Candidate pathway analysis of surfactant proteins identifies CTSH and SFTA2 that influences lung cancer risk.

Pulmonary surfactant is a lipoprotein synthesized and secreted by alveolar type II cells in lung. We evaluated the associations between 200,139 single nucleotide polymorphisms (SNPs) of 40 surfactant-related genes and lung cancer risk using genotyped data from two independent lung cancer genome-wide association studies. Discovery data included 18,082 cases and 13,780 controls of European ancestry. Replication data included 1,914 cases and 3,065 controls of European descent. Using multivariate logistic regression, we found novel SNPs in surfactant-related genes CTSH [rs34577742 C > T, odds ratio (OR) = 0.90, 95% confidence interval (CI) = 0.89-0.93, P = 7.64 × 10-9] and SFTA2 (rs3095153 G > A, OR = 1.16, 95% CI = 1.10-1.21, P = 1.27 × 10-9) associated with overall lung cancer in the discovery data and validated in an independent replication data-CTSH (rs34577742 C > T, OR = 0.88, 95% CI = 0.80-0.96, P = 5.76 × 10-3) and SFTA2 (rs3095153 G > A, OR = 1.14, 95% CI = 1.01-1.28, P = 3.25 × 10-2). Among ever smokers, we found SNPs in CTSH (rs34577742 C > T, OR = 0.89, 95% CI = 0.85-0.92, P = 1.94 × 10-7) and SFTA2 (rs3095152 G > A, OR = 1.20, 95% CI = 1.14-1.27, P = 4.25 × 10-11) associated with overall lung cancer in the discovery data and validated in the replication data-CTSH (rs34577742 C > T, OR = 0.88, 95% CI = 0.79-0.97, P = 1.64 × 10-2) and SFTA2 (rs3095152 G > A, OR = 1.15, 95% CI = 1.01-1.30, P = 3.81 × 10-2). Subsequent transcriptome-wide association study using expression weights from a lung expression quantitative trait loci study revealed genes most strongly associated with lung cancer are CTSH (PTWAS = 2.44 × 10-4) and SFTA2 (PTWAS = 2.32 × 10-6).

Identification of genetically predicted DNA methylation markers associated with non-small cell lung cancer risk among 34,964 cases and 448,579 controls.

BACKGROUND: Although the associations between genetic variations and lung cancer risk have been explored, the epigenetic consequences of DNA methylation in lung cancer development are largely unknown. Here, the genetically predicted DNA methylation markers associated with non-small cell lung cancer (NSCLC) risk by a two-stage case-control design were investigated. METHODS: The genetic prediction models for methylation levels based on genetic and methylation data of 1595 subjects from the Framingham Heart Study were established. The prediction models were applied to a fixed-effect meta-analysis of screening data sets with 27,120 NSCLC cases and 27,355 controls to identify the methylation markers, which were then replicated in independent data sets with 7844 lung cancer cases and 421,224 controls. Also performed was a multi-omics functional annotation for the identified CpGs by integrating genomics, epigenomics, and transcriptomics and investigation of the potential regulation pathways. RESULTS: Of the 29,894 CpG sites passing the quality control, 39 CpGs associated with NSCLC risk (Bonferroni-corrected p ≤ 1.67 × 10-6 ) were originally identified. Of these, 16 CpGs remained significant in the validation stage (Bonferroni-corrected p ≤ 1.28 × 10-3 ), including four novel CpGs. Multi-omics functional annotation showed nine of 16 CpGs were potentially functional biomarkers for NSCLC risk. Thirty-five genes within a 1-Mb window of 12 CpGs that might be involved in regulatory pathways of NSCLC risk were identified. CONCLUSIONS: Sixteen promising DNA methylation markers associated with NSCLC were identified. Changes of the methylation level at these CpGs might influence the development of NSCLC by regulating the expression of genes nearby. PLAIN LANGUAGE SUMMARY: The epigenetic consequences of DNA methylation in lung cancer development are still largely unknown. This study used summary data of large-scale genome-wide association studies to investigate the associations between genetically predicted levels of methylation biomarkers and non-small cell lung cancer risk at the first time. This study looked at how well larotrectinib worked in adult patients with sarcomas caused by TRK fusion proteins. These findings will provide a unique insight into the epigenetic susceptibility mechanisms of lung cancer.

