Inhibition of TXNRD or SOD1 overcomes NRF2-mediated resistance to β-lapachone

Alterations in the NRF2/KEAP1 pathway result in the constitutive activation of NRF2, leading to the aberrant induction of antioxidant and detoxification enzymes, including NQO1. The NQO1 bioactivatable agent β-lapachone can target cells with high NQO1 expression but relies in the generation of reactive oxygen species (ROS), which are actively scavenged in cells with NRF2/KEAP1 mutations. However, whether NRF2/KEAP1 mutations influence the response to β-lapachone treatment remains unknown. To address this question, we assessed the cytotoxicity of β-lapachone in a panel of NSCLC cell lines bearing either wild-type or mutant KEAP1. We found that, despite overexpression of NQO1, KEAP1 mutant cells were resistant to β-lapachone due to enhanced detoxification of ROS, which prevented DNA damage and cell death. To evaluate whether specific inhibition of the NRF2-regulated antioxidant enzymes could abrogate resistance to β-lapachone, we systematically inhibited the four major antioxidant cellular systems using genetic and/or pharmacologic approaches. We demonstrated that inhibition of the thioredoxin-dependent system or copper-zinc superoxide dismutase (SOD1) could abrogate NRF2-mediated resistance to β-lapachone, while depletion of catalase or glutathione was ineffective. Interestingly, inhibition of SOD1 selectively sensitized KEAP1 mutant cells to β-lapachone exposure. Our results suggest that NRF2/KEAP1 mutational status might serve as a predictive biomarker for response to NQO1-bioactivatable quinones in patients. Further, our results suggest SOD1 inhibition may have potential utility in combination with other ROS inducers in patients with KEAP1/NRF2 mutations

Gene expression patterns that predict sensitivity to epidermal growth factor receptor tyrosine kinase inhibitors in lung cancer cell lines and human lung tumors

BACKGROUND: Increased focus surrounds identifying patients with advanced non-small cell lung cancer (NSCLC) who will benefit from treatment with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKI). EGFR mutation, gene copy number, coexpression of ErbB proteins and ligands, and epithelial to mesenchymal transition markers all correlate with EGFR TKI sensitivity, and while prediction of sensitivity using any one of the markers does identify responders, individual markers do not encompass all potential responders due to high levels of inter-patient and inter-tumor variability. We hypothesized that a multivariate predictor of EGFR TKI sensitivity based on gene expression data would offer a clinically useful method of accounting for the increased variability inherent in predicting response to EGFR TKI and for elucidation of mechanisms of aberrant EGFR signalling. Furthermore, we anticipated that this methodology would result in improved predictions compared to single parameters alone both in vitro and in vivo. RESULTS: Gene expression data derived from cell lines that demonstrate differential sensitivity to EGFR TKI, such as erlotinib, were used to generate models for a priori prediction of response. The gene expression signature of EGFR TKI sensitivity displays significant biological relevance in lung cancer biology in that pertinent signalling molecules and downstream effector molecules are present in the signature. Diagonal linear discriminant analysis using this gene signature was highly effective in classifying out-of-sample cancer cell lines by sensitivity to EGFR inhibition, and was more accurate than classifying by mutational status alone. Using the same predictor, we classified human lung adenocarcinomas and captured the majority of tumors with high levels of EGFR activation as well as those harbouring activating mutations in the kinase domain. We have demonstrated that predictive models of EGFR TKI sensitivity can classify both out-of-sample cell lines and lung adenocarcinomas. CONCLUSION: These data suggest that multivariate predictors of response to EGFR TKI have potential for clinical use and likely provide a robust and accurate predictor of EGFR TKI sensitivity that is not achieved with single biomarkers or clinical characteristics in non-small cell lung cancers

An essential role for Stat3 in regulating IgG immune complex‐induced pulmonary inflammation

Growing evidence suggests that transcription factor signal transducer and activator of transcription (Stat) 3 may play an important regulatory role during inflammation. However, the function of Stat3 in acute lung injury (ALI) is largely unknown. In the current study, by using an adenoviral vector expressing a dominant‐negative Stat3 isoform (Ad‐Stat3‐EVA), we determined the role of Stat3 in IgG immune complex (IC)‐induced inflammatory responses and injury in the lung from C57BL/6J mice. We show that IgG IC‐induced DNA binding activity of Stat3 in the lung was significantly inhibited by Stat3‐EVA. We demonstrate that both lung vascular permeability (albumin leak) and lung myeloperoxidase accumulation in the Ad‐Stat‐EVA treated mice were substantially reduced when compared with values in mice receiving control virus (Ad‐GFP) during the injury. Furthermore, intratracheal administration of Ad‐Stat3‐EVA caused significant decreases in the contents of neutrophils, inflammatory cytokines (TNF‐α and IL‐6), chemokines [keratinocyte cell‐derived chemokine, macrophage inflammatory protein (MIP)‐1α, and MIP‐1β], and complement component C5a in bronchoalveolar lavage fluids. Using Stat3‐specific small interfering RNA, we show that knocking down Stat3 expression in alveolar macrophages (MH‐S cells) significantly reduced the production of proinflammatory mediators on IgG IC stimulation. These data suggest that Stat3 plays an essential role in the pathogenesis of IgG IC‐induced ALI by mediating the acute inflammatory responses in the lung and alveolar macrophages.—Tang, H., Yan, C., Cao, J., Sarma, J. V., Haura, E. B., Wu, M., Gao, H. An essential role for Stat3 in regulating IgG immune complex‐induced pulmonary inflammation. FASEB J. 25, 4292–4300 (2011). www.fasebj.orgPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154500/1/fsb2fj11187955.pd

