bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 626: Association of circulating vitamin D concentrations with colorectal cancer risk differs depending on inherited genotypes in combination with dietary lifestyle factors
Authors: Gibbs David C. , McCullough Marjorie L. , Song Mingyang , Um Caroline Y. , Wu Kana , Jenab Mazda , Giovannucci Edward , Bostick Roberd M. , Fedirko Veronika 
Published: August 2019

Abstract
Higher circulating 25-hydroxyvitamin-D [25(OH)D] concentrations - used clinically to assess vitamin D status - are inversely associated with colorectal cancer (CRC) risk. However, it remains unknown whether this association varies by common, inherited polymorphisms encoding common vitamin D-binding protein (DBP) isoforms linked to differences in vitamin D handling and metabolism. We pooled participant-level data from three prospective cohorts in the United States (Cancer Prevention Study-II [CPS-II], Nurses’ Health Study [NHS]) and Western Europe (European Prospective Investigation into Cancer and Nutrition [EPIC]), comprising 1,710 incident CRC cases diagnosed between 1990 and 2011, and 1,649 matched controls selected using incidence density sampling. There were 1,106, 246 and 358 CRC cases in EPIC, CPS-II and NHS, respectively. Pre-diagnostic 25(OH)D measurements were calibrated to the same assay and seasonally-adjusted. Study-specific relative risks (RRs) for 25(OH)D and CRC risk according to DBP2 isoform (determined by the GC rs4588 variant) were estimated using multivariable unconditional logistic regression and pooled using fixed effects models. We also stratified our models by dietary vitamin D intake to account for differences in fortification/supplementation in the US and Europe. Variation in 25(OH)D concentrations across studies reflected differences in vitamin D intake and supplement use. Among individuals with lower vitamin D intakes (≤ 330 IU/day), for each 25 nmol/L increase in 25(OH)D, CRC risk was 30% lower among those with the DBP2 isoform (RR = 0.70, 95% CI = 0.59-0.83), and 5% lower among those without DBP2 (RR = 0.95, 95% CI = 0.82-1.10) (Pheterogeneity by DBP isoform = 0.009). Among individuals with higher vitamin D intakes (&gt;330 IU/day, CPS-II and NHS only), for each 25 nmol/L increase in 25(OH)D, CRC risk was 18% higher among those with DBP2 (RR = 1.18, 95% CI = 0.82-1.10), and 33% lower among those without the DBP2 isoform (RR = 0.67, 95% CI = 0.53-0.85) (Pheterogeneity by DBP isoform = 0.002). These findings suggest that the association of 25(OH)D with CRC risk differs depending on inheritance of the functional DBP2 isoform in combination with levels of dietary vitamin D intake. &lt;!–EndFragment–&gt;
Citation Format: David C. Gibbs, Marjorie L. McCullough, Mingyang Song, Caroline Y. Um, Kana Wu, Mazda Jenab, Edward Giovannucci, Roberd M. Bostick, Veronika Fedirko. Association of circulating vitamin D concentrations with colorectal cancer risk differs depending on inherited genotypes in combination with dietary lifestyle factors [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 626.
Abstract 64: Regulation and functional role of the cell-cell junction-associated RNAi machinery in colon cancer
Authors: Daulagala Amanda C. , Bridges Catherine , Rutledge Lauren , Nair-Menon Joyce , Yost Micheal , Kourtidis Antonis 
Published: August 2019

