The Immune Landscape of Cancer

PLK1 overexpression suppresses homologous recombination and confers cellular sensitivity to PARP inhibition

The overexpression of Polo-like kinase 1 (PLK1) is associated with poor clinical outcomes in various malignancies, making it an attractive target for anticancer therapies. Although recent studies suggest PLK1's involvement in homologous recombination (HR), the impact of its overexpression on HR remains unclear. In this study, we investigated the effect of PLK1 overexpression on HR using bioinformatics and experimental approaches. Analyzing The Cancer Genome Atlas (TCGA) and Cancer Cell Line Encyclopedia (CCLE) datasets with the Homologous Recombination Deficiency (HRD) score, we found a positive correlation between PLK1 expression and HRD score, indicating that increased PLK1 expression suppresses HR. To validate these findings, we performed cell line-based experiments, demonstrating that PLK1 overexpression attenuates RAD51 focus formation and HR, as measured by ASHRA in T47D cells. Since HR-deficient cells are hypersensitive to PARP inhibitors, we further confirmed that PLK1 overexpression increases sensitivity to PARP inhibitors, both in CCLE dataset analysis and experiments using T47D cells. Additionally, we found that the effects of PLK1 overexpression on HR suppression and increased PARP inhibitor sensitivity were mitigated by either a PLK1 kinase inhibitor or the kinase-dead mutant [T210A]. This suggests that PLK1's impact on HR and PARP inhibitor sensitivity is mediated through its kinase activity. Moreover, analysis of clinical ovarian cancer samples revealed that higher PLK1 expression correlates with increased sensitivity to PARP inhibitors. Our results suggest that PLK1 overexpression suppresses homologous recombination, leading to enhanced sensitivity to PARP inhibition, presenting a potential therapeutic strategy for targeting cancers with overexpression of PLK1.

The role of KRT18 in lung adenocarcinoma development: integrative bioinformatics and experimental validation

Lung adenocarcinoma (LUAD) represents one of the most common subtypes of lung cancer with high rates of incidence and mortality, which contributes to substantial health and economic demand across the globe. Treatment today mainly consists of surgery, radiotherapy, and chemotherapy, but their efficacy in advanced stages is often suboptimal and emphasizes the clear need for new biomarkers and therapeutic targets. Using comprehensive bioinformatics analyses consisting of the Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Human Protein Atlas (HPA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC), immune infiltration analysis and functional enrichment analysis, and single-cell analysis, we examined the potential of keratin 18 (KRT18) as a candidate biomarker in advanced LUAD. KRT18 was significantly elevated in LUAD tissue relative to normal adjacent tissue (p < 0.05), and its expression was correlated with poor clinical-pathological features and inferior prognostic outcome. Furthermore, KRT18 expression was associated with several populations of immune cells, suggesting KRT18 may contribute to the local tumor microenvironment and potentially pathways of immune evasion. Survival analysis indicated that elevated KRT18 expression correlated with poor overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI), reinforcing its legitimacy as a prognostic tool (AUC = 0.846). Importantly, gene enrichment analysis found KRT18-associated genes enriched for pathways associated with lymphocyte differentiation and immune response pathways, which provides mechanistic insight into biological effects attributed to KRT18. Notably, NU.1025 has demonstrated the capability of reversing KRT18-modulated oncogenic features, and targeted therapeutic strategies can be developed moving forward. In conclusion, our data demonstrate that KRT18 has utility as a potential biomarker but may also serve as a therapeutic target in LUAD and merit further investigation into underlying mechanistic functions and potential therapeutic roles in the clinic.

MPCD Index for Hepatocellular Carcinoma Patients Based on Mitochondrial Function and Cell Death Patterns

Hepatocellular carcinoma (HCC) is a highly heterogeneous cancer with a poor prognosis. During the development of cancer cells, mitochondria influence various cell death patterns by regulating metabolic pathways such as oxidative phosphorylation. However, the relationship between mitochondrial function and cell death patterns in HCC remains unclear. In this study, we used a comprehensive machine learning framework to construct a mitochondrial functional activity-associated programmed cell death index (MPCDI) based on scRNA-seq and RNA-seq data from TCGA, GEO, and ICGC datasets. The index signature was used to classify HCC patients, and studied the multi-omics features, immune microenvironment, and drug sensitivity of the subtypes. Finally, we constructed the MPCDI signature consisting of four genes (S100A9, FYN, LGALS3, and HMOX1), which was one of the independent risk factors for the prognosis of HCC patients. The HCC patients were divided into high- and low-MPCDI groups, and the immune status was different between the two groups. Patients with a high MPCDI had higher TIDE scores and poorer responses to immunotherapy, suggesting that high-MPCDI patients might not be suitable for immunotherapy. By analyzing the drug sensitivity data of CTRP, GDSC, and PRISM databases, it was found that staurosporine has potential therapeutic significance for patients with a high MPCDI. In summary, based on the characteristics of mitochondria function and PCD patterns, we used single-cell and transcriptome data to identify four genes and construct the MPCDI signature, which provided new perspectives and directions for the clinical diagnosis and personalized treatment of HCC patients.

Comprehensive multi-omics analysis of the prognostic value and immune signature of NCF2 in pan-cancer and its relationship with acute myeloid leukemia

BACKGROUND

The neutrophil cytoplasmic factor 2 (NCF2) gene encodes the p67phox protein, which has been implicated in the pathogenesis of several diseases. However, its specific role in tumorigenesis remains ambiguous. This study seeks to clarify the prognostic implications, immune profile, and therapeutic responses associated with NCF2 across different cancer types.

METHODS

We conducted a comprehensive analysis using multi-omics data to investigate tissue-specific and single-cell specific expression, pan-cancer expression patterns, epigenetic modifications, the immune microenvironment, and therapeutic responses. Our study specifically examined NCF2-associated immune signatures, molecular mechanisms, and potential therapeutic targets in acute myeloid leukemia (AML). Additionally, we performed in vitro experiments to assess how NCF2 knockdown influences cell proliferation, apoptosis, and cell cycle dynamics in AML cell lines U937 and KG-1.

RESULTS

NCF2 is dysregulated in more than two-thirds of cancer types, with elevated expression strongly correlating with poor prognosis in various cancers, including leukemia. Multifactorial Cox analysis has identified NCF2 as an independent prognostic factor for leukemia. Immunological studies have highlighted NCF2's impact on the tumor microenvironment, particularly affecting monocytes and macrophages. Furthermore, NCF2 expression closely correlates with responses to immunotherapy and chemotherapy. In vitro experiments demonstrate that NCF2 knockdown alters proliferation, apoptosis, and cell cycle dynamics of U937 cells and KG-1 cells. Notably, NCF2 is involved in regulating the differentiation of monocytes into macrophages.

CONCLUSIONS

These findings highlight NCF2 as a promising pan-cancer biomarker that significantly impacts tumor microenvironment, therapeutic response, and is critically associated with cell cycle regulation, apoptosis and macrophage transformation in AML.

Programmed cell death pathways in lung adenocarcinoma: illuminating tumor drug resistance and therapeutic opportunities through single-cell analysis

Lung adenocarcinoma (LUAD) is a major contributor to cancer-related deaths, distinguished by its pronounced tumor heterogeneity and persistent challenges in overcoming drug resistance. In this study, we utilized single-cell RNA sequencing (scRNA-seq) to dissect the roles of programmed cell death (PCD) pathways, including apoptosis, necroptosis, pyroptosis, and ferroptosis, in shaping LUAD heterogeneity, immune infiltration, and prognosis. Among these, ferroptosis and pyroptosis were most significantly associated with favorable survival outcomes, highlighting their potential roles in enhancing anti-tumor immunity. Distinct PCD-related LUAD subtypes were identified, characterized by differential pathway activation and immune cell composition. Subtypes enriched with cytotoxic lymphocytes and dendritic cells demonstrated improved survival outcomes and increased potential responsiveness to immunotherapy. Drug sensitivity analysis revealed that these subtypes exhibited heightened sensitivity to targeted therapies and immune checkpoint inhibitors, suggesting opportunities for personalized treatment strategies. Our findings emphasize the interplay between PCD pathways and the tumor microenvironment, providing insights into the mechanisms underlying tumor drug resistance and immune evasion. By linking molecular and immune features to clinical outcomes, this study highlights the potential of targeting PCD pathways to enhance therapeutic efficacy and overcome resistance in LUAD. These results contribute to a growing framework for developing precise and adaptable cancer therapies tailored to specific tumor characteristics.

RASGEF1C as a novel prognostic biomarker for LUAD

Lung adenocarcinoma (LUAD) is a common histologic lung cancer with high morbidity and mortality, and most patients have distant metastases at diagnosis. RasGEF Domain Family Member 1C (RASGEF1C) could regulated Alzheimer's disease. However, its function in various cancers, including LUAD, is poorly understood. In the present study, we discovered that high expression of RASGEF1C in LUAD was associated with poorer prognosis, unfavorable histological features, and poorer pathological staging. In addition, RASGEF1C expression was an independent predictor of overall survival, disease specific survival, and progress free interval in patients with LUAD. High expression of RASGEF1C was linked to signaling pathways that are involved in the immune response and cell proliferation, according to KEGG enrichment analysis. Additionally, we verified that RASGEF1C was highly expressed in LUAD cell lines and that RASGEF1C knockdown dramatically decreased the capacity of LUAD cell lines to invade, migrate, and proliferate. Our research provides mechanistic insights into the function of RASGEF1C in the progression of LUAD and suggests that RASGEF1C is a prospective target for future therapy.

