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

Empagliflozin drives ferroptosis in anoikis-resistant cells by activating miR-128-3p dependent pathway and inhibiting CD98hc in breast cancer

A tumour suppressor miRNA, miR-128-3p, is widely involved in various biological processes and has been found to get downregulated in breast cancer patients. We previously published that ectopically expressed miR-128-3p suppressed migration, invasion, cell cycle arrest, and breast cancer stem cells. In the present study, we explored the role of Empagliflozin (EMPA) as a miR-128-3p functionality-mimicking drug in inducing ferroptosis by inhibiting CD98hc. Given that CD98hc is one of the proteins critical in triggering ferroptosis, we confirmed that miR-128-3p and EMPA inhibited SP1, leading to inhibition of CD98hc expression. Further, transfection with siCD98hc, miR-128-3p mimics, and inhibitors was performed to assess their involvement in the ferroptosis of anoikis-resistant cells. We proved that anoikis-resistant cells possess high ROS and iron levels. Further, miR-128-3p and EMPA treatments induced ferroptosis by inhibiting GSH and enzymatic activity of GPX4 and also induced lipid peroxidation. Moreover, EMPA suppressed bioluminescence of 4T1-Red-FLuc induced thoracic cavity, peritoneal tumour burden and lung nodules in an in-vivo metastatic model of breast cancer. Collectively, we revealed that EMPA sensitized the ECM detached cells to ferroptosis by synergically activating miR-128-3p and lowering the levels of SP1 and CD98hc, making it a potential adjunct drug for breast cancer chemotherapy.

Muscone restores anoikis sensitivity in TMZ-resistant glioblastoma cells by suppressing TOP2A via the EGFR/Integrin β1/FAK signaling pathway

BACKGROUND

Temozolomide (TMZ) resistance is the main obstacle faced by glioblastoma multiforme (GBM) treatment. Muscone, one of the primary active pharmacological ingredients of Shexiang (Moschus), can cross the blood-brain barrier (BBB) and is being investigated as an antineoplastic medication. However, muscone treatment for GBM has received little research, and its possible mechanisms are still unclear.

PURPOSE

This study aims to evaluate the effect and the potential molecular mechanism of muscone on TMZ-resistant GBM cells.

METHODS

The differentially expressed genes (DEGs) between TMZ-resistant GBM cells and TMZ-sensitive GBM cells were screened using GEO2R. By progressively raising the TMZ concentration, a relatively stable TMZ-resistant human GBM cell line was established. The drug-resistance traits of U251-TR cells were assessed via the CCK-8 assay and Western Blot analysis of MGMT and TOP2A expression. Cell viability, cell proliferation, cell migration ability, and drug synergism were detected by the CCK-8 assay, colony formation assay, wound healing assay, and drug interaction relationship test, respectively. Anoikis was quantified by Calcein-AM/EthD-1 staining, MTT assay, and flow cytometry. Measurements of cell cycle arrest, apoptosis, mitochondrial membrane potential (MMP), and reactive oxygen species (ROS) were performed using cell cycle staining, Annexin V-FITC/PI labeling, JC-1 assay, and ROS assay, respectively. DNA damage was measured by TUNEL assay, alkaline comet assay, and γ-H2AX foci assay. GEPIA was used to investigate the link between the anoikis marker (FAK)/drug resistance gene and critical proteins in the EGFR/Integrin β1 signaling pathway. Molecular docking was used to anticipate the probable targets of muscone. The intracellular co-localization and expression of EGFR and FAK were shown using immunofluorescence. The U251-TR cell line stably overexpressing EGFR was constructed using lentiviral transduction to assess the involvement of EGFR-related signaling in anoikis resistance. Western Blot was employed to detect the expression of migration-related proteins, cyclins, anoikis-related proteins, DNA damage/repair-related proteins, and associated pathway proteins.

RESULTS

DEGs analysis identified 97 deregulated chemotherapy-resistant genes and 3779 upregulated genes in TMZ-resistant GBM cells. Subsequent experiments verified TMZ resistance and the hyper-expression of DNA repair-related genes (TOP2A and MGMT) in continuously low-dose TMZ-induced U251-TR cells. Muscone exhibited dose-dependent inhibition of U251-TR cell migration and proliferation, and its co-administration with TMZ showed the potential for enhanced therapeutic efficacy. By downregulating FAK, muscone reduced anoikis resistance in anchorage-independent U251-TR cells. It also caused cell cycle arrest in the G2/M phase by upregulating p21 and downregulating CDK1, CDK2, and Cyclin E1. Muscone-induced anoikis was accompanied by mitochondrial membrane potential collapse, ROS production, an increase in the BAX/Bcl-2 ratio, as well as elevated levels of Cytochrome c (Cyt c), cleaved caspase-9, and cleaved caspase-3. These findings indicated that muscone might trigger mitochondrial-dependent anoikis via ROS generation. Moreover, significant DNA damage, DNA double-strand breaks (DSBs), the formation of γ-H2AX foci, and a reduction in TOP2A expression are also associated with muscone-induced anoikis. Overexpression of EGFR in U251-TR cells boosted the expression of Integrin β1, FAK, β-Catenin, and TOP2A, whereas muscone suppressed the expression levels of EGFR, Integrin β1, β-Catenin, FAK, and TOP2A. Muscone may influence the expression of the key DNA repair enzyme, TOP2A, by suppressing the EGFR/Integrin β1/FAK pathway.

CONCLUSION

We first demonstrated that muscone suppressed TOP2A expression through the EGFR/Integrin β1/FAK pathway, hence restoring anoikis sensitivity in TMZ-resistant GBM cells. These data suggest that muscone may be a promising co-therapeutic agent for enhancing GBM treatment, particularly in cases of TMZ-resistant GBM with elevated TOP2A expression.

