Christophe Legendre

Comparative RNA-Seq and Microarray Analysis of Gene Expression Changes in B-Cell Lymphomas of Canis familiaris

Comparative oncology is a developing research discipline that is being used to assist our understanding of human neoplastic diseases. Companion canines are a preferred animal oncology model due to spontaneous tumor development and similarity to human disease at the pathophysiological level. We use a paired RNA sequencing (RNA-Seq)/microarray analysis of a set of four normal canine lymph nodes and ten canine lymphoma fine needle aspirates to identify technical biases and variation between the technologies and convergence on biological disease pathways. Surrogate Variable Analysis (SVA) provides a formal multivariate analysis of the combined RNA-Seq/microarray data set. Applying SVA to the data allows us to decompose variation into contributions associated with transcript abundance, differences between the technology, and latent variation within each technology. A substantial and highly statistically significant component of the variation reflects transcript abundance, and RNA-Seq appeared more sensitive for detection of transcripts expressed at low levels. Latent random variation among RNA-Seq samples is also distinct in character from that impacting microarray samples. In particular, we observed variation between RNA-Seq samples that reflects transcript GC content. Platform-independent variable decomposition without a priori knowledge of the sources of variation using SVA represents a generalizable method for accomplishing cross-platform data analysis. We identified genes differentially expressed between normal lymph nodes of disease free dogs and a subset of the diseased dogs diagnosed with B-cell lymphoma using each technology. There is statistically significant overlap between the RNA-Seq and microarray sets of differentially expressed genes. Analysis of overlapping genes in the context of biological systems suggests elevated expression and activity of PI3K signaling in B-cell lymphoma biopsies compared with normal biopsies, consistent with literature describing successful use of drugs targeting this pathway in lymphomas.

High-throughput sequencing reveals altered expression of hepatic microRNAs in nonalcoholic fatty liver disease-related fibrosis.

Recent evidence suggests that microRNAs (miRNAs), small, noncoding RNA molecules that regulate gene expression, may play a role in the regulation of metabolic disorders, including nonalcoholic fatty liver disease (NAFLD). To identify miRNAs that mediate NAFLD-related fibrosis, we used high-throughput sequencing to assess miRNAs obtained from liver biopsies of 15 individuals without NAFLD fibrosis (F0) and 15 individuals with severe NAFLD fibrosis or cirrhosis (F3-F4), matched for age, sex, body mass index, type 2 diabetes status, hemoglobin A1c, and use of diabetes medications. We used DESeq2 and Kruskal-Wallis test to identify miRNAs that were differentially expressed between NAFLD patients with or without fibrosis, adjusting for multiple testing using Bonferroni correction. We identified a total of 75 miRNAs showing statistically significant evidence (adjusted P value <0.05) for differential expression between the 2 groups, including 30 upregulated and 45 downregulated miRNAs. Quantitative reverse-transcription polymerase chain reaction analysis of selected miRNAs identified by sequencing validated 9 of 11 of the top differentially expressed miRNAs. We performed functional enrichment analysis of dysregulated miRNAs and identified several potential gene targets related to NAFLD-related fibrosis including hepatic fibrosis, hepatic stellate cell activation, transforming growth factor beta signaling, and apoptosis signaling. We identified forkhead box O3 and F-box WD repeat domain containing 7, E3 ubiquitin protein ligase (FBXW7) as potential targets of miR-182, and found that levels of forkhead box O3, but not FBXW7, were significantly decreased in fibrotic samples. These findings support a role for hepatic miRNAs in the pathogenesis of NAFLD-related fibrosis and yield possible new insight into the molecular mechanisms underlying the initiation and progression of liver fibrosis and cirrhosis.

Deep Clonal Profiling of Formalin Fixed Paraffin Embedded Clinical Samples

Formalin fixed paraffin embedded (FFPE) tissues are a vast resource of annotated clinical samples. As such, they represent highly desirable and informative materials for the application of high definition genomics for improved patient management and to advance the development of personalized therapeutics. However, a limitation of FFPE tissues is the variable quality of DNA extracted for analyses. Furthermore, admixtures of non-tumor and polyclonal neoplastic cell populations limit the number of biopsies that can be studied and make it difficult to define cancer genomes in patient samples. To exploit these valuable tissues we applied flow cytometry-based methods to isolate pure populations of tumor cell nuclei from FFPE tissues and developed a methodology compatible with oligonucleotide array CGH and whole exome sequencing analyses. These were used to profile a variety of tumors (breast, brain, bladder, ovarian and pancreas) including the genomes and exomes of matching fresh frozen and FFPE pancreatic adenocarcinoma samples.

