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Marima R, Basera A, Miya T, Damane BP, Kandhavelu J, Mirza S, Penny C, Dlamini Z. Exosomal long non-coding RNAs in cancer: Interplay, modulation, and therapeutic avenues. Noncoding RNA Res 2024; 9:887-900. [PMID: 38616862 PMCID: PMC11015109 DOI: 10.1016/j.ncrna.2024.03.014] [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: 11/27/2023] [Revised: 03/20/2024] [Accepted: 03/29/2024] [Indexed: 04/16/2024] Open
Abstract
In the intricate field of cancer biology, researchers are increasingly intrigued by the emerging role of exosomal long non-coding RNAs (lncRNAs) due to their multifaceted interactions, complex modulation mechanisms, and potential therapeutic applications. These exosomal lncRNAs, carried within extracellular vesicles, play a vital partin tumorigenesis and disease progression by facilitating communication networks between tumor cells and their local microenvironment, making them an ideal candidates for use in a liquid biopsy approach. However, exosomal lncRNAs remain an understudied area, especially in cancer biology. Therefore this review aims to comprehensively explore the dynamic interplay between exosomal lncRNAs and various cellular components, including interactions with tumor-stroma, immune modulation, and drug resistance mechanisms. Understanding the regulatory functions of exosomal lncRNAs in these processes can potentially unveil novel diagnostic markers and therapeutic targets for cancer. Additionally, the emergence of RNA-based therapeutics presents exciting opportunities for targeting exosomal lncRNAs, offering innovative strategies to combat cancer progression and improve treatment outcomes. Thus, this review provides insights into the current understanding of exosomal lncRNAs in cancer biology, highlighting their crucial roles, regulatory mechanisms, and the evolving landscape of therapeutic interventions. Furthermore, we have also discussed the advantage of exosomes as therapeutic carriers of lncRNAs for the development of personalized targeted therapy for cancer patients.
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Affiliation(s)
- Rahaba Marima
- SAMRC Precision Oncology Research Unit (PORU), DSI/NRF SARChi Chair in Precision Oncology and Cancer Prevention (POCP), Pan African Cancer Research Institute (PACRI), University of Pretoria, South Africa
| | - Afra Basera
- SAMRC Precision Oncology Research Unit (PORU), DSI/NRF SARChi Chair in Precision Oncology and Cancer Prevention (POCP), Pan African Cancer Research Institute (PACRI), University of Pretoria, South Africa
- Department of Medical Oncology, Faculty of Health Sciences, Steve Biko Academic Hospital, University of Pretoria, South Africa
| | - Thabiso Miya
- SAMRC Precision Oncology Research Unit (PORU), DSI/NRF SARChi Chair in Precision Oncology and Cancer Prevention (POCP), Pan African Cancer Research Institute (PACRI), University of Pretoria, South Africa
| | - Botle Precious Damane
- Department of Surgery, Steve Biko Academic Hospital, University of Pretoria, Pretoria, 0028, South Africa
| | - Jeyalakshmi Kandhavelu
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC, USA
| | - Sheefa Mirza
- Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Parktown, 2193, South Africa
| | - Clement Penny
- Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Parktown, 2193, South Africa
| | - Zodwa Dlamini
- SAMRC Precision Oncology Research Unit (PORU), DSI/NRF SARChi Chair in Precision Oncology and Cancer Prevention (POCP), Pan African Cancer Research Institute (PACRI), University of Pretoria, South Africa
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2
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Lim RMH, Lee JY, Kannan B, Ko TK, Chan JY. Molecular and immune pathobiology of human angiosarcoma. Biochim Biophys Acta Rev Cancer 2024; 1879:189159. [PMID: 39032539 DOI: 10.1016/j.bbcan.2024.189159] [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: 05/05/2024] [Revised: 07/15/2024] [Accepted: 07/17/2024] [Indexed: 07/23/2024]
Abstract
Angiosarcoma is a rare endothelial-derived malignancy that is extremely diverse in anatomy, aetiology, molecular and immune characteristics. While novel therapeutic approaches incorporating targeted agents and immunotherapy have yielded significant improvements in patient outcomes across several cancers, their impact on angiosarcoma remains modest. Contributed by its heterogeneous nature, there is currently a lack of novel drug targets in this disease entity and no reliable biomarkers that predict response to conventional treatment. This review aims to examine the molecular and immune landscape of angiosarcoma in association with its aetiology, anatomical sites, prognosis and therapeutic options. We summarise current efforts to characterise angiosarcoma subtypes based on molecular and immune profiling. Finally, we highlight promising technologies such as single-cell spatial "omics" that may further our understanding of angiosarcoma and propose strategies that can be similarly applied for the study of other rare cancers.
