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Challenges and Opportunities in the Statistical Analysis of Multiplex Immunofluorescence Data.

Publication ,  Journal Article
Wilson, CM; Ospina, OE; Townsend, MK; Nguyen, J; Moran Segura, C; Schildkraut, JM; Tworoger, SS; Peres, LC; Fridley, BL
Published in: Cancers (Basel)
June 17, 2021

Immune modulation is considered a hallmark of cancer initiation and progression. The recent development of immunotherapies has ushered in a new era of cancer treatment. These therapeutics have led to revolutionary breakthroughs; however, the efficacy of immunotherapy has been modest and is often restricted to a subset of patients. Hence, identification of which cancer patients will benefit from immunotherapy is essential. Multiplex immunofluorescence (mIF) microscopy allows for the assessment and visualization of the tumor immune microenvironment (TIME). The data output following image and machine learning analyses for cell segmenting and phenotyping consists of the following information for each tumor sample: the number of positive cells for each marker and phenotype(s) of interest, number of total cells, percent of positive cells for each marker, and spatial locations for all measured cells. There are many challenges in the analysis of mIF data, including many tissue samples with zero positive cells or "zero-inflated" data, repeated measurements from multiple TMA cores or tissue slides per subject, and spatial analyses to determine the level of clustering and co-localization between the cell types in the TIME. In this review paper, we will discuss the challenges in the statistical analysis of mIF data and opportunities for further research.

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Published In

Cancers (Basel)

DOI

ISSN

2072-6694

Publication Date

June 17, 2021

Volume

13

Issue

12

Location

Switzerland

Related Subject Headings

  • 3211 Oncology and carcinogenesis
  • 1112 Oncology and Carcinogenesis
 

Citation

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Wilson, C. M., Ospina, O. E., Townsend, M. K., Nguyen, J., Moran Segura, C., Schildkraut, J. M., … Fridley, B. L. (2021). Challenges and Opportunities in the Statistical Analysis of Multiplex Immunofluorescence Data. Cancers (Basel), 13(12). https://doi.org/10.3390/cancers13123031
Wilson, Christopher M., Oscar E. Ospina, Mary K. Townsend, Jonathan Nguyen, Carlos Moran Segura, Joellen M. Schildkraut, Shelley S. Tworoger, Lauren C. Peres, and Brooke L. Fridley. “Challenges and Opportunities in the Statistical Analysis of Multiplex Immunofluorescence Data.Cancers (Basel) 13, no. 12 (June 17, 2021). https://doi.org/10.3390/cancers13123031.
Wilson CM, Ospina OE, Townsend MK, Nguyen J, Moran Segura C, Schildkraut JM, et al. Challenges and Opportunities in the Statistical Analysis of Multiplex Immunofluorescence Data. Cancers (Basel). 2021 Jun 17;13(12).
Wilson, Christopher M., et al. “Challenges and Opportunities in the Statistical Analysis of Multiplex Immunofluorescence Data.Cancers (Basel), vol. 13, no. 12, June 2021. Pubmed, doi:10.3390/cancers13123031.
Wilson CM, Ospina OE, Townsend MK, Nguyen J, Moran Segura C, Schildkraut JM, Tworoger SS, Peres LC, Fridley BL. Challenges and Opportunities in the Statistical Analysis of Multiplex Immunofluorescence Data. Cancers (Basel). 2021 Jun 17;13(12).

Published In

Cancers (Basel)

DOI

ISSN

2072-6694

Publication Date

June 17, 2021

Volume

13

Issue

12

Location

Switzerland

Related Subject Headings

  • 3211 Oncology and carcinogenesis
  • 1112 Oncology and Carcinogenesis