Understanding the cell survival mechanism of anoikis-resistant cancer cells during different steps of metastasis

Development of a biomarker signature associated with anoikis to predict prognosis and immunotherapy response in melanoma

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

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

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

A novel anoikis-related gene signature can predict the prognosis of hepatocarcinoma patients

Background

Hepatocellular carcinoma (HCC) is a major health problem with more than 850,000 cases per year worldwide. This cancer is now the third leading cause of cancer-related deaths worldwide, and the number is rising. Cancer cells develop anoikis resistance which is a vital step during cancer progression and metastatic colonization. However, there is not much research that specifically addresses the role of anoikis in HCC, especially in terms of prognosis.

Methods

This study obtained gene expression data and clinical information from 371 HCC patients through The Cancer Genome Atlas (TCGA) Program and The Gene Expression Omnibus (GEO) databases. A total of 516 anoikis-related genes (ANRGs) were retrieved from GeneCard database and Harmonizome portal. Differential expression analysis identified 219 differentially expressed genes (DEGs), and univariate Cox regression analysis was utilized to select 99 ANRGs associated with the prognosis of HCC patients. A risk scoring model with seven genes was established using the least absolute shrinkage and selection operator (LASSO) regression model, and internal validation of the model was performed.

Results

The identified 99 ANRGs are closely associated with the prognosis of HCC patients. The risk scoring model based on seven characteristic genes demonstrates excellent predictive performance, further validated by receiver operating characteristic (ROC) curves and Kaplan-Meier survival curves. The study reveals significant differences in immune cell infiltration, gene expression, and survival status among different risk groups.

Conclusions

The prognosis of HCC patients can be predicted using a unique prognostic model built on ANRGs in HCC.

CFLAR: A novel diagnostic and prognostic biomarker in soft tissue sarcoma, which positively modulates the immune response in the tumor microenvironment

Anoikis is highly associated with tumor cell apoptosis and tumor prognosis; however, the specific role of anoikis-related genes (ARGs) in soft tissue sarcoma (STS) remains to be fully elucidated. The present study aimed to use a variety of bioinformatics methods to determine differentially expressed anoikis-related genes in STS and healthy tissues. Subsequently, three machine learning algorithms, Least Absolute Shrinkage and Selection Operator, Support Vector Machine and Random Forest, were used to screen genes with the highest importance score. The results of the bioinformatics analyses demonstrated that CASP8 and FADD-like apoptosis regulator (CFLAR) exhibited the highest importance score. Subsequently, the diagnostic and prognostic value of CFLAR in STS development was determined using multiple public and in-house cohorts. The results of the present study demonstrated that CFLAR may be considered a diagnostic and prognostic marker of STS, which acts as an independent prognostic factor of STS development. The present study also aimed to explore the potential role of CFLAR in the STS tumor microenvironment, and the results demonstrated that CFLAR significantly enhanced the immune response of STS, and exerted a positive effect on the infiltration of CD8+ T cells and M1 macrophages in the STS immune microenvironment. Notably, the aforementioned results were verified using multiplex immunofluorescence analysis. Collectively, the results of the present study demonstrated that CFLAR may act as a novel diagnostic and prognostic marker for STS, and may positively regulate the immune response of STS. Thus, the present study provided a novel theoretical basis for the use of CFLAR in STS diagnosis, in predicting clinical outcomes and in tailoring individualized treatment options.

Survival mechanisms of circulating tumor cells and their implications for cancer treatment

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

Metastatic outgrowth via the two-way interplay of autophagy and metabolism

Metastasis represents one of the most dangerous issue of cancer progression, characterized by intricate interactions between invading tumor cells, various proteins, and other cells on the way towards target sites. Tumor cells, while undergoing metastasis, engage in dynamic dialogues with stromal cells and undertake epithelial-mesenchymal transition (EMT) phenoconversion. To ensure survival, tumor cells employ several strategies such as restructuring their metabolic needs to adapt to the alterations of the microenvironmental resources via different mechanisms including macroautophagy (autophagy) and to circumvent anoikis-a form of cell death induced upon detachment from the extracellular matrix (ECM). This review focuses on the puzzling connections of autophagy and energetic metabolism within the context of cancer metastasis.

Unveiling the mechanisms and challenges of cancer drug resistance

Cancer treatment faces many hurdles and resistance is one among them. Anti-cancer treatment strategies are evolving due to innate and acquired resistance capacity, governed by genetic, epigenetic, proteomic, metabolic, or microenvironmental cues that ultimately enable selected cancer cells to survive and progress under unfavorable conditions. Although the mechanism of drug resistance is being widely studied to generate new target-based drugs with better potency than existing ones. However, due to the broader flexibility in acquired drug resistance, advanced therapeutic options with better efficacy need to be explored. Combination therapy is an alternative with a better success rate though the risk of amplified side effects is commonplace. Moreover, recent groundbreaking precision immune therapy is one of the ways to overcome drug resistance and has revolutionized anticancer therapy to a greater extent with the only limitation of being individual-specific and needs further attention. This review will focus on the challenges and strategies opted by cancer cells to withstand the current therapies at the molecular level and also highlights the emerging therapeutic options -like immunological, and stem cell-based options that may prove to have better potential to challenge the existing problem of therapy resistance. Video Abstract.