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Affiliation(s)
| | - Jing Yi Lee
- Cancer Discovery Hub, National Cancer Centre Singapore, Singapore; Duke-NUS Medical School, Singapore
| | - Bavani Kannan
- Cancer Discovery Hub, National Cancer Centre Singapore, Singapore
| | - Tun Kiat Ko
- Cancer Discovery Hub, National Cancer Centre Singapore, Singapore
| | - Jason Yongsheng Chan
- Cancer Discovery Hub, National Cancer Centre Singapore, Singapore; Duke-NUS Medical School, Singapore; Division of Medical Oncology, National Cancer Centre Singapore, Singapore.
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3
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Yang F, Yang J, Wu M, Chen C, Chu X. Tertiary lymphoid structures: new immunotherapy biomarker. Front Immunol 2024; 15:1394505. [PMID: 39026662 PMCID: PMC11254617 DOI: 10.3389/fimmu.2024.1394505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Accepted: 06/13/2024] [Indexed: 07/20/2024] Open
Abstract
Immunotherapy shows substantial advancement in cancer and is becoming widely used in clinical practice. A variety of biomarkers have been proposed to predict the efficacy of immunotherapy, but most of them have low predictive ability. Tertiary lymphoid structures (TLSs), the aggregation of multiple lymphocytes, have been found to exist in various tumor tissues. TLSs have been shown to correlate with patient prognosis and immunotherapy response. This review summarizes the characteristics of TLSs and the inducing factors of TLS formation, presents available evidence on the role of TLSs in predicting immunotherapy response in different cancers, and lastly emphasizes their predictive potential for neoadjuvant immunotherapy efficacy.
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Affiliation(s)
- Fangyuan Yang
- Department of Medical Oncology, Jinling Hospital, Nanjing Medical University, Nanjing, China
| | - Jiahe Yang
- Department of Medical Oncology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Meijuan Wu
- Department of Medical Oncology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Cheng Chen
- Department of Medical Oncology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Xiaoyuan Chu
- Department of Medical Oncology, Jinling Hospital, Nanjing Medical University, Nanjing, China
- Department of Medical Oncology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
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4
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Chan JY. Special Issue "Cancer Immunotherapy: Tumor Microenvironment, Biomarker Discovery and Immune Resistance". Int J Mol Sci 2024; 25:5113. [PMID: 38791152 PMCID: PMC11121284 DOI: 10.3390/ijms25105113] [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: 04/24/2024] [Accepted: 04/29/2024] [Indexed: 05/26/2024] Open
Abstract
Since the launch of this Special Issue entitled "Cancer Immunotherapy: Tumor Microenvironment, Biomarker Discovery and Immune Resistance", the field of cancer immunotherapy has continued to witness rapid growth in the development of novel agents, improvements in our understanding of mechanisms of response and resistance, and the maturation of emerging technologies such as artificial intelligence, machine learning, single-cell sequencing and spatial profiling [...].
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Affiliation(s)
- Jason Yongsheng Chan
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore 168583, Singapore; ; Tel.: +65-6436-8000; Fax: +65-6227-2759
- Cancer Discovery Hub, National Cancer Centre Singapore, Singapore 168583, Singapore
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5
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Qin Y, Huo M, Liu X, Li SC. Biomarkers and computational models for predicting efficacy to tumor ICI immunotherapy. Front Immunol 2024; 15:1368749. [PMID: 38524135 PMCID: PMC10957591 DOI: 10.3389/fimmu.2024.1368749] [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: 01/11/2024] [Accepted: 02/27/2024] [Indexed: 03/26/2024] Open
Abstract
Numerous studies have shown that immune checkpoint inhibitor (ICI) immunotherapy has great potential as a cancer treatment, leading to significant clinical improvements in numerous cases. However, it benefits a minority of patients, underscoring the importance of discovering reliable biomarkers that can be used to screen for potential beneficiaries and ultimately reduce the risk of overtreatment. Our comprehensive review focuses on the latest advancements in predictive biomarkers for ICI therapy, particularly emphasizing those that enhance the efficacy of programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) inhibitors and cytotoxic T-lymphocyte antigen-4 (CTLA-4) inhibitors immunotherapies. We explore biomarkers derived from various sources, including tumor cells, the tumor immune microenvironment (TIME), body fluids, gut microbes, and metabolites. Among them, tumor cells-derived biomarkers include tumor mutational burden (TMB) biomarker, tumor neoantigen burden (TNB) biomarker, microsatellite instability (MSI) biomarker, PD-L1 expression biomarker, mutated gene biomarkers in pathways, and epigenetic biomarkers. TIME-derived biomarkers include immune landscape of TIME biomarkers, inhibitory checkpoints biomarkers, and immune repertoire biomarkers. We also discuss various techniques used to detect and assess these biomarkers, detailing their respective datasets, strengths, weaknesses, and evaluative metrics. Furthermore, we present a comprehensive review of computer models for predicting the response to ICI therapy. The computer