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Covalent inhibitors of Bruton tyrosine kinase (BTK) have transformed the therapy of chronic lymphocytic leukemia (CLL), but continuous therapy has been complicated by the development of resistance. The most common resistance mechanism in patients whose disease progresses on covalent BTK inhibitors (BTKis) is a mutation in the BTK 481 cysteine residue to which the inhibitors bind covalently. Pirtobrutinib is a highly selective, noncovalent BTKi with substantial clinical activity in patients whose disease has progressed on covalent BTKi, regardless of BTK mutation status. Using in vitro ibrutinib-resistant models and cells from patients with CLL, we show that pirtobrutinib potently inhibits BTK-mediated functions including B-cell receptor (BCR) signaling, cell viability, and CCL3/CCL4 chemokine production in both BTK wild-type and C481S mutant CLL cells. We demonstrate that primary CLL cells from responding patients on the pirtobrutinib trial show reduced BCR signaling, cell survival, and CCL3/CCL4 chemokine secretion. At time of progression, these primary CLL cells show increasing resistance to pirtobrutinib in signaling inhibition, cell viability, and cytokine production. We employed longitudinal whole-exome sequencing on 2 patients whose disease progressed on pirtobrutinib and identified selection of alternative-site BTK mutations, providing clinical evidence that secondary BTK mutations lead to resistance to noncovalent BTKis.

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Although BCL2 mutations are reported as later occurring events leading to venetoclax resistance, many other mechanisms of progression have been reported but remain poorly understood. Here we analyze longitudinal tumor samples from eleven patients with disease progression on venetoclax to characterize the clonal evolution of resistance. All patients tested showed increased in vitro resistance to venetoclax at their post-treatment timepoint. We found the previously described acquired BCL2-G101V mutation in only 4/11 patients with 2 patients showing very low variant allele fraction (VAF; 0.03-4.68%). Whole exome sequencing (WES) revealed acquired loss(8p) in 4/11 patients of which 2 patients also have gain (1q21.2-21.3) in the same cells, affecting the MCL-1 gene. In vitro experiments showed that CLL cells from the four patients with loss(8p) were more resistant to venetoclax than those without it, while the cells from two patients also carrying gain (1q21.2-21.3) showed increased sensitivity to MCL-1 inhibition. Progression samples with gain (1q21.2-21.3) were more susceptible to combination MCL-1 inhibitor with venetoclax. Differential gene expression analysis comparing bulk RNAseq data from pre-treatment and progression time points of all patients showed upregulation of proliferation, BCR and NFKB gene sets including MAPK genes. Cells from progression timepoints demonstrated upregulation of surface immunoglobulin M (sIgM) and higher pERK levels compared to the pre-timepoint, suggesting an upregulation of BCR signaling that activates the MAPK pathway. Overall, our data suggest several mechanisms of acquired resistance to venetoclax in CLL that could pave the way for rationally designed combination treatments for venetoclax resistant CLL patients.

Sacituzumab govitecan (SG), the first antibody–drug conjugate (ADC) approved for triple-negative breast cancer, incorporates the anti-TROP2 antibody hRS7 conjugated to a topoisomerase-1 (TOP1) inhibitor payload. We sought to identify mechanisms of SG resistance through RNA and whole-exome sequencing of pretreatment and postprogression specimens. One patient exhibiting de novo progression lacked TROP2 expression, in contrast to robust TROP2 expression and focal genomic amplification of TACSTD2/TROP2 observed in a patient with a deep, prolonged response to SG. Analysis of acquired genomic resistance in this case revealed one phylogenetic branch harboring a canonical TOP1E418K resistance mutation and subsequent frameshift TOP1 mutation, whereas a distinct branch exhibited a novel TACSTD2/TROP2T256R missense mutation. Reconstitution experiments demonstrated that TROP2T256R confers SG resistance via defective plasma membrane localization and reduced cell-surface binding by hRS7. These findings highlight parallel genomic alterations in both antibody and payload targets associated with resistance to SG.Significance:These findings underscore TROP2 as a response determinant and reveal acquired SG resistance mechanisms involving the direct antibody and drug payload targets in distinct metastatic subclones of an individual patient. This study highlights the specificity of SG and illustrates how such mechanisms will inform therapeutic strategies to overcome ADC resistance.This article is highlighted in the In This Issue feature, p. 2355

Figure S1, radiographic assessment of key lesions of patient MGH-18; Figure S2, supplementary genomic analysis for patient MGH-18; Figure S3, supporting data for mechanism of TROP2 T256R; Figure S4, TROP2 immunohistochemistry for metastatic lesions of MGH-18; Table S1, detailed cohort characteristics; Table S2, patient treatment histories; Table S3, supplementary mutational data for MGH-18; Table S4, antibodies used.

Supplementary Table S1. Normalized Average E6 Seroreactivity in HNC Subsites

Figures S1-S3. All supplementary figures are included in this file. Descriptions are given for each figure on the image itself. Supplementary Figure S1: OPC GWAS analysis Supplementary Figure S2: Comparative scatter plot by HNSCC tumor site vs HPV E6 serology Supplementary Figure S3: DAPPLE randomization and extended boundary analysis

Background. Despite substantial progress in the treatment of HER2+ MBC, most patients (pts) still experience disease progression and cancer-related death. HER2-directed TKIs are highly effective therapies for pts with HER2+ MBC; however, an understanding of resistance mechanisms is needed. Pts receiving HER2-directed TKIs with cell-free DNA (cfDNA) sampling across the treatment spectrum present a unique opportunity to examine genomic alterations. Methods. Pts with biopsy-proven HER2+ MBC were selected from DF/HCC approved protocols for ultra-low pass whole genome sequencing if ≥1 cfDNA and/or tissue sample had been collected prior to and after at least six weeks of TKI treatment. Only pts with ≥ 1 sample with tumor fraction (TFx) ≥ 9.5% and ≥ 1 additional sample with TFx ≥ 4.5% were analyzed. Whole exome sequencing (WES) was performed on 19 tumor biopsies and 64 cfDNA samples from 25 pts. WES samples were analyzed, variants called and annotated, copy number profiles inferred, and TFx estimated. PhylogicNDT was used to detect the phylogenetic architecture, and clones were identified as growing, stable, shrinking, or truncal; mutational signatures were called using SignatureAnalyzer. After filtering likely benign variants, mutations were labeled likely resistance mechanisms if there was known evidence of resistance to anti-HER2 therapy in a human breast cancer cell line, breast cancer mouse models, or in vivo. Findings were correlated with pt clinicopathologic data. Results. In 4/8 pts with acquired resistance (TKI treatment ≥ 180 days), we identified alterations in previously characterized pathways and genes that could explain treatment resistance (e.g. PIK3CA, ERBB2, FGFR2). Mutations in growing subclones identified potential novel mechanisms of resistance and included inactivating mutations in CDK12, KMT2D, KMT2C, CHEK2, BRCA2, and FAT1 genes. In 7/17 pts with intrinsic resistance, we identified mutations in overlapping pathways and genes such as ERBB2 and PIK3CA, which were present in both growing subclonal and truncal clones. Four pts with hormone receptor positive disease - two of whom had not received prior aromatase inhibitors - had an activating ESR1 hotspot mutation (D538G). This raises the possibility that activating ESR1 mutations may be involved in resistance in these cases. Mutational signature analysis revealed a subset of samples with widespread APOBEC activation (with and without hyper mutation), subclonal HR/MMR-related signature, and capecitabine-related 5FU signature. Conclusions. Genomic analysis of paired samples from pts with HER2+ MBC identifies candidate resistance mechanisms to anti-HER2 TKIs and clonal evolution over time in the context of heterogeneity in treatment and sample timing. Additional studies will determine the functional role and clinical utility of assessing these alterations to overcome resistance. Citation Format: Heather A. Parsons, Conor Messer, Katheryn Santos, Brian P. Danysh, Melissa E. Hughes, Ashka Patel, Raquel A. Jacobs, Kara Slowik, Julian Hess, Chip Stewart, Kristy Schlueter-Kuck, Kahn Rhrissorrakrai, Filippo Utro, Chaya Levovitz, Nikhil Wagle, Jose Pablo Leone, Rachel Freedman, Laxmi Parida, Ian E. Krop, Gad Getz, Nancy U. Lin. Genomic mechanisms of resistance to tyrosine kinase inhibitors (TKIs) in HER2+ metastatic breast cancer (HER2+ MBC). [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3874.

