Histopathologic and genetic alterations as predictors of response to treatment and survival in lung cancer: A review of published data

A comparison study of monoexponential and fractional order calculus diffusion models and 18F-FDG PET in differentiating benign and malignant solitary pulmonary lesions and their pathological types

Objective

To evaluate the application value of monoexponential, fractional order calculus (FROC) diffusion models and PET imaging to distinguish between benign and malignant solitary pulmonary lesions (SPLs) and malignant SPLs with different pathological types and explore the correlation between each parameter and Ki67 expression.

Methods

A total of 112 patients were enrolled in this study. Prior to treatment, all patients underwent a dedicated thoracic ¹⁸F-FDG PET/MR examination. Five parameters [including apparent diffusion coefficient (ADC) derived from the monoexponential model; diffusion coefficient (D), a microstructural quantity (μ), and fractional order parameter (β) derived from the FROC model and maximum standardized uptake value (SUVmax) derived from PET] were compared between benign and malignant SPLs and different pathological types of malignant SPLs. Independent sample t test, Mann-Whitney U test, DeLong test and receiver operating characteristic (ROC) curve analysis were used for statistical evaluation. Pearson correlation analysis was used to calculate the correlations between Ki-67 and ADC, D, μ, β, and SUVmax.

Results

The ADC and D values were significantly higher and the μ and SUVmax values were significantly lower in the benign group [1.57 (1.37, 2.05) μm²/ms, 1.59 (1.52, 1.72) μm²/ms, 5.06 (3.76, 5.66) μm, 5.15 ± 2.60] than in the malignant group [1.32 (1.03, 1.51) μm²/ms, 1.43 (1.29, 1.52) μm²/ms, 7.06 (5.87, 9.45) μm, 9.85 ± 4.95]. The ADC, D and β values were significantly lower and the μ and SUVmax values were significantly higher in the squamous cell carcinoma (SCC) group [1.29 (0.66, 1.42) μm²/ms, 1.32 (1.02, 1.42) μm²/ms, 0.63 ± 0.10, 9.40 (7.76, 15.38) μm, 11.70 ± 5.98] than in the adenocarcinoma (AC) group [1.40 (1.28, 1.67) μm²/ms, 1.52 (1.44, 1.64) μm²/ms, 0.70 ± 0.10, 5.99 (4.54, 6.87) μm, 8.76 ± 4.18]. ROC curve analysis showed that for a single parameter, μ exhibited the best AUC value in discriminating between benign and malignant SPLs groups and AC and SCC groups (AUC = 0.824 and 0.911, respectively). Importantly, the combination of monoexponential, FROC models and PET imaging can further improve diagnostic performance (AUC = 0.872 and 0.922, respectively). The Pearson correlation analysis showed that Ki67 was positively correlated with μ value and negatively correlated with ADC and D values (r = 0.402, -0.346, -0.450, respectively).

Conclusion

The parameters D and μ derived from the FROC model were superior to ADC and SUVmax in distinguishing benign from malignant SPLs and adenocarcinoma from squamous cell carcinoma, in addition, the combination of multiple parameters can further improve diagnostic performance. The non-Gaussian FROC diffusion model is expected to become a noninvasive quantitative imaging technique for identifying SPLs.

Three-Dimensional Texture Feature Analysis of Pulmonary Nodules in CT Images: Lung Cancer Predictive Models Based on Support Vector Machine Classifier

To extract texture features of pulmonary nodules from three-dimensional views and to assess if predictive models of lung CT images from a three-dimensional texture feature could improve assessments conducted by radiologists. Clinical and CT imaging data for three dimensions (axial, coronal, and sagittal) in pulmonary nodules in 285 patients were collected from multiple centers and the Cancer Imaging Archive after ethics committee approval. Three-dimensional texture feature values (contourlets), and clinical and computed tomography (CT) imaging data were built into support vector machine (SVM) models to predict lung cancer, using four evaluation methods (disjunctive, conjunctive, voting, and synthetic); sensitivity, specificity, the Youden index, discriminant power (DP), and F value were calculated to assess model effectiveness. Additionally, diagnostic accuracy (three-dimensional model, axial model, and radiologist assessment) was assessed using the area under the curves for receiver operating characteristic (ROC) curves. Cross-sectional data from 285 patients (median age, 62 [range, 45-83] years; 115 males [40.4%]) were evaluated. Integrating three-dimensional assessments, the voting method had relatively high effectiveness based on both sensitivity (0.98) and specificity (0.79), which could improve radiologist diagnosis (maximum sensitivity, 0.75; maximum specificity, 0.51) for 23% and 28% respectively. Furthermore, the three-dimensional texture feature model of the voting method has the best diagnosis of precision rate (95.4%). Of all three-dimensional texture feature methods, the result of the voting method was the best, maintaining both high sensitivity and specificity scores. Additionally, the three-dimensional texture feature models were superior to two-dimensional models and radiologist-based assessments.

