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Updated: Jun 24, 2026
08:50
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Genomic determinants and an exploratory prognostic model for immunotherapy outcomes in recurrent or metastatic
Lingling Gu1, Biqing Zhu2, Cuicui Liu3
1Department of Medical Image Center, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing 210000, China.
The Oncologist
|June 23, 2026
Summary
Genomic alterations in cervical cancer can predict responses to immune checkpoint inhibitors (ICIs). A new genomic model identifies high-risk patients, aiding in stratifying immunotherapy outcomes.
Area of Science:
- Oncology
- Genomics
- Immunotherapy
Background:
- Immune checkpoint inhibitors (ICIs) show promise in recurrent or metastatic cervical cancer.
- Patient responses to ICIs are varied, and biomarkers beyond PD-L1 are limited.
Purpose of the Study:
- To identify genomic alterations associated with immunotherapy outcomes in cervical cancer.
- To develop a prognostic model for stratifying patients receiving ICI-based therapy.
Main Methods:
- Targeted sequencing of 437 cancer-related genes in 42 patients undergoing ICI therapy.
- Analysis of progression-free survival (PFS) and development of a genomic risk model.
- Transcriptomic analysis using The Cancer Genome Atlas (TCGA) cohort.
Main Results:
- Frequent alterations included PIK3CA, FBXW7, TERT, BAP1, and EP300.
- Mutations in PIK3CA, EP300, CREBBP, and TERT were linked to prolonged PFS.
- A five-feature genomic model stratified patients into high- and low-risk groups with significant prognostic value.
Conclusions:
- Specific genomic alterations can stratify immunotherapy outcomes in cervical cancer.
- The developed genomic risk model requires validation in larger cohorts.