Genomic and Proteomic Profiling of Lung Cancers: Lung Cancer Classification in the Age of Targeted Therapy

Quantitative Multiplexed Proteomics Could Assist Therapeutic Decision Making in Non-Small Cell Lung Cancer Patients with Ambiguous ALK Test Results

Therapeutic guidance in non-small cell lung cancer (NSCLC) tumors that are positive for anaplastic lymphoma kinase (ALK) fluorescent in situ hybridization (FISH), but negative for ALK immunohistochemistry, is still challenging. Parallel routine screening of 4588 NSCLC cases identified 22 discordant cases. We rechecked these samples using ALK antibodies and selected reaction monitoring (SRM) quantitative multiplexed proteomics screening multiple protein targets, including ALK and MET for the ALK tyrosine kinase inhibitor (TKI), and FR-alpha, hENT1, RRM1, TUBB3, ERCC1, and XRCC1 for chemotherapy. The presence of ALK (31.8%), MET (36.4%), FR-alpha (72.7%), hENT1 (18.2%), RRM1 (31.8%), TUBB3 (72.9%), ERCC1 (4.5%), and a low level of XRCC1 (54.4%) correlated with clinical outcomes. SRM was more sensitive than the ALK D5F3 assay. Among the eight cases receiving ALK TKI, four cases with ALK or MET detected by SRM had complete or partial responses, whereas four cases without ALK or MET showed progression. Twenty-seven treatment outcomes from 20 cases were assessed and cases expressing more than half of the specific predictive proteins were sensitive to matching therapeutic agents and showed longer progression-free survival than the other cases (p < 0.001). SRM showed a potential role in therapeutic decision making in NSCLC patients with ambiguous ALK test results.

Cell-free nucleic acid patterns in disease prediction and monitoring-hype or hope?

Interest in the use of cell-free nucleic acids (CFNAs) as clinical non-invasive biomarker panels for prediction and prevention of multiple diseases has greatly increased over the last decade. Indeed, circulating CFNAs are attributable to many physiological and pathological processes such as imbalanced stress conditions, physical activities, extensive apoptosis of different origin, systemic hypoxic-ischemic events and tumour progression, amongst others. This article highlights the involvement of circulating CFNAs in local and systemic processes dealing with the question, whether specific patterns of CFNAs in blood, their detection, quantity and quality (such as their methylation status) might be instrumental to predict a disease development/progression and could be further utilised for accompanying diagnostics, targeted prevention, creation of individualised therapy algorithms, therapy monitoring and prognosis. Presented considerations conform with principles of 3P medicine and serve for improving individual outcomes and cost efficacy of medical services provided to the population.

OSluca: An Interactive Web Server to Evaluate Prognostic Biomarkers for Lung Cancer

Lung cancer is the principal cause of leading cancer-related incidence and mortality in the world. Various studies have excavated the potential prognostic biomarkers for cancer patients based on gene expression profiles. However, most of these reported biomarkers lack independent validation in multiple cohorts. Herein, we collected 35 datasets with long-term follow-up clinical information from TCGA (2 cohorts), GEO (32 cohorts), and Roepman study (1 cohort), and developed a web server named OSluca (Online consensus Survival for Lung Cancer) to assess the prognostic value of genes in lung cancer. The input of OSluca is an official gene symbol, and the output web page of OSluca displays the survival analysis summary with a forest plot and a survival table from Cox proportional regression in each cohort and combined cohorts. To test the performance of OSluca, 104 previously reported prognostic biomarkers in lung carcinoma were evaluated in OSluca. In conclusion, OSluca is a highly valuable and interactive prognostic web server for lung cancer. It can be accessed at http:// bioinfo.henu.edu.cn/LUCA/LUCAList.jsp.

MicroRNA, epigenetic machinery and lung cancer

Lung cancer is the leading cause of cancer deaths worldwide and over 80% of lung cancer patients are classified as having non-small cell lung cancer. Although there have been technological advancements in the early detection and standard treatment of lung cancer, it is often diagnosed at an advanced stage and is chemoresistant to most available drugs. A number of studies have demonstrated that microRNA is able to modulate various tumorigenic processes, including progression and metastasis, in various mechanisms. In this review we examine the most recent achievements in microRNA and lung cancer treatment and summarize the research progress on the reciprocal regulation between microRNA and epigenetic modifications, as both have been intensively studied in lung cancer. Epigenetic modifications on the human genome regulate gene and microRNA expression at the transcriptional level; inversely, microRNA can also transcriptionally cleave and/or translationally repress the expression of several key enzymes involved in epigenetic processes such as DNA methylation and histone modification. Better understanding of reciprocal regulation between microRNA and epigenetic modifications will underlie the development of novel microRNA orientated diagnostic and therapeutic strategies relating to lung cancer in the near future.

Gene identification for risk of relapse in stage I lung adenocarcinoma patients: a combined methodology of gene expression profiling and computational gene network analysis

Risk assessment and treatment choice remains a challenge in early non-small-cell lung cancer (NSCLC). The aim of this study was to identify novel genes involved in the risk of early relapse (ER) compared to no relapse (NR) in resected lung adenocarcinoma (AD) patients using a combination of high throughput technology and computational analysis. We identified 18 patients (n.13 NR and n.5 ER) with stage I AD. Frozen samples of patients in ER, NR and corresponding normal lung (NL) were subjected to Microarray technology and quantitative-PCR (Q-PCR). A gene network computational analysis was performed to select predictive genes. An independent set of 79 ADs stage I samples was used to validate selected genes by Q-PCR.From microarray analysis we selected 50 genes, using the fold change ratio of ER versus NR. They were validated both in pool and individually in patient samples (ER and NR) by Q-PCR. Fourteen increased and 25 decreased genes showed a concordance between two methods. They were used to perform a computational gene network analysis that identified 4 increased (HOXA10, CLCA2, AKR1B10, FABP3) and 6 decreased (SCGB1A1, PGC, TFF1, PSCA, SPRR1B and PRSS1) genes. Moreover, in an independent dataset of ADs samples, we showed that both high FABP3 expression and low SCGB1A1 expression was associated with a worse disease-free survival (DFS).Our results indicate that it is possible to define, through gene expression and computational analysis, a characteristic gene profiling of patients with an increased risk of relapse that may become a tool for patient selection for adjuvant therapy.

