Immunogenomic profile of colorectal cancer response to immune checkpoint blockade

Bortolomeazzi, Michele; Keddar, Mohamed Reda; Montorsi, Lucia; Acha-Sagredo, Amelia; Benedetti, Lorena; Temelkovski, Damjan; Choi, Subin; Petrov, Nedyalko; Todd, Katrina; Wai, Patty T.; Kohl, Jonny; Denner, Tamara; Nye, Emma; Goldstone, Robert; Ward, Sophia; Wilson, Gareth A.; Bakir, Maise Al; Swanton, Charles; John, Susan; Miles, James; Larijani, Banafshé; Kunene, Victoria; Fontana, Elisa; Arkenau, Hendrik‐Tobias; Parker, Peter J.; Rodriguez‐Justo, Manuel; Shiu, Kai-Keen; Spencer, Jo; Ciccarelli, Francesca D.

doi:10.1101/2020.12.15.422831

Cited by 2 publications

(2 citation statements)

References 51 publications

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“…Bortolomeazzi et al. used IMC in colorectal cancer samples and highlighted that hypermutated colorectal cancers with responses to anti-PD-1 ICI contained high levels of cytotoxic and proliferating CD8+PD-1+ T cells with high interactions with PD-L1+ antigen presenting macrophages ( 43 ).…”

Section: Applications Of Imaging Mass Cytometry In Cancer-dedicated S...mentioning

confidence: 99%

Application of High-Throughput Imaging Mass Cytometry Hyperion in Cancer Research

Rochais

Hémon²,

Pers³

et al. 2022

Front. Immunol.

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Imaging mass cytometry (IMC) enables the in situ analysis of in-depth-phenotyped cells in their native microenvironment within the preserved architecture of a single tissue section. To date, it permits the simultaneous analysis of up to 50 different protein- markers targeted by metal-conjugated antibodies. The application of IMC in the field of cancer research may notably help 1) to define biomarkers of prognostic and theragnostic significance for current and future treatments against well-established and novel therapeutic targets and 2) to improve our understanding of cancer progression and its resistance mechanisms to immune system and how to overcome them. In the present article, we not only provide a literature review on the use of the IMC in cancer-dedicated studies but we also present the IMC method and discuss its advantages and limitations among methods dedicated to deciphering the complexity of cancer tissue.

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Section: Applications Of Imaging Mass Cytometry In Cancer-dedicated S...mentioning

confidence: 99%

Application of High-Throughput Imaging Mass Cytometry Hyperion in Cancer Research

Rochais

Hémon²,

Pers³

et al. 2022

Front. Immunol.

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“…For instance, (Damond et al 2019) used IMC to analyse and characterise the pathogenesis and progression of Type 1 Diabetes in human patients. While (M Bortolomeazzi, Keddar, and Montorsi 2020…”

Section: Introductionmentioning

confidence: 99%

Rarity: Discovering rare cell populations from single-cell imaging data

Marten

Bortolomeazzi

Montorsi

et al. 2022

Preprint

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Background: Cell type identification plays an important role in the analysis and interpretation of single-cell data and can be carried out via supervised or unsupervised clustering approaches. Supervised methods are best suited where we can list all cell types and their respective marker genes a priori. While unsupervised clustering algorithms look for groups of cells with similar expression properties. This property permits the identification of both known and unknown cell populations, making unsupervised methods suitable for discovery.. Success is dependent on the relative strength of the expression signature of each group as well as the number of cells. Rare cell types therefore present a particular challenge that are magnified when they are defined by differentially expressing a small number of genes. Typical unsupervised approaches fail to identify such rare subpopulations, and these cells tend to be absorbed into more prevalent cell types. Results: In order to balance these competing demands, we have developed a novel statistical framework for unsupervised clustering, named Rarity, that enables the discovery process for rare cell types to be more robust, consistent and interpretable. We achieve this by devising a novel clustering method based on a Bayesian latent variable model in which we assign cells to inferred latent binary on/off expression profiles. This lets us achieve increased sensitivity to rare cell populations while also allowing us to control and interpret potential false positive discoveries. Conclusions: We systematically study the challenges associated with rare cell type identification and demonstrate the utility of Rarity on various IMC data sets.

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Immunogenomic profile of colorectal cancer response to immune checkpoint blockade

Cited by 2 publications

References 51 publications

Application of High-Throughput Imaging Mass Cytometry Hyperion in Cancer Research

Application of High-Throughput Imaging Mass Cytometry Hyperion in Cancer Research

Rarity: Discovering rare cell populations from single-cell imaging data

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