Matched Normal Samples Research Articles

Abstract LB374: The microbial landscape of colorectal cancer across 11 countries

Abstract Colorectal cancer (CRC) is the second most frequent cause of cancer-related deaths globally. CRC is influenced by the colorectal microbiome, which plays a pivotal role in inflammation, DNA damage, and production of cancer-promoting metabolites. Most prior CRC microbial studies have identified multiple microbes enriched in tumor samples, but these examinations have generally focused on CRC from a specific country and have not accounted for CRC patient’s tumor site, sex, diet, or geographical location. Further, the interconnection between somatic alterations and microbiome composition has not been comprehensively explored. Here, we examine the microbiome profiles of 963 whole-genome sequenced CRC and their matched-normal blood from 11 different countries with highly varying age-standardized incidence rate (ASR) for colorectal cancer. Matched normal blood samples exhibited a strong intra- and inter-microbial heterogeneity across the 11 countries. In contrast, while CRC tumors exhibited a higher microbial diversity when compared to their matched-normal samples, the top 10 most abundant CRC taxa were strikingly similar across all countries, suggesting a global convergence of the CRC microbiome composition. Moreover, a positive correlation was observed between the colorectal cancer ASR across 11 countries and the CRC microbial diversity (rho=0.91, p-value: 0.0002), suggesting that countries with high incidence rates also have high microbial diversities. After accounting for age, shipment batch, sex, and country-specific effects on the microbiome composition, we observed a core set of five microbial species enriched in CRC across all countries, which included Bacteroides fragilis,Phocaeicola Vulgatus, Faecalibacterium Prausnitzii, Fusobacterium Nucleatum, and Escherichia Coli. A strong correlation (rho=0.84, p-value: 0.0013) was observed between Bacteroides fragilis and a novel mutational signature characterized by A/T[C>G]T and T[T>G]N substitutions. No association was observed between polyketide synthase gene complex (pks)+ microbe and the presence of the pks-derived colibactin mutational signatures. Furthermore, additional associations were observed between the microbiome and other mutational signatures and driver genes. Overall, this study delivers a global atlas of the microbial landscapes of CRC genomes across 11 countries and their links with genetic changes and epidemiological risk factors. Citation Format: Ammal Abbasi, Ludmil Alexandrov. The microbial landscape of colorectal cancer across 11 countries [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB374.

GASOLINE: detecting germline and somatic structural variants from long-reads data

Long-read sequencing allows analyses of single nucleic-acid molecules and produces sequences in the order of tens to hundreds kilobases. Its application to whole-genome analyses allows identification of complex genomic structural-variants (SVs) with unprecedented resolution. SV identification, however, requires complex computational methods, based on either read-depth or intra- and inter-alignment signatures approaches, which are limited by size or type of SVs. Moreover, most currently available tools only detect germline variants, thus requiring separate computation of sample pairs for comparative analyses. To overcome these limits, we developed a novel tool (Germline And SOmatic structuraL varIants detectioN and gEnotyping; GASOLINE) that groups SV signatures using a sophisticated clustering procedure based on a modified reciprocal overlap criterion, and is designed to identify germline SVs, from single samples, and somatic SVs from paired test and control samples. GASOLINE is a collection of Perl, R and Fortran codes, it analyzes aligned data in BAM format and produces VCF files with statistically significant somatic SVs. Germline or somatic analysis of 30×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes $$\\end{document} sequencing coverage experiments requires 4–5 h with 20 threads. GASOLINE outperformed currently available methods in the detection of both germline and somatic SVs in synthetic and real long-reads datasets. Notably, when applied on a pair of metastatic melanoma and matched-normal sample, GASOLINE identified five genuine somatic SVs that were missed using five different sequencing technologies and state-of-the art SV calling approaches. Thus, GASOLINE identifies germline and somatic SVs with unprecedented accuracy and resolution, outperforming currently available state-of-the-art WGS long-reads computational methods.

Identification and prediction of m7G-related Alzheimer's disease subtypes: insights from immune infiltration and machine learning models.

Alzheimer's disease (AD) is a complex and progressive neurodegenerative disorder that primarily affects older individuals. N7-methylguanosine (m7G) is a common RNA chemical modification that impacts the development of numerous diseases. Thus, our work investigated m7G-related AD subtypes and established a predictive model. The datasets for AD patients, including GSE33000 and GSE44770, were obtained from the Gene Expression Omnibus (GEO) database, which were derived from the prefrontal cortex of the brain. We performed differential analysis of m7G regulators and examined the immune signatures differences between AD and matched-normal samples. Consensus clustering was employed to identify AD subtypes based on m7G-related differentially expressed genes (DEGs), and immune signatures were explored among different clusters. Furthermore, we developed four machine learning models based on the expression profiles of m7G-related DEGs and identified five important genes from the optimal model. We evaluated the predictive power of the 5-gene-based model using an external AD dataset (GSE44770). A total of 15 genes related to m7G were found to be dysregulated in patients with AD compared to non-AD patients. This finding suggests that there are differences in immune characteristics between these two groups. Based on the differentially expressed m7G regulators, we categorized AD patients into two clusters and calculated the ESTIMATE score for each cluster. Cluster 2 exhibited a higher ImmuneScore than Cluster 1. We performed the receiver operating characteristic (ROC) analysis to compare the performance of four models, and we found that the Random Forest (RF) model had the highest AUC value of 1.000. Furthermore, we tested the predictive efficacy of a 5-gene-based RF model on an external AD dataset and obtained an AUC value of 0.968. The nomogram, calibration curve, and decision curve analysis (DCA) confirmed the accuracy of our model in predicting AD subtypes. The present study systematically examines the biological significance of m7G methylation modification in AD and investigates its association with immune infiltration characteristics. Furthermore, the study develops potential predictive models to assess the risk of m7G subtypes and the pathological outcomes of patients with AD, which can facilitate risk classification and clinical management of AD patients.