Identifying the miRNA signature associated with survival time in patients with lung adenocarcinoma using miRNA expression profiles

Lung adenocarcinoma is a multifactorial disease. MicroRNA (miRNA) expression profiles are extensively used for discovering potential theranostic biomarkers of lung cancer. This work proposes an optimized support vector regression (SVR) method called SVR-LUAD to simultaneously identify a set of miRNAs referred to the miRNA signature for estimating the survival time of lung adenocarcinoma patients using their miRNA expression profiles. SVR-LUAD uses an inheritable bi-objective combinatorial genetic algorithm to identify a small set of informative miRNAs cooperating with SVR by maximizing estimation accuracy. SVR-LUAD identified 18 out of 332 miRNAs using 10-fold cross-validation and achieved a correlation coefficient of 0.88 ± 0.01 and mean absolute error of 0.56 ± 0.03 year between real and estimated survival time. SVR-LUAD performs well compared to some well-recognized regression methods. The miRNA signature consists of the 18 miRNAs which strongly correlates with lung adenocarcinoma: hsa-let-7f-1, hsa-miR-16-1, hsa-miR-152, hsa-miR-217, hsa-miR-18a, hsa-miR-193b, hsa-miR-3136, hsa-let-7g, hsa-miR-155, hsa-miR-3199-1, hsa-miR-219-2, hsa-miR-1254, hsa-miR-1291, hsa-miR-192, hsa-miR-3653, hsa-miR-3934, hsa-miR-342, and hsa-miR-141. Gene ontology annotation and pathway analysis of the miRNA signature revealed its biological significance in cancer and cellular pathways. This miRNA signature could aid in the development of novel therapeutic approaches to the treatment of lung adenocarcinoma.

Effects of flavopiridol on critical regulation pathways of CD133high/CD44high lung cancer stem cells

BACKGROUND

Flavopiridol a semisynthetic flavone that inhibits cyclin-dependent kinases (CDKs) and has growth-inhibitory activity and induces a blockade of cell-cycle progression at G1-phase and apoptosis in numerous human tumor cell lines and is currently under investigation in phase II clinical trials. Cancer stem cells (CSCs) are comprised of subpopulation of cells in tumors that have been proposed to be responsible for recurrence and resistance to chemotherapy. The aim of the present study was to investigate the effects of flavopiridol in cancer stem cell cytoskeleton, cell adhesion, and epithelial to mesenchymal transition in CSCs.

METHODS

The cells were treated with flavopiridol to determine the inhibitory effect. Cell viability and proliferation were determined by using the WST-1 assay. Caspase activity and immunofluorescence analyses were performed for the evaluation of apoptosis, cell cytoskeleton, and epithelial-mesenchymal transition (EMT) markers. The effects of flavopiridol on the cell cycle were also evaluated. Flow cytometric analysis was used to detect the percentages of CSCs subpopulation. We analyzed the gene expression patterns to predict cell cycle and cell cytoskeleton in CSCs by RT-PCR.

RESULTS

Flavopiridol-induced cytotoxicity and apoptosis at the IC50 dose, resulting in a significant increase expression of caspases activity. Cell cycle analyses revealed that flavopiridol induces G1 phase cell cycle arrest. Flavopiridol significantly decreased the mRNA expressions of the genes that regulate the cell cytoskeleton and cell cycle components and cell motility in CSCs.

CONCLUSION

Our results suggest that Flavopiridol has activity against lung CSCs and may be effective chemotherapeutic molecule for lung cancer treatment.

lncRNA-SNHG7 promotes the proliferation, migration and invasion and inhibits apoptosis of lung cancer cells by enhancing the FAIM2 expression

There is growing evidence that long non-coding RNAs (lncRNAs) are related to cancer development. In the present study, we found that the expression levels of lncRNA-SNHG7 mRNA and protein obviously increased in lung cancer tissues compared to adjacent non-cancerous tissues. Simultaneously, the expression levels of Fas apoptotic inhibitory molecule 2 (FAIM2) also increased in lung cancer tissues. In addition, lncRNA-SNHG7 was of positive relevance with FAIM2 in human lung cancer tissues. Silence of lncRNA‑SNHG7 by siRNA repressed the level of FAIM2 protein and suppressed cell proliferation, migration and invasion and accelerated apoptosis of A594 cells in vitro. Furthermore, silence of FAIM2 by siRNA generated a phenotype similar to silence of lncRNA-SNHG7 by siRNA. Therefore, our research showed that lncRNA-SNHG7 promotes the proliferation, migration and invasion, and inhibits apoptosis of lung cancer cells by enhancing the FAIM2 expression, suggesting that lncRNA-SNHG7 as a key regulator of gene expression, may be a promising therapeutic strategy for the treatment of lung cancer. It may improve the understanding of their biogenesis and function of lung cancer and further provide the theoretical fundamental basis for cancer pathogenesis and treatment.

Clinical Significance of Long Non-Coding RNA CASC8 rs10505477 Polymorphism in Lung Cancer Susceptibility, Platinum-Based Chemotherapy Response, and Toxicity

Long non-coding RNA (lncRNA) CASC8 rs10505477 polymorphism has been identified to be related to risk of many kinds of cancers, such as colorectal cancer, gastric cancer, and invasive ovarian cancer, and it may be involved in the prognosis of gastric cancer patients who have received platinum-based chemotherapy after surgical treatment. So far, there is no study investigating the clinical significance of lncRNA CASC8 rs10505477 in lung cancer susceptibility and treatment. In this study, we genotyped 498 lung cancer patients and 213 healthy control subjects to explore the correlation between the rs10505477 polymorphism and lung cancer risk in a Chinese population. Among the 498 patients, 467 were selected for the chemotherapy response and toxicity study. We found that the single nucleotide polymorphisms (SNP) rs10505477 was greatly related to lung cancer risk in male and adenocarcinoma subgroups in recessive model (adjusted OR = 0.51, 95%CI = 0.29–0.90, p = 0.02; adjusted OR = 0.52, 95%CI = 0.30–0.89, p = 0.02, respectively). It was also closely correlated with platinum-based chemotherapy response in dominant model (adjusted OR = 1.58, 95%CI = 1.05–2.39, p = 0.03). Additionally, we observed that CASC8 rs10505477 polymorphism was significantly relevant to severe hematologic toxicity in non-small-cell lung cancer (NSCLC) subgroup in dominant model (adjusted OR = 0.59, 95%CI = 0.35–0.98, p = 0.04) and in additive model (adjusted OR = 0.62, 95%CI = 0.43–0.90, p = 0.01). Furthermore, it was found that rs10505477 polymorphism was greatly associated with gastrointestinal toxicity in SCLC and cisplatin subgroups in dominant model (adjusted OR = 7.82, 95%CI = 1.36–45.07, p = 0.02; adjusted OR = 1.94, 95%CI = 1.07–3.53, p = 0.03, respectively). Thus, lncRNA CASC8 rs10505477 could serve as a possible risk marker for diagnosing lung cancer, and could be used to forecast the response and toxicity of platinum-based treatment in lung cancer patients.

