Skip to main content
Fig. 1 | Journal of Hematology & Oncology

Fig. 1

From: m6A regulators as predictive biomarkers for chemotherapy benefit and potential therapeutic targets for overcoming chemotherapy resistance in small-cell lung cancer

Fig. 1

Identification of m6A regulators as predictive biomarkers and potential therapeutic targets in small-cell lung cancer with chemotherapy. a The work flow of this study. Thirty m6A regulators were selected from several recently published studies. The predictive regulators were filtered out through Kaplan–Meier curve analysis. The m6A score was constructed using the LASSO Cox regression model and the training cohort. The m6A score was validated in two different cohorts with qPCR data and immunohistochemistry data. Finally, the therapeutic potential of several regulators was explored through in vitro experiments. b A forest plot of the optimum cutoff survival analysis of the m6A regulators in SCLC patients from the training cohort who underwent chemotherapy. c The LASSO model was selected to determine the partial likelihood deviance of different numbers of variables, and 100-fold cross-validation was chosen. d Distribution of the LASSO coefficients of 15 significant regulators. e Distribution of the seven regulators comprising the m6A score, the corresponding m6A score, and survival status in the training cohort. f Survival curve of OS for patients from the training cohort. g Time-dependent ROC curves comparing the prognostic accuracy of the m6A score with other clinicopathological parameters at 5 years in the training cohort. h Distribution of the seven regulators comprising the m6A score, the corresponding m6A score, and survival status in the validation cohort with qPCR data. i Survival curve of OS for patients from the validation cohort. j Survival curve of RFS for patients from the validation cohort. k Time-dependent ROC curves comparing the prognostic accuracy of the m6A score with other clinicopathological parameters at 5 years in the validation cohort. l Representative immunohistochemistry images of the seven regulators comprising the m6A score from the tissue microarray; (+) high expression, (−) low expression (40 ×). m Distribution of the seven regulators comprising the m6A score, the corresponding m6A score, and survival status in the independent cohort. n Survival curve of OS for patients from the independent cohort. o Survival curve of RFS for patients from the independent cohort. p Time-dependent ROC curves comparing the prognostic accuracy of the m6A score with other clinicopathological parameters at 5 years in the independent cohort. q Univariate Cox regression analysis of clinicopathological factors and the m6A score for OS in patients across multiple cohorts. r Multivariate Cox regression analysis of clinicopathological factors and the m6A score for OS in patients across multiple cohorts. s Distribution of the four selected regulators in normal lung and SCLC tissues from GSE40275. t, x Knocking down the expression of G3BP1 significantly increased the sensitivity of SCLC cells to cisplatin. u, y Knocking down the expression of ZCCH4 significantly increased the sensitivity of SCLC cells to cisplatin. v, z Knocking down the expression of METTL5 had no effect on the sensitivity of SCLC cells to cisplatin. w, aa Knocking down the expression of RBMX significantly increased the sensitivity of SCLC cells to cisplatin

Back to article page