Should we continue to use the term non-small-cell lung cancer?

Reporting multitargeted potency of Tiaprofenic acid against lung cancer: Molecular fingerprinting, MD simulation, and MTT-based cell viability assay studies

Lung Cancer (LC) is among the most death-causing cancers, has caused the most destruction and is a gender-neutral cancer, and WHO has kept this cancer on its priority list to find the cure. We have used high-throughput virtual screening, standard precision docking, and extra precise docking for extensive screening of Drug Bank compounds, and the uniqueness of this study is that it considers multiple protein targets of prognosis and metastasis of LC. The docking and MM\GBSA calculation scores for the Tiaprofenic acid (DB01600) against all ten proteins range from -8.422 to -5.727 kcal/mol and - 47.43 to -25.72 kcal/mol, respectively. Also, molecular fingerprinting helped us to understand the interaction pattern of Tiaprofenic acid among all the proteins. Further, we extended our analysis to the molecular dynamic simulation in a neutralised SPC water medium for 100 ns. We analysed the root mean square deviation, fluctuations, and simulative interactions among the protein, ligand, water molecules, and protein-ligand complexes. Most complexes have shown a deviation of <2 Å as cumulative understanding. Also, the fluctuations were lesser, and only a few residues showed the fluctuation with a huge web of interaction between the protein and ligand, providing an edge that supports that the protein and ligand complexes were stable. In the MTT-based Cell Viability Assay, Tiaprofenic Acid exhibited concentration-dependent anti-cancer efficacy against A549 lung cancer cells, significantly reducing viability at 100 μg/mL. These findings highlight its potential as a therapeutic candidate, urging further exploration into the underlying molecular mechanisms for lung cancer treatment.

RNA‑binding protein quaking 5 inhibits the progression of non‑small cell lung cancer by upregulating netrin‑4 expression

It was recently reported that netrin‑4 (Ntn‑4), a component of the extracellular matrix, when downregulated, is involved in the progression of several types of cancer, including breast cancer, colorectal tumours, neuroblastoma and gastric cancer. In the present study, the level of Ntn‑4 was examined in a public non‑small cell lung cancer (NSCLC) dataset from the Netherlands Cancer Institute. This analysis revealed that the mRNA expression level of Ntn‑4 was lower in the samples of patients with NSCLC compared with that in the control samples. Consistent with the mRNA level, the protein level of Ntn‑4 was also found to be decreased in NSCLC cells. However, both the function of Ntn‑4 and the underlying mechanisms of Ntn‑4 downregulation in NSCLC have yet to be fully elucidated. As was anticipated, the overexpression of Ntn‑4 led to a marked decrease in the proliferation, migration and invasion of NSCLC cells. Notably, RNA‑binding protein quaking 5 (Qki‑5) was found to exhibit antitumor activity in lung cancer, not only by enhancing the level of Ntn‑4 by binding to Ntn‑4 mRNA, but also by suppressing the proliferation, invasion and migration of NSCLC cells. However, Qki‑5 is known to be frequently downregulated in NSCLC. Moreover, the knockdown of Ntn‑4 was found to reverse the suppressive effects of Qki‑5 on NSCLC progression both in vitro and in vivo. Taken together, the findings of the present study demonstrate that Ntn‑4 is able to suppress the progression of NSCLC, and that the level of Ntn‑4 can be regulated by Qki‑5. Therefore, Ntn‑4 may be a novel diagnostic and therapeutic target for the treatment of NSCLC.

Efficacy of SPG-ODN 1826 Nanovehicles in Inducing M1 Phenotype through TLR-9 Activation in Murine Alveolar J774A.1 Cells: Plausible Nano-Immunotherapy for Lung Carcinoma

