Mechanisms for Modulating Anoikis Resistance in Cancer and the Relevance of Metabolic Reprogramming

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

A Novel Signature Based on Anoikis Associated with BCR-Free Survival for Prostate Cancer

This study aimed to elucidate the role of anoikis in the progression of prostate cancer (PCa) and to develop a prognostic signature based on anoikis-related genes (ARGs). To achieve this, PCa cases were subjected to nonnegative matrix factorization (NMF) analysis, which allowed for the identification of distinct patterns of anoikis modification. Additionally, immune infiltration was evaluated using single-sample gene-set enrichment analysis (ssGSEA). Survival analysis was performed using the Kaplan-Meier method, and a risk score was generated based on the expression levels of ARGs to quantitatively assess the modification of anoikis in PCa. Using the Least Absolute Shrinkage and Selection Operator (LASSO) method, four hub-genes were identified, and patients were classified into different risk groups based on their individual scores. Importantly, the low-risk subtype was characterized by a significantly improved biochemical recurrence-free survival, underscoring the clinical relevance of the ARG-based prognostic signature. To further improve the prognostic accuracy of the signature, patient age, pathological T stage, Gleason score, and prostate-specific antigen level were incorporated into the analysis, yielding a comprehensive prognostic signature. The clinical relevance of this signature was illustrated through a nomogram, providing a visual representation of the prognostic implications of the ARG-based signature. Taken together, these findings highlight the potential of ARGs in predicting the clinical outcomes of PCa patients and provide a novel and clinically relevant prognostic signature based on the modification of anoikis in PCa.

Construction of stomach adenocarcinoma prognostic signature based on anoikis-related lncRNAs and clinical significance

As a dominant type of gastric cancer, stomach adenocarcinoma (STAD) is characterized by high morbidity and mortality rates. Anoikis factors participate in tumor metastasis and invasion. This study was designed to identify prognostic risk factors in anoikis-related long non-coding RNAs (lncRNAs) for STAD. First, with STAD expression datasets and anoikis-related gene sets downloaded from public databases, anoikis-related prognostic lncRNA signatures (AC091057.1, ADAMTS9.AS1, AC090825.1, AC084880.3, EMX2OS, HHIP.AS1, AC016583.2, EDIL3.DT, DIRC1, LINC01614, and AC103702.2) were screened by Cox regression to establish a prognostic risk model. Kaplan-Meier and receiver operating characteristic curves were used to evaluate the survival status of patients and verify predictive accuracy of the model. Besides, risk score could be an independent prognostic factor to assess the prognosis of STAD patients. Nomograms of the prognostic model that combined clinical information and risk score could effectively predict survival of STAD patients, as validated by calibration curve. Gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses were performed for differentially expressed genes (DEGs) in high- and low-risk groups. These DEGs were related to neurotransmitter transmission, signal transmission, and endocytosis. Moreover, we analyzed immune status of different risk groups and found that STAD patients in low-risk group were more sensitive to immunotherapy. A prognostic risk assessment model for STAD using anoikis-related lncRNA genes was constructed here, which was proven to have high predictive accuracy and thus could offer a reference for prognostic evaluation and clinical treatment of STAD patients.

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

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

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

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

The role of hypoxia and radiation in developing a CTCs-like phenotype in murine osteosarcoma cells

Introduction: Cancer treatment has evolved significantly, yet concerns about tumor recurrence and metastasis persist. Within the dynamic tumor microenvironment, a subpopulation of mesenchymal tumor cells, known as Circulating Cancer Stem Cells (CCSCs), express markers like CD133, TrkB, and CD47, making them radioresistant and pivotal to metastasis. Hypoxia intensifies their stemness, complicating their identification in the bloodstream. This study investigates the interplay of acute and chronic hypoxia and radiation exposure in selecting and characterizing cells with a CCSC-like phenotype. Methods: LM8 murine osteosarcoma cells were cultured and subjected to normoxic (21% O2) and hypoxic (1% O2) conditions. We employed Sphere Formation and Migration Assays, Western Blot analysis, CD133 Cell Sorting, and CD133+ Fluorescent Activated Cell Sorting (FACS) analysis with a focus on TrkB antibody to assess the effects of acute and chronic hypoxia, along with radiation exposure. Results: Our findings demonstrate that the combination of radiation and acute hypoxia enhances stemness, while chronic hypoxia imparts a cancer stem-like phenotype in murine osteosarcoma cells, marked by increased migration and upregulation of CCSC markers, particularly TrkB and CD47. These insights offer a comprehensive understanding of the interactions between radiation, hypoxia, and cellular responses in the context of cancer treatment. Discussion: This study elucidates the complex interplay among radiation, hypoxia, and cellular responses, offering valuable insights into the intricacies and potential advancements in cancer treatment.

Iron affects the sphere-forming ability of ovarian cancer cells in non-adherent culture conditions

Introduction: Detachment from the extracellular matrix (ECM) is the first step of the metastatic cascade. It is a regulated process involving interaction between tumor cells and tumor microenvironment (TME). Iron is a key micronutrient within the TME. Here, we explored the role of iron in the ability of ovarian cancer cells to successfully detach from the ECM. Methods: HEY and PEO1 ovarian cancer cells were grown in 3D conditions. To mimic an iron rich TME, culture media were supplemented with 100 μM Fe3+. Cell mortality was evaluated by cytofluorimetric assay. The invasive potential of tumor spheroids was performed in Matrigel and documented with images and time-lapses. Iron metabolism was assessed by analyzing the expression of CD71 and FtH1, and by quantifying the intracellular labile iron pool (LIP) through Calcein-AM cytofluorimetric assay. Ferroptosis was assessed by quantifying mitochondrial reactive oxygen species (ROS) and lipid peroxidation through MitoSOX and BODIPY-C11 cytofluorimetric assays, respectively. Ferroptosis markers GPX4 and VDAC2 were measured by Western blot. FtH1 knockdown was performed by using siRNA. Results: To generate spheroids, HEY and PEO1 cells prevent LIP accumulation by upregulating FtH1. 3D HEY moderately increases FtH1, and LIP is only slightly reduced. 3D PEO1upregulate FtH1 and LIP results significantly diminished. HEY tumor spheroids prevent iron import downregulating CD71, while PEO1 cells strongly enhance it. Intracellular ROS drop down during the 2D to 3D transition in both cell lines, but more significantly in PEO1 cells. Upon iron supplementation, PEO1 cells continue to enhance CD71 and FtH1 without accumulating the LIP and ROS and do not undergo ferroptosis. HEY, instead, accumulate LIP, undergo ferroptosis and attenuate their sphere-forming ability and invasiveness. FtH1 knockdown significantly reduces the generation of PEO1 tumor spheroids, although without sensitizing them to ferroptosis. Discussion: Iron metabolism reprogramming is a key event in the tumor spheroid generation of ovarian cancer cells. An iron-rich environment impairs the sphere-forming ability and causes cell death only in ferroptosis sensitive cells. A better understanding of ferroptosis sensitivity could be useful to develop effective treatments to kill ECM-detached ovarian cancer cells.

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.

Circular RNA ZNF800 (hsa_circ_0082096) regulates cancer stem cell properties and tumor growth in colorectal cancer

BACKGROUND

Cancer stem cells form a rare cell population in tumors that contributes to metastasis, recurrence and chemoresistance in cancer patients. Circular RNAs (circRNAs) are post-transcriptional regulators of gene expression that sponge targeted microRNA (miRNAs) to affect a multitude of downstream cellular processes. We previously showed in an expression profiling study that circZNF800 (hsa_circ_0082096) was up-regulated in cancer stem cell-enriched spheroids derived from colorectal cancer (CRC) cell lines.

