Moisès Burset

Gene Expression Signature in Urine for Diagnosing and Assessing Aggressiveness of Bladder Urothelial Carcinoma

Purpose: To develop an accurate and noninvasive method for bladder cancer diagnosis and prediction of disease aggressiveness based on the gene expression patterns of urine samples. Experimental Design: Gene expression patterns of 341 urine samples from bladder urothelial cell carcinoma (UCC) patients and 235 controls were analyzed via TaqMan Arrays. In a first phase of the study, three consecutive gene selection steps were done to identify a gene set expression signature to detect and stratify UCC in urine. Subsequently, those genes more informative for UCC diagnosis and prediction of tumor aggressiveness were combined to obtain a classification system of bladder cancer samples. In a second phase, the obtained gene set signature was evaluated in a routine clinical scenario analyzing only voided urine samples. Results: We have identified a 12+2 gene expression signature for UCC diagnosis and prediction of tumor aggressiveness on urine samples. Overall, this gene set panel had 98% sensitivity (SN) and 99% specificity (SP) in discriminating between UCC and control samples and 79% SN and 92% SP in predicting tumor aggressiveness. The translation of the model to the clinically applicable format corroborates that the 12+2 gene set panel described maintains a high accuracy for UCC diagnosis (SN = 89% and SP = 95%) and tumor aggressiveness prediction (SN = 79% and SP = 91%) in voided urine samples. Conclusions: The 12+2 gene expression signature described in urine is able to identify patients suffering from UCC and predict tumor aggressiveness. We show that a panel of molecular markers may improve the schedule for diagnosis and follow-up in UCC patients. Clin Cancer Res; 16(9); 2624–33. ©2010 AACR.

DNA Microarray Expression Profiling of Bladder Cancer Allows Identification of Noninvasive Diagnostic Markers

PURPOSE There is a need in urological practice to identify new bladder cancer molecular markers to further develop noninvasive diagnostic tests. We analyzed bladder cancer gene expression profiles to determine the relevant differentially expressed genes and whether this differential expression is maintained in urine samples. MATERIALS AND METHODS We collected 55 tissue specimens from a total of 43 patients with bladder cancer and 12 controls, and 49 urine samples from bladder washings from a total of 36 patients with bladder cancer and 13 controls between September 2003 and December 2004. DNA microarrays (GeneChip Human Genome U133 Plus 2.0 Array) were used to identify differentially expressed genes at 3 bladder cancer stages. Selected differentially expressed genes were validated in an independent set of bladder washings by quantitative reverse transcriptase-polymerase chain reaction. RESULTS Unsupervised cluster analysis of DNA microarray data showed a clear distinction in control vs tumor samples and low vs high grade tumors. Genes with at least 2-fold differential expression in controls vs tumors (2,937 probe sets or 2,295 genes) and in low vs high grade tumors (674 probe sets or 530 genes) were identified and ranked. Gene expression measurements in bladder washings of the 6 most differentially expressed genes in controls vs tumors were confirmed for the 2 over expressed genes tested by quantitative reverse transcriptase-polymerase chain reaction. All 8 selected differentially expressed genes in low vs high grade tumors were confirmed in bladder washing samples. CONCLUSIONS Bladder cancer analysis by DNA microarrays provides new putative mRNA markers for bladder cancer diagnosis and/or prognosis that can be extrapolated to bladder fluids.

Multiplex preamplification of specific cDNA targets prior to gene expression analysis by TaqMan Arrays

BackgroundAn accurate gene expression quantification using TaqMan Arrays (TA) could be limited by the low RNA quantity obtained from some clinical samples. The novel cDNA preamplification system, the TaqMan PreAmp Master Mix kit (TPAMMK), enables a multiplex preamplification of cDNA targets and therefore, could provide a sufficient amount of specific amplicons for their posterior analysis on TA.FindingsA multiplex preamplification of 47 genes was performed in 22 samples prior to their analysis by TA, and relative gene expression levels of non-preamplified (NPA) and preamplified (PA) samples were compared. Overall, the mean cycle threshold (CT) decrement in the PA genes was 3.85 (ranging from 2.07 to 5.01). A high correlation (r) between the gene expression measurements of NPA and PA samples was found (mean r = 0.970, ranging from 0.937 to 0.994; p < 0.001 in all selected cases). High correlation coefficients between NPA and PA samples were also obtained in the analysis of genes from degraded RNA samples and/or low abundance expressed genes.ConclusionWe demonstrate that cDNA preamplification using the TPAMMK before TA analysis is a reliable approach to simultaneously measure gene expression of multiple targets in a single sample. Moreover, this procedure was validated in genes from degraded RNA samples and low abundance expressed genes. This combined methodology could have wide applications in clinical research, where scarce amounts of degraded RNA are usually obtained and several genes need to be quantified in each sample.

