Comparison of the performance of two targeted metagenomic virus capture probe-based methods using reference control materials and clinical samples.

Viral enrichment by probe hybridization has been reported to significantly increase the sensitivity of viral metagenomics. This study compares the analytical performance of two targeted metagenomic virus capture probe-based methods: (i) SeqCap EZ HyperCap by Roche (ViroCap) and (ii) Twist Comprehensive Viral Research Panel workflow, for diagnostic use. Sensitivity, specificity, and limit of detection were analyzed using 25 synthetic viral sequences spiked in increasing proportions of human background DNA, eight clinical samples, and American Type Culture Collection (ATCC) Virome Virus Mix. Sensitivity and specificity were 95% and higher for both methods using the synthetic and reference controls as gold standard. Combining thresholds for viral sequence read counts and genome coverage [respectively 500 reads per million (RPM) and 10% coverage] resulted in optimal prediction of true positive results. Limits of detection were approximately 50-500 copies/mL for both methods as determined by ddPCR. Increasing proportions of spike-in cell-free human background sequences up to 99.999% (50 ng/mL) did not negatively affect viral detection, suggesting effective capture of viral sequences. These data show analytical performances in ranges applicable to clinical samples, for both probe hybridization metagenomic approaches. This study supports further steps toward more widespread use of viral metagenomics for pathogen detection, in clinical and surveillance settings using low biomass samples. IMPORTANCE: Viral metagenomics has been gradually applied for broad-spectrum pathogen detection of infectious diseases, surveillance of emerging diseases, and pathogen discovery. Viral enrichment by probe hybridization methods has been reported to significantly increase the sensitivity of viral metagenomics. During the past years, a specific hybridization panel distributed by Roche has been adopted in a broad range of different clinical and zoonotic settings. Recently, Twist Bioscience has released a new hybridization panel targeting human and animal viruses. This is the first report comparing the performance of viral metagenomic hybridization panels.

Enrichment of colibactin-associated mutational signatures in unexplained colorectal polyposis patients.

BACKGROUND: Colibactin, a genotoxin produced by polyketide synthase harboring (pks+) bacteria, induces double-strand breaks and chromosome aberrations. Consequently, enrichment of pks+Escherichia coli in colorectal cancer and polyposis suggests a possible carcinogenic effect in the large intestine. Additionally, specific colibactin-associated mutational signatures; SBS88 and ID18 in the Catalogue of Somatic Mutations in Cancer database, are detected in colorectal carcinomas. Previous research showed that a recurrent APC splice variant perfectly fits SBS88. METHODS: In this study, we explore the presence of colibactin-associated signatures and fecal pks in an unexplained polyposis cohort. Somatic targeted Next-Generation Sequencing (NGS) was performed for 379 patients. Additionally, for a subset of 29 patients, metagenomics was performed on feces and mutational signature analyses using Whole-Genome Sequencing (WGS) on Formalin-Fixed Paraffin Embedded (FFPE) colorectal tissue blocks. RESULTS: NGS showed somatic APC variants fitting SBS88 or ID18 in at least one colorectal adenoma or carcinoma in 29% of patients. Fecal metagenomic analyses revealed enriched presence of pks genes in patients with somatic variants fitting colibactin-associated signatures compared to patients without variants fitting colibactin-associated signatures. Also, mutational signature analyses showed enrichment of SBS88 and ID18 in patients with variants fitting these signatures in NGS compared to patients without. CONCLUSIONS: These findings further support colibactins ability to mutagenize colorectal mucosa and contribute to the development of colorectal adenomas and carcinomas explaining a relevant part of patients with unexplained polyposis.

Integrative multiomics enhancer activity profiling identifies therapeutic vulnerabilities in cholangiocarcinoma of different etiologies.