Second-Generation Antimitotics in Cancer Clinical Trials

Mitosis represents a promising target to block cancer cell proliferation. Classical antimitotics, mainly microtubule-targeting agents (MTAs), such as taxanes and vinca alkaloids, are amongst the most successful anticancer drugs. By disrupting microtubules, they activate the spindle assembly checkpoint (SAC), which induces a prolonged delay in mitosis, expected to induce cell death. However, resistance, toxicity, and slippage limit the MTA's effectiveness. With the desire to overcome some of the MTA's limitations, mitotic and SAC components have attracted great interest as promising microtubule-independent targets, leading to the so-called second-generation antimitotics (SGAs). The identification of inhibitors against most of these targets, and the promising outcomes achieved in preclinical assays, has sparked the interest of academia and industry. Many of these inhibitors have entered clinical trials; however, they exhibited limited efficacy as monotherapy, and failed to go beyond phase II trials. Combination therapies are emerging as promising strategies to give a second chance to these SGAs. Here, an updated view of the SGAs that reached clinical trials is here provided, together with future research directions, focusing on inhibitors that target the SAC components.

Histological coherent Raman imaging: a prognostic review

Histopathology plays a central role in diagnosis of many diseases including solid cancers. Efforts are underway to transform this subjective art to an objective and quantitative science. Coherent Raman imaging (CRI), a label-free imaging modality with sub-cellular spatial resolution and molecule-specific contrast possesses characteristics which could support the qualitative-to-quantitative transition of histopathology. In this work we briefly survey major themes related to modernization of histopathology, review applications of CRI to histopathology and, finally, discuss potential roles for CRI in the transformation of histopathology that is already underway.

Evaluation of Detection Methods and Values of Circulating Vascular Endothelial Growth Factor in Lung Cancer

Lung cancer is the deadliest cancer in the world. Angiogenesis plays a crucial role of the incidence, progression, and metastasis in lung cancer. Angiogenesis inhibitors are used to treat non-small cell lung cancer (NSCLC) patients, and the molecular biomarkers are also being assessed to predict treatment response/therapeutic response and patients' prognosis. Vascular endothelial growth factor (VEGF) is a signal protein produced by cells that stimulates angiogenesis. Due to its predictive values of prognosis on NSCLC, a large number of methods have been developed and evaluated to detect VEGF levels in a variety of studies. In this article, we review the detection methods designed to measure the VEGF levels in different body fluids and prognosticate the value of VEGF in treatment, diagnosis and survival in lung cancer.

EGFR, KRAS, and BRAF mutational profiles of female patients with micropapillary predominant invasive lung adenocarcinoma

Background/aim: This study aimed to analyze EGFR, KRAS, and BRAF mutations in females with micropapillary predominant invasive lung adenocarcinoma and their relationships with immunohistochemical and clinicopathological patterns.Materials and methods: A total of 15 females with micropapillary lung adenocarcinoma were selected. Mutational analysis of the EGFR, KRAS, and BRAF genes was carried out. Information regarding the demographic data, tumor size, treatment, and survival time for each patient was collated, and the predominant cell type, secondary architectural growth patterns, psammoma bodies, necrosis, and visceral pleural and angiolymphatic invasions were evaluated.Results: We identified EGFR mutation in six cases, KRAS mutation in three cases, and BRAF mutation in one case. EGFR, c-kit, VEGFR, and bcl-2 positivity was observed in ten, seven, four, and six cases, respectively. All cases were positive for VEGF (strong positivity in 11 cases and weak positivity in four cases) and bcl-2 (strong positivity in nine cases and weak positivity in six cases). Seven (46.6%) cases were positive for c-kit and 10 (66.6%) cases were positive for EGFR. Conclusion: EGFR mutation occurred at a higher incidence rate in micropapillary predominant invasive adenocarcinoma than has previously been found in conventional lung adenocarcinomas. KRAS mutation was observed as having a similar frequency to what was previously observed, but the frequency of BRAF mutation was lower than previously reported.

Time since start of first-line therapy as a predictive clinical marker for nintedanib in patients with previously treated non-small cell lung cancer

Introduction

No predictive clinical or genetic markers have been identified or validated for antiangiogenic agents in lung cancer. We aimed to identify a predictive clinical marker of benefit for nintedanib, an angiokinase inhibitor, using data from two large second-line non-small cell lung cancer Phase III trials (LUME-Lung 1 ([LL1] and LUME-Lung 2).

Methods

Predictive marker identification was conducted in a multi-step process using data from both trials; a hypothesis was generated, confirmed and validated. Statistical analyses included a stepwise selection approach, a recursive partitioning method and the evaluation of HRs, including treatment-by-covariate interactions. The marker was finally validated using a prospectively defined hierarchical testing procedure and treatment-by-covariate interaction for overall survival (OS) based on LL1.

Results

Time since start of first-line therapy (TSFLT) was identified as the only predictive clinical marker. A cut-off of 9 months was chosen for further analysis, based on HRs and recursive partitioning. The prospectively defined final validation using OS data from LL1 established the strong relationship between TSFLT and treatment with nintedanib. Patients with adenocarcinoma with TSFLT <9 months showed a greater survival benefit (median OS 10.9 vs 7.9 months, HR 0.75 [95% CI 0.60–0.92]; p=0.0073) compared with patients in the TSFLT >9 months group (median OS 17.0 vs 15.1 months, HR 0.89 [95% CI 0.66–1.19]).