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

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

Prognostic significance and expression pattern of glucose related genes in breast cancer: A comprehensive computational biology approach

Breast cancer (BC) is the most common type of malignancy globally and the main reason why women die from tumours. The Warburg effect, a characteristic of tumor, describes how most solid tumour cells acclimatize to their diverse surroundings by relying heavily on aerobic glycolysis for production of energy. In addition to producing key metabolic intermediates that are crucial for the production of macromolecules, which enable cancer cell division, invasiveness, and drug resistance, the transformed energy metabolism also supplies tumor cells with ATP for cellular energy. Here, we evaluated the expression profile, prognostic significance, and clinical relevance of glucose-related genes in BC using a bioinformatic approach. To clarify the significance of glucose-related genes in the development of breast tumours, we also performed a functional enrichment investigation of deregulated genes using the STRING and KEGG portal. The study depicted that of the 61 genes examined, 8 genes had a fold change Collapse

Key Words

• Bioinformatics
• Breast cancer
• Deregulation
• Glucose metabolism
• Prognosis
• Survival analysis
• Warburg effect

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MESH Headings Collapse

Grants Collapse

Affiliation(s)

Bader Alshehri Department of Medical Laboratory Sciences, College of Applied Medical Sciences, Majmaah University, Almajmaah 11952, Saudi Arabia

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Activating Transcription Factor 5 Promotes Neuroblastoma Metastasis by Inducing Anoikis Resistance

MYCN-amplified neuroblastoma often presents as a highly aggressive metastatic disease with a poor prognosis. Activating transcription factor 5 (ATF5) is implicated in neural cell differentiation and cancer cell survival. Here, we show that ATF5 is highly expressed in patients with stage 4 high-risk neuroblastoma, with increased expression correlating with a poorer prognosis. We demonstrated that ATF5 promotes the metastasis of neuroblastoma cell lines in vivo. Functionally, ATF5 depletion significantly reduced xenograft tumor growth and metastasis of neuroblastoma cells to the bone marrow and liver. Mechanistically, ATF5 endows tumor cells with resistance to anoikis, thereby increasing their survival in systemic circulation and facilitating metastasis. We identified the proapoptotic BCL-2 modifying factor (BMF) as a critical player in ATF5-regulated neuroblastoma anoikis. ATF5 suppresses BMF under suspension conditions at the transcriptional level, promoting anoikis resistance, whereas BMF knockdown significantly prevents ATF5 depletion-induced anoikis. Therapeutically, we showed that a cell-penetrating dominant-negative ATF5 peptide, CP-d/n-ATF5, inhibits neuroblastoma metastasis to the bone marrow and liver by inducing anoikis sensitivity in circulating tumor cells. Our study identified ATF5 as a metastasis promoter and CP-d/n-ATF5 as a potential antimetastatic therapeutic agent for neuroblastoma.

SIGNIFICANCE

This study shows that resistance to anoikis in neuroblastoma is mediated by ATF5 and offers a rationale for targeting ATF5 to treat metastatic neuroblastoma.

Development of adaptive anoikis resistance promotes metastasis that can be overcome by CDK8/19 Mediator kinase inhibition

Anoikis resistance or evasion of cell death triggered by cell detachment into suspension is a hallmark of cancer that is concurrent with cell survival and metastasis. The effects of frequent matrix detachment encounters on the development of anoikis resistance in cancer remains poorly defined. Here we show using a panel of ovarian cancer models, that repeated exposure to suspension stress in vitro followed by attached recovery growth leads to the development of anoikis resistance paralleling in vivo development of anoikis resistance in ovarian cancer ascites. This resistance is concurrent with enhanced invasion, chemoresistance and the ability of anoikis adapted cells to metastasize to distant sites. Adapted anoikis resistant cells show a heightened dependency on oxidative phosphorylation and can also evade immune surveillance. We find that such acquired anoikis resistance is not genetic, as acquired resistance persists for a finite duration in the absence of suspension stress. Transcriptional reprogramming is however essential to this process, as acquisition of adaptive anoikis resistance in vitro and in vivo is exquisitely sensitive to inhibition of CDK8/19 Mediator kinase, a pleiotropic regulator of transcriptional reprogramming. Our data demonstrate that growth after recovery from repeated exposure to suspension stress is a direct contributor to metastasis and that inhibition of CDK8/19 Mediator kinase during such adaptation provides a therapeutic opportunity to prevent both local and distant metastasis in cancer.

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.