The clonal evolution and therapeutic approaches of lung cancer

According to the World Cancer Research Foundation, the newly diagnosed annual lung cancer cases all over the world are alarmingly high at 12.5 %. It also shows the highest mortality rate among all the cancer types. Nearly 225,000 new lung cancer patients are reported annually in the USA. The lung cancer cells also have very fast growth rates. As a result of this rapid proliferation rate, the lung cancer cells are sensitive to the available therapeutics like the radiation, surgical, or chemo therapy. Notwithstanding all the advances in the field of tumor biology, the mortality rate with lung cancer has remained significantly high. Precise and early diagnosis of the disease can be an important step in the proper and successful setting up of the treatment modalities. There are no comprehensive reviews available that discusses all the basic and updated aspects of lung cancer. This review focuses on the basic aspects of lung cancer like the etiology, risk factors, and clonal evolution. Exposure to smoking comes up as a single major environmental cause of the disease. The classification of lung cancer has also been discussed in detail based on immunohistochemistry. The existing therapeutic approaches as well as the upcoming modern day interventions have been discussed with their pros and cons. Recent techniques like molecular profiling can prove to be highly beneficial if properly standardized. With such advancements in therapy in conjunction with the updated diagnostics, there is a real hope in the treatment of lung cancer.

Pulmonary squamous cell carcinoma and sorafenib

KEY CLINICAL MESSAGE

Pulmonary squamous cell carcinomas are not often thought to sensitive to targeted agents, like their cousin the adenocarcinoma of the lung. With appropriate testing of molecular markers, squamous cell carcinomas, like adenocarcinomas of the lung, melanomas, and renal cell carcinomas, may be found to be sensitive to newer, targeted agents.

miR-150 promotes the proliferation of lung cancer cells by targeting P53

Lung cancer is one of the most common causes for cancer-related death. Previous studies suggested that uncontrolled cell proliferation induced by activation of pro-cancer genes or inhibition of cancer suppressor genes plays an important role in the pathogenesis of lung cancer. Here, we demonstrate that miR-150 is aberrantly upregulated in lung cancer tissue and negatively correlates with the expression of the proapoptotic gene p53 but not EGR2. We show that miR-150 specifically targets the 3'-UTR of p53 and regulates its expression. Inhibition of miR-150 effectively delays cell proliferation and promotes apoptosis, accompanied by increased p53 protein expression. Our data reveals the mechanisms underlying miR-150 regulated lung cancer pathogenesis, which might be beneficial for lung cancer therapy.

Effects of common polymorphism rs11614913 in Hsa-miR-196a2 on lung cancer risk

Background

Emerging evidence suggests that single nucleotide polymorphisms (SNPs) in microRNA-coding genes may participate in the pathogenesis of lung cancer by altering the expression of tumor-related microRNAs. Several studies were investigated in recent years to evaluate the association between hsa-miR-196a2 rs11614913 polymorphism and increased/decreased lung cancer risk. In the present study, we performed a meta-analysis to systematically summarize the possible association.

Methodology/Principal Findings

We performed a meta-analysis of 4 case-control studies that included 2219 lung-cancer cases and 2232 cancer-free controls. We evaluated the strength of the association using odds ratios (ORs) with 95% confidence intervals (CIs). In the overall analysis, it was found that the rs11614913 polymorphism significantly elevated the risk of lung cancer (CC versus (vs.) TT OR = 1.26, 95% CI 1.07–1.49, P = 0.007; CC/CT vs. TT: OR = 1.13, 95% CI 0.98–1.29, P = 0.007; C vs. T: OR = 1.12, 95% CI 1.03–1.22, P = 0.008). In the subgroup analysis by ethnicity, statistically significantly increased cancer risk was found among Asians (CC vs. TT: OR = 1.30, 95% CI 1.10–1.54, P = 0.003; CT vs. TT: OR = 1.16, 95% CI 1.01–1.34, P = 0.039; CC vs. CT/TT: OR = 1.21, 95% CI 1.04–1.41, P = 0.012; C vs. T: OR = 1.14, 95% CI 1.05–1.25, P = 0.002). For Europeans, a significant association with lung cancer risk was found in recessive model (CC vs. CT/TT: OR = 0.63, 95% CI 0.40–0.98, P = 0.040). No publication bias was found in this study.

Conclusions/Significance

Our meta-analysis suggests that the rs11614913 polymorphism is significant associated with the increased risk of lung cancer, especially in Asians. Besides, the C allele of rs11614913 polymorphism may contribute to increased lung cancer risk.

Gene expression profiling and molecular pathway analysis for the identification of early-stage lung adenocarcinoma patients at risk for early recurrence

Clinicohistopathological staging is insufficient to predict disease progression and clinical outcome in lung carcinoma. Based on the results of the principal component analysis of 24 samples of early-stage lung adenocarcinoma, two subgroups were identified within the early-relapse group. The histological classification of all samples of group A was poorly differentiated, whereas one out of three in group B was poorly differentiated. DAVID functional annotation analysis revealed that the molecular pathways enriched in group A included those associated with cell adhesion molecules (CAMs), cell cycle and antigen processing and presentation, whereas those in group B included CAMs, T cell receptor signaling, cytokine-cytokine receptor interaction, toll-like receptor signaling, chemokine signaling, primary immunodeficiency and natural killer cell-mediated cytotoxicity. The CAM pathway was enriched in both groups. This comprehensive gene expression and functional pathway analysis identified a distinct molecular pathway, CAMs, that correlated with the early relapse of patients with early-stage lung adenocarcinoma.

