Subgroup Of Non-small Cell Lung Cancer Patients Research Articles

Abstract 4509: Mitochondrial DNA copy number is inversely associated with overall survival in non-small cell lung cancer

Abstract Mitochondria play an important role in generating energy for vital cellular functions. Alterations in mitochondria function due to mutations or copy number changes can potentially lead to tumorigenesis. Although previous studies have investigated the effect of mitochondrial DNA (mtDNA) depletion on cancer risk, no studies have assessed constitutive mtDNA copy number as a prognostic marker for overall survival in non-small cell lung cancer (NSCLC). Towards this, we measured mtDNA content by a quantitative real-time PCR assay in peripheral blood lymphocytes collected prior to treatment from 1,134 NSCLC cases seen at MD Anderson Cancer Center. A significant inverse dose-response trend was identified for mtDNA content and NSCLC risk (p-value: 0.0076). Those with the highest tertile of mtDNA content had the greatest reduction in risk of dying (HR: 0.81, 95% CI: 0.82-0.97, p-value: 0.014) and a highly significantly enhanced median survival time of 20.20 months compared to only 14.11 months for those with the lowest mtDNA content (p-value: 6.7x10-5). It is known that exposure to tobacco smoke results in the production of reactive oxygen species that can damage mtDNA. Therefore, we also performed stratified analysis based on smoking status. The effect in ever smokers (N=951) mirrored that of the overall population with a significant reduction in risk of death with increasing mtDNA content (p-trend: 0.008) and a dramatic nearly seven month survival advantage for those patients with the highest mtDNA content compared to the lowest (20.73 months compared to 13.98 months, respectively, p-value: 4.1x10-5). Interestingly, mtDNA content was not significant with overall survival in never smokers (N=183), suggesting that the effect in the overall population was driven by the ever smokers and that mtDNA alterations do not play a major role in the course of disease for this unique subgroup of NSCLC patients. Together, these results demonstrate that mtDNA content is a potential prognostic biomarker in NSCLC that can be measured non-invasively prior to treatment to provide needed information regarding course of disease to identify those at high risk for a poor outcome. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4509. doi:1538-7445.AM2012-4509

Abstract 903: Expression of estrogen receptor beta together with aromatase predicts survival in non-small cell lung cancer

Abstract Lung cancer continues to be the leading cause of cancer mortality. There is increasing evidence suggesting estrogens and estrogen signaling play a significant role in lung cancer pathophysiology. Estrogen receptors (ER) alpha and beta are expressed in normal lung and many non-small cell lung cancers. Previously we found that in women 65 years and older with non-small cell lung cancer (NSCLC), higher aromatase levels in tumor cells conferred a worse prognosis for survival. Here we examine whether ER alpha and ER beta levels in conjunction with aromatase can further define different patient groups with respect to survival outcomes and possible treatment regimens. Methods: Immunohistochemistry was performed on a high-density tissue microarray with marker data and clinical information available for 378 patients. Patients were subcategorized by gender, age, smoking status and tumor histology. Survival data was determined using the Cox proportional hazards model and Kaplan-Meier curves. Results: Unlike aromatase, neither ER alpha nor ER beta alone were predictors of survival in NSCLC patients or any subset of these patients examined. However, when coupled with aromatase expression, higher ER beta levels predicted poorer survival in those patients whose tumors expressed higher levels of aromatase. Although this survival difference was present in patients of both genders, it was more pronounced in women > 65 years old, where higher expression of both ER beta and aromatase showed a markedly worse survival rate than that determined by aromatase alone. Conclusion: Combined expression of ER beta with aromatase has predictive value for survival in different gender and age subgroups of NSCLC patients. This predictive value is stronger than each individual marker alone. These results suggest that possibly treatment with aromatase inhibitors alone or combined with estrogen receptor modulators may have benefit in some subpopulations of NSCLC patients. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 903. doi:10.1158/1538-7445.AM2011-903

