BACKGROUND Diffuse low-grade and intermediate-grade gliomas (which together make up the lower-grade gliomas, World Health Organization grades II and III) have highly variable clinical behavior that is not adequately predicted on the basis of histologic class. Some are indolent; others quickly progress to glioblastoma. The uncertainty is compounded by interobserver variability in histologic diagnosis. Mutations in IDH, TP53, and ATRX and codeletion of chromosome arms 1p and 19q (1p/19q codeletion) have been implicated as clinically relevant markers of lower-grade gliomas. METHODS We performed genomewide analyses of 293 lower-grade gliomas from adults, incorporating exome sequence, DNA copy number, DNA methylation, messenger RNA expression, microRNA expression, and targeted protein expression. These data were integrated and tested for correlation with clinical outcomes. RESULTS Unsupervised clustering of mutations and data from RNA, DNA-copy-number, and DNA-methylation platforms uncovered concordant classification of three robust, nonoverlapping, prognostically significant subtypes of lower-grade glioma that were captured more accurately by IDH, 1p/19q, and TP53 status than by histologic class. Patients who had lower-grade gliomas with an IDH mutation and 1p/19q codeletion had the most favorable clinical outcomes. Their gliomas harbored mutations in CIC, FUBP1, NOTCH1, and the TERT promoter. Nearly all lower-grade gliomas with IDH mutations and no 1p/19q codeletion had mutations in TP53 (94%) and ATRX inactivation (86%). The large majority of lower-grade gliomas without an IDH mutation had genomic aberrations and clinical behavior strikingly similar to those found in primary glioblastoma. CONCLUSIONS The integration of genomewide data from multiple platforms delineated three molecular classes of lower-grade gliomas that were more concordant with IDH, 1p/19q, and TP53 status than with histologic class. Lower-grade gliomas with an IDH mutation either had 1p/19q codeletion or carried a TP53 mutation. Most lower-grade gliomas without an IDH mutation were molecularly and clinically similar to glioblastoma. (Funded by the National Institutes of Health.)
In recent years, there has been increased interest in carcinomas of the urologic tract, that demonstrate association with the polyoma virus BK arising in immunosuppressed individuals, though the nature of this association is uncertain. To begin to understand this phenomenon, we reviewed the clinical, morphological, and immunohistochemical features of 11 carcinomas of the urologic tract, mainly urothelial (N = 9) and collecting duct carcinomas (N = 2), occurring during immunosuppression, and expressing polyoma virus T-antigen by immunohistochemistry. These were compared to a control group of carcinomas (N = 8), also arising during immunosuppression, but without T-antigen expression. A subset of both groups were also studied by hybrid capture-based DNA sequencing, probing not only for 479 cancer-related human genes, but also for polyoma and other viral sequences. Polyoma T-antigen-expressing tumors arose in 7 males and 4 females, at a median age of 66, and were aggressive, high-grade tumors with more than 1 variant morphologic pattern identified in 81% of cases, and a majority (73%) presenting at high stage category (>pT3). Diffuse polyoma T-antigen staining was seen in 91% of cases, with co-localization of aberrant p53 staining in 89%. Sequencing detected a lower number of deleterious mutations among T-antigen-expressing cases (average 1.62; 1/8 with TP53 mutation) compared to control cases (average 3.5, 2/4 with TP53 mutation). Only BK virus was detected with clonal integration and breakpoints randomly distributed across the human and viral genomes in 5/5 of the polyoma T-antigen-expressing carcinomas, and in none of the controls (0/4). In summary, these findings identify aggressive clinicopathologic features of polyoma T-antigen-expressing carcinomas, document BK as the strain involved, and associate BK viral integration with T-antigen expression and p53 aberrancy. While the apparent randomness of viral insertion sites is functionally unclear, the differing rates of mutations between T-antigen-expressing and control cases is intriguing.
