Genomics in Oncology
A newly diagnosed cancer patient and their family might have barely moved from the first stage to the next of the five stages of grief but, regardless of the course of their emotional journey, their cancer vocabulary begins to grow from day one. Biopsy, staging, chemo, neutropenia,… words that had meant nothing to them before, take on a very tangible meaning invoking thoughts of hospital beds and days spent being sick. As the battle with cancer continuous, their vocabulary continues to evolve as well. Remission, transplant, … relapse, metastasis, morphine, …hospice; relief alternating with despair, a roller coaster ride with too many ups and downs.
In the last few years, a newer set of words are beginning to make their way into the cancer lexicon- whole genome sequencing (WGS), targeted therapies, biomarkers… words that are becoming associated with some recent successes and cautious optimism as we relentlessly search for a cure to cancer. These partial successes, the understanding that cancer is a genetic disease, and the decreasing cost of whole genome sequencing raise important questions about making tumor sequencing an integral part of cancer treatment.
Central to this discussion are several different scientific and social issues. On the scientific side, intratumor heterogeneity, challenges with data interpretation and management, and physician training in genomics dominate the conversation. In the social area, cost and insurance coverage, and ethical issues remain center stage.
Patients and families turn to genomic medicine to treat cancer
Most of us probably associate being sick with the entire body- a fever, aches, chills and other broad symptoms. When it comes to a disease like cancer, we might take an organizational step or two down to think of a specific organ or tissue: breast, lung or brain cancer.
But increasingly, patient’s stories point clearly toward a finer resolution of cancer diagnosis, down to the level of a single gene. A report in the New York Times last week describes how a team of researchers worked to identify the genetic aberration underlying a colleague’s cancer, and helped treat his leukemia with an off-label drug currently used to treat kidney cancers.
Congratulations to our second travel grant winner! Read on to find out how he uses NextBio Research to explore oncogenic microRNAs.In Malay’s words:
I become truly amazed when I look back on my career and see how a student with undergraduate degrees in Computer Science and Electronics turned into a biology researcher. In the very first week of graduate school, I received an article on microRNAs (miRNAs), a class of short non-coding regulators of protein-coding genes, from my supervisor. Ever since that first read, I have been hooked on these endogeneous RNAs for four years and counting. Read more…
Sirtuin 2 may suppress tumor formation in mice and humans
Sirtuins are a family of proteins that have been implicated in processes ranging from aging and tumor formation to obesity and cerebral ischemia. Seven sirtuin proteins are known to exist in mammals, two of which (SIRT1 and SIRT3), are known tumor suppressor genes. The function of sirtuin 2 (SIRT2) remained unclear however, until recent research from scientists at the National Institute of Health, Vanderbilt University and the University of Texas, Dallas discovered that SIRT2 could play an important role in preventing cancer. In a paper published in Cancer Cell this week, the researchers describe the role of SIRT2 in maintaining genomic stability in cells, a function critical in aging and cancer-related processes.
Distinguishing driver and hitchhiker mutations for targeted chemotherapy
Cancer genomes are complex, with multiple changes in gene sequence, expression profiles and epigenetic changes to regulatory regions. Some of these changes, termed ‘driver’ mutations, are significant to tumor formation and cancer progression, while others are simply ‘hitchhikers’ of little (known) clinical relevance.
As pharmacogenomics progresses towards identifying genetic profiles for stratified medicine strategies, distinguishing driver and hitchhiker mutations becomes essential. Two recent reports from the Translational Genomics Research Institute (TGEN), presented at the 14th World Conference on Lung Cancer, examine signaling pathways in lung cancer to identify novel treatment strategies and potential drug targets.
Two broad categories of lung cancer exist: small cell lung cancer (SCLC), causing about 15% of all lung cancers, and non-small cell lung cancer (NSCLC). Of the three sub-forms of NSCLC, adenocarcinomas are the most prevalent, accounting for more than 50% of all lung cancer cases.
The Cancer Genome Atlas maps genomic changes in ovarian adenocarcinoma
Popping an aspirin cures headaches for nearly everyone regardless of their DNA, but some drugs only work on patients with specific genetic profiles. Herceptin, for example, is effective only in breast cancer patients whose tumors over-express the HER-2 gene, and Gleevec is specifically designed to inhibit an altered enzyme form in leukemia. Several other such drugs, designed for specific gene forms or expression patterns, are currently in use. Understanding the genetic profile of complex diseases like cancer is the first step towards designing more effective therapies.
Last week, we offered five questions you could answer using NextBio’s lastest new application, the Body Atlas. This week we have five more:
#6. Do you know how your favorite gene’s expression compares in cancer cell line models compared to the normal cell type counterpart for a given cancer?
Example: Microseminoprotein-beta (MSMB), a known tumor suppressor in prostate cancer is over 500-fold less in each of the six prostate cancer cell-lines displayed compared to its expression in either the prostate gland as a whole or in luminal cells of the prostate.
#7. If your favorite gene is suspected to play a role in a cancer type, how does its expression compare across all popular cell line models for that cancer? And which might be the best model in which to study it based on its expression level?