Abstract PR008: Landscape of actionable mutations and outcomes in metastatic non-small cell lung cancer across age, sex, and race

Abstract Introduction: Lung cancer is the leading cause of cancer-related death due to frequent diagnosis at an advanced stage, especially among underserved populations. Given the marked heterogeneity in disease course for metastatic non-small cell lung cancer (mNSCLC), we sought to further explore its distribution of genomic alterations and outcomes across population subgroups. Methods: Clinicogenomics data were downloaded from the MSK-MET cohort study, one of the largest publicly accessible databases of metastatic cancer featuring 25775 patients in the February 2022 release. Tumor mutation burden (TMB) was quantified as number of non-synonymous mutations per megabase (Mb) sequenced. Categorical variables were compared using the χ2-test. Analysis of overall survival (OS) was performed using Cox proportional hazards regression. Results: Between 2013 and 2020, tumor and matched-normal samples from 4710 adult patients (58% female) with mNSCLC (86% adenocarcinoma) were obtained for genomic characterization. Median age at diagnosis was 67 years (IQR 59–73) and median OS was 38 months (95% CI 34–40 months). Smoking status and treatment history were unavailable. Patients self-identified as non-Hispanic white (76%), Asian (10%), Black (5%), Hispanic (4%), Native American (1%), or none of the above (1%). Compared to patients of other races, Hispanic patients were more likely to be diagnosed with mNSCLC prior to age 50 (17% vs. 7%, P<0.001); Asian patients had a higher frequency of EGFR mutations (56% vs. 22%, P<0.001), lower frequency of KRAS mutations (11% vs. 32%, P<0.001), and longer OS (HR 0.84, 95% CI 0.72–0.98, P=0.026); Black patients had greater TMB (9% vs. 5% with ≥20 mutations per Mb, P=0.019). Every actionable mutation was more common in non-squamous cell carcinoma (SCC) than SCC, except ROS1 fusions (4% vs. 7%, P<0.001). Across and within each race group, men were more likely to possess no actionable mutations compared to women (29% [range 22–67%] vs. 16% [range 5–20%], P<0.05). In multivariable analysis, male sex, diagnosis earlier than age 50 or later than age 70, non-adenocarcinoma histology, greater TMB, and absence of actionable mutations involving EGFR, ALK, MET, or RET were independently associated with worse OS (P<0.05). Conclusions: In this large clinicogenomic analysis of mNSCLC, men were more likely to have no actionable mutations and worse OS. Diagnosis prior to age 50 (most common among Hispanic patients) and greater TMB (most common among Black patients) also independently conferred worse OS. These findings highlight the wide heterogeneity of molecular features and outcomes in mNSCLC across age, sex, and race, underscoring the need to further individualize workup and management. Citation Format: David C. Qian, Conor E. Steuer, Sibo Tian, Jennifer W. Carlisle, Ticiana A. Leal, Madhusmita Behera, Jeffrey D. Bradley, Suresh S. Ramalingam, Kristin A. Higgins. Landscape of actionable mutations and outcomes in metastatic non-small cell lung cancer across age, sex, and race [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PR008.

Estimating tumor mutational burden from RNA-sequencing without a matched-normal sample

Detection of somatic mutations using patients sequencing data has many clinical applications, including the identification of cancer driver genes, detection of mutational signatures, and estimation of tumor mutational burden (TMB). We have previously developed a tool for detection of somatic mutations using tumor RNA and a matched-normal DNA. Here, we further extend it to detect somatic mutations from RNA sequencing data without a matched-normal sample. This is accomplished via a machine-learning approach that classifies mutations as either somatic or germline based on various features. When applied to RNA-sequencing of >450 melanoma samples high precision and recall are achieved, and both mutational signatures and driver genes are correctly identified. Finally, we show that RNA-based TMB is significantly associated with patient survival, showing similar or higher significance level as compared to DNA-based TMB. Our pipeline can be utilized in many future applications, analyzing novel and existing datasets where only RNA is available.

