532 results match your criteria Cancer Inform[Journal]


Identification of Altered Genes in Gallbladder Cancer as Potential Driver Mutations for Diagnostic and Prognostic Purposes: A Computational Approach.

Cancer Inform 2020 25;19:1176935120922154. Epub 2020 May 25.

Laboratory of Chemical Carcinogenesis and Pharmacogenetics (CQF), Department of Basic and Clinical Oncology (DBOC), Faculty of Medicine, University of Chile, Santiago, Chile.

Prognostic markers for cancer can assist in the evaluation of survival probability of patients and help clinicians to assess the available treatment modalities. Gallbladder cancer (GBC) is a rare tumor that causes 165 087 deaths in the world annually. It is the most common cancer of the biliary tract and has a particularly high incidence in Chile, Japan, and northern India. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935120922154DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7249562PMC

Preprocessing Breast Cancer Data to Improve the Data Quality, Diagnosis Procedure, and Medical Care Services.

Cancer Inform 2020 27;19:1176935120917955. Epub 2020 May 27.

Department of Computer Science and Engineering and IT, Shiraz University, Shiraz, Iran.

In recent years, due to an increase in the incidence of different cancers, various data sources are available in this field. Consequently, many researchers have become interested in the discovery of useful knowledge from available data to assist faster decision-making by doctors and reduce the negative consequences of such diseases. Data mining includes a set of useful techniques in the discovery of knowledge from the data: detecting hidden patterns and finding unknown relations. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935120917955DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7262833PMC

RNA-Seq Reproducibility Assessment of the Sequencing Quality Control Project.

Authors:
Lianbo Yu

Cancer Inform 2020 20;19:1176935120922498. Epub 2020 May 20.

Center for Biostatistics, Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA.

With the widespread RNA-seq applications of different sequencing platforms in biomedical science research in recent years, a systematic evaluation of RNA-seq data quality is crucial and timely. The Sequencing Quality Control (SEQC) project is a large-scale community effort for assessing the performance of RNA-seq technology across different platforms and multiple laboratories, where reference RNA samples with multiple replicates were sequenced at 12 laboratories using 3 sequencing platforms. Different from the SEQC project, we performed an independent and comprehensive analysis of RNA-seq data of the SEQC project to assess sequencing reproducibility across platforms, sequencing sites, sample replicates, and FlowCells, respectively. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935120922498DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7241209PMC

Computational Analysis of , and Mutations in Low-Grade Gliomas Including Oligodendrogliomas and Astrocytomas.

Cancer Inform 2020 15;19:1176935120915839. Epub 2020 Apr 15.

Department of Neurosurgery, Hospital of Specialties, CHU Ibn Sina, Rabat, Medical and Pharmacy School, Mohammed V University Rabat, Morocco.

Introduction: The emergence of new omics approaches, such as genomic algorithms to identify tumor mutations and molecular modeling tools to predict the three-dimensional structure of proteins, has facilitated the understanding of the dynamic mechanisms involved in the pathogenesis of low-grade gliomas including oligodendrogliomas and astrocytomas.

Methods: In this study, we targeted known mutations involved in low-grade gliomas, starting with the sequencing of genomic regions encompassing exon 4 of isocitrate dehydrogenase 1 () and isocitrate dehydrogenase 2 () and the four exons (5-6 and 7-8) of from 32 samples, followed by computational analysis to study the impact of these mutations on the structure and function of 3 proteins , and .

Results: We obtain a mutation that has an effect on the catalytic site of the protein as R132H and on the catalytic site of the protein as R172M. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935120915839DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7160765PMC

A miRNA- and mRNA-seq-Based Feature Selection Approach for Kidney Cancer Biomakers.

Authors:
Shinuk Kim

Cancer Inform 2020 28;19:1176935120908301. Epub 2020 Feb 28.

Department of Civil Engineering, Sangmyung University, Cheonan, Republic of Korea.

Microarray data sets have been used for predicting cancer biomarkers. Yet, replication of the prediction has not been fully satisfied. Recently, new data sets called deep sequencing data sets have been generated, with an advantage of less noise in computational analysis. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935120908301DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7050029PMC
February 2020

A Pan-Cancer and Polygenic Bayesian Hierarchical Model for the Effect of Somatic Mutations on Survival.

Cancer Inform 2020 17;19:1176935120907399. Epub 2020 Feb 17.

Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA.