Biomarkers and molecular testing for early detection, diagnosis, and therapeutic prediction of lung cancer

The search for biomarkers in the management of lung cancer involves the use of multiple platforms to examine changes in gene, protein, and microRNA expression. Multiple studies have been published in an attempt to describe early detection, diagnostic, prognostic, and predictive biomarkers using chiefly tissues and blood elements. Studies are characterized by a lack of commonality of specific biomarkers, and a lack of validated, clinically useful markers. The future of biomarker discovery as a means of tailoring therapy for patients with lung cancer will involve next-generation sequencing along with collaborative efforts to integrate and validate candidate markers.

Measuring molecular biomarkers in epidemiologic studies: laboratory techniques and biospecimen considerations

The future of personalized medicine depends on the ability to efficiently and rapidly elucidate a reliable set of disease-specific molecular biomarkers. High-throughput molecular biomarker analysis methods have been developed to identify disease risk, diagnostic, prognostic, and therapeutic targets in human clinical samples. Currently, high throughput screening allows us to analyze thousands of markers from one sample or one marker from thousands of samples and will eventually allow us to analyze thousands of markers from thousands of samples. Unfortunately, the inherent nature of current high throughput methodologies, clinical specimens, and cost of analysis is often prohibitive for extensive high throughput biomarker analysis. This review summarizes the current state of high throughput biomarker screening of clinical specimens applicable to genetic epidemiology and longitudinal population-based studies with a focus on considerations related to biospecimens, laboratory techniques, and sample pooling.

An immunohistochemical analysis-based decision tree model for estimating the risk of lymphatic metastasis in pN0 squamous cell carcinomas of the lung

AIMS

Lung cancer patients within the pN0 category have a significantly different outcome. The aim of this study was to develop a mathematical model to assist in predicting the prognosis of pN0 lung squamous cell carcinoma (SCC).

METHODS AND RESULTS

Twenty-three proteins were examined by immunohistochemical (IHC) analysis on primary tumour tissues from 319 lung SCC patients. In a training group, using IHC data, a recursive partitioning decision tree (RP-DT) was used to build a model for estimating the risk for lymphatic metastasis. This model was then validated in a test cohort. Of 23 proteins, 8 (matrix metallopeptidase 1, metalloproteinase inhibitor 1, Ras GTPase-activating-like protein IQGAP1, targeting protein for Xklp2, urokinase-type plasminogen activator, cathepsin D, fascin, polymeric immunoglobulin receptor/secretory component) were selected, and generated a tree model in a training group of 255 patients to classify them as at high or low risk of lymphatic invasion, with accuracy of 78.0% (compared to histopathological diagnosis), sensitivity of 83.0% and specificity of 70.3%. When the tree model was applied to the test group, the accuracy, sensitivity and specificity were 76.6%, 76.0% and 76.9%, respectively. The performance of this mathematical model was substantiated further in 34 'problematic' stage I/pN0 patients by survival analysis.

CONCLUSIONS

The RP-DT model, constructed with eight protein markers for estimating lymphatic metastasis risk in pN0 lung SCC, is clinically feasible and practical, using IHC data from the primary tumour.

Cigarette-Smoke-Induced Dysregulation of MicroRNA Expression and Its Role in Lung Carcinogenesis

Dysregulation of microRNAs (miRNAs), particularly their downregulation, has been widely shown to be associated with the development of lung cancer. Downregulation of miRNAs leads to the overactivation of their oncogene targets, while upregulation of some miRNAs leads to inhibition of important tumor suppressors. Research has implicated cigarette smoke in miRNA dysregulation, leading to carcinogenesis. Cigarette smoke may lead to genetic or epigenetic damage to miRNAs, many of which map to fragile sites and some of which contain single nucleotide polymorphisms. Cigarette smoke may also cause dysregulation by affecting regulatory mechanisms controlling miRNA expression. Researchers have shown a correlation between smoke-exposure-induced dysregulation of miRNAs and age. Furthermore, dysregulation seems to be associated with intensity and duration of smoke exposure and duration of cessation. Longer exposure at a threshold level is needed for irreversibility of changes in expression. Better understanding of miRNA dysregulation may allow for improved biomonitoring and treatment regimens for lung cancer.

Identification of genes upregulated in ALK-positive and EGFR/KRAS/ALK-negative lung adenocarcinomas

Activation of the EGFR, KRAS, and ALK oncogenes defines 3 different pathways of molecular pathogenesis in lung adenocarcinoma. However, many tumors lack activation of any pathway (triple-negative lung adenocarcinomas) posing a challenge for prognosis and treatment. Here, we report an extensive genome-wide expression profiling of 226 primary human stage I-II lung adenocarcinomas that elucidates molecular characteristics of tumors that harbor ALK mutations or that lack EGFR, KRAS, and ALK mutations, that is, triple-negative adenocarcinomas. One hundred and seventy-four genes were selected as being upregulated specifically in 79 lung adenocarcinomas without EGFR and KRAS mutations. Unsupervised clustering using a 174-gene signature, including ALK itself, classified these 2 groups of tumors into ALK-positive cases and 2 distinct groups of triple-negative cases (groups A and B). Notably, group A triple-negative cases had a worse prognosis for relapse and death, compared with cases with EGFR, KRAS, or ALK mutations or group B triple-negative cases. In ALK-positive tumors, 30 genes, including ALK and GRIN2A, were commonly overexpressed, whereas in group A triple-negative cases, 9 genes were commonly overexpressed, including a candidate diagnostic/therapeutic target DEPDC1, that were determined to be critical for predicting a worse prognosis. Our findings are important because they provide a molecular basis of ALK-positive lung adenocarcinomas and triple-negative lung adenocarcinomas and further stratify more or less aggressive subgroups of triple-negative lung ADC, possibly helping identify patients who may gain the most benefit from adjuvant chemotherapy after surgical resection.

Bronchoscopic microsampling is a useful complementary diagnostic tool for detecting lung cancer

PURPOSE

Bronchoscopic microsampling (BMS) is a novel and direct method with which to obtain epithelial lining fluid (ELF) from the lungs. Analysis of DNA hypermethylation of tumor suppressor genes (TSGs) is expected to be a sensitive tool for the early detection of lung cancer. It has been reported that the existence of EGFR mutations and EML4-ALK gene rearrangements are related to the sensitivity of corresponding kinase inhibitors. We aimed to evaluate the suitability of ELF as a sample for analyzing molecular changes specific for lung cancer.

