Citations

Abstract Background: Lung cancer kills more people than any other cancer in the United States. In addition to environmental factors, lung cancer has genetic risk factors as well, though the genetic etiology is still not well understood. We have performed whole exome sequencing on 262 individuals from 28 extended families with a family history of lung cancer. Methods: Parametric genetic linkage analysis was performed on these samples using two distinct analyses—the lung cancer only (LCO) analysis, where only patients with lung cancer were coded as affected, and the all aggregated cancers (AAC) analysis, where other cancers seen in the pedigree were coded as affected. Results: The AAC analysis yielded a genome-wide significant result at rs61943670 in POLR3B at 12q23.3. POLR3B has been implicated somatically in lung cancer, but this germline finding is novel and is a significant expression quantitative trait locus in lung tissue. Interesting genome-wide suggestive haplotypes were also found within individual families, particularly near SSPO at 7p36.1 in one family and a large linked haplotype spanning 4q21.3-28.3 in a different family. The 4q haplotype contains potential causal rare variants in DSPP at 4q22.1 and PTPN13 at 4q21.3. Conclusions: Regions on 12q, 7p, and 4q are linked to increased cancer risk in highly aggregated lung cancer families, 12q across families and 7p and 4q within a single family. POLR3B, SSPO, DSPP, and PTPN13 are currently the best candidate genes. Impact: Functional work on these genes is planned for future studies and if confirmed would lead to potential biomarkers for risk in cancer.

Abstract Background: Limited information existed about the distributions of microbial etiology and drug-resistance with severe community-acquired pneumonia (CAP) in China, partly attributing to the antibiotics abuse in rearing livestock for Chinese farmers in recent decades. Moreover, the relevant guidelines have not been updated for at least a decade.Methods: A prospective observational study was carried out in Zhongshan Hospital (Shanghai, China). All consecutive cases of severe CAP diagnosed in Respiratory intensive care unit (ICU) and Emergency ICU were included. We assessed the microbial etiology features and multidrug-resistance (MDR) status. The risk factors were used by multivariate analyses for outcomes.Results: One hundred and twelve adults with severe CAP in ICUs, mean age of 65.7±15.1 years were studied. Etiological diagnoses were established in 76 (67.9%) cases; Klebsiella pneumoniae was the most frequent pathogen in 27 (35.5%) cases followed by Acinetobacter baumannii (n=15, 19.7%) and Methicillin-resistant Staphylococcus aureus (MRSA) (n=9, 11.8%); While Streptococcus pneumoniae (n=3, 3.9%) was ranked the 6 th in the study. The majority of pathogens were the MDR and the 30-days mortality rate was 43.8% in severe CAP patients. Klebsiella pneumoniae (OR, 6.88; 95%CI, 1.13-41.83), Sequential organ failure assessment (SOFA)≥5(OR, 12.30; 95%CI, 1.79-84.55) was associated to death.Conclusions: The study indicates a change in the usual pattern of microbiol etiology of severe CAP and the MDR emerged in the majority of pathogens over a decade in eastern China. Enhanced control of using antibiotics to reduce the acquired resistance is urgent.

