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Niedra H, Peculis R, Saksis R, Mandrika I, Vilisova S, Nazarovs J, Breiksa A, Gerina A, Earl J, Ruz-Caracuel I, Rosas MG, Pukitis A, Senterjakova N, Rovite V. Tumor and α-SMA-expressing stromal cells in pancreatic neuroendocrine tumors have a distinct RNA profile depending on tumor grade. Mol Oncol 2024. [PMID: 39245631 DOI: 10.1002/1878-0261.13727] [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: 09/07/2023] [Revised: 07/12/2024] [Accepted: 08/22/2024] [Indexed: 09/10/2024] Open
Abstract
Alpha-smooth muscle actin (α-SMA) expression in the stroma is linked to the presence of cancer-associated fibroblasts and is known to correlate with worse outcomes in various tumors. In this study, using a GeoMx digital spatial profiling approach, we characterized the gene expression of the tumor and α-SMA-expressing stromal cell compartments in pancreatic neuroendocrine tumors (PanNETs). The profiling was performed on tissues from eight retrospective cases (three grade 1, four grade 2, and one grade 3). Selected regions of interest were segmented geometrically based on tissue morphology and fluorescent signals from synaptophysin and α-SMA markers. The α-SMA-expressing stromal-cell-associated genes were involved in pathways of extracellular matrix modification, whereas, in tumor cells, the gene expression profiles were associated with pathways involved in cell proliferation. The comparison of gene expression profiles across all three PanNET grades revealed that the differences between grades are not only present at the level of the tumor but also in the α-SMA-expressing stromal cells. Furthermore, the tumor cells from regions with a rich presence of adjacent α-SMA-expressing stromal cells revealed an upregulation of matrix metalloproteinase-9 (MMP9) expression in grade 3 tumors. This study provides an in-depth characterization of gene expression profiles in α-SMA-expressing stromal and tumor cells, and outlines potential crosstalk mechanisms.
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Affiliation(s)
- Helvijs Niedra
- Department of Molecular and Functional Genomics, Latvian Biomedical Research and Study Centre, Riga, Latvia
| | - Raitis Peculis
- Department of Molecular and Functional Genomics, Latvian Biomedical Research and Study Centre, Riga, Latvia
| | - Rihards Saksis
- Department of Molecular and Functional Genomics, Latvian Biomedical Research and Study Centre, Riga, Latvia
| | - Ilona Mandrika
- Department of Molecular and Functional Genomics, Latvian Biomedical Research and Study Centre, Riga, Latvia
| | - Sofija Vilisova
- Oncology clinic, Pauls Stradins Clinical University Hospital, Riga, Latvia
| | - Jurijs Nazarovs
- Institute of Pathology, Pauls Stradins Clinical University Hospital, Riga, Latvia
- Department of Pathology, Riga Stradins University, Latvia
| | - Austra Breiksa
- Institute of Pathology, Pauls Stradins Clinical University Hospital, Riga, Latvia
| | - Aija Gerina
- Oncology clinic, Pauls Stradins Clinical University Hospital, Riga, Latvia
| | - Julie Earl
- Ramón y Cajal Health Research Institute (IRYCIS), Ramón y Cajal University Hospital. Ctra. Colmenar Viejo, CIBERONC, Madrid, Spain
| | - Ignacio Ruz-Caracuel
- Ramón y Cajal Health Research Institute (IRYCIS), Ramón y Cajal University Hospital. Ctra. Colmenar Viejo, CIBERONC, Madrid, Spain
- Department of Pathology, Ramón y Cajal University Hospital. Ctra, Colmenar Viejo, Madrid, Spain
| | - Marta Gabriela Rosas
- Department of Pathology, Ramón y Cajal University Hospital. Ctra, Colmenar Viejo, Madrid, Spain
| | - Aldis Pukitis
- Centre of Gastroenterology, Hepatology and Nutrition Therapy, Pauls Stradins Clinical University Hospital, Riga, Latvia
| | - Natalja Senterjakova
- Centre of Gastroenterology, Hepatology and Nutrition Therapy, Pauls Stradins Clinical University Hospital, Riga, Latvia
| | - Vita Rovite
- Department of Molecular and Functional Genomics, Latvian Biomedical Research and Study Centre, Riga, Latvia
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2
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Hong WF, Zhang F, Wang N, Bi JM, Zhang DW, Wei LS, Song ZT, Mills GB, Chen MM, Li XX, Du SS, Yu M. Dynamic immunoediting by macrophages in homologous recombination deficiency-stratified pancreatic ductal adenocarcinoma. Drug Resist Updat 2024; 76:101115. [PMID: 39002266 DOI: 10.1016/j.drup.2024.101115] [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: 05/13/2024] [Revised: 06/19/2024] [Accepted: 06/25/2024] [Indexed: 07/15/2024]
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease, notably resistant to existing therapies. Current research indicates that PDAC patients deficient in homologous recombination (HR) benefit from platinum-based treatments and poly-ADP-ribose polymerase inhibitors (PARPi). However, the effectiveness of PARPi in HR-deficient (HRD) PDAC is suboptimal, and significant challenges remain in fully understanding the distinct characteristics and implications of HRD-associated PDAC. We analyzed 16 PDAC patient-derived tissues, categorized by their homologous recombination deficiency (HRD) scores, and performed high-plex immunofluorescence analysis to define 20 cell phenotypes, thereby generating an in-situ PDAC tumor-immune landscape. Spatial phenotypic-transcriptomic profiling guided by regions-of-interest (ROIs) identified a crucial regulatory mechanism through localized tumor-adjacent macrophages, potentially in an HRD-dependent manner. Cellular neighborhood (CN) analysis further demonstrated the existence of macrophage-associated high-ordered cellular functional units in spatial contexts. Using our multi-omics spatial profiling strategy, we uncovered a dynamic macrophage-mediated regulatory axis linking HRD status with SIGLEC10 and CD52. These findings demonstrate the potential of targeting CD52 in combination with PARPi as a therapeutic intervention for PDAC.
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Affiliation(s)
- Wei-Feng Hong
- Department of Pancreas Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China; Department of Radiation Oncology, Zhejiang Cancer Hospital, Hangzhou 310005, China; Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou 310005, China; Zhejiang Key Laboratory of Radiation Oncology, Hangzhou 310005, China
| | - Feng Zhang
- Department of Pancreas Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
| | - Nan Wang
- Cosmos Wisdom Biotech, co. ltd, Building 10, No. 617 Jiner Road, Hangzhou, Zhejiang, China
| | - Jun-Ming Bi
- Department of Urology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
| | - Ding-Wen Zhang
- Department of Pancreas Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
| | - Lu-Sheng Wei
- Department of Pancreas Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
| | - Zhen-Tao Song
- Mills Institute for Personalized Cancer Care, Fynn Biotechnologies Ltd. Jinan, Shandong, China
| | - Gordon B Mills
- Division of Oncological Sciences, Knight Cancer Institute, Oregon Health & Science University, Portland, USA
| | - Min-Min Chen
- Shenzhen Bay Laboratory, Shenzhen, Guangdong, China
| | - Xue-Xin Li
- Department of Physiology and Pharmacology, Karolinska Institutet, Solna 17165, Sweden.
| | - Shi-Suo Du
- Department of Radiation Oncology, Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China.
| | - Min Yu
- Department of Pancreas Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China.
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3
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Wang J, Alhaskawi A, Dong Y, Tian T, Abdalbary SA, Lu H. Advances in spatial multi-omics in tumors. TUMORI JOURNAL 2024:3008916241271458. [PMID: 39185632 DOI: 10.1177/03008916241271458] [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: 08/27/2024]
Abstract
Single-cell techniques have convincingly demonstrated that tumor tissue usually contains multiple genetically defined cell subclones with different gene mutation sets as well as various transcriptional profiles, but the spatial heterogeneity of the microenvironment and the macrobiological characteristics of the tumor ecosystem have not been described. For the past few years, spatial multi-omics technologies have revealed the cellular interactions, microenvironment, and even systemic tumor-host interactions in the tumor ecosystem at the spatial level, which can not only improve classical therapies such as surgery, radiotherapy, and chemotherapy but also promote the development of emerging targeted therapies in immunotherapy. Here, we review some emerging spatial omics techniques in cancer research and therapeutic applications and propose prospects for their future development.
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Affiliation(s)
- Junyan Wang
- The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Ahmad Alhaskawi
- Department of Orthopedics, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Yanzhao Dong
- Department of Orthopedics, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Tu Tian
- Department of Plastic Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Sahar Ahmed Abdalbary
- Department of Orthopedics, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
- Department of Orthopedic Physical Therapy, Faculty of Physical Therapy, Nahda University in Beni Suef, Beni Suef, Egypt
| | - Hui Lu
- The First Affiliated Hospital, Zhejiang University, Hangzhou, China
- Department of Orthopedics, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
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4
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Koedijk JB, van der Werf I, Penter L, Vermeulen MA, Barneh F, Perzolli A, Meesters-Ensing JI, Metselaar DS, Margaritis T, Fiocco M, de Groot-Kruseman HA, Moeniralam R, Bang Christensen K, Porter B, Pfaff K, Garcia JS, Rodig SJ, Wu CJ, Hasle H, Nierkens S, Belderbos ME, Zwaan CM, Heidenreich O. A multidimensional analysis reveals distinct immune phenotypes and the composition of immune aggregates in pediatric acute myeloid leukemia. Leukemia 2024:10.1038/s41375-024-02381-w. [PMID: 39187578 DOI: 10.1038/s41375-024-02381-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 08/02/2024] [Accepted: 08/13/2024] [Indexed: 08/28/2024]
Abstract
Because of the low mutational burden and consequently, fewer potential neoantigens, children with acute myeloid leukemia (AML) are thought to have a T cell-depleted or 'cold' tumor microenvironment and may have a low likelihood of response to T cell-directed immunotherapies. Understanding the composition, phenotype, and spatial organization of T cells and other microenvironmental populations in the pediatric AML bone marrow (BM) is essential for informing future immunotherapeutic trials about targetable immune-evasion mechanisms specific to pediatric AML. Here, we conducted a multidimensional analysis of the tumor immune microenvironment in pediatric AML and non-leukemic controls. We demonstrated that nearly one-third of pediatric AML cases has an immune-infiltrated BM, which is characterized by a decreased ratio of M2- to M1-like macrophages. Furthermore, we detected the presence of large T cell networks, both with and without colocalizing B cells, in the BM and dissected the cellular composition of T- and B cell-rich aggregates using spatial transcriptomics. These analyses revealed that these aggregates are hotspots of CD8+ T cells, memory B cells, plasma cells and/or plasmablasts, and M1-like macrophages. Collectively, our study provides a multidimensional characterization of the BM immune microenvironment in pediatric AML and indicates starting points for further investigations into immunomodulatory mechanisms in this devastating disease.
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Affiliation(s)
- Joost B Koedijk
- Princess Máxima Center for Pediatric Oncology, 3584 CS, Utrecht, The Netherlands
- Department of Pediatric Oncology, Erasmus MC/Sophia Children's Hospital, 3015 GD, Rotterdam, The Netherlands
| | - Inge van der Werf
- Princess Máxima Center for Pediatric Oncology, 3584 CS, Utrecht, The Netherlands
- Oncode Institute, 3521 AL, Utrecht, The Netherlands
- Sanford Stem Cell Institute, Division of Regenerative Medicine, Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Livius Penter
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
- Department of Hematology, Oncology, and Cancer Immunology, Campus Virchow Klinikum, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- German Cancer Consortium (DKTK), partner site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, BIH Charité Digital Clinician Scientist Program, Charitéplatz 1, 10117, Berlin, Germany
| | - Marijn A Vermeulen
- Princess Máxima Center for Pediatric Oncology, 3584 CS, Utrecht, The Netherlands
| | - Farnaz Barneh
- Princess Máxima Center for Pediatric Oncology, 3584 CS, Utrecht, The Netherlands
| | - Alicia Perzolli
- Princess Máxima Center for Pediatric Oncology, 3584 CS, Utrecht, The Netherlands
- Department of Pediatric Oncology, Erasmus MC/Sophia Children's Hospital, 3015 GD, Rotterdam, The Netherlands
| | | | - Dennis S Metselaar
- Princess Máxima Center for Pediatric Oncology, 3584 CS, Utrecht, The Netherlands
- Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ) and German Consortium (DKTK), Im Neuenheimer Feld 280, Heidelberg, Germany
| | - Thanasis Margaritis
- Princess Máxima Center for Pediatric Oncology, 3584 CS, Utrecht, The Netherlands
| | - Marta Fiocco
- Princess Máxima Center for Pediatric Oncology, 3584 CS, Utrecht, The Netherlands
- Mathematical Institute, Leiden University, Leiden, The Netherlands
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | | | - Rubina Moeniralam
- Princess Máxima Center for Pediatric Oncology, 3584 CS, Utrecht, The Netherlands
| | | | - Billie Porter
- Center for Immuno-Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Kathleen Pfaff
- Center for Immuno-Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Jacqueline S Garcia
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Scott J Rodig
- Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA
| | - Catherine J Wu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Henrik Hasle
- Pediatrics and Adolescent Medicine, Aarhus University Hospital, Aarhus, Denmark
| | - Stefan Nierkens
- Princess Máxima Center for Pediatric Oncology, 3584 CS, Utrecht, The Netherlands
- Center for Translational Immunology, University Medical Center Utrecht, 3584 CX, Utrecht, The Netherlands
| | - Mirjam E Belderbos
- Princess Máxima Center for Pediatric Oncology, 3584 CS, Utrecht, The Netherlands
| | - C Michel Zwaan
- Princess Máxima Center for Pediatric Oncology, 3584 CS, Utrecht, The Netherlands
- Department of Pediatric Oncology, Erasmus MC/Sophia Children's Hospital, 3015 GD, Rotterdam, The Netherlands
| | - Olaf Heidenreich
- Princess Máxima Center for Pediatric Oncology, 3584 CS, Utrecht, The Netherlands.
- University Medical Center Utrecht, 3584 CX, Utrecht, The Netherlands.
- Wolfson Childhood Cancer Research Centre, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK.
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5
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Charoensuksira S, Tantiwong S, Pongklaokam J, Hanvivattanakul S, Surinlert P, Krajarng A, Thanasarnaksorn W, Hongeng S, Ponnikorn S. Disturbance of Immune Microenvironment in Androgenetic Alopecia through Spatial Transcriptomics. Int J Mol Sci 2024; 25:9031. [PMID: 39201715 PMCID: PMC11354591 DOI: 10.3390/ijms25169031] [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: 06/03/2024] [Revised: 08/11/2024] [Accepted: 08/15/2024] [Indexed: 09/03/2024] Open
Abstract
Androgenetic alopecia (AGA) is characterized by microinflammation and abnormal immune responses, particularly in the upper segment of hair follicles (HFs). However, the precise patterns of immune dysregulation remain unclear, partly due to limitations in current analysis techniques to preserve tissue architecture. The infundibulum, a major part of the upper segment of HFs, is associated with significant clusters of immune cells. In this study, we investigated immune cells around the infundibulum, referred to as peri-infundibular immune infiltration (PII). We employed spatial transcriptome profiling, a high-throughput analysis technology, to investigate the immunological disruptions within the PII region. Our comprehensive analysis included an evaluation of overall immune infiltrates, gene set enrichment analysis (GSEA), cellular deconvolution, differential expression analysis, over-representation analysis, protein-protein interaction (PPI) networks, and upstream regulator analysis to identify cell types and molecular dysregulation in immune cells. Our results demonstrated significant differences in immune signatures between the PII of AGA patients (PII-A) and the PII of control donors (PII-C). Specifically, PII-A exhibited an enrichment of CD4+ helper T cells, distinct immune response patterns, and a bias toward a T helper (Th) 2 response. Immunohistochemistry revealed disruptions in T cell subpopulations, with more CD4+ T cells displaying an elevated Th2 response and a reduced Th1-cytotoxic response compared to PII-C. These findings reveal the unique immune landscapes of PII-A and PII-C, suggesting potential for the development of innovative treatment approaches.
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Affiliation(s)
- Sasin Charoensuksira
- Division of Dermatology, Chulabhorn International College of Medicine, Thammasat University, Pathum Thani 12120, Thailand; (S.C.); (S.T.); (J.P.); (W.T.)
| | - Supasit Tantiwong
- Division of Dermatology, Chulabhorn International College of Medicine, Thammasat University, Pathum Thani 12120, Thailand; (S.C.); (S.T.); (J.P.); (W.T.)
| | - Juthapa Pongklaokam
- Division of Dermatology, Chulabhorn International College of Medicine, Thammasat University, Pathum Thani 12120, Thailand; (S.C.); (S.T.); (J.P.); (W.T.)
| | - Sirashat Hanvivattanakul
- Chulabhorn International College of Medicine, Thammasat University, Pathum Thani 12120, Thailand; (S.H.); (P.S.); (A.K.)
| | - Piyaporn Surinlert
- Chulabhorn International College of Medicine, Thammasat University, Pathum Thani 12120, Thailand; (S.H.); (P.S.); (A.K.)
- Research Unit in Synthesis and Applications of Graphene, Thammasat University, Pathum Thani 12120, Thailand
| | - Aungkana Krajarng
- Chulabhorn International College of Medicine, Thammasat University, Pathum Thani 12120, Thailand; (S.H.); (P.S.); (A.K.)
| | - Wilai Thanasarnaksorn
- Division of Dermatology, Chulabhorn International College of Medicine, Thammasat University, Pathum Thani 12120, Thailand; (S.C.); (S.T.); (J.P.); (W.T.)
- Division of Dermatology, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok 10400, Thailand
| | - Suradej Hongeng
- Division of Hematology and Oncology, Department of Pediatrics, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok 10400, Thailand;
| | - Saranyoo Ponnikorn
- Division of Dermatology, Chulabhorn International College of Medicine, Thammasat University, Pathum Thani 12120, Thailand; (S.C.); (S.T.); (J.P.); (W.T.)
- Chulabhorn International College of Medicine, Thammasat University, Pathum Thani 12120, Thailand; (S.H.); (P.S.); (A.K.)
- Thammasat University, Pattaya Campus, Bang Lamung 20150, Thailand
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6
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Kurche JS, Cool CD, Blumhagen RZ, Dobrinskikh E, Heinz D, Herrera JA, Yang IV, Schwartz DA. MUC5B Idiopathic Pulmonary Fibrosis Risk Variant Promotes a Mucosecretory Phenotype and Loss of Small Airway Secretory Cells. Am J Respir Crit Care Med 2024; 210:517-521. [PMID: 38924494 PMCID: PMC11351810 DOI: 10.1164/rccm.202311-2111le] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 06/24/2024] [Indexed: 06/28/2024] Open
Affiliation(s)
- Jonathan S. Kurche
- Geriatric Research, Education, and Clinical Center, and
- Division of Pulmonary Sciences and Critical Care Medicine
| | | | - Rachel Z. Blumhagen
- Center for Genes, Environment, and Health, National Jewish Health, Denver, Colorado
| | | | | | | | - Ivana V. Yang
- Division of Pulmonary Sciences and Critical Care Medicine
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - David A. Schwartz
- Research Division, Rocky Mountain Regional Veterans Administration Medical Center, Aurora, Colorado
- Division of Pulmonary Sciences and Critical Care Medicine
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7
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Li Y, Luo Y. STdGCN: spatial transcriptomic cell-type deconvolution using graph convolutional networks. Genome Biol 2024; 25:206. [PMID: 39103939 DOI: 10.1186/s13059-024-03353-0] [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: 10/01/2023] [Accepted: 07/26/2024] [Indexed: 08/07/2024] Open
Abstract
Spatially resolved transcriptomics integrates high-throughput transcriptome measurements with preserved spatial cellular organization information. However, many technologies cannot reach single-cell resolution. We present STdGCN, a graph model leveraging single-cell RNA sequencing (scRNA-seq) as reference for cell-type deconvolution in spatial transcriptomic (ST) data. STdGCN incorporates expression profiles from scRNA-seq and spatial localization from ST data for deconvolution. Extensive benchmarking on multiple datasets demonstrates that STdGCN outperforms 17 state-of-the-art models. In a human breast cancer Visium dataset, STdGCN delineates stroma, lymphocytes, and cancer cells, aiding tumor microenvironment analysis. In human heart ST data, STdGCN identifies changes in endothelial-cardiomyocyte communications during tissue development.
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Affiliation(s)
- Yawei Li
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
- Center for Collaborative AI in Healthcare, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
| | - Yuan Luo
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA.
- Center for Collaborative AI in Healthcare, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA.
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8
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Jury-Garfe N, Redding-Ochoa J, You Y, Martínez P, Karahan H, Chimal-Juárez E, Johnson TS, Zhang J, Resnick S, Kim J, Troncoso JC, Lasagna-Reeves CA. Enhanced microglial dynamics and a paucity of tau seeding in the amyloid plaque microenvironment contribute to cognitive resilience in Alzheimer's disease. Acta Neuropathol 2024; 148:15. [PMID: 39102080 DOI: 10.1007/s00401-024-02775-1] [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: 05/21/2024] [Revised: 07/09/2024] [Accepted: 07/26/2024] [Indexed: 08/06/2024]
Abstract
Asymptomatic Alzheimer's disease (AsymAD) describes the status of individuals with preserved cognition but identifiable Alzheimer's disease (AD) brain pathology (i.e., beta-amyloid (Aβ) deposits, neuritic plaques, and neurofibrillary tangles) at autopsy. In this study, we investigated the postmortem brains of a cohort of AsymAD subjects to gain insight into the mechanisms underlying resilience to AD pathology and cognitive decline. Our results showed that AsymAD cases exhibit enrichment in core plaques, decreased filamentous plaque accumulation, and increased plaque-surrounding microglia. Less pathological tau aggregation in dystrophic neurites was found in AsymAD brains than in AD brains, and tau seeding activity was comparable to that in healthy brains. We used spatial transcriptomics to characterize the plaque niche further and revealed autophagy, endocytosis, and phagocytosis as the pathways associated with the genes upregulated in the AsymAD plaque niche. Furthermore, the levels of ARP2 and CAP1, which are actin-based motility proteins that participate in the dynamics of actin filaments to allow cell motility, were increased in the microglia surrounding amyloid plaques in AsymAD cases. Our findings suggest that the amyloid-plaque microenvironment in AsymAD cases is characterized by the presence of microglia with highly efficient actin-based cell motility mechanisms and decreased tau seeding compared with that in AD brains. These two mechanisms can potentially protect against the toxic cascade initiated by Aβ, preserving brain health, and slowing AD pathology progression.
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Affiliation(s)
- Nur Jury-Garfe
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Neurosciences Research Building 214G, 320 West 15th Street, Indianapolis, IN, 46202, USA
- Department of Anatomy, Cell Biology and Physiology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Javier Redding-Ochoa
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, USA
| | - Yanwen You
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Neurosciences Research Building 214G, 320 West 15th Street, Indianapolis, IN, 46202, USA
- Department of Anatomy, Cell Biology and Physiology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Pablo Martínez
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Neurosciences Research Building 214G, 320 West 15th Street, Indianapolis, IN, 46202, USA
- Department of Anatomy, Cell Biology and Physiology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Hande Karahan
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Neurosciences Research Building 214G, 320 West 15th Street, Indianapolis, IN, 46202, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, USA
| | - Enrique Chimal-Juárez
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Neurosciences Research Building 214G, 320 West 15th Street, Indianapolis, IN, 46202, USA
- Department of Anatomy, Cell Biology and Physiology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Travis S Johnson
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, USA
| | - Jie Zhang
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Susan Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging and National Institute of Health, Baltimore, MD, USA
| | - Jungsu Kim
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Neurosciences Research Building 214G, 320 West 15th Street, Indianapolis, IN, 46202, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, USA
| | - Juan C Troncoso
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, USA
| | - Cristian A Lasagna-Reeves
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Neurosciences Research Building 214G, 320 West 15th Street, Indianapolis, IN, 46202, USA.
- Department of Anatomy, Cell Biology and Physiology, Indiana University School of Medicine, Indianapolis, IN, USA.
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.
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9
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Ruscitti C, Abinet J, Maréchal P, Meunier M, de Meeûs C, Vanneste D, Janssen P, Dourcy M, Thiry M, Bureau F, Schneider C, Machiels B, Hidalgo A, Ginhoux F, Dewals BG, Guiot J, Schleich F, Garigliany MM, Bellahcène A, Radermecker C, Marichal T. Recruited atypical Ly6G + macrophages license alveolar regeneration after lung injury. Sci Immunol 2024; 9:eado1227. [PMID: 39093958 PMCID: PMC7616420 DOI: 10.1126/sciimmunol.ado1227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 05/31/2024] [Indexed: 08/04/2024]
Abstract
The lung is constantly exposed to airborne pathogens and particles that can cause alveolar damage. Hence, appropriate repair responses are essential for gas exchange and life. Here, we deciphered the spatiotemporal trajectory and function of an atypical population of macrophages after lung injury. Post-influenza A virus (IAV) infection, short-lived monocyte-derived Ly6G-expressing macrophages (Ly6G+ Macs) were recruited to the alveoli of lung perilesional areas. Ly6G+ Macs engulfed immune cells, exhibited a high metabolic potential, and clustered with alveolar type 2 epithelial cells (AT2s) in zones of active epithelial regeneration. Ly6G+ Macs were partially dependent on granulocyte-macrophage colony-stimulating factor and interleukin-4 receptor signaling and were essential for AT2-dependent alveolar regeneration. Similar macrophages were recruited in other models of injury and in the airspaces of lungs from patients with suspected pneumonia. This study identifies perilesional alveolar Ly6G+ Macs as a spatially restricted, short-lived macrophage subset promoting epithelial regeneration postinjury, thus representing an attractive therapeutic target for treating lung damage.
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Affiliation(s)
- Cecilia Ruscitti
- Laboratory of Immunophysiology, GIGA Institute, University of Liège, Liège, Belgium
- Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
| | - Joan Abinet
- Laboratory of Immunophysiology, GIGA Institute, University of Liège, Liège, Belgium
- Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
| | - Pauline Maréchal
- Laboratory of Immunophysiology, GIGA Institute, University of Liège, Liège, Belgium
- Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
| | - Margot Meunier
- Laboratory of Immunophysiology, GIGA Institute, University of Liège, Liège, Belgium
- Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
| | - Constance de Meeûs
- Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
- Department of Pathology, FARAH Institute, University of Liège, Liège, Belgium
| | - Domien Vanneste
- Laboratory of Immunophysiology, GIGA Institute, University of Liège, Liège, Belgium
- Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
| | - Pierre Janssen
- Laboratory of Immunophysiology, GIGA Institute, University of Liège, Liège, Belgium
- Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
| | - Mickael Dourcy
- Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
- Laboratory of Immunology-Vaccinology, FARAH Institute, University of Liège, Liège, Belgium
| | - Marc Thiry
- Laboratory of Cellular and Tissular Biology, GIGA Institute, University of Liège, Liège, Belgium
| | - Fabrice Bureau
- Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
- Laboratory of Cellular and Molecular Immunology, GIGA Institute, University of Liège, Liège, Belgium
| | | | - Benedicte Machiels
- Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
- Laboratory of Immunology-Vaccinology, FARAH Institute, University of Liège, Liège, Belgium
| | - Andres Hidalgo
- Area of Cell & Developmental Biology, Centro Nacional de Investigaciones Cardiovasculares Carlos III, Madrid, Spain
- Vascular Biology and Therapeutics Program and Department of Immunobiology, Yale University School of Medicine, New Haven, CT, USA
| | - Florent Ginhoux
- Shanghai Institute of Immunology, Shanghai JiaoTong University School of Medicine, Shanghai, China
- Inserm U1015, Gustave Roussy, Bâtiment de Médecine Moléculaire, Villejuif, France
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
- Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, Singapore
| | - Benjamin G Dewals
- Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
- Laboratory of Immunology-Vaccinology, FARAH Institute, University of Liège, Liège, Belgium
| | - Julien Guiot
- Laboratory of Pneumology, GIGA Institute, University of Liège, Liège, Belgium
- Department of Respiratory Medicine, CHU University Hospital, Liège, Belgium
| | - Florence Schleich
- Laboratory of Pneumology, GIGA Institute, University of Liège, Liège, Belgium
- Department of Respiratory Medicine, CHU University Hospital, Liège, Belgium
| | - Mutien-Marie Garigliany
- Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
- Department of Pathology, FARAH Institute, University of Liège, Liège, Belgium
| | - Akeila Bellahcène
- Metastasis Research Laboratory, GIGA Institute, University of Liège, Liège, Belgium
| | - Coraline Radermecker
- Laboratory of Immunophysiology, GIGA Institute, University of Liège, Liège, Belgium
- Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
| | - Thomas Marichal
- Laboratory of Immunophysiology, GIGA Institute, University of Liège, Liège, Belgium
- Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
- Walloon Excellence in Life Sciences and Biotechnology (WELBIO) Department, WEL Research Institute, Wavre, Belgium
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10
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Cross A, Harris JM, Arbe-Barnes E, Nixon C, Dhairyawan R, Hall A, Quaglia A, Issa F, Kennedy PTF, McKeating JA, Gill US, Peppa D. Characterisation of HBV and co-infection with HDV and HIV through spatial transcriptomics. EGASTROENTEROLOGY 2024; 2:e100067. [PMID: 39149129 PMCID: PMC11326438 DOI: 10.1136/egastro-2024-100067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Background and aims The intrahepatic processes associated with chronic hepatitis B (CHB), especially in the context of hepatitis delta virus (HDV) and HIV co-infection, require a better understanding. Spatial transcriptomics can provide new insights into the complex intrahepatic biological processes, guiding new personalised treatments. Our aim is to evaluate this method characterising the intrahepatic transcriptional landscape, cellular composition and biological pathways in liver biopsy samples from patients with hepatitis B virus (HBV) and HDV or HIV co-infection. Method The NanoString GeoMx digital spatial profiling platform was employed to assess expression of HBV surface antigen and CD45 in formalin-fixed paraffin-embedded (FFPE) biopsies from three treatment-naïve patients with chronic HBV and HDV or HIV co-infection. The GeoMx Human Whole Transcriptome Atlas assay quantified the expression of genes enriched in specific regions of interest (ROIs). Cell type proportions within ROIs were deconvoluted using a training matrix from the human liver cell atlas. A weighted gene correlation network analysis evaluated transcriptomic signatures across sampled regions. Results Spatially discrete transcriptomic signatures and distinct biological pathways were associated with HBV infection/disease status and immune responses. Shared features including 'cytotoxicity' and 'B cell receptor signalling' were consistent across patients, suggesting common elements alongside individual traits. HDV/HBV co-infection exhibited upregulated genes linked to apoptosis and immune cell recruitment, whereas HIV/HBV co-infection featured genes related to interferon response regulation. Varied cellular characteristics and immune cell populations, with an abundance of γδT cells in the HDV/HBV sample, were observed within analysed regions. Transcriptional differences in hepatocyte function suggest disrupted metabolic processes in HDV/HBV co-infection potentially impacting disease progression. Conclusion This proof-of-principle study shows the value of this platform in investigating the complex immune landscape, highlighting relevant host pathways to disease pathogenesis.
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Affiliation(s)
- Amy Cross
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - James M Harris
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Edward Arbe-Barnes
- Institute of Immunity and Transplantation, Division of Infection and Immunity, University College London, London, UK
| | - Colin Nixon
- Cancer Research UK, Scotalnd Institute, Glasgow, UK
| | - Rageshri Dhairyawan
- Division of Infection and Immunity, Barts Health NHS Trust, London, UK
- Centre for Immunobiology, Barts & The London School of Medicine & Dentistry, QMUL, London, UK
| | - Andrew Hall
- UCL Cancer Institute, Royal Free London NHS Foundation Trust, London, UK
| | - Alberto Quaglia
- UCL Cancer Institute, Royal Free London NHS Foundation Trust, London, UK
| | - Fadi Issa
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Patrick T F Kennedy
- Centre for Immunobiology, Barts & The London School of Medicine & Dentistry, QMUL, London, UK
| | - Jane A McKeating
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Chinese Academy of Medical Sciences Oxford Institute, University of Oxford, Oxford, UK
| | - Upkar S Gill
- Centre for Immunobiology, Barts & The London School of Medicine & Dentistry, QMUL, London, UK
| | - Dimitra Peppa
- Institute of Immunity and Transplantation, Division of Infection and Immunity, University College London, London, UK
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11
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Soul J, Carlsson E, Hofmann SR, Russ S, Hawkes J, Schulze F, Sergon M, Pablik J, Abraham S, Hedrich CM. Tissue gene expression profiles and communication networks inform candidate blood biomarker identification in psoriasis and atopic dermatitis. Clin Immunol 2024; 265:110283. [PMID: 38880200 DOI: 10.1016/j.clim.2024.110283] [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: 02/18/2024] [Revised: 05/24/2024] [Accepted: 06/10/2024] [Indexed: 06/18/2024]
Abstract
Overlapping clinical and pathomechanistic features can complicate the diagnosis and treatment of inflammatory skin diseases, including psoriasis and atopic dermatitis (AD). Spatial transcriptomics allows the identification of disease- and cell-specific molecular signatures that may advance biomarker development and future treatments. This study identified transcriptional signatures in keratinocytes and sub-basal CD4+ and CD8+ T lymphocytes from patients with psoriasis and AD. In silico prediction of ligand:receptor interactions delivered key signalling pathways (interferon, effector T cells, stroma cell and matrix biology, neuronal development, etc.). Targeted validation of selected transcripts, including CCL22, RELB, and JUND, in peripheral blood T cells suggests the chosen approach as a promising tool also in other inflammatory diseases. Psoriasis and AD are characterized by transcriptional dysregulation in T cells and keratinocytes that may be targeted therapeutically. Spatial transcriptomics is a valuable tool in the search for molecular signatures that can be used as biomarkers and/or therapeutic targets.
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Affiliation(s)
- J Soul
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
| | - E Carlsson
- Department of Women's & Children's Health, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, United Kingdom
| | - S R Hofmann
- Department of Pediatrics, Universitätsklinikum Carl Gustav Carus, TU Dresden, Dresden, Germany
| | - S Russ
- Department of Pediatrics, Universitätsklinikum Carl Gustav Carus, TU Dresden, Dresden, Germany
| | - J Hawkes
- Department of Women's & Children's Health, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, United Kingdom
| | - F Schulze
- Department of Pediatrics, Universitätsklinikum Carl Gustav Carus, TU Dresden, Dresden, Germany
| | - M Sergon
- Institut of Pathology, Universitätsklinikum Carl Gustav Carus, TU Dresden, Dresden, Germany
| | - J Pablik
- Institut of Pathology, Universitätsklinikum Carl Gustav Carus, TU Dresden, Dresden, Germany
| | - S Abraham
- Department of Dermatology, Universitätsklinikum Carl Gustav Carus, TU Dresden, Dresden, Germany
| | - C M Hedrich
- Department of Women's & Children's Health, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, United Kingdom; Department of Paediatric Rheumatology, Alder Hey Children's NHS Foundation Trust Hospital, Liverpool, United Kingdom.
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12
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Koedijk JB, van der Werf I, Penter L, Vermeulen MA, Barneh F, Perzolli A, Meesters-Ensing JI, Metselaar DS, Margaritis T, Fiocco M, de Groot-Kruseman HA, Moeniralam R, Bang Christensen K, Porter B, Pfaff K, Garcia JS, Rodig SJ, Wu CJ, Hasle H, Nierkens S, Belderbos ME, Zwaan CM, Heidenreich O. A multidimensional analysis reveals distinct immune phenotypes and the composition of immune aggregates in pediatric acute myeloid leukemia. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.03.03.23286485. [PMID: 37961528 PMCID: PMC10635226 DOI: 10.1101/2023.03.03.23286485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Because of the low mutational burden and consequently, fewer potential neoantigens, children with acute myeloid leukemia (AML) are thought to have a T cell-depleted or 'cold' tumor microenvironment and may have a low likelihood of response to T cell-directed immunotherapies. Understanding the composition, phenotype, and spatial organization of T cells and other microenvironmental populations in the pediatric AML bone marrow (BM) is essential for informing future immunotherapeutic trials about targetable immune-evasion mechanisms specific to pediatric AML. Here, we conducted a multidimensional analysis of the tumor immune microenvironment in pediatric AML and non-leukemic controls. We demonstrated that nearly one-third of pediatric AML cases has an immune-infiltrated BM, which is characterized by a decreased ratio of M2-to M1-like macrophages. Furthermore, we detected the presence of large T cell networks, both with and without colocalizing B cells, in the BM and dissected the cellular composition of T- and B cell-rich aggregates using spatial transcriptomics. These analyses revealed that these aggregates are hotspots of CD8 + T cells, memory B cells, plasma cells and/or plasmablasts, and M1-like macrophages. Collectively, our study provides a multidimensional characterization of the BM immune microenvironment in pediatric AML and indicates starting points for further investigations into immunomodulatory mechanisms in this devastating disease.
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13
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Liu K, Wang Y, Wang C, Guo C, Zhang D, Zhong Y, Yin L, Lu Y, Liu F, Zhang Y, Zhang D. Spatial transcriptomics of gastric cancer brain metastasis reveals atypical vasculature strategies with supportive immune profiles. Gastroenterol Rep (Oxf) 2024; 12:goae067. [PMID: 39027914 PMCID: PMC11257699 DOI: 10.1093/gastro/goae067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Revised: 05/26/2024] [Accepted: 05/31/2024] [Indexed: 07/20/2024] Open
Abstract
Background Gastric cancer brain metastasis (GCBM) represents a rare but highly aggressive malignancy. Metastatic cancer cells are highly heterogeneous and differentially remodels brain vasculature and immune microenvironments, which affects the treatment effectiveness and patient outcome. This study aimed to investigate the spatial interactions among different cell components, especially the vasculature system and the brain microenvironment of GCBM patients. Methods We used digital spatial profiling to examine 140 regions composing tumor, immune, and brain tissues from three GCBM patients. Transcriptomic data with spatial information were analyzed for tissue areas related to different blood recruitment strategies. For validation, independent analysis of patient bulk transcriptomic data and in vivo single-cell transcriptomic data were performed. Results Angiogenesis and blood vessel co-option co-existed within the same GCBM lesion. Tumors with high epithelial-mesenchymal transition and an enhanced transcriptomic gene signature composed of CTNNB1, SPARC, VIM, SMAD3, SMAD4, TGFB1, TGFB2, and TGFB3 were more prone to adopt blood vessel co-option than angiogenesis. Enriched macrophage infiltration, angiogenic chemokines, and NAMPT were found in angiogenic areas, while increased T cells, T cell activating cytokines, and reduced NAMPT were found in vessel co-option regions. Spatially, angiogenesis was enriched at the tumor edge, which showed higher DMBT1 expression than the tumor center. Conclusions This study mapped the orchestrated spatial characteristics of tumor and immunological compositions that support the conventional and atypical vascularization strategies in GCBM. Our data provided molecular insights for more effective combinations of anti-vascular and immune therapies.
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Affiliation(s)
- Kaijing Liu
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, P. R. China
- State Key Laboratory of Oncology in South China, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
| | - Ying Wang
- State Key Laboratory of Oncology in South China, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, P. R. China
| | - Chunhua Wang
- State Key Laboratory of Oncology in South China, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
- Department of Pathology, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, P. R. China
| | - Chengcheng Guo
- State Key Laboratory of Oncology in South China, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
- Department of Neurosurgery/Neuro-oncology, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, P. R. China
| | - Dun Zhang
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, P. R. China
- State Key Laboratory of Oncology in South China, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
| | - Yu Zhong
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, P. R. China
- State Key Laboratory of Oncology in South China, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
| | - Lin Yin
- AccuraMed Technology (Guangzhou) Co., Ltd, Guangzhou, Guangdong, P. R. China
| | - Yunxin Lu
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, P. R. China
- State Key Laboratory of Oncology in South China, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
| | - Furong Liu
- State Key Laboratory of Oncology in South China, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
- Department of Clinical Research, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, P. R. China
| | - Yang Zhang
- State Key Laboratory of Oncology in South China, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
- Department of Clinical Research, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, P. R. China
| | - Dongsheng Zhang
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, P. R. China
- State Key Laboratory of Oncology in South China, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China
- Integrated Traditional Chinese and Western Medicine Research Center, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, P. R. China
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14
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Love NR, Williams C, Killingbeck EE, Merleev A, Saffari Doost M, Yu L, McPherson JD, Mori H, Borowsky AD, Maverakis E, Kiuru M. Melanoma progression and prognostic models drawn from single-cell, spatial maps of benign and malignant tumors. SCIENCE ADVANCES 2024; 10:eadm8206. [PMID: 38996022 PMCID: PMC11244543 DOI: 10.1126/sciadv.adm8206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 06/06/2024] [Indexed: 07/14/2024]
Abstract
Melanoma clinical outcomes emerge from incompletely understood genetic mechanisms operating within the tumor and its microenvironment. Here, we used single-cell RNA-based spatial molecular imaging (RNA-SMI) in patient-derived archival tumors to reveal clinically relevant markers of malignancy progression and prognosis. We examined spatial gene expression of 203,472 cells inside benign and malignant melanocytic neoplasms, including melanocytic nevi and primary invasive and metastatic melanomas. Algorithmic cell clustering paired with intratumoral comparative two-dimensional analyses visualized synergistic, spatial gene signatures linking cellular proliferation, metabolism, and malignancy, validated by protein expression. Metastatic niches included up-regulation of CDK2 and FABP5, which independently predicted poor clinical outcome in 473 patients with melanoma via Cox regression analysis. More generally, our work demonstrates a framework for applying single-cell RNA-SMI technology toward identifying gene regulatory landscapes pertinent to cancer progression and patient survival.
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Affiliation(s)
- Nick R Love
- Department of Dermatology, University of California, Davis, Sacramento, CA 95816, USA
| | - Claire Williams
- NanoString Technologies, a Bruker Company, Seattle, WA 98109, USA
| | | | - Alexander Merleev
- Department of Dermatology, University of California, Davis, Sacramento, CA 95816, USA
| | | | - Lan Yu
- Department of Dermatology, University of California, Davis, Sacramento, CA 95816, USA
| | - John D McPherson
- Department of Biochemistry and Molecular Medicine, University of California, Davis, Sacramento, CA 95816, USA
| | - Hidetoshi Mori
- Department of Pathology and Laboratory Medicine, University of California, Davis, Sacramento, CA 95816, USA
| | - Alexander D Borowsky
- Department of Pathology and Laboratory Medicine, University of California, Davis, Sacramento, CA 95816, USA
| | - Emanual Maverakis
- Department of Dermatology, University of California, Davis, Sacramento, CA 95816, USA
| | - Maija Kiuru
- Department of Dermatology, University of California, Davis, Sacramento, CA 95816, USA
- Department of Pathology and Laboratory Medicine, University of California, Davis, Sacramento, CA 95816, USA
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15
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Shepard RM, Ghebremedhin A, Pratumchai I, Robinson SR, Betts C, Hu J, Sasik R, Fisch KM, Zak J, Chen H, Paradise M, Rivera J, Amjad M, Uchiyama S, Seo H, Campos AD, Dayao DA, Tzipori S, Piedra-Mora C, Das S, Hasteh F, Russo H, Sun X, Xu L, Crotty Alexander L, Duran JM, Odish M, Pretorius V, Kirchberger NC, Chin SM, Von Schalscha T, Cheresh D, Morrey JD, Alargova R, O’Connell B, Martinot TA, Patel SP, Nizet V, Martinot AJ, Coussens LM, Teijaro JR, Varner JA. PI3Kγ inhibition circumvents inflammation and vascular leak in SARS-CoV-2 and other infections. Sci Transl Med 2024; 16:eadi6887. [PMID: 38959328 PMCID: PMC11272418 DOI: 10.1126/scitranslmed.adi6887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 06/04/2024] [Indexed: 07/05/2024]
Abstract
Virulent infectious agents such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and methicillin-resistant Staphylococcus aureus (MRSA) induce tissue damage that recruits neutrophils, monocyte, and macrophages, leading to T cell exhaustion, fibrosis, vascular leak, epithelial cell depletion, and fatal organ damage. Neutrophils, monocytes, and macrophages recruited to pathogen-infected lungs, including SARS-CoV-2-infected lungs, express phosphatidylinositol 3-kinase gamma (PI3Kγ), a signaling protein that coordinates both granulocyte and monocyte trafficking to diseased tissues and immune-suppressive, profibrotic transcription in myeloid cells. PI3Kγ deletion and inhibition with the clinical PI3Kγ inhibitor eganelisib promoted survival in models of infectious diseases, including SARS-CoV-2 and MRSA, by suppressing inflammation, vascular leak, organ damage, and cytokine storm. These results demonstrate essential roles for PI3Kγ in inflammatory lung disease and support the potential use of PI3Kγ inhibitors to suppress inflammation in severe infectious diseases.
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Affiliation(s)
- Ryan M. Shepard
- Moores Cancer Center, University of California, San Diego, La Jolla, CA 92093
| | | | | | - Sally R. Robinson
- Department of Infectious Disease and Global Health, Cummings School of Veterinary Medicine, Tufts University North Grafton, MA 01536
- New England Regional Biosafety Laboratory, Cummings School of Veterinary Medicine, Tufts University, North Grafton, MA 01536
| | - Courtney Betts
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR 97201
| | - Jingjing Hu
- Department of Pathology, University of California, San Diego, La Jolla, CA 92093
| | - Roman Sasik
- Center for Computational Biology & Bioinformatics, University of California, San Diego, La Jolla, CA 92093
| | - Kathleen M. Fisch
- Center for Computational Biology & Bioinformatics, University of California, San Diego, La Jolla, CA 92093
- Department of Obstetrics, Gynecology & Reproductive Sciences, University of California, San Diego, La Jolla, CA 92093
| | - Jaroslav Zak
- Department of Immunology, The Scripps Research Institute, La Jolla CA 92037
| | - Hui Chen
- Moores Cancer Center, University of California, San Diego, La Jolla, CA 92093
| | - Marc Paradise
- Moores Cancer Center, University of California, San Diego, La Jolla, CA 92093
| | - Jason Rivera
- Moores Cancer Center, University of California, San Diego, La Jolla, CA 92093
| | - Mohammad Amjad
- Moores Cancer Center, University of California, San Diego, La Jolla, CA 92093
| | - Satoshi Uchiyama
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093
| | - Hideya Seo
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093
| | - Alejandro D. Campos
- Department of Pathology, University of California, San Diego, La Jolla, CA 92093
| | - Denise Ann Dayao
- Department of Infectious Disease and Global Health, Cummings School of Veterinary Medicine, Tufts University North Grafton, MA 01536
| | - Saul Tzipori
- Department of Infectious Disease and Global Health, Cummings School of Veterinary Medicine, Tufts University North Grafton, MA 01536
| | - Cesar Piedra-Mora
- Department of Comparative Pathobiology, Section of Pathology, Tufts University Cummings School of Veterinary Medicine, North Grafton, MA, USA 01536
| | - Soumita Das
- Department of Pathology, University of California, San Diego, La Jolla, CA 92093
| | - Farnaz Hasteh
- Department of Pathology, University of California, San Diego, La Jolla, CA 92093
| | - Hana Russo
- Department of Pathology, University of California, San Diego, La Jolla, CA 92093
| | - Xin Sun
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093
| | - Le Xu
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093
| | | | - Jason M. Duran
- Department of Medicine, University of California, San Diego, La Jolla, CA 92093
| | - Mazen Odish
- Department of Medicine, University of California, San Diego, La Jolla, CA 92093
| | - Victor Pretorius
- Department of Surgery, University of California, San Diego, La Jolla, CA 92093
| | - Nell C. Kirchberger
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR 97201
| | - Shao-ming Chin
- Moores Cancer Center, University of California, San Diego, La Jolla, CA 92093
| | - Tami Von Schalscha
- Department of Pathology, University of California, San Diego, La Jolla, CA 92093
| | - David Cheresh
- Department of Pathology, University of California, San Diego, La Jolla, CA 92093
| | - John D. Morrey
- The Institute for Antiviral Research, Animal, Dairy and Veterinary Science, Utah State University, Logan, UT 84322
| | | | | | | | - Sandip P. Patel
- Department of Medicine/Medical Oncology, University of California, San Diego, La Jolla, CA 92093
| | - Victor Nizet
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA 92093
| | - Amanda J. Martinot
- Department of Infectious Disease and Global Health, Cummings School of Veterinary Medicine, Tufts University North Grafton, MA 01536
- New England Regional Biosafety Laboratory, Cummings School of Veterinary Medicine, Tufts University, North Grafton, MA 01536
- Department of Comparative Pathobiology, Section of Pathology, Tufts University Cummings School of Veterinary Medicine, North Grafton, MA, USA 01536
| | - Lisa M. Coussens
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR 97201
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201
| | - John R. Teijaro
- Department of Immunology, The Scripps Research Institute, La Jolla CA 92037
| | - Judith A. Varner
- Moores Cancer Center, University of California, San Diego, La Jolla, CA 92093
- Department of Pathology, University of California, San Diego, La Jolla, CA 92093
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16
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Ospina OE, Manjarres-Betancur R, Gonzalez-Calderon G, Soupir AC, Smalley I, Tsai K, Markowitz J, Vallebuona E, Berglund A, Eschrich S, Yu X, Fridley BL. spatialGE: A user-friendly web application to democratize spatial transcriptomics analysis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.27.601050. [PMID: 39005315 PMCID: PMC11244876 DOI: 10.1101/2024.06.27.601050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Spatial transcriptomics (ST) is a powerful tool for understanding tissue biology and disease mechanisms. However, its potential is often underutilized due to the advanced data analysis and programming skills required. To address this, we present spatialGE, a web application that simplifies the analysis of ST data. The application spatialGE provides a user-friendly interface that guides users without programming expertise through various analysis pipelines, including quality control, normalization, domain detection, phenotyping, and multiple spatial analyses. It also enables comparative analysis among samples and supports various ST technologies. We demonstrate the utility of spatialGE through its application in studying the tumor microenvironment of melanoma brain metastasis and Merkel cell carcinoma. Our results highlight the ability of spatialGE to identify spatial gene expression patterns and enrichments, providing valuable insights into the tumor microenvironment and its utility in democratizing ST data analysis for the wider scientific community.
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Affiliation(s)
- Oscar E. Ospina
- Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, USA
| | | | | | - Alex C. Soupir
- Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, USA
| | - Inna Smalley
- Department of Metabolism and Physiology, Moffitt Cancer Center, Tampa, FL, USA
| | - Kenneth Tsai
- Department of Pathology, Moffitt Cancer Center, Tampa, FL, USA
| | - Joseph Markowitz
- Department of Cutaneous Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | - Ethan Vallebuona
- Department of Metabolism and Physiology, Moffitt Cancer Center, Tampa, FL, USA
| | - Anders Berglund
- Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, USA
| | - Steven Eschrich
- Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, USA
| | - Xiaoqing Yu
- Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, USA
| | - Brooke L. Fridley
- Division of Health Services and Outcomes Research, Children’s Mercy, Kansas City, MO, USA
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17
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Boe RH, Triandafillou CG, Lazcano R, Wargo JA, Raj A. Spatial transcriptomics reveals influence of microenvironment on intrinsic fates in melanoma therapy resistance. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.30.601416. [PMID: 39005406 PMCID: PMC11244927 DOI: 10.1101/2024.06.30.601416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Resistance to cancer therapy is driven by both cell-intrinsic and microenvironmental factors. Previous work has revealed that multiple resistant cell fates emerge in melanoma following treatment with targeted therapy and that, in vitro, these resistant fates are determined by the transcriptional state of individual cells prior to exposure to treatment. What remains unclear is whether these resistant fates are shared across different genetic backgrounds and how, if at all, these resistant fates interact with the tumor microenvironment. Through spatial transcriptomics and single-cell RNA sequencing, we uncovered distinct resistance programs in melanoma cells shaped by both intrinsic cellular states and the tumor microenvironment. Consensus non-negative matrix factorization revealed shared intrinsic resistance programs across different cell lines, highlighting the presence of universal and unique resistance pathways. In patient samples, we demonstrated that these resistance programs coexist within individual tumors and associate with diverse immune signatures, suggesting that the tumor microenvironment and distribution of resistant fates are closely connected. Single-cell resolution spatial transcriptomics in xenograft models revealed both intrinsically determined and extrinsically influenced resistant fates. Overall, this work demonstrates that each therapy resistant fate coexists with a distinct immune microenvironment in tumors and that, in vivo, tissue features, such as regions of necrosis, can influence which resistant fate is adopted.
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Affiliation(s)
- Ryan H. Boe
- Genetics and Epigenetics Program, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Catherine G. Triandafillou
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA
| | - Rossana Lazcano
- Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jennifer A. Wargo
- Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Arjun Raj
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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18
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Groen-van Schooten TS, Franco Fernandez R, van Grieken NCT, Bos EN, Seidel J, Saris J, Martínez-Ciarpaglini C, Fleitas TC, Thommen DS, de Gruijl TD, Grootjans J, Derks S. Mapping the complexity and diversity of tertiary lymphoid structures in primary and peritoneal metastatic gastric cancer. J Immunother Cancer 2024; 12:e009243. [PMID: 38955417 PMCID: PMC11218001 DOI: 10.1136/jitc-2024-009243] [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] [Accepted: 06/13/2024] [Indexed: 07/04/2024] Open
Abstract
BACKGROUND Tertiary lymphoid structures (TLSs) are thought to stimulate antitumor immunity and positively impact prognosis and response to immune checkpoint blockade. In gastric cancers (GCs), however, TLSs are predominantly found in GC with poor prognosis and limited treatment response. We, therefore, hypothesize that immune cell composition and function of TLS depends on tumor location and the tumor immune environment. METHODS Spatial transcriptomics and immunohistochemistry were used to characterize the phenotype of CD45+ immune cells inside and outside of TLS using archival resection specimens from GC primary tumors and peritoneal metastases. RESULTS We identified significant intrapatient and interpatient diversity of the cellular composition and maturation status of TLS in GC. Tumor location (primary vs metastatic site) accounted for the majority of differences in TLS maturity, as TLS in peritoneal metastases were predominantly immature. This was associated with higher levels of tumor-infiltrating macrophages and Tregs and less plasma cells compared with tumors with mature TLS. Furthermore, mature TLSs were characterized by overexpression of antitumor immune pathways such as B cell-related pathways, MHC class II antigen presentation while immature TLS were associated with protumor pathways, including T cell exhaustion and enhancement of DNA repair pathways in the corresponding cancer. CONCLUSION The observation that GC-derived peritoneal metastases often contain immature TLS which are associated with immune suppressive regulatory tumor-infiltrating leucocytes, is in keeping with the lack of response to immune checkpoint blockade and the poor prognostic features of peritoneal metastatic GC, which needs to be taken into account when optimizing immunomodulatory strategies for metastatic GC.
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Affiliation(s)
- Tessa S Groen-van Schooten
- Department of Medical Oncology, Amsterdam UMC Locatie VUmc, Amsterdam, The Netherlands
- Oncode Institute, Amsterdam, The Netherlands
| | - Rosalia Franco Fernandez
- Oncode Institute, Amsterdam, The Netherlands
- Department of Gastroenterology and Hepatology & Tytgat Institute for Liver and Intestinal Research, Amsterdam UMC Locatie AMC, Amsterdam, The Netherlands
| | - Nicole C T van Grieken
- Cancer Biology and Immunology, Cancer Centre Amsterdam, Amsterdam, The Netherlands
- Department of Pathology, Amsterdam UMC Locatie VUmc, Amsterdam, The Netherlands
| | - Emma N Bos
- Department of Medical Oncology, Amsterdam UMC Locatie VUmc, Amsterdam, The Netherlands
- Oncode Institute, Amsterdam, The Netherlands
| | - Jens Seidel
- Department of Medical Oncology, Amsterdam UMC Locatie VUmc, Amsterdam, The Netherlands
- Oncode Institute, Amsterdam, The Netherlands
| | - Job Saris
- Oncode Institute, Amsterdam, The Netherlands
- Department of Gastroenterology and Hepatology & Tytgat Institute for Liver and Intestinal Research, Amsterdam UMC Locatie AMC, Amsterdam, The Netherlands
| | | | | | - Daniela S Thommen
- Oncode Institute, Amsterdam, The Netherlands
- Molecular Oncology and Immunology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Tanja D de Gruijl
- Department of Medical Oncology, Amsterdam UMC Locatie VUmc, Amsterdam, The Netherlands
- Cancer Biology and Immunology, Cancer Centre Amsterdam, Amsterdam, The Netherlands
| | - Joep Grootjans
- Oncode Institute, Amsterdam, The Netherlands
- Department of Gastroenterology and Hepatology & Tytgat Institute for Liver and Intestinal Research, Amsterdam UMC Locatie AMC, Amsterdam, The Netherlands
| | - Sarah Derks
- Department of Medical Oncology, Amsterdam UMC Locatie VUmc, Amsterdam, The Netherlands
- Oncode Institute, Amsterdam, The Netherlands
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19
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Nevarez-Mejia J, Pickering H, Sosa RA, Valenzuela NM, Fishbein GA, Baldwin WM, Fairchild RL, Reed EF. Spatial multiomics of arterial regions from cardiac allograft vasculopathy rejected grafts reveal novel insights into the pathogenesis of chronic antibody-mediated rejection. Am J Transplant 2024; 24:1146-1160. [PMID: 38219867 PMCID: PMC11239797 DOI: 10.1016/j.ajt.2024.01.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 12/22/2023] [Accepted: 01/04/2024] [Indexed: 01/16/2024]
Abstract
Cardiac allograft vasculopathy (CAV) causes late graft failure and mortality after heart transplantation. Donor-specific antibodies (DSAs) lead to chronic endothelial cell injury, inflammation, and arterial intimal thickening. In this study, GeoMx digital spatial profiling was used to analyze arterial areas of interest (AOIs) from CAV+DSA+ rejected cardiac allografts (N = 3; 22 AOIs total). AOIs were categorized based on CAV neointimal thickening and underwent whole transcriptome and protein profiling. By comparing our transcriptomic data with that of healthy control vessels of rapid autopsy myocardial tissue, we pinpointed specific pathways and transcripts indicative of heightened inflammatory profiles in CAV lesions. Moreover, we identified protein and transcriptomic signatures distinguishing CAV lesions exhibiting low and high neointimal lesions. AOIs with low neointima showed increased markers for activated inflammatory infiltrates, endothelial cell activation transcripts, and gene modules involved in metalloproteinase activation and TP53 regulation of caspases. Inflammatory and apoptotic proteins correlated with inflammatory modules in low neointima AOIs. High neointima AOIs exhibited elevated TGFβ-regulated transcripts and modules enriched for platelet activation/aggregation. Proteins associated with growth factors/survival correlated with modules enriched for proliferation/repair in high neointima AOIs. Our findings reveal novel insight into immunological mechanisms mediating CAV pathogenesis.
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Affiliation(s)
- Jessica Nevarez-Mejia
- Department of Pathology and Laboratory Medicine, University of California, Los Angeles, California, USA
| | - Harry Pickering
- Department of Pathology and Laboratory Medicine, University of California, Los Angeles, California, USA
| | - Rebecca A Sosa
- Department of Pathology and Laboratory Medicine, University of California, Los Angeles, California, USA
| | - Nicole M Valenzuela
- Department of Pathology and Laboratory Medicine, University of California, Los Angeles, California, USA
| | - Gregory A Fishbein
- Department of Pathology and Laboratory Medicine, University of California, Los Angeles, California, USA
| | - William M Baldwin
- Department of Inflammation & Immunity, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Robert L Fairchild
- Department of Inflammation & Immunity, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Elaine F Reed
- Department of Pathology and Laboratory Medicine, University of California, Los Angeles, California, USA.
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20
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Li YL, Chen CH, Lai YS, Pan MR, Hung WC. Increased blood CSF3R + myeloid-derived suppressor cell is a predictor for breast cancer recurrence. Am J Cancer Res 2024; 14:3171-3185. [PMID: 39005677 PMCID: PMC11236774 DOI: 10.62347/mukd2745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2024] [Accepted: 06/17/2024] [Indexed: 07/16/2024] Open
Abstract
Early detection of cancer recurrence using specific biomarkers remains a clinically unmet need, although methodologies for monitoring tumor markers, cell-free DNA, and circulating tumor cells have been established for decades. Tumor recurrence develops in metastatic or dormant cancer cells under continuous immune surveillance. Alterations in the population and function of immune cells may contribute to cancer recurrence. Here, we utilized an animal model to imitate breast tumor recurrence after surgical resection and investigated the abundance and gene expression profiles of immune cells using NanoString analysis. Bioinformatic analysis of a published single-cell RNA sequencing database of myeloid-derived suppressor cells (MDSCs) was performed to identify common targets between the two studies. Identified biomarkers were validated using human peripheral blood mononuclear cell (PBMC) datasets. The inhibitory effect of MDSCs on T-cell proliferation was assessed in vitro. Our data demonstrated that the number of MDSCs significantly increased during recurrence. Comparison of our NanoString data with a single-cell RNA sequencing dataset of MDSCs in another spontaneous breast cancer model identified colony-stimulating factor 3 receptor (Csf3r)-positive MDSCs as a potential marker for predicting tumor relapse. We validated our findings using two previously published PBMC databases of patients with breast cancer with or without recurrence and confirmed the elevated MDSC gene signature and CSF3R expression in patients with tumor recurrence. 35 patients with breast cancer were also included in our study, that patients with higher levels of CSF3R had worse survival. In vitro experiments demonstrated that Csf3r + MDSCs exhibited enhanced reactive oxygen species (ROS) levels and robust T-cell suppression ability. We conclude that an increase in CSF3R + MDSCs is a potential biomarker for early detection of tumor recurrence in patients with breast cancer.
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Affiliation(s)
- Yen-Liang Li
- National Institute of Cancer Research, National Health Research InstitutesTainan 704, Taiwan
| | - Chung-Hsing Chen
- National Institute of Cancer Research, National Health Research InstitutesTainan 704, Taiwan
| | - You-Syuan Lai
- National Institute of Cancer Research, National Health Research InstitutesTainan 704, Taiwan
| | - Mei-Ren Pan
- Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical UniversityKaohsiung 807, Taiwan
| | - Wen-Chun Hung
- National Institute of Cancer Research, National Health Research InstitutesTainan 704, Taiwan
- School of Pharmacy, College of Pharmacy, Kaohsiung Medical UniversityKaohsiung 807, Taiwan
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21
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Lokhande L, Nilsson D, de Matos Rodrigues J, Hassan M, Olsson LM, Pyl PT, Vasquez L, Porwit A, Gerdtsson AS, Jerkeman M, Ek S. Quantification and Profiling of Early and Late Differentiation Stage T Cells in Mantle Cell Lymphoma Reveals Immunotherapeutic Targets in Subsets of Patients. Cancers (Basel) 2024; 16:2289. [PMID: 39001353 PMCID: PMC11240320 DOI: 10.3390/cancers16132289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Revised: 06/12/2024] [Accepted: 06/13/2024] [Indexed: 07/16/2024] Open
Abstract
With the aim to advance the understanding of immune regulation in MCL and to identify targetable T-cell subsets, we set out to combine image analysis and spatial omic technology focused on both early and late differentiation stages of T cells. MCL patient tissue (n = 102) was explored using image analysis and GeoMx spatial omics profiling of 69 proteins and 1812 mRNAs. Tumor cells, T helper (TH) cells and cytotoxic (TC) cells of early (CD57-) and late (CD57+) differentiation stage were analyzed. An image analysis workflow was developed based on fine-tuned Cellpose models for cell segmentation and classification. TC and CD57+ subsets of T cells were enriched in tumor-rich compared to tumor-sparse regions. Tumor-sparse regions had a higher expression of several key immune suppressive proteins, tentatively controlling T-cell expansion in regions close to the tumor. We revealed that T cells in late differentiation stages (CD57+) are enriched among MCL infiltrating T cells and are predictive of an increased expression of immune suppressive markers. CD47, IDO1 and CTLA-4 were identified as potential targets for patients with T-cell-rich MCL TIME, while GITR might be a feasible target for MCL patients with sparse T-cell infiltration. In subgroups of patients with a high degree of CD57+ TC-cell infiltration, several immune checkpoint inhibitors, including TIGIT, PD-L1 and LAG3 were increased, emphasizing the immune-suppressive features of this highly differentiated T-cell subset not previously described in MCL.
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Affiliation(s)
- Lavanya Lokhande
- Department of Immunotechnology, Lund University, 221 00 Lund, Sweden
| | - Daniel Nilsson
- Department of Immunotechnology, Lund University, 221 00 Lund, Sweden
| | | | - May Hassan
- Department of Immunotechnology, Lund University, 221 00 Lund, Sweden
| | - Lina M. Olsson
- Department of Immunotechnology, Lund University, 221 00 Lund, Sweden
| | - Paul-Theodor Pyl
- Department of Laboratory Medicine, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Lund University, 221 00 Lund, Sweden
| | - Louella Vasquez
- Department of Laboratory Medicine, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Lund University, 221 00 Lund, Sweden
| | - Anna Porwit
- Division of Oncology and Pathology, Department of Clinical Sciences, Lund University, 221 00 Lund, Sweden
| | | | - Mats Jerkeman
- Division of Oncology and Pathology, Department of Clinical Sciences, Lund University, 221 00 Lund, Sweden
| | - Sara Ek
- Department of Immunotechnology, Lund University, 221 00 Lund, Sweden
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22
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Desai P, Takahashi N, Kumar R, Nichols S, Malin J, Hunt A, Schultz C, Cao Y, Tillo D, Nousome D, Chauhan L, Sciuto L, Jordan K, Rajapakse V, Tandon M, Lissa D, Zhang Y, Kumar S, Pongor L, Singh A, Schroder B, Sharma AK, Chang T, Vilimas R, Pinkiert D, Graham C, Butcher D, Warner A, Sebastian R, Mahon M, Baker K, Cheng J, Berger A, Lake R, Abel M, Krishnamurthy M, Chrisafis G, Fitzgerald P, Nirula M, Goyal S, Atkinson D, Bateman NW, Abulez T, Nair G, Apolo A, Guha U, Karim B, El Meskini R, Ohler ZW, Jolly MK, Schaffer A, Ruppin E, Kleiner D, Miettinen M, Brown GT, Hewitt S, Conrads T, Thomas A. Microenvironment shapes small-cell lung cancer neuroendocrine states and presents therapeutic opportunities. Cell Rep Med 2024; 5:101610. [PMID: 38897168 PMCID: PMC11228806 DOI: 10.1016/j.xcrm.2024.101610] [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: 03/02/2023] [Revised: 08/04/2023] [Accepted: 05/17/2024] [Indexed: 06/21/2024]
Abstract
Small-cell lung cancer (SCLC) is the most fatal form of lung cancer. Intratumoral heterogeneity, marked by neuroendocrine (NE) and non-neuroendocrine (non-NE) cell states, defines SCLC, but the cell-extrinsic drivers of SCLC plasticity are poorly understood. To map the landscape of SCLC tumor microenvironment (TME), we apply spatially resolved transcriptomics and quantitative mass spectrometry-based proteomics to metastatic SCLC tumors obtained via rapid autopsy. The phenotype and overall composition of non-malignant cells in the TME exhibit substantial variability, closely mirroring the tumor phenotype, suggesting TME-driven reprogramming of NE cell states. We identify cancer-associated fibroblasts (CAFs) as a crucial element of SCLC TME heterogeneity, contributing to immune exclusion, and predicting exceptionally poor prognosis. Our work provides a comprehensive map of SCLC tumor and TME ecosystems, emphasizing their pivotal role in SCLC's adaptable nature, opening possibilities for reprogramming the TME-tumor communications that shape SCLC tumor states.
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Affiliation(s)
- Parth Desai
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA; Department of Medical Oncology, Fox Chase Cancer Center, Temple University Hospital and Lewis Katz School of Medicine, Philadelphia, PA, USA
| | - Nobuyuki Takahashi
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA; Department of Medical Oncology, National Cancer Center Hospital East, Kashiwa, Japan
| | - Rajesh Kumar
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Samantha Nichols
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Justin Malin
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Allison Hunt
- Women's Health Integrated Research Center, Inova Health System, Falls Church, VA, USA
| | - Christopher Schultz
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Yingying Cao
- Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Desiree Tillo
- CCR Collaborative Bioinformatics, Resource, Office of Science and Technology Resources, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Darryl Nousome
- CCR Collaborative Bioinformatics, Resource, Office of Science and Technology Resources, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Lakshya Chauhan
- Center for Biosystems Science and Engineering, Indian Institute of Science, Bangalore, India
| | - Linda Sciuto
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Kimberly Jordan
- Department of Immunology and Microbiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Vinodh Rajapakse
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Mayank Tandon
- CCR Collaborative Bioinformatics, Resource, Office of Science and Technology Resources, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Delphine Lissa
- Laboratory of Human Carcinogenesis, Center for Cancer Research National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Yang Zhang
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Suresh Kumar
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Lorinc Pongor
- HCEMM Cancer Genomics and Epigenetics Research Group, Szeged, Hungary
| | - Abhay Singh
- Center for Biosystems Science and Engineering, Indian Institute of Science, Bangalore, India
| | - Brett Schroder
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ajit Kumar Sharma
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Tiangen Chang
- Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Rasa Vilimas
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Danielle Pinkiert
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Chante Graham
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Donna Butcher
- Molecular Histopathology Laboratory, Laboratory Animal Sciences Program, Frederick National Laboratory for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, MD, USA
| | - Andrew Warner
- Molecular Histopathology Laboratory, Laboratory Animal Sciences Program, Frederick National Laboratory for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, MD, USA
| | - Robin Sebastian
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Mimi Mahon
- Pain and Palliative care services, National Institutes of Health Clinical Center, Bethesda, MD, USA
| | - Karen Baker
- Pain and Palliative care services, National Institutes of Health Clinical Center, Bethesda, MD, USA
| | - Jennifer Cheng
- Pain and Palliative care services, National Institutes of Health Clinical Center, Bethesda, MD, USA
| | - Ann Berger
- Pain and Palliative care services, National Institutes of Health Clinical Center, Bethesda, MD, USA
| | - Ross Lake
- Laboratory of Genitourinary cancer Pathogenesis, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Melissa Abel
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Manan Krishnamurthy
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - George Chrisafis
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Peter Fitzgerald
- CCR Collaborative Bioinformatics, Resource, Office of Science and Technology Resources, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Micheal Nirula
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Shubhank Goyal
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Devon Atkinson
- Center for Advanced Preclinical Research, Frederick National Laboratory for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, MD, USA
| | - Nicholas W Bateman
- The Henry M. Jackson Foundation for the Advancement of Military Medicine Inc., Bethesda, MD, USA
| | - Tamara Abulez
- The Henry M. Jackson Foundation for the Advancement of Military Medicine Inc., Bethesda, MD, USA
| | - Govind Nair
- National Institute of Neurological Disorders and Stroke, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Andrea Apolo
- Genitourinary Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Udayan Guha
- Thoracic and GI Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Baktiar Karim
- Molecular Histopathology Laboratory, Laboratory Animal Sciences Program, Frederick National Laboratory for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, MD, USA
| | - Rajaa El Meskini
- Center for Advanced Preclinical Research, Frederick National Laboratory for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, MD, USA
| | - Zoe Weaver Ohler
- Center for Advanced Preclinical Research, Frederick National Laboratory for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, MD, USA
| | - Mohit Kumar Jolly
- Center for Biosystems Science and Engineering, Indian Institute of Science, Bangalore, India
| | - Alejandro Schaffer
- Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Eytan Ruppin
- Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - David Kleiner
- Laboratory of Pathology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Markku Miettinen
- Laboratory of Pathology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - G Tom Brown
- Laboratory of Pathology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Stephen Hewitt
- Laboratory of Pathology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Thomas Conrads
- Women's Health Integrated Research Center, Inova Health System, Falls Church, VA, USA
| | - Anish Thomas
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
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23
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Eyers M, Irlam J, Marshall G, Smith V, Baker A, Frost L, Hoskin P, Choudhury A, West C. Digital spatial profiling of the microenvironment of muscle invasive bladder cancer. Commun Biol 2024; 7:737. [PMID: 38890455 PMCID: PMC11189454 DOI: 10.1038/s42003-024-06426-9] [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: 11/02/2023] [Accepted: 06/07/2024] [Indexed: 06/20/2024] Open
Abstract
Muscle invasive bladder cancer (MIBC) is a molecularly diverse disease with varied clinical outcomes. Molecular studies typically employ bulk sequencing analysis, giving a transcriptomic snapshot of a section of the tumour. However, tumour tissues are not homogeneous, but are composed of distinct compartments such as the tumour and stroma. To investigate the molecular profiles of bladder cancer, whilst also maintaining the spatial complexity of the tumours, we employed whole transcriptome Digital Spatial Profiling (DSP). With this method we generated a dataset of transcriptomic profiles of tumour epithelium, stroma, and immune infiltrate. With these data we investigate the spatial relationship of molecular subtype signatures and ligand signalling events. We find that Basal/Squamous and Classical subtypes are mostly restricted to tumour regions, while the stroma-rich subtype signatures are abundant within the stroma itself. Additionally, we identify ligand signalling events occurring between tumour, stroma, and immune infiltrate regions, such as immune infiltrate derived GPNMB, which was highly correlated with VEGFA expression within the tumour. These findings give us new insights into the diversity of MIBC at a molecular level and provide a dataset with detailed spatial information that was not available before in bladder cancer research.
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Affiliation(s)
- Michael Eyers
- Medicines Discovery Catapult, Alderly Park, Cheshire, UK.
| | - Joely Irlam
- Division of Cancer Sciences, University of Manchester, Manchester, UK
| | - Gayle Marshall
- Medicines Discovery Catapult, Alderly Park, Cheshire, UK
| | | | | | - Lucy Frost
- Medicines Discovery Catapult, Alderly Park, Cheshire, UK
| | - Peter Hoskin
- Division of Cancer Sciences, University of Manchester, Manchester, UK
- Mount Vernon Centre for Cancer Treatment, Northwood, UK
| | - Ananya Choudhury
- Division of Cancer Sciences, University of Manchester, Manchester, UK
- The Christie NHS Foundation Trust, Manchester, UK
| | - Catharine West
- Division of Cancer Sciences, University of Manchester, Manchester, UK
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24
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Benjamin K, Bhandari A, Kepple JD, Qi R, Shang Z, Xing Y, An Y, Zhang N, Hou Y, Crockford TL, McCallion O, Issa F, Hester J, Tillmann U, Harrington HA, Bull KR. Multiscale topology classifies cells in subcellular spatial transcriptomics. Nature 2024; 630:943-949. [PMID: 38898271 PMCID: PMC11208150 DOI: 10.1038/s41586-024-07563-1] [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: 03/06/2023] [Accepted: 05/14/2024] [Indexed: 06/21/2024]
Abstract
Spatial transcriptomics measures in situ gene expression at millions of locations within a tissue1, hitherto with some trade-off between transcriptome depth, spatial resolution and sample size2. Although integration of image-based segmentation has enabled impactful work in this context, it is limited by imaging quality and tissue heterogeneity. By contrast, recent array-based technologies offer the ability to measure the entire transcriptome at subcellular resolution across large samples3-6. Presently, there exist no approaches for cell type identification that directly leverage this information to annotate individual cells. Here we propose a multiscale approach to automatically classify cell types at this subcellular level, using both transcriptomic information and spatial context. We showcase this on both targeted and whole-transcriptome spatial platforms, improving cell classification and morphology for human kidney tissue and pinpointing individual sparsely distributed renal mouse immune cells without reliance on image data. By integrating these predictions into a topological pipeline based on multiparameter persistent homology7-9, we identify cell spatial relationships characteristic of a mouse model of lupus nephritis, which we validate experimentally by immunofluorescence. The proposed framework readily generalizes to new platforms, providing a comprehensive pipeline bridging different levels of biological organization from genes through to tissues.
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Affiliation(s)
| | - Aneesha Bhandari
- Centre for Human Genetics, University of Oxford, Oxford, UK
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Jessica D Kepple
- Centre for Human Genetics, University of Oxford, Oxford, UK
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Rui Qi
- Centre for Human Genetics, University of Oxford, Oxford, UK
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Chinese Academy of Medical Sciences Oxford Institute, University of Oxford, Oxford, UK
| | - Zhouchun Shang
- BGI Research, Riga, Latvia
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Yanan Xing
- BGI Research, Riga, Latvia
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | | | | | | | - Tanya L Crockford
- Centre for Human Genetics, University of Oxford, Oxford, UK
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Oliver McCallion
- Translational Research Immunology Group, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Fadi Issa
- Translational Research Immunology Group, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Joanna Hester
- Translational Research Immunology Group, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Ulrike Tillmann
- Mathematical Institute, University of Oxford, Oxford, UK
- Isaac Newton Institute for Mathematical Sciences, University of Cambridge, Cambridge, UK
| | - Heather A Harrington
- Mathematical Institute, University of Oxford, Oxford, UK.
- Centre for Human Genetics, University of Oxford, Oxford, UK.
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany.
- Centre for Systems Biology, Dresden, Dresden, Germany.
- Faculty of Mathematics, Technische Universität Dresden, Dresden, Germany.
| | - Katherine R Bull
- Centre for Human Genetics, University of Oxford, Oxford, UK.
- Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- Chinese Academy of Medical Sciences Oxford Institute, University of Oxford, Oxford, UK.
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25
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Thuilliez C, Moquin-Beaudry G, Khneisser P, Marques Da Costa ME, Karkar S, Boudhouche H, Drubay D, Audinot B, Geoerger B, Scoazec JY, Gaspar N, Marchais A. CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data. BIOINFORMATICS ADVANCES 2024; 4:vbae081. [PMID: 38915885 PMCID: PMC11194756 DOI: 10.1093/bioadv/vbae081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 05/02/2024] [Accepted: 05/29/2024] [Indexed: 06/26/2024]
Abstract
Motivation Spatial transcriptomics enables the analysis of cell crosstalk in healthy and diseased organs by capturing the transcriptomic profiles of millions of cells within their spatial contexts. However, spatial transcriptomics approaches also raise new computational challenges for the multidimensional data analysis associated with spatial coordinates. Results In this context, we introduce a novel analytical framework called CellsFromSpace based on independent component analysis (ICA), which allows users to analyze various commercially available technologies without relying on a single-cell reference dataset. The ICA approach deployed in CellsFromSpace decomposes spatial transcriptomics data into interpretable components associated with distinct cell types or activities. ICA also enables noise or artifact reduction and subset analysis of cell types of interest through component selection. We demonstrate the flexibility and performance of CellsFromSpace using real-world samples to demonstrate ICA's ability to successfully identify spatially distributed cells as well as rare diffuse cells, and quantitatively deconvolute datasets from the Visium, Slide-seq, MERSCOPE, and CosMX technologies. Comparative analysis with a current alternative reference-free deconvolution tool also highlights CellsFromSpace's speed, scalability and accuracy in processing complex, even multisample datasets. CellsFromSpace also offers a user-friendly graphical interface enabling non-bioinformaticians to annotate and interpret components based on spatial distribution and contributor genes, and perform full downstream analysis. Availability and implementation CellsFromSpace (CFS) is distributed as an R package available from github at https://github.com/gustaveroussy/CFS along with tutorials, examples, and detailed documentation.
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Affiliation(s)
- Corentin Thuilliez
- INSERM U1015, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif F-94805, France
| | - Gaël Moquin-Beaudry
- INSERM U1015, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif F-94805, France
| | - Pierre Khneisser
- Department of Medical Biology and Pathology, Gustave Roussy Cancer Campus, Villejuif 94805, France
| | - Maria Eugenia Marques Da Costa
- INSERM U1015, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif F-94805, France
- Department of Pediatric and Adolescent Oncology, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif 94805, France
| | - Slim Karkar
- University Bordeaux, CNRS, IBGC, UMR, Bordeaux 33077, France
- Bordeaux Bioinformatic Center CBiB, University of Bordeaux, Bordeaux 33000, France
| | - Hanane Boudhouche
- INSERM U1015, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif F-94805, France
| | - Damien Drubay
- Office of Biostatistics and Epidemiology, Gustave Roussy, Université Paris-Saclay, Villejuif 94805, France
- Inserm, Université Paris-Saclay, CESP U1018, Oncostat, Labeled Ligue Contre le Cancer, Villejuif 94805, France
| | - Baptiste Audinot
- INSERM U1015, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif F-94805, France
| | - Birgit Geoerger
- INSERM U1015, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif F-94805, France
- Department of Pediatric and Adolescent Oncology, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif 94805, France
| | - Jean-Yves Scoazec
- Department of Medical Biology and Pathology, Gustave Roussy Cancer Campus, Villejuif 94805, France
| | - Nathalie Gaspar
- INSERM U1015, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif F-94805, France
- Department of Pediatric and Adolescent Oncology, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif 94805, France
| | - Antonin Marchais
- INSERM U1015, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif F-94805, France
- Department of Pediatric and Adolescent Oncology, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif 94805, France
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26
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Bishop CR, Yan K, Nguyen W, Rawle DJ, Tang B, Larcher T, Suhrbier A. Microplastics dysregulate innate immunity in the SARS-CoV-2 infected lung. Front Immunol 2024; 15:1382655. [PMID: 38803494 PMCID: PMC11128561 DOI: 10.3389/fimmu.2024.1382655] [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: 02/06/2024] [Accepted: 04/24/2024] [Indexed: 05/29/2024] Open
Abstract
Introduction Global microplastic (MP) pollution is now well recognized, with humans and animals consuming and inhaling MPs on a daily basis, with a growing body of concern surrounding the potential impacts on human health. Methods Using a mouse model of mild COVID-19, we describe herein the effects of azide-free 1 μm polystyrene MP beads, co-delivered into lungs with a SARS-CoV-2 omicron BA.5 inoculum. The effect of MPs on the host response to SARS-CoV-2 infection was analysed using histopathology and RNA-Seq at 2 and 6 days post-infection (dpi). Results Although infection reduced clearance of MPs from the lung, virus titres and viral RNA levels were not significantly affected by MPs, and overt MP-associated clinical or histopathological changes were not observed. However, RNA-Seq of infected lungs revealed that MP exposure suppressed innate immune responses at 2 dpi and increased pro-inflammatory signatures at 6 dpi. The cytokine profile at 6 dpi showed a significant correlation with the 'cytokine release syndrome' signature observed in some COVID-19 patients. Discussion The findings are consistent with the recent finding that MPs can inhibit phagocytosis of apoptotic cells via binding of Tim4. They also add to a growing body of literature suggesting that MPs can dysregulate inflammatory processes in specific disease settings.
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Affiliation(s)
- Cameron R. Bishop
- Inflammation Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Kexin Yan
- Inflammation Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Wilson Nguyen
- Inflammation Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Daniel J. Rawle
- Inflammation Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Bing Tang
- Inflammation Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Thibaut Larcher
- Institut National de Recherche Agronomique, Unité Mixte de Recherche, Oniris, Nantes, France
| | - Andreas Suhrbier
- Inflammation Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- Australian Infectious Disease Research Centre, Global Virus Network (GVN) Center of Excellence, Brisbane, QLD, Australia
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27
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Zhang X, Lan R, Liu Y, Pillarisetty VG, Li D, Zhao CL, Sarkar SA, Liu W, Hanna I, Gupta M, Hajdu C, Melamed J, Shusterman M, Widmer J, Allendorf J, Liu YZ. Enhanced Complement Expression in the Tumor Microenvironment Following Neoadjuvant Therapy: Implications for Immunomodulation and Survival in Pancreatic Ductal Adenocarcinoma. RESEARCH SQUARE 2024:rs.3.rs-4104258. [PMID: 38798691 PMCID: PMC11118688 DOI: 10.21203/rs.3.rs-4104258/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Background Neoadjuvant therapy (NAT) is increasingly being used for pancreatic ductal adenocarcinoma (PDAC) treatment. However, its specific effects on carcinoma cells and the tumor microenvironment (TME) are not fully understood. This study aims to investigate how NAT differentially impacts PDAC's carcinoma cells and TME. Methods Spatial transcriptomics was used to compare gene expression profiles in carcinoma cells and the TME between 23 NAT-treated and 13 NAT-naïve PDAC patients, correlating with their clinicopathologic features. Analysis of an online single-nucleus RNA sequencing (snRNA-seq) dataset was performed for validation of the specific cell types responsible for NAT-induced gene expression alterations. Results NAT not only induces apoptosis and inhibits proliferation in carcinoma cells but also significantly remodels the TME. Notably, NAT induces a coordinated upregulation of multiple key complement genes (C3, C1S, C1R, C4B and C7) in the TME, making the complement pathway one of the most significantly affected pathways by NAT. Patients with higher TME complement expression following NAT exhibit improved overall survival. These patients also exhibit increased immunomodulatory and neurotrophic cancer-associated fibroblasts (CAFs); more CD4+ T cells, monocytes, and mast cells; and reduced immune exhaustion gene expression. snRNA-seq analysis demonstrates C3 complement was specifically upregulated in CAFs but not in other stroma cell types. Conclusions NAT can enhance complement production and signaling within the TME, which is associated with reduced immunosuppression in PDAC. These findings suggest that local complement dynamics could serve as a novel biomarker for prognosis, evaluating treatment response and resistance, and guiding therapeutic strategies in NAT-treated PDAC patients.
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Affiliation(s)
- Xiaofei Zhang
- Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, WI
- Department of Pathology and Laboratory Medicine, New York University Grossman Long Island School of Medicine, Long Island, NY
| | - Ruoxin Lan
- Department of Biostatistics and Data Science, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA
| | - Yongjun Liu
- Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, WI
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA
| | - Venu G Pillarisetty
- Department of Surgery, University of Washington School of Medicine, Seattle, WA
| | - Danting Li
- Department of Biostatistics and Data Science, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA
| | - Chaohui L Zhao
- Department of Pathology and Laboratory Medicine, New York University Grossman Long Island School of Medicine, Long Island, NY
| | - Suparna A. Sarkar
- Department of Pathology and Laboratory Medicine, New York University Grossman School of Medicine, New York, NY
| | - Weiguo Liu
- Department of Pathology and Laboratory Medicine, New York University Grossman Long Island School of Medicine, Long Island, NY
| | - Iman Hanna
- Department of Pathology and Laboratory Medicine, New York University Grossman Long Island School of Medicine, Long Island, NY
| | - Mala Gupta
- Department of Pathology and Laboratory Medicine, New York University Grossman Long Island School of Medicine, Long Island, NY
| | - Cristina Hajdu
- Department of Pathology and Laboratory Medicine, New York University Grossman School of Medicine, New York, NY
| | - Jonathan Melamed
- Department of Pathology and Laboratory Medicine, New York University Grossman Long Island School of Medicine, Long Island, NY
| | - Michael Shusterman
- Department of Oncology, New York University Grossman Long Island School of Medicine, Long Island, NY
| | - Jessica Widmer
- Department of Gastroenterology, New York University Grossman Long Island School of Medicine, Long Island, NY
| | - John Allendorf
- Department of Surgery, New York University Grossman Long Island School of Medicine, Long Island, NY
| | - Yao-Zhong Liu
- Department of Biostatistics and Data Science, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA
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28
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Syed F, Ballew O, Lee CC, Rana J, Krishnan P, Castela A, Weaver SA, Chalasani NS, Thomaidou SF, Demine S, Chang G, Coomans de Brachène A, Alvelos MI, Marselli L, Orr K, Felton JL, Liu J, Marchetti P, Zaldumbide A, Scheuner D, Eizirik DL, Evans-Molina C. Pharmacological inhibition of tyrosine protein-kinase 2 reduces islet inflammation and delays type 1 diabetes onset in mice. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.20.585925. [PMID: 38766166 PMCID: PMC11100605 DOI: 10.1101/2024.03.20.585925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Tyrosine protein-kinase 2 (TYK2), a member of the Janus kinase family, mediates inflammatory signaling through multiple cytokines, including interferon-α (IFNα), interleukin (IL)-12, and IL-23. Missense mutations in TYK2 are associated with protection against type 1 diabetes (T1D), and inhibition of TYK2 shows promise in the management of other autoimmune conditions. Here, we evaluated the effects of specific TYK2 inhibitors (TYK2is) in pre-clinical models of T1D. First, human β cells, cadaveric donor islets, and iPSC-derived islets were treated in vitro with IFNα in combination with a small molecule TYK2i (BMS-986165 or a related molecule BMS-986202). TYK2 inhibition prevented IFNα-induced β cell HLA class I up-regulation, endoplasmic reticulum stress, and chemokine production. In co-culture studies, pre-treatment of β cells with a TYK2i prevented IFNα-induced activation of T cells targeting an epitope of insulin. In vivo administration of BMS-986202 in two mouse models of T1D (RIP-LCMV-GP mice and NOD mice) reduced systemic and tissue-localized inflammation, prevented β cell death, and delayed T1D onset. Transcriptional phenotyping of pancreatic islets, pancreatic lymph nodes (PLN), and spleen during early disease pathogenesis highlighted a role for TYK2 inhibition in modulating signaling pathways associated with inflammation, translational control, stress signaling, secretory function, immunity, and diabetes. Additionally, TYK2i treatment changed the composition of innate and adaptive immune cell populations in the blood and disease target tissues, resulting in an immune phenotype with a diminished capacity for β cell destruction. Overall, these findings indicate that TYK2i has beneficial effects in both the immune and endocrine compartments in models of T1D, thus supporting a path forward for testing TYK2 inhibitors in human T1D.
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Affiliation(s)
- Farooq Syed
- Indiana University School of Medicine, Indianapolis, Indiana, USA
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Pediatrics and the Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Olivia Ballew
- Indiana Biosciences Research Institute, Indianapolis, IN, USA
| | - Chih-Chun Lee
- Indiana University School of Medicine, Indianapolis, Indiana, USA
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Pediatrics and the Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jyoti Rana
- Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Pediatrics and the Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Preethi Krishnan
- Indiana University School of Medicine, Indianapolis, Indiana, USA
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Angela Castela
- ULB Center for Diabetes Research, Medical Faculty, Université Libre de Bruxelles, Brussels, Belgium
| | - Staci A. Weaver
- Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Sofia F. Thomaidou
- Department of Cell and Chemical Biology, Leiden University Medical Center, The Netherlands
| | - Stephane Demine
- Indiana Biosciences Research Institute, Indianapolis, IN, USA
| | - Garrick Chang
- Department of Physics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, USA
| | | | - Maria Ines Alvelos
- ULB Center for Diabetes Research, Medical Faculty, Université Libre de Bruxelles, Brussels, Belgium
| | - Lorella Marselli
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Kara Orr
- Indiana University School of Medicine, Indianapolis, Indiana, USA
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Pediatrics and the Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jamie L. Felton
- Indiana University School of Medicine, Indianapolis, Indiana, USA
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Pediatrics and the Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jing Liu
- Department of Physics and Astronomy, Purdue University, West Lafayette, IN, USA
| | - Piero Marchetti
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Arnaud Zaldumbide
- Department of Cell and Chemical Biology, Leiden University Medical Center, The Netherlands
| | | | - Decio L. Eizirik
- ULB Center for Diabetes Research, Medical Faculty, Université Libre de Bruxelles, Brussels, Belgium
| | - Carmella Evans-Molina
- Indiana University School of Medicine, Indianapolis, Indiana, USA
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Pediatrics and the Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
- Richard L. Roudebush VA Medical Center, Indianapolis, IN, USA
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29
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Fujiwara N, Kimura G, Nakagawa H. Emerging Roles of Spatial Transcriptomics in Liver Research. Semin Liver Dis 2024; 44:115-132. [PMID: 38574750 DOI: 10.1055/a-2299-7880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/06/2024]
Abstract
Spatial transcriptomics, leveraging sequencing- and imaging-based techniques, has emerged as a groundbreaking technology for mapping gene expression within the complex architectures of tissues. This approach provides an in-depth understanding of cellular and molecular dynamics across various states of healthy and diseased livers. Through the integration of sophisticated bioinformatics strategies, it enables detailed exploration of cellular heterogeneity, transitions in cell states, and intricate cell-cell interactions with remarkable precision. In liver research, spatial transcriptomics has been particularly revelatory, identifying distinct zonated functions of hepatocytes that are crucial for understanding the metabolic and detoxification processes of the liver. Moreover, this technology has unveiled new insights into the pathogenesis of liver diseases, such as the role of lipid-associated macrophages in steatosis and endothelial cell signals in liver regeneration and repair. In the domain of liver cancer, spatial transcriptomics has proven instrumental in delineating intratumor heterogeneity, identifying supportive microenvironmental niches and revealing the complex interplay between tumor cells and the immune system as well as susceptibility to immune checkpoint inhibitors. In conclusion, spatial transcriptomics represents a significant advance in hepatology, promising to enhance our understanding and treatment of liver diseases.
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Affiliation(s)
- Naoto Fujiwara
- Department of Gastroenterology and Hepatology, Graduate School of Medicine, Mie University, Mie, Japan
| | - Genki Kimura
- Department of Gastroenterology and Hepatology, Graduate School of Medicine, Mie University, Mie, Japan
| | - Hayato Nakagawa
- Department of Gastroenterology and Hepatology, Graduate School of Medicine, Mie University, Mie, Japan
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30
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Lu Y, Chen QM, An L. SPADE: spatial deconvolution for domain specific cell-type estimation. Commun Biol 2024; 7:469. [PMID: 38632414 PMCID: PMC11024133 DOI: 10.1038/s42003-024-06172-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: 06/06/2023] [Accepted: 04/10/2024] [Indexed: 04/19/2024] Open
Abstract
Understanding gene expression in different cell types within their spatial context is a key goal in genomics research. SPADE (SPAtial DEconvolution), our proposed method, addresses this by integrating spatial patterns into the analysis of cell type composition. This approach uses a combination of single-cell RNA sequencing, spatial transcriptomics, and histological data to accurately estimate the proportions of cell types in various locations. Our analyses of synthetic data have demonstrated SPADE's capability to discern cell type-specific spatial patterns effectively. When applied to real-life datasets, SPADE provides insights into cellular dynamics and the composition of tumor tissues. This enhances our comprehension of complex biological systems and aids in exploring cellular diversity. SPADE represents a significant advancement in deciphering spatial gene expression patterns, offering a powerful tool for the detailed investigation of cell types in spatial transcriptomics.
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Affiliation(s)
- Yingying Lu
- Interdisciplinary Program in Statistics and Data Science, University of Arizona, Tucson, AZ, 85721, USA
| | - Qin M Chen
- College of Pharmacy, University of Arizona, Tucson, AZ, 85721, USA
| | - Lingling An
- Interdisciplinary Program in Statistics and Data Science, University of Arizona, Tucson, AZ, 85721, USA.
- Department of Biosystems Engineering, University of Arizona, Tucson, AZ, 85721, USA.
- Department of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ, 85721, USA.
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31
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Gundle KR, Rajasekaran K, Houlton J, Deutsch GB, Ow TJ, Maki RG, Pang J, Nathan CAO, Clayburgh D, Newman JG, Brinkmann E, Wagner MJ, Pollack SM, Thompson MJ, Li RJ, Mehta V, Schiff BA, Wenig BI, Swiecicki PL, Tang AL, Davis JL, van Zante A, Bertout JA, Jenkins W, Turner A, Grenley M, Burns C, Frazier JP, Merrell A, Sottero KHW, Derry JMJ, Gillespie KC, Mills B, Klinghoffer RA. Early, precise, and safe clinical evaluation of the pharmacodynamic effects of novel agents in the intact human tumor microenvironment. Front Pharmacol 2024; 15:1367581. [PMID: 38681192 PMCID: PMC11048044 DOI: 10.3389/fphar.2024.1367581] [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: 01/09/2024] [Accepted: 03/04/2024] [Indexed: 05/01/2024] Open
Abstract
Introduction: Drug development is systemically inefficient. Research and development costs for novel therapeutics average hundreds of millions to billions of dollars, with the overall likelihood of approval estimated to be as low as 6.7% for oncology drugs. Over half of these failures are due to a lack of drug efficacy. This pervasive and repeated low rate of success exemplifies how preclinical models fail to adequately replicate the complexity and heterogeneity of human cancer. Therefore, new methods of evaluation, early in the development trajectory, are essential both to rule-in and rule-out novel agents with more rigor and speed, but also to spare clinical trial patients from the potentially toxic sequelae (high risk) of testing investigational agents that have a low likelihood of producing a response (low benefit). Methods: The clinical in vivo oncology (CIVO®) platform was designed to change this drug development paradigm. CIVO precisely delivers microdose quantities of up to 8 drugs or combinations directly into patient tumors 4-96 h prior to planned surgical resection. Resected tissue is then analyzed for responses at each site of intratumoral drug exposure. Results: To date, CIVO has been used safely in 6 clinical trials, including 68 subjects, with 5 investigational and 17 approved agents. Resected tissues were analyzed initially using immunohistochemistry and in situ hybridization assays (115 biomarkers). As technology advanced, the platform was paired with spatial biology analysis platforms, to successfully track anti-neoplastic and immune-modulating activity of the injected agents in the intact tumor microenvironment. Discussion: Herein we provide a report of the use of CIVO technology in patients, a depiction of the robust analysis methods enabled by this platform, and a description of the operational and regulatory mechanisms used to deploy this approach in synergistic partnership with pharmaceutical partners. We further detail how use of the CIVO platform is a clinically safe and scientifically precise alternative or complement to preclinical efficacy modeling, with outputs that inform, streamline, and de-risk drug development.
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Affiliation(s)
- Kenneth R. Gundle
- Department of Orthopaedics and Rehabilitation, Oregon Health and Science University, Portland, OR, United States
- Portland Veterans Affairs Medical Center, Portland, OR, United States
| | - Karthik Rajasekaran
- Department of Otorhinolaryngology—Head and Neck Surgery, University of Pennsylvania, Philadelphia, PA, United States
| | - Jeffrey Houlton
- Sarah Cannon Research Institute, Charleston, SC, United States
| | - Gary B. Deutsch
- Zucker School of Medicine at Hofstra/Northwell, New Hyde Park, NY, United States
| | - Thomas J. Ow
- Department of Otorhinolaryngology-Head and Neck Surgery, Montefiore Medical Center/Albert Einstein College of Medicine, Bronx, NY, United States
- Department of Pathology, Montefiore Medical Center/Albert Einstein College of Medicine, Bronx, NY, United States
| | - Robert G. Maki
- Zucker School of Medicine at Hofstra/Northwell, New Hyde Park, NY, United States
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, United States
| | - John Pang
- Department of Otolaryngology/Head and Neck Surgery, Louisiana State University Health Shreveport, Shreveport, LA, United States
| | - Cherie-Ann O. Nathan
- Department of Otolaryngology/Head and Neck Surgery, Louisiana State University Health Shreveport, Shreveport, LA, United States
| | - Daniel Clayburgh
- Portland Veterans Affairs Medical Center, Portland, OR, United States
- Department of Otolaryngology‐Head and Neck Surgery, Oregon Health and Science University, Portland, OR, United States
| | - Jason G. Newman
- Department of Otorhinolaryngology—Head and Neck Surgery, University of Pennsylvania, Philadelphia, PA, United States
| | - Elyse Brinkmann
- Department of Orthopaedics and Sports Medicine, University of Washington School of Medicine, Seattle, WA, United States
| | - Michael J. Wagner
- Division of Oncology, University of Washington, Seattle, WA, United States
| | - Seth M. Pollack
- Division of Oncology, University of Washington, Seattle, WA, United States
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, United States
| | - Matthew J. Thompson
- Department of Orthopaedics and Sports Medicine, University of Washington School of Medicine, Seattle, WA, United States
| | - Ryan J. Li
- Department of Otolaryngology‐Head and Neck Surgery, Oregon Health and Science University, Portland, OR, United States
| | - Vikas Mehta
- Department of Otorhinolaryngology-Head and Neck Surgery, Montefiore Medical Center/Albert Einstein College of Medicine, Bronx, NY, United States
| | - Bradley A. Schiff
- Department of Otorhinolaryngology-Head and Neck Surgery, Montefiore Medical Center/Albert Einstein College of Medicine, Bronx, NY, United States
| | - Barry I. Wenig
- Department of Otolaryngology—Head and Neck Surgery, University of Illinois at Chicago, Chicago, IL, United States
| | - Paul L. Swiecicki
- Department of Hematology Oncology, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Alice L. Tang
- Department of Otolaryngology—Head and Neck Surgery, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Jessica L. Davis
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Annemieke van Zante
- Department of Pathology, University of California San Francisco, San Francisco, CA, United States
| | | | - Wendy Jenkins
- Presage Biosciences, Inc., Seattle, WA, United States
| | | | - Marc Grenley
- Presage Biosciences, Inc., Seattle, WA, United States
| | - Connor Burns
- Presage Biosciences, Inc., Seattle, WA, United States
| | | | | | | | | | | | - Bre Mills
- Presage Biosciences, Inc., Seattle, WA, United States
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Damodharan S, Shireman JM, Xie E, Distler E, Kendziorski C, Dey M. Transcriptomic and Proteomic Spatial Profiling of Pediatric and Adult Diffuse Midline Glioma H3 K27-Altered, Reveals Region Specific Differences and Limited Overlap between mRNA and Protein. RESEARCH SQUARE 2024:rs.3.rs-4139314. [PMID: 38645012 PMCID: PMC11030546 DOI: 10.21203/rs.3.rs-4139314/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Diffuse midline glioma, H3 K27 -altered (DMG-Alt) are highly aggressive malignancies of the central nervous system (CNS) that primarily affect the pediatric population. Large scale spatial transcriptomic studies have implicated that tumor microenvironmental landscape plays an important role in determining the phenotypic differences in tumor presentation and clinical course, however, data connecting overall transcriptomic changes to the protein level is lacking. The NanoString GeoMx™ Digital Spatial Profiler platform was used to determine the spatial transcriptomic and proteomic landscape in a cohort of both pediatric and adult H3 K27 -altered DMG biopsy samples. Three fluorescently labeled antibodies targeting immune cells (CD45), epithelial cells (PanCK), tumor cells ( H3 K27M ) and a nucleic acid stain (SYTO-13) were used to establish regions of interest (ROI) for genomic and proteomic analysis. We found genetic alterations within the tumor which can be delineated across patient age and spatial location. We show that the H3 K27M mutation itself has a profound impact on tumor cells transcriptomics and interestingly we found limited fidelity between overall transcriptome and proteome. Our data also validate the previously described OPC like precursor signature at the proteomic level and reveal a special shift in the signature based on the local TME composition.
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Nolt GL, Keeble AR, Wen Y, Strong AC, Thomas NT, Valentino TR, Brightwell CR, Murach KA, Patrizia S, Weinstabl H, Gollner A, McCarthy JJ, Fry CS, Franti M, Filareto A, Peterson CA, Dungan CM. Inhibition of p53-MDM2 binding reduces senescent cell abundance and improves the adaptive responses of skeletal muscle from aged mice. GeroScience 2024; 46:2153-2176. [PMID: 37872294 PMCID: PMC10828311 DOI: 10.1007/s11357-023-00976-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 10/09/2023] [Indexed: 10/25/2023] Open
Abstract
Skeletal muscle adaptation to external stimuli, such as regeneration following injury and hypertrophy in response to resistance exercise, are blunted with advanced age. The accumulation of senescent cells, along with defects in myogenic progenitor cell (MPC) proliferation, have been strongly linked as contributing factors to age-associated impairment in muscle adaptation. p53 plays an integral role in all these processes, as upregulation of p53 causes apoptosis in senescent cells and prevents mitotic catastrophe in MPCs from old mice. The goal of this study was to determine if a novel pharmaceutical agent (BI01), which functions by upregulating p53 through inhibition of binding to MDM2, the primary p53 regulatory protein, improves muscle regeneration and hypertrophy in old mice. BI01 effectively reduced the number of senescent cells in vitro but had no effect on MPC survival or proliferation at a comparable dose. Following repeated oral gavage with 2 mg/kg of BI01 (OS) or vehicle (OV), old mice (24 months) underwent unilateral BaCl2 injury in the tibialis anterior (TA) muscle, with PBS injections serving as controls. After 7 days, satellite cell number was higher in the TA of OS compared to OV mice, as was the expression of genes involved in ATP production. By 35 days, old mice treated with BI01 displayed reduced senescent cell burden, enhanced regeneration (higher muscle mass and fiber cross-sectional area) and restoration of muscle function relative to OV mice. To examine the impact of 2 mg/kg BI01 on muscle hypertrophy, the plantaris muscle was subjected to 28 days of mechanical overload (MOV) in OS and OV mice. In response to MOV, OS mice had larger plantaris muscles and muscle fibers than OV mice, particularly type 2b + x fibers, associated with reduced senescent cells. Together our data show that BI01 is an effective senolytic agent that may also augment muscle metabolism to enhance muscle regeneration and hypertrophy in old mice.
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Affiliation(s)
- Georgia L Nolt
- Department of Physiology, University of Kentucky, Lexington, KY, USA
- The Center for Muscle Biology, University of Kentucky, Lexington, KY, USA
| | - Alexander R Keeble
- Department of Physiology, University of Kentucky, Lexington, KY, USA
- The Center for Muscle Biology, University of Kentucky, Lexington, KY, USA
| | - Yuan Wen
- The Center for Muscle Biology, University of Kentucky, Lexington, KY, USA
- Department of Physical Therapy, University of Kentucky, Lexington, KY, USA
| | - Aubrey C Strong
- The Center for Muscle Biology, University of Kentucky, Lexington, KY, USA
| | - Nicholas T Thomas
- The Center for Muscle Biology, University of Kentucky, Lexington, KY, USA
- Department of Athletic Training and Clinical Nutrition, University of Kentucky, Lexington, KY, USA
| | - Taylor R Valentino
- Department of Physiology, University of Kentucky, Lexington, KY, USA
- The Center for Muscle Biology, University of Kentucky, Lexington, KY, USA
| | - Camille R Brightwell
- The Center for Muscle Biology, University of Kentucky, Lexington, KY, USA
- Department of Athletic Training and Clinical Nutrition, University of Kentucky, Lexington, KY, USA
| | - Kevin A Murach
- Department of Health, Human Performance, and Recreation, University of Arkansas, Fayetteville, AR, USA
| | - Sini Patrizia
- Regenerative Medicine, Boehringer Ingelheim Pharmaceuticals Inc., 900 Ridgebury Road, Ridgefield, CT, 06877, USA
| | - Harald Weinstabl
- Boehringer Ingelheim RCV, Boehringer Ingelheim Pharmaceuticals Inc., Vienna, Austria
| | - Andreas Gollner
- Boehringer Ingelheim RCV, Boehringer Ingelheim Pharmaceuticals Inc., Vienna, Austria
| | - John J McCarthy
- Department of Physiology, University of Kentucky, Lexington, KY, USA
- The Center for Muscle Biology, University of Kentucky, Lexington, KY, USA
| | - Christopher S Fry
- The Center for Muscle Biology, University of Kentucky, Lexington, KY, USA
- Department of Athletic Training and Clinical Nutrition, University of Kentucky, Lexington, KY, USA
| | - Michael Franti
- Regenerative Medicine, Boehringer Ingelheim Pharmaceuticals Inc., 900 Ridgebury Road, Ridgefield, CT, 06877, USA
| | - Antonio Filareto
- Regenerative Medicine, Boehringer Ingelheim Pharmaceuticals Inc., 900 Ridgebury Road, Ridgefield, CT, 06877, USA.
| | - Charlotte A Peterson
- The Center for Muscle Biology, University of Kentucky, Lexington, KY, USA
- Department of Physical Therapy, University of Kentucky, Lexington, KY, USA
| | - Cory M Dungan
- The Center for Muscle Biology, University of Kentucky, Lexington, KY, USA.
- Department of Physical Therapy, University of Kentucky, Lexington, KY, USA.
- Department of Health, Human Performance, and Recreation, Baylor University, One Bear Place #97313, Waco, TX, 76706, USA.
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Ahn S, Lee HS. Applicability of Spatial Technology in Cancer Research. Cancer Res Treat 2024; 56:343-356. [PMID: 38291743 PMCID: PMC11016655 DOI: 10.4143/crt.2023.1302] [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: 12/10/2023] [Accepted: 01/29/2024] [Indexed: 02/01/2024] Open
Abstract
This review explores spatial mapping technologies in cancer research, highlighting their crucial role in understanding the complexities of the tumor microenvironment (TME). The TME, which is an intricate ecosystem of diverse cell types, has a significant impact on tumor dynamics and treatment outcomes. This review closely examines cutting-edge spatial mapping technologies, categorizing them into capture-, imaging-, and antibody-based approaches. Each technology was scrutinized for its advantages and disadvantages, factoring in aspects such as spatial profiling area, multiplexing capabilities, and resolution. Additionally, we draw attention to the nuanced choices researchers face, with capture-based methods lending themselves to hypothesis generation, and imaging/antibody-based methods that fit neatly into hypothesis testing. Looking ahead, we anticipate a scenario in which multi-omics data are seamlessly integrated, artificial intelligence enhances data analysis, and spatiotemporal profiling opens up new dimensions.
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Affiliation(s)
- Sangjeong Ahn
- Department of Pathology, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Korea
- Artificial Intelligence Center, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Korea
- Department of Medical Informatics, Korea University College of Medicine, Seoul, Korea
| | - Hye Seung Lee
- Department of Pathology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
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Guo J, Tang B, Fu J, Zhu X, Xie W, Wang N, Ding Z, Song Z, Yang Y, Xu G, Xiao X. High-plex spatial transcriptomic profiling reveals distinct immune components and the HLA class I/DNMT3A/CD8 modulatory axis in mismatch repair-deficient endometrial cancer. Cell Oncol (Dordr) 2024; 47:573-585. [PMID: 37847338 PMCID: PMC11090934 DOI: 10.1007/s13402-023-00885-8] [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] [Accepted: 09/23/2023] [Indexed: 10/18/2023] Open
Abstract
PURPOSE Tumors bearing mismatch repair deficiency (MMRd) are characterized by a high load of neoantigens and are believed to trigger immunogenic reactions upon immune checkpoint blockade treatment such as anti-PD-1/PD-L1 therapy. However, the mechanisms are still ill-defined, as multiple cancers with MMRd exhibit variable responses to immune checkpoint inhibitors (ICIs). In endometrial cancer (EC), a distinct tumor microenvironment (TME) exists that may correspond to treatment-related efficacies. We aimed to characterize EC patients with aberrant MMR pathways to identify molecular subtypes predisposed to respond to ICI therapies. METHODS We applied digital spatial profiling, a high-plex spatial transcriptomic approach covering over 1,800 genes, to obtain a highly resolved TME landscape in 45 MMRd-EC patients. We cross-validated multiple biomarkers identified using immunohistochemistry and multiplexed immunofluorescence using in-study and independent cohorts totaling 123 MMRd-EC patients and validated our findings using external TCGA data from microsatellite instability endometrial cancer (MSI-EC) patients. RESULTS High-plex spatial profiling identified a 14-gene signature in the MMRd tumor-enriched regions stratifying tumors into "hot", "intermediate" and "cold" groups according to their distinct immune profiles, a finding highly consistent with the corresponding CD8 + T-cell infiltration status. Our validation studies further corroborated an existing coregulatory network involving HLA class I and DNMT3A potentially bridged through dynamic crosstalk incorporating CCL5. CONCLUSION Our study confirmed the heterogeneous TME status within MMRd-ECs and showed that these ECs can be stratified based on potential biomarkers such as HLA class I, DNMT3A and CD8 in pathological settings for improved ICI therapeutic efficacy in this subset of patients.
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Affiliation(s)
- Jingjing Guo
- Department of Pathology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
- School of Medical and Life Sciences, Chengdu University of TCM, Chengdu, China
| | - Baijie Tang
- Department of Pathology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Jing Fu
- Department of Pathology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Xuan Zhu
- Department of Pathology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
- School of Medical and Life Sciences, Chengdu University of TCM, Chengdu, China
| | - Wenlong Xie
- Department of Pathology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
- School of Medical and Life Sciences, Chengdu University of TCM, Chengdu, China
| | - Nan Wang
- Mills Institute for Personalized Cancer Care, Jinan, China
| | - Zhiyong Ding
- Mills Institute for Personalized Cancer Care, Jinan, China
| | - Zhentao Song
- Mills Institute for Personalized Cancer Care, Jinan, China
| | - Yue Yang
- Department of Pathology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Gang Xu
- Department of Pathology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Xue Xiao
- Department of Pathology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
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Goralski TM, Meyerdirk L, Breton L, Brasseur L, Kurgat K, DeWeerd D, Turner L, Becker K, Adams M, Newhouse DJ, Henderson MX. Spatial transcriptomics reveals molecular dysfunction associated with cortical Lewy pathology. Nat Commun 2024; 15:2642. [PMID: 38531900 PMCID: PMC10966039 DOI: 10.1038/s41467-024-47027-8] [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: 01/30/2024] [Accepted: 03/18/2024] [Indexed: 03/28/2024] Open
Abstract
A key hallmark of Parkinson's disease (PD) is Lewy pathology. Composed of α-synuclein, Lewy pathology is found both in dopaminergic neurons that modulate motor function, and cortical regions that control cognitive function. Recent work has established the molecular identity of dopaminergic neurons susceptible to death, but little is known about cortical neurons susceptible to Lewy pathology or molecular changes induced by aggregates. In the current study, we use spatial transcriptomics to capture whole transcriptome signatures from cortical neurons with α-synuclein pathology compared to neurons without pathology. We find, both in PD and related PD dementia, dementia with Lewy bodies and in the pre-formed fibril α-synucleinopathy mouse model, that specific classes of excitatory neurons are vulnerable to developing Lewy pathology. Further, we identify conserved gene expression changes in aggregate-bearing neurons that we designate the Lewy-associated molecular dysfunction from aggregates (LAMDA) signature. Neurons with aggregates downregulate synaptic, mitochondrial, ubiquitin-proteasome, endo-lysosomal, and cytoskeletal genes and upregulate DNA repair and complement/cytokine genes. Our results identify neurons vulnerable to Lewy pathology in the PD cortex and describe a conserved signature of molecular dysfunction in both mice and humans.
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Affiliation(s)
- Thomas M Goralski
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, 49503, USA
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Lindsay Meyerdirk
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, 49503, USA
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Libby Breton
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, 49503, USA
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Laura Brasseur
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, 49503, USA
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Kevin Kurgat
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, 49503, USA
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Daniella DeWeerd
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, 49503, USA
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Lisa Turner
- Van Andel Institute Pathology Core, Grand Rapids, MI, 49503, USA
| | - Katelyn Becker
- Van Andel Institute Genomics Core, Grand Rapids, MI, 49503, USA
| | - Marie Adams
- Van Andel Institute Genomics Core, Grand Rapids, MI, 49503, USA
| | | | - Michael X Henderson
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, 49503, USA.
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA.
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Ding J, Liu R, Wen H, Tang W, Li Z, Venegas J, Su R, Molho D, Jin W, Wang Y, Lu Q, Li L, Zuo W, Chang Y, Xie Y, Tang J. DANCE: a deep learning library and benchmark platform for single-cell analysis. Genome Biol 2024; 25:72. [PMID: 38504331 PMCID: PMC10949782 DOI: 10.1186/s13059-024-03211-z] [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: 02/07/2023] [Accepted: 03/05/2024] [Indexed: 03/21/2024] Open
Abstract
DANCE is the first standard, generic, and extensible benchmark platform for accessing and evaluating computational methods across the spectrum of benchmark datasets for numerous single-cell analysis tasks. Currently, DANCE supports 3 modules and 8 popular tasks with 32 state-of-art methods on 21 benchmark datasets. People can easily reproduce the results of supported algorithms across major benchmark datasets via minimal efforts, such as using only one command line. In addition, DANCE provides an ecosystem of deep learning architectures and tools for researchers to facilitate their own model development. DANCE is an open-source Python package that welcomes all kinds of contributions.
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Affiliation(s)
- Jiayuan Ding
- Department of Computer Science and Engineering, Michigan State University, East Lansing, USA.
| | - Renming Liu
- Department of Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, USA
| | - Hongzhi Wen
- Department of Computer Science and Engineering, Michigan State University, East Lansing, USA
| | - Wenzhuo Tang
- Department of Statistics and Probability, Michigan State University, East Lansing, USA
| | - Zhaoheng Li
- Department of Biostatistics, University of Washington, Seattle, USA
| | - Julian Venegas
- Department of Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, USA
| | - Runze Su
- Department of Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, USA
- Department of Statistics and Probability, Michigan State University, East Lansing, USA
| | - Dylan Molho
- Department of Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, USA
| | - Wei Jin
- Department of Computer Science and Engineering, Michigan State University, East Lansing, USA
| | - Yixin Wang
- Department of Bioengineering, Stanford University, Palo Alto, USA
| | - Qiaolin Lu
- School of Artificial Intelligence, Jilin University, Jilin, China
| | - Lingxiao Li
- Department of Computer Science, Boston University, Boston, USA
| | - Wangyang Zuo
- Department of Computer Science, Zhejiang University of Technology, Zhejiang, China
| | - Yi Chang
- School of Artificial Intelligence, Jilin University, Jilin, China
| | - Yuying Xie
- Department of Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, USA.
- Department of Statistics and Probability, Michigan State University, East Lansing, USA.
| | - Jiliang Tang
- Department of Computer Science and Engineering, Michigan State University, East Lansing, USA.
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Yabaji SM, Zhernovkov V, Araveti PB, Lata S, Rukhlenko OS, Abdullatif SA, Alekseev Y, Ma Q, Dayama G, Lau NC, Bishai WR, Crossland NA, Campbell JD, Kholodenko BN, Gimelbrant AA, Kobzik L, Kramnik I. Myc Dysregulation in Activated Macrophages Initiates Iron-Mediated Lipid Peroxidation that Fuels Type I Interferon and Compromises TB Resistance. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.05.583602. [PMID: 38496444 PMCID: PMC10942339 DOI: 10.1101/2024.03.05.583602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
A quarter of human population is infected with Mycobacterium tuberculosis, but less than 10% of those infected develop clinical, mostly pulmonary, TB. To dissect mechanisms of susceptibility in immunocompetent individuals, we developed a genetically defined sst1-susceptible mouse model that uniquely reproduces a defining feature of human TB: development of necrotic lung lesions after infection with virulent Mtb. In this study, we explored the connectivity of the sst1-regulated pathways during prolonged macrophage activation with TNF. We determined that the aberrant response of the sst1-susceptible macrophages to TNF was primarily driven by conflicting Myc and antioxidant response pathways that resulted in a coordinated failure to properly sequester intracellular iron and activate ferroptosis inhibitor enzymes. Consequently, iron-mediated lipid peroxidation fueled IFNβ superinduction and sustained the Type I Interferon (IFN-I) pathway hyperactivity that locked the sst1-susceptible macrophages in a state of unresolving stress and compromised their resistance to Mtb. The accumulation of the aberrantly activated, stressed, macrophages within granuloma microenvironment led to the local failure of anti-tuberculosis immunity and tissue necrosis. Our findings suggest a novel link between metabolic dysregulation in macrophages and susceptibility to TB, offering insights into potential therapeutic targets aimed at modulating macrophage function and improving TB control.
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Affiliation(s)
- Shivraj M. Yabaji
- The National Emerging Infectious Diseases Laboratory, Boston University, Boston, MA
| | - Vadim Zhernovkov
- Systems Biology Ireland, School of Medicine, University College Dublin, Dublin 4, Ireland
| | | | - Suruchi Lata
- The National Emerging Infectious Diseases Laboratory, Boston University, Boston, MA
| | - Oleksii S. Rukhlenko
- Systems Biology Ireland, School of Medicine, University College Dublin, Dublin 4, Ireland
| | - Salam Al Abdullatif
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA
| | - Yuriy Alekseev
- The Department of Pathology and Laboratory Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118
| | - Qicheng Ma
- Department of Biochemistry, and Cell Biology and Genome Science Institute, Boston University Chobanian & Avedisian School of Medicine
| | - Gargi Dayama
- Department of Biochemistry, and Cell Biology and Genome Science Institute, Boston University Chobanian & Avedisian School of Medicine
| | - Nelson C. Lau
- The National Emerging Infectious Diseases Laboratory, Boston University, Boston, MA
- Department of Biochemistry, and Cell Biology and Genome Science Institute, Boston University Chobanian & Avedisian School of Medicine
| | - William R. Bishai
- Center for TB Research, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Nicholas A. Crossland
- The National Emerging Infectious Diseases Laboratory, Boston University, Boston, MA
- The Department of Pathology and Laboratory Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118
| | - Joshua D. Campbell
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA
| | - Boris N. Kholodenko
- Systems Biology Ireland, School of Medicine, University College Dublin, Dublin 4, Ireland
- Conway Institute of Biomolecular & Biomedical Research, University College Dublin, Dublin 4, Ireland
- Department of Pharmacology, Yale University School of Medicine, New Haven CT, USA
| | | | | | - Igor Kramnik
- The National Emerging Infectious Diseases Laboratory, Boston University, Boston, MA
- Pulmonary Center, The Department of Medicine, Boston University Chobanian & Avedisian School of Medicine
- Dept. of Microbiology, Boston University Chobanian & Avedisian School of Medicine
- Lead contact
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Glyn T, Williams S, Whitehead M, Eglinton T, West N, Purcell RV. Digital spatial profiling identifies molecular changes involved in development of colitis-associated colorectal cancer. Front Oncol 2024; 14:1247106. [PMID: 38505585 PMCID: PMC10949367 DOI: 10.3389/fonc.2024.1247106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Accepted: 02/01/2024] [Indexed: 03/21/2024] Open
Abstract
Objective Chronic colonic inflammation seen in inflammatory bowel disease (IBD) is a risk factor for colorectal cancer (CRC). Colitis-associated cancers (CAC) are molecularly different from sporadic CRC. This study aimed to evaluate spatially defined molecular changes associated with neoplastic progression to identify mechanisms of action and potential biomarkers for prognostication. Design IBD patients who had undergone colectomy for treatment of their IBD or dysplasia were identified from an institutional database. Formalin-fixed paraffin embedded samples from areas of normal, inflamed, dysplastic and adenocarcinoma tissue were identified for digital spatial profiling using the Nanostring GeoMx™ Cancer Transcriptome Atlas. RNA expression and quantification of 1812 genes was measured and analysed in a spatial context to compare differences in gene expression. Results Sixteen patients were included, nine patients had CAC, two had dysplasia only and five had colitis only. Significant, step-wise differences in gene expression were seen between tissue types, mainly involving progressive over-expression of collagen genes associated with stromal remodelling. Similarly, MYC over-expression was associated with neoplastic progression. Comparison of normal and inflamed tissue from patients who progressed to those who did not also showed significant differences in immune-related genes, including under-expression of thte chemokines CCL18, CCL25 and IL-R7, as well as CD3, CD6 and lysozyme. The known oncogene CD24 was significantly overexpressed. Conclusion Both tissue types and patient groups are molecularly distinguishable on the basis of their gene expression patterns. Further prospective work is necessary to confirm these differences and establish their clinical significance and potential utility as biomarkers.
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Affiliation(s)
- Tamara Glyn
- Department of Surgery and Critical Care, University of Otago, Christchurch, New Zealand
| | - Sarah Williams
- Griffith Health, Griffith University, Gold Coast, QLD, Australia
| | - Martin Whitehead
- Department of Anatomical Pathology, Te Whatu Ora Waitaha, Christchurch, New Zealand
| | - Tim Eglinton
- Department of Surgery and Critical Care, University of Otago, Christchurch, New Zealand
| | - Nicholas West
- Griffith Health, Griffith University, Gold Coast, QLD, Australia
| | - Rachel V. Purcell
- Department of Surgery and Critical Care, University of Otago, Christchurch, New Zealand
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Yan K, Liu Q, Huang R, Jiang Y, Bian Z, Li S, Li L, Shen F, Tsuneyama K, Zhang Q, Lian Z, Guan H, Xu B. Spatial transcriptomics reveals prognosis-associated cellular heterogeneity in the papillary thyroid carcinoma microenvironment. Clin Transl Med 2024; 14:e1594. [PMID: 38426403 PMCID: PMC10905537 DOI: 10.1002/ctm2.1594] [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: 08/02/2023] [Revised: 01/28/2024] [Accepted: 02/05/2024] [Indexed: 03/02/2024] Open
Abstract
BACKGROUND Papillary thyroid carcinoma (PTC) is the most common malignant endocrine tumour, and its incidence and prevalence are increasing considerably. Cellular heterogeneity in the tumour microenvironment is important for PTC prognosis. Spatial transcriptomics is a powerful technique for cellular heterogeneity study. METHODS In conjunction with a clinical pathologist identification method, spatial transcriptomics was employed to characterise the spatial location and RNA profiles of PTC-associated cells within the tissue sections. The spatial RNA-clinical signature genes for each cell type were extracted and applied to outlining the distribution regions of specific cells on the entire section. The cellular heterogeneity of each cell type was further revealed by ContourPlot analysis, monocle analysis, trajectory analysis, ligand-receptor analysis and Gene Ontology enrichment analysis. RESULTS The spatial distribution region of tumour cells, typical and atypical follicular cells (FCs and AFCs) and immune cells were accurately and comprehensively identified in all five PTC tissue sections. AFCs were identified as a transitional state between FCs and tumour cells, exhibiting a higher resemblance to the latter. Three tumour foci were shared among all patients out of the 13 observed. Notably, tumour foci No. 2 displayed elevated expression levels of genes associated with lower relapse-free survival in PTC patients. We discovered key ligand-receptor interactions, including LAMB3-ITGA2, FN1-ITGA3 and FN1-SDC4, involved in the transition of PTC cells from FCs to AFCs and eventually to tumour cells. High expression of these patterns correlated with reduced relapse-free survival. In the tumour immune microenvironment, reduced interaction between myeloid-derived TGFB1 and TGFBR1 in tumour focus No. 2 contributed to tumourigenesis and increased heterogeneity. The spatial RNA-clinical analysis method developed here revealed prognosis-associated cellular heterogeneity in the PTC microenvironment. CONCLUSIONS The occurrence of tumour foci No. 2 and three enhanced ligand-receptor interactions in the AFC area/tumour foci reduced the relapse-free survival of PTC patients, potentially leading to improved prognostic strategies and targeted therapies for PTC patients.
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Affiliation(s)
- Kai Yan
- Guangdong Cardiovascular InstituteGuangdong Provincial People's HospitalGuangdong Academy of Medical SciencesGuangzhouChina
| | - Qing‐Zhi Liu
- Chronic Disease LaboratoryInstitutes for Life SciencesSouth China University of TechnologyGuangzhouChina
| | - Rong‐Rong Huang
- Guangdong Cardiovascular InstituteGuangdong Provincial People's HospitalGuangdong Academy of Medical SciencesGuangzhouChina
| | - Yi‐Hua Jiang
- Guangdong Cardiovascular InstituteGuangdong Provincial People's HospitalGuangdong Academy of Medical SciencesGuangzhouChina
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and ApplicationGuangzhouChina
| | - Zhen‐Hua Bian
- School of Biomedical Sciences and EngineeringSouth China University of TechnologyGuangzhou International CampusGuangzhouChina
| | - Si‐Jin Li
- Department of Thyroid SurgeryGuangzhou First People's HospitalSouth China University of TechnologyGuangzhouChina
| | - Liang Li
- Medical Research InstituteGuangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouChina
| | - Fei Shen
- Department of Thyroid SurgeryGuangzhou First People's HospitalSouth China University of TechnologyGuangzhouChina
| | - Koichi Tsuneyama
- Department of Pathology and Laboratory MedicineInstitute of Biomedical SciencesTokushima University Graduate SchoolTokushimaJapan
| | - Qing‐Ling Zhang
- Department of PathologyGuangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouChina
| | - Zhe‐Xiong Lian
- Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouChina
| | - Haixia Guan
- Department of EndocrinologyGuangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouChina
| | - Bo Xu
- Department of Thyroid SurgeryGuangzhou First People's HospitalSouth China University of TechnologyGuangzhouChina
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Garmire LX, Li Y, Huang Q, Xu C, Teichmann SA, Kaminski N, Pellegrini M, Nguyen Q, Teschendorff AE. Challenges and perspectives in computational deconvolution of genomics data. Nat Methods 2024; 21:391-400. [PMID: 38374264 DOI: 10.1038/s41592-023-02166-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 12/26/2023] [Indexed: 02/21/2024]
Abstract
Deciphering cell-type heterogeneity is crucial for systematically understanding tissue homeostasis and its dysregulation in diseases. Computational deconvolution is an efficient approach for estimating cell-type abundances from a variety of omics data. Despite substantial methodological progress in computational deconvolution in recent years, challenges are still outstanding. Here we enlist four important challenges related to computational deconvolution: the quality of the reference data, generation of ground truth data, limitations of computational methodologies, and benchmarking design and implementation. Finally, we make recommendations on reference data generation, new directions of computational methodologies, and strategies to promote rigorous benchmarking.
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Affiliation(s)
- Lana X Garmire
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
| | - Yijun Li
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Qianhui Huang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Chuan Xu
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | | | - Naftali Kaminski
- Pulmonary, Critical Care & Sleep Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Matteo Pellegrini
- Molecular, Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Quan Nguyen
- Institute for Molecular Bioscience, The University of Queensland and QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Andrew E Teschendorff
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
- UCL Cancer Institute, University College London, London, UK
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42
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Ma C, Zhang Y, Cao Y, Hu CH, Zheng CX, Jin Y, Sui BD. Autonomic neural regulation in mediating the brain-bone axis: mechanisms and implications for regeneration under psychological stress. QJM 2024; 117:95-108. [PMID: 37252831 DOI: 10.1093/qjmed/hcad108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Indexed: 06/01/2023] Open
Abstract
Efficient regeneration of bone defects caused by disease or significant trauma is a major challenge in current medicine, which is particularly difficult yet significant under the emerging psychological stress in the modern society. Notably, the brain-bone axis has been proposed as a prominent new concept in recent years, among which autonomic nerves act as an essential and emerging skeletal pathophysiological factor related to psychological stress. Studies have established that sympathetic cues lead to impairment of bone homeostasis mainly through acting on mesenchymal stem cells (MSCs) and their derivatives with also affecting the hematopoietic stem cell (HSC)-lineage osteoclasts, and the autonomic neural regulation of stem cell lineages in bone is increasingly recognized to contribute to the bone degenerative disease, osteoporosis. This review summarizes the distribution characteristics of autonomic nerves in bone, introduces the regulatory effects and mechanisms of autonomic nerves on MSC and HSC lineages, and expounds the crucial role of autonomic neural regulation on bone physiology and pathology, which acts as a bridge between the brain and the bone. With the translational perspective, we further highlight the autonomic neural basis of psychological stress-induced bone loss and a series of pharmaceutical therapeutic strategies and implications toward bone regeneration. The summary of research progress in this field will add knowledge to the current landscape of inter-organ crosstalk and provide a medicinal basis for the achievement of clinical bone regeneration in the future.
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Affiliation(s)
- C Ma
- State Key Laboratory of Military Stomatology & National Clinical Research Center for Oral Diseases & Shaanxi International Joint Research Center for Oral Diseases, Center for Tissue Engineering, School of Stomatology, The Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Y Zhang
- Department of Medical Rehabilitation, School of Stomatology, The Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Y Cao
- State Key Laboratory of Military Stomatology & National Clinical Research Center for Oral Diseases & Shaanxi International Joint Research Center for Oral Diseases, Center for Tissue Engineering, School of Stomatology, The Fourth Military Medical University, Xi'an, Shaanxi 710032, China
- Department of Orthodontics, School of Stomatology, The Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - C-H Hu
- State Key Laboratory of Military Stomatology & National Clinical Research Center for Oral Diseases & Shaanxi International Joint Research Center for Oral Diseases, Center for Tissue Engineering, School of Stomatology, The Fourth Military Medical University, Xi'an, Shaanxi 710032, China
- Xi'an Institute of Tissue Engineering and Regenerative Medicine, Xi'an, Shaanxi 710032, China
| | - C-X Zheng
- State Key Laboratory of Military Stomatology & National Clinical Research Center for Oral Diseases & Shaanxi International Joint Research Center for Oral Diseases, Center for Tissue Engineering, School of Stomatology, The Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Y Jin
- State Key Laboratory of Military Stomatology & National Clinical Research Center for Oral Diseases & Shaanxi International Joint Research Center for Oral Diseases, Center for Tissue Engineering, School of Stomatology, The Fourth Military Medical University, Xi'an, Shaanxi 710032, China
- Xi'an Institute of Tissue Engineering and Regenerative Medicine, Xi'an, Shaanxi 710032, China
| | - B-D Sui
- State Key Laboratory of Military Stomatology & National Clinical Research Center for Oral Diseases & Shaanxi International Joint Research Center for Oral Diseases, Center for Tissue Engineering, School of Stomatology, The Fourth Military Medical University, Xi'an, Shaanxi 710032, China
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Haug S, Muthusamy S, Li Y, Stewart G, Li X, Treppner M, Köttgen A, Akilesh S. Multi-omic analysis of human kidney tissue identified medulla-specific gene expression patterns. Kidney Int 2024; 105:293-311. [PMID: 37995909 PMCID: PMC10843743 DOI: 10.1016/j.kint.2023.10.024] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Revised: 09/21/2023] [Accepted: 10/23/2023] [Indexed: 11/25/2023]
Abstract
The kidney medulla is a specialized region with important homeostatic functions. It has been implicated in genetic and developmental disorders along with ischemic and drug-induced injuries. Despite its role in kidney function and disease, the medulla's baseline gene expression and epigenomic signatures have not been well described in the adult human kidney. Here we generated and analyzed gene expression (RNA-seq), chromatin accessibility (ATAC-seq), chromatin conformation (Hi-C) and spatial transcriptomic data from the adult human kidney cortex and medulla. Tissue samples were obtained from macroscopically dissected cortex and medulla of tumor-adjacent normal material in nephrectomy specimens from five male patients. We used these carefully annotated specimens to reassign incorrectly labeled samples in the larger public Genotype-Tissue Expression (GTEx) Project, and to extract meaningful medullary gene expression signatures. Using integrated analysis of gene expression, chromatin accessibility and conformation profiles, we found insights into medulla development and function and then validated this by spatial transcriptomics and immunohistochemistry. Thus, our datasets provide a valuable resource for functional annotation of variants from genome-wide association studies and are freely accessible through an epigenome browser portal.
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Affiliation(s)
- Stefan Haug
- Institute of Genetic Epidemiology, Medical Center-University of Freiburg, Freiburg, Germany
| | - Selvaraj Muthusamy
- Department of Pathology, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Yong Li
- Institute of Genetic Epidemiology, Medical Center-University of Freiburg, Freiburg, Germany
| | - Galen Stewart
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA
| | - Xianwu Li
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA
| | - Martin Treppner
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Medical Center-University of Freiburg, Freiburg, Germany.
| | - Shreeram Akilesh
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA.
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Wang L, Hu Y, Gao L. Adjustment of scRNA-seq data to improve cell-type decomposition of spatial transcriptomics. Brief Bioinform 2024; 25:bbae063. [PMID: 38426323 PMCID: PMC10939420 DOI: 10.1093/bib/bbae063] [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: 11/02/2023] [Revised: 01/10/2024] [Accepted: 02/01/2024] [Indexed: 03/02/2024] Open
Abstract
Most sequencing-based spatial transcriptomics (ST) technologies do not achieve single-cell resolution where each captured location (spot) may contain a mixture of cells from heterogeneous cell types, and several cell-type decomposition methods have been proposed to estimate cell type proportions of each spot by integrating with single-cell RNA sequencing (scRNA-seq) data. However, these existing methods did not fully consider the effect of distribution difference between scRNA-seq and ST data for decomposition, leading to biased cell-type-specific genes derived from scRNA-seq for ST data. To address this issue, we develop an instance-based transfer learning framework to adjust scRNA-seq data by ST data to correctly match cell-type-specific gene expression. We evaluate the effect of raw and adjusted scRNA-seq data on cell-type decomposition by eight leading decomposition methods using both simulated and real datasets. Experimental results show that data adjustment can effectively reduce distribution difference and improve decomposition, thus enabling for a more precise depiction on spatial organization of cell types. We highlight the importance of data adjustment in integrative analysis of scRNA-seq with ST data and provide guidance for improved cell-type decomposition.
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Affiliation(s)
- Lanying Wang
- School of Computer Science and Technology, Xidian University, Xi’an 710100, China
| | - Yuxuan Hu
- School of Computer Science and Technology, Xidian University, Xi’an 710100, China
| | - Lin Gao
- School of Computer Science and Technology, Xidian University, Xi’an 710100, China
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45
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Hargarten JC, Ssebambulidde K, Anjum SH, Vaughan MJ, Xu J, Song B, Ganguly A, Park YD, Scott T, Hammoud DA, Olszewski MA, Williamson PR. JAK/STAT Signaling Predominates in Human and Murine Fungal Post-infectious Inflammatory Response Syndrome. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.18.24301483. [PMID: 38293201 PMCID: PMC10827263 DOI: 10.1101/2024.01.18.24301483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Post-infection inflammatory syndromes have been increasingly recognized as a cause of host damage in a variety of infectious diseases including tuberculosis, bacterial meningitis, and COVID-19. Recently, a post-infectious inflammatory response syndrome (PIIRS) was described in non-HIV-infected cryptococcal fungal meningoencephalitis (CM) as a major cause of mortality. Inflammatory syndromes are particularly severe in neurological infections due to the skull's rigid structure which limits unchecked tissue expansion from inflammatory-induced edema. In the present studies, neurologic transcriptional pathway analysis utilizing a murine PIIRS model demonstrated a predominance of Janus kinase/signal transducer and activator of transcription (JAK/STAT) activation. JAK/STAT inhibitor treatment resulted in improvements in CNS damage markers, reductions in intrathecal CD44hiCD62lo CD4+ effector CD4+ T-cells and MHC II+ inflammatory myeloid cells, and weight gains in mice, the latter after treatment with antifungals. Based on these data, pathway-driven steroid-sparing human treatment for steroid-refractory PIIRS was initiated using short courses of the JAK/STAT inhibitor ruxolitinib. These were well tolerated and reduced activated HLA-DR+ CD4+ and CD8+ cells and inflammatory monocytes as well as improved brain imaging. Together, these findings support the role of JAK/STAT in PIIRS as well as further study of JAK/STAT inhibitors as potential adjunctive therapy for PIRS and other neural inflammatory syndromes.
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Affiliation(s)
- Jessica C. Hargarten
- Laboratory of Clinical Immunology and Microbiology (LCIM), Division of Intramural Research (DIR), National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Kenneth Ssebambulidde
- Laboratory of Clinical Immunology and Microbiology (LCIM), Division of Intramural Research (DIR), National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA
- Infectious Diseases Institute, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Seher H. Anjum
- Laboratory of Clinical Immunology and Microbiology (LCIM), Division of Intramural Research (DIR), National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Malcolm J. Vaughan
- Laboratory of Clinical Immunology and Microbiology (LCIM), Division of Intramural Research (DIR), National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Jintao Xu
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan Health System, Ann Arbor, MI, USA
- Research Service, Ann Arbor VA Healthcare System, Department of Veterans Affairs Health System, Ann Arbor, MI, USA
| | - Brian Song
- Research Service, Ann Arbor VA Healthcare System, Department of Veterans Affairs Health System, Ann Arbor, MI, USA
| | - Anutosh Ganguly
- Research Service, Ann Arbor VA Healthcare System, Department of Veterans Affairs Health System, Ann Arbor, MI, USA
| | - Yoon-dong Park
- Laboratory of Clinical Immunology and Microbiology (LCIM), Division of Intramural Research (DIR), National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Terri Scott
- Laboratory of Clinical Immunology and Microbiology (LCIM), Division of Intramural Research (DIR), National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Dima A. Hammoud
- Center for Infectious Disease Imaging (CIDI), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, Maryland, USA
| | - Michal A. Olszewski
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan Health System, Ann Arbor, MI, USA
- Research Service, Ann Arbor VA Healthcare System, Department of Veterans Affairs Health System, Ann Arbor, MI, USA
| | - Peter R. Williamson
- Laboratory of Clinical Immunology and Microbiology (LCIM), Division of Intramural Research (DIR), National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA
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Xu H, Fu H, Long Y, Ang KS, Sethi R, Chong K, Li M, Uddamvathanak R, Lee HK, Ling J, Chen A, Shao L, Liu L, Chen J. Unsupervised spatially embedded deep representation of spatial transcriptomics. Genome Med 2024; 16:12. [PMID: 38217035 PMCID: PMC10790257 DOI: 10.1186/s13073-024-01283-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 01/02/2024] [Indexed: 01/14/2024] Open
Abstract
Optimal integration of transcriptomics data and associated spatial information is essential towards fully exploiting spatial transcriptomics to dissect tissue heterogeneity and map out inter-cellular communications. We present SEDR, which uses a deep autoencoder coupled with a masked self-supervised learning mechanism to construct a low-dimensional latent representation of gene expression, which is then simultaneously embedded with the corresponding spatial information through a variational graph autoencoder. SEDR achieved higher clustering performance on manually annotated 10 × Visium datasets and better scalability on high-resolution spatial transcriptomics datasets than existing methods. Additionally, we show SEDR's ability to impute and denoise gene expression (URL: https://github.com/JinmiaoChenLab/SEDR/ ).
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Affiliation(s)
- Hang Xu
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), Singapore, 138648, Singapore
| | - Huazhu Fu
- Institute of High-Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), Singapore, 138632, Singapore
| | - Yahui Long
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), Singapore, 138648, Singapore
| | - Kok Siong Ang
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), Singapore, 138648, Singapore
| | - Raman Sethi
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), Singapore, 138648, Singapore
| | - Kelvin Chong
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), Singapore, 138648, Singapore
| | - Mengwei Li
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), Singapore, 138648, Singapore
| | - Rom Uddamvathanak
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), Singapore, 138648, Singapore
| | - Hong Kai Lee
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), Singapore, 138648, Singapore
| | - Jingjing Ling
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), Singapore, 138648, Singapore
| | - Ao Chen
- BGI Research-Southwest, BGI, Chongqing, 401329, China
- JFL-BGI STOmics Center, Jinfeng Laboratory, Chongqing, 401329, China
| | - Ling Shao
- UCAS-Terminus AI Lab, University of Chinese Academy of Sciences, Beijing, China
| | | | - Jinmiao Chen
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), Singapore, 138648, Singapore.
- Immunology Translational Research Program, Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University of Singapore (NUS), 5 Science Drive 2, BlkMD4, Level 3, Singapore, 117545, Singapore.
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Zeng L, Li L, Liao X, Zhang L, Yin C, Chen X, Sun J. Population-based high-dimensional analyses identify multiple intrinsic characters for cancer vaccines against lung squamous cell carcinoma. Med Oncol 2024; 41:42. [PMID: 38170412 DOI: 10.1007/s12032-023-02214-3] [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: 03/23/2023] [Accepted: 05/12/2023] [Indexed: 01/05/2024]
Abstract
In lung squamous cell carcinoma (LUSC), current cancer vaccines show promising effects, despite a lack of benefit for a large number of patients. We first identified the tumor antigens into shared and private antigens, and determined the population by clustering analysis in public datasets. For vaccine development, The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) were collected. WGCNA method was furthermore applied to construct a consensus gene co-expression network based on TCGA and CPTAC datasets. The main analyses in bulk sequencing included survival, clinical features, tumor microenvironment (TME), and pathways enrichment. In addition, single-cell RNA (scRNA) analysis of cancer epithelium dissected consensus subtype. We identified the ideal population for cancer vaccines, and candidate neoantigens including AOC1, COL5A2, LGI2, and POSTN. According to subtype analysis, Lung squamous 1 (LSQ1) type exhibited a higher tumor mutational load (TMB) and copy number but no immune infiltration, whereas lung squamous 2 (LSQ2) tumors had a higher global methylation level and more fibroblasts but had less stemness. Meanwhile, trajectory analysis further revealed that the evolution of TME influenced prognosis. We emphasized specific pathways or targets with the potential for combination immunotherapy by consensus network and single-cell RNA analyses. Anti-androgen therapy has been validated in vitro experiments of LUSC as proof of concept. In conclusion, LSQ1 was linked to immune exclusion and might be utilized for vaccination, while LSQ2 was linked to immune dysfunction and could be used for programmed cell death protein 1 (PD1) blocking therapy.
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Affiliation(s)
- Longjin Zeng
- Department of Basic Medicine, Army Medical University, Chongqing, 400038, People's Republic of China
| | - Lingchen Li
- Department of Medical Affairs, Xinqiao Hospital, Army Medical University, Chongqing, 400037, People's Republic of China
| | - Xingyun Liao
- Department of Oncology, Affiliated Tumor Hospital, Chongqing, 400037, People's Republic of China
| | - Lincheng Zhang
- Department of Basic Medicine, Army Medical University, Chongqing, 400038, People's Republic of China
| | - Chenrui Yin
- Department of Basic Medicine, Army Medical University, Chongqing, 400038, People's Republic of China
| | - Xiewan Chen
- Department of Basic Medicine, Army Medical University, Chongqing, 400038, People's Republic of China
| | - Jianguo Sun
- Cancer Institute, Xinqiao Hospital, Army Medical University, Chongqing, 400037, People's Republic of China.
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Shimonov S, Cunningham JM, Talmon R, Aizenbud L, Desai SJ, Rimm D, Schalper K, Kluger H, Kluger Y. SORBET: Automated cell-neighborhood analysis of spatial transcriptomics or proteomics for interpretable sample classification via GNN. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.30.573739. [PMID: 38260586 PMCID: PMC10802254 DOI: 10.1101/2023.12.30.573739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Spatially resolved transcriptomics or proteomics data have the potential to contribute fundamental insights into the mechanisms underlying physiologic and pathological processes. However, analysis of these data capable of relating spatial information, multiplexed markers, and their observed phenotypes remains technically challenging. To analyze these relationships, we developed SORBET, a deep learning framework that leverages recent advances in graph neural networks (GNN). We apply SORBET to predict tissue phenotypes, such as response to immunotherapy, across different disease processes and different technologies including both spatial proteomics and transcriptomics methods. Our results show that SORBET accurately learns biologically meaningful relationships across distinct tissue structures and data acquisition methods. Furthermore, we demonstrate that SORBET facilitates understanding of the spatially-resolved biological mechanisms underlying the inferred phenotypes. In sum, our method facilitates mapping between the rich spatial and marker information acquired from spatial 'omics technologies to emergent biological phenotypes. Moreover, we provide novel techniques for identifying the biological processes that comprise the predicted phenotypes.
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Smith KD, Prince DK, MacDonald JW, Bammler TK, Akilesh S. Challenges and Opportunities for the Clinical Translation of Spatial Transcriptomics Technologies. GLOMERULAR DISEASES 2024; 4:49-63. [PMID: 38600956 PMCID: PMC11006413 DOI: 10.1159/000538344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Accepted: 03/10/2024] [Indexed: 04/12/2024]
Abstract
Background The first spatially resolved transcriptomics platforms, GeoMx (Nanostring) and Visium (10x Genomics) were launched in 2019 and were recognized as the method of the year by Nature Methods in 2020. The subsequent refinement and expansion of these and other technologies to increase -plex, work with formalin-fixed paraffin-embedded tissue, and analyze protein in addition to gene expression have only added to their significance and impact on the biomedical sciences. In this perspective, we focus on two platforms for spatial transcriptomics, GeoMx and Visium, and how these platforms have been used to provide novel insight into kidney disease. The choice of platform will depend largely on experimental questions and design. The application of these technologies to clinically sourced biopsies presents the opportunity to identify specific tissue biomarkers that help define disease etiology and more precisely target therapeutic interventions in the future. Summary In this review, we provide a description of the existing and emerging technologies that can be used to capture spatially resolved gene and protein expression data from tissue. These technologies have provided new insight into the spatial heterogeneity of diseases, how reactions to disease are distributed within a tissue, which cells are affected, and molecular pathways that predict disease and response to therapy. Key Message The upcoming years will see intense use of spatial transcriptomics technologies to better define the pathophysiology of kidney diseases and develop novel diagnostic tests to guide personalized treatments for patients.
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Affiliation(s)
- Kelly D. Smith
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | | | - James W. MacDonald
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA
| | - Theo K. Bammler
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA
| | - Shreeram Akilesh
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
- Kidney Research Institute, Seattle, WA, USA
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Duggan WP, Kisakol B, Woods I, Azimi M, Dussmann H, Fay J, O’Grady T, Maguire B, Reynolds IS, Salvucci M, Slade DJ, McNamara DA, Burke JP, Prehn JH. Spatial transcriptomic analysis reveals local effects of intratumoral fusobacterial infection on DNA damage and immune signaling in rectal cancer. Gut Microbes 2024; 16:2350149. [PMID: 38709233 PMCID: PMC11086019 DOI: 10.1080/19490976.2024.2350149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Accepted: 04/26/2024] [Indexed: 05/07/2024] Open
Abstract
Mucinous colorectal cancer (CRC) is a common histological subtype of colorectal adenocarcinoma, associated with a poor response to chemoradiotherapy. The commensal facultative anaerobes fusobacteria, have been associated with poor prognosis specifically in mesenchymal CRC. Interestingly, fusobacterial infection is especially prevalent in mucinous CRC. The objective of this study was therefore to increase our understanding of beneficial and detrimental effects of fusobacterial infection, by contrasting host cell signaling and immune responses in areas of high vs. low infection, using mucinous rectal cancer as a clinically relevant example. We employed spatial transcriptomic profiling of 106 regions of interest from 8 mucinous rectal cancer samples to study gene expression in the epithelial and immune segments across regions of high versus low fusobacterial infection. Fusobacteria high regions were associated with increased oxidative stress, DNA damage, and P53 signaling. Meanwhile regions of low fusobacterial prevalence were characterized by elevated JAK-STAT, Il-17, Il-1, chemokine and TNF signaling. Immune masks within fusobacterial high regions were characterized by elevated proportions of cytotoxic (CD8+) T cells (p = 0.037), natural killer (NK) cells (p < 0.001), B-cells (p < 0.001), and gamma delta T cells (p = 0.003). Meanwhile, fusobacteria low regions were associated with significantly greater M2 macrophage (p < 0.001), fibroblast (p < 0.001), pericyte (p = 0.002), and endothelial (p < 0.001) counts.
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Affiliation(s)
- William P. Duggan
- Department of Colorectal Surgery, Beaumont Hospital, Dublin 9, Ireland
- Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, Dublin, Ireland
- RCSI Centre for Systems Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Batuhan Kisakol
- Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, Dublin, Ireland
- RCSI Centre for Systems Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Ina Woods
- Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Mohammedreza Azimi
- Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, Dublin, Ireland
- RCSI Centre for Systems Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Heiko Dussmann
- Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, Dublin, Ireland
- RCSI Centre for Systems Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Joanna Fay
- Department of Pathology, Beaumont Hospital, Dublin 9, Ireland
| | - Tony O’Grady
- Department of Pathology, Beaumont Hospital, Dublin 9, Ireland
| | - Barry Maguire
- Department of Colorectal Surgery, Beaumont Hospital, Dublin 9, Ireland
- Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, Dublin, Ireland
- RCSI Centre for Systems Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Ian S. Reynolds
- Department of Colorectal Surgery, Beaumont Hospital, Dublin 9, Ireland
- Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, Dublin, Ireland
- RCSI Centre for Systems Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Manuela Salvucci
- Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, Dublin, Ireland
- RCSI Centre for Systems Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Daniel J. Slade
- Department of Biochemistry, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
| | | | - John P. Burke
- Department of Colorectal Surgery, Beaumont Hospital, Dublin 9, Ireland
| | - Jochen H.M. Prehn
- Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, Dublin, Ireland
- RCSI Centre for Systems Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland
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