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1.
Cancer Res ; 2021 Jan 20.
Artigo em Inglês | MEDLINE | ID: mdl-33472890

RESUMO

Lung cancer is the leading cause of cancer death globally. An improved risk stratification strategy can increase efficiency of low-dose computed tomography (LDCT) screening. Here we assessed whether individual's genetic background has clinical utility for risk stratification in the context of LDCT screening. Based on 13,119 lung cancer patients and 10,008 controls with European ancestry in the International Lung Cancer Consortium, we constructed a polygenic risk score (PRS) via 10-fold cross-validation with regularized penalized regression. The performance of risk model integrating PRS, including calibration and ability to discriminate, was assessed using UK biobank data (N=335,931). Absolute risk was estimated based on age-specific lung cancer incidence and all-cause mortality as competing risk. To evaluate its potential clinical utility, the PRS distribution was simulated in the National Lung Screening Trial, N=50,772 participants). The lung cancer odds ratio (ORs) for individuals at the top decile of the PRS distribution versus those at bottom 10% was 2.39 (95%CI=1.92-3.00, P=1.80x10-14) in the validation set (trend p-value of 5.26 x 10-20). The OR per standard deviation of PRS increase was 1.26 (95%CI=1.20-1.32, P=9.69x10-23) for overall lung cancer risk in the validation set. When considering absolute risks, individuals at different PRS deciles showed differential trajectories of 5-year and cumulative absolute risk. The age reaching the LDCT screening recommendation threshold can vary by 4 to 8 years, depending on the individual's genetic background, smoking status and family history. Collectively, these results suggest that Individual's genetic background may inform the optimal lung cancer LDCT screening strategy.

2.
Clin Lung Cancer ; 2020 Oct 14.
Artigo em Inglês | MEDLINE | ID: mdl-33221175

RESUMO

INTRODUCTION: Lung-MAP S1400K was designed to evaluate the response to telisotuzumab vedotin, an antibody-drug conjugate targeting c-MET, in patients with c-MET-positive squamous cell carcinoma (SCC). PATIENTS AND METHODS: Patients with previously treated SCC with c-MET-positive tumors (H score ≥ 150, Ventana SP44 assay) were enrolled into 2 cohorts: Cohort 1 (immune checkpoint inhibitor-naive) and Cohort 2 (immune checkpoint inhibitor refractory). Telisotuzumab vedotin 2.7 mg/kg was administered intravenously every 3 weeks until disease progression or unacceptable toxicity. Response assessments were performed every 6 weeks. The primary endpoint was response by Response Evaluation Criteria in Solid Tumors (RECIST) v1.1. Secondary endpoints included progression-free survival, overall survival, response within cohort, duration of response, and toxicities. Interim analysis was planned after 20 evaluable patients, with ≥ 3 responses needed to continue enrollment. RESULTS: Forty-nine patients (14% of screened patients) were assigned to S1400K, 28 patients enrolled (15 in Cohort 1 and 13 in Cohort 2), and 23 were eligible. S1400K closed on December 21, 2018 owing to lack of efficacy. Two responses (response rate of 9%; 95% confidence interval, 0%-20%) were reported in cohort 1 (1 complete and 1 unconfirmed partial response), whereas 10 patients had stable disease, with a disease control rate of 52%. The median overall and progression-free survival was 5.6 and 2.4 months, respectively. There were 3 grade 5 events (2 pneumonitis, in Cohort 2, and 1 bronchopulmonary hemorrhage, in Cohort 1). CONCLUSION: Telisotuzumab vedotin failed to meet the pre-specified response needed to justify continuing enrollment to S1400K. Pneumonitis was an unanticipated toxicity observed in patients with SCC.

3.
J Rural Health ; 2020 Nov 18.
Artigo em Inglês | MEDLINE | ID: mdl-33210370

RESUMO

PURPOSE: To determine differences in exceptional survival (ES)-survival of 5 years or more past diagnosis-between stage IV non-small cell lung cancer (NSCLC) patients residing in the Appalachian versus non-Appalachian regions of Kentucky. METHODS: This was a population-based, retrospective case-control study of Kentucky patients, diagnosed with stage IV NSCLC between January 1, 2000, and December 31, 2011. The data were drawn from the Kentucky Cancer Registry. FINDINGS: Findings from the multivariable logistic regression revealed no significant differences in the odds of ES between patients who resided in Appalachian versus non-Appalachian Kentucky. Being female and undergoing surgery only as the first course of treatment were associated with higher odds of ES. Increasing age, unspecified histology, having poorly differentiated or undifferentiated carcinomas, and receiving radiation therapy only as the first course of treatment were associated with decreased odds of ES. CONCLUSION: Differences in the odds of ES among stage IV NSCLC patients were not related to residence in Appalachian versus non-Appalachian Kentucky. ES was associated with other nongenetic and treatment factors that warrant further investigations.