Abstract
Colon cancer is the third most common and the second deadliest type of cancer in the United States. A typical characteristic of colon tumors is the compromised integrity of the colonic epithelial monolayer. The Adherens Junction (AJ) is a cell-cell adhesion complex essential for the maintenance of the epithelial integrity, composed of E-cadherin and the catenin family of proteins. We have recently shown that the E-cadherin-p120 catenin partner PLEKHA7 is critical for epithelial monolayer integrity. We have also revealed that PLEKHA7 recruits the core components of the RNA interference (RNAi) machinery, such as Ago2, DROSHA and DGCR8, as well as miRNAs at the mature apical adherens junctions, to suppress expression of pro-tumorigenic markers, through miRNA-mediated silencing. However, we still haven’t examined the extend of the contribution of this mechanism to colon tumorigenesis and its modes of regulation. We hypothesize that the adherens junction-RNAi mechanism acts as an epithelial sensor that tethers monolayer integrity to cell behavior. To examine this, we generated 3D cultures of well-differentiated Caco2 colon epithelial cells on Matrigel to examine the distribution of RNAi proteins. Indeed, co-localization of PLEKHA7 with RNAi proteins occurs specifically at the apical surface of these spheroids, whereas PLEKHA7 depletion results in loss of junctional localization of RNAi proteins and in enlarged, multilayered structures. Corroborating these results, PLEKHA7 and RNAi components co-localize specifically at the apical surface of normal colon crypts, whereas extensive disruption or loss of this co-localization was observed in colon tumor patient samples. Fibrosis and extensive deposition of extracellular matrix (ECM) due to chronic inflammation is a precursor to colon cancer. ECM can affect adherens junctions integrity, through integrin-Src signaling. Indeed, we have found that Src activity disrupts localization of PLEKHA7 and RNAi proteins to the junctions. To investigate the potential role of ECM in the regulation of the junctional RNAi mechanism, we are now examining Caco2 cells grown on different ECM substrates, as well as under different conditions of mechanical strain, since fibrosis poses mechanical stress on cells. In summary, our data point towards a novel putative tumor suppressor mechanism, of which we are investigating its modes of regulation and its involvement in colon tumorigenesis.
Citation Format: Amanda C. Daulagala, Catherine Bridges, Lauren Rutledge, Joyce Nair-Menon, Micheal Yost, Antonis Kourtidis. Regulation and functional role of the cell-cell junction-associated RNAi machinery in colon 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 64.
Abstract 642: Increasing BMI is associated with tumor volume and uterine weight in endometrial cancer
Authors: Zhang Yingao , Desravines Nerlyne , Moore Dominic T. , Gehrig Paola A. , Clark Leslie H. , Bae-Jump Victoria L. 
Published: August 2019

Abstract
Obesity and diabetes is associated with increased risk and worse outcomes in endometrial cancer (EC). Our previous work has found that obesity leads to more aggressive tumor behavior and a doubling of tumor size in EC mouse models. Thus, we explored the association between endometrial tumor volume (TV) and uterine weight (UW) as a function of BMI in EC patients. We performed a retrospective review of EC patients diagnosed and treated from 2005-2010 at a single tertiary care center. Tumor histology, dimensions, stage, grade, and UW were extracted from surgical pathology reports. Patient age, BMI, and diabetic status were also collected. TV was determined using the formula TV=l*d*w*pi/6. Independent variables include obesity classification, BMI, and diabetic status. Univariable and multivariable regression models were used to assess strength of association. A total of 564 EC patients were evaluated, with either endometrioid (n=522) or serous (n=42) histologies (Table 1). Within the endometrioid subgroup, associations were noted for both increased TV and UW with obesity (TV p=0.02; UW p&lt;0.001) and BMI (TV p=0.007; UW p&lt;0.001). Within the serous subgroup, increased TV was associated with obesity and BMI (p&lt;0.001; p=0.007), but UW was only associated with obesity (p=0.005) and not BMI (p=0.07). Controlling for stage and grade, multivariable models demonstrated similar patterns with obesity status and BMI within both subgroups. Multivariable analyses also demonstrated that having diabetes (n=160) was associated with both higher TV and UW in the endometrioid subgroup (TV p=0.004; UW p=0.02), but not in the serous subgroup (TV p=0.71; UW p=0.12). Obesity and increasing BMI appear to be associated with both increased TV and UW in EC patients, consistent with our previously described findings in murine models. Diabetes was also associated with higher TV and UW, but was only significant in patients with endometrioid ECs. Our results may partially account for the worse outcomes seen in obese EC patients.
Table 1EC HistologyMedianIQREndometrioid (n=522)Uterine Weight (g)Non-obese118.183.0-157.5Obese140.0103.8-200.0Tumor Volume (cm3)Non-obese3.6950.927-9.664Obese4.3591.419-14.216Serous (n=42)Uterine Weight (g)Non-obese116.667.4-166.6Obese189.8127.6-252.6Tumor Volume (cm3)Non-obese3.2490.601-9.382Obese23.8247.356-59.494
Citation Format: Yingao Zhang, Nerlyne Desravines, Dominic T. Moore, Paola A. Gehrig, Leslie H. Clark, Victoria L. Bae-Jump. Increasing BMI is associated with tumor volume and uterine weight in endometrial 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 642.
Abstract 647: Immunoprevention of triple negative breast cancer by a TOP2A multi-peptide vaccine
Authors: Lee Sang Beom , Pan Jing , Jiang Yueqiang , Palen Katie , Johnson Bryon , Fernando Romaine Ingrid , Sei Shizuko , Lubet Ronald , You Ming , Wang Yian 
Published: August 2019