"Pathways": A hope-enhancing intervention for patients undergoing treatment for advanced lung cancer.

OBJECTIVE: Observational data suggest hope is associated with the quality of life and survival of people with cancer. This trial examined the feasibility, acceptability, and preliminary outcomes of "Pathways," a hope intervention for people in treatment for advanced lung cancer. METHODS: Between 2020 and 2022, we conducted a single-arm trial of Pathways among participants who were 3-12 weeks into systemic treatment. Pathways consisted of two individual sessions delivered during infusions and three phone calls in which participants discussed their values, goals, and goal strategies with a nurse or occupational therapist. Participants completed standardized measures of hope and goal interference pre- and post-intervention. Feasibility was defined as ≥60% of eligible patients enrolling, ≥70% of participants completing three or more sessions, ≥70% of participants completing post-assessments, and mean acceptability ratings ≥7 out of 10 on intervention relevance, helpfulness, and convenience. Linear regression fixed effects models with covariates modeled pre-post changes in complete case analysis and multiple imputation models. RESULTS: Fifty two participants enrolled: female (59.6%), non-Hispanic White (84.6%), rural (75.0%), and with low educational attainment (51.9% high school degree or less). Except for enrollment (54%), feasibility and acceptability markers were surpassed (77% adherence, 77% retention, acceptability ratings ≥8/10). There was moderate improvement in hope and goal interference from pre-to post-intervention (d = 0.51, p < 0.05 for hope; d = -0.70, p < 0.005 for goal interference). CONCLUSIONS: Strong feasibility, acceptability, and patient-reported outcome data suggest Pathways is a promising intervention to increase hope and reduce cancer-related goal interference during advanced lung cancer treatment.

Cancer diagnosis is associated with a lower burden of dementia and less Alzheimer's-type neuropathology.

Cancer and Alzheimer's disease are common diseases in ageing populations. Previous research has reported a lower incidence of Alzheimer's disease-type (amnestic) dementia among individuals with a diagnosis of cancer. Both cancer and amnestic dementia are prevalent and potentially lethal clinical syndromes. The current study was conducted to investigate the association of cancer diagnosis with neuropathological and cognitive features of dementia. Data were analysed from longitudinally evaluated participants in a community-based cohort study of brain ageing who came to autopsy at the University of Kentucky Alzheimer's Disease Research Center. These data were linked to the Kentucky Cancer Registry, a population-based state cancer surveillance system, to obtain cancer-related data. We examined the relationship between cancer diagnosis, clinical dementia diagnosis, Mini-Mental State Examination scores and neuropathological features using inverse probability weighting to address bias due to confounding and missing data. To address bias due to inclusion of participants with dementia at cohort baseline, we repeated all analyses restricted to the participants who were cognitively normal at baseline. Included participants (n = 785) had a mean ± standard deviation age of death of 83.8 ± 8.6 years; 60.1% were female. Cancer diagnosis was determined in 190 (24.2%) participants, and a diagnosis of mild cognitive impairment or dementia was determined in 539 (68.7%). APOE ɛ4 allele dosage was lower among participants with cancer diagnosis compared to cancer-free participants overall (P = 0.0072); however, this association was not observed among those who were cognitively normal at baseline. Participants with cancer diagnosis had lower odds of mild cognitive impairment or dementia, and higher cognitive test scores (e.g. Mini-Mental State Examination scores evaluated 6 and ≤2 years ante-mortem, P < 0.001 for both comparisons). Cancer diagnosis also associated with lower odds of higher Braak neurofibrillary tangle stages (III/IV) or (V/VI), moderate/frequent neuritic plaques, moderate/frequent diffuse plaques and moderate/severe cerebral amyloid angiopathy (all P < 0.05). By contrast, TDP-43, α-synuclein and cerebrovascular pathologies were not associated with cancer diagnosis. Cancer diagnosis was associated with a lower burden of Alzheimer's disease pathology and less cognitive impairment. These findings from a community-based cohort with neuropathological confirmation of substrates support the hypothesis that there is an inverse relationship between cancer and Alzheimer's disease.

Durvalumab plus tremelimumab alone or in combination with low-dose or hypofractionated radiotherapy in metastatic non-small-cell lung cancer refractory to previous PD(L)-1 therapy: an open-label, multicentre, randomised, phase 2 trial.

