Anoikis

Rheological transition driven by matrix makes cancer spheroids resilient under confinement

Cancer metastasis through confining peritoneal microenvironments is mediated by spheroids: clusters of disseminated cells. Ovarian cancer spheroids are frequently cavitated; such blastuloid morphologies possess an outer ECM coat. We investigated the effects of these spheroidal morphological traits on their mechanical integrity. Atomic force microscopy showed blastuloids were elastic compared with their prefiguring lumenless moruloid counterparts. Moruloids flowed through microfluidic setups mimicking peritoneal confinement, exhibited asymmetric cell flows during entry, were frequently disintegrated, and showed an incomplete and slow shape recovery upon exit. In contrast, blastuloids exhibited size-uncorrelated transit kinetics, rapid and efficient shape recovery upon exit, symmetric cell flows, and lesser disintegration. Blastuloid ECM debridement phenocopied moruloid traits including lumen loss and greater disintegration. Multiscale computer simulations predicted that higher intercellular adhesion and dynamical lumen make blastuloids resilient. Blastuloids showed higher E-cadherin expression, and their ECM removal decreased membrane E-cadherin localization. E-cadherin knockdown also decreased lumen formation and increased spheroid disintegration. Thus, the spheroidal ECM drives its transition from a labile viscoplastic to a resilient elastic phenotype, facilitating their survival within spatially constrained peritoneal flows.

Redox regulation of focal adhesions

Focal adhesions (FAs), multi-protein complexes that link the extracellular matrix to the intracellular cytoskeleton, are key mediators of cell adhesion, migration, and proliferation. These dynamic structures act as mechanical sensors, transmitting stimuli from the extracellular to intracellular environment activating in this way signaling pathways and enabling cells to adapt to environmental changes. As such, FAs are critical for tissue organization and serve as hubs governing cell spatial arrangement within the organism. The assembly, reactivity, and functional regulation of FAs are tightly controlled by post-translational modifications, including redox modulation by reactive oxygen and nitrogen species. Increasing evidence suggests that redox signaling plays a pivotal role in both the physiological and pathological functions of FAs and their downstream processes. Redox regulation affects various components of the FA complex, including integrins, focal adhesion kinase 1 (FAK1), SRC, adapter proteins, and cytoskeletal elements. In this review, we provide an updated overview of the complex interplay between redox signaling and post-translational modifications in FAs. We explore how redox reactions influence the structure, dynamics, and function of FAs, shedding light on their broader implications in health and disease.

Free fatty acids derived from lipophagy enhanced resistance to anoikis by activating Src in high-invasive clear cell renal cell carcinoma cells

Autophagy-mediated anoikis resistance plays a critical role in the initiation of tumor metastasis. Therefore, we investigated the role and mechanism of anoikis resistance mediated by free fatty acids (FFAs) derived from lipophagy in highly invasive clear cell renal cell carcinoma (ccRCC). Here, we found that the highly invasive ccRCC cell line Himi exhibited enhanced resistance to anoikis and elevated lipophagy levels. The increased lipophagy observed in Himi ccRCC cells contributed to their resistance to anoikis. The nonreceptor tyrosine kinase Src was significantly upregulated in Himi cells cultured under suspension conditions and in patients with poor prognoses. The underlying mechanism revealed that the FFAs released from lipophagy activated the phosphorylated Tyr419 site of Src, thereby promoting ccRCC invasion, facilitating epithelial-mesenchymal transition (EMT), enhancing angiogenesis, and conferring resistance to anoikis. Therefore, the present study revealed that FFAs generated from the degradation of lipid droplets via lipophagy enhanced resistance to anoikis by activating the phosphorylated Tyr419 site of Src in highly invasive ccRCC.

Suppression of Dad1 induces cardiomyocyte death by weakening cell adhesion

As cardiomyocyte loss causes heart failure, inhibition of cardiomyocyte death may be a therapeutic strategy against heart failure. In this study, we have identified defender against cell death 1 (Dad1) as a candidate regulator of cardiomyocyte death, using complementary DNA microarray and siRNA knockdown screening. Dad1 is a subunit of oligosaccharyltransferase (OST) complex that is responsible for protein N-glycosylation; however, its function in cardiomyocytes remains unknown. Importantly, the knockdown of Dad1 using siRNA reduced the viability of neonatal rat cardiomyocytes (NRCMs), accompanied by cleaved caspase3 expression, independent of endoplasmic reticulum stress. Dad1 knockdown impaired cell spreading and reduced myofibrillogenesis in NRCMs, suggesting that Dad1 knockdown induced anoikis, apoptosis by disrupting cell-matrix interactions. Consistently, knockdown of Dad1 impaired N-glycosylation of integrins α5 and β1, accompanied by inactivation of focal adhesion kinase. When cell adhesion was enhanced using adhesamine, fibronectin, or collagen type IV, cardiomyocyte death induced by Dad1 knockdown was reduced. Dad1 knockdown decreased the expression of staurosporine and temperature-sensitive 3 A (Stt3A), a catalytic subunit of OST complex. Interestingly, Stt3A knockdown using Stt3A siRNA reduced the expression of Dad1, indicating that both Dad1 and Stt3A were required for OST stabilization. In conclusion, Dad1 plays an important role in maintaining the expression of mature N-glycosylated integrins and their downstream signaling molecules to suppress cardiomyocyte anoikis.NEW & NOTEWORTHY This study found for the first time that the knockdown of Dad1 induced cardiomyocyte death, accompanied by impairment of myofibrillogenesis and cell spreading. Dad1 regulates the N-glycosylation of integrins in cooperation with Stt3A and preserves cell adhesion activity, promoting cardiomyocyte survival. This is the first demonstration that Dad1 contributes to the maintenance of cardiac homeostasis through the posttranslational modification of integrins, providing a novel insight into the biological significance of OST complex in cardiomyocytes.

T cell population size control by coronin 1 uncovered: from a spot identified by two-dimensional gel electrophoresis to quantitative proteomics

INTRODUCTION

Recent work identified members of the evolutionarily conserved coronin protein family as key regulators of cell population size. This work originated ~25 years ago through the identification, by two-dimensional gel electrophoresis, of coronin 1 as a host protein involved in the virulence of Mycobacterium tuberculosis. We here describe the journey from a spot on a 2D gel to the recent realization that coronin proteins represent key controllers of eukaryotic cell population sizes, using ever more sophisticated proteomic techniques.

AREAS COVERED

We discuss the value of 'old school' proteomics using relatively simple and cost-effective technologies that allowed to gain insights into subcellular proteomes and describe how label-free quantitative (phospho)proteomics using mass spectrometry allowed to disentangle the role for coronin 1 in eukaryotic cell population size control. Finally, we mention potential implications of coronin-mediated cell population size control for health and disease.

EXPERT OPINION

Proteome analysis has been revolutionized by the advent of modern-day mass spectrometers and is indispensable for a better understanding of biology. Here, we discuss how careful dissection of physio-pathological processes by a combination of proteomics, genomics, biochemistry and cell biology may allow to zoom in on the unexplored, thereby possibly tackling hitherto unasked questions and defining novel mechanisms.

Generating suspension-adapted human mesenchymal stromal cells (S-hMSCs) for the scalable manufacture of extracellular vesicles

BACKGROUD

Human mesenchymal stromal cells (hMSCs) are a naturally adherent cell type and one of the most studied cellular agents used in cell therapy over the last 20 years. Their mechanism of action has been primarily associated with paracrine signaling, which has contributed to an increase in the number of studies focused on hMSC-related extracellular vesicles (EVs).

METHODS

In this study, we demonstrate for the first time that human telomerase reverse transcriptase (hTERT) immortalized hMSCs can be adapted to suspension culture, eliminating the need for microcarriers or other matrixes to support cell growth.

RESULTS

This novel cell line, named suspension hMSCs (S-hMSCs), has a doubling time of approximately 55 hours, with a growth rate of 0.423/d. Regarding its immunophenotype characteristics, S-hMSCs retained close to 90% of CD73 and CD105 expression levels, with the CD90 receptor being downregulated during the adherent to suspension adaptation process. An RNA sequencing analysis showed an upregulation of the transcripts coding for CD44, CD46 and CD47 compared to the expression levels in AT-hMSCs and hTERT-hMSCs. The cell line herein established was able to generate EVs using a chemically defined medium formulation with these nanoparticles averaging 150 nm in size and displaying the markers CD63, CD81, and TSG101, while not expressing the negative marker calnexin.

CONCLUSION

This body of evidence, combined with the visual confirmation of EV presence using transmission electron microscopy, demonstrates the EV-producing capabilities of the novel S-hMSCs. This cell line provides a platform for process development, drug discovery and translational studies in the EV field.

Establishment and validation of the prognostic risk model based on the anoikis-related genes in esophageal squamous cell carcinoma

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is a malignant condition in humans. Anoikis-related genes (ARGs) are crucial to cancer progression. Therefore, more studies on the relationship between ARGs and ESCC are warranted.

METHODS

The study acquired ESCC-related transcriptome data from TCGA. Differentially expressed ARGs (DE-ARGs) were obtained by differential analysis and candidates were filtered out by survival analysis. Prognostic genes were determined by Cox and LASSO regression. A risk model was constructed based on prognostic gene expressions. An immune infiltration study was done to explain how these genes contribute to ESCC development. The IC50 test was adopted to assess the clinical response of chemotherapy drugs. Single cell analysis was performed on the GSE145370 dataset. Moreover, the prognostic gene expressions were detected by qRT-PCR.

RESULTS

53 DE-ARGs were screened and four candidate genes including PBK, LAMC2, TNFSF10 and KL were obtained. Cox and LASSO regression identified the two prognostic genes, TNFSF10 and PBK. Immuno-infiltration analysis revealed positive associations of PBK with Macrophages M0 cells, and TNFSF10 with Macrophages M1 cells. The IC50 values of predicted drugs, in the case of Tozasertib 1096 and WIKI4 1940, were significantly variant between risk groups. Single cell analysis revealed that TNFSF10 and PBK levels were higher in epithelial cells than in other cells. The prognostic genes expression results by qRT-PCR were compatible with the dataset analysis.

CONCLUSION

The study established an ARG prognosis model of ESCC. It provided a reference for the research of ARGs in ESCC.

Identification of key biomarkers related to fibrocartilage chondrocytes for osteoarthritis based on bulk, single-cell transcriptomic data

Introduction

Osteoarthritis (OA) is a prevalent joint disease that severely impacts patients' quality of life. Due to its unclear pathogenesis and lack of effective therapeutic targets, discovering new biomarkers for OA is essential. Recently, the role of chondrocyte subpopulations in OA progression has gained significant attention, offering potential insights into the disease. This study aimed to explore the role of fibrocartilage chondrocytes (FC) in the progression of OA and identify key biomarkers related to FC.

Methods

We analyzed single-cell ribonucleic acid sequencing (scRNA-seq) data from samples of OA and normal cartilage, focusing on FC. Microarray data were integrated to identify differentially expressed genes (DEGs). We conducted functional-enrichment analyses, including Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO), and used weighted gene co-expression network analysis (WGCNA) and the least absolute shrinkage and selection operator (LASSO) algorithm to select biomarkers. A novel risk model for OA was constructed using these biomarkers. We then built a transcription factor (TF)-gene interaction network and performed immunohistochemistry (IHC) to validate protein expression levels of these biomarkers in cartilage samples.

Results

The study identified 545 marker genes associated with FC in OA. GO and KEGG analyses revealed their biological functions; microarray analysis identified 243 DEGs on which functional-enrichment analysis were conducted. Using WGCNA and LASSO, we identified six hub genes, on the basis of which we constructed a risk model for OA. In addition, correlation analysis revealed a close association between Forkhead Box (FoxO)-mediated transcription and these these biomarkers. IHC showed significantly lower protein levels of ABCA5, ABCA6 and SLC7A8 in OA samples than in normal samples.

Conclusion

This study used a multi-omics approach to identify six FC-related OA biomarkers (BCL6, ABCA5, ABCA6, CITED2, NR1D1, and SLC7A8) and developed an exploratory risk model. Functional enrichment analysis revealed that the FoxO pathway may be linked to these markers, particularly implicating ABCA5 and ABCA6 in cholesterol homeostasis within chondrocytes. These findings highlight ABCA family members as novel contributors to OA pathogenesis and suggest new therapeutic targets.

A comprehensive genome-based analysis identifies the anti-cancerous role of the anoikis-related gene ADH1A in modulating the pathogenesis of breast cancer

Breast cancer (BC), a widespread and lethal neoplasm, is irrespective of the subtype of BC. Metastasis remains a crucial determinant for unfavorable outcome. The identification of novel diagnostic markers is instrumental in optimizing the treatment regime for BC. The direct correlation between anoikis and the progression/outcome of BC is well established. Nevertheless, the contribution of anoikis-related genes (ARGs) in BC remains obscure at present. We implemented the METABRIC dataset to scrutinize and assess differentially expressed ARGs in BC versus healthy breast tissues. An unsupervised consensus clustering approach for ARGs was employed to classify patients into diverse subtypes. ESTIMATE algorithms were utilized to assess immune infiltrative patterns. Prognostic gene expression patterns were derived from LASSO regression and univariate COX regression analysis. Subsequently, these signatures underwent examination via use of the Kaplan-Meier survival curve. 6 pairs of fresh tissue specimens (tumor and adjacent non-tumor) were employed to assess the expression of 7 ARGs genes via qPCR. Notably, DCN and FOS were not expressed in BC tissue, which had been excluded in our subsequent experiments. Also, among remaining 5 ARGs, solely the expression of ADH1A demonstrated a statistically remarkable disparity between freshly collected cancer tissues and the adjacent ones. ADH1A-overexpressed and ADH1A-sh vectors were transfected into MCF-7 and MCF-7-AR cell lines, respectively. The expression status of FABP4, CALML5, ADH1A, C1orf106, CIDEC, β-catenin, N-cadherin, and Vimentin in the clinical samples were scrutinized using RT-qPCR and western blotting techniques. Migration and invasion through transwell chambers were employed to assess the migratory and invasive potential of the cells. Detailed evaluation of cell proliferation was conducted utilizing a Cell Counting Kit-8 (CCK-8) assay. The apoptotic index of the cells was determined by flow cytometry analysis. An innovative anoikis-associated signature consisting of seven genes, namely ADH1A, DCN, CIEDC, FABP4, FOS, CALML5, and C1orf106, was devised to stratify BC patients into high- and low-risk cohorts. This unique risk assessment model, formulated via the distinctive signature approach, has been validated as an independent prognostic indicator. Additional analysis demonstrated that distinct risk subtypes manifested variances in the tumor microenvironment and drug sensitivities. Suppression of ADH1A enhanced the migratory and invasive capacities and reduced these tumorigenesis-related protein levels, underscoring the prognostic role of ADH1A in the progression of BC. Through our meticulous study, we have elucidated the possible molecular markers and clinical implications of ARGs in BC. Our model, which incorporate seven ARGs, has proven to accurately forecast the survival outcomes of BC patients. Moreover, the thorough molecular study of ADH1A has augmented our comprehension of ARGs in BC and opened a novel avenue for guiding personalized and precise therapeutic interventions for BC patients.

Targeting a key FAK-tor: the therapeutic potential of combining focal adhesion kinase (FAK) inhibitors and chemotherapy for chemoresistant non-small cell lung cancer

INTRODUCTION

NSCLC is the leading cause of cancer-related deaths globally, with a low survival rate primarily due to NSCLC frequently becoming chemoresistant. Focal adhesion kinase (FAK) is a non-receptor tyrosine kinase involved in pathways regulating multiple processes in the cell, including survival, migration, and the TME, that contribute to both tumor progression and drug resistance. Recently, FAK inhibitors (FAKi) have shown promising potential for the treatment of NSCLC.

AREAS COVERED

This narrative review aims to summarize key signaling pathways involving FAK that contribute to tumor progression and drug resistance. It will further provide an overview of FAKi currently in pre- and early-phase clinical trials for solid tumors, as well as the therapeutic potential of combining FAKi with chemotherapy, as this has emerged as a promising strategy to overcome chemoresistance in NSCLC.