4.
BMC Med Genomics ; 13(1): 162, 2020 10 30.
Artigo em Inglês | MEDLINE | ID: mdl-33126877

RESUMO

BACKGROUND: Genome-wide association studies (GWAS) have proven successful in predicting genetic risk of disease using single-locus models; however, identifying single nucleotide polymorphism (SNP) interactions at the genome-wide scale is limited due to computational and statistical challenges. We addressed the computational burden encountered when detecting SNP interactions for survival analysis, such as age of disease-onset. To confront this problem, we developed a novel algorithm, called the Efficient Survival Multifactor Dimensionality Reduction (ES-MDR) method, which used Martingale Residuals as the outcome parameter to estimate survival outcomes, and implemented the Quantitative Multifactor Dimensionality Reduction method to identify significant interactions associated with age of disease-onset. METHODS: To demonstrate efficacy, we evaluated this method on two simulation data sets to estimate the type I error rate and power. Simulations showed that ES-MDR identified interactions using less computational workload and allowed for adjustment of covariates. We applied ES-MDR on the OncoArray-TRICL Consortium data with 14,935 cases and 12,787 controls for lung cancer (SNPs = 108,254) to search over all two-way interactions to identify genetic interactions associated with lung cancer age-of-onset. We tested the best model in an independent data set from the OncoArray-TRICL data. RESULTS: Our experiment on the OncoArray-TRICL data identified many one-way and two-way models with a single-base deletion in the noncoding region of BRCA1 (HR 1.24, P = 3.15 × 10-15), as the top marker to predict age of lung cancer onset. CONCLUSIONS: From the results of our extensive simulations and analysis of a large GWAS study, we demonstrated that our method is an efficient algorithm that identified genetic interactions to include in our models to predict survival outcomes.

5.
Int J Cancer ; 2020 Sep 11.
Artigo em Inglês | MEDLINE | ID: mdl-32914876

RESUMO

At the time of cancer diagnosis, body mass index (BMI) is inversely correlated with lung cancer risk, which may reflect reverse causality and confounding due to smoking behavior. We used two-sample univariable and multivariable Mendelian randomization (MR) to estimate causal relationships of BMI and smoking behaviors on lung cancer and histological subtypes based on an aggregated genome-wide association studies (GWASs) analysis of lung cancer in 29 266 cases and 56 450 controls. We observed a positive causal effect for high BMI on occurrence of small-cell lung cancer (odds ratio (OR) = 1.60, 95% confidence interval (CI) = 1.24-2.06, P = 2.70 × 10-4 ). After adjustment of smoking behaviors using multivariable Mendelian randomization (MVMR), a direct causal effect on small cell lung cancer (ORMVMR = 1.28, 95% CI = 1.06-1.55, PMVMR = .011), and an inverse effect on lung adenocarcinoma (ORMVMR = 0.86, 95% CI = 0.77-0.96, PMVMR = .008) were observed. A weak increased risk of lung squamous cell carcinoma was observed for higher BMI in univariable Mendelian randomization (UVMR) analysis (ORUVMR = 1.19, 95% CI = 1.01-1.40, PUVMR = .036), but this effect disappeared after adjustment of smoking (ORMVMR = 1.02, 95% CI = 0.90-1.16, PMVMR = .746). These results highlight the histology-specific impact of BMI on lung carcinogenesis and imply mediator role of smoking behaviors in the association between BMI and lung cancer.

6.
Oral Oncol ; 111: 104949, 2020 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-32801084

RESUMO

OBJECTIVES: Recurrence rates for head and neck squamous cell carcinoma (HNSCC) approach 50% at 5 years. Current staging fails to identify patients with a worse prognosis who might benefit from intensified treatment, which warrants improved prognostic biomarkers. The purpose of this retrospective case study is to identify potential prognostic biomarkers in patients with HNSCC including APE1 (DNA repair/redox gene regulator), NRF2 and PPARGC1A (redox gene regulators), SOD3 and DCN (antioxidant proteins). MATERIALS AND METHODS: Differential protein expression between benign, carcinoma in situ (CIS), and invasive HNSCC tissue specimens from 77 patients was assessed using immunohistochemistry. Protein expression was analyzed with multivariate, pair-wise, and Kaplan-Meier survival analyses to identify potential prognostic biomarkers. Utilizing The Cancer Genome Atlas's transcriptome database, pair-wise and survival analysis was performed to identify potential prognostic biomarkers. RESULTS: APE1, NRF2, PPARGC1A, SOD3, and DCN expression in HNSCC in relation to, lymph node invasion, and patient survival were examined. Elevated APE1 protein expression in CIS corresponded with reduced survival (p = 0.0243). Increased APE1 gene expression in stage T4a HNSCC was associated with reduced patient survival (p < 0.015). Increased PPARGC1A in invasive tumor correlated with reduced survival (p = 0.0281). Patients with lymph node invasion at diagnosis had significantly increased APE1 protein in the primary sites (p < 0.05). Patients with poorly differentiated invasive tumors had reduced PPARGC1A in CIS proximal to the invasive tumor and had elevated DCN and SOD3 in proximal benign tissue (p < 0.05). CONCLUSIONS: The expression of APE1, DCN, and SOD3 is a potential prognostic signature that identifies patients with worsened survival.