LiquidCNA: Tracking subclonal evolution from longitudinal liquid biopsies using somatic copy number alterations

SummaryCell-free DNA (cfDNA) measured via liquid biopsies provides a way for minimally invasive monitoring of tumor evolutionary dynamics during therapy. Here we present liquidCNA, a method to track subclonal evolution from longitudinally collected cfDNA samples sequenced through cost-effective low-pass whole-genome sequencing. LiquidCNA utilizes somatic copy number alteration (SCNA) to simultaneously genotype and quantify the size of the dominant subclone without requiring B-allele frequency information, matched-normal samples, or prior knowledge on the genetic identity of the emerging clone. We demonstrate the accuracy of liquidCNA in synthetically generated sample sets and in vitro mixtures of cancer cell lines. In vivo application in patients with metastatic lung cancer reveals the progressive emergence of a novel tumor subpopulation. LiquidCNA is straightforward to use, is computationally inexpensive, and enables continuous monitoring of subclonal evolution to understand and control-therapy-induced resistance.

Application of a colorectal cancer ctDNA methylation test in endocrine cancers.

e15533 Background: Assays for circulating tumor DNA (ctDNA) have shown utility for cancer detection and management. It is important to demonstrate cancer specificity of targeted ctDNA biomarkers. Detection of methylated BCAT1 and IKZF1 ctDNA has shown high sensitivity for colorectal cancer (CRC). The aim of this study was to investigate whether hypermethylation of these two biomarkers is also present in prostate or breast adenocarcinoma (PCa or BCa) tissues, and if they are detectable as ctDNA from such cancer patients. Methods: A subset of TCGA data comprising matched tumor and normal samples from PRAD (n = 50), BRCA (n = 90) and COADREAD (n = 44) cohorts were accessed to interrogate DNA methylation (450K) at CpG probes covered by the BCAT1/ IKZF1 ctDNA assay (cg10764357 and cg07589773/cg18607529, respectively). Linear regression of BCAT1/ IKZF1 methylation and tumor staging was performed for cases with AJCC staging data (PRAD n = 503; BRCA n = 788; COADREAD n = 284). Blood was collected from BCa (n = 32) or PCa (n = 101) patients prior to starting treatment at Flinders Medical Centre (South Australia). DNA isolated from plasma was bisulphite-converted and assayed for BCAT1/ IKZF1 methylation. Age-adjusted comparisons of ctDNA positivity were made with blood results from N = 310 pre-treatment CRC patients (60% male), as well as male (N = 344) and female (N = 383) controls with a clear colonoscopy and no history of cancer. Results: BCAT1 and IKZF1 were significantly hypermethylated in PCa and CRC tumors compared to matched normal tissues (Table). Conversely, BCAT1/ IKZF1 CpG probes were hypomethylated in breast tumors compared to matched normal samples. There was no correlation between hypermethylation in IKZF1/ BCAT1 and stage of PCa or CRC. In contrast to PCa in silico findings of hypermethylation, BCAT1/IKZF1 ctDNA methylation was only positive in 7/101 PCa blood samples (6.9%; 95%CI 3.2-13.9%). Three of 32 BCa blood samples (9.4%; 95%CI 2.5-25%) were positive for BCAT1/IKZF1 methylation. These positivity rates were not significantly different to controls at 8.5% for females (p = 0.80 vs BCa) and 8.2% for males (p = 0.73 vs PCa), but all were significantly lower than that observed in CRC cases (59.0%, 183/310; p < 0.001). Conclusions: While interrogation of TCGA datasets revealed IKZF1 and BCAT1 hypermethylation in prostate tumors, detection rate of these biomarkers in blood from PCa patients was not higher than that of non-cancer controls. Likewise, the BCAT1/IKZF1 ctDNA assay positivity rate in BCa patients was also no different to non-cancer controls. These findings highlight the specificity of methylated BCAT1 and IKZF1 ctDNA for detection of CRC.[Table: see text]

Abstract B18: Exome scale liquid biopsy monitoring of putative neoantigens and genomic biomarkers in patients on anti-PD-1 therapy in squamous cell carcinoma of the head and neck

Abstract Monitoring treatment response and potential resistance mechanisms to therapy with typical liquid biopsy panels can be limited by the relatively small number of genes profiled. The limited scope can result in missed therapeutic biomarkers such as neoantigens, which may change dynamically with treatment, as well as potentially missed resistance mechanisms and pathways not typically covered by existing panels. To address these shortcomings, we applied an exome scale liquid biopsy monitoring platform, NeXT Liquid Biopsy, to analyze head and neck squamous cell carcinoma (HNSCC) patients who have received anti-PD1 therapy. Using this platform we sought to (1) identify and monitor neoantigen changes in cell free DNA (cfDNA) as a complement to tumor biopsy-derived neoantigens, (2) compare the differences in putative neoantigens identified in tissue and cfDNA, and (3) identify additional biomarker correlations between cfDNA and solid tumor biopsies. Pre- and post-intervention matched tumor, normal, and plasma samples were obtained from a pilot cohort of 9 patients with HNSCC. Following initial sample collection all patients received a single dose of nivolumab, followed by definitive resection of the primary tumor mass approximately one month later when possible, or a second biopsy where resection was impractical (resection, n=5; biopsy, n=4). Solid tumor and matched normal samples were profiled using ImmunoID NeXT, an augmented exome/transcriptome platform and analysis pipeline. For the plasma samples, we performed exome-scale cfDNA profiling with the ImmunoID NeXT Liquid Biopsy platform to detect somatic variants. Data from these two platforms were compared with corresponding clinical findings. We observed a strong concordance of somatic events between the plasma and tumor in both pre- and post-treatment timepoints. Median post-treatment neoantigen burden was reduced in solid tumor, but increased in cfDNA, when compared to pretreatment timepoints. HLA-specific loss of heterozygosity (LOH) was identified in a number of subjects, likely resulting in reduced neoepitope presentation in those cases. These changes were accompanied by increased immune cell infiltration in the tumor following treatment, with no changes to the CD8+/Treg cell ratio, suggesting consistent immunoregulatory influence. Exome-wide somatic events were reliably detected in cfDNA, providing additional potential biomarkers to complement biomarkers identified in solid tumor. As we increase our cohort size we expect that identification of biomarkers from both exome-scale tissue biopsy and cfDNA will provide a more comprehensive view into therapeutic response and resistance mechanisms in HNSCC patients missed with typical liquid biopsy panels. Citation Format: Charles W. Abbott, Nikita Bedi, Simo V. Zhang, Robin Li, Rachel Marty Pyke, Eric Levy, Rebecca Chernock, Mena Mansour, John B. Sunwoo, A. Dimitrios Colevas, Richard Chen, Sean M. Boyle. Exome scale liquid biopsy monitoring of putative neoantigens and genomic biomarkers in patients on anti-PD-1 therapy in squamous cell carcinoma of the head and neck [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2019 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(3 Suppl):Abstract nr B18.

