Overexpressed integrin alpha 2 inhibits the activation of the transforming growth factor β pathway in pancreatic cancer via the TFCP2-SMAD2 axis

Downregulation of SMAD2 and SMAD4 is associated with poor prognosis and shorter survival in esophageal squamous cell carcinoma

BACKGROUND

Esophageal Squamous Cell Carcinoma (ESCC) presents a serious global health challenge, ranking among the most prevalent cancers worldwide. Small mothers against decapentaplegic 2 (SMAD2) and SMAD4 play a significant role in various types of cancer.

METHODS

This study performed relative mRNA expression level profiling of SMAD2 and SMAD4 using Real time quantitative polymerase chain reaction (qPCR) in tissue and blood of ESCC patients and analyzed their associations with numerous clinical and lifestyle parameters for evaluating prognostic significance along with survival and hazard outcomes.

RESULTS

SMAD2 and SMAD4 relative expression level showed downregulation in both tissue (85% and 87% respectively) and blood samples (80% and 79% respectively), and a significant positive correlation (p < 0.05) between their relative expression level was observed in both tissue and blood levels. Various clinicopathological parameters and food habits revealed significant association (p < 0.05) with SMAD2 and SMAD4 relative expression level. While analyzing survival and hazard in ESCC patients, various parameters revealed significant association (p < 0.05) in univariate model and histopathology grade, node stage, stage of metastasis, betel nut consumption, smoked food consumption and altered SMAD2 and SMAD4 relative expression level in tissue samples revealed significant association (p < 0.05) in the multivariate model, indicating their direct association with ESCC patients' survival and this makes them reliable predictors for ESCC prognosis.

CONCLUSIONS

This study's results revealed that downregulation of SMAD2 and SMAD4 is associated with poor prognosis and ESCC progression emphasizing their potential as potent prognostic factors for survival prediction as well as reliable biomarkers for screening.

A machine learning-based investigation of integrin expression patterns in cancer and metastasis

Integrins, a family of transmembrane receptor proteins, are well known to play important roles in cancer development and metastasis. However, a comprehensive understanding of these roles has not been achieved due to the complex relationships between specific integrins, cancer types, and the stages of cancer progression. Publicly accessible repositories from the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) projects provide rich datasets for exploring these relationships using machine learning (ML). In this study, integrin RNA-Seq expression data of ~ 8 healthy tissues in GTEx and corresponding tumors in TCGA were selected. Integrin expression was used to train ML models to distinguish between different healthy tissues, solid tumors, as well as normal and tumor samples from the same tissue type. These ML models can classify samples by tissue origin or disease status with high accuracy, and the integrins essential to these classifiers were identified. In some cases, the expression of only one or two integrins was needed to classify tissue type, tumor type or disease status with accuracy > 0.9. For example, expression of ITGA7 alone can distinguish healthy and cancerous breast tissue. Additionally, integrin co-expression networks in healthy and cancerous breast tissues were compared and were found to change significantly from healthy to cancer, indicating changes in functional involvement of integrins due to cancer. Integrin expression in metastatic tumors were further examined using data from the AURORA project for Metastatic Breast Cancer (MBC), and several integrins such as ITGAD, ITGA4, ITGAL, and ITGA11 were found to have significantly lower expression in metastases than in primary tumors.

Integrin α2 in the microenvironment and the tumor compartment of digestive (gastrointestinal) cancers: emerging regulators and therapeutic opportunities

Integrins are a family of cell surface membrane receptors and play a crucial role in facilitating bidirectional cell signaling. Integrin α2 (ITGA2) is expressed across a range of cell types, including epithelial cells, platelets, megakaryocytes, and fibroblasts, where it functions as a surface marker and it is implicated in the cell movements. The most recent findings have indicated that ITAG2 has the potential to function as a novel regulatory factor in cancer, responsible for driving tumorigenesis, inducing chemoresistance, regulating genomic instability and remodeling tumor microenvironment. Hence, we primarily focus on elucidating the biological function and mechanism of ITGA2 within the digestive tumor microenvironment, while highlighting its prospective utilization as a therapeutic target for cancer therapy.

Construction and verification of an innovative immune-related and hallmark gene sets prognostic model for bladder cancer

Background

Bladder cancer (BC) is a life-threatening malignancy with high mortality rates. Current prognostic models are insufficient in accurately predicting clinical outcomes, impeding personalized treatment strategies. This study aimed to identify BC subtypes and prognostic gene sets by analyzing changes in immune and hallmark gene sets activity in tumor and adjacent non-tumor tissues to enhance patient outcomes.

