DCS, a novel classifier system based on disulfidptosis reveals tumor microenvironment heterogeneity and guides frontline therapy for clear cell renal carcinoma.

Background: Emerging evidence suggests that cell deaths are involved in tumorigenesis and progression, which may be treated as a novel direction of cancers. Recently, a novel type of programmed cell death, disulfidptosis, was discovered. However, the detailed biological and clinical impact of disulfidptosis and related regulators remains largely unknown. Methods: In this work, we first enrolled pancancer datasets and performed multi-omics analysis, including gene expression, DNA methylation, copy number variation and single nucleic variation profiles. Then we deciphered the biological implication of disulfidptosis in clear cell renal cell carcinoma (ccRCC) by machine learning. Finally, a novel agent targeting at disulfidptosis in ccRCC was identified and verified. Results: We found that disulfidptosis regulators were dysregulated among cancers, which could be explained by aberrant DNA methylation and genomic mutation events. Disulfidptosis scores were depressed among cancers and negatively correlated with epithelial mesenchymal transition. Disulfidptosis regulators could satisfactorily stratify risk subgroups in ccRCC, and a novel subtype, DCS3, owning with disulfidptosis depression, insensitivity to immune therapy and aberrant genome instability were identified and verified. Moreover, treating DCS3 with NU1025 could significantly inhibit ccRCC malignancy. Conclusion: This work provided a better understanding of disulfidptosis in cancers and new insights into individual management based on disulfidptosis.

Machine learning and experimental validation of novel biomarkers for hypertrophic cardiomyopathy and cancers.

Hypertrophic cardiomyopathy (HCM) is a hereditary cardiac disorder marked by anomalous thickening of the myocardium, representing a significant contributor to mortality. While the involvement of immune inflammation in the development of cardiac ailments is well-documented, its specific impact on HCM pathogenesis remains uncertain. Five distinct machine learning algorithms, namely LASSO, SVM, RF, Boruta and XGBoost, were utilized to discover new biomarkers associated with HCM. A unique nomogram was developed using two newly identified biomarkers and subsequently validated. Furthermore, samples of HCM and normal heart tissues were gathered from our institution to confirm the variance in expression levels and prognostic significance of GATM and MGST1. Five novel biomarkers (DARS2, GATM, MGST1, SDSL and ARG2) associated with HCM were identified. Subsequent validation revealed that GATM and MGST1 exhibited significant diagnostic utility for HCM in both the training and test cohorts, with all AUC values exceeding 0.8. Furthermore, a novel risk assessment model for HCM patients based on the expression levels of GATM and MGST1 demonstrated favourable performance in both the training (AUC = 0.88) and test cohorts (AUC = 0.9). Furthermore, our study revealed that GATM and MGST1 exhibited elevated expression levels in HCM tissues, demonstrating strong discriminatory ability between HCM and normal cardiac tissues (AUC of GATM = 0.79; MGST1 = 0.86). Our findings suggest that two specific cell types, monocytes and multipotent progenitors (MPP), may play crucial roles in the pathogenesis of HCM. Notably, GATM and MGST1 were found to be highly expressed in various tumours and showed significant prognostic implications. Functionally, GATM and MGST1 are likely involved in xenobiotic metabolism and epithelial mesenchymal transition in a wide range of cancer types. GATM and MGST1 have been identified as novel biomarkers implicated in the progression of both HCM and cancer. Additionally, monocytes and MPP may also play a role in facilitating the progression of HCM.

Renal cancer: signaling pathways and advances in targeted therapies.

Renal cancer is a highlyheterogeneous malignancy characterized by rising global incidence and mortalityrates. The complex interplay and dysregulation of multiple signaling pathways,including von Hippel-Lindau (VHL)/hypoxia-inducible factor (HIF), phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR), Hippo-yes-associated protein (YAP), Wnt/ß-catenin, cyclic adenosine monophosphate (cAMP), and hepatocyte growth factor (HGF)/c-Met, contribute to theinitiation and progression of renal cancer. Although surgical resection is thestandard treatment for localized renal cancer, recurrence and metastasiscontinue to pose significant challenges. Advanced renal cancer is associatedwith a poor prognosis, and current therapies, such as targeted agents andimmunotherapies, have limitations. This review presents a comprehensiveoverview of the molecular mechanisms underlying aberrant signaling pathways inrenal cancer, emphasizing their intricate crosstalk and synergisticinteractions. We discuss recent advancements in targeted therapies, includingtyrosine kinase inhibitors, and immunotherapies, such as checkpoint inhibitors.Moreover, we underscore the importance of multiomics approaches and networkanalysis in elucidating the complex regulatory networks governing renal cancerpathogenesis. By integrating cutting-edge research and clinical insights, this review contributesto the development of innovative diagnostic and therapeutic strategies, whichhave the potential to improve risk stratification, precision medicine, andultimately, patient outcomes in renal cancer.

