Rapid Diagnostic of Streptococcus suis in Necropsy Samples of Pigs by thrA-Based Loop-Mediated Isothermal Amplification Assay.

Streptococcus (S.) suis presents a serious threat to the pig industry as well as food safety and public health. Although several LAMP assays have been developed for the identification of S. suis, no universal assay is so far available for the field-suitable examination of clinical pig specimens. Based on the thrA housekeeping gene, a new loop-mediated isothermal amplification (LAMP) assay was developed and validated for the detection of S. suis in the brain and joints of pigs. For this LAMP assay, two different methods for the extraction of DNA from brain and joint swabs were compared. Using the LPTV boiling method, the detection limit of LAMP was 1.08 CFU/reaction, while the detection limit was 53.8 CFU/reaction using a commercial DNA extraction kit. The detection limits of thrA-LAMP in combination with the LPTV boiling method were 104-105 CFU/swab in the presence of brain tissue and 103-104 CFU/swab in the presence of joint tissue. The diagnostic quality criteria of LAMP were determined by the examination of 49 brain swabs and 34 joint swabs obtained during routine diagnostic necropsies. Applying the LPTV boiling method to brain swabs, the sensitivity, specificity, and positive and negative predictive values of thrA-LAMP were 88.0, 95.8, 95.7, and 88.5% using cultural investigation as a reference method, and 76.7, 100, 100, and 73.1% using real-time PCR as a reference method. Based on these results, the thrA-LAMP assay combined with the LPTV boiling method is suitable for rapid detection of S. suis from brain swabs.

Evolutionary history of transformation from chronic lymphocytic leukemia to Richter syndrome.

Richter syndrome (RS) arising from chronic lymphocytic leukemia (CLL) exemplifies an aggressive malignancy that develops from an indolent neoplasm. To decipher the genetics underlying this transformation, we computationally deconvoluted admixtures of CLL and RS cells from 52 patients with RS, evaluating paired CLL-RS whole-exome sequencing data. We discovered RS-specific somatic driver mutations (including IRF2BP2, SRSF1, B2M, DNMT3A and CCND3), recurrent copy-number alterations beyond del(9p21)(CDKN2A/B), whole-genome duplication and chromothripsis, which were confirmed in 45 independent RS cases and in an external set of RS whole genomes. Through unsupervised clustering, clonally related RS was largely distinct from diffuse large B cell lymphoma. We distinguished pathways that were dysregulated in RS versus CLL, and detected clonal evolution of transformation at single-cell resolution, identifying intermediate cell states. Our study defines distinct molecular subtypes of RS and highlights cell-free DNA analysis as a potential tool for early diagnosis and monitoring.

Combined PD-1, BRAF and MEK inhibition in BRAFV600E colorectal cancer: a phase 2 trial.

While BRAF inhibitor combinations with EGFR and/or MEK inhibitors have improved clinical efficacy in BRAFV600E colorectal cancer (CRC), response rates remain low and lack durability. Preclinical data suggest that BRAF/MAPK pathway inhibition may augment the tumor immune response. We performed a proof-of-concept single-arm phase 2 clinical trial of combined PD-1, BRAF and MEK inhibition with sparatlizumab (PDR001), dabrafenib and trametinib in 37 patients with BRAFV600E CRC. The primary end point was overall response rate, and the secondary end points were progression-free survival, disease control rate, duration of response and overall survival. The study met its primary end point with a confirmed response rate (24.3% in all patients; 25% in microsatellite stable patients) and durability that were favorable relative to historical controls of BRAF-targeted combinations alone. Single-cell RNA sequencing of 23 paired pretreatment and day 15 on-treatment tumor biopsies revealed greater induction of tumor cell-intrinsic immune programs and more complete MAPK inhibition in patients with better clinical outcome. Immune program induction in matched patient-derived organoids correlated with the degree of MAPK inhibition. These data suggest a potential tumor cell-intrinsic mechanism of cooperativity between MAPK inhibition and immune response, warranting further clinical evaluation of optimized targeted and immune combinations in CRC. ClinicalTrials.gov registration: NCT03668431.

The Four mRNA Bases Have Quite Different (Un)folding Free Energies, Applications to RNA Splicing and Translation Initiation with BindOligoNet.

Expression of mRNA is often regulated by the binding of a small RNA (miRNA, snoRNA, siRNA). While the pairing contribution to the net free energy is well parameterized and can be computed in O(N) time, the cost of removing pre-existing mRNA secondary structure has not received sufficient attention. Conventional methods for computing the unfolding free energy of a target mRNA are costly, scaling like the cube of the number of target bases O(N3). Here we introduce a model to describe the unfolding costs of the binding site, which features surprisingly big differences in the free energy parameters for the four bases. The model is implemented in our O(N) algorithm, BindOligoNet. Donor splice site prediction is more accurate when using our calculation of spliceosomal U1-snRNA to mRNA net binding free energy. Our base-dependent free energies also correlate with efficient ribosome docking near the start codon.

Author Correction: Cas9 activates the p53 pathway and selects for p53-inactivating mutations.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Cas9 activates the p53 pathway and selects for p53-inactivating mutations.

Cas9 is commonly introduced into cell lines to enable CRISPR-Cas9-mediated genome editing. Here, we studied the genetic and transcriptional consequences of Cas9 expression itself. Gene expression profiling of 165 pairs of human cancer cell lines and their Cas9-expressing derivatives revealed upregulation of the p53 pathway upon introduction of Cas9, specifically in wild-type TP53 (TP53-WT) cell lines. This was confirmed at the messenger RNA and protein levels. Moreover, elevated levels of DNA repair were observed in Cas9-expressing cell lines. Genetic characterization of 42 cell line pairs showed that introduction of Cas9 can lead to the emergence and expansion of p53-inactivating mutations. This was confirmed by competition experiments in isogenic TP53-WT and TP53-null (TP53-/-) cell lines. Lastly, Cas9 was less active in TP53-WT than in TP53-mutant cell lines, and Cas9-induced p53 pathway activation affected cellular sensitivity to both genetic and chemical perturbations. These findings may have broad implications for the proper use of CRISPR-Cas9-mediated genome editing.

Analyses of non-coding somatic drivers in 2,658 cancer whole genomes.

The discovery of drivers of cancer has traditionally focused on protein-coding genes1-4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5' region of TP53, in the 3' untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.

Passenger Hotspot Mutations in Cancer.

Current statistical models for assessing hotspot significance do not properly account for variation in site-specific mutability, thereby yielding many false-positives. We thus (i) detail a Log-normal-Poisson (LNP) background model that accounts for this variability in a manner consistent with models of mutagenesis; (ii) use it to show that passenger hotspots arise from all common mutational processes; and (iii) apply it to a ∼10,000-patient cohort to nominate driver hotspots with far fewer false-positives compared with conventional methods. Overall, we show that many cancer hotspot mutations recurring at the same genomic site across multiple tumors are actually passenger events, recurring at inherently mutable genomic sites under no positive selection.

RNA sequence analysis reveals macroscopic somatic clonal expansion across normal tissues.

How somatic mutations accumulate in normal cells is poorly understood. A comprehensive analysis of RNA sequencing data from ~6700 samples across 29 normal tissues revealed multiple somatic variants, demonstrating that macroscopic clones can be found in many normal tissues. We found that sun-exposed skin, esophagus, and lung have a higher mutation burden than other tested tissues, which suggests that environmental factors can promote somatic mosaicism. Mutation burden was associated with both age and tissue-specific cell proliferation rate, highlighting that mutations accumulate over both time and number of cell divisions. Finally, normal tissues were found to harbor mutations in known cancer genes and hotspots. This study provides a broad view of macroscopic clonal expansion in human tissues, thus serving as a foundation for associating clonal expansion with environmental factors, aging, and risk of disease.

Next-generation characterization of the Cancer Cell Line Encyclopedia.

Large panels of comprehensively characterized human cancer models, including the Cancer Cell Line Encyclopedia (CCLE), have provided a rigorous framework with which to study genetic variants, candidate targets, and small-molecule and biological therapeutics and to identify new marker-driven cancer dependencies. To improve our understanding of the molecular features that contribute to cancer phenotypes, including drug responses, here we have expanded the characterizations of cancer cell lines to include genetic, RNA splicing, DNA methylation, histone H3 modification, microRNA expression and reverse-phase protein array data for 1,072 cell lines from individuals of various lineages and ethnicities. Integration of these data with functional characterizations such as drug-sensitivity, short hairpin RNA knockdown and CRISPR-Cas9 knockout data reveals potential targets for cancer drugs and associated biomarkers. Together, this dataset and an accompanying public data portal provide a resource for the acceleration of cancer research using model cancer cell lines.

Comment on "DNA damage is a pervasive cause of sequencing errors, directly confounding variant identification".

Chen et al (Reports, 17 February 2017, p. 752) highlight an important problem of sequencing artifacts caused by DNA damage at the time of sample processing. However, their manuscript contains several errors that led the authors to incorrect conclusions. Moreover, the same sequencing artifacts were previously described and mitigated in The Cancer Genome Atlas and other published sequencing projects.

Widespread Chromosomal Losses and Mitochondrial DNA Alterations as Genetic Drivers in Hürthle Cell Carcinoma.