Alveolar macrophages are the first line of defense against intruding pathogens and play a critical role in cancer immunology. The Toll-like receptor (TLR) family mediates an important role in recognizing and mounting an immune response against intruding microbes. TLR-9 is a member of the intracellular TLR family, which recognizes unmethylated CG motifs from the prokaryotic genome. Upon its activation, TLR-9 triggers downstream of the MyD-88-dependent transcriptional activation of NF-κB, and subsequently results in abundant inflammatory cytokines expression that induces a profound inflammatory milieu. The present exploratory investigation aimed at elucidating the potency of schizophyllan for entrapping ODN 1826 (SPG-ODN 1826)-mediated stimulation of TLR-9 in provoking an inflammatory-type response in murine alveolar macrophages. Schizophyllan (SPG), a representative of the β-glucan family, was used in the present study as a nanovehicle for endosomal trafficking of CpG ODN 1826. TEM analysis of SPG-ODN 1826 nanovehicles revealed that the prepared nanovehicles are spherical and have an average size of about 100 nm. Interestingly, SPG-ODN 1826 nanovehicles were competent in delivering their therapeutic payload within endosomes of murine alveolar macrophage (J774A.1) cells. Exposure of these nanovehicles within LPS stimulated J774A.1, resulted in a significant provocation of reactive oxygen species (ROS) (p < 0.01) in comparison to CpG ODN 1826 alone. Moreover, the formulated nanovehicles succeeded in generating a profound Th1-based cytokine profile constituted by enhanced expression of IFN-γ (p < 0.001) and IL-1β (p < 0.001) inflammatory cytokines. These findings clearly indicated the immunostimulatory potential of SPG-ODN 1826 nanovehicles for inducing the Th1-type phenotype, which would certainly assist in skewing M2 phenotype into the much-desired M1 type during lung cancer.

Studies in lung cancer cytokine proteomics: a review

INTRODUCTION

Proteins are molecules that have role in the progression of the diseases. Proteomics is a tool that can play an effective role in identifying diagnostic and therapeutic biomarkers for lung cancer. Cytokines are proteins that play a decisive role in activating body's immune system in lung cancer. They can increase the growth of the tumor (oncogenic cytokines) or limit tumor growth (anti-tumor cytokines) by regulating related signaling pathways such as proliferation, growth, metastasis, and apoptosis.

AREAS COVERED

In the present study, a total of 223 papers including 196 research papers and 27 review papers, extracted from PubMed and Scopus and published from 1997 to present, are reviewed. The most important involved-cytokines in lung cancer including TNF-α, IFN- γ, TGF-β, VEGF and interleukins such as IL-6, IL-17, IL-8, IL-10, IL-22, IL-1β and IL-18 are introduced. Also, the pathological and biological role of such cytokines in cancer signaling pathways is explained.

EXPERT OPINION

In lung cancer, the cytokine expression changes under the physiological conditions of the immune system, and inflammatory cytokines are associated with the progression of lung cancer. Therefore, the cytokine expression profile can be used in the diagnosis, prognosis, prediction of therapeutic responses, and survival of patients with lung cancer.

3,3',5,5'-tetramethoxybiphenyl-4,4'diol induces cell cycle arrest in G2/M phase and apoptosis in human non-small cell lung cancer A549 cells

Lung cancer is one of the leading causes of cancer-related death worldwide. It has aggressive manifestation, high ability to promote metastasis and late diagnosis. In the present study, we investigated the cytotoxic effect of 3,3',5,5'-tetramethoxybiphenyl-4,4'diol (TMBP), against the A549 human non-small cell lung carcinoma lineage. The A549 cell line was treated for 72h with TMBP (12.5-200 μM) with and subsequently defined the 50% inhibitory concentration (148 μM ± 0.05), from which tests were performed to determine the viability, volume, and regulation of the cell cycle. Finally, we investigated the death mechanisms involved in the action of the treatments by flow cytometry and fluorimetry. The TMBP-treatment of primary cells, peritoneal macrophages, and sheep erythrocytes did not reduce the viability of these cells. On the other hand, TMBP was able to reduce the viability of the investigated cell line, by cytotoxic action and to promote the reduction of cell size. Subsequently, we found that TMBP treatment was able to increase the production of reactive oxygen species, cause mitochondrial depolarization, induce cell cycle arrest in G2/M phase and lead to death by direct apoptosis. Thus, this study revealed that TMBP could be a promising candidate for the development of antitumor drugs targeting lung cancer.

Retrospective observational cohort study on innovation in oncology and progress in survival: How far have we gotten in the two decades of treating patients with advanced non-small cell lung cancer as a single population?