Conclusions

Patients with shorter TSFLT derive a greater progression-free survival and OS benefit from nintedanib. This clinical marker could be used for patient selection and further investigation is warranted regarding pathways promoting aggressive tumour growth and antiangiogenic tyrosine kinase inhibitor benefit.

Long non-coding RNA TUG1 is involved in cell growth and chemoresistance of small cell lung cancer by regulating LIMK2b via EZH2

BACKGROUND

Taurine upregulated gene1 (TUG1) as a 7.1-kb lncRNA, has been shown to play an oncogenic role in various cancers. However, the biological functions of lncRNA TUG1 in small cell lung cancer (SCLC) remain unknown. The aim of this study is to explore the roles of TUG1 in cell growth and chemoresistance of SCLC and its possible molecular mechanism.

METHODS

The expression of TUG1 in thirty-three cases of SCLC tissues and SCLC cell line were examined by quantitative RT-PCR (qRT-PCR). The functional roles of TUG1 in SCLC were demonstrated by CCK8 assay, colony formation assay, wound healing assay and transwell assay, flow cytometry analysis and in vivo study through siRNA or shRNA mediated knockdown. Western blot assays were used to evaluate gene and protein expression in cell lines. Chromatin immunoprecipitation (ChIP) and RNA binding protein immunoprecipitation (RIP) were performed to confirm the molecular mechanism of TUG1 involved in cell growth and chemoresistance of small cell lung cancer.

RESULTS

We found that TUG1 was overexpressed in SCLC tissues, and its expression was correlated with the clinical stage and the shorter survival time of SCLC patients. Moreover, downregulation of TUG1 expression could impair cell proliferation and increased cell sensitivity to anticancer drugs both in vitro and in vivo. We also discovered that TUG1 knockdown significantly promoted cell apoptosis and cell cycle arrest, and inhibited cell migration and invasion in vitro . We further demonstrated that TUG1 can regulate the expression of LIMK2b (a splice variant of LIM-kinase 2) via binding with enhancer of zeste homolog 2 (EZH2), and then promoted cell growth and chemoresistance of SCLC.

CONCLUSIONS

Together, these results suggested that TUG1 mediates cell growth and chemoresistance of SCLC by regulating LIMK2b via EZH2.

MKP1 mediates chemosensitizer effects of E1a in response to cisplatin in non-small cell lung carcinoma cells

The adenoviral gene E1a is known to enhance the antitumor effect of cisplatin, one of the cornerstones of the current cancer chemotherapy. Here we study the molecular basis of E1a mediated sensitivity to cisplatin in an experimental model of Non-small cell lung cancer. Our data show how E1a blocks the induction of autophagy triggered by cisplatin and promotes the apoptotic response in resistant cells. Interestingly, at the molecular level, we present evidences showing how the phosphatase MKP1 is a major determinant of cisplatin sensitivity and its upregulation is strictly required for the induction of chemosensitivity mediated by E1a. Indeed, E1a is almost unable to promote sensitivity in H460, in which the high expression of MKP1 remains unaffected by E1a. However, in resistant cell as H1299, H23 or H661, which display low levels of MKP1, E1a expression promotes a dramatic increase in the amount of MKP1 correlating with cisplatin sensitivity. Furthermore, effective knock down of MKP1 in H1299 E1a expressing cells restores resistance to a similar extent than parental cells.

In summary, the present work reinforce the critical role of MKP1 in the cellular response to cisplatin highlighting the importance of this phosphatase in future gene therapy approach based on E1a gene.

Advances in EGFR as a Predictive Marker in Lung Adenocarcinoma

BACKGROUND

Worldwide, lung cancer is the most common cause of mortality. Toxins from tobacco smoke are known to increase the risk of lung cancer; however, up to 15% of lung cancer-related deaths in men and up to 50% of lung cancer-related deaths in women occur in people who do not smoke. Despite the fact that chemotherapy generally provides a survival benefit for non-small-cell lung cancer, not every patient will respond to therapy and many experience therapy-related adverse events. Thus, predictive markers are used to determine which patients are more likely to respond to a given regimen.

METHODS

We reviewed the current medical literature in English relating to predictive markers that may be positive, such as the presence of an activating EGFR mutation.

RESULTS

The advances in using EGFR as a molecular predictive marker were summarized. This biomarker influences therapeutic response in patients with lung adenocarcinoma. Clinical evidence supporting its value is also reviewed.

CONCLUSIONS

The use of EGFR as a predictive factor in lung adenocarcinoma may help target therapy to individual tumors to achieve the best likelihood for long-term survival and to avoid adverse events from medications unlikely to be effective.

