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Updated: Mar 27, 2026

Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Multi-Omics Profiling Uncovers Predictive Factors for Tumor-Infiltrating Lymphocyte Therapy in Ovarian Cancer
Xiuzhen Wang1, Rui Hou2, Jinguo Chen3
1Department of Gynaecology, Hainan Affiliated Hospital of Hainan Medical University (Hainan General Hospital), Haikou, China.
Background:
Ovarian cancer (OC) remains a challenging malignancy with a poor prognosis, particularly in advanced stages. Tumor-infiltrating lymphocyte (TIL) therapy shows promise but has yielded inconsistent results in OC patients. This study aimed to identify factors predicting successful TIL isolation and expansion in OC.
Methods:
We performed multi-omics profiling on tumor samples from 10 OC patients, including whole-exome sequencing, bulk RNA sequencing, and single-cell RNA sequencing.
Results:
Genomic analysis revealed heterogeneity in tumor mutation burden, copy number variations, and homologous recombination deficiency status across patients. Single-cell profiling uncovered distinct cellular compositions in tumors, yielding successful TIL products (TIL+) vs. those that did not (TIL-). TIL+ tumors exhibited higher immune cell infiltration, particularly CD8+ effector and effector memory T cells. Metabolic profiling revealed enhanced activity in critical T cell subtypes within TIL+ tumors. Analysis of myeloid cells and fibroblasts identified subpopulations uniquely associated with TIL+ or TIL- samples. Cell-to-cell communication network analysis highlighted potential prognostic markers and interactions influencing TIL isolation outcomes.
Conclusion:
Our findings provide insights into factors affecting TIL therapy efficacy in OC and suggest potential strategies for optimizing patient selection and TIL manufacturing protocols.
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