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Validation of the Transcription Association Chromosomal Instability Index Biomarker on RNA Sequencing in Soft Tissue
Ataaillah Benhaddou1,2, Gaëlle Pérot1,3, Philippe Rochaix1,4
1OncoSarc, INSERM U1037, Cancer Research Center in Toulouse (CRCT), Toulouse, France.
Purpose:
Genomic instability (GIN) plays a critical role in cancer progression and treatment responses. Soft tissue sarcomas (STSs) are characterized by extensive chromosomal rearrangements and transcription-associated stress, both of which contribute to poor clinical outcomes. Current standard grading systems including fédération nationale des centres de lutte contre le cancer (FNCLCC) have limited prognostic accuracy for STS, necessitating improved risk stratification. To address this gap, we developed the Mixed Transcription- and Replication-Associated GIN Classifier (MAGIC) and assessed its translatability from whole-genome sequencing to RNA sequencing (RNA-seq).
Methods:
This study analyzed RNA-seq from 226 localized STS tumors to analyze the fusion transcript breakpoint distribution and assess GIN. We computed MAGIC indices transcription association chromosomal instability index (iTRAC) and Replication-Associated Chromosomal INstability index (iRACIN), which are based on GIN linked to transcription and replication processes, respectively. The iTRAC biomarker was evaluated using FNCLCC and Complexity INdex in SARComas (CINSARC) for metastatic risk stratification. Kaplan-Meier and iterative multi-thresholds partitioning analyses assessed prognostic relevance.
Results:
iTRAC significantly stratified patients with distinct metastatic outcomes, outperforming the FNCLCC and CINSARC grading systems. STS patients with medium iTRAC levels showed the poorest metastasis-free survival. Patients classified into iTRAC-high and iTRAC-low groups achieved a better prognosis. Furthermore, iTRAC stratified patients' metastatic risk in treated and nontreated patients, indicating poorer prognosis with chemotherapy in patients with low iTRAC and better prognosis for those with medium iTRAC. By contrast, iRACIN was not measurable in the RNA-seq-based analysis.
Conclusion:
iTRAC demonstrates superior prognostic utility in STS over the current grading systems, effectively stratifying metastatic risk for patients who might benefit from alternative therapeutic strategies. iTRAC holds the potential for personalizing chemotherapeutic approaches, paving the way for a new precision oncology approach in STS.