models include knowledge-based mechanistic models and data-based machine learning (ML) models. Among the knowledge-based mechanistic models are pharmacokinetic/pharmacodynamic (PK/PD) models, partial differential equation (PDE) models, signal networks-based models, quantitative systems pharmacology (QSP) models, and agent-based models (ABMs). ML models include linear regression models, logistic regression models, support vector machine (SVM)/random forest/extra trees/k-nearest neighbors (KNN) models, artificial neural network (ANN) and deep learning models. Additionally, there are hybrid models of systems biology and ML. We summarized the details of these models, outlining the datasets they utilize, their evaluation methods/metrics, and their respective strengths and limitations. By summarizing the major advances in the research on predictive biomarkers and computer models for the therapeutic effect and clinical utility of tumor ICI, we aim to assist researchers in choosing appropriate biomarkers or computer models for research exploration and help clinicians conduct precision medicine by selecting the best biomarkers.
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Affiliation(s)
- Yurong Qin
- Department of Computer Science, City University of Hong Kong, Kowloon, China
- City University of Hong Kong Shenzhen Research Institute, Shenzhen, Guangdong, China
| | - Miaozhe Huo
- Department of Computer Science, City University of Hong Kong, Kowloon, China
- City University of Hong Kong Shenzhen Research Institute, Shenzhen, Guangdong, China
| | - Xingwu Liu
- School of Mathematical Sciences, Dalian University of Technology, Dalian, Liaoning, China
| | - Shuai Cheng Li
- Department of Computer Science, City University of Hong Kong, Kowloon, China
- City University of Hong Kong Shenzhen Research Institute, Shenzhen, Guangdong, China
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6
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Yeo NKW, Lim CK, Yaung KN, Khoo NKH, Arkachaisri T, Albani S, Yeo JG. Genetic interrogation for sequence and copy number variants in systemic lupus erythematosus. Front Genet 2024; 15:1341272. [PMID: 38501057 PMCID: PMC10944961 DOI: 10.3389/fgene.2024.1341272] [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: 11/20/2023] [Accepted: 02/20/2024] [Indexed: 03/20/2024] Open
Abstract
Early-onset systemic lupus erythematosus presents with a more severe disease and is associated with a greater genetic burden, especially in patients from Black, Asian or Hispanic ancestries. Next-generation sequencing techniques, notably whole exome sequencing, have been extensively used in genomic interrogation studies to identify causal disease variants that are increasingly implicated in the development of autoimmunity. This Review discusses the known casual variants of polygenic and monogenic systemic lupus erythematosus and its implications under certain genetic disparities while suggesting an age-based sequencing strategy to aid in clinical diagnostics and patient management for improved patient care.
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Affiliation(s)
- Nicholas Kim-Wah Yeo
- Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Che Kang Lim
- Duke-NUS Medical School, Singapore, Singapore
- Department of Clinical Translation Research, Singapore General Hospital, Singapore, Singapore
| | - Katherine Nay Yaung
- Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Nicholas Kim Huat Khoo
- Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, Singapore
| | - Thaschawee Arkachaisri
- Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Rheumatology and Immunology Service, KK Women's and Children's Hospital, Singapore, Singapore
| | - Salvatore Albani
- Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Rheumatology and Immunology Service, KK Women's and Children's Hospital, Singapore, Singapore
| | - Joo Guan Yeo
- Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Rheumatology and Immunology Service, KK Women's and Children's Hospital, Singapore, Singapore
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7
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Catalano M, Iannone LF, Nesi G, Nobili S, Mini E, Roviello G. Immunotherapy-related biomarkers: Confirmations and uncertainties. Crit Rev Oncol Hematol 2023; 192:104135. [PMID: 37717881 DOI: 10.1016/j.critrevonc.2023.104135] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 08/18/2023] [Accepted: 09/12/2023] [Indexed: 09/19/2023] Open
Abstract
Immunotherapy profoundly changed oncology treatment, becoming one of the main therapeutical strategies. Remarkable improvement has been achieved in survival outcomes, but the percentage of patients who benefit from immunotherapy is still limited. Only one-third of patients receiving immune checkpoint inhibitors (ICIs) achieve long-term response. Several patients are not responsive to treatment or relapse after an initial response. To date, programmed death-ligand 1, microsatellite instability, and tumor mutational burden are the three biomarkers validated to predict the ICIs response, but a single variable seems still insufficient in the patient's selection. Considering the substantial and increasing use of these drugs, the identification of new predictive biomarkers of ICI response is of paramount importance. We summarize the state of the art and the clinical use of immune biomarkers in oncology, highlighting the strength and weaknesses of currently approved biomarkers, describing the emerging tissues and circulating biomarkers, and outlining future perspectives.