We built a novel Bayesian hierarchical survival model based on the somatic mutation profile of patients across 50 genes and 27 cancer types. The pan-cancer quality allows for the model to "borrow" information across cancer types, motivated by the assumption that similar mutation profiles may have similar (but not necessarily identical) effects on survival across different tissues of origin or tumor types. The effect of a mutation at each gene was allowed to vary by cancer type, whereas the mean effect of each gene was shared across cancers. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935120907399DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7029540PMC
February 2020

Metabolic Pathways Enhancement Confers Poor Prognosis in p53 Exon Mutant Hepatocellular Carcinoma.

Cancer Inform 2020 7;19:1176935119899913. Epub 2020 Jan 7.

Department of Food Science and Biotechnology, National Chung Hsing University, Taichung.

RNA-Sequencing (RNA-Seq), the most commonly used sequencing application tool, is not only a method for measuring gene expression but also an excellent media to detect important structural variants such as single nucleotide variants (SNVs), insertion/deletion (Indels), or fusion transcripts. The Cancer Genome Atlas (TCGA) contains genomic data from a variety of cancer types and also provides the raw data generated by TCGA consortium. p53 is among the top 10 somatic mutations associated with hepatocellular carcinoma (HCC). Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119899913DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6947881PMC
January 2020

CNVScope: Visually Exploring Copy Number Aberrations in Cancer Genomes.

Cancer Inform 2019 2;18:1176935119890290. Epub 2019 Dec 2.

Genetics Branch, National Cancer Institute, Center for Cancer Research, National Institutes of Health, Bethesda, MD, USA.

Motivation: DNA copy number (CN) data are a fast-growing source of information used in basic and translational cancer research. Most CN segmentation data are presented without regard to the relationship between chromosomal regions. We offer both a toolkit to help scientists without programming experience visually explore the CN interactome and a package that constructs CN interactomes from publicly available data sets. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119890290DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6887803PMC
December 2019

Identification of Targetable Pathways in Oral Cancer Patients via Random Forest and Chemical Informatics.

Authors:
John Schomberg

Cancer Inform 2019 28;18:1176935119889911. Epub 2019 Nov 28.

CHOC Children's, Orange, CA, USA.

Treatment of head and neck cancer has been slow to change with epidermal growth factor receptor (EGFR) inhibitors, PD1 inhibitors, and taxane-/plant-alkaloid-derived chemotherapies being the only therapies approved by the U.S. Food and Drug Administration (FDA) in the last 10 years for the treatment of head and neck cancers. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119889911DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6883365PMC
November 2019

Optimizing Retrieval of Biospecimens Using the Curated Cancer Clinical Outcomes Database (C3OD).

Cancer Inform 2019 18;18:1176935119886831. Epub 2019 Nov 18.

Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, USA.

To fully support their role in translational and personalized medicine, biorepositories and biobanks must continue to advance the annotation of their biospecimens with robust clinical and laboratory data. Translational research and personalized medicine require well-documented and up-to-date information, but the infrastructure used to support biorepositories and biobanks can easily be out of sync with the host institution. To assist researchers and provide them with accurate pathological, epidemiological, and bio-molecular data, the Biospecimen Repository Core Facility (BRCF) at the University of Kansas Medical Center (KUMC) merges data from medical records, the tumor registry, and pathology reports using the Curated Cancer Clinical Outcomes Database (C3OD). Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119886831DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6864036PMC
November 2019

Drug Tolerant Cells: An Emerging Target With Unique Transcriptomic Features.

Cancer Inform 2019 10;18:1176935119881633. Epub 2019 Oct 10.

Department of Biological Sciences, Birla Institute of Technology and Science (BITS), Pilani, Pilani, India.

Long-term outcome of cancer therapy is often severely perturbed by the acquisition of drug resistance. Recent evidence point toward the survival of a subpopulation of tumor cells under acute drug stress that over time can re-populate the tumor. These transiently existing, weakly proliferative, drug-tolerant cells facilitate tumor cell survival until more stable resistance mechanisms are acquired. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119881633DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6787876PMC
October 2019
1 Read

Preliminary Analysis of Within-Sample Co-methylation Patterns in Normal and Cancerous Breast Samples.

Cancer Inform 2019 5;18:1176935119880516. Epub 2019 Oct 5.

Department of Mathematics, Texas State University, San Marcos, TX, USA.

DNA methylation plays a significant role in regulating the expression of certain genes in both cancerous and normal breast tissues. It is therefore important to study within-sample co-methylation, ie, methylation patterns between consecutive sites in a chromosome. In this article, we develop 2 new methods to compare co-methylation patterns between normal and cancerous breast samples. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119880516DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6778999PMC
October 2019
1 Read

In Silico Genetics Revealing 5 Mutations in Gene Associated With Acute Myeloid Leukemia.

Cancer Inform 2019 19;18:1176935119870817. Epub 2019 Aug 19.

