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.

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 breakage^1-3. The FA repair pathway protects against endogenous and exogenous carcinogenic aldehydes^4-7. 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.

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.

Abstract 2935: Whole genome sequence of triple negative breast cancer (TNBC) tumors of African descent

In the US, BC incidence has recently converged among self-reported European Americans (EA) and African Americans (AA), however BC mortality remains approximately 40% higher among AA compared to EA and other SRR groups. The initial divergence in mortality curves between these groups occurred at the advent of hormone receptor (HR) targeted treatment options, unmasking the heterogeneity of BC diagnoses. Here, we present Whole Genomes Sequencing of 30 Triple Negative Breast Cancers of African women presenting to the clinics in New York. These were collected as part of the ICSBCS cohort to identify ancestry related mutational signatures including complex structural variants which could help better explain etiology of cancer in these population and that we may leveraged for treatment or prognostic purposes. Somatic mutational landscape included higher frequency of TP53 (73%), BRCA1 (40%), ATK1 (37%), CDH1(37%), and CTCF (33%). We confirmed African ancestry of patients through ADMIXTURE and observed (>70%) African ancestry. Comparison between our cohort and TCGA BRCA showed higher tumor mutational burden in our cohort which could be accounted for by greater sensitivity in our updated sequencing technology and analysis pipelines. Mutational signature analysis showed cosmic Signature 3 suggesting evidence of defective homologous recombination and signature 16 with unknown etiology. In addition, we also observed evidence deletions and structural variants such as rigma, pyrgo and typhonas. Ongoing efforts are investigating complex structural variants in our cohort compared to similar populations from other studies while waiting on additional samples.

Citation Format: Samuel Terkper Ahuno, Yajas Shah, Rachel Martini, Andrea Sboner, Nicolas Robine, Olivier Elemento, Marcin Imielinski, Lisa Newman, Melissa Davis. Whole genome sequence of triple negative breast cancer (TNBC) tumors of African descent [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2935.

Abstract 6196: Fanconi anemia pathway deficiency drives copy number variation in squamous cell carcinoma

Fanconi anemia (FA), a model syndrome of genome instability, is caused by a deficiency in DNA interstrand crosslink (ICL) repair resulting in chromosome breakage. The FA repair pathway comprises at least 22 FANC proteins including BRCA1 and BRCA2 and protects against carcinogenic endogenous and exogenous aldehydes. Individuals with FA are hundreds to thousands-fold more likely to develop head and neck (HNSCC), esophageal and anogenital squamous cell carcinomas (SCCs) with a median onset age of 31 years. The aggressive nature of these tumors and poor patient tolerance of platinum and radiation-based therapy have been associated with short survival in FA. Molecular studies of SCCs from individuals with FA (FA SCCs) have been limited, and it is unclear how they relate to sporadic HNSCCs primarily driven by tobacco and alcohol exposure or human papillomavirus (HPV) infection. Here, by sequencing FA SCCs, we demonstrate that the primary genomic signature of FA-deficiency is the presence of a high number of structural variants (SVs). SVs are enriched for small deletions, unbalanced translocations, and fold-back inversions that arise in the context of TP53 loss. The SV breakpoints preferentially localize to early replicating regions, common fragile sites, tandem repeats, and SINE elements. SVs are often connected forming complex rearrangements. Resultant genomic instability underlies elevated copy number alteration (CNA) rates of key HNSCC-associated genes, including PIK3CA, MYC, CSMD1, PTPRD, YAP1, MXD4, and EGFR. In contrast to sporadic HNSCC, we find no evidence of HPV infection in FA HNSCC, although positive cases were identified in gynecologic tumors. A murine allograft model of FA pathway-deficient SCC was enriched in SVs, exhibited dramatic tumor growth advantage, more rapid epithelial-to-mesenchymal transition, and enhanced autonomous inflammatory signaling when compared to an FA pathway-proficient model. In light of the protective role of the FA pathway against SV formation uncovered here, and recent findings of FA pathway insufficiency in the setting of increased formaldehyde load resulting in hematopoietic stem cell failure and carcinogenesis, we propose that high copy-number instability in sporadic HNSCC may result from functional overload of the FA pathway by endogenous and exogenous DNA crosslinking agents. Our work lays the foundation for improved FA patient treatment and demonstrates that FA SCC is a powerful model to study tumorigenesis resulting from DNA crosslinking damage.

Citation Format: Andrew L. Webster, Mathijs A. Sanders, Krupa Patel, Ralf Dietrich, Raymond J. Noonan, Francis P. Lach, Ryan R. White, Audrey M. Goldfarb, Kevin Hadi, Matthew M. Edwards, Frank X. Donovan, Moonjung Jung, Sunandini Sridhar, Olivier Fedrigo, Huasong Tian, Joel Rosiene, Thomas Heineman, Jennifer Kennedy, Lorenzo Bean, Rasim O. Rosti, Rebecca Tryon, Ashlyn-Maree Gonzalez, Allana Rosenberg, Ji-Dung Luo, Thomas Carrol, Eunike Velleuer, Jeff C. Rastatter, Susanne I. Wells, Jordi Surrallés, Grover Bagby, Margaret L. MacMillan, John E. Wagner, Maria Cancio, Farid Boulad, Theresa Scognamiglio, Roger Vaughan, Amnon Koren, Marcin Imielinski, Settara Chandrasekharappa, Arleen D. Auerbach, Bhuvanesh Singh, David Kutler, Peter J. Campbell, Agata Smogorzewska. Fanconi anemia pathway deficiency drives copy number variation in squamous cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6196.

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.

Barrett’s esophagus is a pre-malignant condition that can progress to esophageal cancer. Here, the authors carry out whole genome sequencing of samples from patients who did or did not progress to cancer and find that mutations in many genes occur regardless of progression status, but also find features associated with progressive disease.

Genomic instability is enriched in localized prostate cancers from men of African ancestry

