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Comparative proteomics reveals a diagnostic signature for pulmonary head‐and‐neck cancer metastasis
(2018)
Patients with head‐and‐neck cancer can develop both lung metastasis and primary lung cancer during the course of their disease. Despite the clinical importance of discrimination, reliable diagnostic biomarkers are still lacking. Here, we have characterised a cohort of squamous cell lung (SQCLC) and head‐and‐neck (HNSCC) carcinomas by quantitative proteomics. In a training cohort, we quantified 4,957 proteins in 44 SQCLC and 30 HNSCC tumours. A total of 518 proteins were found to be differentially expressed between SQCLC and HNSCC, and some of these were identified as genetic dependencies in either of the two tumour types. Using supervised machine learning, we inferred a proteomic signature for the classification of squamous cell carcinomas as either SQCLC or HNSCC, with diagnostic accuracies of 90.5% and 86.8% in cross‐ and independent validations, respectively. Furthermore, application of this signature to a cohort of pulmonary squamous cell carcinomas of unknown origin leads to a significant prognostic separation. This study not only provides a diagnostic proteomic signature for classification of secondary lung tumours in HNSCC patients, but also represents a proteomic resource for HNSCC and SQCLC.
Background: Cardiovascular magnetic resonance (CMR) offers quantification of phasic atrial functions based on volumetric assessment and more recently, on CMR feature tracking (CMR-FT) quantitative strain and strain rate (SR) deformation imaging. Inter-study reproducibility is a key requirement for longitudinal studies but has not been defined for CMR-based quantification of left atrial (LA) and right atrial (RA) dynamics.
Methods: Long-axis 2- and 4-chamber cine images were acquired at 9:00 (Exam A), 9:30 (Exam B) and 14:00 (Exam C) in 16 healthy volunteers. LA and RA reservoir, conduit and contractile booster pump functions were quantified by volumetric indexes as derived from fractional volume changes and by strain and SR as derived from CMR-FT. Exam A and B were compared to assess the inter-study reproducibility. Morning and afternoon scans were compared to address possible diurnal variation of atrial function.
Results: Inter-study reproducibility was within acceptable limits for all LA and RA volumetric, strain and SR parameters. Inter-study reproducibility was better for volumetric indexes and strain than for SR parameters and better for LA than for RA dynamics. For the LA, reservoir function showed the best reproducibility (intraclass correlation coefficient (ICC) 0.94–0.97, coefficient of variation (CoV) 4.5–8.2 %), followed by conduit (ICC 0.78–0.97, CoV 8.2–18.5 %) and booster pump function (ICC 0.71–0.95, CoV 18.3–22.7). Similarly, for the RA, reproducibility was best for reservoir function (ICC 0.76–0.96, CoV 7.5–24.0 %) followed by conduit (ICC 0.67–0.91, CoV 13.9–35.9) and booster pump function (ICC 0.73–0.90, CoV 19.4–32.3). Atrial dynamics were not measurably affected by diurnal variation between morning and afternoon scans.
Conclusions: Inter-study reproducibility for CMR-based derivation of LA and RA functions is acceptable using either volumetric, strain or SR parameters with LA function showing higher reproducibility than RA function assessment. Amongst the different functional components, reservoir function is most reproducibly assessed by either technique followed by conduit and booster pump function, which needs to be considered in future longitudinal research studies.
Antiserum against crystallized 20β-hydroxysteroid dehydrogenase from Streptomyces hydrogenans was used for different immunodiffusion and immunoprecipitation tests to quantify the bacterial enzyme in cell-free supernatants of the microorganism. After immunoprecipitation and gel electrophoresis the molecular weight of the subunits of 20β-hydroxysteroid dehydrogenase was calculated to be 27 300 ± 700.