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Growth differentiation factor 15 (GDF15) predicts relapse free and overall survival in unresected Locally Advanced Non-Small Cell Lung Cancer treated with chemo- radiotherapy.
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Abstract
Growth differentiation factor 15 (GDF15) is a cytokine of the TGFβ family. Here, we analyzed GDF15 levels in patients with locally advanced non-small cell lung cancer (LA-NSCLC) who participated in OCOG-ALMERA (NCT02115464), a phase II randomized clinical trial, that investigated metformin in combination with standard-of-care concurrent chemoradiotherapy (cCRT). Methods: Patients were randomized to treatment with platinum-based chemotherapy and concurrent chest radiotherapy (60-66Gy), with or without metformin (2000mg/d). The trial collected tumor volume parameters, survival outcomes, and patient blood plasma at baseline, during (weeks 1 and 6) and 6 months after cCRT. Plasma GDF15 levels were assayed with the ELISA method. Statistical analyses explored associations between GDF15, survival outcomes, and radiotherapy tumor volumes. Results: Baseline plasma levels of GDF15 were elevated in study patients, they increased during cCRT (p < 0.001), and the addition of metformin was associated with a further increase (week 6, p = 0.033). Baseline GDF15 levels correlated with the radiotherapy gross target volume (GTV, p < 0.01), while week 1 of radiotherapy levels correlated with radiotherapy planned target volume (PTV, p < 0.006). In multivariate analysis, baseline plasma GDF15 was prognostic poor relapse-free (RFS) and overall survival (OS) (p = 0.005 and p = 0.002, respectively). Conclusions: GDF15 is a plasma marker that responds to the treatment of unresected LA-NSCLC with cCRT and metformin. GDF15 levels correspond with tumor volume and increased GDF15 levels predict for poor RFS and OS. These results require validation in larger clinical trial datasets.
Springer Science and Business Media LLC
Fiorella Pastena
Gregory Pond
Evangelia E. Tsakiridis
Andre Gouveia
Elham Ahmadi
Olga-Demetra Biziotis
Amr Ali
Anand Swaminath
Gordon Okawara
Peter M Ellis
Bassam Abdulkarim
Naseer Ahmed
Andrew Robinson
Wilson Roa
Mario Valdes
Peter Kavsak
Marcin Wierzbicki
James Wright
Gregory Steinberg
Theodoros Tsakiridis
Title: Growth differentiation factor 15 (GDF15) predicts relapse free and overall survival in unresected Locally Advanced Non-Small Cell Lung Cancer treated with chemo- radiotherapy.
Description:
Abstract
Growth differentiation factor 15 (GDF15) is a cytokine of the TGFβ family.
Here, we analyzed GDF15 levels in patients with locally advanced non-small cell lung cancer (LA-NSCLC) who participated in OCOG-ALMERA (NCT02115464), a phase II randomized clinical trial, that investigated metformin in combination with standard-of-care concurrent chemoradiotherapy (cCRT).
Methods: Patients were randomized to treatment with platinum-based chemotherapy and concurrent chest radiotherapy (60-66Gy), with or without metformin (2000mg/d).
The trial collected tumor volume parameters, survival outcomes, and patient blood plasma at baseline, during (weeks 1 and 6) and 6 months after cCRT.
Plasma GDF15 levels were assayed with the ELISA method.
Statistical analyses explored associations between GDF15, survival outcomes, and radiotherapy tumor volumes.
Results: Baseline plasma levels of GDF15 were elevated in study patients, they increased during cCRT (p < 0.
001), and the addition of metformin was associated with a further increase (week 6, p = 0.
033).
Baseline GDF15 levels correlated with the radiotherapy gross target volume (GTV, p < 0.
01), while week 1 of radiotherapy levels correlated with radiotherapy planned target volume (PTV, p < 0.
006).
In multivariate analysis, baseline plasma GDF15 was prognostic poor relapse-free (RFS) and overall survival (OS) (p = 0.
005 and p = 0.
002, respectively).
Conclusions: GDF15 is a plasma marker that responds to the treatment of unresected LA-NSCLC with cCRT and metformin.
GDF15 levels correspond with tumor volume and increased GDF15 levels predict for poor RFS and OS.
These results require validation in larger clinical trial datasets.
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