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  • American Association for Cancer Research (AACR)  (7)
  • 1
    In: Cancer Research Communications, American Association for Cancer Research (AACR), Vol. 1, No. 2 ( 2021-11-30), p. 115-126
    Abstract: Allogeneic cancer vaccines are designed to induce antitumor immune responses with the goal of impacting tumor growth. Typical allogeneic cancer vaccines are produced by expansion of established cancer cell lines, transfection with vectors encoding immunostimulatory cytokines, and lethal irradiation. More than 100 clinical trials have investigated the clinical benefit of allogeneic cancer vaccines in various cancer types. Results show limited therapeutic benefit in clinical trials and currently there are no FDA-approved allogeneic cancer vaccines. We used recently developed bioinformatics tools including the pVACseq suite of software tools to analyze DNA/RNA-sequencing data from the The Cancer Genome Atlas to examine the repertoire of antigens presented by a typical allogeneic cancer vaccine, and to simulate allogeneic cancer vaccine clinical trials. Specifically, for each simulated clinical trial, we modeled the repertoire of antigens presented by allogeneic cancer vaccines consisting of three hypothetical cancer cell lines to 30 patients with the same cancer type. Simulations were repeated ten times for each cancer type. Each tumor sample in the vaccine and the vaccine recipient was subjected to human leukocyte antigen (HLA) typing, differential expression analyses for tumor-associated antigens (TAA), germline variant calling, and neoantigen prediction. These analyses provided a robust, quantitative comparison between potentially beneficial TAAs and neoantigens versus distracting antigens present in the allogeneic cancer vaccines. We observe that distracting antigens greatly outnumber shared TAAs and neoantigens, providing one potential explanation for the lack of observed responses to allogeneic cancer vaccines. This analysis provides additional rationale for the redirection of efforts toward a personalized cancer vaccine approach. Significance: A comprehensive examination of allogeneic cancer vaccine antigen repertoire using large-scale genomics datasets highlights the large number of distracting antigens and argues for more personalized approaches to immunotherapy that leverage recent strategies in tumor antigen identification.
    Type of Medium: Online Resource
    ISSN: 2767-9764
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2021
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  • 2
    In: Clinical Cancer Research, American Association for Cancer Research (AACR), Vol. 27, No. 1 ( 2021-01-01), p. 357-357
    Type of Medium: Online Resource
    ISSN: 1078-0432 , 1557-3265
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2021
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  • 3
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 82, No. 12_Supplement ( 2022-06-15), p. 5639-5639
    Abstract: Neoantigens are novel peptide sequences resulting from somatic mutations in tumors that upon loading onto major histocompatibility complex (MHC) molecules allow recognition by T cells. Accurate neoantigen identification is thus critical for designing cancer vaccines and predicting response to immunotherapies. Neoantigen identification and prioritization relies on correctly inferring whether the presenting peptide sequence can successfully induce an immune response. As the majority of somatic mutations are SNVs, changes between wildtype and mutant peptide are subtle and require cautious interpretation. An important, yet underappreciated, variable in neoantigen-prediction pipelines is the mutation position within the peptide relative to its anchor positions for the patient’s specific HLA alleles. While a subset of peptide positions are presented to the T-cell receptor for recognition, others are responsible for anchoring to the MHC, making these positional considerations critical for predicting T-cell responses. However, a systematic method for determining anchor locations for the wide range of HLA alleles present in the population and application