bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract B11: Projecting individualized absolute risk of developing gastric cancer in Koreans
Authors: Song Minkyo , Yang Jae Jeong , Sung Hyuna , Kong Seong-Ho , Lee Hyuk-Joon , Kim Hyung-Ho , Kim Sang Gyun , Yang Han-Kwang , Sawada Norie , Tsugane Shoichiro , Inoue Manami , Kang Daehee 
Published: May 2019

Abstract
This abstract is being presented as a short talk in the scientific program. A full abstract is printed in the Proffered Abstracts section (PR15) of the Conference Proceedings.
Citation Format: Minkyo Song, Jae Jeong Yang, Hyuna Sung, Seong-Ho Kong, Hyuk-Joon Lee, Hyung-Ho Kim, Sang Gyun Kim, Han-Kwang Yang, Norie Sawada, Shoichiro Tsugane, Manami Inoue, Daehee Kang. Projecting individualized absolute risk of developing gastric cancer in Koreans. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr B11.
Abstract B14: Modulating effects of green and black tea on biomarkers of chronic inflammation by gender and smoking status
Authors: Hakim Iman A. , Aldaham Sami A. , Foote Janet , Chow H-H Sherry 
Published: May 2019

Abstract
Background/Purpose: Epidemiologic data implies that there are gender differences in lung cancer pathogenesis and possibly increased susceptibility to lung cancer in women. Chronic inflammation has been implicated as important modulator of human health by playing a significant role in both disease prevention and disease development. Several studies have demonstrated increased interleukin 6 (IL-6) and C-reactive protein (CRP) in the blood of smokers. The overall goal of this study was to develop a feasible tea intervention that will serve as a model for the chemoprevention of a wide range of tobacco-related diseases. Our immediate goal, that was addressed over a 4-year study period, was to determine the effects of high tea consumption on biological markers of chronic inflammation that mediate lung cancer risk, including, IL-6, CRP and antioxidant enzyme activities.
Methods: We completed a 6-month randomized, controlled, double-blinded trial in a group of current and former smokers. Participants were stratified on smoking status and gender, and were randomized to green or black tea preparations or a control intervention (matching placebo). Levels of urinary iIL-6 and CRP are used to measure chronic inflammation and levels of superoxide dismutase (SOD) in red blood cells are used to measure antioxidant enzymes.
Results: The study protocol was approved by all parties. A total of 138 participants (78 females and 60 males) completed the study. Our data show that il6 is significantly correlated with years of smoking and pack/year among smokers and former smokers. At the end of the 6-month intervention, female smokers in the green tea group showed a significant decrease in IL-6 (P=0.036) while male former smokers in the black tea group showed a significant decrease in CRP levels (P=0.012). There were no significant changes in dietary and serum antioxidant levels between the different groups.
Conclusion: This data implies that smokers are more likely to benefit from green tea intake while the beneficial effects of black tea are observed among former smokers.
Note: This abstract was not presented at the conference.
Citation Format: Iman A. Hakim, Sami A. Aldaham, Janet Foote, H-H Sherry Chow. Modulating effects of green and black tea on biomarkers of chronic inflammation by gender and smoking status. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr B14.
Abstract B15: Communicating information about personalised genomic risk of melanoma to family, friends, and health professionals
Authors: Cust Anne E. , Smit Amelia K. , Espinoza David , Louise Keogh , Butow Phyllis N. , Dunlop Kate , Kirk Judy , Newson Ainsley J. 
Published: May 2019

Abstract
Background: It is anticipated that cancer risk prediction tools, including those with genomic risk information, will increasingly be used to communicate personalised cancer risk to the public. Receiving information on personal genomic risk of cancer might encourage conversations about cancer prevention and early detection with family, friends and health professionals, but few studies have examined this.
Aims: To explore participant communication about personal genomic risk of melanoma to family, friends and health professionals, using a mixed-methods approach, and to examine results according to participants' genomic risk category (low, average, high).
Methods: We conducted a study examining the impact of giving information on personalised genomic risk of melanoma to the public. Participants (n=101) received a personalised booklet presenting their melanoma genomic risk based on variants in 21 genes, together with telephone-based genetic counselling and generic educational materials. They completed a questionnaire 3-months after receiving their personal genomic risk of melanoma. To further contextualise these data, we conducted semi-structured qualitative interviews with 30 participants.
Results: Participants' communication with health professionals according to melanoma genomic risk category was 41% for high-risk, 16% for average-risk and 13% for low-risk (P=0.02). Communication with family was 83% for high-risk, 65% for average-risk, 79% for low-risk participants (P=0.19); and communication with friends was 55% for high-risk, 43% for average-risk, 54% for low-risk participants (P=0.49). Preliminary thematic analysis found that preventive behaviours and early detection were raised by participants in discussions with family and doctors. Reasons for not communicating genomic risk included: concern about causing worry and not feeling a need to share the information.
Conclusions: Genomic risk information prompted conversations about melanoma risk and prevention, most frequently with family. When stratified by genomic risk, comparable numbers of participants discussed their genomic risk with family and friends, but communication with health professionals was more frequent among participants in a high-risk category.
Citation Format: Anne E. Cust, Amelia K. Smit, David Espinoza, Keogh Louise, Phyllis N. Butow, Kate Dunlop, Judy Kirk, Ainsley J. Newson. Communicating information about personalised genomic risk of melanoma to family, friends, and health professionals. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr B15.
Abstract B29: Terahertz spectral imaging and scanning for early detection of skin cancer
Authors: Rahman Anis , Rahman Aunik K. , Rao Babar 
Published: May 2019