Optimizing response to gefitinib in the treatment of non-small-cell lung cancer

The epidermal growth factor receptor (EGFR) is expressed in the majority of non-small-cell lung cancer (NSCLC). However, only a restricted subgroup of NSCLC patients respond to treatment with the EGFR tyrosine kinase inhibitor (EGFR TKI) gefitinib. Clinical trials have demonstrated that patients carrying activating mutations of the EGFR significantly benefit from treatment with gefitinib. In particular, mutations of the EGFR TK domain have been shown to increase the sensitivity of the EGFR to exogenous growth factors and, at the same time, to EGFR TKIs such as gefitinib. EGFR mutations are more frequent in patients with particular clinical and pathological features such as female sex, nonsmoker status, adenocarcinoma histology, and East Asian ethnicity. A close correlation was found between EGFR mutations and response to gefitinib in NSCLC patients. More importantly, randomized Phase III studies have shown the superiority of gefitinib compared with chemotherapy in EGFR mutant patients in the first-line setting. In addition, gefitinib showed a good toxicity profile with an incidence of adverse events that was significantly lower compared with chemotherapy. Therefore, gefitinib is a major breakthrough for the management of EGFR mutant NSCLC patients and represents the first step toward personalized treatment of NSCLC.

Predictive Biomarkers to Tyrosine Kinase Inhibitors for the Epidermal Growth Factor Receptor in Non-Small-Cell Lung Cancer

The epidermal growth factor receptor (EGFR) and its ligands are frequently expressed in non-small-cell lung cancer (NSCLC). The EGFR tyrosine kinase inhibitors (TKIs) erlotinib and gefitinib have shown clinical activity in NSCLC. However, only a small subgroup of NSCLC patients respond to these agents, suggesting that patients' selection is critical for TKIs sensitivity. In this regard, several studies have tried to individuate prognostic and predictive factors that are associated with sensitivity or resistance to anti-EGFR agents. A strong correlation between activating mutations in the EGFR-TK domain and response to erlotinib and gefitinib has been reported in different trials. However, patients without EGFR mutations might also benefit of treatment with these drugs by experiencing prolonged disease stabilization. No significant correlation between EGFR overexpression and response to treatment has been found, while controversial results have been reported regarding the association between EGFR gene amplification and clinical response to TKIs. Different mechanisms of resistance to EGFR-TKIs have also been described. Mutations of KRAS, that occur in approximately 20% of NSCLC, are associated with reduced response to EGFR-TKIs. The EGFR T790M mutation, that reduces the affinity of the EGFR to gefitinib and erlotinib, and MET gene amplification produce acquired resistance to anti-EGFR agents. Taken together, these findings suggest that several different molecular alterations regulate the sensitivity of NSCLC cells to EGFR-TKIs, and that a comprehensive approach to this phenomenon is necessary for an appropriate selection of patients that should be treated with these drugs.

Targeted Therapy for Locally Advanced or Metastatic Non-Small Cell Lung Cancer—Patient Selection Changes the Fate of Gefitinib

Non-small cell lung cancer (NSCLC) presents one of the greatest clinical challenges in oncology. The prevalence of cigarette smoking is the major cause for the high incidence that makes NSCLC the commonest cause of cancer-related death in the western world. Patients frequently present late, with locally advanced or metastatic disease. In this often incurable situation, treatment is delivered with the aim of maximising quality and duration of life. The chosen therapy should, therefore, carry the lowest risk of side-effects in order to maximise clinical benefit. Conventional chemotherapy is typically associated with a long list of possible side effects that may be at best inconvenient, and at worst, dangerous. This group of patients, who may be frail from advanced age, advanced disease stage or additional co-morbidities, would clearly benefit from less toxic but equally effective therapies. Targeted therapeutic agents that inhibit key cell signalling pathways such as the epidermal growth factor receptor (EGFR) have been developed over the last 15 years and have demonstrated proof of principle in clinical trials. The small molecule tyrosine kinase (TK) inhibitors, such as gefitinib, are now established as particularly effective first-line therapy in the subgroup of NSCLC patients whose tumours display EGFR TK mutations that confer sensitivity. Gefitinib has been shown to be non-inferior to docetaxel in second-line therapy, and to have a better side effect profile and more rapid improvement in quality of life than chemotherapy, particularly in patients over 70 years. The publication of landmark studies and consequent changes in licensing have made 2009 the most significant year for gefitinib to date, and we describe the most recent data in the context of relevant translational research. gefitinib, lung cancer, metastatic, advanced, tyrosine kinase inhibitor, epidermal growth factor receptor