of these to evaluate MT/WT peptide pairs arising in tumors has not been reported. As a result, many neoantigen studies have either failed to adequately consider this crucial factor or have used conventional assumptions to guide their neoantigen identification process. Here, we provide a computational workflow for predicting anchor locations for a wide range of HLA alleles, using a reference dataset generated from clinical and The Cancer Genome Atlas (TCGA) patient samples. We calculated high probability anchor positions for different peptide lengths for over 300 common HLA alleles. Analysis of these results showed clusters of different anchor trends among the HLA alleles analyzed. A subset of these HLA anchor results were orthogonally validated using protein crystallography structures. Analysis of 923 tumor samples showed that 7-41% of neoantigen candidates were potentially misclassified in the neoantigen selection process and can be rescued using allele-specific knowledge of anchor positions. These anchor predictions are currently undergoing experimental validation using both peptide-MHC stability assays as well as fluorescence-based competition binding assays. By incorporating our anchor prediction results into neoantigen prediction pipelines, such as pVACtools, we hope to formalize and streamline the identification process for relevant clinical studies. Citation Format: Huiming Xia, Joshua McMichael, Michelle Becker-Hapak, Onyinyechi C. Onyeador, Rico Buchli, Ethan McClain, Patrick Pence, Suangson Supabphol, Megan M. Richters, Anamika Basu, Cody A. Ramirez, Cristina Puig-Saus, Kelsy C. Cotto, Jasreet Hundal, Susanna Kiwala, S. Peter Goedegebuure, Tanner M. Johanns, Gavin P. Dunn, Antoni Ribas, Christopher A. Miller, William Gillanders, Todd A. Fehniger, Obi L. Griffith, Malachi Griffith. Computational prediction of MHC anchor locations guide neoantigen prediction and prioritization [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 5639.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2022
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  • 4
    In: Clinical Cancer Research, American Association for Cancer Research (AACR), Vol. 26, No. 19 ( 2020-10-01), p. 5140-5152
    Abstract: Pembrolizumab improved survival in patients with recurrent or metastatic head and neck squamous-cell carcinoma (HNSCC). The aims of this study were to determine if pembrolizumab would be safe, result in pathologic tumor response (pTR), and lower the relapse rate in patients with resectable human papillomavirus (HPV)–unrelated HNSCC. Patients and Methods: Neoadjuvant pembrolizumab (200 mg) was administered and followed 2 to 3 weeks later by surgical tumor ablation. Postoperative (chemo)radiation was planned. Patients with high-risk pathology (positive margins and/or extranodal extension) received adjuvant pembrolizumab. pTR was quantified as the proportion of the resection bed with tumor necrosis, keratinous debris, and giant cells/histiocytes: pTR-0 ( & lt;10%), pTR-1 (10%–49%), and pTR-2 (≥50%). Coprimary endpoints were pTR-2 among all patients and 1-year relapse rate in patients with high-risk pathology (historical: 35%). Correlations of baseline PD-L1 and T-cell infiltration with pTR were assessed. Tumor clonal dynamics were evaluated (ClinicalTrials.gov NCT02296684). Results: Thirty-six patients enrolled. After neoadjuvant pembrolizumab, serious (grades 3–4) adverse events and unexpected surgical delays/complications did not occur. pTR-2 occurred in eight patients (22%), and pTR-1 in eight other patients (22%). One-year relapse rate among 18 patients with high-risk pathology was 16.7% (95% confidence interval, 3.6%–41.4%). pTR ≥10% correlated with baseline tumor PD-L1, immune infiltrate, and IFNγ activity. Matched samples showed upregulation of inhibitory checkpoints in patients with pTR-0 and confirmed clonal loss in some patients. Conclusions: Among patients with locally advanced, HPV-unrelated HNSCC, pembrolizumab was safe, and any pathologic response was observed in 44% of patients with 0% pathologic complete responses. The 1-year relapse rate in patients with high-risk pathology was lower than historical.