Abstract
A terahertz diagnosis tool has been developed to identify early stage skin cancer at the cellular level. Here, three different techniques are used where each technique independently identifies a given disease condition compared to healthy skin specimen; thus, collectively forms a diagnostic procedure with minimal falls alarm. Namely, terahertz sub-surface spectral imaging, terahertz absorbance spectroscopy and skin thickness profiling have been used. Terahertz radiation is non-ionizing, therefore, save for in-vivo investigations. It is also more sensitive than other forms of probing energies. In the present work, biopsies from three skin disease conditions have been compared with a healthy skin sample. It was found that the terahertz images clearly visualize healthy skin cells where a regular cellular pattern is visible. In contrast, cancerous skin specimen images exhibit deterioration from regular cellular pattern indicating abnormal conditions. For example, the skin specimen excised by Mohs microsurgery and diagnosed for basal cell carcinoma exhibits cell agglomeration indicating the onset of tumor formation. Similarly, other skin conditions such as squamous cell carcinoma and lentigo maligna exhibit their characteristic images without a regular cell pattern. Since the skin is a layered structure, a thickness profile of the healthy skin clearly exhibits this layering pattern while the layering is significantly diminished for cancerous skin samples. Thus a diminished layering profile is an indication of skin abnormalities. In addition, spectral analyses also exhibit distinguishable differences between different cancer conditions compared to healthy skin spectrum. Details of the methodology and results will be discussed.
Note: This abstract was not presented at the conference.
Citation Format: Anis Rahman, Aunik K. Rahman, Babar Rao. Terahertz spectral imaging and scanning for early detection of skin cancer. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr B29.
Abstract IA02: A brief overview of building and validating absolute risk models
Authors: Pfeiffer Ruth 
Published: May 2019

Abstract
Statistical models that predict disease incidence, disease recurrence or mortality following disease onset have broad public health and clinical applications. Of great importance are models that predict absolute risk, namely the probability of a particular outcome, e.g. breast cancer, in the presence of competing causes of mortality. Although relative risks are useful for assessing the strength of risk factors, they are not nearly as useful as absolute risks for making clinical decisions or establishing policies for disease prevention. That is because such decisions or policies often weigh the favorable effects of an intervention on the disease of interest against the unfavorable effects that the intervention might have on other health outcomes. The common currency for such decisions is the (possibly weighted) absolute risk for each of the health outcomes in the presence and absence of intervention. First, I discuss various approaches to building absolute risk models from various data sources and illustrate them with absolute risk models for breast cancer and thyroid cancer.
Before a risk prediction model can be recommended for clinical or public health applications, one needs to assess how good the predictions are. I will give an overview over various criteria for assessing the performance of a risk model. I assume that we have developed a risk model on training data and assess the performance of the model on independent test or validation data. This approach, termed external validation, provides a more rigorous assessment of the model than testing the model on the training data (internal validation); even though cross-validation techniques are available to reduce the over-optimism bias that can result from testing the model on the training data. I present general criteria for model assessment, such as calibration, predictive accuracy and classification accuracy, and discriminatory accuracy. Calibration measures how well the numbers of events predicted by a model agree with the observed events that arise in a cohort. Calibration is the most important general criterion, because if a model is not well calibrated, other criteria, such as discrimination, can be misleading. Discriminatory accuracy measures how well separated the distributions of risk are for cases and non-cases. Another approach is to tailor the criterion to the particular application. I will also present novel criteria for screening applications or high risk interventions. If losses can be specified in a well-defined decision problem, I will show how models can be assessed with respect to how much they reduce expected loss.
Citation Format: Ruth Pfeiffer. A brief overview of building and validating absolute risk models. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr IA02.
Abstract IA07: Using genetic information in screening and prevention: Perspective of clinicians and policy-makers
Authors: Ransohoff David F. 
Published: May 2019