Abstract
Triple negative breast cancer (TNBC) comprises approximately 20% of all breast cancers, and it has a poor prognosis due to aggressive growth characteristics and lack of effective targeted therapies. Emerging data suggest vaccination as a promising approach to prevent TNBC as well as other cancer types, but appropriate vaccine targets need to be identified. In the present study, we employed in silico analyses to select genes that are uniquely expressed in TNBC. Topoisomerase 2 alpha (Top2A) was found to be highly expressed in human TNBC. Top2A is a key enzyme in DNA replication and has been identified as a target of anti-cancer therapy. Overexpression of Top2A was confirmed in human breast cancer tissue microarrays and in mouse TNBCs derived from C3(1)/TAg mice. Top2A-specific MHC class II epitopes with optimal binding affinity were identified using the “combined scoring system”, based on their potential to elicit a Th1 immune response. Furthermore, all peptides were selected to have 100% amino acid sequence homology between humans and mice for potential clinical translation. Four Top2A peptides with strong immunogenic responses were selected by immunization of tumor naïve mice followed by IFN-γ-based ELISPOT assays. These peptides were combined to form a multi-peptide Top2A vaccine. The anti-tumor efficacy of the Top2A vaccine was tested in a preventive setting using a syngeneic TNBC model in C3(1)/TAg-REAR mice. Vaccinated animals demonstrated a significant reduction in tumor growth when compared to the adjuvant control with tumor size decreasing from 278.1 mm3 in adjuvant control to 150.4 mm3 in vaccinated group (p &lt; 0.05). Taken together, our data clearly demonstrate that the Top2A multi-peptide vaccine is highly immunogenic and provides immunopreventive efficacy against TNBC in mice.
Citation Format: Sang Beom Lee, Jing Pan, Yueqiang Jiang, Katie Palen, Bryon Johnson, Romaine Ingrid Fernando, Shizuko Sei, Ronald Lubet, Ming You, Yian Wang. Immunoprevention of triple negative breast cancer by a TOP2A multi-peptide vaccine [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 647.
Abstract 663: Diagnostic screen for lung cancer using high throughput metabolomics screen
Authors: Plumb Robert S. , Gethings Lee , Peck Andrew 
Published: August 2019

Abstract
Lung cancer is one of the most common cancers in the world. It is a leading cause of cancer death in men and women in the United States, cigarette smoking being leading cause of lung cancer. There are two main types of lung cancer small cell and non-small cell lung cancer (NSCLC). The most common type being NSCLC which accounts for 80-85% of all reported cases. The ability to rapidly detect / diagnose lung cancer at an early stage is critical to successful treatment selection and patient survival.
The use of metabolic profiling in biomedical applications metabolic profiling is being deployed as a method for finding novel, mechanistic, biomarkers of disease with obvious potential for improving diagnosis, and patient stratification. Here we present a rapid, simple and reliable high throughput targeted LC/MS single platform, for the quantification/monitoring of small molecule metabolites, lipids and peptides. The methodology employs a single set of LC/MS conditions which facilitate TCA cycle, bile acids, biogenic amine, free fatty acids, acyl carnitines, lipids and 100 protein panel without need for user intervention.
Plasma from pilot cohort of lung cancer a health control samples were evaluated using this new methodology. The methodology showed excellent reproducibility and accuracy. The peptide analysis showed that 10 peptides were shown to be markers of lung cancer, these are listed in Table 1. Acylcarnitines were quantified over a range of 5 - 625ng/mL data showed that the C14:2 tetradecadienoyl carnitine and C16:1 palmitoleoyl carnitine were elevated in lung cancer samples whereas the C8:1 octenoyl carnitine level was reduced in the lung cancer samples . Although deoxycholic acid and chendeoxycholic acid appeared to be reduced in the lung cancer samples this was determined to be not statistically relevant. A total of 29 amino acids were measured during the analysis. Using t-test with p-value FDR cutoff adjusted to 0.01 the data clearly showed that sarcosine was highly over-expressed in lung cancer samples.
Table 1P02749Apolipoprotein HP19652Alpha-1-acid glycoprotein 2P68871Hemoglobin subunit betaP02671Fibrogen alpha chainP02656Apolipoprotein C-IIIP02750Leucine-rich alpha 2-glycoprotein (LRG)P00738HaptoglobinP02748Complement component C9P02763Alpha-1-acid glycoprotein 1P01011Alpha-1-antichymotrypsin
Note: This abstract was not presented at the meeting.
Citation Format: Robert S. Plumb, Lee Gethings, Andrew Peck. Diagnostic screen for lung cancer using high throughput metabolomics screen [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 663.
Abstract 673: Impact of PD-L1 feedback modulation on the sensitivity of anti-PD-1/PD-L1
Authors: Zhu Jian , Zhu Rebecca L. 
Published: August 2019