A systematic evaluation of copy number alterations detection methods on real SNP array and deep sequencing data

BackgroundThe Copy Number Alterations (CNAs) are discovered to be tightly associated with cancers, so accurately detecting them is one of the most important tasks in the cancer genomics. A series of CNAs detection methods have been proposed and new ones are still being developed. Due to the complexity of CNAs in cancers, no CNAs detection method has been accepted as the gold standard caller. Several evaluation works have made attempts to reveal typical CNAs detection methods’ performance. Limited by the scale of evaluation data, these different comparison works don’t reach a consensus and the researchers are still confused on how to choose one proper CNAs caller for their analysis. Therefore, it needs a more comprehensive evaluation of typical CNAs detection methods’ performance.ResultsIn this work, we use a large-scale real dataset from CAGEKID consortium to evaluate total 12 typical CNAs detection methods. These methods are most widely used in cancer researches and always used as benchmark for the newly proposed CNAs detection methods. This large-scale dataset comprises of SNP array data on 94 samples and the whole genome sequencing data on 10 samples. Evaluations are comprehensively implemented in current scenarios of CNAs detection, which include that detect CNAs on SNP array data, on sequencing data with tumor and normal matched samples and on sequencing data with single tumor sample. Three SNP based methods are firstly ranked. Subsequently, the best SNP based method’s results are used as benchmark to compare six matched samples based methods and three single tumor sample based methods in terms of the preprocessing, recall rate, Jaccard index and segmentation characteristics.ConclusionsOur survey thoroughly reveals 12 typical methods’ superiority and inferiority. We explain why methods show specific characteristics from a methodological standpoint. Finally, we present the guiding principle for choosing one proper CNAs detection method under specific conditions. Some unsolved problems and expectations are also addressed for upcoming CNAs detection methods.

Abstract 1660: Identification of allelic imbalance utilizing heterozygous genotype allele frequencies and intensities

Abstract Allelic imbalance (AI) events, such as amplification, deletion or copy-neutral loss-of-heterozygosity (cn-LOH) can result in the activations of oncogenes or inactivations of tumor suppressor genes that are critical to the process of carcinogenesis and metastasis. However, tumor samples often have low tumor-cellularity and small subclones that require sensitive and robust algorithm for AI detections. To overcome this challenge, our lab has developed an original software application hapLOH (Vattathil and Scheet, 2013) that identifies AI with high sensitivity in SNP array data by utilizing heterozygous genotype allele frequencies in SNP array data using a Hidden Markov Model. Motivated by the plethora of next-generation sequencing (NGS) data, we carried this logic and functionality and developed hapLOHseq (San Lucas et al, 2016) for detection of subtle AI in NGS data using reference and alternate allele read depths and a set of haplotype estimates based on 1000 genome data. Recently, we sought to improve AI detection and provide support for different data types by developing haploh-cn. Haploh-cn extends our previous tools by supporting both SNP array and NGS data, and by incorporating intensity data and Log R ratios (LRR) into the underlying Hidden Markov Model for SNP array data, and incorporating sequencing depth for NGS data. In order to evaluate haploh-cn’s performances, we have downloaded The Cancer Genome Atlas Lung Adenocarcinoma whole exome sequencing data and corresponding Affymetrix SNP6 array data. Then, we simulated tumor cellularity by performing in-silico dilution of NGS and SNP array data. For NGS data, we down sampled tumor sequencing BAM files and mixed in matched-normal sequencing reads. For SNP6 array data, we combined the adjusted B allele frequencies of heterozygous sites in the tumor sample and matched-normal sample. Using the AI events detected in the undiluted tumor samples as the gold standard, we assessed the performance of haploh-cn in the computational diluted samples. Our results showed that haploh-cn had high sensitivity without sacrificing specificity in diluted tumor samples. In summary, haploh-cn is a robust and powerful method for profiling subtle AI in NGS and SNP array data. Citation Format: Kyle Chang, Francis A. San Lucas, Zuhal Ozcan, Smruthy Sivakumar, Yasminka A. Jakubek, Richard G. Fowler, Paul Scheet. Identification of allelic imbalance utilizing heterozygous genotype allele frequencies and intensities [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1660.

