Targeting tumor-associated MUC1 overcomes anoikis-resistance in pancreatic cancer

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.

SERPINE1 Facilitates Metastasis in Gastric Cancer Through Anoikis Resistance and Tumor Microenvironment Remodeling

SERPINE1 is a serine protease inhibitor upregulated in various malignancies and pivotal in gastric cancer (GC) metastasis and the tumor microenvironment (TME). This study elucidates the mechanisms by which SERPINE1 mediates anoikis resistance and fosters an immunosuppressive TME in advanced GC. SERPINE1 is highly expressed in GC tissues and metastatic lesions and serves as an independent risk factor for poor prognosis. The transcriptional activation of SERPINE1 by CEBPB triggers the PI3K/AKT and EMT signaling pathway via autocrine mechanisms, enhancing anoikis resistance and metastatic potential in GC cells. Furthermore, SERPINE1 facilitates M2 macrophage polarization by binding to lipoprotein receptor-related protein 1 (LRP1) in a paracrine manner, suppressing CD8+ T-cell infiltration and functionality in the TME. Therapeutic intervention combining SERPINE1 inhibition with PD-1 blockade exhibits synergistic antitumor effects. Clinically, high SERPINE1 expression is associated with an increased risk of recurrence following immune checkpoint inhibitor therapy in patients with advanced GC. These findings suggest that SERPINE1 is a critical driver of GC progression through anoikis resistance and TME remodeling. Hence, SERPINE1 can offer a promising therapeutic target and represent a predictive biomarker for immunotherapy outcomes in GC.

E2F4 Promotes Malignant Behaviors of Prostate Cancer Through Activating MUC1 Expression Transcriptionally

BACKGROUND

The malignant features of prostate cancer (PC) threaten the patient's life. MUC1 was observably enhanced in PC. However, the reason for higher MUC1 expression in PC is still unclear and deserves to be further investigated.

METHODS

The abundance of MUC1 and E2F4 was evaluated using RT-qPCR in PC patients and PC cells. Pearson correlation coefficient analyzed the relationship between E2F4 and MUC1 in tissues from PC patients. Malignant phenotypes were examined using clone formation, scratch tests, transwell, and flow cytometry. The JASPAR website, luciferase activity assay, and ChIP were employed for validating interplays between E2F4 and the MUC1 promoter.

RESULTS

MUC1 and E2F4 were abnormally elevated in samples of PC patients and PC cells. MUC1 silencing resulted in suppression of growth and metastasis and promotion of cell apoptosis of PC cells. Additionally, E2F4 could provoke the transcriptional activity of MUC1 to enhance MUC1 expression. Furthermore, E2F4 knockdown inhibited malignant features of PC cells, which was abolished by MUC1 overexpression.

CONCLUSION

Our findings revealed that E2F4 silencing led to the suppression of growth and metastasis and the promotion of cell apoptosis of PC cells through reducing MUC1 expression, which offered targeting molecules for PC treatment.

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.

Identification of a novel signature based on RNA methylation-associated anoikis-related genes for predicting prognosis and characterizing immune landscape in colorectal cancer

BACKGROUND

RNA methylation is a potential target for cancer therapy, while anoikis, a form of programmed cell death, is linked to cancer metastasis. However, the prognostic and immune significance of RNA methylation- and anoikis-related genes in colorectal cancer (CRC) remains unknown.

METHODS

Transcriptomic and clinicopathological data for CRC were obtained from TCGA and the GEO databases. A novel signature was constructed based on RNA methylation- and anoikis-related genes using univariate and multivariate Cox regression as well as LASSO Cox regression methods. CRC patients were stratified into low- and high-risk groups based on this signature. Differences in prognosis, immune infiltration, and drug sensitivity between two groups were analyzed. Finally, immunohistochemistry, western blot, and RT-qPCR were employed to validate the expression of the key gene SERPINE1 in CRC tissues and cells, as well as the effect of FTO on its expression.

