التفاصيل البيبلوغرافية
| العنوان: |
DNA methylome and transcriptome landscapes of cancer-associated fibroblasts reveal a smoking-associated malignancy index. |
| المؤلفون: |
Sheng-Fang Su1,2,3, Hao Ho1, Jia-Hua Li1, Ming-Fang Wu1,4, Hsu-Chieh Wang5, Hsiang-Yuan Yeh6, Shuenn-Wen Kuo7, Huei-Wen Chen4, Chao-Chi Ho5 ccho1203@ntu.edu.tw, Ker-Chau Li1,8 kcli@stat.sinica.edu.tw, Su, Sheng-Fang9 (AUTHOR), Ho, Hao10 (AUTHOR), Li, Jia-Hua10 (AUTHOR), Wu, Ming-Fang10 (AUTHOR), Wang, Hsu-Chieh11 (AUTHOR), Yeh, Hsiang-Yuan6 (AUTHOR), Kuo, Shuenn-Wen7 (AUTHOR), Chen, Huei-Wen12 (AUTHOR), Ho, Chao-Chi11 (AUTHOR), Li, Ker-Chau13 (AUTHOR) |
| المصدر: |
Journal of Clinical Investigation. 8/16/2021, Vol. 131 Issue 16, p1-12. 12p. |
| مصطلحات موضوعية: |
*FIBROBLASTS, *DNA methylation, *DISEASE relapse, *SMOKING statistics, *SMOKING, *NON-small-cell lung carcinoma, *TRANSCRIPTOMES, *LUNG cancer, *CANCER cell culture, *DNA, *LUNG tumors, *CANCER relapse, *PROGNOSIS, *CELL physiology, *GENE expression profiling, *GENES |
| مستخلص: |
Unlike the better-studied aberrant epigenome in the tumor, the clinicopathologic impact of DNA methylation in the tumor microenvironment (TME), especially the contribution from cancer-associated fibroblasts (CAFs), remains elusive. CAFs exhibit profound patient-to-patient tumorigenic heterogeneity. We asked whether such heterogeneity may be exploited to quantify the level of TME malignancy. We developed a robust and efficient methylome/transcriptome co-analytical system for CAFs and paired normal fibroblasts (NFs) from non-small-cell lung cancer patients. We found 14,781 CpG sites of CAF/NF differential methylation, of which 3,707 sites showed higher methylation changes in ever-smokers than in nonsmokers. Concomitant CAF/NF differential gene expression analysis pointed to a subset of 54 smoking-associated CpG sites with strong methylation-regulated gene expression. A methylation index that summarizes the β values of these CpGs was built for NF/CAF discrimination (MIND) with high sensitivity and specificity. The potential of MIND in detecting premalignancy across individual patients was shown. MIND succeeded in predicting tumor recurrence in multiple lung cancer cohorts without reliance on patient survival data, suggesting that the malignancy level of TME may be effectively graded by this index. Precision TME grading may provide additional pathological information to guide cancer prognosis and open up more options in personalized medicine. [ABSTRACT FROM AUTHOR] |
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