BACKGROUND: Patients with non-small-cell lung cancer (NSCLC) that is resistant to PD-1 and PD-L1 (PD[L]-1)-targeted therapy have poor outcomes. Studies suggest that radiotherapy could enhance antitumour immunity. Therefore, we investigated the potential benefit of PD-L1 (durvalumab) and CTLA-4 (tremelimumab) inhibition alone or combined with radiotherapy. METHODS: This open-label, multicentre, randomised, phase 2 trial was done by the National Cancer Institute Experimental Therapeutics Clinical Trials Network at 18 US sites. Patients aged 18 years or older with metastatic NSCLC, an Eastern Cooperative Oncology Group performance status of 0 or 1, and progression during previous PD(L)-1 therapy were eligible. They were randomly assigned (1:1:1) in a web-based system by the study statistician using a permuted block scheme (block sizes of three or six) without stratification to receive either durvalumab (1500 mg intravenously every 4 weeks for a maximum of 13 cycles) plus tremelimumab (75 mg intravenously every 4 weeks for a maximum of four cycles) alone or with low-dose (0·5 Gy delivered twice per day, repeated for 2 days during each of the first four cycles of therapy) or hypofractionated radiotherapy (24 Gy total delivered over three 8-Gy fractions during the first cycle only), 1 week after initial durvalumab-tremelimumab administration. Study treatment was continued until 1 year or until progression. The primary endpoint was overall response rate (best locally assessed confirmed response of a partial or complete response) and, along with safety, was analysed in patients who received at least one dose of study therapy. The trial is registered with ClinicalTrials.gov, NCT02888743, and is now complete. FINDINGS: Between Aug 24, 2017, and March 29, 2019, 90 patients were enrolled and randomly assigned, of whom 78 (26 per group) were treated. This trial was stopped due to futility assessed in an interim analysis. At a median follow-up of 12·4 months (IQR 7·8-15·1), there were no differences in overall response rates between the durvalumab-tremelimumab alone group (three [11·5%, 90% CI 1·2-21·8] of 26 patients) and the low-dose radiotherapy group (two [7·7%, 0·0-16·3] of 26 patients; p=0·64) or the hypofractionated radiotherapy group (three [11·5%, 1·2-21·8] of 26 patients; p=0·99). The most common grade 3-4 adverse events were dyspnoea (two [8%] in the durvalumab-tremelimumab alone group; three [12%] in the low-dose radiotherapy group; and three [12%] in the hypofractionated radiotherapy group) and hyponatraemia (one [4%] in the durvalumab-tremelimumab alone group vs two [8%] in the low-dose radiotherapy group vs three [12%] in the hypofractionated radiotherapy group). Treatment-related serious adverse events occurred in one (4%) patient in the durvalumab-tremelimumab alone group (maculopapular rash), five (19%) patients in the low-dose radiotherapy group (abdominal pain, diarrhoea, dyspnoea, hypokalemia, and respiratory failure), and four (15%) patients in the hypofractionated group (adrenal insufficiency, colitis, diarrhoea, and hyponatremia). In the low-dose radiotherapy group, there was one death from respiratory failure potentially related to study therapy. INTERPRETATION: Radiotherapy did not increase responses to combined PD-L1 plus CTLA-4 inhibition in patients with NSCLC resistant to PD(L)-1 therapy. However, PD-L1 plus CTLA-4 therapy could be a treatment option for some patients. Future studies should refine predictive biomarkers in this setting. FUNDING: The US National Institutes of Health and the Dana-Farber Cancer Institute.

Causal relationships between body mass index, smoking and lung cancer: Univariable and multivariable Mendelian randomization.

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.

A probabilistic method for leveraging functional annotations to enhance estimation of the temporal order of pathway mutations during carcinogenesis.

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.

SDA: a semi-parametric differential abundance analysis method for metabolomics and proteomics data.

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.

Is high vitamin B12 status a cause of lung cancer?