RESULTS

We identified 79 differentially expressed RNA methylation-associated anoikis-related genes (RMRARGs) in both cancerous and normal tissues. A signature composed of 9 key genes (BID, FASN, PLK1, CDKN3, MYC, EPHA2, SERPINE1, CD36, PDK4) was established. Kaplan-Meier analysis revealed a poorer prognosis in the high-risk group. Compared to the other three published models, this signature demonstrated superior predictive performance based on the ROC curve analysis. Functional analyses highlighted differences in drug sensitivities and signaling pathways between risk groups. Furthermore, immune analysis results showed that risk score was associated with some immune cells and immune checkpoints. Immunohistochemistry showed high SERPINE1 expression in CRC tissues, with FTO expression positively correlated with SERPINE1. Furthermore, RT-qPCR and western blot indicated FTO knockdown markedly downregulated SERPINE1 levels.

CONCLUSION

Our findings underscore the prognostic value of this signature in CRC patients and its utility in assessing immune status. Additionally, the m6A demethylase FTO regulates the expression of the anoikis-related gene SERPINE1.

The Oncoprotein Mucin 1 in Pancreatic Cancer Onset and Progression: Potential Clinical Implications

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy characterized by poor prognosis, therapeutic resistance, and frequent recurrence. Current therapeutic options for PDAC include surgery, radiotherapy, immunological and targeted approaches. However, all these therapies provide only a slight improvement in patient survival. Consequently, the discovery of novel specific targets is becoming a priority to develop more effective treatments for PDAC. Mucin 1 (MUC1), a transmembrane glycoprotein, is aberrantly glycosylated and frequently overexpressed in pancreatic cancer. Recent studies highlighted the role of this oncoprotein in pancreatic carcinogenesis and its involvement in the acquisition of typical aggressive features of PDAC, like local invasion, metastases, and drug resistance. This review explores the mechanisms by which MUC1 contributes to cancer onset and progression, with a focus on its potential role as a biomarker and novel therapeutic target for pancreatic adenocarcinoma treatment.

Metabolic reprogramming and signaling adaptations in anoikis resistance: mechanisms and therapeutic targets

Anoikis, a form of programmed cell death triggered by detachment from the extracellular matrix (ECM), maintains tissue homeostasis by removing mislocalized or detached cells. Cancer cells, however, have evolved multiple mechanisms to evade anoikis under conditions of ECM detachment, enabling survival and distant metastasis. Studies have identified differentially expressed proteins between suspended and adherent cancer cells, revealing that key metabolic and signaling pathways undergo significant alterations during the acquisition of anoikis resistance. This review explores the regulatory roles of epithelial-mesenchymal transition, cancer stem cell characteristics, metabolic reprogramming, and various signaling pathway alterations in promoting anoikis resistance. And the corresponding reagents and non-coding RNAs that target the aforementioned pathways are reviewed. By discussing the regulatory mechanisms that facilitate anoikis resistance in cancer cells, this review aims to shed light on potential strategies for inhibiting tumor progression and preventing metastasis.

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.

Advances in MUC1 resistance to chemotherapy in pancreatic cancer

The incidence of pancreatic cancer (PC), a highly fatal malignancy, is increasing every year. Chemotherapy is an important treatment for it in addition to surgery, yet most patients become resistant to chemotherapeutic agents within a few weeks of treatment initiation.​ MUC1 is a highly glycosylated transmembrane protein, and studies have shown that aberrantly glycosylated overexpression of MUC1 is involved in regulating the biology of chemoresistance in cancer cells. This article summarizes the mechanism of MUC1 in PC chemoresistance and reviews MUC1-based targeted therapies.

Anoikis in cell fate, physiopathology, and therapeutic interventions

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

KRT19 is regulated by miR-642a-5p and promotes pancreatic cancer progression through the Wnt/β-catenin pathway

Pancreatic cancer (PC) has a really poor prognosis, and we urgently need to delve deeper into its molecular mechanisms. In this study, we found that KRT19 expression was significantly increased in PC tissues and cell lines and it was linked to unfavorable outcomes for patients. Overexpression of KRT19 boosted the proliferation, migration, and invasion of PC cells. Additionally, miR-374b-5p targets KRT19, inhibiting the activation of the Wnt/β-catenin pathway (WBC), which in turn suppresses epithelial-to-mesenchymal transition (EMT) and the progression of PC. Further experiments showed that under hypoxic conditions, HIF1α was positively correlated with KRT19, promoting its expression. The loss of miR-642a-5p and the upregulation of KRT19 induced by hypoxia can significantly favor PC progression. Plus, the increased expression of KRT19 might act as a predictive marker and potential target for PC treatment.

