ONECUT2 is a druggable driver of luminal to basal breast cancer plasticity.

PURPOSE: Tumor heterogeneity complicates patient treatment and can be due to transitioning of cancer cells across phenotypic cell states. This process is associated with the acquisition of independence from an oncogenic driver, such as the estrogen receptor (ER) in breast cancer (BC), resulting in tumor progression, therapeutic failure and metastatic spread. The transcription factor ONECUT2 (OC2) has been shown to be a master regulator protein of metastatic castration-resistant prostate cancer (mCRPC) tumors that promotes lineage plasticity to a drug-resistant neuroendocrine (NEPC) phenotype. Here, we investigate the role of OC2 in the dynamic conversion between different molecular subtypes in BC. METHODS: We analyze OC2 expression and clinical significance in BC using public databases and immunohistochemical staining. In vitro, we perform RNA-Seq, RT-qPCR and western-blot after OC2 enforced expression. We also assess cellular effects of OC2 silencing and inhibition with a drug-like small molecule in vitro and in vivo. RESULTS: OC2 is highly expressed in a substantial subset of hormone receptor negative human BC tumors and tamoxifen-resistant models, and is associated with poor clinical outcome, lymph node metastasis and heightened clinical stage. OC2 inhibits ER expression and activity, suppresses a gene expression program associated with luminal differentiation and activates a basal-like state at the gene expression level. We also show that OC2 is required for cell growth and survival in metastatic BC models and that it can be targeted with a small molecule inhibitor providing a novel therapeutic strategy for patients with OC2 active tumors. CONCLUSIONS: The transcription factor OC2 is a driver of BC heterogeneity and a potential drug target in distinct cell states within the breast tumors.

Epigenetic Regulation of microRNAs in Cancer: Shortening the Distance from Bench to Bedside.

Cancer is a complex disease involving alterations of multiple processes, with both genetic and epigenetic features contributing as core factors to the disease. In recent years, it has become evident that non-coding RNAs (ncRNAs), an epigenetic factor, play a key role in the initiation and progression of cancer. MicroRNAs, the most studied non-coding RNAs subtype, are key controllers in a myriad of cellular processes, including proliferation, differentiation, and apoptosis. Furthermore, the expression of miRNAs is controlled, concomitantly, by other epigenetic factors, such as DNA methylation and histone modifications, resulting in aberrant patterns of expression upon the occurrence of cancer. In this sense, aberrant miRNA landscape evaluation has emerged as a promising strategy for cancer management. In this review, we have focused on the regulation (biogenesis, processing, and dysregulation) of miRNAs and their role as modulators of the epigenetic machinery. We have also highlighted their potential clinical value, such as validated diagnostic and prognostic biomarkers, and their relevant role as chromatin modifiers in cancer therapy.

Methods for analysis of specific DNA methylation status.

Methylation of CpG dinucleotides plays a crucial role in the regulation of gene expression and therefore in the development of different pathologies. Aberrant methylation has been associated to the majority of the diseases, including cancer, neurodegenerative, cardiovascular and autoimmune disorders. Analysis of DNA methylation patterns is crucial to understand the underlying molecular mechanism of these diseases. Moreover, DNA methylation patterns could be used as biomarker for clinical management, such as diagnosis, prognosis and treatment response. Nowadays, a variety of high throughput methods for DNA methylation have been developed to analyze the methylation status of a high number of CpGs at once or even the whole genome. However, identification of specific methylation patterns at specific loci is essential for validation and also as a tool for diagnosis. In this review, we describe the most commonly used approaches to evaluate specific DNA methylation. There are three main groups of techniques that allow the identification of specific regions that are differentially methylated: bisulfite conversion-based methods, restriction enzyme-based approaches, and affinity enrichment-based assays. In the first group, specific restriction enzymes recognize and cleave unmethylated DNA, leaving methylated sequences intact. Bisulfite conversion methods are the most popular approach to distinguish methylated and unmethylated DNA. Unmethylated cytosines are deaminated to uracil by sodium bisulfite treatment, while the methyl cytosines remain unconverted. In the last group, proteins with methylation binding domains or antibodies against methyl cytosines are used to recognize methylated DNA. In this review, we provide the theoretical basis and the framework of each technique as well as the analysis of their strength and the weaknesses.

YES1 Drives Lung Cancer Growth and Progression and Predicts Sensitivity to Dasatinib.

