Anoikis resistance regulates immune infiltration and drug sensitivity in clear-cell renal cell carcinoma: insights from multi omics, single cell analysis and in vitro experiment.

Background: Anoikis is a form of programmed cell death essential for preventing cancer metastasis. In some solid cancer, anoikis resistance can facilitate tumor progression. However, this phenomenon is underexplored in clear-cell renal cell carcinoma (ccRCC). Methods: Using SVM machine learning, we identified core anoikis-related genes (ARGs) from ccRCC patient transcriptomic data. A LASSO Cox regression model stratified patients into risk groups, informing a prognostic model. GSVA and ssGSEA assessed immune infiltration, and single-cell analysis examined ARG expression across immune cells. Quantitative PCR and immunohistochemistry validated ARG expression differences between immune therapy responders and non-responders in ccRCC. Results: ARGs such as CCND1, CDKN3, PLK1, and BID were key in predicting ccRCC outcomes, linking higher risk with increased Treg infiltration and reduced M1 macrophage presence, indicating an immunosuppressive environment facilitated by anoikis resistance. Single-cell insights showed ARG enrichment in Tregs and dendritic cells, affecting immune checkpoints. Immunohistochemical analysis reveals that ARGs protein expression is markedly elevated in ccRCC tissues responsive to immunotherapy. Conclusion: This study establishes a novel anoikis resistance gene signature that predicts survival and immunotherapy response in ccRCC, suggesting that manipulating the immune environment through these ARGs could improve therapeutic strategies and prognostication in ccRCC.

Broadening anticancer spectrum by preprocessing and treatment of T- lymphocytes expressed FcγRI and monoclonal antibodies for refractory cancers.

Background: Chimeric antigen receptor T (CAR-T) cell therapies have achieved remarkable success in the treatment of hematological tumors. However, given the distinct features of solid tumors, particularly heterogeneity, metabolic aggressiveness, and fewer immune cells in tumor microenvironment (TME), the practical utility of CAR-T cells for solid tumors remains as a challenging issue. Meanwhile, although anti-PD-1 monoclonal antibody (mAb) has shown clinical efficacy, most mAbs also show limited clinical benefits for solid tumors due mainly to the issues associated with the lack of immune cells in TME. Thus, the infiltration of targeted immunological active cells into TME could generate synergistic efficacy for mAbs. Methods: We present a combinational strategy for solid tumor treatment, which combines armored-T cells to express Fc-gamma receptor I (FcγRI) fragment on the surfaces for targeting various tumors with therapeutically useful mAbs. Choosing CD20 and HER-2 as the targets, we characterized the in vitro and in vivo efficacy and latent mechanism of the combination drug by using flow cytometry, ELISA and other methods. Results: The combination and preprocessing of armored T-cells with corresponding antibody of Rituximab and Pertuzumab exerted profound anti-tumor effects, which is demonstrated to be mediated by synergistically produced antibody-dependent cellular cytotoxicity (ADCC) effects. Meanwhile, mAb was able to carry armored-T cell by preprocessing for the infiltration to TME in cell derived xenograft (CDX) model. Conclusions: This combination strategy showed a significant increase of safety profiles from the reduction of antibody doses. More importantly, the present strategy could be a versatile tool for a broad spectrum of cancer treatment, with a simple pairing of engineered T cells and a conventional antibody.

Improving cancer immunotherapy in prostate cancer by modulating T cell function through targeting the galectin-1.

Our study aimed to elucidate the role of Galectin-1 (Gal-1) role in the immunosuppressive tumor microenvironment (TME) of prostate cancer (PCa). Our previous findings demonstrated a correlation between elevated Gal-1 expression and advanced PCa stages. In this study, we also observed that Gal-1 is expressed around the tumor stroma and its expression level is associated with PCa progression. We identified that Gal-1 could be secreted by PCa cells, and secreted Gal-1 has the potential to induce T cell apoptosis. Gal-1 knockdown or inhibition of Gal-1 function by LLS30 suppresses T cell apoptosis resulting in increased intratumoral T cell infiltration. Importantly, LLS30 treatment significantly improved the antitumor efficacy of anti-PD-1 in vivo. Mechanistically, LLS30 binds to the carbohydrate recognition domain (CRD) of Gal-1, disrupting its binding to CD45 leading to the suppression of T cell apoptosis. In addition, RNA-seq analysis revealed a novel mechanism of action for LLS30, linking its tumor-intrinsic oncogenic effects to anti-tumor immunity. These findings suggested that tumor-derived Gal-1 contributes to the immunosuppressive TME in PCa by inducing apoptosis in effector T cells. Targeting Gal-1 with LLS30 may offer a strategy to enhance anti-tumor immunity and improve immunotherapy.