MUC1 Is a Downstream Target of STAT3 and Regulates Lung Cancer Cell Survival and Invasion

Signal transducer and activator of transcription 3 (STAT3) is aberrantly activated in human cancer including lung cancer and has been implicated in transformation, tumorigenicity, and metastasis. One putative downstream gene regulated by Stat3 is MUC1 which also has important roles in tumorigenesis. We determined if Stat3 regulates MUC1 in lung cancer cell lines and what function MUC1 plays in lung cancer cell biology. We examined MUC1 expression in non-small cell lung cancer (NSCLC) cell lines and found high levels of MUC1 protein expression associated with higher levels of tyrosine phosphorylated STAT3. STAT3 knockdown downregulated MUC1 expression whereas constitutive STAT3 expression increased MUC1 expression at mRNA and protein levels. MUC1 knockdown induced cellular apoptosis concomitant with reduced Bcl-XL and sensitized cells to cisplatin treatment. MUC1 knockdown inhibited tumor growth and metastasis in an orthotopic mouse model of lung cancer by activating apoptosis and inhibiting cell proliferation in vivo. These results demonstrate that constitutively activated STAT3 regulates expression of MUC1, which mediates lung cancer cell survival and metastasis in vitro and in vivo. MUC1 appears to be a cooperating oncoprotein with multiple oncogenic tyrosine kinase pathways and could be an effective target for the treatment of lung cancer

Utilization of Target Lesion Heterogeneity For Treatment Efficacy assessment in Late Stage Lung Cancer

RATIONALE: Recent studies have discovered several unique tumor response subgroups outside of response classification by Response Evaluation Criteria for Solid Tumors (RECIST), such as mixed response and oligometastasis. These subtypes have a distinctive property, lesion heterogeneity defined as diversity of tumor growth profiles in RECIST target lesions. Furthermore, many cancer clinical trials have been activated to evaluate various treatment options for heterogeneity-related subgroups (e.g., 29 trials so far listed in clinicaltrials.gov for cancer patients with oligometastasis). Some of the trials have shown survival benefit by tailored treatment strategies. This evidence presents the unmet need to incorporate lesion heterogeneity to improve RECIST response classification. METHOD: An approach for Lesion Heterogeneity Classification (LeHeC) was developed using a contemporary statistical approach to assess target lesion variation, characterize patient treatment response, and translate informative evidence to improving treatment strategy. A mixed effect linear model was used to determine lesion heterogeneity. Further analysis was conducted to classify various types of lesion variation and incorporate with RECIST to enhance response classification. A study cohort of 110 target lesions from 36 lung cancer patients was used for evaluation. RESULTS: Due to small sample size issue, the result was exploratory in nature. By analyzing RECIST target lesion data, the LeHeC approach detected a high prevalence (n = 21; 58%) of lesion heterogeneity. Subgroup classification revealed several informative distinct subsets in a descending order of lesion heterogeneity: mix of progression and regression (n = 7), mix of progression and stability (n = 9), mix of regression and stability (n = 5), and non-heterogeneity (n = 15). Evaluation for association of lesion heterogeneity and RECIST best response classification showed lesion heterogeneity commonly occurred in each response group (stable disease: 16/27; 59%; partial response: 3/5; 60%; progression disease: 2/4; 50%). Survival analysis showed a differential trend of overall survival between heterogeneity and non-heterogeneity in RECIST response groups. CONCLUSION: This is the first study to evaluate lesion heterogeneity, an underappreciated metric, for RECIST application in oncology clinical trials. Results indicated lesion heterogeneity is not an uncommon event. The LeHeC approach could enhance RECIST response classification by utilizing granular lesion level discovery of heterogeneity

Functional signaling pathway analysis of lung adenocarcinomas identifies novel therapeutic targets for KRAS mutant tumors