7.
PLoS One ; 15(8): e0237790, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32810185

RESUMO

This study determined the frequency and factors associated with EGFR testing rates and erlotinib treatment as well as associated survival outcomes in patients with non small cell lung cancer in Kentucky. Data from the Kentucky Cancer Registry (KCR) linked with health claims from Medicaid, Medicare and private insurance groups were evaluated. EGFR testing and erlotinib prescribing were identified using ICD-9 procedure codes and national drug codes in claims, respectively. Logistic regression analysis was performed to determine factors associated with EGFR testing and erlotinib prescribing. Cox-regression analysis was performed to determine factors associated with survival. EGFR mutation testing rates rose from 0.1% to 10.6% over the evaluated period while erlotinib use ranged from 3.4% to 5.4%. Factors associated with no EGFR testing were older age, male gender, enrollment in Medicaid or Medicare, smoking, and geographic region. Factors associated with not receiving erlotinib included older age, male gender, enrollment in Medicare or Medicaid, and living in moderate to high poverty. Survival analysis demonstrated EGFR testing or erlotinib use was associated with a higher likelihood of survival. EGFR testing and erlotinib prescribing were slow to be implemented in our predominantly rural state. While population-level factors likely contributed, patient factors, including geographic location (areas with high poverty rates and rural regions) and insurance type, were associated with lack of use, highlighting rural disparities in the implementation of cancer precision medicine.


Assuntos
Carcinoma Pulmonar de Células não Pequenas/tratamento farmacológico , Cloridrato de Erlotinib/uso terapêutico , Testes Genéticos/estatística & dados numéricos , Neoplasias Pulmonares/tratamento farmacológico , Demandas Administrativas em Assistência à Saúde/estatística & dados numéricos , Adulto , Fatores Etários , Idoso , Carcinoma Pulmonar de Células não Pequenas/genética , Carcinoma Pulmonar de Células não Pequenas/mortalidade , Análise Mutacional de DNA/economia , Análise Mutacional de DNA/estatística & dados numéricos , Prescrições de Medicamentos/economia , Prescrições de Medicamentos/estatística & dados numéricos , Uso de Medicamentos/economia , Uso de Medicamentos/estatística & dados numéricos , Receptores ErbB/antagonistas & inibidores , Receptores ErbB/genética , Feminino , Testes Genéticos/economia , Disparidades em Assistência à Saúde/economia , Humanos , Kentucky/epidemiologia , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/mortalidade , Masculino , Medicaid/economia , Medicaid/estatística & dados numéricos , Medicare/economia , Medicare/estatística & dados numéricos , Pessoa de Meia-Idade , Mutação , Pobreza/estatística & dados numéricos , Medicina de Precisão/economia , Medicina de Precisão/estatística & dados numéricos , Sistema de Registros/estatística & dados numéricos , Estudos Retrospectivos , Fatores Sexuais , Análise de Sobrevida , Estados Unidos , Adulto Jovem
8.
J Rural Health ; 2020 Jul 06.
Artigo em Inglês | MEDLINE | ID: mdl-32633045

RESUMO

PURPOSE: Large-scale genomic sequencing studies are driving oncology drug development. However, rural populations, like those residing in Appalachian Kentucky, are underrepresented in these efforts. In this study, we determined the frequency of participation, reasons for nonparticipation, and factors predicting the decision to participate in the Total Cancer Care (TCC) prospective genomic cohort study. METHODS: A total of 1,188 patients were invited to enroll in the TCC prospective cohort from December 2018 to May 2019. Declining patients were queried for their rationale for nonparticipation and their patient data were obtained from the Kentucky Cancer Registry (KCR). Logistic regression was used to assess the association between characteristics and study participation. The association of study participation with survival was modeled with Cox proportional-hazards regression. RESULTS: 90.9% (1,081) patients consented to participate. In multivariate analysis, factors significantly associated with participation were age, gender, treatment status, and race. Though overall more women participated in the study, men were more likely to participate than women when invited (OR 1.57). Younger, Caucasian individuals who had received chemotherapy, but not surgery, were also more likely to participate. Patients in the Kentucky Appalachian cohort were primarily rural, had less educational attainment, and lower socioeconomic status. Kentucky Appalachian patients were no less likely to enroll in TCC than non-Appalachian patients. Consented individuals had higher overall survival compared to those who declined. CONCLUSION: Though minorities, those with low socioeconomic status, and rural populations are underrepresented in genomic studies, they were no less likely to participate when given the opportunity, and participation was associated with better clinical outcomes.