Personalized treatment of Sézary syndrome by targeting a novel CTLA4:CD28 fusion

Matching molecularly targeted therapies with cancer subtype‐specific gene mutations is revolutionizing oncology care. However, for rare cancers this approach is problematic due to the often poor understanding of the diseases natural history and phenotypic heterogeneity, making treatment of these cancers a particularly unmet medical need in clinical oncology. Advanced Sézary syndrome (SS), an aggressive, exceedingly rare variant of cutaneous T‐cell lymphoma (CTCL) is a prototypical example of a rare cancer. Through whole genome and RNA sequencing (RNA‐seq) of a SS patients tumor we discovered a highly expressed gene fusion between CTLA4 (cytotoxic T lymphocyte antigen 4) and CD28 (cluster of differentiation 28), predicting a novel stimulatory molecule on the surface of tumor T cells. Treatment with the CTLA4 inhibitor ipilimumab resulted in a rapid clinical response. Our findings suggest a novel driver mechanism for SS, and cancer in general, and exemplify an emerging model of cancer treatment using exploratory genomic analysis to identify a personally targeted treatment option when conventional therapies are exhausted.

Whole-genome bisulfite sequencing of cell-free DNA identifies signature associated with metastatic breast cancer

BackgroundA number of clinico-pathological criteria and molecular profiles have been used to stratify patients into high- and low-risk groups. Currently, there are still no effective methods to determine which patients harbor micrometastatic disease after standard breast cancer therapy and who will eventually develop local or distant recurrence. The purpose of our study was to identify circulating DNA methylation changes that can be used for prediction of metastatic breast cancer (MBC).ResultsDifferential methylation analysis revealed ~5.0 × 106 differentially methylated CpG loci in MBC compared with healthy individuals (H) or disease-free survivors (DFS). In contrast, there was a strong degree of similarity between H and DFS. Overall, MBC demonstrated global hypomethylation and focal CpG island (CPGI) hypermethylation. Data analysis identified 21 novel hotspots, within CpG islands, that differed most dramatically in MBC compared with H or DFS.ConclusionsThis unbiased analysis of cell-free (cf) DNA identified 21 DNA hypermethylation hotspots associated with MBC and demonstrated the ability to distinguish tumor-specific changes from normal-derived signals at the whole-genome level. This signature is a potential blood-based biomarker that could be advantageous at the time of surgery and/or after the completion of chemotherapy to indicate patients with micrometastatic disease who are at a high risk of recurrence and who could benefit from additional therapy.

Loss of the tumor suppressor SMARCA4 in small cell carcinoma of the ovary, hypercalcemic type (SCCOHT)

Small cell carcinoma of the ovary, hypercalcemic type (SCCOHT), is a rare and understudied cancer with a dismal prognosis. SCCOHTs infrequency has hindered empirical study of its biology and clinical management. However, we and others have recently identified inactivating mutations in the SWI/SNF chromatin remodeling gene SMARCA4 with concomitant loss of SMARCA4 protein in the majority of SCCOHT tumors.1–4 Here we summarize these findings and report SMARCA4 status by targeted sequencing and/or immunohistochemistry (IHC) in an additional 12 SCCOHT tumors, 3 matched germlines, and the cell line SCCOHT-1. We also report the identification of a homozygous inactivating mutation in the gene SMARCB1 in one SCCOHT tumor with wild-type SMARCA4, suggesting that SMARCB1 inactivation may also play a role in the pathogenesis of SCCOHT. To date, SMARCA4 mutations and protein loss have been reported in the majority of 69 SCCOHT cases (including 2 cell lines). These data firmly establish SMARCA4 as a tumor suppressor whose loss promotes the development of SCCOHT, setting the stage for rapid advancement in the biological understanding, diagnosis, and treatment of this rare tumor type.

Open-access synthetic spike-in mRNA-seq data for cancer gene fusions.

BackgroundOncogenic fusion genes underlie the mechanism of several common cancers. Next-generation sequencing based RNA-seq analyses have revealed an increasing number of recurrent fusions in a variety of cancers. However, absence of a publicly available gene-fusion focused RNA-seq data impedes comparative assessment and collaborative development of novel gene fusions detection algorithms. We have generated nine synthetic poly-adenylated RNA transcripts that correspond to previously reported oncogenic gene fusions. These synthetic RNAs were spiked at known molarity over a wide range into total RNA prior to construction of next-generation sequencing mRNA libraries to generate RNA-seq data.ResultsLeveraging a priori knowledge about replicates and molarity of each synthetic fusion transcript, we demonstrate utility of this dataset to compare multiple gene fusion algorithms’ detection ability. In general, more fusions are detected at higher molarity, indicating that our constructs performed as expected. However, systematic detection differences are observed based on molarity or algorithm-specific characteristics. Fusion-sequence specific detection differences indicate that for applications where specific sequences are being investigated, additional constructs may be added to provide quantitative data that is specific for the sequence of interest.ConclusionsTo our knowledge, this is the first publicly available synthetic RNA-seq data that specifically leverages known cancer gene-fusions. The proposed method of designing multiple gene-fusion constructs over a wide range of molarity allows granular performance analyses of multiple fusion-detection algorithms. The community can leverage and augment this publicly available data to further collaborative development of analytical tools and performance assessment frameworks for gene fusions from next-generation sequencing data.