Construction and validation of a regulatory T cells-based classification of renal cell carcinoma: an integrated bioinformatic analysis and clinical cohort study

PURPOSE

Renal cell carcinoma (RCC), exhibiting remarkable heterogeneity, can be highly infiltrated by regulatory T cells (Tregs). However, the relationship between Treg and the heterogeneity of RCC remains to be explored.

METHODS

We acquired single-cell RNA-seq profiles and 537 bulk RNA-seq profiles of TCGA-KIRC cohort. Through clustering, monocle2 pseudotime and prognostic analyses, we identified Treg states-related prognostic genes (TSRPGs), then constructing the RCC Treg states-related prognostic classification (RCC-TSC). We also explored its prognostic significance and multi-omics landmarks. Additionally, we utilized correlation analysis to establish regulatory networks, and predicted candidate inhibitors. More importantly, in Xinhua cohort of 370 patients with kidney neoplasm, we used immunohistochemical (IHC) staining for classification, then employing statistical analyses including Chi-square tests and multivariate Cox proportional hazards regression analysis to explore its clinical relevance.

RESULTS

We defined 44 TSRPGs in four different monocle states, and identified high immune infiltration RCC (HIRC, LAG3+, Mki67+) as the highly exhausted subtype with the worst prognosis in RCC-TSC (p < 0.001). BATF-LAG3-immune cells axis might be its underlying metastasis-related mechanism. Immunotherapy and inhibitors including sunitinib potentially conferred best therapeutic effects for HIRC. Furthermore, we successfully validated HIRC subtype as an independent prognostic factor within the Xinhua cohort (OS, HR = 16.68, 95% CI = 1.88-148.1, p = 0.011; PFS, HR = 4.43, 95% CI = 1.55-12.6, p = 0.005).

CONCLUSION

Through integrated bioinformatics analysis and a large-sample retrospective clinical study, we successfully established RCC-TSC and a diagnostic kit, which could stratify RCC patients with different prognosis and to guide personalized treatment.

Impact of pan-cancer analysis of the exportins family on prognosis, the tumor microenvironment and its potential therapeutic efficacy

This study aims to comprehensively analyze the role of the exportin (XPO) family in the development and progression of cancer. These nuclear transport proteins have been increasingly recognized for their involvement in oncogenic processes and tumor growth. We utilized updated public databases and bioinformatics tools to assess the expression levels of the XPO family and their associations with key oncological markers including patient survival, immune subtypes, tumor microenvironment, stemness scores, drug sensitivity, and DNA methylation across various cancers. Expression levels of XPO family proteins varied significantly across different cancer types, indicating cancer-specific roles. Specific XPO proteins were linked to adverse prognosis in particular cancers. Additionally, expression levels were correlated with classifications of immune subtypes and tumor purity; notably, lower expression levels were often found in tumors with elevated stromal and immune scores. A marked correlation was observed between XPO proteins and RNA stemness scores, whereas the correlation with DNA stemness scores varied. Furthermore, XPO expression levels significantly influenced cancer cell drug sensitivity and generally showed correlations with gene methylation patterns, although these correlations differed among cancer types. Our findings underscore the distinct roles of XPO family members in cancer, linking them to immune infiltration, the tumor microenvironment, and drug sensitivity. These insights not only enhance our understanding of the prognostic and therapeutic potentials of XPO proteins in cancer but also lay the groundwork for further studies into their mechanisms and applications in cancer diagnosis and treatment.

Single-cell transcriptomics reveal the prognostic roles of epithelial and T cells and DNA methylation-based prognostic models in pancreatic cancer

BACKGROUND

Pancreatic adenocarcinoma (PDAC) exhibits a complex microenvironment with diverse cell populations influencing patient prognosis. Single-cell RNA sequencing (scRNA-seq) was used to identify prognosis-related cell types, and DNA methylation (DNAm)-based models were developed to predict outcomes based on their cellular characteristics.

METHODS

We integrated scRNA-seq, bulk data, and clinical information to identify key cell populations associated with prognosis. The TCGA dataset was used for validation, and cell composition was inferred from DNAm data. Prognostic models were constructed based on cell-type-specific DNAm markers, and genomic features were compared across risk groups. Nomograms were created to assess treatment responses in different risk levels.

RESULTS

Epithelial and T cells were major prognostic factors. Genomic analysis showed that epithelial cells in PDAC followed a malignant trajectory. DNAm data from TCGA confirmed the association of higher epithelial and T cell proportions with worse prognosis. Prognostic models based on DNAm markers of these cells effectively predicted patient survival, especially 5-year overall survival (AUC = 0.834). High-risk group with epithelial cell model showed altered pathways (tight junctions, NOTCH, and P53 signaling), while high-risk group with T cell model had changes in glycolysis, hypoxia, and NOTCH signaling, with more KRAS or TP53 mutations. Low-risk groups in the T cell model displayed stronger antitumor immune responses. Treatment predictions and nomograms were developed for clinical use.

CONCLUSIONS

scRNA-seq and DNAm data integration enabled the creation of predictive models based on epithelial and T cell-specific methylation patterns, offering robust prognosis prediction for PDAC patients.

Pinpointing the integration of artificial intelligence in liver cancer immune microenvironment

Liver cancer remains one of the most formidable challenges in modern medicine, characterized by its high incidence and mortality rate. Emerging evidence underscores the critical roles of the immune microenvironment in tumor initiation, development, prognosis, and therapeutic responsiveness. However, the composition of the immune microenvironment of liver cancer (LC-IME) and its association with clinicopathological significance remain unelucidated. In this review, we present the recent developments related to the use of artificial intelligence (AI) for studying the immune microenvironment of liver cancer, focusing on the deciphering of complex high-throughput data. Additionally, we discussed the current challenges of data harmonization and algorithm interpretability for studying LC-IME.

Machine-learning derived identification of prognostic signature to forecast head and neck squamous cell carcinoma prognosis and drug response

Introduction

Head and neck squamous cell carcinoma (HNSCC), a highly heterogeneous malignancy is often associated with unfavorable prognosis. Due to its unique anatomical position and the absence of effective early inspection methods, surgical intervention alone is frequently inadequate for achieving complete remission. Therefore, the identification of reliable biomarker is crucial to enhance the accuracy of screening and treatment strategies for HNSCC.

Method

To develop and identify a machine learning-derived prognostic model (MLDPM) for HNSCC, ten machine learning algorithms, namely CoxBoost, elastic network (Enet), generalized boosted regression modeling (GBM), Lasso, Ridge, partial least squares regression for Cox (plsRcox), random survival forest (RSF), stepwise Cox, supervised principal components (SuperPC), and survival support vector machine (survival-SVM), along with 81 algorithm combinations were utilized. Time-dependent receiver operating characteristics (ROC) curves and Kaplan-Meier analysis can effectively assess the model's predictive performance. Validation was performed through a nomogram, calibration curves, univariate and multivariate Cox analysis. Further analyses included immunological profiling and gene set enrichment analyses (GSEA). Additionally, the prediction of 50% inhibitory concentration (IC50) of potential drugs between groups was determined.

Results

From analyses in the HNSCC tissues and normal tissues, we found 536 differentially expressed genes (DEGs). Subsequent univariate-cox regression analysis narrowed this list to 18 genes. A robust risk model, outperforming other clinical signatures, was then constructed using machine learning techniques. The MLDPM indicated that high-risk scores showed a greater propensity for immune escape and reduced survival rates. Dasatinib and 7 medicine showed the superior sensitivity to the high-risk NHSCC, which had potential to the clinical.

Conclusions

The construction of MLDPM effectively eliminated artificial bias by utilizing 101 algorithm combinations. This model demonstrated high accuracy in predicting HNSCC outcomes and has the potential to identify novel therapeutic targets for HNSCC patients, thus offering significant advancements in personalized treatment strategies.

Modeling intratumor heterogeneity in breast cancer

Reduced therapy response in breast cancer has been correlated with heterogeneity in biomarker composition, expression level, and spatial distribution of cancer cells within a patient tumor. Thus, there is a need for models to replicate cell-cell, cell-stromal, and cell-microenvironment interactions during cancer progression. Traditional two-dimensional (2D) cell culture models are convenient but cannot adequately represent tumor microenvironment histological organization,in vivo3D spatial/cellular context, and physiological relevance. Recently, three-dimensional (3D)in vitrotumor models have been shown to provide an improved platform for incorporating compositional and spatial heterogeneity and to better mimic the biological characteristics of patient tumors to assess drug response. Advances in 3D bioprinting have allowed the creation of more complex models with improved physiologic representation while controlling for reproducibility and accuracy. This review aims to summarize the advantages and challenges of current 3Din vitromodels for evaluating therapy response in breast cancer, with a particular emphasis on 3D bioprinting, and addresses several key issues for future model development as well as their application to other cancers.

The landscape in telomere related gene prognostic signature for survival and medication treatment effectiveness prediction in hepatocellular carcinoma

OBJECTIVE

Telomeres, made of repetitive DNA sequences and shelterin complexes, which were found at the ends of chromosomes and had been extensively studied in cancer research. However, in hepatocellular carcinoma (HCC) was still relatively scarce. In this study, we investigated the correlation between telomerase-related genes (TRGs) and the prognosis and immunotherapy of HCC patients to enhance clinical outcomes.

METHODS

In this work, TRGs were gathered using TelNet, while clinical information and gene expression data for HCC patients were retrieved from the Cancer Genome Atlas (TCGA) database. A risk prediction model based on TRGs was created using COX and Lasso regression analyses, with ROC curves used to assess prognostic efficacy. Univariate and multifactorial COX regression analyses were used to determine if the risk model had an independent impact on prognosis. Nomograms were created to enhance clinical usability, and calibration curves were used to assess predictive ability at various time points. The Tumor Immune Dysfunction and Exclusion (TIDE) score was used to analyze differences in immune infiltrating cells between risk groups. The study analyzed the relationship between risk ratings and drug treatment effectiveness using data from the CellMiner database. The hub gene was identified and its relationship to prognostic markers of HCC patients was examined. The expression of hub genes in immune cell subpopulations was also investigated by single-cell data.

RESULTS

2093 TRGs were identified, with 949 showing significant differences in expression between HCC and paracancerous tissues. Seven risk genes were overexpressed in tumor tissues, leading to lower survival rates in high-risk patients. Risk model could independently predict the prognosis of HCC patients. Analysis of tumor immune infiltrating cells revealed significant differences in cell abundance between risk groups, with notable variations in immune subset enrichment between subgroups. Higher risk scores correlated with increased sensitivity to sorafenib, mitoxantrone, oxaliplatin, gemcitabine, and entinostat, while sensitivity decreased for vincristine, etc. CDCA8 was identified as a key gene in the Protein Interaction Network, while high expression associated with poorer overall survival, tumor proliferation and metastasis. The results of single-cell data analysis suggest that CDCA8 may promote the development of HCC by affecting T lymphocytes.

CONCLUSION

The TRG-based risk model could predict HCC patient prognosis and closely linked to tumor immune environment, which could offer new possibilities for clinical treatment.

Systematic exploration of the molecular characteristics of CD8+ T cells to predict the response to immunotherapy and the prognosis of patients with colon adenocarcinoma

Background

Recently, immunotherapy has been recognized as an innovative treatment with great potential for patients with colon adenocarcinoma (COAD). Although the relationships between immune cells and immune substances are intricate and still unclear, some immune cells and substances could be considered prognostic factors for predicting therapeutic efficacy. To understand the genomic signatures of COAD related to CD8+ T cells that could predict the prognosis of patients receiving immunotherapy and to discover new therapeutic targets, we conducted this study.

Methods

Data were gathered from the TCGA and GEO databases to assess the molecular features of CD8+ T cells. We developed a CD8+ T-cell score (CD8S) to quantify the population of CD8+ T cells in each COAD patient. A thorough analysis of multilevel data was conducted to evaluate overall survival (OS), biological functions, immunological profiles, drug sensitivity, and responses to immunotherapy between the two groups defined by CD8S. Additionally, a series of in vitro experiments were executed to validate the reliability of the signatures associated with CD8+ T cells.

Results

CD8S has been shown to be a reliable prognostic factor for COAD according to different patient and subgroup analyses. Through in vitro experiments, we suggested that TSPYL2 may act as an oncogene in COAD. Through functional analysis, a high expression of genes linked to the cell cycle, cytoskeleton, cell adhesion, and various cancer-related pathways was observed in the high CD8S group, which aids in tumor invasion. Moreover, immune analysis reflected immunosuppression in patients with high CD8S. Patients in the low CD8S group were more sensitive to chemotherapy, targeted drugs, and immunotherapy due to higher genetic variants.

Conclusion

To better understand the biological characteristics and prognostic significance of CD8+ T cells in immunotherapy for COAD, we thoroughly examined the molecular properties of CD8+ T cells in COAD and developed a CD8+ T-cell model.

Cancer specific up-regulated lactate genes associated with immunotherapy resistance in a pan-cancer analysis

Background

Although the lactate pathway has been reported to lead to immune escape through the inhibition of effector T cells, the cancer-intrinsic lactate signature has not been identified, and the immunotherapeutic efficacy and potential mechanism of the lactate signature are still unclear.

Methods

We defined a pan-cancer up-lactate score by comparing malignant tissues and normal tissues in the TCGA cohort. The immunotherapeutic efficacy was evaluated in non-small cell lung cancer (NSCLC), metastatic renal cancer (mRCC), bladder cancer (BLCA) and melanoma cohorts. The cancer cell-intrinsic mechanism to immune checkpoint inhibitors (ICIs) resistance was measured using single cell sequencing (scRNA-seq) data. Pathway activation was evaluated in the TCGA cohort and CPTAC cohort with transcriptomics and proteomics. The co-occurrence of up-lactate signature and mTOR signaling was determined by spatial transcriptomics of the tissue samples. Immunotherapy resistance and pathway regulation were validated in the in-house NSCLC cohort.

Results

Patients with the high up-lactate scores had significantly short overall survival (OS) than those with the low up-lactate scores (p < 0.001) across multiple types of cancers. The up-regulated lactate signature exhibited higher expression in the malignant cells compared with stromal cells and immune cells in multiple scRNA-seq datasets. A high up-lactate score was associated with poor OS in NSCLC, mRCC, BLCA and melanoma patients who received anti-PD(L)1 antibody. The up-lactate score was higher in the responders of cancer cells, but not in immune cells and stromal cells compared with the non-responders (p < 0.05). Moreover, up-lactate score was positively correlated with mTOR signaling across multiple cancers. In patients with NSCLC who received anti-PD-1 antibody, higher up-lactate scores were associated with significantly shorter PFS compared to lower up-lactate scores (p < 0.001). Additionally, the up-lactate score was associated with cold tumor, and was positively correlated with mTOR signaling.

Conclusion

Collectively, we defined a pan-cancer up-lactate signature, which is a feature of malignant cells and is associated with ICIs resistance. This reveals a coherent program with prognostic and predictive value that may be therapeutically targeted.

Exploring the Complexity of Pan-Cancer: Gene Convergences and in silico Analyses

Cancer is a complex and multifaceted group of diseases characterized by highly intricate mechanisms of tumorigenesis and tumor progression, which complicates diagnosis, prognosis, and treatment. In recent years, targeted therapies have gained prominence by focusing on specific mutations and molecular features unique to each tumor type, offering more effective and personalized treatment options. However, it is equally critical to explore the genetic commonalities across different types of cancer, which has led to the rise of pan-cancer studies. These approaches help identify shared therapeutic targets across various tumor types, enabling the development of broader and potentially more widely applicable treatment strategies. This review aims to provide a comprehensive overview of key concepts related to tumors, including tumorigenesis processes, the tumor microenvironment, and the role of extracellular vesicles in tumor biology. Additionally, we explore the molecular interactions and mechanisms driving tumor progression, with a particular focus on the pan-cancer perspective. To achieve this, we conducted an in silico analysis using publicly available datasets, which facilitated the identification of both common and divergent genetic and molecular patterns across different tumor types. By integrating these diverse areas, this review offers a clearer and deeper understanding of the factors influencing tumorigenesis and highlights potential therapeutic targets.

Migrasome regulator TSPAN4 shapes the suppressive tumor immune microenvironment in pan-cancer

Background

Migrasomes are newly identified organelles on the retracting fibers of migrating cells, involved in releasing signaling molecules, expelling damaged mitochondria, and facilitating intercellular communication through phagocytosis. TSPAN4, a key regulator of migrasome formation, is a valuable marker for visualizing these organelles. However, its role in cancer remains unclear.

Methods

We analyzed TSPAN4 expression and its prognostic significance across multiple cancers using TCGA Pan-Cancer (PANCAN), and TCGA TARGET GTEx datasets. The relationship between TSPAN4 and tumor heterogeneity, stemness, and the immunosuppressive tumor microenvironment was explored through RNA-seq and scRNA-seq data. In addition, we examined TSPAN4's role in glioma, focusing on migrasome formation, cell proliferation, and macrophage polarization.

Results

Our analysis reveals that TSPAN4 is aberrantly expressed in various tumors, likely linked to its methylation status. It correlates with tumor heterogeneity, stemness, and a suppressive immune microenvironment. In glioma, TSPAN4 enhances cell proliferation and promotes macrophage polarization toward the immunosuppressive M2 phenotype.

Conclusions

TSPAN4, as a migrasome regulator, plays a crucial role in shaping the immunosuppressive tumor microenvironment in pan-cancer.

Integrative multi-omics analysis reveals a novel subtype of hepatocellular carcinoma with biological and clinical relevance

Background

Hepatocellular carcinoma (HCC) is a highly heterogeneous tumor, and the development of accurate predictive models for prognosis and drug sensitivity remains challenging.

Methods

We integrated laboratory data and public cohorts to conduct a multi-omics analysis of HCC, which included bulk RNA sequencing, proteomic analysis, single-cell RNA sequencing (scRNA-seq), spatial transcriptomics sequencing (ST-seq), and genome sequencing. We constructed a tumor purity (TP) and tumor microenvironment (TME) prognostic risk model. Proteomic analysis validated the TP-TME-related signatures. Joint analysis of scRNA-seq and ST-seq revealed characteristic clusters associated with TP high-risk subtypes, and immunohistochemistry confirmed the expression of key genes. We conducted functional enrichment analysis, transcription factor activity inference, cell-cell interaction, drug efficacy analysis, and mutation information analysis to identify a novel subtype of HCC.

Results

Our analyses constructed a robust HCC prognostic risk prediction model. The patients with TP-TME high-risk subtypes predominantly exhibit hypoxia and activation of the Wnt/beta-catenin, Notch, and TGF-beta signaling pathways. Furthermore, we identified a novel subtype, XPO1+Epithelial. This subtype expresses signatures of the TP risk subtype and aligns with the biological behavior of high-risk patients. Additional analyses revealed that XPO1+Epithelial is influenced primarily by fibroblasts via ligand-receptor interactions, such as FN1-(ITGAV+ITGB1), and constitute a significant component of the TP-TME subtype. Moreover, XPO1+Epithelial interact with monocytes/macrophages, T/NK cells, and endothelial cells through ligand-receptor pairs, including MIF-(CD74+CXCR4), MIF-(CD74+CD44), and VEGFA-VEGFR1R2, respectively, thereby promoting the recruitment of immune-suppressive cells and angiogenesis. The ST-seq cohort treated with Tyrosine Kinase Inhibitors (TKIs) and Programmed Cell Death Protein 1 (PD-1) presented elevated levels of TP and TME risk subtype signature genes, as well as XPO1+Epithelial, T-cell, and endothelial cell infiltration in the treatment response group. Drug sensitivity analyses indicated that TP-TME high-risk subtypes, including sorafenib and pembrolizumab, were associated with sensitivity to multiple drugs. Further exploratory analyses revealed that CTLA4, PDCD1, and the cancer antigens MSLN, MUC1, EPCAM, and PROM1 presented significantly increase expression levels in the high-risk subtype group.

Conclusions

This study constructed a robust prognostic model for HCC and identified novel subgroups at the single-cell level, potentially assisting in the assessment of prognostic risk for HCC patients and facilitating personalized drug therapy.

The pan-cancer landscape of aldo-keto reductase1B10 reveals that its expression is diminished in gastric cancer

Introduction

Aldo-keto reductase 1B10 (AKR1B10) is a multifunctional enzyme, which is important in cancer development and progression, but the landscape of AKR1B10 in pan-cancers and in tumor microenvironment is unclear.

Method

This study integrated the sequencing data of 33 cancer types, including gastric cancer, from TCGA project to explored the expression pattern and genetic and epigenetic alterations of AKR1B10. The association of AKR1B10 expression with clinical progression of cancers was evaluated by Kaplan-Meier analysis; the potential role of AKR1B10 in tumor microenvironment (TME) and immune-related gene expression were analyzed by PURITY, ESTIMATE, TIMER and CIBERSORT algorithms. The expression of AKR1B10 and immune cell markers in gastric cancer were evaluated with multiplex immunofluorescence staining.

Result

Results indicated that AKR1B10 was highly expressed in the gastrointestinal tract in health donors, but the expression of AKR1B10 was significantly changed in most of cancer types, which may be ascribed to DNA methylation in its promoter. The AKR1B10 expression in cancers and its value in disease progression was bidirectional and functionally enriched in metabolism in pan-cancers. In tumor microenvironment, AKR1B10 was significantly correlated with immune cell infiltrations and immune gene expression. In the stomach, along with the diminishing of AKR1B10 expression, CD68+ macrophage increased and CD19+ B cell decreased in gastric cancer.

Discussion

These data indicates that AKR1B10 may be an important factor in the development and progression and a potential therapeutic target for multiple cancers, but plays as a protector in the gastric tissues.

Interferon response and epigenetic modulation by SMARCA4 mutations drive ovarian tumor immunogenicity

Cell-intrinsic mechanisms of immunogenicity in ovarian cancer (OC) are not well understood. Damaging mutations in the SWI/SNF chromatin remodeling complex, such as SMARCA4 (BRG1), are associated with improved response to immune checkpoint blockade; however, the mechanism by which this occurs is unclear. We found that SMARCA4 loss in OC models resulted in increased cancer cell-intrinsic immunogenicity, characterized by up-regulation of long-terminal RNA repeats, increased expression of interferon-stimulated genes, and up-regulation of antigen presentation machinery. Notably, this response was dependent on STING, MAVS, and IRF3 signaling but was independent of the type I interferon receptor. Mouse ovarian and melanoma tumors with SMARCA4 loss demonstrated increased infiltration and activation of cytotoxic T cells, NK cells, and myeloid cells in the tumor microenvironment. These results were recapitulated in BRG1 inhibitor-treated SMARCA4-proficient tumor models, suggesting that modulation of chromatin remodeling through targeting SMARCA4 may serve as a strategy to overcome cancer immune evasion.

The T cell-mediated tumor killing patterns revealed tumor heterogeneous and proposed treatment recommendation in ovary cancer

BACKGROUND

Immune checkpoint inhibitors (ICIs) have greatly improved cancer treatment, but the role of genes related to T cell-mediated tumor killing (TTK) sensitivity in ovarian cancer (OV) is unclear.

METHODS

This study analyzed 1367 OV patients and 11 independent cohorts. The unsupervised clustering was conducted to identify three tumor subtypes based on genes that regulate tumor cell sensitivity to TTK (GSTTKs). The biological characteristics, genetic variations, immunological landscape, and therapeutic evaluation for each subtype were further explored.

RESULTS

Patients were divided into three reproducible subtypes based on 61 GSTKKs associated with prognosis. C1 was likely to be an invasive subtype with the worst prognosis and highly unstable genome. C2 might be an immune-active subtype with the best prognosis, high immune infiltration and preferable response to immunotherapy. C3 might be a metabolic subtype, resistant to immunotherapy, but sensitive to drug therapy. Following an extensive exploration into a variety of distinct molecular features between the three subtypes, the results suggested that C2 patients were considered to derive significant efficacy from immunotherapy. For C1 and C3 patients, chemotherapy might be an ideal treatment strategy.

CONCLUSIONS

In this study, three GSTKKs-based subtypes were identified by assessing TTK patterns in OV. These new insights further improved our understanding of GSTTKs and might refine clinical treatment strategies for OV patients.

Pan-cancer single cell and spatial transcriptomics analysis deciphers the molecular landscapes of senescence related cancer-associated fibroblasts and reveals its predictive value in neuroblastoma via integrated multi-omics analysis and machine learning

Introduction

Cancer-associated fibroblasts (CAFs) are a diverse group of cells that significantly contribute to reshaping the tumor microenvironment (TME), and no research has systematically explored the molecular landscapes of senescence related CAFs (senes CAF) in NB.

Methods

We utilized pan-cancer single cell and spatial transcriptomics analysis to identify the subpopulation of senes CAFs via senescence related genes, exploring its spatial distribution characteristics. Harnessing the maker genes with prognostic significance, we delineated the molecular landscapes of senes CAFs in bulk-seq data. We established the senes CAFs related signature (SCRS) by amalgamating 12 and 10 distinct machine learning (ML) algorithms to precisely diagnose stage 4 NB and to predict prognosis in NB. Based on risk scores calculated by prognostic SCRS, patients were categorized into high and low risk groups according to median risk score. We conducted comprehensive analysis between two risk groups, in terms of clinical applications, immune microenvironment, somatic mutations, immunotherapy, chemotherapy and single cell level. Ultimately, we explore the biological function of the hub gene JAK1 in pan-cancer multi-omics landscape.

Results

Through integrated analysis of pan-cancer spatial and single-cell transcriptomics data, we identified distinct functional subgroups of CAFs and characterized their spatial distribution patterns. With marker genes of senes CAF and leave-one-out cross-validation, we selected RF algorithm to establish diagnostic SCRS, and SuperPC algorithm to develop prognostic SCRS. SCRS demonstrated a stable predictive capability, outperforming the previously published NB signatures and clinic variables. We stratified NB patients into high and low risk group, which showed the low-risk group with a superior survival outcome, an abundant immune infiltration, a different mutation landscape, and an enhanced sensitivity to immunotherapy. Single cell analysis reveals biologically cellular variations underlying model genes of SCRS. Spatial transcriptomics delineated the molecular variant expressions of hub gene JAK1 in malignant cells across cancers, while immunohistochemistry validated the differential protein levels of JAK1 in NB.

Conclusion

Based on multi-omics analysis and ML algorithms, we successfully developed the SCRS to enable accurate diagnosis and prognostic stratification in NB, which shed light on molecular landscapes of senes CAF and clinical utilization of SCRS.

DTX3L-mediated TIRR nuclear export and degradation regulates DNA repair pathway choice and PARP inhibitor sensitivity

53BP1 plays an important role in DNA double-strand break (DSB) repair and this activity is negatively regulated by its interaction with Tudor interacting repair regulator (TIRR). However, how the TIRR-53BP1 repair axis is regulated in response to DNA damage remains elusive. Here, we demonstrate that TIRR is translocated to the cytoplasm and degraded upon DNA damage. Ubiquitination of TIRR at lysine 187 by DTX3L is a critical process that regulates NHEJ pathway activity and PARP inhibitor sensitivity by facilitating XPO1-mediated TIRR nuclear export and degradation after DNA damage. We show that DTX3L is overexpressed in prostate cancers in patients and that decreased expression of TIRR due to DTX3L overexpression impairs the negative regulatory effect of TIRR on 53BP1, which consequently induces HR deficiency and chromosomal instability and sensitizes prostate cancer cells to poly (ADP-ribose) polymerase (PARP) inhibitors. Our work reveals a dual action of DTX3L on TIRR degradation and nuclear exportation and identifies DTX3L as an upstream regulator of the TIRR-53BP1 axis that governs DNA repair pathway choice and PARP inhibitor sensitivity. These findings suggest that TIRR ubiquitination and DTX3L overexpression could be viable biomarkers predicting PARP inhibitor sensitivity in cancers.