METHODS

Spheroids were generated in suspension spheroidal culture. The ZNF800 mRNA, pluripotency stem cell markers and circZNF800 levels were determined by quantitative RT-PCR. CircZNF800-miRNA interactions were shown in RNA pulldown assays and the miRNA levels determined by stem-loop qRT-PCR. The effects of circZNF800 on cell proliferation were tested by EdU staining followed by flowcytometry. Expression of stem cell markers CD44/CD133, Lgr5 and SOX9 was demonstrated in immunofluorescence microscopy. To manipulate the cellular levels of circZNF800, circZNF800 over-expression was achieved via transfection of in vitro synthesized and circularized circZNF800, and knockdown attained using a CRISPR-Cas13d-circZNF800 vector system. Xenografted nude mice were used to demonstrate effects of circZNF800 over-expression and knockdown on tumor growth in vivo.

RESULTS

CircZNF800 was shown to be over-expressed in late-stage tumor tissues of CRC patients. Data showed that circZNF800 impeded expression of miR-140-3p, miR-382-5p and miR-579-3p while promoted the mRNA levels of ALK/ACVR1C, FZD3 and WNT5A targeted by the miRNAs, as supported by alignments of seed sequences between the circZNF800-miRNA, and miRNA-mRNA paired interactions. Analysis in CRC cells and biopsied tissues showed that circZNF800 positively regulated the expression of intestinal stem cell, pluripotency and cancer stem cell markers, and promoted CRC cell proliferation, spheroid and colony formation in vitro, all of which are cancer stem cell properties. In xenografted mice, circZNF800 over-expression promoted tumor growth, while circZNF800 knockdown via administration of CRISPR Cas13d-circZNF800 viral particles at the CRC tumor sites impeded tumor growth.

CONCLUSIONS

CircZNF800 is an oncogenic factor that regulate cancer stem cell properties to lead colorectal tumorigenesis, and may be used as a predictive marker for tumor progression and the CRISPR Cas13d-circZNF800 knockdown strategy for therapeutic intervention of colorectal cancer.

Qizhu Anti-Cancer Recipe promotes anoikis of hepatocellular carcinoma cells by activating the c-Jun N-terminal kinase pathway

Background

Qizhu Anti-Cancer Recipe (QACR) is a traditional Chinese medicine widely used in treating several liver diseases. However, its function and the relevant mechanism underlying its effect in treating hepatocellular carcinoma (HCC) remain unknown. The aim of this study was to explore the effect of QACR in HCC, which are expected to be a potential therapeutic scheme for HCC.

Materials and methods

The chemical compositions of QACR were determined by liquid chromatography/quadrupole time-of-fight mass spectrometry (LC-QTOF-MS). The anoikis-resistant HCC cell proliferation and angiopoiesis were detected using the cell counting kit 8 (CCK8) assay, trypan blue, calcein AM/EthD-1, flow cytometer, Western blot, and tube formation assays. An orthotopic xenograft mouse model was established to evaluate the in vivo effects of the QACR. The expression of proliferating cell nuclear antigen (PCNA), Bcl-2, CD31, caspase-3, caspase-8, caspase-9, PARP-1, DFF40, phospho-c-Jun NH2-terminal kinase (p-JNK), and JNK was assessed using Western blot and immunohistochemical analysis.

Results

QACR reduced the growth and tube formation of anoikis-resistant HCC cells and enhanced cell apoptosis in vitro. In the orthotopic xenograft mouse models, QACR suppressed the tumorigenesis of HCC in vivo. Mechanistically, QACR modulated the JNK pathway. The JNK inhibitor (SP600125) reverses the inhibitory effects of QACR on anoikis-resistant HCC cell proliferation and angiopoiesis.

Conclusion

Our study suggests that QACR suppresses the proliferation and angiopoiesis of anoikis-resistant HCC cells by activating the JNK pathway. Therefore, QACR is a promising new therapeutic strategy for treating hepatocellular carcinoma.

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.

Galectin-1 in Pancreatic Ductal Adenocarcinoma: Bridging Tumor Biology, Immune Evasion, and Therapeutic Opportunities

Pancreatic Ductal Adenocarcinoma (PDAC) remains one of the most challenging malignancies to treat, with a complex interplay of molecular pathways contributing to its aggressive nature. Galectin-1 (Gal-1), a member of the galectin family, has emerged as a pivotal player in the PDAC microenvironment, influencing various aspects from tumor growth and angiogenesis to immune modulation. This review provides a comprehensive overview of the multifaceted role of Galectin-1 in PDAC. We delve into its contributions to tumor stroma remodeling, angiogenesis, metabolic reprogramming, and potential implications for therapeutic interventions. The challenges associated with targeting Gal-1 are discussed, given its pleiotropic functions and complexities in different cellular conditions. Additionally, the promising prospects of Gal-1 inhibition, including the utilization of nanotechnology and theranostics, are highlighted. By integrating recent findings and shedding light on the intricacies of Gal-1's involvement in PDAC, this review aims to provide insights that could guide future research and therapeutic strategies.

Integrated bulk and scRNA sequence identified anoikis-related diagnostic biomarkers and potential association with immune infiltration in type A aortic dissection

Type-A aortic dissection (TAAD) is common life-threatening cardiovascular diseases with high-morbidity and mortality but the concrete etiology of disease remains unclear, which might disturb or delay the early diagnosis for TAAD. Anoikis is a special form of programmed cell-death (PCD) induced by detachment of anchorage-dependent cells from the extracellular matrix (ECM) or neighboring cells, and has been widely applied to identify anoikis-related biomarkers for the prediction and prognosis in oncological fields. However, the specific roles of anoikis-related genes (ARGs) in TAAD remain unclear. In this study, we first identified and validated eight diagnostic ARGs for TAAD based on multiple RNA-sequence datasets, including CHEK2, HIF1A, HK2, HMGA1, SERPINA1, PTPN1, SLC2A1 and VEGFA. The comprehensive functional annotation was evaluated by the integrated functional enrichments analysis. We identified the activation of inflammatory-related pathways, metabolic reprogramming and angiogenesis, and the inhibition of cardiovascular development pathways in TAAD. Immune cell infiltration (ICI) analysis further demonstrated that innate immune-cells were more dominant than adaptive immune-cells in TAAD tissues, especially in macrophages, monocytes, activated-DC, NKT cells and CD56+dim NK cells. The cellular landscape was further validated by single-cell RNA sequence technology with significant associations with anoikis in TAAD patients. Four vital ARGs (HIF1A, HMGA1, SERPINA1 and VEGFA) were ultimately identified along with the changes of differentiation trajectory, and major expressions were conformably concentrated on Macro1-3, Mono1-2 and Mono4 subtypes. These findings provide a promising diagnostic biomarker for the accurately diagnosing the disease and would be helpful to further explore the potential pathogenesis with anoikis process for TAAD.