Methods

Utilizing data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), gene set variation analysis (GSVA) was applied to C7 immune-related and hallmark gene sets from the Molecular Signatures Database (MSigDB). The CancerSubtype R package was utilized for clustering these gene sets into three categories, from which 109 candidate sets were identified using Venn diagrams. A refined subset of seven gene sets was selected through least absolute shrinkage and selection operator (LASSO) regression for the construction of a risk model. Model validity was confirmed with receiver operating characteristic (ROC) and calibration curves, and a nomogram was constructed to integrate risk scores with clinical parameters. Finally, genes from the gene sets of the model were acquired and analyzed for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and protein-protein interactions (PPI) via plugin Molecular Complex Detection (MCODE) and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) in Cytoscape in both tumor and non-tumor tissues.

Results

Three BC subtypes were characterized by immunologic and hallmark gene sets, with subtype 1 patients showing worse survival. The prognostic model, based on seven gene sets, effectively stratified risk, with high-risk patients having significantly shorter survival. GO, KEGG, and PPI analyses indicated distinct influences of non-tumor and tumor tissues on the prognosis of BC patients.

Conclusions

We constructed and validated a novel prognostic model for risk stratification in BC based on immunologic and hallmark genes sets, which presents a novel perspective on rational treatment approaches and accurate prognostic evaluations for BC by considering both tumor and adjacent non-tumor tissues. This highlights the importance of focusing on alterations in both tumor and adjacent non-tumor tissues, rather than solely on the tumor itself.

A Machine Learning-Based Investigation of Integrin Expression Patterns in Cancer and Metastasis

Background

Integrins, a family of transmembrane receptor proteins, play complex roles in cancer development and metastasis. These roles could be better delineated through machine learning of transcriptomic data to reveal relationships between integrin expression patterns and cancer.

Methods

We collected publicly available RNA-Seq integrin expression from 8 healthy tissues and their corresponding tumors, along with data from metastatic breast cancer. We then used machine learning methods, including t-SNE visualization and Random Forest classification, to investigate changes in integrin expression patterns.

Results

Integrin expression varied across tissues and cancers, and between healthy and cancer samples from the same tissue, enabling the creation of models that classify samples by tissue or disease status. The integrins whose expression was important to these classifiers were identified. For example, ITGA7 was key to classification of breast samples by disease status. Analysis in breast tissue revealed that cancer rewires co-expression for most integrins, but the co-expression relationships of some integrins remain unchanged in healthy and cancer samples. Integrin expression in primary breast tumors differed from their metastases, with liver metastasis notably having reduced expression.

Conclusions

Integrin expression patterns vary widely across tissues and are greatly impacted by cancer. Machine learning of these patterns can effectively distinguish samples by tissue or disease status.

Skeletal Muscle Satellite Cells Co-Opt the Tenogenic Gene Scleraxis to Instruct Regeneration

Skeletal muscles connect bones and tendons for locomotion and posture. Understanding the regenerative processes of muscle, bone and tendon is of importance to basic research and clinical applications. Despite their interconnections, distinct transcription factors have been reported to orchestrate each tissue's developmental and regenerative processes. Here we show that Scx expression is not detectable in adult muscle stem cells (also known as satellite cells, SCs) during quiescence. Scx expression begins in activated SCs and continues throughout regenerative myogenesis after injury. By SC-specific Scx gene inactivation (ScxcKO), we show that Scx function is required for SC expansion/renewal and robust new myofiber formation after injury. We combined single-cell RNA-sequencing and CUT&RUN to identify direct Scx target genes during muscle regeneration. These target genes help explain the muscle regeneration defects of ScxcKO, and are not overlapping with Scx -target genes identified in tendon development. Together with a recent finding of a subpopulation of Scx -expressing connective tissue fibroblasts with myogenic potential during early embryogenesis, we propose that regenerative and developmental myogenesis co-opt the Scx gene via different mechanisms.

Selumetinib overcomes ITGA2-induced 5-fluorouracil resistance in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is the third most malignant tumor in the world. 5-fluorouracil (5‑FU) -based chemotherapy is the first-line chemotherapy scheme for CRC, whereas acquired drug resistance poses a huge obstacle to curing CRC patients and the mechanism is still obscure. Therefore, identification of genes associated with 5‑FU chemotherapy and seeking second-line treatment are necessary means to improve survival and prognosis of patients with CRC.