In vitro evaluation of antitumoral efficacy of catalase in combination with traditional chemotherapeutic drugs against human lung adenocarcinoma cells

Lung cancer is the most lethal cancer-related disease worldwide. Since survival rates remain poor, there is an urgent need for more effective therapies that could increase the overall survival of lung cancer patients. Lung tumors exhibit increased levels of oxidative markers with altered levels of antioxidant defenses, and previous studies demonstrated that the overexpression of the antioxidant enzyme catalase (CAT) might control tumor proliferation and aggressiveness. Herein, we evaluated the effect of CAT treatment on the sensitivity of A549 human lung adenocarcinoma cells toward various anticancer treatments, aiming to establish the best drug combination for further therapeutic management of this disease. Exponentially growing A549 cells were treated with CAT alone or in combination with chemotherapeutic drugs (cisplatin, 5-fluorouracil, paclitaxel, daunorubicin, and hydroxyurea). CalcuSyn(®) software was used to assess CAT/drug interactions (synergism or antagonism). Growth inhibition, NFκB activation status, and redox parameters were also evaluated in CAT-treated A549 cells. CAT treatment caused a cytostatic effect, decreased NFκB activation, and modulated the redox parameters evaluated. CAT treatment exhibited a synergistic effect among most of the anticancer drugs tested, which is significantly correlated with an increased H2O2 production. Moreover, CAT combination caused an antagonism in paclitaxel anticancer effect. These data suggest that combining CAT (or CAT analogs) with traditional chemotherapeutic drugs, especially cisplatin, is a promising therapeutic strategy for the treatment of lung cancer.

Correlation between vascular endothelial growth factor and quantitative dual-energy spectral CT in non-small-cell lung cancer

AIM

To explore the correlation between the expression level of vascular endothelial growth factor (VEGF) in non-small-cell lung cancer (NSCLC) tissue and quantitative parameters of spectral computed tomography (CT) imaging.

MATERIALS AND METHODS

Forty-eight patients with NSCLC underwent a spectral CT imaging protocol before surgical tumour resection. The repetition of iodine concentration, water concentration, and CT values at 40 keV in the region of interest were measured. The slopes of spectral attenuation curves (λHU) in the region were also calculated. The level of VEGF expression in the tumour tissue was measured using an immunohistochemical method (MaxVision method). The quantitative parameters of spectral CT imaging were compared among different levels of VEGF expression using one-way analysis of variance (ANOVA) and least significant difference (SLD) test. The correlation between VEGF expression and spectral CT imaging was estimated through Spearman's rank correlation analysis.

RESULTS

There were significant differences in iodine concentrations, λHU, and CT values at 40 KeV in NSCLC between the groups showing negative and moderately positive expression of VEGF (p=0.001, 0.000, and 0.001, respectively) as well as between those showing mildly and moderately positive expression of VEGF (p=0.047, 0.005, and 0.002, respectively). In addition, all of the iodine concentrations, λHU values, and CT values at 40 KeV displayed a significant and positive correlation with the level of VEGF expression (r=0.413, 0.458, and 0.393, respectively, p<0.05).

CONCLUSIONS

Quantitative parameters of spectral CT imaging may be helpful for evaluating the status of angiogenesis in NSCLC.

Expression profiling of receptor tyrosine kinases in high-grade neuroendocrine carcinoma of the lung: a comparative analysis with adenocarcinoma and squamous cell carcinoma

Background

As the comprehensive genomic analysis of small cell lung cancer (SCLC) progresses, novel treatments for this disease need to be explored. With attention to the direct connection between the receptor tyrosine kinases (RTKs) of tumor cells and the pharmacological effects of specific inhibitors, we systematically assessed the RTK expressions of high-grade neuroendocrine carcinomas of the lung [HGNECs, including SCLC and large cell neuroendocrine carcinoma (LCNEC)].

Patients and methods

Fifty-one LCNEC and 61 SCLC patients who underwent surgical resection were enrolled in this research. As a control group, 202 patients with adenocarcinomas (ADCs) and 122 patients with squamous cell carcinomas (SQCCs) were also analyzed. All the tumors were stained with antibodies for 10 RTKs: c-Kit, EGFR, IGF1R, KDR, ERBB2, FGFR1, c-Met, ALK, RET, and ROS1.

Results

The LCNEC and SCLC patients exhibited similar clinicopathological characteristics. The IHC scores for each RTK were almost equivalent between the LCNEC and SCLC groups, but they were significantly different from those of the ADC or SQCC groups. In particular, c-Kit was the only RTK that was remarkably expressed in both LCNECs and SCLCs. On the other hand, about 20 % of the HGNEC tumors exhibited strongly positive RTK expression, and this rate was similar to those for the ADC and SQCC tumors. Intriguingly, strongly positive RTKs were almost mutually exclusive in individual tumors.

Conclusions

Compared with ADC or SQCC, LCNEC and SCLC had similar expression profiles for the major RTKs. The exclusive c-Kit positivity observed among HGNECs suggests that c-Kit might be a distinctive RTK in HGNEC.

Electronic supplementary material

The online version of this article (doi:10.1007/s00432-015-1989-z) contains supplementary material, which is available to authorized users.