Detection of multiple primary lung cancers is increasing in frequency, with up to 15% of all non-small cell lung cancer (NSCLC) patients presenting with two or more anatomically separate tumor nodules on CT scans. Increased detection is in part due to expanded lung cancer screening criteria in an aging population. Distinguishing multiple primary tumors from intrapulmonary metastases can be challenging, yet is critical for determining clinical management. Current models predict development of multiple primary tumors out of a cancerized field, such as occurs due to smoking. The occurrence of multiple primary tumors is unexplained in patients with EGFR-mutant lung cancer (~15% of all NSCLC), lacking environmental exposures. We identified patients with non-small cell lung cancer (NSCLC) who presented with multiple primary EGFR-mutant tumors, in the absence of family history of lung cancer or heavy smoking. We subjected the macrodissected tumors and surrounding normal tissues to whole exome sequencing as well as to analysis of hypermutable poly-guanine (poly-G) repeats, which are two orthogonal methods of lineage tracing. An additional familial case with a germline EGFR-T790M mutation was used to establish parameters for timing of somatic mutations, and functional properties of novel germline variants were modeled in vitro. Of eleven non-familial NSCLC cases with two or more geographically distinct EGFR-mutant lung cancers, two patients harbored a germline EGFR variant allele, which confers moderately enhanced signaling in vitro, followed by a somatically acquired EGFR mutation. In an additional four cases, both whole exome sequencing and poly-G repeat analyses indicate a distant shared somatic cell-of-origin, consistent with embryonic mosaicism. Three cases revealed clinically unappreciated metastasis and two cases remain unexplained. Together, our data suggest that multiple primary lung cancers with somatic EGFR driver mutations may result from genetic susceptibility, attributable either to attenuated EGFR germline variants or to embryonic mosaicism resulting in geographically disparate patches of predisposed lung tissue. Such predisposed cases should be surveilled for early detection of future tumors, and surgical resection in these cases should consider the life-long risk of additional cancers. Citation Format: Risa Burr, Ignaty Leshchiner, Christina L. Costantino, Martin Blohmer, Tilak Sundaresan, Justin Cha, Karsen Seeger, Sara Guay, Brian P. Danysh, Ira Gore, Raquel A. Jacobs, Kara Slowik, Filippo Utro, Kahn Rhrissorrakrai, Chaya Levovitz, Jaimie L. Barth, Taronish Dubash, Brian Chirn, Laxmi Parida, Lecia V. Sequist, Mari Mino-Kenudson, Kamila Naxerova, Shyamala Maheswaran, Gad Getz, Daniel A. Haber. Mechanisms of genetic predisposition to multifocal lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 771.

The emergence of COVID19 created incredible worldwide challenges but offers unique opportunities to understand the physiology of its risk factors and their interactions with complex disease conditions, such as metabolic syndrome. Epidemiological analysis powered by topological data analysis (TDA) is a novel approach to uncover these clinically relevant interactions. Here TDA utilized Explorys data to discover associations among severe COVID19 and metabolic syndrome, and it explored the probative value of drug prescriptions to capture the involvement of RAAS and hypertension with COVID19 as well as modification of risk factor impact by hyperlipidemia on severe COVID19.

Acral melanoma, the most common melanoma subtype among non-Caucasian individuals, is associated with poor prognosis. However, its key molecular drivers remain obscure. Here, we performed integrative genomic and clinical profiling of acral melanomas from a cohort of 104 patients treated in North America or China. We found that recurrent, late-arising amplifications of cytoband chr22q11.21 are a leading determinant of inferior survival, strongly associated with metastasis, and linked to downregulation of immunomodulatory genes associated with response to immune checkpoint blockade. Unexpectedly, LZTR1 – a known tumor suppressor in other cancers – is a key candidate oncogene in this cytoband. Silencing of LZTR1 in melanoma cell lines caused apoptotic cell death independent of major hotspot mutations or melanoma subtypes. Conversely, overexpression of LZTR1 in normal human melanocytes initiated processes associated with metastasis, including anchorage-independent growth, formation of spheroids, and increased levels of MAPK and SRC activities. Our results provide new insights into the etiology of acral melanoma and implicate LZTR1 as a key tumor promoter and therapeutic target

Richter syndrome (RS), an aggressive lymphoma that develops in patients with chronic lymphocytic leukemia (CLL), is a striking example of histologic transformation. While recent therapeutic advances have transformed the treatment landscape of CLL and lymphoma, RS remains associated with dismal overall survival. Despite an advanced genomic and molecular characterization of CLL over the past decade, the current understanding of the genetic factors driving evolution of CLL to RS is limited. To decipher the genetics underlying this transformation, we have performed an integrative analysis of exome, genome and transcriptome data generated from matched RS and CLL samples from a discovery cohort of 53 patients with newly diagnosed RS of DLBCL histology. Through computational deconvolution of CLL and RS clones, we constructed phylogenetic relationships and traced evolution of CLL to RS, confirming both clonal related (87%) and unrelated cases (13%). In addition to identifying recognized RS-risk genetic lesions, we discovered novel RS-specific alterations, including 5 putative somatic driver genes (IRF2BP2, SRSF1, B2M, DNMT3A and EZH2), frequent copy number alterations beyond del(9p21)(CDKN2A/B), (including amp(7q21.2) (CDK6), amp(9p24) (PDL1/L2), and amp(1q23)(MCL1)), and recurrent whole genome duplication and chromothripsis. Integration of exome and genome sequencing data led to the identification of distinct molecular subtypes of RS with prognostic importance. To confirm these molecular subtypes, a validation cohort of 47 RS cases has been assembled with paired exome and transcriptome data. To further investigate the stepwise clonal evolution of CLL to RS, we performed single-cell RNA-sequencing on biopsy samples obtained at diagnosis from 5 individuals with clonally related transformation. Using a novel tool, CNVSingle, we inferred allele specific single-cell copy number alterations that enabled identification of the single-cell clusters representing distinct CLL and RS genetic subclones as well as intermediate, or transitional, evolutionary states. RS cells displayed gene expression enriched in pathways of MYC targets and cell cycle, in line with similar analysis on bulk transcriptomes. Finally, by ultra-low pass (ULP)-WGS sequencing of plasma samples from RS patients, we demonstrate detection of RS tumor DNA in plasma months prior to initial clinical diagnosis (n=3 of 6) or post-allogeneic stem cell transplant relapse (n=2 of 2). cfDNA is thus a promising tool for early detection of emerging RS and RS relapse as well as for non-invasive detection surrounding diagnosis. Altogether, our study defines RS-specific alterations and provides a molecular definition of RS, identifies distinct genetic subtypes of RS with prognostic significance, traces the evolutionary path to RS and suggests future strategies for improved detection. Citation Format: Erin M Parry, Ignaty Leshchiner, Romain Guieze, Connor Johnson, Eugen Tausch, Sameer A Parikh, Camilla K Lemvigh, Conor Messer, Filippo Utro, Chaya Levovitz, Kahn Rhrissorrakrai, Matthew S Davids, Julien Broseus, Shuqiang Li, Ziao Lin, Binyamin A Knisbacher, Christof Schneider, Laura Z Rassenti, Thomas J Kipps, Nitin Jain, William Wierda, Florence Cymbalista, Neil E Kay, Kenneth J Livak, Brian P Danysh, Chip Stewart, Donna Neuberg, Jennifer R Brown, Laxmi Paridi, Stephan Stilgenbauer, Gaddy Getz, Catherine Wu. Evolutionary history of transformation from chronic lymphocytic leukemia to Richter syndrome [abstract]. In: Proceedings of the Third AACR International Meeting: Advances in Malignant Lymphoma: Maximizing the Basic-Translational Interface for Clinical Application; 2022 Jun 23-26; Boston, MA. Philadelphia (PA): AACR; Blood Cancer Discov 2022;3(5_Suppl):Abstract nr A13.

