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Updated: Jun 17, 2026
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Transcriptomic profiling identifies immunotherapy-responsive phenotypes in microsatellite-stable metastatic
Tomas Konecny1,2, Nate Zadirako1,3, Arpine Grigoryan1
1Armenian Bioinformatics Institute (ABI), Yerevan, Armenia.
Abstract:
Conventional immune checkpoint inhibitors (ICIs) remain largely ineffective in microsatellite-stable metastatic colorectal cancer (MSS mCRC), where low tumor immunogenicity and molecular heterogeneity across metastatic sites underpin therapeutic resistance. We present a comprehensive transcriptomics analysis of metastatic and primary tumor biopsies from MSS mCRC patients treated with botensilimab (BOT; Fc-enhanced anti-CTLA-4) ± balstilimab (BAL; anti-PD-1). Self-organizing map (SOM) machine learning stratified tumors into four molecular types, including a liver-like (LIV) subtype characterized by metabolic reprogramming and immunosuppressive signatures, and proliferative (PRO), inflammatory (INF), and mesenchymal (MES) types concordant with pan-cancer classifications. PRO, INF, and MES types were enriched for epithelial tumor cells, immune cells, and fibroblasts, respectively, defining immune-depleted, immune-enriched, and fibrotic states along a plasticity gradient. We observed treatment-related transcriptomic shifts toward immune-enriched states via upregulation of antigen presentation, T cell recruitment, and cytotoxicity pathways. INF and MES tumor types exhibited improved clinical responses and survival vs PRO and LIV types. This study identified distinct tumor microenvironment states that align along an immunophenotype axis marked by CD74, interferon-γ, and APOBEC3 expression identified previously for primary CRC. Our findings provide novel insights into molecular correlates of immunotherapy response in MSS mCRC, potentially informing future therapeutic strategies to expand ICI efficacy to historically unresponsive tumors.
Insights
This study reveals four molecular subtypes in microsatellite-stable metastatic colorectal cancer (MSS mCRC), identifying specific tumor microenvironments that predict response to novel immunotherapy. These findings may help expand treatment efficacy for patients with MSS mCRC.
Area of Science:
- Oncology
- Immunology
- Genomics
Background:
- Microsatellite-stable metastatic colorectal cancer (MSS mCRC) shows resistance to conventional immune checkpoint inhibitors (ICIs).
- Tumor immunogenicity and heterogeneity contribute to therapeutic resistance in MSS mCRC.
- Botensilimab (Fc-enhanced anti-CTLA-4) and balstilimab (anti-PD-1) are novel immunotherapies being investigated.
Purpose of the Study:
- To analyze transcriptomic profiles of MSS mCRC tumors treated with botensilimab ± balstilimab.
- To identify molecular subtypes and their correlation with immunotherapy response.
- To understand the tumor microenvironment's role in treatment resistance and efficacy.
Main Methods:
- Comprehensive transcriptomics analysis of primary and metastatic MSS mCRC tumor biopsies.
- Application of Self-Organizing Map (SOM) machine learning for tumor stratification.
- Correlation of molecular subtypes with clinical response and survival data.
Main Results:
- Four molecular tumor types (liver-like, proliferative, inflammatory, mesenchymal) were identified.
- Tumor types showed distinct cellular compositions and microenvironment states.
- Inflammatory and mesenchymal types demonstrated improved clinical responses and survival compared to liver-like and proliferative types.
- Treatment induced transcriptomic shifts towards immune-enriched states.
Conclusions:
- Distinct tumor microenvironment states in MSS mCRC are associated with immunotherapy response.
- Molecular subtypes identified can inform patient stratification for novel immunotherapies.
- Findings provide insights into expanding ICI efficacy in previously unresponsive MSS mCRC tumors.