PATIENTS AND METHODS

We collected ELF from 61 lung cancer patients by BMS from the airway close to the peripheral lung nodule and purified the nucleic acids. We performed methylation specific PCR in each ELF as well as matched serum and tumor tissue for TSGs for DNA methylation analysis. We also examined EGFR mutations and EML4-ALK rearrangement.

RESULTS

The sensitivity for detecting DNA hypermethylation in ELF vs serum was 74.1% vs 18.5%. We found 60.1% of patients had at least one hypermethylation in ELF, while only 27.9% had it in serum. Of note, DNA hypermethylation was detected even in stage I patients (60.0%) and the detection rate was almost the same level in each stage. We also found the sensitivity for detecting EGFR mutation in ELF vs serum was 58.3% vs 8.3%. We detected an EML4-ALK fusion gene using ELF in one patient.

CONCLUSIONS

BMS is an alternative method to detect cancer specific genetic and epigenetic alterations and will be a useful complementary diagnostic tool for lung cancer.

SUMMARY

Investigation of genetic and epigenetic changes associated with lung cancer has clinical importance for its diagnosis and management. The clinical usefulness of bronchoscopic microsampling (BMS) in lung cancer has not yet been evaluated. This study demonstrates that BMS could be useful for detecting lung cancer specific molecular changes and valuable for early diagnosis and determination of treatment options for lung cancer.

Resection of non-small cell lung cancers reverses tumor-induced gene expression changes in the peripheral immune system

PURPOSE

To characterize the interactions of non-small cell lung cancer (NSCLC) tumors with the immune system at the level of mRNA and microRNA (miRNA) expression and to define expression signatures that characterize the presence of a malignant tumor versus a nonmalignant nodule.

EXPERIMENTAL DESIGN

We have examined the changes of both mRNA and miRNA expression levels in peripheral blood mononuclear cells (PBMC) between paired samples collected from NSCLC patients before and after tumor removal using Illumina gene expression arrays.

RESULTS

We found that malignant tumor removal significantly changes expression of more than 3,000 protein-coding genes, especially genes in pathways associated with suppression of the innate immune response, including natural killer cell signaling and apoptosis-associated ceramide signaling. Binding sites for the ETS domain transcription factors ELK1, ELK4, and SPI1 were enriched in promoter regions of genes upregulated in the presence of a tumor. Additional important regulators included five miRNAs expressed at significantly higher levels before tumor removal. Repressed protein-coding targets of those miRNAs included many transcription factors, several involved in immunologically important pathways. Although there was a significant overlap in the effects of malignant tumors and benign lung nodules on PBMC gene expression, we identified one gene panel which indicates a tumor or nodule presence and a second panel that can distinguish malignant from nonmalignant nodules.

CONCLUSIONS

A tumor presence in the lung influences mRNA and miRNA expression in PBMC and this influence is reversed by tumor removal. These results suggest that PBMC gene expression signatures could be used for lung cancer diagnosis.

Novel strategies for the treatment of small-cell lung carcinoma

Small-cell lung cancer (SCLC) is a disease with a poor prognosis and limited treatment options. Over the past 30 years, basic and clinical research have translated to little innovation in the treatment of this disease. The Study of Picoplatin Efficacy After Relapse (SPEAR) evaluated best supportive care with or without picoplatin for second-line SCLC treatment and failed to meet its primary end point of overall survival. As the largest second-line, randomized study in patients with SCLC, SPEAR provides an opportunity to critically examine the drug development model in this disease. In this Review, we discuss the current standard approach for the management of SCLC that progresses after first-line therapy, analyze the preliminary data that supported the evaluation of picoplatin in this setting, and critically evaluate the SPEAR trial design and results. Lastly, we present advances in the understanding of the molecular biology of SCLC that could potentially inform future clinical trials and hopefully lead to the successful development of molecular targeted agents for the treatment of this disease.

Dietary D-glucarate effects on the biomarkers of inflammation during early post-initiation stages of benzo[a]pyrene-induced lung tumorigenesis in A/J mice

Previous studies showed that dietary calcium D-glucarate (CG) inhibited benzo[a]pyrene (B[a]P)-induced A/J mouse lung tumorigenesis, suppressing cell proliferation and chronic inflammation and inducing apoptosis during late post-initiation stages. The present study aimed to investigate changes in the homeostasis of cytokines in blood serum, as well as alterations in biomarkers of inflammation and apoptosis in lung tissue caused by dietary CG during early post-initiation stages of B[a]P-induced lung tumorigenesis. Two doses of 3 mg of B[a]P were given intragastrically to A/J mice 2 weeks apart. CG administration in the AIN-93G diet (2 and 4%, w/w) commenced at 2 weeks following the second dose of B[a]P. The levels of interleukin (IL)-6, IL-10 and tumor necrosis factor α (TNFα) in blood serum were investigated by FCAP array analysis. Two weeks after the second dose of B[a]P, approximately 8- and 28-fold increases of TNFα and IL-6, respectively, occurred in the blood serum and an approximately 16% decrease of IL-10 levels compared to the untreated control group was noted. At 4 weeks after the second dose of B[a]P and after 2 weeks of CG administration in the diet, the 2 and 4% CG diets significantly reduced the levels of IL-6 and TNFα (by 70 and 33%, respectively). In a dose-related manner, the diets also increased the level of anti-inflammatory cytokine IL-10 compared to the B[a]P group. At 6 weeks after the second dose of B[a]P, the cytokine levels in the serum continued to show a decrease in the CG-treated groups. These events are accompanied by an increased level of cleaved caspase-9 product with a molecular weight of 37 kDa. In conclusion, dietary D-glucarate decreases the level of proinflammatory cytokines, increases the level of the anti-inflammatory cytokine IL-10 during early post-initiation stages of B[a]P-induced lung tumorigenesis in A/J mice and affects apoptotic induction.

