Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell Carcinoma

Ji, Andrew L.; Rubin, Adam J.; Thrane, Kim; Jiang, Sizun; Reynolds, David L.; Meyers, Robin M.; Guo, Margaret; George, Benson M.; Mollbrink, Annelie; Bergenstråhle, Joseph; Larsson, Ludvig; Bai, Yunhao; Zhu, Bokai; Bhaduri, Aparna; Meyers, Jordan M.; Rovira-Clavé, Xavier; Hollmig, S. Tyler; Aasi, Sumaira Z.; Nolan, Garry P.; Lundeberg, Joakim; Khavari, Paul A.

doi:10.1016/j.cell.2020.08.043

Cited by 218 publications

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“…This panel allows the composition, location, and cellular state (e.g., proliferation or cytotoxicity) of TME components to be assessed relative to the expression of trial-targeted immunoregulatory proteins on immune and tumor cells. Since the CODEX antibody conjugation method is similar to that of other multiplexed imaging platforms, it is likely that the panel described here will be compatible with MIBI (25,26), IMC (22) included in this CODEX panel have been utilized in prior MIBI studies (26)(27)(28). While slight modifications to the antibody dilutions may be required when applying this panel across platforms (i.e., to account for small alterations in signal-tonoise ratios stemming from the mode of antibody detection: oligonucleotides in CODEX versus metals in MIBI and IMC), working knowledge of this panel will save considerable time, effort, and resources for researchers interested in studying the TME and immunotherapy responsiveness with multiplexed tissue imaging approaches.…”

Section: Discussionmentioning

confidence: 99%

“…It also includes eight immunoregulatory proteins-ICOS, IDO-1, LAG-3, PD-1, PD-L1, OX40, Tim-3, and VISTA-to simultaneously phenotype, localize, and quantify these functional molecules on individual cells within the TME, adding important insights to the field of cancer immunotherapy. This work serves as a blueprint for customizing CODEX antibody panels and provides researchers and clinicians with a working antibody panel for highdimensional characterization of the TME, with broad adaptability to different malignancies of interest or alternative imaging platforms, such as Imaging Mass Cytometry (IMC) (22)(23)(24), Multiplexed Ion Beam Imaging (MIBI) (25)(26)(27)(28), and tissue-based cyclic immunofluorescence (t-CyCIF) (29).…”

Section: Introductionmentioning

confidence: 99%

“…Marker selection was based on 1) in-house testing of antibody performance in IHC and FFPE-CODEX(16,18,19), 2) IHC experience in clinical pathology laboratories, 3) commercially available fluorophore-conjugated antibodies that either in their conjugated or unconjugated forms work in IHC, 4) IHC and FFPE multiplexed tissue imaging publications, and 5) online databases like The Human Protein Atlas (www.proteinatlas.org)(31). Notably, 51 of the 56 antibodies in this panel have been used in other multiplexed imaging studies (Supplementary Table2)(16,18,23,24,(26)(27)(28)(29). These 51 antibodies were studied in different tissues (e.g., tonsil, breast cancer, colon cancer, pancreatic cancer, squamous cell carcinoma, etc.…”

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confidence: 99%

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Highly Multiplexed Phenotyping of Immunoregulatory Proteins in the Tumor Microenvironment by CODEX Tissue Imaging

et al. 2021

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Immunotherapies are revolutionizing cancer treatment by boosting the natural ability of the immune system. In addition to antibodies against traditional checkpoint molecules or their ligands (i.e., CTLA-4, PD-1, and PD-L1), therapies targeting molecules such as ICOS, IDO-1, LAG-3, OX40, TIM-3, and VISTA are currently in clinical trials. To better inform clinical care and the design of therapeutic combination strategies, the co-expression of immunoregulatory proteins on individual immune cells within the tumor microenvironment must be robustly characterized. Highly multiplexed tissue imaging platforms, such as CO-Detection by indEXing (CODEX), are primed to meet this need by enabling >50 markers to be simultaneously analyzed in single-cells on formalin-fixed paraffin-embedded (FFPE) tissue sections. Assembly and validation of antibody panels is particularly challenging, with respect to the specificity of antigen detection and robustness of signal over background. Herein, we report the design, development, optimization, and application of a 56-marker CODEX antibody panel to eight cutaneous T cell lymphoma (CTCL) patient samples. This panel is comprised of structural, tumor, and immune cell markers, including eight immunoregulatory proteins that are approved or currently undergoing clinical trials as immunotherapy targets. Here we provide a resource to enable extensive high-dimensional, spatially resolved characterization of the tissue microenvironment across tumor types and imaging modalities. This framework provides researchers with a readily applicable blueprint to study tumor immunology, tissue architecture, and enable mechanistic insights into immunotherapeutic targets.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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Highly Multiplexed Phenotyping of Immunoregulatory Proteins in the Tumor Microenvironment by CODEX Tissue Imaging

