Genomic Data from NSCLC Tumors Reveals Correlation between SHP-2 Activity and PD-L1 Expression and Suggests Synergy in Combining SHP-2 and PD-1/PD-L1 Inhibitors

The identification of novel therapies, new strategies for combination of therapies, and repurposing of drugs approved for other indications are all important for continued progress in the fight against lung cancers. Antibodies that target immune checkpoints can unmask an immunologically hot tumor from the immune system of a patient. However, despite accounts of significant tumor regression resulting from these medications, most patients do not respond. In this study, we sought to use protein expression and RNA sequencing data from The Cancer Genome Atlas and two smaller studies deposited onto the Gene Expression Omnibus (GEO) to advance our hypothesis that inhibition of SHP-2, a tyrosine phosphatase, will improve the activity of immune checkpoint inhibitors (ICI) that target PD-1 or PD-L1 in lung cancers. We first collected protein expression data from The Cancer Proteome Atlas (TCPA) to study the association of SHP-2 and PD-L1 expression in lung adenocarcinomas. RNA sequencing data was collected from the same subjects through the NCI Genetic Data Commons and evaluated for expression of the PTPN11 (SHP-2) and CD274 (PD-L1) genes. We then analyzed RNA sequencing data from a series of melanoma patients who were either treatment naïve or resistant to ICI therapy. PTPN11 and CD274 expression was compared between groups. Finally, we analyzed gene expression and drug response data collected from 21 non-small cell lung cancer (NSCLC) patients for PTPN11 and CD274 expression. From the three studies, we hypothesize that the activity of SHP-2, rather than the expression, likely controls the expression of PD-L1 as only a weak relationship between PTPN11 and CD274 expression in either lung adenocarcinomas or melanomas was observed. Lastly, the expression of CD274, not PTPN11, correlates with response to ICI in NSCLC

A MicroRNA Signature of Response to Erlotinib is Descriptive of TGFβ Behaviour in NSCLC

Our previous work identified a 13-gene miRNA signature predictive of response to the epidermal growth factor receptor (EGFR) inhibitor, erlotinib, in Non-Small Cell Lung Cancer cell lines. Bioinformatic analysis of the signature showed a functional convergence on TGFβ canonical signalling. We hypothesized that TGFβ signalling controls expression of the miRNA genes comprising an erlotinib response signature in NSCLC. Western analysis revealed that TGFβ signalling via Smad2/3/4 occurred differently between erlotinib-resistant A549 and erlotinib- sensitive PC9 cells. We showed that TGFβ induced an interaction between Smad4 and putative Smad Binding Elements in PC9. However, qRT-PCR analysis showed that endogenous miR-140/141/200c expression changes resulted from time in treatments, not the treatments themselves. Moreover, flow cytometry indicated that cells exited the cell cycle in the same manner. Taken together these data indicated that the miRNA comprising the signature are likely regulated by the cell cycle rather than by TGFβ. Importantly, this work revealed that TGFβ did not induce EMT in PC9 cells, but rather TGFβ-inhibition induced an EMT-intermediate. These data also show that growth/proliferation signals by constitutively-activated EGFR may rely on TGFβ and a possible relationship between TGFβ and EGFR signalling may prevent EMT progression in this context rather than promote it

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

Statin Use and Venous Thromboembolism in Cancer: A Large, Active Comparator, Propensity Score Matched Cohort Study