Effective strategies to enhance the diagnosis and treatment of RCC: The application of biocompatible materials.

Renal cell carcinoma (RCC) is recognized as one of the three primary malignant tumors affecting the urinary system, posing a significant risk to human health and life. Despite advancements in understanding RCC, challenges persist in its diagnosis and treatment, particularly in early detection and diagnosis due to issues of low specificity and sensitivity. Consequently, there is an urgent need for the development of effective strategies to enhance diagnostic accuracy and treatment outcomes for RCC. In recent years, with the extensive research on materials for applications in the biomedical field, some materials have been identified as promising for clinical applications, e.g., in the diagnosis and treatment of many tumors, including RCC. Herein, we summarize the latest materials that are being studied and have been applied in the early diagnosis and treatment of RCC. While focusing on their adjuvant effects, we also discuss their technical principles and safety, thus highlighting the value and potential of their application. In addition, we also discuss the limitations of the application of these materials and possible future directions, providing new insights for improving RCC diagnosis and treatment.

Corrigendum to 'Effective strategies to enhance the diagnosis and treatment of RCC: The application of biocompatible materials' [Mater. Today Bio 27 (2024) 101149].

[This corrects the article DOI: 10.1016/j.mtbio.2024.101149.].

Identifying novel risk genes in intracranial aneurysm by integrating human proteomes and genetics.

Genome-wide association studies (GWAS) have become increasingly popular for detecting numerous loci associated with intracranial aneurysm (IA), but how these loci function remains unclear. In this study, we employed an integrative analytical pipeline to efficiently transform genetic associations and identify novel genes for IA. Using multidimensional high-throughput data, we integrated proteome-wide association studies (PWAS), transcriptome-wide association studies (TWAS), Mendelian randomization (MR) and Bayesian co-localization analyses to prioritize genes that can increase IA risk by altering their expression and protein abundances in the brain and blood. Moreover, single-cell RNA sequencing (scRNA-seq) of the circle of Willis was performed to enrich filtered genes in cells, and gene set enrichment analysis (GSEA) was conducted for each gene using bulk RNA-seq data for IA. No significant genes with cis-regulated plasma protein levels were proven to be associated with IA. The protein abundances of five genes in the brain were found to be associated with IA. According to cellular enrichment analysis, these five genes were expressed mainly in the endothelium, fibroblasts and vascular smooth muscle cells. Only three genes, CNNM2, GPRIN3 and UFL1, passed MR and Bayesian co-localization analyses. While UFL1 was not validated in confirmation PWAS as it was not profiled, it was validated in TWAS. GSEA suggested these three genes are associated with the cell cycle. In addition, the protein abundance of CNNM2 was found to be associated with IA rupture (based on PWAS, MR and co-localization analyses). Our findings indicated that CNNM2, GPRIN3 and UFL1 (CNNM2 correlated with IA rupture) are potential IA risk genes that may provide a broad hint for future research on possible mechanisms and therapeutic targets for IA.

Deciphering lung adenocarcinoma prognosis and immunotherapy response through an AI-driven stemness-related gene signature.

Lung adenocarcinoma (LUAD) is a leading cause of cancer-related deaths, and improving prognostic accuracy is vital for personalised treatment approaches, especially in the context of immunotherapy. In this study, we constructed an artificial intelligence (AI)-driven stemness-related gene signature (SRS) that deciphered LUAD prognosis and immunotherapy response. CytoTRACE analysis of single-cell RNA sequencing data identified genes associated with stemness in LUAD epithelial cells. An AI network integrating traditional regression, machine learning, and deep learning algorithms constructed the SRS based on genes associated with stemness. Subsequently, we conducted a comprehensive exploration of the connection between SRS and both intrinsic and extrinsic immune environments using multi-omics data. Experimental validation through siRNA knockdown in LUAD cell lines, followed by assessments of proliferation, migration, and invasion, confirmed the functional role of CKS1B, a top SRS gene. The SRS demonstrated high precision in predicting LUAD prognosis and likelihood of benefiting from immunotherapy. High-risk groups classified by the SRS exhibited decreased immunogenicity and reduced immune cell infiltration, indicating challenges for immunotherapy. Conversely, in vitro experiments revealed CKS1B knockdown significantly impaired aggressive cancer phenotypes like proliferation, migration, and invasion of LUAD cells, highlighting its pivotal role. These results underscore a close association between stemness and tumour immunity, offering predictive insights into the immune landscape and immunotherapy responses in LUAD. The newly established SRS holds promise as a valuable tool for selecting LUAD populations likely to benefit from future clinical stratification efforts.

