In-depth proteomic analysis of nonsmall cell lung cancer to discover molecular targets and candidate biomarkers

Unveiling the potential of proteomic and genetic signatures for precision therapeutics in lung cancer management

Lung cancer's enduring global significance necessitates ongoing advancements in diagnostics and therapeutics. Recent spotlight on proteomic and genetic biomarker research offers a promising avenue for understanding lung cancer biology and guiding treatments. This review elucidates genetic and proteomic lung cancer biomarker progress and their treatment implications. Technological strides in mass spectrometry-based proteomics and next-generation sequencing enable pinpointing of genetic abnormalities and abnormal protein expressions, furnishing vital data for precise diagnosis, patient classification, and customized treatments. Biomarker-driven personalized medicine yields substantial treatment improvements, elevating survival rates and minimizing adverse effects. Integrating omics data (genomics, proteomics, etc.) enhances understanding of lung cancer's intricate biological milieu, identifying novel treatment targets and biomarkers, fostering precision medicine. Liquid biopsies, non-invasive tools for real-time treatment monitoring and early resistance detection, gain popularity, promising enhanced management and personalized therapy. Despite advancements, biomarker repeatability and validation challenges persist, necessitating interdisciplinary efforts and large-scale clinical trials. Integrating artificial intelligence and machine learning aids analyzing vast omics datasets and predicting treatment responses. Single-cell omics reveal cellular connections and intratumoral heterogeneity, valuable for combination treatments. Biomarkers enable accurate diagnosis, tailored medicines, and treatment response tracking, significantly impacting personalized lung cancer care. This approach spurs patient-centered trials, empowering active patient engagement. Lung cancer proteomic and genetic biomarkers illuminate disease biology and treatment prospects. Progressing towards individualized efficient therapies is imminent, alleviating lung cancer's burden through ongoing research, omics integration, and technological strides.

Improving combination therapies: targeting A2B-adenosine receptor to modulate metabolic tumor microenvironment and immunosuppression

BACKGROUND

We investigated the role of A2B-adenosine receptor in regulating immunosuppressive metabolic stress in the tumor microenvironment. Novel A2B-adenosine receptor antagonist PBF-1129 was tested for antitumor activity in mice and evaluated for safety and immunologic efficacy in a phase I clinical trial of patients with non-small cell lung cancer.

METHODS

The antitumor efficacy of A2B-adenosine receptor antagonists and their impact on the metabolic and immune tumor microenvironment were evaluated in lung, melanoma, colon, breast, and epidermal growth factor receptor-inducible transgenic cancer models. Employing electron paramagnetic resonance, we assessed changes in tumor microenvironment metabolic parameters, including pO2, pH, and inorganic phosphate, during tumor growth and evaluated the immunologic effects of PBF-1129, including its pharmacokinetics, safety, and toxicity, in patients with non-small cell lung cancer.

RESULTS

Levels of metabolic stress correlated with tumor growth, metastasis, and immunosuppression. Tumor interstitial inorganic phosphate emerged as a correlative and cumulative measure of tumor microenvironment stress and immunosuppression. A2B-adenosine receptor inhibition alleviated metabolic stress, downregulated expression of adenosine-generating ectonucleotidases, increased expression of adenosine deaminase, decreased tumor growth and metastasis, increased interferon γ production, and enhanced the efficacy of antitumor therapies following combination regimens in animal models (anti-programmed cell death 1 protein vs anti-programmed cell death 1 protein plus PBF-1129 treatment hazard ratio = 11.74 [95% confidence interval = 3.35 to 41.13], n = 10, P < .001, 2-sided F test). In patients with non-small cell lung cancer, PBF-1129 was well tolerated, with no dose-limiting toxicities; demonstrated pharmacologic efficacy; modulated the adenosine generation system; and improved antitumor immunity.

CONCLUSIONS

Data identify A2B-adenosine receptor as a valuable therapeutic target to modify metabolic and immune tumor microenvironment to reduce immunosuppression, enhance the efficacy of immunotherapies, and support clinical application of PBF-1129 in combination therapies.

Quantitative proteomics identifies tumour matrisome signatures in patients with non-small cell lung cancer

Introduction

The composition and remodelling of the extracellular matrix (ECM) are important factors in the development and progression of cancers, and the ECM is implicated in promoting tumour growth and restricting anti-tumour therapies through multiple mechanisms. The characterisation of differences in ECM composition between normal and diseased tissues may aid in identifying novel diagnostic markers, prognostic indicators and therapeutic targets for drug development.

Methods

Using tissue from non-small cell lung cancer (NSCLC) patients undergoing curative intent surgery, we characterised quantitative tumour-specific ECM proteome signatures by mass spectrometry.

Results

We identified 161 matrisome proteins differentially regulated between tumour tissue and nearby non-malignant lung tissue, and we defined a collagen hydroxylation functional protein network that is enriched in the lung tumour microenvironment. We validated two novel putative extracellular markers of NSCLC, the collagen cross-linking enzyme peroxidasin and a disintegrin and metalloproteinase with thrombospondin motifs 16 (ADAMTS16), for discrimination of malignant and non-malignant lung tissue. These proteins were up-regulated in lung tumour samples, and high PXDN and ADAMTS16 gene expression was associated with shorter survival of lung adenocarcinoma and squamous cell carcinoma patients, respectively.

Discussion

These data chart extensive remodelling of the lung extracellular niche and reveal tumour matrisome signatures in human NSCLC.

Assay Performance of a Label-Free, Solution-Phase CYFRA 21-1 Determination

CYFRA 21.1, a cytokeratin fragment of epithelial origin, has long been a valuable blood-based biomarker. As with most biomarkers, the clinical diagnostic value of CYFRA 21.1 is dependent on the quantitative performance of the assay. Looking toward translation, it is shown here that a free-solution assay (FSA) coupled with a compensated interferometric reader (CIR) can be used to provide excellent analytical performance in quantifying CYFRA 21.1 in patient serum samples. This report focuses on the analytical performance of the high-sensitivity (hs)-CYFRA 21.1 assay in the context of quantifying the biomarker in two indeterminate pulmonary nodule (IPN) patient cohorts totaling 179 patients. Each of the ten assay calibrations consisted of 6 concentrations, each run as 7 replicates (e.g., 10 × 6 × 7 data points) and were performed on two different instruments by two different operators. Coefficients of variation (CVs) for the hs-CYFRA 21.1 analytical figures of merit, limit of quantification (LOQ) of ca. 60 pg/mL, B _max, initial slope, probe-target binding affinity, and reproducibility of quantifying an unknown were found to range from 2.5 to 8.3%. Our results demonstrate the excellent performance of our FSA-CIR hs-CYFRA 21-1 assay and a proof of concept for potentially redefining the performance characteristics of this existing important candidate biomarker.

Interleukin-11: A Potential Biomarker and Molecular Therapeutic Target in Non-Small Cell Lung Cancer

Non-small cell lung cancer (NSCLC) accounts for 85% of lung cancer and is a fast progressive disease when left untreated. Identification of potential biomarkers in NSCLC is an ongoing area of research that aims to detect, diagnose, and prognosticate patients early to optimize treatment. We review the role of interleukin-11 (IL11), a stromal-cell derived pleiotropic cytokine with profibrotic and cellular remodeling properties, as a potential biomarker in NSCLC. This review identifies the need for biomarkers in NSCLC, the potential sources of IL11, and summarizes the available information leveraging upon published literature, publicly available datasets, and online tools. We identify accumulating evidence suggesting IL11 to be a potential biomarker in NSCLC patients. Further in-depth studies into the pathophysiological effects of IL11 on stromal-tumor interaction in NSCLC are warranted and current available literature highlights the potential value of IL11 detection as a diagnostic and prognostic biomarker in NSCLC.