We assessed the impact of new antineoplastic agents on the overall survival (OS) of advanced non-small cell lung cancer (aNSCLC) patients followed up until 2012. Multivariate regression models were run for OS (outcome) and four proxies for innovation (exposure): Index (InnovInd, for SEER-Research data 1973–2012) and three levels of aggregation of Mean Medication Vintage, i.e. Overall (MMV_Overall), using data aggregated at the State Level (MMV_State), and using patient-level data (MMV_Patient) using data from the US captured in SEER-Medicare 1991–2012. We derived Hazard ratios (HR) from Royston-Parmar models and odds ratios (OR) from a logistic regression on 1-year OS. Including 164,704 patients (median age 72 years, 56.8% stage IV, 61.8% with no comorbidities, 37.8% with adenocarcinoma, 22.9% with squamous-cell, 6.1% were censored). One-year OS improved from 0.22 in 1973 to 0.39 in 2012, in correlation with InnovInd (r = 0.97). Ten new NSCLC drugs were approved and 28 more used off-label. Regression-models results indicate that therapeutic innovation only marginally reduced the risk of dying (HROverall = 0.98 [0.98–0.98], HR_MMV-Patient = 0.98 [0.97–0.98], and HR_MMV-State = 0.98 [0.98–0.98], and slightly improved 1-year survival (OR_MMV-Overall = 1.05 95%CI [1.04–1.05]). These results were validated with data from the Swedish National Health Data registers. Until 2013, aNSCLC patients were treated undifferentiated and the introduction of innovative therapies had statistically significant, albeit modest, effects on survival. Most treatments used off-guidelines highlight the high unmet need; however new advancements in treatment may further improve survival.

Sex and survival in non-small cell lung cancer: A nationwide cohort study

Aim

To in detail delineate sex differences in non-small cell lung cancer outcome and investigate possible underlying drivers.

Methods

We performed a nationwide, population-based cohort study using data on all incident cases of lung squamous cell carcinoma (n = 10,325) and adenocarcinoma (n = 23,465) recorded in the Swedish Lung Cancer Register in 2002–2016. Flexible parametric models were applied to compute adjusted female-to-male hazard ratios (aHRs) and standardized survival proportions over follow-up including age, calendar year, education, marital status, birth country, health care region, performance status, smoking history, comorbidities, and tumor location in the final model.

Results

Women presented with better performance status, were younger, and more often never-smokers. Women with adenocarcinoma also had lower comorbidity burden, less advanced stage, and were more often EGFR positive. Men with adenocarcinoma had a consistently poorer lung cancer-specific survival across stage; HR 0.69; 95% CI 0.63–0.76 (stage IA-IIB) to 0.94; 95% CI 0.88–0.99 (stage IIIB-IV), remaining largely unchanged after adjustments; aHR 0.74; 95% CI 0.66–0.82 to 0.84; 95% CI 0.81–0.87. The same pattern was observed in squamous cell carcinoma, except in stage IIIA disease, where we found no sex differences in survival.

Conclusions

Men with non-small cell lung cancer have a consistently poorer prognosis, even after careful adjustments for a wide range of prognostic factors. While the pattern was similar in both squamous cell and adenocarcinoma, it was larger and more consistent in the latter.

Integrated Analysis of Transcriptome and Prognosis Data Identifies FGF22 as a Prognostic Marker of Lung Adenocarcinoma

Lung adenocarcinoma is one of the most common cancers worldwide. However, the molecular mechanisms of lung adenocarcinoma development are still unclear. This study aimed to investigate the expression profiles of anti-lung cancer target genes in different cancer stages and to explore their functions in tumor development. Lung adenocarcinoma transcriptome and clinical data were downloaded from Genomic Data Commons Data Portal, and the anti-lung cancer target genes were retrieved from the Thomson Reuters Integrity database. The results showed that 16 anti-lung target genes were deregulated in all stages. Among these target genes, fibroblast growth factor 22 showed the most important role in transcription regulatory networks. Further analysis revealed that APC, BRIP1, and PTTG1 may regulate fibroblast growth factor 22 and subsequently influence MAPK signaling pathway, Rap1 signaling pathways, and other tumorigenic processes in all stages. Moreover, high fibroblast growth factor 22 expression leads to poor overall survival (hazard ratio = 1.55, P = .019). These findings provide valuable information for the pathological research and treatment of lung adenocarcinoma. Future studies are needed to verify these results.

