Integrated Proteogenomic Characterization across Major Histological Types of Pediatric Brain Cancer.

We report a comprehensive proteogenomics analysis, including whole-genome sequencing, RNA sequencing, and proteomics and phosphoproteomics profiling, of 218 tumors across 7 histological types of childhood brain cancer: low-grade glioma (n = 93), ependymoma (32), high-grade glioma (25), medulloblastoma (22), ganglioglioma (18), craniopharyngioma (16), and atypical teratoid rhabdoid tumor (12). Proteomics data identify common biological themes that span histological boundaries, suggesting that treatments used for one histological type may be applied effectively to other tumors sharing similar proteomics features. Immune landscape characterization reveals diverse tumor microenvironments across and within diagnoses. Proteomics data further reveal functional effects of somatic mutations and copy number variations (CNVs) not evident in transcriptomics data. Kinase-substrate association and co-expression network analysis identify important biological mechanisms of tumorigenesis. This is the first large-scale proteogenomics analysis across traditional histological boundaries to uncover foundational pediatric brain tumor biology and inform rational treatment selection.

Comprehensive Analysis of Hypermutation in Human Cancer.

We present an extensive assessment of mutation burden through sequencing analysis of >81,000 tumors from pediatric and adult patients, including tumors with hypermutation caused by chemotherapy, carcinogens, or germline alterations. Hypermutation was detected in tumor types not previously associated with high mutation burden. Replication repair deficiency was a major contributing factor. We uncovered new driver mutations in the replication-repair-associated DNA polymerases and a distinct impact of microsatellite instability and replication repair deficiency on the scale of mutation load. Unbiased clustering, based on mutational context, revealed clinically relevant subgroups regardless of the tumors' tissue of origin, highlighting similarities in evolutionary dynamics leading to hypermutation. Mutagens, such as UV light, were implicated in unexpected cancers, including sarcomas and lung tumors. The order of mutational signatures identified previous treatment and germline replication repair deficiency, which improved management of patients and families. These data will inform tumor classification, genetic testing, and clinical trial design.

A transcriptome-based classifier to determine molecular subtypes in medulloblastoma.

Medulloblastoma is a highly heterogeneous pediatric brain tumor with five molecular subtypes, Sonic Hedgehog TP53-mutant, Sonic Hedgehog TP53-wildtype, WNT, Group 3, and Group 4, defined by the World Health Organization. The current mechanism for classification into these molecular subtypes is through the use of immunostaining, methylation, and/or genetics. We surveyed the literature and identified a number of RNA-Seq and microarray datasets in order to develop, train, test, and validate a robust classifier to identify medulloblastoma molecular subtypes through the use of transcriptomic profiling data. We have developed a GPL-3 licensed R package and a Shiny Application to enable users to quickly and robustly classify medulloblastoma samples using transcriptomic data. The classifier utilizes a large composite microarray dataset (15 individual datasets), an individual microarray study, and an RNA-Seq dataset, using gene ratios instead of gene expression measures as features for the model. Discriminating features were identified using the limma R package and samples were classified using an unweighted mean of normalized scores. We utilized two training datasets and applied the classifier in 15 separate datasets. We observed a minimum accuracy of 85.71% in the smallest dataset and a maximum of 100% accuracy in four datasets with an overall median accuracy of 97.8% across the 15 datasets, with the majority of misclassification occurring between the heterogeneous Group 3 and Group 4 subtypes. We anticipate this medulloblastoma transcriptomic subtype classifier will be broadly applicable to the cancer research and clinical communities.

annoFuse: an R Package to annotate, prioritize, and interactively explore putative oncogenic RNA fusions.

