Pub Date : 2026-01-05DOI: 10.1038/s41568-025-00894-9
Changzheng Lu,Wenyan Wang,Yang-Xin Fu
The cyclic guanosine monophosphate-adenosine monophosphate synthase (cGAS)-stimulator of interferon genes (STING) pathway has a crucial role in detecting tumour-derived DNA, whether the pathway is generated spontaneously or induced therapeutically. Activation of the cGAS-STING pathway triggers type I interferon signalling and pro-inflammatory responses in both tumour and immune cells, establishing a delicate balance between pathological inflammation and protective immune responses. Although preclinical studies have highlighted the promise of targeting the cGAS-STING pathway to enhance antitumour immunotherapy, clinical results have fallen short of expectations. In this Review, we outline key advances in understanding the tumour-promoting and tumour-suppressive effects mediated by the cGAS-STING pathway and discuss opportunities and challenges for its integration into future cancer immunotherapy.
{"title":"Opportunities and challenges of targeting cGAS-STING in cancer.","authors":"Changzheng Lu,Wenyan Wang,Yang-Xin Fu","doi":"10.1038/s41568-025-00894-9","DOIUrl":"https://doi.org/10.1038/s41568-025-00894-9","url":null,"abstract":"The cyclic guanosine monophosphate-adenosine monophosphate synthase (cGAS)-stimulator of interferon genes (STING) pathway has a crucial role in detecting tumour-derived DNA, whether the pathway is generated spontaneously or induced therapeutically. Activation of the cGAS-STING pathway triggers type I interferon signalling and pro-inflammatory responses in both tumour and immune cells, establishing a delicate balance between pathological inflammation and protective immune responses. Although preclinical studies have highlighted the promise of targeting the cGAS-STING pathway to enhance antitumour immunotherapy, clinical results have fallen short of expectations. In this Review, we outline key advances in understanding the tumour-promoting and tumour-suppressive effects mediated by the cGAS-STING pathway and discuss opportunities and challenges for its integration into future cancer immunotherapy.","PeriodicalId":19055,"journal":{"name":"Nature Reviews Cancer","volume":"29 1","pages":""},"PeriodicalIF":78.5,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145897396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-02DOI: 10.1038/s41568-025-00897-6
Brendan Reardon, Aedin C Culhane, Eliezer M Van Allen
The number of data points per patient considered at the point-of-care in precision cancer medicine continues to increase, and it is accompanied by a growing challenge of translating these observations into clinical insights. This is a time-intensive and laborious process for oncology professionals and molecular tumour boards. As large clinicogenomic datasets and data-sharing protocols mature alongside machine learning methods, molecular diagnostic workflows have an opportunity to integrate these tools. This integration can help extract more information from next-generation sequencing data, enhance cancer variant interpretation, streamline case review and generate therapeutic hypotheses for biomarker-negative patients at the point-of-care. Although machine learning holds promise for precision oncology, responsible implementation and model evaluation remain essential for clinical adoption.
{"title":"Convergence of machine learning and genomics for precision oncology.","authors":"Brendan Reardon, Aedin C Culhane, Eliezer M Van Allen","doi":"10.1038/s41568-025-00897-6","DOIUrl":"https://doi.org/10.1038/s41568-025-00897-6","url":null,"abstract":"<p><p>The number of data points per patient considered at the point-of-care in precision cancer medicine continues to increase, and it is accompanied by a growing challenge of translating these observations into clinical insights. This is a time-intensive and laborious process for oncology professionals and molecular tumour boards. As large clinicogenomic datasets and data-sharing protocols mature alongside machine learning methods, molecular diagnostic workflows have an opportunity to integrate these tools. This integration can help extract more information from next-generation sequencing data, enhance cancer variant interpretation, streamline case review and generate therapeutic hypotheses for biomarker-negative patients at the point-of-care. Although machine learning holds promise for precision oncology, responsible implementation and model evaluation remain essential for clinical adoption.</p>","PeriodicalId":19055,"journal":{"name":"Nature Reviews Cancer","volume":" ","pages":""},"PeriodicalIF":66.8,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145889829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-02DOI: 10.1038/s41568-025-00902-y
Gabrielle Brewer
By incorporating lectins that target specific tumour-associated carbohydrate antigens, Zhou et al. engineered bispecific antibodies that induce effective T cell activation and tumour regression in various cancers.
