Blood-based lung cancer biomarkers identified through proteomic discovery in cancer tissues, cell lines and conditioned medium

Background

Support for early detection of lung cancer has emerged from the National Lung Screening Trial (NLST), in which low-dose computed tomography (LDCT) screening reduced lung cancer mortality by 20 % relative to chest x-ray. The US Preventive Services Task Force (USPSTF) recently recommended annual screening for the high-risk population, concluding that the benefits (life years gained) outweighed harms (false positive findings, abortive biopsy/surgery, radiation exposure). In making their recommendation, the USPSTF noted that the moderate net benefit of screening was dependent on the resolution of most false-positive results without invasive procedures. Circulating biomarkers may serve as a valuable adjunctive tool to imaging.

Results

We developed a broad-based proteomics discovery program, integrating liquid chromatography/mass spectrometry (LC/MS) analyses of freshly resected lung tumor specimens (n = 13), lung cancer cell lines (n = 17), and conditioned media collected from tumor cell lines (n = 7). To enrich for biomarkers likely to be found at elevated levels in the peripheral circulation of lung cancer patients, proteins were prioritized based on predicted subcellular localization (secreted, cell-membrane associated) and differential expression in disease samples. 179 candidate biomarkers were identified. Several markers selected for further validation showed elevated levels in serum collected from subjects with stage I NSCLC (n = 94), relative to healthy smoker controls (n = 189). An 8-marker model was developed (TFPI, MDK, OPN, MMP2, TIMP1, CEA, CYFRA 21–1, SCC) which accurately distinguished subjects with lung cancer (n = 50) from high risk smokers (n = 50) in an independent validation study (AUC = 0.775).

Conclusions

Integrating biomarker discovery from multiple sample types (fresh tissue, cell lines and conditioned medium) has resulted in a diverse repertoire of candidate biomarkers. This unique collection of biomarkers may have clinical utility in lung cancer detection and diagnoses.

Electronic supplementary material

The online version of this article (doi:10.1186/s12014-015-9090-9) contains supplementary material, which is available to authorized users.

Identification and characterization of angiogenesis targets through proteomic profiling of endothelial cells in human cancer tissues

Genomic and proteomic analysis of normal and cancer tissues has yielded abundant molecular information for potential biomarker and therapeutic targets. Considering potential advantages in accessibility to pharmacological intervention, identification of targets resident on the vascular endothelium within tumors is particularly attractive. By employing mass spectrometry (MS) as a tool to identify proteins that are over-expressed in tumor-associated endothelium relative to normal cells, we aimed to discover targets that could be utilized in tumor angiogenesis cancer therapy. We developed proteomic methods that allowed us to focus our studies on the discovery of cell surface/secreted proteins, as they represent key antibody therapeutic and biomarker opportunities. First, we isolated endothelial cells (ECs) from human normal and kidney cancer tissues by FACS using CD146 as a marker. Additionally, dispersed human colon and lung cancer tissues and their corresponding normal tissues were cultured ex-vivo and their endothelial content were preferentially expanded, isolated and passaged. Cell surface proteins were then preferentially captured, digested with trypsin and subjected to MS-based proteomic analysis. Peptides were first quantified, and then the sequences of differentially expressed peptides were resolved by MS analysis. A total of 127 unique non-overlapped (157 total) tumor endothelial cell over-expressed proteins identified from directly isolated kidney-associated ECs and those identified from ex-vivo cultured lung and colon tissues including known EC markers such as CD146, CD31, and VWF. The expression analyses of a panel of the identified targets were confirmed by immunohistochemistry (IHC) including CD146, B7H3, Thy-1 and ATP1B3. To determine if the proteins identified mediate any functional role, we performed siRNA studies which led to previously unidentified functional dependency for B7H3 and ATP1B3.

Abstract 4568: Multivariate analysis of a panel of protein biomarkers for early detection of non-small cell lung cancer

Introduction: Lung cancer is the leading cause of cancer mortality in the US; it has been estimated that 219,440 individuals will be diagnosed with lung cancer and 159,390 will die from the disease in 2009 alone. Low dose CT, while very sensitive at visualizing early stage tumors, also identifies non malignant solitary pulmonary nodules (false positives) in a significant fraction of smokers. Biomarker panels may have considerable value when combined with imaging protocols in helping to discriminate benign from malignant nodules. We have employed a novel mass spectrometry-based approach to identify serum biomarkers which we have previously shown to detect non-small cell lung cancer (NSCLC) representing all 4 stages of disease. In this study we extend these findings to a cohort highly representative of early stage lung cancer.

