Project description:Understanding the genetic architecture of cancer pathways that distinguishes subsets of human cancer is critical to developing new therapies that better target tumors based upon their molecular expression profiles. In this study, we identify an integrated gene signature from multiple transgenic models of epithelial cancers intrinsic to the functions of the Simean virus 40 T/t-antigens that is associated with the biologic behavior and prognosis for several human epithelial tumors. This genetic signature, composed primarily of genes regulating cell replication, proliferation, DNA repair and apoptosis, is not a general cancer signature. Rather, it is uniquely activated primarily in tumors with aberrant p53, Rb or BRCA1 expression, but not in tumors initiated through the overexpression of myc, ras, her2/neu, or Polyoma middle T oncogenes. Importantly, human breast, lung and prostate tumors expressing this set of genes represent subsets of tumors with the most aggressive phenotype and with poor prognosis. The T/t-antigen signature is highly predictive of human breast cancer prognosis. Since this class of epithelial tumors is generally intractable to currently existing standard therapies, this genetic signature identifies potential targets for novel therapies directed against these lethal forms of cancer. Since the these genetic targets have been discovered using mammary, prostate, and lung T/t-antigen mouse cancer models, these models are rationale candidates for use in pre-clinical testing of therapies focused on these biologically important targets. Keywords: Genetically engineered mouse (GEM) models of cancer, epithelial carcinoma, SV40 T/t-antigen, survival predictor Gene expression profiles from the SV40 T/t-antigen mouse models were compared with respect to specimen type (normal vs. tumor tissue), location of tumor (mammary, lung, prostate, seminal vesicle), and background strain of mice (FVB vs. C57BL/6). A three-way ANOVA model with one interaction effect (type X location) was fitted. Cancer genes that differ among all four tumor locations were identified, as those that had a significant interaction effect at the 0.001 level and showed at least a 2-fold change between the maximal and minimal mean tumor/normal ratio over the different locations (2638 cDNA probes). Based on the ANOVA model, differentially expressed genes between normal and tumor specimens within each tumor location were also identified, as those genes whose expression were significant at the 0.001 level and were at least 2-fold different compared to the mean expression ratio. Overall 3004 unique array features were selected using ANOVA. Further selection was applied based upon identification of differentially expressed genes between normal and tumor tissue for the three epithelial tumors (mammary, lung and prostate). The SV40 T/t-antigen oncogene-specific signature included genes similarly differentially expressed in each epithelial tumor (153 cDNA clones). In contrast, genes were included in a tissue-specific SV40 T/t-antigen tumor signature if they were found to be differentially expressed between the tumor and normal samples exclusively for one location. Two-hundred and eighty three, 220 and 999 cDNA clones were identified as specifically dysregulated in mammary, lung and prostate tumors, respectively). This set of the mammary mouse tumor models was used to demonstrate that the intrinsic SV40 T/t-antigen signature is not a feature of tumors initiated by other oncogenes or inactivation of supressor genes, but is most specific to tumors induced by T/t-antigen.