Targeting anoikis resistance as a strategy for cancer therapy

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

Targeting Nrf2 signaling pathways in the role of bladder cancer: From signal network to targeted therapy

Bladder cancer (BC) is the most common malignancy of the urinary system and often recurs after tumor removal and/or is resistant to chemotherapy. In cancer cells, the activity of the signaling pathway changes significantly, affecting a wide range of cell activities from growth and proliferation to apoptosis, invasion and metastasis. Nrf2 is a transcription factor that plays an important role in cellular defense responses to a variety of cellular stresses. There is increasing evidence that Nrf2 acts as a tumor driver and that it is involved in the maintenance of malignant cell phenotypes. Abnormal expression of Nrf2 has been found to be common in a variety of tumors, including bladder cancer. Over-activation of Nrf2 can lead to DNA damage and the development of bladder cancer, and is also associated with various pathological phenomena of bladder cancer, such as metastasis, angiogenesis, and reduced toxicity and efficacy of therapeutic anticancer drugs to provide cell protection for cancer cells. However, the above process can be effectively inhibited or reversed by inhibiting Nrf2. Therefore, Nrf2 signaling may be a potential targeting pathway for bladder cancer. In this review, we will characterize this signaling pathway and summarize the effects of Nrf2 and crosstalk with other signaling pathways on bladder cancer progression. The focus will be on the impact of Nrf2 activation on bladder cancer progression and current therapeutic strategies aimed at blocking the effects of Nrf2. To better determine how to promote new chemotherapy agents, develop new therapeutic agents, and potential therapeutic targets.

Beyond Death: Unmasking the Intricacies of Apoptosis Escape

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

Transcriptome analysis of human dental pulp cells cultured on a novel cell-adhesive fragment by RNA sequencing

AIM

The aim of the present work was to find an efficient method for safe and reliable expansion of human dental pulp cells (hDPCs) in vitro. Here, we examined the effect of a novel recombinant E8 fragment of Laminin-511 (iMatrix-511) in hDPCs regarding viability and cell spreading. Further, we investigated the underlying mechanisms governing its effects in hDPCs using RNA sequencing (RNA-seq).

METHODOLOGY

hDPCs were obtained from caries-free maxilla third molars (n = 3). CCK-8 assay was conducted to measure the viability of cells cultured on iMatrix-511 and two other ECM proteins. Cell morphology was observed by phase contrast microscope. RNA-seq of hDPCs cultured on iMatrix-511 or noncoated control was performed on Illumina NovaseqTM 6000 platform.

RESULTS

iMatrix-511 (0.5 μg/cm2) enhanced the viability of hDPCs to an extent better than COL-1 and gelatin. Short term culture of hDPCs on iMatrix-511 resulted in 233 differentially expressed genes (DEGs). The top 12 most upregulated genes were XIAP, AL354740, MRFAP1, AC012321, KCND3, TMEM120B, AC009812, GET1-SH3BGR, CNTN3, AC090409, GEN1 and PIK3IP1, whereas the top 12 most downregulated genes were SFN, KRT17, RAB4B-EGLN2, CSTA, KCTD11, ATP6V1G2-DDX39B, AC010323, SBSN, LYPD3, FOSB, AC022400 and CHI3L1. qPCR validation confirmed the significant upregulation of GEN1, KCND3, PIK3IP1 and MRFAP1. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed, with genes enriched in various extracellular matrix interaction, estrogen and fat metabolism-related functions and pathways.

CONCLUSIONS

iMatrix-511 facilitated spreading and proliferation of hDPCs. It enhances expression of anti-apoptotic genes, while inhibits expression of epidermis development-related genes.

ANXA5: A Key Regulator of Immune Cell Infiltration in Hepatocellular Carcinoma

BACKGROUND Hepatocellular carcinoma (HCC) poses a significant threat to human life and is the most prevalent form of liver cancer. The intricate interplay between apoptosis, a common form of programmed cell death, and its role in immune regulation stands as a crucial mechanism influencing tumor metastasis. MATERIAL AND METHODS Utilizing HCC samples from the TCGA database and 61 anoikis-related genes (ARGs) sourced from GeneCards, we analyzed the relationship between ARGs and immune cell infiltration in HCC. Subsequently, we identified long non-coding RNAs (lncRNAs) associated with ARGs, using the least absolute shrinkage and selection operator (LASSO) regression analysis to construct a robust prognostic model. The predictive capabilities of the model were then validated through examination in a single-cell dataset. RESULTS Our constructed prognostic model, derived from lncRNAs linked to ARGs, comprised 11 significant lncRNAs: NRAV, MCM3AP-AS1, OTUD6B-AS1, AC026356.1, AC009133.1, DDX11-AS1, AC108463.2, MIR4435-2HG, WARS2-AS1, LINC01094, and HCG18. The risk score assigned to HCC samples demonstrated associations with immune indicators and the infiltration of immune cells. Further, we identified Annexin A5 (ANXA5) as the pivotal gene among ARGs, with it exerting a prominent role in regulating the lncRNA gene signature. Our validation in a single-cell database elucidated the involvement of ANXA5 in immune cell infiltration, specifically in the regulation of mononuclear cells. CONCLUSIONS This study delves into the intricate correlation between ARGs and immune cell infiltration in HCC, culminating in the development of a novel prognostic model reliant on 11 ARGs-associated lncRNAs. Furthermore, our findings highlight ANXA5 as a promising target for immune regulation in HCC, offering new perspectives for immune therapy in the context of HCC.