Abstract Lung cancer (LC) is the primary cause of cancer-related deaths in the United States. Whereas smoking and other environmental factors strongly increase LC risk, multiple genetic variants also contribute to risk in smokers. Furthermore, among smokers, some families have been identified with an abnormally high prevalence of LC, suggesting that unknown genetic factors can greatly increase LC risk in smokers. The typically short survival after LC diagnosis impedes collection of detailed genotypic information on any single large family pedigree, impairing the identification of putative high-risk factors. Therefore, the Genetic Epidemiology of LC Consortium has collected epidemiological and genetic data from a number of families with high numbers of LC cases from eight different sites across the US. In this study, we have obtained whole exome sequences (WES) from 290 members of 28 families, including 66 LC cases. We used a gene-based approach to allow for the possibility that different families may contain different variants of the same gene. Variants were filtered for i) allele frequency, ii) functional effect using combined annotation-dependent depletion (CADD), and, iii) affecting a gene with either a known or suspected role in cancer. We further selected variants based on their segregation in family pedigrees in a pattern consistent with a large effect on LC risk. Candidate LC risk genes were then identified as those represented in at least two families by the same or different variants. We further culled the list of genes by requiring the presence of at least one rare, functional variant enriched in the WES of 1060 cases relative to 899 controls from the Transdisciplinary Research on Cancer of the Lung consortium. This analysis narrowed our results to two genes, one being E2A, a member of the E family of bHLH transcription factors. Whereas loss-of-function mutations in E2A drive lymphoid cancers, the E2A protein also participates in an oncogenic heterodimer with TWIST1 that promotes the epithelial-mesenchymal transition and is implicated in multiple cancer types. Furthermore, the E2A/TWIST1 heterodimer is the primary TWIST1-containing complex implicated in oncogenesis, and silencing of E2A in KRAS-mutant non-small cell lung cancer (NSCLC) cell lines results in oncogene-stimulated senescence and apoptosis. Our data identified three distinct E2A variants present in all 10 sequenced LC cases in the 5 families in which those variants are found. Finally, two of these E2A variants are located only 57 nucleotides from each other, immediately adjacent to sequences encoding a transcription activation domain, suggesting that both variants alter the same specific protein function. These data identify E2A variants as likely high risk factors for LC in smokers and validate our general approach for identifying genetic factors with a large impact on LC risk. Citation Format: Claudio W. Pikielny, Anthony M. Musolf, Mariza de Andrade, Diptasri Mandal, Colette Gaba, Ping Yang, yafang Li, Ming You, Richard Wilson, Elena Y. Kupert, Marshall W. Anderson, Ann G. Schwartz, Susan M. Pinney, Ambrose I. Granizo-Mackenzie, Yanhong Liu, Ramaswamy Govindan, James McKay, Rayjean Hung, John K. Field, David C. Christiani, Joan E. Bailey-Wilson, Christopher I. Amos. Familial studies identify variants in the E2A transcription factor as putative risk factors for lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr LB-053.

Abstract Lung cancer (LC) kills more people in the United States each year than any other cancer. While it is well known that a variety of environmental factors (particularly tobacco smoke) strongly increase the risk of LC, there are multiple associated genetic variants with small contributions to risk. High aggregation of LC within rare individual families suggest that there are high-risk genetic variants as well. However, these genetic risk factors for LC are under studied due to the rapid fatality of LC. We studied 28 highly aggregated extended high-risk familial lung cancer (HRFLC) families collected from eight different sites across the US. Whole exome sequencing was performed on 290 individuals from these families to identify potential risk variants for HRFLC using genetic linkage analysis. Quality control was performed on the sequence data, filtering on parameters such as read depth, genotype quality, missingness, and Mendelian inconsistencies. Identity-by-descent (IBD) values were also calculated to verify correct familial relationships. Quality control procedures left approximately 400,000 SNVs and indels for analysis.Parametric two-point linkage analysis was performed assuming an autosomal dominant mode of inheritance. Disease allele frequency was set to 1% with a penetrance of 80% for carriers and 1% phenocopy rate. While we did not identify any genome-wide significant variants across the 28 families, multiple suggestive variants were identified. The largest cluster of suggestive variants was located at 14q32 in the CATSPERB gene. Given the likely locus heterogeneity in LC (combined with the lack of power in some families), it is not surprising that none of the variants were significant across the families; looking at the individual family results proved more informative. Long haplotypes linked to LC risk were identified in multiple families. These long runs of positive linkages, which have little to no negative linkage evidence across them, are characteristic of true linkage signals in these types of analysis. Two of the most interesting linked regions were at 7p36.1 and 4q21.23-28.23. The 7p signal (observed in a single family) was genome-wide suggestive and located within the SSPO gene. SSPO has been implicated in breast and skin cancer (melanoma); it is a novel lung cancer signal. The 4q linkage (again observed in a single family) covers a large chunk of 4q and contains multiple potential candidate genes, however, the best candidate gene is PTPN13, a gene implicated in lung cancer but never in familial lung cancer. We are currently evaluating the individual family results of several other pedigrees and plan to perform additional analyses to confirm these linkages. Citation Format: Anthony Musolf, Haiming Sun, Bilal A. Moiz, Claudio W. Pikielny, Mariza de Andrade, Diptasri Mandal, Colette Gaba, Ping Yang, Yafang Li, Ming You, Richard K. Wilson, Elena Y. Kupert, Marshall W. Anderson, Ann G. Schwartz, Susan M. Pinney, Christopher I. Amos, Ramaswamy Govindan, Joan E. Bailey-Wilson. Familial lung cancer exhibits multiple novel linked haplotypes within pedigrees [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4176.

