Abstract
Transcriptional programmes active in haematopoietic cells enable a variety of functions including dedifferentiation, innate immunity and adaptive immunity. Understanding how these programmes function in the context of cancer can provide valuable insights into host immune response, cancer severity and potential therapy response. Here we present a method that uses the transcriptomes of over 200 murine haematopoietic cells, to infer the lineage-specific haematopoietic activity present in human breast tumours. Correlating this activity with patient survival and tumour purity reveals that the transcriptional programmes of many cell types influence patient prognosis and are found in environments of high lymphocytic infiltration. Collectively, these results allow for a detailed and personalized assessment of the patient immune response to a tumour. When combined with routinely collected patient biopsy genomic data, this method can enable a richer understanding of the complex interplay between the host immune system and cancer.
Highlights
Transcriptional programmes active in haematopoietic cells enable a variety of functions including dedifferentiation, innate immunity and adaptive immunity
Using breast cancer as our model, we demonstrate that activity from several lineages correlates with patient survival, and that many of these programmes are associated with the presence of infiltrating haematopoietic cells
When iteratively applied to the 1,992 patients from the METABRIC data set by Curtis et al.[9], this resulted in a 1,992 Â 230 matrix of rank-similarity metrics, hereby referred to as Cell Lineage Scores (CLSs)
Summary
Transcriptional programmes active in haematopoietic cells enable a variety of functions including dedifferentiation, innate immunity and adaptive immunity. We present a method that uses the transcriptomes of over 200 murine haematopoietic cells, to infer the lineage-specific haematopoietic activity present in human breast tumours Correlating this activity with patient survival and tumour purity reveals that the transcriptional programmes of many cell types influence patient prognosis and are found in environments of high lymphocytic infiltration. Many methods have taken advantage of these alterations to computationally estimate immune activity in biopsies from solid tumours[2,3,4,5] These approaches have yielded interesting results, inferring the presence of haematopoietic subpopulations in several cancers using the tumour’s expression of lineage-defining signature genes. These results allow us to sensitively characterize the haematopoietic activity of the tumour microenvironment and predict both anticipated and unanticipated cell combinations that are prognostically significant for patient care
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