Enhancing personalized immune checkpoint therapy by immune archetyping and pharmacological targeting

Deep Learning and Radiomic Signatures Associated with Tumor Immune Heterogeneity Predict Microvascular Invasion in Colon Cancer

RATIONALE AND OBJECTIVES

This study aims to develop and validate a deep learning radiomics signature (DLRS) that integrates radiomics and deep learning features for the non-invasive prediction of microvascular invasion (MVI) in patients with colon cancer (CC). Furthermore, the study explores the potential association between DLRS and tumor immune heterogeneity.

MATERIALS AND METHODS

This study is a multi-center retrospective study that included a total of 1007 patients with colon cancer (CC) from three medical centers and The Cancer Genome Atlas (TCGA-COAD) database. Patients from Medical Centers 1 and 2 were divided into a training cohort (n = 592) and an internal validation cohort (n = 255) in a 7:3 ratio. Medical Center 3 (n = 135) and the TCGA-COAD database (n = 25) were used as external validation cohorts. Radiomics and deep learning features were extracted from contrast-enhanced venous-phase CT images. Feature selection was performed using machine learning algorithms, and three predictive models were developed: a radiomics model, a deep learning (DL) model, and a combined deep learning radiomics (DLR) model. The predictive performance of each model was evaluated using multiple metrics, including the area under the curve (AUC), sensitivity, and specificity. Additionally, differential gene expression analysis was conducted on RNA-seq data from the TCGA-COAD dataset to explore the association between the DLRS and tumor immune heterogeneity within the tumor microenvironment.

RESULTS

Compared to the standalone radiomics and deep learning models, DLR fusion model demonstrated superior predictive performance. The AUC for the internal validation cohort was 0.883 (95% CI: 0.828-0.937), while the AUC for the external validation cohort reached 0.855 (95% CI: 0.775-0.935). Furthermore, stratifying patients from the TCGA-COAD dataset into high-risk and low-risk groups based on the DLRS revealed significant differences in immune cell infiltration and immune checkpoint expression between the two groups (P < 0.05).

CONCLUSION

The contrast-enhanced CT-based DLR fusion model developed in this study effectively predicts the MVI status in patients with CC. This model serves as a non-invasive preoperative assessment tool and reveals a potential association between the DLRS and immune heterogeneity within the tumor microenvironment, providing insights to optimize individualized treatment strategies.

Exploring immune checkpoint inhibitors: Focus on PD-1/PD-L1 axis and beyond

Immunotherapy emerges as a promising approach, marked by recent substantial progress in elucidating how the host immune response impacts tumor development and its sensitivity to various treatments. Immune checkpoint inhibitors have revolutionized cancer therapy by unleashing the power of the immune system to recognize and eradicate tumor cells. Among these, inhibitors targeting the programmed cell death protein 1 (PD-1) and its ligand (PD-L1) have garnered significant attention due to their remarkable clinical efficacy across various malignancies. This review delves into the mechanisms of action, clinical applications, and emerging therapeutic strategies surrounding PD-1/PD-L1 blockade. We explore the intricate interactions between PD-1/PD-L1 and other immune checkpoints, shedding light on combinatorial approaches to enhance treatment outcomes and overcome resistance mechanisms. Furthermore, we discuss the expanding landscape of immune checkpoint inhibitors beyond PD-1/PD-L1, including novel targets such as CTLA-4, LAG-3, TIM-3, and TIGIT. Through a comprehensive analysis of preclinical and clinical studies, we highlight the promise and challenges of immune checkpoint blockade in cancer immunotherapy, paving the way for future advancements in the field.

A pan-cancer analysis of the oncogenic and immunological roles of RGS5 in clear cell renal cell carcinomas based on in vitro experiment validation

BACKGROUND

RGS5, the first gene identified in tumor-resident pericytes, plays a crucial role in angiogenesis. However, its effects on immunology and prognosis in human cancer are still mostly unknown. This study investigates the carcinogenic and immunological roles of RGS5 through a comprehensive pan-cancer analysis.

METHODS

A standardized pan-cancer dataset for RGS5 was obtained from the public database. R software and relevant packages were utilized to analyze the oncogenic and immunological roles. Clinical samples and cellular experiments were conducted to validate RGS5 expression and its biological function in renal cancer.

RESULTS

Bioinformatics analysis revealed that RGS5 is dysregulated in a variety of human malignancies and is significantly associated with patient prognosis. Additionally, RGS5 expression is closely linked to tumor heterogeneity and stemness indicators across different cancer types. Co-expression of RGS5 with genes involved in MHC, immune activation, immunosuppressive proteins, chemokines, and chemokine receptors was observed in various tumors. High expression of RGS5 predicts a good prognosis in patients with renal cancer. In the renal cancer cohort, RGS5 expression strongly correlated with the distribution of tumor-associated fibroblasts. Silencing RGS5 expression can affect the proliferation, migration, and invasion of renal carcinoma cells.