Neuronal survival factor VGF promotes chemoresistance and predicts poor prognosis in lung cancers with neuroendocrine feature

High-grade neuroendocrine tumors (NETs) of the lung consist of small-cell lung cancer (SCLC) and large-cell neuroendocrine carcinoma (LCNEC). Both exhibit aggressive malignancy with poor prognosis. The transformation of lung adenocarcinoma (ADC) to SCLC or LCNEC also contributes to acquired resistance to epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs). Despite initially being responsive to chemotherapy, high-grade NET patients inevitably develop drug resistance; thus, novel therapeutic targets are urgently needed for these patients. This study reported that VGF (nerve growth factor inducible), a factor mainly expressed in neurons during neural development, is highly expressed in SCLC and LCNEC as well as in a subset of ADCs, whereas targeting VGF attenuates cancer cell growth and tumor formation. High VGF expression was associated with advanced stage SCLC and predicted poor prognosis in lung ADC. In addition, EGFR-TKI selection enriched VGF expression in TKI-resistant ADC under epigenetic control. The VGF locus possessed the HDAC1 binding site, and treatment of ADC cells with the HDAC1 inhibitor induced VGF expression. High VGF expression was associated with chemoresistance, and silencing VGF induced BMF and BCL2L11 expression and rendered lung cancer cells sensitive to chemotherapy drugs. These findings suggested the potential of VGF as a prognostic factor and therapeutic target in lung cancers with neuroendocrine feature. This article is protected by copyright. All rights reserved.

18F-FSPG PET imaging for the evaluation of indeterminate pulmonary nodules

Background

¹⁸F-fluorodeoxyglucose (FDG) PET/CT is recommended for evaluation of intermediate-risk indeterminate pulmonary nodules (IPNs). While highly sensitive, the specificity of FDG remains suboptimal for differentiating malignant from benign nodules, particularly in areas where fungal lung diseases are prevalent. Thus, a cancer-specific imaging probe is greatly needed. In this study, we tested the hypothesis that a PET radiotracer (S)-4-(3-[¹⁸F]-fluoropropyl)-L-glutamic acid (FSPG) improves the diagnostic accuracy of IPNs compared to ¹⁸F-FDG PET/CT.

Methods

This study was conducted at a major academic medical center and an affiliated VA medical center. Twenty-six patients with newly discovered IPNs 7-30mm diameter or newly diagnosed lung cancer completed serial PET/CT scans utilizing ¹⁸F-FDG and ¹⁸F-FSPG, without intervening treatment of the lesion. The scans were independently reviewed by two dual-trained diagnostic radiology and nuclear medicine physicians. Characteristics evaluated included quantitative SUVmax values of the pulmonary nodules and metastases.

Results

A total of 17 out of 26 patients had cancer and 9 had benign lesions. ¹⁸F-FSPG was negative in 6 of 9 benign lesions compared to 7 of 9 with ¹⁸F-FDG. ¹⁸F-FSPG and ¹⁸F-FDG were positive in 14 of 17 and 12 of 17 malignant lesions, respectively. ¹⁸F-FSPG detected brain and intracardiac metastases missed by ¹⁸F-FDG PET in one case, while ¹⁸F-FDG detected a metastasis to the kidney missed by ¹⁸F-FSPG.

Conclusion

In this pilot study, there was no significant difference in overall diagnostic accuracy between ¹⁸F-FSPG and ¹⁸F-FDG for the evaluation of IPNs and staging of lung cancer. Additional studies will be needed to determine the clinical utility of this tracer in the management of IPNs and lung cancer.

The impact of the lung EDRN-CVC on Phase 1, 2, & 3 biomarker validation studies

The Early Detection Research Network’s (EDRN) purpose is to discover, develop and validate biomarkers and imaging methods to detect early-stage cancers or at-risk individuals. The EDRN is composed of sites that fall into four categories: Biomarker Developmental Laboratories (BDL), Biomarker Reference Laboratories (BRL), Clinical Validation Centers (CVC) and Data Management and Coordinating Centers. Each component has a crucial role to play within the mission of the EDRN. The primary role of the CVCs is to support biomarker developers through validation trials on promising biomarkers discovered by both EDRN and non-EDRN investigators. The second round of funding for the EDRN Lung CVC at Vanderbilt University Medical Center (VUMC) was funded in October 2016 and we intended to accomplish the three missions of the CVCs: To conduct innovative research on the validation of candidate biomarkers for early cancer detection and risk assessment of lung cancer in an observational study; to compare biomarker performance; and to serve as a resource center for collaborative research within the Network and partner with established EDRN BDLs and BRLs, new laboratories and industry partners. This report outlines the impact of the VUMC EDRN Lung CVC and describes the role in promoting and validating biological and imaging biomarkers.

Analysis of lung cancer-related genetic changes in long-term and low-dose polyhexamethylene guanidine phosphate (PHMG-p) treated human pulmonary alveolar epithelial cells

BACKGROUND

Lung injury elicited by respiratory exposure to humidifier disinfectants (HDs) is known as HD-associated lung injury (HDLI). Current elucidation of the molecular mechanisms related to HDLI is mostly restricted to fibrotic and inflammatory lung diseases. In our previous report, we found that lung tumors were caused by intratracheal instillation of polyhexamethylene guanidine phosphate (PHMG-p) in a rat model. However, the lung cancer-related genetic changes concomitant with the development of these lung tumors have not yet been fully defined. We aimed to discover the effect of long-term exposure of PHMG-p on normal human lung alveolar cells.

METHODS

We investigated whether PHMG-p could increase distorted homeostasis of oncogenes and tumor-suppressor genes, with long-term and low-dose treatment, in human pulmonary alveolar epithelial cells (HPAEpiCs). Total RNA sequencing was performed with cells continuously treated with PHMG-p and harvested after 35 days.

RESULTS

After PHMG-p treatment, genes with transcriptional expression changes of more than 2.0-fold or less than 0.5-fold were identified. Within 10 days of exposure, 2 protein-coding and 5 non-coding genes were selected, whereas in the group treated for 27-35 days, 24 protein-coding and 5 non-coding genes were identified. Furthermore, in the long-term treatment group, 11 of the 15 upregulated genes and 9 of the 14 downregulated genes were reported as oncogenes and tumor suppressor genes in lung cancer, respectively. We also found that 10 genes of the selected 24 protein-coding genes were clinically significant in lung adenocarcinoma patients.

CONCLUSIONS

Our findings demonstrate that long-term exposure of human pulmonary normal alveolar cells to low-dose PHMG-p caused genetic changes, mainly in lung cancer-associated genes, in a time-dependent manner.