[Characteristics of the tumor microenvironment and therapeutic progress in malignant pleural effusion].

Malignant pleural effusion (MPE) can be secondary to various advanced malignant tumors. Although systemic anti tumor therapy may be effective in primary tumors, it cannot reduce the accumulation of MPE in proportion of the patients. The interaction of tumor cells, immune cells, and mesenchymal cells, as well as the abnormal proliferation of tumor-associated blood vessels, together create an immunosuppressive microenvironment for MPE, which promotes the abnormal proliferation of tumor cells and the accumulation of MPE. With the in-depth study of the tumor microenvironment, the application of local systemic anti-tumor therapy with local intrathoracic application of immune checkpoint inhibitors, immune cells, cytokines, and gene-mediated cytotoxic immunotherapy are able to alleviate the immunosuppressive tumor microenvironment and inhibit the accumulation of MPE. This article aimed to describe the tumor microenvironment in MPE and provide clues for identifying novel therapeutic targets.

Targeting cytotoxic lymphocyte antigen 4 (CTLA-4) in breast cancer.

Breast cancer (BC) has a high mortality rate and is one of the most common malignancies in the world. Initially, BC was considered non-immunogenic, but a paradigm shift occurred with the discovery of tumor-infiltrating lymphocytes (TILs) and regulatory T cells (Tregs) in the BC tumor microenvironment. CTLA-4 (Cytotoxic T-lymphocyte-associated protein 4) immunotherapy has emerged as a treatment option for BC, but it has limitations, including suboptimal antitumor effects and toxicity. Research has demonstrated that anti-CTLA-4 combination therapies, such as Treg depletion, cancer vaccines, and modulation of the gut microbiome, are significantly more effective than CTLA-4 monoclonal antibody (mAB) monotherapy. Second-generation CTLA-4 antibodies are currently being developed to mitigate immune-related adverse events (irAEs) and augment antitumor efficacy. This review examines anti-CTLA-4 mAB in BC, both as monotherapy and in combination with other treatments, and sheds light on ongoing clinical trials, novel CTLA-4 therapeutic strategies, and potential utility of biomarkers in BC.

The cuproptosis-related signature predicts the prognosis and immune microenvironments of primary diffuse gliomas: a comprehensive analysis.

BACKGROUND: Evidence has revealed a connection between cuproptosis and the inhibition of tumor angiogenesis. While the efficacy of a model based on cuproptosis-related genes (CRGs) in predicting the prognosis of peripheral organ tumors has been demonstrated, the impact of CRGs on the prognosis and the immunological landscape of gliomas remains unexplored. METHODS: We screened CRGs to construct a novel scoring tool and developed a prognostic model for gliomas within the various cohorts. Afterward, a comprehensive exploration of the relationship between the CRG risk signature and the immunological landscape of gliomas was undertaken from multiple perspectives. RESULTS: Five genes (NLRP3, ATP7B, SLC31A1, FDX1, and GCSH) were identified to build a CRG scoring system. The nomogram, based on CRG risk and other signatures, demonstrated a superior predictive performance (AUC of 0.89, 0.92, and 0.93 at 1, 2, and 3 years, respectively) in the training cohort. Furthermore, the CRG score was closely associated with various aspects of the immune landscape in gliomas, including immune cell infiltration, tumor mutations, tumor immune dysfunction and exclusion, immune checkpoints, cytotoxic T lymphocyte and immune exhaustion-related markers, as well as cancer signaling pathway biomarkers and cytokines. CONCLUSION: The CRG risk signature may serve as a robust biomarker for predicting the prognosis and the potential viability of immunotherapy responses. Moreover, the key candidate CRGs might be promising targets to explore the underlying biological background and novel therapeutic interventions in gliomas.