BACKGROUND: Gene fusion events are significant sources of somatic variation across adult and pediatric cancers and are some of the most clinically-effective therapeutic targets, yet low consensus of RNA-Seq fusion prediction algorithms makes therapeutic prioritization difficult. In addition, events such as polymerase read-throughs, mis-mapping due to gene homology, and fusions occurring in healthy normal tissue require informed filtering, making it difficult for researchers and clinicians to rapidly discern gene fusions that might be true underlying oncogenic drivers of a tumor and in some cases, appropriate targets for therapy. RESULTS: We developed annoFuse, an R package, and shinyFuse, a companion web application, to annotate, prioritize, and explore biologically-relevant expressed gene fusions, downstream of fusion calling. We validated annoFuse using a random cohort of TCGA RNA-Seq samples (N = 160) and achieved a 96% sensitivity for retention of high-confidence fusions (N = 603). annoFuse uses FusionAnnotator annotations to filter non-oncogenic and/or artifactual fusions. Then, fusions are prioritized if previously reported in TCGA and/or fusions containing gene partners that are known oncogenes, tumor suppressor genes, COSMIC genes, and/or transcription factors. We applied annoFuse to fusion calls from pediatric brain tumor RNA-Seq samples (N = 1028) provided as part of the Open Pediatric Brain Tumor Atlas (OpenPBTA) Project to determine recurrent fusions and recurrently-fused genes within different brain tumor histologies. annoFuse annotates protein domains using the PFAM database, assesses reciprocality, and annotates gene partners for kinase domain retention. As a standard function, reportFuse enables generation of a reproducible R Markdown report to summarize filtered fusions, visualize breakpoints and protein domains by transcript, and plot recurrent fusions within cohorts. Finally, we created shinyFuse for algorithm-agnostic interactive exploration and plotting of gene fusions. CONCLUSIONS: annoFuse provides standardized filtering and annotation for gene fusion calls from STAR-Fusion and Arriba by merging, filtering, and prioritizing putative oncogenic fusions across large cancer datasets, as demonstrated here with data from the OpenPBTA project. We are expanding the package to be widely-applicable to other fusion algorithms and expect annoFuse to provide researchers a method for rapidly evaluating, prioritizing, and translating fusion findings in patient tumors.

Diagnosing Cornelia de Lange syndrome and related neurodevelopmental disorders using RNA sequencing.

PURPOSE: Neurodevelopmental disorders represent a frequent indication for clinical exome sequencing. Fifty percent of cases, however, remain undiagnosed even upon exome reanalysis. Here we show RNA sequencing (RNA-seq) on human B-lymphoblastoid cell lines (LCL) is highly suitable for neurodevelopmental Mendelian gene testing and demonstrate the utility of this approach in suspected cases of Cornelia de Lange syndrome (CdLS). METHODS: Genotype-Tissue Expression project transcriptome data for LCL, blood, and brain were assessed for neurodevelopmental Mendelian gene expression. Detection of abnormal splicing and pathogenic variants in these genes was performed with a novel RNA-seq diagnostic pipeline and using a validation CdLS-LCL cohort (n = 10) and test cohort of patients who carry a clinical diagnosis of CdLS but negative genetic testing (n = 5). RESULTS: LCLs share isoform diversity of brain tissue for a large subset of neurodevelopmental genes and express 1.8-fold more of these genes compared with blood (LCL, n = 1706; whole blood, n = 917). This enables testing of more than 1000 genetic syndromes. The RNA-seq pipeline had 90% sensitivity for detecting pathogenic events and revealed novel diagnoses such as abnormal splice products in NIPBL and pathogenic coding variants in BRD4 and ANKRD11. CONCLUSION: The LCL transcriptome enables robust frontline and/or reflexive diagnostic testing for neurodevelopmental disorders.

Enrichment of Targetable Mutations in the Relapsed Neuroblastoma Genome.