Little is known about the complex signaling architecture of KRAS and the interconnected RAS-driven protein-protein interactions, especially as it occurs in human clinical specimens. This study explored the activated and interconnected signaling network of KRAS mutant lung adenocarcinomas (AD) to identify novel therapeutic targets. Thirty-four KRAS mutant (MT) and twenty-four KRAS wild-type (WT) frozen biospecimens were obtained from surgically treated lung ADs. Samples were subjected to Laser Capture Microdissection and Reverse Phase Protein Microarray analysis to explore the expression/activation levels of 150 signaling proteins along with coactivation concordance mapping. An independent set of 90 non-small cell lung cancers (NSCLC) was used to validate selected findings by immunohistochemistry (IHC). Compared to KRAS WT tumors, the signaling architecture of KRAS MT ADs revealed significant interactions between KRAS downstream substrates, the AKT/mTOR pathway, and a number of Receptor Tyrosine Kinases (RTK). Approximately one-third of the KRAS MT tumors had ERK activation greater than the WT counterpart (p < 0.01). Notably 18% of the KRAS MT tumors had elevated activation of the Estrogen Receptor alpha (ER-α) (p=0.02).This finding was verified in an independent population by IHC (p=0.03). KRAS MT lung ADs appear to have a more intricate RAS linked signaling network than WT tumors with linkage to many RTKs and to the AKT-mTOR pathway. Combination therapy targeting different nodes of this network may be necessary to treat this group of patients. In addition, for patients with KRAS MT tumors and activation of the ER-α, anti-estrogen therapy may have important clinical implications

cAMP/CREB-regulated LINC00473 marks LKB1-inactivated lung cancer and mediates tumor growth

The LKB1 tumor suppressor gene is frequently mutated and inactivated in non–small cell lung cancer (NSCLC). Loss of LKB1 promotes cancer progression and influences therapeutic responses in preclinical studies; however, specific targeted therapies for lung cancer with LKB1 inactivation are currently unavailable. Here, we have identified a long noncoding RNA (lncRNA) signature that is associated with the loss of LKB1 function. We discovered that LINC00473 is consistently the most highly induced gene in LKB1-inactivated human primary NSCLC samples and derived cell lines. Elevated LINC00473 expression correlated with poor prognosis, and sustained LINC00473 expression was required for the growth and survival of LKB1-inactivated NSCLC cells. Mechanistically, LINC00473 was induced by LKB1 inactivation and subsequent cyclic AMP–responsive element–binding protein (CREB)/CREB-regulated transcription coactivator (CRTC) activation. We determined that LINC00473 is a nuclear lncRNA and interacts with NONO, a component of the cAMP signaling pathway, thereby facilitating CRTC/CREB-mediated transcription. Collectively, our study demonstrates that LINC00473 expression potentially serves as a robust biomarker for tumor LKB1 functional status that can be integrated into clinical trials for patient selection and treatment evaluation, and implicates LINC00473 as a therapeutic target for LKB1-inactivated NSCLC

Role of LKB1-CRTC1 on Glycosylated COX-2 and Response to COX-2 Inhibition in Lung Cancer

Cyclooxygenase-2 (COX-2) directs the synthesis of prostaglandins including PGE-2 linking inflammation with mitogenic signaling. COX-2 is also an anticancer target, however, treatment strategies have been limited by unreliable expression assays and by inconsistent tumor responses to COX-2 inhibition

Common \u3cem\u3eTDP1\u3c/em\u3e Polymorphisms in Relation to Survival Among Small Cell Lung Cancer Patients: A Multicenter Study from the International Lung Cancer Consortium

Background—DNA topoisomerase inhibitors are commonly used for treating small-cell lung cancer (SCLC). Tyrosyl-DNA phosphodiesterase (TDP1) repairs DNA damage caused by this class of drugs and may therefore influence treatment outcome. In this study, we investigated whether common TDP1 single-nucleotide polymorphisms (SNP) are associated with overall survival among SCLC patients. Methods—Two TDP1 SNPs (rs942190 and rs2401863) were analyzed in 890 patients from 10 studies in the International Lung Cancer Consortium (ILCCO). The Kaplan–Meier method and Cox regression analyses were used to evaluate genotype associations with overall mortality at 36 months postdiagnosis, adjusting for age, sex, race, and tumor stage. Results—Patients homozygous for the minor allele (GG) of rs942190 had poorer survival compared with those carrying AA alleles, with a HR of 1.36 [95% confidence interval (CI): 1.08–1.72, P = 0.01), but no association with survival was observed for patients carrying the AG genotype (HR = 1.04, 95% CI, 0.84–1.29, P = 0.72). For rs2401863, patients homozygous for the minor allele (CC) tended to have better survival than patients carrying AA alleles (HR = 0.79; 95% CI, 0.61–1.02, P = 0.07). Results from the Genotype Tissue Expression (GTEx) Project, the Encyclopedia of DNA Elements (ENCODE), and the ePOSSUM web application support the potential function of rs942190. Conclusions—We found the rs942190 GG genotype to be associated with relatively poor survival among SCLC patients. Further investigation is needed to confirm the result and to determine whether this genotype may be a predictive marker for treatment efficacy of DNA topoisomerase inhibitors