Kalari, Krishna R.

Abstract The role of fusion gene transcripts such as BRC-ABL1 has been long appreciated in hematopoietic malignancies. Recent evidence from next generation sequencing projects has suggested that gene fusion events and the resultant chimaeric transcripts may be expressed in solid tumors. We have developed a novel bioinformatics analytical pipeline to detect fusion gene transcripts from paired-end mRNA-seq data. The bioinformatics tool used for fusion transcript discovery employs multiple steps of false positive filtering and nominates the fusion transcript candidates with high confidence (approaching 100%). The screening and validation of the fusion candidates were quickly carried out using the recommended primer design regions as one of the outputs of the SnowShoes-FD pipeline. This pipeline was used to analyze the transcriptome of 22 breast cancer cell lines and 9 non-transformed breast cell populations. Fifty-four fusion candidates were nominated, all of which were validated using reverse transcription PCR and Sanger sequencing. Five fusion products were predicted to have a second fusion junction point between two fusion partners. These 54 fusion transcripts consist of 103 partner genes that are involved in cell cycle and/or nuclear receptor signaling. No fusion transcripts were identified from the non-transformed breast cell lines. We subsequently analyzed a panel of primary breast tumors, 8 each HER2+, triple negative, and ER+. Fifteen novel fusion transcript candidates have been nominated. Validation and functional analysis of these candidates is in progress. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr LB-276. doi:10.1158/1538-7445.AM2011-LB-276

Abstract Fusion genes and fusion gene products are widely employed as biomarkers and therapeutic targets in hematopoietic cancers, but their applications have yet to be appreciated in solid tumors. Here, we report the use of SnowShoes-FTD, a powerful new analytic pipeline that can identify fusion transcripts and assess their redundancy and tumor subtype-specific distribution in primary tumors. In a study of primary breast tumors, SnowShoes-FTD was used to analyze paired-end mRNA-Seq data from a panel of estrogen receptor (ER)+, HER2+, and triple-negative primary breast tumors, identifying tumor-specific fusion transcripts by comparison with mRNA-Seq data from nontransformed human mammary epithelial cell cultures plus the Illumina Body Map data from normal tissues. We found that every primary breast tumor that was analyzed expressed one or more fusion transcripts. Of the 131 tumor-specific fusion transcripts identified, 86 were “private” (restricted to a single tumor) and 45 were “redundant” (distributed among multiple tumors). Among the redundant fusion transcripts, 7 were unique to ER+ tumors and 8 were unique to triple-negative tumors. In contrast, none of the redundant fusion transcripts were unique to HER2+ tumors. Both private and redundant fusion transcripts were widely expressed in primary breast tumors, with many mapping to genomic loci implicated in breast carcinogenesis and/or risk. Our finding that some fusion transcripts are tumor subtype-specific suggests that these entities may be critical determinants in the etiology of breast cancer subtypes, useful as biomarkers for tumor stratification, or exploitable as cancer-specific therapeutic targets. Cancer Res; 72(8); 1921–8. ©2012 AACR.

Abstract Background Taxane, a class of common anticancer agent, is widely used to treat many cancers. Among the taxanes, paclitaxel and docetaxel are the most commonly used agents. The mechanism of action for taxane drugs is through stabilizing microtubules by enhancing tubulin assembly and against depolymerization, thereby disrupting the dynamics of the microtubule. Large inter-individual variation has been observed in response to taxane treatment. Therefore, in the present study, we conducted a genome-wide association (GWA) study to identify genetic polymorphisms that might contribute to variation in response to taxanes drugs using the “Human Variation Panel” lymphoblastoid cell line (LCL) model system that consists of 287 ethnically defined cell lines. Method Genome-wide SNP and basal gene expression data were obtained for 287 LCLs using Illumina HumanHap 550K, 510S BeadChips, Affymetix SNP Array 6.0 and Affymetrix U133 plus 2.0 GeneChip. Cytotoxicity assay was also performed in the same cell lines for both paclitaxel and docetaxel. Candidate genes were selected based on an integrated analysis of genome-wide SNPs, expression array data and IC50 values (a cytotoxicity phenotype indicating the drug concentration required for 50% inhibition of maximal cell growth) for paclitaxel and docetaxel. SiRNA screening was performed to functionally validate those top candidates, followed by MTS assay in a breast cancer cell line, MDA-MB231. Results Of the 54,000 probe sets considered, 390 probe sets, representing 272 unique annotated genes, were found to be associated with docetaxel cytotoxicity (IC50 value) with p value <10−3, while 176 probe sets, representing 124 unique genes, were associated with paclitaxel IC50. Of these probe sets, 50 probe sets were associated with IC50 for both drugs. Analysis of 1.3 million SNPs identified 11 loci, defined as a region containing at least 1 SNP of p value <10−5 and 1 SNP of p value <10−4 within 50kb, associated with docetaxel IC50, while 7 loci were associated with paclitaxel IC50. One locus was found to be associated with both drugs. Previous studies suggested that gene expression is regulated in a cell-type specific manner. Therefore, based on our analysis and biological implication, we selected 16 top candidate genes that were expressed in our LCLs to perform functional validation studies using siRNA, followed by MTS assay in a breast cancer cell line, MDA-MB231. Functional studies showed that knockdown of SLC44A1 and HSPA5 significantly desensitized the cancer cell to both taxanes treatment. Conclusion GWAS using LCL model system could provide potential pharmacogenomic candidates for future clinical translational studies. Functional validation in tumor cell lines may help determine the genomic mechanism contributing to the inter-individual variation of taxane response. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2599.