Synergistic effects of photodynamic therapy and chemotherapy: Activating the intrinsic/extrinsic apoptotic pathway of anoikis for triple-negative breast cancer treatment

Triple-negative breast cancer (TNBC) is a highly invasive and metastatic subtype of breast cancer that often recurs after surgery. Herein, we developed a cyclodextrin-based tumor-targeted nano delivery system that incorporated the photosensitizer chlorin e6 (Ce6) and the chemotherapeutic agent lonidamine (LND) to form the R6RGD-CMβCD-se-se-Ce6/LND nanoparticles (RCC/LND NPS). This nanosystem could target cancer cells, avoid lysosomal degradation and further localize within the mitochondria. The RCC/LND NPS had pH and redox-responsive to control the release of Ce6 and LND. Consequently, the nanosystem had a synergistic effect by effectively alleviating hypoxia, enhancing the production of cytotoxic reactive oxygen species (ROS) and amplifying the efficacy of photodynamic therapy (PDT). Furthermore, the RCC/LND NPS + light weakened anoikis resistance, disrupted extracellular matrix (ECM), activated both the intrinsic apoptotic pathway (mitochondrial pathway) and extrinsic apoptotic pathway (receptor death pathway) of anoikis. In addition, the nanosystem showed significant anti-TNBC efficacy in vivo. These findings collectively demonstrated that RCC/LND NPS + light enhanced the anticancer effects, induced anoikis and inhibited tumor cell migration and invasion through a synergistic effect of chemotherapy and PDT. Overall, this study highlighted the promising potential of the RCC/LND NPS + light for the treatment of TNBC.

Anoikis-related lncRNA signature predicts prognosis and is associated with immune infiltration in hepatocellular carcinoma

Anoikis is a programmed cell death process triggered when cells are dislodged from the extracellular matrix. Numerous long noncoding RNAs (lncRNAs) have been identified as significant factors associated with anoikis resistance in various tumor types, including glioma, breast cancer, and bladder cancer. However, the relationship between lncRNAs and the prognosis of hepatocellular carcinoma (HCC) has received limited research attention. Further research is needed to investigate this potential link and understand the role of lncRNAs in the progression of HCC. We developed a prognostic signature based on the differential expression of lncRNAs implicated in anoikis in HCC. A co-expression network of anoikis-related mRNAs and lncRNAs was established using data obtained from The Cancer Genome Atlas (TCGA) for HCC. Cox regression analyses were conducted to formulate an anoikis-related lncRNA signature (ARlncSig) in a training cohort, which was subsequently validated in both a testing cohort and a combined dataset comprising the two cohorts. Receiver operating characteristic curves, nomograms, and decision curve analyses based on the ARlncSig score and clinical characteristics demonstrated robust predictive ability. Moreover, gene set enrichment analysis revealed significant enrichment of several immune processes in the high-risk group compared to the low-risk group. Furthermore, significant differences were observed in immune cell subpopulations, expression of immune checkpoint genes, and response to chemotherapy and immunotherapy between the high- and low-risk groups. Lastly, we validated the expression levels of the five lncRNAs included in the signature using quantitative real-time PCR. In conclusion, our ARlncSig model holds substantial predictive value regarding the prognosis of HCC patients and has the potential to provide clinical guidance for individualized immunotherapy. In this study, we obtained 36 genes associated with anoikis from the Gene Ontology and Gene Set Enrichment Analysis databases. We also identified 22 differentially expressed lncRNAs that were correlated with these genes using data from TCGA. Using Cox regression analyses, we developed an ARlncSig in a training cohort, which was then validated in both a testing cohort and a combined cohort comprising data from both cohorts. Additionally, we collected eight pairs of liver cancer tissues and adjacent tissues from the Affiliated Tumor Hospital of Nantong University for further analysis. The aim of this study was to investigate the potential of ARlncSig as a biomarker for liver cancer prognosis. The study developed a risk stratification system called ARlncSig, which uses five lncRNAs to categorize liver cancer patients into low- and high-risk groups. Patients in the high-risk group exhibited significantly lower overall survival rates compared to those in the low-risk group. The model's predictive performance was supported by various analyses including the receiver operating characteristic curve, nomogram calibration, clinical correlation analysis, and clinical decision curve. Additionally, differential analysis of immune function, immune checkpoint, response to chemotherapy, and immune cell subpopulations revealed significant differences between the high- and low-risk groups. Finally, quantitative real-time PCR validated the expression levels of the five lncRNAs. In conclusion, the ARlncSig model demonstrates critical predictive value in the prognosis of HCC patients and may provide clinical guidance for personalized immunotherapy.

EDI3 knockdown in ER-HER2+ breast cancer cells reduces tumor burden and improves survival in two mouse models of experimental metastasis

BACKGROUND

Despite progress understanding the mechanisms underlying tumor spread, metastasis remains a clinical challenge. We identified the choline-producing glycerophosphodiesterase, EDI3 and reported its association with metastasis-free survival in endometrial cancer. We also observed that silencing EDI3 slowed cell migration and other cancer-relevant phenotypes in vitro. Recent work demonstrated high EDI3 expression in ER-HER2+ breast cancer compared to the other molecular subtypes. Silencing EDI3 in ER-HER2+ cells significantly reduced cell survival in vitro and decreased tumor growth in vivo. However, a role for EDI3 in tumor metastasis in this breast cancer subtype was not explored. Therefore, in the present work we investigate whether silencing EDI3 in ER-HER2+ breast cancer cell lines alters phenotypes linked to metastasis in vitro, and metastasis formation in vivo using mouse models of experimental metastasis.