Nintedanib: examining the development and mechanism of action of a novel triple angiokinase inhibitor

Antiangiogenic agents are effective standard-of-care options in several malignancies, but are generally associated with only modest improvements in survival, as well as leading to additional toxicities. Furthermore, almost all patients develop acquired resistance to therapy, possibly due to the activation of alternative proangiogenic pathways. Here we discuss: the rationale for developing nintedanib, an agent that simultaneously inhibits signaling pathways activated by platelet-derived growth factor, FGF, as well as VEGF; how its distinctive inhibitory and pharmacokinetic profile could underlie promising efficacy and tolerability observed in Phase II trials in patients with relapsed/refractory non-small cell lung cancer, advanced ovarian cancer and metastatic colorectal cancer; the ongoing Phase III program that is assessing nintedanib in these areas of major unmet medical need; and recent progress in the development of biomarkers that may predict response to nintedanib.

Contrasting responses of non-small cell lung cancer to antiangiogenic therapies depend on histological subtype

The vascular endothelial growth factor (VEGF) pathway is a clinically validated antiangiogenic target for non-small cell lung cancer (NSCLC). However, some contradictory results have been reported on the biological effects of antiangiogenic drugs. In order to evaluate the efficacy of these drugs in NSCLC histological subtypes, we analyzed the anticancer effect of two anti-VEGFR2 therapies (sunitinib and DC101) in chemically induced mouse models and tumorgrafts of lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC). Antiangiogenic treatments induced vascular trimming in both histological subtypes. In ADC tumors, vascular trimming was accompanied by tumor stabilization. In contrast, in SCC tumors, antiangiogenic therapy was associated with disease progression and induction of tumor proliferation. Moreover, in SCC, anti-VEGFR2 therapies increased the expression of stem cell markers such as aldehyde dehydrogenase 1A1, CD133, and CD15, independently of intratumoral hypoxia. In vitro studies with ADC cell lines revealed that antiangiogenic treatments reduced pAKT and pERK signaling and inhibited proliferation, while in SCC-derived cell lines the same treatments increased pAKT and pERK, and induced survival. In conclusion, this study evaluates for the first time the effect of antiangiogenic drugs in lung SCC murine models in vivo and sheds light on the contradictory results of antiangiogenic therapies in NSCLC.

Comparative evaluation of support vector machines for computer aided diagnosis of lung cancer in CT based on a multi-dimensional data set

Lung cancer is one of the most common forms of cancer resulting in over a million deaths per year worldwide. In this paper, the usage of support vector machine (SVM) classification for lung cancer is investigated, presenting a systematic quantitative evaluation against Boosting, Decision trees, k-nearest neighbor, LASSO regressions, neural networks and random forests. A large database of 5984 regions of interest (ROIs) and 488 input features (including textural features, patient characteristics, and morphological features) were used to train the classifiers and evaluate for their performance. The evaluation for classifiers' performance was based on a tenfold cross validation framework, receiver operating characteristic curve (ROC), and Matthews correlation coefficient. Area under curve (AUC) of SVM, Boosting, Decision trees, k-nearest neighbor, LASSO, neural networks, random forests were 0.94, 0.86, 0.73, 0.72, 0.91, 0.92, and 0.85, respectively. It was proved that SVM classification offered significantly increased classification performance compared to the reference methods. This scheme may be used as an auxiliary tool to differentiate between benign and malignant SPNs of CT images in future.

Computer-aided diagnosis for early-stage lung cancer based on longitudinal and balanced data

Background

Lung cancer is one of the most common forms of cancer resulting in over a million deaths per year worldwide. Typically, the problem can be approached by developing more discriminative diagnosis methods. In this paper, computer-aided diagnosis was used to facilitate the prediction of characteristics of solitary pulmonary nodules in CT of lungs to diagnose early-stage lung cancer.

Methods

The synthetic minority over-sampling technique (SMOTE) was used to account for raw data in order to balance the original training data set. Curvelet-transformation textural features, together with 3 patient demographic characteristics, and 9 morphological features were used to establish a support vector machine (SVM) prediction model. Longitudinal data as the test data set was used to evaluate the classification performance of predicting early-stage lung cancer.

Results

Using the SMOTE as a pre-processing procedure, the original training data was balanced with a ratio of malignant to benign cases of 1∶1. Accuracy based on cross-evaluation for the original unbalanced data and balanced data was 80% and 97%, respectively. Based on Curvelet-transformation textural features and other features, the SVM prediction model had good classification performance for early-stage lung cancer, with an area under the curve of the SVMs of 0.949 (P<0.001). Textural feature (standard deviation) showed benign cases had a higher change in the follow-up period than malignant cases.

Conclusions

With textural features extracted from a Curvelet transformation and other parameters, a sensitive support vector machine prediction model can increase the rate of diagnosis for early-stage lung cancer. This scheme can be used as an auxiliary tool to differentiate between benign and malignant early-stage lung cancers in CT images.

