Biomarkers for cancer immunotherapy outcomes
Inventors
Bild, Andrea • GRIFFITHS, Jason I.
Assignees
National Institutes of Health NIH • City of Hope
Publication Number
US-11708612-B2
Publication Date
2023-07-25
Expiration Date
2040-12-02
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Abstract
Provided herein, inter alia, are improved methods and systems of determining immunotherapy response in subjects prior and during treatment. Provided herein are methods of detecting gene expression in T cells and in monocytes as well as measuring relative abundance of particular immune cell populations and determining responsiveness to anticancer immunotherapy.
Core Innovation
The invention provides improved methods and systems for determining immunotherapy response in subjects prior to and during treatment. It includes methods of detecting gene expression in T cells and in monocytes, measuring the relative abundance of specific immune cell populations, and determining responsiveness to anticancer immunotherapy, particularly treatment with PD-1 inhibitors.
The problem being solved addresses the variability in clinical response to immune checkpoint inhibitors among cancer patients. While immunotherapies targeting pathways such as PD-1/PD-L1 have shown clinical benefits, a significant proportion of patients do not respond. Existing biomarkers, such as PD-L1 tumor expression and tumor mutation burden, require invasive tumor tissue sampling which is often challenging. Furthermore, the relevance of circulating immune cells as non-invasive markers of tumor response is unclear, including whether their numbers, phenotypes, and changes during treatment can predict immunotherapy success.
Claims Coverage
The claims include one independent claim directed to a method of detecting specific gene expression markers in peripheral blood monocytes and treating a subject with a PD-1 inhibitor, highlighting inventive features involving gene expression and immune cell population detection.
Detection of increased expression of multiple specified genes in peripheral blood monocytes
Detecting increased expression of three or more of the following genes in monocytes compared to a control: TNF, FOS, JUN, JUNB, TNFAIP2, TNFAIP3, NFKB1, NFKBIA, or NFKBIZ.
Detection of decreased expression and immune cell population changes compared to a control
Detecting either (a) decreased expression of IKBKB; (b) increased number of CD8+ differentiated cells, increased number of CD4+ naive cells, decreased number of CD4+ differentiated cells, and decreased number of T follicular helper cells; or (c) lower density of total peripheral blood mononuclear cells, lower density of CD4+ effector memory cells, and higher density of classical monocytes.
Detection of additional immune cell parameters by fluorescence-activated cell sorting (FACS)
Detecting one or more of the following: increased expression in T cells of one or more cell death genes (e.g., CASP1, CASP3, CASP7, CASP8); greater number of CTLA4+CD4+ effector memory cells and PD-1+ CD8+ cells; increased numbers of classical, CD86+, and HLADR+ monocytes; fewer CD4+ effector memory cells and greater number of CTLA4+ CD4+ effector memory cells as measured by FACS.
Treatment selecting and administration
Selecting and treating a subject with a PD-1 inhibitor when one or more specified parameters is detected, wherein the PD-1 inhibitor can be a PD-1 antibody such as pembrolizumab, nivolumab, or cemiplimab.
Applicability to gastrointestinal cancers
The methods apply to cancers including gastrointestinal cancers such as colorectal, gastroesophageal, pancreatic, and biliary cancers.
Techniques for detecting gene expression and cell populations
Detecting gene expression using single-cell RNA sequencing, single sample gene set enrichment analysis, Northern blotting, fluorescent in situ hybridization, RT-PCR, serial analysis of gene expression, microarrays, or tiling arrays; and detecting cell counts using single-cell RNA sequencing, affinity-based pseudotime reconstruction, flow cytometry, or immunophenotyping.
The claims cover methods of detecting specific gene expression changes and immune cell population profiles in peripheral blood to identify patients responsive to PD-1 inhibitor treatment and guide therapy, including the use of various gene expression and cell detection techniques, with applications primarily in gastrointestinal cancers.
Stated Advantages
Identification of patients likely to respond to immunotherapy prior to treatment.
Non-invasive measurement of biomarkers through peripheral blood sampling rather than invasive tumor biopsies.
Ability to predict and monitor response to PD-1 immunotherapy dynamically during treatment.
Improved patient stratification leading to optimized timing and selection of immunotherapy relative to chemotherapy.
Potential to reduce adverse events and costs by targeting therapies to responsive patients.
Documented Applications
Predicting response to PD-1 inhibitor immunotherapy in patients with gastrointestinal cancers, including colorectal, gastroesophageal, pancreatic, and biliary cancers.
Monitoring response and guiding continued treatment with PD-1 inhibitors using gene expression and immune cell population profiles from peripheral blood.
Selecting patients for treatment with PD-1 inhibitors based on the detection of specified gene expression and immune cell parameters.
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