{"title":"Double trouble for the tumour glycocode","authors":"Gabrielle Brewer","doi":"10.1038/s41568-025-00902-y","DOIUrl":"10.1038/s41568-025-00902-y","url":null,"abstract":"By incorporating lectins that target specific tumour-associated carbohydrate antigens, Zhou et al. engineered bispecific antibodies that induce effective T cell activation and tumour regression in various cancers.","PeriodicalId":19055,"journal":{"name":"Nature Reviews Cancer","volume":"26 2","pages":"81-81"},"PeriodicalIF":66.8,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145889768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-09DOI: 10.1038/s41568-025-00899-4
Daniela Senft
A study published in Science shows that liver zonation shapes hepatocellular carcinoma (HCC) development. In mice, HCC predominantly originates from zone 3 hepatocytes, where GSTM2 and GSTM3 drive initiation by inhibiting ferroptosis, revealing metabolic vulnerabilities in liver cancer.
{"title":"Being in the zone","authors":"Daniela Senft","doi":"10.1038/s41568-025-00899-4","DOIUrl":"10.1038/s41568-025-00899-4","url":null,"abstract":"A study published in Science shows that liver zonation shapes hepatocellular carcinoma (HCC) development. In mice, HCC predominantly originates from zone 3 hepatocytes, where GSTM2 and GSTM3 drive initiation by inhibiting ferroptosis, revealing metabolic vulnerabilities in liver cancer.","PeriodicalId":19055,"journal":{"name":"Nature Reviews Cancer","volume":"26 1","pages":"6-6"},"PeriodicalIF":66.8,"publicationDate":"2025-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145715002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-08DOI: 10.1038/s41568-025-00893-w
André Veillette,Jiaxin Li,Cristian Camilo Galindo,Dominique Davidson,Zhenghai Tang
The ability of macrophages to eliminate cancer cells through phagocytosis is tightly controlled by pro-phagocytic and inhibitory phagocytic receptors. Pro-phagocytic receptors such as Fc receptors, macrophage-1 antigen (MAC-1; also known as CD11b/CD18) and signalling lymphocytic activation molecule family member 7 (SLAMF7) have been shown to facilitate tumour cell elimination in pre-clinical models, and Fc receptors have been determined critical for the anti-tumour efficacy of several monoclonal antibodies in the clinic. Pre-clinical and early clinical studies have also highlighted that blocking of inhibitory phagocytic checkpoints, most prominently signal-regulatory protein α (SIRPα) and its ligand CD47, is a promising therapeutic approach for cancer. However, concerns about limited efficacy and toxicities in recent clinical trials have led to diminished enthusiasm for this approach. In this Review, we examine the evidence supporting phagocytic checkpoints as targets for cancer therapy, while highlighting current challenges associated with this therapeutic strategy. We also offer recommendations for enhancing the efficacy and safety of this approach in future work.
