Intra-Tumour Signalling Entropy Determines Clinical Outcome in Breast and Lung Cancer

Abstract

The cancer stem cell hypothesis, that a small population of tumour cells are responsible for tumorigenesis and cancer progression, is becoming widely accepted and recent evidence has suggested a prognostic and predictive role for such cells. Intra-tumour heterogeneity, the diversity of the cancer cell population within the tumour of an individual patient, is related to cancer stem cells and is also considered a potential prognostic indicator in oncology. The measurement of cancer stem cell abundance and intra-tumour heterogeneity in a clinically relevant manner however, currently presents a challenge. Here we propose signalling entropy, a measure of signalling pathway promiscuity derived from a sample’s genome-wide gene expression profile, as an estimate of the stemness of a tumour sample. By considering over 500 mixtures of diverse cellular expression profiles, we reveal that signalling entropy also associates with intra-tumour heterogeneity. By analysing 3668 breast cancer and 1692 lung adenocarcinoma samples, we further demonstrate that signalling entropy correlates negatively with survival, outperforming leading clinical gene expression based prognostic tools. Signalling entropy is found to be a general prognostic measure, valid in different breast cancer clinical subgroups, as well as within stage I lung adenocarcinoma. We find that its prognostic power is driven by genes involved in cancer stem cells and treatment resistance. In summary, by approximating both stemness and intra-tumour heterogeneity, signalling entropy provides a powerful prognostic measure across different epithelial cancers.

DUX4 induces a transcriptome more characteristic of a less-differentiated cell state and inhibits myogenesis

“…Signalling entropy is a powerful measure of cell differentiation potential, valid across multiple lineages and in pathology, and we have shown previously that it outperforms other popular methodologies (Banerji et al, 2013, 2015b). The assumption is that stem cells have many options with respect to fate, and so the diversity of genes expressed is high, giving stem cells a high signalling entropy.…”

“…Signalling entropy is a strong correlate of differentiation potential in healthy tissue (Banerji et al, 2013) and is a powerful prognostic factor in cancerous tissue, where it is associated with anaplasia (Banerji et al, 2015b). tMALDUX4 or DUX4c induced similar signalling entropies to control, whereas tMALDUX4–ERD decreased signalling entropy, indicating induction of differentiation.…”

“…Each sample was integrated with a protein interaction network (PIN) to create a sample specific stochastic matrix, P=(p ij ) . The PIN was constructed from previous work (Banerji et al, 2015b) through orthology relations. The i th row of P defines a probability distribution describing rates of reaction of protein i with each of its neighbours.…”

DUX4 induces a transcriptome more characteristic of a less-differentiated cell state and inhibits myogenesis

“…Signalling entropy is a powerful measure of cell differentiation potential, valid across multiple lineages and in pathology, and we have shown previously that it outperforms other popular methodologies (Banerji et al, 2013(Banerji et al, , 2015b. The assumption is that stem cells have many options with respect to fate, and so the diversity of genes expressed is high, giving stem cells a high signalling entropy.…”

Measuring intratumor heterogeneity by network entropy using RNA-seq data

“…A recent application of the network entropy successfully showed the difference between primary tumor and metastatic tumor46. Additionally, Signaling entropy studies by Teschendorff group identified relationship between network entropy and differentiation potential, additionally the prognostic importance474849.…”