EXPERT OPINION

It is becoming increasingly clear that FAK is not an oncogenic driver but rather contributes to tumor progression and drug resistance. Hence, while FAKi have only demonstrated modest results in clinical trials when given by themselves, treatment regimens combining other therapies with FAKi have shown promising potential to overcome drug resistance. Lastly, of particular novelty are FAK-PROTACs (proteolysis-targeting chimaeras), which uniquely target both cytosolic and nuclear FAK.

Identification of Anoikis-Related Genes in Spinal Cord Injury: Bioinformatics and Experimental Validation

Spinal cord injury (SCI) is a serious disease without effective therapeutic strategies. To identify the potential treatments for SCI, it is extremely important to explore the underlying mechanism. Current studies demonstrate that anoikis might play an important role in SCI. In this study, we aimed to identify the key anoikis-related genes (ARGs) providing therapeutic targets for SCI. The mRNA expression matrix of GSE45006 was downloaded from the Gene Expression Omnibus (GEO) database, and the ARGs were downloaded from the Molecular Signatures Database (MSigDB database). Then, the potential differentially expressed ARGs were identified. Next, correlation analysis, gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) analysis were employed for the differentially expressed ARGs. Moreover, miRNA-gene networks were constructed by the hub ARGs. Finally, RNA expression of the top ten hub ARGs was validated in the SCI cell model and rat SCI model. A total of 27 common differentially expressed ARGs were identified at different time points (1, 3, 7, and 14 days) following SCI. The GO and KEGG enrichment analysis of these ARGs indicated several enriched terms related to proliferation, cell cycle, and apoptotic process. The PPI results revealed that most of the ARGs interacted with each other. Ten hub ARGs were further screened, and all the 10 genes were validated in the SCI cell model. In the rat model, only seven genes were validated eventually. We identified 27 differentially expressed ARGs of the SCI through bioinformatic analysis. Seven real hub ARGs (CCND1, FN1, IGF1, MYC, STAT3, TGFB1, and TP53) were identified eventually. These results may expand our understanding of SCI and contribute to the exploration of potential SCI targets.

Unveiling an anoikis-related risk model and the role of RAD9A in colon cancer

OBJECTIVE

Colorectal cancer (CRC), specifically colon adenocarcinoma, is the third most prevalent and the second most lethal form of cancer. Anoikis is found to be specialized form of programmed cell death (PCD), which plays a pivotal role in tumor progression. This study aimed to investigate the role of the anoikis related genes (ARGs) in colon cancer.

METHODS

Consensus unsupervised clustering, differential expression analysis, tumor mutational burden analysis, and analysis of immune cell infiltration were utilized in the study. For the analysis of RNA sequences and clinical data of COAD patients, data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were obtained. A prognostic scoring system for overall survival (OS) prediction was developed using Cox regression and LASSO regression analysis. Furthermore, loss-of-function assay was utilized to explore the role of RAD9A played in the progression of colon cancer.

RESULTS

The prognostic value of a risk score composed of NTRK2, EPHA2, RAD9A, CDC25C, and SNAI1 genes was significant. Furthermore, these findings suggested potential mechanisms that may influence prognosis, supporting the development of individualized treatment plans and management of patient outcomes. Further experiments confirmed that RAD9A could promote proliferation and metastasis of colon cancer cells. These effects may be achieved by affecting the phosphorylation of AKT.

CONCLUSION

Differences in survival time and the tumor immune microenvironment (TIME) were observed between two gene clusters associated with ARGs. In addition, a prognostic risk model was established and confirmed as an independent risk factor. Furthermore, our data indicated that RAD9A promoted tumorigenicityby activating AKT in colon cancer.

Anoikis in cell fate, physiopathology, and therapeutic interventions

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

The oncogenic ADAMTS1-VCAN-EGFR cyclic axis drives anoikis resistance and invasion in renal cell carcinoma

BACKGROUND

Metastasis, the leading cause of renal cell carcinoma (RCC) mortality, involves cancer cells resisting anoikis and invading. Until now, the role of the matrix metalloproteinase (MMP)-related enzyme, A disintegrin and metalloprotease with thrombospondin motifs 1 (ADAMTS1), in RCC anoikis regulation remains unclear.

METHODS

The clinical significance of ADAMTS1 and its associated molecules in patients with RCC was investigated using data from the Gene Expression Omnibus (GEO) and TCGA datasets. Human phosphoreceptor tyrosine kinase (RTK) array, luciferase reporter assays, immunoprecipitation (IP) assays, western blotting, and real-time reverse-transcription quantitative polymerase chain reaction (RT-qPCR) were used to elucidate the underlying mechanisms of ADAMTS1. Functional assays, including anoikis resistance assays, invasion assays, and a Zebrafish xenotransplantation model, were conducted to assess the roles of ADAMTS1 in conferring resistance to anoikis in RCC.

RESULTS

This study found elevated ADAMTS1 transcripts in RCC tissues that were correlated with a poor prognosis. ADAMTS1 manipulation significantly affected cell anoikis through the mitochondrial pathway in RCC cells. Human receptor tyrosine kinase (RTK) array screening identified that epidermal growth factor receptor (EGFR) activation was responsible for ADAMTS1-induced anoikis resistance and invasion. Further investigations revealed that enzymatically active ADAMTS1-induced versican V1 (VCAN V1) proteolysis led to EGFR transactivation, which in turn, through positive feedback, regulated ADAMTS1. Additionally, ADAMTS1 can form a complex with p53 to influence EGFR signaling. In vivo, VCAN or EGFR knockdown reversed ADAMTS1-induced prometastatic characteristics of RCC. A clinical analysis revealed a positive correlation between ADAMTS1 and VCAN or the EGFR and patients with RCC with high ADAMTS1 and VCAN expression had the worst prognoses.

CONCLUSIONS

Our results collectively uncover a novel cyclic axis involving ADAMTS1-VCAN-EGFR, which significantly contributes to RCC invasion and resistance to anoikis, thus presenting a promising therapeutic target for RCC metastasis.

Bioreactor-produced iPSCs-derived dopaminergic neuron-containing neural microtissues innervate and normalize rotational bias in a dose-dependent manner in a Parkinson rat model

A breadth of preclinical studies now support the rationale of pluripotent stem cell-derived cell replacement therapies to alleviate motor symptoms in Parkinsonian patients. Replacement of the primary dysfunctional cell population in the disease, i.e. the A9 dopaminergic neurons, is the major focus of these therapies. To achieve this, most therapeutical approaches involve grafting single-cell suspensions of DA progenitors. However, most cells die during the transplantation process, as cells face anoïkis. One potential solution to address this challenge is to graft solid preparations, i.e. adopting a 3D format. Cryopreserving such a format remains a major hurdle and is not exempt from causing delays in the time to effect, as observed with cryopreserved single-cell DA progenitors. Here, we used a high-throughput cell-encapsulation technology coupled with bioreactors to provide a 3D culture environment enabling the directed differentiation of hiPSCs into neural microtissues. The proper patterning of these neural microtissues into a midbrain identity was confirmed using orthogonal methods, including qPCR, RNAseq, flow cytometry and immunofluorescent microscopy. The efficacy of the neural microtissues was demonstrated in a dose-dependent manner using a Parkinsonian rat model. The survival of the cells was confirmed by post-mortem histological analysis, characterised by the presence of human dopaminergic neurons projecting into the host striatum. The work reported here is the first bioproduction of a cell therapy for Parkinson's disease in a scalable bioreactor, leading to a full behavioural recovery 16 weeks after transplantation using cryopreserved 3D format.

Comprehensive analysis and experimental verification of the mechanism of anoikis related genes in pancreatic cancer

Background

Pancreatic cancer (PC), characterized by its aggressive nature and low patient survival rate, remains a challenging malignancy. Anoikis, a process inhibiting the spread of metastatic cancer cells, is closely linked to cancer progression and metastasis through anoikis-related genes. Nonetheless, the precise mechanism of action of these genes in PC remains unclear.

Methods

Study data were acquired from the Cancer Genome Atlas (TCGA) database, with validation data accessed at the Gene Expression Omnibus (GEO) database. Differential expression analysis and univariate Cox analysis were performed to determine prognostically relevant differentially expressed genes (DEGs) associated with anoikis. Unsupervised cluster analysis was then employed to categorize cancer samples. Subsequently, a least absolute shrinkage and selection operator (LASSO) Cox regression analysis was conducted on the identified DEGs to establish a clinical prognostic gene signature. Using risk scores derived from this signature, patients with cancer were stratified into high-risk and low-risk groups, with further assessment conducted via survival analysis, immune infiltration analysis, and mutation analysis. External validation data were employed to confirm the findings, and Western blot and immunohistochemistry were utilized to validate risk genes for the clinical prognostic gene signature.

Results

A total of 20 prognostic-related DEGs associated with anoikis were obtained. The TCGA dataset revealed two distinct subgroups: cluster 1 and cluster 2. Utilizing the 20 DEGs, a clinical prognostic gene signature comprising two risk genes (CDKN3 and LAMA3) was constructed. Patients with pancreatic adenocarcinoma (PAAD) were classified into high-risk and low-risk groups per their risk scores, with the latter exhibiting a superior survival rate. Statistically significant variation was noted across immune infiltration and mutation levels between the two groups. Validation cohort results were consistent with the initial findings. Additionally, experimental verification confirmed the high expression of CDKN3 and LAMA3 in tumor samples.

Conclusion

Our study addresses the gap in understanding the involvement of genes linked to anoikis in PAAD. The clinical prognostic gene signature developed herein accurately stratifies patients with PAAD, contributing to the advancement of precision medicine for these patients.

mRNA-Lipid Nanoparticle-Mediated Restoration of PTPN14 Exhibits Antitumor Effects by Overcoming Anoikis Resistance in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) poses a challenging prognosis due to early metastasis driven by anoikis resistance. Identifying crucial regulators to overcome this resistance is vital for improving patient outcomes. In this study, a genome-wide CRISPR/Cas9 knockout screen in TNBC cells has identified tyrosine-protein phosphatase nonreceptor type 14 (PTPN14) as a key regulator of anoikis resistance. PTPN14 expression has shown a progressive decrease from normal breast tissue to metastatic tumors. Overexpressing PTPN14 has induced anoikis and inhibited cell proliferation in TNBC cells, while normal human breast cells are unaffected. Mechanistically, PTPN14 is identified as a key factor in dephosphorylating breast cancer antiestrogen resistance 3, a novel substrate, leading to the subsequent inhibition of PI3K/AKT and ERK signaling pathways. Local delivery of in vitro transcribed PTPN14 mRNA encapsulated by lipid nanoparticles in a TNBC mouse model has effectively inhibited tumor growth and metastasis, prolonging survival. The study underscores PTPN14 as a potential therapeutic target for metastatic TNBC, with the therapeutic strategy based on mRNA expression of PTPN14 demonstrating clinical application prospects in alleviating the burden of both primary tumors and metastatic disease.

Granzyme B degrades extracellular matrix and promotes inflammation and choroidal neovascularization

Age-related macular degeneration (AMD) is a common retinal neurodegenerative disease among the elderly. Neovascular AMD (nAMD), a leading cause of AMD-related blindness, involves choroidal neovascularization (CNV), which can be suppressed by anti-angiogenic treatments. However, current CNV treatments do not work in all nAMD patients. Here we investigate a novel target for AMD. Granzyme B (GzmB) is a serine protease that promotes aging, chronic inflammation and vascular permeability through the degradation of the extracellular matrix (ECM) and tight junctions. Extracellular GzmB is increased in retina pigment epithelium (RPE) and mast cells in the choroid of the healthy aging outer retina. It is further increased in donor eyes exhibiting features of nAMD and CNV. Here, we show in RPE-choroidal explant cultures that exogenous GzmB degrades the RPE-choroid ECM, promotes retinal/choroidal inflammation and angiogenesis while diminishing anti-angiogenic factor, thrombospondin-1 (TSP-1). The pharmacological inhibition of either GzmB or mast-cell degranulation significantly reduces choroidal angiogenesis. In line with our in vitro data, GzmB-deficiency reduces the extent of laser-induced CNV lesions and the age-related deterioration of electroretinogram (ERG) responses in mice. These findings suggest that targeting GzmB, a serine protease with no known endogenous inhibitors, may be a potential novel therapeutic approach to suppress CNV in nAMD.

Integrative nomogram model based on anoikis-related genes enhances prognostic evaluation in colorectal cancer

Background

Revealing the role of anoikis resistance plays in CRC is significant for CRC diagnosis and treatment. This study integrated the CRC anoikis-related key genes (CRC-AKGs) and established a novel model for improving the efficiency and accuracy of the prognostic evaluation of CRC.

Methods

CRC-ARGs were screened out by performing differential expression and univariate Cox analysis. CRC-AKGs were obtained through the LASSO machine learning algorithm and the LASSO Risk-Score was constructed to build a nomogram clinical prediction model combined with the clinical predictors. In parallel, this work developed a web-based dynamic nomogram to facilitate the generalization and practical application of our model.

Results

We identified 10 CRC-AKGs and a risk-related prognostic Risk-Score was calculated. Multivariate COX regression analysis indicated that the Risk-Score, TNM stage, and age were independent risk factors that significantly associated with the CRC prognosis(p < 0.05). A prognostic model was built to predict the outcome with satisfied accuracy (3-year AUC = 0.815) for CRC individuals. The web interactive nomogram (https://yuexiaozhang.shinyapps.io/anoikisCRC/) showed strong generalizability of our model. In parallel, a substantial correlation between tumor microenvironment and Risk-Score was discovered in the present work.

Conclusion

This study reveals the potential role of anoikis in CRC and sets new insights into clinical decision-making in colorectal cancer based on both clinical and sequencing data. Also, the interactive tool provides researchers with a user-friendly interface to input relevant clinical variables and obtain personalized risk predictions or prognostic assessments based on our established model.

Lopinavir enhances anoikis by remodeling autophagy in a circRNA-dependent manner

Macroautophagy/autophagy-mediated anoikis resistance is crucial for tumor metastasis. As a key autophagy-related protein, ATG4B has been demonstrated to be a prospective anti-tumor target. However, the existing ATG4B inhibitors are still far from clinical application, especially for tumor metastasis. In this study, we identified a novel circRNA, circSPECC1, that interacted with ATG4B. CircSPECC1 facilitated liquid-liquid phase separation of ATG4B, which boosted the ubiquitination and degradation of ATG4B in gastric cancer (GC) cells. Thus, pharmacological addition of circSPECC1 may serve as an innovative approach to suppress autophagy by targeting ATG4B. Specifically, the circSPECC1 underwent significant m6A modification in GC cells and was subsequently recognized and suppressed by the m6A reader protein ELAVL1/HuR. The activation of the ELAVL1-circSPECC1-ATG4B pathway was demonstrated to mediate anoikis resistance in GC cells. Moreover, we also verified that the above pathway was closely related to metastasis in tissues from GC patients. Furthermore, we determined that the FDA-approved compound lopinavir efficiently enhanced anoikis and prevented metastasis by eliminating repression of ELAVL1 on circSPECC1. In summary, this study provides novel insights into ATG4B-mediated autophagy and introduces a viable clinical inhibitor of autophagy, which may be beneficial for the treatment of GC with metastasis.

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.

Pharmacologically inducing anoikis offers novel therapeutic opportunities in hepatocellular carcinoma

Tumor metastasis occurs in hepatocellular carcinoma (HCC), leading to tumor progression and therapeutic failure. Anoikis is a matrix detachment-induced apoptosis, also known as detachment-induced cell death, and mechanistically prevents tumor cells from escaping their native extracellular matrix to metastasize to new organs. Deciphering the regulators and mechanisms of anoikis in cancer metastasis is urgently needed to treat HCC. Several natural and synthetic products induce anoikis in HCC cells and in vivo models. Here, we first briefly summarize the current understanding of the molecular mechanisms of anoikis regulation and relevant regulators involved in HCC metastasis. Then we discuss the therapeutic potential of pharmacological induction of anoikis as a potential treatment against HCC. Finally, we discuss the key limitations of this therapeutic paradigm and propose possible strategies to overcome them. Cumulatively this review suggests that the pharmacological induction of anoikis can be used a promising therapeutic modality against HCC.

Elucidating prognosis in cervical squamous cell carcinoma and endocervical adenocarcinoma: a novel anoikis-related gene signature model

Background

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) are among the most prevalent gynecologic malignancies globally. The prognosis is abysmal once cervical cancer progresses to lymphatic metastasis. Anoikis, a specialized form of apoptosis induced by loss of cell adhesion to the extracellular matrix, plays a critical role. The prediction model based on anoikis-related genes (ARGs) expression and clinical data could greatly aid clinical decision-making. However, the relationship between ARGs and CESC remains unclear.

Methods

ARGs curated from the GeneCards and Harmonizome portals were instrumental in delineating CESC subtypes and in developing a prognostic framework for patients afflicted with this condition. We further delved into the intricacies of the immune microenvironment and pathway enrichment across the identified subtypes. Finally, our efforts culminated in the creation of an innovative nomogram that integrates ARGs. The utility of this prognostic tool was underscored by Decision Curve Analysis (DCA), which illuminate its prospective benefits in guiding clinical interventions.

Results

In our study, We discerned a set of 17 survival-pertinent, anoikis-related differentially expressed genes (DEGs) in CESC, from which nine were meticulously selected for the construction of prognostic models. The derived prognostic risk score was subsequently validated as an autonomous prognostic determinant. Through comprehensive functional analyses, we observed distinct immune profiles and drug response patterns among divergent prognostic stratifications. Further, we integrated the risk scores with the clinicopathological characteristics of CESC to develop a robust nomogram. DCA corroborated the utility of our model, demonstrating its potential to enhance patient outcomes through tailored clinical treatment strategies.

Conclusion

The predictive signature, encompassing nine pivotal genes, alongside the meticulously constructed nomogram developed in this research, furnishes clinicians with a sophisticated tool for tailoring treatment strategies to individual patients diagnosed with CESC.

An anoikis-related gene signature predicts prognosis, drug sensitivity, and immune microenvironment in cholangiocarcinoma

Background

Cholangiocarcinoma is a malignant invasive biliary tract carcinoma with a poor prognosis. Anoikis-related genes are prognostic features of a variety of cancers. However, the value of prognostication and therapeutic effect of anoikis-related genes in cholangiocarcinoma have not been reported. The aim of this research was developing an ARGs signature associated with cholangiocarcinoma patients.

Methods

We introduced transcriptome data to discover genes that were differentially expressed in cholangiocarcinoma. Subsequently, WGCNA was utilized to screen critical module genes in reference to anoikis. The univariate Cox, Lasso regression and Kaplan-Meier survival were executed to build a prognostic signature. We further performed gene functional enrichment, immune microenvironment and immunotherapy analysis between two risk subgroups. Finally, the pRRophetic algorithm was applied to compare the half inhibitory concentration value of several drugs.

Results

A grand total of 1844 genes with differential expression related to the cholangiocarcinoma patients were identified. Furthermore, we obtained 2678 key module genes related to anoikis. Then, a prognostic signature was developed using the 6 prognostic genes (FXYD2, PCBD1, C1RL, GMNN, LAMA4 and HACL1). Independent prognostic analysis showed that risk score and alcohol could function as separate prognostic variables. We found cetain distinction in the immune microenvironment between the two risk subgroups. Moreover, immunotherapy evaluation showed that the anoikis-related gene signature could be applied as a therapy predictor. Finally, Chemotherapeutic drug sensitivity results showed that the low-risk group responded better to bosutinib, gefitinib, gemcitabine, and paclitaxel, while the high-risk group responded better to axitinib, cisplatin, and imatinib.

Conclusion

The prognostic signature comprised of FXYD2, PCBD1, C1RL, GMNN, LAMA4 and HACL1 based on anoikis-related genes was established, which provided theoretical basis and reference value for the research and treatment of cholangiocarcinoma.

System analysis based on Anoikis-related genes identifies MAPK1 as a novel therapy target for osteosarcoma with neoadjuvant chemotherapy

BACKGROUND

Osteosarcoma (OS) is the most common bone malignant tumor in children, and its prognosis is often poor. Anoikis is a unique mode of cell death.However, the effects of Anoikis in OS remain unexplored.

METHOD

Differential analysis of Anoikis-related genes was performed based on the metastatic and non-metastatic groups. Then LASSO logistic regression and SVM-RFE algorithms were applied to screen out the characteristic genes. Later, Univariate and multivariate Cox regression was conducted to identify prognostic genes and further develop the Anoikis-based risk score. In addition, correlation analysis was performed to analyze the relationship between tumor microenvironment, drug sensitivity, and prognostic models.

RESULTS

We established novel Anoikis-related subgroups and developed a prognostic model based on three Anoikis-related genes (MAPK1, MYC, and EDIL3). The survival and ROC analysis results showed that the prognostic model was reliable. Besides, the results of single-cell sequencing analysis suggested that the three prognostic genes were closely related to immune cell infiltration. Subsequently, aberrant expression of two prognostic genes was identified in osteosarcoma cells. Nilotinib can promote the apoptosis of osteosarcoma cells and down-regulate the expression of MAPK1.

CONCLUSIONS

We developed a novel Anoikis-related risk score model, which can assist clinicians in evaluating the prognosis of osteosarcoma patients in clinical practice. Analysis of the tumor immune microenvironment and chemotherapeutic drug sensitivity can provide necessary insights into subsequent mechanisms. MAPK1 may be a valuable therapeutic target for neoadjuvant chemotherapy in osteosarcoma.

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

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Identification of an anoikis-related gene signature and characterization of immune infiltration in skin cutaneous melanoma

Anoikis is considered strongly associated with a biological procession of tumors. Herein, we utilized anoikis-related genes (ARGs) to predict the prognosis and immunotherapeutic efficacy for skin cutaneous melanoma (SKCM). RNA-seq data were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. After dividing patients into novel subtypes based on the expression of prognostic ARGs, K-M survival was conducted to compare the survival status. Subsequently, differentially expressed ARGs were identified and the predictive model was established. The predictive effects were validated using the areas under the curve about the receiver operating characteristic. Moreover, tumor mutation burden, the enriched functional pathway, immune cells and functions, and the immunotherapeutic response were also analyzed and compared. The distribution of model genes at cell level was visualized by the single-cell seq with tumor immune single-cell hub database. Patients of The Cancer Genome Atlas-SKCM cohort were divided into 2 clusters, the cluster 1 performed a better prognosis. Cluster 2 was more enriched in metabolism-related pathways whereas cluster 1 was more associated with immune pathways. A predictive risk model was established with 6 ARGs, showing the areas under the curves of 1-year, 3-year, and 5-year ROC were 0.715, 0,720, and 0.731, respectively. Moreover, risk score was negatively associated with tumor mutation burden and immune-related pathways enrichment. In addition, patients with high-risk scores performed immunosuppressive status but the decreasing scores enhanced immune cell infiltration, immune function activation, and immunotherapeutic response. In this study, we established a novel signature in predicting prognosis and immunotherapy. It can be considered reliable to formulate the complex treatment for SKCM patients.

Identification and validation of an anoikis-related genes signature for prognostic implication in papillary thyroid cancer

Thyroid cancer, notably papillary thyroid cancer (PTC), is a global health concern with increasing incidence. Anoikis, a regulator of programmed cell death, is pivotal in normal physiology and, when dysregulated, can drive cancer progression and metastasis. This study explored the impact of anoikis on PTC prognosis. Analyzing data from GEO, TCGA, and GeneCards, we identified a prognostic signature consisting of six anoikis-related genes (ARGs): EZH2, PRKCQ, CD36, INHBB, TDGF1, and MMP9. This signature independently predicted patient outcomes, with high-risk scores associated with worse prognoses. A robust predictive ability was confirmed via ROC analysis, and a nomogram achieved a C-index of 0.712. Differences in immune infiltration levels were observed between high- and low-risk groups. Importantly, the high-risk group displayed reduced drug sensitivity and poor responses to immunotherapy. This research provides insights into anoikis in PTC, offering a novel ARG signature for predicting patient prognosis and guiding personalized treatment strategies.