Integrating machine learning and single-cell analysis to uncover lung adenocarcinoma progression and prognostic biomarkers.

The progression of lung adenocarcinoma (LUAD) from atypical adenomatous hyperplasia (AAH) to invasive adenocarcinoma (IAC) involves a complex evolution of tumour cell clusters, the mechanisms of which remain largely unknown. By integrating single-cell datasets and using inferCNV, we identified and analysed tumour cell clusters to explore their heterogeneity and changes in abundance throughout LUAD progression. We applied gene set variation analysis (GSVA), pseudotime analysis, scMetabolism, and Cytotrace scores to study biological functions, metabolic profiles and stemness traits. A predictive model for prognosis, based on key cluster marker genes, was developed using CoxBoost and plsRcox (CPM), and validated across multiple cohorts for its prognostic prediction capabilities, tumour microenvironment characterization, mutation landscape and immunotherapy response. We identified nine distinct tumour cell clusters, with Cluster 6 indicating an early developmental stage, high stemness and proliferative potential. The abundance of Clusters 0 and 6 increased from AAH to IAC, correlating with prognosis. The CPM model effectively distinguished prognosis in immunotherapy cohorts and predicted genomic alterations, chemotherapy drug sensitivity, and immunotherapy responsiveness. Key gene S100A16 in the CPM model was validated as an oncogene, enhancing LUAD cell proliferation, invasion and migration. The CPM model emerges as a novel biomarker for predicting prognosis and immunotherapy response in LUAD patients, with S100A16 identified as a potential therapeutic target.

High Caveolin-1 mRNA expression in triple-negative breast cancer is associated with an aggressive tumor microenvironment, chemoresistance, and poor clinical outcome.

BACKGROUND: Currently, there are few treatment-predictive and prognostic biomarkers in triple-negative breast cancer (TNBC). Caveolin-1 (CAV1) is linked to chemoresistance and several important processes involved in tumor progression and metastasis, such as epithelial-mesenchymal transition (EMT). Herein, we report that high CAV1 gene expression is an independent factor of poor prognosis in TNBC. METHODS: CAV1 gene expression was compared across different molecular features (e.g., PAM50 subtypes). CAV1 expression was assessed in relation to clinical outcomes using Cox regression adjusted for clinicopathological predictors. Differential gene expression and gene set enrichment analyses were applied to compare high- and low-expressing CAV1 tumors. Tumor microenvironment composition of high- and low-expressing CAV1 tumors was estimated using ECOTYPER. Tumor tissue microarrays were used to evaluate CAV1 protein levels in stromal and malignant cells. RESULTS: In the SCAN-B (n = 525) and GSE31519 (n = 327) cohorts, patients with CAV1-high tumors had an increased incidence of early recurrence adjusted HR 1.78 (95% CI 1.12-2.81) and 2.20 (95% CI 1.39-3.47), respectively. In further analysis, high CAV1 gene expression was associated with a molecular profile indicating altered metabolism, neovascularization, chemoresistance, EMT, suppressed immune response, and active tumor microenvironment. Protein levels of CAV1 in malignant and stromal cells were not correlated with CAV1 gene expression. CONCLUSION: CAV1 gene expression in TNBC is a biomarker that merits further investigation in clinical trials and as a therapeutic target.

Identification of intracellular bacteria from multiple single-cell RNA-seq platforms using CSI-Microbes.

The study of the tumor microbiome has been garnering increased attention. We developed a computational pipeline (CSI-Microbes) for identifying microbial reads from single-cell RNA sequencing (scRNA-seq) data and for analyzing differential abundance of taxa. Using a series of controlled experiments and analyses, we performed the first systematic evaluation of the efficacy of recovering microbial unique molecular identifiers by multiple scRNA-seq technologies, which identified the newer 10x chemistries (3' v3 and 5') as the best suited approach. We analyzed patient esophageal and colorectal carcinomas and found that reads from distinct genera tend to co-occur in the same host cells, testifying to possible intracellular polymicrobial interactions. Microbial reads are disproportionately abundant within myeloid cells that up-regulate proinflammatory cytokines like IL1Β and CXCL8, while infected tumor cells up-regulate antigen processing and presentation pathways. These results show that myeloid cells with bacteria engulfed are a major source of bacterial RNA within the tumor microenvironment (TME) and may inflame the TME and influence immunotherapy response.

