Ioana Cutcutache

Primer-BLAST: A tool to design target-specific primers for polymerase chain reaction

BackgroundChoosing appropriate primers is probably the single most important factor affecting the polymerase chain reaction (PCR). Specific amplification of the intended target requires that primers do not have matches to other targets in certain orientations and within certain distances that allow undesired amplification. The process of designing specific primers typically involves two stages. First, the primers flanking regions of interest are generated either manually or using software tools; then they are searched against an appropriate nucleotide sequence database using tools such as BLAST to examine the potential targets. However, the latter is not an easy process as one needs to examine many details between primers and targets, such as the number and the positions of matched bases, the primer orientations and distance between forward and reverse primers. The complexity of such analysis usually makes this a time-consuming and very difficult task for users, especially when the primers have a large number of hits. Furthermore, although the BLAST program has been widely used for primer target detection, it is in fact not an ideal tool for this purpose as BLAST is a local alignment algorithm and does not necessarily return complete match information over the entire primer range.ResultsWe present a new software tool called Primer-BLAST to alleviate the difficulty in designing target-specific primers. This tool combines BLAST with a global alignment algorithm to ensure a full primer-target alignment and is sensitive enough to detect targets that have a significant number of mismatches to primers. Primer-BLAST allows users to design new target-specific primers in one step as well as to check the specificity of pre-existing primers. Primer-BLAST also supports placing primers based on exon/intron locations and excluding single nucleotide polymorphism (SNP) sites in primers.ConclusionsWe describe a robust and fully implemented general purpose primer design tool that designs target-specific PCR primers. Primer-BLAST offers flexible options to adjust the specificity threshold and other primer properties. This tool is publicly available at http://www.ncbi.nlm.nih.gov/tools/primer-blast.

Exome sequencing of liver fluke-associated cholangiocarcinoma

Opisthorchis viverrini–related cholangiocarcinoma (CCA), a fatal bile duct cancer, is a major public health concern in areas endemic for this parasite. We report here whole-exome sequencing of eight O. viverrini–related tumors and matched normal tissue. We identified and validated 206 somatic mutations in 187 genes using Sanger sequencing and selected 15 genes for mutation prevalence screening in an additional 46 individuals with CCA (cases). In addition to the known cancer-related genes TP53 (mutated in 44.4% of cases), KRAS (16.7%) and SMAD4 (16.7%), we identified somatic mutations in 10 newly implicated genes in 14.8–3.7% of cases. These included inactivating mutations in MLL3 (in 14.8% of cases), ROBO2 (9.3%), RNF43 (9.3%) and PEG3 (5.6%), and activating mutations in the GNAS oncogene (9.3%). These genes have functions that can be broadly grouped into three biological classes: (i) deactivation of histone modifiers, (ii) activation of G protein signaling and (iii) loss of genome stability. This study provides insight into the mutational landscape contributing to O. viverrini–related CCA.

Exome sequencing identifies distinct mutational patterns in liver fluke–related and non-infection-related bile duct cancers

The impact of different carcinogenic exposures on the specific patterns of somatic mutation in human tumors remains unclear. To address this issue, we profiled 209 cholangiocarcinomas (CCAs) from Asia and Europe, including 108 cases caused by infection with the liver fluke Opisthorchis viverrini and 101 cases caused by non–O. viverrini–related etiologies. Whole-exome sequencing (n = 15) and prevalence screening (n = 194) identified recurrent somatic mutations in BAP1 and ARID1A, neither of which, to our knowledge, has previously been reported to be mutated in CCA. Comparisons between intrahepatic O. viverrini–related and non–O. viverrini–related CCAs demonstrated statistically significant differences in mutation patterns: BAP1, IDH1 and IDH2 were more frequently mutated in non–O. viverrini CCAs, whereas TP53 mutations showed the reciprocal pattern. Functional studies demonstrated tumor suppressive functions for BAP1 and ARID1A, establishing the role of chromatin modulators in CCA pathogenesis. These findings indicate that different causative etiologies may induce distinct somatic alterations, even within the same tumor type.

Genome-Wide Mutational Signatures of Aristolochic Acid and Its Application as a Screening Tool

Genome-wide mutational signatures of the group 1 carcinogen aristolochic acid are observed in urothelial cancers and liver cancers from Asia. Carcinogen AAlert Aristolochic acid (AA) is a natural compound derived from plants in the Aristolochia genus. For centuries, Aristolochia has been used throughout Asia to treat a variety of ailments as a component of traditional Chinese medicine. In recent years, however, a more sinister side of this herb has come to light when it was linked to kidney damage and cancers of the urinary tract. Now, two studies by Poon et al. and Hoang et al. present a “molecular signature” of AA-induced DNA damage, which helps to explain the mutagenic effects of AA and may also be useful as a way to detect unsuspected AA exposure as a cause of cancer. The molecular signature seen in AA-associated tumors is characterized by a predominance of A:T-to-T:A transversions, a relatively unusual type of mutation that is infrequently seen in other types of cancer, including those caused by other carcinogens. These mutations concentrate at splice sites, causing the inappropriate inclusion or exclusion of entire exons in the resulting mRNA. The overall mutation rate is another notable feature of AA-associated cancers because it is several times higher than the rate of mutations caused by other carcinogens such as tobacco and ultraviolet light. In both studies, the authors also used the molecular signature to discover that AA was a likely cause of tumors previously attributed to other carcinogens. In one case, a urinary tract cancer that had been attributed to smoking and, in the other case, a liver cancer previously attributed to a chronic hepatitis infection were both identified as having the telltale signature of AA mutagenesis. The identification of a specific molecular signature for AA has both clinical and public health implications. For individual patients, the molecular signature could help physicians identify which tumors were caused by AA. Although this information cannot yet be used to optimize the treatment of individual patients, those who are diagnosed with AA-associated cancers could be monitored more closely for the appearance of additional tumors. Meanwhile, a better understanding of the mutagenic effects of AA should also help to strengthen public health efforts to decrease exposure to this carcinogenic herb. Aristolochic acid (AA), a natural product of Aristolochia plants found in herbal remedies and health supplements, is a group 1 carcinogen that can cause nephrotoxicity and upper urinary tract urothelial cell carcinoma (UTUC). Whole-genome and exome analysis of nine AA-associated UTUCs revealed a strikingly high somatic mutation rate (150 mutations/Mb), exceeding smoking-associated lung cancer (8 mutations/Mb) and ultraviolet radiation–associated melanoma (111 mutations/Mb). The AA-UTUC mutational signature was characterized by A:T to T:A transversions at the sequence motif A[C|T]AGG, located primarily on nontranscribed strands. AA-induced mutations were also significantly enriched at splice sites, suggesting a role for splice-site mutations in UTUC pathogenesis. RNA sequencing of AA-UTUC confirmed a general up-regulation of nonsense-mediated decay machinery components and aberrant splicing events associated with splice-site mutations. We observed a high frequency of somatic mutations in chromatin modifiers, particularly KDM6A, in AA-UTUC, demonstrated the sufficiency of AA to induce renal dysplasia in mice, and reproduced the AA mutational signature in experimentally treated human renal tubular cells. Finally, exploring other malignancies that were not known to be associated with AA, we screened 93 hepatocellular carcinoma genomes/exomes and identified AA-like mutational signatures in 11. Our study highlights an unusual genome-wide AA mutational signature and the potential use of mutation signatures as “molecular fingerprints” for interrogating high-throughput cancer genome data to infer previous carcinogen exposures.

Janus Kinase 3–Activating Mutations Identified in Natural Killer/T-cell Lymphoma

UNLABELLED The molecular pathogenesis of natural killer/T-cell lymphoma (NKTCL) is not well understood. We conducted whole-exome sequencing and identified Janus kinase 3 (JAK3) somatic-activating mutations (A572V and A573V) in 2 of 4 patients with NKTCLs. Further validation of the prevalence of JAK3 mutations was determined by Sanger sequencing and high-resolution melt (HRM) analysis in an additional 61 cases. In total, 23 of 65 (35.4%) cases harbored JAK3 mutations. Functional characterization of the JAK3 mutations support its involvement in cytokine-independent JAK/STAT constitutive activation leading to increased cell growth. Moreover, treatment of both JAK3-mutant and wild-type NKTCL cell lines with a novel pan-JAK inhibitor, CP-690550, resulted in dose-dependent reduction of phosphorylated STAT5, reduced cell viability, and increased apoptosis. Hence, targeting the deregulated JAK/STAT pathway could be a promising therapy for patients with NKTCLs. SIGNIFICANCE Gene mutations causing NKTCL have not been fully identified. Through exome sequencing, we identified activating mutations of JAK3 that may play a significant role in the pathogenesis of NKTCLs. Our findings have important implications for the management of patients with NKTCLs.

Exome sequencing identifies highly recurrent MED12 somatic mutations in breast fibroadenoma

Fibroadenomas are the most common breast tumors in women under 30 (refs. 1,2). Exome sequencing of eight fibroadenomas with matching whole-blood samples revealed recurrent somatic mutations solely in MED12, which encodes a Mediator complex subunit. Targeted sequencing of an additional 90 fibroadenomas confirmed highly frequent MED12 exon 2 mutations (58/98, 59%) that are probably somatic, with 71% of mutations occurring in codon 44. Using laser capture microdissection, we show that MED12 fibroadenoma mutations are present in stromal but not epithelial mammary cells. Expression profiling of MED12-mutated and wild-type fibroadenomas revealed that MED12 mutations are associated with dysregulated estrogen signaling and extracellular matrix organization. The fibroadenoma MED12 mutation spectrum is nearly identical to that of previously reported MED12 lesions in uterine leiomyoma but not those of other tumors. Benign tumors of the breast and uterus, both of which are key target tissues of estrogen, may thus share a common genetic basis underpinned by highly frequent and specific MED12 mutations.

Whole-genome reconstruction and mutational signatures in gastric cancer

BackgroundGastric cancer is the second highest cause of global cancer mortality. To explore the complete repertoire of somatic alterations in gastric cancer, we combined massively parallel short read and DNA paired-end tag sequencing to present the first whole-genome analysis of two gastric adenocarcinomas, one with chromosomal instability and the other with microsatellite instability.ResultsIntegrative analysis and de novo assemblies revealed the architecture of a wild-type KRAS amplification, a common driver event in gastric cancer. We discovered three distinct mutational signatures in gastric cancer - against a genome-wide backdrop of oxidative and microsatellite instability-related mutational signatures, we identified the first exome-specific mutational signature. Further characterization of the impact of these signatures by combining sequencing data from 40 complete gastric cancer exomes and targeted screening of an additional 94 independent gastric tumors uncovered ACVR2A, RPL22 and LMAN1 as recurrently mutated genes in microsatellite instability-positive gastric cancer and PAPPA as a recurrently mutated gene in TP53 wild-type gastric cancer.ConclusionsThese results highlight how whole-genome cancer sequencing can uncover information relevant to tissue-specific carcinogenesis that would otherwise be missed from exome-sequencing data.

Genetic and Structural Variation in the Gastric Cancer Kinome Revealed through Targeted Deep Sequencing

Genetic alterations in kinases have been linked to multiple human pathologies. To explore the landscape of kinase genetic variation in gastric cancer (GC), we used targeted, paired-end deep sequencing to analyze 532 protein and phosphoinositide kinases in 14 GC cell lines. We identified 10,604 single-nucleotide variants (SNV) in kinase exons including greater than 300 novel nonsynonymous SNVs. Family-wise analysis of the nonsynonymous SNVs revealed a significant enrichment in mitogen-activated protein kinase (MAPK)-related genes (P < 0.01), suggesting a preferential involvement of this kinase family in GC. A potential antioncogenic role for MAP2K4, a gene exhibiting recurrent alterations in 2 lines, was functionally supported by siRNA knockdown and overexpression studies in wild-type and MAP2K4 variant lines. The deep sequencing data also revealed novel, large-scale structural rearrangement events involving kinases including gene fusions involving CDK12 and the ERBB2 receptor tyrosine kinase in MKN7 cells. Integrating SNVs and copy number alterations, we identified Hs746T as a cell line exhibiting both splice-site mutations and genomic amplification of MET, resulting in MET protein overexpression. When applied to primary GCs, we identified somatic mutations in 8 kinases, 4 of which were recurrently altered in both primary tumors and cell lines (MAP3K6, STK31, FER, and CDKL5). These results demonstrate that how targeted deep sequencing approaches can deliver unprecedented multilevel characterization of a medically and pharmacologically relevant gene family. The catalog of kinome genetic variants assembled here may broaden our knowledge on kinases and provide useful information on genetic alterations in GC.

Genomic landscapes of breast fibroepithelial tumors

Breast fibroepithelial tumors comprise a heterogeneous spectrum of pathological entities, from benign fibroadenomas to malignant phyllodes tumors. Although MED12 mutations have been frequently found in fibroadenomas and phyllodes tumors, the landscapes of genetic alterations across the fibroepithelial tumor spectrum remain unclear. Here, by performing exome sequencing of 22 phyllodes tumors followed by targeted sequencing of 100 breast fibroepithelial tumors, we observed three distinct somatic mutation patterns. First, we frequently observed MED12 and RARA mutations in both fibroadenomas and phyllodes tumors, emphasizing the importance of these mutations in fibroepithelial tumorigenesis. Second, phyllodes tumors exhibited mutations in FLNA, SETD2 and KMT2D, suggesting a role in driving phyllodes tumor development. Third, borderline and malignant phyllodes tumors harbored additional mutations in cancer-associated genes. RARA mutations exhibited clustering in the portion of the gene encoding the ligand-binding domain, functionally suppressed RARA-mediated transcriptional activation and enhanced RARA interactions with transcriptional co-repressors. This study provides insights into the molecular pathogenesis of breast fibroepithelial tumors, with potential clinical implications.

Pipa: pipelined profiling and analysis on multi-core systems

Dynamic instrumentation systems are gaining popularity as means of constructing customized program profiling and analysis tools. However, dynamic instrumentation based analysis tools still suffer from performance problems. The overhead of such systems can be broken down into two components - the overhead of dynamic instrumentation and the time consumed in the user-defined analysis tools. While important progress has been made in reducing the performance penalty of the dynamic instrumentation itself, less attention has been paid to the user-defined component. In this paper, we present PiPA - Pipelined Profiling and Analysis, which is a novel technique for parallelizing dynamic program profiling and analysis by taking advantage of multi-core systems. We implemented a prototype of PiPA using the dynamic instrumentation system DynamoRIO. Our experiments show that PiPA is able to speed up the overall profiling and analysis tasks significantly. Compared to the more than 100x slowdown of Cachegrind and the 32x slowdown of Pin dcache, we achieved a mere 10.5x slowdown on an 8-core system.