{"title":"Targeting phagocytosis checkpoints for cancer immunotherapy.","authors":"André Veillette,Jiaxin Li,Cristian Camilo Galindo,Dominique Davidson,Zhenghai Tang","doi":"10.1038/s41568-025-00893-w","DOIUrl":"https://doi.org/10.1038/s41568-025-00893-w","url":null,"abstract":"The ability of macrophages to eliminate cancer cells through phagocytosis is tightly controlled by pro-phagocytic and inhibitory phagocytic receptors. Pro-phagocytic receptors such as Fc receptors, macrophage-1 antigen (MAC-1; also known as CD11b/CD18) and signalling lymphocytic activation molecule family member 7 (SLAMF7) have been shown to facilitate tumour cell elimination in pre-clinical models, and Fc receptors have been determined critical for the anti-tumour efficacy of several monoclonal antibodies in the clinic. Pre-clinical and early clinical studies have also highlighted that blocking of inhibitory phagocytic checkpoints, most prominently signal-regulatory protein α (SIRPα) and its ligand CD47, is a promising therapeutic approach for cancer. However, concerns about limited efficacy and toxicities in recent clinical trials have led to diminished enthusiasm for this approach. In this Review, we examine the evidence supporting phagocytic checkpoints as targets for cancer therapy, while highlighting current challenges associated with this therapeutic strategy. We also offer recommendations for enhancing the efficacy and safety of this approach in future work.","PeriodicalId":19055,"journal":{"name":"Nature Reviews Cancer","volume":"110 1","pages":""},"PeriodicalIF":78.5,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145704301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-08DOI: 10.1038/s41568-025-00898-5
Shreya Gandhi,Shadi Ahmadian,Peter Buckle,David A Largaespada,Kenneth Aldape,Sheila Mansouri,Gelareh Zadeh
{"title":"A new framework for engaging patients and the public in basic cancer research.","authors":"Shreya Gandhi,Shadi Ahmadian,Peter Buckle,David A Largaespada,Kenneth Aldape,Sheila Mansouri,Gelareh Zadeh","doi":"10.1038/s41568-025-00898-5","DOIUrl":"https://doi.org/10.1038/s41568-025-00898-5","url":null,"abstract":"","PeriodicalId":19055,"journal":{"name":"Nature Reviews Cancer","volume":"132 1","pages":""},"PeriodicalIF":78.5,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145704652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-08DOI: 10.1038/s41568-025-00889-6
Hanzhi Luo, Michael G. Kharas, Samie R. Jaffrey
N6-Methyladenosine (m6A) is a modified nucleotide in mRNAs and non-coding RNAs that influences gene expression, primarily by promoting the degradation of specific transcripts. Recent studies have highlighted the dynamic and context-dependent roles of this RNA modification in cancer, implicating it in tumorigenesis, immune evasion and therapeutic resistance. In this Review, we discuss the functional roles of m6A writers, erasers and readers in cancer. We highlight how m6A dysregulation contributes to oncogenic processes, including cell differentiation and immune microenvironment remodelling. Using haematological malignancies as an example, we highlight the principles of m6A-dependent regulation that may be broadly relevant across cancer types. Notably, inhibitors targeting the m6A writer methyltransferase-like 3 (METTL3) have emerged as potential cancer therapeutics. METTL3 inhibitors not only disrupt m6A-dependent pathways but also elevate double-stranded RNA levels, activating innate immune responses and antitumour immunity. We emphasize the need for high-resolution quantitative m6A mapping in cancer and mechanistic studies to better understand the specific transcripts that exhibit altered patterns of m6A in cancer and to identify patient subgroups most likely to benefit from METTL3 inhibitors. In this Review Luo, Kharas and Jaffrey outline how N6-methyladenosine (m6A) RNA modification affects RNA stability, translation, splicing and immune responses to influence cancer biology. They discuss emerging evidence on how m6A may influence cancer metabolic reprogramming and outline the challenges and opportunities of targeting m6A writers, erasers and readers for cancer therapy.
{"title":"N6-Methyladenosine: an RNA modification as a central regulator of cancer","authors":"Hanzhi Luo, Michael G. Kharas, Samie R. Jaffrey","doi":"10.1038/s41568-025-00889-6","DOIUrl":"10.1038/s41568-025-00889-6","url":null,"abstract":"N6-Methyladenosine (m6A) is a modified nucleotide in mRNAs and non-coding RNAs that influences gene expression, primarily by promoting the degradation of specific transcripts. Recent studies have highlighted the dynamic and context-dependent roles of this RNA modification in cancer, implicating it in tumorigenesis, immune evasion and therapeutic resistance. In this Review, we discuss the functional roles of m6A writers, erasers and readers in cancer. We highlight how m6A dysregulation contributes to oncogenic processes, including cell differentiation and immune microenvironment remodelling. Using haematological malignancies as an example, we highlight the principles of m6A-dependent regulation that may be broadly relevant across cancer types. Notably, inhibitors targeting the m6A writer methyltransferase-like 3 (METTL3) have emerged as potential cancer therapeutics. METTL3 inhibitors not only disrupt m6A-dependent pathways but also elevate double-stranded RNA levels, activating innate immune responses and antitumour immunity. We emphasize the need for high-resolution quantitative m6A mapping in cancer and mechanistic studies to better understand the specific transcripts that exhibit altered patterns of m6A in cancer and to identify patient subgroups most likely to benefit from METTL3 inhibitors. In this Review Luo, Kharas and Jaffrey outline how N6-methyladenosine (m6A) RNA modification affects RNA stability, translation, splicing and immune responses to influence cancer biology. They discuss emerging evidence on how m6A may influence cancer metabolic reprogramming and outline the challenges and opportunities of targeting m6A writers, erasers and readers for cancer therapy.","PeriodicalId":19055,"journal":{"name":"Nature Reviews Cancer","volume":"26 2","pages":"118-136"},"PeriodicalIF":66.8,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145704653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-03DOI: 10.1038/s41568-025-00890-z
Samantha Stone, Jordan P. McPherson, Rajan P. Kulkarni, Arabella Young
During anticancer therapy, patients with cancer are often prescribed medications to combat concomitant health conditions and ameliorate cancer-associated side effects. Despite emerging evidence that many commonly prescribed medications have immunomodulating properties, surprisingly little is known about their interactions with immune checkpoint inhibitors (ICIs) in the treatment of cancer. This Review provides an overview of recent advances characterizing the reported impact of concomitant drug use on ICI-mediated therapeutic response and associated immune-related adverse events, and the potential to repurpose immunomodulatory drugs for other comorbidities to enhance ICI treatment efficacy. Concomitant medications are emerging as a modifiable prognostic factor for immune checkpoint inhibitor treatment outcomes. This Review by Stone et al. highlights the potential immunomodulatory interactions of commonly prescribed medications and supplements, and proposes strategies to make better use of this information to guide clinical care.
{"title":"The impact of concomitant medications on treatment outcomes in patients with cancer receiving immune checkpoint inhibitors","authors":"Samantha Stone, Jordan P. McPherson, Rajan P. Kulkarni, Arabella Young","doi":"10.1038/s41568-025-00890-z","DOIUrl":"10.1038/s41568-025-00890-z","url":null,"abstract":"During anticancer therapy, patients with cancer are often prescribed medications to combat concomitant health conditions and ameliorate cancer-associated side effects. Despite emerging evidence that many commonly prescribed medications have immunomodulating properties, surprisingly little is known about their interactions with immune checkpoint inhibitors (ICIs) in the treatment of cancer. This Review provides an overview of recent advances characterizing the reported impact of concomitant drug use on ICI-mediated therapeutic response and associated immune-related adverse events, and the potential to repurpose immunomodulatory drugs for other comorbidities to enhance ICI treatment efficacy. Concomitant medications are emerging as a modifiable prognostic factor for immune checkpoint inhibitor treatment outcomes. This Review by Stone et al. highlights the potential immunomodulatory interactions of commonly prescribed medications and supplements, and proposes strategies to make better use of this information to guide clinical care.","PeriodicalId":19055,"journal":{"name":"Nature Reviews Cancer","volume":"26 2","pages":"137-158"},"PeriodicalIF":66.8,"publicationDate":"2025-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145663940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-02DOI: 10.1038/s41568-025-00886-9
Yaoyi Dai, Shuai Guo, Yidan Pan, Carla Castignani, Matthew D. Montierth, Peter Van Loo, Wenyi Wang
Cancer tissues are heterogeneous mixtures of tumour, stromal and immune cells, where each component comprises multiple distinct cell types and/or states. Mapping this heterogeneity and understanding the unique contributions of each cell type to the tumour transcriptome is crucial for advancing cancer biology, yet high-throughput expression profiles from tumour tissues only represent combined signals from all cellular sources. Computational deconvolution of these mixed signals has emerged as a powerful approach to dissect both cellular composition and cell-type-specific expression patterns. Here, we provide a comprehensive guide to transcriptomic deconvolution, specifically tailored for cancer researchers, presenting a systematic framework for selecting and applying deconvolution methods, considering the unique complexities of tumour tissues, data availability and method assumptions. We detail 43 deconvolution methods and outline how different approaches serve distinctive applications in cancer research: from understanding tumour-immune surveillance to identifying cancer subtypes, discovering prognostic biomarkers and characterizing spatial tumour architecture. By examining the capabilities and limitations of these methods, we highlight emerging trends and future directions, particularly in addressing tumour cell plasticity and dynamic cell states. Tumour heterogeneity has a substantial impact on tumour progression and treatment response, yet bulk expression data obtained from clinical tumour samples obscure this complexity. Computational deconvolution methods can resolve cell-type-specific signals. This Review offers a practical guide for cancer researchers to select deconvolution methods and maximize the utility of bulk transcriptomic data.