Fluid and Bubble Flow Detach Adherent Cancer Cells to Form Spheroids on a Random Positioning Machine

In preparing space and microgravity experiments, the utilization of ground-based facilities is common for initial experiments and feasibility studies. One approach to simulating microgravity conditions on Earth is to employ a random positioning machine (RPM) as a rotary bioreactor. Combined with a suitable low-mass model system, such as cell cultures, these devices simulating microgravity have been shown to produce results similar to those obtained in a space experiment under real microgravity conditions. One of these effects observed under real and simulated microgravity is the formation of spheroids from 2D adherent cancer cell cultures. Since real microgravity cannot be generated in a laboratory on Earth, we aimed to determine which forces lead to the detachment of individual FTC-133 thyroid cancer cells and the formation of tumor spheroids during culture with exposure to random positioning modes. To this end, we subdivided the RPM motion into different static and dynamic orientations of cell culture flasks. We focused on the molecular activation of the mechanosignaling pathways previously associated with spheroid formation in microgravity. Our results suggest that RPM-induced spheroid formation is a two-step process. First, the cells need to be detached, induced by the cell culture flask's rotation and the subsequent fluid flow, as well as the presence of air bubbles. Once the cells are detached and in suspension, random positioning prevents sedimentation, allowing 3D aggregates to form. In a comparative shear stress experiment using defined fluid flow paradigms, transcriptional responses were triggered comparable to exposure of FTC-133 cells to the RPM. In summary, the RPM serves as a simulator of microgravity by randomizing the impact of Earth's gravity vector especially for suspension (i.e., detached) cells. Simultaneously, it simulates physiological shear forces on the adherent cell layer. The RPM thus offers a unique combination of environmental conditions for in vitro cancer research.

Single-cell and bulk RNA sequencing reveals Anoikis related genes to guide prognosis and immunotherapy in osteosarcoma

Anoikis resistance, a notable factor in osteosarcoma, plays a significant role in tumor invasion and metastasis. This study seeks to identify a distinct gene signature that is specifically associated with the anoikis subcluster in osteosarcoma. Clinical, single-cell, and transcriptional data from TARGET and GEO datasets were used to develop a gene signature for osteosarcoma based on the anoikis subcluster. Univariate Cox and LASSO regression analyses were employed. The signature's predictive value was evaluated using time-dependent ROC and Kaplan-Meier analyses. Functional enrichment analyses and drug sensitivity analyses were conducted. Validation of three modular genes was performed using RT-qPCR and Western blotting. Signature (ZNF583, CGNL1, CXCL13) was developed to predict overall survival in osteosarcoma patients, targeting the anoikis subcluster. The signature demonstrated good performance in external validation. Stratification based on the signature revealed significantly different prognoses. The signature was an independent prognostic factor. The low-risk group showed enhanced immune cell infiltration and improved immune function. Drug sensitivity analysis indicated efficacy of chemotherapy agents. Prognostic nomograms incorporating the signature provided greater predictive accuracy and clinical utility. Signatures related to the anoikis subcluster play a significant role in osteosarcoma progression. Incorporating these findings into clinical decision-making can improve osteosarcoma treatment and patient outcomes.

Construction of an anoikis-associated lncRNA-miRNA-mRNA network reveals the prognostic role of β-elemene in non-small cell lung cancer

β-Elemene is the main active ingredient in Curcumae Rhizoma that exerts antitumour effects. Anoikis affects tumour development through various biological pathways in non-small cell lung cancer (NSCLC), but the regulation between β-elemene and anoikis remains to be explored. First, we explored the molecular expression patterns of anoikis-associated genes (AAGs) using consensus clustering and characterized the impact of AAGs on patient prognosis, clinical characteristics, and genomic instability. In addition, we revealed that AAG regulatory genes have rich interactions with β-elemene targets, and established a lncRNA-miRNA-mRNA network to explain the effect of β-elemene on anoikis. Finally, to reveal the prognostic effect of their correlation, the prognostic scoring model and clinical nomogram of β-elemene and anoikis were successfully established by least absolute shrinkage and selection operator (LASSO) and random forest algorithms. This prognostic scoring model containing noncoding RNA (ncRNA) can indicate the immunotherapy and mutational landscape, providing a novel theoretical basis and direction for the study of the antitumour mechanism of β-elemene in NSCLC patients.