9.
Cancer Epidemiol Biomarkers Prev ; 29(7): 1423-1429, 2020 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-32277007

RESUMO

BACKGROUND: A substantial proportion of cancer driver genes (CDG) are also cancer predisposition genes. However, the associations between genetic variants in lung CDGs and the susceptibility to lung cancer have rarely been investigated. METHODS: We selected expression-related single-nucleotide polymorphisms (eSNP) and nonsynonymous variants of lung CDGs, and tested their associations with lung cancer risk in two large-scale genome-wide association studies (20,871 cases and 15,971 controls of European descent). Conditional and joint association analysis was performed to identify independent risk variants. The associations of independent risk variants with somatic alterations in lung CDGs or recurrently altered pathways were investigated using data from The Cancer Genome Atlas (TCGA) project. RESULTS: We identified seven independent SNPs in five lung CDGs that were consistently associated with lung cancer risk in discovery (P < 0.001) and validation (P < 0.05) stages. Among these loci, rs78062588 in TPM3 (1q21.3) was a new lung cancer susceptibility locus (OR = 0.86, P = 1.65 × 10-6). Subgroup analysis by histologic types further identified nine lung CDGs. Analysis of somatic alterations found that in lung adenocarcinomas, rs78062588[C] allele (TPM3 in 1q21.3) was associated with elevated somatic copy number of TPM3 (OR = 1.16, P = 0.02). In lung adenocarcinomas, rs1611182 (HLA-A in 6p22.1) was associated with truncation mutations of the transcriptional misregulation in cancer pathway (OR = 0.66, P = 1.76 × 10-3). CONCLUSIONS: Genetic variants can regulate functions of lung CDGs and influence lung cancer susceptibility. IMPACT: Our findings might help unravel biological mechanisms underlying lung cancer susceptibility.

10.
Clin Lung Cancer ; 21(4): 357-364.e7, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-32173247

RESUMO

INTRODUCTION: The purpose of this study was to evaluate the efficacy and tolerability of carfilzomib plus irinotecan (C/I) in patients with relapsed small-cell lung cancer (SCLC). PATIENTS AND METHODS: Patients with SCLC who progressed after 1 platinum-containing regimen for recurrent or metastatic disease were eligible. Patients were stratified as: sensitive (SS) (progressive disease > 90 days after chemotherapy) or refractory (RS) (progressive disease 30 to 90 days after chemotherapy) and received up to 6 cycles of C/I; imaging was performed every 2 cycles. The primary endpoint was 6-month overall survival (OS). RESULTS: All 62 patients enrolled were evaluable for efficacy and adverse events. 6-month OS was 59% in the platinum SS and 54% in the platinum RS. The overall response rate was 21.6% (2.7% complete response, 18.9% partial response) in SS (n = 37) and 12.5% (all partial response) in RS (n = 25). The disease control rate was 68% (SS) and 56% (RS). Progression-free survival and OS were 3.6 months (95% confidence interval [CI], 2.6-4.6 months) and 6.9 months (95% CI, 4.3-12.3 months) in SS, and 3.3 months (95% CI, 1.8-3.9 months) and 6.8 months (95% CI, 4.1-11 months) in RS. Twenty-nine (47%) patients experienced ≥ grade 3 adverse events; 8 (12.9%) subjects had grade 4 toxicities. Three treatment-related deaths occurred: myocardial infarction (possible), lung infection (possible), and sepsis (probable). CONCLUSION: In patients with relapsed SCLC, C/I was effective in the treatment of SS and RS. With 4.8% grade 5 toxicity, C/I is a viable option for relapsed patients with SCLC with performance status 0 to 1, particularly in platinum-resistant patients, or subjects who cannot receive immunotherapy.