A proteogenomic portrait of lung squamous cell carcinoma

Lung squamous cell carcinoma (LSCC) remains a leading cause of cancer death with few therapeutic options. We characterized the proteogenomic landscape of LSCC, providing a deeper exposition of LSCC biology with potential therapeutic implications. We identify NSD3 as an alternative driver in FGFR1-amplified tumors and low-p63 tumors overexpressing the therapeutic target survivin. SOX2 is considered undruggable, but our analyses provide rationale for exploring chromatin modifiers such as LSD1 and EZH2 to target SOX2-overexpressing tumors. Our data support complex regulation of metabolic pathways by crosstalk between post-translational modifications including ubiquitylation. Numerous immune-related proteogenomic observations suggest directions for further investigation. Proteogenomic dissection of CDKN2A mutations argue for more nuanced assessment of RB1 protein expression and phosphorylation before declaring CDK4/6 inhibition unsuccessful. Finally, triangulation between LSCC, LUAD, and HNSCC identified both unique and common therapeutic vulnerabilities. These observations and proteogenomics data resources may guide research into the biology and treatment of LSCC.

miR-31 Displays Subtype Specificity in Lung Cancer

miRNA rarely possess pan-oncogenic or tumor-suppressive properties. Most miRNAs function under tissue-specific contexts, acting as either tumor suppressors in one tissue, promoting oncogenesis in another, or having no apparent role in the regulation of processes associated with the hallmarks of cancer. What has been less clear is the role of miRNAs within cell types of the same tissue and the ability within each cell type to contribute to oncogenesis. In this study, we characterize the role of one such tissue-specific miRNA, miR-31, recently identified as the most oncogenic miRNA in lung adenocarcinoma, across the histologic spectrum of human lung cancer. Compared with normal lung tissue, miR-31 was overexpressed in patient lung adenocarcinoma, squamous cell carcinoma, and large-cell neuroendocrine carcinoma, but not small-cell carcinoma or carcinoids. miR-31 promoted tumor growth in mice of xenografted human adenocarcinoma and squamous cell carcinoma cell lines, but not in large- or small-cell carcinoma lines. While miR-31 did not promote primary tumor growth of large- and small-cell carcinoma, it did promote spontaneous metastasis. Mechanistically, miR-31 altered distinct cellular signaling programs within each histologic subtype, resulting in distinct phenotypic differences. This is the first report distinguishing diverse functional roles for this miRNA across the spectrum of lung cancers and suggests that miR-31 has broad clinical value in human lung malignancy. SIGNIFICANCE: These findings demonstrate the oncogenic properties of miR-31 in specific subtypes of lung cancer and highlight it as a potential therapeutic target in these subtypes. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/81/8/1942/F1.large.jpg.

Evaluation of kininogen 1, osteopontin and α-1-antitrypsin in plasma, bronchoalveolar lavage fluid and urine for lung squamous cell carcinoma diagnosis

Lung squamous cell carcinoma (LUSC) progression is accompanied by changes in protein levels that may be reflected in body fluids, such as plasma, bronchoalveolar lavage fluid (BALF) and urine. Certain proteins present in these biofluids can facilitate lung cancer diagnosis. Kininogen 1 (KNG1), osteopontin (OPN) and α-1-antitrypsin (AAT) are associated with tumorigenesis. The present study aimed to explore the combined monitoring of plasma, urine and BALF to gain insight into LUSC by monitoring the levels of the above three protein using ELISA. LUSC (n=31) and healthy controls with benign lung diseases (n=20) were enrolled in the study. KNG1 levels in plasma, BALF and urine were significantly higher in patients with LUSC patients than in controls (P<0.0001, P<0.0001 and P=0.0010, respectively). OPN was upregulated in the plasma and BALF of patients with LUSC relative to controls (P=0.0107 and P=0.0004, respectively), whereas its levels in the urine of healthy controls were significantly higher (P=0.0088). Patients with LUSC had higher AAT levels in plasma, BALF and urine compared with those of the controls (P=0.0022, P=0.0014 and P=0.0005, respectively). Receiver operating characteristic analysis showed an area under the curve (AUC) of 0.81 for KNG1 in plasma, 0.91 in BALF and 0.81 in urine. The AUC for OPN was 0.71 in plasma, 0.83 in BALF and 0.75 in urine. The AUC for AAT was 0.74 in plasma, 0.74 in BALF and 0.86 in urine. Immunohistochemical staining in 20 paired LUSC and adjacent normal tissues showed that KNG1, OPN and AAT levels were higher in LUSC tissues. Therefore, our results showed that KNG1, OPN and AAT in biofluids might be useful for the diagnosis of LUSC. These markers in urine and BALF may be better than in plasma for detecting LUSC.

Proteogenomic landscape of squamous cell lung cancer

How genomic and transcriptomic alterations affect the functional proteome in lung cancer is not fully understood. Here, we integrate DNA copy number, somatic mutations, RNA-sequencing, and expression proteomics in a cohort of 108 squamous cell lung cancer (SCC) patients. We identify three proteomic subtypes, two of which (Inflamed, Redox) comprise 87% of tumors. The Inflamed subtype is enriched with neutrophils, B-cells, and monocytes and expresses more PD-1. Redox tumours are enriched for oxidation-reduction and glutathione pathways and harbor more NFE2L2/KEAP1 alterations and copy gain in the 3q2 locus. Proteomic subtypes are not associated with patient survival. However, B-cell-rich tertiary lymph node structures, more common in Inflamed, are associated with better survival. We identify metabolic vulnerabilities (TP63, PSAT1, and TFRC) in Redox. Our work provides a powerful resource for lung SCC biology and suggests therapeutic opportunities based on redox metabolism and immune cell infiltrates.

Squamous cell lung cancer has dismal prognosis due to the dearth of effective treatments. Here, the authors perform an integrated proteogenomic analysis of the disease, revealing three proteomics-based subtypes and suggesting potential therapeutic opportunities.

Serum thrombospondin-2 is a candidate diagnosis biomarker for early non-small-cell lung cancer

Thrombospondin-2 (THBS2) is a secreted protein overexpressed in numerous cancers and may function as a diagnostic tumor marker. The objective of the present study was to investigate the diagnostic performance of serum THBS2 in early stage non-small-cell lung cancer (NSCLC). Serum THBS2 and Cyfra21-1 level were evaluated in blood samples of 112 patients from NSCLC groups and 51 healthy control (HC) groups. Receiver operator characteristic (ROC) curves were used to evaluate the diagnostic significance. Serum THBS2 level was significantly up-regulated in NSCLC patients compared with healthy control subjects (P<0.0001), and the postoperative THBS2 level decreased significantly (P<0.0001). ROC curves analysis demonstrated that THBS2 was a comparable biomarker as Cyfra21-1 to distinguish early stage NSCLC or lung squamous cell carcinoma (SC) from healthy control subjects. And Cyfra21-1 was observed with significantly improved performances by the combination of THBS2 to distinguish early stage NSCLC (P<0.05) as well as SC (P<0.05) from the control subjects. In addition, THBS2 was estimated to perform well in the diagnosis of patients with Cyfra21-1-negative NSCLC (area under the curve [AUC] = 0.73). In summary, the present study suggested that serum THBS2 might be an early diagnostic biomarker for NSCLC.

Detection of early lung cancer among military personnel (DECAMP) consortium: study protocols

BACKGROUND

Lung cancer is the leading cause of cancer-related death due in large part to our inability to diagnose it at an early and potentially curable stage. Screening for lung cancer via low dose computed tomographic (LDCT) imaging has been demonstrated to improve mortality but also results in a high rate of false positive tests. The identification and application of non-invasive molecular biomarkers that improve the performance of CT imaging for the detection of lung cancer in high risk individuals would aid in clinical decision-making, eliminate the need for unnecessary LDCT follow-up, and further refine the screening criteria for an already large high-risk population.

METHODS

The Detection of Early Lung Cancer Among Military Personnel (DECAMP) consortium is conducting two multicenter prospective studies with the goals of developing an integrated panel of both airway and blood-based molecular biomarkers that discriminate benign and malignant indeterminate nodules detected on CT scan as well as predict the future development of lung cancer in high-risk individuals. To achieve these goals, DECAMP is compiling an extensive array of biospecimens including nasal brushings, serum, plasma and intrathoracic airway samples (bronchial brushings and bronchial biopsies) from normal-appearing airway epithelium.