270

Background: Whole genome sequencing (WGS) of prostate cancers (PC) from American men of African ancestry (AA) is limited despite AA men having twice the incidence of and mortality from PC as compared to their European ancestry (EA) men. Herein we describe analysis of AA PC WGS to identify genomic contributions to incidence and outcome disparities. Methods: WGS data from AA localized hormone naïve (HN) PCs (n = 23) from our institution were combined with publicly available WGS HNPC datasets (n = 5); quantitative predominant genome-wide ancestry was approximated via RFMix. A comparable EA cohort (n = 224) was similarly assembled. Ancestry groups were compared via regression models correcting for Gleason grade, PSA, and pathologic stage. Results: Analysis of known HNPC driver genes revealed lower frequency of PTEN (2/28 v 70/224, 7% v 31%, p = 0.006) and higher frequency of MYC (5/28 v 13/224, 18% v 5%, p = 0.014) and FOXA1 (7/28 v 24/224, 25% v 11%, p = 0.018) alterations in AA tumors relative to EA. An unbiased search for coding and noncoding drivers uncovered recurrent FOXA1 promoter (n = 8, p = 1.1e-8, RR = 3.92) and gene body protein-coding (n = 5, p = 1.2e-6, RR = 7.83) mutations, as targets of somatic selection and affecting nearly half of AA cases. Despite comparable tumor mutational burdens in each group, analysis of genome-wide mutational signatures revealed an AA-specific enrichment of SNVs in trinucleotide contexts associated with mismatch repair deficiency (SBS6, p = 1.68e-2, RR = 49.1). AA tumors also had significantly more small deletions (sig. ID2) relative to EA samples (p = 2.25e-31, RR = 9.47), implying replication slippage at lagging strands. Finally, AA PC genomes had consistently higher MSI scores relative to EA (median [IQR]: 4.03 [3.8-4.53] v 1.52 [1.21-1.85], p = 2.95e-44), yet lower than MSI-H colon cancers. These associations were independent of tissue preservation method or source, suggesting they reflect an ancestry-specific mutational process. Comparison of germline and somatic variants between AA and EA uncovered candidate DNA damage response genes (DDR) for further functional validation. Conclusions: Analysis of the largest AA cohort to date of WGS HNPC has revealed an ancestry-specific somatic mutational processes resulting in elevated rate of MMR-linked SNVs, replication-slippage associated small deletions, and MSI, relative to EA. The uniformity of these data suggest that AAs may harbor an inherited factor contributing to increased somatic genomic instability in the HNPC context. These results are compatible with published analyses demonstrating lower expression of DDR genes in AA versus EA PCs. Greater MSI and indels (via neoantigen formation) may explain the higher response proportions in AA PC patients treated with immune- and radiotherapies. Studies are ongoing to define mechanisms via associations between germline predisposition, somatic modification, and transcriptional outcome.

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.

Abstract P2-06-04: Pathognomonic long molecule footprints of backup repair pathways in homologous recombination deficient cancers

Background: Cancer genomes provide a durable record of the genetic alterations that are acquired during normal cell development and carcinogenesis from DNA damage and DNA repair defects. As DNA repair-deficient tumors often become dependent on backup repair pathways, mutational signatures found in such tumors are thought to reflect the absence of a particular repair pathway as well as the activity of the backup repair mechanism responsible for maintaining genome integrity. While homologous recombination (HR) deficiency is primarily a disorder of double-strand break (DSB) repair, the mutation classes most specifically associated with HR-deficiency in cancer are paradoxically small variants, namely single nucleotide variants and short deletions. Mechanistic and cytogenetic studies, however, indicate that HR-deficiency should compromise structural genomic integrity and yield complex rearrangements. Here we elucidate complex structural variants that are specific for HR-deficient cancers and identify rearrangements that differentiate BRCA1 from BRCA2 loss and illuminate divergent backup DNA repair mechanisms. Methods: To investigate the role of complex SVs in HR-deficient cancers, we assembled a cohort of 2,367 WGS profiles from four tumor types (breast, ovarian, prostate, and pancreatic cancer) known to be associated with HR-deficiency. We identified 48 BRCA1-/- and 87 BRCA2-/- cases and called samples lacking (mono- or biallelic) mutations in BRCA1, BRCA2, or any other HR associated gene (e.g. PALB2, RAD51C) as wild-type. To validate observed structural variant patterns associated with homologous recombination deficiency from this larger dataset, a new cohort of 49 cases of invasive breast cancer with known BRCA1 (N = 29) or BRCA2 (N = 20) deficiency was collected as part of a prospective research study at Memorial Sloan Kettering Cancer Center and sequenced with 10X-linked read WGS in addition to standard Illumina short-read WGS. Results: Analysis of nearly 2,400 short-read whole genomes revealed distinct quasi-reciprocal structural variants (SVs) highly enriched in BRCA1-/- versus BRCA2-/- cancers. Applying high physical coverage (>150X) long molecule WGS to 49 tumor-normal pairs from breast cancer patients with inherited BRCA1 or BRCA2 loss-of-function mutations, we show that these SVs are associated with distinct cis or trans somatic allelic phases despite having nearly identical short read WGS footprints. Trans (crossover) outcomes were found to give rise to large-scale chromosomal variants that mediate the loss-of-heterozygosity patterns previously described as a cardinal feature of HR-deficient cancers. We find that these quasi-reciprocal SVs can be explained as distinct template switching outcomes from a shared intermediate arising after replication fork stalling in HR-deficient cancers. Furthermore, our WGS analyses reveal that BRCA2 genomes are highly enriched in deletions that harbor long (50-1000bp) tracts of inexact microhomology. These events, validated by long molecule WGS, indicate that single-stranded annealing serves as an active backup repair pathway in BRCA2-/- but not BRCA1-/- cancers. Conclusions: These results provide direct genomic evidence linking large-scale structural changes in HR-deficient tumors with specific backup repair pathways that suggest novel, therapeutically targetable dependencies. Our findings elucidate backup repair mechanisms responsible for generating structural variation in HR-deficient tumors, demonstrate the genotype-specific divergence of such compensatory DNA repair, and provide genomic features that improve the detection accuracy of HR-deficiency with utility for the optimal selection of treatment.

Citation Format: Jeremy Setton, Kevin Hadi, Huasong Tian, Arnaud Da Cruz Paula, Joel Rosiene, Zi-Ning Choo, Julie Behr, Xiaotong Yao, Olivier Elemento, Britta Weigelt, Nadeem Riaz, Jorge S Reis-Filho, Marcin Imielinski, Simon N Powell. Pathognomonic long molecule footprints of backup repair pathways in homologous recombination deficient cancers [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-06-04.

Distinct Classes of Complex Structural Variation Uncovered across Thousands of Cancer Genome Graphs

Cancer genomes often harbor hundreds of somatic DNA rearrangement junctions, many of which cannot be easily classified into simple (e.g., deletion) or complex (e.g., chromothripsis) structural variant classes. Applying a novel genome graph computational paradigm to analyze the topology of junction copy number (JCN) across 2,778 tumor whole-genome sequences, we uncovered three novel complex rearrangement phenomena: pyrgo, rigma, and tyfonas. Pyrgo are "towers" of low-JCN duplications associated with early-replicating regions, superenhancers, and breast or ovarian cancers. Rigma comprise "chasms" of low-JCN deletions enriched in late-replicating fragile sites and gastrointestinal carcinomas. Tyfonas are "typhoons" of high-JCN junctions and fold-back inversions associated with expressed protein-coding fusions, breakend hypermutation, and acral, but not cutaneous, melanomas. Clustering of tumors according to genome graph-derived features identified subgroups associated with DNA repair defects and poor prognosis.

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.