Abstract Background Radiation therapy is used to treat half of the all cancer patients. Response to radiation therapy varies widely, in terms of both response and toxicity related events. Previous studies suggested almost 80% of the variation in normal tissue response to radiation treatment was likely to be due to genetic factors. Therefore, we performed a genome-wide association study (GWAS) to identify biomarkers that might help predict radiation response using a the “Human Variation Panel” lymphoblastoid cell lines (LCLs) that consists 287 ethnically defined cell lines. Method Basal gene expression level, 1.3 million genome-wide SNP data were obtained for 287 human LCLs using Affymetrix U133 plus 2.0 GeneChip, Illumina HumanHap 550K, 510S BeadChips and Affymetix SNP Array 6.0. Radiation cytotoxicity assay was also performed to obtain the area under radiation dose response curve (AUC), a summary measure for cytotoxicity for the same cell lines. Functional validation of candidate genes, selected based on the integrated analysis of SNP, expression and AUC data, was performed in multiple cancer cell lines using specific siRNAs followed by MTS and colony formation assays. Results 27 loci, containing at least 2 SNPs of p values <10−4 within 50kb were associated with radiation AUC. 270 expression probe sets were associated with radiation AUC (p< 10−3). The integrated analysis of 27 loci, 54,000 basal expression probe sets and radiation AUC identified 50 unique SNPs associated with AUC were also associated with gene expression of 39 unique annotated genes. In addition, these 39 genes were associated with radiation AUC with p values <10−3. Based on the GWAS and integrated analysis of SNP, expression array and radiation AUC data, 22 genes were selected for functional validation studies using siRNA knock down followed by MTS and colony formation assays in multiple tumor cell lines. C13orf34 (Bora), MAD2L1, PLK4, TPD52 significantly altered the radiation sensitivity in at least 2 cancer cell lines for both MTS and colony formation assays (p<0.05). Knock down of DEPDC1B, a gene containing 2 SNPs at the 3′-end that was significantly related with Bora gene expression level (p<10−4) significantly desensitized cancer cells to radiation treatment. Both microarray data and QRT-PCR analysis indicated that expression levels for those two genes were significantly correlated. Conclusion Our results using the lymphoblastoid cell lines might help identify novel biomarkers that contribute to variation in response to radiation therapy and help understand the mechanisms underlying the association. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3602.

Abstract Two cytidine analogues, gemcitabine (dFdC) and 1-β-d-arabinofuranosylcytosine (AraC), show significant therapeutic effect in a variety of cancers. However, response to these drugs varies widely. Evidence from tumor biopsy samples shows that expression levels for genes involved in the cytidine transport, metabolism, and bioactivation pathway contribute to this variation in response. In the present study, we set out to test the hypothesis that variation in gene expression both within and outside of this “pathway” might influence sensitivity to gemcitabine and AraC. Specifically, Affymetrix U133 Plus 2.0 GeneChip and cytotoxicity assays were performed to obtain basal mRNA expression and IC50 values for both drugs in 197 ethnically defined Human Variation Panel lymphoblastoid cell lines. Genes with a high degree of association with IC50 values were involved mainly in cell death, cancer, cell cycle, and nucleic acid metabolism pathways. We validated selected significant genes by performing real-time quantitative reverse transcription-PCR and selected two representative candidates, NT5C3 (within the pathway) and FKBP5 (outside of the pathway), for functional validation. Those studies showed that down-regulation of NT5C3 and FKBP5 altered tumor cell sensitivity to both drugs. Our results suggest that cell-based model system studies, when combined with complementary functional characterization, may help to identify biomarkers for response to chemotherapy with these cytidine analogues. [Cancer Res 2008;68(17):7050–8]

Abstract Purpose: The proteasome is a multisubunit cellular organelle that functions as a nonlysosomal threonine protease. Proteasomes play a critical role in the degradation of proteins, regulating a variety of cellular processes, and they are also the target for antineoplastic proteasome inhibitors. Genetic variation in proteasome subunits could influence both proteasome function and response to drug therapy. Experimental Design: We resequenced genes encoding the three active proteasome β subunits using 240 DNA samples from four ethnic groups and the β5 subunit gene in 79 DNA samples from multiple myeloma patients who had been treated with the proteasome inhibitor bortezomib. Resequencing was followed by functional studies of polymorphisms identified in the coding region and 3′-flanking region (3′-FR) of PSMB5, the gene encoding the target for clinically useful proteasome inhibitors. Results: Resequencing of 240 DNA samples identified a series of novel ethnic-specific polymorphisms that are not represented in public databases. The PSMB5 3′-FR 1042 G allele significantly increased transcription during reporter gene studies, observations confirmed by genotype-phenotype correlations between single nucleotide polymorphisms (SNP) in PSMB5 and mRNA expression in the 240 lymphoblastoid cell lines from which the resequenced DNA was obtained. Studies with patient DNA samples identified additional novel PSMB5 polymorphisms, including a SNP and an insertion in the 3′-FR. Reporter-gene studies indicated that these two novel polymorphisms might decrease transcription. Conclusions: These results show that nonsynonymous coding SNPs in the PSMB5 gene did not show significant effects on proteasome activity, but SNPs did influence transcription. Future studies might focus on regulatory region polymorphisms.