Validation of a 52-gene risk profile for outcome prediction in patients with idiopathic pulmonary fibrosis: an international, multicentre, cohort study

Abstract

Background The clinical course of Idiopathic Pulmonary Fibrosis (IPF) is unpredictable. Clinical prediction tools are not accurate enough to predict disease outcomes. Methods All-comers with Idiopathic Pulmonary Fibrosis diagnosis were enrolled in a six-cohort study. Peripheral blood mononuclear cells or whole blood was collected at baseline from 425 participants and during follow up from 98 patients. The 52-gene signature was measured by the nCounter® analysis system in four cohorts and extracted from microarray data in two others. The Scoring Algorithm for Molecular Subphenotypes (SAMS) was used to classify patients into low or high risk groups based on a 52-gene signature. Mortality and transplant-free survival were studied using Competing risk and Cox proportional-hazard models, respectively. Time course data and response to anti-fibrotic drugs were analyzed using linear mixed-effect models. Findings The application of SAMS to the 52-gene signature identified two groups of IPF patients (low and high risk) with significant differences in mortality or transplant-free survival in each of the six cohorts (HR 2·03–4·37). Pooled data revealed similar results for mortality (HR:2·18, 95%CI:1·53–3·09, P<0·0001) or transplant-free survival (HR:2·04, 95%CI: 1·52–2·74, P<0·0001). Adding 52-gene risk profiles to the Gender, Age and Physiology (GAP) index significantly improved its mortality predictive accuracy. Temporal changes in SAMS scores were associated with changes in forced vital capacity (FVC) in two cohorts. Untreated patients did not shift their risk profile over time. A simultaneous increase in up score and decrease in down score was predictive of transplant-free survival (HR:3·18· 95%CI 1·16, 8·76, P=0·025) in the Pittsburgh cohort. A simultaneous decrease in up score and increase in down score after initiation of anti-fibrotic drugs was associated with a significant (P=0·005) improvement in FVC in the Yale cohort. Interpretation The peripheral blood 52-gene expression signature is predictive of outcome in patients with IPF. The potential value of the 52-gene signature in predicting response to therapy should be determined in prospective studies.

PD-1 up-regulation on CD4 + T cells promotes pulmonary fibrosis through STAT3-mediated IL-17A and TGF-β1 production

“…Longitudinal increases in programmed cell death-1 (PD-1) + CD4 + T cells are present during sarcoidosis pulmonary progression, with T helper 17 (T H 17) cells as the T cell subset expressing the greatest percentage of PD-1 (10). Furthermore, genome-wide association studies implicate the T H 17 signaling pathway in sarcoidosis pulmonary progression (11); transcriptomic analysis implicates adaptive immune dysfunction in IPF (12, 13). …”

The therapy of idiopathic pulmonary fibrosis: what is next?

“…A number of peripheral blood biomarkers have been studied that can aid in delineating ILDs from other severe lung diseases. The markers Krebs von den Lungen (KL)-6 [24], chitinase-like protein (YKL40) [41,56], leucocytes and circulating innate immune cells [57][58][59], surfactant proteins (SP)-A, -B, -D, among others, have been shown to discriminate IPF from healthy controls [25,27,31]. KL-6 may also discriminate ILDs from other benign lung diseases [24,60].…”

Year in review 2017: Interstitial lung disease, pulmonary vascular disease and sleep

“…Interestingly, in two discovery and validation prospective cohorts of treatment‐naive patients with IPF, high serum MMP7 was associated with poorer survival, but was less informative than other serum markers, including surfactant protein D for diagnosis, CA19‐9 for progressive disease and CA‐125 for dynamic changes . A peripheral blood 52 gene expression signature added prognostic information to the GAP severity score in six independent IPF cohorts, although a control reference set will need to be developed before the signature can be applied to clinical practice . Other studied biomarkers include serum receptor for advanced glycation end product (AGER) associated with worse survival in IPF, and, in pulmonary alveolar proteinosis, serum and bronchoalveolar lavage (BAL) levels of YKL‐40 associated with disease progression …”