Specific Biomarkers Are Associated with Docetaxeland Gemcitabine-Resistant NSCLC Cell Lines

Five-year survival rate for lung cancer is limited to 10% to 15%. Therefore, the identification of novel therapeutic prognostic factors is an urgent requirement. The aim of this study is thus to highlight specific biomarkers in chemoresistant non-small cell lung cancer cell lines. Therefore, we checked-in the control condition as well as after short-term pharmacological treatment with either docetaxel or gemcitabine-the expression of genes such as tumor suppressor genes (CDKN2A, DAPK, FHIT, GSTP1, MGMT, RARβ2, RASSF1A, and TIMP3), genes associated with drug resistance (BRCA1, COX2, ERCC1, IGFBP3, RRM1, and TUBB3), and stemness-related genes (CD133, OCT4, and SLUG) in two cellular models of squamous carcinoma (CAEP) and adenocarcinoma (RAL) of the lung originally established. Their promoter methylation profile was also evaluated. Drug-related genes were upregulated. Cisplatin resistance matched with high levels of BRCA1 and ERCC1 in both cell lines; docetaxel sensitivity of CAEP cells was associated to levels of TUBB3 lower than RAL cells. Although CAEP cells were more sensitive to gemcitabine, both cell lines showed high levels of RRM1. Stemness-related genes were downregulated in the control condition but became upregulated in docetaxel-resistant cells, indicating the selection of a population with stemness features. We did not find an unequivocal correspondence between gene expression and respective DNA promoter methylation status, suggesting the involvement of additional mechanisms of gene expression regulation. These results highlight specific biomarkers consistent with the different responses of the two cell lines to standard pharmacological treatments and indicate specific molecular traits for their chemoresistance.

Expression, prognostic and predictive impact of VEGF and bFGF in non-small cell lung cancer

Despite major advances in cancer therapeutics, the prognosis for lung cancer patients is still poor and the median survival for patients presenting with advanced non-small cell lung cancer (NSCLC) is only 8-10 months. Angiogenesis is an important biological process and a relatively early event during lung cancer pathogenesis. Anti-angiogenic agents are used in treating patients with NSCLC, and their molecular biomarkers are also being assessed to predict response. A better understanding of the biology of angiogenesis in NSCLC may reveal new targets for treating this malignancy. In this article, we review the expression and prognostic impact of the angiogenic growth factors, vascular endothelial growth factor and basic fibroblast growth factor, in NSCLC.

Association of copy number loss of CDKN2B and PTCH1 with poor overall survival in patients with pulmonary squamous cell carcinoma

BACKGROUND AND PURPOSE

Although lung cancer is the leading cause of cancer deaths worldwide, reliable markers allowing prediction of patient survival at the time of initial diagnosis are still lacking. Copy number alterations (CNAs) in tumor tissue DNA have been associated with tumorigenesis and malignant progression. We aimed at identification of gene-level CNAs with prognostic value for survival in pulmonary squamous cell carcinoma (SCC).

METHODS

The CNA status of a panel of 44 genes was analyzed by high-resolution array comparative genomic hybridization (CGH) in 49 SCC samples. Overall survival information (median follow-up, 40 months) for the patients was collected and used to assess outcome correlations with gene CNAs.

RESULTS

Survival analysis showed that both CDKN2B loss and PTCH1 loss were associated with poor survival (both P < .001, log-rank test). Multivariate Cox analysis, including CDKN2B loss and PTCH1 loss as well as age, sex, cigarette smoking status, tumor size, tumor differentiation, and TNM stage showed that CDKN2B loss (hazard ratio [HR], 17.88; 95% confidence interval [CI], 4.40-72.67; P < .001) and PTCH1 loss (HR, 10.81; 95% CI, 1.92-60.98; P = .007) were independent prognostic factors for poor survival. In addition the PTCH1 loss was more frequently found in moderately or poorly differentiated tumors than in well-differentiated tumors (P = .007).

CONCLUSION

These findings suggest that 2 genes of loss, CDKN2B and PTCH1, are associated with poor overall survival in patients with SCC of the lung and may be useful as prognostic markers.

Balance between MKK6 and MKK3 mediates p38 MAPK associated resistance to cisplatin in NSCLC

The p38 MAPK signaling pathway has been proposed as a critical mediator of the therapeutic effect of several antitumor agents, including cisplatin. Here, we found that sensitivity to cisplatin, in a system of 7 non-small cell lung carcinoma derived cell lines, correlated with high levels of MKK6 and marked activation of p38 MAPK. However, knockdown of MKK6 modified neither the response to cisplatin nor the activation of p38 MAPK. Deeper studies showed that resistant cell lines also displayed higher basal levels of MKK3. Interestingly, MKK3 knockdown significantly decreased p38 phosphorylation upon cisplatin exposure and consequently reduced the response to the drug. Indeed, cisplatin poorly activated MKK3 in resistant cells, while in sensitive cell lines MKK3 showed the opposite pattern in response to the drug. Our data also demonstrate that the low levels of MKK6 expressed in resistant cell lines are the consequence of high basal activity of p38 MAPK mediated by the elevated levels of MKK3. This finding supports the existence of a regulatory mechanism between both MAPK kinases through their MAPK. Furthermore, our results were also mirrored in head and neck carcinoma derived cell lines, suggesting our observations boast a potential universal characteristic in cancer resistance of cisplatin. Altogether, our work provides evidence that MKK3 is the major determinant of p38 MAPK activation in response to cisplatin and, hence, the resistance associated with this MAPK. Therefore, these data suggest that the balance between both MKK3 and MKK6 could be a novel mechanism which explains the cellular response to cisplatin.

