The clonal and mutational evolution spectrum of primary triple-negative breast cancers.

Primary triple-negative breast cancers (TNBCs), a tumour type defined by lack of oestrogen receptor, progesterone receptor and ERBB2 gene amplification, represent approximately 16% of all breast cancers. Here we show in 104 TNBC cases that at the time of diagnosis these cancers exhibit a wide and continuous spectrum of genomic evolution, with some having only a handful of coding somatic aberrations in a few pathways, whereas others contain hundreds of coding somatic mutations. High-throughput RNA sequencing (RNA-seq) revealed that only approximately 36% of mutations are expressed. Using deep re-sequencing measurements of allelic abundance for 2,414 somatic mutations, we determine for the first time-to our knowledge-in an epithelial tumour subtype, the relative abundance of clonal frequencies among cases representative of the population. We show that TNBCs vary widely in their clonal frequencies at the time of diagnosis, with the basal subtype of TNBC showing more variation than non-basal TNBC. Although p53 (also known as TP53), PIK3CA and PTEN somatic mutations seem to be clonally dominant compared to other genes, in some tumours their clonal frequencies are incompatible with founder status. Mutations in cytoskeletal, cell shape and motility proteins occurred at lower clonal frequencies, suggesting that they occurred later during tumour progression. Taken together, our results show that understanding the biology and therapeutic responses of patients with TNBC will require the determination of individual tumour clonal genotypes.

Frequent mutation of histone-modifying genes in non-Hodgkin lymphoma.

Follicular lymphoma (FL) and diffuse large B-cell lymphoma (DLBCL) are the two most common non-Hodgkin lymphomas (NHLs). Here we sequenced tumour and matched normal DNA from 13 DLBCL cases and one FL case to identify genes with mutations in B-cell NHL. We analysed RNA-seq data from these and another 113 NHLs to identify genes with candidate mutations, and then re-sequenced tumour and matched normal DNA from these cases to confirm 109 genes with multiple somatic mutations. Genes with roles in histone modification were frequent targets of somatic mutation. For example, 32% of DLBCL and 89% of FL cases had somatic mutations in MLL2, which encodes a histone methyltransferase, and 11.4% and 13.4% of DLBCL and FL cases, respectively, had mutations in MEF2B, a calcium-regulated gene that cooperates with CREBBP and EP300 in acetylating histones. Our analysis suggests a previously unappreciated disruption of chromatin biology in lymphomagenesis.

Integrative analysis of genome-wide loss of heterozygosity and monoallelic expression at nucleotide resolution reveals disrupted pathways in triple-negative breast cancer.

Loss of heterozygosity (LOH) and copy number alteration (CNA) feature prominently in the somatic genomic landscape of tumors. As such, karyotypic aberrations in cancer genomes have been studied extensively to discover novel oncogenes and tumor-suppressor genes. Advances in sequencing technology have enabled the cost-effective detection of tumor genome and transcriptome mutation events at single-base-pair resolution; however, computational methods for predicting segmental regions of LOH in this context are not yet fully explored. Consequently, whole transcriptome, nucleotide-level resolution analysis of monoallelic expression patterns associated with LOH has not yet been undertaken in cancer. We developed a novel approach for inference of LOH from paired tumor/normal sequence data and applied it to a cohort of 23 triple-negative breast cancer (TNBC) genomes. Following extensive benchmarking experiments, we describe the nucleotide-resolution landscape of LOH in TNBC and assess the consequent effect of LOH on the transcriptomes of these tumors using RNA-seq-derived measurements of allele-specific expression. We show that the majority of monoallelic expression in the transcriptomes of triple-negative breast cancer can be explained by genomic regions of LOH and establish an upper bound for monoallelic expression that may be explained by other tumor-specific modifications such as epigenetics or mutations. Monoallelically expressed genes associated with LOH reveal that cell cycle, homologous recombination and actin-cytoskeletal functions are putatively disrupted by LOH in TNBC. Finally, we show how inference of LOH can be used to interpret allele frequencies of somatic mutations and postulate on temporal ordering of mutations in the evolutionary history of these tumors.