Polyphyllin VII induces CTC anoikis to inhibit lung cancer metastasis through EGFR pathway regulation

Circulating tumor cells (CTCs) are cells that detach from the primary tumor and enter the bloodstream, playing a crucial role in the metastasis of lung cancer. Unfortunately, there is currently a lack of drugs specifically designed to target CTCs and prevent tumor metastasis. In this study, we present evidence that polyphyllin VII, a potent anticancer compound, effectively inhibits the metastasis of lung cancer by inducing a process called anoikis in CTCs. We observed that polyphyllin VII had significant cytotoxicity and inhibited colony formation, migration, and invasion in both our newly established cell line CTC-TJH-01 and a commercial lung cancer cell line H1975. Furthermore, we found that polyphyllin VII induced anoikis and downregulated the TrkB and EGFR-MEK/ERK signaling pathways. Moreover, activation of TrkB protein did not reverse the inhibitory effect of polyphyllin VII on CTCs, while upregulation of EGFR protein effectively reversed it. Furthermore, our immunodeficient mouse models recapitulated that polyphyllin VII inhibited lung metastasis, which was associated with downregulation of the EGFR protein, and reduced the number of CTCs disseminated into the lungs by inducing anoikis. Together, these results suggest that polyphyllin VII may be a promising compound for the treatment of lung cancer metastasis by targeting CTCs.

Prognostic analyses of genes associated with anoikis in breast cancer

Breast cancer (BRCA) is the most diagnosed cancer worldwide and is responsible for the highest cancer-associated mortality among women. It is evident that anoikis resistance contributes to tumour cell metastasis, and this is the primary cause of treatment failure for BRCA. However, anoikis-related gene (ARG) expression profiles and their prognostic value in BRCA remain unclear. In this study, a prognostic model of ARGs based on The Cancer Genome Atlas (TCGA) database was established using a least absolute shrinkage and selection operator analysis to evaluate the prognostic value of ARGs in BRCA. The risk factor graph demonstrated that the low-risk group had longer survival than the high-risk group, implying that the prognostic model had a good performance. We identified 11 ARGs that exhibited differential expression between the two risk groups in TCGA and Gene Expression Omnibus databases. Through Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes enrichment analyses, we revealed that the screened ARGs were associated with tumour progression and metastasis. In addition, a protein-protein interaction network showed potential interactions among these ARGs. Furthermore, gene set enrichment analysis suggested that the Notch and Wnt signalling pathways were overexpressed in the high-risk group, and gene set variation analysis revealed that 38 hallmark genes differed between the two groups. Moreover, Kaplan-Meier survival curves and receiver operating characteristic curves were used to identify five ARGs (CD24, KRT15, MIA, NDRG1, TP63), and quantitative polymerase chain reaction was employed to assess the differential expression of these ARGs. Univariate and multivariate Cox regression analyses were then performed for the key ARGs, with the best prediction of 3 year survival. In conclusion, ARGs might play a crucial role in tumour progression and serve as indicators of prognosis in BRCA.

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.

An anoikis-based gene signature for predicting prognosis in malignant pleural mesothelioma and revealing immune infiltration

INTRODUCTION

Malignant pleural mesothelioma (MPM) is an aggressive, treatment-resistant tumor. Anoikis is a particular type of programmed apoptosis brought on by the separation of cell-cell or extracellular matrix (ECM). Anoikis has been recognized as a crucial element in the development of tumors. However, few studies have comprehensively examined the role of anoikis-related genes (ARGs) in malignant mesothelioma.

METHODS

ARGs were gathered from the GeneCard database and the Harmonizome portals. We obtained differentially expressed genes (DEGs) using the GEO database. Univariate Cox regression analysis, and the least absolute shrinkage and selection operator (LASSO) algorithm were utilized to select ARGs associated with the prognosis of MPM. We then developed a risk model, and time-dependent receiver operating characteristic (ROC) analysis and calibration curves were employed to confirm the ability of the model. The patients were divided into various subgroups using consensus clustering analysis. Based on the median risk score, patients were divided into low- and high-risk groups. Functional analysis and immune cell infiltration analysis were conducted to estimate molecular mechanisms and the immune infiltration landscape of patients. Finally, drug sensitivity analysis and tumor microenvironment landscape were further explored.

RESULTS

A novel risk model was constructed based on the six ARGs. The patients were successfully divided into two subgroups by consensus clustering analysis, with a striking difference in the prognosis and landscape of immune infiltration. The Kaplan-Meier survival analysis indicated that the OS rate of the low-risk group was significantly higher than the high-risk group. Functional analysis, immune cell infiltration analysis, and drug sensitivity analysis showed that high- and low-risk groups had different immune statuses and drug sensitivity.

CONCLUSIONS

In summary, we developed a novel risk model to predict MPM prognosis based on six selected ARGs, which could broaden comprehension of personalized and precise therapy approaches for MPM.

A fluorene derivative inhibits human hepatocellular carcinoma cells by ROS-mediated apoptosis, anoikis and autophagy

Fluorene was previously reported to have anticancer activity against human cancer cells. In this study, we examined the in vitro function of 9-methanesulfonylmethylene-2, 3-dimethoxy-9 H -fluorene (MSDF), a novel fluorene derivative, its anticancer potential in human hepatocellular carcinoma (HCC) cells and its underlying molecular mechanism. The disruption of cellular homeostasis caused by MSDF was found to promote reactive oxygen species (ROS) generation, leading to the activation of cellular apoptosis. As a survival strategy, cells undergo autophagy during oxidative stress. MSDF-induced apoptosis occurred through both receptor-mediated extrinsic and mitochondrial-mediated intrinsic routes. The development of acidic vesicular organelles and the accumulation of LC3-II protein suggest an increase in the autophagic process. Apoptosis was detected by double staining. The MAPK/ERK and PI3K/Akt signaling pathways were indeed suppressed during treatment. Along with elevated ROS generation and apoptosis, MSDF also caused anoikis and cell death by causing cells to lose contact with their extracellular matrix. ROS production was induced by MSDF and sustained by an NAC scavenger. MSDF-induced apoptosis led to increased autophagy, as shown by the suppression of apoptosis by Z-VAD-FMK. However, inhibition of autophagy by inhibitor 3-MA increased MSDF-induced apoptosis. More evidence shows that MSDF downregulated the expression of immune checkpoint proteins, suggesting that MSDF could be used in the future as an adjuvant to improve the effectiveness of HCC immunotherapy. Altogether, our results highlight the potential of MSDF as a multitarget drug for the treatment of HCC.

Development of a prognostic model for anoikis and identifies hub genes in hepatocellular carcinoma

Considering the high fatality of hepatocellular carcinoma (HCC), current prognostic systems are insufficient to accurately forecast HCC patients' outcomes. In our study, nine anoikis‑related genes (PTRH2, ITGAV, ANXA5, BIRC5, BDNF, BSG, DAP3, SKP2, and EGF) were determined to establish a risk scoring model using LASSO regression, which could be validated in ICGC dataset. Kaplan-Meier curves and time-dependent receiver operating characteristic (ROC) curve analysis confirmed the risk score possessed an accurate predictive value for the prognosis of HCC patients. The high-risk group showed a higher infiltration of aDCs, macrophages, T-follicular helper cells, and Th2 cells. Besides, PD-L1 was significantly higher in the high-risk group compared to the low-risk group. Several anoikis‑related genes, such as ANX5, ITGAV, BDNF and SKP2, were associated with drug sensitivity in HCC. Finally, we identified BIRC5 and SKP2 as hub genes among the nine model genes using WGCNA analysis. BIRC5 and SKP2 were over-expressed in HCC tissues, and their over-expression was associated with poor prognosis, no matter in our cohort by immunohistochemical staining or in the TCGA cohort by mRNA-Seq. In our cohort, BIRC5 expression was highly associated with the T stage, pathologic stage, histologic grade and AFP of HCC patients. In general, our anoikis-related risk model can enhance the ability to predict the survival outcomes of HCC patients and provide a feasible therapeutic strategy for immunotherapy and drug resistance in HCC. BIRC5 and SKP2 are hub genes of anoikis‑related genes in HCC.