Abstract
How can genetic information be effectively used in screening and prevention?
The conceptual framework and rules of evidence for answering this question - widely used by clinicians, policy-makers, and payors - has been developed over decades in the field of Evidence-Based Medicine, exemplified by the approach of the USPSTF (US Preventive Services Task Force) and EGAPP (Evaluation of Genomic Applications in Practice and Prevention). The framework's principles include using the best evidence (clinical trials where available, and observational data where necessary) assessed in systematic searches that consider quality of each study using specific rules of evidence. Outcomes are projected quantitatively to assess net benefit (benefits vs harms) of prevention and screening strategies.
In this framework, genetic data may provide information about the magnitude of lifetime risk of developing a specific cancer, while other data (including genomic data) may provide information about the current risk that a cancer is present. Risks of appropriate magnitude may direct interventions that can prevent cancer (for example chemoprevention or preventive surgery) or that can detect the presence of early curable cancer or an important precursor.
This talk will describe the quantitative conceptual framework and its rationale, along with the implications, challenges, and opportunities for the use of genetic and genomic information for cancer prevention and screening.
Citation Format: David F. Ransohoff. Using genetic information in screening and prevention: Perspective of clinicians and policy-makers. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr IA07.
Abstract PR14: Development of a cancer risk prediction tool for use in the Risk Estimation For Lifestyle Enhancement Combined Trial (REFLECT)
Authors: Lophatananon Artitaya , Alajmi Kawthar , Thorpe Emma , Hughes John , Blodgett Joanna , Fisher Bernadette , Rogers Simon , Waters Erika K. , Muir Kenneth R. 
Published: May 2019

Abstract
Exposure to modifiable lifestyle and environmental risk factors accounts for approximately 40% of all cancers in the UK. Therefore, primary prevention is of growing importance and an effective and engaging strategy that encourages long-term adoption of healthy lifestyle behaviours is required.
Several multivariable risk prediction models have been developed to assess an individual's risk of developing specific cancers. Such models can be used in a variety of settings for prevention, screening, and guiding investigation and treatment. Models aimed at predicting future disease risk that contains modifiable factors may be of particular use for targeting health promotion activities at an individual level. We have therefore developed a UK version of the well-established U.S. derived “YourDiseaseRisk” model which allow users to quantify their individual risk of developing individual cancers relative to the population average risk.
The UK-Manchester version of “YourDiseaseRisk” computes 10 year cancer risk for 11 cancer types utilising UK figures for prevalence of risk factors and cancer incidence. The model can be used to estimate cancer risk for use in community settings.
Using a variety of qualitative and quantitative methods we have assessed the impact of the REFLECT risk model on public understanding of cancer risk factors and UK NHS Cancer Screening programs. We have also explored public opinion and perceptions regarding the provision of information on of genetic susceptibility to aid in further personalising cancer risk information.
This abstract is also being presented as Poster B10.
Citation Format: Artitaya Lophatananon, Kawthar Alajmi, Emma Thorpe, John Hughes, Joanna Blodgett, Bernadette Fisher, Simon Rogers, Erika K. Waters, Kenneth R. Muir. Development of a cancer risk prediction tool for use in the Risk Estimation For Lifestyle Enhancement Combined Trial (REFLECT). [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr PR14.
Abstract A10: Epigenetic mechanisms in liver tumors: Gene expression analysis of epigenetic machinery in hepatoblastomas
Authors: Rivas Maria , Costa Cecília da , Toledo Silvia , Cypriano Monica , Caires Luiz , Goulart Ernesto , Carraro Dirce , Werneck Isabela , Rosenberg Carla , Zatz Mayana , Krepischi Ana 
Published: May 2019

