APOBEC shapes tumor evolution and age at onset of lung cancer in smokers.

APOBEC enzymes are part of the innate immunity and are responsible for restricting viruses and retroelements by deaminating cytosine residues1,2. Most solid tumors harbor different levels of somatic mutations attributed to the off-target activities of APOBEC3A (A3A) and/or APOBEC3B (A3B)3-6. However, how APOBEC3A/B enzymes shape the tumor evolution in the presence of exogenous mutagenic processes is largely unknown. Here, by combining deep whole-genome sequencing with multi-omics profiling of 309 lung cancers from smokers with detailed tobacco smoking information, we identify two subtypes defined by low (LAS) and high (HAS) APOBEC mutagenesis. LAS are enriched for A3B-like mutagenesis and KRAS mutations, whereas HAS for A3A-like mutagenesis and TP53 mutations. Unlike APOBEC3A, APOBEC3B expression is strongly associated with an upregulation of the base excision repair pathway. Hypermutation by unrepaired A3A and tobacco smoking mutagenesis combined with TP53-induced genomic instability can trigger senescence7, apoptosis8, and cell regeneration9, as indicated by high expression of pulmonary healing signaling pathway, stemness markers and distal cell-of-origin in HAS. The expected association of tobacco smoking variables (e.g., time to first cigarette) with genomic/epigenomic changes are not observed in HAS, a plausible consequence of frequent cell senescence or apoptosis. HAS have more neoantigens, slower clonal expansion, and older age at onset compared to LAS, particularly in heavy smokers, consistent with high proportions of newly generated, unmutated cells and frequent immuno-editing. These findings show how heterogeneity in mutational burden across co-occurring mutational processes and cell types contributes to tumor development, with important clinical implications.

Genomic sequence context differs between germline and somatic structural variants allowing for their differentiation in tumor samples without paired normals.

There is currently no method to distinguish between germline and somatic structural variants (SVs) in tumor samples that lack a matched normal sample. In this study, we analyzed several features of germline and somatic SVs from a cohort of 974 patients from The Cancer Genome Atlas (TCGA). We identified a total of 21 features that differed significantly between germline and somatic SVs. Several of the germline SV features were associated with each other, as were several of the somatic SV features. We also found that these associations differed between the germline and somatic classes, for example, we found that somatic inversions were more likely to be longer events than their germline counterparts. Using these features we trained a support vector machine (SVM) classifier on 555,849 TCGA SVs to computationally distinguish germline from somatic SVs in the absence of a matched normal. This classifier had an ROC curve AUC of 0.984 when tested on an independent test set of 277,925 TCGA SVs. In this dataset, we achieved a positive predictive value (PPV) of 0.81 for an SV called somatic by the classifier being truly somatic. We further tested the classifier on a separate set of 7,623 SVs from pediatric high-grade gliomas (pHGG). In this non-TCGA cohort, our classifier achieved a PPV of 0.828, showing robust performance across datasets.

Most large structural variants in cancer genomes can be detected without long reads.

Short-read sequencing is the workhorse of cancer genomics yet is thought to miss many structural variants (SVs), particularly large chromosomal alterations. To characterize missing SVs in short-read whole genomes, we analyzed 'loose ends'-local violations of mass balance between adjacent DNA segments. In the landscape of loose ends across 1,330 high-purity cancer whole genomes, most large (>10-kb) clonal SVs were fully resolved by short reads in the 87% of the human genome where copy number could be reliably measured. Some loose ends represent neotelomeres, which we propose as a hallmark of the alternative lengthening of telomeres phenotype. These pan-cancer findings were confirmed by long-molecule profiles of 38 breast cancer and melanoma cases. Our results indicate that aberrant homologous recombination is unlikely to drive the majority of large cancer SVs. Furthermore, analysis of mass balance in short-read whole genome data provides a surprisingly complete picture of cancer chromosomal structure.

Long-molecule scars of backup DNA repair in BRCA1- and BRCA2-deficient cancers.