11.
BMC Bioinformatics ; 20(1): 620, 2019 Dec 02.
Artigo em Inglês | MEDLINE | ID: mdl-31791231

RESUMO

BACKGROUND: Cancer arises through accumulation of somatically acquired genetic mutations. An important question is to delineate the temporal order of somatic mutations during carcinogenesis, which contributes to better understanding of cancer biology and facilitates identification of new therapeutic targets. Although a number of statistical and computational methods have been proposed to estimate the temporal order of mutations, they do not account for the differences in the functional impacts of mutations and thus are likely to be obscured by the presence of passenger mutations that do not contribute to cancer progression. In addition, many methods infer the order of mutations at the gene level, which have limited power due to the low mutation rate in most genes. RESULTS: In this paper, we develop a Probabilistic Approach for estimating the Temporal Order of Pathway mutations by leveraging functional Annotations of mutations (PATOPA). PATOPA infers the order of mutations at the pathway level, wherein it uses a probabilistic method to characterize the likelihood of mutational events from different pathways occurring in a certain order. The functional impact of each mutation is incorporated to weigh more on a mutation that is more integral to tumor development. A maximum likelihood method is used to estimate parameters and infer the probability of one pathway being mutated prior to another. Simulation studies and analysis of whole exome sequencing data from The Cancer Genome Atlas (TCGA) demonstrate that PATOPA is able to accurately estimate the temporal order of pathway mutations and provides new biological insights on carcinogenesis of colorectal and lung cancers. CONCLUSIONS: PATOPA provides a useful tool to estimate temporal order of mutations at the pathway level while leveraging functional annotations of mutations.


Assuntos
Carcinogênese/genética , Anotação de Sequência Molecular , Mutação/genética , Probabilidade , Transdução de Sinais/genética , Simulação por Computador , Bases de Dados Genéticas , Humanos , Taxa de Mutação , Neoplasias/genética , Reprodutibilidade dos Testes , Fatores de Tempo
12.
BMC Bioinformatics ; 20(1): 501, 2019 Oct 17.
Artigo em Inglês | MEDLINE | ID: mdl-31623550

RESUMO

BACKGROUND: Identifying differentially abundant features between different experimental groups is a common goal for many metabolomics and proteomics studies. However, analyzing data from mass spectrometry (MS) is difficult because the data may not be normally distributed and there is often a large fraction of zero values. Although several statistical methods have been proposed, they either require the data normality assumption or are inefficient. RESULTS: We propose a new semi-parametric differential abundance analysis (SDA) method for metabolomics and proteomics data from MS. The method considers a two-part model, a logistic regression for the zero proportion and a semi-parametric log-linear model for the possibly non-normally distributed non-zero values, to characterize data from each feature. A kernel-smoothed likelihood method is developed to estimate model coefficients and a likelihood ratio test is constructed for differential abundant analysis. The method has been implemented into an R package, SDAMS, which is available at https://www.bioconductor.org/packages/release/bioc/html/SDAMS.html . CONCLUSION: By introducing the two-part semi-parametric model, SDA is able to handle both non-normally distributed data and large fraction of zero values in a MS dataset. It also allows for adjustment of covariates. Simulations and real data analyses demonstrate that SDA outperforms existing methods.


Assuntos
Espectrometria de Massas/métodos , Metabolômica/métodos , Proteômica/métodos , Software , Modelos Estatísticos
14.
J Biomed Inform ; 97: 103267, 2019 09.
Artigo em Inglês | MEDLINE | ID: mdl-31401235

RESUMO

OBJECTIVE: We study the performance of machine learning (ML) methods, including neural networks (NNs), to extract mutational test results from pathology reports collected by cancer registries. Given the lack of hand-labeled datasets for mutational test result extraction, we focus on the particular use-case of extracting Epidermal Growth Factor Receptor mutation results in non-small cell lung cancers. We explore the generalization of NNs across different registries where our goals are twofold: (1) to assess how well models trained on a registry's data port to test data from a different registry and (2) to assess whether and to what extent such models can be improved using state-of-the-art neural domain adaptation techniques under different assumptions about what is available (labeled vs unlabeled data) at the target registry site. MATERIALS AND METHODS: We collected data from two registries: the Kentucky Cancer Registry (KCR) and the Fred Hutchinson Cancer Research Center (FH) Cancer Surveillance System. We combine NNs with adversarial domain adaptation to improve cross-registry performance. We compare to other classifiers in the standard supervised classification, unsupervised domain adaptation, and supervised domain adaptation scenarios. RESULTS: The performance of ML methods varied between registries. To extract positive results, the basic convolutional neural network (CNN) had an F1 of 71.5% on the KCR dataset and 95.7% on the FH dataset. For the KCR dataset, the CNN F1 results were low when trained on FH data (Positive F1: 23%). Using our proposed adversarial CNN, without any labeled data, we match the F1 of the models trained directly on each target registry's data. The adversarial CNN F1 improved when trained on FH and applied to KCR dataset (Positive F1: 70.8%). We found similar performance improvements when we trained on KCR and tested on FH reports (Positive F1: 45% to 96%). CONCLUSION: Adversarial domain adaptation improves the performance of NNs applied to pathology reports. In the unsupervised domain adaptation setting, we match the performance of models that are trained directly on target registry's data by using source registry's labeled data and unlabeled examples from the target registry.


