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Sarcoma ecosystems : spatial characterization and prognostic significance

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posted on 2024-09-03, 03:39 authored by Yanhong SuYanhong Su

Sarcoma is a highly heterogeneous disease with complex biological activities and unique tumor microenvironments (TME) in distinct subtypes. The limited treatment options and inadequate responses to current therapies necessitate a deeper understanding of sarcoma biology and personalized treatment strategies. Our research comprehensively explores the sarcoma TME through advanced spatial analysis and investigates sarcoma's molecular and genetic profiles through transcriptome and genome sequencing.

In paper I, we focused on undifferentiated pleomorphic sarcoma (UPS) using multiplex immunofluorescence (mIF) staining for in-depth spatial analysis of B cell populations and lymphocyte aggregates (LAs). LAs in UPS were found to be associated with longer overall survival (OS) and metastasis-free survival (MFS). Moreover, we unveiled distinct maturation profiles among B cell subsets, indicative of different phenotypes that contribute to functional ecosystems in TME. LA-positive tumors displayed a more well-differentiated B cell profile throughout the entire tumor section, not limited in LA regions. We introduced the B-index, an integrated measurement tool combining B cell abundance and maturity, which demonstrated predictive power for both MFS and OS. Using the TissUUmap tool, we identified B cell desert areas characterized by extremely low B cell infiltration. LA-positive tumors displayed smaller and more fragmented B cell desert areas.

In paper II, we performed double immunohistochemistry to study CD11c-positive antigen-presenting cells (APCs) and CD8- positive cells in 177 soft tissue sarcoma (STS) patients. We found that CD11c-CD8 interactions in the TME were associated with improved MFS and OS. Transcriptomic analysis in The Cancer Genome Atlas (TCGA) sarcoma cohort supported the prognostic significance of combining CD11c with CD8, irrespective of FOXP3 levels and in the presence of CD274 (PD-L1).

In paper III, we conducted transcriptome and targeted DNA sequencing in 91 synovial sarcomas, identifying three distinct Synovial Sarcoma Clusters (SSCs) mirroring histological subtypes. SSC-I was characterized by high cell proliferation and immune evasion with an unfavorable prognosis. SSC-II was dominated by vascularstromal components and correlated with better outcomes. SSC-III displayed biphasic differentiation, genomic complexity, and immune checkpoint-mediated immune suppression, leading to adverse outcomes, even after a good histological response to neoadjuvant treatment.

In paper IV, we analyzed Ewing sarcoma (ES) transcriptome signatures in four previously published cohorts and identified 29 prognostic RNA-binding protein (RBP) genes, from which we constructed and validated an RBP-associated prognostic risk model (RPRM). The RPRM demonstrated stable predictive value for prognosis, with NSUN7 emerging as an independent and favorable prognostic marker.

In summary, our research integrates spatial analysis of the sarcoma TME to identify unique immune features and prognostic markers. Moreover, we use transcriptomic and genomic analyses to categorize specific sarcoma types for more detailed survival stratification. This work provides a deeper insight into the sarcoma TME and suggests an improved grouping strategy, aiming to shape the development of personalized immunotherapy in the future.

List of scientific papers

I. Yanhong Su, Haoyang Mi, Panagiotis Tsagkozis, Lennart Linke, Andri Papakonstantinou, Nicholas P. Tobin, Christina L. Stragliotto, Arne Östman, Aleksander S. Popel, Felix Haglund de Flon and Monika Ehnman. Spatial profiling of B cell ecosystems in undifferentiated pleomorphic sarcoma. [Manuscript]

II. Yanhong Su, Panagiotis Tsagkozis, Andri Papakonstantinou, Nicholas P. Tobin, Okan Gultekin, Anna Malmerfelt, Katrine Ingelshed, Shi Yong Neo, Johanna Lundquist, Wiem Chaabane, Maya H. Nisancioglu, Lina W. Leiss, Arne Östman, Jonas Bergh, Saikiran Sedimbi, Kaisa Lehti, Andreas Lundqvist, Christina L. Stragliotto, Felix Haglund and Monika Ehnman. CD11c-CD8 Spatial Cross Presentation: A Novel Approach to Link Immune Surveillance and Patient Survival in Soft Tissue Sarcoma. Cancers (Basel). 2021 Mar 9;13(5):1175.
https://doi.org/10.3390/cancers13051175

III. Yi Chen, Yanhong Su, Isabelle Rose Leo, Ioannis Siavelis, Jianming Zeng, Xiaofang Cao, Panagiotis Tsagkozis, Asle C Hesla, Andri Papakonstantinou, Xiao Liu, Wen-Kuan Huang, Binbin Zhao, Monika Ehnman, Henrik Johansson, Yingbo Lin, Janne Lehtiö, Yifan Zhang1, Olle Larsson, and Felix Haglund de Flon. Integrative multi-omics analysis reveals molecular subtypes and tumor evolution of synovial sarcoma. [Manuscript]

IV. Yi Chen, Huafang Su, Yanhong Su, Yifan Zhang, Yingbo Lin and Felix Haglund. Identification of an RNA-Binding-Protein-Based Prognostic Model for Ewing Sarcoma. Cancers (Basel). 2021 Jul 25;13(15):3736.
https://doi.org/10.3390/cancers13153736

History

Defence date

2023-12-08

Department

  • Department of Oncology-Pathology

Publisher/Institution

Karolinska Institutet

Main supervisor

Ehnman, Monika

Co-supervisors

Östman, Arne; Haglund de Flon, Felix; Tobin, Nick

Publication year

2023

Thesis type

  • Doctoral thesis

ISBN

978-91-8017-202-8

Number of supporting papers

4

Language

  • eng

Original publication date

2023-11-14

Author name in thesis

Su, Yanhong

Original department name

Department of Oncology-Pathology

Place of publication

Stockholm

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