AUTHOR=Rubino Franco , Alvarez-Breckenridge Christopher , Akdemir Kadir , Conley Anthony P. , Bishop Andrew J. , Wang Wei-Lien , Lazar Alexander J. , Rhines Laurence D. , DeMonte Franco , Raza Shaan M. TITLE=Prognostic molecular biomarkers in chordomas: A systematic review and identification of clinically usable biomarker panels JOURNAL=Frontiers in Oncology VOLUME=12 YEAR=2022 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.997506 DOI=10.3389/fonc.2022.997506 ISSN=2234-943X ABSTRACT=Introduction and objective

Despite the improvements in management and treatment of chordomas over time, the risk of disease recurrence remains high. Consequently, there is a push to develop effective systemic therapeutics for newly diagnosed and recurrent disease. In order to tailor treatment for individual chordoma patients and develop effective surveillance strategies, suitable clinical biomarkers need to be identified. The objective of this study was to systematically review all prognostic biomarkers for chordomas reported to date in order to classify them according to localization, study design and statistical analysis.

Methods

Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we systematically reviewed published studies reporting biomarkers that correlated with clinical outcomes. We included time-to-event studies that evaluated biomarkers in skull base or spine chordomas. To be included in our review, the study must have analyzed the outcomes with univariate and/or multivariate methods (log-rank test or a Cox-regression model).

Results

We included 68 studies, of which only 5 were prospective studies. Overall, 103 biomarkers were analyzed in 3183 patients. According to FDA classification, 85 were molecular biomarkers (82.5%) mainly located in nucleus and cytoplasm (48% and 27%, respectively). Thirty-four studies analyzed biomarkers with Cox-regression model. Within these studies, 32 biomarkers (31%) and 22 biomarkers (21%) were independent prognostic factors for PFS and OS, respectively.

Conclusion

Our analysis identified a list of 13 biomarkers correlating with tumor control rates and survival. The future point will be gathering all these results to guide the clinical validation for a chordoma biomarker panel. Our identified biomarkers have strengths and weaknesses according to FDA’s guidelines, some are affordable, have a low-invasive collection method and can be easily measured in any health care setting (RDW and D-dimer), but others molecular biomarkers need specialized assay techniques (microRNAs, PD-1 pathway markers, CDKs and somatic chromosome deletions were more chordoma-specific). A focused list of biomarkers that correlate with local recurrence, metastatic spread and survival might be a cornerstone to determine the need of adjuvant therapies.