Current and Evolving Methods to Visualize Biological Data in Cancer Research

Chia, Puey Ling; Gedye, Craig; Boutros, Paul C.; Wheatley‐Price, Paul; John, Thomas

doi:10.1093/jnci/djw031

Cited by 18 publications

(15 citation statements)

References 44 publications

(40 reference statements)

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“…Box plots were performed with GraphPad Prism 5 (GraphPad Software Inc., La Jolla, CA, USA). To visualize the sequence and duration of treatments, patient response, and LDH levels, swimmer plots were employed using ggplot2 package version 3.3.2.9000 [ 51 , 52 ]. The swimmer plots were carried out using R version 4.0.0 (R Core Team) [ 52 ].…”

Section: Methodsmentioning

confidence: 99%

A Pilot Study Comparing the Efficacy of Lactate Dehydrogenase Levels Versus Circulating Cell-Free microRNAs in Monitoring Responses to Checkpoint Inhibitor Immunotherapy in Metastatic Melanoma Patients

Bustos

Gross

Rahimzadeh

et al. 2020

Cancers

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Serum lactate dehydrogenase (LDH) is a standard prognostic biomarker for stage IV melanoma patients. Often, LDH levels do not provide real-time information about the metastatic melanoma patients’ disease status and treatment response. Therefore, there is a need to find reliable blood biomarkers for improved monitoring of metastatic melanoma patients who are undergoing checkpoint inhibitor immunotherapy (CII). The objective in this prospective pilot study was to discover circulating cell-free microRNA (cfmiR) signatures in the plasma that could assess melanoma patients’ responses during CII. The cfmiRs were evaluated by the next-generation sequencing (NGS) HTG EdgeSeq microRNA (miR) Whole Transcriptome Assay (WTA; 2083 miRs) in 158 plasma samples obtained before and during the course of CII from 47 AJCC stage III/IV melanoma patients’ and 73 normal donors’ plasma samples. Initially, cfmiR profiles for pre- and post-treatment plasma samples of stage IV non-responder melanoma patients were compared to normal donors’ plasma samples. Using machine learning, we identified a 9 cfmiR signature that was associated with stage IV melanoma patients being non-responsive to CII. These cfmiRs were compared in pre- and post-treatment plasma samples from stage IV melanoma patients that showed good responses. Circulating miR-4649-3p, miR-615-3p, and miR-1234-3p demonstrated potential prognostic utility in assessing CII responses. Compared to LDH levels during CII, circulating miR-615-3p levels were consistently more efficient in detecting melanoma patients undergoing CII who developed progressive disease. By combining stage III/IV patients, 92 and 17 differentially expressed cfmiRs were identified in pre-treatment plasma samples from responder and non-responder patients, respectively. In conclusion, this pilot study demonstrated cfmiRs that identified treatment responses and could allow for real-time monitoring of patients receiving CII.

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Section: Methodsmentioning

confidence: 99%

A Pilot Study Comparing the Efficacy of Lactate Dehydrogenase Levels Versus Circulating Cell-Free microRNAs in Monitoring Responses to Checkpoint Inhibitor Immunotherapy in Metastatic Melanoma Patients

Bustos

Gross

Rahimzadeh

et al. 2020

Cancers

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“… 18 For patient-level representations, spider plots display individual tumor changes over time relative to baseline burden. 19 Traditionally, these data representations of DOR have been based on the subset of responding patients, defined post randomization, and are thus prone to analysis-by-responder bias. 20 New approaches to visually and statistically describe DOR in all randomized patients (ITT) are needed to avoid this bias.…”

Section: Introductionmentioning

confidence: 99%

Characterizing tumor shrinkage as a measure of clinical benefit for immune checkpoint inhibitors

