Pan-cancer proteogenomics expands the landscape of therapeutic targets.

Fewer than 200 proteins are targeted by cancer drugs approved by the Food and Drug Administration (FDA). We integrate Clinical Proteomic Tumor Analysis Consortium (CPTAC) proteogenomics data from 1,043 patients across 10 cancer types with additional public datasets to identify potential therapeutic targets. Pan-cancer analysis of 2,863 druggable proteins reveals a wide abundance range and identifies biological factors that affect mRNA-protein correlation. Integration of proteomic data from tumors and genetic screen data from cell lines identifies protein overexpression- or hyperactivation-driven druggable dependencies, enabling accurate predictions of effective drug targets. Proteogenomic identification of synthetic lethality provides a strategy to target tumor suppressor gene loss. Combining proteogenomic analysis and MHC binding prediction prioritizes mutant KRAS peptides as promising public neoantigens. Computational identification of shared tumor-associated antigens followed by experimental confirmation nominates peptides as immunotherapy targets. These analyses, summarized at https://targets.linkedomics.org, form a comprehensive landscape of protein and peptide targets for companion diagnostics, drug repurposing, and therapy development.

Enhancing the anticancer immune response with the assistance of drug repurposing and delivery systems.

BACKGROUND: The immune system plays a pivotal role in the initiation, evolution, invasion and metastasis of cancer. Therapeutics aiming at modulating or boosting anticancer immune responses have experienced immense advances during the past decades, for example, anti-PD-1/PD-L1 monoclonal antibodies. MAIN BODY: Concomitant with advancements in the understanding of novel mechanisms of action, conventional or emerging drugs bearing the potential to be repurposed for enhancing anticancer immunity have been identified. Meanwhile, ongoing advances in drug delivery systems enable us to utilise novel therapeutic strategies and impart drugs with fresh modes of action in tumour immunology. CONCLUSION: Herein, we systemically review these kinds of drugs and delivery systems that can unleash the anticancer response through various aspects, including immune recognition, activation, infiltration and tumour killing. We also discuss the current caveats and future directions of these emerging strategies.

Pharmaco-proteogenomic characterization of liver cancer organoids for precision oncology.

Organoid models have the potential to recapitulate the biological and pharmacotypic features of parental tumors. Nevertheless, integrative pharmaco-proteogenomics analysis for drug response features and biomarker investigation for precision therapy of patients with liver cancer are still lacking. We established a patient-derived liver cancer organoid biobank (LICOB) that comprehensively represents the histological and molecular characteristics of various liver cancer types as determined by multiomics profiling, including genomic, epigenomic, transcriptomic, and proteomic analysis. Proteogenomic profiling of LICOB identified proliferative and metabolic organoid subtypes linked to patient prognosis. High-throughput drug screening revealed distinct response patterns of each subtype that were associated with specific multiomics signatures. Through integrative analyses of LICOB pharmaco-proteogenomics data, we identified the molecular features associated with drug responses and predicted potential drug combinations for personalized patient treatment. The synergistic inhibition effect of mTOR inhibitor temsirolimus and the multitargeted tyrosine kinase inhibitor lenvatinib was validated in organoids and patient-derived xenografts models. We also provide a user-friendly web portal to help serve the biomedical research community. Our study is a rich resource for investigation of liver cancer biology and pharmacological dependencies and may help enable functional precision medicine.

Immune Modulatory Effects of Molecularly Targeted Therapy and Its Repurposed Usage in Cancer Immunotherapy.

The fast evolution of anti-tumor agents embodies a deeper understanding of cancer pathogenesis. To date, chemotherapy, targeted therapy, and immunotherapy are three pillars of the paradigm for cancer treatment. The success of immune checkpoint inhibitors (ICIs) implies that reinstatement of immunity can efficiently control tumor growth, invasion, and metastasis. However, only a fraction of patients benefit from ICI therapy, which turns the spotlight on developing safe therapeutic strategies to overcome the problem of an unsatisfactory response. Molecular-targeted agents were designed to eliminate cancer cells with oncogenic mutations or transcriptional targets. Intriguingly, accumulating shreds of evidence demonstrate the immunostimulatory or immunosuppressive capacity of targeted agents. By virtue of the high attrition rate and cost of new immunotherapy exploration, drug repurposing may be a promising approach to discovering combination strategies to improve response to immunotherapy. Indeed, many clinical trials investigating the safety and efficacy of the combination of targeted agents and immunotherapy have been completed. Here, we review and discuss the effects of targeted anticancer agents on the tumor immune microenvironment and explore their potential repurposed usage in cancer immunotherapy.

Expression and Diagnostic Value of miR-497 and miR-1246 in Hepatocellular Carcinoma.

OBJECTIVE: Serum microRNAs (miRNAs) may serve as biomarkers in various cancers. Our study aims to explore the roles of miR-497 and miR-1246 in hepatocellular carcinoma (HCC). METHODS: The expression levels of miR-497 and miR-1246 were measured by RT-PCR. A correlation analysis was conducted between the expression levels of miR-497 and miR-1246 and clinicopathological characteristics of patients. The receiver operating characteristic (ROC) curve was applied to evaluate the diagnostic efficacy in HCC. In addition, bioinformatics tools were also utilized to predict the potential targets of miR-497 and miR-1246. RESULTS: The expression level of miR-497 in HCC was significantly down-regulated compared with the control group while the miR-1246 revealed a significantly higher expression level in HCC. There was a significant correlation demonstrated between the expression levels of miR-497 and miR-1246 in preoperative serum of HCC and the differentiation degree, Tumor Node Metastasis (TNM) classification, and metastasis. The expression levels of serum miR-497 and miR-1246 were significantly associated with the diagnosis, prognosis, and overall survival rate of patients with HCC. Moreover, the potential target genes of miR-497 in HCC include ARL2, UBE2Q1, PHF19, APLN, CHEK1, CASK, SUCO, CCNE1, and KIF23. The low expression of these nine genes is associated with a better prognosis of HCC patients. AUTS2 is a novel target gene of miR-1246, and its low expression is significantly related to the low overall survival rate of HCC patients. CONCLUSIONS: miR-497 and miR-1246 are possibly involved in the progression of HCC by regulating target genes, respectively, and could serve as biomarkers in HCC.