Pub Date : 2024-08-10DOI: 10.1038/s41698-024-00668-w
Wei Hu, Ziqian Zhao, Jianxin Du, Jie Jiang, Minghao Yang, Maojin Tian, Peiqing Zhao
This study sought to elucidate the mechanisms underlying the impact of the interferon signaling pathway on Ferroptosis in tumor cells and its correlation with CD8 + T cell exhaustion. Using mouse models and single-cell sequencing, the researchers studied the interaction between CD8 + T cells and the interferon signaling pathway. Differential gene analysis revealed key genes involved in CD8 + T cell exhaustion, and their downstream factors were explored using bioinformatics tools. The expression levels of interferon-related genes associated with Ferroptosis were analyzed using data from the TCGA database, and their relevance to tumor tissue Ferroptosis and patients’ prognosis was determined. In vitro experiments were conducted to measure the levels of IFN-γ, MDA, and LPO, as well as tumor cell viability and apoptosis. In vivo validation using a mouse tumor model confirmed the results obtained from the in vitro experiments, highlighting the potential of silencing HSPA6 or DNAJB1 in enhancing the efficacy of PD-1 therapy and inhibiting tumor growth and migration.
{"title":"Interferon signaling and ferroptosis in tumor immunology and therapy","authors":"Wei Hu, Ziqian Zhao, Jianxin Du, Jie Jiang, Minghao Yang, Maojin Tian, Peiqing Zhao","doi":"10.1038/s41698-024-00668-w","DOIUrl":"10.1038/s41698-024-00668-w","url":null,"abstract":"This study sought to elucidate the mechanisms underlying the impact of the interferon signaling pathway on Ferroptosis in tumor cells and its correlation with CD8 + T cell exhaustion. Using mouse models and single-cell sequencing, the researchers studied the interaction between CD8 + T cells and the interferon signaling pathway. Differential gene analysis revealed key genes involved in CD8 + T cell exhaustion, and their downstream factors were explored using bioinformatics tools. The expression levels of interferon-related genes associated with Ferroptosis were analyzed using data from the TCGA database, and their relevance to tumor tissue Ferroptosis and patients’ prognosis was determined. In vitro experiments were conducted to measure the levels of IFN-γ, MDA, and LPO, as well as tumor cell viability and apoptosis. In vivo validation using a mouse tumor model confirmed the results obtained from the in vitro experiments, highlighting the potential of silencing HSPA6 or DNAJB1 in enhancing the efficacy of PD-1 therapy and inhibiting tumor growth and migration.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":null,"pages":null},"PeriodicalIF":6.8,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41698-024-00668-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141913468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-09DOI: 10.1038/s41698-024-00660-4
Chen Wei, Yijie Ma, Mengyu Wang, Siyi Wang, Wenyue Yu, Shuailei Dong, Wenying Deng, Liangyu Bie, Chi Zhang, Wei Shen, Qingxin Xia, Suxia Luo, Ning Li
Transcriptional heterogeneity of tumor-associated macrophages (TAMs) has been investigated in individual cancers, but the extent to which these states transcend tumor types and represent a general feature of cancer remains unclear. We performed pan-cancer single-cell RNA sequencing analysis across nine cancer types and identified distinct monocyte/TAM composition patterns. Using spatial analysis from clinical study tissues, we assessed TAM functions in shaping the tumor microenvironment (TME) and influencing immunotherapy. Two specific TAM clusters (pro-inflammatory and pro-tumor) and four TME subtypes showed distinct immunological features, genomic profiles, immunotherapy responses, and cancer prognosis. Pro-inflammatory TAMs resided in immune-enriched niches with exhausted CD8+ T cells, while pro-tumor TAMs were restricted to niches associated with a T-cell-excluded phenotype and hypoxia. We developed a machine learning model to predict immune checkpoint blockade response by integrating TAMs and clinical data. Our study comprehensively characterizes the common features of TAMs and highlights their interaction with the TME.
