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https://www.readbyqxmd.com/read/29340286/cancer-imaging-phenomics-toolkit-quantitative-imaging-analytics-for-precision-diagnostics-and-predictive-modeling-of-clinical-outcome
#1
Christos Davatzikos, Saima Rathore, Spyridon Bakas, Sarthak Pati, Mark Bergman, Ratheesh Kalarot, Patmaa Sridharan, Aimilia Gastounioti, Nariman Jahani, Eric Cohen, Hamed Akbari, Birkan Tunc, Jimit Doshi, Drew Parker, Michael Hsieh, Aristeidis Sotiras, Hongming Li, Yangming Ou, Robert K Doot, Michel Bilello, Yong Fan, Russell T Shinohara, Paul Yushkevich, Ragini Verma, Despina Kontos
The growth of multiparametric imaging protocols has paved the way for quantitative imaging phenotypes that predict treatment response and clinical outcome, reflect underlying cancer molecular characteristics and spatiotemporal heterogeneity, and can guide personalized treatment planning. This growth has underlined the need for efficient quantitative analytics to derive high-dimensional imaging signatures of diagnostic and predictive value in this emerging era of integrated precision diagnostics. This paper presents cancer imaging phenomics toolkit (CaPTk), a new and dynamically growing software platform for analysis of radiographic images of cancer, currently focusing on brain, breast, and lung cancer...
January 2018: Journal of Medical Imaging
https://www.readbyqxmd.com/read/29335532/intelligent-image-based-in-situ-single-cell-isolation
#2
Csilla Brasko, Kevin Smith, Csaba Molnar, Nora Farago, Lili Hegedus, Arpad Balind, Tamas Balassa, Abel Szkalisity, Farkas Sukosd, Katalin Kocsis, Balazs Balint, Lassi Paavolainen, Marton Z Enyedi, Istvan Nagy, Laszlo G Puskas, Lajos Haracska, Gabor Tamas, Peter Horvath
Quantifying heterogeneities within cell populations is important for many fields including cancer research and neurobiology; however, techniques to isolate individual cells are limited. Here, we describe a high-throughput, non-disruptive, and cost-effective isolation method that is capable of capturing individually targeted cells using widely available techniques. Using high-resolution microscopy, laser microcapture microscopy, image analysis, and machine learning, our technology enables scalable molecular genetic analysis of single cells, targetable by morphology or location within the sample...
January 15, 2018: Nature Communications
https://www.readbyqxmd.com/read/29329660/cochlea-ct-radiomics-predicts-chemoradiotherapy-induced-sensorineural-hearing-loss-in-head-and-neck-cancer-patients-a-machine-learning-and-multi-variable-modelling-study
#3
Hamid Abdollahi, Shayan Mostafaei, Susan Cheraghi, Isaac Shiri, Seied Rabi Mahdavi, Anoshirvan Kazemnejad
OBJECTIVES: Immediately or after head-and-neck (H&N) cancer chemoradiotherapy (CRT), patients may undergone significant sensorineural hearing loss (SNHL) which could affect their quality of life. Radiomic feature analysis is proposed to predict SNHL induced by CRT. MATERIAL AND METHODS: 490 image features of 94 cochlea from 47 patients treated with three dimensional conformal RT (3DCRT) for different H&N cancers were extracted from CT images. Different machine learning (ML) algorithms and also least absolute shrinkage and selection operator (LASSO) penalized logistic regression were implemented on radiomic features for feature selection, classification and prediction...
January 9, 2018: Physica Medica: PM
https://www.readbyqxmd.com/read/29327813/computational-tools-for-the-identification-and-interpretation-of-sequence-motifs-in-immunopeptidomes
#4
REVIEW
Bruno Alvarez, Carolina Barra, Morten Nielsen, Massimo Andreatta
Recent advances in proteomics and mass-spectrometry have widely expanded the detectable peptide repertoire presented by major histocompatibility complex (MHC) molecules on the cell surface, collectively known as the immunopeptidome. Finely characterizing the immunopeptidome brings about important basic insights into the mechanisms of antigen presentation, but can also reveal promising targets for vaccine development and cancer immunotherapy. In this report, we describe a number of practical and efficient approaches to analyze immunopeptidomics data, discussing the identification of meaningful sequence motifs in various scenarios and considering current limitations...
