Combined Analysis of Metabolomes, Proteomes, and Transcriptomes of Hepatitis C Virus-Infected Cells and Liver to Identify Pathways Associated With Disease Development.

BACKGROUND & AIMS: The mechanisms of hepatitis C virus (HCV) infection, liver disease progression, and hepatocarcinogenesis are only partially understood. We performed genomic, proteomic, and metabolomic analyses of HCV-infected cells and chimeric mice to learn more about these processes. METHODS: Huh7.5.1dif (hepatocyte-like cells) were infected with culture-derived HCV and used in RNA sequencing, proteomic, metabolomic, and integrative genomic analyses. uPA/SCID (urokinase-type plasminogen activator/severe combined immunodeficiency) mice were injected with serum from HCV-infected patients; 8 weeks later, liver tissues were collected and analyzed by RNA sequencing and proteomics. Using differential expression, gene set enrichment analyses, and protein interaction mapping, we identified pathways that changed in response to HCV infection. We validated our findings in studies of liver tissues from 216 patients with HCV infection and early-stage cirrhosis and paired biopsy specimens from 99 patients with hepatocellular carcinoma, including 17 patients with histologic features of steatohepatitis. Cirrhotic liver tissues from patients with HCV infection were classified into 2 groups based on relative peroxisome function; outcomes assessed included Child-Pugh class, development of hepatocellular carcinoma, survival, and steatohepatitis. Hepatocellular carcinomas were classified according to steatohepatitis; the outcome was relative peroxisomal function. RESULTS: We quantified 21,950 messenger RNAs (mRNAs) and 8297 proteins in HCV-infected cells. Upon HCV infection of hepatocyte-like cells and chimeric mice, we observed significant changes in levels of mRNAs and proteins involved in metabolism and hepatocarcinogenesis. HCV infection of hepatocyte-like cells significantly increased levels of the mRNAs, but not proteins, that regulate the innate immune response; we believe this was due to the inhibition of translation in these cells. HCV infection of hepatocyte-like cells increased glucose consumption and metabolism and the STAT3 signaling pathway and reduced peroxisome function. Peroxisomes mediate ß-oxidation of very long-chain fatty acids; we found intracellular accumulation of very long-chain fatty acids in HCV-infected cells, which is also observed in patients with fatty liver disease. Cells in livers from HCV-infected mice had significant reductions in levels of the mRNAs and proteins associated with peroxisome function, indicating perturbation of peroxisomes. We found that defects in peroxisome function were associated with outcomes and features of HCV-associated cirrhosis, fatty liver disease, and hepatocellular carcinoma in patients. CONCLUSIONS: We performed combined transcriptome, proteome, and metabolome analyses of liver tissues from HCV-infected hepatocyte-like cells and HCV-infected mice. We found that HCV infection increases glucose metabolism and the STAT3 signaling pathway and thereby reduces peroxisome function; alterations in the expression levels of peroxisome genes were associated with outcomes of patients with liver diseases. These findings provide insights into liver disease pathogenesis and might be used to identify new therapeutic targets.

Physiological state co-regulates thousands of mammalian mRNA splicing events at tandem splice sites and alternative exons.

Thousands of tandem alternative splice sites (TASS) give rise to mRNA insertion/deletion variants with small size differences. Recent work has concentrated on the question of biological relevance in general, and the physiological regulation of TASS in particular. We have quantitatively studied 11 representative TASS cases in comparison to one mutually exclusive exon case and two cassette exons (CEs) using a panel of human and mouse tissues, as well as cultured cell lines. Tissues show small but significant differences in TASS isoform ratios, with a variance 4- to 20-fold lower than seen for CEs. Remarkably, in cultured cells, all studied alternative splicing (AS) cases showed a cell-density-dependent shift of isoform ratios with similar time series profiles. A respective genome-wide co-regulation of TASS splicing was shown by next-generation mRNA sequencing data. Moreover, data from human and mouse organs indicate that this co-regulation of TASS occurs in vivo, with brain showing the strongest difference to other organs. Together, the results indicate a physiological AS regulation mechanism that functions almost independently from the splice site context and sequence.