DISCUSSION

This bank of samples is the foundation for multiple DECAMP efforts focused on the identification of those at greatest risk of developing lung cancer as well as the discrimination of benign and malignant pulmonary nodules. The clinical, imaging and biospecimen repositories will serve as a resource for the biomedical community and their investigation of the molecular basis of chronic respiratory disease.

TRIAL REGISTRATION

Retrospectively registered as NCT01785342 - DECAMP-1: Diagnosis and Surveillance of Indeterminate Pulmonary Nodules (DECAMP-1). Date of Registration: February 7, 2013. Retrospectively registered as NCT02504697 - DECAMP-2: Screening of Patients With Early Stage Lung Cancer or at High Risk for Developing Lung Cancer (DECAMP-2). Date of Registration: July 22, 2015.

Urea Cycle Sustains Cellular Energetics upon EGFR Inhibition in EGFR-Mutant NSCLC

Mutations in oncogenes and tumor suppressor genes engender unique metabolic phenotypes crucial to the survival of tumor cells. EGFR signaling has been linked to the rewiring of tumor metabolism in non-small cell lung cancer (NSCLC). We have integrated the use of a functional genomics screen and metabolomics to identify metabolic vulnerabilities induced by EGFR inhibition. These studies reveal that following EGFR inhibition, EGFR-driven NSCLC cells become dependent on the urea cycle and, in particular, the urea cycle enzyme CPS1. Combining knockdown of CPS1 with EGFR inhibition further reduces cell proliferation and impedes cell-cycle progression. Profiling of the metabolome demonstrates that suppression of CPS1 potentiates the effects of EGFR inhibition on central carbon metabolism, pyrimidine biosynthesis, and arginine metabolism, coinciding with reduced glycolysis and mitochondrial respiration. We show that EGFR inhibition and CPS1 knockdown lead to a decrease in arginine levels and pyrimidine derivatives, and the addition of exogenous pyrimidines partially rescues the impairment in cell growth. Finally, we show that high expression of CPS1 in lung adenocarcinomas correlated with worse patient prognosis in publicly available databases. These data collectively reveal that NSCLC cells have a greater dependency on the urea cycle to sustain central carbon metabolism, pyrimidine biosynthesis, and arginine metabolism to meet cellular energetics upon inhibition of EGFR. IMPLICATIONS: Our results reveal that the urea cycle may be a novel metabolic vulnerability in the context of EGFR inhibition, providing an opportunity to develop rational combination therapies with EGFR inhibitors for the treatment of EGFR-driven NSCLC.

Preferential Localization of MUC1 Glycoprotein in Exosomes Secreted by Non-Small Cell Lung Carcinoma Cells

Lung cancer remains to be the leading cause of cancer-related mortality worldwide. Finding new noninvasive biomarkers for lung cancer is still a significant clinical challenge. Exosomes are membrane-bound, nano-sized vesicles that are released by various living cells. Studies on exosomal proteomics may provide clues for developing clinical assays. In this study, we performed semi-quantitative proteomic analysis of proteins that were purified from exosomes of NCI-H838 non-small cell lung cancer cell line, with total cellular membrane proteins as control. In the exosomes, LC-MS/MS by data-independent analysis mode identified 3235 proteins. THBS1, ANXA6, HIST1H4A, COL18A1, MDK, SRGN, ENO1, TUBA4A, SLC3A2, GPI, MIF, MUC1, TALDO1, SLC7A5, ICAM1, HSP90AA1, G6PD, and LRP1 were found to be expressed in exosomes at more than 5-fold higher level as compared to total cellular membrane proteins. A well-known cancer biomarker, MUC1, is expressed at 8.98-fold higher in exosomes than total cellular membrane proteins. Subsequent analysis of plasma exosomes from non-small cell lung cancer (NSCLC) patients by a commercial electrochemiluminescence immunoassay showed that exosomal MUC1 level is 1.5-fold higher than healthy individuals (mean value 1.55 ± 0.16 versus mean value 1.05 ± 0.06, p = 0.0213). In contrast, no significant difference of MUC1 level was found between NSCLC patients and healthy individuals' plasma (mean value 5.48 ± 0.65 versus mean value 4.16 ± 0.49). These results suggest that certain proteins, such as MUC1, are selectively enriched in the exosome compartment. The mechanisms for their preferential localization and their biological roles remain to be studied.

Proteomics: Clinical and research applications in respiratory diseases

The proteome is the study of the protein content of a definable component of an organism in biology. However, the tissue-specific expression of proteins and the varied post-translational modifications, splice variants and protein-protein complexes that may form, make the study of protein a challenging yet vital tool in answering many of the unanswered questions in medicine and biology to date. Indeed, the spatial, temporal and functional composition of proteins in the human body has proven difficult to elucidate for many years. Given the effect of microRNA and epigenetic regulation on silencing and enhancing gene transcription, the study of protein arguably provides more accurate information on homeostasis and perturbation in health and disease. There have been significant advances in the field of proteomics in recent years, with new technologies and platforms available to the research community. In this review, we briefly discuss some of these new technologies and developments in the context of respiratory disease. We also discuss the types of data science approaches to analyses and interpretation of the large volumes of data generated in proteomic studies. We discuss the application of these technologies with regard to respiratory disease and highlight the potential for proteomics in generating major advances in the understanding of respiratory pathophysiology into the future.

Global quantitative analysis of the human brain proteome in Alzheimer's and Parkinson's Disease

Patients with Alzheimer's disease (AD) and Parkinson's disease (PD) often have overlap in clinical presentation and brain neuropathology suggesting that these two diseases share common underlying mechanisms. Currently, the molecular pathways linking AD and PD are incompletely understood. Utilizing Tandem Mass Tag (TMT) isobaric labeling and synchronous precursor selection-based MS3 (SPS-MS3) mass spectrometry, we performed an unbiased quantitative proteomic analysis of post-mortem human brain tissues (n=80) from four different groups defined as controls, AD, PD, and co-morbid AD/PD cases across two brain regions (frontal cortex and anterior cingulate gyrus). In total, we identified 11 840 protein groups representing 10 230 gene symbols, which map to ~65% of the protein coding genes in brain. The utility of including two reference standards in each TMT 10-plex assay to assess intra- and inter-batch variance is also described. Ultimately, this comprehensive human brain proteomic dataset serves as a valuable resource for various research endeavors including, but not limited to, the identification of disease-specific protein signatures and molecular pathways that are common in AD and PD.

The Airway Transcriptome as a Biomarker for Early Lung Cancer Detection

Lung cancer remains the leading cause of cancer-related death due to its advanced stage at diagnosis. Early detection of lung cancer can be improved by better defining who should be screened radiographically and determining which imaging-detected pulmonary nodules are malignant. Gene expression biomarkers measured in normal-appearing airway epithelium provide an opportunity to use lung cancer-associated molecular changes in this tissue for early detection of lung cancer. Molecular changes in the airway may result from an etiologic field of injury and/or field cancerization. The etiologic field of injury reflects the aberrant physiologic response to carcinogen exposure that creates a susceptible microenvironment for cancer initiation. In contrast, field cancerization reflects effects of "first-hit" mutations in a clone of cells from which the tumor ultimately arises or the effects of the tumor on the surrounding tissue. These fields might have value both for assessing lung cancer risk and diagnosis. Cancer-associated gene expression changes in the bronchial airway have recently been used to develop and validate a 23-gene classifier that improves the diagnostic yield of bronchoscopy for lung cancer among intermediate-risk patients. Recent studies have demonstrated that these lung cancer-related gene expression changes extend to nasal epithelial cells that can be sampled noninvasively. While the bronchial gene expression biomarker is being adopted clinically, further work is necessary to explore the potential clinical utility of gene expression profiling in the nasal epithelium for lung cancer diagnosis, lung cancer risk assessment, and precision medicine for lung cancer treatment and chemoprevention. Clin Cancer Res; 24(13); 2984-92. ©2018 AACR.