572 Background: Comprehensive molecular profiling of CRC can inform treatment decisions by identifying patient subgroups at varying risks of death. Microsatellite instability (MSI) is prognostic in CRC and is used to select patients for immunotherapy. High tumor mutational burden (TMB) is associated with genomic instability and is prognostic in melanoma. Expression of p16 protein is prognostic in many tumor types. We used proteomic and genomic profiling to measure MSI, TMB and p16 in CRC tumors and to assess associations with patient survival. Methods: In archived clinical samples of CRC, 76 proteins were quantitated with mass spectrometry-based proteomics. MSI was measured by WGS and RNA-seq; unstable loci were quantified in tumor and normal samples. Cutoffs were derived via ROC analysis: high TMB was defined as > 4.5 somatic mutations per megabase; p16 as > 108 amol/ug. Patients were grouped by microsatellite status (MSI vs. microsatellite stable [MSS]), TMB (high vs. low), and p16 protein expression level. Survival curves were compared with the Mantel-Cox log-rank test. Results: Of 145 samples, 39 (27%) had high TMB and 29 (20%) had MSI. Patients with MSI tumors had longer OS than patients with MSS tumors (HR: 0.096; p = 0.003). Similarly, patients with high TMB had longer OS than those with low TMB (HR: 0.076; p < 0.001). High p16 expression was prognostic of poor survival (HR: 2.874; p = 0.019). Among patients with MSS tumors or low TMB, those with low p16 levels had longer OS than patients with high p16 (HR: 0.257; p = 0.002 and HR: 0.249; p = 0.002, for MSS and low TMB, respectively). A combination of MSS, low TMB, and low p16 also differentiated between long and short survivors (HR: 0.249; p = 0.002). These associations remained after adjustment for tumor sidedness. Further analyses of clinical correlates will be presented. Conclusions: A combination of MSS, low TMB and low p16 expression characterized a subset of patients with longer survival. This is important because patients with MSS tumors have limited treatment options but may respond to CDK4/6 inhibitors due to low p16 expression. Molecular profiling of CRC may identify patient subgroups with a relatively poor prognosis who could benefit from personalized therapy.
Desmoplastic melanomas (DMs) comprise 4% of the overall melanoma burden and have a 5-year survival rate of 85%. DMs are dermal tumors characterized by spindled melanocytes situated within abundant desomplastic stroma. These unusual histological features commonly lead to misdiagnosis. Currently, there are no known genetic drivers. A better understanding of the underlying biology of desmoplastic melanoma would provide biomarkers and therapeutic opportunities. Towards this goal, we performed low-coverage genome and high-coverage exome sequencing of 20 DMs in a discovery cohort, followed by targeted sequencing of 293 candidate genes on a validation cohort of 42 cases. Additionally, high-resolution aCGH was performed on samples from both cohorts. A high mutation burden (median 62 mutations/Mb) ranked desmoplastic melanoma among the most highly mutated cancers sequenced to date. Mutation patterns strongly indicate that UV-radiation is the dominant mutagen and implicate a superficially located cell of origin despite their predominantly intradermal presentation. Novel alterations included recurrent promoter mutations and amplification of NF-kappa B inhibitor epsilon, NFKBIE (IkBϵ) in 14.5% of samples. The promoter mutations typically affect both alleles and occur over a highly conserved DNA region. The mutations are predicted to disrupt a canonical Ets Like Factor 1 (ELF1) binding site. In total, these data imply aberrant NF-kappa B signaling as a pathogenic feature of desmoplastic melanoma. Commonly mutated oncogenes in melanomas, in particular BRAF V600E and NRAS Q61K/R, were absent. Instead, other genetic alterations known to activate the MAPK and PI3K signaling cascades were identified in 73% of samples, affecting NF1, CBL, ERBB2, MAP2K1, MAP3K1, BRAF, EGFR, PTPN11, MET, RAC1, SOS2, NRAS, and PIK3CA. Rb and p53 pathway alterations occurred respectively in 71% and 66% of tumors, affecting RB1, FBXW7, CDK4, PPP6C, CCND1, CDKN2A, TP53, and MDM2. Finally, TERT promoter mutations or amplifications occurred in 90% of tumors. The consequences of the mutations on protein expression levels was confirmed by immunostaining for NF1, EGFR, Rb, CDK4, CCND1, p16, p53, and Mdm2. Collectively, many of these oncogenic mutations are potentially druggable. In conclusion, desmoplastic melanomas harbor distinct genetic alterations that explain their unique biology, and this study illuminates genetic biomarkers and nominates targets for therapeutic intervention. Citation Format: Alan H. Shain, Maria Garrido, Thomas Botton, Eric Talevich, Iweh Yeh, Zack Sanborn, Jongsuk Chung, Nicholas Wang, Hojabr Kakavand, Graham Mann, John Thompson, Thomas Wiesner, Ritu Roy, Adam Olshen, Alexander Gagnon, Joe Gray, Nam Huh, Joe Hur, Klaus Busam, Richard Scolyer, Raymond Cho, Rajmohan Murali, Boris Bastian. Exome sequencing of desmoplastic melanoma reveals recurrent NFKBIE promoter mutations and diverse MAPK/PI3K pathway activating mutations. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2968. doi:10.1158/1538-7445.AM2015-2968
