R01CA265928

A Precision Tumor Neoantigen Identification Pipeline for Cytotoxic T-Lymphocyte-Based Cancer Immunotherapies - Abstract

Programming the immune system to detect neoantigens and destroy tumors is critical for effective immunotherapy. Until now, bioinformatic prediction of neoepitopes on tumors from next-generation sequencing (NGS) information has been used alone or in conjunction with immunological assays to indirectly infer neoepitope identification.

Unfortunately, only a small fraction of predicted epitopes are surface-displayed as HLA-bound peptides (PMHC), a process required for cytolytic T lymphocyte (CTL) targeting. Moreover, immunologic assays suffer from both high false positive and false negative rates, confounding correct identification.

Conventional mass spectrometry (MS) approaches to interrogate the PMHC, referred to as the cell's immune peptidome, suffer from poor HLA recovery, the requirement for multiple sample runs to achieve adequate peptide coverage, and necessitate large numbers of tumor cells, all features impractical for routine clinical use.

Our academic-industrial partnership (AIP) advances the creation of a commercial pipeline to deliver personalized tumor neoantigen identification, integrating NGS-based genomics and transcriptomics, bioinformatics, chemical peptidomics, and a novel, ultrasensitive form of MS.

Our interdisciplinary/multi-institutional strategic alliance combines basic research at Dana Farber Cancer Institute with industrial expertise at CuracCloud Corporation and JPT Peptide Technologies. We propose deployment of an attomole (10-18) Poisson detection liquid chromatography-data independent acquisition (LC-DIA) MS method for antigen discovery to electronically record and capture the entire immune peptidome comprising both numerous self-peptides and sparse neoantigens in a single run from small numbers of tumor cells (106) retrieved by clinical needle biopsy.

This approach changes the aforementioned MS calculus and permits neoantigen search at any point following data collection using existing commercially marketed MS instrumentation.

In Aim 1, neoepitope candidates shall be chemically synthesized in high throughput pools of up to 6,000 peptides per nanoscale run by JPT for MS fragmentation analysis and elution mapping reference standards for definitive neoantigen identification using LC-DIAMS on individual tumor samples based on DFCI technology, optimizing each step.

In Aim 2, we shall use NGS data from tumor cells in conjunction with bioinformatics at CuracCloud to predict neoepitopes arising from coding and non-coding regions capable of interacting with each HLA-A, -B, and/or -C allele of a patient. Machine learning-based neoepitope ranking algorithms incorporating MS data and other results shall be developed for candidate prioritization.

An end-user service shall be established involving all aforementioned integrative technologies. From initial tumor biopsy to identification of neoepitopes, a time scale of approximately one month is anticipated.

This generic neoepitope precision identification pipeline is applicable to multiple immunotherapy protocols as well as immune monitoring of tumor evolution at the original and any metastatic site, informing therapeutic adjustments as required.

Dana-Farber Cancer Institute

TO IMPROVE SCREENING AND EARLY DETECTION STRATEGIES AND TO DEVELOP ACCURATE DIAGNOSTIC TECHNIQUES AND METHODS FOR PREDICTING THE COURSE OF DISEASE IN CANCER PATIENTS. SCREENING AND EARLY DETECTION RESEARCH INCLUDES DEVELOPMENT OF STRATEGIES TO DECREASE CANCER MORTALITY BY FINDING TUMORS EARLY WHEN THEY ARE MORE AMENABLE TO TREATMENT. DIAGNOSIS RESEARCH FOCUSES ON METHODS TO DETERMINE THE PRESENCE OF A SPECIFIC TYPE OF CANCER, TO PREDICT ITS COURSE AND RESPONSE TO THERAPY, BOTH A PARTICULAR THERAPY OR A CLASS OF AGENTS, AND TO MONITOR THE EFFECT OF THE THERAPY AND THE APPEARANCE OF DISEASE RECURRENCE. THESE METHODS INCLUDE DIAGNOSTIC IMAGING AND DIRECT ANALYSES OF SPECIMENS FROM TUMOR OR OTHER TISSUES. SUPPORT IS ALSO PROVIDED FOR ESTABLISHING AND MAINTAINING RESOURCES OF HUMAN TISSUE TO FACILITATE RESEARCH. SMALL BUSINESS INNOVATION RESEARCH (SBIR) PROGRAM: TO EXPAND AND IMPROVE THE SBIR PROGRAM, TO INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT, TO INCREASE SMALL BUSINESS PARTICIPATION IN FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION OF SOCIALLY AND ECONOMICALLY DISADVANTAGED SMALL BUSINESS CONCERNS AND WOMEN-OWNED SMALL BUSINESS CONCERNS IN TECHNOLOGICAL INNOVATION. SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAM: TO STIMULATE AND FOSTER SCIENTIFIC AND TECHNOLOGICAL INNOVATION THROUGH COOPERATIVE RESEARCH AND DEVELOPMENT CARRIED OUT BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO FOSTER TECHNOLOGY TRANSFER BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION OF SOCIALLY AND ECONOMICALLY DISADVANTAGED SMALL BUSINESS CONCERNS AND WOMEN-OWNED SMALL BUSINESS CONCERNS IN TECHNOLOGICAL INNOVATION.

93.394 - Cancer Detection and Diagnosis Research

National Cancer Institute (NCI) [HHS - NIH]

Boston, Massachusetts 022155418 United States

Single Zip Code

Academic-Industrial Partnerships for Translation of Technologies for Diagnosis and Treatment (R01 - Clinical Trial Optional) (PAR-18-530)

Amendment Since initial award the total obligations have increased 372% from $713,250 to $3,363,059.