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Zhou S, Lin N, Yu L, Su X, Liu Z, Yu X, Gao H, Lin S, Zeng Y. Single-cell multi-omics in the study of digestive system cancers. Comput Struct Biotechnol J 2024; 23:431-445. [PMID: 38223343 PMCID: PMC10787224 DOI: 10.1016/j.csbj.2023.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 12/07/2023] [Accepted: 12/07/2023] [Indexed: 01/16/2024] Open
Abstract
Digestive system cancers are prevalent diseases with a high mortality rate, posing a significant threat to public health and economic burden. The diagnosis and treatment of digestive system cancer confront conventional cancer problems, such as tumor heterogeneity and drug resistance. Single-cell sequencing (SCS) emerged at times required and has developed from single-cell RNA-seq (scRNA-seq) to the single-cell multi-omics era represented by single-cell spatial transcriptomics (ST). This article comprehensively reviews the advances of single-cell omics technology in the study of digestive system tumors. While analyzing and summarizing the research cases, vital details on the sequencing platform, sample information, sampling method, and key findings are provided. Meanwhile, we summarize the commonly used SCS platforms and their features, as well as the advantages of multi-omics technologies in combination. Finally, the development trends and prospects of the application of single-cell multi-omics technology in digestive system cancer research are prospected.
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Affiliation(s)
- Shuang Zhou
- The Second Clinical Medical School of Fujian Medical University, Quanzhou, Fujian Province, China
- The Clinical Center of Molecular Diagnosis and Therapy, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China
| | - Nanfei Lin
- The Clinical Center of Molecular Diagnosis and Therapy, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China
| | - Liying Yu
- The Clinical Center of Molecular Diagnosis and Therapy, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China
| | - Xiaoshan Su
- Department of Pulmonary and Critical Care Medicine, The Second Affiliated Hospital of Fujian Medical University, Respirology Medicine Centre of Fujian Province, Quanzhou, China
| | - Zhenlong Liu
- Lady Davis Institute for Medical Research, Jewish General Hospital, & Division of Experimental Medicine, Department of Medicine, McGill University, Montreal, QC, Canada
| | - Xiaowan Yu
- Clinical Laboratory, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China
| | - Hongzhi Gao
- The Clinical Center of Molecular Diagnosis and Therapy, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China
| | - Shu Lin
- Centre of Neurological and Metabolic Research, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China
- Diabetes and Metabolism Division, Garvan Institute of Medical Research, 384 Victoria Street, Darlinghurst, Sydney, NSW 2010, Australia
| | - Yiming Zeng
- Department of Pulmonary and Critical Care Medicine, The Second Affiliated Hospital of Fujian Medical University, Respirology Medicine Centre of Fujian Province, Quanzhou, China
- Fujian Provincial Key Laboratory of Lung Stem Cells, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China
- Jinan Microecological Biomedicine Shandong Laboratory, Jinan, Shandong Province, China
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Haller J, Abedi N, Hafedi A, Shehab O, Wietecha MS. Spatial Transcriptomics Unravel the Tissue Complexity of Oral Pathogenesis. J Dent Res 2024; 103:1331-1339. [PMID: 39382116 DOI: 10.1177/00220345241271934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/10/2024] Open
Abstract
Spatial transcriptomics (ST) is a cutting-edge methodology that enables the simultaneous profiling of global gene expression and spatial information within histological tissue sections. Traditional transcriptomic methods lack the spatial resolution required to sufficiently examine the complex interrelationships between cellular regions in diseased and healthy tissue states. We review the general workflows for ST, from specimen processing to ST data analysis and interpretations of the ST dataset using visualizations and cell deconvolution approaches. We show how recent studies used ST to explore the development or pathogenesis of specific craniofacial regions, including the cranium, palate, salivary glands, tongue, floor of mouth, oropharynx, and periodontium. Analyses of cranial suture patency and palatal fusion during development using ST identified spatial patterns of bone morphogenetic protein in sutures and osteogenic differentiation pathways in the palate, in addition to the discovery of several genes expressed at critical locations during craniofacial development. ST of salivary glands from patients with Sjögren's disease revealed co-localization of autoimmune antigens with ductal cells and a subpopulation of acinar cells that was specifically depleted by the dysregulated autoimmune response. ST of head and neck lesions, such as premalignant leukoplakia progressing to established oral squamous cell carcinomas, oral cancers with perineural invasions, and oropharyngeal lesions associated with HPV infection spatially profiled the complex tumor microenvironment, showing functionally important gene signatures of tumor cell differentiation, invasion, and nontumor cell dysregulation within patient biopsies. ST also enabled the localization of periodontal disease-associated gene expression signatures within gingival tissues, including genes involved in inflammation, and the discovery of a fibroblast subtype mediating the transition between innate and adaptive immune responses in periodontitis. The increased use of ST, especially in conjunction with single-cell analyses, promises to improve our understandings of craniofacial development and pathogenesis at unprecedented tissue-level resolution in both space and time.
