Dataset Information

Discovery and Validation of Predictive Biomarkers of Survival for Non-small Cell Lung Cancer Patients Undergoing Radical Radiotherapy: Two Proteins With Predictive Value.

ABSTRACT: Lung cancer is the most frequent cause of cancer-related death world-wide. Radiotherapy alone or in conjunction with chemotherapy is the standard treatment for locally advanced non-small cell lung cancer (NSCLC). Currently there is no predictive marker with clinical utility to guide treatment decisions in NSCLC patients undergoing radiotherapy. Identification of such markers would allow treatment options to be considered for more effective therapy. To enable the identification of appropriate protein biomarkers, plasma samples were collected from patients with non-small cell lung cancer before and during radiotherapy for longitudinal comparison following a protocol that carries sufficient power for effective discovery proteomics. Plasma samples from patients pre- and during radiotherapy who had survived > 18 mo were compared to the same time points from patients who survived < 14 mo using an 8 channel isobaric tagging tandem mass spectrometry discovery proteomics platform. Over 650 proteins were detected and relatively quantified. Proteins which showed a change during radiotherapy were selected for validation using an orthogonal antibody-based approach. Two of these proteins were verified in a separate patient cohort: values of CRP and LRG1 combined gave a highly significant indication of extended survival post one week of radiotherapy treatment.

SUBMITTER: Walker MJ

PROVIDER: S-EPMC4563120 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature

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Discovery and Validation of Predictive Biomarkers of Survival for Non-small Cell Lung Cancer Patients Undergoing Radical Radiotherapy: Two Proteins With Predictive Value.

Walker Michael J MJ Zhou Cong C Backen Alison A Pernemalm Maria M Williamson Andrew J K AJ Priest Lynsey J C LJ Koh Pek P Faivre-Finn Corinne C Blackhall Fiona H FH Dive Caroline C Whetton Anthony D AD

EBioMedicine 20150619 8

Lung cancer is the most frequent cause of cancer-related death world-wide. Radiotherapy alone or in conjunction with chemotherapy is the standard treatment for locally advanced non-small cell lung cancer (NSCLC). Currently there is no predictive marker with clinical utility to guide treatment decisions in NSCLC patients undergoing radiotherapy. Identification of such markers would allow treatment options to be considered for more effective therapy. To enable the identification of appropriate pro ...[more]

PMID: 26425690

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Project description:Severe xerostomia is noted in the majority of patients irradiated for oropharyngeal cancer (OPC). Extracellular microRNAs (miRNAs) may serve as effective tools allowing prediction of radiation-related toxicity. The aim of this study was to create an efficient prognostic miRNA-based test for severe, patient-rated xerostomia 3 months after primary treatment. This prospective study enrolled OPC patients treated between 2016 and 2018 in three centers in Poland. The primary endpoint was severe (grade ≥3) xerostomia as assessed by the EORTC H&N-35 questionnaires. Initially, a group of 10 patients with severe xerostomia was randomly selected and matched with a comparative group of 10 patients without severe xerostomia. Samples were collected before RT, after receiving 20 Gy and within 24 hours after treatment completion. qPCR arrays (QIAGEN, Hilden, Germany) were used to quantify expression levels of 752 miRNAs in the serum at all timepoints. The resulting logistic-regression based model was validated in additional 60 patients: 30 with grade >3 xerostomia and 30 without. Of 152 eligible patients, we successfully recruited 111 patients. Severe xerostomia 3 months after treatment was reported by 63 patients (56.8%). Mean dose delivered to parotid glands was higher in both exploratory and validation cohort. The model based on miR-185-5p and miR-425-5p expression levels measured before the start of radiotherapy had AUC 0.96 (95% CI: 0.88-1.00). The model based on the same miRNAs remained robust when parameters were measured after 20 Gy (AUC 0.90 (95% CI: 0.75-1.00)). These results were confirmed in the validation group. In the validation group pre-radiotherapy model application yielded 73.3% sensitivity and 80.0% specificity. In the samples taken after 20 Gy, the same two miRNAs yielded 67.7% sensitivity and 72.4% specificity. The model including pretreatment miR-185-5p and miR-425-5p levels together with mean parotid dose, yielded 90.0% sensitivity and 80.0% specificity. In the validation cohort, this model yielded 80.6 % sensitivity and 55.2 % specificity. The model based on miRNA levels measured after 20 Gy and mean parotid dose had 80.0 % sensitivity and 100% specificity in the exploratory group. In the validation cohort its performance fell to 71.0 % sensitivity and 58.6 % specificity. Serum expression levels of miR-425-5p and miR-185-5p measured before the start of radiotherapy or during therapy (after 20 Gy) had a significant prognostic value for the occurrence of severe xerostomia 3 months after treatment completion. The variability explained by miRNAs appears to be, at least partially, independent from the one related to the dosimetric data.

Dataset Information

Discovery and Validation of Predictive Biomarkers of Survival for Non-small Cell Lung Cancer Patients Undergoing Radical Radiotherapy: Two Proteins With Predictive Value.

Publications

Discovery and Validation of Predictive Biomarkers of Survival for Non-small Cell Lung Cancer Patients Undergoing Radical Radiotherapy: Two Proteins With Predictive Value.

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