Stromal Expression Profiling Reveals Immune-Driven Adaption to Malignancy in Canine Melanoma Subtypes.
RNA sequencing
cancer‐associated stroma
canine melanoma
comparative oncology
laser‐capture microdissection
Journal
Veterinary and comparative oncology
ISSN: 1476-5829
Titre abrégé: Vet Comp Oncol
Pays: England
ID NLM: 101185242
Informations de publication
Date de publication:
17 Oct 2024
17 Oct 2024
Historique:
revised:
03
10
2024
received:
27
05
2024
accepted:
04
10
2024
medline:
18
10
2024
pubmed:
18
10
2024
entrez:
18
10
2024
Statut:
aheadofprint
Résumé
Canine mucosal melanoma (CMM) is the most common oral malignancy in dogs and is significantly more aggressive than its cutaneous counterpart (CCM), yet the reasons for this disparity remain unclear. Cancer-associated stroma (CAS) plays a crucial role in tumour progression, but a detailed understanding of CAS in canine melanoma is missing. To assess stromal reprogramming, we analysed CAS from 21 CMM, 14 CCM and normal stroma from 10 skin and 9 oral mucosa samples by laser-capture microdissection followed by RNA sequencing. Results were assessed in relation to subtypes, prognostic factors including mitotic count (MC), ulceration, necrosis, pigmentation and immune cell infiltration (CD3, CD20 and CD68), scored using immunohistochemistry and RNA in situ hybridisation. Stromal reprogramming was evident in both subtypes but significantly more pronounced in CMM. Immune-excluded tumours exhibited higher MC than desert/cold ones. MC strongly correlated with genes associated with B-cells, T-helper cells and CTLA4 in CCM, suggesting CAS reprogramming to depend on tumour malignancy. Finally, we identify an immune-suppressive stromal signature in a subset of CMM characterised by the downregulation of key immune checkpoints and pathways. Together, these findings provide a solid foundation for understanding the role of CAS in canine melanoma, specific to cutaneous and mucosal subtypes.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Edoardo R., Giovanni, Giuseppe und Chiarina Sassella-Stiftung
Organisme : Kurt und Senta Herrmann Stiftung
Organisme : Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
Informations de copyright
© 2024 The Author(s). Veterinary and Comparative Oncology published by John Wiley & Sons Ltd.
Références
A. Prouteau and C. André, “Canine Melanomas as Models for Human Melanomas: Clinical, Histological, and Genetic Comparison,” Genes (Basel) 10, no. 7 (2019): 501.
R. C. Smedley, W. L. Spangler, D. G. Esplin, et al., “Prognostic Markers for Canine Melanocytic Neoplasms: A Comparative Review of the Literature and Goals for Future Investigation,” Veterinary Pathology 48, no. 1 (2011): 54–72.
T. Laver, B. R. Feldhaeusser, C. S. Robat, et al., “Post‐Surgical Outcome and Prognostic Factors in Canine Malignant Melanomas of the Haired Skin: 87 Cases (2003–2015),” Canadian Veterinary Journal 59, no. 9 (2018): 981–987.
T. F. Teixeira, L. B. Gentile, T. C. Da Silva, et al., “Cell Proliferation and Expression of Connexins Differ in Melanotic and Amelanotic Canine Oral Melanomas,” Veterinary Research Communications 38, no. 1 (2014): 29–38.
R. C. Smedley, K. Sebastian, and M. Kiupel, “Diagnosis and Prognosis of Canine Melanocytic Neoplasms,” Veterinary Sciences 9, no. 4 (2022): 175.
K. Pietras and A. Östman, “Hallmarks of Cancer: Interactions With the Tumor Stroma,” Experimental Cell Research 316, no. 8 (2010): 1324–1331.
L. Ying, F. Yan, and D. Xu, “Cancer Patient Stratification Based on the Tumor Microenvironment,” Journal of Thoracic Disease 12, no. 8 (2020): 4522–4526.
J. Galon and D. Bruni, “Approaches to Treat Immune Hot, Altered and Cold Tumours With Combination Immunotherapies,” Nature Reviews Drug Discovery 18, no. 3 (2019): 197–218.
J. Pape, T. Magdeldin, K. Stamati, et al., “Cancer‐Associated Fibroblasts Mediate Cancer Progression and Remodel the Tumouroid Stroma,” British Journal of Cancer 123, no. 7 (2020): 1178–1190.
