DEGs. The significant enrichment of the apoptosis and cell adhesion pathways (i.e., cadherin binding) were shown in functional enrichment analysis. The PPI network was conducted to identify top five hub genes (CASP3, CYCS, HIF1A, IL1B, MCL1). The expression of CASP3 and IL1B were significantly upregulated both in validation cohort and PV mice and downregulated after treatment, suggesting that CASP3 and IL1B could be important indicators for disease surveillance. Conclusion: Our research revealed a relationship between anoikis and PV for the first time by combined analysis of gene level, protein interaction and functional enrichment, allowing novel insights into mechanisms of PV. Moreover, CASP3 and IL1B may become promising indicators of PV development and treatment.

miR-450-5p and miR-202-5p Synergistically Regulate Follicle Development in Black Goat

Follicle maturation is a complex biological process governed by numerous factors, and researchers have observed follicle development by studying the proliferation and apoptosis of follicular granulosa cells (GCs). However, the regulatory mechanisms of GCs proliferation and death during follicle development are largely unknown. To investigate the regulatory mechanisms of lncRNAs, mRNAs, and microRNAs, RNA sequencing (RNA-seq) and small RNA-seq were performed on large (>10 mm) and small follicles (<3 mm) of Leizhou black goat during estrus. We discovered two microRNAs, miR-450-5p and miR-202-5p, which can target GCs in goats and may be involved in follicle maturation, and the effects of miR-450-5p and miR-202-5p on ovarian granulosa cell lines were investigated (KGN). Using cell counting kit-8 (CCK-8) assays, 5-Ethynyl-2’-deoxyuridine (EdU) assay and flow cytometry, miR-202-5p overexpression could suppress the proliferation and induce apoptosis of GCs, whereas miR-450-5p overexpression induced the opposite effects. The dual-luciferase reporter assay confirmed that miR-450-5p could directly target the BMF gene (a BCL2 modifying factor), and miR-202-5p targeted the BCL2 gene. A considerable rise in phosphorylated Akt (p-AKT) protein was observed following the downregulation of BMF by miR-450-5p mimics. After BMF gene RNAi therapy, a notable elevation in p-AKT was detected. Mimics of miR-202-5p inhibited BCL2 protein expression, significantly decreasing p-AMPK protein expression. These results imply that during the follicular development in black goats, the miR-450-5p-BMF axis favored GC proliferation on a wide scale, while the miR-202-5p-BCL2 axis triggered GC apoptosis.

Comparative roadmaps of reprogramming and oncogenic transformation identify Bcl11b and Atoh8 as broad regulators of cellular plasticity

Coordinated changes of cellular plasticity and identity are critical for pluripotent reprogramming and oncogenic transformation. However, the sequences of events that orchestrate these intermingled modifications have never been comparatively dissected. Here, we deconvolute the cellular trajectories of reprogramming (via Oct4/Sox2/Klf4/c-Myc) and transformation (via Ras/c-Myc) at the single-cell resolution and reveal how the two processes intersect before they bifurcate. This approach led us to identify the transcription factor Bcl11b as a broad-range regulator of cell fate changes, as well as a pertinent marker to capture early cellular intermediates that emerge simultaneously during reprogramming and transformation. Multiomics characterization of these intermediates unveiled a c-Myc/Atoh8/Sfrp1 regulatory axis that constrains reprogramming, transformation and transdifferentiation. Mechanistically, we found that Atoh8 restrains cellular plasticity, independent of cellular identity, by binding a specific enhancer network. This study provides insights into the partitioned control of cellular plasticity and identity for both regenerative and cancer biology.

Huyghe, Furlan et al. compare pluripotent reprogramming with oncogenic transformation and identify Bcl11b and Atoh8 as regulators of cellular plasticity in both processes, thus offering a unifying theory on the factors constraining cell fate changes.

Identification and validation of an anoikis-associated gene signature to predict clinical character, stemness, IDH mutation, and immune filtration in glioblastoma

Background

Glioblastoma (GBM) is the most prominent and aggressive primary brain tumor in adults. Anoikis is a specific form of programmed cell death that plays a key role in tumor invasion and metastasis. The presence of anti-anoikis factors is associated with tumor aggressiveness and drug resistance.

Methods

The non-negative matrix factorization algorithm was used for effective dimension reduction for integrated datasets. Differences in the tumor microenvironment (TME), stemness indices, and clinical characteristics between the two clusters were analyzed. Difference analysis, weighted gene coexpression network analysis (WGCNA), univariate Cox regression, and least absolute shrinkage and selection operator regression were leveraged to screen prognosis-related genes and construct a risk score model. Immunohistochemistry was performed to evaluate the expression of representative genes in clinical specimens. The relationship between the risk score and the TME, stemness, clinical traits, and immunotherapy response was assessed in GBM and pancancer.

Results

Two definite clusters were identified on the basis of anoikis-related gene expression. Patients with GBM assigned to C1 were characterized by shortened overall survival, higher suppressive immune infiltration levels, and lower stemness indices. We further constructed a risk scoring model to quantify the regulatory patterns of anoikis-related genes. The higher risk score group was characterized by a poor prognosis, the infiltration of suppressive immune cells and a differentiated phenotype, whereas the lower risk score group exhibited the opposite effects. In addition, patients in the lower risk score group exhibited a higher frequency of isocitrate dehydrogenase (IDH) mutations and a more sensitive response to immunotherapy. Drug sensitivity analysis was performed, revealing that the higher risk group may benefit more from drugs targeting the PI3K/mTOR signaling pathway.

Conclusion

We revealed potential relationships between anoikis-related genes and clinical features, TME, stemness, IDH mutation, and immunotherapy and elucidated their therapeutic value.

Expression of the First Recombinant Anti-Tumoral Snake Venom Kunitz-Type Serine Protease Inhibitor

PIVL is a Kunitz-type serine protease inhibitor that was previously characterized from Tunisian snake venom, Macrovipera lebetina transmediterranea. It reduced glioblastoma cells’ development and significantly blocked angiogenesis in in-vitro and ex-vivo models. PIVL exerted these effects by interfering with αvβ3 integrin. In order to produce a biological active recombinant, the cDNA cloning and expression of PIVL was performed in Escherichia coli (BL21)-DE3 cells using pET-22b (+) vector. The recombinant PIVL protein (rPIVL) was purified by nickel affinity chromatography and has recognized monoclonal anti-His antibody. Functionally, rPIVL exhibited potent anti-tumor cell effects as well as anti-angiogenesis properties. Interestingly, we found that both native PIVL (nPIVL) and rPIVL modulated PI3/AKT and MAPK signaling pathways. In all, our results showed that we have successfully expressed the first active anti-oncogenic snake venom Kunitz-type protease inhibitor that can be a potential therapeutic drug against glioblastoma, in its native or recombinant form.