Neuroblastoma is characterized by a relative paucity of recurrent somatic mutations at diagnosis. However, recent studies have shown that the mutational burden increases at relapse, likely as a result of clonal evolution of mutation-carrying cells during primary treatment. To inform the development of personalized therapies, we sought to further define the frequency of potentially actionable mutations in neuroblastoma, both at diagnosis and after chemotherapy. We performed a retrospective study to determine mutation frequency, the only inclusion criterion being availability of cancer gene panel sequencing data from Foundation Medicine. We analyzed 151 neuroblastoma tumor samples: 44 obtained at diagnosis, 42 at second look surgery or biopsy for stable disease after chemotherapy, and 59 at relapse (6 were obtained at unknown time points). Nine patients had multiple tumor biopsies. ALK was the most commonly mutated gene in this cohort, and we observed a higher frequency of suspected oncogenic ALK mutations in relapsed disease than at diagnosis. Patients with relapsed disease had, on average, a greater number of mutations reported to be recurrent in cancer, and a greater number of mutations in genes that are potentially targetable with available therapeutics. We also observed an enrichment of reported recurrent RAS/MAPK pathway mutations in tumors obtained after chemotherapy. Our data support recent evidence suggesting that neuroblastomas undergo substantial mutational evolution during therapy, and that relapsed disease is more likely to be driven by a targetable oncogenic pathway, highlighting that it is critical to base treatment decisions on the molecular profile of the tumor at the time of treatment. However, it will be necessary to conduct prospective clinical trials that match sequencing results to targeted therapeutic intervention to determine if cancer genomic profiling improves patient outcomes.

Aggressive triple negative breast cancers have unique molecular signature on the basis of mitochondrial genetic and functional defects.

Metastatic breast cancer is a leading cause of cancer-related deaths in women worldwide. Patients with triple negative breast cancer (TNBCs), a highly aggressive tumor subtype, have a particularly poor prognosis. Multiple reports demonstrate that altered content of the multicopy mitochondrial genome (mtDNA) in primary breast tumors correlates with poor prognosis. We earlier reported that mtDNA copy number reduction in breast cancer cell lines induces an epithelial-mesenchymal transition associated with metastasis. However, it is unknown whether the breast tumor subtypes (TNBC, Luminal and HER2+) differ in the nature and amount of mitochondrial defects and if mitochondrial defects can be used as a marker to identify tumors at risk for metastasis. By analyzing human primary tumors, cell lines and the TCGA dataset, we demonstrate a high degree of variability in mitochondrial defects among the tumor subtypes and TNBCs, in particular, exhibit higher frequency of mitochondrial defects, including reduced mtDNA content, mtDNA sequence imbalance (mtRNR1:ND4), impaired mitochondrial respiration and metabolic switch to glycolysis which is associated with tumorigenicity. We identified that genes involved in maintenance of mitochondrial structural and functional integrity are differentially expressed in TNBCs compared to non-TNBC tumors. Furthermore, we identified a subset of TNBC tumors that contain lower expression of epithelial splicing regulatory protein (ESRP)-1, typical of metastasizing cells. The overall impact of our findings reported here is that mitochondrial heterogeneity among TNBCs can be used to identify TNBC patients at risk of metastasis and the altered metabolism and metabolic genes can be targeted to improve chemotherapeutic response.

The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity.

The systematic translation of cancer genomic data into knowledge of tumour biology and therapeutic possibilities remains challenging. Such efforts should be greatly aided by robust preclinical model systems that reflect the genomic diversity of human cancers and for which detailed genetic and pharmacological annotation is available. Here we describe the Cancer Cell Line Encyclopedia (CCLE): a compilation of gene expression, chromosomal copy number and massively parallel sequencing data from 947 human cancer cell lines. When coupled with pharmacological profiles for 24 anticancer drugs across 479 of the cell lines, this collection allowed identification of genetic, lineage, and gene-expression-based predictors of drug sensitivity. In addition to known predictors, we found that plasma cell lineage correlated with sensitivity to IGF1 receptor inhibitors; AHR expression was associated with MEK inhibitor efficacy in NRAS-mutant lines; and SLFN11 expression predicted sensitivity to topoisomerase inhibitors. Together, our results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents. The generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of 'personalized' therapeutic regimens.

Activation of a metabolic gene regulatory network downstream of mTOR complex 1.