Characterization of second primary malignancies post CAR T-cell therapy: real-world insights from the two global pharmacovigilance databases of FAERS and VigiBase.

Background: The FDA's alerts regarding the T-cell lymphoma risk post CAR-T therapy has garnered global attention, yet a comprehensive profile of second primary malignancies (SPMs) following CAR-T treatment is lacking. Methods: We extracted adverse event reports of hematological malignancies (HMs) patients with clearly definable SPMs from the FAERS and VigiBase databases (2017-2023). Disproportionality analysis using reporting odds ratio (ROR) and adjusted ROR was performed to assess associations between SPMs and CAR-T therapy. Time-to-onset analysis explored factors affecting SPM manifestation. Findings: SPMs post CAR T-cell therapy include HMs and solid tumors. T-cell lymphoma and myelodysplastic syndromes were consistently identified as positive signals across the overall and subgroup analyses. Hematological SPMs showed earlier onset with increasing annual incidence post CAR-T therapy, whereas solid tumors exhibit delayed manifestation. SPMs in CAR-T recipients had significantly earlier onset than non-recipients. Furthermore, age-specific characteristics reveal earlier SPM manifestations in pediatric, adolescent, and young adult populations compared to older populations post CAR-T therapy. Interpretation: The current SPM profile highlights the necessity of long-term safety monitoring for all CAR-T recipients given the observed yearly increase of SPMs. Customizing long-term SPM screening across different age groups may enhance early detection and intervention strategies, ultimately improving patient outcomes in the follow-up of CAR-T recipients. Funding: This work was supported by grants from the Natural Science Foundation of Guangdong Province (2018A030313846 and 2021A1515012593), the Science and Technology Planning Project of Guangdong Province (2019A030317020), the National Natural Science Foundation of China (81802257, 81871859, 81772457, 82172750, 82172811, and 82260546), the Guangdong Basic and Applied Basic Research Foundation (Guangdong-Guangzhou Joint Funds) (2022A1515111212), and the Science and Technology Program of Guangzhou (2023A04J1257).

B-cell performance in chemotherapy: Unravelling the mystery of B-cell therapeutic potential.

BACKGROUND AND MAIN BODY: The anti-tumour and tumour-promoting roles of B cells in the tumour microenvironment (TME) have gained considerable attention in recent years. As essential orchestrators of humoral immunity, B cells potentially play a crucial role in anti-tumour therapies. Chemotherapy, a mainstay in cancer treatment, influences the proliferation and function of diverse B-cell subsets and their crosstalk with the TME. Modulating B-cell function by targeting B cells or their associated cells may enhance chemotherapy efficacy, presenting a promising avenue for future targeted therapy investigations. CONCLUSION: This review explores the intricate interplay between chemotherapy and B cells, underscoring the pivotal role of B cells in chemotherapy treatment. We summarise promising B-cell-related therapeutic targets, illustrating the immense potential of B cells in anti-tumour therapy. Our work lays a theoretical foundation for harnessing B cells in chemotherapy and combination strategies for cancer treatment. KEY POINTS: Chemotherapy can inhibit B-cell proliferation and alter subset distributions and functions, including factor secretion, receptor signalling, and costimulation. Chemotherapy can modulate complex B-cell-T-cell interactions with variable effects on anti-tumour immunity. Targeting B-cell surface markers or signalling improves chemotherapy responses, blocks immune evasion and inhibits tumour growth. Critical knowledge gaps remain regarding B-cell interactions in TME, B-cell chemoresistance mechanisms, TLS biology, heterogeneity, spatial distributions, chemotherapy drug selection and B-cell targets that future studies should address.

Reversing MET-Mediated Resistance in Oncogene-Driven NSCLC by MET-Activated Wnt Condensative Prodrug.