Rationale: The characterization of new genetic alterations is essential to assign effective personalized therapies in non-small cell lung cancer (NSCLC). Furthermore, finding stratification biomarkers is essential for successful personalized therapies. Molecular alterations of YES1, a member of the SRC (proto-oncogene tyrosine-protein kinase Src) family kinases (SFKs), can be found in a significant subset of patients with lung cancer.Objectives: To evaluate YES1 (v-YES-1 Yamaguchi sarcoma viral oncogene homolog 1) genetic alteration as a therapeutic target and predictive biomarker of response to dasatinib in NSCLC.Methods: Functional significance was evaluated by in vivo models of NSCLC and metastasis and patient-derived xenografts. The efficacy of pharmacological and genetic (CRISPR [clustered regularly interspaced short palindromic repeats]/Cas9 [CRISPR-associated protein 9]) YES1 abrogation was also evaluated. In vitro functional assays for signaling, survival, and invasion were also performed. The association between YES1 alterations and prognosis was evaluated in clinical samples.Measurements and Main Results: We demonstrated that YES1 is essential for NSCLC carcinogenesis. Furthermore, YES1 overexpression induced metastatic spread in preclinical in vivo models. YES1 genetic depletion by CRISPR/Cas9 technology significantly reduced tumor growth and metastasis. YES1 effects were mainly driven by mTOR (mammalian target of rapamycin) signaling. Interestingly, cell lines and patient-derived xenograft models with YES1 gene amplifications presented a high sensitivity to dasatinib, an SFK inhibitor, pointing out YES1 status as a stratification biomarker for dasatinib response. Moreover, high YES1 protein expression was an independent predictor for poor prognosis in patients with lung cancer.Conclusions: YES1 is a promising therapeutic target in lung cancer. Our results provide support for the clinical evaluation of dasatinib treatment in a selected subset of patients using YES1 status as predictive biomarker for therapy.

5 protein-based signature for resectable lung squamous cell carcinoma improves the prognostic performance of the TNM staging.

INTRODUCTION: Prognostic biomarkers have been very elusive in the lung squamous cell carcinoma (SCC) and none is currently being used in the clinical setting. We aimed to identify and validate the clinical utility of a protein-based prognostic signature to stratify patients with early lung SCC according to their risk of recurrence or death. METHODS: Patients were staged following the new International Association for the Study of Lung Cancer (IASLC) staging criteria (eighth edition, 2018). Three independent retrospective cohorts of 117, 96 and 105 patients with lung SCC were analysed to develop and validate a prognostic signature based on immunohistochemistry for five proteins. RESULTS: We identified a five protein-based signature whose prognostic index (PI) was an independent and significant predictor of disease-free survival (DFS) (p<0.001; HR=4.06, 95% CI 2.18 to 7.56) and overall survival (OS) (p=0.004; HR=2.38, 95% CI 1.32 to 4.31). The prognostic capability of PI was confirmed in an external multi-institutional cohort for DFS (p=0.042; HR=2.01, 95% CI 1.03 to 3.94) and for OS (p=0.031; HR=2.29, 95% CI 1.08 to 4.86). Moreover, PI added complementary information to the newly established IASLC TNM 8th edition staging system. A combined prognostic model including both molecular and anatomical (TNM) criteria improved the risk stratification in both cohorts (p<0.05). CONCLUSION: We have identified and validated a clinically feasible protein-based prognostic model that complements the updated TNM system allowing more accurate risk stratification. This signature may be used as an advantageous tool to improve the clinical management of the patients, allowing the reduction of lung SCC mortality through a more accurate knowledge of the patient's potential outcome.

The oncogenic RNA-binding protein SRSF1 regulates LIG1 in non-small cell lung cancer.