Abstract
The long-term benefits of anti-PD-1/PD-L1 are limited in most cancer patients. Resistance and insensitivity are major challenges of this therapeutic class. Feedback regulation of PD-L1 could serve as a mechanism of drug resistant, especially negative feedback loops where inhibition of PD-L1 may lead to up-regulation of its own expression and function. In this study, computational models were established to investigate PD-L1 feedback modulations to facilitate discovery of biomarkers for drug sensitivity and to inform design of drug combination studies. As of October 2018, over 10,000 publications on cancer and immunosuppressive factors (e.g. PD-1, PD-L1, CTLA4, IDO1, TIM-3, LAG3, TIGIT) were found in PubMed. About 2500 abstracts of these articles were downloaded and systematically analyzed through natural language processing and text mining. Information on gene/drug, pathway/disease along with results from cell/animal/clinical studies were extracted, standardized and integrated into a directed graph-based database. Algorithms were designed to construct networks and identify PD-L1 feedback loops (FBLs). Fisher's Exact tests were performed to evaluate the significance of factors involved in (+) and (-)FBLs. The computationally generated PD-L1 feedback network comprises 102 nodes, 216 interactions with 1080 possible FBLs (502 positive vs 578 negative). In particular, up-regulation of IL10, pEGFR, SRC, HIF1A, ISX, NF-kappaB, pSMAD2/SMAD2, IFN-gamma were strongly associated with up-regulation of PD-L1 upon inhibition of PD-1/PD-L1 (p&lt;0.0001, (-)FBLs). Interestingly, TIM-3, a potential IO target and commonly up-regulated by anti-PD-1/PD-L1, is involved in both (+) and (-)FBLs. Inhibition of TIM-3 (e.g. anti-TIM-3) could decrease IL-10 in Tregs and enhance efficacy of anti-PD-1/PD-L1, but meanwhile, anti-TIM-3 could activate NF-kappaB, IRF7 and STAT1, leading to up-regulation of PD-L1 expression and potential resistance to anti-PD-1/PD-L1. In conclusion, the literature-based network analysis proved to be effective to identify potential regulatory pathways driving resistance to immunotherapies, to prioritize the selection of biomarkers, and to assess risk of drug combinations. Particularly, through the analysis of feedback regulations of PD-L1, novel therapeutic approaches to boost efficacy of anti-PD-1/PD-L1 could be postulated. Targeting genes involved in both (+) and (-)FBLs of PD-L1, such as TIM-3, needs to be carefully evaluated.
Citation Format: Jian Zhu, Rebecca L. Zhu. Impact of PD-L1 feedback modulation on the sensitivity of anti-PD-1/PD-L1 [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 673.
Abstract 676: Leveraging TCGA gene expression data to build predictive models for cancer drug response
Authors: Clayton Evan 
Published: August 2019