Engineering strategies to safely drive CAR T-cells into the future.

Chimeric antigen receptor (CAR) T-cell therapy has proven a breakthrough in cancer treatment in the last decade, giving unprecedented results against hematological malignancies. All approved CAR T-cell products, as well as many being assessed in clinical trials, are generated using viral vectors to deploy the exogenous genetic material into T-cells. Viral vectors have a long-standing clinical history in gene delivery, and thus underwent iterations of optimization to improve their efficiency and safety. Nonetheless, their capacity to integrate semi-randomly into the host genome makes them potentially oncogenic via insertional mutagenesis and dysregulation of key cellular genes. Secondary cancers following CAR T-cell administration appear to be a rare adverse event. However several cases documented in the last few years put the spotlight on this issue, which might have been underestimated so far, given the relatively recent deployment of CAR T-cell therapies. Furthermore, the initial successes obtained in hematological malignancies have not yet been replicated in solid tumors. It is now clear that further enhancements are needed to allow CAR T-cells to increase long-term persistence, overcome exhaustion and cope with the immunosuppressive tumor microenvironment. To this aim, a variety of genomic engineering strategies are under evaluation, most relying on CRISPR/Cas9 or other gene editing technologies. These approaches are liable to introduce unintended, irreversible genomic alterations in the product cells. In the first part of this review, we will discuss the viral and non-viral approaches used for the generation of CAR T-cells, whereas in the second part we will focus on gene editing and non-gene editing T-cell engineering, with particular regard to advantages, limitations, and safety. Finally, we will critically analyze the different gene deployment and genomic engineering combinations, delineating strategies with a superior safety profile for the production of next-generation CAR T-cell.

A mitochondria-related genes associated neuroblastoma signature - based on bulk and single-cell transcriptome sequencing data analysis, and experimental validation.

Background: Neuroblastoma (NB), characterized by its marked heterogeneity, is the most common extracranial solid tumor in children. The status and functionality of mitochondria are crucial in regulating NB cell behavior. While the significance of mitochondria-related genes (MRGs) in NB is still missing in key knowledge. Materials and methods: This study leverages consensus clustering and machine learning algorithms to construct and validate an MRGs-related signature in NB. Single-cell data analysis and experimental validation were employed to characterize the pivotal role of FEN1 within NB cells. Results: MRGs facilitated the classification of NB patients into 2 distinct clusters with considerable differences. The constructed MRGs-related signature and its quantitative indicators, mtScore and mtRisk, effectively characterize the MRGs-related patient clusters. Notably, the MRGs-related signature outperformed MYCN in predicting NB patient prognosis and was adept at representing the tumor microenvironment (TME), tumor cell stemness, and sensitivity to the chemotherapeutic agents Cisplatin, Topotecan, and Irinotecan. FEN1, identified as the most contributory gene within the MRGs-related signature, was found to play a crucial role in the communication between NB cells and the TME, and in the developmental trajectory of NB cells. Experimental validations confirmed FEN1's significant influence on NB cell proliferation, apoptosis, cell cycle, and invasiveness. Conclusion: The MRGs-related signature developed in this study offers a novel predictive tool for assessing NB patient prognosis, immune infiltration, stemness, and chemotherapeutic sensitivity. Our findings unveil the critical function of FEN1 in NB, suggesting its potential as a therapeutic target.

Modulatory effects of cancer stem cell-derived extracellular vesicles on the tumor immune microenvironment.