Current and Prospective Protein Biomarkers of Lung Cancer

Lung cancer is a malignant lung tumor with various histological variants that arise from different cell types, such as bronchial epithelium, bronchioles, alveoli, or bronchial mucous glands. The clinical course and treatment efficacy of lung cancer depends on the histological variant of the tumor. Therefore, accurate identification of the histological type of cancer and respective protein biomarkers is crucial for adequate therapy. Due to the great diversity in the molecular-biological features of lung cancer histological types, detection is impossible without knowledge of the nature and origin of malignant cells, which release certain protein biomarkers into the bloodstream. To date, different panels of biomarkers are used for screening. Unfortunately, a uniform serum biomarker composition capable of distinguishing lung cancer types is yet to be discovered. As such, histological analyses of tumor biopsies and immunohistochemistry are the most frequently used methods for establishing correct diagnoses. Here, we discuss the recent advances in conventional and prospective aptamer based strategies for biomarker discovery. Aptamers like artificial antibodies can serve as molecular recognition elements for isolation detection and search of novel tumor-associated markers. Here we will describe how these small synthetic single stranded oligonucleotides can be used for lung cancer biomarker discovery and utilized for accurate diagnosis and targeted therapy. Furthermore, we describe the most frequently used in-clinic and novel lung cancer biomarkers, which suggest to have the ability of differentiating between histological types of lung cancer and defining metastasis rate.

In-depth proteomic analysis of tissue interstitial fluid for hepatocellular carcinoma serum biomarker discovery

Background:

Hepatocellular carcinoma (HCC) is a primary malignancy of the liver. New serum biomarkers for HCC screening are needed, especially for alpha-fetoprotein (AFP) negative patients. As a proximal fluid between body fluids and intracellular fluid, tissue interstitial fluid (TIF) is a suitable source for serum biomarker discovery.

Methods:

Sixteen paired TIF samples from HCC tumour and adjacent non-tumour tissues were analysed by isobaric tags for relative and absolute quantitation (iTRAQ) method. Two proteins were selected for ELISA validation in serum samples.

Results:

Totally, 3629 proteins were identified and 3357 proteins were quantified in TIF samples. Among them, 232 proteins were significantly upregulated in HCC-TIF and 257 proteins down-regulated. Two overexpressed extracellular matrix proteins, SPARC and thrombospondin-2 (THBS2) were selected for further validation. ELISA result showed that the serum levels of SPARC and THBS2 in HCC patients were both significantly higher than those in healthy controls. The combination of serum SPARC and THBS2 could distinguish HCC (AUC=0.97, sensitivity=86%, specificity=100%) or AFP-negative HCC (AUC=0.95, sensitivity=91%, specificity=93%) from healthy controls. And the combination of serum SPARC and THBS2 could also distinguish HCC patients from benign liver disease patients (AUC=0.93, sensitivity=80%, specificity=94%). In addition, serum THBS2 was found to be a novel independent indicator for poor prognosis of HCC.

Conclusions:

Novel HCC candidate serum markers were found through in-depth proteomic analysis of TIF, which demonstrated the successful utility of TIF in cancer serum biomarker discovery.

Relative protein quantification and accessible biology in lung tumor proteomes from four LC-MS/MS discovery platforms

Discovery proteomics experiments include many options for sample preparation and MS data acquisition, which are capable of creating datasets for quantifying thousands of proteins. To define a strategy that would produce a dataset with sufficient content while optimizing required resources, we compared (1) single-sample LC-MS/MS with data-dependent acquisition to single-sample LC-MS/MS with data-independent acquisition and (2) peptide fractionation with label-free (LF) quantification to peptide fractionation with relative quantification of chemically labeled peptides (sixplex tandem mass tags (TMT)). These strategies were applied to the same set of four frozen lung squamous cell carcinomas and four adjacent tissues, and the overall outcomes of each experiment were assessed. We identified 6656 unique protein groups with LF, 5535 using TMT, 3409 proteins from single-sample analysis with data-independent acquisition, and 2219 proteins from single-sample analysis with data-dependent acquisition. Pathway analysis indicated the number of proteins per pathway was proportional to the total protein identifications from each method, suggesting limited biological bias between experiments. The results suggest the use of single-sample experiments as a rapid tissue assessment tool and digestion quality control or as a technique to maximize output from limited samples and use of TMT or LF quantification as methods for larger amounts of tumor tissue with the selection being driven mainly by instrument time limitations. Data are available via ProteomeXchange with identifiers PXD004682, PXD004683, PXD004684, and PXD005733.

[Omics technologies in diagnostics of lung adenocarcinoma]

To date lung adenocarcinoma (LAC) is the most common type of lung cancer. Numerous studies on LAC biology resulted in identification of crucial mutations in protooncogenes and activating neoplastic transformation pathways. Therapeutic approaches that significantly increase the survival rate of patients with LAC of different etiology have been developed and introduced into clinical practice. However, the main problem in the treatment of LAC is early diagnosis, taking into account both factors and mechanisms responsible in tumor initiation and progression. Identification of a wide biomarker repertoire with high specificity and reliability of detection appears to be a solution to this problem. In this context, proteins with differential expression in normal and pathological condition, suitable for detection in biological fluids are the most promising biomarkers. In this review we have analyzed literature data on studies aimed at search of LAC biomarkers. The major attention has been paid to protein biomarkers as the most promising and convenient subject of clinical diagnosis. The review also summarizes existing knowledge on posttranslational modifications, splice variants, isoforms, as well as model systems and transcriptome changes in LAC.

Proteomic profiling of early degenerative retina of RCS rats

AIM

To identify the underlying cellular and molecular changes in retinitis pigmentosa (RP).

METHODS

Label-free quantification-based proteomics analysis, with its advantages of being more economic and consisting of simpler procedures, has been used with increasing frequency in modern biological research. Dystrophic RCS rats, the first laboratory animal model for the study of RP, possess a similar pathological course as human beings with the diseases. Thus, we employed a comparative proteomics analysis approach for in-depth proteome profiling of retinas from dystrophic RCS rats and non-dystrophic congenic controls through Linear Trap Quadrupole - orbitrap MS/MS, to identify the significant differentially expressed proteins (DEPs). Bioinformatics analyses, including Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation and upstream regulatory analysis, were then performed on these retina proteins. Finally, a Western blotting experiment was carried out to verify the difference in the abundance of transcript factor E2F1.

RESULTS

In this study, we identified a total of 2375 protein groups from the retinal protein samples of RCS rats and non-dystrophic congenic controls. Four hundred thirty-four significantly DEPs were selected by Student's t-test. Based on the results of the bioinformatics analysis, we identified mitochondrial dysfunction and transcription factor E2F1 as the key initiation factors in early retinal degenerative process.

CONCLUSION

We showed that the mitochondrial dysfunction and the transcription factor E2F1 substantially contribute to the disease etiology of RP. The results provide a new potential therapeutic approach for this retinal degenerative disease.

