DNA analysis (i.e., molecular genetics) can be used in evaluating lung cancer, and can reliably separate lung tumors into their morphologic categories of squamous, large cell, small cell, and adenocarcinoma. Gene expression profiling (GEP) may have even more utility in the assessment of patients with non-small cell lung cancers (NSCLCs) and similar histology.
Several investigators have attempted to subclassify these tumors by correlating GEP patterns with clinicopathologic variables.
A series that included 41 lung adenocarcinomas identified three prognostically separate subgroups. The genes involved in this classification included thyroid transcription factor, hepsin, cathepsin L, vascular endothelial growth factor C (VEGF-C), and the intercellular adhesion molecule-1 (ICAM-1).
In another report of 139 lung adenocarcinomas defined four distinct subclasses. Tumors expressing neuroendocrine-type genes had a significantly less favorable survival than those lacking such characteristics. The genes that defined the neuroendocrine cluster adenocarcinomas included dopa decarboxylase, achaete-scute homolog 1, and the serine protease kallikrein 11.
Others used GEP to predict outcome from surgery in 67 patients with resected stage I adenocarcinoma. A specific group of genes distinguished high-risk from lower risk groups, with significantly different survival. Among the 50 genes comprising the risk index were erbB2, VEGF, S100P, cytokeratin 7 and 18, and fas-associated death domain protein.
In another series of 125 patients from Taiwan with surgically resected NSCLC, 16 genes were identified that correlated with increased or decreased survival. Further RT-PCR validation assay confirmed the microarray findings and showed that survival was significantly associated with five of the 16 genes (DUSP6, MMD, STAT1, ERBB3, and LCK). The five-gene signature was further validated in microarray data from patients of Western population and was an independent predictor of recurrence and overall survival for patients with surgical resection of NSCLC without any adjuvant therapy. This GEP profile is being used to select high risk patients for adjuvant chemotherapy in prospective clinical trials.
Lymphoma - Gene expression profiling (GEP) by means of DNA microarrays is an evolving approach to classification, diagnosis, and prognostication of Non-Hodgkin's Lymphoma (NHL).
As an example, diffuse large B-cell lymphoma (DLBCL) is a clinically heterogeneous disease in which approximately 40 percent of patients with advanced stage disease respond well to combination chemotherapy and are long-term survivors. Using GEP, DLBCL has been subclassified into three distinct molecular subgroups, germinal center B-cell-like (GCB), activated B-cell-like (ABC), and other (type 3), that appear to be derived from different stages of B-cell differentiation, utilize different oncogenic mechanisms, and differ clinically in their ability to be cured by multiagent chemotherapy.
Patients whose tumors express genes characteristic of germinal center B cells (GCB) have a significantly better outcome from chemotherapy than those whose gene expression is more typical of activated B cells (ABC). In one series for example, a clustering algorithm applied to 58 patients with DLBCL receiving cyclophosphamide, doxorubicin, vincristine and prednisone (CHOP) chemotherapy separated patients into two groups with very different five-year overall survival rates (70 versus 12 percent).
Although most of the early studies used fresh frozen tissue sections, similar results have been reported with GEP performed on formalin-fixed, paraffin-embedded material. No formal head-to-head comparisons of GEP from fresh versus archived materials have yet been performed.
GEP has also been used to develop a more precise molecular diagnosis of primary mediastinal B-cell lymphoma, a clinically unfavorable entity that cannot be reliably distinguished from other types of diffuse large B-cell lymphoma. These tumors do poorly with CHOP chemotherapy alone and may need more aggressive therapy than used for standard DLBCL.
Finally, GEP has the potential to reveal new therapeutic molecular targets. As an example, the ABC subtype of DLBCL is characterized by constitutive activation of the nuclear factor kappaB (NF-kappaB) signaling pathway; interference with this pathway selectively kills these lymphoma cells. The ubiquitin-proteasomal pathway and the NF-kappaB axis are intimately involved in the control of apoptosis. Inhibitors of this pathway (eg, proteasome inhibitors) can induce apoptosis in human leukemia cells that ectopically express the antiapoptotic protein Bcl-2. One such agent, the synthetic dipeptide boronic acid bortezomib, is a potent promoter of apoptosis in several human tumor cell types.
Summary - The rapidly evolving field of DNA microarray analysis and gene expression profiling has wide-ranging implications for the molecular classification of tumors, refinement of prognostic estimates, and prediction of response to therapy. Despite its exciting potential and significant recent advances, this field remains relatively new, and it is premature to conclude that microarray data can be used as a sole means of classifying cancers or predicting outcomes of treatment.
Among the specific challenges that must be met are the need for larger studies with appropriate validation, standardization of methods and establishment of guidelines for the conduct and reporting of studies, and the formation of repositories and registries where research institutions may deposit data for comparison with independent works involving the same malignant disorder. Finally, DNA microarray-based tests must demonstrate utility in prospectively designed clinical trials before this technology is considered a routine part of clinical evaluation. These studies may eventually establish a new treatment paradigm in personalized cancer therapy in the future.
Dr. Richard Graydon, http://www.medauthor.com, trained as an Oncologist, holding both M.D. and PhD degrees, andspecializes in molecular genetics and cancer research. His education and experience have provided him analytical and clinical skills for keen insight into diagnosis, treatment, and care of cancer patients. See http://www.medauthor.com for further information
By Richard Graydon, M.D.
