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  • 1
    In: Nature Communications, Springer Science and Business Media LLC, Vol. 8, No. 1 ( 2017-11-06)
    Abstract: Whole-exome sequencing of cell-free DNA (cfDNA) could enable comprehensive profiling of tumors from blood but the genome-wide concordance between cfDNA and tumor biopsies is uncertain. Here we report ichorCNA, software that quantifies tumor content in cfDNA from 0.1× coverage whole-genome sequencing data without prior knowledge of tumor mutations. We apply ichorCNA to 1439 blood samples from 520 patients with metastatic prostate or breast cancers. In the earliest tested sample for each patient, 34% of patients have ≥10% tumor-derived cfDNA, sufficient for standard coverage whole-exome sequencing. Using whole-exome sequencing, we validate the concordance of clonal somatic mutations (88%), copy number alterations (80%), mutational signatures, and neoantigens between cfDNA and matched tumor biopsies from 41 patients with ≥10% cfDNA tumor content. In summary, we provide methods to identify patients eligible for comprehensive cfDNA profiling, revealing its applicability to many patients, and demonstrate high concordance of cfDNA and metastatic tumor whole-exome sequencing.
    Type of Medium: Online Resource
    ISSN: 2041-1723
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2017
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  • 2
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 78, No. 13_Supplement ( 2018-07-01), p. LB-225-LB-225
    Abstract: Introduction: Precision medicine approaches to guide therapy selection require routine sampling of tumors. However, tumor biopsies are not always accessible and may be confounded by spatial heterogeneity. Liquid biopsies, including analysis of cell-free DNA (cfDNA), present a non-invasive alternative which may reflect multiple tumors in the body. Previous studies have demonstrated exome-wide concordance between single-site tumor biopsies and cfDNA, but little is known about how cfDNA reflects multiple lesions within a patient. Here we sought to determine how cfDNA reflects the body-wide tumor phylogeny, which will inform the use of cfDNA for cancer precision medicine. Methods: We identified 20 patients with pancreatic cancer who had undergone rapid autopsy. We then screened cfDNA tumor fraction and performed whole-exome sequencing of cfDNA and multiple tumor biopsies for 3 patients with cfDNA tumor fraction & gt;10%. We inferred the tumor phylogeny and then developed a statistical approach to deconvolute the contributions to cfDNA from tumor phylogenetic nodes. Finally, we determined whether shared trunk mutations could be detected in cfDNA and tumor biopsies. Results: For each patient, we found mutations shared between all sites and cfDNA, including putative driver mutations. We found mutations which were clonal in multiple regions were detectable in cfDNA, whereas mutations private to individual sites were never clonal in cfDNA. Through our deconvolution analysis, we found that cfDNA could not be modeled as a simple linear combination of individual sites, but rather that cfDNA represented multiple nodes in the inferred phylogeny. For two pancreatic adenocarcinoma patients, the inferred ancestor of the metastases had high estimated contribution ( & gt;70%) to cfDNA, while the ancestors of the primaries had lower contributions ( & lt;10%). Next, we considered trunk mutations, which originate earliest in the tumor phylogenetic tree. When we analyzed precision for detection of trunk mutations, we found on average, 71% of clonal mutations in metastases were truncal, while only 55% of clonal mutations in primary tumors were truncal. Due to copy number deletions, not all trunk mutations were detected in metastases. Finally, on average, cfDNA had equal or better precision than 83% of primaries and 88% of metastases, suggesting cfDNA may provide more accurate trunk SSNV calls than tumor biopsies. Conclusions: Through analyzing cfDNA and synchronous tumor biopsies from the same patient, we find trunk mutations are enriched in cfDNA as compared to the average single-site biopsy. We also predict that cfDNA represents multiple nodes in the inferred phylogeny. In cases where tumor biopsies are inaccessible, we demonstrate that cfDNA might be a promising alternative to detect trunk SSNVs. These results suggest that cfDNA may be complementary to tumor biopsies for disease monitoring and treatment selection in personalized medicine. Citation Format: Samuel S. Freeman, Ziao Lin, Gavin Ha, Ignaty Leshchiner, Justin Rhoades, Dimitri Livitz, Daniel Rosebrock, Sarah C. Reed, Gregory Gydush, Christopher Lo, Denisse Rotem, Atish D. Choudhury, Daniel G. Stover, Heather A. Parsons, Jesse S. Boehm, J Christopher Love, Matthew Meyerson, Paul Grandgenett, Michael A. Hollingsworth, Viktor A. Adalsteinsson, Gad Getz. Liquid biopsies identify trunk mutations and reflect multiple tumors in a patient [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 LB-225.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2018
