A newly constructed map of the landscape of genetic changes in chronic lymphocytic leukemia (CLL) may provide a better understanding of this complex malignancy, which could lead to more accurate prognoses for patients, improved diagnostics, and novel treatments. These research findings were published by Knisbacher et al in Nature Genetics, and the study was conducted by an international collaboration of investigators, including teams from the Mass General Cancer Center, the Dana-Farber Cancer Institute, and the Broad Institute of MIT and Harvard.
CLL exists as either a slowly or rapidly growing cancer and has been linked to certain genetic mutations, but it has yet to be fully characterized. Previous analyses have provided only fragments of a CLL “map,” each focusing on particular types of patients or limited data. To provide a more thorough understanding of the biological underpinnings of CLL and its molecular subtypes, scientists set out to construct a map from the largest CLL data set to date. To build the CLL map, the team analyzed variations in genetic sequences, gene-expression patterns, and chemical modifications to DNA—or genomic, transcriptomic, and epigenomic data—from 1,148 patients.
“Such a CLL map could eventually be leveraged in the clinic, wherein the genomic features of new patients can be compared with the treatments and outcomes of patients with similar genetic profiles,” said co-senior and co-corresponding author Catherine Wu, MD, Chief of the Division of Stem Cell Transplantation and Cellular Therapies at Dana-Farber Cancer Institute and Professor of Medicine at Harvard Medical School. “This profiling could potentially help more accurately tailor prognosis and treatment of a new patient based on their particular molecular features, getting closer to precision medicine.”
The scientists identified 202 genes—109 of which were novel—that when mutated, could potentially drive CLL, and they refined the characterization of subtypes of CLL with distinct genomic characteristics and prognoses. Beyond genetic sequences, the expression patterns of certain genes further subcategorized CLL and provided valuable prognostic information.
“Our study has revealed that the genetic and biologic landscape of CLL is more complex than previously appreciated,” said co-senior and co-corresponding author Gad Getz, PhD, Director of Bioinformatics at the Mass General Cancer Center and Director of the Cancer Genome Computational Analysis group at the Broad Institute. Patients’ clinical outcomes were associated with a combination of genomic, transcriptomic, and epigenomic features—integrating these data could predict a patient’s likelihood of experiencing remission vs developing more advanced cancer.
“We are releasing a CLL map ‘portal’ that is based on the CLL map and will be an interactive website for translational researchers to use as a resource for further investigation—such as learning more about the different drivers and subtypes of CLL,” said Dr. Getz.
Disclosure: This work was supported by the National Institutes of Health and the Broad/IBM Cancer Resistance Research Project. For full disclosures of the study authors, visit nature.com.The content in this post has not been reviewed by the American Society of Clinical Oncology, Inc. (ASCO®) and does not necessarily reflect the ideas and opinions of ASCO®.