Passenger Genes Research Articles

Detection of novel fusion-transcripts by RNA-Seq in T-cell lymphoblastic lymphoma

Fusions transcripts have been proven to be strong drivers for neoplasia-associated mutations, although their incidence in T-cell lymphoblastic lymphoma needs to be determined yet. Using RNA-Seq we have selected 55 fusion transcripts identified by at least two of three detection methods in the same tumour. We confirmed the existence of 24 predicted novel fusions that had not been described in cancer or normal tissues yet, indicating the accuracy of the prediction. Of note, one of them involves the proto oncogene TAL1. Other confirmed fusions could explain the overexpression of driver genes such as COMMD3-BMI1, LMO1 or JAK3. Five fusions found exclusively in tumour samples could be considered pathogenic (NFYG-TAL1, RIC3-TCRBC2, SLC35A3-HIAT1, PICALM MLLT10 and MLLT10-PICALM). However, other fusions detected simultaneously in normal and tumour samples (JAK3-INSL3, KANSL1-ARL17A/B and TFG-ADGRG7) could be germ-line fusions genes involved in tumour-maintaining tasks. Notably, some fusions were confirmed in more tumour samples than predicted, indicating that the detection methods underestimated the real number of existing fusions. Our results highlight the potential of RNA-Seq to identify new cryptic fusions, which could be drivers or tumour-maintaining passenger genes. Such novel findings shed light on the searching for new T-LBL biomarkers in these haematological disorders.

Transposons and pathogenicity in Xanthomonas: acquisition of murein lytic transglycosylases by TnXax1 enhances Xanthomonas citri subsp. citri 306 virulence and fitness.

Xanthomonas citri subsp. citri 306 (XccA) is the causal agent of type A citrus canker (CC), one of the most significant citriculture diseases. Murein lytic transglycosylases (LT), potentially involved in XccA pathogenicity, are enzymes responsible for peptidoglycan structure assembly, remodeling and degradation. They directly impact cell wall expansion during bacterial growth, septum division allowing cell separation, cell wall remodeling allowing flagellar assembly, bacterial conjugation, muropeptide recycling, and secretion system assembly, in particular the Type 3 Secretion System involved in bacterial virulence, which play a fundamental role in XccA pathogenicity. Information about the XccA LT arsenal is patchy: little is known about family diversity, their exact role or their connection to virulence in this bacterium. Among the LTs with possible involvement in virulence, two paralogue open reading frames (ORFs) (one on the chromosome and one in plasmid pXAC64) are passenger genes of the Tn3 family transposon TnXax1, known to play a significant role in the evolution and emergence of pathogenicity in Xanthomonadales and to carry a variety of virulence determinants. This study addresses LT diversity in the XccA genome and examines the role of plasmid and chromosomal TnXax1 LT passenger genes using site-directed deletion mutagenesis and functional characterization. We identified 13 XccA LTs: 12 belong to families 1A, 1B, 1C, 1D (two copies), 1F, 1G, 3A, 3B (two copies), 5A, 6A and one which is non-categorized. The non-categorized LT is exclusive to the Xanthomonas genus and related to the 3B family but contains an additional domain linked to carbohydrate metabolism. The categorized LTs are probably involved in cell wall remodeling to allow insertion of type 3, 4 and 6 secretion systems, flagellum assembly, division and recycling of cell wall and degradation and control of peptidoglycan production. The TnXax1 passenger LT genes (3B family) are not essential to XccA or for CC development but are implicated in peptidoglycan metabolism, directly impacting bacterial fitness and CC symptom enhancement in susceptible hosts (e.g., Citrus sinensis). This underlines the role of TnXax1 as a virulence and pathogenicity-propagating agent in XccA and suggests that LT acquisition by horizontal gene transfer mediated by TnXax1 may improve bacterial fitness, conferring adaptive advantages to the plant-pathogen interaction process.

Insight Into the Diversity and Possible Role of Plasmids in the Adaptation of Psychrotolerant and Metalotolerant Arthrobacter spp. to Extreme Antarctic Environments.

