Radiotranscriptomics signature‐based predictive nomograms for radiotherapy response in patients with nonsmall cell lung cancer: Combination and association of CT features and serum miRNAs levels
Abstract Purpose We 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). Methods We first used established radi...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-07-01
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| Series: | Cancer Medicine |
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| Online Access: | https://doi.org/10.1002/cam4.3115 |
| _version_ | 1818257569374797824 |
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| author | Liyuan Fan Qiang Cao Xiuping Ding Dongni Gao Qiwei Yang Baosheng Li |
| author_facet | Liyuan Fan Qiang Cao Xiuping Ding Dongni Gao Qiwei Yang Baosheng Li |
| author_sort | Liyuan Fan |
| collection | DOAJ |
| description | Abstract Purpose We 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). Methods We 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. Results Four 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. Conclusions The 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. |
| first_indexed | 2024-12-12T17:45:44Z |
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| institution | Directory Open Access Journal |
| issn | 2045-7634 |
| language | English |
| last_indexed | 2024-12-12T17:45:44Z |
| publishDate | 2020-07-01 |
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| series | Cancer Medicine |
| spelling | doaj.art-b2e8fc68f9eb40df954eb8d51f489d2f2022-12-22T00:16:57ZengWileyCancer Medicine2045-76342020-07-019145065507410.1002/cam4.3115Radiotranscriptomics signature‐based predictive nomograms for radiotherapy response in patients with nonsmall cell lung cancer: Combination and association of CT features and serum miRNAs levelsLiyuan Fan0Qiang Cao1Xiuping Ding2Dongni Gao3Qiwei Yang4Baosheng Li5Cheeloo College of Medicine Shandong University Jinan Shandong ChinaSchool of Computer Science and Engineering Southeast University Nanjing Jiangsu ChinaDepartment of Radiation Oncology Shandong First Medical University and Shandong Academy of Medical Sciences Shandong Cancer Hospital and InstituteHuaiyin Region Jinan Shandong ChinaCheeloo College of Medicine Shandong University Jinan Shandong ChinaCheeloo College of Medicine Shandong University Jinan Shandong ChinaDepartment of Radiation Oncology Shandong First Medical University and Shandong Academy of Medical Sciences Shandong Cancer Hospital and InstituteHuaiyin Region Jinan Shandong ChinaAbstract Purpose We 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). Methods We 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. Results Four 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. Conclusions The 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.https://doi.org/10.1002/cam4.3115CT texture featuresmiRNAsnomogramnonsmall cell lung cancerradiotherapy response |
| spellingShingle | Liyuan Fan Qiang Cao Xiuping Ding Dongni Gao Qiwei Yang Baosheng Li Radiotranscriptomics signature‐based predictive nomograms for radiotherapy response in patients with nonsmall cell lung cancer: Combination and association of CT features and serum miRNAs levels Cancer Medicine CT texture features miRNAs nomogram nonsmall cell lung cancer radiotherapy response |
| title | Radiotranscriptomics signature‐based predictive nomograms for radiotherapy response in patients with nonsmall cell lung cancer: Combination and association of CT features and serum miRNAs levels |
| title_full | Radiotranscriptomics signature‐based predictive nomograms for radiotherapy response in patients with nonsmall cell lung cancer: Combination and association of CT features and serum miRNAs levels |
| title_fullStr | Radiotranscriptomics signature‐based predictive nomograms for radiotherapy response in patients with nonsmall cell lung cancer: Combination and association of CT features and serum miRNAs levels |
| title_full_unstemmed | Radiotranscriptomics signature‐based predictive nomograms for radiotherapy response in patients with nonsmall cell lung cancer: Combination and association of CT features and serum miRNAs levels |
| title_short | Radiotranscriptomics signature‐based predictive nomograms for radiotherapy response in patients with nonsmall cell lung cancer: Combination and association of CT features and serum miRNAs levels |
| title_sort | radiotranscriptomics signature based predictive nomograms for radiotherapy response in patients with nonsmall cell lung cancer combination and association of ct features and serum mirnas levels |
| topic | CT texture features miRNAs nomogram nonsmall cell lung cancer radiotherapy response |
| url | https://doi.org/10.1002/cam4.3115 |
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