Granzymes in health and diseases: the good, the bad and the ugly

Granzymes are a family of serine proteases, composed of five human members: GA, B, H, M and K. They were first discovered in the 1980s within cytotoxic granules released during NK cell- and T cell-mediated killing. Through their various proteolytic activities, granzymes can trigger different pathways within cells, all of which ultimately lead to the same result, cell death. Over the years, the initial consideration of granzymes as mere cytotoxic mediators has changed due to surprising findings demonstrating their expression in cells other than immune effectors as well as new intracellular and extracellular activities. Additional roles have been identified in the extracellular milieu, following granzyme escape from the immunological synapse or their release by specific cell types. Outside the cell, granzyme activities mediate extracellular matrix alteration via the degradation of matrix proteins or surface receptors. In certain contexts, these processes are essential for tissue homeostasis; in others, excessive matrix degradation and extensive cell death contribute to the onset of chronic diseases, inflammation, and autoimmunity. Here, we provide an overview of both the physiological and pathological roles of granzymes, highlighting their utility while also recognizing how their unregulated presence can trigger the development and/or worsening of diseases.

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

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

Develop a Novel Signature to Predict the Survival and Affect the Immune Microenvironment of Osteosarcoma Patients: Anoikis-Related Genes

Objective

Osteosarcoma (OS) represents a prevalent primary bone neoplasm predominantly affecting the pediatric and adolescent populations, presenting a considerable challenge to human health. The objective of this investigation is to develop a prognostic model centered on anoikis-related genes (ARGs), with the aim of accurately forecasting the survival outcomes of individuals diagnosed with OS and offering insights into modulating the immune microenvironment.

Methods

The study's training cohort comprised 86 OS patients sourced from The Cancer Genome Atlas database, while the validation cohort consisted of 53 OS patients extracted from the Gene Expression Omnibus database. Differential analysis utilized the GSE33382 dataset, encompassing three normal samples and 84 OS samples. Subsequently, the study executed gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses. Identification of differentially expressed ARGs associated with OS prognosis was carried out through univariate COX regression analysis, followed by LASSO regression analysis to mitigate overfitting risks and construct a robust prognostic model. Model accuracy was assessed via risk curves, survival curves, receiver operating characteristic curves, independent prognostic analysis, principal component analysis, and t-distributed stochastic neighbor embedding (t-SNE) analysis. Additionally, a nomogram model was devised, exhibiting promising potential in predicting OS patient prognosis. Further investigations incorporated gene set enrichment analysis to delineate active pathways in high- and low-risk groups. Furthermore, the impact of the risk prognostic model on the immune microenvironment of OS was evaluated through tumor microenvironment analysis, single-sample gene set enrichment analysis (ssGSEA), and immune infiltration cell correlation analysis. Drug sensitivity analysis was conducted to identify potentially effective drugs for OS treatment. Ultimately, the verification of the implicated ARGs in the model construction was conducted through the utilization of real-time quantitative polymerase chain reaction (RT-qPCR).

Results

The ARGs risk prognostic model was developed, comprising seven high-risk ARGs (CBS, MYC, MMP3, CD36, SCD, COL13A1, and HSP90B1) and four low-risk ARGs (VASH1, TNFRSF1A, PIP5K1C, and CTNNBIP1). This prognostic model demonstrates a robust capability in predicting overall survival among patients. Analysis of immune correlations revealed that the high-risk group exhibited lower immune scores compared to the low-risk group within our prognostic model. Specifically, CD8+ T cells, neutrophils, and tumor-infiltrating lymphocytes were notably downregulated in the high-risk group, alongside significant downregulation of checkpoint and T cell coinhibition mechanisms. Additionally, three immune checkpoint-related genes (CD200R1, HAVCR2, and LAIR1) displayed significant differences between the high- and low-risk groups. The utilization of a nomogram model demonstrated significant efficacy in prognosticating the outcomes of OS patients. Furthermore, tumor metastasis emerged as an independent prognostic factor, suggesting a potential association between ARGs and OS metastasis. Notably, our study identified eight drugs-Bortezomib, Midostaurin, CHIR.99021, JNK.Inhibitor.VIII, Lenalidomide, Sunitinib, GDC0941, and GW.441756-as exhibiting sensitivity toward OS. The RT-qPCR findings indicate diminished expression levels of CBS, MYC, MMP3, and PIP5K1C within the context of OS. Conversely, elevated expression levels were observed for CD36, SCD, COL13A1, HSP90B1, VASH1, and CTNNBIP1 in OS.

Conclusion

The outcomes of this investigation present an opportunity to predict the survival outcomes among individuals diagnosed with OS. Furthermore, these findings hold promise for progressing research endeavors focused on prognostic evaluation and therapeutic interventions pertaining to this particular ailment.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Identification and clinical validation of the role of anoikis-related genes in diabetic foot

This study aims to investigate the role of anoikis-related genes in diabetic foot (DF) by utilizing bioinformatics analysis to identify key genes associated with anoikis in DF. We selected the GEO datasets GSE7014, GSE80178 and GSE68183 for the extraction and analysis of differentially expressed anoikis-related genes (DE-ARGs). GO analysis and KEGG analysis indicated that DE-ARGs in DF were primarily enriched in apoptosis, positive regulation of MAPK cascade, anoikis, focal adhesion and the PI3K-Akt signalling pathway. Based on the LASSO and SVM-RFE algorithms, we identified six characteristic genes. ROC curve analysis revealed that these six characteristic genes had an area under the curve (AUC) greater than 0.7, indicating good diagnostic efficacy. Expression analysis in the validation set revealed downregulation of CALR in DF, consistent with the training set results. GSEA results demonstrated that CALR was mainly enriched in blood vessel morphogenesis, endothelial cell migration, ECM-receptor interaction and focal adhesion. The HPA database revealed that CALR was moderately enriched in endothelial cells, and CALR was found to interact with 63 protein-coding genes. Functional analysis with DAVID suggested that CALR and associated genes were enriched in the phagosome component. CALR shows promise as a potential marker for the development and treatment of DF.

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.

Intraepithelial lymphocytes are associated with epithelial injury in feline intestinal T-cell lymphoma

Our previous study indicated that cytotoxicity of intraepithelial lymphocytes is a poor prognostic factor in feline intestinal T-cell lymphoma (FITL), but the effect of cytotoxic lymphocytes on mucosal epithelium is still unknown. Thus, we investigated the association between cytotoxic lymphocytes and mucosal epithelium in 71 cases of feline intestinal T-cell lymphoma (FITL): epithelial injury, basement membrane injury, cleaved-caspase-3 positivity of epithelial cells, and the number and Ki67 positivity of intraepithelial lymphocytes in granzyme B (GRB)+ and GRB- FITLs were evaluated. Epithelial injury score and the number of intraepithelial lymphocytes in granzyme B (GRB)+ FITL were significantly higher than those of GRB- FITL (P<0.05, P<0.05), but no significant differences were found in the basement membrane injury score, the percentage of cleaved-caspase-3+ epithelial cells, and the percentage of Ki67+ intraepithelial lymphocytes. There was a significant correlation between the epithelial injury score and the number of intraepithelial lymphocytes (P<0.05), but no significant correlation was observed between the epithelial injury score and Ki67+ percentage of intraepithelial lymphocytes. Because epithelial cell cleaved-caspase-3 positivity was observed in FITL, regardless of GRB expression in lymphocytes, GRB-mediated apoptosis may not contribute to epithelial injury in FITL. The association between increased number of intraepithelial lymphocytes and epithelial injury suggests that intraepithelial lymphocytes infiltration may contribute to epithelial injury in FITL.

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.

Identifying the programmed cell death index of hepatocellular carcinoma for prognosis and therapy response improvement by machine learning: a bioinformatics analysis and experimental validation

Background

Despite advancements in hepatocellular carcinoma (HCC) treatments, the prognosis for patients remains suboptimal. Cumulative evidence suggests that programmed cell death (PCD) exerts crucial functions in HCC. PCD-related genes are potential predictors for prognosis and therapeutic responses.

