Research on understudied lung cancer drivers may improve treatments
Angela Brooks received a $2.5 million award from the NIH R01 program to study how lung cancer gene isoforms influence disease development and treatment
To diagnose and treat cancer, researchers and clinicians typically look at a person’s genetic material to find any mutations in genes that may “drive” cancer, helping to create a specialized treatment plan. They don’t normally look at the gene’s “isoforms” — slightly different versions of the genes that can be created in the body’s processes of translating genetic code into proteins.
Isoforms are difficult to study, but UC Santa Cruz Professor of Biomolecular Engineering Angela Brooks believes they could be key for finding new treatment options for cancer. She has dedicated her research career to identifying gene isoforms and how they can impact cancer; and now has been awarded a $2.5 million grant from the National Institutes of Health’s prestigious R01 program to study how isoforms impact cancer progression and what treatments might be most effective or lead to drug resistance. She will focus specifically on genes related to lung cancer, which is the U.S.’s leading cause of cancer deaths.
“This is a larger-scale study, so we're hoping to really understand the extent of the problem — how much are we missing when we don’t consider the isoforms?” Brooks said. “If we can figure out not only which genes are mutated but also the isoform context, then we have a better sense of characterizing what a driver gene looks like, and better correlate it with drug sensitivity.”
Brooks will pursue this research over the next five years with longtime collaborator Alice Berger, an associate professor at the Fred Hutchinson Cancer Center. Brooks’ graduate student Colette Felton has been highly involved in the preliminary work for this project.
Experimenting with isoforms
Think of an isoform as the fruit in a pie recipe: the rest of the ingredients in the recipe can stay the same, but when just one change is made to the type of fruit used, the pie is transformed. Likewise, a stretch of DNA can code for one gene, but when that code is slightly tweaked in the processing of RNA from a DNA sequence to make proteins, the gene can be somewhat altered. Any given gene could be produced in a variety of isoforms, and a cancer mutation could be present in the gene in any of those isoforms.
In the first phase of this research project, Brooks’ lab will focus on using long-read RNA sequencing to identify all of the potential isoforms that are possible for genes associated with lung cancer. Recent improvements to long-read RNA sequencing technology and methods, led in part by Brooks herself, have made it possible to confidently implement new sequencing technologies to find out in which isoform of the gene the cancer mutation is present.
The researchers hypothesize that the isoform in which the cancer gene is expressed matters to the development of cancer, in that normal tissue might be associated with certain isoforms and cancerous tissue associated with others.
Developing better treatments
The second phase of the project will involve studying samples from lung cancer patients alongside information on how they responded to drug treatment, the researchers expect to find that certain isoforms will correlate with the effectiveness of certain drugs.
“Our argument is that there might be a lot of missing information as to why a clinical trial failed, or different types of potential biomarkers that have been missed because we were not considering what isoform had been expressed,” Brooks said.
The researchers will look at data from a cohort of lung cancer patients who relapsed after receiving treatment to better understand how and why cancers might be resistant to certain drugs, and how to design more effective drugs in the future. They will study samples to find out which isoforms might be contributing to drug resistance using single-cell RNA sequencing and patient-derived xenografts (PDX). This work will also be done in collaboration with University of Virginia School of Medicine Assistant Professor Gloria Sheynkman, an expert in proteogenomics who has developed methods to use transcriptome data to infer information about the proteins that transcripts produce.
They will carry out further experiments, called functional studies, to directly test how a gene functions with different isoforms and mutations. Brooks developed some of the methods needed to do this several years ago with the support of a seed grant from the Santa Cruz Cancer Benefit Group.
Focus on lung cancer
Lung and bronchial cancers are the third most common cancer diagnoses in the U.S. and were the leading cause of U.S. cancer deaths in 2023 according to the National Institutes of Health. Beyond their human health relevance, Brooks and Berger are focusing on lung cancers for this study because lung cancers are one the most frequently mutated cancer types, and many of these mutations impact splicing, the cellular mechanisms that lead to different isoforms of genes.
Lung cancers also tend to be associated with a group of genes called the RAS gene family, and scientists have developed many drugs to target the RAS pathway that can often be effective treatments for lung cancers. This gives Brooks and Berger hope that they will be able to quickly identify new ways to treat lung cancer and understand possible resistance to these treatments.
“If you have drugs that work to target a certain pathway, then if you find something new, you have more of a chance to either repurpose a treatment that already exists or motivate people to develop drugs, because they know it’s targetable,” Brooks said.
The isoform sequencing data they gather will be available for the larger community of cancer researchers and clinicians to access via the UCSC Xena Browser, a resource for storing and accessing genomic data using visual tools to help users better understand the correlation between genes and the features they code for in the body.
While the researchers are focusing this project on lung cancers, the experimental design and methods could be replicated for nearly any other cancer type that a researcher or clinicians wanted to study.