Arthrobacter spp. are coryneform Gram-positive aerobic bacteria, belonging to the class Actinobacteria. Representatives of this genus have mainly been isolated from soil, mud, sludge or sewage, and are usually mesophiles. In recent years, the presence of Arthrobacter spp. was also confirmed in various extreme, including permanently cold, environments. In this study, 36 psychrotolerant and metalotolerant Arthrobacter strains isolated from petroleum-contaminated soil from the King George Island (Antarctica), were screened for the presence of plasmids. The identified replicons were thoroughly characterized in order to assess their diversity and role in the adaptation of Arthrobacter spp. to harsh Antarctic conditions. The screening process identified 11 different plasmids, ranging in size from 8.4 to 90.6 kb. A thorough genomic analysis of these replicons detected the presence of numerous genes encoding proteins that potentially perform roles in adaptive processes such as (i) protection against ultraviolet (UV) radiation, (ii) resistance to heavy metals, (iii) transport and metabolism of organic compounds, (iv) sulfur metabolism, and (v) protection against exogenous DNA. Moreover, 10 of the plasmids carry genetic modules enabling conjugal transfer, which may facilitate their spread among bacteria in Antarctic soil. In addition, transposable elements were identified within the analyzed plasmids. Some of these elements carry passenger genes, which suggests that these replicons may be actively changing, and novel genetic modules of adaptive value could be acquired by transposition events. A comparative genomic analysis of plasmids identified in this study and other available Arthrobacter plasmids was performed. This showed only limited similarities between plasmids of Antarctic Arthrobacter strains and replicons of other, mostly mesophilic, isolates. This indicates that the plasmids identified in this study are novel and unique replicons. In addition, a thorough meta-analysis of 247 plasmids of psychrotolerant bacteria was performed, revealing the important role of these replicons in the adaptation of their hosts to extreme environments.

MaxMIF: A New Method for Identifying Cancer Driver Genes through Effective Data Integration.

Identification of a few cancer driver mutation genes from a much larger number of passenger mutation genes in cancer samples remains a highly challenging task. Here, a novel method for distinguishing the driver genes from the passenger genes by effective integration of somatic mutation data and molecular interaction data using a maximal mutational impact function (MaxMIF) is presented. When evaluated on six somatic mutation datasets of Pan‐Cancer and 19 datasets of different cancer types from TCGA, MaxMIF almost always significantly outperforms all the existing state‐of‐the‐art methods in terms of predictive accuracy, sensitivity, and specificity. It recovers about 30% more known cancer genes in 500 top‐ranked candidate genes than the best among the other tools evaluated. MaxMIF is also highly robust to data perturbation. Intriguingly, MaxMIF is able to identify potential cancer driver genes, with strong experimental data support. Therefore, MaxMIF can be very useful for identifying or prioritizing cancer driver genes in the increasing number of available cancer genomic data.

Abstract 4078: Sleeping Beauty transposon mutagenesis identifies genes involved in colorectal cancer progression

Abstract Cancer genome sequencing studies have identified numerous genes mutated in colorectal cancers (CRC). Majority of genes, however, were infrequently mutated between tumors. Sorting out infrequent driver genes from passenger genes is still challenging, but important since these infrequent driver genes sometimes seed for metastasis or confer drug resistance. In the previous study, we performed Sleeping Beauty (SB) transposon mutagenesis screens in mice and identified 1,333 candidate driver genes in CRC. These gene included known CRC genes such as Apc, Smad4 and Trp53 as well as novel CRC genes. Using publicly available datasets for genes mutated in human CRC, we compared the genes commonly mutated between human and mice, thus we could enrich a set of candidate driver genes. Among them, we especially focused on candidate tumor suppressor genes since tumor suppressor genes play a fundamental role in CRC development. To validate these candidate tumor suppressor genes, we set up the experimental system using the CRISPR-Cas9 system to knockout the genes in the intestinal organoid culture system. We obtained the mouse intestinal tumor organoid carrying Apc mutations and a KrasG12D activating point mutation (AK organoid), and also obtained organoids derived from human CRC. First, we introduced a Cas9 to obtain Cas9 expressing AK organoids and then introduced a set of 10 gRNAs targeting candidate tumor suppressor genes by lentivirus. These organoids were subsequently transplanted to NSG mice subcutaneously. AK organoid with gRNAs induced tumors, in contrast, AK organoids without gRNA did not induced tumors within 1 month after transplantation showing gene knockout by CRISPR-Cas9 induced tumor development. Next we purified genome from tumors and analyzed the ratio for each gRNA. The gRNA with an expanded ratio in tumors compared to organoids before transplantations are likely to be a novel tumor suppressor gene. So far we validated 30 candidate tumor suppressor genes by this approach and pick up Arid2, Acvr2a and Acvr1b. These 3 genes were mutated in ~5% of human CRC. Since single gene knockout for each of 3 genes in AK organoids also caused tumor development, we were able to confirm that these 3 genes were truly tumor suppressor genes in CRC, We are now validating using human CRC organoid. In summary, we have established the experimental system to validate candidate tumor suppressor genes in CRC using the CRISPR-Cas9 system and the organoid culture system. So far we have succeeded in identifying novel tumor suppresser genes such as Arid2, Acvr2a and Acvr1b. We will validate all candidate tumor suppressor genes and reveal the whole driver genes involved in CRC. Our results will give an important insight in finding new drug targets to cure cancers. Citation Format: Haruna Takeda. Sleeping Beauty transposon mutagenesis identifies genes involved in colorectal cancer progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4078.