Methods

A systematic analysis of 14 PCD modes was conducted to determine the correlation between PCD and HCC. A novel machine learning-based integrative framework was utilized to construct the PCD Index (PCDI) for prognosis and therapeutic response prediction. A comprehensive analysis of PCDI genes was performed, leveraging data including single-cell sequencing and proteomics. GBA was selected, and its functions were investigated in HCC cell lines by in vitro experiments.

Results

Two PCD clusters with different clinical and biological characteristics were identified in HCC. With the computational framework, the PCDI was constructed, demonstrating superior prognostic predictive efficacy and surpassing previously published prognostic models. An efficient clinical nomogram based on PCDI and clinicopathological factors was then developed. PCDI was intimately associated with immunological attributes, and PCDI could efficaciously predict immunotherapy response. Additionally, the PCDI could predict the chemotherapy sensitivity of HCC patients. A multilevel panorama of PCDI genes confirmed its stability and credibility. Finally, the knockdown of GBA could suppress both the proliferative and invasive capacities of HCC cells.

Conclusion

This study systematically elucidated the association between PCD and HCC. A robust PCDI was constructed for prognosis and therapy response prediction, which would facilitate clinical management and personalized therapy for HCC.

Loss of NR5A1 in mouse Sertoli cells after sex determination changes cellular identity and induces cell death by anoikis

To investigate the role of the nuclear receptor NR5A1 in the testis after sex determination, we analyzed mice lacking NR5A1 in Sertoli cells (SCs) from embryonic day (E) 13.5 onwards. Ablation of Nr5a1 impaired the expression of genes characteristic of SC identity (e.g. Sox9 and Amh), caused SC death from E14.5 onwards through a Trp53-independent mechanism related to anoikis, and induced disorganization of the testis cords. Together, these effects caused germ cells to enter meiosis and die. Single-cell RNA-sequencing experiments revealed that NR5A1-deficient SCs changed their molecular identity: some acquired a 'pre-granulosa-like' cell identity, whereas other reverted to a 'supporting progenitor-like' cell identity, most of them being 'intersex' because they expressed both testicular and ovarian genes. Fetal Leydig cells (LCs) did not display significant changes, indicating that SCs are not required beyond E14.5 for their emergence or maintenance. In contrast, adult LCs were absent from postnatal testes. In addition, adult mutant males displayed persistence of Müllerian duct derivatives, decreased anogenital distance and reduced penis length, which could be explained by the loss of AMH and testosterone synthesis due to SC failure.

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.

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

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

A promising anoikis-related prognostic signature predicts prognosis of skin cutaneous melanoma

BACKGROUND

Skin cutaneous melanoma (SKCM) is a highly aggressive disease with a poor prognosis for advanced tumors. Anoikis is a caspase-dependent cell death process triggered by extracellular matrix (ECM) detachment, rectifies detachment-induced metabolic defects that compromise cell survival, recent study revealed the crucial role of anoikis for cancer cells to survive during metastasis. However, limited research focused on the role of anoikis in SKCM.

METHODS

Our study utilized the 27 anoikis-related genes (ARGs) to divide SKCM patients into two clusters, and obtain differentially expressed genes (DEGs) for each cluster. These DEGs were used in stepwise Cox regression analysis to develop a prediction model for SKCM patients consisting of nine ARGs, called the anoikis-related signature (ARS). Subsequently, we used the risk scores calculated from the ARS to divide SKCM patients into two groups and explored differences in immune microenvironment, immune checkpoint reactivity, and drug sensitivity between the groups.

RESULTS

Nine ARGs were identified to stratify SKCM patients into two risk groups, patients in the high-risk group had a poor prognosis and suppressed immune cell infiltration. Moreover, higher expression of immune checkpoint molecules and a greater sensitivity to immunotherapy and chemotherapy drugs were observed in the low-risk group. Finally, all of the ARS hub genes were found to be upregulated in SKCM tissues and cell lines.

CONCLUSION

A novel ARGs signature was identified for predicting the prognosis of SKCM. Based on the immune landscape associated with ARS discovered in our study, targeting ARS hub genes may be a promising treatment for SKCM.

Construction of an anoikis‒related prognostic signature to predict immunotherapeutic response and prognosis in hepatocellular carcinoma

PURPOSE

Anoikis resistance is an important inducer of tumor metastasis. The role of anoikis-related genes (ARGs) in hepatocellular carcinoma (HCC) remains unclear.

METHODS

A list of ARGs was obtained and regression analysis was employed to assemble an anoikis-related prognostic signature and risk score formula from mRNA data and clinical prognostic data downloaded from The Cancer Genome Atlas database. Quantitative real-time PCR (qRT-PCR) was performed on clinical samples to validate the selected ARGs expressions. Kaplan‒Meier curves, ROC curves, and Cox regression analyses were used to demonstrated the prognostic value of this signature. Biological functional enrichment analysis and immune infiltration analysis were utilized to analyze the differences in potential biological functions, immune cell infiltration, immune functions, and immunotherapeutic responses.

RESULTS

A prognostic signature based on 6 ARGs and corresponding prognostic nomogram were established. Our qRT-PCR results showed a higher expression of 6 ARGs in HCC tissues (p value < 0.05). Kaplan‒Meier curves, ROC curves, and Cox regression analyses demonstrated good prognostic value of the signature in HCC (p value < 0.05). Significant differences between the enriched biological functions and immune landscapes of patients in different risk groups were discovered (p value < 0.05). In addition, patients with higher risk scores possibly had poor therapeutic response to transhepatic arterial chemotherapy and embolization or sorafenib, but their responses to immunotherapy might be more effective.

CONCLUSION

A successful anoikis-related prognostic signature and corresponding clinical nomogram were established, which might facilitate better predictions of prognosis and therapeutic responses for HCC patients.

Identification of immunological characterization and Anoikis-related molecular clusters in rheumatoid arthritis

Objective: To investigate the potential association between Anoikis-related genes, which are responsible for preventing abnormal cellular proliferation, and rheumatoid arthritis (RA). Methods: Datasets GSE89408, GSE198520, and GSE97165 were obtained from the GEO with 282 RA patients and 28 healthy controls. We performed differential analysis of all genes and HLA genes. We performed a protein-protein interaction network analysis and identified hub genes based on STRING and cytoscape. Consistent clustering was performed with subgrouping of the disease. SsGSEA were used to calculate immune cell infiltration. Spearman's correlation analysis was employed to identify correlations. Enrichment scores of the GO and KEGG were calculated with the ssGSEA algorithm. The WGCNA and the DGIdb database were used to mine hub genes' interactions with drugs. Results: There were 26 differentially expressed Anoikis-related genes (FDR = 0.05, log2FC = 1) and HLA genes exhibited differential expression (P < 0.05) between the disease and control groups. Protein-protein interaction was observed among differentially expressed genes, and the correlation between PIM2 and RAC2 was found to be the highest; There were significant differences in the degree of immune cell infiltration between most of the immune cell types in the disease group and normal controls (P < 0.05). Anoikis-related genes were highly correlated with HLA genes. Based on the expression of Anoikis-related genes, RA patients were divided into two disease subtypes (cluster1 and cluster2). There were 59 differentially expressed Anoikis-related genes found, which exhibited significant differences in functional enrichment, immune cell infiltration degree, and HLA gene expression (P < 0.05). Cluster2 had significantly higher levels in all aspects than cluster1 did. The co-expression network analysis showed that cluster1 had 51 hub differentially expressed genes and cluster2 had 72 hub differentially expressed genes. Among them, three hub genes of cluster1 were interconnected with 187 drugs, and five hub genes of cluster2 were interconnected with 57 drugs. Conclusion: Our study identified a link between Anoikis-related genes and RA, and two distinct subtypes of RA were determined based on Anoikis-related gene expression. Notably, cluster2 may represent a more severe state of RA.