Shotgun transcriptome, spatial omics, and isothermal profiling of SARS-CoV-2 infection reveals unique host responses, viral diversification, and drug interactions

In less than nine months, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) killed over a million people, including >25,000 in New York City (NYC) alone. The COVID-19 pandemic caused by SARS-CoV-2 highlights clinical needs to detect infection, track strain evolution, and identify biomarkers of disease course. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs and a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, viral, and microbial profiling. We applied these methods to clinical specimens gathered from 669 patients in New York City during the first two months of the outbreak, yielding a broad molecular portrait of the emerging COVID-19 disease. We find significant enrichment of a NYC-distinctive clade of the virus (20C), as well as host responses in interferon, ACE, hematological, and olfaction pathways. In addition, we use 50,821 patient records to find that renin-angiotensin-aldosterone system inhibitors have a protective effect for severe COVID-19 outcomes, unlike similar drugs. Finally, spatial transcriptomic data from COVID-19 patient autopsy tissues reveal distinct ACE2 expression loci, with macrophage and neutrophil infiltration in the lungs. These findings can inform public health and may help develop and drive SARS-CoV-2 diagnostic, prevention, and treatment strategies.

Systemic Tissue and Cellular Disruption from SARS-CoV-2 Infection revealed in COVID-19 Autopsies and Spatial Omics Tissue Maps

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus has infected over 115 million people and caused over 2.5 million deaths worldwide. Yet, the molecular mechanisms underlying the clinical manifestations of COVID-19, as well as what distinguishes them from common seasonal influenza virus and other lung injury states such as Acute Respiratory Distress Syndrome (ARDS), remains poorly understood. To address these challenges, we combined transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues, matched with spatial protein and expression profiling (GeoMx) across 357 tissue sections. These results define both body-wide and tissue-specific (heart, liver, lung, kidney, and lymph nodes) damage wrought by the SARS-CoV-2 infection, evident as a function of varying viral load (high vs. low) during the course of infection and specific, transcriptional dysregulation in splicing isoforms, T cell receptor expression, and cellular expression states. In particular, cardiac and lung tissues revealed the largest degree of splicing isoform switching and cell expression state loss. Overall, these findings reveal a systemic disruption of cellular and transcriptional pathways from COVID-19 across all tissues, which can inform subsequent studies to combat the mortality of COVID-19, as well to better understand the molecular dynamics of lethal SARS-CoV-2 infection and other viruses.

A Genomic-Pathologic Annotated Risk Model to Predict Recurrence in Early-Stage Lung Adenocarcinoma

Importance

Recommendations for adjuvant therapy after surgical resection of lung adenocarcinoma (LUAD) are based solely on TNM classification but are agnostic to genomic and high-risk clinicopathologic factors. Creation of a prediction model that integrates tumor genomic and clinicopathologic factors may better identify patients at risk for recurrence.

Objective

To identify tumor genomic factors independently associated with recurrence, even in the presence of aggressive, high-risk clinicopathologic variables, in patients with completely resected stages I to III LUAD, and to develop a computational machine-learning prediction model (PRecur) to determine whether the integration of genomic and clinicopathologic features could better predict risk of recurrence, compared with the TNM system.

Design, Setting, and Participants

This prospective cohort study included 426 patients treated from January 1, 2008, to December 31, 2017, at a single large cancer center and selected in consecutive samples. Eligibility criteria included complete surgical resection of stages I to III LUAD, broad-panel next-generation sequencing data with matched clinicopathologic data, and no neoadjuvant therapy. External validation of the PRecur prediction model was performed using The Cancer Genome Atlas (TCGA). Data were analyzed from 2014 to 2018.

Main Outcomes and Measures

The study end point consisted of relapse-free survival (RFS), estimated using the Kaplan-Meier approach. Associations among clinicopathologic factors, genomic alterations, and RFS were established using Cox proportional hazards regression. The PRecur prediction model integrated genomic and clinicopathologic factors using gradient-boosting survival regression for risk group generation and prediction of RFS. A concordance probability estimate (CPE) was used to assess the predictive ability of the PRecur model.

Results

Of the 426 patients included in the analysis (286 women [67%]; median age at surgery, 69 [interquartile range, 62-75] years), 318 (75%) had stage I cancer. Association analysis showed that alterations in SMARCA4 (clinicopathologic-adjusted hazard ratio [HR], 2.44; 95% CI, 1.03-5.77; P = .042) and TP53 (clinicopathologic-adjusted HR, 1.73; 95% CI, 1.09-2.73; P = .02) and the fraction of genome altered (clinicopathologic-adjusted HR, 1.03; 95% CI, 1.10-1.04; P = .005) were independently associated with RFS. The PRecur prediction model outperformed the TNM-based model (CPE, 0.73 vs 0.61; difference, 0.12 [95% CI, 0.05-0.19]; P < .001) for prediction of RFS. To validate the prediction model, PRecur was applied to the TCGA LUAD data set (n = 360), and a clear separation of risk groups was noted (log-rank statistic, 7.5; P = .02), confirming external validation.

Conclusions and Relevance

The findings suggest that integration of tumor genomics and clinicopathologic features improves risk stratification and prediction of recurrence after surgical resection of early-stage LUAD. Improved identification of patients at risk for recurrence could enrich and enhance accrual to adjuvant therapy clinical trials.

Whole-genome characterization of lung adenocarcinomas lacking the RTK/RAS/RAF pathway

RTK/RAS/RAF pathway alterations (RPAs) are a hallmark of lung adenocarcinoma (LUAD). In this study, we use whole-genome sequencing (WGS) of 85 cases found to be RPA(-) by previous studies from The Cancer Genome Atlas (TCGA) to characterize the minority of LUADs lacking apparent alterations in this pathway. We show that WGS analysis uncovers RPA(+) in 28 (33%) of the 85 samples. Among the remaining 57 cases, we observe focal deletions targeting the promoter or transcription start site of STK11 (n = 7) or KEAP1 (n = 3), and promoter mutations associated with the increased expression of ILF2 (n = 6). We also identify complex structural variations associated with high-level copy number amplifications. Moreover, an enrichment of focal deletions is found in TP53 mutant cases. Our results indicate that RPA(-) cases demonstrate tumor suppressor deletions and genome instability, but lack unique or recurrent genetic lesions compensating for the lack of RPAs. Larger WGS studies of RPA(-) cases are required to understand this important LUAD subset.

Impact of Lineage Plasticity to and from a Neuroendocrine Phenotype on Progression and Response in Prostate and Lung Cancers

Intratumoral heterogeneity can occur via phenotype transitions, often after chronic exposure to targeted anticancer agents. This process, termed lineage plasticity, is associated with acquired independence to an initial oncogenic driver, resulting in treatment failure. In non-small cell lung cancer (NSCLC) and prostate cancers, lineage plasticity manifests when the adenocarcinoma phenotype transforms into neuroendocrine (NE) disease. The exact molecular mechanisms involved in this NE transdifferentiation remain elusive. In small cell lung cancer (SCLC), plasticity from NE to nonNE phenotypes is driven by NOTCH signaling. Herein we review current understanding of NE lineage plasticity dynamics, exemplified by prostate cancer, NSCLC, and SCLC.