Quantitative proteomics in lung cancer

Lung cancer is the most common cause of cancer-related death worldwide, less than 7% of patients survive 10 years following diagnosis across all stages of lung cancer. Late stage of diagnosis and lack of effective and personalized medicine reflect the need for a better understanding of the mechanisms that underlie lung cancer progression. Quantitative proteomics provides the relative different protein abundance in normal and cancer patients which offers the information for molecular interactions, signaling pathways, and biomarker identification. Here we introduce both theoretical and practical applications in the use of quantitative proteomics approaches, with principles of current technologies and methodologies including gel-based, label free, stable isotope labeling as well as targeted proteomics. Predictive markers of drug resistance, candidate biomarkers for diagnosis, and prognostic markers in lung cancer have also been discovered and analyzed by quantitative proteomic analysis. Moreover, construction of protein networks enables to provide an opportunity to interpret disease pathway and improve our understanding in cancer therapeutic strategies, allowing the discovery of molecular markers and new therapeutic targets for lung cancer.

Integration of multiple "OMIC" biomarkers: A precision medicine strategy for lung cancer

More than half of all new lung cancer diagnoses are made in patients with locally advanced or metastatic disease, at which point therapeutic options are scarce. It is anticipated, however, that the widespread use of Low-Dose Computed Tomography (LDCT) screening, will lead to a greater proportion of lung cancers being diagnosed at an early, operable, stage. Still, the overall rate of recurrence for surgically treated Stage I lung cancer patients is up to 30% within 5 years of diagnosis. Thus, the identification and clinical application of biomarkers of early stage lung cancer are a pressing medical need. The integrative analysis of "omic," clinical and epidemiological data for single patients is a core principle of precision medicine. Through rigorous bioinformatics and statistical analyses we have identified biomarkers of early-stage lung cancer based on DNA methylation, expression of mRNA and miRNA, inflammatory cytokines, and urinary metabolites. Beyond a more comprehensive understanding of the molecular taxonomy of lung cancer, these biomarkers can have very practical implications in the context of unmet clinical needs of early stage lung cancer patients: First, current guidelines for LDCT screening broadly include individuals based on age and history of heavy smoking. Tumor-derived circulating biomarkers in the blood and urine associated with lung cancer risk could narrow and prioritize individuals for LDCT screening. Second, a high number of nodules are identified by LDCT, of which fewer than 5% are finally diagnosed as lung cancer. Biomarkers may help discriminate malignant nodules from benign or indolent lesions. Third, the expected rise in the numbers of lung cancer patients diagnosed at an early stage will necessitate new treatment options. Circulating, urinary and tissue-based biomarkers that molecularly categorize Stage I patients after tumor resection can help identify high-risk patients who may benefit from adjuvant chemotherapy or innovative immunotherapy regimens.

Recent mass spectrometry-based proteomics for biomarker discovery in lung cancer, COPD, and asthma

INTRODUCTION

Lung cancer and related diseases have been one of the most common causes of deaths worldwide. Genomic-based biomarkers may hardly reflect the underlying dynamic molecular mechanism of functional protein interactions, which is the center of a disease. Recent developments in mass spectrometry (MS) have made it possible to analyze disease-relevant proteins expressed in clinical specimens by proteomic challenges. Areas covered: To understand the molecular mechanisms of lung cancer and its subtypes, chronic obstructive pulmonary disease (COPD), asthma and others, great efforts have been taken to identify numerous relevant proteins by MS-based clinical proteomic approaches. Since lung cancer is a multifactorial disease that is biologically associated with asthma and COPD among various lung diseases, this study focused on proteomic studies on biomarker discovery using various clinical specimens for lung cancer, COPD, and asthma. Expert commentary: MS-based exploratory proteomics utilizing clinical specimens, which can incorporate both experimental and bioinformatic analysis of protein-protein interaction and also can adopt proteogenomic approaches, makes it possible to reveal molecular networks that are relevant to a disease subgroup and that could differentiate between drug responders and non-responders, good and poor prognoses, drug resistance, and so on.

Bronchoalveolar Lavage Proteomics in Patients with Suspected Lung Cancer

Lung cancer configures as one of the deadliest types of cancer. The future implementation of early screening methods such as exhaled breath condensate analysis and low dose computed tomography (CT) as an alternative to current chest imaging based screening will lead to an increased burden on bronchoscopy units. New approaches for improvement of diagnosis in bronchoscopy units, regarding patient management, are likely to have clinical impact in the future. Diagnostic approaches to address mortality of lung cancer include improved early detection and stratification of the cancers according to its prognosis and further response to drug treatment. In this study, we performed a detailed mass spectrometry based proteome analysis of acellular bronchoalveolar lavage (BAL) fluid samples on an observational prospective cohort consisting of 90 suspected lung cancer cases which were followed during two years. The thirteen new lung cancer cases diagnosed during the follow up time period clustered, based on liquid chromatography-mass spectrometry (LC-MS) data, with lung cancer cases at the time of BAL collection. Hundred and thirty-tree potential biomarkers were identified showing significantly differential expression when comparing lung cancer versus non-lung cancer. The regulated biomarkers showed a large overlap with biomarkers detected in tissue samples.

The airway epithelium undergoes metabolic reprogramming in individuals at high risk for lung cancer

The molecular determinants of lung cancer risk remain largely unknown. Airway epithelial cells are prone to assault by risk factors and are considered to be the primary cell type involved in the field of cancerization. To investigate risk-associated changes in the bronchial epithelium proteome that may offer new insights into the molecular pathogenesis of lung cancer, proteins were identified in the airway epithelial cells of bronchial brushing specimens from risk-stratified individuals by shotgun proteomics. Differential expression of selected proteins was validated by parallel reaction monitoring mass spectrometry in an independent set of individual bronchial brushings. We identified 2,869 proteins, of which 312 proteins demonstrated a trend in expression. Pathway analysis revealed enrichment of carbohydrate metabolic enzymes in high-risk individuals. Glucose consumption and lactate production were increased in human bronchial epithelial BEAS2B cells treated with cigarette smoke condensate for 7 months. Increased lipid biosynthetic capacity and net reductive carboxylation were revealed by metabolic flux analyses of [U-¹³C₅] glutamine in this in vitro model, suggesting profound metabolic reprogramming in the airway epithelium of high-risk individuals. These results provide a rationale for the development of potentially new chemopreventive strategies and selection of patients for surveillance programs.

From Proteomic Analysis to Potential Therapeutic Targets: Functional Profile of Two Lung Cancer Cell Lines, A549 and SW900, Widely Studied in Pre-Clinical Research

Lung cancer is a serious health problem and the leading cause of cancer death worldwide. The standard use of cell lines as in vitro pre-clinical models to study the molecular mechanisms that drive tumorigenesis and access drug sensitivity/effectiveness is of undisputable importance. Label-free mass spectrometry and bioinformatics were employed to study the proteomic profiles of two representative lung cancer cell lines and to unravel the specific biological processes. Adenocarcinoma A549 cells were enriched in proteins related to cellular respiration, ubiquitination, apoptosis and response to drug/hypoxia/oxidative stress. In turn, squamous carcinoma SW900 cells were enriched in proteins related to translation, apoptosis, response to inorganic/organic substances and cytoskeleton organization. Several proteins with differential expression were related to cancer transformation, tumor resistance, proliferation, migration, invasion and metastasis. Combined analysis of proteome and interactome data highlighted key proteins and suggested that adenocarcinoma might be more prone to PI3K/Akt/mTOR and topoisomerase IIα inhibitors, and squamous carcinoma to Ck2 inhibitors. Moreover, ILF3 overexpression in adenocarcinoma, and PCNA and NEDD8 in squamous carcinoma shows them as promising candidates for therapeutic purposes. This study highlights the functional proteomic differences of two main subtypes of lung cancer models and hints several targeted therapies that might assist in this type of cancer.

