By analyzing the genes that are active in tumor cells, scientists may be able to predict whether the most common form of liver cancer, hepatocellular carcinoma, is likely to spread from its original site. Researchers at the National Cancer Institute (NCI), in collaboration with surgeons at the Liver Cancer Institute of Fudan University in Shanghai, report in a study published in Nature Medicine* that they have identified a pattern of gene activity that is unique to hepatocellular carcinoma cells that spread, or metastasize. Knowing whether a tumor is likely to metastasize can help physicians decide on the best treatment strategy for a patient. From the National Cancer Institute :
Metastasis Gene May Be Useful for Diagnosis and Treatment of Liver Cancer
Sunday, March 16, 2003
By analyzing the genes that are active in tumor cells, scientists may be able to predict whether the most common form of liver cancer, hepatocellular carcinoma, is likely to spread from its original site. Researchers at the National Cancer Institute (NCI), in collaboration with surgeons at the Liver Cancer Institute of Fudan University in Shanghai, report in a study published in Nature Medicine* that they have identified a pattern of gene activity that is unique to hepatocellular carcinoma cells that spread, or metastasize. Knowing whether a tumor is likely to metastasize can help physicians decide on the best treatment strategy for a patient.
Additionally, researchers have identified a specific gene required for metastasis. The gene, known as osteopontin, may be a useful diagnostic marker for metastasis. The protein it produces is a potential target for therapeutic agents for metastatic hepatocellular carcinoma.
Hepatocellular carcinoma is one of the most common and aggressive malignant tumors worldwide. Although incidence rates are relatively low in the United States, they are higher in Asia and Africa, where liver cancer risk factors such as hepatitis infection and contamination of food by aflatoxin (a known cancer-causing substance) are more prevalent. Recent studies indicate that the incidence of liver cancer in the United States is rising, while rates of most other cancers are declining. Poor survival among patients with hepatocellular carcinoma is attributed primarily to the high rate of metastasis after treatment, usually spreading to other parts of the liver.
The initial goal of the study was to identify genes that allow researchers to discriminate hepatocellular carcinoma patients’ original tumors from metastastic tumors. Surprisingly, researchers found that the genes expressed in metastatic tumors were identical to those in the original tumor, a finding that challenges the current model of metastasis progression. Differences became apparent, instead, between the activity of genes in tumors that went on to metastasize and genes in tumors that did not spread.
“The fact that gene activity in metastatic tumors is identical to that in the tumors from which they originated, but metastasis-free tumors are distinct, suggests that changes favoring metastasis occur in the original tumor,” said Xin Wei Wang, Ph.D., of NCI’s Center for Cancer Research, the lead investigator on the study. “If we can identify in advance patients whose tumors are likely to metastasize, it will improve our ability to individualize treatment of their disease.”
To reveal key differences between liver tumors that were likely to metastasize and those that were not, researchers compared gene activity in tumor samples. All of the tumor samples were from patients’ original tumors, whether or not those tumors had eventually metastasized.
To measure gene activity, researchers used DNA microarray technology. Microarrays, also known as gene chips, are glass slides that have been coated with thousands of spots of DNA, each representing a different gene. When a gene is active in a cell, it produces RNA copies known as transcripts. To measure the activity of genes, researchers tag the RNA transcripts in the tumor cell with a fluorescent marker. When the tagged RNA transcripts are allowed to bind to their corresponding DNA spots on the gene chip, those spots on the chip light up. Scientists use the pattern and intensity of light emitted to determine the activity of each of the chip’s thousands of genes.
After analyzing the activity of more than 9,000 genes within the tumor cells, a computer algorithm determined that a group of 153 of these genes could be used to distinguish between the two groups of tumors. The activity of these 153 genes differed significantly depending on whether or not a tumor had the potential to spread.
Once scientists had identified the set of genes that could discriminate between hepatocellular tumors with and without metastases, they used these genes to see if they could correctly identify 40 tumor samples. The clinical outcome of these patients was known, but not to the scientists. Of the 40 samples, the test correctly identified 82 percent of the tumors with metastatic potential, and 67 percent of the tumors from patients free of metastasis.
Researchers next examined the set of key genes more closely and identified one gene whose activity was particularly high in tumors with metastatic potential. The gene produces a protein known as osteopontin, which, researchers found, plays an important role in metastasis. Increased activity of the gene leads to an abnormally high level of osteopontin protein in tumor cells, which appears to promote metastasis.
Researchers found that high levels of osteopontin protein made cancer cells grown in the laboratory more likely to invade neighboring tissue. Furthermore, blocking the activity of the protein prevented tumor cells from spreading, in both mice and cells grown in the laboratory. Thus, osteopontin may be useful not only for predicting which cancers are likely to metastasize, but also as a potential therapeutic target for hepatocellular carcinoma.
“Osteopontin can be found in all body fluids, which makes it an excellent diagnostic marker,” said Wang. Also, because osteopontin protein is located on the outside of cells, it may be more easily reached by pharmaceutical agents than drug targets inside the cell, making researchers optimistic about its potential role in treatment.
* Ye Q, et al. Predicting hepatitis B virus-positive metastatic hepatocellular carcinoma using gene expression profiling and supervised machine learning. Nature Medicine 2003. Available online March 17, 2003, at http://www.nature.com/nm.