A Needle Biopsy-based Proteogenomics Approach for Cancer Diagnosis

By LabMedica International staff writers
Posted on 04 Feb 2020
A recent report described a proteogenomics approach for cancer diagnosis, which used tissue-sparing needle biopsy specimen processing and micro-scaled analytical proteomics techniques.

Proteogenomics is the field of biological research that utilizes a combination of proteomics, genomics, and transcriptomics to aid in the discovery and identification of peptides. Proteogenomics is used to identify new peptides by comparing mass spectrometry (MS/MS) spectra against a protein database that has been derived from genomic and transcriptomic information. Genomics deals with the genetic code of entire organisms, while transcriptomics deals with the study of RNA sequencing and transcripts. Proteomics utilizes tandem mass spectrometry and liquid chromatography to identify and study the functions of proteins.

Image: Photomicrograph of cancer cells (Photo courtesy of Baylor College of Medicine)

A critical limitation in proteogenomics studies has been the requirement for biopsy samples that may exceed the size of sources of this clinically important material. To overcome this problem, investigators at Baylor College of Medicine (Houston, TX, USA) and the Broad Institute of MIT and Harvard (Boston, MA, USA) developed methods to generate high-quality DNA, RNA, and protein for deep-scale DNA and RNA sequencing and proteome and phosphoproteome analysis from a single 14 G core needle sample. Extracts prepared from this type of biopsy material were analyzed using a micro-scaled liquid chromatography-mass spectrometry (LC-MS/MS)-based proteome and phosphoproteome analysis pipeline that required only 25 micrograms of peptide per sample.

To demonstrate the potential of this method, the investigators analyzed core needle biopsies from ERBB2 positive breast cancers before and 48 to 72 hours after initiating neoadjuvant trastuzumab-based chemotherapy.

Results revealed greater suppression of ERBB2 protein and both ERBB2 and mTOR target phosphosite levels in cases associated with pathological complete response, and identified potential causes of treatment resistance including the absence of ERBB2 amplification, insufficient ERBB2 activity for therapeutic sensitivity despite ERBB2 amplification, and candidate resistance mechanisms including androgen receptor signaling, mucin overexpression, and an inactive immune microenvironment.

"Patients die from cancer because, at a sufficiently fundamental level, we have not been able to work out what kind of cancer we are treating," said senior author Dr. Matthew Ellis, professor of precision medicine at Baylor College of Medicine. "The analysis of proteogenomics data, which combines information on tens of thousands of proteins and genes together using a system developed by the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (NCI-CPTAC) investigators, provides much more complete details about what is going on in each tumor. However, the application of proteogenomics to both scientific research and cancer diagnosis has been limited by the size of the tissue sample required."

"Importantly, our new methodology includes the analysis of phosphoproteins, which refers to proteins that are activated by the addition of phosphate chemical groups," said Dr. Ellis. "For some cancers, such as ERBB2+ (HER2+) breast cancer, the ability to measure these modifications is critical because they are what drives disease. For the first time, we were able to detect statistically significant reduction of ERBB2 protein phosphorylation after treatment in patients that responded to treatment. We did not see a reduction in this protein for those who did not respond to treatment. In patients that did not respond to treatment, our deep-scale data analyses suggested diverse resistance mechanisms to ERBB2-directed therapeutics that could be addressed with alternative approaches to the ones the patient actually received."

The needle biopsy proteogenomics approach was described in the January 27, 2020, online edition of the journal Nature Communications.

Related Links:
Baylor College of Medicine
Broad Institute of MIT and Harvard



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