Mutational and structural analysis of diffuse large B-cell lymphoma using whole-genome sequencing.

Diffuse large B-cell lymphoma (DLBCL) is a genetically heterogeneous cancer composed of at least 2 molecular subtypes that differ in gene expression and distribution of mutations. Recently, application of genome/exome sequencing and RNA-seq to DLBCL has revealed numerous genes that are recurrent targets of somatic point mutation in this disease. Here we provide a whole-genome-sequencing-based perspective of DLBCL mutational complexity by characterizing 40 de novo DLBCL cases and 13 DLBCL cell lines and combining these data with DNA copy number analysis and RNA-seq from an extended cohort of 96 cases. Our analysis identified widespread genomic rearrangements including evidence for chromothripsis as well as the presence of known and novel fusion transcripts. We uncovered new gene targets of recurrent somatic point mutations and genes that are targeted by focal somatic deletions in this disease. We highlight the recurrence of germinal center B-cell-restricted mutations affecting genes that encode the S1P receptor and 2 small GTPases (GNA13 and GNAI2) that together converge on regulation of B-cell homing. We further analyzed our data to approximate the relative temporal order in which some recurrent mutations were acquired and demonstrate that ongoing acquisition of mutations and intratumoral clonal heterogeneity are common features of DLBCL. This study further improves our understanding of the processes and pathways involved in lymphomagenesis, and some of the pathways mutated here may indicate new avenues for therapeutic intervention.

Alternative expression analysis by RNA sequencing.

In alternative expression analysis by sequencing (ALEXA-seq), we developed a method to analyze massively parallel RNA sequence data to catalog transcripts and assess differential and alternative expression of known and predicted mRNA isoforms in cells and tissues. As proof of principle, we used the approach to compare fluorouracil-resistant and -nonresistant human colorectal cancer cell lines. We assessed the sensitivity and specificity of the approach by comparison to exon tiling and splicing microarrays and validated the results with reverse transcription-PCR, quantitative PCR and Sanger sequencing. We observed global disruption of splicing in fluorouracil-resistant cells characterized by expression of new mRNA isoforms resulting from exon skipping, alternative splice site usage and intron retention. Alternative expression annotation databases, source code, a data viewer and other resources to facilitate analysis are available at http://www.alexaplatform.org/alexa_seq/.

Analysis of genomic diversity in Mexican Mestizo populations to develop genomic medicine in Mexico.

Mexico is developing the basis for genomic medicine to improve healthcare of its population. The extensive study of genetic diversity and linkage disequilibrium structure of different populations has made it possible to develop tagging and imputation strategies to comprehensively analyze common genetic variation in association studies of complex diseases. We assessed the benefit of a Mexican haplotype map to improve identification of genes related to common diseases in the Mexican population. We evaluated genetic diversity, linkage disequilibrium patterns, and extent of haplotype sharing using genomewide data from Mexican Mestizos from regions with different histories of admixture and particular population dynamics. Ancestry was evaluated by including 1 Mexican Amerindian group and data from the HapMap. Our results provide evidence of genetic differences between Mexican subpopulations that should be considered in the design and analysis of association studies of complex diseases. In addition, these results support the notion that a haplotype map of the Mexican Mestizo population can reduce the number of tag SNPs required to characterize common genetic variation in this population. This is one of the first genomewide genotyping efforts of a recently admixed population in Latin America.

LY-CoV1404 (bebtelovimab) potently neutralizes SARS-CoV-2 variants.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-neutralizing monoclonal antibodies (mAbs) can reduce the risk of hospitalization from coronavirus disease 2019 (COVID-19) when administered early. However, SARS-CoV-2 variants of concern (VOCs) have negatively affected therapeutic use of some authorized mAbs. Using a high-throughput B cell screening pipeline, we isolated LY-CoV1404 (bebtelovimab), a highly potent SARS-CoV-2 spike glycoprotein receptor binding domain (RBD)-specific antibody. LY-CoV1404 potently neutralizes authentic SARS-CoV-2, B.1.1.7, B.1.351, and B.1.617.2. In pseudovirus neutralization studies, LY-CoV1404 potently neutralizes variants, including B.1.1.7, B.1.351, B.1.617.2, B.1.427/B.1.429, P.1, B.1.526, B.1.1.529, and the BA.2 subvariant. Structural analysis reveals that the contact residues of the LY-CoV1404 epitope are highly conserved, except for N439 and N501. The binding and neutralizing activity of LY-CoV1404 is unaffected by the most common mutations at these positions (N439K and N501Y). The broad and potent neutralization activity and the relatively conserved epitope suggest that LY-CoV1404 has the potential to be an effective therapeutic agent to treat all known variants.

LY-CoV1404 (bebtelovimab) potently neutralizes SARS-CoV-2 variants.

SARS-CoV-2 neutralizing monoclonal antibodies (mAbs) can reduce the risk of hospitalization when administered early during COVID-19 disease. However, the emergence of variants of concern has negatively impacted the therapeutic use of some authorized mAbs. Using a high throughput B-cell screening pipeline, we isolated a highly potent SARS-CoV-2 spike glycoprotein receptor binding domain (RBD)-specific antibody called LY-CoV1404 (also known as bebtelovimab). LY-CoV1404 potently neutralizes authentic SARS-CoV-2 virus, including the prototype, B.1.1.7, B.1.351 and B.1.617.2). In pseudovirus neutralization studies, LY-CoV1404 retains potent neutralizing activity against numerous variants including B.1.1.7, B.1.351, B.1.617.2, B.1.427/B.1.429, P.1, B.1.526, B.1.1.529, and the BA.2 subvariant and retains binding to spike proteins with a variety of underlying RBD mutations including K417N, L452R, E484K, and N501Y. Structural analysis reveals that the contact residues of the LY-CoV1404 epitope are highly conserved with the exception of N439 and N501. Notably, the binding and neutralizing activity of LY-CoV1404 is unaffected by the most common mutations at these positions (N439K and N501Y). The breadth of reactivity to amino acid substitutions present among current VOC together with broad and potent neutralizing activity and the relatively conserved epitope suggest that LY-CoV1404 has the potential to be an effective therapeutic agent to treat all known variants causing COVID-19. In Brief: LY-CoV1404 is a potent SARS-CoV-2-binding antibody that neutralizes all known variants of concern and whose epitope is rarely mutated. Highlights: LY-CoV1404 potently neutralizes SARS-CoV-2 authentic virus and known variants of concern including the B.1.1.529 (Omicron), the BA.2 Omicron subvariant, and B.1.617.2 (Delta) variantsNo loss of potency against currently circulating variantsBinding epitope on RBD of SARS-CoV-2 is rarely mutated in GISAID databaseBreadth of neutralizing activity and potency supports clinical development.

SNVMix: predicting single nucleotide variants from next-generation sequencing of tumors.

