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

Blood Cancer Clinical Trials Long-term Follow-up Using Integrated Healthcare Systems Data (BLISS): protocol for a data-linkage study integrating randomised clinical trials with national healthcare systems data.

BMJ open·2026
Same author

The density of tumour infiltrating lymphocytes in oesophago-gastric cancer varies with disease stage, geographical region and treatment: a post hoc analysis of nine phase III clinical trials.

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association·2026
Same author

Patient-reported health-related quality of life in previously untreated chronic lymphocytic leukaemia: Results from the randomised phase 3 FLAIR trial comparing ibrutinib-rituximab versus fludarabine-cyclophosphamide-rituximab.

British journal of haematology·2026
Same author

Radiotherapy patterns and factors associated with pneumonitis in PACIFIC-R, a real-world study of patients with unresectable stage III non-small-cell lung cancer treated with durvalumab after chemoradiotherapy.

Clinical and translational radiation oncology·2026
Same author

Volume and location of screen-detected lung nodules associated with lung cancer within two-year follow-up: Post hoc analysis from the UK Lung Cancer Screening (UKLS) trial.

Lung cancer (Amsterdam, Netherlands)·2026
Same author

Germline HLA heterozygosity is associated with decreased lung cancer risk.

HGG advances·2026

Related Experiment Video

Updated: Jun 27, 2026

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions
09:00

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions

Published on: April 18, 2025

Sample size determination in clinical proteomic profiling experiments using mass spectrometry for class comparison.

David A Cairns1, Jennifer H Barrett, Lucinda J Billingham

  • 1Clinical and Biomedical Proteomics Group, Cancer Research UK Clinical Centre, Leeds Institute of Molecular Medicine, St. James's University Hospital, Leeds, UK. d.a.cairns@leeds.ac.uk

Proteomics
|December 5, 2008
PubMed
Summary

Calculating appropriate sample sizes is crucial for mass spectrometry (MS) based proteomic profiling studies. This research provides a protocol for sample size calculations, considering biological and technical variations for accurate disease marker discovery.

More Related Videos

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
10:37

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Published on: November 15, 2017

Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors
08:08

Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors

Published on: February 27, 2015

Related Experiment Videos

Last Updated: Jun 27, 2026

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions
09:00

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions

Published on: April 18, 2025

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
10:37

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Published on: November 15, 2017

Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors
08:08

Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors

Published on: February 27, 2015

Area of Science:

  • Biochemistry
  • Proteomics
  • Analytical Chemistry

Background:

  • Mass spectrometry (MS) techniques like MALDI-TOF and SELDI-TOF are vital for disease marker discovery, especially in the low molecular weight proteome.
  • Experimental design in proteomic profiling often overlooks the critical factor of sample size.
  • Robust statistical planning is essential for reliable results in high-throughput biological studies.

Purpose of the Study:

  • To develop a standardized protocol for sample size calculations in mass spectrometry-based proteomic profiling.
  • To integrate estimates of biological and technical variation into sample size determination.
  • To provide a framework for optimizing experimental design in disease marker discovery studies.

Main Methods:

  • Development of a sample size calculation protocol based on a linear mixed-effects model.
  • Utilizing pilot experiments to estimate components of biological and technical variance.
  • Validation of the protocol by comparing results with larger existing studies.

Main Results:

  • The proposed protocol effectively estimates necessary sample sizes for proteomic profiling studies.
  • Pilot experiments provide reliable variance estimates for sample size calculations.
  • Calculations are sensitive to specific sample types and preparation methods, necessitating tailored approaches.

Conclusions:

  • Implementing sample size calculations is essential for the validity of MS-based proteomic profiling studies.
  • A linear mixed-effects model approach effectively accounts for inherent experimental variations.
  • Future proteomic studies should incorporate sample- and preparation-specific sample size calculations for enhanced reliability and reproducibility.