Rare FGFR fusion genes in cervical cancer and transcriptome-based subgrouping of patients with a poor prognosis

BackgroundAlthough cervical cancer is often characterized as preventable, its incidence continues to increase in low- and middle-income countries, underscoring the need to develop novel therapeutics for this disease.This study assessed the distribution of fusion genes across cancer types and used an RNA-based classification to divide cervical cancer patients with a poor prognosis into subgroups. Material and MethodsRNA sequencing of 116 patients with cervical cancer was conducted. Fusion genes were extracted using StarFusion program. To identify a high-risk group for recurrence, 65 patients who received postoperative adjuvant therapy were subjected to non-negative matrix factorization to identify differentially expressed genes between recurrent and nonrecurrent groups. ResultsWe identified three cases with FGFR3-TACC3 and one with GOPC-ROS1 fusion genes as potential targets. A search of publicly available data from cBioPortal (21,789 cases) and the Center for Cancer Genomics and Advanced Therapeutics (32,608 cases) showed that the FGFR3 fusion is present in 1.5% and 0.6% of patients with cervical cancer, respectively. The frequency of the FGFR3 fusion gene was higher in cervical cancer than in other cancers, regardless of ethnicity. Non-negative matrix factorization identified that the patients were classified into four Basis groups. Pathway enrichment analysis identified more extracellular matrix kinetics dysregulation in Basis 3 and more immune system dysregulation in Basis 4 than in the good prognosis group. CIBERSORT analysis showed that the fraction of M1 macrophages was lower in the poor prognosis group than in the good prognosis group. ConclusionsThe distribution of FGFR fusion genes in patients with cervical cancer was determined by RNA-based analysis and used to classify patients into clinically relevant subgroups.

Automated summary

This study determined the distribution of FGFR fusion genes in cervical cancer patients using RNA-based analysis, and classified patients into clinically relevant subgroups. The results showed a higher frequency of FGFR fusion genes in cervical cancer compared to other cancers, and different gene expression patterns were associated with prognosis.