Department of Biotechnology, Africa City of Technology, Khartoum North, Sudan.

Background: Acute myeloid leukemia (AML) is an extremely heterogeneous malignant disorder; AML has been reported as one of the main causes of death in children. The objective of this work was to classify the most deleterious mutation in CCAAT/enhancer-binding protein-alpha () and to predict their influence on the functional, structural, and expression levels by various Bioinformatics analysis tools.

Methods: The single nucleotide polymorphisms (SNPs) were claimed from the National Center for Biotechnology Information (NCBI) database and then submitted into various functional analysis tools, which were done to predict the influence of each SNP, followed by structural analysis of modeled protein followed by predicting the mutation effect on energy stability; the most damaging mutations were chosen for additional investigation by Mutation3D, Project hope, ConSurf, BioEdit, and UCSF Chimera tools. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119870817DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6777061PMC
August 2019
1 Read

Separating the Local and Malignant Dimensions of Cancer Adaptation.

Cancer Inform 2019 5;18:1176935119872954. Epub 2019 Sep 5.

Université Claude Bernard Lyon 1 (Univ Lyon), INSERM 1052, CNRS 5286, Centre Léon Bérard Cancer Research Center of Lyon, Lyon, France.

The repeatability observed across cancers arising in the same tissue can help understand the evolutionary process of tumour initiation. We recently developed a framework to quantify the local malignant adaptation of genetic clones in tissue-specific environments. In this Commentary, we argue that such a 1-dimensional model can be improved by separating its 2 components to obtain a dual scale: local adaptation, dictating proliferation rates in the local environment, and malignant adaptation, influencing the likelihood that a clone becomes cancerous and invasive. Read More

View Article

Download full-text PDF

Source
http://journals.sagepub.com/doi/10.1177/1176935119872954
Publisher Site
http://dx.doi.org/10.1177/1176935119872954DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6728660PMC
September 2019
1 Read

Hierarchical Classification of Cancers of Unknown Primary Using Multi-Omics Data.

Cancer Inform 2019 30;18:1176935119872163. Epub 2019 Aug 30.

Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark.

A cancer of unknown primary (CUP) is a metastatic cancer for which standard diagnostic tests fail to locate the primary cancer. As standard treatments are based on the cancer type, such cases are hard to treat and have very poor prognosis. Using molecular data from the metastatic cancer to predict the primary site can make treatment choice easier and enable targeted therapy. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119872163DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6719477PMC

Hemimethylation Patterns in Breast Cancer Cell Lines.

Cancer Inform 2019 29;18:1176935119872959. Epub 2019 Aug 29.

Global Engineering Systems, Cypress Semiconductor, Austin, TX, USA.

DNA methylation is an epigenetic event that involves adding a methyl group to the cytosine (C) site, especially the one that pairs with a guanine (G) site (ie, CG or CpG site), in a human genome. This event plays an important role in both cancerous and normal cell development. Previous studies often assume symmetric methylation on both DNA strands. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119872959DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6716185PMC

Multiple Omics Data Integration to Identify Long Noncoding RNA Responsible for Breast Cancer-Related Mortality.

Cancer Inform 2019 24;18:1176935119871933. Epub 2019 Aug 24.

Department of Statistics, Texas A&M University, College Station, TX, USA.

Long non-coding RNAs (lncRNAs) are a large and diverse class of transcribed RNAs, which have been shown to play a significant role in developing cancer. In this study, we apply integrative modeling framework to integrate the DNA copy number variation (CNV), lncRNA expression, and downstream target protein expression to predict patient survival in breast cancer. We develop a 3-stage model combining a mechanical model (lncRNA regressed on CNV and target proteins regressed on lncRNA) and a clinical model (survival regressed on estimated effects from the mechanical models). Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119871933DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6710679PMC

Dedicator of Cytokinesis 4: A Potential Prognostic and Predictive Biomarker Within the Metastatic Spread of Breast Cancer to Bone.

Cancer Inform 2019 26;18:1176935119866842. Epub 2019 Aug 26.

Department of Oncology & Metabolism, Academic Unit of Clinical Oncology, The University of Sheffield, Sheffield, UK.

Metastasis to bone occurs in over 70% of patients with advanced breast cancer resulting in skeletal complications, including pathological fractures, hypercalcaemia, and bone pain. Significant advances have been made in the treatment of bone metastases, including the use of antiresorptive drugs, such as bisphosphonates, as well as antibody-based therapies targeting key signalling intermediates within the process of cancer-mediated bone destruction. Despite these advances, treatment is not without side effects, including osteonecrosis of the jaw therefore biomarkers predictive of which patients are at high risk of developing bone spread are required to enable personalized medicine initiatives within this important disease area. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119866842DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6712742PMC
August 2019
1 Read

On the Bias of Precision Estimation Under Separate Sampling.