CONCLUSIONS

RGS5 expression in tumors is intricately associated with various clinical features, particularly concerning tumor progression and patient prognosis.

Machine learning and multi-omics characterization of SLC2A1 as a prognostic factor in hepatocellular carcinoma: SLC2A1 is a prognostic factor in HCC

Hepatocellular carcinoma (HCC) is characterized by high incidence, significant mortality, and marked heterogeneity, making accurate molecular subtyping essential for effective treatment. Using multi-omics data from HCC patients, we applied diverse clustering algorithms to identify three HCC subtypes (HSs) with distinct prognostic characteristics. Among these, HS1 emerged as an immune-compromised subtype associated with the poorest prognosis. Additionally, we developed a novel, robust, and highly accurate machine learning-guided prognostic signature (MLPS) by integrating multiple machine learning algorithms and their combinations. Our study also identified SLC2A1, the core gene of MLPS, as being highly expressed during advanced stages of tumor progression. Knockdown experiments demonstrated that reducing SLC2A1 expression significantly suppressed the malignant behavior of HCC cells. Furthermore, SLC2A1 expression was linked to responsiveness to dasatinib and vincristine, suggesting potential therapeutic relevance. MLPS and SLC2A1 offer promising tools for individualized prognosis prediction and targeted therapy in HCC, providing new opportunities to improve patient outcomes.

Understanding the tumor microenvironment for personalized immunotherapy in early-onset head and neck squamous cell carcinoma

Early-onset head and neck squamous cell carcinoma (HNSCC) has been increasingly observed in recent years, exhibiting distinct tumor behavior and a unique tumor microenvironment (TME) compared to older age groups. Studies suggest that early-onset HNSCC is associated with specific risk factors and prognostic outcomes, while the underlying mechanisms driving these age-related differences remain unclear. In this review, we systematically examined original studies involving young HNSCC patient samples, focusing on the characteristics of the TME and potential for personalized immunotherapy. While further evidence is needed, our findings indicate that the TME in early-onset HNSCC often exhibits higher aggressiveness and immune suppression. Consequently, tailored immunotherapy may offer a promising therapeutic strategy for this distinct patient population.

Comprehensive analysis of stearoyl-coenzyme A desaturase in prostate adenocarcinoma: insights into gene expression, immune microenvironment and tumor progression

Prostate adenocarcinoma (PRAD) is a prevalent global malignancy which depends more on lipid metabolism for tumor progression compared to other cancer types. Although Stearoyl-coenzyme A desaturase (SCD) is documented to regulate lipid metabolism in multiple cancers, landscape analysis of its implications in PRAD are still missing at present. Here, we conducted an analysis of diverse cancer datasets revealing elevated SCD expression in the PRAD cohort at both mRNA and protein levels. Interestingly, the elevated expression was associated with SCD promoter hypermethylation and genetic alterations, notably the L134V mutation. Integration of comprehensive tumor immunological and genomic data revealed a robust positive correlation between SCD expression levels and the abundance of CD8+ T cells and macrophages. Further analyses identified significant associations between SCD expression and various immune markers in tumor microenvironment. Single-cell transcriptomic profiling unveiled differential SCD expression patterns across distinct cell types within the prostate tumor microenvironment. The Gene Ontology and Kyoto Encyclopedia of Genes and Genome analyses showed that SCD enriched pathways were primarily related to lipid biosynthesis, cholesterol biosynthesis, endoplasmic reticulum membrane functions, and various metabolic pathways. Gene Set Enrichment Analysis highlighted the involvement of elevated SCD expression in crucial cellular processes, including the cell cycle and biosynthesis of cofactors pathways. In functional studies, SCD overexpression promoted the proliferation, metastasis and invasion of prostate cancer cells, whereas downregulation inhibits these processes. This study provides comprehensive insights into the multifaceted roles of SCD in PRAD pathogenesis, underscoring its potential as both a therapeutic target and prognostic biomarker.

Unveiling the functional roles of patient-derived tumour organoids in assessing the tumour microenvironment and immunotherapy

Recent studies have established the pivotal roles of patient-derived tumour organoids (PDTOs), innovative three-dimensional (3D) culture systems, in various biological and medical applications. PDTOs, as promising tools, have been established and extensively used for drug screening, prediction of immune response and assessment of immunotherapeutic effectiveness in various cancer types, including glioma, ovarian cancer and so on. The overarching goal is to facilitate the translation of new therapeutic modalities to guide personalised immunotherapy. Notably, there has been a recent surge of interest in the co-culture of PDTOs with immune cells to investigate the dynamic interactions between tumour cells and immune microenvironment. A comprehensive and in-depth investigation is necessary to enhance our understanding of PDTOs as promising testing platforms for cancer immunotherapy. This review mainly focuses on the latest updates on the applications and challenges of PDTO-based methods in anti-cancer immune responses. We strive to provide a comprehensive understanding of the potential and prospects of PDTO-based technologies as next-generation strategies for advancing immunotherapy approaches.