    Type of Medium: Online Resource
    ISSN: 1078-0432 , 1557-3265
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2020
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  • 5
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 75, No. 22_Supplement_2 ( 2015-11-15), p. PR03-PR03
    Abstract: Acute myeloid leukemia is heterogeneous with respect to clinical outcome and molecular pathogenesis. Approximately 20% of AML cases are refractory to induction chemotherapy, and about 50% of patients ultimately relapse within a time interval that ranges from months to years. At the molecular level, diverse chromosomal abnormalities and genetic mutations have been observed across patients1. Although several clinical factors (age, white blood cell count), cytogenetic aberrations (t[15;17] translocation, loss of chromosome 5) 2-4, and genetic mutations (DNMT3A, FLT3) have been associated with differences in survival 5,6, these factors are of limited prognostic utility. Moreover, few studies have integrated sequence data with clinical and cytogentic factors to build predictive models of patient outcome. Here, we sought to identify genomic predictors of refractory disease or early relapse. We used whole genome and exome sequencing to analyze the genomes of 71 adult de novo AML patients treated with anthracycline and cytarabine-based induction chemotherapy. Of these, 34 had refractory disease or relapsed within 6 months, 12 relapsed in 6-12 months, and 25 had a long first remission ( & gt;12 months). We also developed an enhanced exome sequencing (EES) approach to identify and follow leukemia-associated variants over time. In 12 additional patients that achieved morphologic remission after induction chemotherapy, we used EES to identify and track variants at time of diagnosis, time of morphologic remission (roughly 30 days later), and a final time point corresponding to eventual relapse (n=8) or extended remission (n=4). No novel coding or non-coding variants present at the time of diagnosis were found to be predictive of refractory disease or early relapse. Using EES, however, we were able to detect leukemia-associated variants in the initial remission bone marrow in all eight patients who eventually relapsed. One persistent leukemia-associated variant was also detected in one patient still in remission, but all other variants in that patient were eliminated. We also detected 64 somatic variants that became enriched following chemotherapy, but were not detected in the original leukemic cells. These may represent relapse-specific variants or oligoclonal hematopoiesis after bone marrow recovery. Overall, our data suggest that the persistence of leukemia-associated variants after bone marrow recovery from cytotoxic therapy is strongly correlated with relapse, and may be used to complement more traditional, morphologic measures of leukemic cell clearance. 1. Cancer Genome Atlas Research N. Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. The New England Journal of Medicine 2013;368:2059-74. 2. Byrd JC, Mrozek K, Dodge RK, et al. Pretreatment cytogenetic abnormalities are predictive of induction success, cumulative incidence of relapse, and overall survival in adult patients with de novo acute myeloid leukemia: results from Cancer and Leukemia Group B (CALGB 8461). Blood 2002;100:4325-36. 3. Grimwade D, Hills RK, Moorman AV, et al. Refinement of cytogenetic classification in acute myeloid leukemia: determination of prognostic significance of rare recurring chromosomal abnormalities among 5876 younger adult patients treated in the United Kingdom Medical Research Council trials. Blood 2010;116:354-65. 4. Schlenk RF, Dohner K, Krauter J, et al. Mutations and treatment outcome in cytogenetically normal acute myeloid leukemia. The New England Journal of Medicine 2008;358:1909-18. 5. Kihara R, Nagata Y, Kiyoi H, et al. Comprehensive analysis of genetic alterations and their prognostic impacts in adult acute myeloid leukemia patients. Leukemia 2014;28:1586-95. 6. Ley TJ, Ding L, Walter MJ, et al. DNMT3A mutations in acute myeloid leukemia. The New England Journal of Medicine 2010;363:2424-33. This abstract is also presented as a poster at the Translation of the Cancer Genome conference. Citation Format: Jeffery M. Klco, Christopher A. Miller, Malachi Griffith, Allegra Petti, David H. Spencer, Shamika Ketkar-Kulkarni, Lukas D. Wartman, Matthew Christopher, Tamara L. Lamprecht, Jacqueline E. Payton, Jack Baty, Sharon E. Heath, Obi L. Griffith, Dong Shen, Jasreet Hundal, Gue Su Chang, Robert S. Fulton, Michelle O'laughlin, Catrina Fronick, Vincent Magrini, Ryan Demeter, David E. Larson, Shashikant Kulkarni, Bradley A. Ozenberger, John S. Welch, Matthew J. Walker, Timothy A. Graubert, Peter Westervelt, Jerald P. Radich, Daniel C. Link, Elaine R. Mardis, John F. DiPersio, Richard K. Wilson. Genomic approaches for risk assessment in acute myeloid leukemia. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr PR03.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2015