METHODS

To inducibly silence EDI3, luciferase-expressing HCC1954 cells were transduced with lentiviral particles containing shRNA oligos targeting EDI3 under the control of doxycycline. The effect on cell migration, adhesion, colony formation and anoikis was determined in vitro, and significant findings were confirmed in a second ER-HER2+ cell line, SUM190PT. Doxycycline-induced HCC1954-luc shEDI3 cells were injected into the tail vein or peritoneum of immunodeficient mice to generate lung and peritoneal metastases, respectively and monitored using non-invasive bioluminescence imaging. Metabolite levels in cells and tumor tissue were analyzed using targeted mass spectrometry and MALDI mass spectrometry imaging (MALDI-MSI), respectively.

RESULTS

Inducibly silencing EDI3 reduced cell adhesion and colony formation, as well as increased susceptibility to anoikis in HCC1954-luc cells, which was confirmed in SUM190PT cells. No influence on cell migration was observed. Reduced luminescence was seen in lungs and peritoneum of mice injected with cells expressing less EDI3 after tail vein and intraperitoneal injection, respectively, indicative of reduced metastasis. Importantly, mice injected with EDI3-silenced cells survived longer. Closer analysis of the peritoneal organs revealed that silencing EDI3 had no effect on metastatic organotropism but instead reduced metastatic burden. Finally, metabolic analyses revealed significant changes in choline and glycerophospholipid metabolites in cells and in pancreatic metastases in vivo.

CONCLUSIONS

Reduced metastasis upon silencing supports EDI3's potential as a treatment target in metastasizing ER-HER2+ breast cancer.

The emerging role of lactate in tumor microenvironment and its clinical relevance

In recent years, the significant impact of lactate in the tumor microenvironment has been greatly documented. Acting not only as an energy substance in tumor metabolism, lactate is also an imperative signaling molecule. It plays key roles in metabolic remodeling, protein lactylation, immunosuppression, drug resistance, epigenetics and tumor metastasis, which has a tight relation with cancer patients' poor prognosis. This review illustrates the roles lactate plays in different aspects of tumor progression and drug resistance. From the comprehensive effects that lactate has on tumor metabolism and tumor immunity, the therapeutic targets related to it are expected to bring new hope for cancer therapy.

CEACAM6 expression and function in tumor biology: a comprehensive review

Carcinoembryonic antigen-related cell adhesion molecule 6 (CEACAM6) is an immunoglobulin superfamily protein primarily expressed on epithelial surfaces and myeloid cells. It plays a significant role in cancer progression by inhibiting apoptosis, promoting drug resistance, and facilitating cancer cell invasion and metastasis. Overexpression of CEACAM6 has been observed in various cancers, including lung, breast, colorectal, and hepatocellular cancers, and is associated with poorer overall survival and disease-free survival. Its differential expression on tumor cell surfaces makes it a promising cancer marker. This review aims to provide a comprehensive summary of CEACAM6's role in different cancer types, its involvement in signaling pathways, and recent advancements in CEACAM6-targeted treatments.

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

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

Apigenin: Molecular Mechanisms and Therapeutic Potential against Cancer Spreading

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

Overcoming Nutrient Stress: Integrin αvβ3-Driven Metabolic Adaptation Supports Tumor Initiation

Nutrient stress accompanies several stages of tumor progression, including metastasis formation. Metabolic reprogramming is a hallmark of cancer, and it has been associated with stress tolerance and anchorage-independent cell survival. Adaptive responses are required to support cancer cell survival under these conditions. In this issue of Cancer Research, Nam and colleagues showed that the extracellular matrix (ECM) receptor integrin β3 was upregulated in lung cancer cells in response to nutrient starvation, resulting in increased cell survival that was independent from ECM binding. Delving into the molecular mechanisms responsible for this, the authors found that integrin β3 promoted glutamine metabolism and oxidative phosphorylation (OXPHOS) by activating a Src/AMPK/PGC1α signaling pathway. Importantly, in vivo experiments confirmed that OXPHOS inhibition suppressed tumor initiation in an orthotopic model of lung cancer, while β3 knockout completely abrogated tumor initiation. These observations indicate that targeting signaling pathways downstream of αvβ3 could represent a promising therapeutic avenue to prevent lung cancer progression and metastasis. See related article by Nam et al., p. 1630.

Identification and validation of a prognostic anoikis-related gene signature in papillary thyroid carcinoma by integrated analysis of single-cell and bulk RNA-sequencing

Papillary thyroid carcinoma (PTC) prognosis may be deteriorated due to the metastases, and anoikis palys an essential role in the tumor metastasis. However, the potential effect of anoikis-related genes on the prognosis of PTC was unclear. The mRNA and clinical information were obtained from the cancer genome atlas database. Hub genes were identified and risk model was constructed using Cox regression analysis. Kaplan-Meier (K-M) curve was applied for the survival analysis. Immune infiltration and immune therapy response were calculated using CIBERSORT and TIDE. The identification of cell types and cell interaction was performed by Seurat, SingleR and CellChat packages. GO, KEGG, and GSVA were applied for the enrichment analysis. Protein-protein interaction network was constructed in STRING and Cytoscape. Drug sensitivity was assessed in GSCA. Based on bulk RNA data, we identified 4 anoikis-related risk signatures, which were oncogenes, and constructed a risk model. The enrichment analysis found high risk group was enriched in some immune-related pathways. High risk group had higher infiltration of Tregs, higher TIDE score and lower levels of monocytes and CD8 T cells. Based on scRNA data, we found that 4 hub genes were mainly expressed in monocytes and macrophages, and they interacted with T cells. Hub genes were significantly related to immune escape-related genes. Drug sensitivity analysis suggested that cyclin dependent kinase inhibitor 2A may be a better chemotherapy target. We constructed a risk model which could effectively and steadily predict the prognosis of PTC. We inferred that the immune escape may be involved in the development of PTC.

