Abstract
PurposeWe aimed to establish radiotranscriptomics signatures based on serum miRNA levels and computed tomography (CT) texture features and develop nomogram models for predicting radiotherapy response in patients with nonsmall cell lung cancer (NSCLC).MethodsWe first used established radioresistant NSCLC cell lines for miRNA selection. At the same time, patients (103 for training set and 71 for validation set) with NSCLC were enrolled. Their pretreatment contrast‐enhanced CT texture features were extracted and their serum miRNA levels were obtained. Then, radiotranscriptomics feature selection was implemented with the least absolute shrinkage and selection operator (LASSO), and signatures were generated by logistic or Cox regression for objective response rate (ORR), overall survival (OS), and progression‐free survival (PFS). Afterward, radiotranscriptomics signature‐based nomograms were constructed and assessed for clinical use.ResultsFour miRNAs and 22 reproducible contrast‐enhanced CT features were used for radiotranscriptomics feature selection and we generated ORR‐, OS‐, and PFS‐ related radiotranscriptomics signatures. In patients with NSCLC who received radiotherapy, the radiotranscriptomics signatures were independently associated with ORR, OS, and PFS in both the training (OR: 2.94, P < .001; HR: 2.90, P < .001; HR: 3.58, P = .001) and validation set (OR: 2.94, P = .026; HR: 2.14, P = .004; HR: 2.64, P = .016). We also obtained a satisfactory nomogram for ORR. The C‐index values for the ORR nomogram were 0.86 [95% confidence interval (CI), 0.75 to 0.92] in the training set and 0.81 (95% CI, 0.69 to 0.89) in the validation set. The calibration‐in‐the‐large and calibration slope performed well. Decision curve analysis indicated a satisfactory net benefit.ConclusionsThe radiotranscriptomics signature could be an independent biomarker for evaluating radiotherapeutic responses in patients with NSCLC. The radiotranscriptomics signature‐based nomogram could be used to predict patients’ ORR, which would represent progress in individualized medicine.
Highlights
Lung cancer has a high incidence worldwide, second only to prostate cancer in males and breast cancer in females.[1]
The C-index values for the objective response rate (ORR) nomogram were 0.86 in the training set and 0.81 in the validation set
Compared to the significant efforts that have been devoted to the development of miRNAs as diagnostic biomarkers, efforts focused on their function as predictors for therapeutic effects started late but are meaningful.[19]
Summary
Lung cancer has a high incidence worldwide, second only to prostate cancer in males and breast cancer in females.[1] It is the most lethal cancer type and causes one-quarter of all cancer deaths worldwide.[1] The 5-year overall survival (OS) of lung cancer patients is less than 20% and that of patients with distant metastasis is only approximately 5%.2. More than 50% of lung cancer patients receive radiotherapy for both thoracic disease and extra thoracic metastatic sites.[3] In contrast to small cell lung cancer (SCLC), patients with nonsmall cell lung cancer (NSCLC) exhibit wide individual heterogeneity in radiotherapeutic effects. It is of significant benefit to predict the prognosis of patients with NSCLC for optimal treatment
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