PURPOSEDrug development is becoming increasingly expensive and time consuming. Drug repurposing is one potential solution to accelerate drug discovery. However, limited research exists on the use of electronic health record (EHR) data for drug repurposing, and most published studies have been conducted in a hypothesis-driven manner that requires a predefined hypothesis about drugs and new indications. Whether EHRs can be used to detect drug repurposing signals is not clear. We want to demonstrate the feasibility of mining large, longitudinal EHRs for drug repurposing by detecting candidate noncancer drugs that can potentially be used for the treatment of cancer.PATIENTS AND METHODSBy linking cancer registry data to EHRs, we identified 43,310 patients with cancer treated at Vanderbilt University Medical Center (VUMC) and 98,366 treated at the Mayo Clinic. We assessed the effect of 146 noncancer drugs on cancer survival using VUMC EHR data and sought to replicate significant associations (false discovery rate < .1) using the identical approach with Mayo Clinic EHR data. To evaluate replicated signals further, we reviewed the biomedical literature and clinical trials on cancers for corroborating evidence.RESULTSWe identified 22 drugs from six drug classes (statins, proton pump inhibitors, angiotensin-converting enzyme inhibitors, β-blockers, nonsteroidal anti-inflammatory drugs, and α-1 blockers) associated with improved overall cancer survival (false discovery rate < .1) from VUMC; nine of the 22 drug associations were replicated at the Mayo Clinic. Literature and cancer clinical trial evaluations also showed very strong evidence to support the repurposing signals from EHRs.CONCLUSIONMining of EHRs for drug exposure–mediated survival signals is feasible and identifies potential candidates for antineoplastic repurposing. This study sets up a new model of mining EHRs for drug repurposing signals.

e23111 Background: Acupuncture has been shown to reduce aromatase inhibitor-induced arthralgias, as well as possibly hot flashes and fatigue, but research has been limited. The purpose of this study was to evaluate real world perceived benefit of acupuncture for commonly experienced symptoms among breast cancer survivors. Methods: Breast cancer survivors who had used acupuncture for cancer- or treatment-related symptoms were identified using an ongoing prospective Mayo Clinic Breast Disease Registry (MCBDR) cohort. In addition, Mayo Clinic electronic health records (EHR) were queried to identify additional participants. All identified patients were mailed a survey with acupuncture-related questions. Respondents were also asked to recall their severity of arthralgia, myalgia, post-surgical pain, hot flashes, nausea/vomiting, fatigue, depression, anxiety, insomnia, lymphedema, headache, and neuropathy from 1 to 5 (1 = mild, 5 = severe) before and after acupuncture treatment. Results: Acupuncture use was reported among 413 participants in MCBDR (12% of all enrollees) and 73 patients were identified in the Mayo EHR. 241 eligible women returned surveys (median age at diagnosis 50 yrs). Mean symptom severity scores decreased from before to after acupuncture by at least 1 point for all queried symptoms (Table). Conclusions: Acupuncture is frequently used by patients for a variety of breast cancer-related symptoms. Those who do pursue acupuncture usually perceive few toxicities and substantial benefits. Cost may be a barrier to treatment for some. [Table: see text]