Assuntos
Aprendizado de Máquina , Mutação , Neoplasias/genética , Neoplasias/patologia , Sistema de Registros/estatística & dados numéricos , Carcinoma Pulmonar de Células não Pequenas/genética , Carcinoma Pulmonar de Células não Pequenas/patologia , Biologia Computacional , Mineração de Dados , Aprendizado Profundo , Receptores ErbB/genética , Humanos , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patologia , Redes Neurais de Computação
15.
JCO Clin Cancer Inform ; 3: 1-15, 2019 05.
Artigo em Inglês | MEDLINE | ID: mdl-31058542

RESUMO

PURPOSE: SEER registries do not report results of epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) mutation tests. To facilitate population-based research in molecularly defined subgroups of non-small-cell lung cancer (NSCLC), we assessed the validity of natural language processing (NLP) for the ascertainment of EGFR and ALK testing from electronic pathology (e-path) reports of NSCLC cases included in two SEER registries: the Cancer Surveillance System (CSS) and the Kentucky Cancer Registry (KCR). METHODS: We obtained 4,278 e-path reports from 1,634 patients who were diagnosed with stage IV nonsquamous NSCLC from September 1, 2011, to December 31, 2013, included in CSS. We used 855 CSS reports to train NLP systems for the ascertainment of EGFR and ALK test status (reported v not reported) and test results (positive v negative). We assessed sensitivity, specificity, and positive and negative predictive values in an internal validation sample of 3,423 CSS e-path reports and repeated the analysis in an external sample of 1,041 e-path reports from 565 KCR patients. Two oncologists manually reviewed all e-path reports to generate gold-standard data sets. RESULTS: NLP systems yielded internal validity metrics that ranged from 0.95 to 1.00 for EGFR and ALK test status and results in CSS e-path reports. NLP showed high internal accuracy for the ascertainment of EGFR and ALK in CSS patients-F scores of 0.95 and 0.96, respectively. In the external validation analysis, NLP yielded metrics that ranged from 0.02 to 0.96 in KCR reports and F scores of 0.70 and 0.72, respectively, in KCR patients. CONCLUSION: NLP is an internally valid method for the ascertainment of EGFR and ALK test information from e-path reports available in SEER registries, but future work is necessary to increase NLP external validity.


Assuntos
Quinase do Linfoma Anaplásico/genética , Carcinoma Pulmonar de Células não Pequenas/diagnóstico , Carcinoma Pulmonar de Células não Pequenas/etiologia , Neoplasias Pulmonares/diagnóstico , Neoplasias Pulmonares/etiologia , Mutação , Processamento de Linguagem Natural , Adulto , Idoso , Algoritmos , Carcinoma Pulmonar de Células não Pequenas/epidemiologia , Análise Mutacional de DNA , Receptores ErbB/genética , Feminino , Testes Genéticos , Humanos , Kentucky/epidemiologia , Neoplasias Pulmonares/epidemiologia , Aprendizado de Máquina , Masculino , Pessoa de Meia-Idade , Vigilância da População , Sistema de Registros , Reprodutibilidade dos Testes , Programa de SEER
16.
Oncotarget ; 10(19): 1760-1774, 2019 Mar 05.
Artigo em Inglês | MEDLINE | ID: mdl-30956756

RESUMO

The development of cancer is driven by the accumulation of many oncogenesis-related genetic alterations and tumorigenesis is triggered by complex networks of involved genes rather than independent actions. To explore the epistasis existing among oncogenesis-related genes in lung cancer development, we conducted pairwise genetic interaction analyses among 35,031 SNPs from 2027 oncogenesis-related genes. The genotypes from three independent genome-wide association studies including a total of 24,037 lung cancer patients and 20,401 healthy controls with Caucasian ancestry were analyzed in the study. Using a two-stage study design including discovery and replication studies, and stringent Bonferroni correction for multiple statistical analysis, we identified significant genetic interactions between SNPs in RGL1:RAD51B (OR=0.44, p value=3.27x10-11 in overall lung cancer and OR=0.41, p value=9.71x10-11 in non-small cell lung cancer), SYNE1:RNF43 (OR=0.73, p value=1.01x10-12 in adenocarcinoma) and FHIT:TSPAN8 (OR=1.82, p value=7.62x10-11 in squamous cell carcinoma) in our analysis. None of these genes have been identified from previous main effect association studies in lung cancer. Further eQTL gene expression analysis in lung tissues provided information supporting the functional role of the identified epistasis in lung tumorigenesis. Gene set enrichment analysis revealed potential pathways and gene networks underlying molecular mechanisms in overall lung cancer as well as histology subtypes development. Our results provide evidence that genetic interactions between oncogenesis-related genes play an important role in lung tumorigenesis and epistasis analysis, combined with functional annotation, provides a valuable tool for uncovering functional novel susceptibility genes that contribute to lung cancer development by interacting with other modifier genes.