Methodology: Validation of non small cell lung cancer markers was performed by ELISA analysis on a cohort of sera collected at the NYU Langone Medical Center. In this study lung cancer cases represent predominantly early stage disease (65 stage I/ 91 all cancer). Controls comprise current and former healthy smokers (n=90) as well as subjects with non-malignant lung disease (COPD, n=46). Samples were randomly divided into a training set (cancer n=39; smokers n= 38; COPD n=20) and a test set (cancer n=52; smokers n=52; COPD n=26). Logistic regression analysis revealed several multi-marker panels capable of distinguishing malignant samples from matched controls in the training set. A classifier developed for each panel was then applied to the test set. Multivariate approaches were employed to analyze this data together with other key clinical parameters including: tumor stage, size, histology and lung-function data.

Results: Markers for the panel were selected based on both individual marker performance and complementation of the performance of the relevant biomarker panel. Logistic regression analysis on the training set revealed a 9-marker panel which resolved malignant samples with 90% sensitivity at 96% specificity (AUC=0.977). The panel resolved malignant lesions under 1 cm and demonstrated good discrimination of COPD patients. A 6-marker panel was identified with similar performance characteristics (AUC=0.974). Applying the classifier generated from the training set to the test set also showed strong performance in this study, with an AUC of 0.92 for the 9 marker set in preliminary analyses.

Conclusion: Panels of lung biomarkers identified initially through proteomic analysis have shown robust performance in a study cohort strongly biased toward early-stage disease. The findings from these studies suggest that these biomarker panels provide the performance and flexibility to design tests suitable for a variety of diagnostic applications such as screening high risk subjects prior to CT scanning and improving the discrimination of nodules identified by radiologic imaging.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4568.

Immune modulator CD70 as a potential cisplatin resistance predictive marker in ovarian cancer

OBJECTIVE

We have used mass-spectrometry (MS) based proteomics platform to identify cell surface proteins over-expressed on a cisplatin resistant derivative of an ovarian cancer cell line A2780.

METHODS

Membrane associated glycoproteins from A2780 and its cisplatin resistant derivative cell line, A2780cis, were processed for liquid chromatography (LC)-MS based analysis. The expression of proteins found at elevated levels in A2780cis cell line was confirmed using flow cytometry and Taqman analysis. The expression of these proteins was further evaluated in unrelated ovarian cancer cell lines using MS analysis and flow cytometry. Immunohistochemical (IHC) analysis was performed using ovarian tumor tissues to evaluate the protein density on the cell surface. Monoclonal antibodies were used in an alamar blue proliferation assay to examine the cytotoxic effects on cell proliferation in resistant cell lines.

RESULTS

Six proteins were identified by LC-MS as being over-expressed on cell surface of A2780cis cell line. Mass spectrometry and flow cytometry confirmed the over-expression of CD49f, CD70 and Her-2/neu in other cisplatin resistant ovarian cancer cell lines. Immunohistochemical analysis revealed that only CD70 was expressed at moderate levels in ovarian tumors. When cisplatin resistant ovarian cell lines A2780cis and SKOV-3 were treated with antibody against CD70, there was a significant decrease in cell proliferation.

CONCLUSION

Using a MS based proteomics approach we have shown that expression of CD70 is associated with cisplatin resistance in ovarian cancer cell lines. Follow-up examination of these tumor cell line findings in clinical tumor specimens with available pathology staging and cisplatin treatment history is warranted.

Reactions of Charged Phenyl Radicals with Aliphatic Amino Acids in the Gas Phase

Gas-phase reactivity of five differently substituted positively charged phenyl radicals was examined toward six amino acids by using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR). The reactivity of the radicals studied was determined by the electrophilicity of the radical, which can be characterized by the radical's electron affinity (EA). The larger the electron affinity of the radical, the higher the overall reaction rate. In addition to the expected H-atom abstraction, several unprecedented reaction pathways were observed, including NH2 abstraction, SH abstraction, and SCH3 abstraction. These reaction pathways dominate for the most electrophilic radicals, and they may not follow radical but rather nucleophilic addition-elimination mechanisms. Hydrogen abstraction from glycine was also investigated theoretically. The results indicate that hydrogen abstraction from alphaC of glycine is both kinetically and thermodynamically favored over the NH2 group. The ordering of transition state energies for hydrogen abstraction from the alphaC and NH2 groups was found to reflect the radicals' EA ordering.