KEY TAKEAWAYS
- The study aimed to investigate the efficacy of multi-biomarker profiles in predicting prognosis and immunotherapy response in patients with advanced CC.
- Researchers noticed that multi-biomarker profiles can significantly improve prognosis prediction and immunotherapy response identification.
Cervical cancer (CC) poses a global health challenge, with a particularly poor prognosis in cases of recurrence, metastasis, or advanced stages. A single biomarker is inadequate to predict CC prognosis or identify CC patients likely to benefit from immunotherapy, presumably owing to tumor complexity and heterogeneity.
Xu Zhang and the team aimed to assess the efficacy of multi-biomarker profiles in predicting prognosis and immunotherapy response in patients with advanced CC.
They performed an inclusive analysis using advanced Olink proteomics to examine 92 oncology-related proteins in plasma from CC patients receiving immunotherapy. The analysis compared protein expression levels from pre-therapy to therapy-Cycle 6 between the partial response (PR) group and the progressive disease (PD) group, respectively.
About 55 proteins were identified to exhibit differential expression trends across pre-therapy and post-therapy in both PR and PD groups. Enriched GO terms and KEGG pathways were associated with vital oncological and immunological processes. A logistic regression model using 5 proteins (ITGB5, TGF-α, TLR3, WIF-1, and ERBB3) with the highest AUC values demonstrated good predictive performance for the prognosis of CC patients undergoing immunotherapy and showed potential across different cancer types.
The effectiveness of these proteins in prognosis prediction was further validated using TCGA-CESC datasets. A negative correlation and previously unidentified roles of WIF-1 in CC immunotherapy were also first determined.
The study concluded that multi-biomarker profiles effectively predict CC prognosis and identify patients who benefit most from immunotherapy, particularly those with limited treatment options and traditionally poor prognosis. This approach paves the way for personalized immunotherapeutic treatments and improved clinical strategies.
The study received no funds.
Source: https://pubmed.ncbi.nlm.nih.gov/38835778/
Zhang X, Li J, Yang L, et al. (2024). “Targeted proteomics-determined multi-biomarker profiles developed classifier for prognosis and immunotherapy responses of advanced cervical cancer.” Front Immunol. 2024 May 21;15:1391524. doi: 10.3389/fimmu.2024.1391524. PMID: 38835778; PMCID: PMC11148239.
