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S. Küffer
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MINI 08 - Prognostic/Predictive Biomarkers (ID 106)
- Event: WCLC 2015
- Type: Mini Oral
- Track: Biology, Pathology, and Molecular Testing
- Presentations: 1
- Moderators:T.E. Stinchcombe, N. Pavlakis
- Coordinates: 9/07/2015, 16:45 - 18:15, Mile High Ballroom 4a-4f
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MINI08.12 - Proteomic Profiling of Pulmonary Cancer with Squamous Cell Histology (ID 1377)
17:55 - 18:00 | Author(s): S. Küffer
- Abstract
Background:
Pathologic differentiation of neoplastic lesions in the lung with squamous cell histology is challenging as appropriate diagnostic immunohistochemical biomarkers are lacking. In particular patients with head and neck cancer and a smoking history can develop both lung metastases and primary lung cancer. Differentiation of primary lung cancer and lung metastases of head and neck cancer is clinically important for therapy and risk stratification. Furthermore, molecular targeted therapies for squamous cell carcinoma of the lung are largely lacking to date. Recent genetic studies uncovered multiple genetic subgroups of squamous cell carcinoma of the lung and moreover potential drug targets. However, the correlation between protein-expression/signaling activation patterns and genetic alterations is strongly influenced by co- and post-transcriptional as well as post-translational regulation. We characterized a broad panel of primary patient-derived formalin-fixed squamous cell carcinomas from lung and head and neck cancer by quantitative mass spectrometry to identify proteomic diagnostic biomarkers, signaling patterns and potential novel drug targets.
Methods:
Proteins were extracted from formalin-fixed paraffin-embedded (FFPE) microdissected patient-derived cancer tissues by using the “filter-aided sample preparation (FASP)” method. Purified proteins were subsequently mixed with a cancer-matched isotope labeled quantification standard (Super-SILAC standard) that allows for identification and quantification of thousands of proteins and their phosphorylation sites by high-end mass spectrometry. Using bioinformatics we determined the protein expression and signaling patterns. The biomarkers discovered were validated by immunohistochemistry in additional independent tumor tissues.
Results:
In this study we quantitatively characterized the proteomes of 60 primary patient-derived non-small cell lung cancer specimens with squamous cell histology and 25 squamous cell carcinomas from the head and neck region derived from patients that developed lung tumors with similar histology in the course of their disease. Using the Super-SILAC-based mass spectrometric approach we were able to identify and quantify around 2500 proteins per sample. Unsupervised clustering- and principal component analyses revealed that the detected protein expression patterns show a strong correlation with the cellular origin of the analyzed carcinomas. Furthermore, secondary lesions with similar histological morphology in the lung in patients with squamous cell carcinoma of the head and neck region could be classified as primary or metastatic cancer according to their protein expression profiles.
Conclusion:
Collectively, this study provides a large set of proteomic biomarkers that can be used to improve lung cancer diagnostics in the future. In particular the differential diagnosis of squamous cell carcinoma/metastases in the lung, that has so far been difficult due to the lack of biomarkers, will be improved by the biomarker panels presented here. Moreover, the expression and activation patterns of kinases discovered in our study is of interest regarding potential novel lung cancer therapies as overexpression or hyperactivation of certain kinases can potentially contribute to the malignant phenotype of lung cancer cells.