Abstract PO-10: Histone 1 deficiency drives lymphoma through disruption of 3D chromatin architecture

Linker histone H1 binds to nucleosomes and causes chromatin compaction, yet little is known about their biologic function. Somatic missense mutations in histone 1 genes (HIST1H1B-E) occur in ~30% of follicular lymphomas and DLBCL, with significant mutual co-occurrence among these alleles, most frequently involving H1C and H1E. Examining whole exomes in 547 DLBCL patients, we found significant enrichment for H1 gene SNVs and copy number loss in the MCD class of ABC-DLBCLs as compared to other subtypes. Next we performed a genetic driver analysis in 101 DLBCLs with matched germline control to identify mutations significantly enriched over background somatic variation. We find that lymphoma-associated H1 alleles H1C and H1E are true genetic driver mutations in lymphomas. Lymphoma H1 mutations affect the H1 globular domain or C-terminus. We found that the globular domain mutants fail to bind to chromatin whereas C-ter mutants fail to compact chromatin as shown by atomic force microscopy, in vitro assembled nucleosome arrays, and FRAP assays in live cells. Hence both types of mutation confer loss of function. Constitutive H1C/E knockout mice are healthy and have no overt phenotype. However, immunization with T cell-dependent antigen caused significant GC hyperplasia (p=0.013) and disruption of polarity due to expansion in the number of centrocytes. Notably, H1C/EDKO GC B-cells readily outcompeted WT GC B-cells in mixed chimera experiments, indicating that they have superior fitness (p=0.0086). We performed RNA-seq in H1C/EDKO GC B-cells, which revealed an aberrant gene derepression signature. Strikingly, these same genes are upregulated during induced pluripotency (iPS cell) reprogramming and are normally silenced during early development by the PRC2 complex (p &lt;0.05 to 1e-05). Indeed, histone mass spectrometry showed reduced H3K27me3 (p=0.0003) and increased H3K36me2 (p =0.001) in H1C/EDKO GC B cells. This prompted us to characterize the epigenome of purified H1C/EDKO vs WT GC B cells using Hi-C, ATAC-seq, and ChIP-seq for multiple histone marks. H1 deficiency causes profound architectural remodeling of the genome characterized by large-scale yet focal compartment shifts from compartment B to compartment A. The degree of decompaction results in distinct epigenetic states, primarily due to gain of H3K36me2 and/or loss of repressive H3K27me3. Strikingly, the H1C/EDKO primitive stem cell gene expression signature was highly significantly enriched (NES 1.24, FDR&lt;0.001) in the RNA-seq profiles of independent cohorts of DLBCL patients with H1C and H1E mutations. We crossed H1C+/-H1E+/- mice with VavP-Bcl2 transgenic mice and observed significant acceleration of lymphomagenesis (p=0.0001). Consistent with acquisition of stem cell characteristics, H1C+/-H1E+/-;VavP-Bcl2 but not VavP-Bcl2 primary lymphoma cells manifested lymphoma-initiating functionality after secondary transplantation into recipient animals.

Citation Format: Nevin Z. Yusufova, Matt Teater, Andreas Kloetgen, Alexey Soshnev, Adewola Osunade, Christopher Chin, Ashley Doane, Louis Staudt, David Scott, Neil Kelleher, Aristotelis Tsirigos, Marcin Imielinski, Yael David, David Allis, Ethel Cesarman, Ari Melnick. Histone 1 deficiency drives lymphoma through disruption of 3D chromatin architecture [abstract]. In: Proceedings of the AACR Virtual Meeting: Advances in Malignant Lymphoma; 2020 Aug 17-19. Philadelphia (PA): AACR; Blood Cancer Discov 2020;1(3_Suppl):Abstract nr PO-10.

Abstract 5895: Whole-genome characterization of lung adenocarcinomas lacking alterations in RTK/RAS/RAF/MAPK pathway

Lung adenocarcinomas (LUAD) are typically characterized by genetic activation of the receptor tyrosine kinase (RTK)/RAS/RAF/MAP kinase (MAPK) pathway. A minority of LUAD cases (20-25%) lack apparent genetic alterations in this pathway, and thus are ineligible for most targeted therapies. These candidate “oncogene negative” LUADs may harbor novel classes of oncogenic drivers or represent a biologically distinct class of tumors. To characterize the genomic landscape of oncogene-negative LUADs, we nominated 98 cases that were found to lack an activating RTK/RAS/RAF/MAPK pathway alteration in a TCGA study utilizing whole exome sequencing, microarray, and transcriptome data. We profiled these tumors with high-depth whole genome sequencing (WGS), with the goal of identifying noncoding and structural variant driver DNA alterations in both known and novel loci. Of the 98 cases, 20 harbored somatic KRAS mutations that had been missed in the prior WES and transcriptome studies because of insufficient coverage, including 8 cases with the recently targetable p.G12C mutation. 16 samples harbored oncogenic or loss-of-function structural variants in FGFR1, MAPK1, EGFR, NF1, RASA1, ARAF, NTRK2 and NRG1. 5 other samples with SNV or indels in EGFR, ERBB2 and SOS1 were reclassified as oncogene positive. Thus via comprehensive genomic analysis, we confirmed that 57 of the 98 WGS cases did not harbor any detectable alterations in genes encoding any known RTK/RAS/RAF/MAPK members, representing 13% cases chosen as “lung adenocarcinomas” for the TCGA study. Among the 57 confirmed oncogene-negative LUADs, we identified focal deletions targeting the promoter and transcription start site of tumor suppressor genes STK11, KEAP1 and SMARCA4 in 10 samples. Expression and methylation profiling suggested an enrichment of the TP53-deficient phenotype, including cell cycle and FOXM1 deregulation, among the oncogene-negative samples. Moreover, novel promoter mutations associated with increased expression were identified in ILF2, which regulates DNA damage response pathways. Finally, a subset of confirmed oncogene-negative LUADs harbored increased expression of neuroendocrine markers, suggesting that these oncogene-negative samples may either be mis-diagnosed as LUAD or represent LUAD with mixed features of other subtypes of lung cancer; indeed, 14 of the 57 confirmed oncogene-negative cases show histological features of large cell neuroendocrine lung carcinoma. This would suggest that 10% of the cases in this study are both lung adenocarcinoma and “oncogene-negative” to date. Our results provide some of the first comprehensive genomic characterization of oncogene-negative LUADs, implicating TP53 and structural variants in the pathogenesis of this common and difficult to treat entity.

Citation Format: Jian Carrot-Zhang, Siddhartha Devarakonda, Nicolas Robine, Xiaotong Yao, Tiago C. Silva, Jeff Damrauer, Aditya Deshpande, Ming-Sound Tsao, Christina Yao, Chris Wong, Lisui Bao, Hyo Young Choi, Ina Felau, Jean C. Zenklusen, Gordon Robertson, Tuan Trieua, Wei-Wei Liang, Meng Zhou, Esther Rheinbay, Neil Hayes, Ekta Khurana, Li Ding, Peter Laird, Olivier Elemento, John Weinstein, David Kwiatkowski, Chris Benz, Josh Stuart, Lixing Yang, Mauro Castro, William Travis, Katherine Hoadley, Ben Berman, TCGA Analysis Network, Matthew Meyerson, Ramaswamy Govindan, Marcin Imielinski. Whole-genome characterization of lung adenocarcinomas lacking alterations in RTK/RAS/RAF/MAPK pathway [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5895.