Development of the prognostic value in lung adenocarcinoma based on anoikis-related genes and initial experimental validation

BACKGROUND

Lung adenocarcinoma (LUAD) is a highly aggressive cancer in advanced stages and has the highest cancer-related death across the world. Anoikis has emerged as a specific form of apoptotic cell death that may play a vital role in the formation and development of tumors.

METHODS

Based on The Cancer Genome Atlas dataset, we developed a novel anoikis-related genes (ARGs) signature in LUAD and evaluated the differences between low and high-risk groups in clinical characteristics, expression patterns, immune cell infiltration, and drug sensitivity, etc. According to multivariate Cox regression analysis, the risk score was identified as a significant independent prognostic factor. The possible biological pathways of ARGs' were assessed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. The immune infiltration landscape and risk score of ARGs were analyzed by ESTIMATE and CIBERSORT analysis. A nomogram grounded on six key ARGs and clinicopathological features was provided. Moreover, experiment validation of the expression patterns of six hub ARGs in lung cancer cell lines was conducted.

RESULTS

We identified 53 survival-related LUAD anoikis-related differentially expressed genes and finally six hub anoikis genes (LDHA, SLC2A1, SERPINB5, ITGB4, BRCA2, and PIK3R1) were selected to construct an ARG model. The risk model could efficiently cluster the patients into low- and high-risk groups which could accurately predict clinical outcomes for LUAD patients. There is evidence that the prognostic risk score is a remarkable prognostic factor in determining overall survival. Different immune statuses and drug sensitivity between low- and high-risk groups were explored according to functional analysis. On the basis of risk scores and LUAD clinicopathological features, a novel nomogram was developed. Ultimately, all six key genes except for PIK3R1 were proved to be upregulated in LUAD tissues and cell lines by bioinformatics analysis and experimental validation.

CONCLUSIONS

The result of the present study suggest that ARGs could be carcinogenic to LUAD and could be used as an effective stratification factor to customize therapies and forecast the survival rate in LUAD patients.

Insights into the tumor-stromal-immune cell metabolism cross talk in ovarian cancer

The ovarian cancer tumor microenvironment (TME) consists of a constellation of abundant cellular components, extracellular matrix, and soluble factors. Soluble factors, such as cytokines, chemokines, structural proteins, extracellular vesicles, and metabolites, are critical means of noncontact cellular communication acting as messengers to convey pro- or antitumorigenic signals. Vast advancements have been made in our understanding of how cancer cells adapt their metabolism to meet environmental demands and utilize these adaptations to promote survival, metastasis, and therapeutic resistance. The stromal TME contribution to this metabolic rewiring has been relatively underexplored, particularly in ovarian cancer. Thus, metabolic activity alterations in the TME hold promise for further study and potential therapeutic exploitation. In this review, we focus on the cellular components of the TME with emphasis on 1) metabolic signatures of ovarian cancer; 2) understanding the stromal cell network and their metabolic cross talk with tumor cells; and 3) how stromal and tumor cell metabolites alter intratumoral immune cell metabolism and function. Together, these elements provide insight into the metabolic influence of the TME and emphasize the importance of understanding how metabolic performance drives cancer progression.

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.

How do prolonged anchorage-free lifetimes strengthen non-small-cell lung cancer cells to evade anoikis? - A link with altered cellular metabolomics

BACKGROUND

Malignant cells adopt anoikis resistance to survive anchorage-free stresses and initiate cancer metastasis. It is still unknown how varying periods of anchorage loss contribute to anoikis resistance, cell migration, and metabolic reprogramming of cancerous cells.

RESULTS

Our study demonstrated that prolonging the anchorage-free lifetime of non-small-cell lung cancer NCI-H460 cells for 7 days strengthened anoikis resistance, as shown by higher half-life and capability to survive and grow without anchorage, compared to wild-type cells or those losing anchorage for 3 days. While the prolonged anchorage-free lifetime was responsible for the increased aggressive feature of survival cells to perform rapid 3-dimensional migration during the first 3 h of a transwell assay, no significant influence was observed with 2-dimensional surface migration detected at 12 and 24 h by a wound-healing method. Metabolomics analysis revealed significant alteration in the intracellular levels of six (oxalic acid, cholesterol, 1-ethylpyrrolidine, 1-(3-methylbutyl)-2,3,4,6-tetramethylbenzene, β-alanine, and putrescine) among all 37 identified metabolites during 7 days without anchorage. Based on significance values, enrichment ratios, and impact scores of all metabolites and their associated pathways, three principal metabolic activities (non-standard amino acid metabolism, cell membrane biosynthesis, and oxidative stress response) offered potential links with anoikis resistance.

CONCLUSIONS

These findings further our insights into the evolution of anoikis resistance in lung cancer cells and identify promising biomarkers for early lung cancer diagnosis.

Anoikis resistance--protagonists of breast cancer cells survive and metastasize after ECM detachment

Breast cancer exhibits the highest global incidence among all tumor types. Regardless of the type of breast cancer, metastasis is a crucial cause of poor prognosis. Anoikis, a form of apoptosis initiated by cell detachment from the native environment, is an outside-in process commencing with the disruption of cytosolic connectors such as integrin-ECM and cadherin-cell. This disruption subsequently leads to intracellular cytoskeletal and signaling pathway alterations, ultimately activating caspases and initiating programmed cell death. Development of an anoikis-resistant phenotype is a critical initial step in tumor metastasis. Breast cancer employs a series of stromal alterations to suppress anoikis in cancer cells. Comprehensive investigation of anoikis resistance mechanisms can inform strategies for preventing and regressing metastatic breast cancer. The present review first outlines the physiological mechanisms of anoikis, elucidating the alterations in signaling pathways, cytoskeleton, and protein targets that transpire from the outside in upon adhesion loss in normal breast cells. The specific anoikis resistance mechanisms induced by pathological changes in various spatial structures during breast cancer development are also discussed. Additionally, the genetic loci of targets altered in the development of anoikis resistance in breast cancer, are summarized. Finally, the micro-RNAs and targeted drugs reported in the literature concerning anoikis are compiled, with keratocin being the most functionally comprehensive. Video Abstract.

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.

Inhibition of protein translation under matrix-deprivation stress in breast cancer cells

Matrix-deprivation stress leads to cell-death by anoikis, whereas overcoming anoikis is critical for cancer metastasis. Work from our lab and others has identified a crucial role for the cellular energy sensor AMPK in anoikis-resistance, highlighting a key role for metabolic reprogramming in stress survival. Protein synthesis is a major energy-consuming process that is tightly regulated under stress. Although an increase in protein synthesis in AMPK-depleted experimentally-transformed MEFs has been associated with anoikis, the status and regulation of protein translation in epithelial-origin cancer cells facing matrix-detachment remains largely unknown. Our study shows that protein translation is mechanistically abrogated at both initiation and elongation stages by the activation of the unfolded protein response (UPR) pathway and inactivation of elongation factor eEF2, respectively. Additionally, we show inhibition of the mTORC1 pathway known for regulation of canonical protein synthesis. We further functionally assay this inhibition using SUnSET assay, which demonstrates repression of global protein synthesis in MDA-MB-231 and MCF7 breast cancer cells when subjected to matrix-deprivation. In order to gauge the translational status of matrix-deprived cancer cells, we undertook polysome profiling. Our data revealed reduced but continuous mRNA translation under matrix-deprivation stress. An integrated analysis of transcriptomic and proteomic data further identifies novel targets that may aid cellular adaptations to matrix-deprivation stress and can be explored for therapeutic intervention.