ProcessDriver: A computational pipeline to identify copy number drivers and associated disrupted biological processes in cancer

Copy number amplifications and deletions that are recurrent in cancer samples harbor genes that confer a fitness advantage to cancer tumor proliferation and survival. One important challenge in computational biology is to separate the causal (i.e., driver) genes from passenger genes in large, aberrated regions. Many previous studies focus on the genes within the aberration (i.e., cis genes), but do not utilize the genes that are outside of the aberrated region and dysregulated as a result of the aberration (i.e., trans genes). We propose a computational pipeline, called ProcessDriver, that prioritizes candidate drivers by relating cis genes to dysregulated trans genes and biological processes. ProcessDriver is based on the assumption that a driver cis gene should be closely associated with the dysregulated trans genes and biological processes, as opposed to previous studies that assume a driver cis gene should be the most correlated gene to the copy number of an aberrated region. We applied our method on breast, bladder and ovarian cancer data from the Cancer Genome Atlas database. Our results included previously known driver genes and cancer genes, as well as potentially novel driver genes. Additionally, many genes in the final set of drivers were linked to new tumor events after initial treatment using survival analysis. Our results highlight the importance of selecting driver genes based on their widespread downstream effects in trans.

Identification of novel mutations in endometrial cancer patients by whole-exome sequencing.

The aim of the present study was to identify genomic alterations in Taiwanese endometrial cancer patients. This information is vitally important in Taiwan, where endometrial cancer is the second most common gynecological cancer. We performed whole-exome sequencing on DNA from 14 tumor tissue samples from Taiwanese endometrial cancer patients. We used the Genome Analysis Tool kit software package for data analysis, and the dbSNP, Catalogue of Somatic Mutations in Cancer (COSMIC) and The Cancer Genome Atlas (TCGA) databases for comparisons. Variants were validated via Sanger sequencing. We identified 143 non-synonymous mutations in 756 canonical cancer-related genes and 1,271 non-synonymous mutations in non-canonical cancer-related genes in 14 endometrial samples. PTEN, KRAS and PIK3R1 were the most frequently mutated canonical cancer-related genes. Our results revealed nine potential driver genes (MAPT, IL24, MCM6, TSC1, BIRC2, CIITA, DST, CASP8 and NOTCH2) and 21 potential passenger genes (ARMCX4, IGSF10, VPS13C, DCT, DNAH14, TLN1, ZNF605, ZSCAN29, MOCOS, CMYA5, PCDH17, UGT1A8, CYFIP2, MACF1, NUDT5, JAKMIP1, PCDHGB4, FAM178A, SNX6, IMP4 and PCMTD1). The detected molecular aberrations led to putative activation of the mTOR, Wnt, MAPK, VEGF and ErbB pathways, as well as aberrant DNA repair, cell cycle control and apoptosis pathways. We characterized the mutational landscape and genetic alterations in multiple cellular pathways of endometrial cancer in the Taiwanese population.

The use of gene interaction networks to improve the identification of cancer driver genes.

Bioinformaticians have implemented different strategies to distinguish cancer driver genes from passenger genes. One of the more recent advances uses a pathway-oriented approach. Methods that employ this strategy are highly dependent on the quality and size of the pathway interaction network employed, and require a powerful statistical environment for analyses. A number of genomic libraries are available in R. DriverNet and DawnRank employ pathway-based methods that use gene interaction graphs in matrix form. We investigated the benefit of combining data from 3 different sources on the prediction outcome of cancer driver genes by DriverNet and DawnRank. An enriched dataset was derived comprising 13,862 genes with 372,250 interactions, which increased its accuracy by 17% and 28%, respectively, compared to their original networks. The study identified 33 new candidate driver genes. Our study highlights the potential of combining networks and weighting edges to provide greater accuracy in the identification of cancer driver genes.

