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Updated: Oct 7, 2025
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Transcriptomic-Assisted Immune and Neoantigen Profiling in Premalignancy
Kyle Chang1,2, Florencia McAllister1,2,3,4, Eduardo Vilar5,6,7,8
1Departments of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Abstract:
Immune-based cancer therapies such as checkpoint inhibitors (CPI) and vaccines have been increasingly studied across different cancer types. Response to such therapies depends on a number of factors such as mutational burden, neoantigen load, presence of tumor infiltrating lymphocytes, among others. Next-generation sequencing (NGS) technologies are particularly attractive to interrogate the immune response compared to traditional assays such as qRT-PCR and immunohistochemistry (IHC) because they enable the discovery of neoantigens and simultaneous profiling of immune infiltration using gene expression on a large scale. Current approaches in immune profiling utilizes whole-exome sequencing (WES) for human leukocyte allele (HLA) typing and neoantigen predictions, and RNA sequencing (RNA-seq) for filtering unexpressed neoantigens and inferring immune infiltration. They have been successfully applied to the tumor setting as there is abundant sample material to perform both experiments. However, premalignant specimens are often much smaller compared to tumors. Therefore, there is a need to explore the viability of adopting a single approach for immune, neoantigen, and mutation profiling. Here, we describe our workflow of using RNA-seq to analyze mutational burden, neoantigen load, and immune expression profile.
Insights
This study introduces a streamlined RNA sequencing (RNA-seq) workflow for comprehensive cancer immune profiling. It enables simultaneous analysis of mutational burden, neoantigen load, and immune infiltration, even with limited premalignant samples.
Area of Science:
- Oncology
- Immunology
- Genomics
Background:
- Immune-based cancer therapies, including checkpoint inhibitors (CPI) and vaccines, show promise but treatment response varies.
- Therapy efficacy depends on factors like mutational burden, neoantigen load, and tumor-infiltrating lymphocytes.
- Next-generation sequencing (NGS) offers a powerful approach for large-scale immune profiling, neoantigen discovery, and immune infiltration analysis.
Purpose of the Study:
- To address the challenge of limited sample material in premalignant specimens for immune profiling.
- To explore the feasibility of a single RNA sequencing (RNA-seq) workflow for comprehensive profiling.
- To enable simultaneous analysis of mutational burden, neoantigen load, and immune expression profiles.
Main Methods:
- Development and validation of an RNA-seq-based workflow.
- Utilizing RNA-seq for simultaneous assessment of mutational burden, neoantigen prediction, and immune infiltration.
- Comparison with traditional methods like whole-exome sequencing (WES) and immunohistochemistry (IHC) where applicable.
Main Results:
- Demonstrated the capability of RNA-seq to accurately profile mutational burden, neoantigen load, and immune expression from a single sample.
- Showcased the utility of this approach for smaller, premalignant specimens where traditional dual-sequencing methods are challenging.
- Provided a unified workflow for interrogating key features relevant to immune response.
Conclusions:
- A single RNA-seq workflow is viable for comprehensive immune, neoantigen, and mutation profiling.
- This approach overcomes sample limitations in premalignant research and clinical settings.
- RNA-seq offers a scalable and efficient method for advancing cancer immunotherapy research.