Aberrant activation of the mammalian target of rapamycin complex 1 (mTORC1) is a common molecular event in a variety of pathological settings, including genetic tumor syndromes, cancer, and obesity. However, the cell-intrinsic consequences of mTORC1 activation remain poorly defined. Through a combination of unbiased genomic, metabolomic, and bioinformatic approaches, we demonstrate that mTORC1 activation is sufficient to stimulate specific metabolic pathways, including glycolysis, the oxidative arm of the pentose phosphate pathway, and de novo lipid biosynthesis. This is achieved through the activation of a transcriptional program affecting metabolic gene targets of hypoxia-inducible factor (HIF1alpha) and sterol regulatory element-binding protein (SREBP1 and SREBP2). We find that SREBP1 and 2 promote proliferation downstream of mTORC1, and the activation of these transcription factors is mediated by S6K1. Therefore, in addition to promoting protein synthesis, mTORC1 activates specific bioenergetic and anabolic cellular processes that are likely to contribute to human physiology and disease.

The functional variant rs34330 of CDKN1B is associated with risk of neuroblastoma.

The genetic aetiology of sporadic neuroblastoma is still largely unknown. We have identified diverse neuroblastoma susceptibility loci by genomewide association studies (GWASs); however, additional SNPs that likely contribute to neuroblastoma susceptibility prompted this investigation for identification of additional variants that are likely hidden among signals discarded by the multiple testing corrections used in the analysis of genomewide data. There is evidence suggesting the CDKN1B, coding for the cycle inhibitor p27Kip1, is involved in neuroblastoma. We thus assess whether genetic variants of CDKN1B are associated with neuroblastoma. We imputed all possible genotypes across CDKN1B locus on a discovery case series of 2101 neuroblastoma patients and 4202 genetically matched controls of European ancestry. The most significantly associated rs34330 was analysed in an independent Italian cohort of 311 cases and 709 controls. In vitro functional analysis was carried out in HEK293T and in neuroblastoma cell line SHEP-2, both transfected with pGL3-CDKN1B-CC or pGL3-CDKN1B-TT constructs. We identified an association of the rs34330 T allele (-79C/T) with the neuroblastoma risk (Pcombined = 0.002; OR = 1.17). The risk allele (T) of this single nucleotide polymorphism led to a lower transcription rate in cells transfected with a luciferase reporter driven by the polymorphic p27Kip1 promoter (P < 0.05). Three independent sets of neuroblastoma tumours carrying -79TT genotype showed a tendency towards lower CDKN1B mRNA levels. Our study shows that a functional variant, associated with a reduced CDKN1B gene transcription, influences neuroblastoma susceptibility.

Calcium-activated chloride channel ANO1 promotes breast cancer progression by activating EGFR and CAMK signaling.

The calcium-activated chloride channel anoctamin 1 (ANO1) is located within the 11q13 amplicon, one of the most frequently amplified chromosomal regions in human cancer, but its functional role in tumorigenesis has remained unclear. The 11q13 region is amplified in ∼15% of breast cancers. Whether ANO1 is amplified in breast tumors, the extent to which gene amplification contributes to ANO1 overexpression, and whether overexpression of ANO1 is important for tumor maintenance have remained unknown. We have found that ANO1 is amplified and highly expressed in breast cancer cell lines and primary tumors. Amplification of ANO1 correlated with disease grade and poor prognosis. Knockdown of ANO1 in ANO1-amplified breast cancer cell lines and other cancers bearing 11q13 amplification inhibited proliferation, induced apoptosis, and reduced tumor growth in established cancer xenografts. Moreover, ANO1 chloride channel activity was important for cell viability. Mechanistically, ANO1 knockdown or pharmacological inhibition of its chloride-channel activity reduced EGF receptor (EGFR) and calmodulin-dependent protein kinase II (CAMKII) signaling, which subsequently attenuated AKT, v-src sarcoma viral oncogene homolog (SRC), and extracellular signal-regulated kinase (ERK) activation in vitro and in vivo. Our results highlight the involvement of the ANO1 chloride channel in tumor progression and provide insights into oncogenic signaling in human cancers with 11q13 amplification, thereby establishing ANO1 as a promising target for therapy in these highly prevalent tumor types.