Common genetic variants in cell cycle pathway are associated with survival in stage III-IV non-small-cell lung cancer

Cell cycle progression contributes to the cellular response to DNA-damaging factors, such as chemotherapy and radiation. We hypothesized that the genetic variations in cell cycle pathway genes may modulate treatment responses and affect survival in patients with advanced non-small-cell lung cancer (NSCLC). We genotyped 374 single-nucleotide polymorphisms (SNPs) from 49 cell cycle-related genes in 598 patients with stages III-IV NSCLC treated with first-line platinum-based chemotherapy with/without radiation. We analyzed the individual and combined associations of these SNPs with survival and evaluated their gene-gene interactions using survival tree analysis. In the analysis of survival in all the patients, 39 SNPs reached nominal significance (P < 0.05) and 4 SNPs were significant at P <0.01. However, none of these SNPs remained significant after correction for multiple comparisons at a false discovery rate of 10%. In stratified analysis by treatment modality, after adjusting for multiple comparisons, nine SNPs in chemotherapy alone and one SNP in chemoradiation remained significant. The most significant SNP in chemotherapy group was CCNB2:rs1486878 [hazard ratio (HR) = 1.69, 95% confidence interval (CI), 1.25-2.30, P = 0.001]. TP73: rs3765701 was the only significant SNP in chemoradiation group (HR = 1.87; 95% CI = 1.35-2.59, P = 1.8 × 10(-4)). In cumulative analysis, we found a significant gene-dosage effect in patients receiving chemotherapy alone. Survival tree analysis demonstrated potential higher order gene-gene and gene-treatment interactions, which could be used to predict survival status based on distinct genetic signatures. These results suggest that genetic variations in cell cycle pathway genes may affect the survival of patients with stages III-IV NSCLC individually and jointly.

Validation of cofilin-1 as a biomarker in non-small cell lung cancer: application of quantitative method in a retrospective cohort

PURPOSE

Cofilin is a cytoskeletal protein whose overexpression has been associated with aggressiveness in several types of malignancies. Here, we established and optimized a simple semi-quantitative immunohistochemistry (SQ-IHC) method for cofilin quantification in tumor biopsies, and applied it in a retrospective cohort of NSCLC patients aiming at validating the use of cofilin-1 as a prognostic biomarker.

METHODS

The SQ-IHC method for cofilin-1 quantification was established and applied in a NSCLC cohort. An archival collection of biopsies from 50 patients with clinicopathological information and 5 years follow-up was accessed. Association between cofilin-1 immunocontent and clinical outcome was assessed using standard Kaplan-Meier mortality curves and the log-rank test. To evaluate the robustness of our findings, three different partitional clustering strategies were used to stratify patients into two groups according to the biomarker expression level (hierarchical clustering, Kmeans and median cutoff).

RESULTS

In all the three different partitional clustering we used, survival analysis showed that patient with high cofilin-1 immunocontent had a lower overall survival rate (P < 0.05), and could be used to discriminate between good and bad prognosis. No other correlation was found when the variables age, sex or histological type were tested in association with patients outcome or with cofilin immunocontent.

CONCLUSIONS

Our method showed good sensitivity/specificity to indicate the outcome of patients according to their cofilin immunocontent in biological samples. Its application in a retrospective cohort and the results presented here are an important step toward the validation process of cofilin-1 as a prognostic biomarker.

A benefit-risk assessment of erlotinib in non-small-cell lung cancer and pancreatic cancer

Non-small-cell lung cancer (NSCLC) and pancreatic cancer represent two major causes of cancer-related morbidity and mortality worldwide. Conventional cytotoxic agents seem to have reached a therapeutic plateau in the last decade but prognosis remains dismal for both tumour types. Recent advances in molecular biology have allowed the development of novel molecular agents that target specific pathways implicated in the process of neoplastic transformation. Epidermal growth factor receptor (EGFR) represents an appealing therapeutic target in both malignancies and a number of EGFR-targeting agents have recently been approved for the first- or second-line treatment of locally advanced, recurrent or metastatic disease. Erlotinib, an orally administered EGFR tyrosine kinase inhibitor has recently received approval by both the US FDA and the European Medicines Agency (EMA) for the treatment of advanced NSCLC after chemotherapy failure and in combination with gemcitabine for the treatment of advanced pancreatic cancer, on the basis of large, randomized, phase III trials that demonstrated survival benefit over standard therapy or best supportive care. Erlotinib toxicity, as reported in these trials, seems to be modest, with the most prevalent adverse events being fatigue, acneiform rash and diarrhoea. However, recent pharmacovigilance reports, as well as sporadic case reports from the literature, raise concern of some serious adverse events, including pulmonary toxicity, sepsis and some rare cases of treatment-related deaths. In the current review, we present an evidence-based summary of the benefits and risks associated with erlotinib treatment in both advanced NSCLC and pancreatic cancer. Evidence for survival benefit in each of the drug's indications is provided, and treatment-related risks and costs are discussed. Finally, synthetic evaluation of the benefit-risk equilibrium is attempted, in order to help clinicians put this drug into perspective.

