Statistical analysis of single-cell protein data
Immune modulation is considered a hallmark of cancer initiation and progression, with immune cell density being consistently associated with clinical outcomes of individuals with cancer. Multiplex immunofluorescence (mIF) microscopy combined with automated image analysis is a novel and increasingly used technique that allows for the assessment and visualization of the tumor microenvironment (TME). Recently, application of this new technology to tissue microarrays (TMAs) or whole tissue sections from large cancer studies has been used to characterize different cell populations in the TME with enhanced reproducibility and accuracy. Generally, mIF data has been used to examine the presence and abundance of immune cells in the tumor and stroma compartments; however, this aggregate measure assumes uniform patterns of immune cells throughout the TME and overlooks spatial heterogeneity. Recently, the spatial contexture of the TME has been explored with a variety of statistical methods. In this PSB workshop, speakers will present some of the state-of-the-art statistical methods for assessing the TIME from mIF data.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:29 |
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| Enthalten in: |
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing - 29(2024) vom: 31., Seite 654-660 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Fridley, Brooke L [VerfasserIn] |
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| Themen: |
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| Anmerkungen: |
Date Completed 03.01.2024 Date Revised 03.01.2024 published: Print Citation Status MEDLINE |
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| Förderinstitution / Projekttitel: |
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NLM366509535 |
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| 520 | |a Immune modulation is considered a hallmark of cancer initiation and progression, with immune cell density being consistently associated with clinical outcomes of individuals with cancer. Multiplex immunofluorescence (mIF) microscopy combined with automated image analysis is a novel and increasingly used technique that allows for the assessment and visualization of the tumor microenvironment (TME). Recently, application of this new technology to tissue microarrays (TMAs) or whole tissue sections from large cancer studies has been used to characterize different cell populations in the TME with enhanced reproducibility and accuracy. Generally, mIF data has been used to examine the presence and abundance of immune cells in the tumor and stroma compartments; however, this aggregate measure assumes uniform patterns of immune cells throughout the TME and overlooks spatial heterogeneity. Recently, the spatial contexture of the TME has been explored with a variety of statistical methods. In this PSB workshop, speakers will present some of the state-of-the-art statistical methods for assessing the TIME from mIF data | ||
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| 700 | 1 | |a Chervoneva, Inna |e verfasserin |4 aut | |
| 700 | 1 | |a Wrobel, Julia |e verfasserin |4 aut | |
| 700 | 1 | |a Ma, Siyuan |e verfasserin |4 aut | |
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