Identification of a Novel Oxidative Stress- and Anoikis-Related Prognostic Signature and Its Immune Landscape Analysis in Non-Small Cell Lung Cancer

The objective of this study was to identify a kind of prognostic signature based on oxidative stress- and anoikis-related genes (OARGs) for predicting the prognosis and immune landscape of NSCLC. Initially, We identified 47 differentially expressed OARGs that primarily regulate oxidative stress and epithelial cell infiltration through the PI3K-Akt pathway. Subsequently, 10 OARGs related to prognosis determined two potential clusters. A cluster was associated with a shorter survival level, lower immune infiltration, higher stemness index and tumor mutation burden. Next, The best risk score model constructed by prognostic OARGs was the Random Survival Forest model, and it included SLC2A1, LDHA and PLAU. The high-risk group was associated with cluster A and poor prognosis, with a higher tumor mutation burden, stemness index and proportion of M0-type macrophages, and a lower immune checkpoint expression level, immune function score and IPS score. The calibration curve and decision-making curve showed that the risk score combined with clinical pathological characteristics could be used to construct a nomogram for guiding the clinical treatment strategies. Finally, We found that all three hub genes were highly expressed in tumor tissues, and LDHA expression was mainly regulated by has-miR-338-3p, has-miR-330-5p and has-miR-34c-5p. Altogether, We constructed an OARG-related prognostic signature to reveal potential relationships between the signature and clinical characteristics, TME, stemness, tumor mutational burden, drug sensitivity and immune landscape in NSCLC patients.

Exploring the dynamic interplay between cancer stem cells and the tumor microenvironment: implications for novel therapeutic strategies

Cancer stem cells (CSCs) have emerged as key contributors to tumor initiation, growth, and metastasis. In addition, CSCs play a significant role in inducing immune evasion, thereby compromising the effectiveness of cancer treatments. The reciprocal communication between CSCs and the tumor microenvironment (TME) is observed, with the TME providing a supportive niche for CSC survival and self-renewal, while CSCs, in turn, influence the polarization and persistence of the TME, promoting an immunosuppressive state. Consequently, these interactions hinder the efficacy of current cancer therapies, necessitating the exploration of novel therapeutic approaches to modulate the TME and target CSCs. In this review, we highlight the intricate strategies employed by CSCs to evade immune surveillance and develop resistance to therapies. Furthermore, we examine the dynamic interplay between CSCs and the TME, shedding light on how this interaction impacts cancer progression. Moreover, we provide an overview of advanced therapeutic strategies that specifically target CSCs and the TME, which hold promise for future clinical and translational studies in cancer treatment.

Development of a prognostic model based on anoikis-related genes for predicting clinical prognosis and immunotherapy of hepatocellular carcinoma

Hepatocellular Carcinoma (HCC) is the predominant cause of cancer-related mortality worldwide. The majority of HCC patients are diagnosed at advanced stages of the disease, with a high likelihood of metastasis and unfavorable prognosis. Anoikis resistance is a crucial factor contributing to tumor invasion and metastasis, although its specific role in HCC remains unclear. Based on the results of univariate Cox regression and least absolute shrink-age and selection operator (LASSO) analysis, a subset of anoikis-related genes (ARGs) significantly associated with overall survival (OS) was identified. A multivariate Cox regression analysis subsequently identified PDK4, STK11, and TFDP1 as three prognostic ARGs, which were then used to establish a prognostic risk model. Differences in OS caused by risk stratification in HCC patients were demonstrated. The nomogram analysis indicated that the ARGs prognostic signature served as an independent prognostic predictor. In vitro experiments further confirmed the abnormal expression of selected ARGs in HCC. The association between risk scores and OS was further examined through Kaplan-Meier analysis, CIBERSORT analysis, and single-sample gene set enrichment analysis (ssGSEA). This study is a pioneering effort to integrate multiple ARGs and establish a risk-predictive model, providing a unique perspective for the development of personalized and precise therapeutic strategies for HCC.

Cancer metastasis: Molecular mechanisms and clinical perspectives

Metastatic progression combined with non-responsiveness towards systemic therapy often shapes the course of disease for cancer patients and commonly determines its lethal outcome. The complex molecular events that promote metastasis are a combination of both, the acquired pro-metastatic properties of cancer cells and a metastasis-permissive or -supportive tumor micro-environment (TME). Yet, dissemination is a challenging process for cancer cells that requires a series of events to enable cancer cell survival and growth. Metastatic cancer cells have to initially detach themselves from primary tumors, overcome the challenges of their intravasal journey and colonize distant sites that are suited for their metastases. The implicated obstacles including anoikis and immune surveillance, can be overcome by intricate intra- and extracellular signaling pathways, which we will summarize and discuss in this review. Further, emerging modulators of metastasis, like the immune-microenvironment, microbiome, sublethal cell death engagement, or the nervous system will be integrated into the existing working model of metastasis.

Anoikis-associated signatures predict prognosis and immune response in bladder cancer

Objective: Anoikis is a type of programmed cell death that occurs in normal epithelial and endothelial cells. However, the specific role of anoikis regulators (ANRs) in bladder cancer (BLCA) remains unknown. Therefore, the objective of this study was to find subgroups that could identify different levels of anoikis resistance in BLCA and construct an anoikis scoring system to assess prognosis. Method: By obtaining ANRs from public datasets, subgroups of BLCA with varying degrees of anoikis resistance were identified, and risk was determined. Result: ANRs affects the occurrence and prognosis of BLCA and can be predicted by establishing risk models. Conclusion: The anoikis scoring system and anoikis-associated risk profiles may help develop more effective and personalized treatment strategies for BLCA patients.

