Citations

Abstract Aromatase [cytochrome P450 19 (CYP19)] is a critical enzyme for estrogen biosynthesis, and aromatase inhibitors are of increasing importance in the treatment of breast cancer. We set out to identify and characterize genetic polymorphisms in the aromatase gene, CYP19, as a step toward pharmacogenomic studies of aromatase inhibitors. Specifically, we “resequenced” all coding exons, all upstream untranslated exons plus their presumed core promoter regions, all exon-intron splice junctions, and a portion of the 3′-untranslated region of CYP19 using 240 DNA samples from four ethnic groups. Eighty-eight polymorphisms were identified, resulting in 44 haplotypes. Functional genomic studies were done with the four nonsynonymous coding single nucleotide polymorphisms (cSNP) that we observed, two of which were novel. Those cSNPs altered the following amino acids: Trp39Arg, Thr201Met, Arg264Cys, and Met364Thr. The Cys264, Thr364, and double variant Arg39Cys264 allozymes showed significant decreases in levels of activity and immunoreactive protein when compared with the wild-type (WT) enzyme after transient expression in COS-1 cells. A slight decrease in protein level was also observed for the Arg39 allozyme, whereas Met201 displayed no significant changes in either activity or protein level when compared with the WT enzyme. There was also a 4-fold increase in apparent Km value for Thr364 with androstenedione as substrate. Of the recombinant allozymes, only the double mutant (Arg39Cys264) displayed a significant change from the WT enzyme in inhibitor constant for the aromatase inhibitors exemestane and letrozole. These observations indicate that genetic variation in CYP19 might contribute to variation in the pathophysiology of estrogen-dependent disease.

Abstract Purpose: Patients with a preoperative cytologic diagnosis of a suspicious thyroid nodule present a therapeutic dilemma because surgery differs for benign and malignant lesions. To address this issue, several molecular markers, including human telomerase reverse transcriptase (TERT), have been tested as markers of thyroid cancer. Because most studies select cases falling into well-defined categories to test new markers, they may overestimate their discriminatory power when applied to samples that are difficult to classify. Fine-needle aspirates (FNAs) of the thyroid with indeterminate cytology are an example of such cases. Experimental Design: We examined whether assessing TERT mRNA by reverse transcription-PCR could have improved the surgical management in a cohort of 100 patients undergoing thyroidectomy for indeterminate FNA results. Results: Ninety percent of 48 cancers were TERT positive, as were 35% of 52 benign lesions. When 10 cases with concomitant lymphocytic thyroiditis were excluded, the overall sensitivity of TERT was 91% (95% confidence interval, 80–98%) and specificity was 79% (64–90%). No clinical or tumor variable contributed to the predictive ability of TERT except for tumor size, which added only marginally. Basing the surgical approach on the TERT assay alone would have reduced lobectomies performed for malignant disease from 11 to 4 cases and reduced total thyroidectomies for benign lesions from to 15 to 9, an overall 50% reduction in suboptimal treatment. Conclusions: The overall performance of preoperative differential diagnosis for thyroid tumors with indeterminate FNA results can be substantially improved by the inclusion of molecular markers such as TERT.