Abstract
Liver tumors in children are rare and account for only 1-4% of all pediatric solid tumors. While hepatocellular carcinoma is predominant in adults, the most common liver cancer in children is hepatoblastoma, an embryonal tumor. The prognosis of patients with advanced tumor stages remains poor as well as surviving children often face severe effects following aggressive chemotherapy.
Hepatoblastomas carry a low mutational burden, and the impairment of epigenetic mechanisms, which are the core of embryogenesis and development, stands out as an alternative route for tumorigenesis.
The main objective of this study was to explore the role of genes associated with methylation and hydroxymethylation in hepatoblastomas. The expression of seven genes of the epigenetic machinery (DNMT1, DNMT3A, DNMT3L, UHRF1, TET1, TET2, and TET3) was analyzed by qPCR (Taqman). The cohort of tumors consisted of 21 hepatoblastomas and a control group of 8 non-tumor differentiated liver tissues. Additionally, a 5hmC quantification assay (Quest 5-hmC DNA ELISA Kit) was applied to assess the level of 5hmC in tumors.
TET1 and TET2 genes, whose proteins are responsible for the active demethylation of 5-methylcytosine (5mC), and consequent production of 5-hydroxymethylcytosine (5hmC), were found to be upregulated. A significant increase in the 5hmC levels was also evident in tumor samples when compared to nontumoral tissues.
We have shown in hepatoblastomas an upregulated profile of TET1 and TET2 enzymes with a resulting elevation of 5hmC level in tumors. Our data suggest that hepatoblastomas could present a pluripotency pattern of gene expression when compared to differentiated livers; to address this issue, the expression levels of three genes associated with pluripotency (POU5F1, SOX2 and NANOG) were evaluated, with no significant alteration.
Therefore, although hepatoblastomas have a more undifferentiated molecular profile than mature hepatocytes, our results indicate that tumor cells are already commited with the differentiation process. Altogether, these data suggest that the development of hepatoblastomas is associated with a blockage in the stages of hepatoblasts.
Citation Format: Maria Rivas, Cecília da Costa, Silvia Toledo, Monica Cypriano, Luiz Caires, Ernesto Goulart, Dirce Carraro, Isabela Werneck, Carla Rosenberg, Mayana Zatz, Ana Krepischi. Epigenetic mechanisms in liver tumors: Gene expression analysis of epigenetic machinery in hepatoblastomas [abstract]. In: Proceedings of the AACR International Conference held in cooperation with the Latin American Cooperative Oncology Group (LACOG) on Translational Cancer Medicine; May 4-6, 2017; São Paulo, Brazil. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(1_Suppl):Abstract nr A10.
Abstract A25: Intragroup genomic, transcriptional, and epigenomic variability is higher in sporadic than in BRCA1-associated hereditary triple-negative breast tumors
Authors: Nakamura Kivvi Duarte de Mello , Ramalho Rodrigo Fernandes , Brianese Rafael Canfield , Krepischi Ana , Barros Bruna D. F. , Carraro Dirce Maria 
Published: May 2019

Abstract
Intra-tumor genetic heterogeneity is a possible cause of therapy resistance and has consequences in the disease progression and patient survival. Triple-negative breast cancer (TNBC) is associated with rapid growth, early metastasis, and worse prognosis than other breast cancer subtypes. Close association has been identified between TNBC and germline loss-of-function mutations in BRCA1 gene which trigger the tumorigenic process in hereditary TNBC. Although at genomic level, TNBC was previously characterized as more heterogeneous than other breast cancer subtypes, the difference in genomic, epigenomic, and transcriptional variability between two groups of TNBC—sporadic (BRCA1-proficent) and hereditary (BRCA1-associated)—remains unclear. Here, we investigated both sporadic and hereditary TNBC, by using data from copy-number alterations (CNAs) array, methylation array, and RNA-Seq. A total of 80 samples, 40 TNBC BRCA1-proficient (classified as sporadic), 18 TNBC with BRCA1 germline mutation (classifed as hereditary) and 22 normal breast tissues used as controls, were used. Data from methylation and CNA arrays were analyzed with the RnBeads and snapCGH softwares, respectively. RNA-seq data was analyzed mainly with the STAR aligner, Bioconductor-GenomicFeatures and DESeq2 softwares. To assess the intragroup genomic, transcriptional, and epigenomic variability we used the inter-quantile difference between patients of the same group. Our results clearly demonstrated that the TNBC BRCA1-proficient group has a higher intragroup heterogeneity than the BRCA1-mutated group regarding (i) global pattern of gene expression, (ii) number and intensity of CNAs (copy number alterations), and (iii) level of promoter methylation. Moreover, normal breast samples showed the lowest intra-group heterogeneity for the last two features. Then, our results show higher genomic, transcriptional, and epigenomic variability in sporadic than hereditary TNBC and motivates further molecular subtyping of the sporadic TNBCs, which may reveal new targets to improve TNBC treatment.
Citation Format: Kivvi Duarte de Mello Nakamura, Rodrigo Fernandes Ramalho, Rafael Canfield Brianese, Ana Krepischi, Bruna D. F. Barros, Dirce Maria Carraro. Intragroup genomic, transcriptional, and epigenomic variability is higher in sporadic than in BRCA1-associated hereditary triple-negative breast tumors [abstract]. In: Proceedings of the AACR International Conference held in cooperation with the Latin American Cooperative Oncology Group (LACOG) on Translational Cancer Medicine; May 4-6, 2017; São Paulo, Brazil. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(1_Suppl):Abstract nr A25.