A novel anoikis-related risk model predicts prognosis in patients with colorectal cancer and responses to different immunotherapy strategies

PURPOSE

We aimed to study the role of anoikis-related genes (ARGs) in colorectal cancer (CRC) using bioinformatics.

METHODS

GSE39582 and GSE39084, which collectively contain 363 CRC samples, were downloaded from the NCBI Gene Expression Omnibus (GEO) database as a test set. TCGA-COADREAD, with 376 CRC samples, was downloaded from the UCSC database as a validation set. Univariate Cox regression analysis was used to screen for ARGs that were significantly associated with prognosis. The top 10 ARGs were used to classify the samples into different subtypes based on unsupervised cluster analysis. The immune environments of the different subtypes were analyzed. ARGs that were significantly associated with CRC prognosis were used to construct a risk model. Univariate and multivariate Cox regression analyses were used to screen independent prognostic factors and construct a nomogram.

RESULTS

Four anoikis-related subtypes (ARSs) with differential prognoses and immune microenvironments were identified. KRAS and epithelial-mesenchymal transition pathways were enriched in subtype B, which had the worst prognosis. Three ARGs (DLG1, AKT3, and LPAR1) were used to construct the risk model. Both the test and validation sets showed worse outcomes for patients in the high-risk group than those in the low-risk group. Risk score was found to be an independent prognostic factor for CRC. Moreover, there was a difference in drug sensitivity between the high- and low-risk groups.

CONCLUSION

The identified ARGs and risk scores were associated with CRC prognosis and could predict the responses of patients with CRC to immunotherapy strategies.

Targeting redox regulation and autophagy systems in cancer stem cells

Cancer is a dysregulated cellular level pathological condition that results in tumor formation followed by metastasis. In the heterogeneous tumor architecture, cancer stem cells (CSCs) are essential to push forward the progression of tumors due to their strong pro-tumor properties such as stemness, self-renewal, plasticity, metastasis, and being poorly responsive to radiotherapy and chemotherapeutic agents. Cancer stem cells have the ability to withstand various stress pressures by modulating transcriptional and translational mechanisms, and adaptable metabolic changes. Owing to CSCs heterogeneity and plasticity, these cells display varied metabolic and redox profiles across different types of cancers. It has been established that there is a disparity in the levels of Reactive Oxygen Species (ROS) generated in CSCs vs Non-CSC and these differential levels are detected across different tumors. CSCs have unique metabolic demands and are known to change plasticity during metastasis by passing through the interchangeable epithelial and mesenchymal-like phenotypes. During the metastatic process, tumor cells undergo epithelial to mesenchymal transition (EMT) thus attaining invasive properties while leaving the primary tumor site, similarly during the course of circulation and extravasation at a distant organ, these cells regain their epithelial characteristics through Mesenchymal to Epithelial Transition (MET) to initiate micrometastasis. It has been evidenced that levels of Reactive Oxygen Species (ROS) and associated metabolic activities vary between the epithelial and mesenchymal states of CSCs. Similarly, the levels of oxidative and metabolic states were observed to get altered in CSCs post-drug treatments. As oxidative and metabolic changes guide the onset of autophagy in cells, its role in self-renewal, quiescence, proliferation and response to drug treatment is well established. This review will highlight the molecular mechanisms useful for expanding therapeutic strategies based on modulating redox regulation and autophagy activation to targets. Specifically, we will account for the mounting data that focus on the role of ROS generated by different metabolic pathways and autophagy regulation in eradicating stem-like cells hereafter referred to as cancer stem cells (CSCs).

The Multikinase Inhibitor AD80 Induces Mitotic Catastrophe and Autophagy in Pancreatic Cancer Cells

Significant advances in understanding the molecular complexity of the development and progression of pancreatic cancer have been made, but this disease is still considered one of the most lethal human cancers and needs new therapeutic options. In the present study, the antineoplastic effects of AD80, a multikinase inhibitor, were investigated in models of pancreatic cancer. AD80 reduced cell viability and clonogenicity and induced polyploidy in pancreatic cancer cells. At the molecular level, AD80 reduced RPS6 and histone H3 phosphorylation and induced γH2AX and PARP1 cleavage. Additionally, the drug markedly decreased AURKA phosphorylation and expression. In PANC-1 cells, AD80 strongly induced autophagic flux (consumption of LC3B and SQSTM1/p62). AD80 modulated 32 out of 84 autophagy-related genes and was associated with vacuole organization, macroautophagy, response to starvation, cellular response to nitrogen levels, and cellular response to extracellular stimulus. In 3D pancreatic cancer models, AD80 also effectively reduced growth independent of anchorage and cell viability. In summary, AD80 induces mitotic aberrations, DNA damage, autophagy, and apoptosis in pancreatic cancer cells. Our exploratory study establishes novel targets underlying the antineoplastic activity of the drug and provides insights into the development of therapeutic strategies for this disease.

