A Nine-Gene Signature for Predicting the Response to Preoperative Chemoradiotherapy in Patients with Locally Advanced Rectal Cancer.
In-Ja ParkYun Suk YuBilal MustafaJin Young ParkYong Bae SeoGun-Do KimJinpyo KimChang Min KimHyun Deok NohSeung-Mo HongYeon Wook KimMi-Ju KimAdnan Ahmad AnsariLuigi BuonaguroSung-Min AhnChang-Sik YuPublished in: Cancers (2020)
Preoperative chemoradiotherapy (PCRT) and subsequent surgery is the standard multimodal treatment for locally advanced rectal cancer (LARC), albeit PCRT response varies among the individuals. This creates a dire necessity to identify a predictive model to forecast treatment response outcomes and identify patients who would benefit from PCRT. In this study, we performed a gene expression study using formalin-fixed paraffin-embedded (FFPE) tumor biopsy samples from 156 LARC patients (training cohort n = 60; validation cohort n = 96); we identified the nine-gene signature (FGFR3, GNA11, H3F3A, IL12A, IL1R1, IL2RB, NKD1, SGK2, and SPRY2) that distinctively differentiated responders from non-responders in the training cohort (accuracy = 86.9%, specificity = 84.8%, sensitivity = 81.5%) as well as in an independent validation cohort (accuracy = 81.0%, specificity = 79.4%, sensitivity = 82.3%). The signature was independent of all pathological and clinical features and was robust in predicting PCRT response. It is readily applicable to the clinical setting using FFPE samples and Food and Drug Administration (FDA) approved hardware and reagents. Predicting the response to PCRT may aid in tailored therapies for respective responders to PCRT and improve the oncologic outcomes for LARC patients.
Keyphrases
- rectal cancer
- locally advanced
- gene expression
- end stage renal disease
- chronic kidney disease
- ejection fraction
- neoadjuvant chemotherapy
- newly diagnosed
- drug administration
- squamous cell carcinoma
- radiation therapy
- patients undergoing
- minimally invasive
- genome wide
- prognostic factors
- dna methylation
- coronary artery disease
- prostate cancer
- lymph node
- risk assessment
- smoking cessation
- transcription factor
- chronic pain
- combination therapy