Early Detection of Breast Cancer Based on Gene-Expression
Early Detection of Breast Cancer Based on Gene-Expression
Introduction: Existing methods to detect breast cancer in asymptomatic patients have limitations, and there is a need to develop more accurate and convenient methods. In this study, we investigated whether early detection of breast cancer is possible by analyzing gene-expression patterns in peripheral blood cells.
Methods: Using macroarrays and nearest-shrunken-centroid method, we analyzed the expression pattern of 1,368 genes in peripheral blood cells of 24 women with breast cancer and 32 women with no signs of this disease. The results were validated using a standard leave-one-out cross-validation approach.
Results: We identified a set of 37 genes that correctly predicted the diagnostic class in at least 82% of the samples. The majority of these genes had a decreased expression in samples from breast cancer patients, and predominantly encoded proteins implicated in ribosome production and translation control. In contrast, the expression of some defense-related genes was increased in samples from breast cancer patients.
Conclusion: The results show that a blood-based gene-expression test can be developed to detect breast cancer early in asymptomatic patients. Additional studies with a large sample size, from women both with and without the disease, are warranted to confirm or refute this finding.
Early detection of breast cancer can improve the chances of successful treatment and recovery. To date, mammographic screening is the most reliable method to detect breast cancer in asymptomatic patients. Although highly effective, it has significant limitations, so that the development of more accurate, convenient, and objective detection methods is needed. In the absence of microcalcification, mammography often fails to detect tumors that are less than 5 mm in size, and also mammograms of women with dense breast tissue are difficult to interpret. For example, in a study of over 11,000 women with no clinical symptoms of breast cancer, the sensitivity of mammography was only 48% for the subset of women with extremely dense breasts, compared with 78% sensitivity for the entire sample of women in the study. In addition, when an abnormality has been detected, further tests involving invasive steps must complement mammography to establish whether the detected abnormality is a cancer.
A vast amount of literature is already available describing the potential use of large-scale gene expression analysis in disease diagnosis, including breast cancer. However, most published work with implications in cancer diagnosis has involved clinical samples comprising either diseased tissues or cells. Obtaining such samples for clinical purposes requires a prior knowledge of both their presence and their location in the body. A gene-expression-based test to detect cancers that does not rely upon the availability of tissues or cells from the diseased area has not yet been described.
It has recently been suggested that circulating leukocytes can be viewed as scouts, continuously maintaining a vigilant and comprehensive surveillance of the body for signs of infection or other threats, including cancer. In line with this view, we show that peripheral blood can be used to develop a gene-expression-based test for early detection of breast cancer. The rationale for using blood cells as monitors for a malignant disease elsewhere in the body is based on the hypothesis that a malignant growth will cause characteristic changes in the biochemical environment of blood. These changes will affect the expression pattern of certain genes in blood cells.
In this pilot study, we have analyzed gene-expression patterns in peripheral blood cells of women diagnosed with breast cancer and women with no signs of this disease. We have identified a panel of genes with distinct expression patterns in cancer versus noncancer samples. The results indicate that breast cancer causes characteristic changes in the biochemical environment of blood already during early stages of disease development. Blood cells sense and respond to the change by decreasing the expression of genes involved in protein synthesis and increasing the expression of defense-related genes. We show that the expression pattern of the identified genes can be used to discriminate and predict the class of breast cancer and non-breast-cancer samples with high accuracy. Our findings should pave way for the development of a blood-based gene-expression test for early detection of breast cancer.
Introduction: Existing methods to detect breast cancer in asymptomatic patients have limitations, and there is a need to develop more accurate and convenient methods. In this study, we investigated whether early detection of breast cancer is possible by analyzing gene-expression patterns in peripheral blood cells.
Methods: Using macroarrays and nearest-shrunken-centroid method, we analyzed the expression pattern of 1,368 genes in peripheral blood cells of 24 women with breast cancer and 32 women with no signs of this disease. The results were validated using a standard leave-one-out cross-validation approach.
Results: We identified a set of 37 genes that correctly predicted the diagnostic class in at least 82% of the samples. The majority of these genes had a decreased expression in samples from breast cancer patients, and predominantly encoded proteins implicated in ribosome production and translation control. In contrast, the expression of some defense-related genes was increased in samples from breast cancer patients.
Conclusion: The results show that a blood-based gene-expression test can be developed to detect breast cancer early in asymptomatic patients. Additional studies with a large sample size, from women both with and without the disease, are warranted to confirm or refute this finding.
Early detection of breast cancer can improve the chances of successful treatment and recovery. To date, mammographic screening is the most reliable method to detect breast cancer in asymptomatic patients. Although highly effective, it has significant limitations, so that the development of more accurate, convenient, and objective detection methods is needed. In the absence of microcalcification, mammography often fails to detect tumors that are less than 5 mm in size, and also mammograms of women with dense breast tissue are difficult to interpret. For example, in a study of over 11,000 women with no clinical symptoms of breast cancer, the sensitivity of mammography was only 48% for the subset of women with extremely dense breasts, compared with 78% sensitivity for the entire sample of women in the study. In addition, when an abnormality has been detected, further tests involving invasive steps must complement mammography to establish whether the detected abnormality is a cancer.
A vast amount of literature is already available describing the potential use of large-scale gene expression analysis in disease diagnosis, including breast cancer. However, most published work with implications in cancer diagnosis has involved clinical samples comprising either diseased tissues or cells. Obtaining such samples for clinical purposes requires a prior knowledge of both their presence and their location in the body. A gene-expression-based test to detect cancers that does not rely upon the availability of tissues or cells from the diseased area has not yet been described.
It has recently been suggested that circulating leukocytes can be viewed as scouts, continuously maintaining a vigilant and comprehensive surveillance of the body for signs of infection or other threats, including cancer. In line with this view, we show that peripheral blood can be used to develop a gene-expression-based test for early detection of breast cancer. The rationale for using blood cells as monitors for a malignant disease elsewhere in the body is based on the hypothesis that a malignant growth will cause characteristic changes in the biochemical environment of blood. These changes will affect the expression pattern of certain genes in blood cells.
In this pilot study, we have analyzed gene-expression patterns in peripheral blood cells of women diagnosed with breast cancer and women with no signs of this disease. We have identified a panel of genes with distinct expression patterns in cancer versus noncancer samples. The results indicate that breast cancer causes characteristic changes in the biochemical environment of blood already during early stages of disease development. Blood cells sense and respond to the change by decreasing the expression of genes involved in protein synthesis and increasing the expression of defense-related genes. We show that the expression pattern of the identified genes can be used to discriminate and predict the class of breast cancer and non-breast-cancer samples with high accuracy. Our findings should pave way for the development of a blood-based gene-expression test for early detection of breast cancer.
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