Adaptive anti-tumor immune responses are important determinants of clinical outcomes in patients with diverse cancer types, and increasingly a target of emerging cancer therapies. A central unmet need is a better understanding of the targets of anti-tumor immune responses necessary for effective active immunotherapies and vaccination strategies. We are currently conducting a clinical trial of therapeutic vaccination for patients with Mantle Cell Lymphoma (NCT00490529), a heretofore incurable hematologic malignancy. In this application we will use a combination of novel technologies and bioinformatics platforms to discover the genetic and immunological determinants of the immune responses that we have induced. Our central hypothesis is that clinical and immunological responses in patients with this disease after their therapeutic vaccination are determined by the somatic mutations encoded in their tumor genomes. Alterations in the tumor proteome, such as novel (neo-) antigenic peptides generated in the process of somatic mutation, can serve as potent substrates for specific anti-tumor immune responses when appropriately presented in the context of major histocompatibility complex (MHC) to effector T-cells, and in turn recognized by their antigen receptors. We will test these hypotheses in close collaboration with ICBP@Stanford, first taking advantage of systematic methodologies for interrogation of the tumor coding genome, transcriptome, and MHC-peptidome to discover somatic mutations that are predicted (Aim 1) and/or observed (Aim 2) to bind cognate MHC. We will synthesize and assemble synthetic versions of these candidate peptide neoantigens with corresponding MHC molecules, and use them in large peptide-MHC `tetramer' panels to interrogate the T lymphocyte responses induced by tumor vaccination in the patients (Aim 3). In molecularly profiling, and functionally tracking these dynamic responses in serial blood specimens from patients before and after immunization, we aim to differentiate patients with or without clinical responses to this therapy, and to better predict their distinct outcomes. We anticipate that this integrated approach will reveal the interplay between nascent and induced immune responses and genetic factors in control of disease progression in MCL and inform new ways of battling this deadly disease. This approach should also have relevance to other cancers.

Public Health Relevance

Non-Hodgkin Lymphomas are a leading cause of cancer and the majority of patients with this disease remain incurable. While immunity is important in control of this disease and other cancers, currently, there are no clinically validated molecular biomarkers that predict which cancer patients benefit from vaccination. Our application seeks to address this unmet need, in defining the utility of a biomarker that could allow individualization of therapeutic strategies in an aggressive lymphoma, and potentially lead to improved outcomes could have a significant public health impact.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01CA194389-02
Application #
9070633
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Hughes, Shannon K
Project Start
2015-06-01
Project End
2020-05-31
Budget Start
2016-06-01
Budget End
2017-05-31
Support Year
2
Fiscal Year
2016
Total Cost
Indirect Cost
Name
Stanford University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94304
Przybyl, Joanna; Chabon, Jacob J; Spans, Lien et al. (2018) Combination Approach for Detecting Different Types of Alterations in Circulating Tumor DNA in Leiomyosarcoma. Clin Cancer Res 24:2688-2699
Olsson, Niclas; Schultz, Liora M; Zhang, Lichao et al. (2018) T-Cell Immunopeptidomes Reveal Cell Subtype Surface Markers Derived From Intracellular Proteins. Proteomics 18:e1700410
Lill, Jennie R; van Veelen, Peter A; Tenzer, Stefan et al. (2018) Minimal Information About an Immuno-Peptidomics Experiment (MIAIPE). Proteomics 18:e1800110
Chaudhuri, Aadel A; Chabon, Jacob J; Lovejoy, Alexander F et al. (2017) Early Detection of Molecular Residual Disease in Localized Lung Cancer by Circulating Tumor DNA Profiling. Cancer Discov 7:1394-1403
Khodadoust, Michael S; Olsson, Niclas; Wagar, Lisa E et al. (2017) Antigen presentation profiling reveals recognition of lymphoma immunoglobulin neoantigens. Nature 543:723-727
Myklebust, June H; Brody, Joshua; Kohrt, Holbrook E et al. (2017) Distinct patterns of B-cell receptor signaling in non-Hodgkin lymphomas identified by single-cell profiling. Blood 129:759-770
Scherer, Florian; Kurtz, David M; Diehn, Maximilian et al. (2017) High-throughput sequencing for noninvasive disease detection in hematologic malignancies. Blood 130:440-452
Kunder, Christian A; Roncador, Giovanna; Advani, Ranjana H et al. (2017) KLHL6 Is Preferentially Expressed in Germinal Center-Derived B-Cell Lymphomas. Am J Clin Pathol 148:465-476
Newman, Aaron M; Gentles, Andrew J; Liu, Chih Long et al. (2017) Data normalization considerations for digital tumor dissection. Genome Biol 18:128
Newman, Aaron M; Lovejoy, Alexander F; Klass, Daniel M et al. (2016) Integrated digital error suppression for improved detection of circulating tumor DNA. Nat Biotechnol 34:547-555

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