METHODS

The Cancer Therapeutics Response Portal (CTRP) database and Genomics of Drug Sensitivity in Cancer (GDSC) database were used to identify CRC-related genes and potential second-line therapies for 5-FU-resistant CRC. The single-cell RNA sequencing data for CRC tissues were obtained from a GEO dataset. The relationship between ITGA2 and 5-FU-resistant was investigated in vitro and in vivo models.

RESULTS

ACOX1 and ITGA2 were identified as risk biomarkers associated with 5-FU-resistance. We developed a risk signature, consisting of ACOX1 and ITGA2, that was able to distinguish well between 5-FU-resistance and 5-FU-sensitive. The single-cell sequencing data showed that ITGA2 was mainly enriched in malignant cells. ITGA2 was negatively correlated with IC50 values of most small molecule inhibitors, of which selumetinib had the highest negative correlation. Finally, knocking down ITGA2 can make 5-FU-resistant CRC cells sensitive to 5-FU and combining with selumetinib can improve the therapeutic effect of 5-FU resistant cells.

CONCLUSION

In summary, our findings demonstrated the critical role of ITGA2 in enhancing chemotherapy resistance in CRC cells and suggested that selumetinib can restore the sensitivity of chemotherapy-resistant CRC cells to 5-FU by inhibiting ITGA2 expression.

Advances in Integrated Multi-omics Analysis for Drug-Target Identification

As an essential component of modern drug discovery, the role of drug-target identification is growing increasingly prominent. Additionally, single-omics technologies have been widely utilized in the process of discovering drug targets. However, it is difficult for any single-omics level to clearly expound the causal connection between drugs and how they give rise to the emergence of complex phenotypes. With the progress of large-scale sequencing and the development of high-throughput technologies, the tendency in drug-target identification has shifted towards integrated multi-omics techniques, gradually replacing traditional single-omics techniques. Herein, this review centers on the recent advancements in the domain of integrated multi-omics techniques for target identification, highlights the common multi-omics analysis strategies, briefly summarizes the selection of multi-omics analysis tools, and explores the challenges of existing multi-omics analyses, as well as the applications of multi-omics technology in drug-target identification.

Genkwanin alleviates intervertebral disc degeneration via regulating ITGA2/PI3K/AKT pathway and inhibiting apoptosis and senescence

Intervertebral disc degeneration (IVDD) is a progressive degenerative disease influenced by various factors. Genkwanin, a known anti-inflammatory flavonoid, has not been explored for its potential in IVDD management. This study aims to investigate the effects and mechanisms of genkwanin on IVDD. In vitro, cell experiments revealed that genkwanin dose-dependently inhibited Interleukin-1β-induced expression levels of inflammatory factors (Interleukin-6, inducible nitric oxide synthase, cyclooxygenase-2) and degradation metabolic protein (matrix metalloproteinase-13). Concurrently, genkwanin upregulated the expression of synthetic metabolism genes (type II collagen, aggrecan). Moreover, genkwanin effectively reduced the phosphorylation of phosphatidylinositol 3-kinase (PI3K)/AKT/mammalian target of rapamycin, mitogen-activated protein kinase (MAPK), and nuclear factor-κB (NF-κB) pathways. Transcriptome sequencing analysis identified integrin α2 (ITGA2) as a potential target of genkwanin, and silencing ITGA2 reversed the activation of PI3K/AKT pathway induced by Interleukin-1β. Furthermore, genkwanin alleviated Interleukin-1β-induced senescence and apoptosis in nucleus pulposus cells. In vivo animal experiments demonstrated that genkwanin mitigated the progression of IVDD in the rat model through imaging and histological examinations. In conclusion, This study suggest that genkwanin inhibits inflammation in nucleus pulposus cells, promotes extracellular matrix remodeling, suppresses cellular senescence and apoptosis, through the ITGA2/PI3K/AKT, NF-κB and MAPK signaling pathways. These findings indicate that genkwanin may be a promising therapeutic candidate for IVDD.

Predictive three-biomarker panel in peripheral blood mononuclear cells for detecting hepatocellular carcinoma