OBJECTIVES: Cholangiocarcinoma (CCA) is a heterogeneous malignancy with high mortality and dismal prognosis, and an urgent clinical need for new therapies. Knowledge of the CCA epigenome is largely limited to aberrant DNA methylation. Dysregulation of enhancer activities has been identified to affect carcinogenesis and leveraged for new therapies but is uninvestigated in CCA. Our aim is to identify potential therapeutic targets in different subtypes of CCA through enhancer profiling. DESIGN: Integrative multiomics enhancer activity profiling of diverse CCA was performed. A panel of diverse CCA cell lines, patient-derived and cell line-derived xenografts were used to study identified enriched pathways and vulnerabilities. NanoString, multiplex immunohistochemistry staining and single-cell spatial transcriptomics were used to explore the immunogenicity of diverse CCA. RESULTS: We identified three distinct groups, associated with different etiologies and unique pathways. Drug inhibitors of identified pathways reduced tumour growth in in vitro and in vivo models. The first group (ESTRO), with mostly fluke-positive CCAs, displayed activation in estrogen signalling and were sensitive to MTOR inhibitors. Another group (OXPHO), with mostly BAP1 and IDH-mutant CCAs, displayed activated oxidative phosphorylation pathways, and were sensitive to oxidative phosphorylation inhibitors. Immune-related pathways were activated in the final group (IMMUN), made up of an immunogenic CCA subtype and CCA with aristolochic acid (AA) mutational signatures. Intratumour differences in AA mutation load were correlated to intratumour variation of different immune cell populations. CONCLUSION: Our study elucidates the mechanisms underlying enhancer dysregulation and deepens understanding of different tumourigenesis processes in distinct CCA subtypes, with potential significant therapeutics and clinical benefits.

mSigHdp: hierarchical Dirichlet process mixture modeling for mutational signature discovery.

Mutational signatures are characteristic patterns of mutations caused by endogenous or exogenous mutational processes. These signatures can be discovered by analyzing mutations in large sets of samples-usually somatic mutations in tumor samples. Most programs for discovering mutational signatures are based on non-negative matrix factorization (NMF). Alternatively, signatures can be discovered using hierarchical Dirichlet process (HDP) mixture models, an approach that has been less explored. These models assign mutations to clusters and view each cluster as being generated from the signature of a particular mutational process. Here, we describe mSigHdp, an improved approach to using HDP mixture models to discover mutational signatures. We benchmarked mSigHdp and state-of-the-art NMF-based approaches on four realistic synthetic data sets. These data sets encompassed 18 cancer types. In total, they contained 3.5 × 107 single-base-substitution mutations representing 32 signatures and 6.1 × 106 small insertion and deletion mutations representing 13 signatures. For three of the four data sets, mSigHdp had the best positive predictive value for discovering mutational signatures, and for all four data sets, it had the best true positive rate. Its CPU usage was similar to that of the NMF-based approaches. Thus, mSigHdp is an important and practical addition to the set of tools available for discovering mutational signatures.

The sensitivity of pan-TRK immunohistochemistry in solid tumours: A meta-analysis.

INTRODUCTION: Since the approval of neurotrophic tropomyosin receptor kinase (NTRK) tyrosine kinase inhibitors for fist-line advanced stage pan-cancer therapy, pathologists and molecular biologists have been facing a complex question: how should the large volume of specimens be screened for NTRK fusions? Immunohistochemistry is fast and cheap, but the sensitivity compared to RNA NGS is unclear. METHODS: We performed RNA-based next-generation sequencing on 1,329 cases and stained 24 NTRK-rearranged cases immunohistochemically with pan-TRK (ERP17341). Additionally, we performed a meta-analysis of the literature. After screening 580 studies, 200 additional NTRK-rearranged cases from 13 studies, analysed with sensitive molecular diagnostics as well as pan-TRK IHC, were included. RESULTS: In the included 224 NTRK-rearranged solid tumours, the sensitivity for pan-TRK IHC was 82% and the false-negative rate was 18%. NTRK3 fusions had more false negatives (27%) compared to NTRK1 (6%) and NTRK2 (14%) (p = 0.0006). Membranous, nuclear and peri-nuclear staining patterns strongly correlated with different fusion products, with membranous staining being more prevalent in NTRK1 and NTRK2, nuclear in NTRK3, and perinuclear in NTRK1. CONCLUSION: Despite a reduction in the number of molecular analysis, using pan-TRK immunohistochemistry as a prescreening method to detect NTRK fusions in solid tumours will miss 18% of all NTRK-fused cases (especially involving NTRK3). Therefore, the most comprehensive and optimal option to detect NTRK fusions is to perform molecular testing on all eligible cases. However, in case of financial or logistical limitations, an immunohistochemistry-first approach is defensible in tumours with a low prevalence of NTRK fusions.

Mutational analysis of driver genes defines the colorectal adenoma: in situ carcinoma transition.