Pan-Cancer Analysis Reveals Differential Susceptibility of Bidirectional Gene Promoters to DNA Methylation, Somatic Mutations, and Copy Number Alterations.

Bidirectional gene promoters affect the transcription of two genes, leading to the hypothesis that they should exhibit protection against genetic or epigenetic changes in cancer. Therefore, they provide an excellent opportunity to learn about promoter susceptibility to somatic alteration in tumors. We tested this hypothesis using data from genome-scale DNA methylation (14 cancer types), simple somatic mutation (10 cancer types), and copy number variation profiling (14 cancer types). For DNA methylation, the difference in rank differential methylation between tumor and tumor-adjacent normal matched samples based on promoter type was tested by the Wilcoxon rank sum test. Logistic regression was used to compare differences in simple somatic mutations. For copy number alteration, a mixed effects logistic regression model was used. The change in methylation between non-diseased tissues and their tumor counterparts was significantly greater in single compared to bidirectional promoters across all 14 cancer types examined. Similarly, the extent of copy number alteration was greater in single gene compared to bidirectional promoters for all 14 cancer types. Furthermore, among 10 cancer types with available simple somatic mutation data, bidirectional promoters were slightly more susceptible. These results suggest that selective pressures related with specific functional impacts during carcinogenesis drive the susceptibility of promoter regions to somatic alteration.

Abstract A26: Analysis of alternative splicing events in high- and low-grade bladder tumors

Abstract Functioning primarily in the rearrangement of identical pre-mRNA into different molecules, the alternative splicing (AS) contributes to the organism proteomic diversity. There are still unknown AS events, especially the aberrant splicing events that are associated to nonfunctional final products or tumorigenesis. For instance, hallmarks, such as apoptosis, metastasis, and angiogenesis, of certain types of cancer are known to be affected by some kind of aberrant splicing event. As examples, for BCLX gene, antiapoptotic and proapoptotic isoforms have been discovered, and, for the VEGFA gene, changes between proangiogenic and antiangiogenic isoforms expression have been detected in tumors and normal-matched samples, as well as among several distinct tissues. We hypothesize that AS events can also be associated and contribute to the origin and maintenance of specific tumor types and sub-types. We characterized the AS events in 35 samples of primary bladder tumors, classified as 20 high-grade (cells poorly differentiated, invasive and metastatic tumor), 11 low-grade (cell differentiated, noninvasive tumor), and 5 normal tissues. To access the AS events, we generated in total 2.5 billion of reads using RNAseq. The next step was mapping these reads against the human reference genome, using a set of in-house and publicly available pipelines to detect AS events in high-/low-grade bladder samples and normal tissues. As result, we observed 992 significant splicing events on high-grade tumors as compared to normal samples, 796 significant events on low-grade versus normal samples, and 871 significant events on low-grade versus high-grade tumors. After looking for some of these events in combinations of tumor grades and control, we found a tumor-specific isoform for RPS24 gene and five splicing events of genes RPL13A, RPL3, RPL37A, RPS27A, and RPL34 that are unique to high-grade tumors. We believe that these low-/high-grade AS specific events should be further studied in order to contribute to the understanding and to the development of new drugs for bladder tumors presenting low- or high-grade. Citation Format: André Luiz Ventura Sávio, Ricardo Piuco, Katia Ramos Moreira Leite, Daisy Maria Favero Salvadori, Pedro Alexandre Favoretto Galante, Luiz Otavio Ferraz Penalva. Analysis of alternative splicing events in high- and low-grade bladder tumors [abstract]. In: Proceedings of the AACR International Conference held in cooperation with the Latin American Cooperative Oncology Group (LACOG) on Translational Cancer Medicine; May 4-6, 2017; São Paulo, Brazil. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(1_Suppl):Abstract nr A26.

Altered peritumoral microRNA expression predicts head and neck cancer patients with a high risk of recurrence

Head and neck squamous cell carcinoma is typically characterized by a high incidence of local recurrences. It has been extensively shown that mucosa from head and neck squamous cell carcinoma patients carries both genetic and gene expression alterations, which are mostly attributable to major etiologic agents of head and neck squamous cell carcinoma. We previously identified a signature of microRNAs (miRNAs) whose high expression in tumors is predictive of recurrence. Here, we investigated whether the deregulation of miRNA expression in the tumor-surrounding mucosa is correlated to disease recurrence. Specifically, comparing the miRNA expression in matched tumoral, peritumoral, and normal tissues collected from head and neck squamous cell carcinoma patients, we identified 35 miRNAs that are deregulated in both tumoral and peritumoral tissues as compared with normal matched samples. Four of these composed a miRNA signature that predicts head and neck squamous cell carcinoma local recurrence independently from prognostic clinical variables. The predictive power of the miRNA signature increased when using the expression levels derived from both the peritumoral and the tumoral tissues. The expression signal of the miRNAs composing the predictive signature correlated with the transcriptional levels of genes mostly associated with proliferation. Our results show that expression of miRNAs in tumor-surrounding mucosa may strongly contribute to the identification of head and neck squamous cell carcinoma patients at high risk of local recurrence.