A Gprc5a tumor suppressor loss of expression signature is conserved, prevalent, and associated with survival in human lung adenocarcinomas

Increasing the understanding of the impact of changes in oncogenes and tumor suppressor genes is essential for improving the management of lung cancer. Recently, we identified a new mouse lung-specific tumor suppressor-the G protein-coupled receptor 5A (Gprc5a). Microarray analysis of the transcriptomes of lung epithelial cells cultured from normal tracheas of Gprc5a knockout and wild-type mice defined a loss-of-Gprc5a gene signature, which revealed many aberrations in cancer-associated pathways. To assess the relevance of this mouse tumor suppressor to human lung cancer, the loss-of-Gprc5a signature was cross species compared with and integrated with publicly available gene expression data of human normal lung tissue and non-small cell lung cancers. The loss-of-Gprc5a signature was prevalent in human lung adenocarcinomas compared with squamous cell carcinomas or normal lung. Furthermore, it identified subsets of lung adenocarcinomas with poor outcome. These results demonstrate that gene expression patterns of Gprc5a loss in nontumorigenic mouse lung epithelial cells are evolutionarily conserved and important in human lung adenocarcinomas.

Peptidic tumor targeting agents: the road from phage display peptide selections to clinical applications

Cancer has become the number one cause of death amongst Americans, killing approximately 1,600 people per day. Novel methods for early detection and the development of effective treatments are an eminent priority in medicine. For this reason, isolation of tumor-specific ligands is a growing area of research. Tumor-specific binding agents can be used to probe the tumor cell surface phenotype and to customize treatment accordingly by conjugating the appropriate cell-targeting ligand to an anticancer drug. This refines the molecular diagnosis of the tumor and creates guided drugs that can target the tumor while sparing healthy tissues. Additionally, these targeting agents can be used as in vivo imaging agents that allow for earlier detection of tumors and micrometastasis. Phage display is a powerful technique for the isolation of peptides that bind to a particular target with high affinity and specificity. The biopanning of intact cancer cells or tumors in animals can be used as the bait to isolate peptides that bind to cancer-specific cell surface biomarkers. Over the past 10 years, unbiased biopanning of phage-displayed peptide libraries has generated a suite of cancer targeting peptidic ligands. This review discusses the recent advances in the isolation of cancer-targeting peptides by unbiased biopanning methods and highlights the use of the isolated peptides in clinical applications.

Understanding prognostic gene expression signatures in lung cancer

In non-small-cell lung cancer (NSCLC), molecular profiling of tumors has led to the identification of gene expression patterns that are associated with specific phenotypes and prognosis. Such correlations could identify early-stage patients who are at increased risk of disease recurrence and death after complete surgical resection and who might benefit from adjuvant therapy. Profiling may also identify aberrant molecular pathways that might lead to specific molecularly targeted therapies. The technology behind the capturing and correlating of molecular profiles with clinical and biologic endpoints have evolved rapidly since microarrays were first developed a decade ago. In this review, we discuss multiple methods that have been used to derive prognostic gene expression signatures in NSCLC. Despite the diversity in the approaches used, 3 main steps are followed. First, the expression levels of several hundred to tens of thousands of genes are quantified by microarray or quantitative polymerase chain reaction techniques; the data are then preprocessed, normalized, and possibly filtered. In the second step, expression data are combined and grouped by clustering, risk score generation, or other means, to generate a gene signature that correlates with a clinical outcome, usually survival. Finally, the signature is validated in datasets of independent cohorts. This review discusses the concepts and methodologies involved in these analytical steps, primarily to facilitate the understanding of reports on large dataset gene expression studies that focus on prognostic signatures in NSCLC.

MALDI profiling of human lung cancer subtypes

BACKGROUND

Proteomics is expected to play a key role in cancer biomarker discovery. Although it has become feasible to rapidly analyze proteins from crude cell extracts using mass spectrometry, complex sample composition hampers this type of measurement. Therefore, for effective proteome analysis, it becomes critical to enrich samples for the analytes of interest. Despite that one-third of the proteins in eukaryotic cells are thought to be phosphorylated at some point in their life cycle, only a low percentage of intracellular proteins is phosphorylated at a given time.

METHODOLOGY/PRINCIPAL FINDINGS

In this work, we have applied chromatographic phosphopeptide enrichment techniques to reduce the complexity of human clinical samples. A novel method for high-throughput peptide profiling of human tumor samples, using Parallel IMAC and MALDI-TOF MS, is described. We have applied this methodology to analyze human normal and cancer lung samples in the search for new biomarkers. Using a highly reproducible spectral processing algorithm to produce peptide mass profiles with minimal variability across the samples, lineal discriminant-based and decision tree-based classification models were generated. These models can distinguish normal from tumor samples, as well as differentiate the various non-small cell lung cancer histological subtypes.

CONCLUSIONS/SIGNIFICANCE

A novel, optimized sample preparation method and a careful data acquisition strategy is described for high-throughput peptide profiling of small amounts of human normal lung and lung cancer samples. We show that the appropriate combination of peptide expression values is able to discriminate normal lung from non-small cell lung cancer samples and among different histological subtypes. Our study does emphasize the great potential of proteomics in the molecular characterization of cancer.

MicroRNAs in the pathogenesis of Lung Cancer

Lung cancer is the leading cause of cancer related deaths in the United States. It is estimated that in 2008 there were 215,000 new diagnoses of lung cancer and 163,000 deaths. Despite emerging technologies for potential early diagnosis and discovery of novel targeted therapies, the overall 5-year survival remains a disappointing 15%. Explanations for the poor survival include late presentation of disease, a lack of markers for early detection, and both phenotypic and genotypic heterogeneity within patients of similar histologic classification. To further understand this heterogeneity and thus complexity of lung cancer, investigators have applied various technologies including high throughput analysis of both the genome and proteome. Such approaches have been successful in identifying signatures that may clarify molecular differences in tumors, identify new targets, and improve prognostication. In the last decade, investigators have identified a new mode of gene regulation in the form of noncoding RNAs termed microRNAs (miRNAs or miRs). First determined to be of importance in larval development, microRNAs are approximately 19-22 nucleotide single stranded RNAs that regulate genes by either inducing mRNA degradation or inhibiting translation. MiRNAs have been implicated in several cellular processes including apoptosis, development, proliferation, and differentiation. By regulating hundreds of genes simultaneously, miRNAs have the capacity for regulation of biologic networks. Global alterations in miRNA expression in both solid organ and hematological malignancies suggest their importance in the pathogenesis of disease. To date, both in vivo and in vitro studies in lung cancer demonstrate a dysregulation of miRNA expression. Furthermore, investigators are beginning to identify individual targets and pathways of miRNAs relevant to lung tumorigenesis. Thus, miRNAs may identify critical targets and be important in the pathogenesis of lung cancer.