The romantic history of signaling pathway discovery in cell death: an updated review

Cell death is a fundamental physiological process in all living organisms. Processes such as embryonic development, organ formation, tissue growth, organismal immunity, and drug response are accompanied by cell death. In recent years with the development of electron microscopy as well as biological techniques, especially the discovery of novel death modes such as ferroptosis, cuprotosis, alkaliptosis, oxeiptosis, and disulfidptosis, researchers have been promoted to have a deeper understanding of cell death modes. In this systematic review, we examined the current understanding of modes of cell death, including the recently discovered novel death modes. Our analysis highlights the common and unique pathways of these death modes, as well as their impact on surrounding cells and the organism as a whole. Our aim was to provide a comprehensive overview of the current state of research on cell death, with a focus on identifying gaps in our knowledge and opportunities for future investigation. We also presented a new insight for macroscopic intracellular survival patterns, namely that intracellular molecular homeostasis is central to the balance of different cell death modes, and this viewpoint can be well justified by the signaling crosstalk of different death modes. These concepts can facilitate the future research about cell death in clinical diagnosis, drug development, and therapeutic modalities.

Glycosylation: mechanisms, biological functions and clinical implications

Protein post-translational modification (PTM) is a covalent process that occurs in proteins during or after translation through the addition or removal of one or more functional groups, and has a profound effect on protein function. Glycosylation is one of the most common PTMs, in which polysaccharides are transferred to specific amino acid residues in proteins by glycosyltransferases. A growing body of evidence suggests that glycosylation is essential for the unfolding of various functional activities in organisms, such as playing a key role in the regulation of protein function, cell adhesion and immune escape. Aberrant glycosylation is also closely associated with the development of various diseases. Abnormal glycosylation patterns are closely linked to the emergence of various health conditions, including cancer, inflammation, autoimmune disorders, and several other diseases. However, the underlying composition and structure of the glycosylated residues have not been determined. It is imperative to fully understand the internal structure and differential expression of glycosylation, and to incorporate advanced detection technologies to keep the knowledge advancing. Investigations on the clinical applications of glycosylation focused on sensitive and promising biomarkers, development of more effective small molecule targeted drugs and emerging vaccines. These studies provide a new area for novel therapeutic strategies based on glycosylation.

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.

Beyond Death: Unmasking the Intricacies of Apoptosis Escape

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

A Diagnostic Model for Parkinson's Disease Based on Anoikis-Related Genes

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

Tumor-associated carbohydrate antigens of MUC1 - Implication in cancer development

Glycosylation of cancerous epithelial MUC1 protein is specifically altered in comparison to that which is presented by healthy cells. One of such changes is appearing tumor-associated carbohydrate antigens (TACAs) which are rare in normal tissues and are highly correlated with poor clinical outcomes and cancer progression. This review summarizes and describes the role of Tn, T antigens, their sialylated forms as well as fucosylated Lewis epitopes in different aspects of tumor development, progression, and metastasis. Finally, applications of MUC1 glycan epitopes as potential targets for therapeutic strategy of cancers are notified. One of the novelties of this review is presentation of TACAs as inherently connected with MUC1 mucin.

Transcriptome and single-cell transcriptomics reveal prognostic value and potential mechanism of anoikis in skin cutaneous melanoma

BACKGROUND

Skin cutaneous melanoma (SKCM) is a highly lethal cancer, ranking among the top four deadliest cancers. This underscores the urgent need for novel biomarkers for SKCM diagnosis and prognosis. Anoikis plays a vital role in cancer growth and metastasis, and this study aims to investigate its prognostic value and mechanism of action in SKCM.

METHODS

Utilizing consensus clustering, the SKCM samples were categorized into two distinct clusters A and B based on anoikis-related genes (ANRGs), with the B group exhibiting lower disease-specific survival (DSS). Gene set enrichment between distinct clusters was examined using Gene Set Variation Analysis (GSVA) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis.

