NEW YORK (GenomeWeb News) – Gene expression data — as well as cellular proliferation and immune markers — can be used to better classify metastatic melanoma tumors, a new study suggests.
Researchers from New York University, the University of California at Riverside, and the University of Minnesota assessed gene expression data, cell proliferation, and immune function in dozens of metastatic melanoma tumors in an effort to come up with more ways to refine the classification of these tumors. In so doing, they identified hundreds of genes linked to survival, including genes involved in immune system and cell division functions.
The research, scheduled to appear online this week in the Proceedings of the National Academy of Science, suggests enhanced expression of immune-related genes is associated with good outcomes while up-regulation of cell proliferation genes tend to correlate with poor outcomes. By looking at differentially expressed genes, the team also found a gene expression signature with prognostic value in metastatic tumors from individuals with advanced melanoma.
"Our data indicate that metastatic melanoma is biologically diverse and that there is a need to tailor clinical trials toward the molecular and cellular profile of each patient," senior author Nina Bhardwaj, a cancer, dermatology, and pathology researcher at the NYU Langone Medical Center, and her co-authors wrote.
Limited treatment options are available for advanced melanoma skin cancer, Bhardwaj and her colleagues explained. And because these treatments typically don't cure the disease, locally advanced melanoma can progress to metastatic melanoma, in which the cancer spreads to other organs. Overall survival rates for metastatic melanoma are low, though some individuals can survive for relatively long periods of time.
"The ability to predict survival in metastatic melanoma with greater accuracy could improve current treatment decisions and aid in the design of new therapies that might be tailored to specific subgroups of patients," the researchers noted. "It would potentially be useful to biologically sub-classify melanoma that has already metastasized, beyond the use of the conventional Tumor, Node, Metastasis (TNM) staging, into categories that more accurately predict patient survival."
In its study, the team attempted to identify differences in metastatic melanoma survival by integrating genetic, molecular, and cellular data for 44 metastatic melanoma tumors from 38 patients. Five of the tumors tested came from individuals with stage IV melanoma, while 39 came from stage III melanoma cases. For each patient, follow-up data was available for between two and 38 months, with a median follow-up time of 20 months.
Using Affymetrix Human Genome U133 Plus 2.0 arrays, the researchers assessed gene expression in the tumors. They then employed the Significant Analysis of Microarrays to pinpoint genes whose expression differed by 1.5 times or more in patients with longer survival times compared with those with short survival.
The team also looked at mitotic index, an indicator of cellular proliferation, and two immune-related measurements: the number of tumor infiltrating leukocytes (TIL) and CD3+ T-cells present in the metastatic tumor.
Gene expression, mitotic index, TIL, and CD3+ data each improved the accuracy with which the researchers could classify the tumors and predict survival over existing TNM approaches, the team reported.
By adding expression, proliferation, and immune data, the researchers were able to identify a low-risk patient group, with a median survival time of nearly 1,100 days, and a high-risk patient group, with a median survival of less than 500 days. The team found similar results in an independent validation group involving 52 metastatic tumors from stage III and IV melanoma patients.
In terms of gene expression, the researchers identified 266 genes linked to survival. Among them: 40 transcripts for genes contributing to either innate or adaptive immune system response. These immune genes were generally upregulated in individuals with better outcomes.
"The upregulation of immune system transcripts in metastatic lesions of patients with longer survival suggests that the immune response may keep tumor growth and metastasis in check in these patients," the authors explained.
On the other hand, increased expression of genes involved in cellular proliferation processes such as cell division, cytoskeleton function, and cell cycle control were associated with poor survival outcomes.
Using their differentially expressed gene data, the researchers developed a prognostic genetic signature that can accurately classify the majority of melanoma cases, though the sensitivity and specificity varied depending on the number of genes evaluated.
Even so, the team found, the mitotic index of metastatic tumors independently added the most information to the existing TNM classification scheme. "MI provides a relatively simple and effective way to further differentiate a patient's ability to fight metastatic melanoma, either used alone or in combination with gene expression analysis," they wrote.