The complex interplay of tumor-infiltrating cells in driving therapeutic resistance pathways

Drug resistance remains a significant challenge in cancer treatment. Recently, the interactions among various cell types within the tumor microenvironment (TME) have deepened our understanding of the mechanisms behind treatment resistance. Therefore, this review aims to synthesize current research focusing on infiltrating cells and drug resistance suggesting that targeting the TME could be a viable strategy to combat this issue. Numerous factors, including inflammation, metabolism, senescence, hypoxia, and angiogenesis, contribute to drug resistance could be a viable strategy to combat this issue. Overexpression of STAT3 is commonly associated with drug-resistant cancer cells or stromal cells. Current research often generalizes the impact of stromal cells on resistance, lacking specificity and statistical robustness. Thus, future research should take notice of this issue and aim to provide high-quality evidence. Despite the existing limitations, targeting the TME to overcome therapy resistance hold promising and valuable potential.

The interplay between metal ions and immune cells in glioma: pathways to immune escape

This review explores the intricate roles of metal ions-iron, copper, zinc, and selenium-in glioma pathogenesis and immune evasion. Dysregulated metal ion metabolism significantly contributes to glioma progression by inducing oxidative stress, promoting angiogenesis, and modulating immune cell functions. Iron accumulation enhances oxidative DNA damage, copper activates hypoxia-inducible factors to stimulate angiogenesis, zinc influences cell proliferation and apoptosis, and selenium modulates the tumor microenvironment through its antioxidant properties. These metal ions also facilitate immune escape by upregulating immune checkpoints and secreting immunosuppressive cytokines. Targeting metal ion pathways with therapeutic strategies such as chelating agents and metalloproteinase inhibitors, particularly in combination with conventional treatments like chemotherapy and immunotherapy, shows promise in improving treatment efficacy and overcoming resistance. Future research should leverage advanced bioinformatics and integrative methodologies to deepen the understanding of metal ion-immune interactions, ultimately identifying novel biomarkers and therapeutic targets to enhance glioma management and patient outcomes.

Effect of FGFR alteration on prognosis in 1963 urothelial carcinoma patients with immune checkpoint inhibitors: Implying combination of FGFR inhibitor and immunotherapy for FGFR-altered urothelial carcinoma

Immune checkpoint inhibitors (ICIs) are essential for urothelial carcinoma (UC) treatment. Fibroblast growth factor receptor (FGFR) alterations, as common oncogenic drivers in UC, have been reported to drive T cell depletion of UC immune microenvironment via up-regulating FGFR signaling, which indicated FGFR alterations potentially result in reduced response to ICIs. In addition, the selective pan-FGFR inhibitor showed better clinical benefit in clinical trials, indicating FGFR has emerged as critical therapeutic target via inhibiting FGFR signaling. The present study aims to evaluate prognosis and response to ICIs between FGFR-altered UC patients and FGFR-wildtype UC patients via 1963 UC patients and offers new insights into personalized precision therapy and combination therapy for UC.

Inhibiting autophagy enhanced mitotic catastrophe-mediated anticancer immune responses by regulating the cGAS-STING pathway

Given the limitations of the response rate and efficacy of immune checkpoint inhibitors (ICIs) in clinical applications, exploring new therapeutic strategies for cancer immunotherapy is necessary. We found that 5-(3,4,5-trimethoxybenzoyl)-4-methyl-2-(p-tolyl)imidazole (BZML), a microtubule-targeting agent, exhibited potent anticancer activity by inducing mitotic catastrophe in A549/Taxol and L929 cells. Nuclear membrane disruption and nuclease reduction provided favorable conditions for cGAS-STING pathway activation in cells with mitotic catastrophe. Similar results were obtained in paclitaxel-, docetaxel- and doxorubicin-induced mitotic catastrophe in various cancer cells. Notably, the surface localization of CALR and MHC-I and the release of HMGB1 were also significantly increased in cells with mitotic catastrophe, but not in apoptotic cells, suggesting that mitotic catastrophe is an immunogenic cell death. Furthermore, activated CD8+T cells enhanced the anticancer effects originating from mitotic catastrophe induced by BZML. Inhibiting the cGAS-STING pathway failed to affect BZML-induced mitotic catastrophe but could inhibit mitotic catastrophe-mediated anticancer immune effects. Interestingly, the expression of p-TBK1 first increased and then declined; however, autophagy inhibition reversed the decrease in p-TBK1 expression and enhanced mitotic catastrophe-mediated anticancer immune effects. Collectively, the inhibition of autophagy can potentiate mitotic catastrophe-mediated anticancer immune effects by regulating the cGAS-STING pathway, which explains why the anticancer immune effects induced by chemotherapeutics have not fully exerted their therapeutic efficacy in some patients and opens a new area of research in cancer immunotherapy.