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Affiliation(s)
- Martina Catalano
- 1 Section of Clinical Pharmacology and Oncology, Department of Health Sciences, University of Florence, 50139 Florence, Italy
| | - Luigi Francesco Iannone
- 1 Section of Clinical Pharmacology and Oncology, Department of Health Sciences, University of Florence, 50139 Florence, Italy
| | - Gabriella Nesi
- Section of Pathological Anatomy, Department of Health Sciences, University of Florence, 50139 Florence, Italy
| | - Stefania Nobili
- Department of Neuroscience, Psychology, Drug Research and Child Health (NEUROFARBA), University of Florence, 50139 Florence, Italy
| | - Enrico Mini
- 1 Section of Clinical Pharmacology and Oncology, Department of Health Sciences, University of Florence, 50139 Florence, Italy
| | - Giandomenico Roviello
- 1 Section of Clinical Pharmacology and Oncology, Department of Health Sciences, University of Florence, 50139 Florence, Italy.
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8
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Jiang A, Liu Y, Chen O, Liu Z, Cai H, Wang L, Qi L. Editorial: Multi-omics approaches for decoding heterogeneity in cancer immunotherapy. Front Pharmacol 2023; 14:1324212. [PMID: 38026999 PMCID: PMC10656594 DOI: 10.3389/fphar.2023.1324212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 10/24/2023] [Indexed: 12/01/2023] Open
Affiliation(s)
- Aimin Jiang
- Department of Urology, Changhai Hospital, Naval Medical University, Shanghai, China
| | - Ying Liu
- Department of Urology, Changhai Hospital, Naval Medical University, Shanghai, China
| | - Ouyang Chen
- Department of Cell Biology, Duke University Medical Center, Durham, NC, United States
| | - Zhigang Liu
- Dongguan Key Laboratory of Precision Diagnosis and Treatment for Tumors, Dongguan, Guangdong, China
| | - Hongzhou Cai
- Department of Urology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Linhui Wang
- Department of Urology, Changhai Hospital, Naval Medical University, Shanghai, China
| | - Lin Qi
- Department of Orthopedics, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital, Changsha, Hunan, China
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9
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Chan JY, Somasundaram N, Grigoropoulos N, Lim F, Poon ML, Jeyasekharan A, Yeoh KW, Tan D, Lenz G, Ong CK, Lim ST. Evolving therapeutic landscape of diffuse large B-cell lymphoma: challenges and aspirations. Discov Oncol 2023; 14:132. [PMID: 37466782 PMCID: PMC10361453 DOI: 10.1007/s12672-023-00754-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 07/13/2023] [Indexed: 07/20/2023] Open
Abstract
Diffuse large B-cell lymphoma (DLBCL) represents the commonest subtype of non-Hodgkin lymphoma and encompasses a group of diverse disease entities, each harboring unique molecular and clinico-pathological features. The understanding of the molecular landscape of DLBCL has improved significantly over the past decade, highlighting unique genomic subtypes with implications on targeted therapy. At the same time, several new treatment modalities have been recently approved both in the frontline and relapsed settings, ending a dearth of negative clinical trials that plagued the past decade. Despite that, in the real-world setting, issues like drug accessibility, reimbursement policies, physician and patient preference, as well as questions regarding optimal sequencing of treatment options present difficulties and challenges in day-to-day oncology practice. Here, we review the recent advances in the therapeutic armamentarium of DLBCL and discuss implications on the practice landscape, with a particular emphasis on the context of the healthcare system in Singapore.
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Affiliation(s)
- Jason Yongsheng Chan
- Division of Medical Oncology, National Cancer Centre Singapore, 30 Hospital Blvd, Singapore, 168583, Singapore.