Background—Statins have been shown to have a protective effect for venous thromboembolism (VTE) in the general population. This study sought to assess the association between statins and the risk for cancer-associated deep vein thrombosis (DVT) and pulmonary embolism (PE). Methods—Patients with newly diagnosed cancer were followed for up to one year in a healthcare claims database (2010–2013). Three treatment groups included statin users, non-statin cholesterol lowering medication users, and an untreated group with pre-existing indications for statin therapy (hyperlipidemia, diabetes, or heart disease). Propensity score matched groups were compared using competing risks survival models for DVT and PE outcomes reporting the hazard ratios (HR) between the treatment groups. Sensitivity analyses assessed the influence of age and individual medications. Results—The total cohort included 170,459 patients, which, after matching, were similar on baseline characteristics. The overall model showed a statistically significant protective effect for statins compared to no treatment attributed only to leukemia for DVT (HR = 0.77, 95% CI 0.61–0.99) and colorectal cancers for PE (HR = 0.80, 95% CI 0.64–0.99) in stratified analyses. There were generally no differences in outcomes between statins and non-statins and no individual statin use showed results different from the class effect. Conclusions—In this propensity score matched sample of patients with cancer, statins were shown to have a small protective effect in some cancers for DVT or PE compared to no treatment and little difference compared to an active control group. The lack of effect was consistent across statins and was also not found for any of the sensitivity analyses included

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

A gene expression predictor of response to EGFR-targeted therapy stratifies progression-free survival to cetuximab in KRAS wild-type metastatic colorectal cancer

<p>Abstract</p> <p>Background</p> <p>The anti-EGFR monoclonal antibody cetuximab is used in metastatic colorectal cancer (CRC), and predicting responsive patients garners great interest, due to the high cost of therapy. Mutations in the KRAS gene occur in ~40% of CRC and are a negative predictor of response to cetuximab. However, many KRAS-wildtype patients do not benefit from cetuximab. We previously published a gene expression predictor of sensitivity to erlotinib, an EGFR inhibitor. The purpose of this study was to determine if this predictor could identify KRAS-wildtype CRC patients who will benefit from cetuximab therapy.</p> <p>Methods</p> <p>Microarray data from 80 metastatic CRC patients subsequently treated with cetuximab were extracted from the study by Khambata-Ford et al. The study included KRAS status, response, and PFS for each patient. The gene expression data were scaled and analyzed using our predictive model. An improved predictive model of response was identified by removing features in the 180-gene predictor that introduced noise.</p> <p>Results</p> <p>Forty-three of eighty patients were identified as harboring wildtype-KRAS. When the model was applied to these patients, the predicted-sensitive group had significantly longer PFS than the predicted-resistant group (median 88 days vs. 56 days; mean 117 days vs. 63 days, respectively, p = 0.008). Kaplan-Meier curves were also significantly improved in the predicted-sensitive group (p = 0.0059, HR = 0.4109. The model was simplified to 26 of the original 180 genes and this further improved stratification of PFS (median 147 days vs. 56.5 days in the predicted sensitive and resistant groups, respectively, p < 0.0001). However, the simplified model will require further external validation, as features were selected based on their correlation to PFS in this dataset.</p> <p>Conclusion</p> <p>Our model of sensitivity to EGFR inhibition stratified PFS following cetuximab in KRAS-wildtype CRC patients. This study represents the first true external validation of a molecular predictor of response to cetuximab in KRAS-WT metastatic CRC. Our model may hold clinical utility for identifying patients responsive to cetuximab and may therefore minimize toxicity and cost while maximizing benefit.</p

FTO Gene Associated Fatness in Relation to Body Fat Distribution and Metabolic Traits throughout a Broad Range of Fatness