Homologous recombination (HR) deficiency is associated with DNA rearrangements and cytogenetic aberrations1. Paradoxically, the types of DNA rearrangements that are specifically associated with HR-deficient cancers only minimally affect chromosomal structure2. Here, to address this apparent contradiction, we combined genome-graph analysis of short-read whole-genome sequencing (WGS) profiles across thousands of tumours with deep linked-read WGS of 46 BRCA1- or BRCA2-mutant breast cancers. These data revealed a distinct class of HR-deficiency-enriched rearrangements called reciprocal pairs. Linked-read WGS showed that reciprocal pairs with identical rearrangement orientations gave rise to one of two distinct chromosomal outcomes, distinguishable only with long-molecule data. Whereas one (cis) outcome corresponded to the copying and pasting of a small segment to a distant site, a second (trans) outcome was a quasi-balanced translocation or multi-megabase inversion with substantial (10 kb) duplications at each junction. We propose an HR-independent replication-restart repair mechanism to explain the full spectrum of reciprocal pair outcomes. Linked-read WGS also identified single-strand annealing as a repair pathway that is specific to BRCA2 deficiency in human cancers. Integrating these features in a classifier improved discrimination between BRCA1- and BRCA2-deficient genomes. In conclusion, our data reveal classes of rearrangements that are specific to BRCA1 or BRCA2 deficiency as a source of cytogenetic aberrations in HR-deficient cells.

The importance of escalating molecular diagnostics in patients with low-grade pediatric brain cancer.

Pilocytic astrocytomas are the most common pediatric brain tumors, typically presenting as low-grade neoplasms. We report two cases of pilocytic astrocytoma with atypical tumor progression. Case 1 involves a 12-yr-old boy with an unresectable suprasellar tumor, negative for BRAF rearrangement but harboring a BRAF p.V600E mutation. He experienced tumor size reduction and stable disease following dabrafenib treatment. Case 2 describes a 6-yr-old boy with a thalamic tumor that underwent multiple resections, with no actionable driver detected using targeted next-generation sequencing. Whole-genome and RNA-seq analysis identified an internal tandem duplication in FGFR1 and RAS pathway activation. Future management options include FGFR1 inhibitors. These cases demonstrate the importance of escalating molecular diagnostics for pediatric brain cancer, advocating for early reflexing to integrative whole-genome sequencing and transcriptomic profiling when targeted panels are uninformative. Identifying molecular drivers can significantly impact treatment decisions and improve patient outcomes.

Molecular Evolution of Classic Hodgkin Lymphoma Revealed Through Whole-Genome Sequencing of Hodgkin and Reed Sternberg Cells.

The rarity of malignant Hodgkin and Reed Sternberg (HRS) cells in classic Hodgkin lymphoma (cHL) limits the ability to study the genomics of cHL. To circumvent this, our group has previously optimized fluorescence-activated cell sorting to purify HRS cells. Using this approach, we now report the whole-genome sequencing landscape of HRS cells and reconstruct the chronology and likely etiology of pathogenic events leading to cHL. We identified alterations in driver genes not previously described in cHL, APOBEC mutational activity, and the presence of complex structural variants including chromothripsis. We found that high ploidy in cHL is often acquired through multiple, independent chromosomal gains events including whole-genome duplication. Evolutionary timing analyses revealed that structural variants enriched for RAG motifs, driver mutations in B2M, BCL7A, GNA13, and PTPN1, and the onset of AID-driven mutagenesis usually preceded large chromosomal gains. This study provides a temporal reconstruction of cHL pathogenesis. SIGNIFICANCE: Previous studies in cHL were limited to coding sequences and therefore not able to comprehensively decipher the tumor complexity. Here, leveraging cHL whole-genome characterization, we identify driver events and reconstruct the tumor evolution, finding that structural variants, driver mutations, and AID mutagenesis precede chromosomal gains. This article is highlighted in the In This Issue feature, p. 171.

Whole-genome characterization of myoepithelial carcinomas of the soft tissue.