A large proportion of colorectal carcinomas (CRC) evolve from colorectal adenomas. However, not all individuals with colonic adenomas have a risk of CRC substantially higher than those of the general population. The aim of the study was to determine the differences or similarities of mutation profile among low- and high-grade adenomas and in situ carcinoma with detailed follow up. We have investigated the mutation spectrum of well-known genes involved in CRC (such as APC, BRAF, EGFR, NRAS, KRAS, PIK3CA, POLE, POLD1, SMAD4, PTEN, and TP53) in a large, well-defined series of 96 adenomas and in situ carcinomas using a high-throughput genotyping technique. Besides, the microsatellite instability and APC and MLH1 promoter methylation were studied as well. We observed a high frequency of pathogenic variants in the studied genes. The APC, KRAS and TP53 mutation frequencies were slightly lower in adenoma samples than in in situ carcinoma samples. Further, when we stratified mutation frequency based on the grade, the frequency distribution was as follows: low-grade adenoma-high-grade adenomas-in situ carcinoma: APC gene 42.9-56.0-54.5%; KRAS gene 32.7-32.0-45.5%; TP53 gene 8.2-20.0-18.2%. The occurrence of KRAS mutation was associated with the presence of villous histology and methylation of the APC promoter was significantly associated with the presence of POLE genetic variations. However, no association was noticed with the presence of any singular mutation and occurrence of subsequent adenoma or CRC. Our data supports the multistep model of gradual accumulation of mutations, especially in the driver genes, such as APC, TP53 and KRAS.

Accuracy of mutational signature software on correlated signatures.

Mutational signatures are characteristic patterns of mutations generated by exogenous mutagens or by endogenous mutational processes. Mutational signatures are important for research into DNA damage and repair, aging, cancer biology, genetic toxicology, and epidemiology. Unsupervised learning can infer mutational signatures from the somatic mutations in large numbers of tumors, and separating correlated signatures is a notable challenge for this task. To investigate which methods can best meet this challenge, we assessed 18 computational methods for inferring mutational signatures on 20 synthetic data sets that incorporated varying degrees of correlated activity of two common mutational signatures. Performance varied widely, and four methods noticeably outperformed the others: hdp (based on hierarchical Dirichlet processes), SigProExtractor (based on multiple non-negative matrix factorizations over resampled data), TCSM (based on an approach used in document topic analysis), and mutSpec.NMF (also based on non-negative matrix factorization). The results underscored the complexities of mutational signature extraction, including the importance and difficulty of determining the correct number of signatures and the importance of hyperparameters. Our findings indicate directions for improvement of the software and show a need for care when interpreting results from any of these methods, including the need for assessing sensitivity of the results to input parameters.

Recurrent mutations in topoisomerase IIα cause a previously undescribed mutator phenotype in human cancers.

Topoisomerases nick and reseal DNA to relieve torsional stress associated with transcription and replication and to resolve structures such as knots and catenanes. Stabilization of the yeast Top2 cleavage intermediates is mutagenic in yeast, but whether this extends to higher eukaryotes is less clear. Chemotherapeutic topoisomerase poisons also elevate cleavage, resulting in mutagenesis. Here, we describe p.K743N mutations in human topoisomerase hTOP2α and link them to a previously undescribed mutator phenotype in cancer. Overexpression of the orthologous mutant protein in yeast generated a characteristic pattern of 2- to 4-base pair (bp) duplications resembling those in tumors with p.K743N. Using mutant strains and biochemical analysis, we determined the genetic requirements of this mutagenic process and showed that it results from trapping of the mutant yeast yTop2 cleavage complex. In addition to 2- to 4-bp duplications, hTOP2α p.K743N is also associated with deletions that are absent in yeast. We call the combined pattern of duplications and deletions ID_TOP2α. All seven tumors carrying the hTOP2α p.K743N mutation showed ID_TOP2α, while it was absent from all other tumors examined (n = 12,269). Each tumor with the ID_TOP2α signature had indels in several known cancer genes, which included frameshift mutations in tumor suppressors PTEN and TP53 and an activating insertion in BRAF. Sequence motifs found at ID_TOP2α mutations were present at 80% of indels in cancer-driver genes, suggesting that ID_TOP2α mutagenesis may contribute to tumorigenesis. The results reported here shed further light on the role of topoisomerase II in genome instability.

Highly recurrent CBS epimutations in gastric cancer CpG island methylator phenotypes and inflammation.