- Cancer and Stem Cell Biology, Duke-NUS Medical School, National Cancer Centre Singapore, 8 College Road, Singapore, 169857, Singapore.
| | - Nagavalli Somasundaram
- Division of Medical Oncology, National Cancer Centre Singapore, 30 Hospital Blvd, Singapore, 168583, Singapore
- Cancer and Stem Cell Biology, Duke-NUS Medical School, National Cancer Centre Singapore, 8 College Road, Singapore, 169857, Singapore
| | - Nicholas Grigoropoulos
- Cancer and Stem Cell Biology, Duke-NUS Medical School, National Cancer Centre Singapore, 8 College Road, Singapore, 169857, Singapore
- Department of Haematology, Singapore General Hospital, Singapore, Singapore
| | - Francesca Lim
- Cancer and Stem Cell Biology, Duke-NUS Medical School, National Cancer Centre Singapore, 8 College Road, Singapore, 169857, Singapore
- Department of Haematology, Singapore General Hospital, Singapore, Singapore
| | - Michelle Limei Poon
- Department of Haematology, National University Cancer Institute, Singapore, Singapore
| | - Anand Jeyasekharan
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
- Department of Haematology-Oncology, National University Cancer Institute, Singapore, Singapore
| | - Kheng Wei Yeoh
- Cancer and Stem Cell Biology, Duke-NUS Medical School, National Cancer Centre Singapore, 8 College Road, Singapore, 169857, Singapore
- Division of Radiation Oncology, National University Cancer Institute, Singapore, Singapore
| | - Daryl Tan
- Mount Elizabeth Novena Hospital, Singapore, Singapore
| | - Georg Lenz
- Department of Medicine A, Department of Hematology, Oncology and Pneumology, University Hospital Münster, Münster, Germany
| | - Choon Kiat Ong
- Cancer and Stem Cell Biology, Duke-NUS Medical School, National Cancer Centre Singapore, 8 College Road, Singapore, 169857, Singapore.
- Lymphoma Genomic Translational Research Laboratory, Cellular and Molecular Research, National Cancer Centre Singapore, Singapore, Singapore.
| | - Soon Thye Lim
- Division of Medical Oncology, National Cancer Centre Singapore, 30 Hospital Blvd, Singapore, 168583, Singapore.
- Cancer and Stem Cell Biology, Duke-NUS Medical School, National Cancer Centre Singapore, 8 College Road, Singapore, 169857, Singapore.
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10
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Khodayari S, Khodayari H, Saeedi E, Mahmoodzadeh H, Sadrkhah A, Nayernia K. Single-Cell Transcriptomics for Unlocking Personalized Cancer Immunotherapy: Toward Targeting the Origin of Tumor Development Immunogenicity. Cancers (Basel) 2023; 15:3615. [PMID: 37509276 PMCID: PMC10377122 DOI: 10.3390/cancers15143615] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 07/11/2023] [Accepted: 07/12/2023] [Indexed: 07/30/2023] Open
Abstract
Cancer immunotherapy is a promising approach for treating malignancies through the activation of anti-tumor immunity. However, the effectiveness and safety of immunotherapy can be limited by tumor complexity and heterogeneity, caused by the diverse molecular and cellular features of tumors and their microenvironments. Undifferentiated tumor cell niches, which we refer to as the "Origin of Tumor Development" (OTD) cellular population, are believed to be the source of these variations and cellular heterogeneity. From our perspective, the existence of distinct features within the OTD is expected to play a significant role in shaping the unique tumor characteristics observed in each patient. Single-cell transcriptomics is a high-resolution and high-throughput technique that provides insights into the genetic signatures of individual tumor cells, revealing mechanisms of tumor development, progression, and immune evasion. In this review, we explain how single-cell transcriptomics can be used to develop personalized cancer immunotherapy by identifying potential biomarkers and targets specific to each patient, such as immune checkpoint and tumor-infiltrating lymphocyte function, for targeting the OTD. Furthermore, in addition to offering a possible workflow, we discuss the future directions of, and perspectives on, single-cell transcriptomics, such as the development of powerful analytical tools and databases, that will aid in unlocking personalized cancer immunotherapy through the targeting of the patient's cellular OTD.
