Nomogram for Prediction of Pathologic Complete Remission Using Morphometric Change and Biomarker Expression in Rectal Cancer After Preoperative Chemoradiotherapy

Abstract

Numerous molecular markers and imaging tools have been studied to predict pathologic complete remission (pCR) after preoperative chemoradiotherapy (CRT) for rectal cancer. However, none of these has not shown definite outcomes. The aim of this study is to develop a nomogram to predict pCR by analyzing relevant biomarkers and endoscopic findings. Tumor specimens have been collected prospectively from 120 patients before preoperative CRT in patients with rectal cancer between November 2011 and April 2014. All patients underwent curative resection with total mesorectal excision at 8 weeks after completeness of preoperative CRT. Using reverse transcriptase polymerase chain reaction (RT-PCR) analysis, mRNA expression levels of seven candidate biomarkers (p53, p21, Ki-67, VEGF, CD133, CD24, CD44) were evaluated from fresh tumor samples before CRT. The expression of mRNA was indicated with ΔCt by correction according to the expression of GAPDH (target Ct – GAPDH Ct). The relative quantity of mRNA in pathologic complete remission (pCR) tissue to that in non-pCR tissue was calculated from the relative ratios of 2-ΔCt between two conditions. Lower ΔCt and Higher 2-ΔCt mean higher expression of mRNA. Endoscopic evaluation has been done pre- and post-preoperative CRT. Clinical complete remission by endoscopic finding was no visualization of tumor, white scar, and red scar. Clinical variables were also evaluated. Univariate and multivariate logistic regression analysis with clinical and biologic variables were used to make a predictive model for pCR. Nomogram was developed in a training set (n=80) and validated in external validation set (n=40). Both discrimination and calibration were measured by the area under a receiver operating characteristic (ROC) curve (AUC) and calibration plot, respectively. The pCR was shown in 24 patients (30%). Among seven biomarkers, the mRNA expression levels of four biomarkers (p53, p21, Ki67, CD133) significantly correlated with pCR in training set. Patients showing low expression of p53 and/or high expression of p21, Ki67, CD133 exhibited a significantly greater pCR rate. Among 27 patients showing endoscopic clinical complete response (cCR) after preoperative CRT, 17 patients (63.0%) demonstrated pCR. Lower tumor location showed a higher pCR rate than middle tumor [19 (38.8%) vs. 5(16.1%), p = 0.031]. By logistic regression analysis, tumor location, endoscopic finding after preCRT and four biomarkers (p53, p21, Ki67, CD133) were significantly correlated with pCR. Based on the multivariate prediction model with these variables, a nomogram were drawn for prediction for pCR, and which showed good discrimination ability in training set (AUC=0.945) and validation set (AUC=0.922). The calibration plot demonstrated good agreement between actual and predicted pCR in both patient set. The nomogram for prediction of pCR may be useful in treatment decisions after preoperative CRT to select complete responders for a wait-and-see policy or sphincter preserving surgery.

직장암의 수술 전 화학방사선요법 치료 후 병리학적 완전관해를 예측하기 위해 수 많은 분자 수준의 표지자와 영상학적 도구들이 사용되어 왔다. 하지만 종양의 치료 반응 평가에 대한 명확한 결과를 보여주는 방법은 없었다. 본 연구의 목적은 관련 바이오마커 및 내시경 소견을 분석함으로써 병리학적 완전관해를 예측하는 노모그램을 제시하는 것이다. 종양 검체는 2011년 11월에서 2014년 4월 사이 수술 전 화학방사선요법을 시행 받기 전의 직장암 환자 120명으로부터 전향적으로 채취되었다. 모든 환자는 수술 전 화학방사선요법 종료 후 8주 뒤에 전직장간막 절제술로 근치적 수술을 받았다. 역전사 중합효소 연쇄반응 (RT-PCR) 분석을 통하여 신선 종양 검체로부터 7 개의 바이오마커 (p53, p21, Ki-67, VEGF, CD133, CD24, CD44)의 mRNA 발현 수준을 평가하였다. mRNA의 발현 정도는 GAPDH의 발현 정도에 따라 교정 (목표 Ct – GAPDH Ct)하여 ΔCt로 나타내었다. 병리학적으로 완전관해를 보이지 않은 검체의 mRNA에 대한 완전관해를 보인 검체의 mRNA의 상대적인 양은 두 검체의 2-ΔCt 값의 상대비로 계산하였다. 낮은 ΔCt와 높은 2-ΔCt 값은 mRNA의 발현 수준이 높다는 것을 의미한다. 내시경 검사는 선행 항암방사선 치료 전과 후(선행 항암방사선 치료 종료 후 4주 뒤)에 실시하였다. 내시경 검사를 통해 임상적으로 완전 관해를 판단한 기준은 육안적으로 종양이 보이지 않고, 백색 반흔 혹은 적색 반흔이 남아있는 경우로 하였다. 임상적 변수 또한 평가하였다. 병리학적 완전관해 예측모델을 구축하기 위해 임상변수 및 생물학적 변수를 로지스틱 회기 모형을 이용하여 단변량 및 다변량 분석을 시행하였다. 80명의 훈련 집합(training set)에 대하여 노모그램 (Nomogram)을 개발하고 40명의 외부 검증 집합 (validation set)에서 검증을 ...