Hepatocellular carcinoma (HCC) ranks among the most prevalent cancers and accounts for a significant proportion of cancer-associated deaths worldwide. This disease, marked by multifaceted etiology, often poses diagnostic challenges. Finding a reliable and non-invasive diagnostic method seems to be necessary. In this study, we analyzed the gene expression profiles of 20 HCC patients, 12 individuals with chronic hepatitis, and 15 healthy controls. Enrichment analysis revealed that platelet aggregation, secretory granule lumen, and G-protein-coupled purinergic nucleotide receptor activity were common biological processes, cellular components, and molecular function in HCC and chronic hepatitis B (CHB) compared to healthy controls, respectively. Furthermore, pathway analysis demonstrated that "estrogen response" was involved in the pathogenesis of HCC and CHB conditions, while, "apoptosis" and "coagulation" pathways were specific for HCC. Employing computational feature selection and logistic regression classification, we identified candidate genes pivotal for diagnostic panel development and evaluated the performance of these panels. Subsequent machine learning evaluations assessed these panels' performance in an independent cohort. Remarkably, a 3-marker panel, comprising RANSE2, TNF-α, and MAP3K7, demonstrated the best performance in qRT-PCR-validated experimental data, achieving 98.4% accuracy and an area under the curve of 1. Our findings highlight this panel's promising potential as a non-invasive approach not only for detecting HCC but also for distinguishing HCC from CHB patients.

Stabilization of KPNB1 by deubiquitinase USP7 promotes glioblastoma progression through the YBX1-NLGN3 axis

BACKGROUND

Glioblastoma (GBM) is the most common malignant tumor of the central nervous system. It is an aggressive tumor characterized by rapid proliferation, diffuse tumor morphology, and poor prognosis. Unfortunately, current treatments, such as surgery, radiotherapy, and chemotherapy, are unable to achieve good outcomes. Therefore, there is an urgent need to explore new treatment targets. A detailed mechanistic exploration of the role of the nuclear pore transporter KPNB1 in GBM is lacking. This study demonstrated that KPNB1 regulated GBM progression through a transcription factor YBX1 to promote the expression of post-protrusion membrane protein NLGN3. This regulation was mediated by the deubiquitinating enzyme USP7.

METHODS

A tissue microarray was used to measure the expression of KPNB1 and USP7 in glioma tissues. The effects of KPNB1 knockdown on the tumorigenic properties of glioma cells were characterized by colony formation assays, Transwell migration assay, EdU proliferation assays, CCK-8 viability assays, and apoptosis analysis using flow cytometry. Transcriptome sequencing identified NLGN3 as a downstream molecule that is regulated by KPNB1. Mass spectrometry and immunoprecipitation were performed to analyze the potential interaction between KPNB1 and YBX1. Moreover, the nuclear translocation of YBX1 was determined with nuclear-cytoplasmic fractionation and immunofluorescence staining, and chromatin immunoprecipitation assays were conducted to study DNA binding with YBX1. Ubiquitination assays were performed to determine the effects of USP7 on KPNB1 stability. The intracranial orthotopic tumor model was used to detect the efficacy in vivo.

RESULTS

In this study, we found that the nuclear receptor KPNB1 was highly expressed in GBM and could mediate the nuclear translocation of macromolecules to promote GBM progression. Knockdown of KPNB1 inhibited the progression of GBM, both in vitro and in vivo. In addition, we found that KPNB1 could regulate the downstream expression of Neuroligin-3 (NLGN3) by mediating the nuclear import of transcription factor YBX1, which could bind to the NLGN3 promoter. NLGN3 was necessary and sufficient to promote glioma cell growth. Furthermore, we found that deubiquitinase USP7 played a critical role in stabilizing KPNB1 through deubiquitination. Knockdown of USP7 expression or inhibition of its activity could effectively impair GBM progression. In vivo experiments also demonstrated the promoting effects of USP7, KPNB1, and NLGN3 on GBM progression. Overall, our results suggested that KPNB1 stability was enhanced by USP7-mediated deubiquitination, and the overexpression of KPNB1 could promote GBM progression via the nuclear translocation of YBX1 and the subsequent increase in NLGN3 expression.

CONCLUSION

This study identified a novel and targetable USP7/KPNB1/YBX1/NLGN3 signaling axis in GBM cells.

From inflammation to metastasis: The central role of miR-155 in modulating NF-κB in cancer

Cancer is a multifaceted, complex disease characterized by unchecked cell growth, genetic mutations, and dysregulated signalling pathways. These factors eventually cause evasion of apoptosis, sustained angiogenesis, tissue invasion, and metastasis, which makes it difficult for targeted therapeutic interventions to be effective. MicroRNAs (miRNAs) are essential gene expression regulators linked to several biological processes, including cancer and inflammation. The NF-κB signalling pathway, a critical regulator of inflammatory reactions and oncogenesis, has identified miR-155 as a significant participant in its modulation. An intricate network of transcription factors known as the NF-κB pathway regulates the expression of genes related to inflammation, cell survival, and immunological responses. The NF-κB pathway's dysregulation contributes to many cancer types' development, progression, and therapeutic resistance. In numerous cancer models, the well-studied miRNA miR-155 has been identified as a crucial regulator of NF-κB signalling. The p65 subunit and regulatory molecules like IκB are among the primary targets that miR-155 directly targets to alter NF-κB activity. The molecular processes by which miR-155 affects the NF-κB pathway are discussed in this paper. It also emphasizes the miR-155's direct and indirect interactions with important NF-κB cascade elements to control the expression of NF-κB subunits. We also investigate how miR-155 affects NF-κB downstream effectors in cancer, including inflammatory cytokines and anti-apoptotic proteins.