Abstract
Personalized oncology promises to increase the success rate of cancer drug therapy by using molecular tumor profiles to determine the optimal therapeutic for an individual. 5-Fluorouracil and Gemcitabine are two Food and Drug Administration approved chemotherapeutics commonly prescribed to cancer patients. Here, we build machine learning models using gene expression data from patients’ primary tumors to predict their response, positive or negative, to these drugs. We compared several clustering and classification methods for predicting response. Of those tested, Clara was found to be the best clustering algorithm while random forest was the best classification method, with prediction accuracy up to 86%. We determined that models trained across several cancers outperform single cancer models. We also found that genes most informative for predicting drug response were enriched in well-known cancer signaling pathways, highlighting their potential significance in chemotherapy prognosis. Ultimately, such predictive models may aid oncologists with making critical treatment decisions.
Citation Format: Evan Clayton. Leveraging TCGA gene expression data to build predictive models for cancer drug response [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 676.
Abstract 68: Comparative transcriptome analysis of primary tumor and matched tumor thrombus reveals that coagulation cascades activation contributes to the venous metastases of osteosarcoma
Authors: Ji Tao , Wang Yifei , Guo Yi , Li Dasen , Liang Haijie , Ren Tingting , Guo Wei 
Published: August 2019

Abstract
Comparative transcriptome analysis of primary tumor and matched tumor thrombus reveals that coagulation cascades activation contributes to the venous metastases of osteosarcoma
Osteosarcoma is the most frequent malignant primary tumor of bone in children and adolescents with an approximately 5-year survival about 50-60%. Lung metastasis remains as the most challenging condition during treatment and follow-up, which has been regarded as the main reason for bottle neck of prognosis. Tumor thrombus is occasionally diagnosed in patients with malignant tumor. It usually exists during tumor angiogenesis associated with proliferation and metastasis. The presentation shows aggressive features and advanced stage of the disease. Tumor thrombus is associated with highly metastasis potential. Based on the evolution theory of tumor metastasis, tumor thrombus can be the intermediate phase between local invasion and distal metastasis. In order to investigate the underlying mechanism and identify candidate metastasis driver genes, we collected a set of high quality paired tumor tissue, both the primary site and corresponding tumor thrombus that were treated by thrombectomy. In this study, we present a large-scale transcriptome analysis, by RNA sequencing, of 4 patients diagnosed with large pelvic osteosarcoma with tumor thrombus. The dysregulated genes between primary site and thrombus suggested that the complement and coagulation cascades, focal adhesion and extracellular matrix receptor was correlated with the formation of tumor thrombus. Tissue factor was identified as a major marker in coagulation pathway activation. We also identified NOTCH2NL-NBPF1 fusion genes in all four patients. All of these findings broaden our knowledge of osteosarcoma thrombus and may also contribute to the novel mechanism of metastasis in osteosarcoma.
Citation Format: Tao Ji, Yifei Wang, Yi Guo, Dasen Li, Haijie Liang, Tingting Ren, Wei Guo. Comparative transcriptome analysis of primary tumor and matched tumor thrombus reveals that coagulation cascades activation contributes to the venous metastases of osteosarcoma [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 68.
Abstract 681: Methylation biomarkers of cellular response to demethylating drug
Authors: Wang Xuewei , Kocher Jean-Pierre , Sun Zhifu 
Published: August 2019

Abstract
DNA methylation plays an import role in both tumorigenesis and therapy resistance. Demethylating drug regimens have shown efficacy in hematological malignancies, and are actively studied for other cancer types. High variability in patients’ responses to these drugs has been observed and highlights the demand to identify predictive biomarkers for these demethylating drugs. In particular, decitabine (latest FDA-approved demethylating drug) demonstrated as the most potent agent and has the best response on hematological cell lines. Two public datasets were collected to identify methylation biomarkers of decitabine. The first one is from Genomics of Drug Sensitivity in Cancer, with methylation data from Illumina 450K array and drug response from cell lines. The other one is a publicly available patient dataset (methylations from RRBS sequencing and decitabine response from clinic). 64900 CpG sites common to the two methylation platforms were used to train machine learning model (Elastic Net), based on the methylation data and decitabine response (AUC) from 108 hematological cell lines in GDSC. 73 CpGs were identified as predictive biomarkers by Elastic Net. The trained model was then used to make predictions on 39 patients (20 responders and 19 non-responders) with their methylation profiles of the same set of CpGs. The predicted response of responder group is indeed better than non-responder group (p-value = 0.0501), indicating the validity of identified methylation biomarkers. The top one CpG identified by Elastic Net resides in the promoter region of gene C20orf85, and is significantly hypermethylated in non-responder group (p-value = 0.0458), suggesting its potential involvement in the resistance to decitabine.
Citation Format: Xuewei Wang, Jean-Pierre Kocher, Zhifu Sun. Methylation biomarkers of cellular response to demethylating drug [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 681.