A signature based on anoikis-related genes for the evaluation of prognosis, immunoinfiltration, mutation, and therapeutic response in ovarian cancer

Background

Ovarian cancer (OC) is a highly lethal and aggressive gynecologic cancer, with an overall survival rate that has shown little improvement over the decades. Robust models are urgently needed to distinguish high-risk cases and predict reliable treatment options for OC. Although anoikis-related genes (ARGs) have been reported to contribute to tumor growth and metastasis, their prognostic value in OC remains unknown. The purpose of this study was to construct an ARG pair (ARGP)-based prognostic signature for patients with OC and elucidate the potential mechanism underlying the involvement of ARGs in OC progression.

Methods

The RNA-sequencing and clinical information data of OC patients were obtained from The Center Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A novel algorithm based on pairwise comparison was utilized to select ARGPs, followed by the Least Absolute Shrinkage and Selection Operator Cox analysis to construct a prognostic signature. The predictive ability of the model was validated using an external dataset, a receiver operating characteristic curve, and stratification analysis. The immune microenvironment and the proportion of immune cells were analyzed in high- and low-risk OC cases using seven algorithms. Gene set enrichment analysis and weighted gene co-expression network analysis were performed to investigate the potential mechanisms of ARGs in OC occurrence and prognosis.

Results

The 19-ARGP signature was identified as an important prognostic predictor for 1-, 2-, and 3-year overall survival of patients with OC. Gene function enrichment analysis showed that the high-risk group was characterized by the infiltration of immunosuppressive cells and the enrichment of adherence-related signaling pathway, suggesting that ARGs were involved in OC progression by mediating immune escape and tumor metastasis.

Conclusion

We constructed a reliable ARGP prognostic signature of OC, and our findings suggested that ARGs exerted a vital interplay in OC immune microenvironment and therapeutic response. These insights provided valuable information regarding the molecular mechanisms underlying this disease and potential targeted therapies.

Long non-coding RNAs modulate tumor microenvironment to promote metastasis: novel avenue for therapeutic intervention

Cancer is a devastating disease and the primary cause of morbidity and mortality worldwide, with cancer metastasis responsible for 90% of cancer-related deaths. Cancer metastasis is a multistep process characterized by spreading of cancer cells from the primary tumor and acquiring molecular and phenotypic changes that enable them to expand and colonize in distant organs. Despite recent advancements, the underlying molecular mechanism(s) of cancer metastasis is limited and requires further exploration. In addition to genetic alterations, epigenetic changes have been demonstrated to play an important role in the development of cancer metastasis. Long non-coding RNAs (lncRNAs) are considered one of the most critical epigenetic regulators. By regulating signaling pathways and acting as decoys, guides, and scaffolds, they modulate key molecules in every step of cancer metastasis such as dissemination of carcinoma cells, intravascular transit, and metastatic colonization. Gaining a good knowledge of the detailed molecular basis underlying lncRNAs regulating cancer metastasis may provide previously unknown therapeutic and diagnostic lncRNAs for patients with metastatic disease. In this review, we concentrate on the molecular mechanisms underlying lncRNAs in the regulation of cancer metastasis, the cross-talk with metabolic reprogramming, modulating cancer cell anoikis resistance, influencing metastatic microenvironment, and the interaction with pre-metastatic niche formation. In addition, we also discuss the clinical utility and therapeutic potential of lncRNAs for cancer treatment. Finally, we also represent areas for future research in this rapidly developing field.

Different Ways to Die: Cell Death Pathways and Their Association With Spinal Cord Injury

Cell death is a systematic/nonsystematic process of cessation of normal morphology and functional properties of the cell to replace and recycle old cells with new also promoting inflammation in some cases. It is a complicated process comprising multiple pathways. Some are well-explored, and others have just begun to be. The research on appropriate control of cell death pathways after acute and chronic damage of neuronal cells is being widely researched today due to the lack of regeneration and recovering potential of a neuronal cell after sustaining damage and the inability to control the direction of neuronal growth. In the progression and onset of various neurological diseases, impairments in programmed cell death signaling processes, like necroptosis, apoptosis, ferroptosis, pyroptosis, and pathways directly or indirectly linked, like autophagy as in nonprogrammed necrosis, are observed. Spinal cord injury (SCI) involves the temporary or permanent disruption of motor activities due to the death of a neuronal and glial cell in the spinal cord accompanied by axonal degeneration. Recent years have seen a significant increase in research on the intricate biochemical interactions that occur after a SCI. Different cell death pathways may significantly impact the subsequent damage processes that lead to the eventual neurological deficiency after an injury to the spinal cord. A better knowledge of the molecular basis of the involved cell death pathways might help enhance neuronal and glial survival and neurological deficits, promoting a curative path for SCI.

Characterization of anoikis-based molecular heterogeneity in pancreatic cancer and pancreatic neuroendocrine tumor and its association with tumor immune microenvironment and metabolic remodeling

Background

Accumulating evidence suggests that anoikis plays a crucial role in the onset and progression of pancreatic cancer (PC) and pancreatic neuroendocrine tumors (PNETs); nevertheless, the prognostic value and molecular characteristics of anoikis in cancers are yet to be determined.

Materials and methods

We gathered and collated the multi-omics data of several human malignancies using the TCGA pan-cancer cohorts. We thoroughly investigated the genomics and transcriptomics features of anoikis in pan-cancer. We then categorized a total of 930 patients with PC and 226 patients with PNETs into distinct clusters based on the anoikis scores computed through single-sample gene set enrichment analysis. We then delved deeper into the variations in drug sensitivity and immunological microenvironment between the various clusters. We constructed and validated a prognostic model founded on anoikis-related genes (ARGs). Finally, we conducted PCR experiments to explore and verify the expression levels of the model genes.

Results

Initially, we identified 40 differentially expressed anoikis-related genes (DE-ARGs) between pancreatic cancer (PC) and adjacent normal tissues based on the TCGA, GSE28735, and GSE62452 datasets. We systematically explored the pan-cancer landscape of DE-ARGs. Most DE-ARGs also displayed differential expression trends in various tumors, which were strongly linked to favorable or unfavorable prognoses of patients with cancer, especially PC. Cluster analysis successfully identified three anoikis-associated subtypes for PC patients and two anoikis-associated subtypes for PNETs patients. The C1 subtype of PC patients showed a higher anoikis score, poorer prognosis, elevated expression of oncogenes, and lower level of immune cell infiltration, whereas the C2 subtype of PC patients had the exact opposite characteristics. We developed and validated a novel and accurate prognostic model for PC patients based on the expression traits of 13 DE-ARGs. In both training and test cohorts, the low-risk subpopulations had significantly longer overall survival than the high-risk subpopulations. Dysregulation of the tumor immune microenvironment could be responsible for the differences in clinical outcomes between low- and high-risk groups.

Conclusions

These findings provide fresh insights into the significance of anoikis in PC and PNETs. The identification of subtypes and construction of models have accelerated the progress of precision oncology.