The SH2-domain of SHIP1 interacts with the SHIP1 C-terminus: impact on SHIP1/Ig-α interaction.

The SH2-containing inositol 5'-phosphatase, SHIP1, negatively regulates signal transduction from the B cell antigen receptor (BCR). The mode of coupling between SHIP1 and the BCR has not been elucidated so far. In comparison to wild-type cells, B cells expressing a mutant IgD- or IgM-BCR containing a C-terminally truncated Ig-α respond to pervanadate stimulation with markedly reduced tyrosine phosphorylation of SHIP1 and augmented activation of protein kinase B. This indicates that SHIP1 is capable of interacting with the C-terminus of Ig-α. Employing a system of fluorescence resonance energy transfer in S2 cells, we can clearly demonstrate interaction between the SH2-domain of SHIP1 and Ig-α. Furthermore, a fluorescently labeled SH2-domain of SHIP1 translocates to the plasma membrane in an Ig-α-dependent manner. Interestingly, whereas the SHIP1 SH2-domain can be pulled-down with phospho-peptides corresponding to the immunoreceptor tyrosine-based activation motif (ITAM) of Ig-α from detergent lysates, no interaction between full-length SHIP1 and the phosphorylated Ig-α ITAM can be observed. Further studies show that the SH2-domain of SHIP1 can bind to the C-terminus of the SHIP1 molecule, most probably by inter- as well as intra-molecular means, and that this interaction regulates the association between different forms of SHIP1 and Ig-α.

The molecular diversity of Luminal A breast tumors.

Breast cancer is a collection of diseases with distinct molecular traits, prognosis, and therapeutic options. Luminal A breast cancer is the most heterogeneous, both molecularly and clinically. Using genomic data from over 1,000 Luminal A tumors from multiple studies, we analyzed the copy number and mutational landscape of this tumor subtype. This integrated analysis revealed four major subtypes defined by distinct copy-number and mutation profiles. We identified an atypical Luminal A subtype characterized by high genomic instability, TP53 mutations, and increased Aurora kinase signaling; these genomic alterations lead to a worse clinical prognosis. Aberrations of chromosomes 1, 8, and 16, together with PIK3CA, GATA3, AKT1, and MAP3K1 mutations drive the other subtypes. Finally, an unbiased pathway analysis revealed multiple rare, but mutually exclusive, alterations linked to loss of activity of co-repressor complexes N-Cor and SMRT. These rare alterations were the most prevalent in Luminal A tumors and may predict resistance to endocrine therapy. Our work provides for a further molecular stratification of Luminal A breast tumors, with potential direct clinical implications.

Association of High Tumor Mutation Burden in Non-Small Cell Lung Cancers With Increased Immune Infiltration and Improved Clinical Outcomes of PD-L1 Blockade Across PD-L1 Expression Levels.