Screening and identification of a peptide specifically targeted to NCI-H1299 from a phage display peptide library

In this study, a NCI-H1299 (Non-Small Cell Lung Cancer, NSCLC) and a normal lung cell line (Small Airway Epithelial Cells, SAEC) were used for the subtractive screening in vitro with a phage display-12 peptide library. After three rounds of panning, there was an obvious enrichment for the phages specifically binding to the NCI-H1299 cells, and the output/input ratio of phages increased about 875-fold (from 0.4x10(4) to 3.5x10(6)). A group of peptides being capable of binding specifically to the NCI-H1299 cells were obtained, and the affinity of these peptides to bind to the targeted cells and tissues was studied. Through a cell-based ELISA, immunocytochemical staining, immunohistochemical staining, and immunofluorescence, a M13 phage isolated and identified from the above screenings, and a synthetic peptide ZS-1 (sequence EHMALTYPFRPP) corresponded to the sequence of the surface protein of the M13 phage were demonstrated to be capable of binding to the tumor cell surfaces of NCI-H1299 and A549 cell lines and biopsy specimens, but not to normal lungs tissue samples, other different cancer cells, or nontumor surrounding lung tissues. In conclusion, the peptide ZS-1 may be a potential candidate of biomarker ligands used for targeted drug delivery in therapy of lung cancer.

A functional genetic variant in microRNA-196a2 is associated with increased susceptibility of lung cancer in Chinese

microRNAs (miRNA) are a new class of non-protein-coding, small RNAs that function as tumor suppressors or oncogenes. They participate in diverse biological pathways and function as gene regulators. Recently, we conducted a survey of common single nucleotide polymorphisms (SNP) in miRNA sequences and reported that, among four SNPs (rs2910164, rs2292832, rs11614913, and rs3746444) in pre-miRNAs, rs11614913 in miR-196a2 might affect mature miR-196a expression and target mRNA-binding activity and was significantly associated with non-small cell lung cancer survival. However, it remains largely unknown whether miRNA SNPs may alter lung cancer susceptibility. In the current study, we evaluated associations between the above four SNPs in pre-miRNAs and lung cancer susceptibility in a case-control study of 1,058 incident lung cancer patients and 1,035 cancer-free controls in a Chinese population. We found that miR-196a2 rs11614913 variant homozygote CC was associated with approximately 25% significantly increased risk of lung cancer compared with their wild-type homozygote TT and heterozygote TC (odds ratio, 1.25; 95% confidence interval, 1.01-1.54). However, no significant effects were observed on the association between the other three SNPs and lung cancer risk. These findings suggest that functional SNP rs11614913 in miR-196a2 could also contribute to lung cancer susceptibility.

MicroRNAs: novel biomarkers for human cancer

BACKGROUND

MicroRNAs (miRNAs), small RNA molecules of approximately 22 nucleotides, have been shown to be up- or downregulated in specific cell types and disease states. These molecules have become recognized as one of the major regulatory gatekeepers of coding genes in the human genome.

CONTENT

We review the structure, nomenclature, mechanism of action, technologies used for miRNA detection, and associations of miRNAs with human cancer. miRNAs are produced in a tissue-specific manner, and changes in miRNA within a tissue type can be correlated with disease status. miRNAs appear to regulate mRNA translation and degradation via mechanisms that are dependent on the degree of complementarity between the miRNA and mRNA molecules. miRNAs can be detected via several methods, such as microarrays, bead-based arrays, and quantitative real-time PCR. The tissue concentrations of specific miRNAs have been associated with tumor invasiveness, metastatic potential, and other clinical characteristics for several types of cancers, including chronic lymphocytic leukemia, and breast, colorectal, hepatic, lung, pancreatic, and prostate cancers.

SUMMARY

By targeting and controlling the expression of mRNA, miRNAs can control highly complex signal-transduction pathways and other biological pathways. The biologic roles of miRNAs in cancer suggest a correlation with prognosis and therapeutic outcome. Further investigation of these roles may lead to new approaches for the categorization, diagnosis, and treatment of human cancers.

Conventional and Proteomic Technologies for the Detection of Early Stage Malignancies: Markers for Ovarian Cancer

Our understanding of the tumor microenvironment continues to evolve and allows for the identification of biomarkers that should detect the presence of early stage malignancies. Recent advances in computational analysis and biomedical technologies have come together to elucidate signatures associated with cancer and that are capable of identifying unique tumor-specific proteins. Within the tumor microenvironment, we continue to characterize the proteophysiology of the different steps associated with tumor progression. The urgent need for biomarkers accurately detecting early-stage epithelial ovarian cancer has prompted us, and others, to engage in a search for specific peptide signatures that may discriminate transformed cells from those of the normal ovarian microenvironment. This endeavor also provides new insights into the biology of the disease, which may not only be applicable to detection but may also help to initiate new therapies and optimize patient care.

Advances in genomic and proteomic studies of non-small-cell lung cancer: clinical and translational research perspective

Recent years have brought tremendous progress in the development of genomic and proteomic platforms to study cancer biology. Tests based on these platforms are helpful in early diagnosis, prognosis, and prediction of treatment benefit. Molecular studies performed on minimally invasive material (plasma, sputum) from individuals participating in longitudinal or case-control studies have approximately 70%-90% sensitivity and specificity to detect lung cancer. In operable non-small-cell lung cancer, genomic and proteomic studies yield better prognostic information than pathologic staging. There are several examples of successful identification of predictive assays for benefit from chemotherapy (ERCC1, RRM1, p27Kip1, and p53 expression) or targeted therapies (epidermal growth factor receptor [EGFR] gene copy number, EGFR activating mutations, EGFR protein expression, serum proteomic profile). These markers should be prospectively tested in clinical studies before they can be routinely used in the clinic.