January 12, 2018: Proteomics
https://www.readbyqxmd.com/read/29322935/classifying-cancer-genome-aberrations-by-their-mutually-exclusive-effects-on-transcription
#5
Jonathan B Dayton, Stephen R Piccolo
BACKGROUND: Malignant tumors are typically caused by a conglomeration of genomic aberrations-including point mutations, small insertions, small deletions, and large copy-number variations. In some cases, specific chemotherapies and targeted drug treatments are effective against tumors that harbor certain genomic aberrations. However, predictive aberrations (biomarkers) have not been identified for many tumor types and treatments. One way to address this problem is to examine the downstream, transcriptional effects of genomic aberrations and to identify characteristic patterns...
December 21, 2017: BMC Medical Genomics
https://www.readbyqxmd.com/read/29315279/a-regression-model-for-predicting-shape-deformation-after-breast-conserving-surgery
#6
Hooshiar Zolfagharnasab, Sílvia Bessa, Sara P Oliveira, Pedro Faria, João F Teixeira, Jaime S Cardoso, Hélder P Oliveira
Breast cancer treatments can have a negative impact on breast aesthetics, in case when surgery is intended to intersect tumor. For many years mastectomy was the only surgical option, but more recently breast conserving surgery (BCS) has been promoted as a liable alternative to treat cancer while preserving most part of the breast. However, there is still a significant number of BCS intervened patients who are unpleasant with the result of the treatment, which leads to self-image issues and emotional overloads...
January 9, 2018: Sensors
https://www.readbyqxmd.com/read/29312619/systematic-assessment-of-cervical-cancer-initiation-and-progression-uncovers-genetic-panels-for-deep-learning-based-early-diagnosis-and-proposes-novel-diagnostic-and-prognostic-biomarkers
#7
Nguyen Phuoc Long, Kyung Hee Jung, Sang Jun Yoon, Nguyen Hoang Anh, Tran Diem Nghi, Yun Pyo Kang, Hong Hua Yan, Jung Eun Min, Soon-Sun Hong, Sung Won Kwon
Although many outstanding achievements in the management of cervical cancer (CxCa) have obtained, it still imposes a major burden which has prompted scientists to discover and validate new CxCa biomarkers to improve the diagnostic and prognostic assessment of CxCa. In this study, eight different gene expression data sets containing 202 cancer, 115 cervical intraepithelial neoplasia (CIN), and 105 normal samples were utilized for an integrative systems biology assessment in a multi-stage carcinogenesis manner...
December 12, 2017: Oncotarget
https://www.readbyqxmd.com/read/29312547/development-and-validation-of-a-machine-learning-based-predictive-model-to-improve-the-prediction-of-inguinal-status-of-anal-cancer-patients-a-preliminary-report
#8
Berardino De Bari, Mauro Vallati, Roberto Gatta, Laëtitia Lestrade, Stefania Manfrida, Christian Carrie, Vincenzo Valentini
Introduction: The role of prophylactic inguinal irradiation (PII) in the treatment of anal cancer patients is controversial. We developped an innovative algorithm based on the Machine Learning (ML) allowing the tailoring of the prescription of PII. Results: Once verified on the independent testing set, J48 showed the better performances, with specificity, sensitivity, and accuracy rates in predicting relapsing patients of 86.4%, 50.0% and 83.1% respectively (vs 36...
December 12, 2017: Oncotarget
https://www.readbyqxmd.com/read/29311420/computer-aided-diagnosis-of-lung-cancer-the-effect-of-training-datasets-on-classification-accuracy-of-lung-nodules
#9
Jing Gong, Ji-Yu Liu, Xi-Wen Sun, Bin Zheng, Sheng-Dong Nie
This study aims to develop a computer-aided diagnosis (CADx) scheme for classification between malignant and benign lung nodules, and also assess whether CADx performance changes in detecting nodules associated with early and advanced stage lung cancer. Methods: The study involves 243 biopsy-confirmed pulmonary nodules. Among them, 76 are benign, 81 are stage I and 86 are stage III malignant nodules. Cases are partitioned into 3 datasets involving: (1) all nodules, (2) benign and stage I malignant nodules, and (3) benign and stage III malignant nodules...
January 9, 2018: Physics in Medicine and Biology
https://www.readbyqxmd.com/read/29304754/integration-of-multiple-networks-and-pathways-identifies-cancer-driver-genes-in-pan-cancer-analysis
#10
Claudia Cava, Gloria Bertoli, Antonio Colaprico, Catharina Olsen, Gianluca Bontempi, Isabella Castiglioni
BACKGROUND: Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network...