1562 Background: In Caucasian-predominant populations, overweight or obese NSCLC pts (BMI≥25-kg/m2) have better prognosis while underweight (BMI≤18.5-kg/m2) pts have a worse prognosis. A large pooled sample allowed us to evaluate the role of ethnicity in this BMI-NSCLC OS relationship. Methods: Using individual data, survival analysis was performed on 15 ILCCO studies, assessing the interactions between ethnicity and BMI on overall survival (OS). Adjusted Hazard Ratios (aHR) from Cox models and adjusted penalized smoothing spline plots were generated. Results: Among 13416 (77%) Caucasian, 2975 (17%) Asian, and 935 (5%) Black NSCLC pts analyzed, we confirmed that for all pts, being underweight at NSCLC diagnosis was associated with worse OS (aHR=1.68, CI 1.5-1.8, p<0.001), while overweight/obese pts had improved survival (aHR 0.89, CI 0.8-0.9, p<0.001), when compared to pts with normal BMI. In general, Black pts had poorer OS than Caucasian pts (aHR 1.26 CI 1.1-1.4, p<0.001). However, the BMI-OS relationship differed according to ethnicity (BMI-ethnicity interaction, p=0.009): Caucasian underweight pts had poorer OS (aHR 1.67, CI 1.5-1.8, P<0.001) while overweight/obese pts had improved OS (aHR 0.89, CI 0.8-0.9, P<0.001). In Asian pts, these two associations were aHR 1.15, CI 0.8-1.5, P=0.33, and aHR 0.91, CI 0.7-1.1, P=0.32, respectively. In Black pts, these two associations were aHR 1.06, CI 0.7-1.5, p=0.73 and 0.75, CI 0.6-0.8 p<0.001, respectively. For overweight/obese patients, as BMI rises from 25-kg/m2 through 45-kg/m2, the prognosis worsens for Caucasian pts, remains stable for Asian pts, but improves for Black pts. Conclusions: InCaucasian pts, being underweight had a greater negative impact on OS than for Asian or Black pts, while being obese had a greater beneficial impact in Blacks than in other ethnic groups. These ethnic differences likely reflect genetically-informed muscle/adipose tissue distributions, where Black pts may have less sarcopenic obesity than other ethnicities. In future prognostic studies, BMI relationships must account for ethnic differences.

Abstract An ultimate goal of precision medicine in lung cancer treatment is to restore patient health with maximized quality of life (QOL). Results from Mayo Clinic studies show that a significant improvement in fatigue, dyspnea, and pain scales could lead to better overall QOL. Although treatments and guidelines for clinical implementation to alleviate these key symptoms are available, few cancer patients receive adequate therapy, mostly because of limitations in current care delivery systems and unclear clinicians’ roles. For optimal care of lung cancer survivors in different subpopulations, three barriers must be overcome: physicians’ lack of knowledge, unwarranted practice variation, and uncertainty regarding care provider roles. Appropriate culturally adapted, tested and validated tools for QOL measures must be developed, rather than directly translating existing tools between different languages and across cultures or diverse subpopulations. Finally, lack of sensitive, adequate, and relevant tools in measuring health-related QOL (HRQOL) has long been an issue for effective data collection, demanding a global consensus on a set of core components that reflect the needs of all critical parties for the best cure and care, supporting patients to achieve optimal HRQOL.

Abstract Rationale Chronic obstructive pulmonary disease is an independent risk factor for lung cancer, but the underlying molecular mechanisms are unknown. We hypothesized that lung stromal cells activate pathological gene expression programs that support oncogenesis. Objectives To identify molecular mechanisms operating in the lung stroma that support the development of lung cancer. Methods The study included subjects with and without lung cancer across a spectrum of lung-function values. We conducted a multiomics analysis of nonmalignant lung tissue to quantify the transcriptome, translatome, and proteome. Measurements and Main Results Cancer-associated gene expression changes predominantly manifested as alterations in the efficiency of mRNA translation modulating protein levels in the absence of corresponding changes in mRNA levels. The molecular mechanisms that drove these cancer-associated translation programs differed based on lung function. In subjects with normal to mildly impaired lung function, the mammalian target of rapamycin (mTOR) pathway served as an upstream driver, whereas in subjects with severe airflow obstruction, pathways downstream of pathological extracellular matrix emerged. Consistent with a role during cancer initiation, both the mTOR and extracellular matrix gene expression programs paralleled the activation of previously identified procancer secretomes. Furthermore, an in situ examination of lung tissue showed that stromal fibroblasts expressed cancer-associated proteins from two procancer secretomes: one that included IL-6 (in cases of mild or no airflow obstruction), and one that included BMP1 (in cases of severe airflow obstruction). Conclusions Two distinct stromal gene expression programs that promote cancer initiation are activated in patients with lung cancer depending on lung function. Our work has implications both for screening strategies and for personalized approaches to cancer treatment.