A novel anoikis-related signature predicts prognosis risk and treatment responsiveness in diffuse large B-cell lymphoma

BACKGROUND

Although anoikis plays a role in cancer metastasis and aggressiveness, it has rarely been reported in diffuse large B cell lymphoma (DLBCL).

METHODS

We obtained RNA sequencing data and matched clinical data from the GEO database. An anoikis-related genes (ARGs)-based risk signature was developed in GSE10846 training cohort and validated in three other cohorts. Additionally, we predicted half-maximal inhibitory concentration (IC50) of drugs based on bioinformatics method and obtained the actual IC50 to some chemotherapy drugs via cytotoxicity assay.

RESULTS

The high-risk group, as determined by our signature, was associated with worse prognosis and an immunosuppressive environment in DLBCL. Meanwhile, the nomogram based on eight variables had more accurate ability in forecasting the prognosis than the international prognostic index in DLBCL. The prediction of IC50 indicated that DLBCL patients in the high-risk group were more sensitive to doxorubicin, IPA-3, lenalidomide, gemcitabine, and CEP.701, while patients in the low-risk group were sensitive to cisplatin and dasatinib. Consistent with the prediction, cytotoxicity assay suggested the higher sensitivity to doxorubicin and gemcitabine and the lower sensitivity to dasatinib in the high-risk group in DLBCL.

CONCLUSION

The ARG-based signature may provide a promising direction for prognosis prediction and treatment optimization for DLBCL patients.

Anoikis patterns via machine learning strategy and experimental verification exhibit distinct prognostic and immune landscapes in melanoma

BACKGROUND

Anoikis is a cell death programmed to eliminate dysfunctional or damaged cells induced by detachment from the extracellular matrix. Utilizing an anoikis-based risk stratification is anticipated to understand melanoma's prognostic and immune landscapes comprehensively.

METHODS

Differential expression genes (DEGs) were analyzed between melanoma and normal skin tissues in The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression data sets. Next, least absolute shrinkage and selection operator, support vector machine-recursive feature elimination algorithm, and univariate and multivariate Cox analyses on the 308 DEGs were performed to build the prognostic signature in the TCGA-melanoma data set. Finally, the signature was validated in GSE65904 and GSE22155 data sets. NOTCH3, PIK3R2, and SOD2 were validated in our clinical samples by immunohistochemistry.

RESULTS

The prognostic model for melanoma patients was developed utilizing ten hub anoikis-related genes. The overall survival (OS) of patients in the high-risk subgroup, which was classified by the optimal cutoff value, was remarkably shorter in the TCGA-melanoma, GSE65904, and GSE22155 data sets. Low-risk patients exhibited low immune cell infiltration and high expression of immunophenoscores and immune checkpoints. They also demonstrated increased sensitivity to various drugs, including dasatinib and dabrafenib. NOTCH3, PIK3R2, and SOD2 were notably associated with OS by univariate Cox analysis in the GSE65904 data set. The clinical melanoma samples showed remarkably higher protein expressions of NOTCH3 (P = 0.003) and PIK3R2 (P = 0.009) than the para-melanoma samples, while the SOD2 protein expression remained unchanged.

CONCLUSIONS

In this study, we successfully established a prognostic anoikis-connected signature using machine learning. This model may aid in evaluating patient prognosis, clinical characteristics, and immune treatment modalities for melanoma.

Identification of the molecular subtypes and signatures to predict the prognosis, biological functions, and therapeutic response based on the anoikis-related genes in colorectal cancer

BACKGROUND

Tumors that resist anoikis, a programmed cell death triggered by detachment from the extracellular matrix, promote metastasis; however, the role of anoikis-related genes (ARGs) in colorectal cancer (CRC) stratification, prognosis, and biological functions remains unclear.

METHODS

We obtained transcriptomic profiles of CRC and 27 ARGs from The Cancer Genome Atlas, the Gene Expression Omnibus, and MSigDB databases, respectively. CRC tissue samples were classified into two clusters based on the expression pattern of ARGs, and their functional differences were explored. Hub genes were screened using weighted gene co-expression network analysis, univariate analysis, and least absolute selection and shrinkage operator analysis, and validated in cell lines, tissues, or the Human Protein Atlas database. We constructed an ARG-risk model and nomogram to predict prognosis in patients with CRC, which was validated using an external cohort. Multifaceted landscapes, including stemness, tumor microenvironment (TME), immune landscape, and drug sensitivity, between high- and low-risk groups were examined.

RESULTS

Patients with CRC were divided into C1 and C2 clusters. Cluster C1 exhibited higher TME scores, whereas cluster C2 had favorable outcomes and a higher stemness index. Eight upregulated hub ARGs (TIMP1, P3H1, SPP1, HAMP, IFI30, ADAM8, ITGAX, and APOC1) were utilized to construct the risk model. The qRT-PCR, Western blotting, and immunohistochemistry results were consistent with those of the bioinformatics analysis. Patients with high risk exhibited worse overall survival (p < 0.01), increased stemness, TME, immune checkpoint expression, immune infiltration, tumor mutation burden, and drug susceptibility compared with the patients with low risk.

CONCLUSION

Our results offer a novel CRC stratification based on ARGs and a risk-scoring system that could predict the prognosis, stemness, TME, immunophenotypes, and drug susceptibility of patients with CRC, thereby improving their prognosis. This stratification may facilitate personalized therapies.

Construction of a gene signature associated with anoikis to evaluate the prognosis and immune infiltration in patients with colorectal cancer

Background

Colorectal cancer (CRC) is characterized by a high metastasis rate, leading to poor prognosis and increased mortality. Anoikis, a physiological process, serves as a crucial barrier against metastasis. The objective of this research is to construct a prognostic model for CRC based on genes associated with anoikis.

