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Challenges and Opportunities in the Statistical Analysis of Multiplex Immunofluorescence Data

1
Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL 33612, USA
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Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL 33612, USA
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Department of Pathology, Moffitt Cancer Center, Tampa, FL 33612, USA
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Department of Epidemiology, Emory University, Atlanta, GA 30322, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Ewan Millar
Cancers 2021, 13(12), 3031; https://doi.org/10.3390/cancers13123031
Received: 14 May 2021 / Revised: 11 June 2021 / Accepted: 14 June 2021 / Published: 17 June 2021
Immune modulation is considered a hallmark of cancer initiation and progression, and has offered promising opportunities for therapeutic manipulation. Multiplex immunofluorescence (mIF) technology has enabled the tumor immune microenvironment (TIME) to be studied at an increased scale, in terms of both the number of markers and the number of samples. Another benefit of mIF technology is the ability to measure not only the abundance but also the spatial location of multiple cells types within a tissue sample simultaneously, allowing for assessment of the co-localization of different types of immune markers. Thus, the use of mIF technologies have enable researchers to characterize patient, clinical, and tumor characteristics in the hope of identifying patients whom might benefit from immunotherapy treatments. In this review we outline some of the challenges and opportunities in the statistical analyses of mIF data to study the TIME.
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. View Full-Text
Keywords: digital pathology; cancer; tumor immune microenvironment; data science digital pathology; cancer; tumor immune microenvironment; data science
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MDPI and ACS Style

Wilson, C.M.; Ospina, O.E.; Townsend, M.K.; Nguyen, J.; Moran Segura, C.; Schildkraut, J.M.; Tworoger, S.S.; Peres, L.C.; Fridley, B.L. Challenges and Opportunities in the Statistical Analysis of Multiplex Immunofluorescence Data. Cancers 2021, 13, 3031. https://doi.org/10.3390/cancers13123031

AMA Style

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. 2021; 13(12):3031. https://doi.org/10.3390/cancers13123031

Chicago/Turabian Style

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 2021. "Challenges and Opportunities in the Statistical Analysis of Multiplex Immunofluorescence Data" Cancers 13, no. 12: 3031. https://doi.org/10.3390/cancers13123031

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