In recent years, the relevance of RNA metabolism has been increasingly recognized in a variety of diseases. Modifications in the levels of RNA-binding proteins elicit changes in the expression of cancer-related genes. Here we evaluate whether SRSF1 regulates the expression of DNA repair genes, and whether this regulation has a relevant role in lung carcinogenesis. An in silico analysis was performed to evaluate the association between the expression of SRSF1 and DNA repair genes. In vitro functional analyses were conducted in SRSF1 or DNA ligase 1 (LIG1)-downregulated non-small cell lung cancer (NSCLC) cell lines. In addition, the prognostic value of LIG1 was evaluated in NSCLC patients by immunohistochemistry. We found a significant correlation between the DNA repair gene LIG1 and SRSF1 in NSCLC cell lines. Moreover, SRSF1 binds to LIG1 mRNA and regulates its expression by increasing its mRNA stability and enhancing its translation in an mTOR-dependent manner. Furthermore, siRNA-mediated LIG1 inhibition reduced proliferation and increased apoptosis of NSCLC cells. Finally, the expression of LIG1 was an independent prognostic factor for NSCLC, as confirmed in a series of 210 patients. These results show that LIG1 is regulated by the oncoprotein SRSF1 and plays a relevant role in lung cancer cell proliferation and progression. LIG1 is associated with poor prognosis in non-small lung cancer patients.

A novel protein-based prognostic signature improves risk stratification to guide clinical management in early-stage lung adenocarcinoma patients.

Each of the pathological stages (I-IIIa) of surgically resected non-small-cell lung cancer has hidden biological heterogeneity, manifested as heterogeneous outcomes within each stage. Thus, the finding of robust and precise molecular classifiers with which to assess individual patient risk is an unmet medical need. Here, we identified and validated the clinical utility of a new prognostic signature based on three proteins (BRCA1, QKI, and SLC2A1) to stratify early-stage lung adenocarcinoma patients according to their risk of recurrence or death. Patients were staged according to the new International Association for the Study of Lung Cancer (IASLC) staging criteria (8th edition, 2018). A test cohort (n = 239) was used to assess the value of this new prognostic index (PI) based on the three proteins. The prognostic signature was developed by Cox regression with the use of stringent statistical criteria (TRIPOD: Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis). The model resulted in a highly significant predictor of 5-year outcome for disease-free survival (p < 0.001) and overall survival (p < 0.001). The prognostic ability of the model was externally validated in an independent multi-institutional cohort of patients (n = 114, p = 0.021). We also demonstrated that this molecular classifier adds relevant information to the gold standard TNM-based pathological staging, with a highly significant improvement of the likelihood ratio. We subsequently developed a combined PI including both the molecular and the pathological data that improved the risk stratification in both cohorts (p ≤ 0.001). Moreover, the signature may help to select stage I-IIA patients who might benefit from adjuvant chemotherapy. In summary, this protein-based signature accurately identifies those patients with a high risk of recurrence and death, and adds further prognostic information to the TNM-based clinical staging, even when the new IASLC 8th edition staging criteria are applied. More importantly, it may be a valuable tool for selecting patients for adjuvant therapy. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Complement C4d-specific antibodies for the diagnosis of lung cancer.

Development of molecular markers that help to identify high-risk individuals or diagnose indeterminate pulmonary nodules could have a major impact on lung cancer clinical management. In this study, we evaluated the diagnostic potential of a newly-developed ELISA that specifically detects complement C4d. We measured this marker in five independent cohorts of plasma and bronchoalveolar lavage samples from lung cancer patients and controls. In case-control studies, the area under the ROC curve for the diagnosis of lung cancer was 0.82 (95%CI = 0.72-0.92) in plasma samples, and 0.80 (95%CI = 0.69 to 0.90) in bronchoalveolar lavage fluids. In a set of plasma samples from the MILD CT-screening trial, the assay was unable to discriminate between asymptomatic high-risk individuals with or without early stage lung cancer. On the contrary, in two independent cohorts of individuals with indeterminate pulmonary nodules, plasma samples from patients with lung cancer nodules presented higher levels of C4d than those from patients with benign nodules. Using a target population of patients with 8 to 30 mm nodules, the test identified likely benign lung nodules with 84% negative predictive value and 54% positive predictive value, at 89% specificity and 44% sensitivity. In conclusion, the specific determination of C4d may serve as an adjunct to current clinical practice in the diagnosis of indeterminate pulmonary nodules.

Blockade of the Complement C5a/C5aR1 Axis Impairs Lung Cancer Bone Metastasis by CXCL16-mediated Effects.

RATIONALE: C5aR1 (CD88), a receptor for complement anaphylatoxin C5a, is a potent immune mediator. Its impact on malignant growth and dissemination of non-small cell lung cancer cells is poorly understood. OBJECTIVES: To investigate the contribution of the C5a/C5aR1 axis to the malignant phenotype of non-small cell lung cancer cells, particularly in skeletal colonization, a preferential lung metastasis site. METHODS: Association between C5aR1 expression and clinical outcome was assessed in silico and validated by immunohistochemistry. Functional significance was evaluated by lentiviral gene silencing and ligand l-aptamer inhibition in in vivo models of lung cancer bone metastasis. In vitro functional assays for signaling, migration, invasion, metalloprotease activity, and osteoclastogenesis were also performed. MEASUREMENTS AND MAIN RESULTS: High levels of C5aR1 in human lung tumors were significantly associated with shorter recurrence-free survival, overall survival, and bone metastasis. Silencing of C5aR1 in lung cancer cells led to a substantial reduction in skeletal metastatic burden and osteolysis in in vivo models. Furthermore, metalloproteolytic, migratory, and invasive tumor cell activities were modulated in vitro by C5aR1 stimulation or gene silencing. l-Aptamer blockade or C5aR1 silencing significantly reduced the osseous metastatic activity of lung cancer cells in vivo. This effect was associated with decreased osteoclastogenic activity in vitro and was rescued by the exogenous addition of the chemokine CXCL16. CONCLUSIONS: Disruption of C5aR1 signaling in lung cancer cells abrogates their tumor-associated osteoclastogenic activity, impairing osseous colonization. This study unveils the role played by the C5a/C5aR1 axis in lung cancer dissemination and supports its potential use as a novel therapeutic target.

Telomere shortening and accelerated aging in COPD: findings from the BODE cohort.

BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) may be associated with accelerated aging. Telomere shortening is a biomarker of aging. Cross-sectional studies describe shorter telomeres in COPD compared with matched controls. No studies have described telomere length trajectory and its relationship with COPD progression. We investigated telomere shortening over time and its relationship to clinical and lung function parameters in a COPD cohort and smoker controls without COPD. METHODS: At baseline leukocyte telomere length was measured by qPCR in 121 smokers with COPD and 121 without COPD matched by age (T/S0). The measurements were repeated in 70 of those patients with COPD and 73 non-COPD smokers after 3 years of follow up (T/S3). RESULTS: At initial measurement, telomeres were shorter in COPD patients when compared to smoker controls (T/S = 0.68 ± 0.25 vs. 0.88 ± 0.52, p = 0.003) independent from age and sex. During the follow-up period, we observed an accelerated telomere shortening in individuals with COPD in contrast to smoker controls (T/S0 = 0.66 ± 0.21 vs. T/S3 = 0.46 ± 0.16, p < 0.001, for the patients with COPD and T/S0 = 0.83 ± 0.56 vs. T/S3 = 0.74 ± 0.52, p = 0.023 for controls; GLIM, p = 0.001). This shortening was inversely related to the baseline telomere length (r = -0.49, p < 0.001). No significant relationship was found between the rate of change in telomere length and change in lung function in the patients with COPD (p > 0.05). CONCLUSIONS: Compared with smokers, patients with COPD have accelerated telomere shortening and this rate of attrition depends on baseline telomere length. Furthermore, the telomere length and its rate of shortening did not relate to clinical and lung function parameters changes over 3 years of follow-up.

A Combined PD-1/C5a Blockade Synergistically Protects against Lung Cancer Growth and Metastasis.

Disruption of the programmed cell death protein 1 (PD-1) pathway with immune checkpoint inhibitors represents a major breakthrough in the treatment of non-small cell lung cancer. We hypothesized that combined inhibition of C5a/C5aR1 and PD-1 signaling may have a synergistic antitumor effect. The RMP1-14 antibody was used to block PD-1, and an L-aptamer was used to inhibit signaling of complement C5a with its receptors. Using syngeneic models of lung cancer, we demonstrate that the combination of C5a and PD-1 blockade markedly reduces tumor growth and metastasis and leads to prolonged survival. This effect is accompanied by a negative association between the frequency of CD8 T cells and myeloid-derived suppressor cells within tumors, which may result in a more complete reversal of CD8 T-cell exhaustion. Our study provides support for the clinical evaluation of anti-PD-1 and anti-C5a drugs as a novel combination therapeutic strategy for lung cancer.Significance: Using a variety of preclinical models of lung cancer, we demonstrate that the blockade of C5a results in a substantial improvement in the efficacy of anti-PD-1 antibodies against lung cancer growth and metastasis. This study provides the preclinical rationale for the combined blockade of PD-1/PD-L1 and C5a to restore antitumor immune responses, inhibit tumor cell growth, and improve outcomes of patients with lung cancer. Cancer Discov; 7(7); 694-703. ©2017 AACR.This article is highlighted in the In This Issue feature, p. 653.

Genomic Profiling of Patient-Derived Xenografts for Lung Cancer Identifies B2M Inactivation Impairing Immunorecognition.

Purpose: We aimed to maximize the performance of detecting genetic alterations in lung cancer using high-throughput sequencing for patient-derived xenografts (PDXs).Experimental Design: We undertook an integrated RNA and whole-exome sequencing of 14 PDXs. We focused on the genetic and functional analysis of ß2-microglobulin (B2M), a component of the HLA class-I complex.Results: We identified alterations in genes involved in various functions, such as B2M involved in immunosurveillance. We extended the mutational analysis of B2M to about 230 lung cancers. Five percent of the lung cancers carried somatic mutations, most of which impaired the correct formation of the HLA-I complex. We also report that genes such as CALR, PDIA3, and TAP1, which are involved in the maturation of the HLA-I complex, are altered in lung cancer. By gene expression microarrays, we observed that restitution of B2M in lung cancer cells upregulated targets of IFNα/IFNγ. Furthermore, one third of the lung cancers lacked the HLA-I complex, which was associated with lower cytotoxic CD8+ lymphocyte infiltration. The levels of B2M and HLA-I proteins correlated with those of PD-L1. Finally, a deficiency in HLA-I complex and CD8+ infiltration tended to correlate with reduced survival of patients with lung cancer treated with anti-PD-1/anti-PD-L1.Conclusions: Here, we report recurrent inactivation of B2M in lung cancer. These observations, coupled with the mutations found at CALR, PDIA3, and TAP1, and the downregulation of the HLA-I complex, indicate that an abnormal immunosurveillance axis contributes to lung cancer development. Finally, our observations suggest that an impaired HLA-I complex affects the response to anti-PD-1/anti-PD-L1 therapies. Clin Cancer Res; 23(12); 3203-13. ©2016 AACR.

Strategies to design clinical studies to identify predictive biomarkers in cancer research.

The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework-the DESIGN guidelines-to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field.

Targeted depletion of PIK3R2 induces regression of lung squamous cell carcinoma.

Oncogenic mutations in the PI3K/AKT pathway are present in nearly half of human tumors. Nonetheless, inhibitory compounds of the pathway often induce pathway rebound and tumor resistance. We find that lung squamous cell carcinoma (SQCC), which accounts for ~20% of lung cancer, exhibits increased expression of the PI3K subunit PIK3R2, which is at low expression levels in normal tissues. We tested a new approach to interfere with PI3K/AKT pathway activation in lung SQCC. We generated tumor xenografts of SQCC cell lines and examined the consequences of targeting PIK3R2 expression. In tumors with high PIK3R2 expression, and independently of PIK3CA, KRAS, or PTEN mutations, PIK3R2 depletion induced lung SQCC xenograft regression without triggering PI3K/AKT pathway rebound. These results validate the use PIK3R2 interfering tools for the treatment of lung squamous cell carcinoma.

A large-scale analysis of alternative splicing reveals a key role of QKI in lung cancer.

Increasing interest has been devoted in recent years to the understanding of alternative splicing in cancer. In this study, we performed a genome-wide analysis to identify cancer-associated splice variants in non-small cell lung cancer. We discovered and validated novel differences in the splicing of genes known to be relevant to lung cancer biology, such as NFIB, ENAH or SPAG9. Gene enrichment analyses revealed an important contribution of alternative splicing to cancer-related molecular functions, especially those involved in cytoskeletal dynamics. Interestingly, a substantial fraction of the altered genes found in our analysis were targets of the protein quaking (QKI), pointing to this factor as one of the most relevant regulators of alternative splicing in non-small cell lung cancer. We also found that ESYT2, one of the QKI targets, is involved in cytoskeletal organization. ESYT2-short variant inhibition in lung cancer cells resulted in a cortical distribution of actin whereas inhibition of the long variant caused an increase of endocytosis, suggesting that the cancer-associated splicing pattern of ESYT2 has a profound impact in the biology of cancer cells. Finally, we show that low nuclear QKI expression in non-small cell lung cancer is an independent prognostic factor for disease-free survival (HR = 2.47; 95% CI = 1.11-5.46, P = 0.026). In conclusion, we identified several splicing variants with functional relevance in lung cancer largely regulated by the splicing factor QKI, a tumor suppressor associated with prognosis in lung cancer.

Epigenetic alterations leading to TMPRSS4 promoter hypomethylation and protein overexpression predict poor prognosis in squamous lung cancer patients.

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related death worldwide, which highlights the need of innovative therapeutic options. Although targeted therapies can be successfully used in a subset of patients with lung adenocarcinomas (ADC), they are not appropriate for patients with squamous cell carcinomas (SCC). In addition, there is an unmet need for the identification of prognostic biomarkers that can select patients at risk of relapse in early stages. Here, we have used several cohorts of NSCLC patients to analyze the prognostic value of both protein expression and DNA promoter methylation status of the prometastatic serine protease TMPRSS4. Moreover, expression and promoter methylation was evaluated in a panel of 46 lung cancer cell lines. We have demonstrated that a high TMPRSS4 expression is an independent prognostic factor in SCC. Similarly, aberrant hypomethylation in tumors, which correlates with high TMPRSS4 expression, is an independent prognostic predictor in SCC. The inverse correlation between expression and methylation status was also observed in cell lines. In vitro studies showed that treatment of cells lacking TMPRSS4 expression with a demethylating agent significantly increased TMPRSS4 levels. In conclusion, TMPRSS4 is a novel independent prognostic biomarker regulated by epigenetic changes in SCC and a potential therapeutic target in this tumor type, where targeted therapy is still underdeveloped.

A Novel Epigenetic Signature for Early Diagnosis in Lung Cancer.

PURPOSE: Lung cancer remains as the leading cause of cancer-related death worldwide, mainly due to late diagnosis. Cytology is the gold-standard method for lung cancer diagnosis in minimally invasive respiratory samples, despite its low sensitivity. We aimed to identify epigenetic biomarkers with clinical utility for cancer diagnosis in minimally/noninvasive specimens to improve accuracy of current technologies. EXPERIMENTAL DESIGN: The identification of novel epigenetic biomarkers in stage I lung tumors was accomplished using an integrative genome-wide restrictive analysis of two different large public databases. DNA methylation levels for the selected biomarkers were validated by pyrosequencing in paraffin-embedded tissues and minimally invasive and noninvasive respiratory samples in independent cohorts. RESULTS: We identified nine cancer-specific hypermethylated genes in early-stage lung primary tumors. Four of these genes presented consistent CpG island hypermethylation compared with nonmalignant lung and were associated with transcriptional silencing. A diagnostic signature was built using multivariate logistic regression model based on the combination of four genes: BCAT1, CDO1, TRIM58, and ZNF177 Clinical diagnostic value was also validated in multiple independent cohorts and yielded a remarkable diagnostic accuracy in all cohorts tested. Calibrated and cross-validated epigenetic model predicts with high accuracy the probability to detect cancer in minimally and noninvasive samples. We demonstrated that this epigenetic signature achieved higher diagnostic efficacy in bronchial fluids as compared with conventional cytology for lung cancer diagnosis. CONCLUSIONS: Minimally invasive epigenetic biomarkers have emerged as promising tools for cancer diagnosis. The herein obtained epigenetic model in combination with current diagnostic protocols may improve early diagnosis and outcome of lung cancer patients. Clin Cancer Res; 22(13); 3361-71. ©2016 AACR.

TMPRSS4 induces cancer stem cell-like properties in lung cancer cells and correlates with ALDH expression in NSCLC patients.