17.
Cancer Control ; 26(1): 1073274819845873, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31014079

RESUMO

Recent metabolic and genetic research has demonstrated that risk for specific histological types of lung cancer varies in relation to cigarette smoking and obesity. This study investigated the spatial and temporal distribution of lung cancer histological types in Kentucky, a largely rural state with high rates of smoking and obesity, to discern population-level trends that might reflect variation in these and other risk factors. The Kentucky Cancer Registry provided residential geographic coordinates for lung cancer cases diagnosed from 1995 through 2014. We used multinomial and discrete Poisson spatiotemporal scan statistics, adjusted for age, gender, and race, to characterize risk for specific histological types-small cell, adenocarcinoma, squamous cell, and other types-throughout Kentucky and compared to maps of risk factors. Toward the end of the study period, adenocarcinoma was more common among all population subgroups in north-central Kentucky, where smoking and obesity are less prevalent. During the same time frame, squamous cell, small cell, and other types were more common in rural Appalachia, where smoking and obesity are more prevalent, and in some high poverty urban areas. Spatial and temporal patterns in the distribution of histological types of lung cancer are likely related to regional variation in multiple risk factors. High smoking and obesity rates in the Appalachian region, and likely in high poverty urban areas, appeared to coincide with high rates of squamous cell and small cell lung cancer. In north-central Kentucky, environmental exposures might have resulted in higher risk for adenocarcinoma specifically.


Assuntos
Adenocarcinoma de Pulmão/epidemiologia , Fumar Cigarros/epidemiologia , Neoplasias Pulmonares/epidemiologia , Obesidade/epidemiologia , Carcinoma de Pequenas Células do Pulmão/epidemiologia , Adenocarcinoma de Pulmão/patologia , Idoso , Análise por Conglomerados , Feminino , Humanos , Kentucky/epidemiologia , Neoplasias Pulmonares/patologia , Masculino , Pessoa de Meia-Idade , Fatores de Risco , Carcinoma de Pequenas Células do Pulmão/patologia , Análise Espaço-Temporal
18.
Invest New Drugs ; 37(6): 1218-1230, 2019 12.
Artigo em Inglês | MEDLINE | ID: mdl-30820810

RESUMO

Background AR-67 is a novel camptothecin analogue at early stages of drug development. The phase 1 clinical trial in cancer patients with solid tumors was completed and a population pharmacokinetic model (POP PK) was developed to facilitate further development of this investigational agent. Methods Pharmacokinetic data collected in the phase 1 clinical trial were utilized for the development of a population POP PK by implementing the non-linear mixed effects approach. Patient characteristics at study entry were evaluated as covariates in the model. Subjects (N = 26) were treated at nine dosage levels (1.2-12.4 mg/m2/day) on a daily × 5 schedule. Hematological toxicity data were modeled against exposure metrics. Results A two-compartment POP PK model best described the disposition of AR-67 by fitting a total of 328 PK observations from 25 subjects. Following covariate model selection, age remained as a significant covariate on central volume. The final model provided a good fit for the concentration versus time data and PK parameters were estimated with good precision. Clearance, inter-compartmental clearance, central volume and peripheral volume were estimated to be 32.2 L/h, 28.6 L/h, 6.83 L and 25.0 L, respectively. Finally, exposure-pharmacodynamic analysis using Emax models showed that plasma drug concentration versus time profiles are better predictors of AR-67-related hematologic toxicity were better predictors of leukopenia and thrombocytopenia, as compared to total dose. Conclusions A POP PK model was developed to characterize AR-67 pharmacokinetics and identified age as a significant covariate. Exposure PK metrics Cmax and AUC were shown to predict hematological toxicity. Further efforts to identify clinically relevant determinants of AR-67 disposition and effects in a larger patient population are warranted.