Genome-wide copy number variation pattern analysis and a classification signature for non-small cell lung cancer

The accurate classification of non-small cell lung carcinoma (NSCLC) into lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) is essential for both clinical practice and lung cancer research. Although the standard WHO diagnosis of NSCLC on biopsy material is rapid and economic, more than 13% of NSCLC tumors in the USA are not further classified. The purpose of this study was to analyze the genome-wide pattern differences in copy number variations (CNVs) and to develop a CNV signature as an adjunct test for the routine histopathologic classification of NSCLCs. We investigated the genome-wide CNV differences between these two tumor types using three independent patient datasets. Approximately half of the genes examined exhibited significant differences between LUAD and LUSC tumors and the corresponding non-malignant tissues. A new classifier was developed to identify signature genes out of 20 000 genes. Thirty-three genes were identified as a CNV signature of NSCLC. Using only their CNV values, the classification model separated the LUADs from the LUSCs with an accuracy of 0.88 and 0.84, respectively, in the training and validation datasets. The same signature also classified NSCLC tumors from their corresponding non-malignant samples with an accuracy of 0.96 and 0.98, respectively. We also compared the CNV patterns of NSCLC tumors with those of histologically similar tumors arising at other sites, such as the breast, head, and neck, and four additional tumors. Of greater importance, the significant differences between these tumors may offer the possibility of identifying the origin of tumors whose origin is unknown.

Comparison of human lung cancer cell radiosensitivity after irradiations with therapeutic protons and carbon ions

The aim of this study was to investigate effects of irradiations with the therapeutic proton and carbon ion beams in two non-small cell lung cancers, CRL5876 adenocarcinoma and HTB177 large cell lung carcinoma. The DNA damage response dynamics, cell cycle regulation, and cell death pathway activation were followed. Viability of both cell lines was lower after carbon ions compared to the therapeutic proton irradiations. HTB177 cells showed higher recovery than CRL5876 cells seven days following the treatments, but the survival rates of both cell lines were lower after exposure to carbon ions with respect to therapeutic protons. When analyzing cell cycle distribution of both CRL5876 and HTB177 cells, it was noticed that therapeutic protons predominantly induced G1 arrest, while the cells after carbon ions were arrested in G2/M phase. The results illustrated that differences in the levels of phosphorylated H2AX, a double-strand break marker, exist after therapeutic proton and carbon ion irradiations. We also observed dose- and time-dependent increase in the p53 and p21 levels after applied irradiations. Carbon ions caused larger increase in the quantity of p53 and p21 compared to therapeutic protons. These results suggested that various repair mechanisms were induced in the treated cells. Considering the fact that we have not observed any distinct change in the Bax/Bcl-2 ratio following irradiations, it seemed that different types of cell death were involved in the response to the two types of irradiations that were applied.

An Expression Signature as an Aid to the Histologic Classification of Non-Small Cell Lung Cancer

PURPOSE

Most non-small cell lung cancers (NSCLC) are now diagnosed from small specimens, and classification using standard pathology methods can be difficult. This is of clinical relevance as many therapy regimens and clinical trials are histology dependent. The purpose of this study was to develop an mRNA expression signature as an adjunct test for routine histopathologic classification of NSCLCs.

EXPERIMENTAL DESIGN

A microarray dataset of resected adenocarcinomas (ADC) and squamous cell carcinomas (SCC) was used as the learning set for an ADC-SCC signature. The Cancer Genome Atlas (TCGA) lung RNAseq dataset was used for validation. Another microarray dataset of ADCs and matched nonmalignant lung was used as the learning set for a tumor versus nonmalignant signature. The classifiers were selected as the most differentially expressed genes and sample classification was determined by a nearest distance approach.

RESULTS

We developed a 62-gene expression signature that contained many genes used in immunostains for NSCLC typing. It includes 42 genes that distinguish ADC from SCC and 20 genes differentiating nonmalignant lung from lung cancer. Testing of the TCGA and other public datasets resulted in high prediction accuracies (93%-95%). In addition, a prediction score was derived that correlates both with histologic grading and prognosis. We developed a practical version of the Classifier using the HTG EdgeSeq nuclease protection-based technology in combination with next-generation sequencing that can be applied to formalin-fixed paraffin-embedded (FFPE) tissues and small biopsies.