Myoepithelial carcinomas (MECs) of soft tissue are rare and aggressive tumors affecting young adults and children, but their molecular landscape has not been comprehensively explored through genome sequencing. Here, we present the whole-exome sequencing (WES), whole-genome sequencing (WGS), and RNA sequencing findings of two MECs. Patients 1 and 2 (P1, P2), both male, were diagnosed at 27 and 37 yr of age, respectively, with shoulder (P1) and inguinal (P2) soft tissue tumors. Both patients developed metastatic disease, and P2 died of disease. P1 tumor showed a rhabdoid cytomorphology and a complete loss of INI1 (SMARCB1) expression, associated with a homozygous SMARCB1 deletion. The tumor from P2 showed a clear cell/small cell morphology, retained INI1 expression and strong S100 positivity. By WES and WGS, tumors from both patients displayed low tumor mutation burdens, and no targetable alterations in cancer genes were detected. P2's tumor harbored an EWSR1::KLF15 rearrangement, whereas the tumor from P1 showed a novel ASCC2::GGNBP2 fusion. WGS evidenced a complex genomic event involving mainly Chromosomes 17 and 22 in the tumor from P1, which was consistent with chromoplexy. These findings are consistent with previous reports of EWSR1 rearrangements (50% of cases) in MECs and provide a genetic basis for the loss of SMARCB1 protein expression observed through immunohistochemistry in 10% of 40% of MEC cases. The lack of additional driver mutations in these tumors supports the hypothesis that these alterations are the key molecular events in MEC evolution. Furthermore, the presence of complex structural variant patterns, invisible to WES, highlights the novel biological insights that can be gained through the application of WGS to rare cancers.

Genomic signature of Fanconi anaemia DNA repair pathway deficiency in cancer.

Fanconi anaemia (FA), a model syndrome of genome instability, is caused by a deficiency in DNA interstrand crosslink repair resulting in chromosome breakage1-3. The FA repair pathway protects against endogenous and exogenous carcinogenic aldehydes4-7. Individuals with FA are hundreds to thousands fold more likely to develop head and neck (HNSCC), oesophageal and anogenital squamous cell carcinomas8 (SCCs). Molecular studies of SCCs from individuals with FA (FA SCCs) are limited, and it is unclear how FA SCCs relate to sporadic HNSCCs primarily driven by tobacco and alcohol exposure or infection with human papillomavirus9 (HPV). Here, by sequencing genomes and exomes of FA SCCs, we demonstrate that the primary genomic signature of FA repair deficiency is the presence of high numbers of structural variants. Structural variants are enriched for small deletions, unbalanced translocations and fold-back inversions, and are often connected, thereby forming complex rearrangements. They arise in the context of TP53 loss, but not in the context of HPV infection, and lead to somatic copy-number alterations of HNSCC driver genes. We further show that FA pathway deficiency may lead to epithelial-to-mesenchymal transition and enhanced keratinocyte-intrinsic inflammatory signalling, which would contribute to the aggressive nature of FA SCCs. We propose that the genomic instability in sporadic HPV-negative HNSCC may arise as a result of the FA repair pathway being overwhelmed by DNA interstrand crosslink damage caused by alcohol and tobacco-derived aldehydes, making FA SCC a powerful model to study tumorigenesis resulting from DNA-crosslinking damage.

Recurrent somatic mutations as predictors of immunotherapy response.

Immune checkpoint blockade (ICB) has transformed the treatment of metastatic cancer but is hindered by variable response rates. A key unmet need is the identification of biomarkers that predict treatment response. To address this, we analyzed six whole exome sequencing cohorts with matched disease outcomes to identify genes and pathways predictive of ICB response. To increase detection power, we focus on genes and pathways that are significantly mutated following correction for epigenetic, replication timing, and sequence-based covariates. Using this technique, we identify several genes (BCLAF1, KRAS, BRAF, and TP53) and pathways (MAPK signaling, p53 associated, and immunomodulatory) as predictors of ICB response and develop the Cancer Immunotherapy Response CLassifiEr (CIRCLE). Compared to tumor mutational burden alone, CIRCLE led to superior prediction of ICB response with a 10.5% increase in sensitivity and a 11% increase in specificity. We envision that CIRCLE and more broadly the analysis of recurrently mutated cancer genes will pave the way for better prognostic tools for cancer immunotherapy.

Identifying synergistic high-order 3D chromatin conformations from genome-scale nanopore concatemer sequencing.

High-order three-dimensional (3D) interactions between more than two genomic loci are common in human chromatin, but their role in gene regulation is unclear. Previous high-order 3D chromatin assays either measure distant interactions across the genome or proximal interactions at selected targets. To address this gap, we developed Pore-C, which combines chromatin conformation capture with nanopore sequencing of concatemers to profile proximal high-order chromatin contacts at the genome scale. We also developed the statistical method Chromunity to identify sets of genomic loci with frequencies of high-order contacts significantly higher than background ('synergies'). Applying these methods to human cell lines, we found that synergies were enriched in enhancers and promoters in active chromatin and in highly transcribed and lineage-defining genes. In prostate cancer cells, these included binding sites of androgen-driven transcription factors and the promoters of androgen-regulated genes. Concatemers of high-order contacts in highly expressed genes were demethylated relative to pairwise contacts at the same loci. Synergies in breast cancer cells were associated with tyfonas, a class of complex DNA amplicons. These results rigorously link genome-wide high-order 3D interactions to lineage-defining transcriptional programs and establish Pore-C and Chromunity as scalable approaches to assess high-order genome structure.

