Background
A better understanding of locally advanced cervical cancer (LACC) is mandatory for further improving the rates of disease control, since a significant proportion of patients still fail to respond or undergo relapse after concurrent chemoradiation treatment (CRT), and survival for these patients has generally remained poor.
Conclusions
Our results define a predictive gene signature that can help in cervical cancer patient stratification, thus providing a useful tool towards more personalized treatment modalities.
Methods
To identify specific markers of CRT response, we compared pretreatment biopsies from LACC patients with pathological complete response (sensitive) with those from patients showing macroscopic residual tumor (resistant) after neoadjuvant CRT, using a proteomic approach integrated with gene expression profiling. The study of the underpinning mechanisms of chemoradiation response was carried out through in vitro models of cervical cancer.
Results
We identified annexin A2 (ANXA2), N-myc downstream regulated gene 1 (NDRG1) and signal transducer and activator of transcription 1 (STAT1) as biomarkers of LACC patients' responsiveness to CRT. The dataset collected through qPCR on these genes was used as training dataset to implement a Random Forest algorithm able to predict the response of new patients to this treatment. Mechanistic investigations demonstrated the key role of the identified genes in the balance between death and survival of tumor cells. Conclusions: Our results define a predictive gene signature that can help in cervical cancer patient stratification, thus providing a useful tool towards more personalized treatment modalities.