BACKGROUND: CIMP (CpG island methylator phenotype) is an epigenetic molecular subtype, observed in multiple malignancies and associated with the epigenetic silencing of tumor suppressors. Currently, for most cancers including gastric cancer (GC), mechanisms underlying CIMP remain poorly understood. We sought to discover molecular contributors to CIMP in GC, by performing global DNA methylation, gene expression, and proteomics profiling across 14 gastric cell lines, followed by similar integrative analysis in 50 GC cell lines and 467 primary GCs. RESULTS: We identify the cystathionine beta-synthase enzyme (CBS) as a highly recurrent target of epigenetic silencing in CIMP GC. Likewise, we show that CBS epimutations are significantly associated with CIMP in various other cancers, occurring even in premalignant gastroesophageal conditions and longitudinally linked to clinical persistence. Of note, CRISPR deletion of CBS in normal gastric epithelial cells induces widespread DNA methylation changes that overlap with primary GC CIMP patterns. Reflecting its metabolic role as a gatekeeper interlinking the methionine and homocysteine cycles, CBS loss in vitro also causes reductions in the anti-inflammatory gasotransmitter hydrogen sulfide (H2S), with concomitant increase in NF-κB activity. In a murine genetic model of CBS deficiency, preliminary data indicate upregulated immune-mediated transcriptional signatures in the stomach. CONCLUSIONS: Our results implicate CBS as a bi-faceted modifier of aberrant DNA methylation and inflammation in GC and highlights H2S donors as a potential new therapy for CBS-silenced lesions.

Mutational processes in cancer preferentially affect binding of particular transcription factors.

Protein binding microarrays provide comprehensive information about the DNA binding specificities of transcription factors (TFs), and can be used to quantitatively predict the effects of DNA sequence variation on TF binding. There has also been substantial progress in dissecting the patterns of mutations, i.e., the "mutational signatures", generated by different mutational processes. By combining these two layers of information we can investigate whether certain mutational processes tend to preferentially affect binding of particular classes of TFs. Such preferential alterations of binding might predispose to particular oncogenic pathways. We developed and implemented a method, termed "Signature-QBiC", that integrates protein binding microarray data with the signatures of mutational processes, with the aim of predicting which TFs' binding profiles are preferentially perturbed by particular mutational processes. We used Signature-QBiC to predict the effects of 47 signatures of mutational processes on 582 human TFs. Pathway analysis showed that binding of TFs involved in NOTCH1 signaling is strongly affected by the signatures of several mutational processes, including exposure to ultraviolet radiation. Additionally, toll-like-receptor signaling pathways are also vulnerable to disruption by this exposure. This study provides a novel overview of the effects of mutational processes on TF binding and the potential of these processes to activate oncogenic pathways through mutating TF binding sites.

The mutational landscape of early- and typical-onset oral tongue squamous cell carcinoma.

BACKGROUND: The incidence of oral tongue squamous cell carcinoma (OTSCC) is increasing among younger birth cohorts. The etiology of early-onset OTSCC (diagnosed before the age of 50 years) and cancer driver genes remain largely unknown. METHODS: The Sequencing Consortium of Oral Tongue Cancer was established through the pooling of somatic mutation data of oral tongue cancer specimens (n = 227 [107 early-onset cases]) from 7 studies and The Cancer Genome Atlas. Somatic mutations at microsatellite loci and Catalog of Somatic Mutations in Cancer mutation signatures were identified. Cancer driver genes were identified with the MutSigCV and WITER algorithms. Mutation comparisons between early- and typical-onset OTSCC were evaluated via linear regression with adjustments for patient-related factors. RESULTS: Two novel driver genes (ATXN1 and CDC42EP1) and 5 previously reported driver genes (TP53, CDKN2A, CASP8, NOTCH1, and FAT1) were identified. Six recurrent mutations were identified, with 4 occurring in TP53. Early-onset OTSCC had significantly fewer nonsilent mutations even after adjustments for tobacco use. No associations of microsatellite locus mutations and mutation signatures with the age of OTSCC onset were observed. CONCLUSIONS: This international, multicenter consortium is the largest study to characterize the somatic mutational landscape of OTSCC and the first to suggest differences by age of onset. This study validates multiple previously identified OTSCC driver genes and proposes 2 novel cancer driver genes. In analyses by age, early-onset OTSCC had a significantly smaller somatic mutational burden that was not explained by differences in tobacco use. LAY SUMMARY: This study identifies 7 specific areas in the human genetic code that could be responsible for promoting the development of tongue cancer. Tongue cancer in young patients (under the age of 50 years) has fewer overall changes to the genetic code in comparison with tongue cancer in older patients, but the authors do not think that this is due to differences in smoking rates between the 2 groups. The cause of increasing cases of tongue cancer in young patients remains unclear.