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  • 3
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 80, No. 16_Supplement ( 2020-08-15), p. 6670-6670
    Abstract: Cancer immunotherapy with checkpoint blockade has improved survival and outcomes in melanoma, but still a majority of patients do not respond. Both high tumor mutation burden (TMB) and high T cell infiltration have been associated with response, but integrative models based on DNA or RNA assays have not been comprehensively explored and validated. Focusing on melanomas from patients receiving checkpoint blockade, we generated new and aggregated existing datasets of whole exome sequencing (WES) (n = 189 total) and bulk RNA sequencing (n = 154 total) to derive genomic and transcriptomic factors that predict survival and response to immunotherapy in melanoma. We quantified T and B cell infiltrates using rearranged T cell receptor (TCR) and immunoglobulin (Ig) sequences, respectively, from DNA or RNA sequencing. High levels of rearranged TCR reads or rearranged Ig reads in RNA-seq were associated with survival (P = 0.0046, P = 0.015) and response (P = 0.0034, P = 0.047). We created RNA-based metrics of T and B cell burden (TCBRNA or BCBRNA) by normalizing the number of rearranged TCR reads by the total number of mapped reads. When we analyzed WES data in patients for whom DNA and RNA were extracted from the same region, we found that the TCBDNA correlated with TCBRNA (rho = 0.73) and BCBDNA with BCBRNA (rho = 0.41), demonstrating that the level of lymphocyte infiltration can be estimated using rearranged TCR or Ig reads from tumor WES alone. We found that TCBDNA and BCBDNA both associated with survival (P = 0.0023 and 0.0089). In a combined model, patients with high TMB and high TCB DNA survived longer (P = 2.4e-4, HR = 2.68) and had a higher response rate (Fisher P = 0.028). This combined model was superior to models with TMB or TCBDNA alone. Similarly, patients with high TMB and high BCBDNA had longer survival and higher response rates (log-rank P = 0.0029, HR = 2.64, Fisher P = 0.015). We reanalyzed stage III/IV melanomas from TCGA and found that the TMB high, TCBDNA high subgroup had increased survival (P = 0.007). Next, clustering of tumor transcriptomes identified 5 tumor subtypes based on melanocyte differentiation, immune infiltration and keratin levels. These melanoma subtypes were associated with survival outcomes after immunotherapy (P = 0.019). We found that TBX3, a tumor-expressed transcription factor enriched in poorly differentiated melanomas, was over-expressed among non-responders within the immune-infiltrated subtype and among all patients (P = 3.9e-4, P = 8.7e-5). Patients whose tumors had high immune infiltrate and low expression of TBX3 had longer survival (P = 1.6e-5, HR = 3.39), however this subgroup did not have longer survival in an independent cohort (n = 73, P = 0.10, HR = 2.63). In conclusion, we demonstrate both RNA-based (immune infiltrate and tumor subtype) and DNA-based metrics (TMB/TCB or TMB/BCB) can be used as pre-treatment predictors of survival after checkpoint blockade in melanoma. Citation Format: Samuel S. Freeman, Moshe Sade-Feldman, Jaegil Kim, Chip Stewart, Arvind Ravi, Monica Arniella, Keren Yizhak, Ignaty Leshchiner, Liudmila Elagina, Oliver Spiro, Dimitri Livitz, Daniel Rosebrock, François Aguet, Jian Carrot-Zhang, Anna Gonye, Gavin Ha, Ziao Lin, Jonathan H. Chen, Dennie T. Frederick, Michal Barzily-Rokni, Marc R. Hammond, Hans Vitzthum, Shauna M. Blackmon, Yunxin J. Jiao, Donald P. Lawrence, Lyn M. Duncan, Anat Stemmer-Rachamimov, Jennifer A. Wargo, Keith T. Flaherty, Genevieve M. Boland, Ryan J. Sullivan, Matthew Meyerson, Gad Getz, Nir Hacohen. Combined signals from tumor and immune cells predict outcomes of checkpoint inhibition in melanoma [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 6670.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2020
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  • 4
    In: Cell Reports Medicine, Elsevier BV, Vol. 3, No. 2 ( 2022-02), p. 100500-
    Type of Medium: Online Resource
    ISSN: 2666-3791
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
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  • 5
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 78, No. 13_Supplement ( 2018-07-01), p. 3001-3001
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2018
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