Importance: Although tumor mutation burden (TMB) has been explored as a potential biomarker of immunotherapy efficacy in solid tumors, there still is a lack of consensus about the optimal TMB threshold that best discriminates improved outcomes of immune checkpoint inhibitor therapy among patients with non-small cell lung cancer (NSCLC). Objectives: To determine the association between increasing TMB levels and immunotherapy efficacy across clinically relevant programmed death ligand-1 (PD-L1) levels in patients with NSCLC. Design, Setting, and Participants: This multicenter cohort study included patients with advanced NSCLC treated with immunotherapy who received programmed cell death-1 (PD-1) or PD-L1 inhibition in the Dana-Farber Cancer Institute (DFCI), Memorial Sloan Kettering Cancer Center (MSKCC), and in the Stand Up To Cancer (SU2C)/Mark Foundation data sets. Clinicopathological and genomic data were collected from patients between September 2013 and September 2020. Data analysis was performed from November 2021 to February 2022. Exposures: Treatment with PD-1/PD-L1 inhibition without chemotherapy. Main Outcomes and Measures: Association of TMB levels with objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). Results: In the entire cohort of 1552 patients with advanced NSCLC who received PD-1/PD-L1 blockade, the median (range) age was 66 (22-92) years, 830 (53.5%) were women, and 1347 (86.8%) had cancer with nonsquamous histologic profile. A regression tree modeling ORR as a function of TMB identified 2 TMB groupings in the discovery cohort (MSKCC), defined as low TMB (≤19.0 mutations per megabase) and high TMB (>19.0 mutations per megabase), which were associated with increasing improvements in ORR, PFS, and OS in the discovery cohort and in 2 independent cohorts (DFCI and SU2C/Mark Foundation). These TMB levels also were associated with significant improvements in outcomes of immunotherapy in each PD-L1 tumor proportion score subgroup of less than 1%, 1% to 49%, and 50% or higher. The ORR to PD-1/PD-L1 inhibition was as high as 57% in patients with high TMB and PD-L1 expression 50% or higher and as low as 8.7% in patients with low TMB and PD-L1 expression less than 1%. Multiplexed immunofluorescence and transcriptomic profiling revealed that high TMB levels were associated with increased CD8-positive, PD-L1-positive T-cell infiltration, increased PD-L1 expression on tumor and immune cells, and upregulation of innate and adaptive immune response signatures. Conclusions and Relevance: These findings suggest that increasing TMB levels are associated with immune cell infiltration and an inflammatory T-cell-mediated response, resulting in increased sensitivity to PD-1/PD-L1 blockade in NSCLC across PD-L1 expression subgroups.

Accurate prediction of NAGNAG alternative splicing.

Alternative splicing (AS) involving NAGNAG tandem acceptors is an evolutionarily widespread class of AS. Recent predictions of alternative acceptor usage reported better results for acceptors separated by larger distances, than for NAGNAGs. To improve the latter, we aimed at the use of Bayesian networks (BN), and extensive experimental validation of the predictions. Using carefully constructed training and test datasets, a balanced sensitivity and specificity of >or=92% was achieved. A BN trained on the combined dataset was then used to make predictions, and 81% (38/47) of the experimentally tested predictions were verified. Using a BN learned on human data on six other genomes, we show that while the performance for the vertebrate genomes matches that achieved on human data, there is a slight drop for Drosophila and worm. Lastly, using the prediction accuracy according to experimental validation, we estimate the number of yet undiscovered alternative NAGNAGs. State of the art classifiers can produce highly accurate prediction of AS at NAGNAGs, indicating that we have identified the major features of the 'NAGNAG-splicing code' within the splice site and its immediate neighborhood. Our results suggest that the mechanism behind NAGNAG AS is simple, stochastic, and conserved among vertebrates and beyond.

A pan-cancer survey of cell line tumor similarity by feature-weighted molecular profiles.

Patient-derived cell lines are often used in pre-clinical cancer research, but some cell lines are too different from tumors to be good models. Comparison of genomic and expression profiles can guide the choice of pre-clinical models, but typically not all features are equally relevant. We present TumorComparer, a computational method for comparing cellular profiles with higher weights on functional features of interest. In this pan-cancer application, we compare ∼600 cell lines and ∼8,000 tumor samples of 24 cancer types, using weights to emphasize known oncogenic alterations. We characterize the similarity of cell lines and tumors within and across cancers by using multiple datum types and rank cell lines by their inferred quality as representative models. Beyond the assessment of cell lines, the weighted similarity approach is adaptable to patient stratification in clinical trials and personalized medicine.

TassDB2 - A comprehensive database of subtle alternative splicing events.

