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Factors predictive of second-line chemotherapy in soft tissue sarcoma: An analysis of the National Genomic Profiling
Takao Mochizuki1,2, Masachika Ikegami2,3, Toru Akiyama1
1Department of Orthopaedic Surgery, Saitama Medical Center, Jichi Medical University, Saitama, Japan.
Abstract:
Of the drugs used in second-line chemotherapy for soft tissue sarcoma (STS), trabectedin is effective for liposarcoma and leiomyosarcoma (L-sarcoma), eribulin for liposarcoma, and pazopanib for non-liposarcoma. The indications for these drugs in STS other than L-sarcoma have not been established. Here we explored the prognosis, mutation profiles, and drug-response factors in STS using real-world big data. Clinicogenomic data on 1761 patients with sarcoma who underwent FoundationOne CDx were obtained from a national database in Japan. Patients with TP53 and KDM2D mutations had a significantly shorter survival period of 253 (95% CI, 99-404) and 330 (95% CI, 20-552) days, respectively, than those without mutations. Non-supervised clustering based on mutation profiles generated 13 tumor clusters. The response rate (RR) to trabectedin was highest in an MDM2-amplification cluster (odds ratio [OR]: 2.2; p = 0.2). The RR was lowest for eribulin in an MDM2-amplification cluster (OR: 0.4; p = 0.03) and highest in a TERT-mutation cluster (OR: 3.0; p = 0.03). The RR was highest for pazopanib in a PIK3CA/PTEN-wild type cluster (OR: 2.1; p = 0.03). In particular, patients harboring mutations in genes regulating the PI3K/Akt/mTOR pathway had a lower RR than patients without mutations (OR: 0.3; p = 0.04). In STS, mutation profiles were more useful in predicting the drug response than histology. The present study demonstrated the potential of tailored therapy guided by mutation profiles established by comprehensive genomic profiling testing in optimizing second-line chemotherapy for STS. The findings of this study will hopefully contribute some valuable insights into enhancing STS treatment strategies and outcomes.
Insights
Genomic mutation profiles, not histology, better predict soft tissue sarcoma (STS) drug response. Comprehensive genomic profiling can guide tailored second-line chemotherapy for improved patient outcomes in STS.
Area of Science:
- Oncology
- Genomics
- Pharmacology
Background:
- Second-line chemotherapy for soft tissue sarcoma (STS) includes trabectedin, eribulin, and pazopanib, with established efficacy in specific subtypes like liposarcoma and leiomyosarcoma.
- Indications for these agents in STS subtypes beyond liposarcoma and leiomyosarcoma remain largely undefined.
- Real-world data is crucial for understanding prognostic factors and optimizing treatment strategies in diverse STS populations.
Purpose of the Study:
- To explore prognosis, mutation profiles, and drug-response factors in STS using a large, real-world dataset.
- To identify specific genetic mutations associated with survival outcomes in STS patients.
- To determine the predictive value of mutation profiles for guiding second-line chemotherapy selection in STS.
Main Methods:
- Utilized clinicogenomic data from 1761 Japanese patients with sarcoma who underwent FoundationOne CDx testing.
- Performed non-supervised clustering based on mutation profiles to identify distinct tumor clusters.
- Analyzed response rates (RR) to trabectedin, eribulin, and pazopanib in relation to specific mutation profiles and gene pathway alterations.
Main Results:
- TP53 and KDM2D mutations were significantly associated with shorter survival periods.
- Thirteen distinct tumor clusters were identified based on mutation profiles.
- Specific mutation profiles correlated with differential response rates to trabectedin (MDM2-amplification), eribulin (MDM2-amplification, TERT-mutation), and pazopanib (PIK3CA/PTEN-wild type).
- Mutations in the PI3K/Akt/mTOR pathway were linked to lower drug response rates.
Conclusions:
- Mutation profiles are more predictive of drug response in STS than traditional histology.
- Comprehensive genomic profiling can identify actionable targets and guide personalized second-line chemotherapy selection.
- Tailored therapy based on genomic insights holds significant potential for improving treatment strategies and outcomes in soft tissue sarcoma.