January 6, 2018: BMC Genomics
https://www.readbyqxmd.com/read/29304138/the-use-of-automated-ki67-analysis-to-predict-oncotype-dx-risk-of-recurrence-categories-in-early-stage-breast-cancer
#11
Satbir Singh Thakur, Haocheng Li, Angela M Y Chan, Roxana Tudor, Gilbert Bigras, Don Morris, Emeka K Enwere, Hua Yang
Ki67 is a commonly used marker of cancer cell proliferation, and has significant prognostic value in breast cancer. In spite of its clinical importance, assessment of Ki67 remains a challenge, as current manual scoring methods have high inter- and intra-user variability. A major reason for this variability is selection bias, in that different observers will score different regions of the same tumor. Here, we developed an automated Ki67 scoring method that eliminates selection bias, by using whole-slide analysis to identify and score the tumor regions with the highest proliferative rates...
2018: PloS One
https://www.readbyqxmd.com/read/29301500/using-resistin-glucose-age-and-bmi-to-predict-the-presence-of-breast-cancer
#12
Miguel Patrício, José Pereira, Joana Crisóstomo, Paulo Matafome, Manuel Gomes, Raquel Seiça, Francisco Caramelo
BACKGROUND: The goal of this exploratory study was to develop and assess a prediction model which can potentially be used as a biomarker of breast cancer, based on anthropometric data and parameters which can be gathered in routine blood analysis. METHODS: For each of the 166 participants several clinical features were observed or measured, including age, BMI, Glucose, Insulin, HOMA, Leptin, Adiponectin, Resistin and MCP-1. Machine learning algorithms (logistic regression, random forests, support vector machines) were implemented taking in as predictors different numbers of variables...
January 4, 2018: BMC Cancer
https://www.readbyqxmd.com/read/29298978/a-machine-learning-approach-to-integrate-big-data-for-precision-medicine-in-acute-myeloid-leukemia
#13
Su-In Lee, Safiye Celik, Benjamin A Logsdon, Scott M Lundberg, Timothy J Martins, Vivian G Oehler, Elihu H Estey, Chris P Miller, Sylvia Chien, Jin Dai, Akanksha Saxena, C Anthony Blau, Pamela S Becker
Cancers that appear pathologically similar often respond differently to the same drug regimens. Methods to better match patients to drugs are in high demand. We demonstrate a promising approach to identify robust molecular markers for targeted treatment of acute myeloid leukemia (AML) by introducing: data from 30 AML patients including genome-wide gene expression profiles and in vitro sensitivity to 160 chemotherapy drugs, a computational method to identify reliable gene expression markers for drug sensitivity by incorporating multi-omic prior information relevant to each gene's potential to drive cancer...
January 3, 2018: Nature Communications
https://www.readbyqxmd.com/read/29298797/development-and-validation-of-a-gene-signature-for-patients-with-head-and-neck-squamous-cell-carcinomas-treated-by-postoperative-radio-chemo-therapy
#14
Stefan Schmidt, Annett Linge, Alex Zwanenburg, Stefan Leger, Fabian Lohaus, Constanze Krenn, Steffen Appold, Volker Gudziol, Alexander Nowak, Clare von Neubeck, Ingeborg Tinhofer, Volker Budach, Ali Sak, Martin Stuschke, Panagiotis Balermpas, Claus Rödel, Hatice Bunea, Anca Ligia Grosu, Amir Abdollahi, Juergen Debus, Ute Ganswindt, Claus Belka, Steffi U Pigorsch, Stephanie Elisabeth Combs, David Mönnich, Daniel Zips, Gustavo B Baretton, Frank Buchholz, Michael Baumann, Mechthild Krause, Steffen Löck
PURPOSE: The aim of this study was to identify and independently validate a novel gene signature predicting loco-regional tumor control (LRC) for treatment individualization of patients with locally advanced HPV-negative head and neck squamous cell carcinomas (HNSCC) who are treated with postoperative radio(chemo)therapy (PORT-C). EXPERIMENTAL DESIGN: Gene expression analyses were performed using nanoString technology on a multicenter training cohort of 130 patients and an independent validation cohort of 121 patients...
January 3, 2018: Clinical Cancer Research: An Official Journal of the American Association for Cancer Research
https://www.readbyqxmd.com/read/29297284/automated-classification-and-characterization-of-the-mitotic-spindle-following-knockdown-of-a-mitosis-related-protein
#15
Matloob Khushi, Imraan M Dean, Erdahl T Teber, Megan Chircop, Jonathan W Arthur, Neftali Flores-Rodriguez
BACKGROUND: Cell division (mitosis) results in the equal segregation of chromosomes between two daughter cells. The mitotic spindle plays a pivotal role in chromosome alignment and segregation during metaphase and anaphase. Structural or functional errors of this spindle can cause aneuploidy, a hallmark of many cancers. To investigate if a given protein associates with the mitotic spindle and regulates its assembly, stability, or function, fluorescence microscopy can be performed to determine if disruption of that protein induces phenotypes indicative of spindle dysfunction...