SETD2 Haploinsufficiency Enhances Germinal Center-Associated AICDA Somatic Hypermutation to Drive B-cell Lymphomagenesis.

SETD2 is the sole histone methyltransferase responsible for H3K36me3, with roles in splicing, transcription initiation, and DNA damage response. Homozygous disruption of SETD2 yields a tumor suppressor effect in various cancers. However, SETD2 mutation is typically heterozygous in diffuse large B-cell lymphomas. Here we show that heterozygous Setd2 deficiency results in germinal center (GC) hyperplasia and increased competitive fitness, with reduced DNA damage checkpoint activity and apoptosis, resulting in accelerated lymphomagenesis. Impaired DNA damage sensing in Setd2-haploinsufficient germinal center B (GCB) and lymphoma cells associated with increased AICDA-induced somatic hypermutation, complex structural variants, and increased translocations including those activating MYC. DNA damage was selectively increased on the nontemplate strand, and H3K36me3 loss was associated with greater RNAPII processivity and mutational burden, suggesting that SETD2-mediated H3K36me3 is required for proper sensing of cytosine deamination. Hence, Setd2 haploinsufficiency delineates a novel GCB context-specific oncogenic pathway involving defective epigenetic surveillance of AICDA-mediated effects on transcribed genes. SIGNIFICANCE: Our findings define a B cell-specific oncogenic effect of SETD2 heterozygous mutation, which unleashes AICDA mutagenesis of nontemplate strand DNA in the GC reaction, resulting in lymphomas with heavy mutational burden. GC-derived lymphomas did not tolerate SETD2 homozygous deletion, pointing to a novel context-specific therapeutic vulnerability. This article is highlighted in the In This Issue feature, p. 1599.

Somatic whole genome dynamics of precancer in Barrett's esophagus reveals features associated with disease progression.

While the genomes of normal tissues undergo dynamic changes over time, little is understood about the temporal-spatial dynamics of genomes in premalignant tissues that progress to cancer compared to those that remain cancer-free. Here we use whole genome sequencing to contrast genomic alterations in 427 longitudinal samples from 40 patients with stable Barrett's esophagus compared to 40 Barrett's patients who progressed to esophageal adenocarcinoma (ESAD). We show the same somatic mutational processes are active in Barrett's tissue regardless of outcome, with high levels of mutation, ESAD gene and focal chromosomal alterations, and similar mutational signatures. The critical distinction between stable Barrett's versus those who progress to cancer is acquisition and expansion of TP53-/- cell populations having complex structural variants and high-level amplifications, which are detectable up to six years prior to a cancer diagnosis. These findings reveal the timing of common somatic genome dynamics in stable Barrett's esophagus and define key genomic features specific to progression to esophageal adenocarcinoma, both of which are critical for cancer prevention and early detection strategies.

System-wide transcriptome damage and tissue identity loss in COVID-19 patients.

The molecular mechanisms underlying the clinical manifestations of coronavirus disease 2019 (COVID-19), and what distinguishes them from common seasonal influenza virus and other lung injury states such as acute respiratory distress syndrome, remain poorly understood. To address these challenges, we combine transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues to define body-wide transcriptome changes in response to COVID-19. We then match these data with spatial protein and expression profiling across 357 tissue sections from 16 representative patient lung samples and identify tissue-compartment-specific damage wrought by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, evident as a function of varying viral loads during the clinical course of infection and tissue-type-specific expression states. Overall, our findings reveal a systemic disruption of canonical cellular and transcriptional pathways across all tissues, which can inform subsequent studies to combat the mortality of COVID-19 and to better understand the molecular dynamics of lethal SARS-CoV-2 and other respiratory infections.

Discovery of Candidate DNA Methylation Cancer Driver Genes.