Cancer Bioenergetics and Tumor Microenvironments-Enhancing Chemotherapeutics and Targeting Resistant Niches through Nanosystems

Cancer is an impending bottleneck in the advanced scientific workflow to achieve diagnostic, prognostic, and therapeutic success. Most cancers are refractory to conventional diagnostic and chemotherapeutics due to their limited targetability, specificity, solubility, and side effects. The inherent ability of each cancer to evolve through various genetic and epigenetic transformations and metabolic reprogramming underlies therapeutic limitations. Though tumor microenvironments (TMEs) are quite well understood in some cancers, each microenvironment differs from the other in internal perturbations and metabolic skew thereby impeding the development of appropriate diagnostics, drugs, vaccines, and therapies. Cancer associated bioenergetics modulations regulate TME, angiogenesis, immune evasion, generation of resistant niches and tumor progression, and a thorough understanding is crucial to the development of metabolic therapies. However, this remains a missing element in cancer theranostics, necessitating the development of modalities that can be adapted for targetability, diagnostics and therapeutics. In this challenging scenario, nanomaterials are modular platforms for understanding TME and achieving successful theranostics. Several nanoscale particles have been successfully researched in animal models, quite a few have reached clinical trials, and some have achieved clinical success. Nanoparticles exhibit an intrinsic capability to interact with diverse biomolecules and modulate their functions. Furthermore, nanoparticles can be functionalized with receptors, modulators, and drugs to facilitate specific targeting with reduced toxicity. This review discusses the current understanding of different theranostic nanosystems, their synthesis, functionalization, and targetability for therapeutic modulation of bioenergetics, and metabolic reprogramming of the cancer microenvironment. We highlight the potential of nanosystems for enhanced chemotherapeutic success emphasizing the questions that remain unanswered.

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

Background

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

Methods

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

Results

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

Conclusion

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

COPS3 inhibition promotes cell proliferation blockage and anoikis via regulating PFKFB3 in osteosarcoma cancer cells

As a key component of the COP9 signalosome complex, which participates in a variety of physiological processes, COPS3 is intimately related to multiple cancers. It promotes cell proliferation, progression and metastasis in several cancer cells. However, whether COPS3 participates in regulating anoikis, a specific kind of apoptosis and functions as an essential modulator of cell metastasis, has not yet been studied. Here, we found COPS3 is highly expressed in several cancers especially in osteosarcoma (OS). Overexpression of COPS3 promoted cell proliferation, cell viability and migration/invasion in both control cells and oxaliplatin (Oxa) treated cells. On the contrary, knockdown of COPS3 further enhanced the cytotoxicity of Oxa. Utilizing bioinformatics analysis, we found that COPS3 was higher expressed in the metastatic group, and associated with the extra-cellular matrix (ECM) receptor interaction pathway, which involve in regulating anoikis. In an anoikis model, COPS3 expression varied and genetic modification of COPS3 influenced the cell death enhanced by Oxa. PFKFB3, an essential modulator of glycolysis, was found to interact with COPS3. Inhibition of PFKFB3 promoted apoptosis and anoikis enhanced by Oxa, and COPS3 overexpression failed to rescue this cell death. On the contrary, in the COPS3 knockdown cells, overexpression of PFKFB3 recovered the anoikis resistance, indicating COPS3 function upstream of PFKFB3. In summary, our results elucidated that COPS3 modulated anoikis via affecting PFKFB3 in OS cancer cells.

Small molecule '4ab' induced autophagy and endoplasmic reticulum stress-mediated death of aggressive cancer cells grown under adherent and floating conditions

Metastasis is the leading cause of death in cancer patients and a major challenging aspect of cancer biology. Various adaptive molecular signaling pathways play a crucial role in cancer metastasis and later in the formation of secondary tumors. Aggressive cancer cells like triple negative breast cancer (TNBCs) are more inclined to undergo metastasis hence having a high recurrence rate and potential of micro-metastasis. Tumor cells in circulation known as circulating tumor cells (CTCs) offer an attractive drug target to treat metastatic disease. Cell cycle regulation and stress response of CTCs in blood has a crucial role in their survival and progression and thus may be considered therapeutically active hotspots. The cyclin D/cyclin-dependent kinase (CDK) pathway regulates cell cycle checkpoints, a process that is frequently dysregulated in cancer cells. Selective CDK inhibitors can limit the phosphorylation of cell cycle regulatory proteins by inducing cell cycle phase arrest, and thus may be an effective therapeutic strategy for aggressive cancer cells in their dividing phase at the primary or secondary site. However, during the floating condition, cancer cells halt their multiplication process and proceed through the various steps of metastasis. Current study showed that a novel CDK inhibitor 4ab induced autophagy and endoplasmic reticulum (ER) stress in agressive cancer cells grown under adherent and floating conditions resulting in paraptosis. Further, our results showed that 4ab efficiently induced cell death in aggressive cancer cells through ER stress-mediated activation of JNK signaling. Additionally, was observed that treatment of 4ab in tumor-bearing mice displayed a significant reduction in tumor burden and micro-metastasis. The outcome of these studies showed that 4ab can be a potential anti-tumor and anti-metastatic agent. Graphical representation of 4ab: image representing the effect of 4ab on death-inducing pathways in aggressive cancer cells. 4ab induces ER stress and activates autophagy leading to vacuolation of there by causing apoptosis in aggressive cancer cells.

