Cargando…

A statistical framework for analyzing hypothesized interactions between cells imaged using multispectral microscopy and multiple immunohistochemical markers

BACKGROUND: Multispectral microscopy and multiple staining can be used to identify cells with distinct immunohistochemical (IHC) characteristics. We present here a method called hypothesized interaction distribution (HID) analysis for characterizing the statistical distribution of pair-wise spatial...

Descripción completa

Detalles Bibliográficos
Autores principales: Rose, Chris J., Naidoo, Khimara, Clay, Vanessa, Linton, Kim, Radford, John A., Byers, Richard J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3678742/
https://www.ncbi.nlm.nih.gov/pubmed/23766940
http://dx.doi.org/10.4103/2153-3539.109856
_version_ 1782272893291331584
author Rose, Chris J.
Naidoo, Khimara
Clay, Vanessa
Linton, Kim
Radford, John A.
Byers, Richard J.
author_facet Rose, Chris J.
Naidoo, Khimara
Clay, Vanessa
Linton, Kim
Radford, John A.
Byers, Richard J.
author_sort Rose, Chris J.
collection PubMed
description BACKGROUND: Multispectral microscopy and multiple staining can be used to identify cells with distinct immunohistochemical (IHC) characteristics. We present here a method called hypothesized interaction distribution (HID) analysis for characterizing the statistical distribution of pair-wise spatial relationships between cells with particular IHC characteristics and apply it to clinical data. MATERIALS AND METHODS: We retrospectively analyzed data from a study of 26 follicular lymphoma patients in which sections were stained for CD20 and YY1. HID analysis, using leave-one-out validation, was used to assign patients to one of two groups. We tested the null hypothesis of no difference in Kaplan–Meier survival curves between the groups. RESULTS: Shannon entropy of HIDs assigned patients to groups that had significantly different survival curves (median survival was 7.70 versus 110 months, P = 0.00750). Hypothesized interactions between pairs of cells positive for both CD20 and YY1 were associated with poor survival. CONCLUSIONS: HID analysis provides quantitative inferences about possible interactions between spatially proximal cells with particular IHC characteristics. In follicular lymphoma, HID analysis was able to distinguish between patients with poor versus good survival, and it may have diagnostic and prognostic utility in this and other diseases.
format Online
Article
Text
id pubmed-3678742
institution National Center for Biotechnology Information
language English
publishDate 2013
publisher Medknow Publications & Media Pvt Ltd
record_format MEDLINE/PubMed
spelling pubmed-36787422013-06-13 A statistical framework for analyzing hypothesized interactions between cells imaged using multispectral microscopy and multiple immunohistochemical markers Rose, Chris J. Naidoo, Khimara Clay, Vanessa Linton, Kim Radford, John A. Byers, Richard J. J Pathol Inform Symposium - Original Research BACKGROUND: Multispectral microscopy and multiple staining can be used to identify cells with distinct immunohistochemical (IHC) characteristics. We present here a method called hypothesized interaction distribution (HID) analysis for characterizing the statistical distribution of pair-wise spatial relationships between cells with particular IHC characteristics and apply it to clinical data. MATERIALS AND METHODS: We retrospectively analyzed data from a study of 26 follicular lymphoma patients in which sections were stained for CD20 and YY1. HID analysis, using leave-one-out validation, was used to assign patients to one of two groups. We tested the null hypothesis of no difference in Kaplan–Meier survival curves between the groups. RESULTS: Shannon entropy of HIDs assigned patients to groups that had significantly different survival curves (median survival was 7.70 versus 110 months, P = 0.00750). Hypothesized interactions between pairs of cells positive for both CD20 and YY1 were associated with poor survival. CONCLUSIONS: HID analysis provides quantitative inferences about possible interactions between spatially proximal cells with particular IHC characteristics. In follicular lymphoma, HID analysis was able to distinguish between patients with poor versus good survival, and it may have diagnostic and prognostic utility in this and other diseases. Medknow Publications & Media Pvt Ltd 2013-03-30 /pmc/articles/PMC3678742/ /pubmed/23766940 http://dx.doi.org/10.4103/2153-3539.109856 Text en Copyright: © 2013 Rose CJ. http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Symposium - Original Research
Rose, Chris J.
Naidoo, Khimara
Clay, Vanessa
Linton, Kim
Radford, John A.
Byers, Richard J.
A statistical framework for analyzing hypothesized interactions between cells imaged using multispectral microscopy and multiple immunohistochemical markers
title A statistical framework for analyzing hypothesized interactions between cells imaged using multispectral microscopy and multiple immunohistochemical markers
title_full A statistical framework for analyzing hypothesized interactions between cells imaged using multispectral microscopy and multiple immunohistochemical markers
title_fullStr A statistical framework for analyzing hypothesized interactions between cells imaged using multispectral microscopy and multiple immunohistochemical markers
title_full_unstemmed A statistical framework for analyzing hypothesized interactions between cells imaged using multispectral microscopy and multiple immunohistochemical markers
title_short A statistical framework for analyzing hypothesized interactions between cells imaged using multispectral microscopy and multiple immunohistochemical markers
title_sort statistical framework for analyzing hypothesized interactions between cells imaged using multispectral microscopy and multiple immunohistochemical markers
topic Symposium - Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3678742/
https://www.ncbi.nlm.nih.gov/pubmed/23766940
http://dx.doi.org/10.4103/2153-3539.109856
work_keys_str_mv AT rosechrisj astatisticalframeworkforanalyzinghypothesizedinteractionsbetweencellsimagedusingmultispectralmicroscopyandmultipleimmunohistochemicalmarkers
AT naidookhimara astatisticalframeworkforanalyzinghypothesizedinteractionsbetweencellsimagedusingmultispectralmicroscopyandmultipleimmunohistochemicalmarkers
AT clayvanessa astatisticalframeworkforanalyzinghypothesizedinteractionsbetweencellsimagedusingmultispectralmicroscopyandmultipleimmunohistochemicalmarkers
AT lintonkim astatisticalframeworkforanalyzinghypothesizedinteractionsbetweencellsimagedusingmultispectralmicroscopyandmultipleimmunohistochemicalmarkers
AT radfordjohna astatisticalframeworkforanalyzinghypothesizedinteractionsbetweencellsimagedusingmultispectralmicroscopyandmultipleimmunohistochemicalmarkers
AT byersrichardj astatisticalframeworkforanalyzinghypothesizedinteractionsbetweencellsimagedusingmultispectralmicroscopyandmultipleimmunohistochemicalmarkers
AT rosechrisj statisticalframeworkforanalyzinghypothesizedinteractionsbetweencellsimagedusingmultispectralmicroscopyandmultipleimmunohistochemicalmarkers
AT naidookhimara statisticalframeworkforanalyzinghypothesizedinteractionsbetweencellsimagedusingmultispectralmicroscopyandmultipleimmunohistochemicalmarkers
AT clayvanessa statisticalframeworkforanalyzinghypothesizedinteractionsbetweencellsimagedusingmultispectralmicroscopyandmultipleimmunohistochemicalmarkers
AT lintonkim statisticalframeworkforanalyzinghypothesizedinteractionsbetweencellsimagedusingmultispectralmicroscopyandmultipleimmunohistochemicalmarkers
AT radfordjohna statisticalframeworkforanalyzinghypothesizedinteractionsbetweencellsimagedusingmultispectralmicroscopyandmultipleimmunohistochemicalmarkers
AT byersrichardj statisticalframeworkforanalyzinghypothesizedinteractionsbetweencellsimagedusingmultispectralmicroscopyandmultipleimmunohistochemicalmarkers