Acral melanoma, the most common melanoma subtype among non-Caucasian individuals, is associated with poor prognosis. However, its key molecular drivers remain obscure. Here, we performed integrative genomic and clinical profiling of acral melanomas from a cohort of 104 patients treated in North America or China. We found that recurrent, late-arising amplifications of cytoband chr22q11.21 are a leading determinant of inferior survival, strongly associated with metastasis, and linked to downregulation of immunomodulatory genes associated with response to immune checkpoint blockade. Unexpectedly, LZTR1 – a known tumor suppressor in other cancers – is a key candidate oncogene in this cytoband. Silencing of LZTR1 in melanoma cell lines caused apoptotic cell death independent of major hotspot mutations or melanoma subtypes. Conversely, overexpression of LZTR1 in normal human melanocytes initiated processes associated with metastasis, including anchorage-independent growth, formation of spheroids, and increased levels of MAPK and SRC activities. Our results provide new insights into the etiology of acral melanoma and implicate LZTR1 as a key tumor promoter and therapeutic target.

Motivation Sampling circulating tumor DNA, ctDNA, using liquid biopsies offers clinically important benefits for monitoring of cancer progression. A single ctDNA sample represents a mixture of shed tumor DNA from all known and unknown lesions within a patient. Although shedding levels have been suggested to hold the key to identifying targetable lesions and uncovering treatment resistance mechanisms, the amount of DNA shed by any one specific lesion is still not well characterized. We designed the LSM (Lesion Shedding Model) to order lesions from the strongest to the poorest shedding for a given patient. Our framework intrinsically models for missing/hidden lesions and operates on blood ctDNA and lesion assays to estimate the potential relative shedding levels of lesions into the blood. By characterizing the lesion-specific ctDNA shedding levels, we can better understand the mechanisms of shedding as well as more accurately contextualize and interpret ctDNA assays to improve their clinical impact. Results We verified the accuracy of the LSM under controlled conditions using a simulation approach as well as testing on two gastrointestinal cancer patients. In the simulation we created a synthetic blood ctDNA sample per patient, where specific lesions are assigned predefined shedding levels. The simulated data mirrors real data lesion genomic similarities. The LSM correctly obtains a partial order of the lesions, i.e. accurately stratifies the lesions by their assigned shedding levels for simulations on two patients with strikingly different numbers of biopsied lesions, 4 and 17. The LSM’s accuracy in identifying the top shedding lesion was not impacted by the higher number of lesions considered. We then applied LSM to two gastrointestinal cancer patients with available ctDNA blood samples and multiple biopsied lesions and found that indeed there were lesions that were consistently shedding more than other lesions into the patients’ blood. We also found that in both patients the top shedding lesion was one of the only clinically progressing lesions at the time of biopsy suggesting a connection between high ctDNA shedding and clinical progression. The LSM provides a much needed framework with which to understand ctDNA shedding and how to apply ctDNA assays. Availability Binary is available at https://github.com/ComputationalGenomics/LSM

Detecting cancer at early stages or upon recurrence is critical to decreasing cancer morbidity and mortality. We developed TuFEst (Tumor Fraction Estimator), a cost-effective computational approach for pan-cancer detection and tumor burden estimation from ultra-low coverage whole genome sequencing (~0.1x, ULP-WGS) of minimally invasive cell-free DNA (cfDNA). Current state-of-the-art methods estimate tumor fraction (TF) from ULP-WGS depending exclusively on total copy number variation, which loses tumor signal in either copy number-quiet tumors or tumors with copy-neutral loss-of-heterozygosity. Additionally, it is difficult in many cases to distinguish clonal from sub-clonal copy-number events, therefore complicating the ability to estimate tumor fraction. On the other hand, fragments shed into the blood from cancer cells, i.e., circulating tumor DNA (ctDNA), of various cancer types show significantly different length distribution than that from normal cells in healthy donors. By synergistically integrating both (i) copy number variation and (ii) altered fragment length signals, TuFEst successfully achieved higher sensitivity and more accurate TF estimation than current methods in >200 cfDNA samples across different cancer types, even in low tumor-fraction cases (TF < 0.1%). Application of TuFEst to serial cfDNA samples from blood biopsies demonstrate its utility in accurately estimating TF in ~100 cfDNAs, suggesting that TuFEst can be used to detect early cancer recurrence during different treatments. In one breast cancer patient receiving CDK4/6 therapy, TuFEst indicated disease progression 262 days earlier than routine imaging. Altogether, our work suggests that accurate TF estimation from cfDNA can not only aid in detecting cancer at early stages but also provide evidence of disease progression during treatment. We believe that such a non-invasive, cost-effective, pan-cancer detection method will benefit both initial cancer screening and monitoring of resistance to therapy in clinical applications. Citation Format: Ziao Lin, Chip Stewart, Elizabeth E. Martin, Brian P. Danysh, Raquel A. Jacobs, Kara Slowik, Lee Lawton, Elizabeth Lightbody, Kahn Rhrissorrakrai, Filippo Utro, Chaya Levovitz, Carrie Cibulskis, Irene M. Ghobrial, Margaret Shipp, Ryan B. Corcoran, Dejan Juric, Laxmi Parida, Heather A. Parsons, Gad Getz. TuFEst: a sensitive and cost-effective pan-cancer detection approach with accurate tumor fraction estimation [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 5162.

We studied resistance mechanisms to hormone therapy and CDK4/6 cell cycle inhibitors in ER+ breast cancer by analyzing whole-exome, whole-genome, single-cell, and bulk transcriptomes in 120 autopsy samples from 13 patients obtained by the Massachusetts General Hospital Rapid Autopsy program. For each patient, we inferred the clonal structure of the samples and tracked the metastatic spread of different clones throughout the body. For 7 patients, we also analyzed serial cfDNA samples to identify clones that were selected for during treatment. We identified significantly recurrent and convergent (arising independently in distinct clones) acquired mutations in ESR1, KRAS, and chromatin modifier genes, in particular, mutations in KMT2C, which may represent mechanisms of drug resistance in this clinical setting. To experimentally study the role of KMT2C mutations, we used CRISPR/Cas9 to knock out KMT2C in the ER+ CAMA1 breast cancer cell line that is sensitive to both ER and CDK4/6 inhibition. KMT2C knock-out cells demonstrated significantly increased viability under treatment with fulvestrant (ERi), palbociclib (CDK4/6i), or their combination compared to the control cell lines. We show that this increased drug resistance is driven by downregulation of the ESR1 pathway, suggesting a decreased dependency on ER signaling for cell cycle progression. In addition to the early survival benefit, KMT2C knock-out resulted in a dramatic outgrowth of cells under long-term fulvestrant treatment. The KMT2C KO fulvestrant-resistant outgrown cells were highly resistant to the CDK4/6 inhibitors palbociclib, ribociclib, and abemaciclib compared to control cells, as well as to novel ERalpha inhibitors and a range of targeted therapies currently in clinical trials. By testing a panel of compounds on KMT2C KO and control cell lines, we propose potential novel therapeutic strategies that may help overcome the development of resistance in KMT2C-mutant cells. These findings suggest that KMT2C mutations may be a mechanism of acquired resistance to CDK4/6 inhibitor combinations, and subsequent treatment with therapies directed towards ER or CDK4/6 pathways may be ineffective and other treatment avenues need to be developed. Citation Format: Elizaveta Leshchiner, Ignaty Leshchiner, Elizabeth E. Martin, Christopher T. Chen, Thomas Zhang, Christopher Pinto, Kahn Rhrissorrakrai, Filippo Utro, Chaya Levovitz, Raquel A. Jacobs, Brian P. Danysh, Kara Slowik, Maida Broudo, Laxmi Parida, Dejan Juric, Gad Getz. Chromatin modifier alterations confer resistance to endocrine deprivation and CDK4/6 inhibitors in ER+ breast cancer and drive convergent evolution in patient autopsy lesions [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 1789.