Pathway Implications of Aberrant Global Methylation in Adrenocortical Cancer

Context Adrenocortical carcinomas (ACC) are a rare tumor type with a poor five-year survival rate and limited treatment options. Objective Understanding of the molecular pathogenesis of this disease has been aided by genomic analyses highlighting alterations in TP53, WNT, and IGF signaling pathways. Further elucidation is needed to reveal therapeutically actionable targets in ACC. Design In this study, global DNA methylation levels were assessed by the Infinium HumanMethylation450 BeadChip Array on 18 ACC tumors and 6 normal adrenal tissues. A new, non-linear correlation approach, the discretization method, assessed the relationship between DNA methylation/gene expression across ACC tumors. Results This correlation analysis revealed epigenetic regulation of genes known to modulate TP53, WNT, and IGF signaling, as well as silencing of the tumor suppressor MARCKS, previously unreported in ACC. Conclusions DNA methylation may regulate genes known to play a role in ACC pathogenesis as well as known tumor suppressors.

Mitochondrial genomic backgrounds affect nuclear DNA methylation and gene expression

Mitochondrial DNA (mtDNA) mutations and polymorphisms contribute to many complex diseases, including cancer. Using a unique mouse model that contains nDNA from one mouse strain and homoplasmic mitochondrial haplotypes from different mouse strain(s)-designated Mitochondrial Nuclear Exchange (MNX)-we showed that mtDNA could alter mammary tumor metastasis. Because retrograde and anterograde communication exists between the nuclear and mitochondrial genomes, we hypothesized that there are differential mtDNA-driven changes in nuclear (n)DNA expression and DNA methylation. Genome-wide nDNA methylation and gene expression were measured in harvested brain tissue from paired wild-type and MNX mice. Selective differential DNA methylation and gene expression were observed between strains having identical nDNA, but different mtDNA. These observations provide insights into how mtDNA could be altering epigenetic regulation and thereby contribute to the pathogenesis of metastasis. Cancer Res; 77(22); 6202-14. ©2017 AACR.

Altered expression of MALAT1 lncRNA in nonalcoholic steatohepatitis fibrosis regulates CXCL5 in hepatic stellate cells

&NA; In the present study, we sought to identify long noncoding RNA (lncRNA) expression profiles in nonalcoholic steatohepatitis (NASH) patients with histologic evidence of lobular inflammation and advanced fibrosis. We profiled lncRNA expression using RNA‐sequencing of wedge liver biopsies from 24 nonalcoholic fatty liver disease (NAFLD) patients with normal liver histology, 53 NAFLD patients with lobular inflammation, and 65 NAFLD patients with advanced fibrosis. Transcript profiling identified 4432 and 4057 differentially expressed lncRNAs in comparisons of normal tissue with lobular inflammation and fibrosis samples, respectively. Functional enrichment analysis revealed lncRNA participation in transforming growth factor beta 1 and tumor necrosis factor signaling, insulin resistance, and extracellular matrix maintenance. Several lncRNAs were highly expressed in fibrosis relative to normal tissue, including nuclear paraspeckle assembly transcript 1, hepatocellular carcinoma upregulated lncRNA, and metastasis‐associated lung adenocarcinoma transcript 1 (MALAT1). Two potential target mRNAs, syndecan 4 (SDC4), and C‐X‐C motif chemokine ligand 5 (CXCL5) were identified for hepatocellular carcinoma upregulated lncRNA and MALAT1, respectively, but only CXCL5 showed differential expression among the different histologic classes. Knockdown of MALAT1 expression reduced CXCL5 transcript and protein levels by 50% and 30%, respectively, in HepG2 cells. The expression of MALAT1 and CXCL5 was upregulated in activated hepatic stellate (LX‐2) cells compared to cells in the quiescent state, and MALAT1 expression was regulated by hyperglycemia and insulin in HepG2 cells, but only by insulin in LX‐2 cells. Dysregulated lncRNA expression is associated with inflammation and fibrosis in NASH. Functionally relevant differences in MALAT1 expression may contribute to the development of fibrosis in NASH through mechanisms involving inflammatory chemokines.