Vitamin B supplementation can have side effects for human health, including cancer risk. We aimed to elucidate the role of vitamin B12 in lung cancer etiology via direct measurements of pre-diagnostic circulating vitamin B12 concentrations in a nested case-control study, complemented with a Mendelian randomization (MR) approach in an independent case-control sample. We used pre-diagnostic biomarker data from 5183 case-control pairs nested within 20 prospective cohorts, and genetic data from 29,266 cases and 56,450 controls. Exposures included directly measured circulating vitamin B12 in pre-diagnostic blood samples from the nested case-control study, and 8 single nucleotide polymorphisms associated with vitamin B12 concentrations in the MR study. Our main outcome of interest was increased risk for lung cancer, overall and by histological subtype, per increase in circulating vitamin B12 concentrations. We found circulating vitamin B12 to be positively associated with overall lung cancer risk in a dose response fashion (odds ratio for a doubling in B12 [ORlog2B12 ] = 1.15, 95% confidence interval (95%CI) = 1.06-1.25). The MR analysis based on 8 genetic variants also indicated that genetically determined higher vitamin B12 concentrations were positively associated with overall lung cancer risk (OR per 150 pmol/L standard deviation increase in B12 [ORSD ] = 1.08, 95%CI = 1.00-1.16). Considering the consistency of these two independent and complementary analyses, these findings support the hypothesis that high vitamin B12 status increases the risk of lung cancer.

Population pharmacokinetic analysis of AR-67, a lactone stable camptothecin analogue, in cancer patients with solid tumors.

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.

Spatiotemporal Analysis of Lung Cancer Histological Types in Kentucky, 1995-2014.

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.

Cross-registry neural domain adaptation to extract mutational test results from pathology reports.

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.

Cetuximab plus carboplatin and paclitaxel with or without bevacizumab versus carboplatin and paclitaxel with or without bevacizumab in advanced NSCLC (SWOG S0819): a randomised, phase 3 study.

BACKGROUND: EGFR antibodies have shown promise in patients with advanced non-small-cell lung cancer (NSCLC), particularly with squamous cell histology. We hypothesised that EGFR copy number by fluorescence in-situ hybridisation (FISH) can identify patients most likely to benefit from these drugs combined with chemotherapy and we aimed to explore the activity of cetuximab with chemotherapy in patients with advanced NSCLC who are EGFR FISH-positive. METHODS: We did this open-label, phase 3 study (SWOG S0819) at 277 sites in the USA and Mexico. We randomly assigned (1:1) eligible patients with treatment-naive stage IV NSCLC to receive paclitaxel (200 mg/m2; every 21 days) plus carboplatin (area under the curve of 6 by modified Calvert formula; every 21 days) or carboplatin plus paclitaxel and bevacizumab (15 mg/kg; every 21 days), either with cetuximab (250 mg/m2 weekly after loading dose; cetuximab group) or without (control group), stratified by bevacizumab treatment, smoking status, and M-substage using a dynamic-balancing algorithm. Co-primary endpoints were progression-free survival in patients with EGFR FISH-positive cancer and overall survival in the entire study population. We analysed clinical outcomes with the intention-to-treat principle and analysis of safety outcomes included patients who received at least one dose of study drug. This study is registered with ClinicalTrials.gov (number NCT00946712). FINDINGS: Between Aug 13, 2009, and May 30, 2014, we randomly assigned 1313 patients to the control group (n=657; 277 with bevacizumab and 380 without bevacizumab in the intention-to-treat population) or the cetuximab group (n=656; 283 with bevacizumab and 373 without bevacizumab in the intention-to-treat population). EGFR FISH was assessable in 976 patients and 400 patients (41%) were EGFR FISH-positive. The median follow-up for patients last known to be alive was 35·2 months (IQR 22·9-39·9). After 194 progression-free survival events in the cetuximab group and 198 in the control group in the EGFR FISH-positive subpopulation, progression-free survival did not differ between treatment groups (hazard ratio [HR] 0·92, 95% CI 0·75-1·12; p=0·40; median 5·4 months [95% CI 4·5-5·7] vs 4·8 months [3·9-5·5]). After 570 deaths in the cetuximab group and 593 in the control group, overall survival did not differ between the treatment groups in the entire study population (HR 0·93, 95% CI 0·83-1·04; p=0·22; median 10·9 months [95% CI 9·5-12·0] vs 9·2 months [8·7-10·3]). In the prespecified analysis of EGFR FISH-positive subpopulation with squamous cell histology, overall survival was significantly longer in the cetuximab group than in the control group (HR 0·58, 95% CI 0·36-0·86; p=0·0071), although progression-free survival did not differ between treatment groups in this subgroup (0·68, 0·46-1·01; p=0·055). Overall survival and progression-free survival did not differ among patients who were EGFR FISH non-positive with squamous cell histology (HR 1·04, 95% CI 0·78-1·40; p=0·77; and 1·02, 0·77-1·36; p=0·88 respectively) or patients with non-squamous histology regardless of EGFR FISH status (for EGFR FISH-positive 0·88, 0·68-1·14; p=0·34; and 0·99, 0·78-1·27; p=0·96; respectively; and for EGFR FISH non-positive 1·00, 0·85-1·17; p=0·97; and 1·03, 0·88-1·20; p=0·69; respectively). The most common grade 3-4 adverse events were decreased neutrophil count (210 [37%] in the cetuximab group vs 158 [25%] in the control group), decreased leucocyte count (103 [16%] vs 74 [20%]), fatigue (81 [13%] vs 74 [20%]), and acne or rash (52 [8%] vs one [<1%]). 59 (9%) patients in the cetuximab group and 31 (5%) patients in the control group had severe adverse events. Deaths related to treatment occurred in 32 (6%) patients in the cetuximab group and 13 (2%) patients in the control group. INTERPRETATION: Although this study did not meet its primary endpoints, prespecified subgroup analyses of patients with EGFR FISH-positive squamous-cell carcinoma cancers are encouraging and support continued evaluation of anti-EGFR antibodies in this subpopulation. FUNDING: National Cancer Institute and Eli Lilly and Company.