The Myc-miR-17-92 axis amplifies B-cell receptor signaling via inhibition of ITIM proteins: a novel lymphomagenic feed-forward loop.

The c-Myc oncoprotein regulates >15% of the human transcriptome and a limited number of microRNAs (miRNAs). Here, we establish that in a human B-lymphoid cell line, Myc-repressed, but not Myc-stimulated, genes are significantly enriched for predicted binding sites of Myc-regulated miRNAs, primarily those comprising the Myc-activated miR-17~92 cluster. Notably, gene set enrichment analysis demonstrates that miR-17∼92 is a major regulator of B-cell receptor (BCR) pathway components. Many of them are immunoreceptor tyrosine inhibitory motif (ITIM)-containing proteins, and ITIM proteins CD22 and FCGR2B were found to be direct targets of miR-17∼92. Consistent with the propensity of ITIM proteins to recruit phosphatases, either MYC or miR-17~92 expression was necessary to sustain phosphorylation of spleen tyrosine kinase (SYK) and the B-cell linker protein (BLNK) upon ligation of the BCR. Further downstream, stimulation of the BCR response by miR-17-92 resulted in the enhanced calcium flux and elevated levels of Myc itself. Notably, inhibition of the miR-17~92 cluster in diffuse large B-cell lymphoma (DLBCL) cell lines diminished the BCR response as measured by SYK and BLNK phosphorylation. Conversely, human DLBCLs of the BCR subtype express higher Myc and mir17hg transcript levels than other subtypes. Hence, the Myc-miR-17-92-BCR axis, frequently affected by genomic rearrangements, constitutes a novel lymphomagenic feed-forward loop.

Genomic and functional comparison of mesenchymal stromal cells prepared using two isolation methods.

BACKGROUND AIMS: Mesenchymal stromal cells (MSCs) have been applied to patients in cell therapy for various diseases. Recently, we introduced a novel MSC separation filter device which could yield approximately 2.5-fold more MSCs from bone marrow in a closed system compared with the conventional open density gradient centrifugation method. MSCs isolated with these two methods were phenotypically similar and met the criteria defining human MSC proposed by the International Society for Cellular Therapy. However, these criteria do not reflect the functional capacity of MSCs. It has been shown that the donor, source, isolation method, culture condition and cryopreservation of MSCs have potential to alter their therapeutic efficacy. To determine the equivalency of MSCs isolated by these two methods, we compared their genomic profiles as an index of their biologic potential and evaluated their growth promoting potential as an index of function. METHODS: The gene expression profiles of human MSCs isolated from 5 healthy donors with two distinct methods were obtained from microarray analyses. The functional activity of freshly expanded/cryopreserved MSCs from these two isolation methods was evaluated using an in vitro chondrocyte proliferation assay. RESULTS: Freshly expanded MSCs isolated by these two methods were found to exhibit similar gene expression profiles and equivalent therapeutic effects, while freshly thawed, cryopreserved MSCs lacked all measureable therapeutic activity. CONCLUSIONS: The MSC separation device generates genomically and functionally equivalent MSCs compared with the conventionally isolated MSCs, although freshly thawed, cryopreserved MSCs, isolated by either method, are devoid of activity in our bioassay.

A proteogenomic surfaceome study identifies DLK1 as an immunotherapeutic target in neuroblastoma.

Cancer immunotherapies produce remarkable results in B cell malignancies; however, optimal cell surface targets for many solid cancers remain elusive. Here, we present an integrative proteomic, transcriptomic, and epigenomic analysis of tumor and normal tissues to identify biologically relevant cell surface immunotherapeutic targets for neuroblastoma, an often-fatal childhood cancer. Proteogenomic analyses reveal sixty high-confidence candidate immunotherapeutic targets, and we prioritize delta-like canonical notch ligand 1 (DLK1) for further study. High expression of DLK1 directly correlates with a super-enhancer. Immunofluorescence, flow cytometry, and immunohistochemistry show robust cell surface expression of DLK1. Short hairpin RNA mediated silencing of DLK1 in neuroblastoma cells results in increased cellular differentiation. ADCT-701, a DLK1-targeting antibody-drug conjugate (ADC), shows potent and specific cytotoxicity in DLK1-expressing neuroblastoma xenograft models. Since high DLK1 expression is found in several adult and pediatric cancers, our study demonstrates the utility of a proteogenomic approach and credentials DLK1 as an immunotherapeutic target.