Clinicopathological features and epidermal growth factor receptor mutations associated with epithelial–mesenchymal transition in non‐small cell lung cancer

Small molecular inhibitors of the epidermal growth factor receptor (EGFR) have been extensively studied in non-small cell lung cancer (NSCLC) patients. The discovery of molecular biomarkers that identify the subgroups of NSCLC patients benefiting from EGFR tyrosine kinase inhibitor (TKI) has become an important area of investigation. Recent studies have suggested that epithelial-mesenchymal transition (EMT) in tumours decreases the cellular requirements for EGFR signalling pathway, and this may provide a molecular signature to define those NSCLC patients most likely to respond to treatment with targeted EGFR TKI. This research explored the clinicopathological features and EGFR mutations associated with EMT in NSCLC. The EMT status in surgically resected specimens from 62 patients with NSCLC was tested by immunohistochemical staining. The frequency of tumour epithelial phenotype was calculated and the strength of the association with clinicopathological features and EGFR genotype was determined by logistic regression. The overall frequency of the epithelial phenotype was 35.48% (22 of 62). Based on univariate analyses, the frequency of the epithelial phenotype (E-cadherin-positive) was greater for EGFR mutants versus wild types (77.78% vs 18.18%; P < 0.0001) and women versus men (54.55% vs 25%; P = 0.02). Multivariate logistic analysis showed that only the EGFR genotype (odds ratio, 0.063; 95% CI: 0.013-0.3; P = 0.0005) was significantly associated with the epithelial phenotype. In patients with NSCLC, there is a higher frequency of epithelial markers in patients with EGFR mutation.

Validation of proteomic classifier for clinical benefit from erlotinib as first line treatment for advanced non-small cell lung cancer (ECOG 3503)

7508 Background: In this study we tested the ability of our serum mass spectrometry classifier of clinical benefit from gefitinib to classify pre-treatment sera and plasma samples from non-small cell lung cancer (NSCLC) patients treated first line with erlotinib in ECOG E3503. Methods: Pretreatment serum and plasma samples were available from 73 of the 96 previously untreated advanced NSCLC patients treated with single agent erlotinib on ECOG protocol 3503, 13 subjects had only serum samples, and 10 had only plasma samples. All of these samples analyzed in replicate by MALDI mass spectrometry (MS). A prediction algorithm we established based on a training cohort of 139 patients treated second or third line with gefitinib was used to classify these patients for survival and time to progression, and results obtained from serum and plasma were compared when both were available Results: We found that the signals for the 8 distinct mass-to-charge (m/z) features used in our classifier were highly concordant between serum and plasma samples from the same patient, and that there was no difference in the classification of the patients between serum and plasma when both were available. Therefore we classified all 96 patients using serum if available, and plasma if not. The classification algorithm very successfully classified patients into groups with good and poor survival (median survival of 306 days vs 107 days, p = 0.0007). With the available follow-up, the time to progression was also statistically significant in this group (p = 0.007, data not shown). In a Cox multivariate analysis including the most significant univariate parameters PS (0 vs. 1 vs 2), number of involved sites (=3 vs &gt;3) and prior weight loss (&lt;5% vs = 5%), the MALDI MS classification algorithm retained independent significance at p = 0.03, with a hazard ratio of 0.53. Conclusions: This multi-institutional ECOG study demonstrates that MALDI MS can assist in the pre-treatment selection of a subgroup of NSCLC patients who are likely to show improved survival after treatment with first line erlotinib. No significant financial relationships to disclose.

