Using Big Data to Improve Metastatic Breast Cancer Research

Researchers are investigating ways to use big data to improve metastatic breast cancer research, according to a recent study published in Nature Communications.
 
The availability of large-scale genomic data provides an opportunity to evaluate their use in metastatic cancer research. With very few therapeutic options available for this patient population, cancer metastasis leads to death in approximately 90% of patients.
 
Currently, cell lines are used as models to study metastatic cancer, but the extent to which cell lines can capture the genetic makeup of tumors is unknown, according to the study authors.
 
For the study, the researchers used data from genomic databases to draw comparisons between breast cancer cell lines and tumor samples. By analyzing the data, they found substantial genomic differences between MDA-MB-231, a cancer cell line used in nearly all metastatic breast cancer research, and metastatic tumor samples from patients.
 
Key differences suggested that cell lines poorly recaptured somatic mutation patterns of metastatic breast cancer samples, whereas their copy number variation profiles were more consistent. Additionally, the researchers noted that cell lines carried many specific genomic alternations, possibly due to culture effects.
 
“I couldn’t believe the result,” senior author Bin Chen, PhD, assistant professor in the College of Human Medicine, said in a press release about the study. “All evidence pointed to large differences between the two. But, on the flip side, we were able to identify other cell lines that closely resembled the tumors and could be considered, along with other criteria, as better options for this research.”
 
The researchers have previously proposed different computational methods to measure the similarity between cell lines and patient samples. They indicated that gene expression is one of the most informative features to predict drug response and weighting cell lines based on their transcriptome similarity with patient samples can increase predictive power in gene expression-based drug discovery.
 
The analysis suggested that organoids, which use 3D tissue cultures, resemble the transcriptome of patient samples more closely than cell lines, according to the authors. These organoids are able to capture more of the complexities of how tumors form and grow, the researchers noted. According to the study, the organoids’ high genomic similarity with patient samples warrants further investigation.
 
“We hope that the recommendations in this study may facilitate improved precision in selecting relevant cell lines for modeling in metastatic breast cancer research, which may accelerate the translational research,” the researchers concluded.
 
References
 
Liu K, Newbury P, Glicksberg BS, Evaluating cell lines as models for metastatic breast cancer through integrative analysis of genomic data. Nature Communications. 2019. https://www.nature.com/articles/s41467-019-10148-6
 
Big data helps identify better ways to research breast cancer’s spread [news release]. Michigan State University. https://msutoday.msu.edu/news/2019/big-data-helps-identify-better-way-to-research-breast-cancers-spread/. Accessed May 15, 2019.
 
 



Stay up to date on the latest news in specialty pharmacy by getting Specialty Pharmacy Times in your mailbox or inbox for free!

Click here to sign up for free for the bi-monthly Specialty Pharmacy Times print journal delivered to your address.

Click here to sign up for our email newsletters delivered every Monday, Wednesday, and Friday, in addition to breaking news alerts.

Click here to follow us on Facebook. 

Click here to follow us on Twitter. 

Click here to join our LinkedIn group. 


Related Articles

The presence of human papillomavirus type 16 antibodies marked an approximately 100-fold increase in risk of throat cancer in white individuals.
Colon cancer may spread to other parts of the body before original tumors are clinically detectable.
Top news of the day from across the health care landscape.
Company Profile >
Industry Guide >
Market News >
Peer Exchange >
Conferences >
Subscribe >
Specialty Times Resources
About Us
Advertise
Careers
Contact Us
Terms & Conditions
Privacy
MJH Associates >
Pharmacy Times
OTCGuide
American Journal of Managed Care
Cure
MD Magazine
ONCLive
Targeted Oncology
Physicians' Education Resource
Pharmacy & Healthcare Communications, LLC
2 Clarke Drive
Suite 100
Cranbury, NJ 08512
P: 609-716-7777
F: 609-716-4747

Copyright Specialty Pharmacy Times 2006-2019
Pharmacy & Healthcare Communications, LLC. All Rights Reserved.
 

$vacMongoViewPlus$