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Affiliation(s)
- J Haller
- Department of Periodontics, College of Dentistry, University of Illinois Chicago, Chicago, IL, USA
| | - N Abedi
- Department of Oral Biology, College of Dentistry, University of Illinois Chicago, Chicago, IL, USA
| | - A Hafedi
- Department of Oral Biology, College of Dentistry, University of Illinois Chicago, Chicago, IL, USA
| | - O Shehab
- Department of Periodontics, College of Dentistry, University of Illinois Chicago, Chicago, IL, USA
| | - M S Wietecha
- Department of Oral Biology, College of Dentistry, University of Illinois Chicago, Chicago, IL, USA
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Pan Z, Zhou R, Wang Y. shinySRT: shareable and interactive visualization of spatially resolved data. J Genet Genomics 2024; 51:1147-1150. [PMID: 38897429 DOI: 10.1016/j.jgg.2024.06.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Revised: 06/05/2024] [Accepted: 06/13/2024] [Indexed: 06/21/2024]
Affiliation(s)
- Zhenzhong Pan
- Department of Neurosurgery and State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Ran Zhou
- Department of Neurosurgery and State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
| | - Yuan Wang
- Department of Neurosurgery and State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
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Wang N, Hong W, Wu Y, Chen Z, Bai M, Wang W, Zhu J. Next-generation spatial transcriptomics: unleashing the power to gear up translational oncology. MedComm (Beijing) 2024; 5:e765. [PMID: 39376738 PMCID: PMC11456678 DOI: 10.1002/mco2.765] [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: 04/20/2024] [Revised: 08/30/2024] [Accepted: 09/03/2024] [Indexed: 10/09/2024] Open
Abstract
The growing advances in spatial transcriptomics (ST) stand as the new frontier bringing unprecedented influences in the realm of translational oncology. This has triggered systemic experimental design, analytical scope, and depth alongside with thorough bioinformatics approaches being constantly developed in the last few years. However, harnessing the power of spatial biology and streamlining an array of ST tools to achieve designated research goals are fundamental and require real-world experiences. We present a systemic review by updating the technical scope of ST across different principal basis in a timeline manner hinting on the generally adopted ST techniques used within the community. We also review the current progress of bioinformatic tools and propose in a pipelined workflow with a toolbox available for ST data exploration. With particular interests in tumor microenvironment where ST is being broadly utilized, we summarize the up-to-date progress made via ST-based technologies by narrating studies categorized into either mechanistic elucidation or biomarker profiling (translational oncology) across multiple cancer types and their ways of deploying the research through ST. This updated review offers as a guidance with forward-looking viewpoints endorsed by many high-resolution ST tools being utilized to disentangle biological questions that may lead to clinical significance in the future.
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Affiliation(s)
- Nan Wang
- Cosmos Wisdom Biotech Co. LtdHangzhouChina
| | - Weifeng Hong
- Department of Radiation OncologyZhejiang Cancer HospitalHangzhouChina
- Hangzhou Institute of Medicine (HIM)Chinese Academy of SciencesHangzhouChina
- Zhejiang Key Laboratory of Radiation OncologyHangzhouChina
| | - Yixing Wu
- Department of Pulmonary and Critical Care MedicineZhongshan HospitalFudan UniversityShanghaiChina
| | - Zhe‐Sheng Chen
- Department of Pharmaceutical SciencesCollege of Pharmacy and Health SciencesInstitute for BiotechnologySt. John's UniversityQueensNew YorkUSA
| | - Minghua Bai
- Department of Radiation OncologyZhejiang Cancer HospitalHangzhouChina
- Hangzhou Institute of Medicine (HIM)Chinese Academy of SciencesHangzhouChina
- Zhejiang Key Laboratory of Radiation OncologyHangzhouChina
| | | | - Ji Zhu
- Department of Radiation OncologyZhejiang Cancer HospitalHangzhouChina
- Hangzhou Institute of Medicine (HIM)Chinese Academy of SciencesHangzhouChina
- Zhejiang Key Laboratory of Radiation OncologyHangzhouChina
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Liang W, Zhu Z, Xu D, Wang P, Guo F, Xiao H, Hou C, Xue J, Zhi X, Ran R. The burgeoning spatial multi-omics in human gastrointestinal cancers. PeerJ 2024; 12:e17860. [PMID: 39285924 PMCID: PMC11404479 DOI: 10.7717/peerj.17860] [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: 03/27/2024] [Accepted: 07/14/2024] [Indexed: 09/19/2024] Open
Abstract
The development and progression of diseases in multicellular organisms unfold within the intricate three-dimensional body environment. Thus, to comprehensively understand the molecular mechanisms governing individual development and disease progression, precise acquisition of biological data, including genome, transcriptome, proteome, metabolome, and epigenome, with single-cell resolution and spatial information within the body's three-dimensional context, is essential. This foundational information serves as the basis for deciphering cellular and molecular mechanisms. Although single-cell multi-omics technology can provide biological information such as genome, transcriptome, proteome, metabolome, and epigenome with single-cell resolution, the sample preparation process leads to the loss of spatial information. Spatial multi-omics technology, however, facilitates the characterization of biological data, such as genome, transcriptome, proteome, metabolome, and epigenome in tissue samples, while retaining their spatial context. Consequently, these techniques significantly enhance our understanding of individual development and disease pathology. Currently, spatial multi-omics technology has played a vital role in elucidating various processes in tumor biology, including tumor occurrence, development, and metastasis, particularly in the realms of tumor immunity and the heterogeneity of the tumor microenvironment. Therefore, this article provides a comprehensive overview of spatial transcriptomics, spatial proteomics, and spatial metabolomics-related technologies and their application in research concerning esophageal cancer, gastric cancer, and colorectal cancer. The objective is to foster the research and implementation of spatial multi-omics technology in digestive tumor diseases. This review will provide new technical insights for molecular biology researchers.
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Affiliation(s)
- Weizheng Liang
- Central Laboratory, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei province, China
| | - Zhenpeng Zhu
- Department of Surgery, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei Province, China
- Hebei North University, Zhangjiakou, Hebei Province, China
| | - Dandan Xu
- Central Laboratory, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei province, China
| | - Peng Wang
- Department of Surgery, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei Province, China
- Hebei North University, Zhangjiakou, Hebei Province, China
| | - Fei Guo
- Department of Surgery, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei Province, China
| | - Haoshan Xiao
- Department of Surgery, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei Province, China
- Hebei North University, Zhangjiakou, Hebei Province, China
| | - Chenyang Hou
- Department of Surgery, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei Province, China
- Hebei North University, Zhangjiakou, Hebei Province, China
| | - Jun Xue
- Department of Surgery, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei Province, China
| | - Xuejun Zhi
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei province, China
| | - Rensen Ran
- Central Laboratory, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei province, China
- Department of Chemical Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
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Xia T, Hu L, Zuo L, Cao L, Zhang Y, Xu M, Lu Q, Zhang L, Pan T, Zhang B, Ma B, Chen C, Guo J, Shi C, Li M, Liu C, Li Y, Zhang Y, Fang S. ST-GEARS: Advancing 3D downstream research through accurate spatial information recovery. Nat Commun 2024; 15:7806. [PMID: 39242563 PMCID: PMC11379900 DOI: 10.1038/s41467-024-51935-0] [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: 01/04/2024] [Accepted: 08/20/2024] [Indexed: 09/09/2024] Open
Abstract
Three-dimensional Spatial Transcriptomics has revolutionized our understanding of tissue regionalization, organogenesis, and development. However, existing approaches overlook either spatial information or experiment-induced distortions, leading to significant discrepancies between reconstruction results and in vivo cell locations, causing unreliable downstream analysis. To address these challenges, we propose ST-GEARS (Spatial Transcriptomics GEospatial profile recovery system through AnchoRS). By employing innovative Distributive Constraints into the Optimization scheme, ST-GEARS retrieves anchors with exceeding precision that connect closest spots across sections in vivo. Guided by the anchors, it first rigidly aligns sections, next solves and denoises Elastic Fields to counteract distortions. Through mathematically proved Bi-sectional Fields Application, it eventually recovers the original spatial profile. Studying ST-GEARS across number of sections, sectional distances and sequencing platforms, we observed its outstanding performance on tissue, cell, and gene levels. ST-GEARS provides precise and well-explainable 'gears' between in vivo situations and in vitro analysis, powerfully fueling potential of biological discoveries.
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Affiliation(s)
- Tianyi Xia
- BGI Research, Beijing, 102601, China
- BGI Research, Shenzhen, 518083, China
| | - Luni Hu
- BGI Research, Beijing, 102601, China
- BGI Research, Shenzhen, 518083, China
| | | | - Lei Cao
- BGI Research, Beijing, 102601, China
- BGI Research, Shenzhen, 518083, China
| | - Yunjia Zhang
- BGI Research, Beijing, 102601, China
- BGI Research, Shenzhen, 518083, China
| | - Mengyang Xu
- BGI Research, Shenzhen, 518083, China
- BGI Research, Qingdao, 266555, China
| | - Qin Lu
- BGI Research, Shenzhen, 518083, China
| | - Lei Zhang
- BGI Research, Beijing, 102601, China
- BGI Research, Shenzhen, 518083, China
| | - Taotao Pan
- BGI Research, Beijing, 102601, China
- BGI Research, Shenzhen, 518083, China
| | - Bohan Zhang
- BGI Research, Beijing, 102601, China
- BGI Research, Shenzhen, 518083, China
| | - Bowen Ma
- BGI Research, Beijing, 102601, China
- BGI Research, Shenzhen, 518083, China
| | - Chuan Chen
- BGI Research, Beijing, 102601, China
- BGI Research, Shenzhen, 518083, China
| | | | | | - Mei Li
- BGI Research, Shenzhen, 518083, China
| | - Chao Liu
- BGI Research, Beijing, 102601, China.
- BGI Research, Shenzhen, 518083, China.
| | - Yuxiang Li
- BGI Research, Shenzhen, 518083, China.
- BGI Research, Wuhan, 430074, China.
- Guangdong Bigdata Engineering Technology Research Center for Life Sciences, BGI research, Shenzhen, 518083, China.
| | - Yong Zhang
- BGI Research, Shenzhen, 518083, China.
- BGI Research, Wuhan, 430074, China.
- Guangdong Bigdata Engineering Technology Research Center for Life Sciences, BGI research, Shenzhen, 518083, China.
| | - Shuangsang Fang
- BGI Research, Beijing, 102601, China.
- BGI Research, Shenzhen, 518083, China.
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Maciejewski K, Czerwinska P. Scoping Review: Methods and Applications of Spatial Transcriptomics in Tumor Research. Cancers (Basel) 2024; 16:3100. [PMID: 39272958 PMCID: PMC11394603 DOI: 10.3390/cancers16173100] [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: 07/19/2024] [Revised: 08/30/2024] [Accepted: 08/30/2024] [Indexed: 09/15/2024] Open
Abstract
Spatial transcriptomics (ST) examines gene expression within its spatial context on tissue, linking morphology and function. Advances in ST resolution and throughput have led to an increase in scientific interest, notably in cancer research. This scoping study reviews the challenges and practical applications of ST, summarizing current methods, trends, and data analysis techniques for ST in neoplasm research. We analyzed 41 articles published by the end of 2023 alongside public data repositories. The findings indicate cancer biology is an important focus of ST research, with a rising number of studies each year. Visium (10x Genomics, Pleasanton, CA, USA) is the leading ST platform, and SCTransform from Seurat R library is the preferred method for data normalization and integration. Many studies incorporate additional data types like single-cell sequencing and immunohistochemistry. Common ST applications include discovering the composition and function of tumor tissues in the context of their heterogeneity, characterizing the tumor microenvironment, or identifying interactions between cells, including spatial patterns of expression and co-occurrence. However, nearly half of the studies lacked comprehensive data processing protocols, hindering their reproducibility. By recommending greater transparency in sharing analysis methods and adapting single-cell analysis techniques with caution, this review aims to improve the reproducibility and reliability of future studies in cancer research.
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Affiliation(s)
- Kacper Maciejewski
- Undergraduate Research Group "Biobase", Poznan University of Medical Sciences, 61-701 Poznan, Poland
| | - Patrycja Czerwinska
- Undergraduate Research Group "Biobase", Poznan University of Medical Sciences, 61-701 Poznan, Poland
- Department of Cancer Immunology, Poznan University of Medical Sciences, 61-866 Poznan, Poland
- Department of Diagnostics and Cancer Immunology, Greater Poland Cancer Centre, 61-866 Poznan, Poland
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Wu R, Horimoto Y, Oshi M, Benesch MGK, Khoury T, Takabe K, Ishikawa T. Emerging measurements for tumor-infiltrating lymphocytes in breast cancer. Jpn J Clin Oncol 2024; 54:620-629. [PMID: 38521965 PMCID: PMC11144297 DOI: 10.1093/jjco/hyae033] [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: 12/18/2023] [Accepted: 03/01/2024] [Indexed: 03/25/2024] Open
Abstract
Tumor-infiltrating lymphocytes are a general term for lymphocytes or immune cells infiltrating the tumor microenvironment. Numerous studies have demonstrated tumor-infiltrating lymphocytes to be robust prognostic and predictive biomarkers in breast cancer. Recently, immune checkpoint inhibitors, which directly target tumor-infiltrating lymphocytes, have become part of standard of care treatment for triple-negative breast cancer. Surprisingly, tumor-infiltrating lymphocytes quantified by conventional methods do not predict response to immune checkpoint inhibitors, which highlights the heterogeneity of tumor-infiltrating lymphocytes and the complexity of the immune network in the tumor microenvironment. Tumor-infiltrating lymphocytes are composed of diverse immune cell populations, including cytotoxic CD8-positive T lymphocytes, B cells and myeloid cells. Traditionally, tumor-infiltrating lymphocytes in tumor stroma have been evaluated by histology. However, the standardization of this approach is limited, necessitating the use of various novel technologies to elucidate the heterogeneity in the tumor microenvironment. This review outlines the evaluation methods for tumor-infiltrating lymphocytes from conventional pathological approaches that evaluate intratumoral and stromal tumor-infiltrating lymphocytes such as immunohistochemistry, to the more recent advancements in computer tissue imaging using artificial intelligence, flow cytometry sorting and multi-omics analyses using high-throughput assays to estimate tumor-infiltrating lymphocytes from bulk tumor using immune signatures or deconvolution tools. We also discuss higher resolution technologies that enable the analysis of tumor-infiltrating lymphocytes heterogeneity such as single-cell analysis and spatial transcriptomics. As we approach the era of personalized medicine, it is important for clinicians to understand these technologies.
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Affiliation(s)
- Rongrong Wu
- Department of Breast Surgery and Oncology, Tokyo Medical University, Tokyo, Japan
- Department of Surgical Oncology, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Yoshiya Horimoto
- Department of Breast Surgery and Oncology, Tokyo Medical University, Tokyo, Japan
- Department of Breast Oncology, Juntendo University Hospital, Tokyo, Japan
| | - Masanori Oshi
- Department of Surgical Oncology, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
- Department of Gastroenterological Surgery, Yokohama City University Graduate School of Medicine, Yokohama, Japan
| | - Matthew G K Benesch
- Department of Surgical Oncology, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Thaer Khoury
- Department of Pathology & Laboratory Medicine, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Kazuaki Takabe
- Department of Breast Surgery and Oncology, Tokyo Medical University, Tokyo, Japan
- Department of Surgical Oncology, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
- Department of Gastroenterological Surgery, Yokohama City University Graduate School of Medicine, Yokohama, Japan
- Department of Surgery, University at Buffalo Jacobs School of Medicine and Biomedical Sciences, The State University of New York, Buffalo, NY, USA
- Department of Surgery, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
- Department of Breast Surgery, Fukushima Medical University, Fukushima, Japan
| | - Takashi Ishikawa
- Department of Breast Surgery and Oncology, Tokyo Medical University, Tokyo, Japan
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Wu R, Ji P, Hua Y, Li H, Zhang W, Wei Y. Research progress in isolation and identification of rumen probiotics. Front Cell Infect Microbiol 2024; 14:1411482. [PMID: 38836057 PMCID: PMC11148321 DOI: 10.3389/fcimb.2024.1411482] [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: 04/03/2024] [Accepted: 04/30/2024] [Indexed: 06/06/2024] Open
Abstract
With the increasing research on the exploitation of rumen microbial resources, rumen probiotics have attracted much attention for their positive contributions in promoting nutrient digestion, inhibiting pathogenic bacteria, and improving production performance. In the past two decades, macrogenomics has provided a rich source of new-generation probiotic candidates, but most of these "dark substances" have not been successfully cultured due to the restrictive growth conditions. However, fueled by high-throughput culture and sorting technologies, it is expected that the potential probiotics in the rumen can be exploited on a large scale, and their potential applications in medicine and agriculture can be explored. In this paper, we review and summarize the classical techniques for isolation and identification of rumen probiotics, introduce the development of droplet-based high-throughput cell culture and single-cell sequencing for microbial culture and identification, and finally introduce promising cultureomics techniques. The aim is to provide technical references for the development of related technologies and microbiological research to promote the further development of the field of rumen microbiology research.