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Affiliation(s)
- Saeed Khodayari
- International Center for Personalized Medicine (P7MEDICINE), Luise-Rainer-Str. 6-12, 40235 Düsseldorf, Germany
| | - Hamid Khodayari
- International Center for Personalized Medicine (P7MEDICINE), Luise-Rainer-Str. 6-12, 40235 Düsseldorf, Germany
| | - Elnaz Saeedi
- Oxford Clinical Trials Research Unit, Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford OX3 7LD, UK
| | - Habibollah Mahmoodzadeh
- Breast Disease Research Center, Tehran University of Medical Sciences, Tehran 1819613844, Iran
| | | | - Karim Nayernia
- International Center for Personalized Medicine (P7MEDICINE), Luise-Rainer-Str. 6-12, 40235 Düsseldorf, Germany
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11
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Wang SS, Lewis MJ, Pitzalis C. DNA Methylation Signatures of Response to Conventional Synthetic and Biologic Disease-Modifying Antirheumatic Drugs (DMARDs) in Rheumatoid Arthritis. Biomedicines 2023; 11:1987. [PMID: 37509625 PMCID: PMC10377185 DOI: 10.3390/biomedicines11071987] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 07/03/2023] [Accepted: 07/11/2023] [Indexed: 07/30/2023] Open
Abstract
Rheumatoid arthritis (RA) is a complex condition that displays heterogeneity in disease severity and response to standard treatments between patients. Failure rates for conventional, target synthetic, and biologic disease-modifying rheumatic drugs (DMARDs) are significant. Although there are models for predicting patient response, they have limited accuracy, require replication/validation, or for samples to be obtained through a synovial biopsy. Thus, currently, there are no prediction methods approved for routine clinical use. Previous research has shown that genetics and environmental factors alone cannot explain the differences in response between patients. Recent studies have demonstrated that deoxyribonucleic acid (DNA) methylation plays an important role in the pathogenesis and disease progression of RA. Importantly, specific DNA methylation profiles associated with response to conventional, target synthetic, and biologic DMARDs have been found in the blood of RA patients and could potentially function as predictive biomarkers. This review will summarize and evaluate the evidence for DNA methylation signatures in treatment response mainly in blood but also learn from the progress made in the diseased tissue in cancer in comparison to RA and autoimmune diseases. We will discuss the benefits and challenges of using DNA methylation signatures as predictive markers and the potential for future progress in this area.
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Affiliation(s)
- Susan Siyu Wang
- Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Queen Mary University of London and Barts Health NIHR BRC & NHS Trust, London EC1M 6BQ, UK
| | - Myles J Lewis
- Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Queen Mary University of London and Barts Health NIHR BRC & NHS Trust, London EC1M 6BQ, UK
| | - Costantino Pitzalis
- Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Queen Mary University of London and Barts Health NIHR BRC & NHS Trust, London EC1M 6BQ, UK
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12
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Loh JW, Lee JY, Lim AH, Guan P, Lim BY, Kannan B, Lee ECY, Gu NX, Ko TK, Ng CCY, Lim JCT, Yeong J, Lim JQ, Ong CK, Teh BT, Chan JY. Spatial transcriptomics reveal topological immune landscapes of Asian head and neck angiosarcoma. Commun Biol 2023; 6:461. [PMID: 37106027 PMCID: PMC10140281 DOI: 10.1038/s42003-023-04856-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 04/20/2023] [Indexed: 04/29/2023] Open
Abstract
Angiosarcomas are rare malignant tumors of the endothelium, arising commonly from the head and neck region (AS-HN) and recently associated with ultraviolet (UV) exposure and human herpesvirus-7 infection. We examined 81 cases of angiosarcomas, including 47 cases of AS-HN, integrating information from whole genome sequencing, gene expression profiling and spatial transcriptomics (10X Visium). In the AS-HN cohort, we observed recurrent somatic mutations in CSMD3 (18%), LRP1B (18%), MUC16 (18%), POT1 (16%) and TP53 (16%). UV-positive AS-HN harbored significantly higher tumor mutation burden than UV-negative cases (p = 0.0294). NanoString profiling identified three clusters with distinct tumor inflammation signature scores (p < 0.001). Spatial transcriptomics revealed topological profiles of the tumor microenvironment, identifying dominant but tumor-excluded inflammatory signals in immune-hot cases and immune foci even in otherwise immune-cold cases. In conclusion, spatial transcriptomics reveal the tumor immune landscape of angiosarcoma, and in combination with multi-omic information, may improve implementation of treatment strategies.