Genome-wide interaction study of smoking behavior and non-small cell lung cancer risk in Caucasian population.

Non-small cell lung cancer is the most common type of lung cancer. Both environmental and genetic risk factors contribute to lung carcinogenesis. We conducted a genome-wide interaction analysis between single nucleotide polymorphisms (SNPs) and smoking status (never- versus ever-smokers) in a European-descent population. We adopted a two-step analysis strategy in the discovery stage: we first conducted a case-only interaction analysis to assess the relationship between SNPs and smoking behavior using 13336 non-small cell lung cancer cases. Candidate SNPs with P-value <0.001 were further analyzed using a standard case-control interaction analysis including 13970 controls. The significant SNPs with P-value <3.5 × 10-5 (correcting for multiple tests) from the case-control analysis in the discovery stage were further validated using an independent replication dataset comprising 5377 controls and 3054 non-small cell lung cancer cases. We further stratified the analysis by histological subtypes. Two novel SNPs, rs6441286 and rs17723637, were identified for overall lung cancer risk. The interaction odds ratio and meta-analysis P-value for these two SNPs were 1.24 with 6.96 × 10-7 and 1.37 with 3.49 × 10-7, respectively. In addition, interaction of smoking with rs4751674 was identified in squamous cell lung carcinoma with an odds ratio of 0.58 and P-value of 8.12 × 10-7. This study is by far the largest genome-wide SNP-smoking interaction analysis reported for lung cancer. The three identified novel SNPs provide potential candidate biomarkers for lung cancer risk screening and intervention. The results from our study reinforce that gene-smoking interactions play important roles in the etiology of lung cancer and account for part of the missing heritability of this disease.

Phase 1b trial of proteasome inhibitor carfilzomib with irinotecan in lung cancer and other irinotecan-sensitive malignancies that have progressed on prior therapy (Onyx IST reference number: CAR-IST-553).

Introduction Proteasome inhibition is an established therapy for many malignancies. Carfilzomib, a novel proteasome inhibitor, was combined with irinotecan to provide a synergistic approach in relapsed, irinotecan-sensitive cancers. Materials and Methods Patients with relapsed irinotecan-sensitive cancers received carfilzomib (Day 1, 2, 8, 9, 15, and 16) at three dose levels (20/27 mg/m2, 20/36 mg/m2 and 20/45 mg/m2/day) in combination with irinotecan (Days 1, 8 and 15) at 125 mg/m2/day. Key eligibility criteria included measurable disease, a Zubrod PS of 0 or 1, and acceptable organ function. Patients with stable asymptomatic brain metastases were eligible. Dose escalation utilized a standard 3 + 3 design. Results Overall, 16 patients were enrolled to three dose levels, with four patients replaced. Three patients experienced dose limiting toxicity (DLT) and the maximum tolerated dose (MTD) was exceeded in Cohort 3. The RP2 dose was carfilzomib 20/36 mg/m2 (given on Days 1, 2, 8, 9, 15, and 16) and irinotecan 125 mg/m2 (Days 1, 8 and 15). Common Grade (Gr) 3 and 4 toxicities included fatigue (19%), thrombocytopenia (19%), and diarrhea (13%). Conclusions Irinotecan and carfilzomib were well tolerated, with common toxicities of fatigue, thrombocytopenia and neutropenic fever. Objective clinical response was 19% (one confirmed partial response (PR) in small cell lung cancer (SCLC) and two unconfirmed); stable disease (SD) was 6% for a disease control rate (DCR) of 25%. The recommended phase II dose was carfilzomib 20/36 mg/m2 and irinotecan125 mg/m2. The phase II evaluation is ongoing in relapsed small cell lung cancer.

