Sept. 18, 2007 | Multiple myeloma patients vary widely in how they ultimately respond to treatment, but now researchers in the Myeloma Institute for Research and Therapy (MIRT) at the University of Arkansas for Medical Sciences (UAMS) in Little Rock, Ark., have identified a small subset of genes whose level of activation could predict low and high-risk cases and potentially guide their therapy in the future.
For the last seven years, the UAMS researchers have followed 532 multiple myeloma patients after blood stem cell transplant procedures to correlate gene expression patterns in patients’ tumor cells at diagnosis with their outcome following treatment. The goal was to produce a genomic profile that can chart the severity of the disease and to better understand the molecular basis of disease aggressiveness.
The researchers have determined that the activity of as few as 17 genes of the more than 25,000 analyzed could determine if a patient had a high or low probability of early death due to their illness. They will present their findings today in
The researchers found that 13 percent of newly diagnosed patients exhibited a genetic pattern linked to a high risk for poor outcome. At the same time, some patients’ tumors initially presented with a low risk score at diagnosis, but upon relapse shifted to a high risk score. This conversion had a significantly negatively impact on post-relapse survival rates as well.
Importantly the authors showed that patients with previously recognized high-risk features, like the t(4;14)(p16;q32) translocation, that had low-risk gene profiles scores defined by the 17-gene model, had a significantly longer survival than those with the translocation and the high-risk score.
“There are enormous differences between how different people fare with a diagnosis of multiple myeloma. While most do very well, others have a highly aggressive form of the disease and this is not recognized well with current prognostic variables,” said lead researcher John D. Shaughnessy, Ph.D., director of the MIRT’s Division of Basic Sciences and a professor of medicine in the UAMS College of Medicine. “If we can determine with confidence, a patient’s risk early, we can better guide these patients toward therapies that might be more effective for them based on the genomic profile of the disease.”
Shaughnessy’s colleague, Fenghuang Zhan, M.D., Ph.D, an assistant professor of medicine in the UAMS College of Medicine, is presenting the findings on behalf of the research team at the Molecular Diagnostics meeting.
Multiple myeloma is a cancer that affects the white blood cells known as plasma cells that reside in the bone marrow, where they produce antibodies that protect from infections. Nearly 14,600 new cases of multiple myeloma occur each year in the </O:P>
The disease is most often treated with high-dose chemotherapy followed by a blood stem cell transplant to promote blood cell recovery following the myeloablative chemotherapy. While multiple myeloma usually responds well to initial treatment, it often becomes drug resistant and prone to relapse. According to the researchers, survival varies greatly between low-risk and high-risk patients.
“At 24 months, about 90 percent of low-risk patients will be alive, whereas about 50 percent of the high-risk patients have succumbed to the disease,” Zhan said.
To understand the possible molecular mechanisms driving the progression of multiple myeloma, Shaughnessy and his colleagues began a massive effort to categorize the differences in gene expression patterns, that is, which genes are activated and inactivated, in relatively indolent and in aggressive forms of the disease.
Using purified tumor cells taken from 532 newly diagnosed patients who went on to receive uniform therapy, the researchers screened more than 54,000 gene expression tags found in the human genome. The researchers were looking for differences in expression patterns that were reproducibly different in the comparison of these 54,000 tags in those patients that experienced a long versus a short survival. About 13 percent of all the patients they studied fit into the high-risk category.
The high and low risk groups were defined by a risk score that increased in 76 percent of relapsed patients. What was remarkable was that the authors found that if a risk score increased at relapse and went above the high risk cut point, the patient was likely to experience a inferior post-relapse survival relative to those that had low risk at both diagnosis and relapse, but intermediate to those with high risk at diagnosis.
“The observation of an increase in the gene expression risk score between diagnosis and relapse provided strong evidence that small subsets of high-risk cells can be present in patients with a low-risk score, and suggests that current therapeutics are unable to eliminate these cells that form the bulk of the relapsing disease. These data indicate that when there is tumor cell heterogeneity, that current therapies effectively kill the low-risk cells, but leave behind cells that exhibit this high-risk genetic profile,” Shaughnessy said.
Shaughnessy said experiments are now under way to definitively prove this concept. He also stated that, “If proven true, developmental therapeutic efforts should be focused in the genes whose expression is linked to high-ris. It will be important to determine if this gene expression signature is simply a biomarker or causally related to the aggressive clinical phenotype.”
Initially, the researchers identified 70 genes linked to early cancer-related death, although further analysis was able to whittle the number down to 17. Remarkably, about 30 percent of the genes that predict high risk are found on chromosome 1, enough so that Shaughnessy was able to recognize a trend among the genes, based on where they are located on each chromosome in the human genome. The majority of genes that were up regulated – or over-produced – in the high-risk form of the disease were located on the long arm of chromosome 1, while the majority of genes that were down regulated – or suppressed – were found on the short arm (or p arm) of the same chromosome.
“The data suggest that, indeed there might be a “smoking gun” evident in the gene expression signature, in that defects in chromosome 1 appear to be related to the acquisition of high risk in patients with multiple myeloma,” Shaughnessy said. “Gene expression profiles have now provided us with signposts that should help tailor therapies based on risk category. Importantly, these data may provide researchers with key insights into molecular mechanisms driving disease severity, which might also represent targets for future therapies.”
Funding for this research was provided through grants from the National Cancer Institute, The Lebow Fund to Cure Myeloma, and the
Links on This Page
Myeloma Institute for Research and Therapy: http://myeloma.uams.edu/
Myeloma Researchers Find New Tool for Identifying High-Risk Cases: http://www.uams.edu/update/absolutenm/templates/myeloma/myeloma_news.asp?articleid=6220&zoneid=132
Molecular Diagnostics in Cancer Therapeutic Development: http://www.aacr.org/home/scientists/meetings–workshops/molecular-diagnostics-in-cancer-therapeutic-development.aspx