This is a guest post from the Faculty of 1000 on the cancer cell lines that are “irreplaceable tools in [the] cancer research toolbox.”
Wouldn’t it be great if we knew all there was to know about every type of cancer cell? With this kind of knowledge, we would be able to offer personalized treatment to cancer patients that would attack their specific tumor in the most efficient way possible, improving both survival rates and quality of life during therapy. Unfortunately, we’re still facing major challenges in cancer research, right down to the level of knowing which cell samples to target with particular anti-cancer drugs. However, in a recent paper published in Nature, Barretina and colleagues go some way to providing a preclinical model system reflecting the genomic diversity of human cancers, ‘the Cancer Cell Line Encyclopedia’.
Tumors are incredibly diverse, even within individual cancer classifications, which means large patient cohorts are required if clinical studies are to arrive at solid conclusions. Even when patient samples are obtained, cancer cells and tissue are often limited in quantity and sometimes not suitable for drug testing. With these methodological barriers in place, systematically translating cancer genomic data into practicable knowledge of tumor biology and therapeutic possibilities can be difficult.
In their study, evaluated on F1000, Barretina’s group describe the Cancer Cell Line Encyclopedia through coupling sequencing data from 947 human cancer cell lines with the pharmacological profiles of 24 anticancer drugs. This collection of data allowed the authors to identify genetic and cell-line expression-based predictors of drug sensitivity for different tumor cell lines. In a review of the article, F1000 Faculty Members Diane Jelinek and Xiaosheng Wu, of the Hematology Faculty, highlight the potential of using these cell lines as a modeling tool for predicting and testing the sensitivity of new cancer drugs. Jelinek and Wu go on to describe the cancer cell lines identified in this study as “irreplaceable tools in our cancer research toolbox“.
This research clearly has exciting potential for the future. The authors envision large, pharmacologically annotated cell-line collections that could help to identify the most effective strategies for anticancer therapy. This, in turn, could lead to the generation of genetic predictors of drug responses and, eventually, the emergence of ‘personalized’ cancer therapy regimens for individual patients. In the same way that a tailor-made suit can boost your self-confidence in the workplace, bespoke cancer therapy could significantly improve a patient’s confidence in their treatment by offering them the best possible therapy options.
Faculty of 1000 is a post-publication review service in Biology and Medicine that identifies and evaluates the most interesting and important papers published worldwide. 10,000 Faculty Members and Associates – experts in their field – cover some 350 defined specialty sections and collectively contribute 1300-1500 article evaluations a month. These evaluations are published immediately on F1000 and constitute an up-to-date and comprehensive guide to the best of the scientific literature.