BACKGROUND: Subtle alternative splicing events involving tandem splice sites separated by a short (2-12 nucleotides) distance are frequent and evolutionarily widespread in eukaryotes, and a major contributor to the complexity of transcriptomes and proteomes. However, these events have been either omitted altogether in databases on alternative splicing, or only the cases of experimentally confirmed alternative splicing have been reported. Thus, a database which covers all confirmed cases of subtle alternative splicing as well as the numerous putative tandem splice sites (which might be confirmed once more transcript data becomes available), and allows to search for tandem splice sites with specific features and download the results, is a valuable resource for targeted experimental studies and large-scale bioinformatics analyses of tandem splice sites. Towards this goal we recently set up TassDB (Tandem Splice Site DataBase, version 1), which stores data about alternative splicing events at tandem splice sites separated by 3 nt in eight species. DESCRIPTION: We have substantially revised and extended TassDB. The currently available version 2 contains extensive information about tandem splice sites separated by 2-12 nt for the human and mouse transcriptomes including data on the conservation of the tandem motifs in five vertebrates. TassDB2 offers a user-friendly interface to search for specific genes or for genes containing tandem splice sites with specific features as well as the possibility to download result datasets. For example, users can search for cases of alternative splicing where the proportion of EST/mRNA evidence supporting the minor isoform exceeds a specific threshold, or where the difference in splice site scores is specified by the user. The predicted impact of each event on the protein is also reported, along with information about being a putative target for the nonsense-mediated decay (NMD) pathway. Links are provided to the UCSC genome browser and other external resources. CONCLUSION: TassDB2, available via http://www.tassdb.info, provides comprehensive resources for researchers interested in both targeted experimental studies and large-scale bioinformatics analyses of short distance tandem splice sites.

Identification and characterization of NAGNAG alternative splicing in the moss Physcomitrella patens.

BACKGROUND: Alternative splicing (AS) involving tandem acceptors that are separated by three nucleotides (NAGNAG) is an evolutionarily widespread class of AS, which is well studied in Homo sapiens (human) and Mus musculus (mouse). It has also been shown to be common in the model seed plants Arabidopsis thaliana and Oryza sativa (rice). In one of the first studies involving sequence-based prediction of AS in plants, we performed a genome-wide identification and characterization of NAGNAG AS in the model plant Physcomitrella patens, a moss. RESULTS: Using Sanger data, we found 295 alternatively used NAGNAG acceptors in P. patens. Using 31 features and training and test datasets of constitutive and alternative NAGNAGs, we trained a classifier to predict the splicing outcome at NAGNAG tandem splice sites (alternative splicing, constitutive at the first acceptor, or constitutive at the second acceptor). Our classifier achieved a balanced specificity and sensitivity of >or= 89%. Subsequently, a classifier trained exclusively on data well supported by transcript evidence was used to make genome-wide predictions of NAGNAG splicing outcomes. By generation of more transcript evidence from a next-generation sequencing platform (Roche 454), we found additional evidence for NAGNAG AS, with altogether 664 alternative NAGNAGs being detected in P. patens using all currently available transcript evidence. The 454 data also enabled us to validate the predictions of the classifier, with 64% (80/125) of the well-supported cases of AS being predicted correctly. CONCLUSION: NAGNAG AS is just as common in the moss P. patens as it is in the seed plants A. thaliana and O. sativa (but not conserved on the level of orthologous introns), and can be predicted with high accuracy. The most informative features are the nucleotides in the NAGNAG and in its immediate vicinity, along with the splice sites scores, as found earlier for NAGNAG AS in animals. Our results suggest that the mechanism behind NAGNAG AS in plants is similar to that in animals and is largely dependent on the splice site and its immediate neighborhood.

Assessing the fraction of short-distance tandem splice sites under purifying selection.