Chimeric Antigen Receptor (CAR)-T cell therapy has revolutionized the treatment of hematologic malignancies. Approximately half of patients with refractory large B-cell lymphomas achieve durable responses from CD19-targeting CAR-T treatment, across the commercially available CAR-T products with differing designs. Known failure mechanisms such as antigen loss account for only a fraction of cases without durable responses, and this knowledge gap has limited advances in CAR-T engineering and optimal targeting to patients. We hypothesized that characterization of the transcriptional programs and temporal evolution of CAR-T and host immune cell populations could provide novel insights into the basis of clinical response to CAR-T cell therapy for B cell lymphoma. We performed 10X single-cell RNA sequencing on serial samples collected from 32 individuals with high grade B cell lymphoma treated with the two first FDA-approved CD19 CAR-T products: axicabtagene ciloleucel (axi-cel, utilizing a CD28z costimulatory domain) and tisagenlecleucel (tisa-cel, with a 4-1BB domain). We analyzed 106 samples, including pre-infusion blood samples, infusion product, and post-infusion T cells sorted by flow cytometry into CAR+ and CAR- populations. Analyzing 602,577 single-cell transcriptomes, we discerned major differences in the dynamics of response of the two products. Tisa-cel responders showed dramatic expansion of CD8+ T cells at day 7 after infusion, which represented less than 10% of cells in the product. Conversely, CD8+ T cells in products of non-responders failed to expand to the same degree post-infusion and had a more effector- than memory-like T cell phenotype. In one tisa-cel–treated patient who had no CD8+ T cell expansion after initial infusion and relapsed at 6 months post-infusion, re-treatment with a second dose of the same product led to a durable response and was associated with greater CD8+ T cell expansion as well as a shift in CD4+ T phenotype from cytotoxic to helper. In contrast, axi-cel responders had pre-expanded effector populations distributed more heterogeneously among CD4+ and CD8+ T cells. Finally, we identified nominal elevations in CAR-T regulatory cells (CAR-Tregs) among both axi-cel and tisa-cel non-responders in our dataset, which we confirmed in an external dataset. These small increases in CAR-Tregs were sufficient to uniformly suppress conventional CAR-T cell expansion and drive late relapses in an in vivo mouse model of lymphoma after treatment with CARs with either CD28z or 4-1BB co-stimulatory domains. In summary, this represents the largest CAR-T scRNAseq cohort established thus far and provides important insights into (i) the temporal dynamics of a successful CAR-T response, (ii) the molecular phenotypes of CAR-T cells with different costimulatory domains, and (iii) the capacity for small increases in CAR-Tregs to drive relapse. Citation Format: Nicholas J. Haradhvala, Mark B. Leick, Katie Maurer, Satyen Gohil, Rebecca C. Larson, Estelle Yao, Matthew J. Frigault, Shuqiang Li, Kenneth J. Livak, Kahn Rhrissorrakrai, Filippo Utro, Chaya Levovitz, Raquel A. Jacobs, Kara Slowik, Brian P. Danysh, Laxmi Parida, Catherine J. Wu, Gad Getz, Marcela V. Maus. Differential dynamics of response at single cell resolution between axi-cel and tisa-cel CAR-T therapy in refractory B-cell lymphomas [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 3575.

Richter’s syndrome (RS) arising from chronic lymphocytic leukemia (CLL) is a striking example of an aggressive malignant histology that emerges from indolent cancer. RS is a major barrier to disease control in CLL and is associated with poor clinical outcomes and limited survival. The genetic basis of RS is poorly understood, and its relationship to the antecedent CLL remains incompletely characterized. To study RS, we performed whole-exome sequencing (WES) on samples collected from 52 patients with RS of diffuse large B cell lymphoma (DLBCL) histology. For this genomic characterization, samples from 42 patients were analyzed as ‘trios’ (matched germline, CLL and RS tissue DNA) and those from 10 as ‘duos’ (matched CLL and RS DNA). Beyond addressing contamination of CLL DNA in the germline sample, we developed methods for discriminating between the RS and CLL clones which often coexist in the same samples. The discovery cohort revealed that RS and CLL were clonally-related in 45/52 (87%) cases based on WES analysis, with a distinct RS clone emerging from a CLL subclone. The remaining 13% were determined to be clonally unrelated. RS clones presented ~3x higher rates of additional mutations than the ancestral CLL clones from which they developed. We identified novel RS somatic driver mutations (in IRF2BP2, SRSF1, B2M, DNMT3A and others), a high rate of copy number variations with recurrent deletions (e.g., del(17p) [TP53], del(13q14.3), del(7q36), and del(15q13.11) [MGA], del(9p21.3) [CDKN2A/B], del(16q12.2)), focal amplifications (amp(7q21.2) [CDK6], amp(8q24.2) [RECQL4, MYC], amp(13q31.2) [ERCC5], and frequent whole genome duplication. To further investigate RS and CLL clonal evolution, we performed single-cell RNA-sequencing on biopsies at the time of RS diagnosis in 5 individuals with clonally related transformation. Using our novel tool, CNVSingle, we inferred allele specific single-cell copy number alterations, yielding cluster-specific copy number profiles that matched the WES results of individual subclones of the RS and CLL populations. This enabled mapping genetic clones to specific expression patterns. Finally, we devised and tested a methodology that uses cfDNA for early detection of emerging Richter’s disease and have successfully identified Richter‘s tumor DNA in the blood several months prior to the clinical diagnosis. Our study thus defines drivers, distinct molecular subtypes and evolutionary path to RS and suggests strategies for its improved detection. Citation Format: Erin M. Parry, Ignaty Leshchiner, Romain Guièze, Connor Johnson, Eugen Tausch, Sameer Parikh, Camilla Lemvigh, Conor Messer, Daniel Rosebrock, Filippo Utro, Chaya Levovitz, Kahn Rhrissorrakrai, Matthew Davids, Raquel A. Jacobs, Kara Slowik, Julien Broseus, Shanye Yin, Shuqiang Li, Geoff Fell, Ziao Lin, Binyamin A. Knisbacher, Neil Ruthen, Dimitri Livitz, Christof Schneider, Jialin Ma, Julian Hess, Laura Z. Rassenti, Thomas J. Kipps, Nitin Jain, William Wierda, Florence Cymbalista, Neil E. Kay, Kenneth J. Livak, Brian P. Danysh, Chip Stewart, Donna Neuberg, Jennifer R. Brown, Laxmi Parida, Stephan Stilgenbauer, Gad Getz, Catherine J. Wu. Evolutionary history of transformation from chronic lymphocytic leukemia to Richter’s syndrome [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 4007.

Studies of therapeutic resistance in cancer have conventionally focused on identification of acquired exome mutations in tissue or circulating DNA at progression. However, this strategy has generated limited insights into resistance to CDK4/6 inhibitor and endocrine therapy combinations, which are the key first-line treatment modality in ER+ breast cancer. We utilized an alternative approach of integrated proteogenomic analysis of 8 pairs of pre- and post-treatment biopsies, 67 rapid autopsy samples, and 17 plasma samples from 12 ER+ breast cancer patients treated with CDK4/6 inhibitor combinations at a large academic center. In addition to whole exome sequencing, RNA sequencing, and immunohistochemistry (IHC) profiling on all tissue samples, we performed deep-scale mass spectrometry-based proteomics and phospho-proteomics on 35 rapid autopsy samples from 5 patients that had sufficient protein yields for analysis. We describe a patient with acquired Rb IHC loss after treatment progression without a Rb1 genetic alteration detected in exome sequencing or Rb transcript loss at her post-progression biopsy. Integrated proteogenomic analysis of ten autopsy lesions from this patient revealed convergent Rb protein loss across all tumor lesions, including lesions with and without Rb1 exome alterations. ESR1 mutations were frequently acquired at post-treatment biopsies at high cancer cell fractions, but a pre-existing ESR1-mutant subclone was nevertheless lost in a patient who acquired a concurrent Rb1-mutant subclone in the same tumor lesion. This suggests ESR1 mutations confer a relative fitness advantage that can nevertheless be mitigated in the presence of more potent synchronous resistance mechanisms. To investigate whether circulating tumor DNA reflects DNA shed specifically by progressing tumor lesions, we modeled the DNA shedding of tumor lesions into the plasma for 3 patients with both rapid autopsy and serial plasma samples available. In some instances, new lesions began shedding significant amounts of DNA months prior to their initial radiographic appearance. Together, these results illustrate the value of integrated multi-omics interrogation of different sample types to investigate therapeutic resistance and advance precision oncology. Citation Format: Christopher T. Chen, Ignaty Leshchiner, Liz Martin, Harry Kane, Kahn Rhrissorrakrai, Filippo Utro, Chaya Levovitz, Michael Gillette, Shankha Satpathy, Christopher Pinto, Daniel McLoughlin, Read Allen, Brian P. Danysh, Kara Slowik, Raquel A. Jacobs, Steven Carr, Laxmi Parida, Gad Getz, Dejan Juric. Proteogenomic characterization of CDK4/6 inhibitor-resistant ER+ breast cancer [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2021 Oct 7-10. Philadelphia (PA): AACR; Mol Cancer Ther 2021;20(12 Suppl):Abstract nr P065.