DriverFinder: A Gene Length-Based Network Method to Identify Cancer Driver Genes

Integration of multi-omics data of cancer can help people to explore cancers comprehensively. However, with a large volume of different omics and functional data being generated, there is a major challenge to distinguish functional driver genes from a sea of inconsequential passenger genes that accrue stochastically but do not contribute to cancer development. In this paper, we present a gene length-based network method, named DriverFinder, to identify driver genes by integrating somatic mutations, copy number variations, gene-gene interaction network, tumor expression, and normal expression data. To illustrate the performance of DriverFinder, it is applied to four cancer types from The Cancer Genome Atlas including breast cancer, head and neck squamous cell carcinoma, thyroid carcinoma, and kidney renal clear cell carcinoma. Compared with some conventional methods, the results demonstrate that the proposed method is effective. Moreover, it can decrease the influence of gene length in identifying driver genes and identify some rare mutated driver genes.

Abstract 3837: Passenger deletion of ENO1 as a collateral lethality target in cancer

Abstract Large scale genomic characterization efforts such as TCGA have painted an unprecedentedly detailed picture of the genetic alterations that underlie tumorigenesis. Yet, the majority of genetic alterations are passenger rather than driver events and are considered unactionable. We have previously proposed that passenger or collateral deletions could serve as pharmacologically targetable vulnerabilities Collateral Lethality, in case passenger genes are homozygously deleted and member of a paralogous gene family carrying out an essential housekeeping function. We have presented proof-of-principal, whereby passenger deletion of the glycolytic gene Enolase 1 (ENO1) as part of the 1p36-tumor suppressor locus, renders glioma cells harboring such deletions highly sensitive to ablation of its redundant paralogue, ENO2. While our original analysis identified ENO1-homozygous deletions in Glioblastoma (GBM), recent bioinformatics analyzes, backed by immunohistochemistry, show that ENO1-homozygous deletions also occur in Hepatocellular Carcinoma and Cholangiocarcinoma. In GBM, multisector analysis of primary and recurrent tumors, indicate that ENO1 deletion is an early event which is homogenously distributed through the primary tumor and persist during recurrence. To pharmacologically exploit ENO1-deletion, we have pursued two approaches. First, we have synthesized cell-permeable prodrug derivatives of the natural Enolase inhibitor SF2312. The lead compound, POMHEX, shows potent killing of ENO1-deleted glioma cells in the low nM range while ENO1-restored isogenic or normal cells can tolerate μM doses. POMHEX has a short half-life yet can eradicate intracranial xenografted ENO1-deleted tumors, provided extensive breakdown of the blood-brain barrier. Our second approach to targeting ENO1-deletion consisted of chemical biology screening of drug libraries for the ability to kill ENO1-deleted but not isogenic rescued cells. We find that ENO1-deleted cells show a dramatic sensitization to inhibitors of the mitochondrial electron transport chain. These include tool compounds such as rotenone as well as compounds not previously associated with mitochondria, such as Mubritinib and an experimental anti-neoplastic agent previously described as a HIF1-inhibitor, now known to inhibit mitochondrial Complex I. The latter agent shows potent activity against ENO1-deleted intracranial xenografts. The likely cause for this sensitivity is the inability of ENO1-deleted cells to compensatory upregulate glycolysis in response mitochondrial inhibition, the typical response of ENO1-intact glioma cells and normal cells. Together, these data indicate that passenger deletion of ENO1 is an encouraging drug-target and provide support for collateral lethality as a viable therapeutic strategy, which, given the large number of passenger deletions in the cancer genome, may be broadly applicable. Citation Format: Yu-Hsi Lin, Nikunj Satani, Naima Hammoudi, Joe Marszalek, Yuting Sun, Marina Protopopova, Maria E. Di Francesco, Barbara Czako, Alan Wang, Ronald A. DePinho, Florian L. Muller. Passenger deletion of ENO1 as a collateral lethality target in cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3837.

Copy Number Alterations in Enzyme-Coding and Cancer-Causing Genes Reprogram Tumor Metabolism.