Prognostic significance of CNNM4 in ovarian cancer: a comprehensive bioinformatics analysis

Background

Ovarian cancer (OV) is a common malignancy in the female reproductive system, characterized by poor prognosis and high recurrence rates. The discovery of dependable molecular markers is crucial for improving the timeliness of detection, diagnosis, and treatment, ultimately aiming to lower fatality rates. CNNM4 (cyclin and CBS domain divalent metal cation transport mediator 4), a member of the CNNM (Cyclin M) family, binds to PRL (prolactin) to regulate magnesium homeostasis and influence tumor cell proliferation. Although CNNM4 is implicated in various cancers, its role in OV remains unclear.

Methods

In vitro experiments assessed CNNM4 expression and its impact on the proliferation and migration of OV cells. Comparisons of TCGA and GTEx data were used to identify correlations between clinical features and outcomes. The role of CNNM4 in OV was further explored through comprehensive bioinformatics analyses.

Results

Elevated levels of CNNM4 expression were observed in OV cells and tissues, and were linked to a poor prognosis. CNNM4 could modulate the proliferation and migration of various OV cell lines, including IOSE-80, SKOV-3, and A2780. Through involvement in multiple signaling pathways, evidenced by GSVA and GSEA, CNNM4 was implicated in OV progression. CNNM4 positively regulated the infiltration level of Macrophages M2, T cells CD4 memory resting and NK cells resting, and had a negative regulation effect on NK cells activated and T cells gamma delta. Moreover, CNNM4 is related to drug sensitivity of OV. A prediction model based on CNNM4 expression and clinical symptoms was constructed to predict OV prognosis.

Conclusion

CNNM4 may affect the progression of OV and is associated with a poor prognosis. It has potential as a biomarker for predicting survival and as a target for therapeutic interventions in OV patients.

SpliceMutr Enables Pan-Cancer Analysis of Splicing-Derived Neoantigen Burden in Tumors

SIGNIFICANCE

SpliceMutr shows that splicing antigenicity changes in response to ICI therapies and that native modulation of the splicing machinery through mutations increases the contribution of splicing to the neoantigen load of some The Cancer Genome Atlas cancer subtypes. Future studies of the relationship between splicing antigenicity and immune checkpoint inhibitor response pan-cancer are essential to establish the interplay between antigen heterogeneity and immunotherapy regimen on patient response.

MAML3-fusions modulate vascular and immune tumour microenvironment and confer high metastatic risk in pheochromocytoma and paraganglioma

Pheochromocytomas and paragangliomas are rare neuroendocrine tumours. Around 20-25 % of patients develop metastases, for which there is an urgent need of prognostic markers and therapeutic stratification strategies. The presence of a MAML3-fusion is associated with increased metastatic risk, but neither the processes underlying disease progression, nor targetable vulnerabilities have been addressed. We have compiled a cohort of 850 patients, which has shown a 3.65 % fusion prevalence and represents the largest MAML3-positive series reported to date. While MAML3-fusions mainly cause single pheochromocytomas, we also observed somatic post-zygotic events, resulting in multiple tumours in the same patient. MAML3-tumours show increased expression of neuroendocrine-to-mesenchymal transition markers, MYC-targets, and angiogenesis-related genes, leading to a distinct tumour microenvironment with unique vascular and immune profiles. Importantly, our findings have identified MAML3-tumours specific vulnerabilities beyond Wnt-pathway dysregulation, such as a rich vascular network, and overexpression of PD-L1 and CD40, suggesting potential therapeutic targets.

SNRPB2 in the pan-cancer landscape: A bioinformatics exploration and validation in hepatocellular carcinoma

Aberrant splicing is a significant contributor to gene expression abnormalities in cancer. SNRPB2, a component of U2 small nuclear ribonucleoprotein particles (snRNPs), contributes to the assembly of the spliceosome, the molecular machinery responsible for splicing. To date, few studies have investigated the role of SNRPB2 in tumorigenesis. We examined data sourced from various public databases, such as The Cancer Genome Atlas(TCGA), the Clinical Proteomic Tumor Analysis Consortium(CPTAC), and Gene Expression Omnibus(GEO). Our investigation included gene expression, genomic and epigenomic scrutiny, gene set enrichment assessment(GSEA), and immune cell infiltration evaluation. Furthermore, we performed empirical validation to ascertain the impact of SNRPB2 suppression on the proliferation and migration of liver cancer cells. Analysis of gene expression revealed widespread upregulation of SNRPB2 across a spectrum of cancer types, with heightened levels of SNRPB2 expression in numerous tumors linked to unfavorable prognosis. Genomic and epigenomic assessments revealed connections between SNRPB2 expression and variations in SNRPB2 copy number, DNA methylation patterns, and RNA modifications. Through gene set enrichment analysis, the involvement of SNRPB2 in vital biological processes and pathways related to cancer was identified. Furthermore, scrutiny of immune cell infiltration suggested a potential relationship between SNRPB2 and the tumor microenvironment, which was reinforced by multiple single-cell sequencing profiles. Subsequent experimental validation revealed that silencing SNRPB2 effectively impeded the proliferation and migration of liver cancer cells. Taken together, these findings underscore the prospective utility of SNRPB2 as a prognostic biomarker and a promising candidate for immunotherapy in cancer. It is necessary to engage in additional exploration into its underlying mechanisms and clinical treatment potential.

The Molecular Classification of Pheochromocytomas and Paragangliomas: Discovering the Genomic and Immune Landscape of Metastatic Disease

Pheochromocytomas (PCCs) and paragangliomas (PGLs, together PPGLs) are the most hereditary tumors known. PPGLs were considered benign, but the fourth edition of the World Health Organisation (WHO) classification redefined all PPGLs as malignant neoplasms with variable metastatic potential. The metastatic rate differs based on histopathology, genetic background, size, and location of the tumor. The challenge in predicting metastatic disease lies in the absence of a clear genotype-phenotype correlation among the more than 20 identified genetic driver variants. Recent advances in molecular clustering based on underlying genetic alterations have paved the way for improved cluster-specific personalized treatments. However, despite some clusters demonstrating a higher propensity for metastatic disease, cluster-specific therapies have not yet been widely adopted in clinical practice. Comprehensive genomic profiling and transcriptomic analyses of large PPGL cohorts have identified potential new biomarkers that may influence metastatic potential. It appears that no single biomarker alone can reliably predict metastatic risk; instead, a combination of these biomarkers may be necessary to develop an effective prediction model for metastatic disease. This review evaluates current guidelines and recent genomic and transcriptomic findings, with the aim of accurately identifying novel biomarkers that could contribute to a predictive model for mPPGLs, thereby enhancing patient care and outcomes.

Role of gut microbiota in tumorigenesis and antitumoral therapies: an updated review

Gut microbiota plays a prominent role in regulation of host nutrientmetabolism, drug and xenobiotics metabolism, immunomodulation and defense against pathogens. It synthesizes numerous metabolites thatmaintain the homeostasis of host. Any disbalance in the normalmicrobiota of gut can lead to pathological conditions includinginflammation and tumorigenesis. In the past few decades, theimportance of gut microbiota and its implication in various diseases, including cancer has been a prime focus in the field of research. Itplays a dual role in tumorigenesis, where it can accelerate as wellas inhibit the process. Various evidences validate the effects of gutmicrobiota in development and progression of malignancies, wheremanipulation of gut microbiota by probiotics, prebiotics, dietarymodifications and faecal microbiota transfer play a significant role.In this review, we focus on the current understanding of theinterrelationship between gut microbiota, immune system and cancer,the mechanisms by which they play dual role in promotion andinhibition of tumorigenesis. We have also discussed the role ofcertain bacteria with probiotic characteristics which can be used tomodulate the outcome of the various anti-cancer therapies under theinfluence of the alteration in the composition of gut microbiota.Future research primarily focusing on the microbiota as a communitywhich affect and modulate the treatment for cancer would benoteworthy in the field of oncology. This necessitates acomprehensive knowledge of the roles of individual as well asconsortium of microbiota in relation to physiology and response ofthe host.