DNA sequencing of the small bowel adenocarcinomas to identify targetable ErbB2 mutations.

e15800 Background: Small bowel adenocarcinoma (SBA) is a rare malignancy of the digestive tract with limited knowledge about its genetic alterations. Methods: Eighteen tumor and normal matched samples were sequenced using the whole-exome-Illumina platform. Various agnostic analysis methods were used to identify relevant somatic mutations and the results were compared with the available TCGA datasets. To test potential targetable mutations we developed eight patient-derived xenografts (PDX) and three cell lines from freshly-collected primary or metastatic SBA tissues. Two kinase-activating ErbB2 mutations (V842I and Y803H) and one wild-type (wt) ErbB2 (n = 30) PDX models were used to measure the effect of Dacomitinib (Daco) on tumor growth. ErbB2-mutant tumor-derived cell lines were tested for Daco and Lapatinib (Lapa) response in-vitro. Reverse-phase-protein-arrays (RPPA) were used to identify molecular changes. Results: Several unexpected oncogenic mechanisms were suggested by the pattern of somatic mutations across the dataset, including mutations in the Notch and Hippo pathways. In addition, we found 6/18 APC truncating mutations exclusive to mutations in ZNRF3 or RNF43 genes, suggesting that non-APC wnt-activating mechanisms are important in SBA, while considered a minority in CRC. Importantly, 6/18 samples displayed ErbB2 mutations, of which 4 resided in the kinase domain, D769Y, V777L, Y803H and V842I. Nanomolar doses of both Lapa and Daco significantly inhibited ErbB2-mutants’ cell proliferation in-vitro. Target inhibition was confirmed by the RPPA results: EGFR-Y1068, ErbB2-Y1248 and PKCα-S657 dephosphorylation, PCNA reduction and PARP cleavage increase. In-vivo-administered Daco resulted in significant tumor reduction in ErbB2-V841I (39%, p = 0.03) and ErbB2-Y803H (59%, p = 0.03) tumors, and had no anti-tumor effect on wt-ErbB2 tumors. Conclusions: The generation of in-vitro and in-vivo model systems from rare cancers is possible and provides a valuable resource into understanding potentially relevant targetable mutations. Our findings suggest that SBA patients with ErbB2-activating mutations should be considered for clinical trials targeting this alteration.

CLImAT-HET: detecting subclonal copy number alterations and loss of heterozygosity in heterogeneous tumor samples from whole-genome sequencing data

BackgroundCopy number alterations (CNA) and loss of heterozygosity (LOH) represent a large proportion of genetic structural variations of cancer genomes. These aberrations are continuously accumulated during the procedure of clonal evolution and patterned by phylogenetic branching. This invariably results in the emergence of multiple cell populations with distinct complement of mutational landscapes in tumor sample. With the advent of next-generation sequencing technology, inference of subclonal populations has become one of the focused interests in cancer-associated studies, and is usually based on the assessment of combinations of somatic single-nucleotide variations (SNV), CNA and LOH. However, cancer samples often have several inherent issues, such as contamination of normal stroma, tumor aneuploidy and intra-tumor heterogeneity. Addressing these critical issues is imperative for accurate profiling of clonal architecture.MethodsWe present CLImAT-HET, a computational method designed for capturing clonal diversity in the CNA/LOH dimensions by taking into account the intra-tumor heterogeneity issue, in the case where a reference or matched normal sample is absent. The algorithm quantitatively represents the clonal identification problem using a factorial hidden Markov model, and takes an integrated analysis of read counts and allele frequency data. It is able to infer subclonal CNA and LOH events as well as the fraction of cells harboring each event.ResultsThe results on simulated datasets indicate that CLImAT-HET has high power to identify CNA/LOH segments, it achieves an average accuracy of 0.87. It can also accurately infer proportion of each clonal population with an overall Pearson correlation coefficient of 0.99 and a mean absolute error of 0.02. CLImAT-HET shows significant advantages when compared with other existing methods. Application of CLImAT-HET to 5 primary triple negative breast cancer samples demonstrates its ability to capture clonal diversity in the CAN/LOH dimensions. It detects two clonal populations in one sample, and three clonal populations in one other sample.ConclusionsCLImAT-HET, a novel algorithm is introduced to infer CNA/LOH segments from heterogeneous tumor samples. We demonstrate CLImAT-HET’s ability to accurately recover clonal compositions using tumor WGS data without a match normal sample.

Evaluation of microsatellite instability (MSI) status in 11,573 diverse solid tumors using comprehensive genomic profiling (CGP).

1523Background: MSI status is predictive of anti-PD-1/L1 therapy efficacy independent of tumor histology. This study describes the development and validation of a novel computational method to assess MSI status. In addition, we sought to determine the MSI prevalence and mutation characteristics in the cohort by applying the method to 11,573 clinical solid tumor cases previously assayed with CGP. Methods: To determine MSI status, 114 intronic homopolymer repeat loci with adequate coverage on the CGP panel were analyzed for length variability and compiled into an overall MSI score via principal components analysis. Translation of the MSI score to MSI-H (microsatellite high) or MSS (microsatellite stable) was established using training data. A matched-normal sample is not required, and CGP is accurate when tumor content is at least 20%. Results: Our methodology was validated in 69 samples with MSI status (20 MSI-H, 49 MSS) previously determined by standard clinical testing (PCR or immunohistochemistry). Conc...