The amplification of MET is a major cause of acquired resistance to targeted therapy in EGFR-mutant non-small-cell lung cancer (NSCLC), only to be temporarily restrained by the partial efficacy of MET inhibitors. This study reveals that the MET inhibitor has unexpectedly limited efficacy due to amplified MET triggering a strong positive feedback loop in the Wnt/ß-catenin signaling pathway, allowing optimal functionality even when the MET pathway is suppressed again. To test this conjecture and specifically target the Wnt/ß-catenin pathway, a cleverly designed Wnt condensative pro drug called WntSI is developed using reversible supramolecular self-assembly driven by liquidliquid phase separation (LLPS). This process involves a MET/pH-responsive peptide (Tyr-Pep) and a potent Wnt inhibitor known as CA. Upon recognition and phosphorylation of Tyr-Pep by over expressed MET in cells, it disrupts LLPS propensity and facilitates the disintegration of WntSI. Consequently,this enables it to suppress the carcinogenic effect mediated by ß-catenin,effectively overcoming acquired resistance to EGFR-TKIs caused by MET amplification in both cell line-derived and patient-derived tumor xenograft (PDX) mouse models while maintaining exceptional biosecurity. This effective strategy not only suppresses the Wnt/ß-catenin signaling pathway selectively, but also serves as an innovative example for pro-drug development through biologically responsive LLPS.

ß-Catenin in Dendritic Cells Negatively Regulates CD8 T Cell Immune Responses through the Immune Checkpoint Molecule Tim-3.

Recent studies have demonstrated that ß-catenin in dendritic cells (DCs) serves as a key mediator in promoting both CD4 and CD8 T cell tolerance, although the mechanisms underlying how ß-catenin exerts its functions remain incompletely understood. Here, we report that activation of ß-catenin leads to the up-regulation of inhibitory molecule T-cell immunoglobulin and mucin domain 3 (Tim-3) in type 1 conventional DCs (cDC1s). Using a cDC1-targeted vaccine model with anti-DEC-205 engineered to express the melanoma antigen human gp100 (anti-DEC-205-hgp100), we demonstrated that CD11c-ß-cateninactive mice exhibited impaired cross-priming and memory responses of gp100-specific CD8 T (Pmel-1) cells upon immunization with anti-DEC-205-hgp100. Single-cell RNA sequencing (scRNA-seq) analysis revealed that ß-catenin in DCs negatively regulated transcription programs for effector function and proliferation of primed Pmel-1 cells, correlating with suppressed CD8 T cell immunity in CD11c-ß-cateninactive mice. Further experiments showed that treating CD11c-ß-cateninactive mice with an anti-Tim-3 antibody upon anti-DEC-205-hgp100 vaccination led to restored cross-priming and memory responses of gp100-specific CD8 T cells, suggesting that anti-Tim-3 treatment likely synergizes with DC vaccines to improve their efficacy. Indeed, treating B16F10-bearing mice with DC vaccines using anti-DEC-205-hgp100 in combination with anti-Tim-3 treatment resulted in significantly reduced tumor growth compared with treatment with the DC vaccine alone. Taken together, we identified the ß-catenin/Tim-3 axis as a potentially novel mechanism to inhibit anti-tumor CD8 T cell immunity and that combination immunotherapy of a DC-targeted vaccine with anti-Tim-3 treatment leads to improved anti-tumor efficacy.

MOICS, a novel classier deciphering immune heterogeneity and aid precise management of clear cell renal cell carcinoma at multiomics level.

Recent studies have indicated that the tumor immune microenvironment plays a pivotal role in the initiation and progression of clear cell renal cell carcinoma (ccRCC). However, the characteristics and heterogeneity of tumor immunity in ccRCC, particularly at the multiomics level, remain poorly understood. We analyzed immune multiomics datasets to perform a consensus cluster analysis and validate the clustering results across multiple internal and external ccRCC datasets; and identified two distinctive immune phenotypes of ccRCC, which we named multiomics immune-based cancer subtype 1 (MOICS1) and subtype 2 (MOICS2). The former, MOICS1, is characterized by an immune-hot phenotype with poor clinical outcomes, marked by significant proliferation of CD4+ and CD8+ T cells, fibroblasts, and high levels of immune inhibitory signatures; the latter, MOICS2, exhibits an immune-cold phenotype with favorable clinical characteristics, characterized by robust immune activity and high infiltration of endothelial cells and immune stimulatory signatures. Besides, a significant negative correlation between immune infiltration and angiogenesis were identified. We further explored the mechanisms underlying these differences, revealing that negatively regulated endopeptidase activity, activated cornification, and neutrophil degranulation may promote an immune-deficient phenotype, whereas enhanced monocyte recruitment could ameliorate this deficiency. Additionally, significant differences were observed in the genomic landscapes between the subtypes: MOICS1 exhibited mutations in TTN, BAP1, SETD2, MTOR, MUC16, CSMD3, and AKAP9, while MOICS2 was characterized by notable alterations in the TGF-ß pathway. Overall, our work demonstrates that multi-immune omics remodeling analysis enhances the understanding of the immune heterogeneity in ccRCC and supports precise patient management.