Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A U1-U3 snRNA-snoRNA interaction couples SF3B1 mutation to chromatin-state rewiring and genome instability.

bioRxiv : the preprint server for biology·2026
Same author

Fully human anti-FOLR1 T-cell engager demonstrates potent activity in CBFA2T3::GLIS2 acute megakaryoblastic leukemia.

Blood neoplasia·2026
Same author

Clinical implications of RAS mutations in AML: prognostic significance is based upon the involved gene and mutation complexity.

Blood advances·2026
Same author

CD84 is a specific target for acute myeloid leukemia CAR-T cell therapy.

Nature communications·2026
Same author

Combining menin and MEK inhibition to target poor prognosis KMT2A-rearranged RAS pathway-mutant acute myeloid leukemia.

Blood advances·2026
Same author

DLK1 is a GATA1s-driven dependency and therapeutic target in Down syndrome-associated myeloid leukemia.

Blood advances·2026

Related Experiment Video

Updated: Apr 21, 2026

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
11:02

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing

Published on: October 18, 2013

20.1K

Sample processing obscures cancer-specific alterations in leukemic transcriptomes.

Heidi Dvinge1, Rhonda E Ries2, Janine O Ilagan1

  • 1Computational Biology Program, Public Health Sciences Division, Basic Sciences Division, and.

Proceedings of the National Academy of Sciences of the United States of America
|November 12, 2014
PubMed
Summary

Standard blood collection alters gene expression in hematopoietic cells, impacting cancer genomics research. Keeping blood on ice minimizes these critical transcriptional changes.

Keywords:
RNA splicingbatch effectsleukemianonsense-mediated decay

More Related Videos

Comparative Lesions Analysis Through a Targeted Sequencing Approach
08:16

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Published on: November 5, 2019

7.4K
Flow-sorting and Exome Sequencing of the Reed-Sternberg Cells of Classical Hodgkin Lymphoma
08:53

Flow-sorting and Exome Sequencing of the Reed-Sternberg Cells of Classical Hodgkin Lymphoma

Published on: June 10, 2017

10.6K

Related Experiment Videos

Last Updated: Apr 21, 2026

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
11:02

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing

Published on: October 18, 2013

20.1K
Comparative Lesions Analysis Through a Targeted Sequencing Approach
08:16

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Published on: November 5, 2019

7.4K
Flow-sorting and Exome Sequencing of the Reed-Sternberg Cells of Classical Hodgkin Lymphoma
08:53

Flow-sorting and Exome Sequencing of the Reed-Sternberg Cells of Classical Hodgkin Lymphoma

Published on: June 10, 2017

10.6K

Area of Science:

  • Genomics and Molecular Biology
  • Cancer Research
  • Hematology

Background:

  • Genomic studies aim to identify cancer-associated alterations.
  • Standard blood collection procedures are widely used for sample acquisition.

Purpose of the Study:

  • To investigate the impact of standard blood collection procedures on hematopoietic cell transcriptomes.
  • To identify potential confounding factors in cancer genomics data due to sample processing.
  • To develop methods to mitigate or detect these technical artifacts.

Main Methods:

  • Analysis of transcriptional and posttranscriptional landscapes of hematopoietic cells post-collection.
  • Comparison of gene expression and alternative splicing in leukemic transcriptomes versus reference normal transcriptomes.
  • Development and application of biomarkers to detect sample incubation effects.
  • Evaluation of the effect of cold storage (on ice) on sample transcriptomes.

Main Results:

  • Standard blood collection induces rapid, significant changes in hematopoietic cell transcriptomes, including pathway activation, pseudogene/antisense RNA/isoform upregulation, and RNA surveillance inhibition.
  • These processing-induced changes affect common cancer gene targets and pathways like chromatin modification, RNA splicing, and immune signaling.
  • Incubation effects explain up to 40% of gene expression and splicing differences in published leukemic transcriptomes.
  • Biomarkers for detecting prolonged incubation were developed, and cold storage was shown to markedly reduce transcriptomic changes.

Conclusions:

  • Technical artifacts from blood sample processing can significantly confound cancer genomics and pan-cancer analyses.
  • Awareness and mitigation of these effects, such as by using cold storage, are crucial for accurate cancer research.
  • The study underscores the importance of considering cellular heterogeneity and technical variability when interpreting tumor molecular data.