RESULTS

We created a predictive model based on three anoikis-related differently expressed genes (DEGs), specifically, FASLG, IGF1, and PIK3R2. Moreover, the mechanism of these prognostic genes within the model was investigated at the cellular level using the single-cell sequencing dataset GSE115978. This analysis revealed that the FASLG gene was highly expressed on cluster 1 of Exhausted CD8( +) T (Tex) cells.

CONCLUSIONS

In conclusion, we have established a novel classification system for SKCM based on anoikis, which carries substantial clinical implications for SKCM patients. Notably, the elevated expression of the FASLG gene on cluster 1 of Tex cells could significantly impact SKCM prognosis through anoikis, thus offering a promising target for the development of immunotherapy for SKCM.

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.

Molecular crosstalk between MUC1 and STAT3 influences the anti-proliferative effect of Napabucasin in epithelial cancers

MUC1 is a transmembrane glycoprotein that is overexpressed and aberrantly glycosylated in epithelial cancers. The cytoplasmic tail of MUC1 (MUC1 CT) aids in tumorigenesis by upregulating the expression of multiple oncogenes. Signal transducer and activator of transcription 3 (STAT3) plays a crucial role in several cellular processes and is aberrantly activated in many cancers. In this study, we focus on recent evidence suggesting that STAT3 and MUC1 regulate each other's expression in cancer cells in an auto-inductive loop and found that their interaction plays a prominent role in mediating epithelial-to-mesenchymal transition (EMT) and drug resistance. The STAT3 inhibitor Napabucasin was in clinical trials but was discontinued due to futility. We found that higher expression of MUC1 increased the sensitivity of cancer cells to Napabucasin. Therefore, high-MUC1 tumors may have a better outcome to Napabucasin therapy. We report how MUC1 regulates STAT3 activity and provide a new perspective on repurposing the STAT3-inhibitor Napabucasin to improve clinical outcome of epithelial cancer treatment.

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.

MUC1 and MUC16: critical for immune modulation in cancer therapeutics

The Mucin (MUC) family, a range of highly glycosylated macromolecules, is ubiquitously expressed in mammalian epithelial cells. Such molecules are pivotal in establishing protective mucosal barriers, serving as defenses against pathogenic assaults. Intriguingly, the aberrant expression of specific MUC proteins, notably Mucin 1 (MUC1) and Mucin 16 (MUC16), within tumor cells, is intimately associated with oncogenesis, proliferation, and metastasis. This association involves various mechanisms, including cellular proliferation, viability, apoptosis resistance, chemotherapeutic resilience, metabolic shifts, and immune surveillance evasion. Due to their distinctive biological roles and structural features in oncology, MUC proteins have attracted considerable attention as prospective targets and biomarkers in cancer therapy. The current review offers an exhaustive exploration of the roles of MUC1 and MUC16 in the context of cancer biomarkers, elucidating their critical contributions to the mechanisms of cellular signal transduction, regulation of immune responses, and the modulation of the tumor microenvironment. Additionally, the article evaluates the latest advances in therapeutic strategies targeting these mucins, focusing on innovations in immunotherapies and targeted drugs, aiming to enhance customization and accuracy in cancer treatments.

MUC1 Drives the Progression and Chemoresistance of Clear Cell Renal Carcinomas

While the transmembrane glycoprotein mucin 1 (MUC1) is clustered at the apical borders of normal epithelial cells, with transformation and loss of polarity, MUC1 is found at high levels in the cytosol and is uniformly distributed over the entire surface of carcinoma cells, where it can promote tumor progression and adversely affects the response to therapy. Clear cell renal cell carcinoma (ccRCC), the main histotype of kidney cancer, is typically highly resistant to conventional and targeted therapies for reasons that remain largely unknown. In this context, we investigated whether MUC1 also plays a pivotal role in the cellular and molecular events driving ccRCC progression and chemoresistance. We showed, using loss- and gain-of-function approaches in ccRCC-derived cell lines, that MUC1 not only influences tumor progression but also induces a multi-drug-resistant profile reminiscent of the activation of ABC drug efflux transporters. Overall, our results suggest that targeting MUC1 may represent a novel therapeutic approach to limit ccRCC progression and improve drug sensitivity.

