Dataset Information

Discovery and evaluation of protein biomarkers as a signature of wellness in late stage cancer patients in early phase clinical trials

ABSTRACT: TARGET (Tumour characterisation to Guide Experimental Targeted therapy) seeks to optimise the pathway for molecular characterisation of all patients entering early phase cancer trials to inform clinical decision-making on optimal therapy. Performance status (PS) was developed to assess a patient’s ability to perform a variety of activities to further inform clinical decision making on optimal therapy including appropriate inclusion in clinical trials. However, the quality of present algorithms to assess performance status are limited and based on a semi-quantitative clinician assessment. In particular, a common eligibility criterion for entry into early phase cancer clinical trials is a life expectancy of >3 or 6 months. Here we investigate proteomics as a means of more objective and quantitative assessment of both performance status and thus likely prognosis prior to clinical trial enrolment. Improved patient stratification at enrolment would reduce the number of patients unnecessarily exposed to potentially toxic drugs and decrease withdrawal from trials. Plasma samples from patients enrolled into the TARGET trial were analysed using the mass spectrometry (MS) technique: Sequential window acquisition of all theoretical fragment ion spectra (SWATH) MS. SWATH-MS was used on a discovery cohort of 73 patients to identify proteins that could differentiate patients into either a good or poor prognosis. A three-protein panel showed a stronger prediction of overall survival (p = 0.000086) compared to PS (p = 0.001). This panel was then tested against a validation cohort of 77 patients. The panel was determined as being a significant (p = 0.000451) predictor of overall survival whereas PS was not significant. The panel had a receiver operating characteristic curve area under the curve (AUC) of 0.73 in the validation set; the AUC of PS was 0.54. This signature can now be developed further in larger patient populations to assess its utility in a clinical setting.

INSTRUMENT(S): TripleTOF 6600

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Plasma

SUBMITTER: Bethany Geary

LAB HEAD: Bethany Geary

PROVIDER: PXD023553 | Pride | 2022-07-05

REPOSITORIES: Pride

ACCESS DATA

Similar Datasets

Project description:Differentially methylated oral squamous cell carcinoma (OSCC) biomarkers, identified in-vitro and validated in well-characterized surgical specimens, have shown poor clinical correlation in cohorts with different risk profiles. To overcome this lack of relevance we used the HumanMethylation27 BeadChip, publicly available methylation and expression array data, and Quantitative Methylation Specific PCR to uncover differential methylation in OSCC clinical samples with heterogeneous risk profiles. A two stage-design consisting of Discovery and Prevalence screens was used to identify differential promoter methylation and deregulated pathways in patients diagnosed with OSCC and head and neck squamous cell carcinoma. Promoter methylation of KIF1A (k=0.64), HOXA9 (k=0.60), NID2 (k=0.60), and EDNRB (k=0.60) had a moderate to substantial agreement with clinical diagnosis in the Discovery screen. HOXA9 had 68% sensitivity, 100% specificity and a 0.81 AUC. NID2 had 71% sensitivity, 100% specificity and a 0.79 AUC. In the Prevalence screen HOXA9 (k=0.82) and NID2 (k=0.80) had an almost perfect agreement with histologic diagnosis. HOXA9 had 85% sensitivity, 97% specificity and a 0.95 AUC. NID2 had 87% sensitivity, 95% specificity and a 0.91 AUC. A HOXA9 and NID2 gene panel had 94% sensitivity, 97% specificity and a 0.97 AUC. In saliva from OSCC cases and controls HOXA9 had 75% sensitivity, 53% specificity and a 0.75 AUC. NID2 had 87% sensitivity, 21% specificity and a 0.73 AUC. This Phase I Biomarker Development Trial identified a panel of differentially methylated genes in normal and OSCC clinical samples from patients with heterogeneous risk profiles. This panel may be useful for early detection and cancer prevention studies. The 12 samples analyzed comprise equal numbers of three tissue-types: Primary oral squamous cell carcinoma, Oral leukoplakia and Normal oral mucosa. Gender, age and smoking-status were approximately equally represented in these goups. Normal oral mucosa served as a control.

Dataset Information

Discovery and evaluation of protein biomarkers as a signature of wellness in late stage cancer patients in early phase clinical trials

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure