Classification of clinical outcomes using high-throughput informatics: Part 2 - parametric method reviews

Cambon, Alex; Baumgartner, K.B.; Brock, Guy; Cooper, Nigel G. F.; Wu, Dongfeng; Rai, S.N.

doi:10.3233/mas-140321

Cited by 3 publications

(3 citation statements)

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“…With the same design two data sets were generated for training set and then for test set. As summarized in Cambon et al [34, 35], there are different approaches to classification of higher dimensional data sets based on biosensor signals. In the recent past, group classification of cervical cancer versus control samples were done based on differential scanning calorimetry thermograms.…”

Section: Resultsmentioning

confidence: 99%

Label-free capture of breast cancer cells spiked in buffy coats using carbon nanotube antibody micro-arrays

et al. 2016

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We demonstrate the rapid and label-free capture of breast cancer cells spiked in buffy coats using nanotube-antibody micro-arrays. Single wall carbon nanotube arrays were manufactured using photo-lithography, metal deposition, and etching techniques. Anti-epithelial cell adhesion molecule (EpCAM) antibodies were functionalized to the surface of the nanotube devices using 1-pyrene-butanoic acid succinimidyl ester functionalization method. Following functionalization, plain buffy coat and MCF7 cell spiked buffy coats were adsorbed on to the nanotube device and electrical signatures were recorded for differences in interaction between samples. A statistical classifier for the 'liquid biopsy' was developed to create a predictive model based on dynamic time warping to classify device electrical signals that corresponded to plain (control) or spiked buffy coats (case). In training test, the device electrical signals originating from buffy versus spiked buffy samples were classified with ~100% sensitivity, ~91% specificity and ~96% accuracy. In the blinded test, the signals were classified with ~91% sensitivity, ~82% specificity and ~86% accuracy. A heatmap was generated to visually capture the relationship between electrical signatures and the sample condition. Confocal microscopic analysis of devices that were classified as spiked buffy coats based on their electrical signatures confirmed the presence of cancer cells, their attachment to the device and overexpression of EpCAM receptors. The cell numbers were counted to be ~1-17 cells per 5 µl per device suggesting single cell sensitivity in spiked buffy coats that is scalable to higher volumes using the micro-arrays.

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Section: Resultsmentioning

confidence: 99%

Label-free capture of breast cancer cells spiked in buffy coats using carbon nanotube antibody micro-arrays

et al. 2016

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“…Another critical approach is to build a prediction model to identify groups of individuals (such as cases and controls). Unlike high-throughput data analysis with tens of thousands of biomarker (genes), which involves hierarchical modeling, principal component analysis, heat map, and other methods, with a lesser number of biomarkers (miRNAs), we apply an ANOVA/ANCOVA model for model fitting and a logistic model for prediction [ 94 , 95 ]. The classification method based on a logistic model is simple and is extensively used [ 88 , 96 , 97 ].…”

Section: Methodsmentioning

confidence: 99%

Assay Reproducibility in Clinical Studies of Plasma miRNA

et al. 2015

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There are increasing reports of plasma miRNAs as biomarkers of human disease but few standards in methodologic reporting, leading to inconsistent data. We systematically reviewed plasma miRNA studies published between July 2013-June 2014 to assess methodology. Six parameters were investigated: time to plasma extraction, methods of RNA extraction, type of miRNA, quantification, cycle threshold (Ct) setting, and methods of statistical analysis. We compared these data with a proposed standard methodologic technique. Beginning with initial screening for 380 miRNAs using microfluidic array technology and validation in an additional cohort of patients, we compared 11 miRNAs that exhibited differential expression between 16 patients with benign colorectal neoplasms (advanced adenomas) and 16 patients without any neoplasm (controls). Plasma was isolated immediately, 12, 24, 48, or 72 h following phlebotomy. miRNA was extracted using two different techniques (Trizol LS with pre-amplification or modified miRNeasy). We performed Taqman-based RT-PCR assays for the 11 miRNAs with subsequent analyses using a variable Ct setting or a fixed Ct set at 0.01, 0.03, 0.05, or 0.5. Assays were performed in duplicate by two different operators. RNU6 was the internal reference. Systematic review yielded 74 manuscripts meeting inclusion criteria. One manuscript (1.4%) documented all 6 methodological parameters, while < 5% of studies listed Ct setting. In our proposed standard technique, plasma extraction ≤12 h provided consistent ΔCt. miRNeasy extraction yielded higher miRNA concentrations and fewer non-expressed miRNAs compared to Trizol LS (1/704 miRNAs [0.14%] vs 109/704 miRNAs [15%], not expressed, respectively). A fixed Ct bar setting of 0.03 yielded the most reproducible data, provided that <10% miRNA were non-expressed. There was no significant intra-operator variability. There was significant inter-operator variation using Trizol LS extraction, while this was negligible using modified miRNeasy. For standardized reporting, we recommend plasma extraction ≤ 12 h, using modified miRNeasy extraction and utilizing a 0.03 Ct.

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“…There can be multiple biomarker classifiers which can produce a similar effect in classification between sensitive and non-sensitive patients, and choosing the ideal and optimal one becomes difficult. A detailed review of the parametric [ 58 ] and nonparametric [ 59 ] methods of classification and dimension reduction of clinical outcomes using high-throughput informatics can form a basis for applications in melanoma studies. These classification algorithms can be applied in ASD.…”

Section: Discussionmentioning

confidence: 99%

Adaptive Signature Design- review of the biomarker guided adaptive phase –III controlled design

Bhattacharyya

Shesh

2019

Contemporary Clinical Trials Communications

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Genomics having a profound impact on oncology drug development necessitates the use of genomic signatures for therapeutic strategy and emerging medicine proposals. Since its advent in the arena of clinical trials biomarker-related predictive methods for the identification and selection of patient subgroups, with optimal treatment response, are widely used. Genetic signatures which are accountable for the differential response to treatments are experimentally recognizable and analytically validated in phase II stage of clinical trials. The availability of robust and validated biomarkers in phase III is limited. Hence, the development of a clinical trial design without the availability of biomarker identity for treatment-sensitive patients becomes indispensable. Adaptive Signature Design (ASD) is a design procedure of developing and validating a predictive classifier (diagnostic testing strategy) when the signature of subjects responding differentially to treatment is remote in the context of the study. This review provides a detailed methodology and statistical background of this pioneering design developed by Freidlin and Simon (2005). In addition, it concentrates on the advances in ASD regarding statistical issues such as predictive assay identification, classification techniques, statistical methods, subgroup search, choice of differentially expressed genes, and multiplicity correction. The statistical methodology behind the design is explained with the intent of building the ground steps for future research approachable, especially for beginning researchers. Most of the existing research articles give a microcosmic view of the design and lack in describing the details behind the methodology. This study covers those details and marks the novelty of our research.

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Classification of clinical outcomes using high-throughput informatics: Part 2 - parametric method reviews

Cited by 3 publications

References 0 publications

Label-free capture of breast cancer cells spiked in buffy coats using carbon nanotube antibody micro-arrays

Label-free capture of breast cancer cells spiked in buffy coats using carbon nanotube antibody micro-arrays

Assay Reproducibility in Clinical Studies of Plasma miRNA

Adaptive Signature Design- review of the biomarker guided adaptive phase –III controlled design

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