SMAD Proteins in TGF-β Signalling Pathway in Cancer: Regulatory Mechanisms and Clinical Applications

Suppressor of mother against decapentaplegic (SMAD) family proteins are central to one of the most versatile cytokine signalling pathways in metazoan biology, the transforming growth factor-β (TGF-β) pathway. The TGF-β pathway is widely known for its dual role in cancer progression as both an inhibitor of tumour cell growth and an inducer of tumour metastasis. This is mainly mediated through SMAD proteins and their cofactors or regulators. SMAD proteins act as transcription factors, regulating the transcription of a wide range of genes, and their rich post-translational modifications are influenced by a variety of regulators and cofactors. The complex role, mechanisms, and important functions of SMAD proteins in tumours are the hot topics in current oncology research. In this paper, we summarize the recent progress on the effects and mechanisms of SMAD proteins on tumour development, diagnosis, treatment and prognosis, and provide clues for subsequent research on SMAD proteins in tumours.

Molecular and metabolic regulation of immunosuppression in metastatic pancreatic ductal adenocarcinoma

Immunosuppression is a hallmark of pancreatic ductal adenocarcinoma (PDAC), contributing to early metastasis and poor patient survival. Compared to the localized tumors, current standard-of-care therapies have failed to improve the survival of patients with metastatic PDAC, that necessecitates exploration of novel therapeutic approaches. While immunotherapies such as immune checkpoint blockade (ICB) and therapeutic vaccines have emerged as promising treatment modalities in certain cancers, limited responses have been achieved in PDAC. Therefore, specific mechanisms regulating the poor response to immunotherapy must be explored. The immunosuppressive microenvironment driven by oncogenic mutations, tumor secretome, non-coding RNAs, and tumor microbiome persists throughout PDAC progression, allowing neoplastic cells to grow locally and metastasize distantly. The metastatic cells escaping the host immune surveillance are unique in molecular, immunological, and metabolic characteristics. Following chemokine and exosomal guidance, these cells metastasize to the organ-specific pre-metastatic niches (PMNs) constituted by local resident cells, stromal fibroblasts, and suppressive immune cells, such as the metastasis-associated macrophages, neutrophils, and myeloid-derived suppressor cells. The metastatic immune microenvironment differs from primary tumors in stromal and immune cell composition, functionality, and metabolism. Thus far, multiple molecular and metabolic pathways, distinct from primary tumors, have been identified that dampen immune effector functions, confounding the immunotherapy response in metastatic PDAC. This review describes major immunoregulatory pathways that contribute to the metastatic progression and limit immunotherapy outcomes in PDAC. Overall, we highlight the therapeutic vulnerabilities attributable to immunosuppressive factors and discuss whether targeting these molecular and immunological "hot spots" could improve the outcomes of PDAC immunotherapies.

ITGA2 overexpression inhibits DNA repair and confers sensitivity to radiotherapies in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a dismal disease with a 5-year survival rate of less than 10%, despite the recent advances in chemoradiotherapy. The sensitivity of the PDAC patients to chemoradiotherapy varies widely, especially to radiotherapy, suggesting the need for more elucidation of the underlying mechanisms. In this study, a novel function of the nuclear ITGA2, the alpha subunit of transmembrane collagen receptor integrin alpha-2/beta-1, regulating the DNA damage response (DDR), was identified. First, analyzing The Cancer Genome Atlas (TCGA) PDAC data set indicated that the expression status of ITGA2 was negatively correlated with the genome stability parameters. The study further demonstrated that ITGA2 specially inhibited the activity of the non-homologous end joining (NHEJ) pathway and conferred the sensitivity to radiotherapy in PDAC by restraining the recruitment of DNA-dependent protein kinase catalytic subunit (DNA-PKcs) to Ku70/80 heterodimer during DDR. Considering the overexpression of ITGA2 and its associated with the poor prognosis of PDAC patients, this study suggested that the ITGA2 expression status could be used as an indicator for radiotherapy and DNA damage reagents, and the radiotherapy in combination with the overexpression of ITGA2 might be a viable treatment strategy for the PDAC patients.