Cancer stem cells (CSCs), accounting for only a minor cell proportion (< 1%) within tumors, have profound implications in tumor initiation, metastasis, recurrence, and treatment resistance due to their inherent ability of self-renewal, multi-lineage differentiation, and tumor-initiating potential. In recent years, accumulating studies indicate that CSCs and tumor immune microenvironment act reciprocally in driving tumor progression and diminishing the efficacy of cancer therapies. Extracellular vesicles (EVs), pivotal mediators of intercellular communications, build indispensable biological connections between CSCs and immune cells. By transferring bioactive molecules, including proteins, nucleic acids, and lipids, EVs can exert mutual influence on both CSCs and immune cells. This interaction plays a significant role in reshaping the tumor immune microenvironment, creating conditions favorable for the sustenance and propagation of CSCs. Deciphering the intricate interplay between CSCs and immune cells would provide valuable insights into the mechanisms of CSCs being more susceptible to immune escape. This review will highlight the EV-mediated communications between CSCs and each immune cell lineage in the tumor microenvironment and explore potential therapeutic opportunities.

Collagen in hepatocellular carcinoma: A novel biomarker and therapeutic target.

HCC is globally recognized as a major health threat. Despite significant progress in the development of treatment strategies for liver cancer, recurrence, metastasis, and drug resistance remain key factors leading to a poor prognosis for the majority of liver cancer patients. Thus, there is an urgent need to develop effective biomarkers and therapeutic targets for HCC. Collagen, the most abundant and diverse protein in the tumor microenvironment, is highly expressed in various solid tumors and plays a crucial role in the initiation and progression of tumors. Recent studies have shown that abnormal expression of collagen in the tumor microenvironment is closely related to the occurrence, development, invasion, metastasis, drug resistance, and treatment of liver cancer, making it a potential therapeutic target and a possible diagnostic and prognostic biomarker for HCC. This article provides a comprehensive review of the structure, classification, and origin of collagen, as well as its role in the progression and treatment of HCC and its potential clinical value, offering new insights into the diagnosis, treatment, and prognosis assessment of liver cancer.

Using a pan-cancer atlas to investigate tumour associated macrophages as regulators of immunotherapy response.

The paradigm for macrophage characterization has evolved from the simple M1/M2 dichotomy to a more complex model that encompasses the broad spectrum of macrophage phenotypic diversity, due to differences in ontogeny and/or local stimuli. We currently lack an in-depth pan-cancer single cell RNA-seq (scRNAseq) atlas of tumour-associated macrophages (TAMs) that fully captures this complexity. In addition, an increased understanding of macrophage diversity could help to explain the variable responses of cancer patients to immunotherapy. Our atlas includes well established macrophage subsets as well as a number of additional ones. We associate macrophage composition with tumour phenotype and show macrophage subsets can vary between primary and metastatic tumours growing in sites like the liver. We also examine macrophage-T cell functional cross talk and identify two subsets of TAMs associated with T cell activation. Analysis of TAM signatures in a large cohort of immune checkpoint inhibitor-treated patients (CPI1000 + ) identify multiple TAM subsets associated with response, including the presence of a subset of TAMs that upregulate collagen-related genes. Finally, we demonstrate the utility of our data as a resource and reference atlas for mapping of novel macrophage datasets using projection. Overall, these advances represent an important step in both macrophage classification and overcoming resistance to immunotherapies in cancer.

A comprehensive review of computational cell cycle models in guiding cancer treatment strategies.

This article reviews the current knowledge and recent advancements in computational modeling of the cell cycle. It offers a comparative analysis of various modeling paradigms, highlighting their unique strengths, limitations, and applications. Specifically, the article compares deterministic and stochastic models, single-cell versus population models, and mechanistic versus abstract models. This detailed analysis helps determine the most suitable modeling framework for various research needs. Additionally, the discussion extends to the utilization of these computational models to illuminate cell cycle dynamics, with a particular focus on cell cycle viability, crosstalk with signaling pathways, tumor microenvironment, DNA replication, and repair mechanisms, underscoring their critical roles in tumor progression and the optimization of cancer therapies. By applying these models to crucial aspects of cancer therapy planning for better outcomes, including drug efficacy quantification, drug discovery, drug resistance analysis, and dose optimization, the review highlights the significant potential of computational insights in enhancing the precision and effectiveness of cancer treatments. This emphasis on the intricate relationship between computational modeling and therapeutic strategy development underscores the pivotal role of advanced modeling techniques in navigating the complexities of cell cycle dynamics and their implications for cancer therapy.