Mass Spectrometry to Classify Non–Small-Cell Lung Cancer Patients for Clinical Outcome After Treatment With Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors: A Multicohort Cross-Institutional Study

Some but not all patients with non-small-cell lung cancer (NSCLC) respond to treatment with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs). We developed and tested the ability of a predictive algorithm based on matrix-assisted laser desorption ionization (MALDI) mass spectrometry (MS) analysis of pretreatment serum to identify patients who are likely to benefit from treatment with EGFR TKIs. Serum collected from NSCLC patients before treatment with gefitinib or erlotinib were analyzed by MALDI MS. Spectra were acquired independently at two institutions. An algorithm to predict outcomes after treatment with EGFR TKIs was developed from a training set of 139 patients from three cohorts. The algorithm was then tested in two independent validation cohorts of 67 and 96 patients who were treated with gefitinib and erlotinib, respectively, and in three control cohorts of patients who were not treated with EGFR TKIs. The clinical outcomes of survival and time to progression were analyzed. An algorithm based on eight distinct m/z features was developed based on outcomes after EGFR TKI therapy in training set patients. Classifications based on spectra acquired at the two institutions had a concordance of 97.1%. For both validation cohorts, the classifier identified patients who showed improved outcomes after EGFR TKI treatment. In one cohort, median survival of patients in the predicted "good" and "poor" groups was 207 and 92 days, respectively (hazard ratio [HR] of death in the good versus poor groups = 0.50, 95% confidence interval [CI] = 0.24 to 0.78). In the other cohort, median survivals were 306 versus 107 days (HR = 0.41, 95% CI = 0.17 to 0.63). The classifier did not predict outcomes in patients who did not receive EGFR TKI treatment. This MALDI MS algorithm was not merely prognostic but could classify NSCLC patients for good or poor outcomes after treatment with EGFR TKIs. This algorithm may thus assist in the pretreatment selection of appropriate subgroups of NSCLC patients for treatment with EGFR TKIs.

Serum Proteomic Classifier for Predicting Response to Epidermal Growth Factor Receptor Inhibitor Therapy: Have We Built a Better Mousetrap?

The ability to predict treatment response and clinical (survival) outcomes is one of the two “holy grails” of cancer biomarker development, the other being early detection or risk stratification by population screening ( 1 ). In advanced non – small-cell lung cancer (NSCLC), small-molecule tyrosine kinase inhibitors (TKIs) of the epidermal growth factor receptor (EGFR) represent a breakthrough for targeted therapy, yet only a small proportion of patients (especially among non – East Asians) appear to benefit from these expensive agents ( 2 , 3 ). Previous studies have shown that EGFR immunohistochemistry, tyrosine kinase domain mutations, and/or EGFR gene copy number by fluorescent in situ hybridization (FISH) are biomarkers that are potentially useful to select patients more likely to benefit from EGFR TKIs ( 4 – 6 ). Aside from the incomplete validation of these markers for routine clinical implementation, mutation and FISH analyses are limited by tissue availability and, at times, technical feasibility ( 5 ). Therefore, a strongly predictive but simple blood-based test has great potential for becoming the ultimate biomarker for selecting patients who are likely to benefit from EGFR TKI therapy. In this issue of the Journal, Taguchi et al. ( 7 ) report a proteomic algorithm (signature) that classifi es patients according to their likely outcomes after EGFR TKI therapy. This algorithm was generated by matrix-assisted laser desorption ionization (MALDI) mass spectroscopy (MS) analysis of pretreatment sera or plasma of patients. The authors used a training set of 139 patients treated with second- or greater-line gefi tinib who were recruited from three separate institutions in Europe or Asia to discover eight MALDI signature peaks that form the predictive algorithm. This classifi er was then validated in two independent cohorts of gefi tinibor erlotinib-treated patients from Italy and the United States. In fact, this study marks the fi rst large-scale multi-institutional evaluation of an MS-based protein signature in the serum or plasma of NSCLC patients for predicting EGFR TKI – related clinical outcomes. The study showed that, despite variability in the source or nature of samples studied and in the spectra generated by different operators, the data preprocessing and normalization procedures were able to generate MALDI MS features that were reproducible in two independent laboratories. Furthermore, the clinical outcome classifi er (which classifi ed patients into good, poor, or undefi ned classes) was validated in two independent cohorts of patients receiving fi rst- or greater-line gefi tinib or erlotinib therapy. More important, the authors claim that the algorithm is predictive and not prognostic, in that its classifi cation capability failed in three separate cohorts of patients who were not treated with EGFR TKIs. The authors conclude that their eight-peak MALDI MS algorithm might assist in the pretreatment selection of appropriate subgroups of NSCLC pa tients for

