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https://www.readbyqxmd.com/read/27899404/tapping-big-data-to-help-little-patients
#1
(no author information available yet)
Through a large-scale tumor-sequencing effort for pediatric brain cancer, researchers hope to bring personalized care to young patients.
November 29, 2016: Cancer Discovery
https://www.readbyqxmd.com/read/27873078/advances-in-decoding-breast-cancer-brain-metastasis
#2
Chenyu Zhang, Dihua Yu
The past decade has witnessed impressive advances in cancer treatment ushered in by targeted and immunotherapies. However, with significantly prolonged survival, upon recurrence, more patients become inflicted by brain metastasis, which is mostly refractory to all currently available therapeutic regimens. Historically, brain metastasis is an understudied area in cancer research, partly due to the dearth of appropriate experimental models that closely simulate the special biological features of metastasis in the unique brain environment and to the sophistication of techniques required to perform in-depth studies of the extremely complex and challenging brain metastasis...
November 21, 2016: Cancer Metastasis Reviews
https://www.readbyqxmd.com/read/27855850/-epidemiological-investigation-of-colorectal-cancer-perspective-prospective-and-challenges-in-a-big-data-context
#3
EDITORIAL
J M García Torrecillas, M Ferrer Márquez, Á Reina Duarte, F Rubio-Gil
No abstract text is available yet for this article.
November 2016: Semergen
https://www.readbyqxmd.com/read/27819294/big-genomics-and-clinical-data-analytics-strategies-for-precision-cancer-prognosis
#4
Ghim Siong Ow, Vladimir A Kuznetsov
The field of personalized and precise medicine in the era of big data analytics is growing rapidly. Previously, we proposed our model of patient classification termed Prognostic Signature Vector Matching (PSVM) and identified a 37 variable signature comprising 36 let-7b associated prognostic significant mRNAs and the age risk factor that stratified large high-grade serous ovarian cancer patient cohorts into three survival-significant risk groups. Here, we investigated the predictive performance of PSVM via optimization of the prognostic variable weights, which represent the relative importance of one prognostic variable over the others...
November 7, 2016: Scientific Reports
https://www.readbyqxmd.com/read/27810834/cancer-subtype-discovery-based-on-integrative-model-of-multigenomic-data
#5
Shu-Guang Ge, Junfeng Xia, Wen Sha, Chun-Hou Zheng
One major goal of large-scale cancer omics study is to understand molecular mechanisms of cancer and find new biomedical targets. To deal with the high-dimensional multidimensional cancer omics data (DNA methylation, mRNA expression, etc.), which can be used to discover new insight on identifying cancer subtypes, clustering methods are usually used to find an effective low-dimensional subspace of the original data and then cluster cancer samples in the reduced subspace. However, due to data-type diversity and big data volume, few methods can integrate these data and map them into an effective low-dimensional subspace...
October 26, 2016: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/27810046/high-density-lipoprotein-cholesterol-and%C3%A2-cause-specific-mortality-in-individuals%C3%A2-without-previous-cardiovascular-conditions-the-canheart-study
#6
Dennis T Ko, David A Alter, Helen Guo, Maria Koh, Geoffrey Lau, Peter C Austin, Gillian L Booth, William Hogg, Cynthia A Jackevicius, Douglas S Lee, Harindra C Wijeysundera, John T Wilkins, Jack V Tu
BACKGROUND: The prognostic importance of high-density lipoprotein cholesterol (HDL-C) as a specific risk factor for cardiovascular (CV) disease has been challenged by recent clinical trials and genetic studies. OBJECTIVES: This study sought to reappraise the association of HDL-C level with CV and non-CV mortality using a "big data" approach. METHODS: An observational cohort study was conducted using the CANHEART (Cardiovascular Health in Ambulatory Care Research Team) dataset, which was created by linking together 17 different individual-level data sources...
November 8, 2016: Journal of the American College of Cardiology
https://www.readbyqxmd.com/read/27809451/gastric-cancer-and-family-history
#7
REVIEW
Yoon Jin Choi, Nayoung Kim
Gastric cancer is associated with high morbidity and mortality rates worldwide. Identifying individuals at high risk is important for surveillance and prevention of gastric cancer. Having first-degree relatives diagnosed with gastric cancer is a strong and consistent risk factor for gastric cancer, but the pathogenic mechanisms behind this familial aggregation are unclear. Against this background, we reviewed the risk factors for gastric cancer in those with a first-degree relative with gastric cancer, and the possible causes for familial clustering of gastric cancer including bacterial factors, inherited genetic susceptibility, environmental factors or a combination thereof...