Epigenetic alterations, such as promoter hypermethylation, may drive cancer through tumor suppressor gene inactivation. However, we have limited ability to differentiate driver DNA methylation (DNAme) changes from passenger events. We developed DNAme driver inference-MethSig-accounting for the varying stochastic hypermethylation rate across the genome and between samples. We applied MethSig to bisulfite sequencing data of chronic lymphocytic leukemia (CLL), multiple myeloma, ductal carcinoma in situ, glioblastoma, and to methylation array data across 18 tumor types in TCGA. MethSig resulted in well-calibrated quantile-quantile plots and reproducible inference of likely DNAme drivers with increased sensitivity/specificity compared with benchmarked methods. CRISPR/Cas9 knockout of selected candidate CLL DNAme drivers provided a fitness advantage with and without therapeutic intervention. Notably, DNAme driver risk score was closely associated with adverse outcome in independent CLL cohorts. Collectively, MethSig represents a novel inference framework for DNAme driver discovery to chart the role of aberrant DNAme in cancer. SIGNIFICANCE: MethSig provides a novel statistical framework for the analysis of DNA methylation changes in cancer, to specifically identify candidate DNA methylation driver genes of cancer progression and relapse, empowering the discovery of epigenetic mechanisms that enhance cancer cell fitness.This article is highlighted in the In This Issue feature, p. 2113.

Characterizing genetic intra-tumor heterogeneity across 2,658 human cancer genomes.

Intra-tumor heterogeneity (ITH) is a mechanism of therapeutic resistance and therefore an important clinical challenge. However, the extent, origin, and drivers of ITH across cancer types are poorly understood. To address this, we extensively characterize ITH across whole-genome sequences of 2,658 cancer samples spanning 38 cancer types. Nearly all informative samples (95.1%) contain evidence of distinct subclonal expansions with frequent branching relationships between subclones. We observe positive selection of subclonal driver mutations across most cancer types and identify cancer type-specific subclonal patterns of driver gene mutations, fusions, structural variants, and copy number alterations as well as dynamic changes in mutational processes between subclonal expansions. Our results underline the importance of ITH and its drivers in tumor evolution and provide a pan-cancer resource of comprehensively annotated subclonal events from whole-genome sequencing data.

Integrated mutational landscape analysis of uterine leiomyosarcomas.

Uterine leiomyosarcomas (uLMS) are aggressive tumors arising from the smooth muscle layer of the uterus. We analyzed 83 uLMS sample genetics, including 56 from Yale and 27 from The Cancer Genome Atlas (TCGA). Among them, a total of 55 Yale samples including two patient-derived xenografts (PDXs) and 27 TCGA samples have whole-exome sequencing (WES) data; 10 Yale and 27 TCGA samples have RNA-sequencing (RNA-Seq) data; and 11 Yale and 10 TCGA samples have whole-genome sequencing (WGS) data. We found recurrent somatic mutations in TP53, MED12, and PTEN genes. Top somatic mutated genes included TP53, ATRX, PTEN, and MEN1 genes. Somatic copy number variation (CNV) analysis identified 8 copy-number gains, including 5p15.33 (TERT), 8q24.21 (C-MYC), and 17p11.2 (MYOCD, MAP2K4) amplifications and 29 copy-number losses. Fusions involving tumor suppressors or oncogenes were deetected, with most fusions disrupting RB1, TP53, and ATRX/DAXX, and one fusion (ACTG2-ALK) being potentially targetable. WGS results demonstrated that 76% (16 of 21) of the samples harbored chromoplexy and/or chromothripsis. Clinically actionable mutational signatures of homologous-recombination DNA-repair deficiency (HRD) and microsatellite instability (MSI) were identified in 25% (12 of 48) and 2% (1 of 48) of fresh frozen uLMS, respectively. Finally, we found olaparib (PARPi; P = 0.002), GS-626510 (C-MYC/BETi; P < 0.000001 and P = 0.0005), and copanlisib (PIK3CAi; P = 0.0001) monotherapy to significantly inhibit uLMS-PDXs harboring derangements in C-MYC and PTEN/PIK3CA/AKT genes (LEY11) and/or HRD signatures (LEY16) compared to vehicle-treated mice. These findings define the genetic landscape of uLMS and suggest that a subset of uLMS may benefit from existing PARP-, PIK3CA-, and C-MYC/BET-targeted drugs.