Hürthle cell carcinoma of the thyroid (HCC) is a form of thyroid cancer recalcitrant to radioiodine therapy that exhibits an accumulation of mitochondria. We performed whole-exome sequencing on a cohort of primary, recurrent, and metastatic tumors, and identified recurrent mutations in DAXX, TP53, NRAS, NF1, CDKN1A, ARHGAP35, and the TERT promoter. Parallel analysis of mtDNA revealed recurrent homoplasmic mutations in subunits of complex I of the electron transport chain. Analysis of DNA copy-number alterations uncovered widespread loss of chromosomes culminating in near-haploid chromosomal content in a large fraction of HCC, which was maintained during metastatic spread. This work uncovers a distinct molecular origin of HCC compared with other thyroid malignancies.

Author Correction: Molecular subtypes of diffuse large B cell lymphoma are associated with distinct pathogenic mechanisms and outcomes.

In the version of this article originally published, an asterisk was omitted from Fig. 1a. The asterisk has been added to the figure. Additionally, a "NOTCH2" label was erroneously included in Fig. 4a. The label has been removed. The errors have been corrected in the PDF and HTML versions of this article.

Publisher Correction: Molecular subtypes of diffuse large B cell lymphoma are associated with distinct pathogenic mechanisms and outcomes.

In the version of this article originally published, some text above the "Tri-nucleotide sequence motifs" label in Fig. 2a appeared incorrectly. The text was garbled and should have appeared as nucleotide codes.Additionally, the labels on the bars in Fig. 2c were not italicized in the original publication. These are gene symbols, and they should have been italicized.The colored labels above the graphs in Fig. 4b were also erroneously not italicized. These labels represent gene names and loci, and they should have been italicized.

Molecular subtypes of diffuse large B cell lymphoma are associated with distinct pathogenic mechanisms and outcomes.

Diffuse large B cell lymphoma (DLBCL), the most common lymphoid malignancy in adults, is a clinically and genetically heterogeneous disease that is further classified into transcriptionally defined activated B cell (ABC) and germinal center B cell (GCB) subtypes. We carried out a comprehensive genetic analysis of 304 primary DLBCLs and identified low-frequency alterations, captured recurrent mutations, somatic copy number alterations, and structural variants, and defined coordinate signatures in patients with available outcome data. We integrated these genetic drivers using consensus clustering and identified five robust DLBCL subsets, including a previously unrecognized group of low-risk ABC-DLBCLs of extrafollicular/marginal zone origin; two distinct subsets of GCB-DLBCLs with different outcomes and targetable alterations; and an ABC/GCB-independent group with biallelic inactivation of TP53, CDKN2A loss, and associated genomic instability. The genetic features of the newly characterized subsets, their mutational signatures, and the temporal ordering of identified alterations provide new insights into DLBCL pathogenesis. The coordinate genetic signatures also predict outcome independent of the clinical International Prognostic Index and suggest new combination treatment strategies. More broadly, our results provide a roadmap for an actionable DLBCL classification.

Comprehensive Characterization of Cancer Driver Genes and Mutations.

Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithms to identify drivers now exist, but systematic attempts to combine and optimize them on large datasets are few. We report a PanCancer and PanSoftware analysis spanning 9,423 tumor exomes (comprising all 33 of The Cancer Genome Atlas projects) and using 26 computational tools to catalog driver genes and mutations. We identify 299 driver genes with implications regarding their anatomical sites and cancer/cell types. Sequence- and structure-based analyses identified >3,400 putative missense driver mutations supported by multiple lines of evidence. Experimental validation confirmed 60%-85% of predicted mutations as likely drivers. We found that >300 MSI tumors are associated with high PD-1/PD-L1, and 57% of tumors analyzed harbor putative clinically actionable events. Our study represents the most comprehensive discovery of cancer genes and mutations to date and will serve as a blueprint for future biological and clinical endeavors.

Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines.

The Cancer Genome Atlas (TCGA) cancer genomics dataset includes over 10,000 tumor-normal exome pairs across 33 different cancer types, in total >400 TB of raw data files requiring analysis. Here we describe the Multi-Center Mutation Calling in Multiple Cancers project, our effort to generate a comprehensive encyclopedia of somatic mutation calls for the TCGA data to enable robust cross-tumor-type analyses. Our approach accounts for variance and batch effects introduced by the rapid advancement of DNA extraction, hybridization-capture, sequencing, and analysis methods over time. We present best practices for applying an ensemble of seven mutation-calling algorithms with scoring and artifact filtering. The dataset created by this analysis includes 3.5 million somatic variants and forms the basis for PanCan Atlas papers. The results have been made available to the research community along with the methods used to generate them. This project is the result of collaboration from a number of institutes and demonstrates how team science drives extremely large genomics projects.