Somatic copy number alterations frequently occur in the cancer genome affecting not only oncogenic or tumor suppressive genes, but also passenger and potential codriver genes. An intrinsic feature resulting from such genomic perturbations is the deregulation in the metabolism of tumor cells. In this study, we have shown that metabolic and cancer-causing genes are unexpectedly often proximally positioned in the chromosome and share loci with coaltered copy numbers across multiple cancers (19 cancer types from The Cancer Genome Atlas). We have developed an analysis pipeline, Identification of Metabolic Cancer Genes (iMetCG), to infer the functional impact on metabolic remodeling from such coamplifications and codeletions and delineate genes driving cancer metabolism from those that are neutral. Using our identified metabolic genes, we were able to classify tumors based on their tissue and developmental origins. These metabolic genes were similar to known cancer genes in terms of their network connectivity, isoform frequency, and evolutionary features. We further validated these identified metabolic genes by (i) using gene essentiality data from several tumor cell lines, (ii) showing that these identified metabolic genes are strong indicators for patient survival, and (iii) observing a significant overlap between our identified metabolic genes and known cancer-metabolic genes. Our analyses revealed a hitherto unknown generic mechanism for large-scale metabolic reprogramming in cancer cells based on linear gene proximities between cancer-causing and -metabolic genes. We have identified 119 new metabolic cancer genes likely to be involved in rewiring cancer cell metabolism. Cancer Res; 76(14); 4058-67. ©2016 AACR.

A Systems Biology Interpretation of Array Comparative Genomic Hybridization (aCGH) Data through Phylogenetics.

Array Comparative Genomic Hybridization (aCGH) is a rapid screening technique to detect gene deletions and duplications, providing an overview of chromosomal aberrations throughout the entire genome of a tumor, without the need for cell culturing. However, the heterogeneity of aCGH data obfuscates existing methods of data analysis. Analysis of aCGH data from a systems biology perspective or in the context of total aberrations is largely absent in the published literature. We present here a novel alternative to the functional analysis of aCGH data using the phylogenetic paradigm that is well-suited to high dimensional datasets of heterogeneous nature, but has not been widely adapted to aCGH data. Maximum parsimony phylogenetic analysis sorts out genetic data through the simplest presentation of the data on a cladogram, a graphical evolutionary tree, thus providing a powerful and efficient method for aCGH data analysis. For example, the cladogram models the multiphasic changes in the cancer genome and identifies shared early mutations in the disease progression, providing a simple yet powerful means of aCGH data interpretation. As such, applying maximum parsimony phylogenetic analysis to aCGH results allows for the differentiation between drivers and passenger genes aberrations in cancer specimens. In addition to offering a novel methodology to analyze aCGH results, we present here a crucial software suite that we wrote to carry out the analysis. In a broader context, we wish to underscore that phylogenetic analysis of aCGH data is a non-parametric method that circumvents the pitfalls and frustrations of standard analytical techniques that rely on parametric statistics. Organizing the data in a cladogram as explained in this research article provides insights into the disease common aberrations, as well as the disease subtypes and their shared aberrations (the synapomorphies) of each subtype. Hence, we report the method and make the software suite publicly and freely available at http://software.phylomcs.com so that researchers can test alternative and innovative approaches to the analysis of aCGH data.

Quantitative Proteomic Verification of Membrane Proteins as Potential Therapeutic Targets Located in the 11q13 Amplicon in Cancers.

Tumor types can be defined cytologically by their regions of chromosomal amplification, which often results in the high expression of both mRNA and proteins of certain genes contained within the amplicon. An important strategy for defining therapeutically relevant targets in these situations is to ascertain which genes are amplified at the protein level and, concomitantly, are key drivers for tumor growth or maintenance. Furthermore, so-called passenger genes that are amplified with driver genes and a manifest on the cell surface can be attractive targets for an antibody-drug conjugate approach (ADC). We employed a tandem mass spectrometry proteomics approach using tumor cell lines to identify the cell surface proteins whose expression correlates with the 11q13 amplicon. The 11q13 amplicon is one of the most frequently amplified chromosomal regions in human cancer, being present in 45% of head and neck and oral squamous cell carcinoma (OSCC) and 13-21% of breast and liver carcinomas. Using a panel of tumor cell lines with defined 11q13 genomic amplification, we identified the membrane proteins that are differentially expressed in an 11q13 amplified cell line panel using membrane-enriched proteomic profiling. We found that DSG3, CD109, and CD14 were differentially overexpressed in head and neck and breast tumor cells with 11q13 amplification. The level of protein expression of each gene was confirmed by Western blot and FACS analysis. Because proteins with high cell surface expression on selected tumor cells could be potential antibody drug conjugate targets, we tested DSG3 and CD109 in antibody piggyback assays and validated that DSG3 and CD109 expression was sufficient to induce antibody internalization and cell killing in 11q13-amplified cell lines. Our results suggest that proteomic profiling using genetically stratified tumors can identify candidate antibody drug conjugate targets. Data are available via ProteomeXchange with the identifier PXD002486.