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 research status and prospects of MUC1 in immunology

In immune processes, molecular - molecular interactions are complex. As MUC1 often appears to be an important molecule in inflammation and tumor immunity, it is necessary to summarize the leading countries, authors, journals, and the cooperation among these entities and, most importantly, to determine the main research directions related to MUC1 in this field and the associated research frontiers. A total of 3,397 related studies published from 2012-2021 were retrieved from the Web of Science core database. The search strategy is TS= (MUC1 OR Mucin-1) refined by WEB OF SCIENCE CATEGORY (IMMUNOLOGY) AND [excluding] PUBLICATION YEARS: (2022) AND DOCUMENT TYPES: (ARTICLE OR REVIEW) AND LANGUAGES: (ENGLISH) AND WEB OF SCIENCE INDEX: (Web of Science Core Collection. SCI), with a timespan of 2012 to 2021. Documented bibliometric visual analysis was performed by CiteSpace and VOSviewer. The number of studies has increased every year. There are 1,982 articles and 1,415 reviews from 89 countries and regions, 3,722 organizations, 1,042 journals, and 17,948 authors. The United States, China, and Germany are the major countries producing publications on this issue. The most published author is Finn OJ and the most influential author is June CH. The key words "chimeric antigen receptor" and "T-cell" highlight the current hot spots and future trends in this field. Research on MUC1 in the field of immunology is still evolving. Through the bibliometric analysis of the existing publications, the current research hotspots and future development trends in this field can be obtained.

Development and validation of a novel anoikis-related gene signature in clear cell renal cell carcinoma

Background

Despite numerous treatments available, clear cell renal cell carcinoma (ccRCC) remains a deadly and invasive cancer. Anoikis-related genes (ARGs) are essential regulators of tumor metastasis and development. However, the potential roles of ARGs in ccRCC remain unclear.

Methods

Based on the TCGA-KIRC cohort and GeneCards database, we identified differentially expressed ARGs in ccRCC. Then a 4 ARGs risk model was created by Cox regression and LASSO. The Kaplan-Meier and receiver operating characteristic (ROC) curves were utilized to verify the predictive efficacy of the prognostic signature. Subsequently, the possible molecular mechanism of ARGs was investigated by functional enrichment analysis. To assess the immune infiltration, immune checkpoint genes, and immune function in various risk groups, single sample gene set enrichment (ssGSEA) algorithm was employed. Furthermore, the low-risk and high-risk groups were compared in terms of tumor mutation burden (TMB). Ultimately, we analyzed the protein expression of these four ARGs utilizing the western blot test.

Results

Four genes were utilized to create a risk signature that may predict prognosis, enabling the classification of KIRC patients into groups with low or high risk. The reliability of the signature was examined utilizing survival analysis and ROC analysis. According to the multivariate Cox regression result, the risk score was a reliable independent prognostic predictor for KIRC patients. The novel risk model could differentiate between KIRC patients with various clinical outcomes and represent KIRC's specific immune status. An analysis of the correlation of TMB and risk score indicated a positive correlation between them, with high TMB being potentially linked to worse outcomes.

Conclusion

Based on our findings, the prognostic signature of ARGs may be employed as an independent prognostic factor for ccRCC patients. It may introduce alternative perspectives on prognosis evaluation and serve as a prominent reference for personalized and precise therapy in KIRC.

Predicting Disease-Associated N7-Methylguanosine (m7G) Sites via Random Walk on Heterogeneous Network

Recent studies revealed that the modification of N7-methylguanosine (m7G) has associations with many human diseases. Effectively identifying disease-associated m7G methylation sites would provide crucial clues for disease diagnosis and treatment. Previous studies have developed computational methods to predict disease-associated m7G sites based on similarities among m7G sites and diseases. However, few have focused on the influence of the known m7G-disease association information on calculating similarity measures of m7G site and disease, which potentially promotes the identification of the disease-associated m7G sites. In this work, we propose а computational method called m7GDP-RW to predict m7G-disease associations by random walk algorithm. m7GDP-RW first incorporates the feature information of m7G site and disease with the known m7G-disease associations to compute m7G site similarity and disease similarity. Then m7GDP-RW combines the known m7G-disease associations with the computed similarity of m7G site and disease to construct a m7G-disease heterogeneous network. Finally, m7GDP-RW utilizes a two-pass random walk with restart algorithm to find novel m7G-disease associations on the heterogeneous network. The experimental results show that our method achieves higher prediction accuracy compared to the existing methods. The study case also demonstrates the effectiveness of m7GDP-RW in discovering potential m7G-disease associations.