Richter's syndrome (RS) arising from chronic lymphocytic leukemia (CLL) is a striking example of an aggressive malignant histology that emerges from indolent cancer. A major barrier to disease control in CLL, RS is associated with poor clinical outcomes and limited survival. The genetic basis of RS is poorly understood and its relationship to antecedent CLL remains incompletely characterized. Notable challenges to the genomic study of RS includes those of sample acquisition, the distinction between true tumor events rather than sequence artifacts in archival fixed tissue, and the limitations of available computational techniques for deconvoluting admixtures of CLL and RS DNA within the same biopsy specimen. To address these challenges and characterize the genetic profile of RS, we performed whole-exome sequencing (WES) on samples collected from 42 patients with RS of diffuse large B cell lymphoma (DLBCL) histology. For this genomic characterization, samples from 37 patients were analyzed as 'trios' (matched germline, CLL and RS tissue DNA) and those from 5 as 'duos' (matched CLL and RS DNA). CLL diagnosis preceeded RS diagnosis by a median of 60.6 months (range 0.1-234.5). The median number of prior CLL-directed therapies was 2 (range 0-10). 8 patients had no prior CLL-directed therapy, while 9 were exposed to novel agents. The median time from most proximal CLL sampling to RS was 2.7 months (range: 82.2 months pre- to 3.8 months post RS diagnosis). Critical analytic innovations applied to this dataset included addressing contamination of CLL DNA in the germline sample (through the tool DeTIN) and generating the ability to discriminate between clones arising from RS or from CLL, even while both histologies were commonly co-existing within originating biopsies (via the tool PhylogicNDT). From this discovery cohort of 42 cases, 36 (86%) revealed RS and CLL to be clonally-related based on WES analysis, with a distinct RS clone emerging from an existing CLL subclone. Of the 6 (14%) cases determined to be clonally unrelated by WES, 4 had been previously examined by IGHV sequencing; only 1 of 4 was categorized as clonally unrelated, likely due to CLL and RS admixture. RS displayed mutational signatures reflecting aging (CpG), canonical AID, and non-canonical AID processes. Through deconvoluting clonal composition using PhylogicNDT in related sample trios (n=31), we established several notable differences compared to antecedent CLL. First, RS clones presented higher rates of additional mutations than the ancestral CLL clones from which they developed (2.47 vs. 0.86 Mut/Mb, p To further investigate RS and CLL clonal evolution at high resolution, we performed single-cell RNA-sequencing (10x Genomics), on biopsies at the time of RS diagnosis in 5 individuals with clonally related transformation. Data analysis and clustering was conducted using Seurat(v3) with doublet removal (DoubletFinder). We identified CNV in single-cell transcriptomes that matched the WES copy-number profiles of individual subclones of the RS and CLL populations and thus linked subclones identified by WES to single-cell expression clusters and states, revealing CLL, RS and intermediate evolutionary cell states. In conclusion, we identify that RS arises from CLL subclones through distinct mutational trajectories. Further molecular subclassification of RS, including genetic characterization of additional cases, and linking mutational data with clinical outcomes is ongoing and has potential to alter clinical classification and prognostication of RS. Disclosures Guieze: abbvie: Honoraria, Other: advisory board, travel funds; janssen cilag: Honoraria, Other: advisory board, travel funds; roche: Other: travle funds; gilead: Honoraria, Other: travel funds; astrazanecka: Honoraria, Other: advisory board. Leshchiner:PACT Pharma, Inc.: Consultancy. Tausch:Roche: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria, Research Funding; Janssen-Cilag: Consultancy, Honoraria, Research Funding. Davids:Genentech: Consultancy, Research Funding; Janssen: Consultancy; Gilead Sciences: Consultancy; Novartis: Consultancy, Research Funding; MEI Pharma: Consultancy, Research Funding; Surface Oncology: Research Funding; AbbVie: Consultancy; Adaptive Biotechnologies: Consultancy; Merck: Consultancy; Pharmacyclics: Consultancy, Research Funding; TG Therapeutics: Consultancy, Research Funding; Verastem: Consultancy, Research Funding; Syros Pharmaceuticals: Consultancy; Sunesis: Consultancy; Zentalis: Consultancy; AstraZeneca: Consultancy, Research Funding; Ascentage Pharma: Consultancy, Research Funding; Eli Lilly: Consultancy; Research to Practice: Honoraria; Celgene: Consultancy; BeiGene: Consultancy; Bristol Myers Squibb: Research Funding. Elagina:AbbVie: Current Employment. Jain:TG Therapeutics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Servier: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Precision Bioscienes: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Incyte: Research Funding; Pfizer: Research Funding; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Fate Therapeutics: Research Funding; Verastem: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Research Funding; Cellectis: Research Funding; BeiGene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Aprea Therapeutics: Research Funding; Genentech: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; ADC Therapeutics: Research Funding; AstraZeneca: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Kipps:Oncternal Therapeutics, Inc.: Other: Cirmtuzumab was developed by Thomas J. Kipps in the Thomas J. Kipps laboratory and licensed by the University of California to Oncternal Therapeutics, Inc., which provided stock options and research funding to the Thomas J. Kipps laboratory, Research Funding; Celgene: Honoraria, Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Genentech/Roche: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; VelosBio: Research Funding; Pharmacyclics/ AbbVie, Breast Cancer Research Foundation, MD Anderson Cancer Center, Oncternal Therapeutics, Inc., Specialized Center of Research (SCOR) - The Leukemia and Lymphoma Society (LLS), California Institute for Regenerative Medicine (CIRM): Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Ascerta/AstraZeneca, Celgene, Genentech/F. Hoffmann-La Roche, Gilead, Janssen, Loxo Oncology, Octernal Therapeutics, Pharmacyclics/AbbVie, TG Therapeutics, VelosBio, and Verastem: Membership on an entity's Board of Directors or advisory committees. Broséus:Novartis: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; AstraZeneca: Consultancy, Honoraria; Gilead: Honoraria. Kay:MEI Pharma: Research Funding; Cytomx: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Juno Theraputics: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; Morpho-sys: Membership on an entity's Board of Directors or advisory committees. Purroy:AstraZenica: Current Employment. Utro:IBM: Current Employment. Rhrissorrakrai:IBM: Current Employment. Levovitz:IBM: Current Employment. Parikh:GlaxoSmithKline: Honoraria; Pharmacyclics: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; MorphoSys: Research Funding; TG Therapeutics: Research Funding; Merck: Research Funding; AbbVie: Honoraria, Research Funding; Ascentage Pharma: Research Funding; Genentech: Honoraria; Verastem Oncology: Honoraria. Brown:Abbvie, Acerta, AstraZeneca, Beigene, Invectys, Juno/Celgene, Kite, Morphosys, Novartis, Octapharma, Pharmacyclics, Sunesis, TG Therapeutics, Verastem: Consultancy; Gilead, Loxo, Sun, Verastem: Research Funding; Janssen, Teva: Speakers Bureau. Parida:IBM: Current Employment. Neuberg:Madrigak Pharmaceuticals: Current equity holder in publicly-traded company; Pharmacyclics: Research Funding; Celgene: Research Funding. Stilgenbauer:Novartis: Consultancy, Honoraria, Other, Research Funding; Mundipharma: Consultancy, Honoraria, Other, Research Funding; Janssen-Cilag: Consultancy, Honoraria, Other: travel support, Research Funding; Gilead: Consultancy, Honoraria, Other: travel support, Research Funding; GlaxoSmithKline: Consultancy, Honoraria, Other: travel support, Research Funding; Genentech: Consultancy, Honoraria, Other: travel support, Research Funding; Genzyme: Consultancy, Honoraria, Other: travel support, Research Funding; Pharmacyclics: Consultancy, Honoraria, Other, Research Funding; Boehringer-Ingelheim: Consultancy, Honoraria, Other: travel support, Research Funding; Celgene: Consultancy, Honoraria, Other: travel support, Research Funding; F. Hoffmann-LaRoche: Consultancy, Honoraria, Other: travel support, Research Funding; Amgen: Consultancy, Honoraria, Other: travel support, Research Funding; AbbVie: Consultancy, Honoraria, Other: travel support, Research Funding. Getz:Scorpion Therapeutics: Consultancy, Current equity holder in publicly-traded company, Other: Founder; IBM: Research Funding; Pharmacyclics: Research Funding; Broad Institute: Patents & Royalties: MuTect, ABSOLUTE, MutSig, MSMuTect, MSMutSig, POLYSOLVER and TensorQTL. Wu:Pharmacyclics: Research Funding; BionTech: Current equity holder in publicly-traded company.