Comprehensive genomic profiling in routine clinical practice leads to a low rate of benefit from genotype-directed therapy.

BACKGROUND: Describe a single-center real-world experience with comprehensive genomic profiling (CGP) to identify genotype directed therapy (GDT) options for patients with malignancies refractory to standard treatment options. METHODS: Patients who had CGP by a CLIA-certified laboratory between November 2012 and December 2015 were included. The medical records were analyzed retrospectively after Institutional Review Board (IRB) approval. The treating oncologist made the decision to obtain the assay to provide potential therapeutic options. The objectives of this study were to determine the proportion of patients who benefited from GDT, and to identify barriers to receiving GDT. RESULTS: A total of 125 pediatric and adult patients with a histologically confirmed diagnosis of malignancy were included. Among these, 106 samples were from adult patients, and 19 samples were from pediatric patients. The median age was 54 years for adults. The majority had stage IV malignancy (53%) and were pretreated with 2-3 lines of therapy (45%). The median age was 8 years for pediatric patients. The majority had brain tumors (47%) and had received none or 1 line of therapy (58%) when the profiling was requested. A total of 111 (92%) patients had genomic alterations and were candidates for GDT either via on/off-label use or a clinical trial (phase 1 through 3). Fifteen patients (12%) received GDT based on these results including two patients who were referred for genomically matched phase 1 clinical trials. Three patients (2%) derived benefit from their GDT that ranged from 2 to 6 months of stable disease. CONCLUSIONS: CGP revealed potential treatment options in the majority of patients profiled. However, multiple barriers to therapy were identified, and only a small minority of the patients derived benefit from GDT.

p16INK4a Status and Response to Induction Low-Dose Fractionated Radiation in Advanced Head and Neck Cancer.

OBJECTIVE: To evaluate the impact of p16INK4a (p16) expression on clinical efficacy of induction low-dose fractionated radiation therapy (LDFRT) with concurrent chemotherapy in patients with locally advanced squamous cell carcinoma of the head and neck (SCCHN). STUDY DESIGN: Historical cohort study. SETTING: Tertiary medical center. METHODS: A total of 66 Patients with locally advanced SCCHN were enrolled in 2 clinical trials using paclitaxel, carboplatin, and concurrent LDFRT induction therapy. Patients were evaluated for response to induction by a multidisciplinary team and then were given definitive treatment. Adequate tissue samples from the pretreatment biopsies of 42 individuals were identified and analyzed for p16 expression. Expression was correlated with clinical outcomes. RESULTS: Of 42 tumors, 15 (35.7%) were positive for p16. Patients with p16-positive tumors had improved response to induction, but this was not statistically significant (P = .06). Five-year overall survival was 80% in p16-positive patients and 58% in p16-negative patients (P = .025). CONCLUSIONS: p16 Expression affects treatment response in patients treated with induction LDFRT with concurrent chemotherapy. This is similar to results reported for standard induction chemotherapy.

Responsive Hydrogel Nanoparticles for Pulmonary Delivery.