The genomic regulation of metastatic dormancy

The genomics and pathways governing metastatic dormancy are critically important drivers of long-term patient survival given the considerable portion of cancers that recur aggressively months to years after initial treatments. Our understanding of dormancy has expanded greatly in the last two decades, with studies elucidating that the dormant state is regulated by multiple genes, microenvironmental (ME) interactions, and immune components. These forces are exerted through mechanisms that are intrinsic to the tumor cell, manifested through cross-talk between tumor and ME cells including those from the immune system, and regulated by angiogenic processes in the nascent micrometastatic niche. The development of new in vivo and 3D ME models, as well as enhancements to decades-old tumor cell pedigree models that span the development of metastatic dormancy to aggressive growth, has helped fuel what arguably is one of the least understood areas of cancer biology that nonetheless contributes immensely to patient mortality. The current review focuses on the genes and molecular pathways that regulate dormancy via tumor-intrinsic and ME cells, and how groups have envisioned harnessing these therapeutically to benefit patient survival.

The multi-omics analysis identifies a novel cuproptosis-anoikis-related gene signature in prognosis and immune infiltration characterization of lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) has emerged as one of the most aggressive lethal cancers. Anoikis serves as programmed apoptosis initiated by the detachment of cells from the extracel-lular matrix. Cuproptosis is distinct from traditional cell death modalities. The above two modes are both closely related to tumor progression, prognosis, and treatment. However, whether they have synergistic effects in LUAD deserves further investigation.

Methods

The anoikis-related prognostic genes (ANRGs) co-expressed with cuproptosis-associated genes (CAGs) were screened using correlation analysis, analysis of variance, least absolute shrinkage, and selection operator (LASSO), and COX regression followed by functional analysis, and then LUAD risk score model was constructed. Using consensus clustering, the relationship between different subtypes and clinicopathological features, immune infiltration characteristics, and somatic mutations was analyzed. A nomogram was developed by incorporating clinical information, which provided a prediction of the survival of patients. Finally, a comprehensive analysis of ANRGs was performed and verified by the HPA database.

Results

A total of 27 ANRGs associated with cuproptosis were obtained. On this basis, three distinct ANRGs subtypes were identified, and the differences between clinical prognosis and immune infiltration were observed. A risk score model has been constructed by incorporating seven ANRGs signatures (EIF2AK3, IKZF3, ITGAV, OGT, PLK1, TRAF2, XRCC5). A highly reliable nomogram was developed to help formulate treatment strategies based on risk score and the clinicopathological features of LUAD. The seven-gene signature was turned out to be strongly linked to immune cells and validated in single-cell data. Immunohistochemistry proved that all of them are highly expressed in LUAD tissues.

Conclusion

This study reveals the potential relationship between cuproptosis-related ANRGs and clinicopathological features, tumor microenvironment (TME), and mutation characteristics, which can be applied for predicting the prognosis of LUAD and help develop individualized treatment strategies.

Anoikis patterns exhibit distinct prognostic and immune landscapes in Osteosarcoma

OBJECTIVES

Osteosarcoma is highly aggressive and prone to metastasis, with a poor prognosis. Increasing evidence identified anoikis has a critical effect in tumor metastasis and invasion. However, the prognostic value of anoikis-related genes (ANRGs) in osteosarcoma and their role in the immune landscape of osteosarcoma remain unclear.

METHODS

The RNA sequencing and clinical data of patients with osteosarcoma were extracted from the TARGET and GEO databases, and ANRGs were identified from the GeneCards database. Unsupervised clustering analysis was employed to identify anoikis-related patterns. The ESTIMATE, TIMER and ssGSEA algorithms were used to assess the immune microenvironment of different subtypes. A prognostic signature based on the identified ANRGs was constructed via univariate, LASSO and multivariate Cox regression analyses. KEGG, GO and GSEA were used for functional enrichment of genes associated with different risk subtypes. qPCR, WB and IHC were used to validate the expression of candidate genes.

RESULTS

Two anoikis-related patterns with distinct clinical features and immune statuses were identified based on prognosis-related ANRGs. Cluster 2 had more active immunogenicity and a better prognosis than Cluster 1. Subsequently, we developed and validated an anoikis prognostic signature demonstrating excellent predictive ability for the prognosis of osteosarcoma. Anoikis risk score was positively associated with osteosarcoma metastasis and was identified as an independent prognostic marker. Additionally, a nomogram was established to predict the 3- and 5-year survival probability of patients with osteosarcoma. Functional enrichment analysis revealed that immune dysregulation was correlated with poor prognosis. Besides, patients in the low-risk group had higher infiltration levels of immune cells and more active immune function than patients in the high-risk group. Drug sensitivity analysis revealed several chemotherapeutic agents for the treatment of different subtypes of osteosarcoma.

