Mid-Infrared Imaging Characterization to Differentiate Lung Cancer Subtypes.

Introduction: Lung cancer is the most common malignancy worldwide. Squamous cell carcinoma (SQ) and adenocarcinoma (LUAD) are the two most frequent histological subtypes. Small cell carcinoma (SCLC) subtype has the worst prognosis. Differential diagnosis is essential for proper oncological treatment. Life science associated mid- and near-infrared based microscopic techniques have been developed exponentially, especially in the past decade. Vibrational spectroscopy is a potential non-destructive approach to investigate malignancies. Aims: Our goal was to differentiate lung cancer subtypes by their label-free mid-infrared spectra using supervised multivariate analyses. Material and Methods: Formalin-fixed paraffin-embedded (FFPE) samples were selected from the archives. Three subtypes were selected for each group: 10-10 cases SQ, LUAD and SCLC. 2 µm thick sections were cut and laid on aluminium coated glass slides. Transflection optical setup was applied on Perkin-Elmer infrared microscope. 250 × 600 µm areas were imaged and the so-called mid-infrared fingerprint region (1800-648cm-1) was further analysed with linear discriminant analysis (LDA) and support vector machine (SVM) methods. Results: Both "patient-based" and "pixel-based" approaches were examined. Patient-based analysis by using 3 LDA models and 2 SVM models resulted in different separations. The higher the cut-off value the lower is the accuracy. The linear C-support vector classification (C-SVC) SVM resulted in the best (100%) accuracy for the three subtypes using a 50% cut-off value. The pixel-based analysis gave, similarly, the linear C-SVC SVM model to be the most efficient in the statistical indicators (SQ sensitivity 81.65%, LUAD sensitivity 82.89% and SCLC sensitivity 88.89%). The spectra cut-off, the kernel function and the algorithm function influence the accuracy. Conclusion: Mid-Infrared imaging could be used to differentiate FFPE lung cancer subtypes. Supervised multivariate tools are promising to accurately separate lung tumor subtypes. The long-term perspective is to develop a spectroscopy-based diagnostic tool, revolutionizing medical differential diagnostics, especially cancer identification.

TRPA1 receptor is upregulated in human oral lichen planus.

OBJECTIVE: Oral lichen planus (OLP) is a chronic inflammatory disease of unknown etiology with antigen-specific and non-specific mechanisms. Transient receptor potential ankyrin 1 (TRPA1) is a non-selective cation channel activated by noxious stimuli such as oxidative stress products evoking pain and release of proinflammatory mediators from sensory nerve endings culminating in neurogenic inflammation. Extraneuronal TRPA1s, for example, on immune cells possess yet unknown functions. SUBJECTS AND METHODS: We studied the buccal mRNA expression (qPCR) and protein localization (immunohistochemistry) of TRPA1 receptors and key OLP mediator transcripts in oral mucosa samples of healthy volunteers (n = 9), OLP patients (n = 43), and OLP-like hyperkeratotic patients (n = 12). RESULTS: We measured 27.7- and 25.5-fold TRPA1 mRNA increase in OLP and OLP-like hyperkeratotic patients compared to healthy controls. TRPA1 transcripts elevated 2.4-fold in hypertensive OLP but not in hyperkeratotic patients compared to counterparts, reduced by 1.6-fold by angiotensin-convertase inhibitor intake. TRPA1 messenger RNA was more coexpressed with transcripts of tumor necrosis factor α than with interferon γ. Keratinocytes, macrophages but not T cells expressed TRPA1. CONCLUSIONS: We provided evidence for the extraneuronal presence and upregulation of the proinflammatory TRPA1 receptor in buccal samples of patients with OLP. This may implicate the ion channel in the pathomechanism of OLP.