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Colon Cancer Proteogenomic Analysis May Uncover New Potential Treatments

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Key Points

  • The genomic data set indicated that SOX9 is a tumor-suppressor gene, but proteomic data challenged the indication that SOX9 was a tumor suppressor.
  • Through bioinformatics analyses, the team identified new clues regarding why immunotherapy does not work for all mismatch repair–deficient colon cancers that may lead to new therapeutic approaches. 
  • All the data reported are accessible to researchers in a Web tool called LinkedOmics.

A new study analyzing the entire set of genes and all the proteins produced by colon cancer tissues from patient samples has revealed a more comprehensive view of the tumor, pointing to novel cancer biologic mechanisms and possible new therapeutic strategies. This multidisciplinary and multi-institutional study—published by Vasaikar et al in the journal  Cellstrongly supports the comprehensive characterization of tumor tissues as a means to guiding further research, which could lead to early diagnostic strategies and new treatments.

“This is the first study that analyzed all the proteins and genes in tissue samples from a group of patients with colon cancer, comparing tumor and normal adjacent tissues,” said corresponding study author Bing Zhang, PhD, Professor of Molecular and Human Genetics and the Lester and Sue Smith Breast Center at Baylor College of Medicine, Houston.

Study Methods and Findings

As part of the National Cancer Institute Clinical Proteomic Tumor Analysis Consortium, the team generated the genomic and proteomic data and applied bioinformatics analyses to the data. The result is the first systematic catalog of the different proteins produced by colon cancer tumors and adjacent normal tissues.

“We were able not only to confirm previously described colon cancer molecular markers but also to uncover new differences between proteins produced by tumors and normal tissue that may be worth further study,” said Dr. Zhang, who also is a member of the Dan L Duncan Comprehensive Cancer Center and a McNair scholar at Baylor.

Furthermore, the researchers learned that genomic and proteomic data complement each other in ways that provide researchers with a better understanding of what goes on inside colon cancer cells.

“One example is SOX9,” Zhang said. “Our genomic data set indicated that SOX9 is a tumor-suppressor gene because it is frequently mutated in colon cancer in ways that suggested that the function of the protein coded by the gene would be destroyed and that the protein would not be produced or produced in a lesser amount. But when we looked at the proteomic data—at the actual protein in cancer tissue—we observed quite the opposite: SOX9 protein was abundant in these tumors, more than normal. The proteomic data thus challenged the indication that SOX9 was a tumor suppressor.” Further bioinformatic analyses suggested to Dr. Zhang and colleagues possible explanations for this and other apparent contradictions between the genomic and the proteomic data, as well as other findings.

“Analysis of the genes tells us what might possibly go wrong. But we don’t know exactly what has gone wrong until we analyze the proteins,” said study author Tao Liu, PhD, senior scientist in the Integrative Omics Group at Pacific Northwest National Laboratory, and whose team, as part of this study, performed the most detailed measurements of protein activity in colon cancer ever conducted.

In addition to the SOX9 findings, the team discovered other new interesting insights that can guide research to improve colon cancer treatments. For instance, the U.S. Food and Drug Administration has approved the use of a biologic marker called DNA mismatch repair–deficiency for identifying patients who are candidates for checkpoint inhibitor–based immunotherapy. However, only a subset of patients with this biomarker respond to the therapy.

Through bioinformatic analyses, Dr. Zhang and his colleagues identified new clues regarding why immunotherapy does not work for all mismatch repair–deficient colon cancers that may lead to new therapeutic approaches. “Our data revealed a surprising relationship between enzymes of metabolism and immune cells in some colon tumors, which presents a new opportunity to improve immunotherapies,” said the researchers.

All the data reported are accessible to researchers in a Web tool called LinkedOmics, which also provides computational tools for further exploration of this dataset. “We hope that this resource will be useful to researchers interested in investigating new aspects of colon cancer,” Dr. Zhang concluded.

Disclosure: This work was supported the National Cancer Institute Clinical Proteomic Tumor Analysis Consortium, the Cancer Prevention & Research Institutes of Texas, and by funding from the McNair Medical Institute at The Robert and Janice McNair Foundation. For full disclosures of the study authors, visit cell.com.

The content in this post has not been reviewed by the American Society of Clinical Oncology, Inc. (ASCO®) and does not necessarily reflect the ideas and opinions of ASCO®.


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