The NCI-60 cell lines are the most frequently studied human tumor cell lines in cancer research. This panel has generated the most extensive cancer pharmacology database worldwide. In addition, these ...cell lines have been intensely investigated, providing a unique platform for hypothesis-driven research focused on enhancing our understanding of tumor biology. Here, we report a comprehensive analysis of coding variants in the NCI-60 panel of cell lines identified by whole exome sequencing, providing a list of possible cancer specific variants for the community. Furthermore, we identify pharmacogenomic correlations between specific variants in genes such as TP53, BRAF, ERBBs, and ATAD5 and anticancer agents such as nutlin, vemurafenib, erlotinib, and bleomycin showing one of many ways the data could be used to validate and generate novel hypotheses for further investigation. As new cancer genes are identified through large-scale sequencing studies, the data presented here for the NCI-60 will be an invaluable resource for identifying cell lines with mutations in such genes for hypothesis-driven research. To enhance the utility of the data for the greater research community, the genomic variants are freely available in different formats and from multiple sources including the CellMiner and Ingenuity websites.
In this study, we use a k‐mean clustering approach to investigate the weather patterns responsible for extreme wind speed events throughout Mexico using 40 years of the ERA‐5 atmospheric reanalysis. ...Generally, we find a large geographical split between the weather patterns that generate the strongest winds across the country. The highest wind power production periods therefore occur at different times in different regions across the country. In the South, these are associated with cold surge events, where an anticyclone is present in the Gulf of Mexico resulting in a strong Northerly flow across the Isthmus of Tehuantepec. In the North‐East, Easterly trade winds are responsible for the strongest wind events, whereas in the North‐West, it is the proximity of the North Pacific High. However, the weakest winds and lowest power production periods occur at the same times for all stations with the exception of Baja California Sur, meaning that low wind power production may be unavoidable at these times. The El Niño Southern Oscillation is found to influence wind speeds at some locations across Mexico at sub‐seasonal time‐scales. We report that statistically stronger wind speeds are observed during the Summer during El Niño months than during La Niña months for both sites in Chiapas and Oaxaca.
The eight weather patterns obtained via k‐means cluster on the ERA‐5 reanalysis 500 hPa geopotential height over Mexico. The colour contours show the ERA‐5 mean‐sea level pressure with the black vectors showing winds. Weather patterns 1 and 8 are associated with the weakest winds across most of the country, whereas weather pattern 5 has the strongest, particularly for Chiapas and Oaxaca, where wind farms are located.
High-throughput 'omics' technologies that generate molecular profiles for biospecimens have been extensively used in preclinical studies to reveal molecular subtypes and elucidate the biological ...mechanisms of disease, and in retrospective studies on clinical specimens to develop mathematical models to predict clinical endpoints. Nevertheless, the translation of these technologies into clinical tests that are useful for guiding management decisions for patients has been relatively slow. It can be difficult to determine when the body of evidence for an omics-based test is sufficiently comprehensive and reliable to support claims that it is ready for clinical use, or even that it is ready for definitive evaluation in a clinical trial in which it may be used to direct patient therapy. Reasons for this difficulty include the exploratory and retrospective nature of many of these studies, the complexity of these assays and their application to clinical specimens, and the many potential pitfalls inherent in the development of mathematical predictor models from the very high-dimensional data generated by these omics technologies. Here we present a checklist of criteria to consider when evaluating the body of evidence supporting the clinical use of a predictor to guide patient therapy. Included are issues pertaining to specimen and assay requirements, the soundness of the process for developing predictor models, expectations regarding clinical study design and conduct, and attention to regulatory, ethical, and legal issues. The proposed checklist should serve as a useful guide to investigators preparing proposals for studies involving the use of omics-based tests. The US National Cancer Institute plans to refer to these guidelines for review of proposals for studies involving omics tests, and it is hoped that other sponsors will adopt the checklist as well.
Abstract Introduction We evaluated the performance of multiparametric prostate magnetic resonance imaging (mp-MRI) and MRI/transrectal ultrasound (TRUS) fusion–guided biopsy (FB) for monitoring ...patients with prostate cancer on active surveillance (AS). Materials and methods Patients undergoing mp-MRI and FB of target lesions identified on mp-MRI between August 2007 and August 2014 were reviewed. Patients meeting AS criteria (Clinical stage T1c, Gleason grade≤6, prostate-specific antigen density≤0.15, tumor involving≤2 cores, and≤50% involvement of any single core) based on extended sextant 12-core TRUS biopsy (systematic biopsy SB) were included. They were followed with subsequent 12-core biopsy as well as mp-MRI and MRI/TRUS fusion biopsy at follow-up visits until Gleason score progression (Gleason≥7 in either 12-core or MRI/TRUS fusion biopsy). We evaluated whether progression seen on mp-MRI (defined as an increase in suspicion level, largest lesion diameter, or number of lesions) was predictive of Gleason score progression. Results Of 152 patients meeting AS criteria on initial SB (mean age of 61.4 years and mean prostate-specific antigen level of 5.26 ng/ml), 34 (22.4%) had Gleason score≥7 on confirmatory SB/FB. Of the 118 remaining patients, 58 chose AS and had at least 1 subsequent mp-MRI with SB/FB (median follow-up = 16.1 months). Gleason progression was subsequently documented in 17 (29%) of these men, in all cases to Gleason 3+4. The positive predictive value and negative predictive value of mp-MRI for Gleason progression was 53% (95% CI: 28%–77%) and 80% (95% CI: 65%–91%), respectively. The sensitivity and specificity of mp-MRI for increase in Gleason were also 53% and 80%, respectively. The number needed to biopsy to detect 1 Gleason progression was 8.74 for SB vs. 2.9 for FB. Conclusions Stable findings on mp-MRI are associated with Gleason score stability. mp-MRI appears promising as a useful aid for reducing the number of biopsies in the management of patients on AS. A prospective evaluation of mp-MRI as a screen to reduce biopsies in the follow-up of men on AS appears warranted.