CONCLUSIONS

Our RNA classifier provides an objective, quantitative method to aid in the pathologic diagnosis of lung cancer. Clin Cancer Res; 22(19); 4880-9. ©2016 AACR.

The Overexpression of FEN1 and RAD54B May Act as Independent Prognostic Factors of Lung Adenocarcinoma

Synthetic lethality arises when a combination of mutations in two or more genes leads to cell death. However, the prognostic role of concordant overexpression of synthetic lethality genes in protein level rather than a combination of mutations is not clear. In this study, we explore the prognostic role of combined overexpression of paired genes in lung adenocarcinoma. We used immunohistochemical staining to investigate 24 paired genes in 93 lung adenocarcinoma patients and Kaplan-Meier analysis and Cox proportional hazards models to evaluate their prognostic roles. Among 24 paired genes, only FEN1 (Flap endonuclease 1) and RAD54B (RAD54 homolog B) were overexpressed in lung adenocarcinoma patients with poor prognosis. Patients with expression of both FEN1 and RAD54B were prone to have advanced nodal involvement and significantly poor prognosis (HR = 2.35, P = 0.0230). These results suggest that intensive follow up and targeted therapy might improve clinical outcome for patients who show expression of both FEN1 and RAD54B.

Stratifying tumour subtypes based on copy number alteration profiles using next-generation sequence data

MOTIVATION

The role of personalized medicine and target treatment in the clinical management of cancer patients has become increasingly important in recent years. This has made the task of precise histological substratification of cancers crucial. Increasingly, genomic data are being seen as a valuable classifier. Specifically, copy number alteration (CNA) profiles generated by next-generation sequencing (NGS) can become a determinant for tumours subtyping. The principle purpose of this study is to devise a model with good prediction capability for the tumours histological subtypes as a function of both the patients covariates and their genome-wide CNA profiles from NGS data.

RESULTS

We investigate a logistic regression for modelling tumour histological subtypes as a function of the patients' covariates and their CNA profiles, in a mixed model framework. The covariates, such as age and gender, are considered as fixed predictors and the genome-wide CNA profiles are considered as random predictors. We illustrate the application of this model in lung and oral cancer datasets, and the results indicate that the tumour histological subtypes can be modelled with a good fit. Our cross-validation indicates that the logistic regression exhibits the best prediction relative to other classification methods we considered in this study. The model also exhibits the best agreement in the prediction between smooth-segmented and circular binary-segmented CNA profiles.

AVAILABILITY AND IMPLEMENTATION

An R package to run a logistic regression is available in http://www1.maths.leeds.ac.uk/~arief/R/CNALR/.

CONTACT

a.gusnanto@leeds.ac.uk

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Verification of the biomarker candidates for non-small-cell lung cancer using a targeted proteomics approach

Lung cancer, with its high metastatic potential and high mortality rate, is the worldwide leading cause of cancer-related deaths. High-throughput "omics"-based platforms have accelerated the discovery of biomarkers for lung cancer, and the resulting candidates are to be evaluated for their diagnostic potential as noninvasive biomarkers. The evaluation of the biomarker candidates involves the quantitative measurement of large numbers of proteins in bodily fluids using advanced mass spectrometric techniques. In this study, a robust pipeline based on targeted proteomics was developed for biomarker verification in plasma samples and applied to verifying lung cancer biomarker candidates. Highly multiplexed liquid chromatrography-selected reaction monitoring (LC-SRM) assays for 95 potential tumor markers for non-small-cell lung cancer (NSCLC) were generated to screen plasma samples obtained from 72, early to late stage, patients. A total of 17 proteins were verified as potent tumor markers detectable in plasma and, where available, verified by enzyme-linked immunosorbent assays (ELISAs). A novel plasma-based biomarker, zyxin, fulfilled the criteria for a potential early diagnostic marker for NSCLC.