Shotgun Transcriptome and Isothermal Profiling of SARS-CoV-2 Infection Reveals Unique Host Responses, Viral Diversification, and Drug Interactions

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused thousands of deaths worldwide, including >18,000 in New York City (NYC) alone. The sudden emergence of this pandemic has highlighted a pressing clinical need for rapid, scalable diagnostics that can detect infection, interrogate strain evolution, and identify novel patient biomarkers. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs, plus a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, bacterial, and viral profiling. We applied both technologies across 857 SARS-CoV-2 clinical specimens and 86 NYC subway samples, providing a broad molecular portrait of the COVID-19 NYC outbreak. Our results define new features of SARS-CoV-2 evolution, nominate a novel, NYC-enriched viral subclade, reveal specific host responses in interferon, ACE, hematological, and olfaction pathways, and examine risks associated with use of ACE inhibitors and angiotensin receptor blockers. Together, these findings have immediate applications to SARS-CoV-2 diagnostics, public health, and new therapeutic targets.

Patterns of somatic structural variation in human cancer genomes

A key mutational process in cancer is structural variation, in which rearrangements delete, amplify or reorder genomic segments that range in size from kilobases to whole chromosomes1-7. Here we develop methods to group, classify and describe somatic structural variants, using data from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), which aggregated whole-genome sequencing data from 2,658 cancers across 38 tumour types8. Sixteen signatures of structural variation emerged. Deletions have a multimodal size distribution, assort unevenly across tumour types and patients, are enriched in late-replicating regions and correlate with inversions. Tandem duplications also have a multimodal size distribution, but are enriched in early-replicating regions-as are unbalanced translocations. Replication-based mechanisms of rearrangement generate varied chromosomal structures with low-level copy-number gains and frequent inverted rearrangements. One prominent structure consists of 2-7 templates copied from distinct regions of the genome strung together within one locus. Such cycles of templated insertions correlate with tandem duplications, and-in liver cancer-frequently activate the telomerase gene TERT. A wide variety of rearrangement processes are active in cancer, which generate complex configurations of the genome upon which selection can act.

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1-3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10-18.

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.

The evolutionary history of 2,658 cancers

Cancer develops through a process of somatic evolution1,2. Sequencing data from a single biopsy represent a snapshot of this process that can reveal the timing of specific genomic aberrations and the changing influence of mutational processes3. Here, by whole-genome sequencing analysis of 2,658 cancers as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA)4, we reconstruct the life history and evolution of mutational processes and driver mutation sequences of 38 types of cancer. Early oncogenesis is characterized by mutations in a constrained set of driver genes, and specific copy number gains, such as trisomy 7 in glioblastoma and isochromosome 17q in medulloblastoma. The mutational spectrum changes significantly throughout tumour evolution in 40% of samples. A nearly fourfold diversification of driver genes and increased genomic instability are features of later stages. Copy number alterations often occur in mitotic crises, and lead to simultaneous gains of chromosomal segments. Timing analyses suggest that driver mutations often precede diagnosis by many years, if not decades. Together, these results determine the evolutionary trajectories of cancer, and highlight opportunities for early cancer detection.

Abstract 909: Single-cell transcriptomic profiling of non-small cell lung cancer uncovers inter- and intracell population structure across TCGA lung adenocarcinoma and lung squamous cancer subtypes

Lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) are the most prevalent types of non-all cell lung cancer (NSCLC), a leading cause of cancer death worldwide. In this study, we analyzed the transcriptomes of ~45,000 single cells (scRNA) from 13 NSCLC patients, including 5 LUAD cases which were collected and profiled at our institution. To correlate genomes and transcriptomes we performed Whole-Genome Sequencing (WGS) on 3 of these 5 LUAD cases. By comparing tumor tissue with matched adjacent non-malignant lung tissue we are able to confidently distinguish 13 cell-type specific clusters that unambiguously match previously characterized lineages. We developed algorithms for the identification of malignant cells derived from tumor tissue through scRNA analysis of copy number alterations and single nucleotide variants (SNV). Joint analysis of WGS and scRNA confirmed an enrichment of tobacco-associated SNVs among malignant cells of the tumor. Stromal cell types demonstrated consistent expression patterns across cases, while malignant cells demonstrated both inter- and intra-tumoral heterogeneity in their expression of signatures related to GPCR signaling, 3’ UTR mediated translational regulation, and cell-cell junction organization. In particular, one case displayed a unique pattern of intra-tumoral heterogeneity, as a subset of malignant cells robustly express a marker of pulmonary neuroendocrine cells, CGRP. Employing immunohistochemistry, the spatial organization of these malignant cells is revealed to be mutually exclusive within the tumor microenvironment and overlapping in expression of clinical markers of small-cell lung cancer. Finally, we deconvolved bulk TCGA LUAD and LUSC gene expression samples and analyzed the relationship between cell type specific gene expression in cell types of the lung and passenger mutation topographies. Our results provide insight into the molecular and clinical correlates of deconvolved NSCLC transcriptomes and provide a novel methodology with which to explore genomic variation at a single cell resolution. Furthermore, our dataset provides a resource for illuminating cancer-cell transcriptional changes and revealing key molecular drivers of tumor-stromal interactions in lung cancer.

Citation Format: Kofi E. Gyan, Aditya Deshpande, Shaham Beg, Huasong Tian, Joel Rosiene, Marlon Stoeckius, Peter Smibert, Davide Risso, Juan Miguel Mosquera, Marcin Imielinski. Single-cell transcriptomic profiling of non-small cell lung cancer uncovers inter- and intracell population structure across TCGA lung adenocarcinoma and lung squamous cancer subtypes [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 909.

Abstract 218: The evolutionary history of 2,658 cancers

Cancer develops through a continuous process of somatic evolution. Whole genome sequencing provides a snapshot of the tumor genome at the point of sampling, however, the data can contain information that permits the reconstruction of a tumor's evolutionary past.

Here, we apply such life history analyses on an unprecedented scale, to a set of 2,658 tumors spanning 39 cancer types. We estimated the timing of large chromosomal gains during tumor evolution, by comparing the rates of doubled to non-doubled point mutations within gained regions. Although we find that such events typically occur in the second half of clonal evolution, we also observe distinctive and early chromosomal gains in some cancer types, such as gains of chromosomes 7, 19 and 20 in glioblastoma, and isochromosome 17q in medulloblastoma. By integrating these results with the qualitative timing of individual driver mutations, we obtained an overall ranking, from early to late, of frequent somatic events per cancer type, which both identified novel patterns of tumor evolution, and incorporated additional detail into known models, such as the progression of APC-KRAS-TP53 in colorectal cancer proposed by Vogelstein and Fearon.

