From Genes to Survival Rates: The Power of Proteogenomic Data in Predicting Cancer Outcomes

From Genes to Survival Rates: The Power of Proteogenomic Data in Predicting Cancer Outcomes

Table of Contents

Summary

The identification of oncogenic driver mechanisms and pathways shared across cancer types can allow targeted therapies originally developed to treat one type of cancer to be used across different cancers. In a newly published study, researchers used a multi-omics analysis to identify shared oncogenic driver pathways across ten cancer types. 

Multi-omic clustering reveals shared oncogenic driver pathways and functional tumor states 

Large-scale DNA sequencing has been a crucial tool in identifying mutations that drive cancer. However, a more comprehensive understanding emerges when this genomic data is combined with proteogenomics, which incorporates information from epigenomics, transcriptomics, and proteomics. In a report published in the journal Cell, Li et al. analyzed an enormous proteogenomic dataset from the Clinical Proteomics Tumor Analysis Consortium (CPTAC) of 1,064 cancer cases across ten different cancer types. 

Identifying Multi-Omic Clusters in Cancer Research

The researchers grouped tumors based on similarities in their transcriptomes, proteomes, and phosphoproteomes revealing four main multi-omic clusters. Each cluster displayed distinct characteristics. For instance, Cluster A was associated with specific types of cancer and showed signs of low immune activity, while Cluster B had a high immune cell presence. Moreover, specific genetic mutations seemed to favor particular clusters. By digging deeper into each cluster, researchers identified proteins and pathways that are differentially active, giving insight into the functional differences among tumor groups. 

Pathways and Their Ability to Predict Survival Rates

Further analysis demonstrated that these protein-based pathways varied by cancer type, and these variations could predict patient survival rates. For instance, one cancer type (clear cell renal cell carcinoma) displayed a superior prognosis when categorized in clusters associated with another cancer type (pancreatic ductal adenocarcinoma). Another type, glioblastoma, showed variations in a particular pathway linked to an aggressive cancer form and poor patient outcomes. 

In sum, this extensive study offers a layered, multi-faceted view of cancer, bridging the gap between genetic mutations and their functional consequences in cancer cells. This could potentially pave the way for more personalized and effective therapeutic strategies.

Outsourcing Bioinformatics Analysis: How Bridge Informatics Can Help

Groundbreaking studies like these are made possible by technological advances making biological data generation, storage and analysis faster and more accessible than ever before. From pipeline development and software engineering to deploying existing bioinformatics tools, Bridge Informatics can help you on every step of your research journey.
As experts across data types from leading sequencing platforms, we can help you tackle the challenging computational tasks of storing, analyzing and interpreting genomic and transcriptomic data. Bridge Informatics’ bioinformaticians are trained bench biologists, so they understand the biological questions driving your computational analysis. Click here to schedule a free introductory call with a member of our team.



Lauren Dembeck, Ph.D., Geneticist & Science Writer, Bridge Informatics

Lauren Dembeck, Ph.D., is an experienced science and medical writer. During her doctoral research at North Carolina State University, she conducted genome-wide association studies to identify genetic variants contributing to natural variation in complex traits and used a combination of classical and molecular genetics approaches in validation studies. Lauren was a postdoctoral fellow at the Okinawa Institute of Science and Technology in Japan. During her postdoc, she used fluorescence-activated cell sorting paired with high-throughput sequencing approaches to study the formation and regulation of neuronal circuits. 

She is part of our team of expert content writers at Bridge Informatics, bringing our readers and customers everything they need to know at the cutting edge of bioinformatics research. If you’re interested in reaching out, please email [email protected] or [email protected].

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