Metastasis involves a series of changes in cancer cells that promote their escape from the primary tumor and colonization to a new organ. This process is related to the transition from an epithelial to a mesenchymal phenotype (EMT). Recently, some authors have shown that migratory cells with an EMT phenotype share properties of cancer stem cells (CSCs), which allow them to form a new tumor mass. The type II transmembrane serine protease TMPRSS4 is highly expressed in some solid tumors, promotes metastasis and confers EMT features to cancer cells. We hypothesized that TMPRSS4 could also provide CSC properties. Overexpression of TMPRSS4 reduces E-cadherin and induces N-cadherin and vimentin in A549 lung cancer cells, supporting an EMT phenotype. These changes are accompanied by enhanced migration, invasion and tumorigenicity in vivo. TMPRSS4 expression was highly increased in a panel of lung cancer cells cultured as tumorspheres (a typical assay to enrich for CSCs). H358 and H441 cells with knocked-down TMPRSS4 levels were significantly less able to form primary and secondary tumorspheres than control cells. Moreover, they showed a lower proportion of ALDH+ cells (examined by FACS analysis) and lower expression of some CSC markers than controls. A549 cells overexpressing TMPRSS4 conferred the opposite phenotype and were also more sensitive to the CSC-targeted drug salinomycin than control cells, but were more resistant to regular chemotherapeutic drugs (cisplatin, gemcitabine and 5-fluorouracil). Analysis of 70 NSCLC samples from patients revealed a very significant correlation between TMPRSS4 expression and CSC markers ALDH (p = 0.0018) and OCT4 (p = 0.0004), suggesting that TMPRSS4 is associated with a CSC phenotype in patients' tumors. These results show that TMPRSS4, in addition to inducing EMT, can also promote CSC features in lung cancer; therefore, CSC-targeting drugs could be an appropriate treatment for TMPRSS4+ tumors.

Combined clinical and genomic signatures for the prognosis of early stage non-small cell lung cancer based on gene copy number alterations.

BACKGROUND: The development of a more refined prognostic methodology for early non-small cell lung cancer (NSCLC) is an unmet clinical need. An accurate prognostic tool might help to select patients at early stages for adjuvant therapies. RESULTS: A new integrated bioinformatics searching strategy, that combines gene copy number alterations and expression, together with clinical parameters was applied to derive two prognostic genomic signatures. The proposed methodology combines data from patients with and without clinical data with a priori information on the ability of a gene to be a prognostic marker. Two initial candidate sets of 513 and 150 genes for lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC), respectively, were generated by identifying genes which have both: a) significant correlation between copy number and gene expression, and b) significant prognostic value at the gene expression level in external databases. From these candidates, two panels of 7 (ADC) and 5 (SCC) genes were further identified via semi-supervised learning. These panels, together with clinical data (stage, age and sex), were used to construct the ADC and SCC hazard scores combining clinical and genomic data. The signatures were validated in two independent datasets (n = 73 for ADC, n = 97 for SCC), confirming that the prognostic value of both clinical-genomic models is robust, statistically significant (P = 0.008 for ADC and P = 0.019 for SCC) and outperforms both the clinical models (P = 0.060 for ADC and P = 0.121 for SCC) and the genomic models applied separately (P = 0.350 for ADC and P = 0.269 for SCC). CONCLUSION: The present work provides a methodology to generate a robust signature using copy number data that can be potentially used to any cancer. Using it, we found new prognostic scores based on tumor DNA that, jointly with clinical information, are able to predict overall survival (OS) in patients with early-stage ADC and SCC.

Stratification of resectable lung adenocarcinoma by molecular and pathological risk estimators.

BACKGROUND: Mortality in early stage, resectable lung cancer is sufficiently high to warrant consideration of post-surgical treatment. Novel markers to stratify resectable lung cancer patients may help with the selection of treatment to improve outcome. METHODS: Primary tumour tissue from 485 patients, surgically treated for stage I-II lung adenocarcinoma, was analysed for the RNA expression of 31 cell cycle progression (CCP) genes by quantitative polymerase chain reaction (PCR). The expression average, the CCP score, was combined with pathological stage into a prognostic score (PS). Cox proportional hazards regression assessed prediction of 5-year lung cancer mortality above clinical variables. The PS threshold was tested for risk discrimination by the Mantel-Cox log-rank test. RESULTS: The CCP score added significant information above clinical markers (all patients, P=0.0029; stage I patients, P=0.013). The prognostic score was a superior predictor of outcome compared to pathological stage alone (PS, P=0.00084; stage, P=0.24). Five-year lung cancer mortality was significantly different between the low-risk (90%, 95% confidence interval (CI) 81-95%), and high-risk groups (65%, 95% CI 57-72%), P=4.2×10(-6)). CONCLUSIONS: The CCP score is an independent prognostic marker in early stage lung adenocarcinoma. The prognostic score provides superior risk estimates than stage alone. The threefold higher risk in the high-risk group defines a subset of patients that should consider therapeutic choices to improve outcome.