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Pan-Cancer Study Points to Possible Protein Targets

NEW YORK – A team from the US and China has uncovered potential treatment targets through a pan-cancer analysis of proteins and peptides identified using an integrated multiomic analytical strategy.

For a study published in Cell on Monday, researchers from the US and China performed a proteogenomic analysis using data for 1,043 tumors from 10 cancer types profiled for the Clinical Proteomic Tumor Analysis Consortium (CPTAC), enabling them to search for potential drug approaches based on data for nearly 2,900 protein targets.

"While genomic studies have significantly enhanced our understanding of cancer biology and genomic drivers, most cancer patients still receive nonspecific chemotherapy and radiotherapy, which are low in efficacy and high in toxicity," co-first author Jonathan Lei, a molecular and human genetics researcher at Baylor College of Medicine, explained in an email, prompting the CPTAC to characterize proteins that may be targetable in future small-molecule drug development efforts.

With an integrative analysis of exome sequencing, RNA-seq, array-based DNA methylation, and mass spectroscopy data in the pan-cancer samples, together with 524 normal samples, the team assessed genetic mutations, gene expression, transcript features, epigenetics, proteomic, and phosphoproteomic profiles, focusing on proteins and peptide effects that pointed to a specific treatment target or approach.

"Proteins quantified in samples included inhibited targets of approved oncology drugs (tier 1), approved non-oncology drugs (tier 2), and drugs in any clinical/preclinical phase (tier 3), which could be used for biomarker selection and repurposing," Lei explained.

The team also took a look at proteins that may be subject to future drug development work, Lei noted, including proteins in families that tend to be targeted by small-molecule inhibitors and membrane proteins that might be susceptible to antibody, antibody-drug conjugate, or engineered T-cell treatments.

Along with genetic screening outcomes in cancer cell lines and available drug target insights from established databases, for example, the phosphoproteomic data helped the team focus in on possible drug targets based on proteins with higher-than-usual expression or activation in the cancers considered.

Based on synthetic lethal interactions identified, meanwhile, the investigators narrowed in on apparent tumor suppressors. In addition, their subsequent immune system-centered analyses — including neoantigen searches informed by major histocompatibility complex binding clues — highlighted possible immunotherapy-based treatment strategies.

"Our analysis provides insights into existing cancer drug targets and systematically identifies candidate new targets for drug repurposing development," the authors wrote. "These include overexpressed and hyperactivated protein dependencies, protein dependencies associated with the loss of tumor suppressor genes (TSGs), and putative neoantigens and tumor-associated antigens."

For their part, he and his colleagues are currently seeking collaborators to not only validate protein targets highlighted in the study but also come up with therapies aimed at proteins not yet targeted by approved drug approaches. They are also expanding the suite of omics types profiled across still other cancer types and subtypes — from acetylomic or glycoproteomic analyses to ubiquitylomic profiling.

The investigators brought data from the study together in a web portal, providing a resource meant to support future drug development, repurposing, and companion diagnostic development efforts.

The group has also "experimentally validated some of the novel protein and peptide targets identified from our computational analyses," Lei noted.

"From the clinical perspective, this study provides strong rationale for protein and peptide targets that could be investigated further and/or form the basis for future biomarker-driven clinical trials," he explained.