SIAH2 antagonizes TYK2-STAT3 signaling in lung carcinoma cells

The Janus tyrosine kinases JAK1-3 and tyrosine kinase-2 (TYK2) are frequently hyperactivated in tumors. In lung cancers JAK1 and JAK2 induce oncogenic signaling through STAT3. A putative role of TYK2 in these tumors has not been reported. Here, we show a previously not recognized TYK2-STAT3 signaling node in lung cancer cells. We reveal that the E3 ubiquitin ligase seven-in-absentia-2 (SIAH2) accelerates the proteasomal degradation of TYK2. This mechanism consequently suppresses the activation of STAT3. In agreement with these data the analysis of primary non-small-cell lung cancer (NSCLC) samples from three patient cohorts revealed that compared to lung adenocarcinoma (ADC), lung squamous cell carcinoma (SCC) show significantly higher levels of SIAH2 and reduced STAT3 phosphorylation levels. Thus, SIAH2 is a novel molecular marker for SCC. We further demonstrate that an activation of the oncologically relevant transcription factor p53 in lung cancer cells induces SIAH2, depletes TYK2, and abrogates the tyrosine phosphorylation of STAT1 and STAT3. This mechanism appears to be different from the inhibition of phosphorylated JAKs through the suppressor of cytokine signaling (SOCS) proteins. Our study may help to identify molecular mechanisms affecting lung carcinogenesis and potential therapeutic targets.

Classification of lung cancer using ensemble-based feature selection and machine learning methods

Lung cancer is one of the leading causes of death worldwide. There are three major types of lung cancers, non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC) and carcinoid. NSCLC is further classified into lung adenocarcinoma (LADC), squamous cell lung cancer (SQCLC) as well as large cell lung cancer. Many previous studies demonstrated that DNA methylation has emerged as potential lung cancer-specific biomarkers. However, whether there exists a set of DNA methylation markers simultaneously distinguishing such three types of lung cancers remains elusive. In the present study, ROC (Receiving Operating Curve), RFs (Random Forests) and mRMR (Maximum Relevancy and Minimum Redundancy) were proposed to capture the unbiased, informative as well as compact molecular signatures followed by machine learning methods to classify LADC, SQCLC and SCLC. As a result, a panel of 16 DNA methylation markers exhibits an ideal classification power with an accuracy of 86.54%, 84.6% and a recall 84.37%, 85.5% in the leave-one-out cross-validation (LOOCV) and independent data set test experiments, respectively. Besides, comparison results indicate that ensemble-based feature selection methods outperform individual ones when combined with the incremental feature selection (IFS) strategy in terms of the informative and compact property of features. Taken together, results obtained suggest the effectiveness of the ensemble-based feature selection approach and the possible existence of a common panel of DNA methylation markers among such three types of lung cancer tissue, which would facilitate clinical diagnosis and treatment.

Glyceraldehyde-3-phosphate dehydrogenase gene over expression correlates with poor prognosis in non small cell lung cancer patients

BACKGROUND

Glycolysis in presence of oxygen with high glucose consumption is known to be the metabolism of choice in many tumors. In lung cancer this phenomenon is routinely exploited in diagnostic PET imaging of fluorodeoxyglucose uptake, but not much is known about the prognostic capabilities of glycolysis level assessment in resected lung tumor samples.

METHODS

In this retrospective study, we used real time polymerase chain reaction(RQ-PCR) to assess the expression level of the gene for Glyceraldehyde 3-phosphate dehydrogenase(GAPDH), key enzyme for glucose breakdown, in tumor samples from 82 consecutive early stages resected non small cell lung cancer(NSCLC) patients. We then compared our results in six large publicly available NSCLC microarray datasets collecting data from over 1250 total patients.

RESULTS

In our study GAPDH gene over expression was found to be an adverse prognostic factor in early stages NSCLC (n = 82 HR = 1.30 p = 0.050). This result was confirmed in 5 of 6 public datasets analyzed: Shedden et al. 2008: n = 442 HR = 1.54 p < 0.0001; Lee et al. 2008: n = 138 HR = 1.31 p = 0.043; Tomida et al. 2009: n = 117 HR = 1.59 p = 0.004; Roepman et al. 2009: n = 172 (TPI1 gene) HR = 1.51 p = 0.009; Okayama et al. 2012: n = 226 HR = 3.19 p < 0.0001; Botling et al. 2013: n = 196 HR = 1.00 p = 0.97). Furthermore, in the large and clinically well annotated Shedden et al. microarray dataset, GAPDH hazard ratio did not change whether calculated for the whole dataset or for the subgroup of adjuvant naive patients only (n = 330 HR = 1.49 p < 0.0001).