Several investigators have attempted to subclassify these tumors by correlating GEP patterns with clinicopathologic variables.
A series that included 41 lung adenocarcinomas identified three prognostically separate subgroups. The genes involved in this classification included thyroid transcription factor, hepsin, cathepsin L, vascular endothelial growth factor C (VEGF-C), and the intercellular adhesion molecule-1 (ICAM-1).
In another report of 139 lung adenocarcinomas defined four distinct subclasses. Tumors expressing neuroendocrine-type genes had a significantly less favorable survival than those lacking such characteristics. The genes that defined the neuroendocrine cluster adenocarcinomas included dopa decarboxylase, achaete-scute homolog 1, and the serine protease kallikrein 11.
Others used GEP to predict outcome from surgery in 67 patients with resected stage I adenocarcinoma. A specific group of genes distinguished high-risk from lower risk groups, with significantly different survival. Among the 50 genes comprising the risk index were erbB2, VEGF, S100P, cytokeratin 7 and 18, and fas-associated death domain protein.
In another series of 125 patients from Taiwan with surgically resected NSCLC, 16 genes were identified that correlated with increased or decreased survival. Further RT-PCR validation assay confirmed the microarray findings and showed that survival was significantly associated with five of the 16 genes (DUSP6, MMD, STAT1, ERBB3, and LCK). The five-gene signature was further validated in microarray data from patients of Western population and was an independent predictor of recurrence and overall survival for patients with surgical resection of NSCLC without any adjuvant therapy. This GEP profile is being used to select high risk patients for adjuvant chemotherapy in prospective clinical trials.
Lymphoma - Gene expression profiling (GEP) by means of DNA microarrays is an evolving approach to classification, diagnosis, and prognostication of Non-Hodgkin's Lymphoma (NHL).
As an example, diffuse large B-cell lymphoma (DLBCL) is a clinically heterogeneous disease in which approximately 40 percent of patients with advanced stage disease respond well to combination chemotherapy and are long-term survivors. Using GEP, DLBCL has been subclassified into three distinct molecular subgroups, germinal center B-cell-like (GCB), activated B-cell-like (ABC), and other (type 3), that appear to be derived from different stages of B-cell differentiation, utilize different oncogenic mechanisms, and differ clinically in their ability to be cured by multiagent chemotherapy.
Patients whose tumors express genes characteristic of germinal center B cells (GCB) have a significantly better outcome from chemotherapy than those whose gene expression is more typical of activated B cells (ABC). In one series for example, a clustering algorithm applied to 58 patients with DLBCL receiving cyclophosphamide, doxorubicin, vincristine and prednisone (CHOP) chemotherapy separated patients into two groups with very different five-year overall survival rates (70 versus 12 percent).
Although most of the early studies used fresh frozen tissue sections, similar results have been reported with GEP performed on formalin-fixed, paraffin-embedded material. No formal head-to-head comparisons of GEP from fresh versus archived materials have yet been performed.
GEP has also been used to develop a more precise molecular diagnosis of primary mediastinal B-cell lymphoma, a clinically unfavorable entity that cannot be reliably distinguished from other types of diffuse large B-cell lymphoma. These tumors do poorly with CHOP chemotherapy alone and may need more aggressive therapy than used for standard DLBCL.
Finally, GEP has the potential to reveal new therapeutic molecular targets. As an example, the ABC subtype of DLBCL is characterized by constitutive activation of the nuclear factor kappaB (NF-kappaB) signaling pathway; interference with this pathway selectively kills these lymphoma cells. The ubiquitin-proteasomal pathway and the NF-kappaB axis are intimately involved in the control of apoptosis. Inhibitors of this pathway (eg, proteasome inhibitors) can induce apoptosis in human leukemia cells that ectopically express the antiapoptotic protein Bcl-2. One such agent, the synthetic dipeptide boronic acid bortezomib, is a potent promoter of apoptosis in several human tumor cell types.
Summary - The rapidly evolving field of DNA microarray analysis and gene expression profiling has wide-ranging implications for the molecular classification of tumors, refinement of prognostic estimates, and prediction of response to therapy. Despite its exciting potential and significant recent advances, this field remains relatively new, and it is premature to conclude that microarray data can be used as a sole means of classifying cancers or predicting outcomes of treatment.
Among the specific challenges that must be met are the need for larger studies with appropriate validation, standardization of methods and establishment of guidelines for the conduct and reporting of studies, and the formation of repositories and registries where research institutions may deposit data for comparison with independent works involving the same malignant disorder. Finally, DNA microarray-based tests must demonstrate utility in prospectively designed clinical trials before this technology is considered a routine part of clinical evaluation. These studies may eventually establish a new treatment paradigm in personalized cancer therapy in the future.
Dr. Richard Graydon, http://www.medauthor.com, trained as an Oncologist, holding both M.D. and PhD degrees, andspecializes in molecular genetics and cancer research. His education and experience have provided him analytical and clinical skills for keen insight into diagnosis, treatment, and care of cancer patients. See http://www.medauthor.com for further information
By Richard Graydon, M.D.
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