IRF5 suppresses metastasis through the regulation of tumor-derived extracellular vesicles and pre-metastatic niche formation.

Metastasis is driven by extensive cooperation between a tumor and its microenvironment, resulting in the adaptation of molecular mechanisms that evade the immune system and enable pre-metastatic niche (PMN) formation. Little is known of the tumor-intrinsic factors that regulate these mechanisms. Here we show that expression of the transcription factor interferon regulatory factor 5 (IRF5) in osteosarcoma (OS) and breast carcinoma (BC) clinically correlates with prolonged survival and decreased secretion of tumor-derived extracellular vesicles (t-dEVs). Conversely, loss of intra-tumoral IRF5 establishes a PMN that supports metastasis. Mechanistically, IRF5-positive tumor cells retain IRF5 transcripts within t-dEVs that contribute to altered composition, secretion, and trafficking of t-dEVs to sites of metastasis. Upon whole-body pre-conditioning with t-dEVs from IRF5-high or -low OS and BC cells, we found increased lung metastatic colonization that replicated findings from orthotopically implanted cancer cells. Collectively, our findings uncover a new role for IRF5 in cancer metastasis through its regulation of t-dEV programming of the PMN.

Extracellular Matrix Structure and Interaction with Immune Cells in Adult Astrocytic Tumors.

The extracellular matrix (ECM) is a dynamic set of molecules produced by the cellular component of normal and pathological tissues of the embryo and adult. ECM acts as critical regulator in various biological processes such as differentiation, cell proliferation, angiogenesis, and immune control. The most frequent primary brain tumors are gliomas and by far the majority are adult astrocytic tumors (AATs). The prognosis for patients with these neoplasms is poor and the treatments modestly improves survival. In the literature, there is a fair number of studies concerning the composition of the ECM in AATs, while the number of studies relating the composition of the ECM with the immune regulation is smaller. Circulating ECM proteins have emerged as a promising biomarker that reflect the general immune landscape of tumor microenvironment and may represent a useful tool in assessing disease activity. Given the importance it can have for therapeutic and prognostic purposes, the aim of our study is to summarize the biological properties of ECM components and their effects on the tumor microenvironment and to provide an overview of the interactions between major ECM proteins and immune cells in AATs. As the field of immunotherapy in glioma is quickly expanding, we retain that current data together with future studies on ECM organization and functions in glioma will provide important insights into the tuning of immunotherapeutic approaches.

M2-type tumor-associated macrophages upregulated PD-L1 expression in cervical cancer via the PI3K/AKT pathway.

BACKGROUND AND PURPOSE: PD-1/PD-L1 inhibitors have become a promising therapy. However, the response rate is lower than 30% in patients with cervical cancer (CC), which is related to immunosuppressive components in tumor microenvironment (TME). Tumor-associated macrophages (TAMs), as one of the most important immune cells, are involved in the formation of tumor suppressive microenvironment. Therefore, it will provide a theoretical basis for curative effect improvement about the regulatory mechanism of TAMs on PD-L1 expression. METHODS: The clinical data and pathological tissues of CC patients were collected, and the expressions of PD-L1, CD68 and CD163 were detected by immunohistochemistry. Bioinformatics was used to analyze the macrophage subtypes involved in PD-L1 regulation. A co-culture model was established to observe the effects of TAMs on the morphology, migration and invasion function of CC cells, and the regulatory mechanism of TAMs on PD-L1. RESULTS: PD-L1 expression on tumor cells could predict the poor prognosis of patients. And there was a strong correlation between PD-L1 expression with CD163+TAMs infiltration. Similarly, PD-L1 expression was associated with M1/M2-type TAMs infiltration in bioinformatics analysis. The results of cell co-culture showed that M1/M2-type TAMs could upregulate PD-L1 expression, especially M2-type TAMs may elevate the PD-L1 expression via PI3K/AKT pathway. Meanwhile, M1/M2-type TAMs can affect the morphological changes, and enhance migration and invasion abilities of CC cells. CONCLUSIONS: PD-L1 expression in tumor cells can be used as a prognostic factor and is closely related to CD163+TAMs infiltration. In addition, M2-type TAMs can upregulate PD-L1 expression in CC cells through PI3K/AKT pathway, enhance the migration and invasion capabilities, and affect the tumor progression.