The confluence of deep sequencing and powerful machine learning is providing an unprecedented peek at the darkest of the dark genomic matter, the non-coding genomic regions lacking any functional annotation. While deep sequencing uncovers rare tumor variants, the heterogeneity of the disease confounds the best of machine learning (ML) algorithms. Here we set out to answer if the dark-matter of the genome encompass signals that can distinguish the fine subtypes of disease that are otherwise genomically indistinguishable. We introduce a novel stochastic regularization, ReVeaL, that empowers ML to discriminate subtle cancer subtypes even from the same ‘cell of origin’. Analogous to heritability, implicitly defined on whole genome, we use predictability (F1 score) definable on portions of the genome. In an effort to distinguish cancer subtypes using dark-matter DNA, we applied ReVeaL to a new WGS dataset from 727 patient samples with seven forms of hematological cancers and assessed the predictivity over several genomic regions including genic, non-dark, non-coding, non-genic, and dark. ReVeaL enabled improved discrimination of cancer subtypes for all segments of the genome. The non-genic, non-coding and dark-matter had the highest F1 scores, with dark-matter having the highest level of predictability. Based on ReVeaL’s predictability of different genomic regions, dark-matter contains enough signal to significantly discriminate fine subtypes of disease. Hence, the agglomeration of rare variants, even in the hitherto unannotated and ill-understood regions of the genome, may play a substantial role in the disease etiology and deserve much more attention., Author summary Many subtypes of cancer are unable to be distinguished based on their genomic profiles. With the ever-increasing use of sequencing, we now have the ability to look deeper into the genome and pick up on hidden signals in areas typically considered irrelevant to disease. To overcome the issue of rare variants and the vast amount of heterogeneity found in these non-coding sectors, we introduce a new algorithm capable of correcting for both challenges, ReVeaL. Using this approach, we are able to demonstrate that the non-coding regions of the genome have more signal for distinguishing subtle subtypes of disease compared to all the coding regions. Specifically, we show that the darkest unexplored genomic regions, the non-coding genome with no functional annotation whatsoever in the literature, have the strongest signal. Thus dark-matter does indeed matter and should not be ignored but rather considered for the continued pressing task of finding biomarkers of disease to adequately treat our patients.

During cancer therapy, tumor heterogeneity can drive the evolution of multiple tumor subclones harboring unique resistance mechanisms in an individual patient1–3. Previous case reports and small case series have suggested that liquid biopsy (specifically, cell-free DNA (cfDNA)) may better capture the heterogeneity of acquired resistance4–8. However, the effectiveness of cfDNA versus standard single-lesion tumor biopsies has not been directly compared in larger-scale prospective cohorts of patients following progression on targeted therapy. Here, in a prospective cohort of 42 patients with molecularly defined gastrointestinal cancers and acquired resistance to targeted therapy, direct comparison of postprogression cfDNA versus tumor biopsy revealed that cfDNA more frequently identified clinically relevant resistance alterations and multiple resistance mechanisms, detecting resistance alterations not found in the matched tumor biopsy in 78% of cases. Whole-exome sequencing of serial cfDNA, tumor biopsies and rapid autopsy specimens elucidated substantial geographic and evolutionary differences across lesions. Our data suggest that acquired resistance is frequently characterized by profound tumor heterogeneity, and that the emergence of multiple resistance alterations in an individual patient may represent the ‘rule’ rather than the ‘exception’. These findings have profound therapeutic implications and highlight the potential advantages of cfDNA over tissue biopsy in the setting of acquired resistance. Direct prospective comparison of circulating tumor DNA and tissue biopsy sequencing shows the superiority of liquid biopsies for capturing clinically relevant alterations mediating resistance to targeted therapies in cancer patients.

Sampling cfDNA using liquid biopsies offers clinically important benefits for monitoring of cancer progression. A single cfDNA sample represents a mixture of shed tumor DNA from all known and unknown lesions within the patient. However, the amount of DNA shed by any one specific lesion is not well characterized. We design an LSM (Lesion Shedding Model) that is able to order the lesions from the strongest to the poorest shedding for a given patient. Our framework intrinsically models for missing/hidden lesions and operates on blood and lesion cfDNA assays to estimate the potential relative shedding levels of lesions into the blood. We verify the accuracy of the model under controlled conditions using a simulation approach to create a synthetic blood cfDNA sample per patient, where specific lesions are assigned predefined shedding levels. The simulated data mirrors real data lesion genomic similarities. The LSM correctly obtains a partial order of the lesions, i.e. accurately stratifies the lesions by their assigned shedding levels, in 83% (10/12) simulated data sets. We then applied LSM to a cohort of 12 cancer patients with available cfDNA blood samples and multiple biopsied lesions and found that indeed there were lesions that were consistently shedding more than other lesions into the patients' blood. From this analysis we are then able to probe whether there are detectable tissue-specific differences in the shedding behavior of lesions. In most patients a top shedding lesion(s) was identified. Trends emerged across lesions whereby pancreatic and gallbladder lesions tended to be higher shedders than other lesions and abdominal cavity lesions tended to be low shedding lesions. The LSM represents one of the first attempts to characterize the contributions of distinct lesions in cfDNA. With an accurate understanding of lesion cfDNA contribution, we can begin to look for patterns in shedding behavior that associate with clinical features of the lesions, such as response to treatment, tissue of origin, age, growth, etc. As sample size increases, the LSM will also be able to address the question of whether a cfDNA biopsy would provide sufficient coverage of the entire space of lesions present in the patient, or, if biopsies of individual lesions would be necessary. Such insights would further increase the impact and applicability of liquid biopsies in the clinic. Citation Format: Filippo Utro, Kahn Rhrissorrakrai, Chaya Levovitz, Ignaty Leshchiner, Liz Martin, Christopher Chen, Christopher Pinto, Brian Danysh, Kara Slowik, Lipika Goyal, Read Allen, Maida Williams Broudo, Dejan Juric, Gad Getz, Laxmi Parida. Estimation of lesion-specific mutation shedding in cfDNA from rapid autopsy study [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 1509.

Only a minority of those exposed to human papillomavirus (HPV) develop HPV-related cervical and oropharyngeal cancer. Because host immunity affects infection and progression to cancer, we tested the hypothesis that genetic variation in immune-related genes is a determinant of susceptibility to oropharyngeal cancer and other HPV-associated cancers by performing a multitier integrative computational analysis with oropharyngeal cancer data from a head and neck cancer genome-wide association study (GWAS). Independent analyses, including single-gene, gene-interconnectivity, protein–protein interaction, gene expression, and pathway analysis, identified immune genes and pathways significantly associated with oropharyngeal cancer. TGFβR1, which intersected all tiers of analysis and thus selected for validation, replicated significantly in the head and neck cancer GWAS limited to HPV-seropositive cases and an independent cervical cancer GWAS. The TGFβR1 containing p38–MAPK pathway was significantly associated with oropharyngeal cancer and cervical cancer, and TGFβR1 was overexpressed in oropharyngeal cancer, cervical cancer, and HPV+ head and neck cancer tumors. These concordant analyses implicate TGFβR1 signaling as a process dysregulated across HPV-related cancers. This study demonstrates that genetic variation in immune-related genes is associated with susceptibility to oropharyngeal cancer and implicates TGFβR1/TGFβ signaling in the development of both oropharyngeal cancer and cervical cancer. Better understanding of the immunogenetic basis of susceptibility to HPV-associated cancers may provide insight into host/virus interactions and immune processes dysregulated in the minority of HPV-exposed individuals who progress to cancer. Cancer Res; 74(23); 6833–44. ©2014 AACR.