CN-II expression predicts survival in patients receiving gemcitabine for advanced non-small cell lung cancer

Resistance to gemcitabine is likely to be multifactorial and could involve a number of mechanisms involved in drug penetration, metabolism and targeting. In vitro studies of resistant human cell lines have confirmed that human equilibrative nucleoside transporter 1 (hENT1)-deficient cells display resistance to gemcitabine. Overexpression of certain nucleotidases, such as cN-II, has also been frequently shown in gemcitabine-resistant models. In this study, we applied immunohistochemical methods to assess the protein abundance of cN-II, hENT1, human concentrative nucleoside transporter 3 (hCNT3) and deoxycitidine kinase (dCK) in malignant cells in from 43 patients with treatment-naïve locally advanced or metastatic non-small cell lung cancer (NSCLC). All patients subsequently received gemcitabine-based chemotherapy. Response to chemotherapy, progression-free survival (PFS), and overall survival (OS) were correlated with abundance of these proteins. Among the 43 samples, only 7 (16%) expressed detectable hENT1, with a low percentage of positive cells, 18 expressed hCNT3 (42%), 36 (86%) expressed cN-II and 28 (66%) expressed dCK. In univariate analysis, only cN-II expression levels were correlated with overall survival. None of the parameters were correlated with freedom from progression survival nor with response. Patients with low levels of expression of cN-II (less than 40% positively stained cells) had worse overall survival than patients with higher levels of cN-II expression (6 months and 11 months, respectively). In a multivariate analysis taking into account age, sex, weight loss, stage and immunohistochemical results, cN-II was the only predictive factor associated with overall survival. This study suggests that cN-II nucleotidase expression levels identify subgroups of NSCLC patients with different outcomes under gemcitabine-based therapy. Larger prospective studies are warranted to confirm the predictive value of cN-II in these patients.

Simple cytokeratins in the serum of patients with lung cancer: relationship to cell death.

An important role in differentiation and proliferation has been demonstrated for the 20 cytokeratin (CK) polypeptides. The serum of 24 patients with biopsy-proven non-small cell lung cancer (NSCLC) and a similar number of controls was examined for evidence of CK8 and CK18. Using enzyme-linked immunosorbent assay (ELISA), all the control sera were negative, but 9 of the 24 patients were positive (mean 2.62 ng/ml; range 1.4-5.8; P = 0.0036). Western blotting confirmed the results of the ELISA in all cases, and indicated full size CK polypeptides. Advanced stage disease patients were more likely to be seropositive (P = 0.00024). Biopsy specimens showed CK8 expression in all 24 cases by immunochemistry and CK18 in 22 cases. This is the first study to demonstrate that a subgroup of NSCLC patients have intact CK8 and CK18 peptides in their serum, and their detection may correlate with advanced disease.