Natural products targeting signaling pathways associated with regulated cell death in gastric cancer: Recent advances and perspectives

Gastric cancer (GC) is one of the most serious gastrointestinal malignancies with high morbidity and mortality. The complexity of GC process lies in the multi-phenotypic linkage regulation, in which regulatory cell death (RCD) is the core link, which largely dominates the fate of GC cells and becomes a key determinant of GC development and prognosis. In recent years, increasing evidence has been reported that natural products can prevent and inhibit the development of GC by regulating RCDs, showing great therapeutic potential. In order to further clarify its key regulatory characteristics, this review focused on specific expressions of RCDs, combined with a variety of signaling pathways and their crosstalk characteristics, sorted out the key targets and action rules of natural products targeting RCD. It is highlighted that a variety of core biological pathways and core targets are involved in the decision of GC cell fate, including the PI3K/Akt signaling pathway, MAPK-related signaling pathways, p53 signaling pathway, ER stress, Caspase-8, gasdermin D (GSDMD), and so on. Moreover, natural products target the crosstalk of different RCDs by modulating above signaling pathways. Taken together, these findings suggest that targeting various RCDs in GC with natural products is a promising strategy, providing a reference for further clarifying the molecular mechanism of natural products treating GC, which warrants further investigations in this area.

Identification of anoikis-related subtypes and development of risk stratification system in skin cutaneous melanoma

Background

Anoikis, a form of apoptosis induced by cell detachment, plays a key role in cancer metastasis. However, the potential roles of anoikis-related genes (ARGs) in assessing the prognosis of skin cutaneous melanoma (SKCM) and the tumor microenvironment (TME) remain unclear.

Methods

The data from TCGA corresponding to transcriptomic expression patterns for patients with SKCM were downloaded and utilized to screen distinct molecular subtypes by a non-negative matrix factorization algorithm. The prognostic signature was constructed by least absolute shrinkage and selection operator (LASSO) Cox regression and was validated in SKCM patients from the GEO cohort. Moreover, the relationship of the ARG_score with prognosis, tumor-infiltrating immune cells, gene mutation, microsatellite instability (MSI), and immunotherapy efficacy.

Results

We screened 100 anoikis-related differentially expressed genes between SKCM tissues and normal skin tissues, which could divide all patients into three different subtypes with significantly distinct prognosis and immune cell infiltration. Then, an anoikis-related signature was developed based on subtype-related DEGs, which could classify all SKCM patients into low and high ARG_score groups with differing overall survival (OS) rates. ARG_score was confirmed to be a strong independent prognostic indicator for SKCM patients. By combining ARG_score with clinicopathological features, a nomogram was constructed, which could accurately predict the individual OS of patients with SKCM. Moreover, low ARG_score patients presented with higher levels of immune cell infiltration, TME score, higher tumor mutation burden, and better immunotherapy responses.

Conclusions

Our comprehensive analysis of ARGs in SKCM provides important insights into the immunological microenvironment within the tumor of SKCM patients and helps to forecast prognosis and the response to immunotherapy in SKCM patients, thereby making it easier to tailor more effective treatment strategies to individual patients.

Transient Receptor Potential Ankyrin 1 (TRPA1) Channel as a Sensor of Oxidative Stress in Cancer Cells

Moderate levels of reactive oxygen species (ROS), such as hydrogen peroxide (H₂O₂), fuel tumor metastasis and invasion in a variety of cancer types. Conversely, excessive ROS levels can impair tumor growth and metastasis by triggering cancer cell death. In order to cope with the oxidative stress imposed by the tumor microenvironment, malignant cells exploit a sophisticated network of antioxidant defense mechanisms. Targeting the antioxidant capacity of cancer cells or enhancing their sensitivity to ROS-dependent cell death represent a promising strategy for alternative anticancer treatments. Transient Receptor Potential Ankyrin 1 (TRPA1) is a redox-sensitive non-selective cation channel that mediates extracellular Ca²⁺ entry upon an increase in intracellular ROS levels. The ensuing increase in intracellular Ca²⁺ concentration can in turn engage a non-canonical antioxidant defense program or induce mitochondrial Ca²⁺ dysfunction and apoptotic cell death depending on the cancer type. Herein, we sought to describe the opposing effects of ROS-dependent TRPA1 activation on cancer cell fate and propose the pharmacological manipulation of TRPA1 as an alternative therapeutic strategy to enhance cancer cell sensitivity to oxidative stress.

DUSP6 is a memory retention feedback regulator of ERK signaling for cellular resilience of human pluripotent stem cells in response to dissociation

Cultured human pluripotent stem cells (hPSCs) grow as colonies that require breakdown into small clumps for further propagation. Although cell death mechanism by single-cell dissociation of hPSCs has been well defined, how hPSCs respond to the deadly stimulus and recover the original status remains unclear. Here we show that dissociation of hPSCs immediately activates ERK, which subsequently activates RSK and induces DUSP6, an ERK-specific phosphatase. Although the activation is transient, DUSP6 expression persists days after passaging. DUSP6 depletion using the CRISPR/Cas9 system reveals that DUSP6 suppresses the ERK activity over the long term. Elevated ERK activity by DUSP6 depletion increases both viability of hPSCs after single-cell dissociation and differentiation propensity towards mesoderm and endoderm lineages. These findings provide new insights into how hPSCs respond to dissociation in order to maintain pluripotency.

Development and validation of a novel anoikis-related gene signature for predicting prognosis in ovarian cancer

Anoikis plays a critical role in variable cancer types. However, studies that focus on the prognostic values of anoikis-related genes (ANRGs) in OV are scarce. Cohorts with transcriptome data and corresponding clinicopathologic data of OV patients were collected and consolidated from public databases. Multiple bioinformatics approaches were used to screen key genes from 446 anoikis-related genes, including Cox regression analysis, random survival forest analysis, and Kaplan-Meier analysis of best combinations. A five-gene signature was constructed in the discovery cohort (TCGA) and validated in four validation cohorts (GEO). Risk score of the signature stratified patients into high-risk (HRisk) and low-risk (LRisk) subgroups. Patients in the HRisk group were associated with worse OS than those in the LRisk group in both the TCGA cohort (p<0.0001, HR=2.718, 95%CI:1.872-3.947) and the four GEO cohorts (p<0.05). Multivariate Cox regression analyses confirmed that the risk score served as an independent prognostic factor in both cohorts. The signature's predictive capacity was further demonstrated by the nomogram analysis. Pathway enrichment analysis revealed that immunosuppressive and malignant progression-related pathways were enriched in the HRisk group, including TGF-β, WNT and ECM pathways. The LRisk group was characterized by immune-active signaling pathways (interferon-gamma, T cell activation, etc.) and higher proportions of anti-tumor immune cells (NK, M1, etc.) while HRisk patients were associated with higher stromal scores and less TCR richness. In conclusion, the signature reveals a close relationship between the anoikis and prognosis and may provide a potential therapeutic target for OV patients.