Cancer Inform 2019 15;18:1176935119860822. Epub 2019 Jul 15.

Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA.

Observational case-control studies for biomarker discovery in cancer studies often collect data that are sampled separately from the case and control populations. We present an analysis of the bias in the estimation of the precision of classifiers designed on separately sampled data. The analysis consists of both theoretical and numerical results, which show that classifier precision estimates can display strong bias under separating sampling, with the bias magnitude depending on the difference between the true case prevalence in the population and the sample prevalence in the data. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119860822DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6636226PMC
July 2019
1 Read

Rewiring of the Transcription Factor Network in Acute Myeloid Leukemia.

Cancer Inform 2019 25;18:1176935119859863. Epub 2019 Jun 25.

Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.

Acute myeloid leukemia (AML) is a highly heterogeneous cancer associated with different patterns of gene expression determined by the nature of their DNA mutations. These mutations mostly act to deregulate gene expression by various mechanisms at the level of the nucleus. By performing genome-wide epigenetic profiling of cis-regulatory elements, we found that AML encompasses different mutation-specific subclasses associated with the rewiring of the gene regulatory networks that drive differentiation into different directions away from normal myeloid development. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119859863DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6595639PMC
June 2019
2 Reads

Automated Classification of Malignant and Benign Breast Cancer Lesions Using Neural Networks on Digitized Mammograms.

Cancer Inform 2019 16;18:1176935119857570. Epub 2019 Jun 16.

Faculty of Information and Computers, Assiut University, Assiut, Egypt.

We propose a novel neural network approach for the classification of abnormal mammographic images into benign or malignant based on their texture representations. The proposed framework has the capability of mapping high dimensional feature space into a lower-dimension, in a supervised way. The main contribution of the proposed classifier is to introduce a new neuron structure for map representation and adopt a supervised learning technique for feature classification. Read More

View Article

Download full-text PDF

Source
http://journals.sagepub.com/doi/10.1177/1176935119857570
Publisher Site
http://dx.doi.org/10.1177/1176935119857570DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6580711PMC
June 2019
4 Reads

Leveraging Image-Derived Phenotypic Measurements for Drug-Target Interaction Predictions.

Cancer Inform 2019 12;18:1176935119856595. Epub 2019 Jun 12.

Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA.

In recent years, protein kinases have become some of the most significant drug targets in cancer patients. Kinases are known to regulate the activity of many human proteins, and consequently their inhibition has been used to control cancer proliferation. A significant challenge in drug discovery is the rapid and efficient identification of new small molecules. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119856595DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6563400PMC
June 2019
3 Reads

A Holistic Evaluation of Articles on PD-1 and PD-L1 Published Between 1975 and 2017: A Bibliometric Analysis.

Cancer Inform 2019 4;18:1176935119852620. Epub 2019 Jun 4.

Department of Dermatology, Hitit University Erol Olçok Education and Research Hospital, Çorum, Turkey.

Background: Bibliometrics has been used for assessing and predicting trends in macro-health science and medical systems, especially in the field of cancer. Bibliometric and scientometric studies in the field of programmed cell death 1/programmed cell death 1 ligand 1 (PD-1/PD-L1) may guide further research in this field.

Objective: To perform bibliometric analysis of articles on PD-1 and PD-L1 published in the academic literature during 1975 to 2017. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119852620DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6552349PMC

Machine Learning-Enhanced T Cell Neoepitope Discovery for Immunotherapy Design.

Cancer Inform 2019 23;18:1176935119852081. Epub 2019 May 23.

Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal.

Immune responses mediated by T cells are aimed at specific peptides, designated T cell epitopes, that are recognized when bound to human leukocyte antigen (HLA) molecules. The HLA genes are remarkably polymorphic in the human population allowing a broad and fine-tuned capacity to bind a wide array of peptide sequences. Polymorphisms might generate neoepitopes by impacting the HLA-peptide interaction and potentially alter the level and type of generated T cell responses. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119852081DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6535895PMC
May 2019
5 Reads

Pathway Interactions Based on Drug-Induced Datasets.

Authors:
Shinuk Kim

Cancer Inform 2019 23;18:1176935119851518. Epub 2019 May 23.

Department of Civil Engineering, Sangmyung University, Cheonan, Republic of Korea.

In this study, we identified enrichment pathway connections from MCF7 breast cancer epithelial cells that were treated with 87 drugs. We extracted drug-treated samples, where the sample size was greater than or equal to 5. The drugs included 17-allylamino-geldanamycin, LY294002, trichostatin A, valproic acid, sirolimus, and wortmannin, which had sample sizes of 11, 8, 7, 7, 7, and 5, respectively. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119851518DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6535899PMC
May 2019
11 Reads

A Molecular and Morphological Deep-Dive Into Metaplastic Breast Cancers.

Cancer Inform 2019 17;18:1176935119850155. Epub 2019 May 17.

UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia.

Metaplastic breast cancers (MBC) are relatively rare but account for significant global breast cancer mortality. Typically presenting without oestrogen and progesterone receptors or HER2 expression, these triple negative breast cancers are the archetypal 'stem cell-like' tumours that show a variety of metaplastic elements, including squamous, spindle, and chondroid. Given the vast heterogeneity in MBC by definition, large cohort studies are needed to draw conclusions. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119850155DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6535896PMC
May 2019
8 Reads

Deregulation of a Network of mRNA and miRNA Genes Reveals That CK2 and MEK Inhibitors May Synergize to Induce Apoptosis KRAS-Active NSCLC.

Cancer Inform 2019 9;18:1176935119843507. Epub 2019 May 9.

Department of Pharmaceutical Sciences, Markey Cancer Center, University of Kentucky, Lexington, KY, USA.

KRAS-activation mutations occur in 25% to 40% of lung adenocarcinomas and are a known mechanism of epidermal growth factor receptor inhibitor (EGFRI) resistance. There are currently no targeted therapies approved specifically for the treatment of KRAS-active non-small cell lung cancers (NSCLC). Attempts to target mutant KRAS have failed in clinical studies leaving no targeted therapy option for these patients. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119843507DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6509975PMC
May 2019
2 Reads

Development and Validation of a Nomogram Prognostic Model for Patients With Advanced Non-Small-Cell Lung Cancer.

Cancer Inform 2019 5;18:1176935119837547. Epub 2019 Apr 5.

Quantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA.

Importance: Nomogram prognostic models can facilitate cancer patient treatment plans and patient enrollment in clinical trials.

Objective: The primary objective is to provide an updated and accurate prognostic model for predicting the survival of advanced non-small-cell lung cancer (NSCLC) patients, and the secondary objective is to validate a published nomogram prognostic model for NSCLC using an independent patient cohort.

Design: 1817 patients with advanced NSCLC from the control arms of 4 Phase III randomized clinical trials were included in this study. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119837547DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6452590PMC
April 2019
3 Reads

Distinct DNA Sequence Preference for Histone Occupancy in Primary and Transformed Cells.

Cancer Inform 2019 19;18:1176935119843835. Epub 2019 Apr 19.

HoMeCell Lab, Discipline of Biological Engineering, Indian Institute of Technology Gandhinagar, Gandhinagar, India.

Genome-wide occupancy of several histone modifications in various cell types has been studied using chromatin immunoprecipitation (ChIP) sequencing. Histone occupancy depends on DNA sequence features like inter-strand symmetry of base composition and periodic occurrence of TT/AT. However, whether DNA sequence motifs act as an additional effector of histone occupancy is not known. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119843835DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6475841PMC

Anticancer Activity of Methanol Extract of Leaves and Fruits Against Proliferation, Apoptosis, and Necrosis in Huh7it Cells.

Cancer Inform 2019 19;18:1176935119842576. Epub 2019 Apr 19.

Department of Biology, Faculty of Science and Technology, Universitas Airlangga, Surabaya, Indonesia.

The polyphenol plant extracts have previously been demonstrated to act as chemopreventive and anticancer agents. is a rich source of polyphenols, yet its antioxidant and anticancer activities remain poorly characterized. This study aimed to determine the anticancer activity of leaf and fruit extracts by investigating their impact on proliferation, apoptosis, and Huh7it cell necrosis. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119842576DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6475848PMC
April 2019
2 Reads

Interchromosomal Translocations as a Means to Map Chromosome Territories in Breast Cancer.

Cancer Inform 2019 16;18:1176935119842573. Epub 2019 Apr 16.

Department of Mathematics, Vanderbilt University, Nashville, TN, USA.

The genome-wide identification of mutated genes is an important advance in our understanding of tumor biology, but several fundamental questions remain open. How do these genes act together to promote cancer development and, a related question, how are they spatially arranged in the nucleus to allow coordinated expression? We examined the nuclear topography of mutated genes in breast cancer and their relation to chromosome territories (CTs). We performed a literature review and analyzed 1 type of mutation, interchromosomal translocations, in 1546 primary breast cancers to infer the spatial arrangement of chromosomes. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119842573DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6469281PMC
April 2019
2 Reads

High-Throughput Mutation Data Now Complement Transcriptomic Profiling: Advances in Molecular Pathway Activation Analysis Approach in Cancer Biology.

Cancer Inform 2019 25;18:1176935119838844. Epub 2019 Mar 25.

Institute for Personalized Medicine, I.M. Sechenov First Moscow State Medical University, Moscow, Russia.

We recently reviewed the current progress in the use of high-throughput molecular "omics" data for the quantitative analysis of molecular pathway activation. These quantitative metrics may be used in many ways, and we focused on their application as tumor biomarkers. Here, we provide an update of the most recent conceptual findings related to pathway analysis in tumor biology, which were not included in the previous review. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119838844DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6434430PMC
March 2019
2 Reads

Predicting Complete Remission of Acute Myeloid Leukemia: Machine Learning Applied to Gene Expression.

Cancer Inform 2019 15;18:1176935119835544. Epub 2019 Mar 15.

Center for Biomedical Informatics & Information Technology, National Cancer Institute, Rockville, MD, USA.

Machine learning (ML) is a useful tool for advancing our understanding of the patterns and significance of biomedical data. Given the growing trend on the application of ML techniques in precision medicine, here we present an ML technique which predicts the likelihood of complete remission (CR) in patients diagnosed with acute myeloid leukemia (AML). In this study, we explored the question of whether ML algorithms designed to analyze gene-expression patterns obtained through RNA sequencing (RNA-seq) can be used to accurately predict the likelihood of CR in pediatric AML patients who have received induction therapy. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119835544DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6423478PMC
March 2019
2 Reads

Predicting Outcomes in Patients With Diffuse Large B-Cell Lymphoma Treated With Standard of Care.

Cancer Inform 2019 15;18:1176935119835538. Epub 2019 Mar 15.

Millennium Pharmaceuticals, Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited, Cambridge, MA, USA.

In diffuse large B-cell lymphoma (DLBCL), predictive modeling may contribute to targeted drug development by enrichment of the study populations enrolled in clinical trials of DLBCL investigational drugs to include patients with lower likelihood of responding to standard of care. In clinical practice, predictive modeling has the potential to optimize therapy choices in DLBCL. The objectives of this study were to create a model for predicting health outcomes in patients with DLBCL treated with standard of care and determine informative predictors of health outcomes for patients with DLBCL. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119835538DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6421613PMC
March 2019
10 Reads

Visual Analytics of Genomic and Cancer Data: A Systematic Review.

Cancer Inform 2019 13;18:1176935119835546. Epub 2019 Mar 13.

The Tumour Bank, Children's Cancer Research Unit, Kids Research, The Children's Hospital at Westmead, Westmead, NSW, Australia.

Visual analytics and visualisation can leverage the human perceptual system to interpret and uncover hidden patterns in big data. The advent of next-generation sequencing technologies has allowed the rapid production of massive amounts of genomic data and created a corresponding need for new tools and methods for visualising and interpreting these data. Visualising genomic data requires not only simply plotting of data but should also offer a decision or a choice about what the message should be conveyed in the particular plot; which methodologies should be used to represent the results must provide an easy, clear, and accurate way to the clinicians, experts, or researchers to interact with the data. Read More

View Article

Download full-text PDF

Source
http://journals.sagepub.com/doi/10.1177/1176935119835546
Publisher Site
http://dx.doi.org/10.1177/1176935119835546DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6416684PMC
March 2019
50 Reads

Transcriptomics Signature from Next-Generation Sequencing Data Reveals New Transcriptomic Biomarkers Related to Prostate Cancer.

Cancer Inform 2019 13;18:1176935119835522. Epub 2019 Mar 13.

School of Computer Science, University of Windsor, Windsor, ON, Canada.

Prostate cancer is one of the most common types of cancer among Canadian men. Next-generation sequencing using RNA-Seq provides large amounts of data that may reveal novel and informative biomarkers. We introduce a method that uses machine learning techniques to identify transcripts that correlate with prostate cancer development and progression. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119835522DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6416685PMC
March 2019
1 Read

Clinically Relevant Biomarker Discovery in High-Risk Recurrent Neuroblastoma.

Cancer Inform 2019 11;18:1176935119832910. Epub 2019 Mar 11.

Department of Pediatrics, Division of Child and Adolescent Health, UNN - University Hospital of North-Norway, Tromsø, Norway.

Neuroblastoma is a pediatric cancer of the developing sympathetic nervous system. High-risk neuroblastoma patients typically undergo an initial remission in response to treatment, followed by recurrence of aggressive tumors that have become refractory to further treatment. The need for biomarkers that can select patients not responding well to therapy in an early phase is therefore needed. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119832910DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6413431PMC
March 2019
2 Reads

Correlation Patterns Between DNA Methylation and Gene Expression in The Cancer Genome Atlas.