Nanoparticles represent one of the most widely studied classes of advanced drug delivery platforms in recent years due to a wide range of unique properties and capabilities that can be utilized to improve upon traditional drug administration. Conversely, hydrogel nanoparticles (HNPs) - also called nanogels - represent a unique class of materials that combine the intrinsic advantages of nanotechnology with the inherent capabilities of hydrogels. Responsive hydrogels pose a particularly interesting class of materials that can sense and respond to external stimuli and previous reports of inhalable hydrogel particles have highlighted their potential in pulmonary delivery. Here, we synthesized two different pH-responsive HNPs, designated HNP120 and HNP270, by incorporating functional monomers with a common crosslinker and characterized their physicochemical properties. One of the HNP systems was selected for incorporation into a composite dry powder by spray drying, and the aerodynamic performance of the resulting powder was evaluated. The HNP120s displayed a hydrodynamic diameter of approximately 120 nm in their fully swollen state and a minimal diameter of around 80 nm while the HNP270s were approximately 270 nm and 115 nm, respectively. Electron microscopy confirmed particle size- and morphological uniformity of the HNPs. The HNP120s were spray dried into composite dry powders for inhalation and cascade impaction studies showed good aerosol performance with a mass median aerosol diameter (MMAD) of 4.82 ± 0.37 and a fine particle fraction > 30%. The HNPs released from the spray dried composites retained their responsive behavior thereby illustrating the potential for these materials as intelligent drug delivery systems that combine the advantages of nanotechnology, lung targeting through pulmonary delivery, and stimuli-responsive hydrogels.

Cancer research provides a model for advancing clinical trials in dementia in the era of disease-modifying Alzheimer's-type dementia therapies.

Dementia and cancer are multifactorial, widely-feared, age-associated clinical syndromes that are increasing in prevalence. There have been major breakthroughs in clinical cancer research leading to some effective treatments, whereas the field of dementia has achieved comparatively limited success in clinical research. The lessons of cancer research may help those in the dementia research field in confronting some of the dilemmas faced when the clinical care regimen is not entirely safe or efficacious. Cancer clinical trials have assumed that untreated individuals with cancer are at high risk for morbidity and mortality after primary diagnoses. Thus, patients deserve a choice of clinical interventions, either standard of care or experimental, even if the benefits are not certain and the therapy's side effects are potentially severe. The prognosis for many individuals at risk for dementia carries a correspondingly high level of risk for both mortality and severe morbidity, particularly if one focuses on "health-span" rather than lifespan. Caregivers and patients can be strongly impacted by dementia and the many troubling associated symptoms that often go well beyond amnesia. Polls, surveys, and a literature on "dementia worry" strongly underscore that the public fears dementia. While there are institutional and industry hurdles that complicate enrollment in randomized trials, the gravity of the future morbidity and mortality inherent in a dementia diagnosis may require reconsideration of the current protective stance that limits the freedom of at-risk individuals (either symptomatic or asymptomatic) to participate and potentially benefit from ongoing clinical research. There is also evidence from both cancer and dementia research that individuals enrolled in the placebo arms of clinical trials have unexpectedly good outcomes, indicating that participation in clinical trial can have medical benefits to enrollees. To highlight aspects of cancer clinical research that may inform present and future dementia clinical research, this review highlights three main themes: the risk of side effects should be weighed against the often dire consequences of non-treatment; the desirability of long-term incremental (rather than "magic bullet") clinical advances; and, the eventual importance of combination therapies, reflecting that the dementia clinical syndrome has many underlying biological pathways.

A Probabilistic Approach to Estimate the Temporal Order of Pathway Mutations Accounting for Intra-Tumor Heterogeneity.

The development of cancer involves the accumulation of somatic mutations in several essential biological pathways. Delineating the temporal order of pathway mutations during tumorigenesis is crucial for comprehending the biological mechanisms underlying cancer development and identifying potential targets for therapeutic intervention. Several computational and statistical methods have been introduced for estimating the order of somatic mutations based on mutation profile data from a cohort of patients. However, one major issue of current methods is that they do not take into account intra-tumor heterogeneity (ITH), which limits their ability to accurately discern the order of pathway mutations. To address this problem, we propose PATOPAI, a probabilistic approach to estimate the temporal order of mutations at the pathway level by incorporating ITH information as well as pathway and functional annotation information of mutations. PATOPAI uses a maximum likelihood approach to estimate the probability of pathway mutational events occurring in a specific sequence, wherein it focuses on the orders that are consistent with the phylogenetic structure of the tumors. Applications to whole exome sequencing data from The Cancer Genome Atlas (TCGA) illustrate our method's ability to recover the temporal order of pathway mutations in several cancer types.