A new nano approach to prevent tumor growth in the local treatment of glioblastoma: Temozolomide and rutin-loaded hybrid layered composite nanofiber

Total resection of glioblastoma (GB) tumors is nearly impossible, and systemic administration of temozolomide (TMZ) is often inadequate. This study presents a hybrid layered composite nanofiber mesh (LHN) designed for localized treatment in GB tumor bed. The LHN, consisting of polyvinyl alcohol and core-shell polylactic acid layers, was loaded with TMZ and rutin. In vitro analysis revealed that LHNTMZ and LHNrutin decelerated epithelial-mesenchymal transition and growth of stem-like cells, while the combination, LHNTMZ +rutin, significantly reduced sphere size compared to untreated and LHNTMZ-treated cells (P < 0.0001). In an orthotopic C6-induced GB rat model, LHNTMZ +rutin therapy demonstrated a more pronounced tumor-reducing effect than LHNTMZ alone. Tumor volume, assessed by magnetic resonance imaging, was significantly reduced in LHNTMZ +rutin-treated rats compared to untreated controls. Structural changes in tumor mitochondria, reduced membrane potential, and decreased PARP expression indicated the activation of apoptotic pathways in tumor cells, which was further confirmed by a reduction in PHH3, indicating decreased mitotic activity of tumor cells. Additionally, the local application of LHNs in the GB model mitigated aggressive tumor features without causing local tissue inflammation or adverse systemic effects. This was evidenced by a decrease in the angiogenesis marker CD31, the absence of inflammation or necrosis in H&E staining of the cerebellum, increased production of IFN-γ, decreased levels of interleukin-4 in splenic T cells, and lower serum AST levels. Our findings collectively indicate that LHNTMZ +rutin is a promising biocompatible model for the local treatment of GB.

Predictive value of ZFHX4 mutation for the efficacy of immune checkpoint inhibitors in non-small cell lung cancer and melanoma

Studies have shown that the Zinc finger homeobox 4 (ZFHX4) might be a factor in the prognosis of malignancies. However, little is known about the association between the ZFHX4 mutation and the effectiveness of immune checkpoint inhibitors (ICIs) in non-small cell lung cancer (NSCLC) and melanoma. Three public ICIs-treated NSCLC cohorts were divided into discovery cohort (n=75) and validation cohort (n=62), which were used to evaluate the relationship between ZFHX4 mutation and ICIs effectiveness in NSCLC. Seven ICIs-treated melanoma cohorts (n = 418) were used to analyze the relationship between ZFHX4 mutation and immunotherapy efficacy in melanoma. NSCLC and skin cutaneous melanoma (SKCM) cohorts from The Cancer Genome Atlas (TCGA) were used to investigate underlying mechanism. Patients with ZFHX4 mutant-type (ZFHX4-Mut) showed a superior objective response rate (ORR) (P < 0.01) and longer progression-free survival (PFS) (P < 0.05) than patients with ZFHX4 wild-type (ZFHX4-WT) in NSCLC cohorts. In the melanoma cohorts, patients carrying ZFHX4-Mut had a higher ORR (P = 0.042) and longer overall survival (OS) (P = 0.011). Besides, patients with NSCLC and melanoma harboring ZFHX4-Mut had a higher tumor mutation burden (TMB) (P<0.001) and tumor neoantigen burden (TNB) (P<0.001) than those harboring ZFHX4-WT. ZFHX4 mutation was associated with higher levels of plasma B cells, activated CD4+ memory T cells, and CD8+ T cells. Seven DNA damage repair pathways were significantly enriched in the ZFHX4-Mut group. ZFHX4 mutation could serve as a predicter for the efficacy of ICIs therapy in NSCLC and melanoma.

Necroptosis-based glioblastoma prognostic subtypes: implications for TME remodeling and therapy response

BACKGROUND

Glioblastoma (GBM) is an aggressive primary brain tumor with a high recurrence rate and poor prognosis. Necroptosis, a pathological hallmark of GBM, is poorly understood in terms of its role in prognosis, tumor microenvironment (TME) alteration, and immunotherapy.

METHODS & RESULTS

We assessed the expression of 55 necroptosis-related genes in GBM and normal brain tissues. We identified necroptosis-stratified clusters using Uni-Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression to establish the 10-gene Glioblastoma Necroptosis Index (GNI). GNI demonstrated significant prognostic efficacy in the TCGA dataset (n = 160) and internal validation dataset (n = 345) and in external validation cohorts (n = 591). The GNI-high subgroup displayed a mesenchymal phenotype, lacking the IDH1 mutation, and MGMT methylation. This subgroup was characterized by significant enrichment in inflammatory and humoral immune pathways with prominent cell adhesion molecules (CD44 and ICAM1), inflammatory cytokines (TGFB1, IL1B, and IL10), and chemokines (CX3CL1, CXCL9, and CCL5). The TME in this subgroup showed elevated infiltration of M0 macrophages, neutrophils, mast cells, and regulatory T cells. GNI-related genes appeared to limit macrophage polarization, as confirmed by immunohistochemistry and flow cytometry. The top 30% high-risk score subset exhibited increased CD8 T cell infiltration and enhanced cytolytic activity. GNI showed promise in predicting responses to immunotherapy and targeted treatment.

CONCLUSIONS

Our study highlights the role of necroptosis-related genes in glioblastoma (GBM) and their effects on the tumor microenvironment and patient prognosis. TheGNI demonstrates potential as a prognostic marker and provides insights into immune characteristics and treatment responsiveness.

Therapeutic treatments targeting communication between angiogenic and immune microenvironments in thyroid cancers

Thyroid cancer treatment has recently been revolutionized by the introduction of specific targeted therapies (e.g. BRAFV600E or highly selective RET inhibitors), anti-angiogenic agents (e.g. tyrosine kinase inhibitors (TKIs)) and immune checkpoint inhibitors, which significantly ameliorate outcomes in selected groups of thyroid cancer patients. Targeted and anti-angiogenic treatments are characterized by transient and partial efficacy, due to primary or secondary tumor resistance mechanisms, and toxicity profile. Immune therapy-based approaches are producing preliminary results. Herein, we review and prospectively discuss immune microenvironment in non-medullary and medullary thyroid cancers and its interplays with angiogenic microenvironment (endothelial cells and pericytes). In addition, we discuss how these interactions might be targeted using combined therapies. Furthermore, we will review chimeric antigen receptor (CAR) T cells treatment that potentially may ensure a more durable and effective response in advanced thyroid cancers. In sum, angiogenic and immune microenvironments show functional connectivity in TCs. Therapies with anti-angiogenic and immune checkpoint inhibitors combined with specific targeted therapy inhibitors with a tolerable toxicity profile may overcome drug resistance and provide better clinical outcomes than single agents.

Understanding the biological processes of kidney carcinogenesis: an integrative multi-omics approach

Biological mechanisms related to cancer development can leave distinct molecular fingerprints in tumours. By leveraging multi-omics and epidemiological information, we can unveil relationships between carcinogenesis processes that would otherwise remain hidden. Our integrative analysis of DNA methylome, transcriptome, and somatic mutation profiles of kidney tumours linked ageing, epithelial-mesenchymal transition (EMT), and xenobiotic metabolism to kidney carcinogenesis. Ageing process was represented by associations with cellular mitotic clocks such as epiTOC2, SBS1, telomere length, and PBRM1 and SETD2 mutations, which ticked faster as tumours progressed. We identified a relationship between BAP1 driver mutations and the epigenetic upregulation of EMT genes (IL20RB and WT1), correlating with increased tumour immune infiltration, advanced stage, and poorer patient survival. We also observed an interaction between epigenetic silencing of the xenobiotic metabolism gene GSTP1 and tobacco use, suggesting a link to genotoxic effects and impaired xenobiotic metabolism. Our pan-cancer analysis showed these relationships in other tumour types. Our study enhances the understanding of kidney carcinogenesis and its relation to risk factors and progression, with implications for other tumour types.

Evolutionary View of Liver Pathology

Evolutionary medicine emerged in the late twentieth century, integrating principles of natural selection and adaptation with the health sciences. Today, with a rapidly widening gap between the biology of Homo sapiens and its environment, maladaptation or maladaptive disorders can be detected in almost all diseases, including liver dysfunction. However, in hepatology, as in most medical specialties, evolutionary considerations are neglected because the majority of the medical community is not familiar with evolutionary principles. The aim of this brief review is to highlight an evolutionary approach that may facilitate understanding various liver diseases.

Recent progress in molecular classification of phaeochromocytoma and paraganglioma

Phaeochromocytomas (PC) and paragangliomas (PG) are neural crest cancers with high heritability. Recent advances in molecular profiling, including multi-omics and single cell genomics has identified up to seven distinct molecular subtypes. These subtypes are defined by mutations involving hypoxia-inducible factors (HIFs), Krebs cycle, kinase and WNT signalling, but are also defined by chromaffin differentiation states. PCPG have a dominant proangiogenic microenvironment linked to HIF pathway activity and are generally considered "immune cold" tumours with a high number of macrophages. PCPG subtypes can indicate increased metastatic risk but secondary mutations in telomere maintenance genes TERT or ATRX are required to drive the metastatic phenotype. Molecular profiling can identify molecular therapeutic (e.g. RET and EPAS1) and radiopharmaceutical targets while also helping to support variant pathogenicity and familial risk. Molecular profiling and subtyping of PCPG therefore confers the possibility of nuanced prognostication and individual treatment stratification but this still requires large-scale prospective validation.