MOTIVATION: Next-generation sequencing (NGS) has enabled whole genome and transcriptome single nucleotide variant (SNV) discovery in cancer. NGS produces millions of short sequence reads that, once aligned to a reference genome sequence, can be interpreted for the presence of SNVs. Although tools exist for SNV discovery from NGS data, none are specifically suited to work with data from tumors, where altered ploidy and tumor cellularity impact the statistical expectations of SNV discovery. RESULTS: We developed three implementations of a probabilistic Binomial mixture model, called SNVMix, designed to infer SNVs from NGS data from tumors to address this problem. The first models allelic counts as observations and infers SNVs and model parameters using an expectation maximization (EM) algorithm and is therefore capable of adjusting to deviation of allelic frequencies inherent in genomically unstable tumor genomes. The second models nucleotide and mapping qualities of the reads by probabilistically weighting the contribution of a read/nucleotide to the inference of a SNV based on the confidence we have in the base call and the read alignment. The third combines filtering out low-quality data in addition to probabilistic weighting of the qualities. We quantitatively evaluated these approaches on 16 ovarian cancer RNASeq datasets with matched genotyping arrays and a human breast cancer genome sequenced to >40x (haploid) coverage with ground truth data and show systematically that the SNVMix models outperform competing approaches. AVAILABILITY: Software and data are available at http://compbio.bccrc.ca CONTACT: sshah@bccrc.ca SUPPLEMANTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The neutralizing antibody, LY-CoV555, protects against SARS-CoV-2 infection in nonhuman primates.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) poses a public health threat for which preventive and therapeutic agents are urgently needed. Neutralizing antibodies are a key class of therapeutics that may bridge widespread vaccination campaigns and offer a treatment solution in populations less responsive to vaccination. Here, we report that high-throughput microfluidic screening of antigen-specific B cells led to the identification of LY-CoV555 (also known as bamlanivimab), a potent anti-spike neutralizing antibody from a hospitalized, convalescent patient with coronavirus disease 2019 (COVID-19). Biochemical, structural, and functional characterization of LY-CoV555 revealed high-affinity binding to the receptor-binding domain, angiotensin-converting enzyme 2 binding inhibition, and potent neutralizing activity. A pharmacokinetic study of LY-CoV555 conducted in cynomolgus monkeys demonstrated a mean half-life of 13 days and a clearance of 0.22 ml hour-1 kg-1, consistent with a typical human therapeutic antibody. In a rhesus macaque challenge model, prophylactic doses as low as 2.5 mg/kg reduced viral replication in the upper and lower respiratory tract in samples collected through study day 6 after viral inoculation. This antibody has entered clinical testing and is being evaluated across a spectrum of COVID-19 indications, including prevention and treatment.

LY-CoV555, a rapidly isolated potent neutralizing antibody, provides protection in a non-human primate model of SARS-CoV-2 infection.

SARS-CoV-2 poses a public health threat for which therapeutic agents are urgently needed. Herein, we report that high-throughput microfluidic screening of antigen-specific B-cells led to the identification of LY-CoV555, a potent anti-spike neutralizing antibody from a convalescent COVID-19 patient. Biochemical, structural, and functional characterization revealed high-affinity binding to the receptor-binding domain, ACE2 binding inhibition, and potent neutralizing activity. In a rhesus macaque challenge model, prophylaxis doses as low as 2.5 mg/kg reduced viral replication in the upper and lower respiratory tract. These data demonstrate that high-throughput screening can lead to the identification of a potent antiviral antibody that protects against SARS-CoV-2 infection. ONE SENTENCE SUMMARY: LY-CoV555, an anti-spike antibody derived from a convalescent COVID-19 patient, potently neutralizes SARS-CoV-2 and protects the upper and lower airways of non-human primates against SARS-CoV-2 infection.

Genome-Wide Profiles of Extra-cranial Malignant Rhabdoid Tumors Reveal Heterogeneity and Dysregulated Developmental Pathways.

Malignant rhabdoid tumors (MRTs) are rare lethal tumors of childhood that most commonly occur in the kidney and brain. MRTs are driven by SMARCB1 loss, but the molecular consequences of SMARCB1 loss in extra-cranial tumors have not been comprehensively described and genomic resources for analyses of extra-cranial MRT are limited. To provide such data, we used whole-genome sequencing, whole-genome bisulfite sequencing, whole transcriptome (RNA-seq) and microRNA sequencing (miRNA-seq), and histone modification profiling to characterize extra-cranial MRTs. Our analyses revealed gene expression and methylation subgroups and focused on dysregulated pathways, including those involved in neural crest development.

Cross-cancer profiling of molecular alterations within the human autophagy interaction network.