To estimate how mutational processes acting on the tumor genome change over time, we classified mutations in each sample according to three broad time periods (early clonal, late clonal, and subclonal), and quantified the activity of mutational signatures in each period. Most mutational processes appear to remain remarkably constant, however, certain signatures show clear and consistent changes during clonal evolution. Particularly, mutational signatures associated with exposure to carcinogens, such as smoking and UV light, tend to decrease over time. In contrast, signatures associated with defective endogenous processes, such as APOBEC mutagenesis and defective double strand break repair, show an increase between early and late phases of tumor evolution.

Making use of clock-like mutational signatures, we converted mutational time estimates for large events, such as whole genome duplication (WGD), and the emergence of the most recent common ancestor (MRCA), into real time estimates, which allowed us to combine our analyses into overall timelines of cancer evolution, per tumor type. For example, the typical timeline of ovarian adenocarcinoma development shows that early tumor evolution is characterized by mutations in TP53, and widespread genome instability, with WGD events taking place on average 8 years prior to diagnosis. In later stages of evolution, signatures of defective repair processes increase, and the MRCA emerges on average 1 year before diagnosis.

Taken together, these data reveal the common and divergent evolutionary trajectories available to a cancer, which might be crucial in understanding specific tumor biology, and in providing new opportunities for early detection and cancer prevention.

Citation Format: Clemency Jolly, Moritz Gerstung, Ignaty Leshchiner, Stefan C. Dentro, Santiago Gonzalez, Thomas J. Mitchell, Yulia Rubanova, Pavana Anur, Daniel Rosebrock, Kaixian Yu, Maxime Tarabichi, Amit Deshwar, Jeff Wintersinger, Kortine Kleinheinz, Ignacio Vásquez-García, Kerstin Haase, Subhajit Sengupta, Geoff Macintyre, Salem Malikic, Nilgun Donmez, Dimitri G. Livitz, Mark Cmero, Jonas Demeulemeester, Steve Schumacher, Yu Fan, Xiaotong Yao, Juhee Lee, Matthias Schlesner, Paul C. Boutros, David D. Bowtell, Hongtu Zhu, Gad Getz, Marcin Imielinski, Rameen Beroukhim, S Cenk Sahinalp, Yuan Ji, Martin Peifer, Florian Markowetz, Ville Mustonen, Ke Juan, Wenyi Wang, Quaid D. Morris, Paul T. Spellman, David C. Wedge, Peter Van Loo, PCAWG Evolution and Heterogeneity Working Group. The evolutionary history of 2,658 cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 218.

Abstract NG03: Chromosomal instability promotes metastasis through a cytosolic DNA response

Chromosomal instability (CIN) is a hallmark of cancer and it results from ongoing errors in chromosome segregation during mitosis. While CIN is a major driver of tumor evolution, its role in metastasis has not been established. Here we show that CIN promotes metastasis by sustaining a tumor-cell autonomous response to cytosolic DNA. Errors in chromosome segregation create a preponderance of micronuclei whose rupture spills genomic DNA into the cytosol. This leads to the activation of the cGAS-STING cytosolic DNA-sensing pathway and downstream noncanonical NF-κB signaling. Genetic suppression of CIN significantly delays metastasis even in highly aneuploid tumor models, whereas inducing continuous chromosome segregation errors promotes cellular invasion and metastasis in a STING-dependent manner. Using single-cell RNA sequencing, we uncover a CIN-induced transcriptional switch from a proliferative and metabolically active state to a mesenchymal phenotype associated with inflammatory pathways, offering an opportunity to target chromosome segregation errors for therapeutic benefit. Our work reveals an unexpected link between CIN, cytosolic DNA sensing pathways, and metastasis. The use of an isogenic system has enabled us to dissect the role of CIN from that of aneuploidy. Importantly, while we do not discount the role of CIN in generating karyotypic heterogeneity that can serve as the substrate for natural selection, our work demonstrates that continuous chromosome missegregation is also required to replenish cytosolic DNA pools leading to chronic upregulation of inflammatory pathways. In non-transformed settings, cytosolic DNA sensing is incompatible with viability. Unlike normal cells, chromosomally unstable cells are awash with cytosolic DNA and have adapted to coexist with a chronically active cGAS-STING pathway by suppressing downstream type I interferon signaling and instead upregulating the alternative NF-κB pathway. Persistent STING activation mediates carcinogen-induced tumor formation and we now show that tumor cells co-opt this otherwise lethal program to spread to distant organs. The evolutionary benefit of the noncanonical pathway might justify the scarcity of inactivating mutations in cGAS and STING among human cancers. The emergence, and subsequent tolerance, of CIN represents an important bottleneck during tumor evolution. Our single-cell analysis revealed that CIN induces a transcriptional switch whereby cells shift from a proliferative and highly metabolic state, ideally suited for primary tumor growth, to a chromosomally unstable and mesenchymal state associated with upregulation of inflammatory pathways. These two largely mutually exclusive states likely account for the reversibility in chromosome missegregation rates seen in primary tumors and metastases, and provide an explanation for the negative effect of aneuploidy during early tumorigenesis. Interestingly, this mutual exclusivity was recently observed in a pan-cancer genomic analysis of metastatic tumors, and it leads us to suggest that CIN underlies the subset of metastases that are characterized by EMT and inflammation. By providing a mechanistic link between CIN and metastasis, our work opens new avenues to target chromosomally unstable tumors for therapeutic benefit.

Citation Format: Samuel F. Bakhoum, Bryon Ngo, Ashley L. Bakhoum, Julie-Ann Cavallo, Charles J. Murphy, Peter Ly, Pragya Shah, Roshan K. Sriram, Thomas B.k. Watkins, Neil K. Taunk, Mercedes Duran, Chantal Pauli, Christine Shaw, Kalyani Chadalavada, Vinagolu K. Rajasekhar, Giulio Genovese, Subramanian Venkatesan, Nicolai J. Birkbak, Nicholas McGranahan, Mark Lundquist, Quincy LaPlant, John H. Healey, Olivier Elemento, Christine H. Chung, Nancy Y. Lee, Marcin Imielinski, Gouri Nanjangud, Dana Pe'er, Don W. Cleveland, Simon N. Powell, Jan Lammerding, Charles Swanton, Lewis C. Cantley. Chromosomal instability promotes metastasis through a cytosolic DNA response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr NG03.

SvABA: genome-wide detection of structural variants and indels by local assembly

Structural variants (SVs), including small insertion and deletion variants (indels), are challenging to detect through standard alignment-based variant calling methods. Sequence assembly offers a powerful approach to identifying SVs, but is difficult to apply at scale genome-wide for SV detection due to its computational complexity and the difficulty of extracting SVs from assembly contigs. We describe SvABA, an efficient and accurate method for detecting SVs from short-read sequencing data using genome-wide local assembly with low memory and computing requirements. We evaluated SvABA's performance on the NA12878 human genome and in simulated and real cancer genomes. SvABA demonstrates superior sensitivity and specificity across a large spectrum of SVs and substantially improves detection performance for variants in the 20–300 bp range, compared with existing methods. SvABA also identifies complex somatic rearrangements with chains of short (<1000 bp) templated-sequence insertions copied from distant genomic regions. We applied SvABA to 344 cancer genomes from 11 cancer types and found that short templated-sequence insertions occur in ∼4% of all somatic rearrangements. Finally, we demonstrate that SvABA can identify sites of viral integration and cancer driver alterations containing medium-sized (50–300 bp) SVs.