Many alternative splice events result in subtle mRNA changes, and most of them occur at short-distance tandem donor and acceptor sites. The splicing mechanism of such tandem sites likely involves the stochastic selection of either splice site. While tandem splice events are frequent, it is unknown how many are functionally important. Here, we use phylogenetic conservation to address this question, focusing on tandems with a distance of 3-9 nucleotides. We show that previous contradicting results on whether alternative or constitutive tandem motifs are more conserved between species can be explained by a statistical paradox (Simpson's paradox). Applying methods that take biases into account, we found higher conservation of alternative tandems in mouse, dog, and even chicken, zebrafish, and Fugu genomes. We estimated a lower bound for the number of alternative sites that are under purifying (negative) selection. While the absolute number of conserved tandem motifs decreases with the evolutionary distance, the fraction under selection increases. Interestingly, a number of frameshifting tandems are under selection, suggesting a role in regulating mRNA and protein levels via nonsense-mediated decay (NMD). An analysis of the intronic flanks shows that purifying selection also acts on the intronic sequence. We propose that stochastic splice site selection can be an advantageous mechanism that allows constant splice variant ratios in situations where a deviation in this ratio is deleterious.

Improved identification of conserved cassette exons using Bayesian networks.

BACKGROUND: Alternative splicing is a major contributor to the diversity of eukaryotic transcriptomes and proteomes. Currently, large scale detection of alternative splicing using expressed sequence tags (ESTs) or microarrays does not capture all alternative splicing events. Moreover, for many species genomic data is being produced at a far greater rate than corresponding transcript data, hence in silico methods of predicting alternative splicing have to be improved. RESULTS: Here, we show that the use of Bayesian networks (BNs) allows accurate prediction of evolutionary conserved exon skipping events. At a stringent false positive rate of 0.5%, our BN achieves an improved true positive rate of 61%, compared to a previously reported 50% on the same dataset using support vector machines (SVMs). Incorporating several novel discriminative features such as intronic splicing regulatory elements leads to the improvement. Features related to mRNA secondary structure increase the prediction performance, corroborating previous findings that secondary structures are important for exon recognition. Random labelling tests rule out overfitting. Cross-validation on another dataset confirms the increased performance. When using the same dataset and the same set of features, the BN matches the performance of an SVM in earlier literature. Remarkably, we could show that about half of the exons which are labelled constitutive but receive a high probability of being alternative by the BN, are in fact alternative exons according to the latest EST data. Finally, we predict exon skipping without using conservation-based features, and achieve a true positive rate of 29% at a false positive rate of 0.5%. CONCLUSION: BNs can be used to achieve accurate identification of alternative exons and provide clues about possible dependencies between relevant features. The near-identical performance of the BN and SVM when using the same features shows that good classification depends more on features than on the choice of classifier. Conservation based features continue to be the most informative, and hence distinguishing alternative exons from constitutive ones without using conservation based features remains a challenging problem.

Analysis of renal cancer cell lines from two major resources enables genomics-guided cell line selection.

The utility of cancer cell lines is affected by the similarity to endogenous tumour cells. Here we compare genomic data from 65 kidney-derived cell lines from the Cancer Cell Line Encyclopedia and the COSMIC Cell Lines Project to three renal cancer subtypes from The Cancer Genome Atlas: clear cell renal cell carcinoma (ccRCC, also known as kidney renal clear cell carcinoma), papillary (pRCC, also known as kidney papillary) and chromophobe (chRCC, also known as kidney chromophobe) renal cell carcinoma. Clustering copy number alterations shows that most cell lines resemble ccRCC, a few (including some often used as models of ccRCC) resemble pRCC, and none resemble chRCC. Human ccRCC tumours clustering with cell lines display clinical and genomic features of more aggressive disease, suggesting that cell lines best represent aggressive tumours. We stratify mutations and copy number alterations for important kidney cancer genes by the consistency between databases, and classify cell lines into established gene expression-based indolent and aggressive subtypes. Our results could aid investigators in analysing appropriate renal cancer cell lines.

Inhibition of the Nuclear Export Receptor XPO1 as a Therapeutic Target for Platinum-Resistant Ovarian Cancer.