The inevitable emergence of acquired resistance is a major limitation to the clinical benefit of precision medicine strategies. Single-lesion tumor biopsies have long been the mainstay of understanding acquired resistance, but recent data suggest tumor biopsies may under-represent the molecular heterogeneity of acquired resistance. Alternatively, studies have suggested that liquid biopsy approaches analyzing cell-free DNA (cfDNA) may offer significant advantages, but extensive prospective comparisons of matched liquid vs. tumor biopsies obtained at the time of acquired resistance are lacking. Here, we assess systematic liquid biopsy upon acquired resistance to targeted therapy in 44 patients across seven molecularly defined subtypes of gastrointestinal cancers. Liquid biopsy at disease progression identified at least one functionally validated molecular mechanism of resistance in 75% of patients, wherein 52% exhibited >1 resistance alteration (range 2-9, median 3 per patient). In 23 patients in whom a matched post-progression tumor biopsy could be obtained, tumor biopsy was less effective than liquid biopsy in identifying resistance mechanisms, with resistance alterations detected in only 48% of patients, and multiple resistance mechanisms detected in only 9% of cases. In matched cases, liquid biopsy detected at least one resistance alteration not detected in tumor biopsy in 78% of cases. Targeted analysis and whole-exome sequencing of serial cfDNA, multiple post-progression biopsies, and rapid autopsy specimens from select cases revealed key insights into the geographic and complex characteristics of heterogeneity captured by liquid biopsy in the setting of acquired resistance. These data illustrate that acquired resistance is characterized by frequent and profound tumor heterogeneity, and suggests that liquid biopsy may more effectively identify heterogeneous clinically relevant resistance alterations compared to standard tumor biopsy. Citation Format: Aparna R. Parikh, Ignaty Leshchiner, Liudmila Elagina, Lipika Goyal, Chaya Levovitz, Giulia Siravegna, Dimitri Livitz, Kahn Rhrissorrakrai, Liz Martin, Emily E. Van Seventer, Megan Hanna, Kara Slowik, Filippo Utro, Christopher J. Pinto, Alicia Wong, Brian P. Danysh, Ferran Fece de la Cruz, Isobel J. Fetter, Brandon Nadres, Heather A. Shahzade, Jill N. Allen, Lawrence S. Blaszkowsky, Jeffrey W. Clark, Bruce Giantonio, Janet E. Murphy, Ryan D. Nipp, Eric Roeland, David P. Ryan, Colin D. Weekes, Eunice L. Kwak, Jason E. Faris, Francois Aguet, Ipsita Guha, Mehlika Hazar-Rethinam, Dora Dias-Santagata, David T. Ting, Andrew X. Zhu, Theodore S. Hong, Todd R. Golub, A J. Iafrate, Viktor Adalsteinsson, Alberto Bardelli, Laxmi Parida, Dejan Juric, Gad Getz, Ryan B. Corcoran. Liquid biopsy versus tissue biopsy to assess acquired resistance and tumor heterogeneity in gastrointestinal cancers [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 LB-257.

The confluence of deep sequencing and powerful machine learning is providing an unprecedented peek at the darkest of the dark genomic matter. While deep sequencing uncovers rare tumor variants, the heterogeneity of the disease confounds the best of machine learning (ML) algorithms. Here we set out to answer if the dark-matter of the genome encompass signals that can classify the fine subtypes of disease that are otherwise gnomically indistinguishable. We introduce a novel stochastic regularization, ReVeal, that empowers ML to classify subtle cancer subtypes even from the same ‘cell of origin’. Analogous to heritability, implicitly defined on whole genome, we use predictability (F1 score) definable on portions of the genome. In an effort to classify cancer subtypes using dark-matter DNA, we applied ReVeal to a new WGS dataset from 727 patient samples with seven forms of hematological cancers and assessed the predictivity over several genomic regions including genic, non-dark, non-coding, non-genic, dark. ReVeal allowed the classification of all segments of the genome better than standard ML algorithms. The non-genic, non-coding and the dark-matter had the highest F1 scores with dark-matter having the highest level of predictability (F1 = 0.78). Based on ReVeal’s predictability of different sectors of the genome, dark matter contains signal significant enough to classify fine subtypes of disease. The agglomeration of rare variants, even in the hitherto unannotated and ill-understood regions of the genome, may play a substantial role in the disease etiology and deserve much more attention. Citation Format: Laxmi Parida, Claudia Haferlach, Kahn Rhrissorrakrai, Filippo Utro, Chaya Levovitz, Kern Wolfgang, Niroshan Nadarajah, Stephan Hutter, Manja Meggendorfer, Wencke Walter, Constance Baer, Torsten Haferlach. Defining subtle cancer subtypes using the darkest DNA [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 4259.

Background:Fat grafting has emerged as a useful method for breast contouring in aesthetic and reconstructive patients. Advancements have been made in fat graft harvest and delivery, but the ability to judge the overall success of fat grafting remains limited. The authors applied three-dimensional im

The Broad/IBM Cancer Resistance Project has partnered with Broad Genomics to pilot the use of cutting edge sequencing technology for the analysis of cell free DNA in blood biopsies. Working closely with the Broad's Cancer Program, Broad Genomics has developed a suite of liquid biopsy sequencing products designed to provide optimal flexibility in conducting research studies with a broad range of applications including; biomarker discovery, treatment resistance monitoring, and detection of minimal residual disease (MRD) post-surgery. Cell-free DNA is extracted from the blood, and a dual unique-molecular-indexed library is created. From this library, low coverage whole genome (ultra-low-pass 0.1x coverage) data is generated to survey sample quality and evaluate the tumor fraction in the liquid specimen. Utilizing the same library, additional assays can be selected for processing based on the research aim (Targeted Panel Assays, MRD Detection or Whole Exomes). Since our approach utilizes the same genomic material for whole genome and targeted sequencing assays, it is possible to maximize the information learned from each valuable and limited liquid biopsy specimen. Our study design takes advantage of the discovery potential of combined tissue-based sequencing and serial liquid biopsy analysis to elucidate mechanisms of cancer resistance by tracking the evolution of clonal and subclonal populations in patients samples over time. This collaboration will utilize the ultra-low-pass sequencing and whole exome sequencing together with custom analysis pipelines to correlate the genomic events with patient clinical data. We aim to process 3,000 samples from 1,000 patients over the next 3 years. To date we have processed close to 500 samples through the ultra-low-pass pipeline and 100 samples through the whole exome sequencing pipeline (results to be provided).The ability to successfully investigate treatment resistant cancers from non-invasive liquid biopsies presents new opportunities for identifying markers, understanding dynamics and monitoring tumor dissemination and clonal evolution. Citation Format: Gad Getz, Carrie Cibulskis, Ignaty Leshchiner, Megan Hanna, Dimitri Livitz, Kara Slowik, Chaya Levovitz, Filippo Utro, Kahn Rhrissorrakrai, Denisse Rotem, Gregory Gydush, Sarah C. Reed, Justin Rhoades, Gavin Ha, Samuel S. Freeman, Christopher Lo, Mark Fleharty, Justin Abreu, Katie Larkin, Michelle Cipicchio, Brendan Blumenstiel, Matt DeFelice, Jonna Grimsby, Susanna Hamilton, Niall Lennon, Viktor A. Adalsteinsson, Laxmi Parida. Broad/IBM Project: Discovery of treatment resistance mechanisms through use of liquid biopsy genomics services [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 3001.