Abstract Purpose: Advanced-stage epithelial ovarian cancer has a poor prognosis with long-term survival in less than 30% of patients. When the disease is detected in stage I, more than 90% of patients can be cured by conventional therapy. Screening for early-stage disease with individual serum tumor markers, such as CA125, is limited by the fact that no single marker is up-regulated and shed in adequate amounts by all ovarian cancers. Consequently, use of multiple markers in combination might detect a larger fraction of early-stage ovarian cancers. Experimental Design: To identify potential candidates for novel markers, we have used Affymetrix human genome arrays (U95 series) to analyze differences in gene expression of 41,441 known genes and expressed sequence tags between five pools of normal ovarian surface epithelial cells (OSE) and 42 epithelial ovarian cancers of different stages, grades, and histotypes. Recursive descent partition analysis (RDPA) was performed with 102 probe sets representing 86 genes that were up-regulated at least 3-fold in epithelial ovarian cancers when compared with normal OSE. In addition, a panel of 11 genes known to encode potential tumor markers [mucin 1, transmembrane (MUC1), mucin 16 (CA125), mesothelin, WAP four-disulfide core domain 2 (HE4), kallikrein 6, kallikrein 10, matrix metalloproteinase 2, prostasin, osteopontin, tetranectin, and inhibin] were similarly analyzed. Results: The 3-fold up-regulated genes were examined and four genes [Notch homologue 3 (NOTCH3), E2F transcription factor 3 (E2F3), GTPase activating protein (RACGAP1), and hematological and neurological expressed 1 (HN1)] distinguished all tumor samples from normal OSE. The 3-fold up-regulated genes were analyzed using RDPA, and the combination of elevated claudin 3 (CLDN3) and elevated vascular endothelial growth factor (VEGF) distinguished the cancers from normal OSE. The 11 known markers were analyzed using RDPA, and a combination of HE4, CA125, and MUC1 expression could distinguish tumor from normal specimens. Expression at the mRNA level in the candidate markers was examined via semiquantitative reverse transcription-PCR and was found to correlate well with the array data. Immunohistochemistry was performed to identify expression of the genes at the protein level in 158 ovarian cancers of different histotypes. A combination of CLDN3, CA125, and MUC1 stained 157 (99.4%) of 158 cancers, and all of the tumors were detected with a combination of CLDN3, CA125, MUC1, and VEGF. Conclusions: Our data are consistent with the possibility that a limited number of markers in combination might identify >99% of epithelial ovarian cancers despite the heterogeneity of the disease.

Abstract Purpose: Epithelial ovarian cancers are thought to arise from flattened epithelial cells that cover the ovarian surface or that line inclusion cysts. During malignant transformation, different histotypes arise that resemble epithelial cells from normal fallopian tube, endometrium, and intestine. This study compares gene expression in serous, endometrioid, clear cell, and mucinous ovarian cancers with that in the normal tissues that they resemble. Experimental Design: Expression of 63,000 probe sets was measured in 50 ovarian cancers, in 5 pools of normal ovarian epithelial brushings, and in mucosal scrapings from 4 normal fallopian tube, 5 endometrium, and 4 colon specimens. Using rank-sum analysis, genes whose expressions best differentiated the ovarian cancer histotypes and normal ovarian epithelium were used to determine whether a correlation based on gene expression existed between ovarian cancer histotypes and the normal tissues they resemble. Results: When compared with normal ovarian epithelial brushings, alterations in serous tumors correlated with those in normal fallopian tube (P = 0.0042) but not in other normal tissues. Similarly, mucinous cancers correlated with those in normal colonic mucosa (P = 0.0003), and both endometrioid and clear cell histotypes correlated with changes in normal endometrium (P = 0.0172 and 0.0002, respectively). Mucinous cancers displayed the greatest number of alterations in gene expression when compared with normal ovarian epithelial cells. Conclusion: Studies at a molecular level show distinct expression profiles of different histologies of ovarian cancer and support the long-held belief that histotypes of ovarian cancers come to resemble normal fallopian tube, endometrial, and colonic epithelium. Several potential molecular markers for mucinous ovarian cancers have been identified.

