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Title: ‘N-of-1- pathways ’ unveils personal deregulated mechanisms from a single pair of RNA-Seq samples: Towards precision medicine

Journal Article · · Journal of the American Medical Informatics Association
 [1];  [2];  [2];  [3];  [2];  [4];  [3];  [3];  [5];  [6];  [4];  [7]
  1. Univ. of Arizona, Tucson, AZ (United States); Univ. of Illinois at Chicago, Chicago, IL (United States); EISTI (Ecole Internationale des Sciences du Traitement de l'Information), Cergy-Pontoise (France)
  2. Univ. of Arizona, Tucson, AZ (United States); Univ. of Illinois at Chicago, Chicago, IL (United States)
  3. Univ. of Illinois at Chicago, Chicago, IL (United States)
  4. Argonne National Lab. (ANL), Argonne, IL (United States); Univ. of Chicago, Chicago, IL (United States)
  5. Univ. of Illinois at Chicago, Chicago, IL (United States); Univ. of Illinois Cancer Center, Chicago, IL (United States)
  6. Univ. of Arizona, Tucson, AZ (United States)
  7. Univ. of Arizona, Tucson, AZ (United States); Univ. of Illinois at Chicago, Chicago, IL (United States); Argonne National Lab. (ANL), Argonne, IL (United States)
+ Show Author Affiliations

Background: The emergence of precision medicine allowed the incorporation of individual molecular data into patient care. This research entails, DNA sequencing predicts somatic mutations in individual patients. However, these genetic features overlook dynamic epigenetic and phenotypic response to therapy. Meanwhile, accurate personal transcriptome interpretation remains an unmet challenge. Further, N-of-1 (single-subject) efficacy trials are increasingly pursued, but are underpowered for molecular marker discovery. Method: ‘N-of-1-pathways’ is a global framework relying on three principles: (i) the statistical universe is a single patient; (ii) significance is derived from geneset/biomodules powered by paired samples from the same patient; and (iii) similarity between genesets/biomodules assesses commonality and differences, within-study and cross-studies. Thus, patient gene-level profiles are transformed into deregulated pathways. From RNA-Seq of 55 lung adenocarcinoma patients, N-of-1-pathways predicts the deregulated pathways of each patient. Results: Cross-patient N-of-1-pathways obtains comparable results with conventional genesets enrichment analysis (GSEA) and differentially expressed gene (DEG) enrichment, validated in three external evaluations. Moreover, heatmap and star plots highlight both individual and shared mechanisms ranging from molecular to organ-systems levels (eg, DNA repair, signaling, immune response). Patients were ranked based on the similarity of their deregulated mechanisms to those of an independent gold standard, generating unsupervised clusters of diametric extreme survival phenotypes (p=0.03). Conclusions: The N-of-1-pathways framework provides a robust statistical and relevant biological interpretation of individual disease-free survival that is often overlooked in conventional cross-patient studies. It enables mechanism-level classifiers with smaller cohorts as well as N-of-1 studies.

Research Organization:
Argonne National Laboratory (ANL), Argonne, IL (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC02-06CH11357
OSTI ID:
1225365
Journal Information:
Journal of the American Medical Informatics Association, Vol. 21, Issue 6; ISSN 1067-5027
Publisher:
Oxford University PressCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 28 works
Citation information provided by
Web of Science

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Cited By (16)

Unmet Needs in Systemic Sclerosis Understanding and Treatment: the Knowledge Gaps from a Scientist’s, Clinician’s, and Patient’s Perspective journal September 2017
The mechanism of cancer drug addiction in ALK-positive T-Cell lymphoma journal December 2019
Interpretation of ‘Omics dynamics in a single subject using local estimates of dispersion between two transcriptomes posted_content January 2019
Evaluating single-subject study methods for personal transcriptomic interpretations to advance precision medicine journal September 2018
N-of-1-pathways MixEnrich: advancing precision medicine via single-subject analysis in discovering dynamic changes of transcriptomes journal May 2017
Evaluating single-subject study methods for personal transcriptomic interpretations to advance precision medicine journal July 2019
Detecting gene signature activation in breast cancer in an absolute, single-patient manner journal March 2017
Exploiting Drug Addiction Mechanisms to Select against MAPKi-Resistant Melanoma journal September 2017
Potential Diagnostic Power of Blood Circular RNA Expression in Active Pulmonary Tuberculosis journal January 2018
Developing a ‘personalome’ for precision medicine: emerging methods that compute interpretable effect sizes from single-subject transcriptomes journal December 2017
Dynamic changes of RNA-sequencing expression for precision medicine: N-of-1-pathways Mahalanobis distance within pathways of single subjects predicts breast cancer survival journal June 2015
Analysis of aggregated cell–cell statistical distances within pathways unveils therapeutic-resistance mechanisms in circulating tumor cells journal June 2016
A genome-by-environment interaction classifier for precision medicine: personal transcriptome response to rhinovirus identifies children prone to asthma exacerbations journal July 2017
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59 BASIC BIOLOGICAL SCIENCES
N-of-1
single subject design
precision medicine
personalized medicine
personal transcriptome
geneset