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Updated: Aug 26, 2025
Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
Published on: October 25, 2011
Exploration of the underlying biological differences and targets in ovarian cancer patients with diverse
Jinjin Chen1, Surong Chen1, Xichao Dai1
1Oncology Department, The First People's Hospital of Yancheng City, The Yancheng Clinical College of Xuzhou Medical University, Yancheng, China.
Background:
Preclinical trials of immunotherapy in ovarian cancer (OC) have shown promising results. This makes it meaningful to prospectively examine the biological mechanisms explaining the differences in response performances to immunotherapy among OC patients.
Methods:
Open-accessed data was obtained from the Cancer Genome Atlas and Gene Expression Omnibus database. All the analysis was conducted using the R software.
Results:
We firstly performed the TIDE analysis to evaluate the immunotherapy response rate of OC patients. The machine learning algorithm LASSO logistic regression and SVM-RFE were used to identify the characteristic genes. The genes DPT, RUNX1T1, PTPRN, LSAMP, FDCSP and COL6A6 were selected for molecular typing. Our result showed that the patients in Cluster1 might have a better prognosis and might be more sensitive to immunotherapy, including PD-1 and CTLA4 therapy options. Pathway enrichment analysis showed that in Cluster2, the pathway of EMT, TNFα/NF-kB signaling, IL2/STAT5 signaling, inflammatory response, KRAS signaling, apical junction, complement, interferon-gamma response and allograft rejection were significantly activated. Also, genomic instability analysis was performed to identify the underlying genomic difference between the different Cluster patients. Single-cell analysis showed that the DPT, COL6A6, LSAMP and RUNX1T1 were mainly expressed in the fibroblasts. We then quantified the CAFs infiltration in the OC samples. The result showed that patients with low CAFs infiltration might have a lower TIDE score and a higher proportion of immunotherapy responders. Also, we found all the characteristic genes DPT, RUNX1T1, PTPRN, LSAMP, FDCSP and COL6A6 were upregulated in the patients with high CAFs infiltration. Immune infiltration analysis showed that the patients in Cluster2 might have a higher infiltration of naive B cells, activated NK cells and resting Dendritic cells.
Conclusions:
In summary, our study provides new insights into ovarian cancer immunotherapy. Meanwhile, specific targets DPT, RUNX1T1, PTPRN, LSAMP, FDCSP, COL6A6 and CAFs were identified for OC immunotherapy.
Insights
This study identifies key genes (DPT, RUNX1T1, PTPRN, LSAMP, FDCSP, COL6A6) and cancer-associated fibroblasts (CAFs) as crucial factors influencing ovarian cancer immunotherapy response. Lower CAFs infiltration correlates with better treatment outcomes.
Area of Science:
- Oncology
- Immunology
- Genomics
Background:
- Preclinical immunotherapy trials in ovarian cancer (OC) show promise.
- Understanding response variability is crucial for effective treatment.
Purpose of the Study:
- To investigate biological mechanisms behind differential immunotherapy responses in OC.
- To identify predictive biomarkers for immunotherapy efficacy.
Main Methods:
- Utilized open-accessed data from TCGA and GEO databases.
- Applied TIDE analysis, LASSO, and SVM-RFE for gene identification and molecular typing.
- Conducted pathway enrichment, genomic instability, single-cell, and immune infiltration analyses.
Main Results:
- Identified six characteristic genes (DPT, RUNX1T1, PTPRN, LSAMP, FDCSP, COL6A6) for molecular subtyping.
- Cluster1 patients showed better prognosis and potential sensitivity to PD-1/CTLA4 therapies.
- High CAFs infiltration correlated with upregulated characteristic genes and potentially poorer immunotherapy response.
- Cluster2 exhibited activated inflammatory and signaling pathways; specific immune cell infiltrations were noted.
Conclusions:
- Discovered novel molecular subtypes and predictive biomarkers for OC immunotherapy.
- Highlighted the role of CAFs infiltration in modulating treatment response.
- Identified specific genes and CAFs as potential therapeutic targets for enhancing OC immunotherapy.
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