Discriminating somatic and germline mutations in tumor DNA samples without matching normals.

Tumor analyses commonly employ a correction with a matched normal (MN), a sample from healthy tissue of the same individual, in order to distinguish germline mutations from somatic mutations. Since the majority of variants found in an individual are thought to be common within the population, we constructed a set of 931 samples from healthy, unrelated individuals, originating from two different sequencing platforms, to serve as a virtual normal (VN) in the absence of such an associated normal sample. Our approach removed (1) >96% of the germline variants also removed by the MN sample and (2) a large number (2%–8%) of additional variants not corrected for by the associated normal. The combination of the VN with the MN improved the correction for polymorphisms significantly, with up to ∼30% compared with MN and ∼15% compared with VN only. We determined the number of unrelated genomes needed in order to correct at least as efficiently as the MN is about 200 for structural variations (SVs) and about 400 for single-nucleotide variants (SNVs) and indels. In addition, we propose that the removal of common variants with purely position-based methods is inaccurate and incurs additional false-positive somatic variants, and more sophisticated algorithms, which are capable of leveraging information about the area surrounding variants, are needed for optimal accuracy. Our VN correction method can be used to analyze any list of variants, regardless of sequencing platform of origin. This VN methodology is available for use on our public Galaxy server.

Abstract PR06: The ampullary adenocarcinoma, its molecular characterization and differentiation from the pancreatic ductal adenocarcinoma, duodenal adenocarcinoma, and cholangiocarcinoma

Abstract The ampulla of Vater is a region where the pancreatic duct, biliary duct, and intestinal duodenum converge creating a complex epithelial cellular environment from which the ampullary adenocarcinomas (AMPAC) arise to form a group of histopathologically heterogenous tumors. The confluence of three organs at the ampulla of Vater gives rise to complexity in diagnosis, treatment and outcomes. Previous studies have focused mainly on marker identification to differentiate between the AMPAC intestinal and pancreatobiliary subtypes. It is established by immunohistochemistry and expression analysis that the intestinal subtype correlates with better prognosis. However, no large scale genomic profiling has been untaken. To better understand the diverse make-up of the AMPAC subtypes and to potentially help guide treatment, we analyzed 94 AMPAC of intestinal, pancreatobiliary, and mixed subtypes; 33 cholangioadenocarcinomas (CAC); and 11 duodenal adenocarcinomas (DUOAC) and their normal matched samples by whole exome sequencing, SNP array and RNA seq. Whole exome revealed that AMPAC, DUOAC, and CAC shared in common with pancreatic ductal adenocarcinoma (PDAC) high mutation rate in KRAS and TP53, loss and mutation in CDKN2A and SMAD4. ATM, a key component of the DNA damage repair pathway significantly mutated in PDAC, was also mutated in AMPAC, but not in DUOA or CAC. In contrast, loss of function mutation in NF1, an important component of the KRAS pathway, rarely mutated in PDAC, was significantly mutated (12%) and exhibited allelic loss uniquely in AMPAC. Mutations in major gene components of the PIK and wnt signaling, observed in intestinal cancers were detected in DUOAC and AMPAC but not in CAC. The AMPAC, mutations in these genes were found in both intestinal and pancreatobiliary subtypes. We also observed microsatellite instability (MSI), a common feature of gastrointestinal cancers, in 5% AMPAC, 36% of DUOAC , and 3% CAC tumors. The MSI tumors showed mutation frequencies of 17 to 113 mutations per megabase compared to 0.1 to 9.3 mutations per megabase in non-MSI tumors. In our previous study of 94 PDAC, none were MSI. Copy number analysis by SNP array revealed frequent arm-level loss in chromosome 9p, 17p, and 18q in common with all cancers. The patters of copy number change differed most clearly between CAC and DUOAC; AMPAC shared characteristics of both. Gene expression by RNAseq revealed a strong intestinal signature, including high expression of the colon cancer biomarker KRT20, in the intestinal AMPAC but not in pancreatobiliary subtype. The theme that emerges from our study is that the AMPAC shares more similarity in molecular characteristics with gastrointestinal than pancreatic ductal cancers. Interestingly, the histological subtypes of intestinal (30), pancreatobilliary (43) or mixed (10) tumors recognized by pathologists is not strongly reflected in the molecular properties of the AMPAC tumors. Pancreatobiliary subtype shows mutations associated with intestinal tumors but not PDAC, for example 32% of pancreatobilary tumors harbor PIK3CA, PIK3R1, PTEN or wnt pathway members such as CTNNB1, and APC. Patient outcomes for these various mutation profiles are under investigation. From a clinical and therapeutic perspective, targets potentially include ERB-family, ALK and BRCA1/2, mutated tumors, which collectively represent 20% of the patients. An additional 5% of patients are MSI. MSI is a favorable prognostic marker in colorectal and endometrial cancers, and has therapeutic implications. In conclusion, future diagnosis and treatment decision may gain insight by including screening for specific mutations in the characterization of AMPAC. This abstract is also presented as Poster A1. Citation Format: Marie-Claude Gingras, Amber Johns, Anthony Gill, Michael Overman, Christian Pilarsky, Sean Grimmond, Andrew Biankin, David Wheeler, Richard Gibbs. The ampullary adenocarcinoma, its molecular characterization and differentiation from the pancreatic ductal adenocarcinoma, duodenal adenocarcinoma, and cholangiocarcinoma. [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Innovations in Research and Treatment; May 18-21, 2014; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2015;75(13 Suppl):Abstract nr PR06.