Aptamer-functionalized quantum dots as theranostic nanotools against cancer and bacterial infections: A comprehensive overview of recent trends

Aptamers (Apts) are synthetic nucleic acid ligands that can be engineered to target various molecules, including amino acids, proteins, and pharmaceuticals. Through a series of adsorption, recovery, and amplification steps, Apts are extracted from combinatorial libraries of synthesized nucleic acids. Using aptasensors in bioanalysis and biomedicine can be improved by combining them with nanomaterials. Moreover, Apt-associated nanomaterials, including liposomes, polymeric, dendrimers, carbon nanomaterials, silica, nanorods, magnetic NPs, and quantum dots (QDs), have been widely used as promising nanotools in biomedicine. Following surface modifications and conjugation with appropriate functional groups, these nanomaterials can be successfully used in aptasensing. Advanced biological assays can use Apts immobilized on QD surfaces through physical interaction and chemical bonding. Accordingly, modern QD aptasensing platforms rely on interactions between QDs, Apts, and targets to detect them. QD-Apt conjugates can be used to directly detect prostate, ovarian, colorectal, and lung cancers or simultaneously detect biomarkers associated with these malignancies. Tenascin-C, mucin 1, prostate-specific antigen, prostate-specific membrane antigen, nucleolin, growth factors, and exosomes are among the cancer biomarkers that can be sensitively detected using such bioconjugates. Furthermore, Apt-conjugated QDs have shown great potential for controlling bacterial infections such as Bacillus thuringiensis, Pseudomonas aeruginosa, Escherichia coli, Acinetobacter baumannii, Campylobacter jejuni, Staphylococcus aureus, and Salmonella typhimurium. This comprehensive review discusses recent advancements in the design of QD-Apt bioconjugates and their applications in cancer and bacterial theranostics.

Tiliroside Combined with Anti-MUC1 Monoclonal Antibody as Promising Anti-Cancer Strategy in AGS Cancer Cells

Specific changes in mucin-type O-glycosylation are common for many cancers, including gastric ones. The most typical alterations include incomplete synthesis of glycan structures, enhanced expression of truncated O-glycans (Tn, T antigens and their sialylated forms), and overexpression of fucosylation. Such altered glycans influence many cellular activities promoting cancer development. Tiliroside is a glycosidic dietary flavonoid with pharmacological properties, including anti-cancer. In this study, we aim to assess the effect of the combined action of anti-MUC1 and tiliroside on some cancer-related factors in AGS gastric cancer cells. Cancer cells were treated with 40, 80, and 160 µM tiliroside, 5 µg/mL anti-MUC1, and flavonoid together with mAb. Real-Time PCR, ELISA, and Western blotting were applied to examine MUC1 expression, specific, tumor-associated antigens, enzymes taking part in their formation, Gal-3, Akt, and NF-κB. MUC1 expression was significantly reduced by mAb action. The combined action of anti-MUC1 and tiliroside was more effective in comparison with monotherapy in the case of C1GalT1, ST3GalT1, FUT4, Gal-3, NF-κB, Akt mRNAs, and Tn antigen, as well as sialyl T antigen expression. The results of our study indicate that applied combined therapy may be a promising anti-gastric cancer strategy.

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.

Synergistic apoptosis by combination of metformin and an O-GlcNAcylation inhibitor in colon cancer cells

BACKGROUND

Although autophagy is an important mediator of metformin antitumor activity, the role of metformin in the crosstalk between autophagy and apoptosis remains unclear. The aim was to confirm the anticancer effect by inducing apoptosis by co-treatment with metformin and OSMI-1, an inhibitor of O-GlcNAcylation, in colon cancer cells.