Linking molecular classification of hepatocellular carcinoma and personalized medicine: preliminary steps

PURPOSE OF REVIEW

The development of high-throughput technologies able to simultaneously investigate thousands of genes (e.g. single nucleotide polymorphism-array, gene expression microarray, etc.) has opened a new era in translational research. Obtaining a molecular classification of hepatocellular carcinoma, however, remains a striking challenge. This review summarizes the molecular classifications of hepatocellular carcinoma reported so far, analyzes the status of targeted therapies tested in clinical trials, and evaluates feasibility of personalized medicine approaches in hepatocellular carcinoma.

RECENT FINDINGS

Different investigators attempted to classify patients according to their liver cancer molecular background, a feature that will path the way for trial enrichment and personalized medicine. Currently, hepatocellular carcinoma can be classified in molecular classes according to Wnt-beta-catenin pathway activation, proliferation signature activation (associated with chromosomal instability), and other subgroups. In parallel, the first-time-ever positive results of a phase III trial in advanced hepatocellular carcinoma with the multikinase inhibitor sorafenib have encouraged this approach.

SUMMARY

Selection of patient candidates according to their tumor molecular background is a reality in human malignancies. Thus, a molecular classification is essential to allow the development of new targets, and to customize therapies in patients with hepatocellular carcinoma.

Quantum dot self-assembly for protein detection with sub-picomolar sensitivity

A novel approach to sensitive and rapid antigen detection is described. In the presence of a specific antigen, quantum dot-antibody conjugates rapidly self-assemble into agglomerates that are typically more than 1 order of magnitude larger than their individual components. The size distribution of the agglomerated colloids depends on, among other things, the relative concentration of quantum dot conjugates and antigen molecules. Quantum dot agglomerates mediated by antigen recognition were characterized by measuring their light scattering and fluorescence characteristics in an unmodified flow cytometer. Protein antigens angiopoietin-2 and mouse IgG were detected to sub-picomolar concentrations using this method. This simple technique enables the potential simultaneous detection of multiple antigenic biomarkers directly from physiological media and could be used for early detection and frequent screening of cancers and other diseases.

Proteomic profiling of endothelial cells in human lung cancer

Genomic and proteomic analysis of normal and diseased tissues have yielded an abundance of molecular information for diagnostic and potential therapeutic targets. Changing the target of analysis from poorly accessible cells within tissues to easily accessible vascular endothelium has theoretical advantages in tissue-specific targeting. In this study, we sought to map a large-scale proteome of microvascular endothelium in human non-small cell lung cancer (NSCLC) and normal lung tissues, and identify lung cancer-related endothelial cell (EC)-selective proteins. Endothelial cells were isolated within NSCLC tissues and adjacent-normal lung tissue of lung cancer patients by using CD31-immunomagnetic beads. The complex proteins from the ECs were separated by one-dimensional gel electrophoresis, and the proteins in each gel band were digested by trypsin. Peptides were separated by online reverse-phase liquid-chromatography and analyzed by electrospray ionization (ESI) ion trap tandem mass spectrometry. Approximately 600-1000 proteins were identified in each individual sample. Five patient cases of paired individual data, extracted from the protein identification data sets of both normal- and cancer-derived ECs, were analyzed by subtractive proteomics. An average of 300 proteins was specifically identified from each lung cancer-derived EC isolate, compared to normal lung-derived ECs. With the use of several comparative analyses, we identified among those 300 proteins, 16 common candidate proteins that were detected in at least 3 of 5 cases specific to lung cancer-derived ECs. Proteins selectively identified in cancer-derived ECs, including coatomer protein complex, subunit gamma (COPG), and peroxiredoxin 4 (PRDX4), were validated by Western blot analysis. In an additional experiment in which 16 cancer samples were analyzed by immunohistochemistry, PRDX4, thymopoietin (TMPO), and COPG were confirmed to be abundantly expressed in lung cancer-derived ECs and in cancerous lung cells. Further ongoing analysis of these 16 candidate proteins will determine their potential applicability to NSCLC-specific diagnosis and therapeutics.

Baseline results of the Depiscan study: A French randomized pilot trial of lung cancer screening comparing low dose CT scan (LDCT) and chest X-ray (CXR)

BACKGROUND

Lung cancer has the highest mortality-rate per cancer, with an overall 5-year survival <15%. Several non-randomized studies pointed out the high sensitivity of low dose computed tomography (LDCT) to detect early stage lung cancer. In France, Depiscan, a pilot RCT of LDCT versus chest X-ray (CXR), started on October 2002 to determine the feasibility of enrollment by general practitioners (GPs), investigations and diagnostic procedures by university hospital radiologists and multidisciplinary teams, data management by centralized clinical research assistants, and anticipate the future management of a large national trial.

METHODS

GPs and occupational physicians (OPs) selected and enrolled 1000 subjects in 1 year. Eligible subjects were asymptomatic males or females aged 50-75 years with a current or former cigarette smoking history of >/=15 cigarettes per day for at least 20 years (former smokers having quit <15 years prior to enrollment). Based to randomization, annual LDCT or CXR screenings were planned at baseline and annually for 2 years.

RESULTS

Between October 2002 and December 2004, 765 subjects were enrolled by 89 out of the 232 participating GPs and OPs. Complete clinical and imaging baseline data were available for 621 individuals out of the 765 enrolled, due to 144 noncompliant subjects who withdrew their consent. At least one nodule was detected in 152 out of 336 subjects (45.2%) in the LDCT screening, versus 21 out of 285 subjects (7.4%) in the CXR screening arm. Eight lung cancers were detected in the LDCT arm and one in the CXR arm.

DISCUSSION

This pilot trial allows estimating that non-calcified nodules are 10 [6.36-17.07] times more often detected from LDCT than from CXR. However enrollment by GPs was more difficult than expected with 41% active investigators and a high rate (19%) of noncompliant patients. This experience speaks to the need for a high level of GPs formation and a large, coordinated clinical research team in such a trial.

TRIAL REGISTRATION NUMBER

02526.

International comparisons of survival from lung cancer: pitfalls and warnings

Population-based survival data can provide valuable comparative data on outcome but should be interpreted with caution. Differences in data collection and analysis, patient and tumor characteristics and treatment options can have an impact on reported results. Ideally, data from the whole population, including clinical-only diagnoses, should be reported and the methods of case identification described. The relative survival rates should preferably be given. Data on patient characteristics such as age, sex, ethnicity and socioeconomic deprivation should be described, together with tumor details such as pathology and clinical stage. Whenever possible, details on the use of treatments should be reported.