Methods

The study involved differential analysis and univariate Cox analysis of anoikis-related genes (ARGs), resulting in the selection of 47 genes closely associated with prognosis. Subsequently, unsupervised k-means clustering analysis was conducted on all patients to identify distinct clusters. Survival analysis, principal component analysis (PCA), and t-distributed stochastic neighbor embedding (t-SNE) analysis were performed on the different clusters to investigate associations within the clusters. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were utilized to assess metabolic pathway enrichment between the identified clusters. Furthermore, single-sample GSEA (ssGSEA) was applied to explore variations in immune infiltration. Multivariable Cox regression and least absolute shrinkage and selection operator (LASSO) analyses were conducted to construct a risk model based on ten signatures, which enabled the grouping of all samples according to their risk scores. The prognostic value of the model was validated using receiver operating characteristic (ROC) curves, area under the curve (AUC) calculations, and survival curves. Additionally, the expression of candidate genes was validated using quantitative real-time polymerase chain reaction (qRT-PCR).

Results

Forty-seven survival-related ARGs were screened out. Somatic mutation analysis showed that these genes revealed a high mutation rate. Based on their expression, two clusters were identified. Cluster B patients exhibited a shortened overall survival and higher immune infiltration. A risk scoring model including ten genes was subsequently developed, which exhibited excellent prognostic predictive ability for CRC, as evidenced by the survival curve, ROC curve, and AUC curve. In addition, a nomogram was developed for predicting 3- and 5-year survival probabilities. The qRT-PCR results indicated the dissimilarities among the ten signatures in the tumor tissues and adjacent tissues of patients with CRC were fundamentally consistent with the analytical findings.

Conclusions

This study comprehensively evaluated the prognostic significance of ARGs in CRC. It identified two distinct anoikis-related clusters and examined their respective immune microenvironments. Furthermore, an ARGs signature was developed to effectively predict the prognosis of CRC, thereby establishing a solid foundation for investigating the clinical prognostic role of anoikis in CRC.

Effects of syndecan-4 silencing on the extracellular matrix remodeling in anoikis-resistant endothelial cells

Anoikis is a process of programmed cell death induced by the loss of cell/matrix interactions. In previous work, we have shown that the acquisition of anoikis resistance upregulates syndecan-4 (SDC4) expression in endothelial cells. In addition, SDC4 gene silencing by microRNA interference reverses the transformed phenotype of anoikis-resistant endothelial cells. Due to this role of SDC4 in regulating the behavior of anoikis-resistant endothelial cells, we have evaluated that the functional consequences of SDC4 silencing in the extracellular matrix (ECM) remodeling in anoikis-resistant rabbit aortic endothelial cells submitted to SDC4 gene silencing (miR-Syn4-Adh-1-EC). For this, we evaluated the expression of adhesive proteins, ECM receptors, nonreceptor protein-tyrosine kinases, and ECM-degrading enzymes and their inhibitors. Altered cell behavior was monitored by adhesion, migration, and tube formation assays. We found that SDC4 silencing led to a decrease in migration and angiogenic capacity of anoikis-resistant endothelial cells; this was accompanied by an increase in adhesion to fibronectin. Furthermore, after SDC4 silencing, we observed an increase in the expression of fibronectin, collagen IV, and vitronectin, and a decrease in the expression of integrin α5β1 and αvβ3, besides that, silenced cells show an increase in Src and FAK expression. Quantitative polymerase chain reaction and Western blot analysis demonstrated that SDC4 silencing leads to altered gene and protein expression of MMP2, MMP9, and HSPE. Compared with parental cells, SDC4 silenced cells showed a decrease in nitric oxide production and eNOS expression. In conclusion, these data demonstrate that SDC4 plays an important role in ECM remodeling. In addition, our findings represent an important step toward understanding the mechanism by which SDC4 can reverse the transformed phenotype of anoikis-resistant endothelial cells.

Validation and identification of anoikis-related lncRNA signatures for improving prognosis in clear cell renal cell carcinoma

BACKGROUND

Clear cell carcinoma (ccRCC) usually has a high metastasis rate and high mortality rate. To enable precise risk stratification, there is a need for novel biomarkers. As one form of apoptosis, anoikis results from the disruption of cell-cell connection or cell-ECM attachment. However, the impact of anoikis-related lncRNAs on ccRCC has not yet received adequate attention.

METHODS

The study utilized univariate Cox regression analysis in order to identify the overall survival (OS) associated anoikis-related lncRNAs (ARLs), followed by the LASSO algorithm for selection. On this basis, a risk model was subsequently established using five anoikis-related lncRNAs. To dig the inner molecular mechanism, KEGG, GO, and GSVA analyses were conducted. Additionally, the immune infiltration landscape was estimated using the ESTIMATE, CIBERSORT, and ssGSEA algorithms.

RESULTS

The study constructed a novel risk model based on five ARLs (AC092611.2, AC027601.2, AC103809.1, AL133215.2, and AL162586.1). Patients categorized as low-risk exhibited significantly better OS. Notably, the study observed marked different immune infiltration landscapes and drug sensitivity by risk stratification. Additionally, the study preliminarily explored potential signal pathways associated with risk stratification.

CONCLUSION

The study exhibited the crucial role of ARLs in the carcinogenesis of ccRCC, potentially through differential immune infiltration. Furthermore, the established risk model could serve as a valuable stratification factor for predicting OS prognosis.