Background: We evaluate the feasibility, quality, and analytical potential of whole-transcriptome RNA-seq on over one thousand clinical FFPE tumor samples. Transcriptional profiling of RNA is used for clinical decision making in many tumor types. Clinical analysis of RNA is complicated by the common use of formalin-fixed paraffin-embedded (FFPE) tissue storage, which can cause low yield and RNA degradation. Methods: RNA was extracted from FFPE material using commercially available kits using an RNAseH based ribodeplete. Multiple libraries per sample are sequenced using standard Illumina sequencing. Bowtie2, RSEM, and custom software are used for alignment, transcript quantification, fusion detection, and variant expression analysis. Results: We observe a >85% success rate on whole transcriptome RNA-seq on our cohort of more than 1000 samples. We find reliable transcript quantification upon successful sequencing, and on a subset of samples quantify differences between FFPE and fresh-frozen material when using ribodeplete. We also compare transcriptional profiles of clinical FFPE samples to an independent set of fresh frozen, poly-A capture samples from The Cancer Genome Atlas (TCGA) and show differences between poly-A capture and ribodeplete RNA isolation methods as well as FFPE vs. FF effects. We present a robust mapping methodology for comparison of public FF poly-A dataset to our FFPE ribodeplete samples. We demonstrate that we are able to utilize this joint gene expression space to perform site of origin prediction on FFPE samples. This is especially important for clinical application in analyzing Cancer of Unknown Primary (CUP) samples as well as detecting outlier samples whose molecular features may suggest additional therapeutic avenues. Finally, we show reliable detection of fusion transcripts from FFPE RNA-seq material from whole-transcriptome analysis and expression of somatic tumor variants detected from DNA sequencing. Conclusions: Large scale sequencing of RNA from clinical FFPE materials provides reliable transcriptomic results comparable to existing public databases of RNA, enabling research on cohorts of tumors that are FFPE-banked and unavailable as frozen tissue. Citation Format: Yulia Newton, Justin Golovato, Mark Johnson, Shahrooz Rabizadeh, Zack Sanborn, Steve Benz, Charles J. Vaske. Analysis of whole transcriptome RNA-seq of large numbers of clinical FFPE samples [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 3398.
Background: As only a subset of patients respond to immunotherapies, therapeutic biomarkers are needed to predict which patients will benefit and which should be spared from potentially toxic treatment. Proteins expressed by tumor cells and by the immune microenvironment may predict response to immune checkpoint inhibitors. In non-inflamed tumors, chemotherapy and targeted therapy may stimulate an immune response thereby affecting the relationship between tumor and immune system. Combinations of immunotherapies and conventional therapies are the subject of ongoing clinical trials. We hypothesized that genomic and proteomic evaluation of multiple immune biomarkers in tumor tissue and in lymphocytes would identify a signature that could (a) differentiate between responders and non-responders to checkpoint inhibitors and (b) identify candidates for combination therapy. Methods: A pathologist marked areas of tumor and tumor-associated lymphocytes on archived tissue sections (N=2) of non-small cell lung cancer (NSCLC) and melanoma. The marked areas were microdissected and solubilized to tryptic peptides. In each liquefied tumor sample, 110 protein biomarkers, including 60 immunomarkers were quantified with a mass spectrometry-based proteomic assay. The genomic material was analyzed by whole genome sequencing (WGS) and RNA-seq. Results: Tumor and lymphocytes expressed several immunomarker proteins (eg, PDL1, IDO1, B7H3, B7-2, STAT1, GBP1). The melanoma patient’s tumor and lymphocytes expressed protein markers for response to immunotherapy (PDL1 and IDO1), and the tumor had high mutational burden as identified by WGS. Furthermore, biomarker analysis suggested sensitivity to BRAF inhibitors and resistance to platinum and taxane. The NSCLC patient’s tumor and lymphocytes expressed IDO1 protein, but genomic analysis suggested a non-inflamed tumor. Based on expression levels of ERCC1 and hENT1, one possible regimen for this patient is platinum plus gemcitabine followed by immunotherapy. In one patient, comparison of protein expression in tumor-associated lymphocytes versus distal lymphocytes (>1 mm from marked tumor areas) showed variation < 10% for 11 proteins and < 30% for 14 proteins. Conclusions: Both lymphocytes and tumor expressed immunoproteins that may be used to select patients for approved immunotherapies or clinical trials. Proteomic and genomic profiling also characterized biomarkers that inform selection of targeted therapies and chemotherapies. Ongoing clinical trials of immunotherapy and combination therapies could benefit from precise, quantitative molecular stratification of patients. Protein level cutoffs that correlate with response to immunotherapy are in development. Citation Format: Sarit Schwartz, Robert Heaton, Yuan Tian, Zack Sanborn, Shankar Sellappan, Kerry Scott, Fabiola Cecchi, Steve Benz, Todd Hembrough. Using “omics” to select immunotherapy and conventional therapy combinations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2666. doi:10.1158/1538-7445.AM2017-2666
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