Cancer Inform 2019 11;18:1176935119828776. Epub 2019 Feb 11.

Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA.

Background: DNA methylation is a form of epigenetic modification that has been shown to play a significant role in gene regulation. In cancer, DNA methylation plays an important role by regulating the expression of oncogenes. The role of DNA methylation in the onset and progression of various cancer types is now being elucidated as more large-scale data become available. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119828776DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6376553PMC
February 2019
2 Reads

MicroRNAs in Female Malignancies.

Cancer Inform 2019 13;18:1176935119828746. Epub 2019 Feb 13.

University of Aberdeen, School of Medicine and Dentistry, Aberdeen, UK.

MicroRNAs (miRNAs) are endogenous 22-nucleotide RNAs that can play a fundamental regulatory role in the gene expression of various organisms. Current research suggests that miRNAs can assume pivotal roles in carcinogenesis. In this article, through bioinformatics mining and computational analysis, we determine a single miRNA commonly involved in the development of breast, cervical, endometrial, ovarian, and vulvar cancer, whereas we underline the existence of 7 more miRNAs common in all examined malignancies with the exception of vulvar cancer. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935119828746DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6376555PMC
February 2019
1 Read

Optimization of Dose Schedules for Chemotherapy of Early Colon Cancer Determined by High-Performance Computer Simulations.

Cancer Inform 2019 10;18:1176935118822804. Epub 2019 Jan 10.

Department of Genetics and Cancer of New Jersey, Rutgers University, Piscataway, NJ, USA.

Cancer chemotherapy dose schedules are conventionally applied intermittently, with dose duration of the order of hours, intervals between doses of days or weeks, and cycles repeated for weeks. The large number of possible combinations of values of duration, interval, and lethality has been an impediment to empirically determine the optimal set of treatment conditions. The purpose of this project was to determine the set of parameters for duration, interval, and lethality that would be most effective for treating early colon cancer. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935118822804DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6330731PMC
January 2019
2 Reads

Machine Learning With K-Means Dimensional Reduction for Predicting Survival Outcomes in Patients With Breast Cancer.

Cancer Inform 2018 9;17:1176935118810215. Epub 2018 Nov 9.

Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Objective: Despite existing prognostic markers, breast cancer prognosis remains a difficult subject due to the complex relationships between many contributing factors and survival. This study seeks to integrate multiple clinicopathological and genomic factors with dimensional reduction across machine learning algorithms to compare survival predictions.

Methods: This is a secondary analysis of the data from a prospective cohort study of female patients with breast cancer enrolled in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC). Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935118810215DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6238199PMC
November 2018
21 Reads

Cross-cancer Prediction: A Novel Machine Learning Approach to Discover Molecular Targets for Development of Treatments for Multiple Cancers.

Cancer Inform 2018 22;17:1176935118805398. Epub 2018 Oct 22.

Department of Mathematics and Statistics, University of Maryland, Baltimore County, Baltimore, MD, USA.

Conventional cancer drug development has long been limited to organ- or tissue-specific cancer types. However, it has become increasingly known that specific genetic abnormalities are responsible for the carcinogenesis of multiple cancers. The recent US Food and Drug Administration (FDA) approval of the first multi-cancer drug, Keytruda, has demonstrated the feasibility of developing new drugs that target multiple cancers. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935118805398DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6198390PMC
October 2018
38 Reads

A Visually Interpretable, Dictionary-Based Approach to Imaging-Genomic Modeling, With Low-Grade Glioma as a Case Study.

Cancer Inform 2018 5;17:1176935118802796. Epub 2018 Oct 5.

Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA.

Radiomics is a rapidly growing field in which sophisticated imaging features are extracted from radiology images to predict clinical outcomes/responses, genetic alterations, and other outcomes relevant to a patient's prognosis or response to therapy. This approach can effectively capture intratumor phenotypic heterogeneity by interrogating the "larger" image field, which is not possible with traditional biopsy procedures that interrogate specific subregions alone. Most models in radiomics derive numerous imaging features (eg, texture, shape, size) from a radiology data set and then learn complex nonlinear hypotheses to solve a given prediction task. Read More

View Article

Download full-text PDF

Source
http://journals.sagepub.com/doi/10.1177/1176935118802796
Publisher Site
http://dx.doi.org/10.1177/1176935118802796DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6174641PMC
October 2018
6 Reads

Using Semantic Web Technologies to Enable Cancer Genomics Discovery at Petabyte Scale.

