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.

ABCB1 and ABCG2 drug transporters are differentially expressed in non-small cell lung cancers (NSCLC) and expression is modified by cisplatin treatment via altered Wnt signaling.

BACKGROUND: Lung cancer (LC) is still the most common cause of cancer related deaths worldwide. Non-small cell lung cancer (NSCLC) accounts for 85% of all LC cases but is not a single entity. It is now accepted that, apart from the characteristic driver mutations, the unique molecular signatures of adeno- (AC) and squamous cell carcinomas (SCC), the two most common NSCLC subtypes should be taken into consideration for their management. Therapeutic interventions, however, frequently lead to chemotherapy resistance highlighting the need for in-depth analysis of regulatory mechanisms of multidrug resistance to increase therapeutic efficiency. METHODS: Non-canonical Wnt5a and canonical Wnt7b and ABC transporter expressions were tested in primary human LC (n = 90) resections of AC and SCC. To investigate drug transporter activity, a three dimensional (3D) human lung aggregate tissue model was set up using differentiated primary human lung cell types. Following modification of the canonical, beta-catenin dependent Wnt pathway or treatment with cisplatin, drug transporter analysis was performed at mRNA, protein and functional level using qRT-PCR, immunohistochemistry, immune-fluorescent staining and transport function analysis. RESULTS: Non-canonical Wnt5a is significantly up-regulated in SCC samples making the microenvironment different from AC, where the beta-catenin dependent Wnt7b is more prominent. In primary cancer tissues ABCB1 and ABCG2 expression levels were different in the two NSCLC subtypes. Non-canonical rhWnt5a induced down-regulation of both ABCB1 and ABCG2 transporters in the primary human lung aggregate tissue model recreating the SCC-like transporter pattern. Inhibition of the beta-catenin or canonical Wnt pathway resulted in similar down-regulation of both ABC transporter expression and function. In contrast, cisplatin, the frequently used adjuvant chemotherapeutic agent, activated beta-catenin dependent signaling that lead to up-regulation of both ABCB1 and ABCG2 transporter expression and activity. CONCLUSIONS: The difference in the Wnt microenvironment in AC and SCC leads to variations in ABC transporter expression. Cisplatin via induction of canonical Wnt signaling up-regulates ABCB1 and ABCG2 drug transporters that are not transporters for cisplatin itself but are transporters for drugs that are frequently used in combination therapy with cisplatin modulating drug response.

Increased Wnt5a in squamous cell lung carcinoma inhibits endothelial cell motility.

BACKGROUND: Angiogenesis is important both in normal tissue function and disease and represents a key target in lung cancer (LC) therapy. Unfortunately, the two main subtypes of non-small-cell lung cancers (NSCLC) namely, adenocarcinoma (AC) and squamous cell carcinoma (SCC) respond differently to anti-angiogenic e.g. anti-vascular endothelial growth factor (VEGF)-A treatment with life-threatening side effects, often pulmonary hemorrhage in SCC. The mechanisms behind such adverse reactions are still largely unknown, although peroxisome proliferator activator receptor (PPAR) gamma as well as Wnt-s have been named as molecular regulators of the process. As the Wnt microenvironments in NSCLC subtypes are drastically different, we hypothesized that the particularly high levels of non-canonical Wnt5a in SCC might be responsible for alterations in blood vessel growth and result in serious adverse reactions. METHODS: PPARgamma, VEGF-A, Wnt5a, miR-27b and miR-200b levels were determined in resected adenocarcinoma and squamous cell carcinoma samples by qRT-PCR and TaqMan microRNA assay. The role of PPARgamma in VEGF-A expression, and the role of Wnts in overall regulation was investigated using PPARgamma knock-out mice, cancer cell lines and fully human, in vitro 3 dimensional (3D), distal lung tissue aggregates. PPARgamma mRNA and protein levels were tested by qRT-PCR and immunohistochemistry, respectively. PPARgamma activity was measured by a PPRE reporter system. The tissue engineered lung tissues expressing basal level and lentivirally delivered VEGF-A were treated with recombinant Wnts, chemical Wnt pathway modifiers, and were subjected to PPARgamma agonist and antagonist treatment. RESULTS: PPARgamma down-regulation and VEGF-A up-regulation are characteristic to both AC and SCC. Increased VEGF-A levels are under direct control of PPARgamma. PPARgamma levels and activity, however, are under Wnt control. Imbalance of both canonical (in AC) and non-canonical (in SCC) Wnts leads to PPARgamma down-regulation. While canonical Wnts down-regulate PPARgamma directly, non-canonical Wnt5a increases miR27b that is known regulator of PPARgamma. CONCLUSION: During carcinogenesis the Wnt microenvironment alters, which can downregulate PPARgamma leading to increased VEGF-A expression. Differences in the Wnt microenvironment in AC and SCC of NSCLC lead to PPARgamma decrease via mechanisms that differentially alter endothelial cell motility and branching which in turn can influence therapeutic response.