Project description:Understanding the genetic architecture of cancer pathways that distinguishes subsets of human cancer is critical to developing new therapies that better target tumors based upon their molecular expression profiles. In this study, we identify an integrated gene signature from multiple transgenic models of epithelial cancers intrinsic to the functions of the Simean virus 40 T/t-antigens that is associated with the biologic behavior and prognosis for several human epithelial tumors. This genetic signature, composed primarily of genes regulating cell replication, proliferation, DNA repair and apoptosis, is not a general cancer signature. Rather, it is uniquely activated primarily in tumors with aberrant p53, Rb or BRCA1 expression, but not in tumors initiated through the overexpression of myc, ras, her2/neu, or Polyoma middle T oncogenes. Importantly, human breast, lung and prostate tumors expressing this set of genes represent subsets of tumors with the most aggressive phenotype and with poor prognosis. The T/t-antigen signature is highly predictive of human breast cancer prognosis. Since this class of epithelial tumors is generally intractable to currently existing standard therapies, this genetic signature identifies potential targets for novel therapies directed against these lethal forms of cancer. Since the these genetic targets have been discovered using mammary, prostate, and lung T/t-antigen mouse cancer models, these models are rationale candidates for use in pre-clinical testing of therapies focused on these biologically important targets. Keywords: Genetically engineered mouse (GEM) models of cancer, epithelial carcinoma, SV40 T/t-antigen, survival predictor Gene expression profiles from the SV40 T/t-antigen mouse models were compared with respect to specimen type (normal vs. tumor tissue), location of tumor (mammary, lung, prostate, seminal vesicle), and background strain of mice (FVB vs. C57BL/6). A three-way ANOVA model with one interaction effect (type X location) was fitted. Cancer genes that differ among all four tumor locations were identified, as those that had a significant interaction effect at the 0.001 level and showed at least a 2-fold change between the maximal and minimal mean tumor/normal ratio over the different locations (2638 cDNA probes). Based on the ANOVA model, differentially expressed genes between normal and tumor specimens within each tumor location were also identified, as those genes whose expression were significant at the 0.001 level and were at least 2-fold different compared to the mean expression ratio. Overall 3004 unique array features were selected using ANOVA. Further selection was applied based upon identification of differentially expressed genes between normal and tumor tissue for the three epithelial tumors (mammary, lung and prostate). The SV40 T/t-antigen oncogene-specific signature included genes similarly differentially expressed in each epithelial tumor (153 cDNA clones). In contrast, genes were included in a tissue-specific SV40 T/t-antigen tumor signature if they were found to be differentially expressed between the tumor and normal samples exclusively for one location. Two-hundred and eighty three, 220 and 999 cDNA clones were identified as specifically dysregulated in mammary, lung and prostate tumors, respectively).

Project description:Understanding the genetic architecture of cancer pathways that distinguishes subsets of human cancer is critical to developing new therapies that better target tumors based upon their molecular expression profiles. In this study, we identify an integrated gene signature from multiple transgenic models of epithelial cancers intrinsic to the functions of the Simean virus 40 T/t-antigens that is associated with the biologic behavior and prognosis for several human epithelial tumors. This genetic signature, composed primarily of genes regulating cell replication, proliferation, DNA repair and apoptosis, is not a general cancer signature. Rather, it is uniquely activated primarily in tumors with aberrant p53, Rb or BRCA1 expression, but not in tumors initiated through the overexpression of myc, ras, her2/neu, or Polyoma middle T oncogenes. Importantly, human breast, lung and prostate tumors expressing this set of genes represent subsets of tumors with the most aggressive phenotype and with poor prognosis. The T/t-antigen signature is highly predictive of human breast cancer prognosis. Since this class of epithelial tumors is generally intractable to currently existing standard therapies, this genetic signature identifies potential targets for novel therapies directed against these lethal forms of cancer. Since the these genetic targets have been discovered using mammary, prostate, and lung T/t-antigen mouse cancer models, these models are rationale candidates for use in pre-clinical testing of therapies focused on these biologically important targets. Keywords: SuperSeries Gene expression profiles from the SV40 T/t-antigen mouse models were compared with respect to specimen type (normal vs. tumor tissue), location of tumor (mammary, lung, prostate, seminal vesicle), and background strain of mice (FVB vs. C57BL/6). A three-way ANOVA model with one interaction effect (type X location) was fitted. Cancer genes that differ among all four tumor locations were identified, as those that had a significant interaction effect at the 0.001 level and showed at least a 2-fold change between the maximal and minimal mean tumor/normal ratio over the different locations (2638 cDNA probes). Based on the ANOVA model, differentially expressed genes between normal and tumor specimens within each tumor location were also identified, as those genes whose expression were significant at the 0.001 level and were at least 2-fold different compared to the mean expression ratio. Overall 3004 unique array features were selected using ANOVA. Further selection was applied based upon identification of differentially expressed genes between normal and tumor tissue for the three epithelial tumors (mammary, lung and prostate). The SV40 T/t-antigen oncogene-specific signature included genes similarly differentially expressed in each epithelial tumor (153 cDNA clones). In contrast, genes were included in a tissue-specific SV40 T/t-antigen tumor signature if they were found to be differentially expressed between the tumor and normal samples exclusively for one location. Two-hundred and eighty three, 220 and 999 cDNA clones were identified as specifically dysregulated in mammary, lung and prostate tumors, respectively).

Dataset Information

Mus musculus

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets