1
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Tindall RR, Yang Y, Hernandez I, Qin A, Li J, Zhang Y, Gomez TH, Younes M, Shen Q, Bailey-Lundberg JM, Zhao Z, Kraushaar D, Castro P, Cao Y, Zheng WJ, Ko TC. Aging- and alcohol-associated spatial transcriptomic signature in mouse acute pancreatitis reveals heterogeneity of inflammation and potential pathogenic factors. J Mol Med (Berl) 2024; 102:1051-1061. [PMID: 38940937 DOI: 10.1007/s00109-024-02460-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 03/15/2024] [Accepted: 06/07/2024] [Indexed: 06/29/2024]
Abstract
The rapidly aging population is consuming more alcohol, leading to increased alcohol-associated acute pancreatitis (AAP) with high mortality. However, the mechanisms remain undefined, and currently there are no effective therapies available. This study aims to elucidate aging- and alcohol-associated spatial transcriptomic signature by establishing an aging AAP mouse model and applying Visium spatial transcriptomics for understanding of the mechanisms in the context of the pancreatic tissue. Upon alcohol diet feeding and caerulein treatment, aging mice (18 months) developed significantly more severe AAP with 5.0-fold increase of injury score and 2.4-fold increase of amylase compared to young mice (3 months). Via Visium spatial transcriptomics, eight distinct tissue clusters were revealed from aggregated transcriptomes of aging and young AAP mice: five acinar, two stromal, and one islet, which were then merged into three clusters: acinar, stromal, and islet for the comparative analysis. Compared to young AAP mice, > 1300 differentially expressed genes (DEGs) and approximately 3000 differentially regulated pathways were identified in aging AAP mice. The top five DEGs upregulated in aging AAP mice include Mmp8, Ppbp, Serpina3m, Cxcl13, and Hamp with heterogeneous distributions among the clusters. Taken together, this study demonstrates spatial heterogeneity of inflammatory processes in aging AAP mice, offering novel insights into the mechanisms and potential drivers for AAP development. KEY MESSAGES: Mechanisms regarding high mortality of AAP in aging remain undefined. An aging AAP mouse model was developed recapturing clinical exhibition in humans. Spatial transcriptomics identified contrasted DEGs in aging vs. young AAP mice. Top five DEGs were Mmp8, Ppbp, Serpina3m, Cxcl13, and Hamp in aging vs. young AAP mice. Our findings shed insights for identification of molecular drivers in aging AAP.
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Affiliation(s)
- Rachel R Tindall
- Department of Surgery, UTHealth at Houston, Houston, TX, 77030, USA
| | - Yuntao Yang
- McWilliams School of Biomedical Informatics, UTHealth at Houston, Houston, TX, 77030, USA
| | | | - Amy Qin
- Department of Surgery, UTHealth at Houston, Houston, TX, 77030, USA
| | - Jiajing Li
- Department of Surgery, UTHealth at Houston, Houston, TX, 77030, USA
| | - Yinjie Zhang
- Department of Surgery, UTHealth at Houston, Houston, TX, 77030, USA
| | - Thomas H Gomez
- Center for Laboratory Animal Medicine and Care, UTHealth at Houston, Houston, TX, 77030, USA
| | - Mamoun Younes
- Department of Pathology, George Washington University School of Medicine and Health Sciences, Washington, DC, 20037, USA
| | - Qiang Shen
- Department of Interdisciplinary Oncology, Louisiana State Univ. Health Sciences Center, New Orleans, LA, 70112, USA
| | - Jennifer M Bailey-Lundberg
- Department of Anesthesiology, Critical Care and Pain Medicine, UTHealth at Houston, Houston, TX, 77030, USA
| | - Zhongming Zhao
- Center for Precision Health, McWilliams School of Biomedical Informatics, UTHealth at Houston, Houston, TX, 77030, USA
| | - Daniel Kraushaar
- Genomic and RNA Profiling Core, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Patricia Castro
- Human Tissue Acquisition & Pathology Core, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Yanna Cao
- Department of Surgery, UTHealth at Houston, Houston, TX, 77030, USA.
| | - W Jim Zheng
- McWilliams School of Biomedical Informatics, UTHealth at Houston, Houston, TX, 77030, USA.
| | - Tien C Ko
- Department of Surgery, UTHealth at Houston, Houston, TX, 77030, USA.
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2
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Li X, Qiu P. Gene representation bias in spatial transcriptomics. J Bioinform Comput Biol 2024:2450007. [PMID: 39036848 DOI: 10.1142/s0219720024500070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/23/2024]
Abstract
For sequencing-based spatial transcriptomics data, the gene-spot count matrix is highly sparse. This feature is similar to scRNA-seq. The goal of this paper is to identify whether there exist genes that are frequently under-detected in Visium compared to bulk RNA-seq, and the underlying potential mechanism of under-detection in Visium. We collected paired Visium and bulk RNA-seq data for 28 human samples and 19 mouse samples, which covered diverse tissue sources. We compared the two data types and observed that there indeed exists a collection of genes frequently under-detected in Visium compared to bulk RNA-seq. We performed a motif search to examine the last 350 bp of the frequently under-detected genes, and we observed that the poly (T) motif was significantly enriched in genes identified from both human and mouse data, which matches with our previous finding about frequently under-detected genes in scRNA-seq. We hypothesized that the poly (T) motif may be able to form a hairpin structure with the poly (A) tails of their mRNA transcripts, making it difficult for their mRNA transcripts to be captured during Visium library preparation.
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Affiliation(s)
- Xinling Li
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States
| | - Peng Qiu
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States
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3
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Mateiou C, Lokhande L, Diep LH, Knulst M, Carlsson E, Ek S, Sundfeldt K, Gerdtsson A. Spatial tumor immune microenvironment phenotypes in ovarian cancer. NPJ Precis Oncol 2024; 8:148. [PMID: 39026018 PMCID: PMC11258306 DOI: 10.1038/s41698-024-00640-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 07/09/2024] [Indexed: 07/20/2024] Open
Abstract
Immunotherapy has largely failed in ovarian carcinoma (OC), likely due to that the vast tumor heterogeneity and variation in immune response have hampered clinical trial outcomes. Tumor-immune microenvironment (TIME) profiling may aid in stratification of OC tumors for guiding treatment selection. Here, we used Digital Spatial Profiling combined with image analysis to characterize regions of spatially distinct TIME phenotypes in OC to assess whether immune infiltration pattern can predict presence of immuno-oncology targets. Tumors with diffuse immune infiltration and increased tumor-immune spatial interactions had higher presence of IDO1, PD-L1, PD-1 and Tim-3, while focal immune niches had more CD163 macrophages and a preliminary worse outcome. Immune exclusion was associated with presence of Tregs and Fibronectin. High-grade serous OC showed an overall stronger immune response and presence of multiple targetable checkpoints. Low-grade serous OC was associated with diffuse infiltration and a high expression of STING, while endometrioid OC had higher presence of CTLA-4. Mucinous and clear cell OC were dominated by focal immune clusters and immune-excluded regions, with mucinous tumors displaying T-cell rich immune niches.
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Affiliation(s)
- Claudia Mateiou
- Department of Pathology and Cytology, Institute of Biomedicine, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
| | | | - Lan Hoa Diep
- Department of Immunotechnology, Lund University, Lund, Sweden
| | - Mattis Knulst
- Department of Immunotechnology, Lund University, Lund, Sweden
| | - Elias Carlsson
- Department of Immunotechnology, Lund University, Lund, Sweden
| | - Sara Ek
- Department of Immunotechnology, Lund University, Lund, Sweden
| | - Karin Sundfeldt
- Department of Obstetrics and Gynecology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
| | - Anna Gerdtsson
- Department of Immunotechnology, Lund University, Lund, Sweden.
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4
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Tocci P, Roman C, Sestito R, Caprara V, Sacconi A, Molineris I, Tonon G, Blandino G, Bagnato A. The endothelin-1-driven tumor-stroma feed-forward loops in high-grade serous ovarian cancer. Clin Sci (Lond) 2024; 138:851-862. [PMID: 38884602 PMCID: PMC11230866 DOI: 10.1042/cs20240346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Revised: 05/30/2024] [Accepted: 06/17/2024] [Indexed: 06/18/2024]
Abstract
The high-grade serous ovarian cancer (HG-SOC) tumor microenvironment (TME) is constellated by cellular elements and a network of soluble constituents that contribute to tumor progression. In the multitude of the secreted molecules, the endothelin-1 (ET-1) has emerged to be implicated in the tumor/TME interplay; however, the molecular mechanisms induced by the ET-1-driven feed-forward loops (FFL) and associated with the HG-SOC metastatic potential need to be further investigated. The tracking of the patient-derived (PD) HG-SOC cell transcriptome by RNA-seq identified the vascular endothelial growth factor (VEGF) gene and its associated signature among those mostly up-regulated by ET-1 and down-modulated by the dual ET-1R antagonist macitentan. Within the ligand-receptor pairs concurrently expressed in PD-HG-SOC cells, endothelial cells and activated fibroblasts, we discovered two intertwined FFL, the ET-1/ET-1R and VEGF/VEGF receptors, concurrently activated by ET-1 and shutting-down by macitentan, or by the anti-VEGF antibody bevacizumab. In parallel, we observed that ET-1 fine-tuned the tumoral and stromal secretome toward a pro-invasive pattern. Into the fray of the HG-SOC/TME double and triple co-cultures, the secretion of ET-1 and VEGF, that share a common co-regulation, was inhibited upon the administration of macitentan. Functionally, macitentan, mimicking the effect of bevacizumab, interfered with the HG-SOC/TME FFL-driven communication that fuels the HG-SOC invasive behavior. The identification of ET-1 and VEGF FFL as tumor and TME actionable vulnerabilities, reveals how ET-1R blockade, targeting the HG-SOC cells and the TME simultaneously, may represent an effective therapeutic option for HG-SOC patients.
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Affiliation(s)
- Piera Tocci
- Preclinical Models and New Therapeutic Agents Unit, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Regina Elena National Cancer Institute, Rome, Italy
| | - Celia Roman
- Preclinical Models and New Therapeutic Agents Unit, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Regina Elena National Cancer Institute, Rome, Italy
| | - Rosanna Sestito
- Preclinical Models and New Therapeutic Agents Unit, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Regina Elena National Cancer Institute, Rome, Italy
| | - Valentina Caprara
- Preclinical Models and New Therapeutic Agents Unit, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Regina Elena National Cancer Institute, Rome, Italy
| | - Andrea Sacconi
- Translational Oncology Research Unit, IRCCS, Regina Elena National Cancer Institute, Rome, Italy
| | - Ivan Molineris
- Department of Life Science and System Biology, University of Turin, Turin, Italy
| | - Giovanni Tonon
- Center for Omics Sciences (COSR) and Functional Genomics of Cancer Unit, Division of Experimental Oncology, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Università Vita-Salute San Raffaele, 20132, Milan, Italy
| | - Giovanni Blandino
- Translational Oncology Research Unit, IRCCS, Regina Elena National Cancer Institute, Rome, Italy
| | - Anna Bagnato
- Preclinical Models and New Therapeutic Agents Unit, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Regina Elena National Cancer Institute, Rome, Italy
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5
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Laury AR, Zheng S, Aho N, Fallegger R, Hänninen S, Saez-Rodriguez J, Tanevski J, Youssef O, Tang J, Carpén OM. Opening the Black Box: Spatial Transcriptomics and the Relevance of Artificial Intelligence-Detected Prognostic Regions in High-Grade Serous Carcinoma. Mod Pathol 2024; 37:100508. [PMID: 38704029 DOI: 10.1016/j.modpat.2024.100508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 04/04/2024] [Accepted: 04/22/2024] [Indexed: 05/06/2024]
Abstract
Image-based deep learning models are used to extract new information from standard hematoxylin and eosin pathology slides; however, biological interpretation of the features detected by artificial intelligence (AI) remains a challenge. High-grade serous carcinoma of the ovary (HGSC) is characterized by aggressive behavior and chemotherapy resistance, but also exhibits striking variability in outcome. Our understanding of this disease is limited, partly due to considerable tumor heterogeneity. We previously trained an AI model to identify HGSC tumor regions that are highly associated with outcome status but are indistinguishable by conventional morphologic methods. Here, we applied spatially resolved transcriptomics to further profile the AI-identified tumor regions in 16 patients (8 per outcome group) and identify molecular features related to disease outcome in patients who underwent primary debulking surgery and platinum-based chemotherapy. We examined formalin-fixed paraffin-embedded tissue from (1) regions identified by the AI model as highly associated with short or extended chemotherapy response, and (2) background tumor regions (not identified by the AI model as highly associated with outcome status) from the same tumors. We show that the transcriptomic profiles of AI-identified regions are more distinct than background regions from the same tumors, are superior in predicting outcome, and differ in several pathways including those associated with chemoresistance in HGSC. Further, we find that poor outcome and good outcome regions are enriched by different tumor subpopulations, suggesting distinctive interaction patterns. In summary, our work presents proof of concept that AI-guided spatial transcriptomic analysis improves recognition of biologic features relevant to patient outcomes.
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Affiliation(s)
- Anna Ray Laury
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland; Department of Pathology, University of Helsinki and HUS Diagnostic Center, Helsinki University Hospital, Helsinki, Finland.
| | - Shuyu Zheng
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Niina Aho
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Robin Fallegger
- Institute for Computational Biomedicine, Faculty of Medicine, Heidelberg University and Heidelberg University Hospital, Heidelberg, Germany
| | - Satu Hänninen
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland; Department of Pathology, University of Helsinki and HUS Diagnostic Center, Helsinki University Hospital, Helsinki, Finland
| | - Julio Saez-Rodriguez
- Institute for Computational Biomedicine, Faculty of Medicine, Heidelberg University and Heidelberg University Hospital, Heidelberg, Germany
| | - Jovan Tanevski
- Institute for Computational Biomedicine, Faculty of Medicine, Heidelberg University and Heidelberg University Hospital, Heidelberg, Germany; Department of Knowledge Technologies, Jožef Stefan Institute, Ljubljana, Slovenia
| | - Omar Youssef
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland; Clinical and Chemical Pathology Department, National Cancer Institute, Cairo University, Cairo, Egypt
| | - Jing Tang
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland; Department of Biochemistry and Developmental Biology, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
| | - Olli Mikael Carpén
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland; Department of Pathology, University of Helsinki and HUS Diagnostic Center, Helsinki University Hospital, Helsinki, Finland; iCAN Digital Precision Cancer Medicine Flagship, University of Helsinki, Helsinki, Finland
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6
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Balan D, Kampan NC, Plebanski M, Abd Aziz NH. Unlocking ovarian cancer heterogeneity: advancing immunotherapy through single-cell transcriptomics. Front Oncol 2024; 14:1388663. [PMID: 38873253 PMCID: PMC11169633 DOI: 10.3389/fonc.2024.1388663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 05/15/2024] [Indexed: 06/15/2024] Open
Abstract
Ovarian cancer, a highly fatal gynecological cancer, warrants the need for understanding its heterogeneity. The disease's prevalence and impact are underscored with statistics on mortality rates. Ovarian cancer is categorized into distinct morphological groups, each with its characteristics and prognosis. Despite standard treatments, survival rates remain low due to relapses and chemoresistance. Immune system involvement is evident in ovarian cancer's progression, although the tumor employs immune evasion mechanisms. Immunotherapy, particularly immune checkpoint blockade therapy, is promising, but ovarian cancer's heterogeneity limits its efficacy. Single-cell sequencing technology could be explored as a solution to dissect the heterogeneity within tumor-associated immune cell populations and tumor microenvironments. This cutting-edge technology has the potential to enhance diagnosis, prognosis, and personalized immunotherapy in ovarian cancer, reflecting its broader application in cancer research. The present review focuses on recent advancements and the challenges in applying single-cell transcriptomics to ovarian cancer.
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Affiliation(s)
- Dharvind Balan
- Department of Obstetrics and Gynaecology, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Nirmala Chandralega Kampan
- Department of Obstetrics and Gynaecology, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Magdalena Plebanski
- School of Health and Biomedical Sciences, RMIT University, Bundoora, VIC, Australia
| | - Nor Haslinda Abd Aziz
- Department of Obstetrics and Gynaecology, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
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7
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Mori Y, Okimoto Y, Sakai H, Kanda Y, Ohata H, Shiokawa D, Suzuki M, Yoshida H, Ueda H, Sekizuka T, Tamura R, Yamawaki K, Ishiguro T, Mateos RN, Shiraishi Y, Yatabe Y, Hamada A, Yoshihara K, Enomoto T, Okamoto K. Targeting PDGF signaling of cancer-associated fibroblasts blocks feedback activation of HIF-1α and tumor progression of clear cell ovarian cancer. Cell Rep Med 2024; 5:101532. [PMID: 38670097 PMCID: PMC11149410 DOI: 10.1016/j.xcrm.2024.101532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 01/04/2024] [Accepted: 04/04/2024] [Indexed: 04/28/2024]
Abstract
Ovarian clear cell carcinoma (OCCC) is a gynecological cancer with a dismal prognosis; however, the mechanism underlying OCCC chemoresistance is not well understood. To explore the intracellular networks associated with the chemoresistance, we analyze surgical specimens by performing integrative analyses that combine single-cell analyses and spatial transcriptomics. We find that a chemoresistant OCCC subpopulation with elevated HIF activity localizes mainly in areas populated by cancer-associated fibroblasts (CAFs) with a myofibroblastic phenotype, which is corroborated by quantitative immunostaining. CAF-enhanced chemoresistance and HIF-1α induction are recapitulated in co-culture assays, which show that cancer-derived platelet-derived growth factor (PDGF) contributes to the chemoresistance and HIF-1α induction via PDGF receptor signaling in CAFs. Ripretinib is identified as an effective receptor tyrosine kinase inhibitor against CAF survival. In the co-culture system and xenograft tumors, ripretinib prevents CAF survival and suppresses OCCC proliferation in the presence of carboplatin, indicating that combination of conventional chemotherapy and CAF-targeted agents is effective against OCCC.
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MESH Headings
- Female
- Humans
- Cancer-Associated Fibroblasts/metabolism
- Cancer-Associated Fibroblasts/pathology
- Cancer-Associated Fibroblasts/drug effects
- Hypoxia-Inducible Factor 1, alpha Subunit/metabolism
- Hypoxia-Inducible Factor 1, alpha Subunit/genetics
- Ovarian Neoplasms/pathology
- Ovarian Neoplasms/metabolism
- Ovarian Neoplasms/drug therapy
- Ovarian Neoplasms/genetics
- Platelet-Derived Growth Factor/metabolism
- Signal Transduction/drug effects
- Animals
- Mice
- Cell Line, Tumor
- Drug Resistance, Neoplasm/drug effects
- Drug Resistance, Neoplasm/genetics
- Disease Progression
- Coculture Techniques
- Cell Proliferation/drug effects
- Mice, Nude
- Adenocarcinoma, Clear Cell/metabolism
- Adenocarcinoma, Clear Cell/pathology
- Adenocarcinoma, Clear Cell/drug therapy
- Adenocarcinoma, Clear Cell/genetics
- Feedback, Physiological/drug effects
- Xenograft Model Antitumor Assays
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Affiliation(s)
- Yutaro Mori
- Advanced Comprehensive Research Organization, Teikyo University, Tokyo 173-0003, Japan; Department of Obstetrics and Gynecology, Niigata University Graduate School of Medical and Dental Sciences, Niigata 951-8520, Japan
| | - Yoshie Okimoto
- Advanced Comprehensive Research Organization, Teikyo University, Tokyo 173-0003, Japan
| | - Hiroaki Sakai
- Advanced Comprehensive Research Organization, Teikyo University, Tokyo 173-0003, Japan
| | - Yusuke Kanda
- Advanced Comprehensive Research Organization, Teikyo University, Tokyo 173-0003, Japan
| | - Hirokazu Ohata
- Advanced Comprehensive Research Organization, Teikyo University, Tokyo 173-0003, Japan
| | - Daisuke Shiokawa
- Ehime University Hospital Translational Research Center, Shitsukawa, Toon, Ehime 791-0295, Japan
| | - Mikiko Suzuki
- Division of Molecular Pharmacology, National Cancer Center Research Institute, Tokyo 104-0045, Japan
| | - Hiroshi Yoshida
- Department of Diagnostic Pathology, National Cancer Center Hospital, Tokyo 104-0045, Japan
| | - Haruka Ueda
- Department of Obstetrics and Gynecology, Niigata University Graduate School of Medical and Dental Sciences, Niigata 951-8520, Japan
| | - Tomoyuki Sekizuka
- Department of Obstetrics and Gynecology, Niigata University Graduate School of Medical and Dental Sciences, Niigata 951-8520, Japan
| | - Ryo Tamura
- Department of Obstetrics and Gynecology, Niigata University Graduate School of Medical and Dental Sciences, Niigata 951-8520, Japan
| | - Kaoru Yamawaki
- Department of Obstetrics and Gynecology, Niigata University Graduate School of Medical and Dental Sciences, Niigata 951-8520, Japan
| | - Tatsuya Ishiguro
- Department of Obstetrics and Gynecology, Niigata University Graduate School of Medical and Dental Sciences, Niigata 951-8520, Japan
| | - Raul Nicolas Mateos
- Division of Genome Analysis Platform Development, National Cancer Center Research Institute, Tokyo 104-0045, Japan
| | - Yuichi Shiraishi
- Division of Genome Analysis Platform Development, National Cancer Center Research Institute, Tokyo 104-0045, Japan
| | - Yasushi Yatabe
- Department of Diagnostic Pathology, National Cancer Center Hospital, Tokyo 104-0045, Japan
| | - Akinobu Hamada
- Division of Molecular Pharmacology, National Cancer Center Research Institute, Tokyo 104-0045, Japan
| | - Kosuke Yoshihara
- Department of Obstetrics and Gynecology, Niigata University Graduate School of Medical and Dental Sciences, Niigata 951-8520, Japan
| | - Takayuki Enomoto
- Department of Obstetrics and Gynecology, Niigata University Graduate School of Medical and Dental Sciences, Niigata 951-8520, Japan
| | - Koji Okamoto
- Advanced Comprehensive Research Organization, Teikyo University, Tokyo 173-0003, Japan.
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8
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Ospina OE, Soupir AC, Manjarres-Betancur R, Gonzalez-Calderon G, Yu X, Fridley BL. Differential gene expression analysis of spatial transcriptomic experiments using spatial mixed models. Sci Rep 2024; 14:10967. [PMID: 38744956 PMCID: PMC11094014 DOI: 10.1038/s41598-024-61758-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 05/09/2024] [Indexed: 05/16/2024] Open
Abstract
Spatial transcriptomics (ST) assays represent a revolution in how the architecture of tissues is studied by allowing for the exploration of cells in their spatial context. A common element in the analysis is delineating tissue domains or "niches" followed by detecting differentially expressed genes to infer the biological identity of the tissue domains or cell types. However, many studies approach differential expression analysis by using statistical approaches often applied in the analysis of non-spatial scRNA data (e.g., two-sample t-tests, Wilcoxon's rank sum test), hence neglecting the spatial dependency observed in ST data. In this study, we show that applying linear mixed models with spatial correlation structures using spatial random effects effectively accounts for the spatial autocorrelation and reduces inflation of type-I error rate observed in non-spatial based differential expression testing. We also show that spatial linear models with an exponential correlation structure provide a better fit to the ST data as compared to non-spatial models, particularly for spatially resolved technologies that quantify expression at finer scales (i.e., single-cell resolution).
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Affiliation(s)
- Oscar E Ospina
- Department of Biostatistics & Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Alex C Soupir
- Department of Biostatistics & Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | | | | | - Xiaoqing Yu
- Department of Biostatistics & Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Brooke L Fridley
- Department of Biostatistics & Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
- Biostatistics and Epidemiology Core, Division of Health Services & Outcomes Research, Children's Mercy, Kansas City, MO, USA.
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9
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Xu AM, Haro M, Walts AE, Hu Y, John J, Karlan BY, Merchant A, Orsulic S. Spatiotemporal architecture of immune cells and cancer-associated fibroblasts in high-grade serous ovarian carcinoma. SCIENCE ADVANCES 2024; 10:eadk8805. [PMID: 38630822 PMCID: PMC11023532 DOI: 10.1126/sciadv.adk8805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Accepted: 03/15/2024] [Indexed: 04/19/2024]
Abstract
High-grade serous ovarian carcinoma (HGSOC), the deadliest form of ovarian cancer, is typically diagnosed after it has metastasized and often relapses after standard-of-care platinum-based chemotherapy, likely due to advanced tumor stage, heterogeneity, and immune evasion and tumor-promoting signaling from the tumor microenvironment. To understand how spatial heterogeneity contributes to HGSOC progression and early relapse, we profiled an HGSOC tissue microarray of patient-matched longitudinal samples from 42 patients. We found spatial patterns associated with early relapse, including changes in T cell localization, malformed tertiary lymphoid structure (TLS)-like aggregates, and increased podoplanin-positive cancer-associated fibroblasts (CAFs). Using spatial features to compartmentalize the tissue, we found that plasma cells distribute in two different compartments associated with TLS-like aggregates and CAFs, and these distinct microenvironments may account for the conflicting reports about the role of plasma cells in HGSOC prognosis.
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Affiliation(s)
- Alexander M. Xu
- Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
- Division of Hematology and Cellular Therapy, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Marcela Haro
- Department of Obstetrics and Gynecology and Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Ann E. Walts
- Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Ye Hu
- Department of Obstetrics and Gynecology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Joshi John
- Department of Veterans Affairs, Greater Los Angeles Healthcare System, Los Angeles, CA 90073, USA
- Department of Medicine, Division of Geriatrics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Beth Y. Karlan
- Department of Obstetrics and Gynecology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- Jonsson Comprehensive Cancer Center, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Akil Merchant
- Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
- Division of Hematology and Cellular Therapy, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Sandra Orsulic
- Department of Obstetrics and Gynecology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- Department of Veterans Affairs, Greater Los Angeles Healthcare System, Los Angeles, CA 90073, USA
- Jonsson Comprehensive Cancer Center, University of California Los Angeles, Los Angeles, CA 90095, USA
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10
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Denisenko E, de Kock L, Tan A, Beasley AB, Beilin M, Jones ME, Hou R, Muirí DÓ, Bilic S, Mohan GRKA, Salfinger S, Fox S, Hmon KPW, Yeow Y, Kim Y, John R, Gilderman TS, Killingbeck E, Gray ES, Cohen PA, Yu Y, Forrest ARR. Spatial transcriptomics reveals discrete tumour microenvironments and autocrine loops within ovarian cancer subclones. Nat Commun 2024; 15:2860. [PMID: 38570491 PMCID: PMC10991508 DOI: 10.1038/s41467-024-47271-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 03/26/2024] [Indexed: 04/05/2024] Open
Abstract
High-grade serous ovarian carcinoma (HGSOC) is genetically unstable and characterised by the presence of subclones with distinct genotypes. Intratumoural heterogeneity is linked to recurrence, chemotherapy resistance, and poor prognosis. Here, we use spatial transcriptomics to identify HGSOC subclones and study their association with infiltrating cell populations. Visium spatial transcriptomics reveals multiple tumour subclones with different copy number alterations present within individual tumour sections. These subclones differentially express various ligands and receptors and are predicted to differentially associate with different stromal and immune cell populations. In one sample, CosMx single molecule imaging reveals subclones differentially associating with immune cell populations, fibroblasts, and endothelial cells. Cell-to-cell communication analysis identifies subclone-specific signalling to stromal and immune cells and multiple subclone-specific autocrine loops. Our study highlights the high degree of subclonal heterogeneity in HGSOC and suggests that subclone-specific ligand and receptor expression patterns likely modulate how HGSOC cells interact with their local microenvironment.
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Affiliation(s)
- Elena Denisenko
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Nedlands, Perth, WA, 6009, Australia.
| | - Leanne de Kock
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Nedlands, Perth, WA, 6009, Australia
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON, Canada
| | - Adeline Tan
- Anatomical Pathology Department, Clinipath, Sonic Healthcare, Perth, WA, 6017, Australia
| | - Aaron B Beasley
- Centre for Precision Health, Edith Cowan University, Joondalup, WA, 6027, Australia
| | - Maria Beilin
- Department of Gynaecological Oncology, Bendat Family Comprehensive Cancer Centre, St John of God Subiaco Hospital, 12 Salvado Rd, Subiaco, WA, 6008, Australia
| | - Matthew E Jones
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Nedlands, Perth, WA, 6009, Australia
| | - Rui Hou
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Nedlands, Perth, WA, 6009, Australia
| | - Dáithí Ó Muirí
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Nedlands, Perth, WA, 6009, Australia
| | - Sanela Bilic
- Department of Gynaecological Oncology, Bendat Family Comprehensive Cancer Centre, St John of God Subiaco Hospital, 12 Salvado Rd, Subiaco, WA, 6008, Australia
| | - G Raj K A Mohan
- Department of Gynaecological Oncology, Bendat Family Comprehensive Cancer Centre, St John of God Subiaco Hospital, 12 Salvado Rd, Subiaco, WA, 6008, Australia
- School of Medicine, University of Notre Dame, Fremantle, WA, 6160, Australia
| | | | - Simon Fox
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Nedlands, Perth, WA, 6009, Australia
| | - Khaing P W Hmon
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Nedlands, Perth, WA, 6009, Australia
| | - Yen Yeow
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Nedlands, Perth, WA, 6009, Australia
| | | | - Rhea John
- NanoString Technologies, Seattle, WA, USA
| | | | | | - Elin S Gray
- Centre for Precision Health, Edith Cowan University, Joondalup, WA, 6027, Australia
| | - Paul A Cohen
- Division of Obstetrics and Gynaecology, Medical School, University of Western Australia, 35 Stirling Highway, Crawley, WA, 6009, Australia.
- Institute for Health Research, The University of Notre Dame Australia, 32 Mouat Street Fremantle, Fremantle, WA, 6160, Australia.
| | - Yu Yu
- Division of Obstetrics and Gynaecology, Medical School, University of Western Australia, 35 Stirling Highway, Crawley, WA, 6009, Australia.
- Curtin Medical School, Curtin University, 410 Koorliny Way, Bentley, WA, 6102, Australia.
- Curtin Health Innovation Research Institute, Curtin University B305, Bentley, WA, 6102, Australia.
| | - Alistair R R Forrest
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Nedlands, Perth, WA, 6009, Australia.
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11
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Nersesian S, Arseneau RJ, Mejia JP, Lee SN, Westhaver LP, Griffiths NW, Grantham SR, Meunier L, Communal L, Mukherjee A, Mes-Masson AM, Arnason T, Nelson BH, Boudreau JE. Improved overall survival in patients with high-grade serous ovarian cancer is associated with CD16a+ immunologic neighborhoods containing NK cells, T cells and macrophages. Front Immunol 2024; 14:1307873. [PMID: 38318505 PMCID: PMC10838965 DOI: 10.3389/fimmu.2023.1307873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 12/22/2023] [Indexed: 02/07/2024] Open
Abstract
Background For patients with high grade serous carcinoma of the ovary (HGSC), survival rates have remained static for the last half century. Despite the presence of tumor mutations and infiltration of immune cells, existing immunotherapies have achieved little success against HGSC. These observations highlight a gap in the understanding of how the immune system functions and interacts within HGSC tumors. Methods We analyzed duplicate core samples from 939 patients with HGSC to understand patterns of immune cell infiltration, localization, and associations with clinical features. We used high-parameter immunohistochemical/Opal multiplex, digital pathology, computational biology, and multivariate analysis to identify immune cell subsets and their associations with HGSC tumors. Results We defined six patterns of cellular infiltration by spatially restricted unsupervised clustering of cell subsets. Each pattern was represented to some extent in most patient samples, but their specific distributions differed. Overall (OS) and progression-free survival (PFS) corresponded with higher infiltration of CD16a+ cells, and their co-localization with macrophages, T cells, NK cells, in one of six cellular neighborhoods that we defined with our spatial assessment. Conclusions Immune cell neighborhoods containing CD16a+ cells are associated with improved OS and PFS for patients with HGSC. Patterns of immunologic neighborhoods differentiate patient outcomes, and could inform future, more precise approaches to treatment.
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Affiliation(s)
- Sarah Nersesian
- Department of Microbiology and Immunology, Dalhousie University, Halifax, NS, Canada
- Beatrice Hunter Cancer Research Institute, Halifax, NS, Canada
| | - Riley J. Arseneau
- Beatrice Hunter Cancer Research Institute, Halifax, NS, Canada
- Department of Pathology, Dalhousie University, Halifax, NS, Canada
| | - Jorge P. Mejia
- Department of Microbiology and Immunology, Dalhousie University, Halifax, NS, Canada
- Beatrice Hunter Cancer Research Institute, Halifax, NS, Canada
| | - Stacey N. Lee
- Department of Microbiology and Immunology, Dalhousie University, Halifax, NS, Canada
- Beatrice Hunter Cancer Research Institute, Halifax, NS, Canada
| | | | | | | | - Liliane Meunier
- Centre de recherche du Centre hospitalier de l’Université de Montréal and Institut du cancer de Montréal, Montreal, QC, Canada
| | - Laudine Communal
- Centre de recherche du Centre hospitalier de l’Université de Montréal and Institut du cancer de Montréal, Montreal, QC, Canada
| | | | - Anne-Marie Mes-Masson
- Centre de recherche du Centre hospitalier de l’Université de Montréal and Institut du cancer de Montréal, Montreal, QC, Canada
- Department of Medicine, Université de Montréal, Montreal, QC, Canada
| | - Thomas Arnason
- Department of Pathology, Dalhousie University, Halifax, NS, Canada
- Department of Pathology & Laboratory Medicine, QEII Health Sciences Centre, Nova Scotia Health (Central Zone), Halifax, NS, Canada
| | - Brad H. Nelson
- Deeley Research Centre, British Columbia Cancer Research Institute, Victoria, BC, Canada
- Department of Biochemistry and Microbiology, University of Victoria, Victoria, BC, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Jeanette E. Boudreau
- Department of Microbiology and Immunology, Dalhousie University, Halifax, NS, Canada
- Beatrice Hunter Cancer Research Institute, Halifax, NS, Canada
- Department of Pathology, Dalhousie University, Halifax, NS, Canada
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12
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Zhang L, Cascio S, Mellors JW, Buckanovich RJ, Osmanbeyoglu HU. Single-cell analysis reveals the stromal dynamics and tumor-specific characteristics in the microenvironment of ovarian cancer. Commun Biol 2024; 7:20. [PMID: 38182756 PMCID: PMC10770164 DOI: 10.1038/s42003-023-05733-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 12/20/2023] [Indexed: 01/07/2024] Open
Abstract
High-grade serous ovarian carcinoma (HGSOC) is a heterogeneous disease, and a highstromal/desmoplastic tumor microenvironment (TME) is associated with a poor outcome. Stromal cell subtypes, including fibroblasts, myofibroblasts, and cancer-associated mesenchymal stem cells, establish a complex network of paracrine signaling pathways with tumor-infiltrating immune cells that drive effector cell tumor immune exclusion and inhibit the antitumor immune response. In this work, we integrate single-cell transcriptomics of the HGSOC TME from public and in-house datasets (n = 20) and stratify tumors based upon high vs. low stromal cell content. Although our cohort size is small, our analyses suggest a distinct transcriptomic landscape for immune and non-immune cells in high-stromal vs. low-stromal tumors. High-stromal tumors have a lower fraction of certain T cells, natural killer (NK) cells, and macrophages, and increased expression of CXCL12 in epithelial cancer cells and cancer-associated mesenchymal stem cells (CA-MSCs). Analysis of cell-cell communication indicate that epithelial cancer cells and CA-MSCs secrete CXCL12 that interacte with the CXCR4 receptor, which is overexpressed on NK and CD8+ T cells. Dual IHC staining show that tumor infiltrating CD8 T cells localize in proximity of CXCL12+ tumor area. Moreover, CXCL12 and/or CXCR4 antibodies confirm the immunosuppressive role of CXCL12-CXCR4 in high-stromal tumors.
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Affiliation(s)
- Linan Zhang
- Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15206, USA
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, 15232, USA
- Department of Applied Mathematics, School of Mathematics and Statistics, Ningbo University, Ningbo, Zhejiang, 315211, China
| | - Sandra Cascio
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, 15232, USA
- Magee-Womens Research Institute, Pittsburgh, PA, 15213, USA
- Division of Gynecologic Oncology, Department of Obstetrics, Gynecology, and Reproductive Sciences, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15213, USA
| | - John W Mellors
- Division of Infectious Diseases, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15213, USA
| | - Ronald J Buckanovich
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, 15232, USA
- Magee-Womens Research Institute, Pittsburgh, PA, 15213, USA
- Division of Hematology/Oncology, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15232, USA
| | - Hatice Ulku Osmanbeyoglu
- Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15206, USA.
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, 15232, USA.
- Department of Bioengineering, University of Pittsburgh School of Engineering, Pittsburgh, PA, 15219, USA.
- Department of Biostatistics, University of Pittsburgh School of Public Health, Pittsburgh, PA, 15261, USA.
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13
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Blanc-Durand F, Clemence Wei Xian L, Tan DSP. Targeting the immune microenvironment for ovarian cancer therapy. Front Immunol 2023; 14:1328651. [PMID: 38164130 PMCID: PMC10757966 DOI: 10.3389/fimmu.2023.1328651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 12/05/2023] [Indexed: 01/03/2024] Open
Abstract
Ovarian cancer (OC) is an aggressive malignancy characterized by a complex immunosuppressive tumor microenvironment (TME). Immune checkpoint inhibitors have emerged as a breakthrough in cancer therapy by reactivating the antitumor immune response suppressed by tumor cells. However, in the case of OC, these inhibitors have failed to demonstrate significant improvements in patient outcomes, and existing biomarkers have not yet identified promising subgroups. Consequently, there remains a pressing need to understand the interplay between OC tumor cells and their surrounding microenvironment to develop effective immunotherapeutic approaches. This review aims to provide an overview of the OC TME and explore its potential as a therapeutic strategy. Tumor-infiltrating lymphocytes (TILs) are major actors in OC TME. Evidence has been accumulating regarding the spontaneous TILS response against OC antigens. Activated T-helpers secrete a wide range of inflammatory cytokines with a supportive action on cytotoxic T-cells. Simultaneously, mature B-cells are recruited and play a significant antitumor role through opsonization of target antigens and T-cell recruitment. Macrophages also form an important subset of innate immunity (M1-macrophages) while participating in the immune-stimulation context. Finally, OC has shown to engage a significant natural-killer-cells immune response, exerting direct cytotoxicity without prior sensitization. Despite this initial cytotoxicity, OC cells develop various strategies to induce an immune-tolerant state. To this end, multiple immunosuppressive molecules are secreted to impair cytotoxic cells, recruit regulatory cells, alter antigen presentation, and effectively evade immune response. Consequently, OC TME is predominantly infiltrated by immunosuppressive cells such as FOXP3+ regulatory T-cells, M2-polarized macrophages and myeloid-derived suppressor cells. Despite this strong immunosuppressive state, PD-1/PD-L1 inhibitors have failed to improve outcomes. Beyond PD-1/PD-L1, OC expresses multiple other immune checkpoints that contribute to immune evasion, and each representing potential immune targets. Novel immunotherapies are attempting to overcome the immunosuppressive state and induce specific immune responses using antibodies adoptive cell therapy or vaccines. Overall, the OC TME presents both opportunities and obstacles. Immunotherapeutic approaches continue to show promise, and next-generation inhibitors offer exciting opportunities. However, tailoring therapies to individual immune characteristics will be critical for the success of these treatments.
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Affiliation(s)
- Felix Blanc-Durand
- Department of Haematology-Oncology, National University Cancer Institute, Singapore (NCIS), National University Hospital, Singapore, Singapore
- Yong Loo Lin School of Medicine and Cancer Science Institute (CSI), National University of Singapore (NUS), Singapore, Singapore
| | - Lai Clemence Wei Xian
- Department of Haematology-Oncology, National University Cancer Institute, Singapore (NCIS), National University Hospital, Singapore, Singapore
- Yong Loo Lin School of Medicine and Cancer Science Institute (CSI), National University of Singapore (NUS), Singapore, Singapore
| | - David S. P. Tan
- Department of Haematology-Oncology, National University Cancer Institute, Singapore (NCIS), National University Hospital, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University Centre for Cancer Research (N2CR) and Cancer Science Institute (CSI), National University of Singapore, Singapore, Singapore
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14
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Yang H, Gu X, Fan R, Zhu Q, Zhong S, Wan X, Chen Q, Zhu L, Feng F. Deciphering tumor immune microenvironment differences between high-grade serous and endometrioid ovarian cancer to investigate their potential in indicating immunotherapy response. J Ovarian Res 2023; 16:223. [PMID: 37993916 PMCID: PMC10664484 DOI: 10.1186/s13048-023-01284-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 09/17/2023] [Indexed: 11/24/2023] Open
Abstract
BACKGROUND Ovarian cancer is a significant public health concern with a poor prognosis for epithelial ovarian cancer. To explore the potential of immunotherapy in treating epithelial ovarian cancer, we investigated the immune microenvironments of 52 patients with epithelial ovarian cancer, including 43 with high-grade serous ovarian cancer and 9 with endometrioid ovarian cancer. RESULTS Fresh tumor tissue was analyzed for genetic mutations and various parameters related to immune evasion and infiltration. The mean stromal score (stromal cell infiltration) in high-grade serous ovarian cancer was higher than in endometrioid ovarian cancer. The infiltration of CD8 T cells and exhausted CD8 T cells were found to be more extensive in high-grade serous ovarian cancer. Tumor Immune Dysfunction and Exclusion scores, T cell exclusion scores, and cancer-associated fibroblasts (CAF) scores were also higher in the high-grade serous ovarian cancer group, suggesting that the number of cytotoxic lymphocytes in the tumor microenvironment of high-grade serous ovarian cancer is likely lower compared to endometrioid ovarian cancer. CONCLUSIONS The high mean stromal score and more extensive infiltration and exhaustion of CD8 T cells in high-grade serous ovarian cancer indicate that high-grade serous ovarian cancer exhibits a higher level of cytotoxic T cell infiltration, yet these T cells tend to be in a dysfunctional state. Higher Tumor Immune Dysfunction and Exclusion scores, T cell exclusion scores, and CAF scores in high-grade serous ovarian cancers suggest that immune escape is more likely to occur in high-grade serous ovarian cancer, thus endometrioid ovarian cancer may be more conducive to immunotherapy. Therefore, it is crucial to design immunotherapy clinical trials for ovarian cancer to distinguish between high-grade serous and endometrioid ovarian cancer from the outset. This distinction will help optimize treatment strategies and improve outcomes for patients with different subtypes.
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Affiliation(s)
- Hua Yang
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, National Clinical Research Center for Obstetric & Gynecologic Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, No.1 Shuai Fu Yuan, Wang Fu Jing Street, Beijing, China
| | - Xiangyu Gu
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, National Clinical Research Center for Obstetric & Gynecologic Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, No.1 Shuai Fu Yuan, Wang Fu Jing Street, Beijing, China
- 4+4 Medical Doctor Program, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Rong Fan
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, National Clinical Research Center for Obstetric & Gynecologic Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, No.1 Shuai Fu Yuan, Wang Fu Jing Street, Beijing, China
| | - Qun Zhu
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, National Clinical Research Center for Obstetric & Gynecologic Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, No.1 Shuai Fu Yuan, Wang Fu Jing Street, Beijing, China
- Department of Obstetrics and Gynecology, Beijing Puren Hospital, Beijing, China
| | - Sen Zhong
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, National Clinical Research Center for Obstetric & Gynecologic Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, No.1 Shuai Fu Yuan, Wang Fu Jing Street, Beijing, China
| | - Xirun Wan
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, National Clinical Research Center for Obstetric & Gynecologic Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, No.1 Shuai Fu Yuan, Wang Fu Jing Street, Beijing, China
| | | | - Lan Zhu
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, National Clinical Research Center for Obstetric & Gynecologic Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, No.1 Shuai Fu Yuan, Wang Fu Jing Street, Beijing, China.
| | - Fengzhi Feng
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, National Clinical Research Center for Obstetric & Gynecologic Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, No.1 Shuai Fu Yuan, Wang Fu Jing Street, Beijing, China.
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15
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Szymanowski W, Szymanowska A, Bielawska A, Lopez-Berestein G, Rodriguez-Aguayo C, Amero P. Aptamers as Potential Therapeutic Tools for Ovarian Cancer: Advancements and Challenges. Cancers (Basel) 2023; 15:5300. [PMID: 37958473 PMCID: PMC10647731 DOI: 10.3390/cancers15215300] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 10/23/2023] [Accepted: 10/27/2023] [Indexed: 11/15/2023] Open
Abstract
Ovarian cancer (OC) is the most common lethal gynecologic cause of death in women worldwide, with a high mortality rate and increasing incidence. Despite advancements in the treatment, most OC patients still die from their disease due to late-stage diagnosis, the lack of effective diagnostic methods, and relapses. Aptamers, synthetic, short single-stranded oligonucleotides, have emerged as promising anticancer therapeutics. Their ability to selectively bind to target molecules, including cancer-related proteins and receptors, has revolutionized drug discovery and biomarker identification. Aptamers offer unique insights into the molecular pathways involved in cancer development and progression. Moreover, they show immense potential as drug delivery systems, enabling targeted delivery of therapeutic agents to cancer cells while minimizing off-target effects and reducing systemic toxicity. In the context of OC, the integration of aptamers with non-coding RNAs (ncRNAs) presents an opportunity for precise and efficient gene targeting. Additionally, the conjugation of aptamers with nanoparticles allows for accurate and targeted delivery of ncRNAs to specific cells, tissues, or organs. In this review, we will summarize the potential use and challenges associated with the use of aptamers alone or aptamer-ncRNA conjugates, nanoparticles, and multivalent aptamer-based therapeutics for the treatment of OC.
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Affiliation(s)
- Wojciech Szymanowski
- Department of Biotechnology, Medical University of Bialystok, 15-222 Bialystok, Poland; (W.S.); (A.B.)
| | - Anna Szymanowska
- Department of Experimental Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (A.S.); (G.L.-B.); (C.R.-A.)
| | - Anna Bielawska
- Department of Biotechnology, Medical University of Bialystok, 15-222 Bialystok, Poland; (W.S.); (A.B.)
| | - Gabriel Lopez-Berestein
- Department of Experimental Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (A.S.); (G.L.-B.); (C.R.-A.)
- Center for RNA Interference and Non-Coding RNA, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Cristian Rodriguez-Aguayo
- Department of Experimental Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (A.S.); (G.L.-B.); (C.R.-A.)
- Center for RNA Interference and Non-Coding RNA, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Paola Amero
- Department of Experimental Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (A.S.); (G.L.-B.); (C.R.-A.)
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16
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Zhang X, Cao Q, Rajachandran S, Grow EJ, Evans M, Chen H. Dissecting mammalian reproduction with spatial transcriptomics. Hum Reprod Update 2023; 29:794-810. [PMID: 37353907 PMCID: PMC10628492 DOI: 10.1093/humupd/dmad017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Revised: 05/15/2023] [Indexed: 06/25/2023] Open
Abstract
BACKGROUND Mammalian reproduction requires the fusion of two specialized cells: an oocyte and a sperm. In addition to producing gametes, the reproductive system also provides the environment for the appropriate development of the embryo. Deciphering the reproductive system requires understanding the functions of each cell type and cell-cell interactions. Recent single-cell omics technologies have provided insights into the gene regulatory network in discrete cellular populations of both the male and female reproductive systems. However, these approaches cannot examine how the cellular states of the gametes or embryos are regulated through their interactions with neighboring somatic cells in the native tissue environment owing to tissue disassociations. Emerging spatial omics technologies address this challenge by preserving the spatial context of the cells to be profiled. These technologies hold the potential to revolutionize our understanding of mammalian reproduction. OBJECTIVE AND RATIONALE We aim to review the state-of-the-art spatial transcriptomics (ST) technologies with a focus on highlighting the novel biological insights that they have helped to reveal about the mammalian reproductive systems in the context of gametogenesis, embryogenesis, and reproductive pathologies. We also aim to discuss the current challenges of applying ST technologies in reproductive research and provide a sneak peek at what the field of spatial omics can offer for the reproduction community in the years to come. SEARCH METHODS The PubMed database was used in the search for peer-reviewed research articles and reviews using combinations of the following terms: 'spatial omics', 'fertility', 'reproduction', 'gametogenesis', 'embryogenesis', 'reproductive cancer', 'spatial transcriptomics', 'spermatogenesis', 'ovary', 'uterus', 'cervix', 'testis', and other keywords related to the subject area. All relevant publications until April 2023 were critically evaluated and discussed. OUTCOMES First, an overview of the ST technologies that have been applied to studying the reproductive systems was provided. The basic design principles and the advantages and limitations of these technologies were discussed and tabulated to serve as a guide for researchers to choose the best-suited technologies for their own research. Second, novel biological insights into mammalian reproduction, especially human reproduction revealed by ST analyses, were comprehensively reviewed. Three major themes were discussed. The first theme focuses on genes with non-random spatial expression patterns with specialized functions in multiple reproductive systems; The second theme centers around functionally interacting cell types which are often found to be spatially clustered in the reproductive tissues; and the thrid theme discusses pathological states in reproductive systems which are often associated with unique cellular microenvironments. Finally, current experimental and computational challenges of applying ST technologies to studying mammalian reproduction were highlighted, and potential solutions to tackle these challenges were provided. Future directions in the development of spatial omics technologies and how they will benefit the field of human reproduction were discussed, including the capture of cellular and tissue dynamics, multi-modal molecular profiling, and spatial characterization of gene perturbations. WIDER IMPLICATIONS Like single-cell technologies, spatial omics technologies hold tremendous potential for providing significant and novel insights into mammalian reproduction. Our review summarizes these novel biological insights that ST technologies have provided while shedding light on what is yet to come. Our review provides reproductive biologists and clinicians with a much-needed update on the state of art of ST technologies. It may also facilitate the adoption of cutting-edge spatial technologies in both basic and clinical reproductive research.
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Affiliation(s)
- Xin Zhang
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Qiqi Cao
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Shreya Rajachandran
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Edward J Grow
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Melanie Evans
- Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Haiqi Chen
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA
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17
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Li Z, Gu H, Xu X, Tian Y, Huang X, Du Y. Unveiling the novel immune and molecular signatures of ovarian cancer: insights and innovations from single-cell sequencing. Front Immunol 2023; 14:1288027. [PMID: 38022625 PMCID: PMC10654630 DOI: 10.3389/fimmu.2023.1288027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2023] [Accepted: 10/20/2023] [Indexed: 12/01/2023] Open
Abstract
Ovarian cancer is a highly heterogeneous and lethal malignancy with limited treatment options. Over the past decade, single-cell sequencing has emerged as an advanced biological technology capable of decoding the landscape of ovarian cancer at the single-cell resolution. It operates at the level of genes, transcriptomes, proteins, epigenomes, and metabolisms, providing detailed information that is distinct from bulk sequencing methods, which only offer average data for specific lesions. Single-cell sequencing technology provides detailed insights into the immune and molecular mechanisms underlying tumor occurrence, development, drug resistance, and immune escape. These insights can guide the development of innovative diagnostic markers, therapeutic strategies, and prognostic indicators. Overall, this review provides a comprehensive summary of the diverse applications of single-cell sequencing in ovarian cancer. It encompasses the identification and characterization of novel cell subpopulations, the elucidation of tumor heterogeneity, the investigation of the tumor microenvironment, the analysis of mechanisms underlying metastasis, and the integration of innovative approaches such as organoid models and multi-omics analysis.
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Affiliation(s)
- Zhongkang Li
- Department of Obstetrics and Gynecology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Haihan Gu
- Department of Pharmacy, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Xiaotong Xu
- Department of Obstetrics and Gynecology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Yanpeng Tian
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Xianghua Huang
- Department of Obstetrics and Gynecology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Yanfang Du
- Department of Obstetrics and Gynecology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
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18
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Azzalini E, Stanta G, Canzonieri V, Bonin S. Overview of Tumor Heterogeneity in High-Grade Serous Ovarian Cancers. Int J Mol Sci 2023; 24:15077. [PMID: 37894756 PMCID: PMC10606847 DOI: 10.3390/ijms242015077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 10/10/2023] [Indexed: 10/29/2023] Open
Abstract
Ovarian cancers encompass a group of neoplasms originating from germinal tissues and exhibiting distinct clinical, pathological, and molecular features. Among these, epithelial ovarian cancers (EOCs) are the most prevalent, comprising five distinct tumor histotypes. Notably, high-grade serous ovarian cancers (HGSOCs) represent the majority, accounting for over 70% of EOC cases. Due to their silent and asymptomatic behavior, HGSOCs are generally diagnosed in advanced stages with an evolved and complex genomic state, characterized by high intratumor heterogeneity (ITH) due to chromosomal instability that distinguishes HGSOCs. Histologically, these cancers exhibit significant morphological diversity both within and between tumors. The histologic patterns associated with solid, endometrioid, and transitional (SET) and classic subtypes of HGSOCs offer prognostic insights and may indicate specific molecular profiles. The evolution of HGSOC from primary to metastasis is typically characterized by clonal ITH, involving shared or divergent mutations in neoplastic sub-clones within primary and metastatic sites. Disease progression and therapy resistance are also influenced by non-clonal ITH, related to interactions with the tumor microenvironment and further genomic changes. Notably, significant alterations occur in nonmalignant cells, including cancer-associated fibroblast and immune cells, during tumor progression. This review provides an overview of the complex nature of HGSOC, encompassing its various aspects of intratumor heterogeneity, histological patterns, and its dynamic evolution during progression and therapy resistance.
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Affiliation(s)
- Eros Azzalini
- Department of Medical Sciences (DSM), University of Trieste, 34149 Trieste, Italy; (E.A.); (G.S.); (V.C.)
| | - Giorgio Stanta
- Department of Medical Sciences (DSM), University of Trieste, 34149 Trieste, Italy; (E.A.); (G.S.); (V.C.)
| | - Vincenzo Canzonieri
- Department of Medical Sciences (DSM), University of Trieste, 34149 Trieste, Italy; (E.A.); (G.S.); (V.C.)
- Pathology Unit, Centro di Riferimento Oncologico (CRO) IRCCS, Aviano-National Cancer Institute, 33081 Pordenone, Italy
| | - Serena Bonin
- Department of Medical Sciences (DSM), University of Trieste, 34149 Trieste, Italy; (E.A.); (G.S.); (V.C.)
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19
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Du J, An ZJ, Huang ZF, Yang YC, Zhang MH, Fu XH, Shi WY, Hou J. Novel insights from spatial transcriptome analysis in solid tumors. Int J Biol Sci 2023; 19:4778-4792. [PMID: 37781515 PMCID: PMC10539699 DOI: 10.7150/ijbs.83098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 08/03/2023] [Indexed: 10/03/2023] Open
Abstract
Since its first application in 2016, spatial transcriptomics has become a rapidly evolving technology in recent years. Spatial transcriptomics enables transcriptomic data to be acquired from intact tissue sections and provides spatial distribution information and remedies the disadvantage of single-cell RNA sequencing (scRNA-seq), whose data lack spatially resolved information. Presently, spatial transcriptomics has been widely applied to various tissue types, especially for the study of tumor heterogeneity. In this review, we provide a summary of the research progress in utilizing spatial transcriptomics to investigate tumor heterogeneity and the microenvironment with a focus on solid tumors. We summarize the research breakthroughs in various fields and perspectives due to the application of spatial transcriptomics, including cell clustering and interaction, cellular metabolism, gene expression, immune cell programs and combination with other techniques. As a combination of multiple transcriptomics, single-cell multiomics shows its superiority and validity in single-cell analysis. We also discuss the application prospect of single-cell multiomics, and we believe that with the progress of data integration from various transcriptomics, a multilayered subcellular landscape will be revealed.
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Affiliation(s)
- Jun Du
- Department of Hematology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujiang Road, Shanghai, 200127, China
| | - Zhi-Jie An
- School of Medicine, Shanghai Jiao Tong University, Shanghai, 200025, China
| | - Zou-Fang Huang
- Ganzhou Key Laboratory of Hematology, Department of Hematology, The First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi, 341000, China
| | - Yu-Chen Yang
- School of Medicine, Shanghai Jiao Tong University, Shanghai, 200025, China
| | - Ming-Hui Zhang
- School of Medicine, Shanghai Jiao Tong University, Shanghai, 200025, China
| | - Xue-Hang Fu
- Department of Hematology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujiang Road, Shanghai, 200127, China
| | - Wei-Yang Shi
- Ministry of Education Key Laboratory of Marine Genetics and Breeding, College of Marine Life Sciences, Ocean University of China, Qingdao 266003, China
| | - Jian Hou
- Department of Hematology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujiang Road, Shanghai, 200127, China
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20
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Szymanowska A, Rodriguez-Aguayo C, Lopez-Berestein G, Amero P. Non-Coding RNAs: Foes or Friends for Targeting Tumor Microenvironment. Noncoding RNA 2023; 9:52. [PMID: 37736898 PMCID: PMC10514839 DOI: 10.3390/ncrna9050052] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 08/17/2023] [Accepted: 08/22/2023] [Indexed: 09/23/2023] Open
Abstract
Non-coding RNAs (ncRNAs) are a group of molecules critical for cell development and growth regulation. They are key regulators of important cellular pathways in the tumor microenvironment. To analyze ncRNAs in the tumor microenvironment, the use of RNA sequencing technology has revolutionized the field. The advancement of this technique has broadened our understanding of the molecular biology of cancer, presenting abundant possibilities for the exploration of novel biomarkers for cancer treatment. In this review, we will summarize recent achievements in understanding the complex role of ncRNA in the tumor microenvironment, we will report the latest studies on the tumor microenvironment using RNA sequencing, and we will discuss the potential use of ncRNAs as therapeutics for the treatment of cancer.
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Affiliation(s)
- Anna Szymanowska
- Department of Experimental Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA; (A.S.); (C.R.-A.); (G.L.-B.)
| | - Cristian Rodriguez-Aguayo
- Department of Experimental Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA; (A.S.); (C.R.-A.); (G.L.-B.)
- Center for RNA Interference and Non-Coding RNA, Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA
| | - Gabriel Lopez-Berestein
- Department of Experimental Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA; (A.S.); (C.R.-A.); (G.L.-B.)
- Center for RNA Interference and Non-Coding RNA, Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA
| | - Paola Amero
- Department of Experimental Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA; (A.S.); (C.R.-A.); (G.L.-B.)
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21
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Guo D, Zhang S, Gao Y, Shi J, Wang X, Zhang Z, Zhang Y, Wang Y, Zhao K, Li M, Wang A, Wang P, Gou Y, Zhang M, Liu M, Zhang Y, Chen R, Sun J, Wang S, Wu X, Liang Z, Chen J, Lang J. Exploring the cellular and molecular differences between ovarian clear cell carcinoma and high-grade serous carcinoma using single-cell RNA sequencing and GEO gene expression signatures. Cell Biosci 2023; 13:139. [PMID: 37525249 PMCID: PMC10391916 DOI: 10.1186/s13578-023-01087-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 07/13/2023] [Indexed: 08/02/2023] Open
Abstract
The two most prevalent subtypes of epithelial ovarian carcinoma (EOC) are ovarian clear cell carcinoma (OCCC) and high-grade serous ovarian carcinoma (HGSC). Patients with OCCC have a poor prognosis than those with HGSC due to chemoresistance, implying the need for novel treatment target. In this study, we applied single-cell RNA sequencing (scRNA-seq) together with bulk RNA-seq data from the GEO (Gene Expression Omnibus) database (the GSE189553 dataset) to characterize and compare tumor heterogeneity and cell-level evolution between OCCC and HGSC samples. To begin, we found that the smaller proportion of an epithelial OCCC cell subset in the G2/M phase might explain OCCC chemoresistance. Second, we identified a possible pathogenic OCCC epithelial cell subcluster that overexpresses LEFTY1. Third, novel biomarkers separating OCCC from HGSC were discovered and subsequently validated on a wide scale using immunohistochemistry. Amine oxidase copper containing 1 (AOC1) was preferentially expressed in OCCC over HGSC, while S100 calcium-binding protein A2 (S100A2) was detected less frequently in OCCC than in HGSC. In addition, we discovered that metabolic pathways were enriched in the epithelial compartment of the OCCC samples. In vitro experiments verified that inhibition of oxidative phosphorylation or glycolysis pathways exerted direct antitumor effects on both OCCC and HGSC cells, while targeting glutamine metabolism or ferroptosis greatly attenuated chemosensitivity only in OCCC cells. Finally, to determine whether there were any variations in immune cell subsets between OCCC and HGSC, data from scRNA-seq and mass cytometry were pooled for analysis. In summary, our work provides the first holistic insights into the cellular and molecular distinctions between OCCC and HGSC and is a valuable source for discovering new targets to leverage in clinical treatments to improve the poor prognosis of patients with OCCC.
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Affiliation(s)
- Dan Guo
- Clinical Biobank, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- Department of Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Sumei Zhang
- Clinical Biobank, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- Department of Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yike Gao
- Department of Pathology, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, China
| | - Jinghua Shi
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
| | - Xiaoxi Wang
- Clinical Biobank, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- Department of Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Zixin Zhang
- Clinical Biobank, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- Department of Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yaran Zhang
- Clinical Biobank, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- Department of Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yuming Wang
- Department of Pathology, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, China
| | - Kun Zhao
- Clinical Biobank, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- Department of Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Mei Li
- Department of Pathology, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, China
| | - Anqi Wang
- Clinical Biobank, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- Department of Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Pan Wang
- Department of Pathology, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, China
- Department of Pathology, Affiliated Hospital of Hebei University, Baoding, China
| | - Yanqin Gou
- Department of Pathology, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, China
- Department of Pathology, People's Hospital of Ningxia Hui Autonomous Region, Yinchuan, China
| | - Miao Zhang
- Clinical Biobank, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- Department of Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Meiyu Liu
- Clinical Biobank, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- Department of Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yuhan Zhang
- Department of Pathology, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, China
| | - Rui Chen
- Department of Pathology, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, China
| | - Jian Sun
- Department of Pathology, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, China.
| | - Shu Wang
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
- National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China.
| | - Xunyao Wu
- Clinical Biobank, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
- Department of Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
| | - Zhiyong Liang
- Department of Pathology, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, China
| | - Jie Chen
- Department of Pathology, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, China
| | - Jinghe Lang
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
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Suzuki T, Conant A, Curow C, Alexander A, Ioffe Y, Unternaehrer JJ. Role of epithelial-mesenchymal transition factor SNAI1 and its targets in ovarian cancer aggressiveness. JOURNAL OF CANCER METASTASIS AND TREATMENT 2023; 9:25. [PMID: 38009093 PMCID: PMC10673625 DOI: 10.20517/2394-4722.2023.34] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/28/2023]
Abstract
Ovarian cancer remains the most lethal gynecologic malignancy in the USA. For over twenty years, epithelial-mesenchymal transition (EMT) has been characterized extensively in development and disease. The dysregulation of this process in cancer has been identified as a mechanism by which epithelial tumors become more aggressive, allowing them to survive and invade distant tissues. This occurs in part due to the increased expression of the EMT transcription factor, SNAI1 (Snail). In the case of epithelial ovarian cancer, Snail has been shown to contribute to cancer invasion, stemness, chemoresistance, and metabolic changes. Thus, in this review, we focus on summarizing current findings on the role of EMT (specifically, factors downstream of Snail) in determining ovarian cancer aggressiveness.
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Affiliation(s)
- Tise Suzuki
- Division of Biochemistry, Department of Basic Sciences, Loma Linda University, Loma Linda, CA 92354, USA
| | - Ashlyn Conant
- Division of Biochemistry, Department of Basic Sciences, Loma Linda University, Loma Linda, CA 92354, USA
| | - Casey Curow
- Division of Biochemistry, Department of Basic Sciences, Loma Linda University, Loma Linda, CA 92354, USA
- University of Redlands, Department of Biology, Redlands, CA 92373, USA
| | - Audrey Alexander
- Division of Biochemistry, Department of Basic Sciences, Loma Linda University, Loma Linda, CA 92354, USA
- Division of Natural and Mathematical Sciences, Department of Biological Sciences, California Baptist University, Riverside, CA 92504, USA
| | - Yevgeniya Ioffe
- Department of Gynecology and Obstetrics, Division of Gynecologic Oncology, Loma Linda University Medical Center, Loma Linda, CA 92354, USA
| | - Juli J Unternaehrer
- Division of Biochemistry, Department of Basic Sciences, Loma Linda University, Loma Linda, CA 92354, USA
- Department of Gynecology and Obstetrics, Loma Linda University, Loma Linda, CA 92354, USA
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23
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Ferri-Borgogno S, Zhu Y, Sheng J, Burks JK, Gomez JA, Wong KK, Wong ST, Mok SC. Spatial Transcriptomics Depict Ligand-Receptor Cross-talk Heterogeneity at the Tumor-Stroma Interface in Long-Term Ovarian Cancer Survivors. Cancer Res 2023; 83:1503-1516. [PMID: 36787106 PMCID: PMC10159916 DOI: 10.1158/0008-5472.can-22-1821] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 12/06/2022] [Accepted: 02/10/2023] [Indexed: 02/15/2023]
Abstract
Advanced high-grade serous ovarian cancer (HGSC) is an aggressive disease that accounts for 70% of all ovarian cancer deaths. Nevertheless, 15% of patients diagnosed with advanced HGSC survive more than 10 years. The elucidation of predictive markers of these long-term survivors (LTS) could help identify therapeutic targets for the disease, and thus improve patient survival rates. To investigate the stromal heterogeneity of the tumor microenvironment (TME) in ovarian cancer, we used spatial transcriptomics to generate spatially resolved transcript profiles in treatment-naïve advanced HGSC from LTS and short-term survivors (STS) and determined the association between cancer-associated fibroblasts (CAF) heterogeneity and survival in patients with advanced HGSC. Spatial transcriptomics and single-cell RNA-sequencing data were integrated to distinguish tumor and stroma regions, and a computational method was developed to investigate spatially resolved ligand-receptor interactions between various tumor and CAF subtypes in the TME. A specific subtype of CAFs and its spatial location relative to a particular ovarian cancer cell subtype in the TME correlated with long-term survival in patients with advanced HGSC. Also, increased APOE-LRP5 cross-talk occurred at the stroma-tumor interface in tumor tissues from STS compared with LTS. These findings were validated using multiplex IHC. Overall, this spatial transcriptomics analysis revealed spatially resolved CAF-tumor cross-talk signaling networks in the ovarian TME that are associated with long-term survival of patients with HGSC. Further studies to confirm whether such cross-talk plays a role in modulating the malignant phenotype of HGSC and could serve as a predictive biomarker of patient survival are warranted. SIGNIFICANCE Generation of spatially resolved gene expression patterns in tumors from patients with ovarian cancer surviving more than 10 years allows the identification of novel predictive biomarkers and therapeutic targets for better patient management. See related commentary by Kelliher and Lengyel, p. 1383.
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Affiliation(s)
- Sammy Ferri-Borgogno
- Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Ying Zhu
- Systems Medicine and Bioengineering Department, Houston Methodist Cancer Center, Houston Methodist Hospital, Houston, TX 77030, USA
- Departments of Pathology and Laboratory Medicine and Radiology, Houston Methodist Hospital, Weill Cornell Medicine, Houston, TX 77030, USA
| | - Jianting Sheng
- Systems Medicine and Bioengineering Department, Houston Methodist Cancer Center, Houston Methodist Hospital, Houston, TX 77030, USA
- Departments of Pathology and Laboratory Medicine and Radiology, Houston Methodist Hospital, Weill Cornell Medicine, Houston, TX 77030, USA
| | - Jared K. Burks
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Javier A. Gomez
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Kwong Kwok Wong
- Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Stephen T.C. Wong
- Systems Medicine and Bioengineering Department, Houston Methodist Cancer Center, Houston Methodist Hospital, Houston, TX 77030, USA
- Departments of Pathology and Laboratory Medicine and Radiology, Houston Methodist Hospital, Weill Cornell Medicine, Houston, TX 77030, USA
| | - Samuel C. Mok
- Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
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24
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Spatial RNA sequencing methods show high resolution of single cell in cancer metastasis and the formation of tumor microenvironment. Biosci Rep 2023; 43:232194. [PMID: 36459212 PMCID: PMC9950536 DOI: 10.1042/bsr20221680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 11/30/2022] [Accepted: 12/02/2022] [Indexed: 12/03/2022] Open
Abstract
Cancer metastasis often leads to death and therapeutic resistance. This process involves the participation of a variety of cell components, especially cellular and intercellular communications in the tumor microenvironment (TME). Using genetic sequencing technology to comprehensively characterize the tumor and TME is therefore key to understanding metastasis and therapeutic resistance. The use of spatial transcriptome sequencing enables the localization of gene expressions and cell activities in tissue sections. By examining the localization change as well as gene expression of these cells, it is possible to characterize the progress of tumor metastasis and TME formation. With improvements of this technology, spatial transcriptome sequencing technology has been extended from local regions to whole tissues, and from single sequencing technology to multimodal analysis combined with a variety of datasets. This has enabled the detection of every single cell in tissue slides, with high resolution, to provide more accurate predictive information for tumor treatments. In this review, we summarize the results of recent studies dealing with new multimodal methods and spatial transcriptome sequencing methods in tumors to illustrate recent developments in the imaging resolution of micro-tissues.
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25
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Liu HT, Chen SY, Peng LL, Zhong L, Zhou L, Liao SQ, Chen ZJ, Wang QL, He S, Zhou ZH. Spatially resolved transcriptomics revealed local invasion-related genes in colorectal cancer. Front Oncol 2023; 13:1089090. [PMID: 36816947 PMCID: PMC9928961 DOI: 10.3389/fonc.2023.1089090] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 01/16/2023] [Indexed: 02/04/2023] Open
Abstract
Objective Local invasion is the first step of metastasis, the main cause of colorectal cancer (CRC)-related death. Recent studies have revealed extensive intertumoral and intratumoral heterogeneity. Here, we focused on revealing local invasion-related genes in CRC. Methods We used spatial transcriptomic techniques to study the process of local invasion in four CRC tissues. First, we compared the pre-cancerous, cancer center, and invasive margin in one section (S115) and used pseudo-time analysis to reveal the differentiation trajectories from cancer center to invasive margin. Next, we performed immunohistochemical staining for RPL5, STC1, AKR1B1, CD47, and HLA-A on CRC samples. Moreover, we knocked down AKR1B1 in CRC cell lines and performed CCK-8, wound healing, and transwell assays to assess cell proliferation, migration, and invasion. Results We demonstrated that 13 genes were overexpressed in invasive clusters, among which the expression of CSTB and TM4SF1 was correlated with poor PFS in CRC patients. The ribosome pathway was increased, while the antigen processing and presentation pathway was decreased along CRC progression. RPL5 was upregulated, while HLA-A was downregulated along cancer invasion in CRC samples. Pseudo-time analysis revealed that STC1, AKR1B1, SIRPA, C4orf3, EDNRA, CES1, PRRX1, EMP1, PPIB, PLTP, SULF2, and EGFL6 were unpregulated along the trajectories. Immunohistochemic3al staining showed the expression of STC1, AKR1B1, and CD47 was increased along cancer invasion in CRC samples. Knockdown of AKR1B1 inhibited CRC cells' proliferation, migration, and invasion. Conclusions We revealed the spatial heterogeneity within CRC tissues and uncovered some novel genes that were associated with CRC invasion.
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Affiliation(s)
- Hong-Tao Liu
- Department of Gastroenterology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Si-Yuan Chen
- Department of Gastroenterology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China,Centre for Lipid Research & Key Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education), Institute for Viral Hepatitis, Department of Infectious Diseases, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Ling-Long Peng
- Department of Gastrointestinal Surgery, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Li Zhong
- Department of Gastroenterology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Li Zhou
- Department of Gastroenterology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Si-Qi Liao
- Department of Gastroenterology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Zhi-Ji Chen
- Department of Gastroenterology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Qing-Liang Wang
- Department of Pathology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Song He
- Department of Gastroenterology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China,*Correspondence: Zhi-Hang Zhou, ; Song He,
| | - Zhi-Hang Zhou
- Department of Gastroenterology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China,*Correspondence: Zhi-Hang Zhou, ; Song He,
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26
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Ospina O, Soupir A, Fridley BL. A Primer on Preprocessing, Visualization, Clustering, and Phenotyping of Barcode-Based Spatial Transcriptomics Data. Methods Mol Biol 2023; 2629:115-140. [PMID: 36929076 DOI: 10.1007/978-1-0716-2986-4_7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Abstract
Recent developments in spatially resolved transcriptomics (ST) have resulted in a large number of studies characterizing the architecture of tissues, the spatial distribution of cell types, and their interactions. Furthermore, ST promises to enable the discovery of more accurate drug targets while also providing a better understanding of the etiology and evolution of complex diseases. The analysis of ST brings similar challenges as seen in other gene expression assays such as scRNA-seq; however, there is the additional spatial information that warrants the development of suitable algorithms for the quality control, preprocessing, visualization, and other discovery-enabling approaches (e.g., clustering, cell phenotyping). In this chapter, we review some of the existing algorithms to perform these analytical tasks and highlight some of the unmet analytical challenges in the analysis of ST data. Given the diversity of available ST technologies, we focus this chapter on the analysis of barcode-based RNA quantitation techniques.
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Affiliation(s)
- Oscar Ospina
- Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, USA
| | - Alex Soupir
- Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, USA
| | - Brooke L Fridley
- Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA.
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Yu Q, Jiang M, Wu L. Spatial transcriptomics technology in cancer research. Front Oncol 2022; 12:1019111. [PMID: 36313703 PMCID: PMC9606570 DOI: 10.3389/fonc.2022.1019111] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Accepted: 09/21/2022] [Indexed: 08/25/2023] Open
Abstract
In recent years, spatial transcriptomics (ST) technologies have developed rapidly and have been widely used in constructing spatial tissue atlases and characterizing spatiotemporal heterogeneity of cancers. Currently, ST has been used to profile spatial heterogeneity in multiple cancer types. Besides, ST is a benefit for identifying and comprehensively understanding special spatial areas such as tumor interface and tertiary lymphoid structures (TLSs), which exhibit unique tumor microenvironments (TMEs). Therefore, ST has also shown great potential to improve pathological diagnosis and identify novel prognostic factors in cancer. This review presents recent advances and prospects of applications on cancer research based on ST technologies as well as the challenges.
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Affiliation(s)
- Qichao Yu
- Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Miaomiao Jiang
- Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, China
| | - Liang Wu
- Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, China
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Biswas A, Ghaddar B, Riedlinger G, De S. Inference on spatial heterogeneity in tumor microenvironment using spatial transcriptomics data. COMPUTATIONAL AND SYSTEMS ONCOLOGY 2022; 2:e21043. [PMID: 36035873 PMCID: PMC9410565 DOI: 10.1002/cso2.1043] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
In the tumor microenvironment (TME), functional interactions among tumor, immune, and stromal cells and the extracellular matrix play key roles in tumor progression, invasion, immune modulation, and response to treatment. Intratumor heterogeneity is ubiquitous not only at the genetic and transcriptomic levels but also in the composition and characteristics of TME. However, quantitative inference on spatial heterogeneity in the TME is still limited. Here, we propose a framework to use network graph-based spatial statistical models on spatially annotated molecular data to gain insights into modularity and spatial heterogeneity in the TME. Applying the framework to spatial transcriptomics data from pancreatic ductal adenocarcinoma samples, we observed significant global and local spatially correlated patterns in the abundance score of tumor cells; in contrast, immune cell types showed dispersed patterns in the TME. Hypoxia, EMT, and inflammation signatures contributed to intra-tumor spatial variations. Spatial patterns in cell type abundance and pathway signatures in the TME potentially impact tumor growth dynamics and cancer hallmarks. Tumor biopsies are integral to the diagnosis and clinical management of cancer patients; our data suggest that owing to intra-tumor non-genetic spatial heterogeneity, individual biopsies may underappreciate the extent of clinically relevant, functional variations across geographic regions within tumors.
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Affiliation(s)
- Antara Biswas
- Rutgers Cancer Institute, Rutgers the State University of New Jersey, New Brunswick, New Jersey, USA
| | - Bassel Ghaddar
- Rutgers Cancer Institute, Rutgers the State University of New Jersey, New Brunswick, New Jersey, USA
| | - Gregory Riedlinger
- Rutgers Cancer Institute, Rutgers the State University of New Jersey, New Brunswick, New Jersey, USA
| | - Subhajyoti De
- Rutgers Cancer Institute, Rutgers the State University of New Jersey, New Brunswick, New Jersey, USA
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Knowledge-graph-based cell-cell communication inference for spatially resolved transcriptomic data with SpaTalk. Nat Commun 2022; 13:4429. [PMID: 35908020 PMCID: PMC9338929 DOI: 10.1038/s41467-022-32111-8] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 07/18/2022] [Indexed: 12/19/2022] Open
Abstract
Spatially resolved transcriptomics provides genetic information in space toward elucidation of the spatial architecture in intact organs and the spatially resolved cell-cell communications mediating tissue homeostasis, development, and disease. To facilitate inference of spatially resolved cell-cell communications, we here present SpaTalk, which relies on a graph network and knowledge graph to model and score the ligand-receptor-target signaling network between spatially proximal cells by dissecting cell-type composition through a non-negative linear model and spatial mapping between single-cell transcriptomic and spatially resolved transcriptomic data. The benchmarked performance of SpaTalk on public single-cell spatial transcriptomic datasets is superior to that of existing inference methods. Then we apply SpaTalk to STARmap, Slide-seq, and 10X Visium data, revealing the in-depth communicative mechanisms underlying normal and disease tissues with spatial structure. SpaTalk can uncover spatially resolved cell-cell communications for single-cell and spot-based spatially resolved transcriptomic data universally, providing valuable insights into spatial inter-cellular tissue dynamics. Cell-cell communication is a vital feature involving numerous biological processes. Here, the authors develop SpaTalk, a cell-cell communication inference method using knowledge graph for spatially resolved transcriptomic data, providing valuable insights into spatial intercellular tissue dynamics.
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Peng Z, Ye M, Ding H, Feng Z, Hu K. Spatial transcriptomics atlas reveals the crosstalk between cancer-associated fibroblasts and tumor microenvironment components in colorectal cancer. Lab Invest 2022; 20:302. [PMID: 35794563 PMCID: PMC9258101 DOI: 10.1186/s12967-022-03510-8] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 06/27/2022] [Indexed: 11/10/2022]
Abstract
Background The tumor-promoting role of tumor microenvironment (TME) in colorectal cancer has been widely investigated in cancer biology. Cancer-associated fibroblasts (CAFs), as the main stromal component in TME, play an important role in promoting tumor progression and metastasis. Hence, we explored the crosstalk between CAFs and microenvironment in the pathogenesis of colorectal cancer in order to provide basis for precision therapy. Methods We integrated spatial transcriptomics (ST) and bulk-RNA sequencing datasets to explore the functions of CAFs in the microenvironment of CRC. In detail, single sample gene set enrichment analysis (ssGSEA), gene set variation analysis (GSVA), pseudotime analysis and cell proportion analysis were utilized to identify the cell types and functions of each cell cluster. Immunofluorescence and immunohistochemistry were applied to confirm the results based on bioinformatics analysis. Results We profiled the tumor heterogeneity landscape and identified two distinct types of CAFs, which myo-cancer-associated fibroblasts (mCAFs) is associated with myofibroblast-like cells and inflammatory-cancer-associated fibroblasts (iCAFs) is related to immune inflammation. When we carried out functional analysis of two types of CAFs, we uncovered an extensive crosstalk between iCAFs and stromal components in TME to promote tumor progression and metastasis. Noticeable, some anti-tumor immune cells such as NK cells, monocytes were significantly reduced in iCAFs-enriched cluster. Then, ssGSEA analysis results showed that iCAFs were related to EMT, lipid metabolism and bile acid metabolism etc. Besides, when we explored the relationship of chemotherapy and microenvironment, we detected that iCAFs influenced immunosuppressive cells and lipid metabolism reprogramming in patient who underwent chemotherapy. Additionally, we identified the clinical role of iCAFs through a public database and confirmed it were related to poor prognosis. Conclusions In summary, we identified two types of CAFs using integrated data and explored their functional significance in TME. This in-depth understanding of CAFs in microenvironment may help us to elucidate its cancer-promoting functions and offer hints for therapeutic studies. Supplementary Information The online version contains supplementary material available at 10.1186/s12967-022-03510-8.
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