November 2016: Korean Journal of Internal Medicine
https://www.readbyqxmd.com/read/27808589/challenges-for-drug-discovery-and-development-in-china
#8
Kam Lun Hon, Vivian W Y Lee
The drug development industry is restructuring worldwide in terms of the research and development process. As with pharmaceuticals in the west and worldwide, China faces major challenges for drug discovery and development. Areas covered. In this review, the authors discuss anti-cancer, anti-allergy, anti-infectious, and proprietary Chinese Medicines (pCM) for various chronic diseases (such as the allergic diseases: eczema, asthma and allergic rhinitis), which remain the contemporary therapeutic strategies that are being explored and developed...
November 3, 2016: Expert Opinion on Drug Discovery
https://www.readbyqxmd.com/read/27806357/virtues-and-weaknesses-of-dna-methylation-as-a-test-for-cervical-cancer-prevention
#9
Attila T Lorincz
Epigenetics is the study of heritable and non-heritable genetic coding that is additive to information contained within classical DNA base pair sequences. Differential methylation has a fundamental role in the development and outcome of malignancies, chronic and degenerative diseases and aging. DNA methylation can be measured accurately and easily via various molecular methods and has become a key technology for research and healthcare delivery, with immediate roles in the elucidation of disease natural history, diagnostics and drug discovery...
November 3, 2016: Acta Cytologica
https://www.readbyqxmd.com/read/27806312/systematic-approach-identifies-rhoa-as-a-potential-biomarker-therapeutic-target-for-asian-gastric-cancer
#10
Hae Ryung Chang, Seungyoon Nam, Jinhyuk Lee, Jin-Hee Kim, Hae Rim Jung, Hee Seo Park, Sungjin Park, Young Zoo Ahn, Iksoo Huh, Curt Balch, Ja-Lok Ku, Garth Powis, Taesung Park, Jin-Hyun Jeong, Yon Hui Kim
Gastric cancer (GC) is a highly heterogeneous disease, in dire need of specific, biomarker-driven cancer therapies. While the accumulation of cancer "Big Data" has propelled the search for novel molecular targets for GC, its specific subpathway and cellular functions vary from patient to patient. In particular, mutations in the small GTPase gene RHOA have been identified in recent genome-wide sequencing of GC tumors. Moreover, protein overexpression of RHOA was reported in Chinese populations, while RHOA mutations were found in Caucasian GC tumors...
October 28, 2016: Oncotarget
https://www.readbyqxmd.com/read/27803103/big-data-led-cancer-research-application-and-insights
#11
James A L Brown, Triona Ni Chonghaile, Kyle B Matchett, Niamh Lynam-Lennon, Patrick A Kiely
Insights distilled from integrating multiple big-data or "omic" datasets have revealed functional hierarchies of molecular networks driving tumorigenesis and modifiers of treatment response. Identifying these novel key regulatory and dysregulated elements is now informing personalized medicine. Crucially, although there are many advantages to this approach, there are several key considerations to address. Here, we examine how this big data-led approach is impacting many diverse areas of cancer research, through review of the key presentations given at the Irish Association for Cancer Research Meeting and importantly how the results may be applied to positively affect patient outcomes...
November 1, 2016: Cancer Research
https://www.readbyqxmd.com/read/27748866/proteins-associated-with-egfr-tkis-resistance-in-patients-with-non-small-cell-lung-cancer-revealed-by-mass-spectrometry
#12
Shaoyu Yang, Xueqin Chen, Yuelong Pan, Jiekai Yu, Xin Li, Shenglin Ma
The present study aimed to identify potential serum biomarkers for predicting the clinical outcomes of patients with advanced non-small cell lung cancer (NSCLC) treated with epidermal growth factor receptor tyrosine kinase inhibitors (EGFR‑TKIs). A total of 61 samples were collected and analyzed using the integrated approach of magnetic bead‑based weak cation exchange chromatography and matrix‑assisted laser desorption/ionization‑time of flight‑mass spectrometry. The Zhejiang University Protein Chip Data Analysis system was used to identify the protein spectra of patients that are resistant and sensitive to EGFR‑TKIs...
November 2016: Molecular Medicine Reports
https://www.readbyqxmd.com/read/27740960/-omics-approaches-in-breast-cancer-research-and-clinical-practice
#13
Priyakshi Kalita-de Croft, Fares Al-Ejeh, Amy E McCart Reed, Jodi M Saunus, Sunil R Lakhani
Our understanding of the natural history of breast cancer has evolved alongside technologies to study its genomic, transcriptomic, proteomic, and metabolomics landscapes. These technologies have helped decipher multiple molecular pathways dysregulated in breast cancer. First-generation 'omics analyses considered each of these dimensions individually, but it is becoming increasingly clear that more holistic, integrative approaches are required to fully understand complex biological systems. The 'omics represent an exciting era of discovery in breast cancer research, although important issues need to be addressed to realize the clinical utility of these data through precision cancer care...