{"title":"A guide to transcriptomic deconvolution in cancer","authors":"Yaoyi Dai, Shuai Guo, Yidan Pan, Carla Castignani, Matthew D. Montierth, Peter Van Loo, Wenyi Wang","doi":"10.1038/s41568-025-00886-9","DOIUrl":"10.1038/s41568-025-00886-9","url":null,"abstract":"Cancer tissues are heterogeneous mixtures of tumour, stromal and immune cells, where each component comprises multiple distinct cell types and/or states. Mapping this heterogeneity and understanding the unique contributions of each cell type to the tumour transcriptome is crucial for advancing cancer biology, yet high-throughput expression profiles from tumour tissues only represent combined signals from all cellular sources. Computational deconvolution of these mixed signals has emerged as a powerful approach to dissect both cellular composition and cell-type-specific expression patterns. Here, we provide a comprehensive guide to transcriptomic deconvolution, specifically tailored for cancer researchers, presenting a systematic framework for selecting and applying deconvolution methods, considering the unique complexities of tumour tissues, data availability and method assumptions. We detail 43 deconvolution methods and outline how different approaches serve distinctive applications in cancer research: from understanding tumour-immune surveillance to identifying cancer subtypes, discovering prognostic biomarkers and characterizing spatial tumour architecture. By examining the capabilities and limitations of these methods, we highlight emerging trends and future directions, particularly in addressing tumour cell plasticity and dynamic cell states. Tumour heterogeneity has a substantial impact on tumour progression and treatment response, yet bulk expression data obtained from clinical tumour samples obscure this complexity. Computational deconvolution methods can resolve cell-type-specific signals. This Review offers a practical guide for cancer researchers to select deconvolution methods and maximize the utility of bulk transcriptomic data.","PeriodicalId":19055,"journal":{"name":"Nature Reviews Cancer","volume":"26 2","pages":"84-103"},"PeriodicalIF":66.8,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145657027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-28DOI: 10.1038/s41568-025-00896-7
Gabrielle Brewer
A common side effect of treatment with taxane-based chemotherapy is peripheral neuropathy. Now, Fonseca et al. uncover the endoplasmic reticulum (ER) stress response in leukocytes as the effective mediator of paclitaxel-induced peripheral nerve damage.
{"title":"ER stress sparks nerve pain","authors":"Gabrielle Brewer","doi":"10.1038/s41568-025-00896-7","DOIUrl":"10.1038/s41568-025-00896-7","url":null,"abstract":"A common side effect of treatment with taxane-based chemotherapy is peripheral neuropathy. Now, Fonseca et al. uncover the endoplasmic reticulum (ER) stress response in leukocytes as the effective mediator of paclitaxel-induced peripheral nerve damage.","PeriodicalId":19055,"journal":{"name":"Nature Reviews Cancer","volume":"26 1","pages":"5-5"},"PeriodicalIF":66.8,"publicationDate":"2025-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145613711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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