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

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

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

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

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

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

Programmed cell death-index (PCDi) as a prognostic biomarker and predictor of drug sensitivity in cervical cancer: a machine learning-based analysis of mRNA signatures

Purpose: Cervical cancer is a significant public health concern, particularly in developing countries. Despite available treatment strategies, the prognosis for patients with locally advanced cervical cancer and beyond remains poor. Therefore, an accurate prediction model that can reliably forecast prognosis is essential in clinical setting. Programmed cell death (PCD) mechanisms are diverse and play a critical role in tumor growth, survival, and metastasis, making PCD a potential reliable prognostic marker for cervical cancer. Methods: In this study, we created a novel prognostic indicator, programmed cell death-index (PCDi), based on a 10-fold cross-validation framework for comprehensive analysis of PCD-associated genes. Results: Our PCDi-based prognostic model outperformed previously published signature models, stratifying cervical cancer patients into two distinct groups with significant differences in overall survival prognosis, tumor immune features, and drug sensitivity. Higher PCDi scores were associated with poorer prognosis. The nomogram survival model integrated PCDi and clinical characteristics, demonstrating higher prognostic prediction performance. Furthermore, our study investigated the immune features of cervical cancer patients and found that those with high PCDi scores had lower infiltrating immune cells, lower potential of T cell dysfunction, and higher potential of T cell exclusion. Patients with high PCDi scores were resistant to classic chemotherapy regimens, including cisplatin, docetaxel, and paclitaxel, but showed sensitivity to the inhibitor SB505124 and Trametinib. Conclusion: Our findings suggest that PCD-related gene signature could serve as a useful biomarker to reliably predict prognosis and guide treatment decisions in cervical cancer.

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

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

Identification and validation of anoikis-related lncRNAs for prognostic significance and immune microenvironment characterization in ovarian cancer

Anoikis, a form of apoptotic cell death resulting from inadequate cell-matrix interactions, has been implicated in tumor progression by regulating tumor angiogenesis and metastasis. However, the potential roles of anoikis-related long non-coding RNAs (arlncRNAs) in the tumor microenvironment are not well understood. In this study, five candidate lncRNAs were screened through least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis based on differentially expressed lncRNAs associated with anoikis-related genes (ARGs) from TCGA and GSE40595 datasets. The prognostic accuracy of the risk model was evaluated using Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curves. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis (GSEA) analyses revealed significant differences in immune-related hallmarks and signal transduction pathways between the high-risk and low-risk groups. Additionally, immune infiltrate analysis showed significant differences in the distribution of macrophages M2, follicular T helper cells, plasma cells, and neutrophils between the two risk groups. Lastly, silencing the expression of PRR34_AS1 and SPAG5_AS1 significantly increased anoikis-induced cell death in ovarian cancer cells. In conclusion, our study constructed a risk model that can predict clinicopathological features, tumor microenvironment characteristics, and prognosis of ovarian cancer patients. The immune-related pathways identified in this study may offer new treatment strategies for ovarian cancer.

Cancer Metastasis-on-a-Chip for Modeling Metastatic Cascade and Drug Screening

Microfluidic chips are valuable tools for studying intricate cellular and cell-microenvironment interactions. Traditional in vitro cancer models lack accuracy in mimicking the complexities of in vivo tumor microenvironment. However, cancer-metastasis-on-a-chip (CMoC) models combine the advantages of 3D cultures and microfluidic technology, serving as powerful platforms for exploring cancer mechanisms and facilitating drug screening. These chips are able to compartmentalize the metastatic cascade, deepening the understanding of its underlying mechanisms. This article provides an overview of current CMoC models, focusing on distinctive models that simulate invasion, intravasation, circulation, extravasation, and colonization, and their applications in drug screening. Furthermore, challenges faced by CMoC and microfluidic technologies are discussed, while exploring promising future directions in cancer research. The ongoing development and integration of these models into cancer studies are expected to drive transformative advancements in the field.

Role of bio-flavonols and their derivatives in improving mitochondrial dysfunctions associated with pancreatic tumorigenesis

Mitochondria, a cellular metabolic center, efficiently fulfill cellular energy needs and regulate crucial metabolic processes, including cellular proliferation, differentiation, apoptosis, and generation of reactive oxygen species. Alteration in the mitochondrial functions leads to metabolic imbalances and altered extracellular matrix dynamics in the host, utilized by solid tumors like pancreatic cancer (PC) to get energy benefits for fast-growing cancer cells. PC is highly heterogeneous and remains unidentified for a longer time because of its complex pathophysiology, retroperitoneal position, and lack of efficient diagnostic approaches, which is the foremost reason for accounting for the seventh leading cause of cancer-related deaths worldwide. PC cells often respond poorly to current therapeutics because of dense stromal barriers in the pancreatic tumor microenvironment, which limit the drug delivery and distribution of antitumor immune cell populations. As an alternative approach, various natural compounds like flavonoids are reported to possess potent antioxidant and anticancerous properties and are less toxic than current chemotherapeutic drugs. Therefore, we aim to summarize the current state of knowledge regarding the pharmacological properties of flavonols in PC in this review from the perspective of mitigating mitochondrial dysfunctions associated with cancer cells. Our literature survey indicates that flavonols efficiently regulate cellular metabolism by scavenging reactive oxygen species, mitigating inflammation, and arresting the cell cycle to promote apoptosis in tumor cells via intrinsic mitochondrial pathways. In particular, flavonols proficiently inhibit the cancer-associated proliferation and inflammatory pathways such as EGFR/MAPK, PI3K/Akt, and nuclear factor κB in PC. Overall, this review provides in-depth evidence about the therapeutic potential of flavonols for future anticancer strategies against PC; still, more multidisciplinary human interventional studies are required to dissect their pharmacological effect accurately.

Identification of prognostic value of anoikis-related gene score model combined with tumor microenvironment score models in esophageal squamous cell carcinoma

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) has poor survival. Effective prognostic models with high application value remain lack.

