An ionising radiation-induced specific transcriptional signature of inflammation-associated genes in whole blood from radiotherapy patients: a pilot study

Abstract

Background: This communication reports the identification of a new panel of transcriptional changes in inflammation-associated genes observed in response to ionising radiation received by radiotherapy patients.

Methods: Peripheral blood samples were taken with ethical approval and informed consent from a total of 20 patients undergoing external beam radiotherapy for breast, lung, gastrointestinal or genitourinary tumours. Nanostring nCounter analysis of transcriptional changes was carried out in samples prior and 24 h post-delivery of the 1st radiotherapy fraction, just prior to the 5th or 6th fraction, and just before the last fraction.

Results: Statistical analysis with BRB-ArrayTools, GLM MANOVA and nSolver, revealed a radiation responsive panel of genes which varied by patient group (type of cancer) and with time since exposure (as an analogue for dose received), which may be useful as a biomarker of radiation response.

Conclusion: Further validation in a wider group of patients is ongoing, together with work towards a full understanding of patient specific responses in support of personalised approaches to radiation medicine.

Keywords: Blood; Cancer; Gene expression; Inflammation; Ionising radiation; NCounter; RT-qPCR; Radiotherapy; Transcription.

Fig. 1

Volcano plots displaying − log10 of the p-value and log2 of the FC of the differential expression analysis between the time points “before the start of the treatment” and a 24 h after first fraction, b before 5th–6th faction, c before last fraction. Horizontal lines indicate various adjusted p-value thresholds when there are significant differences. The 40 most statistically significant genes are labelled in the plot (blue dots) (c)

Fig. 2

GSA: Gene set analysis with global significance scores and directed global significance scores. a Global significance score plot: orange denotes gene sets whose genes exhibit extensive differential expression with the covariate, blue denotes gene sets with less differential expression. b Directed global significance score plot: red denotes gene sets whose genes exhibit extensive over-expression with the covariate, blue denotes gene sets with extensive under-expression

Fig. 3

Pathway changes in the different time points a Heatmap of pathways scores including the 4 time points and the 6 cancer types: orange indicates high scores; blue indicates low scores. Scores are displayed on the same scale via a Z-transformation. b Individual pathway scores for each time point c Heatmap of pathways scores comparing the time point “before” and “before last fraction” together with the 6 cancer types

Fig. 4

Immune cell profiling analysis indicating cell type abundance measurements versus time points. Raw cell type measurements are calculated as the log2 expression of each cell type’s marker genes

Fig. 5

mRNA expression levels of IL7 and CD40LG in blood from radiotherapy patients analysed by nCounter analysis (a, c) and RT-qPCR (b, d). Blood samples from 20 patients, comprising those with endometrial, breast, lung, prostate, oesophageal and colon cancer, were analysed. Blood was collected at four time points: before the start of the treatment, at 24 h after the first fraction, before 5th–6th fraction and before the last fraction. Individual data points are shown for all patients, together with the mean ± SD (each patient is represented with a different symbol). Each cancer group was color coded. Statistical analyses were performed in log-transformed data. *Significantly different from the control (before treatment) (paired t test, P ≤ 0.05). RU, relative units