Nipple-sparing mastectomy (NSM) as a therapeutic or prophylactic procedure for breast cancer is rapidly gaining popularity as the literature continues to support it safety. The lateral inframammary fold (IMF) approach provides adequate exposure and eliminates visible scars on the anterior surface of the breast, making this incision cosmetically superior to radial or periareolar approaches. We reviewed 55 consecutive NSMs performed through a lateral IMF incision with immediate implant-based reconstruction, with or without tissue expansion, between June 2008 and June 2011. Prior to incision, breasts were lightly infiltrated with dilute anesthetic solution with epinephrine. Sharp dissection, rather than electrocautery, was used as much as possible to minimize thermal injury to the mastectomy flap. When indicated, acellular dermal matrix was placed as an inferolateral sling. Subsequent fat grafting to correct contour deformities was performed in select patients. Three-dimensional (3D) photographs assessed changes in volume, antero-posterior projection, and ptosis. Mean patient age was 46 years, and mean follow-up time was 12 months. Twelve mastectomies (22%) were therapeutic, and the remaining 43 (78%) were prophylactic. Seven of the nine sentinel lymph node biopsies (including one axillary dissection) (78%) were performed through the lateral IMF incision without the need for a counter-incision. Acellular dermal matrix was used in 34 (62%) breasts. Average permanent implant volume was 416 cc (range 176–750 cc), and average fat grafting volume was 86 cc (range 10–177 cc). In one patient a positive intraoperative subareolar biopsy necessitated resection of the nipple-areola complex (NAC), and in two other patients NAC resection was performed at a subsequent procedure based on the final pathology report. Mastectomy flap necrosis, requiring operative debridement, occurred in two breasts (4%), both in the same patient. One of these breasts required a salvage latissimus dorsi myocutaneous flap to complete the reconstruction. Three nipples (6%) required office debridement for partial necrosis and operative reconstruction later. No patient had complete nipple necrosis. No statistically significant differences existed between therapeutic and prophylactic mastectomies for developing partial skin and/or nipple necrosis (p = 0.35). Three episodes (5%) of cellulitis occurred, which responded to antibiotics without the need for explantation. Morphological outcomes using 3D scan measurements showed reconstructed breasts were larger, more projected, and less ptotic than the preoperative breasts (196 versus 248 cc, 80 versus 90 mm, 146 versus 134 mm, p

Background Datasets generated on deep-sequencing platforms have been deposited in various public repositories such as the Gene Expression Omnibus (GEO), Sequence Read Archive (SRA) hosted by the NCBI, or the DNA Data Bank of Japan (ddbj). Despite being rich data sources, they have not been used much due to the difficulty in locating and analyzing datasets of interest. Results Geoseq http://geoseq.mssm.edu provides a new method of analyzing short reads from deep sequencing experiments. Instead of mapping the reads to reference genomes or sequences, Geoseq maps a reference sequence against the sequencing data. It is web-based, and holds pre-computed data from public libraries. The analysis reduces the input sequence to tiles and measures the coverage of each tile in a sequence library through the use of suffix arrays. The user can upload custom target sequences or use gene/miRNA names for the search and get back results as plots and spreadsheet files. Geoseq organizes the public sequencing data using a controlled vocabulary, allowing identification of relevant libraries by organism, tissue and type of experiment. Conclusions Analysis of small sets of sequences against deep-sequencing datasets, as well as identification of public datasets of interest, is simplified by Geoseq. We applied Geoseq to, a) identify differential isoform expression in mRNA-seq datasets, b) identify miRNAs (microRNAs) in libraries, and identify mature and star sequences in miRNAS and c) to identify potentially mis-annotated miRNAs. The ease of using Geoseq for these analyses suggests its utility and uniqueness as an analysis tool.

OBJECTIVES: Human papilloma virus (HPV)-related cancer of the oropharynx (OPC) makes up an increasing proportion of head and neck cancers (HNC). Since viral infection and progression to cancer are both strongly influenced by the immune system, the host immune response is one potential determinant of susceptibility to HPV-related cancers. The overall goal of this project is to identify immune-genetic variants associated with an increased risk of developing virally-mediated HNC. STUDY DESIGN: Data from a HNC Genome Wide Association Study (GWAS) performed by the International Agency for Research on Cancer (IARC) and the Centre National de Gestion (CNG) was evaluated for associations between genetic variants in immune genes and the risk of developing OPC. METHODS: An association analysis using multivariate logistic regression was performed on the HNC GWAS data limited to OPC. We analyzed all SNPs intersecting immune genes based on Gene Ontology using a multi tier computational approach which included single gene analysis, gene-gene interaction (GGI) analysis, pathway analysis and protein-protein interaction (PPI) analysis. Results were validated in 2 in-silico replications: the HNC GWAS limited to individuals with serologic evidence of HPV infection, and a cervical cancer GWAS. RESULTS: The OPC GWAS found 17 immune SNPs to be associated with OPC at a significance level of p CONCLUSIONS: The high degree of concordance among multiple independent tiers of analysis, strongly implicates variations in immune-related genes as modulators of susceptibility to HPV-mediated HNC and highlights TGFB signaling as a process potentially dysregulated across HPV-related cancers. Thus data highlights the role of host immunogenetics as a modulator of virally-related cancer risk and the utility of multi-component computational strategies in testing biologically based hypothesis about mechanisms of disease susceptibility. Citation Format: Chaya Levovitz, Dan Chen, Emma Ivansson, Ulf Gyllensten, James McKay, Paul Brennan, Paolo Boffetta, Andrew Sikora. TGFBR1 and other immune-related genes modify susceptibility to HPV-associated head and neck cancer. [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 4175. doi:10.1158/1538-7445.AM2014-4175

OBJECTIVES: Human papilloma virus (HPV)-related cancer of the oropharynx (tonsil and tongue base) makes up an increasing proportion of head and neck cancers. This raises the possibility that the host immune response may modulate susceptibility to HPV-related head and neck cancer. The overall goal of this project is to identify candidate immune-related genes associated with an increased risk of developing virally-mediated head and neck squamous cell carcinoma (HNSCC). STUDY DESIGN: Data from a two-phased Genome Wide Association Study (GWAS) performed by the International Head and Neck Cancer Epidemiology Consortium (INHANCE) was evaluated for associations between genetic variants in candidate immune related genes and the risk of developing HNSCC. METHODS: We analyzed the GWAS dataset using a hypothesis-driven multi-candidate gene approach which incorporates improved methods for data quality control and candidate gene prioritization. This involved performing an association analysis using multi-variate logistic regression with over 300,000 SNPs. The candidate gene list, including over 900 immune-related genes, was developed using the Gene Ontology (GO) database and prioritized by both the GO priority score and a novel literature based ranking schema. Separate association analyses were performed on all samples and then on samples from patients with oropharyngeal cancer only. RESULTS: After adjusting for multiple testing, 15 of the immune related candidate genes had p values that reached significance in the association study performed on oropharyngeal samples including CBFA2T3, MAPKAPK2, ZAP70, CRTAM, PBX1, MAPK10, CD80, IL10, SOCS5, TGFBR1, EBF1, IGF1R, LYN, ITGAV. Mutations in many of these genes have previously been implicated in cancer risk, viral host-response, or epithelial immunity. CONCLUSIONS: Our analysis suggests that the immune system may modulate risk of developing virally-mediated HNSCC. Genes identified in this study may provide biomarkers for patient or population risk assessments that can potentially be used in implementing behavioral interventions, HPV vaccination, and other preventative strategies. Validation of immune-related genes associated with HNSCC susceptibility may provide clues to pathogenic mechanisms driving the acquisition of virally-related HNSCC. This abstract has been submitted on behalf of ARCAGE and the CE UADT. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 2988. doi:1538-7445.AM2012-2988

Recent genomic and bioinformatic advances have motivated the development of numerous network models intending to describe graphs of biological, technological, and sociological origin. In most cases the success of a model has been evaluated by how well it reproduces a few key features of the real-world data, such as degree distributions, mean geodesic lengths, and clustering coefficients. Often pairs of models can reproduce these features with indistinguishable fidelity despite being generated by vastly different mechanisms. In such cases, these few target features are insufficient to distinguish which of the different models best describes real world networks of interest; moreover, it is not clear a priori that any of the presently-existing algorithms for network generation offers a predictive description of the networks inspiring them. We present a method to assess systematically which of a set of proposed network generation algorithms gives the most accurate description of a given biological network. To derive discriminative classifiers, we construct a mapping from the set of all graphs to a high-dimensional (in principle infinite-dimensional) "word space". This map defines an input space for classification schemes which allow us to state unambiguously which models are most descriptive of a given network of interest. Our training sets include networks generated from 17 models either drawn from the literature or introduced in this work. We show that different duplication-mutation schemes best describe the E. coli genetic network, the S. cerevisiae protein interaction network, and the C. elegans neuronal network, out of a set of network models including a linear preferential attachment model and a small-world model. Our method is a first step towards systematizing network models and assessing their predictability, and we anticipate its usefulness for a number of communities.