Cancer Inform 2018 28;17:1176935118774787. Epub 2018 Sep 28.

Seven Bridges Genomics Inc., Cambridge, MA, USA.

Increased efforts in cancer genomics research and bioinformatics are producing tremendous amounts of data. These data are diverse in origin, format, and content. As the amount of available sequencing data increase, technologies that make them discoverable and usable are critically needed. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935118774787DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6166304PMC
September 2018
8 Reads

Corrigendum.

Authors:

Cancer Inform 2018 17;17:1176935118803150. Epub 2018 Sep 17.

[This corrects the article DOI: 10.1177/1176935118786260.]. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935118803150DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6144489PMC
September 2018
2 Reads

An Introduction to the Mathematical Modeling in the Study of Cancer Systems Biology.

Cancer Inform 2018 12;17:1176935118799754. Epub 2018 Sep 12.

Division of Cardiac Surgery, Baystate Medical Center, Springfield, MA, USA.

Background: Frequently occurring in cancer are the aberrant alterations of regulatory onco-metabolites, various oncogenes/epigenetic stochasticity, and suppressor genes, as well as the deficient mismatch repair mechanism, chronic inflammation, or those deviations belonging to the other cancer characteristics. How these aberrations that evolve overtime determine the global phenotype of malignant tumors remains to be completely understood. Dynamic analysis may have potential to reveal the mechanism of carcinogenesis and can offer new therapeutic intervention. Read More

View Article

Download full-text PDF

Source
http://journals.sagepub.com/doi/10.1177/1176935118799754
Publisher Site
http://dx.doi.org/10.1177/1176935118799754DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6136108PMC
September 2018
18 Reads

Sequential Experimental Design for Optimal Structural Intervention in Gene Regulatory Networks Based on the Mean Objective Cost of Uncertainty.

Cancer Inform 2018 6;17:1176935118790247. Epub 2018 Aug 6.

Department of Electrical & Computer Engineering, Texas A&M University, College Station, TX, USA.

Scientists are attempting to use models of ever-increasing complexity, especially in medicine, where gene-based diseases such as cancer require better modeling of cell regulation. Complex models suffer from uncertainty and experiments are needed to reduce this uncertainty. Because experiments can be costly and time-consuming, it is desirable to determine experiments providing the most useful information. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935118790247DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6080085PMC
August 2018
6 Reads

Multiscale Tumor Modeling With Drug Pharmacokinetic and Pharmacodynamic Profile Using Stochastic Hybrid System.

Cancer Inform 2018 27;17:1176935118790262. Epub 2018 Jul 27.

Department of Electrical and Computer Engineering (ECE), Prairie View A&M University, Prairie View, TX, USA.

Effective cancer treatment strategy requires an understanding of cancer behavior and development across multiple temporal and spatial scales. This has resulted into a growing interest in developing multiscale mathematical models that can simulate cancer growth, development, and response to drug treatments. This study thus investigates multiscale tumor modeling that integrates drug pharmacokinetic and pharmacodynamic (PK/PD) information using stochastic hybrid system modeling framework. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935118790262DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6073835PMC
July 2018
31 Reads

Bayesian Classification of Proteomics Biomarkers from Selected Reaction Monitoring Data using an Approximate Bayesian Computation-Markov Chain Monte Carlo Approach.

Cancer Inform 2018 1;17:1176935118786927. Epub 2018 Aug 1.

Department of Electrical & Computer Engineering and Center for Bioinformatics and Genomic Systems Engineering, Texas A&M University, College Station, TX, USA.

Selected reaction monitoring (SRM) has become one of the main methods for low-mass-range-targeted proteomics by mass spectrometry (MS). However, in most SRM-MS biomarker validation studies, the sample size is very small, and in particular smaller than the number of proteins measured in the experiment. Moreover, the data can be noisy due to a low number of ions detected per peptide by the instrument. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935118786927DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6071182PMC
August 2018
2 Reads

A Supervised Learning Tool for Prostate Cancer Foci Detection and Aggressiveness Identification using Multiparametric magnetic resonance imaging/magnetic resonance spectroscopy imaging.

Cancer Inform 2018 10;17:1176935118786260. Epub 2018 Jul 10.

Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD, USA.

Prostate cancer is the most frequently diagnosed cancer in men in the United States. The current main methods for diagnosing prostate cancer include prostate-specific antigen test and transrectal biopsy. Prostate-specific antigen screening has been criticized for overdiagnosis and unnecessary treatment, and transrectal biopsy is an invasive procedure with low sensitivity for diagnosis. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1177/1176935118786260DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6043929PMC
July 2018
45 Reads