Aberrant activation or disruption of autophagy promotes tumorigenesis in various preclinical models of cancer, but whether the autophagy pathway is a target for recurrent molecular alteration in human cancer patient samples is unknown. To address this outstanding question, we surveyed 211 human autophagy-associated genes for tumor-related alterations to DNA sequence and RNA expression levels and examined their association with patient survival outcomes in multiple cancer types with sequence data from The Cancer Genome Atlas consortium. We found 3 (RB1CC1/FIP200, ULK4, WDR45/WIPI4) and one (ATG7) core autophagy genes to be under positive selection for somatic mutations in endometrial carcinoma and clear cell renal carcinoma, respectively, while 29 autophagy regulators and pathway interactors, including previously identified KEAP1, NFE2L2, and MTOR, were significantly mutated in 6 of the 11 cancer types examined. Gene expression analyses revealed that GABARAPL1 and MAP1LC3C/LC3C transcripts were less abundant in breast cancer and non-small cell lung cancers than in matched normal tissue controls; ATG4D transcripts were increased in lung squamous cell carcinoma, as were ATG16L2 transcripts in kidney cancer. Unsupervised clustering of autophagy-associated mRNA levels in tumors stratified patient overall survival in 3 of 9 cancer types (acute myeloid leukemia, clear cell renal carcinoma, and head and neck cancer). These analyses provide the first comprehensive resource of recurrently altered autophagy-associated genes in human tumors, and highlight cancer types and subtypes where perturbed autophagy may be relevant to patient overall survival.

Mutation discovery in regions of segmental cancer genome amplifications with CoNAn-SNV: a mixture model for next generation sequencing of tumors.

Next generation sequencing has now enabled a cost-effective enumeration of the full mutational complement of a tumor genome-in particular single nucleotide variants (SNVs). Most current computational and statistical models for analyzing next generation sequencing data, however, do not account for cancer-specific biological properties, including somatic segmental copy number alterations (CNAs)-which require special treatment of the data. Here we present CoNAn-SNV (Copy Number Annotated SNV): a novel algorithm for the inference of single nucleotide variants (SNVs) that overlap copy number alterations. The method is based on modelling the notion that genomic regions of segmental duplication and amplification induce an extended genotype space where a subset of genotypes will exhibit heavily skewed allelic distributions in SNVs (and therefore render them undetectable by methods that assume diploidy). We introduce the concept of modelling allelic counts from sequencing data using a panel of Binomial mixture models where the number of mixtures for a given locus in the genome is informed by a discrete copy number state given as input. We applied CoNAn-SNV to a previously published whole genome shotgun data set obtained from a lobular breast cancer and show that it is able to discover 21 experimentally revalidated somatic non-synonymous mutations in a lobular breast cancer genome that were not detected using copy number insensitive SNV detection algorithms. Importantly, ROC analysis shows that the increased sensitivity of CoNAn-SNV does not result in disproportionate loss of specificity. This was also supported by analysis of a recently published lymphoma genome with a relatively quiescent karyotype, where CoNAn-SNV showed similar results to other callers except in regions of copy number gain where increased sensitivity was conferred. Our results indicate that in genomically unstable tumors, copy number annotation for SNV detection will be critical to fully characterize the mutational landscape of cancer genomes.

Somatic mutations altering EZH2 (Tyr641) in follicular and diffuse large B-cell lymphomas of germinal-center origin.

Follicular lymphoma (FL) and the GCB subtype of diffuse large B-cell lymphoma (DLBCL) derive from germinal center B cells. Targeted resequencing studies have revealed mutations in various genes encoding proteins in the NF-kappaB pathway that contribute to the activated B-cell (ABC) DLBCL subtype, but thus far few GCB-specific mutations have been identified. Here we report recurrent somatic mutations affecting the polycomb-group oncogene EZH2, which encodes a histone methyltransferase responsible for trimethylating Lys27 of histone H3 (H3K27). After the recent discovery of mutations in KDM6A (UTX), which encodes the histone H3K27me3 demethylase UTX, in several cancer types, EZH2 is the second histone methyltransferase gene found to be mutated in cancer. These mutations, which result in the replacement of a single tyrosine in the SET domain of the EZH2 protein (Tyr641), occur in 21.7% of GCB DLBCLs and 7.2% of FLs and are absent from ABC DLBCLs. Our data are consistent with the notion that EZH2 proteins with mutant Tyr641 have reduced enzymatic activity in vitro.