Proteomic profiling of lung adenocarcinoma indicates heightened DNA repair, antioxidant mechanisms and identifies LASP1 as a potential negative predictor of survival

BACKGROUND

Lung cancer is the leading cause of cancer mortality in the United States. Non-small cell lung cancer accounts for 85% of all lung cancers for which adenocarcinoma is the most common histological type. Management of lung cancer is hindered by high false-positive rates due to difficulty resolving between benign and malignant tumors. Better molecular analysis comparing malignant and non-malignant tissues will provide important evidence of the underlying biology contributing to tumorigenesis.

METHODS

We utilized a proteomics approach to analyze 38 malignant and non-malignant paired tissue samples obtained from current or former smokers with early stage (Stage IA/IB) lung adenocarcinoma. Statistical mixed effects modeling and orthogonal partial least squares discriminant analysis were used to identify key cancer-associated perturbations in the adenocarcinoma proteome. Identified proteins were subsequently assessed against clinicopathological variables.

RESULTS

Top cancer-associated protein alterations were characterized by: (1) elevations in APEX1, HYOU1 and PDIA4, indicative of increased DNA repair machinery and heightened anti-oxidant defense mechanisms; (2) increased LRPPRC, STOML2, COPG1 and EPRS, suggesting altered tumor metabolism and inflammation; (3) reductions in SPTB, SPTA1 and ANK1 implying dysregulation of membrane integrity; and (4) decreased SLCA41 suggesting altered pH regulation. Increased protein levels of HYOU1, EPRS and LASP1 in NSCLC adenocarcinoma was independently validated by tissue microarray immunohistochemistry. Immunohistochemistry for HYOU1 and EPRS indicated AUCs of 0.952 and 0.841, respectively, for classifying tissue as malignant. Increased LASP1 correlated with poor overall survival (HR 3.66 per unit increase; CI 1.37-9.78; p = 0.01).

CONCLUSION

These results reveal distinct proteomic changes associated with early stage lung adenocarcinoma that may be useful prognostic indicators and therapeutic targets.

Identification and Characterization of Potential Biomarkers by Quantitative Tissue Proteomics of Primary Lung Adenocarcinoma

Lung cancer is the leading cause of cancer-related death worldwide. Both diagnostic and prognostic biomarkers are urgently needed to increase patient survival. In this study, we identified/quantified 1763 proteins from paired adenocarcinoma (ADC) tissues with different extents of lymph node (LN) involvement using an iTRAQ-based quantitative proteomic analysis. Based on a bioinformatics analysis and literature search, we selected six candidates (ERO1L, PABPC4, RCC1, RPS25, NARS, and TARS) from a set of 133 proteins that presented a 1.5-fold increase in expression in ADC tumors without LN metastasis compared with adjacent normal tissues. These six proteins were further verified using immunohistochemical staining and Western blot analyses. The protein levels of these six candidates were higher in tumor tissues compared with adjacent normal tissues. The ERO1L and NARS levels were positively associated with LN metastasis. Importantly, ERO1L overexpression in patients with early-stage ADC was positively correlated with poor survival, suggesting that ERO1L overexpression in primary sites of early-stage cancer tissues indicates a high risk for cancer micrometastasis. Moreover, we found that knockdown of either ERO1L or NARS reduced the viability and migration ability of ADC cells. Our results collectively provide a potential biomarker data set for ADC diagnosis/prognosis and reveal novel roles of ERO1L and NARS in ADC progression.

Quantitative Proteomic Analysis of Duck Ovarian Follicles Infected with Duck Tembusu Virus by Label-Free LC-MS

Duck Tembusu virus (DTMUV) is a newly emerging pathogenic flavivirus that has caused massive economic losses to the duck industry in China. DTMUV infection mainly results in significant decreases in egg production in egg-laying ducks within 1–2 weeks post infection. However, information on the comparative protein expression of host tissues in response to DTMUV infection is limited. In the present study, the cellular protein response to DTMUV infection in duck ovarian follicles was analyzed using nano-flow high-performance liquid chromatography-electrospray tandem mass spectrometry. Quantitative proteomic analysis revealed 131 differentially expressed proteins, among which 53 were up regulated and 78 were down regulated. The identified proteins were involved in the regulation of essential processes such as cellular structure and integrity, RNA processing, protein biosynthesis and modification, vesicle transport, signal transduction, and mitochondrial pathway. Some selected proteins that were found to be regulated in DTMUV-infected tissues were screened by quantitative real-time PCR to examine their regulation at the transcriptional level, western blot analysis was used to validate the changes of some selected proteins on translational level. To our knowledge, this study is the first to analyze the proteomic changes in duck ovarian follicles following DTMUV infection. The protein-related information obtained in this study may be useful to understand the host response to DTMUV infection and the inherent mechanism of DTMUV replication and pathogenicity.

Cancer-Specific Production of N-Acetylaspartate via NAT8L Overexpression in Non-Small Cell Lung Cancer and Its Potential as a Circulating Biomarker

In order to identify new cancer-associated metabolites that may be useful for early detection of lung cancer, we performed a global metabolite profiling of a non-small cell lung cancer (NSCLC) line and immortalized normal lung epithelial cells from the same patient. Among several metabolites with significant cancer/normal differences, we identified a unique metabolic compound, N-acetylaspartate (NAA), in cancer cells-undetectable in normal lung epithelium. NAA's cancer-specific detection was validated in additional cancer and control lung cells as well as selected NSCLC patient tumors and control tissues. NAA's cancer specificity was further supported in our analysis of NAA synthetase (gene symbol: NAT8L) gene expression levels in The Cancer Genome Atlas: elevated NAT8L expression in approximately 40% of adenocarcinoma and squamous cell carcinoma cases (N = 577), with minimal expression in all nonmalignant lung tissues (N = 74). We then showed that NAT8L is functionally involved in NAA production of NSCLC cells through siRNA-mediated suppression of NAT8L, which caused selective reduction of intracellular and secreted NAA. Our cell culture experiments also indicated that NAA biosynthesis in NSCLC cells depends on glutamine availability. For preliminary evaluation of NAA's clinical potential as a circulating biomarker, we developed a sensitive NAA blood assay and found that NAA blood levels were elevated in 46% of NSCLC patients (N = 13) in comparison with age-matched healthy controls (N = 21) among individuals aged 55 years or younger. Taken together, these results indicate that NAA is produced specifically in NSCLC tumors through NAT8L overexpression, and its extracellular secretion can be detected in blood. Cancer Prev Res; 9(1); 43-52. ©2015 AACR.

A Pilot Proteogenomic Study with Data Integration Identifies MCT1 and GLUT1 as Prognostic Markers in Lung Adenocarcinoma

We performed a pilot proteogenomic study to compare lung adenocarcinoma to lung squamous cell carcinoma using quantitative proteomics (6-plex TMT) combined with a customized Affymetrix GeneChip. Using MaxQuant software, we identified 51,001 unique peptides that mapped to 7,241 unique proteins and from these identified 6,373 genes with matching protein expression for further analysis. We found a minor correlation between gene expression and protein expression; both datasets were able to independently recapitulate known differences between the adenocarcinoma and squamous cell carcinoma subtypes. We found 565 proteins and 629 genes to be differentially expressed between adenocarcinoma and squamous cell carcinoma, with 113 of these consistently differentially expressed at both the gene and protein levels. We then compared our results to published adenocarcinoma versus squamous cell carcinoma proteomic data that we also processed with MaxQuant. We selected two proteins consistently overexpressed in squamous cell carcinoma in all studies, MCT1 (SLC16A1) and GLUT1 (SLC2A1), for further investigation. We found differential expression of these same proteins at the gene level in our study as well as in other public gene expression datasets. These findings combined with survival analysis of public datasets suggest that MCT1 and GLUT1 may be potential prognostic markers in adenocarcinoma and druggable targets in squamous cell carcinoma. Data are available via ProteomeXchange with identifier PXD002622.