Purpose: The high fatality-to-case ratio of ovarian cancer is directly related to platinum resistance. Exportin-1 (XPO1) is a nuclear exporter that mediates nuclear export of multiple tumor suppressors. We investigated possible clinicopathologic correlations of XPO1 expression levels and evaluated the efficacy of XPO1 inhibition as a therapeutic strategy in platinum-sensitive and -resistant ovarian cancer.Experimental Design: XPO1 expression levels were analyzed to define clinicopathologic correlates using both TCGA/GEO datasets and tissue microarrays (TMA). The effect of XPO1 inhibition, using the small-molecule inhibitors KPT-185 and KPT-330 (selinexor) alone or in combination with a platinum agent on cell viability, apoptosis, and the transcriptome was tested in immortalized and patient-derived ovarian cancer cell lines (PDCL) and platinum-resistant mice (PDX). Seven patients with late-stage, recurrent, and heavily pretreated ovarian cancer were treated with an oral XPO1 inhibitor.Results: XPO1 RNA overexpression and protein nuclear localization were correlated with decreased survival and platinum resistance in ovarian cancer. Targeted XPO1 inhibition decreased cell viability and synergistically restored platinum sensitivity in both immortalized ovarian cancer cells and PDCL. The XPO1 inhibitor-mediated apoptosis occurred through both p53-dependent and p53-independent signaling pathways. Selinexor treatment, alone and in combination with platinum, markedly decreased tumor growth and prolonged survival in platinum-resistant PDX and mice. In selinexor-treated patients, tumor growth was halted in 3 of 5 patients, including one with a partial response, and was safely tolerated by all.Conclusions: Taken together, these results provide evidence that XPO1 inhibition represents a new therapeutic strategy for overcoming platinum resistance in women with ovarian cancer. Clin Cancer Res; 23(6); 1552-63. ©2016 AACR.

Genomic and transcriptomic hallmarks of poorly differentiated and anaplastic thyroid cancers.

BACKGROUND: Poorly differentiated thyroid cancer (PDTC) and anaplastic thyroid cancer (ATC) are rare and frequently lethal tumors that so far have not been subjected to comprehensive genetic characterization. METHODS: We performed next-generation sequencing of 341 cancer genes from 117 patient-derived PDTCs and ATCs and analyzed the transcriptome of a representative subset of 37 tumors. Results were analyzed in the context of The Cancer Genome Atlas study (TCGA study) of papillary thyroid cancers (PTC). RESULTS: Compared to PDTCs, ATCs had a greater mutation burden, including a higher frequency of mutations in TP53, TERT promoter, PI3K/AKT/mTOR pathway effectors, SWI/SNF subunits, and histone methyltransferases. BRAF and RAS were the predominant drivers and dictated distinct tropism for nodal versus distant metastases in PDTC. RAS and BRAF sharply distinguished between PDTCs defined by the Turin (PDTC-Turin) versus MSKCC (PDTC-MSK) criteria, respectively. Mutations of EIF1AX, a component of the translational preinitiation complex, were markedly enriched in PDTCs and ATCs and had a striking pattern of co-occurrence with RAS mutations. While TERT promoter mutations were rare and subclonal in PTCs, they were clonal and highly prevalent in advanced cancers. Application of the TCGA-derived BRAF-RAS score (a measure of MAPK transcriptional output) revealed a preserved relationship with BRAF/RAS mutation in PDTCs, whereas ATCs were BRAF-like irrespective of driver mutation. CONCLUSIONS: These data support a model of tumorigenesis whereby PDTCs and ATCs arise from well-differentiated tumors through the accumulation of key additional genetic abnormalities, many of which have prognostic and possible therapeutic relevance. The widespread genomic disruptions in ATC compared with PDTC underscore their greater virulence and higher mortality. FUNDING: This work was supported in part by NIH grants CA50706, CA72597, P50-CA72012, P30-CA008748, and 5T32-CA160001; the Lefkovsky Family Foundation; the Society of Memorial Sloan Kettering; the Byrne fund; and Cycle for Survival.

Evaluating cell lines as tumour models by comparison of genomic profiles.

Cancer cell lines are frequently used as in vitro tumour models. Recent molecular profiles of hundreds of cell lines from The Cancer Cell Line Encyclopedia and thousands of tumour samples from the Cancer Genome Atlas now allow a systematic genomic comparison of cell lines and tumours. Here we analyse a panel of 47 ovarian cancer cell lines and identify those that have the highest genetic similarity to ovarian tumours. Our comparison of copy-number changes, mutations and mRNA expression profiles reveals pronounced differences in molecular profiles between commonly used ovarian cancer cell lines and high-grade serous ovarian cancer tumour samples. We identify several rarely used cell lines that more closely resemble cognate tumour profiles than commonly used cell lines, and we propose these lines as the most suitable models of ovarian cancer. Our results indicate that the gap between cell lines and tumours can be bridged by genomically informed choices of cell line models for all tumour types.

Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal.

The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.

The mutational landscape of adenoid cystic carcinoma.

Adenoid cystic carcinomas (ACCs) are among the most enigmatic of human malignancies. These aggressive salivary gland cancers frequently recur and metastasize despite definitive treatment, with no known effective chemotherapy regimen. Here we determined the ACC mutational landscape and report the exome or whole-genome sequences of 60 ACC tumor-normal pairs. These analyses identified a low exonic somatic mutation rate (0.31 non-silent events per megabase) and wide mutational diversity. Notably, we found mutations in genes encoding chromatin-state regulators, such as SMARCA2, CREBBP and KDM6A, suggesting that there is aberrant epigenetic regulation in ACC oncogenesis. Mutations in genes central to the DNA damage response and protein kinase A signaling also implicate these processes. We observed MYB-NFIB translocations and somatic mutations in MYB-associated genes, solidifying the role of these aberrations as critical events in ACC. Lastly, we identified recurrent mutations in the FGF-IGF-PI3K pathway (30% of tumors) that might represent new avenues for therapy. Collectively, our observations establish a molecular foundation for understanding and exploring new treatments for ACC.

Comparative genomic analysis of primary versus metastatic colorectal carcinomas.

PURPOSE: To compare the mutational and copy number profiles of primary and metastatic colorectal carcinomas (CRCs) using both unpaired and paired samples derived from primary and metastatic disease sites. PATIENTS AND METHODS: We performed a multiplatform genomic analysis of 736 fresh frozen CRC tumors from 613 patients. The cohort included 84 patients in whom tumor tissue from both primary and metastatic sites was available and 31 patients with pairs of metastases. Tumors were analyzed for mutations in the KRAS, NRAS, BRAF, PIK3CA, and TP53 genes, with discordant results between paired samples further investigated by analyzing formalin-fixed, paraffin-embedded tissue and/or by 454 sequencing. Copy number aberrations in primary tumors and matched metastases were analyzed by comparative genomic hybridization (CGH). RESULTS: TP53 mutations were more frequent in metastatic versus primary tumors (53.1% v 30.3%, respectively; P < .001), whereas BRAF mutations were significantly less frequent (1.9% v 7.7%, respectively; P = .01). The mutational status of the matched pairs was highly concordant (> 90% concordance for all five genes). Clonality analysis of array CGH data suggested that multiple CRC primary tumors or treatment-associated effects were likely etiologies for mutational and/or copy number profile differences between primary tumors and metastases. CONCLUSION: For determining RAS, BRAF, and PIK3CA mutational status, genotyping of the primary CRC is sufficient for most patients. Biopsy of a metastatic site should be considered in patients with a history of multiple primary carcinomas and in the case of TP53 for patients who have undergone interval treatment with radiation or cytotoxic chemotherapies.