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  • 6
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 75, No. 22_Supplement_1 ( 2015-11-15), p. PR11-PR11
    Abstract: Acute myeloid leukemia is heterogeneous with respect to clinical outcome and molecular pathogenesis. Approximately 20% of AML cases are refractory to induction chemotherapy, and about 50% of patients ultimately relapse within a time interval that ranges from months to years. At the molecular level, diverse chromosomal abnormalities and genetic mutations have been observed across patients1. Although several clinical factors (age, white blood cell count), cytogenetic aberrations (t[15;17] translocation, loss of chromosome 5) 2-4, and genetic mutations (DNMT3A, FLT3) have been associated with differences in survival 5,6, these factors are of limited prognostic utility. Moreover, few studies have integrated sequence data with clinical and cytogentic factors to build predictive models of patient outcome. Here, we sought to identify genomic predictors of refractory disease or early relapse. We used whole genome and exome sequencing to analyze the genomes of 71 adult de novo AML patients treated with anthracycline and cytarabine-based induction chemotherapy. Of these, 34 had refractory disease or relapsed within 6 months, 12 relapsed in 6-12 months, and 25 had a long first remission ( & gt;12 months). We also developed an enhanced exome sequencing (EES) approach to identify and follow leukemia-associated variants over time. In 12 additional patients that achieved morphologic remission after induction chemotherapy, we used EES to identify and track variants at time of diagnosis, time of morphologic remission (roughly 30 days later), and a final time point corresponding to eventual relapse (n=8) or extended remission (n=4). No novel coding or non-coding variants present at the time of diagnosis were found to be predictive of refractory disease or early relapse. Using EES, however, we were able to detect leukemia-associated variants in the initial remission bone marrow in all eight patients who eventually relapsed. One persistent leukemia-associated variant was also detected in one patient still in remission, but all other variants in that patient were eliminated. We also detected 64 somatic variants that became enriched following chemotherapy, but were not detected in the original leukemic cells. These may represent relapse-specific variants or oligoclonal hematopoiesis after bone marrow recovery. Overall, our data suggest that the persistence of leukemia-associated variants after bone marrow recovery from cytotoxic therapy is strongly correlated with relapse, and may be used to complement more traditional, morphologic measures of leukemic cell clearance. 1. Cancer Genome Atlas Research N. Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. The New England Journal of Medicine 2013;368:2059-74. 2. Byrd JC, Mrozek K, Dodge RK, et al. Pretreatment cytogenetic abnormalities are predictive of induction success, cumulative incidence of relapse, and overall survival in adult patients with de novo acute myeloid leukemia: results from Cancer and Leukemia Group B (CALGB 8461). Blood 2002;100:4325-36. 3. Grimwade D, Hills RK, Moorman AV, et al. Refinement of cytogenetic classification in acute myeloid leukemia: determination of prognostic significance of rare recurring chromosomal abnormalities among 5876 younger adult patients treated in the United Kingdom Medical Research Council trials. Blood 2010;116:354-65. 4. Schlenk RF, Dohner K, Krauter J, et al. Mutations and treatment outcome in cytogenetically normal acute myeloid leukemia. The New England Journal of Medicine 2008;358:1909-18. 5. Kihara R, Nagata Y, Kiyoi H, et al. Comprehensive analysis of genetic alterations and their prognostic impacts in adult acute myeloid leukemia patients. Leukemia 2014;28:1586-95. 