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Affiliation(s)
- Jui Wan Loh
- Cancer Discovery Hub, National Cancer Centre Singapore, Singapore, Singapore
| | - Jing Yi Lee
- Cancer Discovery Hub, National Cancer Centre Singapore, Singapore, Singapore
| | - Abner Herbert Lim
- Laboratory of Cancer Epigenome, Division of Medical Sciences, National Cancer Centre Singapore, Singapore, Singapore
| | - Peiyong Guan
- Genome Institute of Singapore, Agency of Science, Technology and Research (ASTAR), Singapore, Singapore
| | - Boon Yee Lim
- Cancer Discovery Hub, National Cancer Centre Singapore, Singapore, Singapore
| | - Bavani Kannan
- Cancer Discovery Hub, National Cancer Centre Singapore, Singapore, Singapore
| | | | - Ning Xin Gu
- MGI Tech Singapore PTE LTD, Singapore, Singapore
| | - Tun Kiat Ko
- Cancer Discovery Hub, National Cancer Centre Singapore, Singapore, Singapore
| | | | - Jeffrey Chun Tatt Lim
- Institute of Molecular and Cell Biology, Agency of Science, Technology and Research (ASTAR), Singapore, Singapore
| | - Joe Yeong
- Institute of Molecular and Cell Biology, Agency of Science, Technology and Research (ASTAR), Singapore, Singapore
| | - Jing Quan Lim
- Lymphoma Genomic Translational Research Laboratory, Division of Cellular and Molecular Research, National Cancer Centre Singapore, Singapore, Singapore
| | - Choon Kiat Ong
- Lymphoma Genomic Translational Research Laboratory, Division of Cellular and Molecular Research, National Cancer Centre Singapore, Singapore, Singapore
- Program in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore, Singapore
| | - Bin Tean Teh
- Laboratory of Cancer Epigenome, Division of Medical Sciences, National Cancer Centre Singapore, Singapore, Singapore.
- Institute of Molecular and Cell Biology, Agency of Science, Technology and Research (ASTAR), Singapore, Singapore.
- Program in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore, Singapore.
| | - Jason Yongsheng Chan
- Cancer Discovery Hub, National Cancer Centre Singapore, Singapore, Singapore.
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore, Singapore.
- Oncology Academic Clinical Program, Duke-NUS Medical School, Singapore, Singapore.
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13
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Li T, Li Y, Zhu X, He Y, Wu Y, Ying T, Xie Z. Artificial intelligence in cancer immunotherapy: Applications in neoantigen recognition, antibody design and immunotherapy response prediction. Semin Cancer Biol 2023; 91:50-69. [PMID: 36870459 DOI: 10.1016/j.semcancer.2023.02.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 02/13/2023] [Accepted: 02/28/2023] [Indexed: 03/06/2023]
Abstract
Cancer immunotherapy is a method of controlling and eliminating tumors by reactivating the body's cancer-immunity cycle and restoring its antitumor immune response. The increased availability of data, combined with advancements in high-performance computing and innovative artificial intelligence (AI) technology, has resulted in a rise in the use of AI in oncology research. State-of-the-art AI models for functional classification and prediction in immunotherapy research are increasingly used to support laboratory-based experiments. This review offers a glimpse of the current AI applications in immunotherapy, including neoantigen recognition, antibody design, and prediction of immunotherapy response. Advancing in this direction will result in more robust predictive models for developing better targets, drugs, and treatments, and these advancements will eventually make their way into the clinical setting, pushing AI forward in the field of precision oncology.
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Affiliation(s)
- Tong Li
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Yupeng Li
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Xiaoyi Zhu
- MOE/NHC Key Laboratory of Medical Molecular Virology, Shanghai Institute of Infectious Disease and Biosecurity, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai, China; Shanghai Engineering Research Center for Synthetic Immunology, Shanghai, China
| | - Yao He
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Yanling Wu
- MOE/NHC Key Laboratory of Medical Molecular Virology, Shanghai Institute of Infectious Disease and Biosecurity, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai, China; Shanghai Engineering Research Center for Synthetic Immunology, Shanghai, China
| | - Tianlei Ying
- MOE/NHC Key Laboratory of Medical Molecular Virology, Shanghai Institute of Infectious Disease and Biosecurity, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai, China; Shanghai Engineering Research Center for Synthetic Immunology, Shanghai, China.
| | - Zhi Xie
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China; Center for Precision Medicine, Sun Yat-sen University, Guangzhou, China.