Annotation of Genes Having Candidate Somatic Mutations in Acute Myeloid Leukemia with Whole-Exome Sequencing Using Concept Lattice Analysis

In cancer genome studies, the annotation of newly detected oncogene/tumor suppressor gene candidates is a challenging process. We propose using concept lattice analysis for the annotation and interpretation of genes having candidate somatic mutations in whole-exome sequencing in acute myeloid leukemia (AML). We selected 45 highly mutated genes with whole-exome sequencing in 10 normal matched samples of the AML-M2 subtype. To evaluate these genes, we performed concept lattice analysis and annotated these genes with existing knowledge databases.

Necrotizing vasculitis and ulcerative colitis.

Abstract Objectives Two of the main target tissues of SARS-coronavirus 2 are the oral cavity pharynx-larynx epithelium, the main virus entry site, and the lung epithelium. The virus enters host cells through binding of the Spike protein to ACE2 receptor and subsequent S priming by the TMPRSS2 protease. Herein we aim to assess differences in both ACE2 and TMPRSS2 expression in normal tissues from oral cavity-pharynx-larynx and lung tissues as well as neoplastic tissues from the same histological areas. The information provided in this study may contribute to better understanding of SARS-coronavirus 2 ability to interact with different biological systems and contributes to cumulative knowledge on potential mechanisms to inhibit its diffusion. Materials and Methods The study has been conducted using The Cancer Genome Atlas (TCGA) and the Regina Elena Institute (IRE) databases and validated by experimental model in HNSCC and Lung cancer cells. Data from one COVID19 positive patient who was operated on for HNSCC was also included. We have analyzed 478 tumor samples and 44 normal samples from TCGA HNSCC cohort for whom both miRNA and mRNA sequencing was available. The dataset included 391 HPV- and 85 HPV+ cases, with 331 P53 mutated and 147 P53 wild type cases respectively. 352 out of 478 samples were male and 126 female. In IRE cohort we analyzed 66 tumor samples with matched normal sample for miRNA profiling and 23 tumor\normal matched samples for mRNA profiling. 45 out of 66 tumors from IRE cohort were male and 21 female, 38 were P53 mutated and 27 wild type. Most patients (63 of 66) in IRE cohort were HPV negative. Normalized TCGA HNSCC gene expression and miRNA expression data were obtained from Broad Institute TCGA Genome Data Analysis Center (http://gdac.broadinstitute.org/). mRNA expression data from IRE cohort used in this study has been deposited to NCBI’s Gene Expression Omnibus and is accessible through GEO series accession number GSE107591. In order to inference about potential molecular modulation of TMPRSS2, we also included miRNAs expression for the 66 IRE cohort matched tumor and normal samples from Agilent platform. DNA methylation data for TCGA tumors were obtained from Wanderer (http://maplab.imppc.org/wanderer/). We used miRWalk and miRNet web tools for miRNA-target interaction prediction and pathway enrichment analysis. The correlation and regression analyses as well as the miRNA and gene modulation and the survival analysis were conducted using Matlab R2019. Results TMPRSS2 expression in HNSCC was significantly reduced compared to the normal tissues and had a prognostic value in HNSCC patients. Reduction of TMPRSS2 expression was more evident in women than in men, in TP53 mutated versus wild TP53 tumors as well as in HPV negative patients compared to HPV positive counterparts. Functionally, we assessed the multivariate effect on TMPRSS2 in a single regression model. We observed that all variables had an independent effect on TMPRSS2 in HNSCC patients with HPV negative, TP53 mutated status and with elevated TP53-dependent Myc-target genes associated with low TMPRSS2 expression. Investigation of the molecular modulation of TMPRSS2 in both HNSCC and lung cancers revealed that expression of microRNAs targeting TMPRSS2 anti-correlated in both TCGA and IRE HNSCC datasets, while there was not evidence of TMPRSS2 promoter methylation in both tumor cohorts. Interestingly, the anti-correlation between microRNAs and TMPRSS2 expression was corroborated by testing this association in a SARS-CoV-2 positive HNSCC patient. Conclusions Collectively, these findings suggest that tumoral tissues, herein exemplified by HNSCC and lung cancers might be more resistant to SARS-CoV-2 infection due to reduced expression of TMPRSS2. The protective mechanism might occur, at least partially, through the aberrant activation of TMPRSS2 targeting microRNAs; thereby providing strong evidence on the role of non-coding RNA molecule in host viral infection. These observations may help to better assess the frailty of SARS-CoV-2 positive cancer patients.