Illustration of colorectal cancer

Colon cancer ranks third in prevalence and fourth in cancer deaths among all cancers worldwide. However, due to its extreme heterogeneity, progress has been slow towards precision diagnostics and treatments. The National Cancer Institute’s Proteomic Tumor Analysis Consortium, led by researchers at Baylor College of Medicine, embarked upon a mission to crack the molecular mysteries behind colon cancer, with the first comprehensive and integrated proteogenomic analysis of patient cohorts. Their study, published in Cell last week, illuminates novel drivers of colon cancer growth, mechanisms of treatment resistance and unique strategies for beating this challenging disease.

“Proteomic difference between tumor and normal tissues are critical for cancer biomarker discovery, but have not been systematically characterized in large tumor cohorts,” said lead author Dr. Bing Zhang, professor of molecular and human genetics and the Lester and Sue Smith Breast Center at Baylor.  In a landmark first, Zhang and his team comprehensively profile genetic, proteomic and phosphoproteomic information from colon cancers and normal adjacent tissues. Through comparative analysis and integration of multi-omics data, they discover numerous new biomarkers and drug targets for advancing precision treatments. “Our study confirms the value of proteogenomic integration in uncovering novel cancer biology and … utility in generating therapeutic hypothesis.  (This approach) revealed new therapeutic opportunities for targeting signaling proteins, metabolic enzymes and tumor antigens in colon cancer treatment,” Zhang explained.

For example, the team identifies many proteins that are over-expressed in colon cancers, which may serve as novel biomarkers for precision diagnostics. Alternatively, such antigens may be useful in immunotherapy development and for generating personalized anti-cancer vaccines.

The insights provided by this study point to novel strategies for combating treatment-resistant colon cancers, particularly microsatellite instability-high (MSI-H) tumors which are notoriously resistant to the latest immune checkpoint blockade treatments.

In some cases proteomics data confirms and complement genomics data, providing a more complete picture of cancer biology.  However, in other cases it reveals false assumptions. “Proteogenomics integration may correct inaccurate genomics-based inferences and lead to unexpected discoveries and therapeutic opportunities,” said Zhang. In one such case, the team finds SOX9 to be an overexpressed oncogene, rather than a tumor suppressor.

With phosphoproteomic analysis, the team is able to see how proteins are modified within cancer cells to drive tumor growth, providing insights into cancer signaling pathways that are otherwise unattainable using only genetic analysis. “Signaling proteins and pathways are often attractive therapeutic targets for cancer treatment, yet global phosphoproteomic analyses on human colon cancer are lacking,” said Zhang. Their study fills this gap, yielding many promising therapeutic strategies. For example, they find that phosphorylation of the oncogene RB is a key driver of colon cancer growth, suggesting a novel treatment strategy to apply currently available CK2 inhibitors to block the enzyme that adds this modification.

While the study provides many new directions for colon cancer research and precision treatments, it also supplies a valuable informational resource which Zhang hopes will yield further insights and clinical advances.  All of the data is publicly available through the LinkedOmics portal, a multi-omics database made possible through The Cancer Genome Atlas project. With datasets from 32 cancer types and multiple tools for integrative data analysis, the resource will enable researchers to utilize Zhang’s data set to generate novel discoveries, and to translate these advances beyond colon cancers to other fields of oncology.

The study was conducted as part of the National Cancer Institute’s Proteomic Tumor Analysis Consortium, which was launched in 2011 to accelerate precision oncology advances by supporting large-scale molecular- omics studies. Collaborators included Baylor College of Medicine, the Department of Energy’s Pacific Northwest National Laboratory, Vanderbilt University, Washington University and the National Cancer Institute.

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