6. Ley TJ, Ding L, Walter MJ, et al. DNMT3A mutations in acute myeloid leukemia. The New England Journal of Medicine 2010;363:2424-33. Citation Format: Jeffery M. Klco, Christopher A. Miller, Malachi Griffith, Allegra Petti, David H. Spencer, Shamika Ketkar-Kulkarni, Lukas D. Wartman, Matthew Christopher, Tamara L. Lamprecht, Jacqueline E. Payton, Jack Baty, Sharon E. Heath, Obi L. Griffith, Dong Shen, Jasreet Hundal, Gue Su Chang, Robert S. Fulton, Michelle O'laughlin, Catrina Fronick, Vincent Magrini, Ryan Demeter, David E. Larson, Shashikant Kulkarni, Bradley A. Ozenberger, John S. Welch, Matthew J. Walker, Timothy A. Graubert, Peter Westervelt, Jerald P. Radich, Daniel C. Link, Elaine R. Mardis, John F. DiPersio, Richard K. Wilson. Genomic approaches for risk assessment in acute myeloid leukemia. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr PR11.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2015
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  • 7
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 75, No. 15_Supplement ( 2015-08-01), p. 4109-4109
    Abstract: Introduction: Death from colorectal cancer (CRC) occurs via sequelae of metastases. Our lack of understanding of the mechanisms driving metastatic formation is a critical barrier to the identification and direct targeting of critical genes and pathways. This is further complicated by tumor heterogeneity and subclonal architecture. To reconstruct the patterns of tumor evolution and metastasis in CRC, we have conducted the first comprehensive clonality analysis of ten patients. Methods: Primary tumor, metastases in multiple liver segments, and matched normal tissues were procured from consented patients during operative resection. Deep exome (∼200x coverage) and whole genome sequencing (∼50x coverage) were used to identify somatic mutations and estimate variant allele frequency (VAF) for somatic single nucleotide variants (SNVs). Clonal architecture and evolution models were derived from the SNVs by VAF-based clustering, clonal ordering, and phylogeny analysis. Results: Non-silent somatic alterations were enriched in genes known to be involved in CRC and other major cancers, including APC, TP53, KRAS, PIK3CA and TCF7L2. Each patient had a founding clone originating from the primary tumor (carrying non-silent mutations in at least one cancer driver gene) that survived to metastasis, possibly following evolution and acquisition of additional somatic mutations. Branched evolution was common and spatially-distinct liver metastases within the same patient sometimes arose from different (sub)clones in the primary tumor. Unique subclones appeared to arise in all metastatic samples, and in some cases, were shared among various metastases of the same patient. This suggests that one metastasis seeded another or an ancestor common to those metastases was present in the primary tumor or elsewhere, but not observed due to spatial heterogeneity. In several cases, mutations in the dominant clone of the primary tumor were absent from metastases, suggesting these were subclonal events in more aggressive cancer cells that arose in the primary tumor after metastasis. These additional somatic events may involve (possibly novel) cancer driver genes. Conclusions: Understanding the genomic events driving tumor evolution and metastasis is critical for explaining why existing therapies fail and determining optimal treatment strategies. Our analyses have outlined several clonal evolution patterns in metastatic CRC. We are currently using ultra-deep targeted and multi-region sequencing to validate genomic alterations in our CRC cohort to refine clonal evolution models and evaluate which subclones may be biologically relevant to disease progression and treatment resistance. Additionally, by revealing critical altered genes and pathways associated with metastatic clones we can improve our understanding of the mechanisms driving metastasis in CRC that may lead to novel targeted cancer therapies. Citation Format: Ha X. Dang, Julie Grossman, Brian S. White, Matthew Strand, David E. Larson, Jason Walker, Elizabeth Pittman, Timothy Fleming, Peter S. Goedegebuure, Robert S. Fulton, Christopher A. Miller, Malachi Griffith, Kian H. Lim, Timothy J. Ley, Richard K. Wilson, Elaine R. Mardis, A.Craig Lockhart, Ryan C. Fields, Christopher A. Maher. Clonal evolution of metastatic colorectal cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4109. doi:10.1158/1538-7445.AM2015-4109
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2015
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    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
    Location Call Number Limitation Availability
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