CONCLUSION

Our study demonstrated the role of ANRGs in osteosarcoma progression, providing insights into clinical decision making in osteosarcoma.

Construction of an original anoikis-related prognostic model closely related to immune infiltration in gastric cancer

Background: Anoikis is considered as a particular type of programmed cell death, the weakness or resistance of which contributes greatly to the development and progression of most malignant solid tumors. However, the latent impact of anoikis-related genes (ARGs) on gastric cancer (GC) is still ambiguous. Based on these, this study established an anoikis-related prognostic model of GC to identify the prognosis of patients and provide more effective treatment in clinical practice. Methods: First, we extracted four public datasets containing the gene expression and clinicopathological information of GC, which were worked as the training and validating sets, separately. Then, an anoikis-related survival-predicted model of GC was developed via Lasso and COX regression analyses and verified by using the Kaplan-Meier (KM) curve and receiver operating characteristic (ROC) curve analyses. Next, we assigned GC patients to two groups characterized by the risk score calculated and analyzed somatic mutation, functional pathways, and immune infiltration between the different two groups. Finally, a unique nomogram was offered to clinicians to forecast the personal survival probability of GC patients. Results: Based on seven anoikis-related markers screened and identified, a carcinogenic model of risk score was produced. Patients placed in the high-score group suffered significantly worse overall survival (OS) in four cohorts. Additionally, the model revealed a high sensitivity and specificity to prognosticate the prognoses of GC patients [area under the ROC curve (AUC) at 5-year = 0.713; GSE84437, AUC at 5-year = 0.639; GSE15459, AUC at 5-year = 0.672; GSE62254, AUC at 5-year = 0.616]. Apart from the excellent predictive performance, the model was also identified as an independent prediction factor from other clinicopathological characteristics. Combining anoikis-related prognostic model with GC clinical features, we built a more comprehensive nomogram to foresee the likelihood of survival of GC patients in a given year, showing a well-accurate prediction performance. Conclusion: In summary, this study created a new anoikis-related signature for GC, which has potentially provided new critical insights into survival prediction and individualized therapy development.

CPT1A promotes anoikis resistance in esophageal squamous cell carcinoma via redox homeostasis

Anoikis resistance was a prominent hallmark of cancer metastasis, and lipo-genic characteristics have been identified as another metabolic alteration during tumorigenesis. However, their crosstalk has not been fully elucidated, especially in advanced esophageal squamous cell carcinoma (ESCC). In this study, we showed, for the first time, that the key enzyme carnitine O-palmitoyl transferase 1 (CPT1A), which is involved in fatty acid oxidation (FAO), was markedly upregulated in ESCC cells upon detached culture via a metabolism PCR array. Overexpression of CPT1A was associated with poor survival of ESCC patients and could protect ESCC cells from apoptosis via maintaining redox homeostasis through supply of GSH and NADPH. Mechanistically, detached culture conditions enhanced the expression of the transcription factor ETV4 and suppressed the expression of the ubiquitin enzyme RNF2, which were responsible for the elevated expression of CPT1A at the mRNA and protein levels, respectively. Moreover, genetic or pharmacologic disruption of CPT1A switched off the NADPH supply and therefore prevented the anchorage-independent growth of ESCC cells in vitro and lung metastases of xenografted tumor models in vivo. Collectively, our results provide novel insights into how ESCC cancer cells exploit metabolic switching to form distant metastases and some evidence for the link between anoikis and FAO.

Redox balance and autophagy regulation in cancer progression and their therapeutic perspective

Cellular ROS production participates in various cellular functions but its accumulation decides the cell fate. Malignant cells have higher levels of ROS and active antioxidant machinery, a characteristic hallmark of cancer with an outcome of activation of stress-induced pathways like autophagy. Autophagy is an intracellular catabolic process that produces alternative raw materials to meet the energy demand of cells and is influenced by the cellular redox state thus playing a definite role in cancer cell fate. Since damaged mitochondria are the main source of ROS in the cell, however, cancer cells remove them by upregulating the process of mitophagy which is known to play a decisive role in tumorigenesis and tumor progression. Chemotherapy exploits cell machinery which results in the accumulation of toxic levels of ROS in cells resulting in cell death by activating either of the pathways like apoptosis, necrosis, ferroptosis or autophagy in them. So understanding these redox and autophagy regulations offers a promising method to design and develop new cancer therapies that can be very effective and durable for years. This review will give a summary of the current therapeutic molecules targeting redox regulation and autophagy for the treatment of cancer. Further, it will highlight various challenges in developing anticancer agents due to autophagy and ROS regulation in the cell and insights into the development of future therapies.