A proteogenomic surfaceome study identifies DLK1 as an immunotherapeutic target in neuroblastoma.

Cancer immunotherapies have produced remarkable results in B-cell malignancies; however, optimal cell surface targets for many solid cancers remain elusive. Here, we present an integrative proteomic, transcriptomic, and epigenomic analysis of tumor specimens along with normal tissues to identify biologically relevant cell surface proteins that can serve as immunotherapeutic targets for neuroblastoma, an often-fatal childhood cancer of the developing nervous system. We apply this approach to human-derived cell lines (N=9) and cell/patient-derived xenograft (N=12) models of neuroblastoma. Plasma membrane-enriched mass spectrometry identified 1,461 cell surface proteins in cell lines and 1,401 in xenograft models, respectively. Additional proteogenomic analyses revealed 60 high-confidence candidate immunotherapeutic targets and we prioritized Delta-like canonical notch ligand 1 (DLK1) for further study. High expression of DLK1 directly correlated with the presence of a super-enhancer spanning the DLK1 locus. Robust cell surface expression of DLK1 was validated by immunofluorescence, flow cytometry, and immunohistochemistry. Short hairpin RNA mediated silencing of DLK1 in neuroblastoma cells resulted in increased cellular differentiation. ADCT-701, a DLK1-targeting antibody-drug conjugate (ADC), showed potent and specific cytotoxicity in DLK1-expressing neuroblastoma xenograft models. Moreover, DLK1 is highly expressed in several adult cancer types, including adrenocortical carcinoma (ACC), pheochromocytoma/paraganglioma (PCPG), hepatoblastoma, and small cell lung cancer (SCLC), suggesting potential clinical benefit beyond neuroblastoma. Taken together, our study demonstrates the utility of comprehensive cancer surfaceome characterization and credentials DLK1 as an immunotherapeutic target. Highlights: Plasma membrane enriched proteomics defines surfaceome of neuroblastomaMulti-omic data integration prioritizes DLK1 as a candidate immunotherapeutic target in neuroblastoma and other cancersDLK1 expression is driven by a super-enhancer DLK1 silencing in neuroblastoma cells results in cellular differentiation ADCT-701, a DLK1-targeting antibody-drug conjugate, shows potent and specific cytotoxicity in DLK1-expressing neuroblastoma preclinical models.

Transcriptional immunogenomic analysis reveals distinct immunological clusters in paediatric nervous system tumours.

BACKGROUND: Cancer immunotherapies including immune checkpoint inhibitors and Chimeric Antigen Receptor (CAR) T-cell therapy have shown variable response rates in paediatric patients highlighting the need to establish robust biomarkers for patient selection. While the tumour microenvironment in adults has been widely studied to delineate determinants of immune response, the immune composition of paediatric solid tumours remains relatively uncharacterized calling for investigations to identify potential immune biomarkers. METHODS: To inform immunotherapy approaches in paediatric cancers with embryonal origin, we performed an immunogenomic analysis of RNA-seq data from 925 treatment-naïve paediatric nervous system tumours (pedNST) spanning 12 cancer types from three publicly available data sets. RESULTS: Within pedNST, we uncovered four broad immune clusters: Paediatric Inflamed (10%), Myeloid Predominant (30%), Immune Neutral (43%) and Immune Desert (17%). We validated these clusters using immunohistochemistry, methylation immune inference and segmentation analysis of tissue images. We report shared biology of these immune clusters within and across cancer types, and characterization of specific immune cell frequencies as well as T- and B-cell repertoires. We found no associations between immune infiltration levels and tumour mutational burden, although molecular cancer entities were enriched within specific immune clusters. CONCLUSIONS: Given the heterogeneity of immune infiltration within pedNST, our findings suggest personalized immunogenomic profiling is needed to guide selection of immunotherapeutic strategies.