Abstract Background A systematic literature review of magnetic resonance imaging (MRI)–targeted prostate biopsy demonstrates poor adherence to the Standards for the Reporting of Diagnostic Accuracy ...(STARD) recommendations for the full and transparent reporting of diagnostic studies. Objective To define and recommend Standards of Reporting for MRI-targeted Biopsy Studies (START). Design, setting, and participants Each member of a panel of 23 experts in urology, radiology, histopathology, and methodology used the RAND/UCLA appropriateness methodology to score a 258-statement premeeting questionnaire. The collated responses were presented at a face-to-face meeting, and each statement was rescored after group discussion. Outcome measurements and statistical analysis Measures of agreement and consensus were calculated for each statement. The most important statements, based on group median score, the degree of group consensus, and the content of the group discussion, were used to create a checklist of reporting criteria (the START checklist). Results and limitations The strongest recommendations were to report histologic results of standard and targeted cores separately using Gleason score and maximum cancer core length. A table comparing detection rates of clinically significant and clinically insignificant disease by targeted and standard approaches should also be used. It was recommended to report the recruitment criteria for MRI-targeted biopsy, prior biopsy status of the population, a brief description of the MRI sequences, MRI reporting method, radiologist experience, and image registration technique. There was uncertainty about which histologic criteria constitute clinically significant cancer when the prostate is sampled using MRI-targeted biopsy, and it was agreed that a new definition of clinical significance in this setting needed to be derived in future studies. Conclusions Use of the START checklist would improve the quality of reporting in MRI-targeted biopsy studies and facilitate a comparison between standard and MRI-targeted approaches.
Developments in whole genome biotechnology have stimulated statistical focus on prediction methods. We review here methodology for classifying patients into survival risk groups and for using ...cross-validation to evaluate such classifications. Measures of discrimination for survival risk models include separation of survival curves, time-dependent ROC curves and Harrell's concordance index. For high-dimensional data applications, however, computing these measures as re-substitution statistics on the same data used for model development results in highly biased estimates. Most developments in methodology for survival risk modeling with high-dimensional data have utilized separate test data sets for model evaluation. Cross-validation has sometimes been used for optimization of tuning parameters. In many applications, however, the data available are too limited for effective division into training and test sets and consequently authors have often either reported re-substitution statistics or analyzed their data using binary classification methods in order to utilize familiar cross-validation. In this article we have tried to indicate how to utilize cross-validation for the evaluation of survival risk models; specifically how to compute cross-validated estimates of survival distributions for predicted risk groups and how to compute cross-validated time-dependent ROC curves. We have also discussed evaluation of the statistical significance of a survival risk model and evaluation of whether high-dimensional genomic data adds predictive accuracy to a model based on standard covariates alone.
BACKGROUND
Active surveillance (AS) is an attempt to avoid overtreatment of clinically insignificant prostate cancer (PCa); however, patient selection remains controversial. Multiparametric prostate ...magnetic resonance imaging (MP‐MRI) may help better select AS candidates.
METHODS
We reviewed a cohort of men who underwent MP‐MRI with MRI/Ultrasound fusion–guided prostate biopsy and selected potential AS patients at entry using Johns Hopkins criteria. MP‐MRI findings were assessed, including number of lesions, dominant lesion diameter, total lesion volume, prostate volume, and lesion density (calculated as total lesion volume/prostate volume). Lesions were assigned a suspicion score for cancer by MRI. AS criteria were reapplied based on the confirmatory biopsy, and accuracy of MP‐MRI in predicting AS candidacy was assessed. Logistic regression modeling and chi‐square statistics were used to assess associations between MP‐MRI interpretation and biopsy results.
RESULTS
Eighty‐five patients qualified for AS with a mean age of 60.2 years and mean prostate‐specific antigen level of 4.8 ng/mL. Of these, 25 patients (29%) were reclassified as not meeting AS criteria based on confirmatory biopsy. Number of lesions, lesion density, and highest MRI lesion suspicion were significantly associated with confirmatory biopsy AS reclassification. These MRI‐based factors were combined to create a nomogram that generates a probability for confirmed AS candidacy.
CONCLUSION
As clinicians counsel patients with PCa, MP‐MRI may contribute to the decision‐making process when considering AS. Three MRI‐based factors (number of lesions, lesion suspicion, and lesion density) were associated with confirmatory biopsy outcome and reclassification. A nomogram using these factors has promising predictive accuracy for which future validation is necessary. Cancer 2013;119:3359–66. Published 2013. This article is a U.S. Government work and is in the public domain in the USA
Multiparametric prostate magnetic resonance imaging (MRI) may be useful in the selection of candidates for active surveillance of prostate cancer. A nomogram has been generated that predicts the probability of surveillance candidacy based solely on MRI‐derived factors.
Molecularly targeted cancer drugs are often developed with companion diagnostics that attempt to identify which patients will have better outcome on the new drug than the control regimen. Such ...predictive biomarkers are playing an increasingly important role in precision oncology. For diagnostic tests, sensitivity, specificity, positive predictive value, and negative predictive are usually used as performance measures. This paper discusses these indices for predictive biomarkers, provides methods for their calculation with survival or response endpoints, and describes assumptions involved in their use.
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