Validation Study of a Noninvasive Urine Test for Diagnosis and Prognosis Assessment of Bladder Cancer: Evidence for Improved Models

PURPOSE We validated the performance of our previously reported test for bladder cancer based on urine gene expression patterns using an independent cohort. We also ascertained whether alternative models could achieve better accuracy. MATERIALS AND METHODS Gene expression patterns of the previously reported 48 genes, including the 12 + 2 genes of the signature, were analyzed by TaqMan® arrays in an independent set of 207 urine samples. We pooled all samples analyzed to date to obtain a larger training set of 404 and used it to search for putative improved new models. RESULTS Our 12 + 2 gene expression signature had overall 80% sensitivity with 86% specificity (AUC 0.914) to discriminate between bladder cancer and control samples. It had 75% sensitivity and 75% specificity (AUC 0.83) to predict tumor aggressiveness in the validation set of urine samples. After grouping all samples 3 new signatures for diagnosis containing 2, 5 and 10 genes, respectively, and 1 containing 6 genes for prognosis were designed. Diagnostic performance of the 2, 5, 10 and 12-gene signatures was maintained or improved in the enlarged sample set (AUC 0.913, 0.941, 0.949 and 0.944, respectively). Performance to predict aggressiveness was also improved in the 14 and 6-gene signatures (AUC 0.855 and 0.906, respectively). CONCLUSIONS This validation study confirms the accuracy of the 12 + 2 gene signature as a noninvasive tool for assessing bladder cancer. We present improved models with fewer genes that must be validated in future studies.

Perfil de expresión génica en el cáncer de próstata: identificación de marcadores candidatos para el diagnóstico no invasivo

OBJECTIVE To analyze gene expression profiles of prostate cancer (PCa) with the aim of determining the relevant differentially expressed genes and subsequently ascertain whether this differential expression is maintained in post-prostatic massage (PPM) urine samples. MATERIAL AND METHODS Forty-six tissue specimens (36 from PCa patients and 10 controls) and 158 urine PPM-urines (113 from PCa patients and 45 controls) were collected between December 2003 and May 2007. DNA microarrays were used to identify genes differentially expressed between tumour and control samples. Ten genes were technically validated in the same tissue samples by quantitative RT-PCR (RT-qPCR). Forty two selected differentially expressed genes were validated in an independent set of PPM-urines by qRT-PCR. RESULTS Multidimensional scaling plot according to the expression of all the microarray genes showed a clear distinction between control and tumour samples. A total of 1047 differentially expressed genes (FDR≤.1) were indentified between both groups of samples. We found a high correlation in the comparison of microarray and RT-qPCR gene expression levels (r=.928, P<.001). Thirteen genes maintained the same fold change direction when analyzed in PPM-urine samples and in four of them (HOXC6, PCA3, PDK4 and TMPRSS2-ERG), these differences were statistically significant (P<.05). CONCLUSION The analysis of PCa by DNA microarrays provides new putative mRNA markers for PCa diagnosis that, with caution, can be extrapolated to PPM-urines.

Sequence Similarity Based Gene Prediction

The Human Genome Project is entering the large scale sequencing phase. During the next few years, millions of bases will be sequenced daily in the genome centers worldwide, and, in order to analyze them, methods to reliably predict the genes encoded in genomic sequences are becoming essential. As the databases of known coding sequences increase in size, gene prediction methods based on sequence similarity to coding sequences-mainly, proteins and ESTs—are becoming increasingly useful, and they are routinely used to identify putative genes in anonymous genomic sequences (see, for instance, The C. Elegans Sequencing Consortium, 1998). There is little systematic knowledge, however, on the accuracy of sequence similarity based gene predictions, in particular of the ability of these methods to correctly infer the exonic structure of the genes in higher eukariotic organisms. In this chapter, we will address this shortcoming, by evaluating the accuracy of gene predictions derived exclusively from sequence similarity database searches. In practice, we will use two programs from the popular BLAST suite (Altschul et al., 1990; Altschul and Gish, 1996): BLASTX (Gish and States, 1993), using a

1274 NONINVASIVE TEST FOR DIAGNOSIS AND AGGRESSIVENESS ASSESSMENT OF BLADDER CANCER: VALIDATION STUDY

Table 2: Bladder Cancers Detected Placebo Vitamin E Selenium Combination Years of Follow-up (median, IQR) 7.0 (6.1, 8.0) 7.0 (6.0, 8.0) 7.0 (6.0, 8.0) 7.0 (6.0, 8.0) No. of Bladder Cancers 53 56 60 55 Stage CIS 3 4 4 3 TA 32 26 30 36 T1 10 18 19 7 T1 6 6 6 7 Unknown 2 2 1 2 Grade Well differentiated 21 18 23 29 Moderately differentiated 9 7 10 5 Poorly differentiated 22 29 26 19 Unknown 1 2 1 2 N-stage N0 3 2 3 5 N1 3 2 1 0 NX 47 52 56 50 M-stage M0 2 0 3 3 M1 3 3 0 1 MX 48 53 57 51 Histology Urothelial cell 51 53 59 50 Squamous cell 1 0 1 0 Adenocarcinoma 0 0 0 1 Small cell 0 1 0 0 Other/Unknown 1 2 0 4 Deaths (cause) Bladder cancer 6 6 3 3 Other cause 5 3 4 5 Source of Funding: This work was supported in part by Public Health Service Cooperative Agreement grant CA37429 awarded by the National Cancer Institute, National Institutes of Health, Department of Health and Human Services, and in part by the National Center for Complementary and Alternative Medicine (National Institutes of Health). Study agents and packaging were provided by Perrigo Company (Allegan, Michigan), Sabinsa Corporation (Piscataway, New Jersey), Tishcon Corporation (Westbury, New York), and DSM Nutritional Products Inc. (Parsipanny, New Jersey).