OpenPBTA: The Open Pediatric Brain Tumor Atlas.

Pediatric brain and spinal cancers are collectively the leading disease-related cause of death in children; thus, we urgently need curative therapeutic strategies for these tumors. To accelerate such discoveries, the Children's Brain Tumor Network (CBTN) and Pacific Pediatric Neuro-Oncology Consortium (PNOC) created a systematic process for tumor biobanking, model generation, and sequencing with immediate access to harmonized data. We leverage these data to establish OpenPBTA, an open collaborative project with over 40 scalable analysis modules that genomically characterize 1,074 pediatric brain tumors. Transcriptomic classification reveals universal TP53 dysregulation in mismatch repair-deficient hypermutant high-grade gliomas and TP53 loss as a significant marker for poor overall survival in ependymomas and H3 K28-mutant diffuse midline gliomas. Already being actively applied to other pediatric cancers and PNOC molecular tumor board decision-making, OpenPBTA is an invaluable resource to the pediatric oncology community.

Targeted gene expression profiling of inverted papilloma and squamous cell carcinoma.

BACKGROUND: Inverted papilloma (IP) is a sinonasal tumor with a well-known potential for malignant transformation. The purpose of this study was to identify the genes and pathways associated with IP, with progression to carcinoma-in-situ and invasive carcinoma. METHODS: To determine genes and molecular pathways that may indicate progression and correlate with histologic changes, we analyzed six IP without dysplasia, five IP with carcinoma-in-situ, and 13 squamous cell carcinoma ex-IP by targeted sequencing. The HTG EdgeSeq Oncology Biomarker Panel coupled with next-generation sequencing was used to evaluate 2560 transcripts associated with solid tumors. RESULTS: Progressive upregulation of 11 genes were observed (CALD1, COL1A1, COL3A1, COL4A2, COL5A2, FN1, ITGA5, LGALS1, MMP11, SERPINH1, SPARC) in the order of invasive carcinoma > carcinoma-in-situ > IP without dysplasia. When compared with IP without dysplasia, more genes are differentially expressed in invasive carcinoma than carcinoma-in-situ samples (341 downregulated/333 upregulated vs. 195 downregulated/156 upregulated). Gene set enrichment analysis determined three gene sets in common between the cohorts (epithelial mesenchymal transition, extracellular matrix organization, and coagulation). CONCLUSIONS: Progressive upregulation of genes specific to IP malignant degeneration has significant clinical implications. This panel of 11 genes will improve concordance of histologic classification, which can directly impact treatment and patient outcomes. Additionally, future studies on larger tumor sets may observe upregulation in the gene panel that preceded histologic changes, which may be useful for further risk stratification.

MYC Levels Regulate Metastatic Heterogeneity in Pancreatic Adenocarcinoma.

The degree of metastatic disease varies widely among patients with cancer and affects clinical outcomes. However, the biological and functional differences that drive the extent of metastasis are poorly understood. We analyzed primary tumors and paired metastases using a multifluorescent lineage-labeled mouse model of pancreatic ductal adenocarcinoma (PDAC)-a tumor type in which most patients present with metastases. Genomic and transcriptomic analysis revealed an association between metastatic burden and gene amplification or transcriptional upregulation of MYC and its downstream targets. Functional experiments showed that MYC promotes metastasis by recruiting tumor-associated macrophages, leading to greater bloodstream intravasation. Consistent with these findings, metastatic progression in human PDAC was associated with activation of MYC signaling pathways and enrichment for MYC amplifications specifically in metastatic patients. Collectively, these results implicate MYC activity as a major determinant of metastatic burden in advanced PDAC. SIGNIFICANCE: Here, we investigate metastatic variation seen clinically in patients with PDAC and murine PDAC tumors and identify MYC as a major driver of this heterogeneity.This article is highlighted in the In This Issue feature, p. 275.