et al. 2021

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“…Through this method, our group has been able to study the alterations that occur during cancer initiation and progression, as well as identify potential biomarkers that may be relevant for tumor development. Recently, a study published by Ji et al identified four tumor subpopulations within cSCC, with one population composed of tumor-specific keratinocytes unique to cancer [ 28 ]. A comparison of differential expression analyses between tumor-specific keratinocytes and RDEB-cSCC-iKC may provide more insight on the utility and validity of the iKC model.…”

Section: Discussionmentioning

confidence: 99%

Reprogramming and Differentiation of Cutaneous Squamous Cell Carcinoma Cells in Recessive Dystrophic Epidermolysis Bullosa

Rami

Łaczmański

Jacków-Nowicka

et al. 2020

IJMS

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The early onset and rapid progression of cutaneous squamous cell carcinoma (cSCC) leads to high mortality rates in individuals with recessive dystrophic epidermolysis bullosa (RDEB). Currently, the molecular mechanisms underlying cSCC development in RDEB are not well understood and there are limited therapeutic options. RDEB-cSCC arises through the accumulation of genetic mutations; however, previous work analyzing gene expression profiles have not been able to explain its aggressive nature. Therefore, we generated a model to study RDEB-cSCC development using cellular reprograming and re-differentiation technology. We compared RDEB-cSCC to cSCC that were first reprogrammed into induced pluripotent stem cells (RDEB-cSCC-iPSC) and then differentiated back to keratinocytes (RDEB-cSCC-iKC). The RDEB-cSCC-iKC cell population had reduced proliferative capacities in vitro and in vivo, suggesting that reprogramming and re-differentiation leads to functional changes. Finally, we performed RNA-seq analysis for RDEB-cSCC, RDEB-cSCC-iPSC, and RDEB-cSCC-iKC and identified different gene expression signatures between these cell populations. Taken together, this cell culture model offers a valuable tool to study cSCC and provides a novel way to identify potential therapeutic targets for RDEB-cSCC.

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“…The 10X Genomics Visium technology has been applied to skin squamous cells carcinoma (196). The authors identified multiple cells responsible for immunosuppressive functions in dendritic cells, exhausted T cells and Tregs, refining local tumor structures.…”

Section: Spatial Genomicsmentioning

confidence: 99%

Cutaneous Melanoma Classification: The Importance of High-Throughput Genomic Technologies

Scatena

Murtas

Tomei³

2021

Front. Oncol.

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Cutaneous melanoma is an aggressive tumor responsible for 90% of mortality related to skin cancer. In the recent years, the discovery of driving mutations in melanoma has led to better treatment approaches. The last decade has seen a genomic revolution in the field of cancer. Such genomic revolution has led to the production of an unprecedented mole of data. High-throughput genomic technologies have facilitated the genomic, transcriptomic and epigenomic profiling of several cancers, including melanoma. Nevertheless, there are a number of newer genomic technologies that have not yet been employed in large studies. In this article we describe the current classification of cutaneous melanoma, we review the current knowledge of the main genetic alterations of cutaneous melanoma and their related impact on targeted therapies, and we describe the most recent high-throughput genomic technologies, highlighting their advantages and disadvantages. We hope that the current review will also help scientists to identify the most suitable technology to address melanoma-related relevant questions. The translation of this knowledge and all actual advancements into the clinical practice will be helpful in better defining the different molecular subsets of melanoma patients and provide new tools to address relevant questions on disease management. Genomic technologies might indeed allow to better predict the biological - and, subsequently, clinical - behavior for each subset of melanoma patients as well as to even identify all molecular changes in tumor cell populations during disease evolution toward a real achievement of a personalized medicine.

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Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell Carcinoma

Cited by 218 publications

References 0 publications

Highly Multiplexed Phenotyping of Immunoregulatory Proteins in the Tumor Microenvironment by CODEX Tissue Imaging

Highly Multiplexed Phenotyping of Immunoregulatory Proteins in the Tumor Microenvironment by CODEX Tissue Imaging

Reprogramming and Differentiation of Cutaneous Squamous Cell Carcinoma Cells in Recessive Dystrophic Epidermolysis Bullosa

Cutaneous Melanoma Classification: The Importance of High-Throughput Genomic Technologies

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