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14
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Yap DRY, Lim JQ, Huang D, Ong CK, Chan JY. Emerging predictive biomarkers for novel therapeutics in peripheral T-cell and natural killer/T-cell lymphoma. Front Immunol 2023; 14:1068662. [PMID: 36776886 PMCID: PMC9909478 DOI: 10.3389/fimmu.2023.1068662] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 01/09/2023] [Indexed: 01/27/2023] Open
Abstract
Peripheral T-cell lymphoma (PTCL) and natural killer/T-cell lymphoma (NKTCL) are rare subtypes of non-Hodgkin's lymphoma that are typically associated with poor treatment outcomes. Contemporary first-line treatment strategies generally involve the use of combination chemoimmunotherapy, radiation and/or stem cell transplant. Salvage options incorporate a number of novel agents including epigenetic therapies (e.g. HDAC inhibitors, DNMT inhibitors) as well as immune checkpoint inhibitors. However, validated biomarkers to select patients for individualized precision therapy are presently lacking, resulting in high treatment failure rates, unnecessary exposure to drug toxicities, and missed treatment opportunities. Recent advances in research on the tumor and microenvironmental factors of PTCL and NKTCL, including alterations in specific molecular features and immune signatures, have improved our understanding of these diseases, though several issues continue to impede progress in clinical translation. In this Review, we summarize the progress and development of the current predictive biomarker landscape, highlight potential knowledge gaps, and discuss the implications on novel therapeutics development in PTCL and NKTCL.
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Affiliation(s)
- Daniel Ren Yi Yap
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore, Singapore
| | - Jing Quan Lim
- Lymphoma Genomic Translational Research Laboratory, Division of Cellular and Molecular Research, National Cancer Centre Singapore, Singapore, Singapore
| | - Dachuan Huang
- Lymphoma Genomic Translational Research Laboratory, Division of Cellular and Molecular Research, National Cancer Centre Singapore, Singapore, Singapore
| | - Choon Kiat Ong
- Lymphoma Genomic Translational Research Laboratory, Division of Cellular and Molecular Research, National Cancer Centre Singapore, Singapore, Singapore
| | - Jason Yongsheng Chan
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore, Singapore
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15
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Decoding Roles of Exosomal lncRNAs in Tumor-Immune Regulation and Therapeutic Potential. Cancers (Basel) 2022; 15:cancers15010286. [PMID: 36612282 PMCID: PMC9818565 DOI: 10.3390/cancers15010286] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 12/12/2022] [Accepted: 12/29/2022] [Indexed: 01/03/2023] Open
Abstract
Exosomes are nanovesicles secreted into biofluids by various cell types and have been implicated in different physiological and pathological processes. Interestingly, a plethora of studies emphasized the mediating role of exosomes in the bidirectional communication between donor and recipient cells. Among the various cargoes of exosomes, long non-coding RNAs (lncRNAs) have been identified as crucial regulators between cancer cells and immune cells in the tumor microenvironment (TME) that can interfere with innate and adaptive immune responses to affect the therapeutic efficiency. Recently, a few major studies have focused on the exosomal lncRNA-mediated interaction between cancer cells and immune cells infiltrated into TME. Nevertheless, a dearth of studies pertains to the immune regulating role of exosomal lncRNAs in cancer and is still in the early stages. Comprehensive mechanisms of exosomal lncRNAs in tumor immunity are not well understood. Herein, we provide an overview of the immunomodulatory function of exosomal lncRNAs in cancer and treatment resistance. In addition, we also summarize the potential therapeutic strategies toward exosomal lncRNAs in TME.
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16
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Rationale Efficacy and Safety Evidence of Lenvatinib and Pembrolizumab Association in Anaplastic Thyroid Carcinoma. Curr Oncol 2022; 29:7718-7731. [PMID: 36290887 PMCID: PMC9601195 DOI: 10.3390/curroncol29100610] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 10/10/2022] [Accepted: 10/12/2022] [Indexed: 01/13/2023] Open
Abstract
Anaplastic thyroid carcinoma (ATC) are highly aggressive malignant tumors with poor overall prognosis despite multimodal therapy. As ATC are extremely rare, no randomized controlled study has been published for metastatic disease. Thyrosine kinase inhibitors, especially lenvatinib and immune checkpoint inhibitors such as pembrolizumab, are emerging drugs for ATC. Few studies have reported the efficacity of pembrolizumab and lenvatinib association, resulting in its frequent off-label use. In this review, we discuss rationale efficacy and safety evidence for the association of lenvatinib and pembrolizumab in ATC. First, we discuss preclinical rationale for pembrolizumab monotherapy, lenvatinib monotherapy and synergistic action of pembrolizumab and lenvatinib in the metastatic setting. We also discuss clinical evidence for immunotherapy and pembrolizumab in ATC through the analysis of studies evaluating immunotherapy, lenvatinib and pembrolizumab lenvatinib association in ATC. In addition, we discuss the safety of this association and potential predictive biomarkers of efficiency.
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