A common single nucleotide polymorphism (SNP) of FTO (rs9939609, T/A) is associated with total body fatness. We investigated the association of this SNP with abdominal and peripheral fatness and obesity-related metabolic traits in middle-aged men through a broad range of fatness present already in adolescence.Obese young Danish men (n = 753, BMI > or = 31.0 kg/m(2)) and a randomly selected group (n = 879) from the same population were examined in three surveys (mean age 35, 46 and 49 years, respectively). The traits included anthropometrics, body composition, oral glucose tolerance test, blood lipids, blood pressure, fibrinogen and aspartate aminotransferase. Logistic regression analysis was used to assess the age-adjusted association between the phenotypes and the odds ratios for the FTO rs9939609 (TT and TA genotype versus the AA genotype), for anthropometrics and body composition estimated per unit z-score. BMI was strongly associated with the AA genotype in all three surveys: OR = 1.17, p = 1.1*10(-6), OR = 1.20, p = 1.7*10(-7), OR = 1.17, p = 3.4*10(-3), respectively. Fat body mass index was also associated with the AA genotype (OR = 1.21, p = 4.6*10(-7) and OR = 1.21, p = 1.0*10(-3)). Increased abdominal fatness was associated with the AA genotype when measured as waist circumference (OR = 1.21, p = 2.2*10(-6) and OR = 1.19, p = 5.9*10(-3)), sagittal abdominal diameter (OR = 1.17, p = 1.3*10(-4) and OR = 1.18, p = 0.011) and intra-abdominal adipose tissue (OR = 1.21, p = 0.005). Increased peripheral fatness measured as hip circumference (OR = 1.19, p = 1.3*10(-5) and OR = 1.18, p = 0.004) and lower body fat mass (OR = 1.26, p = 0.002) was associated with the AA genotype. The AA genotype was significantly associated with decreased Stumvoll insulin sensitivity index (OR = 0.93, p = 0.02) and with decreased non-fasting plasma HDL-cholesterol (OR = 0.57, p = 0.037), but not with any other of the metabolic traits. However, all significant results for both body fat distribution and metabolic traits were explained by a mediating effect of total fat mass.The association of the examined FTO SNP to general fatness throughout the range of fatness was confirmed, and this association explains the relation between the SNP and body fat distribution and decreased insulin sensitivity and HDL-cholesterol. The SNP was not significantly associated with other metabolic traits suggesting that they are not derived from the general accumulation of body fat

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Student public commitment in a school-based diabetes prevention project: impact on physical health and health behavior

<p>Abstract</p> <p>Background</p> <p>As concern about youth obesity continues to mount, there is increasing consideration of widespread policy changes to support improved nutritional and enhanced physical activity offerings in schools. A critical element in the success of such programs may be to involve students as spokespeople for the program. Making such a public commitment to healthy lifestyle program targets (improved nutrition and enhanced physical activity) may potentiate healthy behavior changes among such students and provide a model for their peers. This paper examines whether student's "public commitment"--voluntary participation as a peer communicator or in student-generated media opportunities--in a school-based intervention to prevent diabetes and reduce obesity predicted improved study outcomes including reduced obesity and improved health behaviors.</p> <p>Methods</p> <p>Secondary analysis of data from a 3-year randomized controlled trial conducted in 42 middle schools examining the impact of a multi-component school-based program on body mass index (BMI) and student health behaviors. A total of 4603 students were assessed at the beginning of sixth grade and the end of eighth grade. Process evaluation data were collected throughout the course of the intervention. All analyses were adjusted for students' baseline values. For this paper, the students in the schools randomized to receive the intervention were further divided into two groups: those who participated in public commitment activities and those who did not. Students from comparable schools randomized to the assessment condition constituted the control group.</p> <p>Results</p> <p>We found a lower percentage of obesity (greater than or equal to the 95^thpercentile for BMI) at the end of the study among the group participating in public commitment activities compared to the control group (21.5% vs. 26.6%, p = 0.02). The difference in obesity rates at the end of the study was even greater among the subgroup of students who were overweight or obese at baseline; 44.6% for the "public commitment" group, versus 53.2% for the control group (p = 0.01). There was no difference in obesity rates between the group not participating in public commitment activities and the control group (26.4% vs. 26.6%).</p> <p>Conclusions</p> <p>Participating in public commitment activities during the HEALTHY study may have potentiated the changes promoted by the behavioral, nutrition, and physical activity intervention components.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov number, <a href="http://www.clinicaltrials.gov/ct2/show/NCT00458029">NCT00458029</a></p