Abstract Purpose: The objective of this study was to use gene expression profiling to identify novel biomarkers that are predictive of aggressive behavior in clear cell renal cell carcinoma (CCRCC). Experimental Design: Candidate genes were discovered using Human Genome U133 Plus 2 Arrays and validated on independent samples by quantitative reverse transcription-PCR (RT-PCR). Both the discovery and the validation cohorts included nonaggressive primary CCRCC, aggressive primary CCRCC, metastatic CCRCC, and nonneoplastic kidney adjacent to tumor. Results: Aggressive primary and metastatic CCRCC displayed no significant differences in gene expression. In contrast, we identified significant differences in gene expression between nonaggressive and aggressive CCRCC (including metastatic CCRCC). Thirty-four of the 35 transcripts that displayed the most significant differential expression by microarray analysis also displayed significant differential expression in independent validation studies using quantitative RT-PCR (P < 0.001 for 31 candidates and P < 0.005 for the remaining three candidates). Hierarchical clustering of the quantitative RT-PCR data using our candidate markers accurately grouped 88% (23 of 26) of aggressive and metastatic CCRCC samples, 100% (14 of 14) of nonaggressive CCRCC samples, and 100% (15 of 15) of nonneoplastic samples into separate clusters. Finally, we evaluated the ability of protein expression levels of one of our candidate markers (survivin) to predict survival among a cohort of 183 CCRCC patients treated surgically at Mayo Clinic from 1990 to 1992. In multivariate analysis, expression of survivin (BIRC5) was inversely associated with cancer-specific survival (P = 0.017). Conclusion: We used a combination of genomic profiling and validation by quantitative PCR to identify a panel of candidate biomarkers for determining CCRCC aggressiveness. Our data also indicate that the gene expression alterations that result in aggressive behavior and metastatic potential can be identified in the primary tumor.

Abstract Purpose: Women with advanced epithelial ovarian cancer are routinely treated with platinum-paclitaxel chemotherapy following cytoreductive surgery, yet only ∼20% achieve long-term disease-free survival. We hypothesized that differences in gene expression before treatment could distinguish patients with short versus long time to recurrence after administration of platinum-paclitaxel combination chemotherapy. Experimental Design: To test this hypothesis, gene expression profiling of 79 primary surgically resected tumors from women with advanced-stage, high-grade epithelial ovarian cancer was done using cDNA microarrays containing 30,721 genes. Supervised learning algorithms were applied in an effort to develop a binary classifier that could discriminate women at risk for early (≤21 months) versus late (>21 months) relapse after initial chemotherapy. Results: A 14-gene predictive model was developed using a set of training samples (n = 51) and subsequently tested using an independent set of test samples (n = 28). This model correctly predicted the outcome of 24 of the 28 test samples (86% accuracy) with 95% positive predictive value for early relapse. Conclusions: Predictive markers for early recurrence can be identified for platinum-paclitaxel combination chemotherapy in primary ovarian carcinoma. The proposed 14-gene model requires further validation.

Abstract The MutLα heterodimer formed by mismatch repair (MMR) proteins MLH1 and PMS2 is a major component of the MMR complex, yet mutations in the PMS2 gene are rare in the etiology of hereditary nonpolyposis colorectal cancer. Evidence from five published cases suggested that contrary to the Knudson principle, PMS2 mutations cause hereditary nonpolyposis colorectal cancer or Turcot syndrome only when they are biallelic in the germline or abnormally expressed. As candidates for PMS2 mutations, we selected seven patients whose colon tumors stained negative for PMS2 and positive for MLH1 by immunohistochemistry. After conversion to haploidy, truncating germline mutations of PMS2 were found in two patients (2192delTAACT and deletion of exon 8). These mutations abrogated PMS2 protein in germline cells by Western analysis. In two additional patients, PMS2 protein from one allele also was abrogated. Novel or previously described missense variants of PMS2 were detected, but their pathogenicity is undetermined. We detected and characterized a new transcript, PMS2CL, showing 98% sequence identity with exons 9 and 11–15 of PMS2 and emanating from a locus close to PMS2 in chromosome 7p. Its predicted protein product was not detected. Thus, in addition to several previously described PMS2-related genes resembling the 5′ end of PMS2, at least one related gene resembles the 3′ end of PMS2. In conclusion, both detectable and presently undefined germline mutations are deleterious and produce susceptibility to cancer by the two-hit mechanism. Paralogous genes interfere with mutation detection, resulting in underdiagnosis of PMS2 mutations. Mutation detection in PMS2 requires haploid DNA.