Identifying overlapping mutated driver pathways by constructing gene networks in cancer.

BackgroundLarge-scale cancer genomic projects are providing lots of data on genomic, epigenomic and gene expression aberrations in many cancer types. One key challenge is to detect functional driver pathways and to filter out nonfunctional passenger genes in cancer genomics. Vandin et al. introduced the Maximum Weight Sub-matrix Problem to find driver pathways and showed that it is an NP-hard problem.MethodsTo find a better solution and solve the problem more efficiently, we present a network-based method (NBM) to detect overlapping driver pathways automatically. This algorithm can directly find driver pathways or gene sets de novo from somatic mutation data utilizing two combinatorial properties, high coverage and high exclusivity, without any prior information. We firstly construct gene networks based on the approximate exclusivity between each pair of genes using somatic mutation data from many cancer patients. Secondly, we present a new greedy strategy to add or remove genes for obtaining overlapping gene sets with driver mutations according to the properties of high exclusivity and high coverage.ResultsTo assess the efficiency of the proposed NBM, we apply the method on simulated data and compare results obtained from the NBM, RME, Dendrix and Multi-Dendrix. NBM obtains optimal results in less than nine seconds on a conventional computer and the time complexity is much less than the three other methods. To further verify the performance of NBM, we apply the method to analyze somatic mutation data from five real biological data sets such as the mutation profiles of 90 glioblastoma tumor samples and 163 lung carcinoma samples. NBM detects groups of genes which overlap with known pathways, including P53, RB and RTK/RAS/PI(3)K signaling pathways. New gene sets with p-value less than 1e-3 are found from the somatic mutation data.ConclusionsNBM can detect more biologically relevant gene sets. Results show that NBM outperforms other algorithms for detecting driver pathways or gene sets. Further research will be conducted with the use of novel machine learning techniques.

A TALE of transposition: Tn3-like transposons play a major role in the spread of pathogenicity determinants of Xanthomonas citri and other xanthomonads.

ABSTRACTMembers of the genus Xanthomonas are among the most important phytopathogens. A key feature of Xanthomonas pathogenesis is the translocation of type III secretion system (T3SS) effector proteins (T3SEs) into the plant target cells via a T3SS. Several T3SEs and a murein lytic transglycosylase gene (mlt, required for citrus canker symptoms) are found associated with three transposition-related genes in Xanthomonas citri plasmid pXAC64. These are flanked by short inverted repeats (IRs). The region was identified as a transposon, TnXax1, with typical Tn3 family features, including a transposase and two recombination genes. Two 14-bp palindromic sequences within a 193-bp potential resolution site occur between the recombination genes. Additional derivatives carrying different T3SEs and other passenger genes occur in different Xanthomonas species. The T3SEs include transcription activator-like effectors (TALEs). Certain TALEs are flanked by the same IRs as found in TnXax1 to form mobile insertion cassettes (MICs), suggesting that they may be transmitted horizontally. A significant number of MICs carrying other passenger genes (including a number of TALE genes) were also identified, flanked by the same TnXax1 IRs and delimited by 5-bp target site duplications. We conclude that a large fraction of T3SEs, including individual TALEs and potential pathogenicity determinants, have spread by transposition and that TnXax1, which exhibits all of the essential characteristics of a functional transposon, may be involved in driving MIC transposition. We also propose that TALE genes may diversify by fork slippage during the replicative Tn3 family transposition. These mechanisms may play a crucial role in the emergence of Xanthomonas pathogenicity.

Personalized cancer medicine: present status and future perspectives

결핵은 결핵균에 의하여 발생하는 질환이다. 따라서, 진단 은 결핵균을 증명하거나 결핵균에 의해 손상된 조직소견을 확인하면 된다. 치료도 결핵균을 죽일 수 있는 항균제를 사 용하면 대부분 해결된다. 암이라는 진단은 결핵과 다르다. 우리나라에 흔한 ‘위암’의 경우, 위장에는 대부분 선암이 발생하지만 악성림프종이나 육종 등도 생긴다. 반대로 ‘선암’은 위장뿐만 아니라, 유방, Most cancers have oncogenes and tumor suppressor genes. First successful drug targeting a oncogene is imatinib. It was very effective for chronic myelogenous leukemia as well as gastrointestinal stromal tumors. Many other targeted agents showed good response: trastuzumab for breast cancer, epidermal growth factor receptor tyrosine kinase inhibitors for non-small cell lung cancer, etc. Tests for EGFR and ALK gene mutation are routinely recommended for adenocarcinoma of lung cancer for selection of anticancer treatment. In addition, large-scale genomic data generation (next generation sequencing) is feasible in a clinical setting and gives us high hope for personalized cancer medicine. However, there are many hurdles to overcome. Driver genes must be distinguished from the passenger genes that are present in tumor DNA. In case of targeted cancer therapy, emergence of drug resistance due to tumor cell heterogeneity and clonal evolution is difficult to manage. Genetic testing for cancer risk showed some success in preventing familial breast or ovarian cancers, but it cannot be generalized in other tumors. Application of genetic information in cancer medicine showed promise but evidence-based approach is needed in clinical practice.

The Architecture and Evolution of Cancer Neochromosomes

We isolated and analyzed, at single-nucleotide resolution, cancer-associated neochromosomes from well- and/or dedifferentiated liposarcomas. Neochromosomes, which can exceed 600 Mb in size, initially arise as circular structures following chromothripsis involving chromosome 12. The core of the neochromosome is amplified, rearranged, and corroded through hundreds of breakage-fusion-bridge cycles. Under selective pressure, amplified oncogenes are overexpressed, while coamplified passenger genes may be silenced epigenetically. New material may be captured during punctuated chromothriptic events. Centromeric corrosion leads to crisis, which is resolved through neocentromere formation or native centromere capture. Finally, amplification terminates, and the neochromosome core is stabilized in linear form by telomere capture. This study investigates the dynamic mutational processes underlying the life history of a special form of cancer mutation.

Abstract A85: Passenger genes on tumor-associated amplicons function as tumor rejection antigens

Abstract Tumors frequently contain DNA copy number amplifications (amplicons) that are driven by overexpression of an oncogene but often lead to high expression of neighboring passenger genes. We hypothesized that proteins encoded on amplicons which are present at high frequency in particular types of cancer could serve as shared tumor rejection antigens. The ERBB2 (HER2) amplicon on 17q12-21 has a core region of approximately 280kB in size and is frequently present in multiple copies in 10-15% of breast and gastric cancers. Analysis of data from TCGA breast cancer project and multiple other mRNA expression studies show that ERBB2 overexpression is highly correlated with expression of some, but not all, adjacent genes. From the set of amplicon genes we selected MIEN, GRB7, PGAP3, PNMT, ORMDL3, and GSDMB as candidates for stimulating an immune response because these proteins are minimally expressed in normal tissues. Immunohistochemistry of tissue microarrays showed expression of these proteins in HER2+ breast cancer cells but not in HER2 non-amplified breast tumors. We used the epitope identification programs, NetCTLpan and NetMHCII (Center for Biological Sequence Analysis at the Technical University of Denmark) to identify several candidate peptides with high binding affinity <50 nM to common HLA alleles. In vitro sensitization of normal donor PBMC with several of these peptides led to IFN γ production. Moreover, DCs pulsed with tumor lysate from HER2 amplified tumor cells were able to sensitize T cells against epitopes derived from amplicon proteins indicating that the natural abundance of these antigens in tumors is sufficient for cross-presentation to T cells. The TM15 murine breast cancer line has amplification of a syntenic region surrounding Her2/neu and 50-fold over-expression of pnmt by qPCR. Mice vaccinated with recombinant murine PNMT rejected TM15 tumor challenge without apparent toxicity. These findings indicate that tumor genomic data can be used to identify candidate tumor antigens and epitope prediction can be used to engineer a T cell immune response to break tolerance to these normal proteins. It appears that a therapeutic window can be established to target amplicon-derived antigens due to substantially higher expression in tumor cells relative to normal tissues. Moreover, peptide sequence differences between human and murine proteins at sites of immunogenic epitopes provide an opportunity to generate high-affinity TCR in HLA transgenic mice. Although shared tumor antigens such as HER2 have served as targets for cancer immunotherapy there have been some difficulties with off-target toxicity against normal tissues due to broad expression. Selection of over-expressed passenger genes that exceed a threshold for T cell responsiveness only in tumor but not normal tissues might lead to greater efficacy. This strategy potentially could be applied to other tumor-associated amplicons such as MYCN to search for peptide epitopes from passenger genes which are predicted to have high affinity for common HLA alleles. Citation Format: Michael Berk, Arun Modi, Mona Patel, Li-Xin Wang, Gregory Plautz. Passenger genes on tumor-associated amplicons function as tumor rejection antigens. [abstract]. In: Proceedings of the AACR Special Conference on Pediatric Cancer at the Crossroads: Translating Discovery into Improved Outcomes; Nov 3-6, 2013; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2013;74(20 Suppl):Abstract nr A85.

Abstract 2897: ERBB2 amplicon passenger genes: A novel class of breast cancer antigens

Abstract DNA copy number amplification at the ERBB2 locus on 17q12-21 is a frequent genomic event, present in 10-15% of breast tumors. This gene-dense amplicon contains several genes that are aberrantly overexpressed in ERBB2+ breast cancer. We hypothesized that a subset of amplicon genes with minimal expression in normal tissue could serve as candidates for shared tumor-specific antigens. We eliminated from consideration other amplicon genes with high expression in specific tissues or broad expression in normal tissues due to the potential for autoimmune toxicity. Immunohistochemistry of a breast tumor microarray showed expression of MIEN, GRB7, PGAP3 proteins specifically in ERBB2+ tumor cells but not in stroma or in ERBB2 non-amplified breast tumor samples. We tested several peptide epitopes with predicted high affinity for HLA-A2 (<50 nM) and confirmed that these could stabilize MHC expression on T2 cells. In vitro sensitization of normal donor lymphocytes with the predicted epitopes led to production of IFN-γ. Moreover, Dendritic cells pulsed with lysate from SKBR3 (ERBB2 amplified) but not MCF7 breast cancer cells could sensitize autologous lymphocytes to epitopes from amplicon proteins. This suggests that the natural abundance of the amplicon proteins in ERBB2 positive tumors is sufficient to provide cross-priming. To test whether the amplicon proteins could serve as tumor-rejection antigens we used the murine TM15 breast cancer cell line which has amplification of a syntenic region surrounding the murine Her2/neu gene. Quantitative PCR showed 50-fold overexpression of the amplicon gene pnmt in TM15 cells. Mice vaccinated with recombinant murine or human PNMT protein, but not ovalbumin, rejected challenge with TM15 tumor without any overt toxicity and developed memory against delayed re-challenge.These data indicate that normal host genes which are in immediate proximity to the oncogene ERBB2 are abnormally expressed at high levels in ERBB2+ breast tumor cells. Although the molecular mechanism leading to aberrant expression is unknown, analysis of several breast cancer microarray databases as well as TCGA data also show a very high correlation between ERBB2 overexpression and high expression of these passenger genes so this seems to be a general phenomenon. T lymphocytes normally have tolerance to non-mutated host proteins however tolerance can be reversed with proper sensitization conditions. Antigen overexpression in tumor cells might allow effector T cells to surpass an activation threshold while preserving tolerance for normal tissue. DNA copy number amplification of specific oncogenes is a frequent genomic event in cancer so the general strategy of targeting passenger genes on amplicons may have broader use in cancer immunotherapy. Citation Format: Gregory E. Plautz, Arun Modi, Li-Xin Wang. ERBB2 amplicon passenger genes: A novel class of breast cancer antigens. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2897. doi:10.1158/1538-7445.AM2014-2897

Identifying driver genes in cancer by triangulating gene expression, gene location, and survival data.

Driver genes are directly responsible for oncogenesis and identifying them is essential in order to fully understand the mechanisms of cancer. However, it is difficult to delineate them from the larger pool of genes that are deregulated in cancer (ie, passenger genes). In order to address this problem, we developed an approach called TRIAngulating Gene Expression (TRIAGE through clinico-genomic intersects). Here, we present a refinement of this approach incorporating a new scoring methodology to identify putative driver genes that are deregulated in cancer. TRIAGE triangulates – or integrates – three levels of information: gene expression, gene location, and patient survival. First, TRIAGE identifies regions of deregulated expression (ie, expression footprints) by deriving a newly established measure called the Local Singular Value Decomposition (LSVD) score for each locus. Driver genes are then distinguished from passenger genes using dual survival analyses. Incorporating measurements of gene expression and weighting them according to the LSVD weight of each tumor, these analyses are performed using the genes located in significant expression footprints. Here, we first use simulated data to characterize the newly established LSVD score. We then present the results of our application of this refined version of TRIAGE to gene expression data from five cancer types. This refined version of TRIAGE not only allowed us to identify known prominent driver genes, such as MMP1, IL8, and COL1A2, but it also led us to identify several novel ones. These results illustrate that TRIAGE complements existing tools, allows for the identification of genes that drive cancer and could perhaps elucidate potential future targets of novel anticancer therapeutics.