METHODS

Bulk RNA seq and single cell RNA-seq data were retrieved from the XENA-TCGA-ESCC cohort and GSE188900. The anoikis-related gene score (ANO score) model and tumor microenvironment score (TME score) model were constructed and merged into three subgroups. Functional annotation was analyzed by Gene Ontology terms. Univariate and multivariate Cox regression analysis, least absolute shrinkage and selection operator regression analysis and weighted gene coexpression network analysis were performed to construct prognostic prediction models and identify prognostic value. Kaplan-Meier survival curves were drawn for evaluating the overall survival (OS) of patients classified by different score subgroups. Immunotherapy response and mutation analyses were also conducted.

RESULTS

In the ANO score model, TNFSF10 was an independent factor for the prognosis of ESCC patients. The area under the curve values of the ANO-TME score model in predicting the OS were 0.638 at 5 years and 0.632 at 7 years. Patients in the ANO low score-TME high score group had a much longer OS than patients in any other ANO-TME score subgroup (p < 0.001), suggesting a higher prognostic value. The differentially expressed genes of the ANO low score-TME high score group were mainly involved in cell adhesion molecules, nucleotide excision repair, the TGF-β signaling pathway and mismatch repair. TP53 (92%), TTN (38%) and NFE2L2 (31%) were the top genes with highest mutant frequency in the ANO low score-TME high score group.

CONCLUSIONS

A novel prognostic prediction model with high application value was constructed and identified for ESCC patients, which may provide evidence for immunotherapy in the treatment of ESCC.

Amoxetamide A, a new anoikis inducer, produced by combined-culture of Amycolatopsis sp. and Tsukamurella pulmonis

Cancer cells including colorectal cancer cells are resistant to anoikis, an anchorage-independent programmed death, which enables metastasis and subsequent survival in a new tumor microenvironment. In this study, we identified a new anoikis inducer, amoxetamide A (1) with a β-lactone moiety, that was produced by combined-culture of Amycolatopsis sp. 26-4 and mycolic acid-containing bacteria (MACB) Tsukamurella pulmonis TP-B0596. The structure of 1 including the stereochemistry of C8 was determined by MS and NMR spectroscopy and modified Mosher's method, and the absolute configurations of C11 and C12 were suggested as 11R and 12S, respectively, by GIAO NMR calculations. Amoxetamide A (1) exhibited anoikis-inducing activity in human colorectal cancer HT-29 cells in anchorage-independent culture conditions.

Anoikis-related signature identifies tumor microenvironment landscape and predicts prognosis and drug sensitivity in colorectal cancer

Background: Anoikis, a mechanism of programmed apoptosis, plays an important role in growth and metastasis of tumors. However, there are still few available comprehensive reports on the impact of anoikis on colorectal cancer. Method: A clustering analysis was done on 133 anoikis-related genes in GSE39582, and we compared clinical features between clusters, the tumor microenvironment was analyzed with algorithms such as "Cibersort" and "ssGSEA". We investigated risk scores of clinical feature groups and anoikis-associated gene mutations after creating a predictive model. We incorporated clinical traits to build a nomogram. Additionally, the quantitative real-time PCR was employed to investigate the mRNA expression of selected anoikis-associated genes. Result: We identified two anoikis-related clusters with distinct prognoses, clinical characteristics, and biological functions. One of the clusters was associated with anoikis resistance, which activated multiple pathways encouraging tumor metastasis. In our prognostic model, oxaliplatin may be a sensitive drug for low-risk patients. The nomogram showed good ability to predict survival time. And SIRT3, PIK3CA, ITGA3, DAPK1, and CASP3 increased in CRC group through the PCR assay. Conclusion: Our study identified two distinct modes of anoikis in colorectal cancer, with active metastasis-promoting pathways inducing an anti-anoikis subtype, which has a stronger propensity for metastasis and a worse prognosis than an anoikis-activated subtype. Massive immune cell infiltration may be an indicator of anoikis resistance. Anoikis' role in the colorectal cancer remains to be investigated.

RHOAL57V drives the development of diffuse gastric cancer through IGF1R-PAK1-YAP1 signaling

Cancer-associated mutations in the guanosine triphosphatase (GTPase) RHOA are found at different locations from the mutational hotspots in the structurally and biochemically related RAS. Tyr42-to-Cys (Y42C) and Leu57-to-Val (L57V) substitutions are the two most prevalent RHOA mutations in diffuse gastric cancer (DGC). RHOAY42C exhibits a gain-of-function phenotype and is an oncogenic driver in DGC. Here, we determined how RHOAL57V promotes DGC growth. In mouse gastric organoids with deletion of Cdh1, which encodes the cell adhesion protein E-cadherin, the expression of RHOAL57V, but not of wild-type RHOA, induced an abnormal morphology similar to that of patient-derived DGC organoids. RHOAL57V also exhibited a gain-of-function phenotype and promoted F-actin stress fiber formation and cell migration. RHOAL57V retained interaction with effectors but exhibited impaired RHOA-intrinsic and GAP-catalyzed GTP hydrolysis, which favored formation of the active GTP-bound state. Introduction of missense mutations at KRAS residues analogous to Tyr42 and Leu57 in RHOA did not activate KRAS oncogenic potential, indicating distinct functional effects in otherwise highly related GTPases. Both RHOA mutants stimulated the transcriptional co-activator YAP1 through actin dynamics to promote DGC progression; however, RHOAL57V additionally did so by activating the kinases IGF1R and PAK1, distinct from the FAK-mediated mechanism induced by RHOAY42C. Our results reveal that RHOAL57V and RHOAY42C drive the development of DGC through distinct biochemical and signaling mechanisms.

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.