Fig 1.
Rationale behind signalling entropy as a prognostic factor in cancer.
A) A high signalling entropy of a tumour sample indicates a promiscuous, stem cell like intra-cellular signalling regime and a heterogeneous cancer cell population. The consequence of a high entropy is thus a tumour with a plastic phenotype, capable of activating diverse pathways in response to treatment. High signalling entropy tumours are thus likely to result in higher patient mortality. B) Signalling entropy (denoted SR/max SR) computed for 528 distinct pairwise mixtures of 33 homogeneous tissue samples reveals that our measure is super-additive and hence will be raised, on average, in mixed samples compared to homogeneous samples. C) Signalling entropy is raised on average in mixed samples as compared to homogeneous samples, considering the same 33 homogeneous tissue samples as Fig. 1B. The p-value corresponds to a two tailed paired Wilcoxon signed rank test, and reveals that signalling entropy is significantly elevated in the admixed cell populations on average.
Fig 2.
Prognostic implications of signalling entropy in breast cancer.
A) The plots display the concordance index for signalling entropy in each data set alongside its 95% confidence interval. The overall concordance index was derived via meta-analysis using a random effects model. The vertical line denotes concordance index = 0.5, data sets where the confidence interval for the concordance index crosses this line did not reach significance. Meta-analysis of signalling entropy across 10 breast cancer data sets reveals that our measure is significantly prognostic across both ER positive and ER negative subtypes. Meta-analysis across 7 breast cancer data sets reveals that our measure is also significantly prognostic within the grade 2 stratum. B) The plots display the negative of the log10 of the p-value for a survival analysis using Cox-regression on 5-year censored data, evaluating the prognostic significance of signalling entropy and MammaPrint in each data set. The overall p-value was produced by a Fisher’s combined test. The vertical red line on each plot denotes p = 0.05; data sets in which the bar crosses this line reached significance for the corresponding score. Meta-analysis comparison of signalling entropy with MammaPrint across 10 breast cancer data sets, demonstrates that only signalling entropy is significantly prognostic across ER negative samples.
Fig 3.
Prognostic implications of signalling entropy in lung adenocarcinoma.
A) The plots display the concordance index for signalling entropy in each data set alongside its 95% confidence interval. The overall concordance index was derived via meta-analysis using a random effects model. The vertical line denotes concordance index = 0.5, data sets where the confidence interval for the concordance index crosses this line did not reach significance. Meta-analysis of signalling entropy across 7 lung adenocarcinoma data sets reveals that our measure is significantly prognostic across all samples and within the stage I stratum. B) The plots display the negative of the log10 of the p-value for a survival analysis using Cox-regression on 3-year censored data, evaluating the prognostic significance of signalling entropy and tumour stage in each data set. The overall p-value was produced by a Fisher’s combined test. The vertical red line on each plot denotes p = 0.05; data sets in which the bar crosses this line reached significance for the corresponding score. Meta-analysis comparison of signalling entropy with pathological tumour stage across 7 lung adenocarcinoma data sets, demonstrates that signalling entropy outperforms the stage Ia/b sub staging across stage I samples.
Fig 4.
Meta-analysis comparison of the breast cancer SE score with MammaPrint.
A) Survival analysis statistics for the SE score and MammaPrint over ER positive samples and ER negative samples separately, c-index denotes concordance index and p denotes p-value. B) & C) The plots display the concordance index for the SE score and MammaPrint in each data set alongside 95% confidence intervals. The overall concordance indices were derived and compared via meta-analysis using a random effects model. The vertical line denotes concordance index = 0.5, data sets where the confidence interval for the concordance index crosses this line did not reach significance. Meta-analysis reveals that the SE score performs comparably to MammaPrint in ER positive samples (B) and outperforms MammaPrint across ER negative samples (C).
Fig 5.
Meta-analysis comparison of the lung cancer SE score with the expression of CADM1.
A) Survival analysis statistics for the SE score and CADM1 expression over all samples and stage I samples, statistics across stage I samples are provided for the 2 scores combined with stage Ia/b status, c-index denotes concordance index and p denotes p-value. B) The plots display the concordance index for the SE score, CADM1 expression and pathological tumour stage in each data set alongside 95% confidence intervals. The overall concordance indices were derived and compared via meta-analysis using a random effects model. The vertical line denotes concordance index = 0.5, data sets where the confidence interval for the concordance index crosses this line did not reach significance. Meta-analysis across 5 validation data sets reveals that the SE score performs comparably to tumour stage, whilst CADM1 expression is outperformed by tumour stage. (C) The plots display the concordance index for the SE score and CADM1 expression combined with stage Ia/b status, as well as stage Ia/b status alone, for stage I samples in each data set alongside 95% confidence intervals. Meta-analysis across 5 validation data sets reveals that only the SE score adds prognostic value to stage Ia/b status.