Self-Renewal Inhibition in Breast Cancer Stem Cells: Moonlight Role of PEDF in Breast Cancer

Breast cancer is the leading cause of death among females in developed countries. Although the implementation of screening tests and the development of new therapies have increased the probability of remission, relapse rates remain high. Numerous studies have indicated the connection between cancer-initiating cells and slow cellular cycle cells, identified by their capacity to retain long labeling (LT+). In this study, we perform new assays showing how stem cell self-renewal modulating proteins, such as PEDF, can modify the properties, percentage of biomarker-expressing cells, and carcinogenicity of cancer stem cells. The PEDF signaling pathway could be a useful tool for controlling cancer stem cells' self-renewal and therefore control patient relapse, as PEDF enhances resistance in breast cancer patient cells' in vitro culture. We have designed a peptide consisting of the C-terminal part of this protein, which acts by blocking endogenous PEDF in cell culture assays. We demonstrate that it is possible to interfere with the self-renewal capacity of cancer stem cells, induce anoikis in vivo, and reduce resistance against docetaxel treatment in cancer patient cells in in vitro culture. We have also demonstrated that this modified PEDF protein produces a significant decrease in the percentage of expressed cancer stem cell markers.

An anoikis-related lncRNA signature is a useful tool for predicting the prognosis of patients with lung adenocarcinoma

Background

Anoikis-related long non-coding RNAs (ARLs) play a critical role in tumor metastasis and progression, suggesting that they may serve as risk markers for cancer. This study aimed to investigate the prognostic value of ARLs in patients with lung adenocarcinoma (LUAD).

Methods

Clinical data, RNA sequencing (RNA-seq) data, and mutation data from the LUAD project were obtained from The Cancer Genome Atlas (TCGA) database. The Molecular Signatures Database (MSigDB) and the GeneCard database were used to collect an anoikis-related gene (ARG) set. Pearson correlation analysis was performed to identify ARLs. LASSO and Cox regression were then used to establish a prognostic risk signature for ARLs. The median risk score served as the basis for categorizing patients into high and low-risk groups. Kaplan-Meier analysis was utilized to compare the prognosis between these two groups. The study also examined the associations between risk scores and prognosis, clinicopathological characteristics, immune status, tumor mutation burden (TMB), and chemotherapeutic agents. LncRNA expression was assessed using quantitative real-time PCR (qRT-PCR).

Results

A total of 480 RNA expression profiles, 501 ARGs, and 2698 ARLs were obtained from the database. A prognostic ARL signature for LUAD was established, consisting of 9 lncRNAs. Patients in the low-risk group exhibited significantly better prognosis compared to those in the high-risk group (P < 0.001). The 9 lncRNAs from the ARL signature were identified as independent prognostic factors (P < 0.001). The signature demonstrated high accuracy in predicting LUAD prognosis, with area under the curve values exceeding 0.7. The risk scores for ARLs showed strong negative correlations with stroma score (P = 5.9E-07, R = -0.23), immune score (P = 9.7E-09, R = -0.26), and microenvironment score (P = 8E-11, R = -0.29). Additionally, the low-risk group exhibited significantly higher TMB compared to the high-risk group (P = 4.6E-05). High-risk status was significantly associated with lower half-maximal inhibitory concentrations for most chemotherapeutic drugs.

Conclusion

This newly constructed signature based on nine ARLs is a useful instrument for the risk stratification of LUAD patients. The signature has potential clinical significance for predicting the prognosis of LUAD patients and guiding personalized immunotherapy.

Liquid biopsy after resection of pancreatic adenocarcinoma and its relation to oncological outcomes. Systematic review and meta-analysis

BACKGROUND

It has been hypothesised that manipulation during surgery releases tumoral components into circulation. We investigate the effect of surgery on plasma-borne DNA biomarkers and the oncological outcomes in resectable pancreatic ductal adenocarcinoma (PDAC). We also compare non-touch isolation techniques (NTIT) with standard techniques.

MATERIALS AND METHODS

We performed a systematic review and a meta-analysis of studies analysing liquid biopsy as circulating tumour DNA (ctDNA), circulating tumour cells (CTCs), and messenger RNA (mRNA) in resectable PDAC patients who underwent surgery and its association with overall survival (OS) and disease-free survival (DFS). Research in EMBASE, Web of Science and PubMed was performed. The ctDNA shift negative-to-positive (ctDNA -/+) or ctDNA shift positive-to-negative (ctDNA +/-) before and after surgery was evaluated.

RESULTS

Twelve studies comprising 413 patients were included. Shorter OS and DFS were identified in patients with positive ctDNA status before (HR = 2.28, p = 0.005 and HR = 2.16, p = 0.006) or after surgery (HR = 3.88, p < 0.0001 and HR = 3.81, p = 0.03), respectively. Surgical resection increased the rate of ctDNA +/-. There were no differences in OS or DFS in the ctDNA +/- group compared with ctDNA +/+ or ctDNA -/+. However, there was a trend to shorter OS in the ctDNA -/+ group (HR = 5.00, p = 0.09). No differences between NTIT and standard techniques on liquid biopsy status were found.

CONCLUSION

Positive ctDNA in the perioperative period is associated with a worse prognosis. Surgical resection has a role in the negativisation of liquid biopsy status. More studies are needed to assess the potential of minimally invasive techniques on ctDNA dynamics.

The study of an anoikis-related signature to predict glioma prognosis and immune infiltration

BACKGROUND

Gliomas are the most common highly aggressive primary malignant brain tumors in adults with different biological behaviors and clinically heterogeneous features. About the extremely poor prognosis of gliomas, the search for potential therapeutic modalities and targets is crucial.

METHOD

We extracted the anoikis-related genes (ARG) from GeneCards and obtained differentially expressed genes in normal and glioma tissues from the GSE4290 dataset to obtain intersect differentially expressed ARG in gliomas by differential analysis. KEGG and GO analyses were used to evaluate the potential pathways and molecular processes of these genes. Based on The Cancer Genome Atlas (TCGA) training cohort, we performed the Least Absolute Shrinkage and Selection Operator (LASSO) regression and Cox regression to construct an ARG prognostic model and validated them in the TCGA testing cohort and the Chinese Glioma Genome Atlas (CGGA) validation cohort. Subsequently, we further explored the differences in clinical characteristics, tumor mutation burden (TMB), and the immune microenvironment in the high- and low-risk groups. Univariate and multifactorial regression analyses and nomogram construction were also performed. Moreover, we evaluated the expression levels of key genes via public databases, qPCR analysis and IHC staining, and further assessed the clinical prognostic value.

RESULTS

The regulatory model based on quantitative ARG prognostic models showed that patients in the high-risk group were associated with poorer survival prognosis, poorer clinical characteristics, and higher TMB levels. Moreover, the high-risk group had high levels of immune infiltration and upregulated immune checkpoint gene expression. The ARG prognostic model and the Nomogram showed good predictive performance. Expression and survival analysis of five prognostic ARG signatures (ETV4, HMOX1, MYC, NFE2L2, and UBE2C) showed that these genes have potential prognostic value.

CONCLUSION

Our constructed ARG prognostic risk model provides a potential therapeutic target and theoretical basis for predicting the prognosis of glioma patients and guiding individualized immunotherapy.

Diverse regulated cell death modes predict the immune microenvironment and drug sensitivity in lung adenocarcinoma

Integrated action modes of regulated cell death (RCD) in lung adenocarcinoma (LUAD) have not been comprehensively dissected. Here, we adopted 15 RCD modes, including 1350 related genes, and established RCD signature scores. We found that LUAD patients with high RCD scores had a significantly worse prognosis in all four different cohorts (TCGA, KM-plotter, GSE31210, and GSE30219). Our nomogram established based on the RCD score and clinical characteristics performed well in both the discovery and validation sets. There was a close correlation between the RCD scores and LUAD molecular subtypes identified by unsupervised consensus clustering. Furthermore, we profiled the tumor microenvironment via deconvolution and found significant differences in immune activity, transcription factor activity and molecular pathway enrichment between the RCD-high and RCD-low groups. More importantly, we revealed that the regulation of antigen presentation is the crucial mechanism underlying RCD. In addition, higher RCD scores predict poorer sensitivity to multiple therapeutic drugs, which indicates that RCD scores may serve as a promising predictor of chemotherapy and immunotherapy outcomes. In summary, this work is the first to reveal the internal links between RCD modes, LUAD, and cancer immunity and highlights the necessity of RCD scores in personalizing treatment plans.

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.