Kelleher

Cai

Botwood

et al. 2021

J Immunother Cancer

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BackgroundWe explored whether the effectiveness of immune checkpoint inhibitors (ICIs) can be characterized by incorporating a composite of duration of response (DOR) to complement traditional Response Evaluation Criteria in Solid Tumors (RECIST) criteria for objective response rate (ORR) in an intent-to-treat (ITT) population. Furthermore, the correlation of this novel endpoint, characterized by the restricted mean time in response (RMTR), with overall survival (OS) will be examined.MethodsWe analyzed ORR alone or in combination with DOR (RMTR) in available phase I, II, and III trials evaluating nivolumab monotherapy or in combination with ipilimumab across solid tumor types. ORR was evaluated per RECIST V.1.1. DOR was estimated using individual patient data in ITT populations regardless of RECIST response, with non-responders imputed as zero. Associations between ORR alone or RMTR and OS were evaluated in the ITT population. DOR curves were generated using the Kaplan-Meier product limit method, and 6-month RMTR, a measure of response durability, was derived from the area under the curves. For ORR and RMTR in the ITT population, the strength of association with OS was analyzed using Pearson correlation coefficients (r).ResultsNivolumab treatment was associated with longer response durations than active control in responder and ITT populations. Similarly, ORR and RMTR were both significantly correlated with OS (ORR vs OS: r=0.684, p=0.02; RMTR vs OS: r=0.695, p=0.018).ConclusionsCombining ORR and DOR (RMTR) to objectively characterize tumor shrinkage in an ITT patient population is a novel approach that appears to correlate well with OS in patients treated with nivolumab monotherapy or in combination with ipilimumab. This endpoint may provide a more complete characterization of tumor shrinkage to incorporate into the design of future ICI clinical trials. However, confirmation of this approach will require further research.

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“…Accordingly, newer generation visualization tools are needed to assist with the analyses and interpretation of these increasingly high-dimensional and complex data sets. Several resources now offer a variety of techniques for visualizing metabolomics data structure and exploring the inter-relations between individual and groups of metabolites [2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21].…”

Section: Introductionmentioning

confidence: 99%

“…The most commonly used methods for visually analyzing and representing associations between metabolites and outcomes are borrowed from conventional statistics and other biological fields [2]. Methods such as Manhattan plots, bar and scatter plots, and heatmaps are commonly used for visualizing information on the association between metabolites and outcomes.…”

Section: Introductionmentioning

confidence: 99%

A Single Visualization Technique for Displaying Multiple Metabolite–Phenotype Associations

et al. 2019

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To assist with management and interpretation of human metabolomics data, which are rapidly increasing in quantity and complexity, we need better visualization tools. Using a dataset of several hundred metabolite measures profiled in a cohort of ~1500 individuals sampled from a population-based community study, we performed association analyses with eight demographic and clinical traits and outcomes. We compared frequently used existing graphical approaches with a novel ‘rain plot’ approach to display the results of these analyses. The ‘rain plot’ combines features of a raindrop plot and a conventional heatmap to convey results of multiple association analyses. A rain plot can simultaneously indicate effect size, directionality, and statistical significance of associations between metabolites and several traits. This approach enables visual comparison features of all metabolites examined with a given trait. The rain plot extends prior approaches and offers complementary information for data interpretation. Additional work is needed in data visualizations for metabolomics to assist investigators in the process of understanding and convey large-scale analysis results effectively, feasibly, and practically.

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Current and Evolving Methods to Visualize Biological Data in Cancer Research

Cited by 18 publications

References 44 publications

A Pilot Study Comparing the Efficacy of Lactate Dehydrogenase Levels Versus Circulating Cell-Free microRNAs in Monitoring Responses to Checkpoint Inhibitor Immunotherapy in Metastatic Melanoma Patients

A Pilot Study Comparing the Efficacy of Lactate Dehydrogenase Levels Versus Circulating Cell-Free microRNAs in Monitoring Responses to Checkpoint Inhibitor Immunotherapy in Metastatic Melanoma Patients

Characterizing tumor shrinkage as a measure of clinical benefit for immune checkpoint inhibitors

A Single Visualization Technique for Displaying Multiple Metabolite–Phenotype Associations

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