Identification of Cuproptosis-Related Patterns Predict Prognosis and Immunotherapy Response in Hepatocellular Carcinoma

A novel copper-dependent mode of death, cuproptosis, has been newly identified. This study developed a cuproptosis score (CS) based on the cuproptosis model to analyse the association of CS with prognosis, immune cell infiltration, drug sensitivity and immunotherapy response in hepatocellular carcinoma (HCC) patients. A typing model of cuproptosis was constructed based on the expression of 19 cuproptosis-related genes (CRGs). A total of 485 samples were divided into high scoring group (HSG) and low scoring group (LSG) according to CS, and the drug sensitivity and responsiveness to immunotherapy were evaluated by combining the immunophenotype score (IPS), oncoPredict, the tumour immune dysfunction and rejection (TIDE). The use of weighted gene coexpression network analysis (WGCNA) identified key prognostic genes for cuproptosis. Western blotting was used to detect the expression level of the key gene. The CRG key gene glutaminase (GLS) is highly expressed in HCC, and patients with high expression of GLS have a poorer prognosis. Furthermore, cell function experiments, such as proliferation, migration and invasion assays, confirmed that GLS knockdown significantly changed the incidence and progression of HCC. This study suggests that new biological markers associated with cuproptosis can be used in the clinical diagnosis of HCC patients to predict prognosis and therapeutic targets.

Spatial heterogeneity of infiltrating immune cells in the tumor microenvironment of non-small cell lung cancer

Tumor-infiltrating lymphocytes (TILs) are essential components of the tumor microenvironment (TME) of non-small cell lung cancer (NSCLC). Still, it is difficult to describe due to their heterogeneity. In this study, five cell markers from NSCLC patients were analyzed. We segmented tumor cells (TCs) and TILs using Efficientnet-B3 and explored their quantitative information and spatial distribution. After that, we simulated multiplex immunohistochemistry (mIHC) by overlapping continuous single chromogenic IHCs slices. As a result, the proportion and the density of programmed cell death-ligand 1 (PD-L1)-positive TCs were the highest in the core. CD8+ T cells were the closest to the tumor (median distance: 41.71 μm), while PD-1+T cells were the most distant (median distance: 62.2μm), and our study found that most lymphocytes clustered together within the peritumoral range of 10-30 μm where cross-talk with TCs could be achieved. We also found that the classification of TME could be achieved using CD8+ T-cell density, which is correlated with the prognosis of patients. In addition, we achieved single chromogenic IHC slices overlap based on CD4-stained IHC slices. We explored the number and spatial distribution of cells in heterogeneous TME of NSCLC patients and achieved TME classification. We also found a way to show the co-expression of multiple molecules economically.

Single-Cell Analysis of Bone Marrow CD8+ T Cells in Myeloid Neoplasms Reveals Pathways Associated with Disease Progression and Response to Treatment with Azacitidine

SIGNIFICANCE

Immunophenotypic analysis identified a BM CD57+CXCR3+ subset of CD8+ T cells associated with response to AZA in patients with MDS and AML. Single-cell RNA sequencing analysis revealed that IFN signaling is linked to the response to treatment, whereas TGF-β signaling is associated with treatment failure, providing insights into new therapeutic approaches.

Uncovering the potential of APOD as a biomarker in gastric cancer: A retrospective and multi-center study

Gastric cancer (GC) poses a significant health challenge worldwide, necessitating the identification of predictive biomarkers to improve prognosis. Dysregulated lipid metabolism is a well-recognized hallmark of tumorigenesis, prompting investigation into apolipoproteins (APOs). In this study, we focused on apolipoprotein D (APOD) following comprehensive analyses of APOs in pan-cancer. Utilizing data from the TCGA-STAD and GSE62254 cohorts, we elucidated associations between APOD expression and multiple facets of GC, including prognosis, tumor microenvironment (TME), cancer biomarkers, mutations, and immunotherapy response, and identified potential anti-GC drugs. Single-cell analyses and immunohistochemical staining confirmed APOD expression in fibroblasts within the GC microenvironment. Additionally, we independently validated the prognostic significance of APOD in the ZN-GC cohort. Our comprehensive analyses revealed that high APOD expression in GC patients was notably associated with unfavorable clinical outcomes, reduced microsatellite instability and tumor mutation burden, alterations in the TME, and diminished response to immunotherapy. These findings provide valuable insights into the potential prognostic and therapeutic implications of APOD in GC.

Tumor Expression of CD83 Reduces Glioma Progression and Is Associated with Reduced Immunosuppression

SIGNIFICANCE

Immunosuppression in malignant glioma remains a barrier to therapeutic development. CD83 overexpression in human and mouse glioma increases survival. CD83+ tumor cells promote signatures related to cytotoxic T cells, enhanced activation of CD8+ T cells, and increased proinflammatory cytokines. These findings suggest that tumor-expressed CD83 could mediate tumor-immune communications.

Novel pharmacotherapies for the treatment of liposarcoma: a comprehensive update

INTRODUCTION

Liposarcomas are malignancies of adipocytic lineage and represent one of the most common types of soft tissue sarcomas. They encompass multiple histologies, each with unique molecular profiles. Treatment for localized disease includes resection, potentially with perioperative radiation or systemic therapy. Treatment for unresectable or metastatic disease revolves around palliative systemic therapy, for which improved therapies are urgently needed.

AREAS COVERED

We reviewed the literature on novel therapies in clinical development for liposarcomas within the past 5 years and discuss their potential impact on future treatment strategies.

EXPERT OPINION

Understanding of the molecular characteristics of liposarcoma subtypes has led to testing of several targeted therapies, including inhibitors of amplified gene products (CDK4 and MDM2) and upregulated proteins (XPO1). Immuno-oncology has played an increasing role in the treatment of liposarcomas, with checkpoint inhibition showing promise in dedifferentiated liposarcomas, and immune therapies targeting cancer testis antigens NY-ESO-1 and MAGE family proteins poised to become an option for myxoid/round cell liposarcomas. The search for novel agents from existing classes (tyrosine kinase inhibitors) with efficacy in liposarcoma also continues. Combination therapies as well as biomarker identification for patient selection of therapies warrant ongoing exploration.

Inhibition of Selenoprotein I promotes ferroptosis and reverses resistance to platinum chemotherapy by impairing Akt phosphorylation in ovarian cancer

Ovarian cancer (OV) ranks among the deadliest gynecological cancer, known for its high risk of relapse and metastasis, and a general resistance to conventional platinum-based chemotherapy. Selenoprotein I (SELENOI) is a crucial mediator implicated in human hereditary spastic paraplegia. However, its role in human tumors remains poorly elucidated. Here, we comprehensively analyzed SELENOI expression patterns, functions, and clinical implications across various malignancies through the integration of bulk transcriptomics, cancer databases, and in vitro and in vivo experiments. Pan-cancer analysis indicated upregulated SELENOI expression across various cancers, correlating with augmented malignancy, suppressed tumor immunity and poor prognosis. Knockdown of SELENOI caused G0/G1-phase cell cycle arrest and diminished aggressive cancer phenotypes in OV cells. Moreover, SELENOI inhibition augments ferroptosis and reverses the cisplatin resistance in OV cells by modulating Akt phosphorylation. Conversely, overexpression of SELENOI in OV cells enhanced therapeutic sensitivity to cisplatin by upregulating Akt phosphorylation. Importantly, in vivo studies demonstrated that SELENOI inhibition suppressed ovarian tumor growth and enhanced cisplatin's anticancer effects. These findings highlight the significant role of SELENOI in OV by modulating ferroptosis and chemotherapy resistance. Targeting SELENOI represents a promising therapeutic approach to promote the efficacy of platinum-based chemotherapy in OV, particularly in cases of resistance.

Integrating bulk and single-cell transcriptomics to elucidate the role and potential mechanisms of autophagy in aging tissue

PURPOSE

Autophagy is frequently observed in tissues during the aging process, yet the tissues most strongly correlated with autophagy during aging and the underlying regulatory mechanisms remain inadequately understood. The purpose of this study is to identify the tissues with the highest correlation between autophagy and aging, and to explore the functions and mechanisms of autophagy in the aging tissue microenvironment.

METHODS

Integrated bulk RNA-seq from over 7000 normal tissue samples, single-cell sequencing data from blood samples of different ages, more than 2000 acute myeloid leukemia (AML) bulk RNA-seq, and multiple sets of AML single-cell data. The datasets were analysed using various bioinformatic approaches.

RESULTS

Blood tissue exhibited the highest positive correlation between autophagy and aging among healthy tissues. Single-cell resolution analysis revealed that in aged blood, classical monocytes (C. monocytes) are most closely associated with elevated autophagy levels. Increased autophagy in these monocytes correlated with a higher proportion of C. monocytes, with hypoxia identified as a crucial contributing factor. In AML, a representative myeloid blood disease, enhanced autophagy was accompanied by an increased proportionof C. monocytes. High autophagy levels in monocytes are associated with pro-inflammatory gene upregulation and Reactive Oxygen Species (ROS) accumulation, contributing to tissue aging.

CONCLUSION

This study revealed that autophagy is most strongly correlated with aging in blood tissue. Enhanced autophagy levels in C. monocytes demonstrate a positive correlation with increased secretion of pro-inflammatory factors and elevated production of ROS, which may contribute to a more rapid aging process. This discovery underscores the critical role of autophagy in blood aging and suggests potential therapeutic targets to mitigate aging-related health issues.