Anoikis in phenotypic reprogramming of the prostate tumor microenvironment

Prostate cancer is one of the most common malignancies in males wherein 1 in 8 men are diagnosed with this disease in their lifetime. The urgency to find novel therapeutic interventions is associated with high treatment resistance and mortality rates associated with castration-resistant prostate cancer. Anoikis is an apoptotic phenomenon for normal epithelial or endothelial cells that have lost their attachment to the extracellular matrix (ECM). Tumor cells that lose their connection to the ECM can die via apoptosis or survive via anoikis resistance and thus escaping to distant organs for metastatic progression. This review discusses the recent advances made in our understanding of the signaling effectors of anoikis in prostate cancer and the approaches to translate these mechanistic insights into therapeutic benefits for reducing lethal disease outcomes (by overcoming anoikis resistance). The prostate tumor microenvironment is a highly dynamic landscape wherein the balance between androgen signaling, cell lineage changes, epithelial-mesenchymal transition (EMT), extracellular matrix interactions, actin cytoskeleton remodeling as well as metabolic changes, confer anoikis resistance and metastatic spread. Thus, these mechanisms also offer unique molecular treatment signatures, exploitation of which can prime prostate tumors to anoikis induction with a high translational significance.

VSTM2L contributes to anoikis resistance and acts as a novel biomarker for metastasis and clinical outcome in ovarian cancer

The majority of patients are diagnosed when ovarian cancer (OC) has metastasized, making surgery and chemotherapy less effective. Thus, there is an urgent need to elucidate the mechanisms underlying metastasis and to further explore novel diagnostic biomarkers of OC metastasis. Here, we conducted a genome-wide CRISPR-Cas9 screen for anoikis resistance to identify key genes associated with OC metastasis. Further, bioinformatic analysis was performed using TCGA and GTEx datasets to explore the genes associated with OC progression and prognosis. After integrated analysis, the V-set and transmembrane domain-containing protein 2-like (VSTM2L) was identified as a crucial gene closely associated with OC metastasis, progression, and prognosis. Further validation using a patient-based cohort suggested that VSTM2L expression was significantly higher in metastatic lesions than in primary lesions. Subsequently, an in vitro assay showed that VSTM2L silencing increased SKOV3 cell death and hampered spheroid formation. Mechanistically, GSEA highlighted that epithelial-mesenchymal transition (EMT)-related pathways was positively associated with VSTM2L expression. Consistently, the validation based on the VSTM2L silence suggested the involvement of VSTM2L in EMT-related TGF-β and NF-κB signaling. Meanwhile, the addition of VSTM2L-containing medium did not provoke those signaling, indicating VSTM2L functions as an intracellular protein to activate TGF-β and NF-κB signaling. In summary, our study revealed that VSTM2L is a novel player involved in anoikis resistance and is a promising biomarker of OC metastasis and prognosis.

A review on regulation of cell cycle by extracellular matrix

The extracellular matrix (ECM) is a network of structural proteins, glycoproteins and proteoglycans that assists independent cells in aggregating and forming highly organized functional structures. ECM serves numerous purposes and is an essential component of tissue structure and functions. Initially, the role of ECM was considered to be confined to passive functions like providing mechanical strength and structural identity to tissues, serving as barriers and platforms for cells. The doors to understanding ECM's proper role in tissue functioning opened with the discovery of cellular receptors, integrins to which ECM components binds and influences cellular activities. Understanding and utilizing ECM's potential to control cellular function has become a topic of much interest in recent decades, providing different outlooks to study processes involved in developmental programs, wound healing and tumour progression. On another front, the regulatory mechanisms operating to prevent errors in the cell cycle have been topics of a titanic amount of studies. This is expected as many diseases, most infamously cancer, are associated with defects in their functioning. This review focuses on how ECM, through different methods, influences the progression of the somatic cell cycle and provides deeper insights into molecular mechanisms of functional communication between adhesion complex, signalling pathways and cell cycle machinery.

ALDOC- and ENO2- driven glucose metabolism sustains 3D tumor spheroids growth regardless of nutrient environmental conditions: a multi-omics analysis

BACKGROUND

Metastases are the major cause of cancer-related morbidity and mortality. By the time cancer cells detach from their primary site to eventually spread to distant sites, they need to acquire the ability to survive in non-adherent conditions and to proliferate within a new microenvironment in spite of stressing conditions that may severely constrain the metastatic process. In this study, we gained insight into the molecular mechanisms allowing cancer cells to survive and proliferate in an anchorage-independent manner, regardless of both tumor-intrinsic variables and nutrient culture conditions.

METHODS

3D spheroids derived from lung adenocarcinoma (LUAD) and breast cancer cells were cultured in either nutrient-rich or -restricted culture conditions. A multi-omics approach, including transcriptomics, proteomics, and metabolomics, was used to explore the molecular changes underlying the transition from 2 to 3D cultures. Small interfering RNA-mediated loss of function assays were used to validate the role of the identified differentially expressed genes and proteins in H460 and HCC827 LUAD as well as in MCF7 and T47D breast cancer cell lines.

RESULTS

We found that the transition from 2 to 3D cultures of H460 and MCF7 cells is associated with significant changes in the expression of genes and proteins involved in metabolic reprogramming. In particular, we observed that 3D tumor spheroid growth implies the overexpression of ALDOC and ENO2 glycolytic enzymes concomitant with the enhanced consumption of glucose and fructose and the enhanced production of lactate. Transfection with siRNA against both ALDOC and ENO2 determined a significant reduction in lactate production, viability and size of 3D tumor spheroids produced by H460, HCC827, MCF7, and T47D cell lines.

CONCLUSIONS

Our results show that anchorage-independent survival and growth of cancer cells are supported by changes in genes and proteins that drive glucose metabolism towards an enhanced lactate production. Notably, this finding is valid for all lung and breast cancer cell lines we have analyzed in different nutrient environmental conditions. broader Validation of this mechanism in other cancer cells of different origin will be necessary to broaden the role of ALDOC and ENO2 to other tumor types. Future in vivo studies will be necessary to assess the role of ALDOC and ENO2 in cancer metastasis.

Anoikis-related long non-coding RNA signatures to predict prognosis and small molecular drug response in cervical cancer

Background: Cervical cancer (CC) is a major health threat to females, and distal metastasis is common in patients with advanced CC. Anoikis is necessary for the development of distal metastases. Understanding the mechanisms associated with anoikis in CC is essential to improve its survival rate. Methods: The expression matrix of long non-coding RNAs (lncRNAs) from cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) patients was extracted from The Cancer Genome Atlas (TCGA), and highly relevant anoikis-related lncRNAs (ARLs) were identified by the single sample gene set enrichment analysis (ssGSEA) method. ARLs-related molecular subtypes were discerned based on prognosis-related ARLs. ARLs-related prognostic risk score (APR_Score) was calculated and risk model was constructed using LASSO COX and COX models. In addition, we also assessed immune cell activity in the immune microenvironment (TME) for both subtypes and APR_Score groups. A nomogram was utilized for predicting improved clinical outcome. Finally, this study also discussed the potential of ARLs-related signatures in predicting response to immunotherapy and small molecular drugs. Results: Three ARLs-related subtypes were identified from TCGA-CESC (AC1, AC2, and AC3), with AC3 patients having the highest ARG scores, higher angiogenesis scores, and the worst prognosis. AC3 had lower immune cell scores in TME but higher immune checkpoint gene expression and higher potential for immune escape. Next, we constructed a prognostic risk model consisting of 7-ARLs. The APR_Score exhibited a greater robustness as an independent prognostic indicator in predicting prognosis, and the nomogram was a valuable tool for survival prediction. ARLs-related signatures emerged as a potential novel indicator for immunotherapy and small molecular drug selection. Conclusion: We firstly constructed novel ARLs-related signatures capable of predicting prognosis and offered novel ideas for therapy response in CC patients.

