R version 3.6.3

Correlations between mutations and response to therapy were assessed by the Fisher exact test and trend test across the response groups (prop.trend.test function in R). Comparison of continuous variables between groups was performed by the Mann-Whitney rank test, while the Wilcoxon rank test was used for paired samples. Survival data were assessed by a Cox regression analysis, calculating hazard ratios for each parameter. For Kaplan-Meier plots, patient subgroups were compared by the log rank test (for further details, see Additional file 1). Genomic Identifications of Significant Targets in Cancer (GISTIC) 2.0 [35 (link)] was used to identify frequent focal- and arm-level amplifications and deletions.
Statistical analyses were performed using R, version 3.6.3, or the SPSS 26/PASW 17.0 software package. All p-values reported are two-tailed, and p < 0.05 was considered statistically significant.

All statistical analyses were performed with R (version 3.6.3) and SPSS v26.0
(SPSS Inc., USA). The statistical difference between two groups was compared
using unpaired Student's t-test and comparisons among multiple
groups were analyzed using one-way analysis of variance (ANOVA) with Tukey's
post hoc test for pairwise comparison. P value of <0.05
was considered statistically significant and all tests were two-sided.

Statistical analysis and charts preparation were carried out using R (version 3.6.3) and SPSS (version 25). Student’s t-test was used for comparison between the two groups, and variance analysis was used for data comparison between multiple groups. p-values < 0.05 were considered statistically significant.

All statistical analyses are carried out using R (version 3.6.3) and SPSS 22.0. Pearson correlation analysis was used to determine the correlation, and survival analysis was performed using the log-rank test. p < 0.05 was considered statistically different.

All statistical analyses were performed with R (version 3.6.3) and SPSS v26.0 (SPSS Inc, Chicago, IL). Statistical significance between groups was determined using two tailed Student s t test. P value of <0.05 was considered statistically significant and all tests were two sided.

The distribution of two sets of continuous variables was compared using a t-test. If continuous variables did not follow a normal distribution, the Mann–Whitney U test was applied. Unless explicitly stated, the association between categorical variables was evaluated using Pearson’s chi-square test. To divide the samples assessed into groups according to high versus low TMEscore, the MaxStat R package was used. Survival curves were compared using the Kaplan–Meier method with a log-rank t-test. The influence of the TMEscore on survival was additionally evaluated through the Cox proportional hazard model. The independence of association was verified by a multivariate Cox regression model of survival. The resulting p-values of differently expressed genes between two groups were corrected for multiple testing by the Benjamini–Hochberg method. All reported p-values are two-sided. R (version 3.6.3) and SPSS (version 17.0; SPSS Inc., Chicago, IL, USA) were used to perform statistical analyses. Figures were generated with the ggplot R package and GraphPad Prism 8 (GraphPad Prism Software, San Diego, CA, USA). Two-sided p < 0.05 was considered significant.

Shapiro–Wilk test was used for testing the normality of all continuous variables. Normally distributed continuous variables were expressed as means ± SD, while abnormally distributed continuous variables were expressed as median (the 25th and 75th quartiles). Categorical variables were presented as frequencies and percentages (%). To determine significant variables between surviving and non-surviving groups in AAD and type A AAD derivation cohort, chi-squared tests were performed for categorical variables, and Wilcoxon rank-sum and one-way ANOVA tests were performed for continuous variables. Logistic regression was performed to develop fast-to-use prognostic models for AAD and type A AAD patients. All analyses were conducted using R (version 3.6.3) and SPSS (version 25). All statistical analyses were two-sided, and the significance level was set to p < 0.05.