Predictive role of HPGD gene in carcinogenesis and immune environment monitoring in human cervical cancer

Background15-Hydroxyprostaglandin dehydrogenase (15-PGDH, gene symbol HPGD) is considered a tumor suppressor, and its expression is often proportional to the anticancer response. However, the clinical significance of HPGD/15-PGDH in predicting immune response and its diagnosis and prognosis value in cervical cancer remains unclear.ObjectiveThis study aims to explore the clinical significance of HPGD/15-PGDH in predicting carcinogenesis, prognosis, and sensitivity to immuno- and chemotherapy in cervical cancer.MethodsA comprehensive evaluation of the diagnostic, treatment-sensitive, and prognostic value of HPGD/15-PGDH in cervical cancer was conducted by bioinformatics analysis of public databases and validation of real cohort data.ResultsBioinformatics analysis showed that HPGD expression was decreased in cervical cancer and did not independently predict patient prognosis. Low HPGD expression was linked to resistance to certain chemotherapies, potentially due to immunosuppression triggered by low HPGD levels. Validation in clinical samples from the local hospital confirmed the decreased 15-PGDH expression and increased COX-2 expression in HPV16-positive cervical cancer patients and increased immune suppression during cancer progression.ConclusionsHPGD/15-PGDH is a potential biomarker for predicting the progression, immune response, and chemotherapy sensitivity of cervical cancer, with implications that it is of great value for the diagnosis and individual-based treatment of cervical cancer.

Pan-cancer landscape of disulfidptosis across human tumors

Objective

Disulfidptosis is a newly discovered disulfide stress-induced cell death form. Clinical significance and biological mechanisms of disulfidptosis in human cancers need to be further elucidated. Thus, this study was designed to characterize pan-cancer landscape of disulfidptosis across human tumors.

Methods

Multi-omics features (transcriptomics, genomics, and DNA methylation) of disulfidptosis genes were investigated in TCGA pan-cancer cohorts. A disulfidptosis score system was defined across human tumors via ssGSEA. The activity of classical oncogenic pathways and hallmarks of cancer as well as the infiltration of immunocyte subpopulations were estimated, respectively. Drug sensitivity was inferred, and immune checkpoint blockade (ICB) response was evaluated in an independent cohort IMvigor210. ACHN, CAL-27, and NCI-H23 cells were transiently transfected with GYS1 siRNAs, and cell apoptosis and proliferation were measured through TUNEL and EdU assays, respectively.

Results

Aberrant mRNA expression and DNA methylation of disulfidptosis genes as well as their genomic alterations were found in human tumors. The disulfidptosis score was utilized for quantifying the activity of disulfidptosis, which enabled to estimate patient prognosis. The disulfidptosis score presented positive correlations to angiogenesis and EMT, indicating the role of disulfidptosis in mediating tumor malignant features. Moreover, the score was negatively linked with infiltrating immune and stromal cells in the immune microenvironment. In the ICB cohort, shorter survival time was observed in patients with high disulfidptosis score, indicating the potential of disulfidptosis score in influencing clinical benefits from ICB. Additionally, tumors with low disulfidptosis score exhibited higher sensitivity to a few small molecular compounds, e.g., Sabutoclax, PRIMA-1MET, BIBR-1532, and Elephantin. Knockdown of disulfidptosis gene GYS1 effectively hindered tumor progression.

Conclusion

Collectively, our findings depict a pan-cancer map of disulfidptosis to inform functional and therapeutic research.

Identification of HER2-positive breast cancer molecular subtypes with potential clinical implications in the ALTTO clinical trial

In HER2-positive breast cancer, clinical outcome and sensitivity to HER2-targeted therapies are influenced by both tumor and microenvironment features. However, we are currently unable to depict the molecular heterogeneity of this disease with sufficient granularity. Here, by performing gene expression profiling in HER2-positive breast cancers from patients receiving adjuvant trastuzumab in the ALTTO clinical trial (NCT00490139), we identify and characterize five molecular subtypes associated with the risk of distant recurrence: immune-enriched, proliferative/metabolic-enriched, mesenchymal/stroma-enriched, luminal, and ERBB2-dependent. Additionally, we validate the biological profiles of the subtypes and explore their prognostic/predictive value in external cohorts, namely the NeoALTTO trial (NCT00553358), SCAN-B (NCT02306096), I-SPY2 (NCT01042379), METABRIC and TCGA. Immune-enriched tumors present better survival outcomes, in contrast to mesenchymal/stroma-enriched and proliferative/metabolic-enriched tumors, while luminal and ERBB2-dependent tumors are characterized by low and high rates of pathological complete response, respectively. Of note, these molecular subtypes provide the rationale for treatment approaches leveraging the heterogeneous biology of HER2-positive breast cancer.

Mutation-guided chemotherapy-free strategy in first-line immunotherapy for low PD-L1-expressing non-squamous NSCLC

BACKGROUND

The necessity of platinum-doublet chemotherapy in first-line immunotherapy for non-squamous non-small cell lung cancer (nsqNSCLC) with programmed death-ligand 1 (PD-L1) expression on less than 50% of tumor cells remains poorly investigated. Biomarkers predicting this necessity can guide chemotherapy-free treatment to minimize unnecessary toxicity.

METHODS

Treated with immune checkpoint inhibitor monotherapy (ICI-mono), chemotherapy, or combination (ICI-chemo), 790 low PD-L1-expressing nsqNSCLCs (in-house: n=83; public: n=707) were analyzed for development and validation of the interaction score for additional chemotherapy (ISAC). Transcriptomic (public, n=11) and multiplex immunofluorescence data (in-house, n=100) were analyzed to evaluate the immune microenvironment.

RESULTS

ICI-chemo, compared with ICI-mono, tended to prolong progression-free survival (PFS; HR=0.72, p=0.004) and overall survival (OS; HR=0.77, p=0.071) as first-line therapy in low PD-L1-expressing nsqNSCLCs. The added value of chemotherapy was observed in the ISAC-low subgroup (PFS: HR=0.48, p<0.001; OS: HR=0.53, p=0.001) rather than the ISAC-high subgroup (PFS: HR=1.08, p=0.65; OS: HR=1.14, p=0.56). This predictive utility was independent of tumor mutational burden and PD-L1 expression, indicated by subgroup and multivariable analyses. A high ISAC was associated with adaptive immune resistance reflected by more proinflammatory (eg, CD8+ T cells and M1 macrophages) rather than anti-inflammatory tumor-infiltrating immune cells (eg, M2 macrophages) and high expression of immune checkpoints except for PD-L1 (eg, programmed cell death protein-1).

CONCLUSION

A high ISAC was identified as a significant predictor for virtually no added value of platinum-doublet chemotherapy for first-line ICI treatment in low PD-L1-expressing nsqNSCLC. Our findings may help refine personalized therapeutic strategies for nsqNSCLC, thereby improving efficacy and reducing undue toxicity.

Comprehensive Analysis Reveals That ISCA1 Is Correlated with Ferroptosis-Related Genes Across Cancers and Is a Biomarker in Thyroid Carcinoma

BACKGROUND

ISCA1 (Iron-Sulfur Cluster Assembly 1) is involved in the assembly of iron-sulfur (Fe-S) clusters, which are vital for electron transport and enzyme activity. Some studies suggest the potential involvement of ISCA1 in tumor progression through interactions with ferroptosis-related genes (FRGs) and the tumor immune microenvironment (TME). However, there has been no systematic analysis of its role in FRGs and the TME or its predictive value for prognosis and immunotherapy response across different cancer types.

METHODS

In this study, we analyzed the expression and prognosis of ISCA1 RNA, CNV, methylation, and protein in multiple tumor tissues via data from the TCGA and CPTAC databases and clinical information. We conducted a comprehensive analysis of the correlations between ISCA1 and FRGs, immune-related genes (including immune regulatory genes and immune checkpoint genes), immune cell infiltration, immune infiltration scores, tumor stemness, and genomic heterogeneity.

RESULTS

We performed drug prediction and validation through molecular docking and molecular dynamics analysis to identify candidate drugs that could promote or inhibit ISCA1 RNA expression. Our findings revealed that ISCA1 could serve as a biomarker in thyroid carcinoma, play a role with different FRGs in various cell types, and mediate different ligand-receptor pathways for cell-cell communication.

CONCLUSIONS

Overall, our study highlights the potential of ISCA1 as a novel biomarker for predicting prognosis and immunotherapeutic efficacy in thyroid carcinoma and suggests its potential for developing novel antitumor drugs or improving immunotherapy.

Analysis and experimental validation of disulfidptosis related genes solute carrier family 3 member 2 (SLC3A2) in endometrial cancer

Disulfidptosis, a novel cell death paradigm triggered by disulfide stress, remains underexplored, particularly its implications for endometrial cancer (EC). This study focused on the prognostic significance of disulfidptosis-related genes (DRGs) in EC, highlighting the pivotal role of SLC3A2. To predict EC patient outcomes, we developed a model centered on DRGs, employing LASSO-Cox regression for its construction. The model revealed a strong correlation between DRG risk score, gene set enrichment analysis (GSEA), single-sample GSEA (ssGSEA), clinical characteristics, the tumor microenvironment (TME), and the response to immunotherapy. Key genes were pinpointed using random forest maps. To establish SLC3A2's oncogenic effects in EC, we conducted comprehensive studies including apoptosis, cell cycle, TRANSWELL, CCK-8, and tumor xenograft assays. SLC3A2 expression was further confirmed via qRT-PCR. The impact of SLC3A2 on EC's malignant behavior was corroborated through both in vitro and in vivo experiments.