Assuntos
Antineoplásicos Fitogênicos/farmacocinética , Camptotecina/análogos & derivados , Modelos Biológicos , Neoplasias/metabolismo , Compostos de Organossilício/farmacocinética , Adulto , Idoso , Antineoplásicos Fitogênicos/sangue , Camptotecina/sangue , Camptotecina/farmacocinética , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Neoplasias/sangue , Compostos de Organossilício/sangue
19.
PLoS One ; 14(2): e0212340, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30811496

RESUMO

Appalachian Kentucky (App KY) leads the nation in lung cancer incidence and mortality. Trace elements, such as As, have been associated with lung cancers in other regions of the country and we hypothesized that a population-based study would reveal higher trace element concentrations in App KY individuals with cancer compared to controls. Using toenail and drinking water trace element concentrations, this study investigated a possible association between lung cancer incidence and trace-element exposure in residents of this region. This population-based case-control study had 520 subjects, and 367 subjects provided toenail samples. Additionally, we explored the relationship between toenail and fingernail trace-element concentrations to determine if fingernails could be used as a surrogate for toenails when patients are unable to provide toenail samples. We found that, contrary to our initial hypothesis, trace element concentrations (Al, As, Cr, Mn, Co, Fe, Ni, Cu, Se, and Pb) were not higher in cancer cases than controls with the exception of Zn where concentrations were slightly higher in cases. In fact, univariate logistic regression models showed that individuals with lower concentrations of several elements (Al, Mn, Cr, and Se) were more likely to have lung cancer, although only Mn was significant in multivariate models which controlled for confounding factors. While drinking water concentrations of Al, Cr and Co were positively related to cancer incidence in univariate models, only Co remained significant in multivariate models. However, since the drinking water concentrations were extremely low and not reflected in the toenail concentrations, the significance of this finding is unclear. We also found that fingernail concentrations were not consistently predictive of toenail concentrations, indicating that fingernails should not be used as surrogates for toenails in future studies.


Assuntos
Água Potável/análise , Cabelo/química , Neoplasias Pulmonares/epidemiologia , Unhas/química , Oligoelementos/análise , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Região dos Apalaches/epidemiologia , Estudos de Casos e Controles , Feminino , Humanos , Incidência , Kentucky/epidemiologia , Neoplasias Pulmonares/metabolismo , Masculino , Pessoa de Meia-Idade , Adulto Jovem
20.
Cancer Epidemiol Biomarkers Prev ; 28(5): 935-942, 2019 05.
Artigo em Inglês | MEDLINE | ID: mdl-30700444

RESUMO

BACKGROUND: Platelets are a critical element in coagulation and inflammation, and activated platelets are linked to cancer risk through diverse mechanisms. However, a causal relationship between platelets and risk of lung cancer remains unclear. METHODS: We performed single and combined multiple instrumental variable Mendelian randomization analysis by an inverse-weighted method, in addition to a series of sensitivity analyses. Summary data for associations between SNPs and platelet count are from a recent publication that included 48,666 Caucasian Europeans, and the International Lung Cancer Consortium and Transdisciplinary Research in Cancer of the Lung data consisting of 29,266 cases and 56,450 controls to analyze associations between candidate SNPs and lung cancer risk. RESULTS: Multiple instrumental variable analysis incorporating six SNPs showed a 62% increased risk of overall non-small cell lung cancer [NSCLC; OR, 1.62; 95% confidence interval (CI), 1.15-2.27; P = 0.005] and a 200% increased risk for small-cell lung cancer (OR, 3.00; 95% CI, 1.27-7.06; P = 0.01). Results showed only a trending association with NSCLC histologic subtypes, which may be due to insufficient sample size and/or weak effect size. A series of sensitivity analysis retained these findings. CONCLUSIONS: Our findings suggest a causal relationship between elevated platelet count and increased risk of lung cancer and provide evidence of possible antiplatelet interventions for lung cancer prevention. IMPACT: These findings provide a better understanding of lung cancer etiology and potential evidence for antiplatelet interventions for lung cancer prevention.


Assuntos
Adenocarcinoma de Pulmão/sangue , Plaquetas/patologia , Carcinoma Pulmonar de Células não Pequenas/sangue , Carcinoma de Células Escamosas/sangue , Neoplasias Pulmonares/sangue , Carcinoma de Pequenas Células do Pulmão/sangue , Adenocarcinoma de Pulmão/genética , Adenocarcinoma de Pulmão/patologia , Biomarcadores Tumorais/sangue , Biomarcadores Tumorais/genética , Carcinoma Pulmonar de Células não Pequenas/genética , Carcinoma Pulmonar de Células não Pequenas/patologia , Carcinoma de Células Escamosas/genética , Carcinoma de Células Escamosas/patologia , Estudos de Casos e Controles , Predisposição Genética para Doença , Humanos , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patologia , Análise da Randomização Mendeliana , Contagem de Plaquetas , Polimorfismo de Nucleotídeo Único , Prognóstico , Fatores de Risco , Carcinoma de Pequenas Células do Pulmão/genética , Carcinoma de Pequenas Células do Pulmão/patologia
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