Researchers use proteogenomics to higher perceive the organic complexity of breast most cancers


Researchers at Baylor College of Medicine, the Broad Institute of MIT, and Harvard, as well as other institutions, have used powerful proteogenomic approaches to better understand the biological complexities of breast cancer. Using this approach, researchers were able to suggest more accurate diagnostics for known treatment goals, identify new tumor susceptibilities for translation into treatments for aggressive tumors, and imply new mechanisms for resistance in the treatment of breast cancer. The study appears in the journal Cell.

Proteogenomics combines laboratory techniques for next-generation DNA and RNA sequencing with mass spectrometric analysis for deep, unbiased quantification of proteins and protein modifications in cancer cells, as well as computational methods for the integrated analysis of this data. Such proteogenomic approaches have been applied extensively to the study of cancer by researchers at the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (NCI-CPTAC).

Importantly, our analysis included the identification of phosphorylation and acetylation, protein modifications that provide information about the activity of individual proteins. Protein acetylation had not previously been studied in breast cancer. These new approaches promise biological insights into difficult-to-treat breast cancers and the ability to analyze the heterogeneity of responses. “

Dr. Matthew Ellis, Co-Corresponding Author, Breast Cancer Oncologist and Professor and Director of the Lester and Sue Smith Breast Center at Baylor College of Medicine, McNair Scholar at Baylor, and Susan G. Komen Scholar

Analyzing changes in the genetic code and the resulting changes in protein function at the same time provides a much more complete picture of what is going on in breast cancer tumors than analyzing each component in isolation.

More precise dates

The researchers’ first proteogenomic analysis of breast cancer using residual samples from the cancer genomatlas provided evidence of the principle that proteogenomics represents an advance in breast cancer profiling. The current study represents a major advance in that it included tissue samples collected using protocols that specifically preserve protein modifications, analyzed many more samples, performed genomics and proteomic characterization on exactly the same tissue fragments, and added a protein acetylation profile to the protein, phosphorylation. , DNA and RNA measurements. Proteogenomic analysis techniques have matured significantly in recent years, and these innovative approaches have been applied to this data set.

Researchers performed proteogenomic analyzes of 122 treatment-naïve primary breast cancer samples. Your measurements generated an enormous amount of data? around 38,000 protein phosphorylation sites and almost 10,000 protein acetylation sites per tumor as well as sequencing of the entire exome and the RNA? Need for advanced calculation methods to analyze and integrate the information. “Complex analyzes like this are now routinely performed on large proteogenomic datasets and we are developing tools to automate the process,” said Dr. DR Mani, a co-author and senior computer scientist at Broad.

“We describe the proteogenomic characterization of the largest set of breast cancer specimens to date that have been specifically collected for this type of analysis in order to maximize the accuracy and accuracy of the results,” said Ellis. “Every tumor cell has literally hundreds of genomic changes. Most of the time, we don’t understand their meaning clinically or biologically. The approach we illustrate allows a deeper and more complete understanding of each individual’s breast cancer.”

Identification of drug targets

For example, the analyzes showed that some breast cancer subtypes have certain targeted enzymes called kinases that are more phosphorylated than other cancers, indicating greater activity and therefore targeting ability. These analyzes included recently identified drug targets such as CDK4 / 6 and its regulatory context, as well as programmed cell death receptors and ligands that are the targets of new immunotherapeutic agents. The integrated analyzes also identified new sets of estrogen receptor positive breast cancers that could be treated with these agents. This is important in that these agents are currently limited to estrogen receptor negative diseases.

Additional analyzes produced completely new insights into the metabolic weaknesses of ER + and ER- breast cancer. “Our global analysis of the acetyl proteome, the first in breast tumors, revealed new details of the subtype-specific metabolism of breast cancer,” said co-author Dr. Steven A. Carr, Director of Proteomics at Broad.

Improve diagnosis and treatment

The researchers hope that their results will motivate breast cancer scientists to investigate the therapeutic or diagnostic potential of the new biological changes they identified in this study. They are also optimistic that their results will fuel efforts to translate proteogenomics into a cancer profiling approach that can be routinely used in the clinic to improve diagnosis and treatment.

“We believe that proteogenomic approaches will continue to help us identify new therapeutic target candidates, better understand the immune landscape of breast and other cancers, gain insight into response and resistance, and ultimately make progress toward our goal of personalized cancer care.” , according to co-corresponding author Dr. Michael Gillette, pulmonologist and intensive care physician at Massachusetts General Hospital and senior group leader, proteomics at Broad. “Science is powerful and exciting, but in the end, what we can deliver to the patient is what makes it important.”

The full list of all contributors to this work and their affiliations, as well as financial support for this study, can be found in the journal Cell.


Baylor College of Medicine

Journal reference:

K. Krug et al. (2020) Proteogenomic Landscape of Breast Cancer Formation and Targeted Therapy. Cell.


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