Deep Convolutional Neural Networks Enable Discrimination of Heterogeneous Digital Pathology Images

Pathological evaluation of tumor tissue is pivotal for diagnosis in cancer patients and automated image analysis approaches have great potential to increase precision of diagnosis and help reduce human error. In this study, we utilize several computational methods based on convolutional neural networks (CNN) and build a stand-alone pipeline to effectively classify different histopathology images across different types of cancer. In particular, we demonstrate the utility of our pipeline to discriminate between two subtypes of lung cancer, four biomarkers of bladder cancer, and five biomarkers of breast cancer. In addition, we apply our pipeline to discriminate among four immunohistochemistry (IHC) staining scores of bladder and breast cancers. Our classification pipeline includes a basic CNN architecture, Google's Inceptions with three training strategies, and an ensemble of two state-of-the-art algorithms, Inception and ResNet. Training strategies include training the last layer of Google's Inceptions, training the network from scratch, and fine-tunning the parameters for our data using two pre-trained version of Google's Inception architectures, Inception-V1 and Inception-V3. We demonstrate the power of deep learning approaches for identifying cancer subtypes, and the robustness of Google's Inceptions even in presence of extensive tumor heterogeneity. On average, our pipeline achieved accuracies of 100%, 92%, 95%, and 69% for discrimination of various cancer tissues, subtypes, biomarkers, and scores, respectively. Our pipeline and related documentation is freely available at https://github.com/ih-_lab/CNN_Smoothie.

The cancer precision medicine knowledge base for structured clinical-grade mutations and interpretations

Objective: This paper describes the Precision Medicine Knowledge Base (PMKB; https://pmkb.weill.cornell.edu), an interactive online application for collaborative editing, maintenance, and sharing of structured clinical-grade cancer mutation interpretations.

Materials and Methods: PMKB was built using the Ruby on Rails Web application framework. Leveraging existing standards such as the Human Genome Variation Society variant description format, we implemented a data model that links variants to tumor-specific and tissue-specific interpretations. Key features of PMKB include support for all major variant types, standardized authentication, distinct user roles including high-level approvers, and detailed activity history. A REpresentational State Transfer (REST) application-programming interface (API) was implemented to query the PMKB programmatically.

Results: At the time of writing, PMKB contains 457 variant descriptions with 281 clinical-grade interpretations. The EGFR, BRAF, KRAS, and KIT genes are associated with the largest numbers of interpretable variants. PMKB’s interpretations have been used in over 1500 AmpliSeq tests and 750 whole-exome sequencing tests. The interpretations are accessed either directly via the Web interface or programmatically via the existing API.

Discussion: An accurate and up-to-date knowledge base of genomic alterations of clinical significance is critical to the success of precision medicine programs. The open-access, programmatically accessible PMKB represents an important attempt at creating such a resource in the field of oncology.

Conclusion: The PMKB was designed to help collect and maintain clinical-grade mutation interpretations and facilitate reporting for clinical cancer genomic testing. The PMKB was also designed to enable the creation of clinical cancer genomics automated reporting pipelines via an API.

Insertions and Deletions Target Lineage-Defining Genes in Human Cancers

Certain cell types function as factories, secreting large quantities of one or more proteins that are central to the physiology of the respective organ. Examples include surfactant proteins in lung alveoli, albumin in liver parenchyma, and lipase in the stomach lining. Whole-genome sequencing analysis of lung adenocarcinomas revealed noncoding somatic mutational hotspots near VMP1/MIR21 and indel hotspots in surfactant protein genes (SFTPA1, SFTPB, and SFTPC). Extrapolation to other solid cancers demonstrated highly recurrent and tumor-type-specific indel hotspots targeting the noncoding regions of highly expressed genes defining certain secretory cellular lineages: albumin (ALB) in liver carcinoma, gastric lipase (LIPF) in stomach carcinoma, and thyroglobulin (TG) in thyroid carcinoma. The sequence contexts of indels targeting lineage-defining genes were significantly enriched in the AATAATD DNA motif and specific chromatin contexts, including H3K27ac and H3K36me3. Our findings illuminate a prevalent and hitherto unrecognized mutational process linking cellular lineage and cancer.

Modeling cancer rearrangement landscapes

Cancer genome sequences contain footprints of somatic mutational processes, whose analysis in large tumor sequencing datasets has revealed novel mutational signatures, correlative features of variant topography, and complex events. Many of these analytic results have yet to reconciled with decades of mechanistic genome integrity research performed in controlled model systems. However, a new generation of genome-integrity experiments combining computational modeling, data analytics, and high-throughput sequencing are emerging to link mechanisms to patterns. Conversely, analytic studies evaluating quantitative footprints of specific genome integrity hypotheses will be critical in fitting naturally occurring mutational patterns to the predictions of a particular mechanistic model. Such quantitative and mechanistic studies will form the foundation of an emerging systems biology of genome integrity.

High-throughput Phenotyping of Lung Cancer Somatic Mutations

Recent genome sequencing efforts have identified millions of somatic mutations in cancer. However, the functional impact of most variants is poorly understood. Here we characterize 194 somatic mutations identified in primary lung adenocarcinomas. We present an expression-based variant-impact phenotyping (eVIP) method that uses gene expression changes to distinguish impactful from neutral somatic mutations. eVIP identified 69% of mutations analyzed as impactful and 31% as functionally neutral. A subset of the impactful mutations induces xenograft tumor formation in mice and/or confers resistance to cellular EGFR inhibition. Among these impactful variants are rare somatic, clinically actionable variants including EGFR S645C, ARAF S214C and S214F, ERBB2 S418T, and multiple BRAF variants, demonstrating that rare mutations can be functionally important in cancer.