I. Porcellato, S. Silvestri, L. Menchetti, et al., “Tumour‐Infiltrating Lymphocytes in Canine Melanocytic Tumours: An Investigation on the Prognostic Role of CD3+ and CD20+ Lymphocytic Populations,” Veterinary and Comparative Oncology 18, no. 3 (2020): 370–380.
I. Porcellato, M. Sforna, A. Lo Giudice, et al., “Tumor‐Associated Macrophages in Canine Oral and Cutaneous Melanomas and Melanocytomas: Phenotypic and Prognostic Assessment,” Frontiers in Veterinary Science 9 (2022): 878949.
V. B. Stevenson, S. N. Perry, M. Todd, W. R. Huckle, and T. LeRoith, “PD‐1, PD‐L1, and PD‐L2 Gene Expression and Tumor Infiltrating Lymphocytes in Canine Melanoma,” Veterinary Pathology 58, no. 4 (2021): 692–698.
A. Prouteau, S. Mottier, A. Primot, et al., “Canine Oral Melanoma Genomic and Transcriptomic Study Defines Two Molecular Subgroups With Different Therapeutical Targets,” Cancers (Basel) 14, no. 2 (2022): 276.
K. Wong, L. van der Weyden, C. R. Schott, et al., “Cross‐Species Genomic Landscape Comparison of Human Mucosal Melanoma With Canine Oral and Equine Melanoma,” Nature Communications 10, no. 1 (2019): 353.
M. Gillard, E. Cadieu, C. De Brito, et al., “Naturally Occurring Melanomas in Dogs as Models for Non‐UV Pathways of Human Melanomas,” Pigment Cell and Melanoma Research 27, no. 1 (2014): 90–102.
C. Brachelente, K. Cappelli, S. Capomaccio, et al., “Transcriptome Analysis of Canine Cutaneous Melanoma and Melanocytoma Reveals a Modulation of Genes Regulating Extracellular Matrix Metabolism and Cell Cycle,” Scientific Reports 7, no. 1 (2017): 6386.
F. Guscetti, S. Nassiri, E. Beebe, I. Rito Brandao, R. Graf, and E. Markkanen, “Molecular Homology Between Canine Spontaneous Oral Squamous Cell Carcinomas and Human Head‐and‐Neck Squamous Cell Carcinomas Reveals Disease Drivers and Therapeutic Vulnerabilities,” Neoplasia 22, no. 12 (2020): 778–788.
A. Pöschel, E. Beebe, L. Kunz, et al., “Identification of Disease‐Promoting Stromal Components by Comparative Proteomic and Transcriptomic Profiling of Canine Mammary Tumors Using Laser‐Capture Microdissected FFPE Tissue,” Neoplasia 23, no. 4 (2021): 400–412.
E. Beebe, Z. Motamed, L. Opitz, et al., “Defining the Molecular Landscape of Cancer‐Associated Stroma in Cutaneous Squamous Cell Carcinoma,” Journal of Investigative Dermatology 142, no. 12 (2022): 3304–3312.
P. Amini, S. Nassiri, A. Malbon, and E. Markkanen, “Differential Stromal Reprogramming in Benign and Malignant Naturally Occurring Canine Mammary Tumours Identifies Disease‐Modulating Stromal Components,” Scientific Reports 10, no. 1 (2020): 1–13.
P. Amini, S. Nassiri, J. Ettlin, A. Malbon, and E. Markkanen, “Next‐Generation RNA Sequencing of FFPE Subsections Reveals Highly Conserved Stromal Reprogramming Between Canine and Human Mammary Carcinoma,” Disease Models and Mechanisms 12, no. 8 (2019): dmm040444.
J. Ettlin, A. Bauer, L. Opitz, A. Malbon, and E. Markkanen, “Deciphering Stromal Changes Between Metastatic and Non‐metastatic Canine Mammary Carcinomas,” Journal of Mammary Gland Biology and Neoplasia 28, no. 1 (2023): 1–16.
P. Amini, J. Ettlin, L. Opitz, E. Clementi, A. Malbon, and E. Markkanen, “An Optimised Protocol for Isolation of RNA From Small Sections of Laser‐Capture Microdissected FFPE Tissue Amenable for Next‐Generation Sequencing,” BMC Molecular Biology 18, no. 1 (2017): 22.
J. Ettlin, E. Clementi, P. Amini, A. Malbon, and E. Markkanen, “Analysis of Gene Expression Signatures in Cancer‐Associated Stroma From Canine Mammary Tumours Reveals Molecular Homology to Human Breast Carcinomas,” International Journal of Molecular Sciences 18, no. 5 (2017): 1101.