November 2016: Advances in Anatomic Pathology
https://www.readbyqxmd.com/read/27738762/molecular-pathological-epidemiology-new-developing-frontiers-of-big-data-science-to-study-etiologies-and-pathogenesis
#14
Tsuyoshi Hamada, NaNa Keum, Reiko Nishihara, Shuji Ogino
Molecular pathological epidemiology (MPE) is an integrative field that utilizes molecular pathology to incorporate interpersonal heterogeneity of a disease process into epidemiology. In each individual, the development and progression of a disease are determined by a unique combination of exogenous and endogenous factors, resulting in different molecular and pathological subtypes of the disease. Based on "the unique disease principle," the primary aim of MPE is to uncover an interactive relationship between a specific environmental exposure and disease subtypes in determining disease incidence and mortality...
October 13, 2016: Journal of Gastroenterology
https://www.readbyqxmd.com/read/27730285/big-data-mining-powers-fungal-research-recent-advances-in-fission-yeast-systems-biology-approaches
#15
Zhe Wang
Biology research has entered into big data era. Systems biology approaches therefore become the powerful tools to obtain the whole landscape of how cell separate, grow, and resist the stresses. Fission yeast Schizosaccharomyces pombe is wonderful unicellular eukaryote model, especially studying its division and metabolism can facilitate to understanding the molecular mechanism of cancer and discovering anticancer agents. In this perspective, we discuss the recent advanced fission yeast systems biology tools, mainly focus on metabolomics profiling and metabolic modeling, protein-protein interactome and genetic interaction network, DNA sequencing and applications, and high-throughput phenotypic screening...
October 11, 2016: Current Genetics
https://www.readbyqxmd.com/read/27728850/effectiveness-of-hpv-vaccination-in-women-reaching-screening-age-in-italy
#16
F M Carozzi, C Ocello, E Burroni, H Faust, M Zappa, E Paci, A Iossa, P Bonanni, M Confortini, C Sani
BACKGROUND AND OBJECTIVES: A randomized trial was conducted in Tuscany, Italy, to evaluate the effectiveness of HPV vaccination for 25year old (yo) women who attend at the first time cervical cancer screening. The trial also evaluated immune response after vaccination, reductions of cytological abnormalities and the impact of vaccination on screening activity. STUDY DESIGN: During 2010-2011, all 25 yo women who were invited to the Florence cervical cancer screening programme were also asked to participate in the trial...
October 3, 2016: Journal of Clinical Virology: the Official Publication of the Pan American Society for Clinical Virology
https://www.readbyqxmd.com/read/27722147/advancing-cancer-prevention-and-behavior-theory-in-the-era-of-big-data
#17
Audie A Atienza, Katrina J Serrano, William T Riley, Richard P Moser, William M Klein
The era of "Big Data" presents opportunities to substantively address cancer prevention and control issues by improving health behaviors and refining theoretical models designed to understand and intervene in those behaviors. Yet, the terms "model" and "Big Data" have been used rather loosely, and clarification of these terms is required to advance the science in this area. The objectives of this paper are to discuss conceptual definitions of the terms "model" and "Big Data", as well as examine the promises and challenges of Big Data to advance cancer prevention and control research using behavioral theories...
September 2016: Journal of Cancer Prevention
https://www.readbyqxmd.com/read/27687329/comparison-among-dimensionality-reduction-techniques-based-on-random-projection-for-cancer-classification
#18
Haozhe Xie, Jie Li, Qiaosheng Zhang, Yadong Wang
Random Projection (RP) technique has been widely applied in many scenarios because it can reduce high-dimensional features into low-dimensional space within short time and meet the need of real-time analysis of massive data. There is an urgent need of dimensionality reduction with fast increase of big genomics data. However, the performance of RP is usually lower. We attempt to improve classification accuracy of RP through combining other reduction dimension methods such as Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Feature Selection (FS)...
September 21, 2016: Computational Biology and Chemistry
https://www.readbyqxmd.com/read/27685652/sparktext-biomedical-text-mining-on-big-data-framework
#19
Zhan Ye, Ahmad P Tafti, Karen Y He, Kai Wang, Max M He
BACKGROUND: Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment. RESULTS: In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database...
2016: PloS One
https://www.readbyqxmd.com/read/27644659/head-and-neck-cancer-in-saudi-arabia-a-systematic-review
#20
Turki Y Alhazzazi, Faisal T Alghamdi
BACKGROUND: Head and neck cancer (HNC) is the ninth most common cancer worldwide, and has a poor 5-year survival rate averaging 50%, which has not changed for decades. A high prevalence of HNC has been reported in the southwestern region of Saudi Arabia, as compared to other areas of the country. However, data in regards to HNC are scattered and not well documented. Thus, the aim of this systematic review was to gather all available and updated important information regarding HNC in Saudi Arabia, and highlight the gaps of knowledge in our country with regard to this disease...
2016: Asian Pacific Journal of Cancer Prevention: APJCP
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