[Research Progress of Biomakers Proteomics-based in Lung Cancer]

蛋白组学技术可以应用于癌症研究来检测差异蛋白质表达以发现癌症生物标志物。肺癌的生物标志物在肺癌早期诊断、指导治疗和预后监测方面起着关键作用。因此，迫切需要确定新的早期诊断和预后指标以开辟新的治疗途径。本文简要介绍了基于蛋白质组学的肺癌生物标志物的最新研究报告。他包括作为诊断、预后和预测性的生物标志物，以及基于最近发表文献的基础上和我们所做的相关工作的总结。

Targeting SLC1a5-mediated glutamine dependence in non-small cell lung cancer

We previously elucidated the pleotropic role of solute carrier family A1 member 5 (SLC1A5) as the primary transporter of glutamine (Gln), a modulator of cell growth and oxidative stress in non-small cell lung cancer (NSCLC). The aim of our study was to evaluate SLC1A5 as a potential new therapeutic target and candidate biomarker predictive of survival and response to therapy. SLC1A5 targeting was examined in a panel of NSCLC and human bronchial cell lines by RNA interference and by a small molecular inhibitor, gamma-l-glutamyl-p-nitroanilide (GPNA). The effects of targeting SLC1A5 on cell growth, Gln uptake, ATP level, autophagy and cell death were examined. Inactivation of SLC1A5 genetically or pharmacologically decreased Gln consumption, inhibited cell growth, induced autophagy and apoptosis in a subgroup of NSCLC cell lines that overexpress SLC1A5. Targeting SLC1A5 function decreased tumor growth in NSCLC xenografts. A multivariate Cox proportional hazards analysis indicates that patients with increased SLC1A5 mRNA expression have significantly shorter overall survival (p = 0.01, HR = 1.24, 95% CI: 1.05-1.46), adjusted for age, gender, smoking history and disease stage. In an immunohistochemistry study on 207 NSCLC patients, SLC1A5 protein expression remained highly significant prognostic value in both univariate (p < 0.0001, HR = 1.45, 95% CI: 1.15-1.50) and multivariate analyses (p = 0.04, HR = 1.22, 95% CI: 1.01-1.31). These results position SLC1A5 as a new candidate prognostic biomarker for selective targeting of Gln-dependent NSCLC.

The value of proteomics in lung cancer

Many studies have identified the prognostic and predictive value of proteins or peptides in lung cancer but most failed to provide strong evidence for their clinical applicability. The strongest predictive proteins seem to be fatty acid-binding protein heart (H-FABP), and the 8-peak mass spectrography signature of VeriStrat. When focusing on VeriStrat, a 'VeriStrat good' profile did not discriminate between chemotherapy and erlotinib. The 'VeriStrat poor' profile showed a better outcome to chemotherapy than to erlotinib. VeriStrat is a prognostic test and only the "poor profile" discriminates for the type of therapy that should be chosen. Whether it adds useful information in patients with advanced non-small cell lung cancer (NSCLC) and wild type EGFR mutations is still doubtful. The position of the VeriStrat test in clinical practice is still not clear and we are waiting for prospective studies where biomarker test are involved in clinical decision.

Kinomic profiling of electromagnetic navigational bronchoscopy specimens: a new approach for personalized medicine

Purpose

Researchers are currently seeking relevant lung cancer biomarkers in order to make informed decisions regarding therapeutic selection for patients in so-called “precision medicine.” However, there are challenges to obtaining adequate lung cancer tissue for molecular analyses. Furthermore, current molecular testing of tumors at the genomic or transcriptomic level are very indirect measures of biological response to a drug, particularly for small molecule inhibitors that target kinases. Kinase activity profiling is therefore theorized to be more reflective of invivo biology than many current molecular analysis techniques. As a result, this study seeks to prove the feasibility of combining a novel minimally invasive biopsy technique that expands the number of lesions amenable for biopsy with subsequent exvivo kinase activity analysis.

Methods

Eight patients with lung lesions of varying location and size were biopsied using the novel electromagnetic navigational bronchoscopy (ENB) technique. Basal kinase activity (kinomic) profiles and exvivo interrogation of samples in combination with tyrosine kinase inhibitors erlotinib, crizotinib, and lapatinib were performed by PamStation 12 microarray analysis.

Results

Kinomic profiling qualitatively identified patient specific kinase activity profiles as well as patient and drug specific changes in kinase activity profiles following exposure to inhibitor. Thus, the study has verified the feasibility of ENB as a method for obtaining tissue in adequate quantities for kinomic analysis and has demonstrated the possible use of this tissue acquisition and analysis technique as a method for future study of lung cancer biomarkers.

Conclusions

We demonstrate the feasibility of using ENB-derived biopsies to perform kinase activity assessment in lung cancer patients.

Biological network module-based model for the analysis of differential expression in shotgun proteomics

Protein differential expression analysis plays an important role in the understanding of molecular mechanisms as well as the pathogenesis of complex diseases. With the rapid development of mass spectrometry, shotgun proteomics using spectral counts has become a prevailing method for the quantitative analysis of complex protein mixtures. Existing methods in differential proteomics expression typically carry out analysis at the single-protein level. However, it is well-known that proteins interact with each other when they function in biological processes. In this study, focusing on biological network modules, we proposed a negative binomial generalized linear model for differential expression analysis of spectral count data in shotgun proteomics. In order to show the efficacy of the model in protein expression analysis at the level of protein modules, we conducted two simulation studies using synthetic data sets generated from theoretical distribution of count data and a real data set with shuffled counts. Then, we applied our method to a colorectal cancer data set and a nonsmall cell lung cancer data set. When compared with single-protein analysis methods, the results showed that module-based statistical model which takes account of the interactions among proteins led to more effective identification of subtle but coordinated changes at the systems level.

Proteomic profiles of human lung adeno and squamous cell carcinoma using super-SILAC and label-free quantification approaches

Nonsmall cell lung cancer (NSCLC) accounts for 85% of lung cancers, and is subdivided into two major histological subtypes: adenocarcinoma (ADC) and squamous cell carcinoma (SCC). There is an unmet need to further subdivide NSCLC according to distinctive molecular features that may be associated with responsiveness to therapies. Four primary tumor-derived xenograft proteomes (two-each ADC and SCC) were quantitatively compared by using a super-SILAC labeling approach together with ultrahigh-resolution MS. Proteins highly differentially expressed in the two subtypes were identified, including 30 that were validated in an independent cohort of 12 NSCLC primary tumor-derived xenograft tumors whose proteomes were quantified by an alternative, label-free shotgun MS methodology. The 30-protein signature contains metabolism enzymes including phosphoglycerate dehydrogenase, which is more highly expressed in SCC, as well as a comprehensive set of cytokeratins and other components of the epithelial barrier, which is therefore distinctly different between ADC and SCC. These results demonstrate the utility of the super-SILAC method for the characterization of primary tissues, and compatibility with datasets derived from different MS-based platforms. The validation of proteome signatures of NSCLC subtypes supports the further development and application of MS-based quantitative proteomics as a basis for precision classifications and treatments of tumors. All MS data have been deposited in the ProteomeXchange with identifier PXD000438 (http://proteomecentral.proteomexchange.org/dataset/PXD000438).