CONCLUSION

GAPDH gene over expression in resected tumor samples is an adverse prognostic factor in NSCLC. Our results confirm the prognostic value of glucose metabolism assessment in NSCLC.

Subtyping non-small cell lung cancer: relevant issues and operative recommendations for the best pathology practice

Morphology still remains the cornerstone in lung cancer classification and cytology and small biopsy samples should be interpreted by morphology, whenever feasible, according to shared and widely agreed-upon diagnostic schemes. However, as novel therapy strategies are being offered on the basis of the diverse tumor characteristics, pathologists are now challenged by the need to offer clinicians more detailed typing of non-small cell lung cancer, not otherwise specified (NSCLC-NOS), especially when dealing with limited diagnostic material or poorly differentiated tumors. Close integration of morphology, immunohistochemistry, and clinical data is highly warranted according to a multidisciplinary approach to limit the category of NSCLC-NOS as much as possible or exclude unsuspected metastases, so rendering more definite and clinically useful diagnoses. Among the many proposed immunohistochemical markers, which as a whole are more practical and diagnostically useful than cumbersome and expensive molecular assays, a 2-hit model including thyroid transcription factor-1 (TTF-1) and p40 (the latter more specific for squamous differentiation than p63) seems to be the most effective to basically highlight adenocarcinoma (positivity for TTF-1 regardless of p63) and squamous (always strongly and diffusely positive for p40 or p63 and negative for TTF-1) differentiation. This minimalist 2-hit diagnostic approach paves the way to novel perspectives in clinical trials on lung cancer, and it is also in keeping with the need of strategically preserving diagnostic material for molecular assays that are essential for personalizing therapies.

Monoclonal antibodies in lung cancer

INTRODUCTION

Lung cancer is the leading cause of cancer death worldwide. As clinical benefits to conventional cancer therapies are still formidable, there is an urgent need for novel agents and approaches to improve the overall clinical outcomes for patients with lung cancer.

AREAS COVERED

This article reviews the current understanding of targeted therapy for lung cancer with monoclonal antibodies (mAbs), mainly bevacizumab and cetuximab. The results from several key clinical trials validating the effectiveness and safety of bevacizumab and cetuximab, the relation of cancer biomarkers, the polymorphic correlation of targeted genes with the therapeutic outcome of mAb-based treatment, as well as the impact of Biomarker-integrated Approaches of Targeted Therapy for Lung Cancer Elimination (BATTLE) trial on personalised treatment of lung cancer are discussed.

EXPERT OPINION

The addition of bevacizumab or cetuximab to chemotherapy has shown promising benefits to the patients with non-small-cell lung cancer. However, the overall benefits of mAb-based targeted therapy to lung cancer patients vary among individuals. It is therefore necessary to define reliable predictive biomarkers in an effort to better identify patients who are most likely to benefit from treatment with these novel agents in lung cancer.

The evolving role of the pathologist in the management of lung cancer

Major advances in pathology, molecular biology, patient diagnosis and care, as well as the advent of personalized therapy, have resulted in a greatly increased role for the pathologist, who has emerged as a key member of the lung cancer management team. A new multidisciplinary, clinically relevant classification of pulmonary adenocarcinoma has resulted in a paradigm shift in how we view and practice lung cancer pathology. In the future, the role of the pathologist will continue to grow and become fully integrated with clinical care.

MicroRNAs As Biomarkers For Clinical Features Of Lung Cancer

Each year about 1.4 million people die from lung cancer worldwide. Despite efforts in prevention, diagnosis and treatment, survival rate remains poor for this disease. This unfortunate situation is largely due to the fact that a high proportion of cases are diagnosed at advanced stages, highlighting the great need for identifying new biomarkers in order to improve early diagnosis and treatment. Recent studies on microRNAs have not only shed light on their involvement in tumor development and progression, but also suggested their potential utility as biomarkers for subtype diagnostics, staging and prediction of treatment response. This review article summarizes the impact of microRNAs on lung cancer biology, and highlights their role in the detection and classification of lung cancer as well as direct targets for drug development.