Abstract 4368: High-throughput phenotyping of lung cancer somatic mutations

Recent cancer genome sequencing and analysis has identified millions of somatic mutations in cancer. However, the functional impact of most variants is poorly understood, limiting the use of this genetic knowledge for clinical decision-making. Here we describe a new high-throughput approach, expression-based variant impact phenotyping (eVIP), which uses gene expression changes to infer somatic mutation impact. We generated a lentiviral expression library representing 53 genes and 194 somatic mutations identified in primary lung adenocarcinomas. Next, we introduced this library into A549 lung adenocarcinoma cells and 96 hours later performed gene expression profiling using Luminex-based L1000 profiling. We built a computational pipeline, eVIP, to compare mutant and wild-type expression signatures to infer whether variants were gain-of-function, change-of-function, loss-of-function, or neutral. Overall, eVIP identified 69% of mutations as impactful whereas 31% appeared functionally neutral. A very high rate, 92%, of missense mutations in the KEAP1 and STK11 tumor suppressor genes were found to inactivate or diminish protein function. As a complementary approach, we assessed which mutations are epistatic to EGFR or capable of initiating xenograft tumor formation in vivo. A subset of the impactful mutations identified by eVIP could induce xenograft tumor formation in mice and/or confer resistance to cellular EGFR inhibition. Among these mutations were 20 rare or non-canonical somatic variants in clinically-actionable or -relevant oncogenes including EGFR S645C, ARAF S214C and S214F, ERBB2 S418T, and PIK3CA E600K. eVIP can, in principle, characterize any genetic variant, independent of prior knowledge of gene function. Further application of eVIP should significantly advance the pace of functional characterization of mutations identified from genome sequencing.

Citation Format: Alice H. Berger, Angela N. Brooks, Xiaoyun Wu, Yashaswi Shrestha, Candace Chouinard, Federica Piccioni, Mukta Bagul, Atanas Kamburov, Marcin Imielinski, Larson Hogstrom, Cong Zhu, Xiaoping Yang, Sasha Pantel, Ryo Sakai, Nathan Kaplan, David Root, Rajiv Narayan, Ted Natoli, David Lahr, Itay Tirosh, Pablo Tamayo, Gad Getz, Bang Wong, John Doench, Aravind Subramanian, Todd R. Golub, Matthew Meyerson, Jesse S. Boehm. High-throughput phenotyping of lung cancer somatic mutations. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4368.

Abstract PR08: NF1, MET, and RIT1 mutations are RAS-pathway driver events in lung adenocarcinoma

Lung adenocarcinoma is comprised of distinct mutational subtypes characterized by mutually exclusive oncogenic alterations such as EGFR and KRAS mutations. Identification of these oncogenic events has transformed treatment strategies and drug development for lung adenocarcinoma. However, such mutations have been identified in only 50-60% of lung adenocarcinoma cases in the United States.

We analyzed SNP array, exome, and RNA sequencing data from 230 primary lung adenocarcinomas to identify known and novel mutually exclusive driver events. MET exon 14 skipping was present in 10/230 tumors (4.3%) and only RNA sequencing data allowed robust detection of this event. To identify novel driver events, we performed a focused statistical analysis of the 87/230 tumors (38%) that lacked a mutation in MET or other known oncogenes. Copy number analysis revealed rare, focal amplifications of MET and ERBB2 that were enriched in this subset. Exome analysis revealed significant enrichment of TP53, KEAP1, NF1, and RIT1 mutations in the previously oncogene-negative subset. Of these mutated genes, only NF1 and RIT1 displayed mutual exclusivity with the other known and candidate driver events.

Whereas TP53, KEAP1, and NF1 are well-documented cancer genes, little is known about the role of RIT1 in human cancer. RIT1 is a RAS-subfamily small GTPase with significant homology to HRAS, NRAS, and KRAS. Mutations in RIT1 were present in ∼2% of cases and clustered in the switch II domain. Ectopic expression of mutated RIT1 in murine fibroblasts and human immortalized lung epithelial cells conferred anchorage-independent growth and tumor forming capability. cDNA sequencing identified a p.M90I missense mutation in the NCI-H2110 cell line. Knockdown of RIT1 in NCI-H2110 cells revealed the role of RIT1 in regulation of PI3K and MEK signaling. Consistently, combination PI3K/mTOR/MEK inhibition could inhibit cellular transformation induced by ectopic expression of mutated RIT1, and PI3K/mTOR inhibition suppressed in vivo tumor growth of NCI-H2110 cells.

Recently, RIT1 mutations were described in myeloid malignancies and Noonan syndrome. Our data, together with these reported observations, indicate that RIT1 is a RAS-pathway oncogene in lung adenocarcinoma. In addition, PI3K/mTOR inhibition with or without MEK inhibition should be explored as a therapeutic strategy for RIT1-mutated lung or other RIT1-mutated cancers. This work expands the number of U.S. lung adenocarcinoma tumors with identified driver events from 62% to 75% and nominates these additional alterations as candidate therapeutic targets.

This abstract is also presented as Poster B26.

Citation Format: Alice H. Berger, Angela N. Brooks, Marcin Imielinski, Andrew Cherniack, Fujiko Duke, Nathan Kaplan, Jeremiah Wala, Matthew Meyerson. NF1, MET, and RIT1 mutations are RAS-pathway driver events in lung adenocarcinoma. [abstract]. In: Proceedings of the AACR Special Conference on RAS Oncogenes: From Biology to Therapy; Feb 24-27, 2014; Lake Buena Vista, FL. Philadelphia (PA): AACR; Mol Cancer Res 2014;12(12 Suppl):Abstract nr PR08. doi: 10.1158/1557-3125.RASONC14-PR08

Abstract 4263: Identifying somatic mutation hotspots across protein family alignments

In cancer, somatic driver mutations often target “hotspots” of paralogous residues across evolutionarily related members of a single protein family. These hotspots usually confer a dominant oncogenic function, such as constitutive catalytic activity or binding. These hotspots generally represent the most “druggable” genetic alterations. Examples of protein families targeted in such a manner include the Ras and receptor Tyrosine Kinase family. Protein family hotspots are not directly assessed by standard computational approaches for statistically nominating genes under positive somatic selection, such as MutSig, InVex, or MuSic. These methods only assess single genes for statistical enrichment of total mutation burden or the presence of mutation hotspots. As a result, such approaches are only powered to detect protein family hotspots in cases where each (or at least one) protein family member is very frequently mutated (e.g. KRAS, NRAS, HRAS). They are not powered to detect hotspots in highly functionally redundant families, of which each member may be only mutated in &lt;&lt;1% of a tumor type. To directly identify such protein-family hotspots, we have developed a computational framework, MutPfam. This framework superimposes mutation data onto Pfam (http://pfam.sanger.ac.uk/) (protein family and subfamily multiple sequence alignments and identifies statistically significant hotspots. We demonstate our method on protein families involved in the catalysis of small-molecular catabolism using the TCGA Pan-Cancer dataset (https://tcga-data.nci.nih.gov/) comprising somatic mutation calls for 4608 whole-exome sequenced patients and 21 tumor types. As we demonstrate, our framework enables the de novo discovery of mutation hotspots across protein families. Though developed for somatic mutation analysis, this framework could also be applied to the analysis of inherited mutations. Computational issues meriting future investigation include (1) alternate definitions of protein alignments and sub-families (e.g. involving three dimensional structure, biophysical constraints) (2) improved statistical modeling of the local background mutation rate (incorporating local genomic covariates that mediate heterogeneity) (3) incorporation of variant functional impact scores for missense variants.

Citation Format: Marcin Imielinski, Charles Du, Matthew Meyerson. Identifying somatic mutation hotspots across protein family alignments. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4263. doi:10.1158/1538-7445.AM2014-4263