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.

Metabolomics in oncology

BACKGROUND

Oncogenic transformation alters intracellular metabolism and contributes to the growth of malignant cells. Metabolomics, or the study of small molecules, can reveal insight about cancer progression that other biomarker studies cannot. Number of metabolites involved in this process have been in spotlight for cancer detection, monitoring, and therapy.

RECENT FINDINGS

In this review, the "Metabolomics" is defined in terms of current technology having both clinical and translational applications. Researchers have shown metabolomics can be used to discern metabolic indicators non-invasively using different analytical methods like positron emission tomography, magnetic resonance spectroscopic imaging etc. Metabolomic profiling is a powerful and technically feasible way to track changes in tumor metabolism and gauge treatment response across time. Recent studies have shown metabolomics can also predict individual metabolic changes in response to cancer treatment, measure medication efficacy, and monitor drug resistance. Its significance in cancer development and treatment is summarized in this review.

CONCLUSION

Although in infancy, metabolomics can be used to identify treatment options and/or predict responsiveness to cancer treatments. Technical challenges like database management, cost and methodical knowhow still persist. Overcoming these challenges in near further can help in designing new treatment régimes with increased sensitivity and specificity.

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

The third leading cause of cancer-related deaths in the United States is pancreatic cancer, more than 95% of which is pancreatic ductal adenocarcinoma (PDA). The incidence rate of PDA nearly matches its mortality rate and the best treatment till date is surgical resection for which only 25% are eligible. Tumor recurrence and metastasis are the main causes of cancer-related mortality. MUC1 is a transmembrane glycoprotein expressed on most epithelial cells. It is overexpressed and aberrantly glycosylated in cancer and is known as tumor-associated MUC1 (tMUC1). More than 80% of PDAs express tMUC1. A monoclonal antibody called TAB004 has been developed specifically against human tMUC1 extracellular domain. We report that treatment with TAB004 significantly reduced the colony forming potential of multiple PDA cell lines while sparing normal pancreatic epithelial cell line. Binding of TAB004 to tMUC1 compromised desmosomal integrity, induced ER stress and anoikis in PDA cells. The mechanisms underlying TAB004's antitumor effects were found to be reduced activation of the EGFR-PI3K signaling pathway, and degradation of tMUC1, thereby reducing expression of its transcriptional targets, c-Src and c-Myc. This reduction in oncogenic signaling triggered anoikis as indicated by reduced expression of antiapoptotic proteins, PTRH2 and BCL2. TAB004 treatment slowed the growth of PDA xenograft compared to IgG control and enhanced survival of mice when combined with 5-FU. Since TAB004 significantly reduced colony forming potential and triggered anoikis in the PDA cells, we suggest that it could be used as a potential prophylactic agent to curb tumor relapse after surgery, prevent metastasis and help increase the efficacy of chemotherapeutic agents.

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.

A mathematical model of wound healing in bovine corneal endothelium

We developed a mathematical model to describe healing processes in bovine corneal endothelial (BCE) cells in culture, triggered by mechanical wounds with parallel edges. Previous findings from our laboratory show that, in these cases, BCE monolayers exhibit an approximately constant healing velocity. Also, that caspase-dependent apoptosis occurs, with the fraction of apoptotic cells increasing with the distance traveled by the healing edge. In addition, in this study we report the novel findings that, for wound scratch assays performed preserving the basal extracellular matrix: i) the healing cells increase their en face surface area in a characteristic fashion, and ii) the average length of the segments of the cell columns actively participating in the healing process increases linearly with time. These latter observations preclude the utilization of standard traveling wave formalisms to model wound healing in BCE cells. Instead, we developed and studied a simple phenomenological model based on a plausible formula for the spreading dynamics of the individual healing cells, that incorporates original evidence about the process in BCE cells. The model can be simulated to: i) obtain an approximately constant healing velocity; ii) reproduce the profile of the healing cell areas, and iii) obtain approximately linear time dependences of the mean cell area and average length of the front active segments per column. In view of its accuracy to account for the experimental observations, the model can also be acceptably employed to quantify the appearance of apoptotic cells during BCE wound healing. The strategy utilized here could offer a novel formal framework to represent modifications undergone by some epithelial cell lines during wound healing.

Identification of Anoikis-Related Subgroups and Prognosis Model in Liver Hepatocellular Carcinoma

Resistance to anoikis is a key characteristic of many cancer cells, promoting cell survival. However, the mechanism of anoikis in hepatocellular carcinoma (HCC) remains unknown. In this study, we applied differentially expressed overlapping anoikis-related genes to classify The Cancer Genome Atlas (TCGA) samples using an unsupervised cluster algorithm. Then, we employed weighted gene coexpression network analysis (WGCNA) to identify highly correlated genes and constructed a prognostic risk model based on univariate Cox proportional hazards regression. This model was validated using external datasets from the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO). Finally, we used a CIBERSORT algorithm to investigate the correlation between risk score and immune infiltration. Our results showed that the TCGA cohorts could be divided into two subgroups, with subgroup A having a lower survival probability. Five genes (BAK1, SPP1, BSG, PBK and DAP3) were identified as anoikis-related prognostic genes. Moreover, the prognostic risk model effectively predicted overall survival, which was validated using ICGC and GEO datasets. In addition, there was a strong correlation between infiltrating immune cells and prognostic genes and risk score. In conclusion, we identified anoikis-related subgroups and prognostic genes in HCC, which could be significant for understanding the molecular mechanisms and treatment of HCC.

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.

Construction of a novel anoikis-related prognostic model and analysis of its correlation with infiltration of immune cells in neuroblastoma

Background

Anoikis resistance (AR) plays an important role in the process of metastasis, which is an important factor affecting the risk stage of neuroblastoma (NB). This study aims to construct an anoikis-related prognostic model and analyze the characteristics of hub genes, important pathways and tumor microenvironment of anoikis-related subtypes of NB, so as to provide help for the clinical diagnosis, treatment and research of NB.

Methods

We combined transcriptome data of GSE49710 and E-MTAB-8248, screened anoikis-related genes (Args) closely related to the prognosis of NB by univariate cox regression analysis, and divided the samples into anoikis-related subtypes by consistent cluster analysis. WGCNA was used to screen hub genes, GSVA and GSEA were used to analyze the differentially enriched pathways between anoikis-related subtypes. We analyzed the infiltration levels of immune cells between different groups by SsGSEA and CIBERSORT. Lasso and multivariate regression analyses were used to construct a prognostic model. Finally, we analyzed drug sensitivity through the GDSC database.

Results

721 cases and 283 Args were included in this study. All samples were grouped into two subtypes with different prognoses. The analyses of WGCNA, GSVA and GSEA suggested the existence of differentially expressed hub genes and important pathways in the two subtypes. We further constructed an anoikis-related prognostic model, in which 15 Args participated. This model had more advantages in evaluating the prognoses of NB than other commonly used clinical indicators. The infiltration levels of 9 immune cells were significantly different between different risk groups, and 13 Args involved in the model construction were correlated with the infiltration levels of immune cells. There was a relationship between the infiltration levels of 6 immune cells and riskscores. Finally, we screened 15 drugs with more obvious effects on NB in high-risk group.

Conclusion

There are two anoikis-related subtypes with different prognoses in the population of NB. The anoikis-related prognostic model constructed in this study can accurately predict the prognoses of children with NB, and has a good guiding significance for clinical diagnosis, treatment and research of NB.