[Long-term survival of personalized surgical treatment of locally advanced non-small cell lung cancer based on molecular staging]

BACKGROUND AND OBJECTIVE

Approximately 35%-40% of patients with newly diagnosed non-small cell Lung cancer have locally advanced disease. The average survival time of these patients only have 6-8 months with chemotherapy. The aim of this study is to explore and summarize the probability of detection of micrometastasis in peripheral blood for molecular staging, and for selection of indication of surgical treatment, and beneficiary of neoadjuvant chemotherapy and postoperative adjuvant therapy in locally advanced lung cancer; to summarize the long-time survival result of personalized surgical treatment of 516 patients with locally advanced non-small cell lung cancer based on molecular staging methods.

METHODS

CK19 mRNA expression of peripheral blood samples was detected in 516 lung cancer patients by RT-PCR before operation for molecular diagnosis of micrometastasis, personalized molecular staging, and for selection of indication of surgical treatment and the beneficiary of neoadjuvant chemotherapy and postoperative adjuvant therapy in patients with locally advanced nonsmall cell lung cancer invaded heart, great vessels or both. The long-term survival result of personalized surgical treatment was retrospectively analyzed in 516 patients with locally advanced non-small cell lung cancer based on molecular staging methods.

RESULTS

There were 322 patients with squamous cell carcinoma and 194 cases with adenocarcinoma in the series of 516 patients with locally advanced lung cancer involved heart, great vessels or both. There were 112 patients with IIIA disease and 404 cases with IIIB disease according to P-TNM staging. There were 97 patients with M-IIIA disease, 278 cases with M-IIIB disease and 141 cases with III disease according to our personalized molecular staging. Of the 516 patients, bronchoplastic procedures and pulmonary artery reconstruction was carried out in 256 cases; lobectomy combined with resection and reconstruction of partial left atrium was performed in 41 cases; Double sleeve lobectomy combined with resection and reconstruction of super vena cava was carried out in 90 cases; Lobectomy combined with resection and reconstruction of diaphragm was performed in 3 cases; Double sleeve lobectomy combined with resection and reconstruction of partial left atrium was performed in 30 cases; Bronchoplastic procedures and pulmonary artery reconstruction combined with reconstruction of aorta sheath was carried out in 10 cases; Right pneumonectomy combined with resection and reconstruction partial left atrium, total right diaphragm with Dacron, and post cava and right liver vein was performed in one case; Lobectomy combined with resection and reconstruction of carina was carried out in 10 cases; Bronchoplastic procedures and pulmonary artery reconstruction combined with resection and reconstruction of carina and superior vane cava, or combined with superior vena cava and left atrium, or with carina and left atrium was performed in 55 cases in this series. Five patients died of operative complications and the operative mortality was 0.97%. CK19 mRNA expression was found in 141 patients. The positive rate of CK19 mRNA expression was 27.3% in peripheral blood samples in the 516 cases. The positive rates of micrometastasis in peripheral blood was significantly related to histological classification, P-TNM staging and N staging of the cancer (P < 0.05), but not to age, sex, smoking status of the patients, and size of primary tumor, and locations of the tumor (P > 0.05). The median survival time was 43.74 months. The 1, 3, 5 and 10 year survival rates of the 516 cases was 89.1%, 39.3%, 19.8% and 10.4%, respectively. The postoperative survival rate was remarkably correlated with micrometastasis in peripheral blood, histological classification of the tumor, size of primary cancer and lymph mode involvement (P < 0.05). The results of multivariable Cox model analysis showed that "personalized molecular P-TNM staging", micrometastasis in peripheral blood, pathological types of the tumor and mediastinal lymph node metastasis of the cancer were the most significant factors for predicting prognosis in the patients with locally advanced nonsmall lung cancer.

CONCLUSIONS

(1) Micrometastasis was existed in peripheral blood of patients with lung cancer, which can not be detected with conventional methods. (2) Detecting of CK19 mRNA expression in peripheral blood in lung cancer patients can be used for diagnosis of micrometastasis of lung cancer and "molecular staging" and "molecular P-TNM staging" for lung cancer patients. It will be helpful for selection of surgical treatment indication, the beneficiary of neoadjuvant chemotherapy and postoperative adjuvant therapy in the patients with locally advanced non-small cell lung cancer. (3) Personalized surgical treatment can significantly improve prognosis and increase curative rate and long-term survival rate of locally advanced nonsmall cell lung cancer based on personalized molecular staging.