Tumor cell-intrinsic MELK enhanced CCL2-dependent immunosuppression to exacerbate hepatocarcinogenesis and confer resistance of HCC to radiotherapy.

BACKGROUND: The outcome of hepatocellular carcinoma (HCC) is limited by its complex molecular characteristics and changeable tumor microenvironment (TME). Here we focused on elucidating the functional consequences of Maternal embryonic leucine zipper kinase (MELK) in the tumorigenesis, progression and metastasis of HCC, and exploring the effect of MELK on immune cell regulation in the TME, meanwhile clarifying the corresponding signaling networks. METHODS: Bioinformatic analysis was used to validate the prognostic value of MELK for HCC. Murine xenograft assays and HCC lung metastasis mouse model confirmed the role of MELK in tumorigenesis and metastasis in HCC. Luciferase assays, RNA sequencing, immunopurification-mass spectrometry (IP-MS) and coimmunoprecipitation (CoIP) were applied to explore the upstream regulators, downstream essential molecules and corresponding mechanisms of MELK in HCC. RESULTS: We confirmed MELK to be a reliable prognostic factor of HCC and identified MELK as an effective candidate in facilitating the tumorigenesis, progression, and metastasis of HCC; the effects of MELK depended on the targeted regulation of the upstream factor miR-505-3p and interaction with STAT3, which induced STAT3 phosphorylation and increased the expression of its target gene CCL2 in HCC. In addition, we confirmed that tumor cell-intrinsic MELK inhibition is beneficial in stimulating M1 macrophage polarization, hindering M2 macrophage polarization and inducing CD8 + T-cell recruitment, which are dependent on the alteration of CCL2 expression. Importantly, MELK inhibition amplified RT-related immune effects, thereby synergizing with RT to exert substantial antitumor effects. OTS167, an inhibitor of MELK, was also proven to effectively impair the growth and progression of HCC and exert a superior antitumor effect in combination with radiotherapy (RT). CONCLUSIONS: Altogether, our findings highlight the functional role of MELK as a promising target in molecular therapy and in the combination of RT therapy to improve antitumor effect for HCC.

Evaluation of secretome biomarkers in glioblastoma cancer stem cells: A bioinformatics analysis.

BACKGROUND: Glioblastoma (GBM) is a malignant brain tumor that frequently occurs alongside other central nervous system (CNS) conditions. The secretome of GBM cells contains a diverse array of proteins released into the extracellular space, influencing the tumor microenvironment. These proteins can serve as potential biomarkers for GBM due to their involvement in key biological processes, exploring the secretome biomarkers in GBM research represents a cutting-edge strategy with significant potential for advancing diagnostic precision, treatment monitoring, and ultimately improving outcomes for patients with this challenging brain cancer. AIM: This study was aimed to investigate the roles of secretome biomarkers and their pathwayes in GBM through bioinformatics analysis. METHODS AND RESULTS: Using data from the Gene Expression Omnibus and the Cancer Genome Atlas datasets-where both healthy and cancerous samples were analyzed-we used a quantitative analytical framework to identify differentially expressed genes (DEGs) and cell signaling pathways that might be related to GBM. Then, we performed gene ontology studies and hub protein identifications to estimate the roles of these DEGs after finding disease-gene connection networks and signaling pathways. Using the GEPIA Proportional Hazard Model and the Kaplan-Meier estimator, we widened our analysis to identify the important genes that may play a role in both progression and the survival of patients with GBM. In total, 890 DEGs, including 475 and 415 upregulated and downregulated were identified, respectively. Our results revealed that SQLE, DHCR7, delta-1 phospholipase C (PLCD1), and MINPP1 genes are highly expressed, and the Enolase 2 (ENO2) and hexokinase-1 (HK1) genes are low expressions. CONCLUSION: Hence, our findings suggest novel mechanisms that affect the occurrence of GBM development, growth, and/or establishment and may also serve as secretory biomarkers for GBM prognosis and possible targets for therapy. So, continued research in this field may uncover new avenues for therapeutic interventions and contribute to the ongoing efforts to combat GBM effectively.