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Affiliation(s)
| | - Peng Ji
- College of Veterinary Medicine, Gansu Agricultural University, Lanzhou, China
| | | | | | | | - Yanming Wei
- College of Veterinary Medicine, Gansu Agricultural University, Lanzhou, China
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Li J, Wang Y, Raina MA, Xu C, Su L, Guo Q, Ma Q, Wang J, Xu D. scBSP: A fast and accurate tool for identifying spatially variable genes from spatial transcriptomic data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.06.592851. [PMID: 38765956 PMCID: PMC11100755 DOI: 10.1101/2024.05.06.592851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Spatially resolved transcriptomics have enabled the inference of gene expression patterns within two and three-dimensional space, while introducing computational challenges due to growing spatial resolutions and sparse expressions. Here, we introduce scBSP, an open-source, versatile, and user-friendly package designed for identifying spatially variable genes in large-scale spatial transcriptomics. scBSP implements sparse matrix operation to significantly increase the computational efficiency in both computational time and memory usage, processing the high-definition spatial transcriptomics data for 19,950 genes on 181,367 spots within 10 seconds. Applied to diverse sequencing data and simulations, scBSP efficiently identifies spatially variable genes, demonstrating fast computational speed and consistency across various sequencing techniques and spatial resolutions for both two and three-dimensional data with up to millions of cells. On a sample with hundreds of thousands of sports, scBSP identifies SVGs accurately in seconds to on a typical desktop computer.
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Johnson AL, Lopez-Bertoni H. Cellular diversity through space and time: adding new dimensions to GBM therapeutic development. Front Genet 2024; 15:1356611. [PMID: 38774283 PMCID: PMC11106394 DOI: 10.3389/fgene.2024.1356611] [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: 12/15/2023] [Accepted: 04/15/2024] [Indexed: 05/24/2024] Open
Abstract
The current median survival for glioblastoma (GBM) patients is only about 16 months, with many patients succumbing to the disease in just a matter of months, making it the most common and aggressive primary brain cancer in adults. This poor outcome is, in part, due to the lack of new treatment options with only one FDA-approved treatment in the last decade. Advances in sequencing techniques and transcriptomic analyses have revealed a vast degree of heterogeneity in GBM, from inter-patient diversity to intra-tumoral cellular variability. These cutting-edge approaches are providing new molecular insights highlighting a critical role for the tumor microenvironment (TME) as a driver of cellular plasticity and phenotypic heterogeneity. With this expanded molecular toolbox, the influence of TME factors, including endogenous (e.g., oxygen and nutrient availability and interactions with non-malignant cells) and iatrogenically induced (e.g., post-therapeutic intervention) stimuli, on tumor cell states can be explored to a greater depth. There exists a critical need for interrogating the temporal and spatial aspects of patient tumors at a high, cell-level resolution to identify therapeutically targetable states, interactions and mechanisms. In this review, we discuss advancements in our understanding of spatiotemporal diversity in GBM with an emphasis on the influence of hypoxia and immune cell interactions on tumor cell heterogeneity. Additionally, we describe specific high-resolution spatially resolved methodologies and their potential to expand the impact of pre-clinical GBM studies. Finally, we highlight clinical attempts at targeting hypoxia- and immune-related mechanisms of malignancy and the potential therapeutic opportunities afforded by single-cell and spatial exploration of GBM patient specimens.
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Affiliation(s)
- Amanda L. Johnson
- Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, MD, United States
- Department of Neurology, Baltimore, MD, United States
| | - Hernando Lopez-Bertoni
- Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, MD, United States
- Department of Neurology, Baltimore, MD, United States
- Oncology, Baltimore, MD, United States
- Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins University School of Medicine, Baltimore, MD, United States
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