December 28, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/29290259/radiomics-and-radiogenomics-in-lung-cancer-a-review-for-the-clinician
#16
REVIEW
Rajat Thawani, Michael McLane, Niha Beig, Soumya Ghose, Prateek Prasanna, Vamsidhar Velcheti, Anant Madabhushi
Lung cancer is responsible for a large proportion of cancer-related deaths across the globe, with delayed detection being perhaps the most significant factor for its high mortality rate. Though the National Lung Screening Trial argues for screening of certain at-risk populations, the practical implementation of these screening efforts has not yet been successful and remains in high demand. Radiomics refers to the computerized extraction of data from radiologic images, and provides unique potential for making lung cancer screening more rapid and accurate using machine learning algorithms...
January 2018: Lung Cancer: Journal of the International Association for the Study of Lung Cancer
https://www.readbyqxmd.com/read/29288987/machine-learning-based-prediction-of-brain-metastasis-of-patients-with-iiia-n2-lung-adenocarcinoma-by-a-three-mirna-signature
#17
Shuangtao Zhao, Jiangyong Yu, Luhua Wang
OBJECTIVES: MicroRNAs (miRNAs) play a key role in governing posttranscriptional regulation through binding to the mRNAs of target genes. This study is to assess miRNAs expression profiles for identifying brain metastasis-related miRNAs to develop the predictive model by microarray in tumor tissues. METHODS: For this study, we screened the significant brain metastasis-related miRNAs from 77 lung adenocarcinoma (LUAD) patients with brain metastasis (BM+) or non-brain metastasis (BM-)...
December 27, 2017: Translational Oncology
https://www.readbyqxmd.com/read/29288495/pan-cancer-insights-from-the-cancer-genome-atlas-the-pathologist-s-perspective
#18
REVIEW
Lee A D Cooper, Elizabeth G Demicco, Joel H Saltz, Reid T Powell, Arvind Rao, Alexander J Lazar
The Cancer Genome Atlas (TCGA) represents one of several international consortia dedicated to performing comprehensive genomic and epigenomic analyses of selected tumor types to advance understanding of disease and provide an open-access resource for worldwide cancer research. Thirty-three tumor types (selected by histology or tissue of origin, to include both common and rare diseases), comprising over 11,000 specimens were subjected to DNA sequencing, copy number and methylation analysis, and transcriptomic, proteomic, and histologic evaluation...
December 30, 2017: Journal of Pathology
https://www.readbyqxmd.com/read/29286167/serum-microrna-panel-excavated-by-machine-learning-as-a-potential-biomarker-for-the-detection-of-gastric-cancer
#19
Yao Huang, Jie Zhu, Wenshuai Li, Ziqiang Zhang, Panpan Xiong, Hong Wang, Jun Zhang
Early detection of gastric cancer (GC) is crucial to improve the therapeutic effect and prolong the survival of patients. MicroRNAs (miRNAs) are a group of small non-protein-coding RNAs that function as repressors of diverse genes. We aimed to identify a microRNA panel in the serum of patients to predict GC non-invasively with high accuracy and sensitivity. Using six types of classifiers, we selected three markers (miR‑21-5p, miR-22-3p and miR-29c-3p) from a published miRNA profiling study (GSE23739) which was treated as a training set...
December 19, 2017: Oncology Reports
https://www.readbyqxmd.com/read/29283496/quantitative-assessment-of-cancer-cell-morphology-and-motility-using-telecentric-digital-holographic-microscopy-and-machine-learning
#20
Van K Lam, Thanh C Nguyen, Byung M Chung, George Nehmetallah, Christopher B Raub
The noninvasive, fast acquisition of quantitative phase maps using digital holographic microscopy (DHM) allows tracking of rapid cellular motility on transparent substrates. On two-dimensional surfaces in vitro, MDA-MB-231 cancer cells assume several morphologies related to the mode of migration and substrate stiffness, relevant to mechanisms of cancer invasiveness in vivo. The quantitative phase information from DHM may accurately classify adhesive cancer cell subpopulations with clinical relevance. To test this, cells from the invasive breast cancer MDA-MB-231 cell line were cultured on glass, tissue-culture treated polystyrene, and collagen hydrogels, and imaged with DHM followed by epifluorescence microscopy after staining F-actin and nuclei...
December 28, 2017: Cytometry. Part A: the Journal of the International Society for Analytical Cytology
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