Adjuvant therapy for non-small cell lung cancer

OBJECTIVE

Adjuvant chemotherapy is recommended for most patients submitted to resection due to non-small cell lung cancer (NSCLC) staged as II or IIIA. However, although various chemotherapy regimens that include cisplatin have been used in phase III trials, the best choice remains unclear. The objective of this study was to describe the experience of the Instituto Nacional do Câncer (INCA, Brazilian National Cancer Institute), located in the city of Rio de Janeiro, Brazil, with the use of the cisplatin-etoposide combination in such patients, with a special focus on survival data.

METHODS

We retrospectively evaluated the medical charts of the patients receiving adjuvant therapy for NSCLC at the INCA between 2004 and 2008.

RESULTS

We included 51 patients, all of whom were treated with the cisplatin-etoposide combination. The median follow-up period was 31 months, and the median overall survival was 57 months. In the univariate analysis, median survival was lower in the patients submitted to chemotherapy plus radiotherapy than in those submitted to chemotherapy alone (19 vs. 57 months; p < 0.001), and there was a trend toward lower median survival in stage III patients than in stage I-II patients (34 vs. 57 months; p = 0.22). Overall survival was not significantly associated with gender (p = 0.70), histological pattern (p = 0.33), or cisplatin dose (p = 0.13).

CONCLUSIONS

Our results support the use of adjuvant chemotherapy, and our survival data are similar to those reported in major randomized clinical trials. However, long-term follow-up is warranted in this population.

Molecular biology of lung cancer: clinical implications

Lung cancer is a heterogeneous disease clinically, biologically, histologically, and molecularly. Understanding the molecular causes of this heterogeneity, which might reflect changes occurring in different classes of epithelial cells or different molecular changes occurring in the same target lung epithelial cells, is the focus of current research. Identifying the genes and pathways involved, determining how they relate to the biological behavior of lung cancer, and their utility as diagnostic and therapeutic targets are important basic and translational research issues. This article reviews current information on the key molecular steps in lung cancer pathogenesis, their timing, and clinical implications.

Targeted therapies for lung cancer: clinical experience and novel agents

Although lung cancer remains the leading cancer killer in the United States, recently a number of developments indicate future clinical benefit. These include evidence that computed tomography-based screening decreases lung cancer mortality, the use of stereotactic radiation for early-stage tumors, the development of molecular methods to predict chemotherapy sensitivity, and genome-wide expression and mutation analysis data that have uncovered oncogene "addictions" as important therapeutic targets. Perhaps the most significant advance in the treatment of this challenging disease is the introduction of molecularly targeted therapies, a term that currently includes monoclonal antibodies and small-molecule tyrosine kinase inhibitors. The development of effective targeted therapeutics requires knowledge of the genes and pathways involved and how they relate to the biologic behavior of lung cancer. Drugs targeting the epidermal growth factor receptor, anaplastic lymphoma kinase, and vascular endothelial growth factor are now U.S. Food and Drug Administration approved for the treatment of advanced non-small cell lung cancer. These agents are generally better tolerated than conventional chemotherapy and show dramatic efficacy when their use is coupled with a clear understanding of clinical data, mechanism, patient selection, drug interactions, and toxicities. Integrating genome-wide tumor analysis with drug- and targeted agent-responsive phenotypes will provide a wealth of new possibilities for lung cancer-targeted therapeutics. Ongoing research efforts in these areas as well as a discussion of emerging targeted agents being evaluated in clinical trials are the subjects of this review.

A computational index derived from whole-genome copy number analysis is a novel tool for prognosis in early stage lung squamous cell carcinoma

Squamous cell carcinoma of the lung is remarkable for the extent to which the same chromosomal abnormalities are detected in individual tumours. We have used next generation sequencing at low coverage to produce high resolution copy number karyograms of a series of 89 non-small cell lung tumours specifically of the squamous cell subtype. Because this methodology is able to create karyograms from formalin-fixed paraffin-embedded material, we were able to use archival stored samples for which survival data were available and correlate frequently occurring copy number changes with disease outcome. No single region of genomic change showed significant correlation with survival. However, adopting a whole-genome approach, we devised an algorithm that relates to total genomic damage, specifically the relative ratios of copy number states across the genome. This algorithm generated a novel index, which is an independent prognostic indicator in early stage squamous cell carcinoma of the lung.