Multiple neoplasia in a patient with Gitelman syndrome harboring germline monoallelic MUTYH mutation.

Gitelman syndrome is a rare, recessively inherited disease characterized by chronic hypokalemia and hypomagnesemia as a result of defective electrolyte co-transport at the level of the distal convoluted tubule of the kidney. Here, we present the first report of a patient with Gitelman syndrome who developed multiple neoplasia including colorectal polyposis, synchronous colorectal cancers, recurrent breast fibroadenomata and a desmoid tumor. Whole-exome sequencing confirmed germline compound heterozygous mutations of c.179C > T and c.1326C > G in SLC12A3, and in addition, identified a monoallelic germline c.934-2A > G splice site mutation in MUTYH. In vitro, magnesium deficiency potentiated oxidative DNA damage in lymphoblastoid cell lines derived from the same patient. We postulate that monoallelic MUTYH mutations may manifest in the presence of cooperative non-genetic mechanisms, in this case possibly magnesium deficiency from Gitelman syndrome.

Multiomic analysis and immunoprofiling reveal distinct subtypes of human angiosarcoma.

Angiosarcomas are rare, clinically aggressive tumors with limited treatment options and a dismal prognosis. We analyzed angiosarcomas from 68 patients, integrating information from multiomic sequencing, NanoString immuno-oncology profiling, and multiplex immunohistochemistry and immunofluorescence for tumor-infiltrating immune cells. Through whole-genome sequencing (n = 18), 50% of the cutaneous head and neck angiosarcomas exhibited higher tumor mutation burden (TMB) and UV mutational signatures; others were mutationally quiet and non-UV driven. NanoString profiling revealed 3 distinct patient clusters represented by lack (clusters 1 and 2) or enrichment (cluster 3) of immune-related signaling and immune cells. Neutrophils (CD15+), macrophages (CD68+), cytotoxic T cells (CD8+), Tregs (FOXP3+), and PD-L1+ cells were enriched in cluster 3 relative to clusters 2 and 1. Likewise, tumor inflammation signature (TIS) scores were highest in cluster 3 (7.54 vs. 6.71 vs. 5.75, respectively; P < 0.0001). Head and neck angiosarcomas were predominant in clusters 1 and 3, providing the rationale for checkpoint immunotherapy, especially in the latter subgroup with both high TMB and TIS scores. Cluster 2 was enriched for secondary angiosarcomas and exhibited higher expression of DNMT1, BRD3/4, MYC, HRAS, and PDGFRB, in keeping with the upregulation of epigenetic and oncogenic signaling pathways amenable to targeted therapies. Molecular and immunological dissection of angiosarcomas may provide insights into opportunities for precision medicine.

A tumor-associated splice-isoform of MAP2K7 drives dedifferentiation in MBNL1-low cancers via JNK activation.

Master splicing regulator MBNL1 shapes large transcriptomic changes that drive cellular differentiation during development. Here we demonstrate that MBNL1 is a suppressor of tumor dedifferentiation. We surveyed MBNL1 expression in matched tumor/normal pairs across The Cancer Genome Atlas and found that MBNL1 was down-regulated in several common cancers. Down-regulation of MBNL1 predicted poor overall survival in breast, lung, and stomach adenocarcinomas and increased relapse and distant metastasis in triple-negative breast cancer. Down-regulation of MBNL1 led to increased tumorigenic and stem/progenitor-like properties in vitro and in vivo. A discrete set of alternative splicing events (ASEs) are shared between MBNL1-low cancers and embryonic stem cells including a MAP2K7∆exon2 splice variant that leads to increased stem/progenitor-like properties via JNK activation. Accordingly, JNK inhibition is capable of reversing MAP2K7∆exon2-driven tumor dedifferentiation in MBNL1-low cancer cells. Our work elucidates an alternative-splicing mechanism that drives tumor dedifferentiation and identifies biomarkers that predict enhanced susceptibility to JNK inhibition.