N. L. Bray, H. Pimentel, P. Melsted, and L. Pachter, “Near‐Optimal Probabilistic RNA‐Seq Quantification,” Nature Biotechnology 34, no. 5 (2016): 525–527.
S. Durinck, P. T. Spellman, E. Birney, and W. Huber, “Mapping Identifiers for the Integration of Genomic Datasets With the R/Bioconductor Package BiomaRt,” Nature Protocols 4, no. 8 (2009): 1184–1191.
C. Soneson, M. I. Love, and M. D. Robinson, “Differential Analyses for RNA‐Seq: Transcript‐Level Estimates Improve Gene‐Level Inferences,” F1000Res 4 (2015): 1521.
H. Wickham, Ggplot2: Elegant Graphics for Data Analysis (New York: Springer‐Verlag, 2016).
M. I. Love, W. Huber, and S. Anders, “Moderated Estimation of Fold Change and Dispersion for RNA‐Seq Data With DESeq2,” Genome Biology 15, no. 12 (2014): 550.
A. Subramanian, P. Tamayo, V. K. Mootha, et al., “Gene Set Enrichment Analysis: A Knowledge‐Based Approach for Interpreting Genome‐Wide Expression Profiles,” Proceedings of the National Academy of Sciences of the United States of America 102, no. 43 (2005): 15545–15550.
A. Liberzon, A. Subramanian, R. Pinchback, H. Thorvaldsdóttir, P. Tamayo, and J. P. Mesirov, “Molecular Signatures Database (MSigDB) 3.0,” Bioinformatics 27, no. 12 (2011): 1739–1740.
B. Zhang, S. Kirov, and J. Snoddy, “WebGestalt: An Integrated System for Exploring Gene Sets in Various Biological Contexts,” Nucleic Acids Research 33 (2005): W741–W748.
Z. Gu, R. Eils, and M. Schlesner, “Complex Heatmaps Reveal Patterns and Correlations in Multidimensional Genomic Data,” Bioinformatics 32, no. 18 (2016): 2847–2849.
GitHub ‐ kassambara/ggcorrplot, “Visualization of a Correlation Matrix Using ggplot2,” 2023, https://github.com/kassambara/ggcorrplot.
F. Azimi, R. A. Scolyer, P. Rumcheva, et al., “Tumor‐Infiltrating Lymphocyte Grade is an Independent Predictor of Sentinel Lymph Node Status and Survival in Patients With Cutaneous Melanoma,” Journal of Clinical Oncology 30, no. 21 (2012): 2678–2683.
S. Pisamai, S. W. Edwards, C. W. Cheng, et al., “Tissue Transcriptome Profiling and Pathway Analyses Revealed Novel Potential Biomarkers in the Tumor Progression of Canine Oral Melanoma,” Research in Veterinary Science 165 (2023): 105036.
R. G. Ladstein, I. M. Bachmann, O. Straume, and L. A. Akslen, “Tumor Necrosis is a Prognostic Factor in Thick Cutaneous Melanoma,” American Journal of Surgical Pathology 36, no. 10 (2012): 1477–1482.
X. Shi, S. Xia, Y. Chu, et al., “CARD11 is a Prognostic Biomarker and Correlated With Immune Infiltrates in Uveal Melanoma,” PLoS One 16, no. 8 (2021): e0255293.
R. A. Bartolomé, I. Molina‐Ortiz, R. Samaniego, P. Sánchez‐Mateos, X. R. Bustelo, and J. Teixidó, “Activation of Vav/Rho GTPase Signaling by CXCL12 Controls Membrane‐Type Matrix Metalloproteinase–Dependent Melanoma Cell Invasion,” Cancer Research 66, no. 1 (2006): 248–258.
S. Mei, A. M. Alchahin, I. Tsea, et al., “Single‐Cell Analysis of Immune and Stroma Cell Remodeling in Clear Cell Renal Cell Carcinoma Primary Tumors and Bone Metastatic Lesions,” Genome Medicine 16, no. 1 (2024): 1–21.
A. J. Radtke, E. Postovalova, A. Varlamova, et al., “Multi‐Omic Profiling of Follicular Lymphoma Reveals Changes in Tissue Architecture and Enhanced Stromal Remodeling in High‐Risk Patients,” Cancer Cell 42, no. 3 (2024): 444–463.e10.
S. M. Hossain, G. Gimenez, P. A. Stockwell, et al., “Innate Immune Checkpoint Inhibitor Resistance is Associated With Melanoma Sub‐Types Exhibiting Invasive and De‐Differentiated Gene Expression Signatures,” Frontiers in Immunology 13 (2022): 13.