New! Sign up for our free email newsletter.
Science News
from research organizations

Method improves detection of potential therapeutic tumor targets in human biopsies

Date:
January 16, 2024
Source:
Baylor College of Medicine
Summary:
Researchers report the development of a methodology to detect small amounts of potential tumor therapeutic targets, specificacally enzymes called kinases, that are present in biopsy samples. Therapies that directly inhibit cancer-promoting activities of some of these kinases have proven to be effective for patients in which individual driving kinases can be diagnosed.
Share:
FULL STORY

Many cancers, including some types of breast cancer, are driven by alterations in the activity of cellular enzymes called kinases. Therapies that directly inhibit these cancer-promoting activities have proven to be effective for patients in which individual driving kinases can be diagnosed.

One major challenge to this therapeutic approach is to accurately quantify tumor kinases in human biopsy samples. Many kinases are not abundantly present and are therefore more difficult to measure accurately. Although currently there are methods to quantify small amounts of kinases, measuring multiple kinases concurrently is cumbersome and impractical in a clinical setting where rapid data return is critical. It is crucial to develop methodologies to enrich kinases present in clinical samples, an important step toward effective personalized medicine.

In a study published in Clinical Proteomics, researchers at Baylor College of Medicine and collaborating institutions report the development of a kinase inhibitor pulldown assay (KiP) that can optimally enrich and quantify the small amounts of kinases present in biopsy samples in combination with mass-spectrometry techniques.

The researchers established the coverage and quantitative fidelity of the assay for kinases in a single-shot approach, optimized a 100-kinase targeted panel and determined the effectiveness of KiP in subtyping breast cancer patient-derived animal models and two breast cancer patient sample cohorts.

"Our study represents a convergence of advanced technologies, redefining basic medical research and paving the way for future clinical applications," said first author Dr. Alexander Saltzman, senior bioinformatics analyst at the Mass Spectrometry Proteomics Core at Baylor.

"This paper emphasizes that new methods in protein mass spectrometry hold great promise for better definition of the individual druggable landscape present in each cancer and should be more widely used for research and, ultimately, clinical care," said co-corresponding author Dr. Matthew Ellis, faculty at Baylor's Lester and Sue Smith Breast Center.

"This methodology's approach to identifying key kinases in cancer may even extend beyond these enzymes and into other low-abundance and biologically relevant targets," said co-corresponding author Dr. Beom-Jun Kim, currently an associate director at AstraZeneca and an assistant professor at Baylor at the time of research.

Doug W. Chan, Matthew V. Holt, Junkai Wang, Eric J. Jaehnig, Meenakshi Anurag, Purba Singh and Anna Malovannayaalso contributed to this work. The authors are affiliated with Baylor College of Medicine, the Lester and Sue Smith Breast Center and/or the Dan L Duncan Comprehensive Cancer Center.

This work was supported by CPTAC PTRC grant National Cancer Institute's Specialized Programs of Research Excellence (SPORE) (U01 CA214125) and a CPTAC PGDAC Award (U24 CA210954). Ellis received support from a CPRIT Established Investigator Award (RR140033) and from Ralph and Lisa Eads. Ellis also is a McNair Medical Institute Scholar. The BCM Mass Spectrometry Proteomics Core is supported in part by a Dan L Duncan Comprehensive Cancer Center Award (P30 CA125123), CPRIT Core Facility Awards (RP170005 and RP210227) and an NIH High-End Instrumentation Award (S10 OD026804).


Story Source:

Materials provided by Baylor College of Medicine. Note: Content may be edited for style and length.


Journal Reference:

  1. Alexander B. Saltzman, Doug W. Chan, Matthew V. Holt, Junkai Wang, Eric J. Jaehnig, Meenakshi Anurag, Purba Singh, Anna Malovannaya, Beom-Jun Kim, Matthew J. Ellis. Kinase inhibitor pulldown assay (KiP) for clinical proteomics. Clinical Proteomics, 2024; 21 (1) DOI: 10.1186/s12014-023-09448-3

Cite This Page:

Baylor College of Medicine. "Method improves detection of potential therapeutic tumor targets in human biopsies." ScienceDaily. ScienceDaily, 16 January 2024. <www.sciencedaily.com/releases/2024/01/240116191540.htm>.
Baylor College of Medicine. (2024, January 16). Method improves detection of potential therapeutic tumor targets in human biopsies. ScienceDaily. Retrieved March 2, 2024 from www.sciencedaily.com/releases/2024/01/240116191540.htm
Baylor College of Medicine. "Method improves detection of potential therapeutic tumor targets in human biopsies." ScienceDaily. www.sciencedaily.com/releases/2024/01/240116191540.htm (accessed March 2, 2024).

Explore More
from ScienceDaily

RELATED STORIES