METHODS

Cell viability was measured by MTT in colon cancer cell lines HCT116 and SW620 cells. Co-treatment with metformin and OSMI-1 induced autophagy and apoptosis, which was analyzed using western blot, reverse transcription-polymerase chain reaction (RT-PCR) analysis, and fluorescence-activated cell sorting (FACS). Combined treatment with metformin and OSMI-1 synergistically inhibit the growth of HCT116 was confirmed by xenograft tumors.

RESULTS

We showed that metformin inhibited mammalian target of rapamycin (mTOR) activity by inducing high levels of C/EBP homologous protein (CHOP) expression through endoplasmic reticulum (ER) stress and activating adenosine monophosphate-activated protein kinase (AMPK) to induce autophagy in HCT116 cells. Interestingly, metformin increased O-GlcNAcylation and glutamine:fructose-6-phosphate amidotransferase (GFAT) levels in HCT116 cells. Thus, metformin also blocks autophagy by enhancing O-GlcNAcylation, whereas OSMI-1 increases autophagy via ER stress. In contrast, combined metformin and OSMI-1 treatment resulted in continuous induction of autophagy and disruption of O-GlcNAcylation homeostasis, resulting in excessive autophagic flux, which synergistically induced apoptosis. Downregulation of Bcl2 promoted apoptosis via the activation of c-Jun N-terminal kinase (JNK) and CHOP overexpression, synergistically inducing apoptosis. The activation of IRE1α/JNK signaling by OSMI-1 and PERK/CHOP signaling by metformin combined to inhibit Bcl2 activity, ultimately leading to the upregulation of cytochrome c release and activation of caspase-3.

CONCLUSIONS

In conclusion, combinatorial treatment of HCT116 cells with metformin and OSMI-1 resulted in more synergistic apoptosis being induced by enhancement of signal activation through ER stress-induced signaling rather than the cell protective autophagy function. These results in HCT116 cells were also confirmed in xenograft models, suggesting that this combination strategy could be utilized for colon cancer treatment.

Understanding and targeting anoikis in metastasis for cancer therapies

The development of effective treatments for cancers requires investigations for a more detailed and comprehensive understanding of the basic cellular mechanisms involved in carcinogenesis, cancer progression, and metastasis. One of those driving mechanisms is anoikis, a special type of apoptosis, which is induced by losing anchorage from the extracellular matrix (ECM). In other words, resisting death in detached cells (cells without ECM) forms an anoikis-resistant phenotype. Since the anoikis-resistance state compensates for the initial steps of cancer metastasis, this review aimed to discuss mechanisms of gaining anoikis/anoikis resistance phenotype in tumor cells. Finally, we highlighted the significance of anoikis in malignancies so as to provide clear insight into cancer diagnosis and therapy development.

MUC1 promotes lung metastases of liver cancer by impairing anti-tumor immunity

PURPOSE

MUC1 is a membrane bound protein that can regulate tumor progression but its role in tumor metastasis and the metastatic microenvironment remains unclear.

METHODS

We performed differential gene analysis for primary liver cancer (n = 31) and lung metastases (n = 31) using the Gene Expression Omnibus (GEO) dataset (GSE141016) and obtained RNA sequencing data from 374 liver cancer and 50 normal tissues from The Cancer Genome Atlas (TCGA). We analyzed the prognostic value of MUC1 and the relationship between MUC1 and the TME using online databases and a clinical cohort. Immunohistochemistry detected MUC1 in normal liver, liver cancer, and lung metastases. Multiplex immunohistochemistry staining detected immune cells in the metastatic microenvironment.

RESULTS

High MUC1 expression levels in hepatocellular carcinoma are associated with worse clinical prognosis and higher rates of lung metastasis. In addition, we observed a correlation between MUC1 and multiple immune cells in the metastatic microenvironment. In paired primary liver cancer and lung metastatic tumor tissues from the same patient, we observed higher MUC1 protein levels in lung metastases than in primary liver cancer. Furthermore, MUC1 was negatively correlated with CD8+T and Treg cells in the metastatic tumor microenvironment and positively correlated with DC. In addition, we found that MUC1 was associated with CD8+T cell activation and function using flow cytometry in another cohort of patients with liver cancer.

CONCLUSION

These data confirm the potential of MUC1 as a prognostic marker and therapeutic target.