已对个别癌症中肿瘤相关巨噬细胞（TAMs）的转录异质性进行了研究，但这些状态在多大程度上超越了肿瘤类型并代表了癌症的普遍特征仍不清楚。我们对九种癌症类型进行了泛癌症单细胞 RNA 测序分析，发现了不同的单核细胞/TAM 组成模式。利用临床研究组织的空间分析，我们评估了 TAM 在塑造肿瘤微环境 (TME) 和影响免疫疗法方面的功能。两个特定的TAM集群（促炎和促瘤）和四个TME亚型显示出不同的免疫学特征、基因组特征、免疫疗法反应和癌症预后。促炎症TAM驻留在免疫丰富的壁龛中，CD8+ T细胞耗竭，而促肿瘤TAM则被限制在与T细胞排斥表型和缺氧相关的壁龛中。我们开发了一种机器学习模型，通过整合TAMs和临床数据来预测免疫检查点阻断反应。我们的研究全面描述了TAMs的共同特征，并强调了它们与TME的相互作用。
{"title":"Tumor-associated macrophage clusters linked to immunotherapy in a pan-cancer census","authors":"Chen Wei, Yijie Ma, Mengyu Wang, Siyi Wang, Wenyue Yu, Shuailei Dong, Wenying Deng, Liangyu Bie, Chi Zhang, Wei Shen, Qingxin Xia, Suxia Luo, Ning Li","doi":"10.1038/s41698-024-00660-4","DOIUrl":"10.1038/s41698-024-00660-4","url":null,"abstract":"Transcriptional heterogeneity of tumor-associated macrophages (TAMs) has been investigated in individual cancers, but the extent to which these states transcend tumor types and represent a general feature of cancer remains unclear. We performed pan-cancer single-cell RNA sequencing analysis across nine cancer types and identified distinct monocyte/TAM composition patterns. Using spatial analysis from clinical study tissues, we assessed TAM functions in shaping the tumor microenvironment (TME) and influencing immunotherapy. Two specific TAM clusters (pro-inflammatory and pro-tumor) and four TME subtypes showed distinct immunological features, genomic profiles, immunotherapy responses, and cancer prognosis. Pro-inflammatory TAMs resided in immune-enriched niches with exhausted CD8+ T cells, while pro-tumor TAMs were restricted to niches associated with a T-cell-excluded phenotype and hypoxia. We developed a machine learning model to predict immune checkpoint blockade response by integrating TAMs and clinical data. Our study comprehensively characterizes the common features of TAMs and highlights their interaction with the TME.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":null,"pages":null},"PeriodicalIF":6.8,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11310399/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141907293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-08DOI: 10.1038/s41698-024-00663-1
Rajat Thawani, Matteo Repetto, Clare Keddy, Katelyn Nicholson, Kristen Jones, Kevin Nusser, Catherine Z. Beach, Guilherme Harada, Alexander Drilon, Monika A. Davare
The grammar in this abstract is generally correct, but there’s a minor issue with sentence structure in one part. Here’s a slightly revised version with improved grammar and flow: ROS1 tyrosine kinase inhibitors (TKIs) are highly effective in ROS1-positive non-small cell lung cancer, but resistance remains a challenge. We investigated the activity of various TKIs against wildtype and mutant ROS1, focusing on the emerging L2086F resistance mutation. Using Ba/F3 and NIH3T3 cell models, CRISPR/Cas9-edited isogenic wildtype and mutant patient-derived cell lines, and in vivo tumor growth studies, we compared type I TKIs (crizotinib, entrectinib, taletrectinib, lorlatinib, and repotrectinib) to type II TKIs (cabozantinib and merestinib) and the type I FLT3 inhibitor gilteritinib. The ROS1 L2086F mutant kinase showed resistance to type I TKIs, while type II TKIs retained activity. Gilteritinib inhibited both wildtype and L2086F mutant ROS1 but was ineffective against the G2032R mutation. Structural analyses revealed distinct binding poses for cabozantinib and gilteritinib, explaining their efficacy against L2086F. Clinical cases demonstrated cabozantinib’s effectiveness in patients with TKI-resistant, ROS1 L2086F mutant NSCLCs. This study provides the first comprehensive report of ROS1 L2086F in the context of later-generation TKIs, including macrocyclic inhibitors. While cabozantinib effectively inhibits ROS1 L2086F, its multi-kinase inhibitor nature highlights the need for more selective and better-tolerated TKIs to overcome kinase-intrinsic resistance. Gilteritinib may offer an alternative for targeting ROS1 L2086F with distinct off-target toxicities, but further studies are required to fully evaluate its potential in this setting.
这篇摘要的语法基本正确，但有一部分的句子结构存在小问题。以下是稍作修改的版本，语法和语流都有所改进：ROS1酪氨酸激酶抑制剂（TKIs）对ROS1阳性非小细胞肺癌非常有效，但耐药性仍然是一个挑战。我们研究了各种TKIs对野生型和突变型ROS1的活性，重点是新出现的L2086F耐药突变。利用 Ba/F3 和 NIH3T3 细胞模型、CRISPR/Cas9 编辑的同源野生型和突变型患者衍生细胞系以及体内肿瘤生长研究，我们比较了 I 型 TKIs（crizotinib、entrectinib、taletrectinib、lorlatinib 和 repotrectinib）和 II 型 TKIs（cabozantinib 和 merestinib）以及 I 型 FLT3 抑制剂吉特替尼。ROS1 L2086F突变激酶对I型TKIs表现出耐药性，而II型TKIs则保持活性。吉特替尼对野生型和L2086F突变型ROS1均有抑制作用，但对G2032R突变无效。结构分析表明，卡博替尼和吉特替尼的结合位置不同，这也是它们对L2086F有效的原因。临床病例显示，卡博替尼对TKI耐药的ROS1 L2086F突变NSCLC患者有效。本研究首次全面报告了ROS1 L2086F在包括大环抑制剂在内的新一代TKIs中的情况。虽然卡博替尼能有效抑制ROS1 L2086F，但其多激酶抑制剂的特性突出表明，需要选择性更强、耐受性更好的TKIs来克服激酶内在耐药性。吉尔替尼可能为靶向ROS1 L2086F提供了一种具有明显脱靶毒性的替代方案，但要全面评估其在这种情况下的潜力，还需要进一步的研究。
{"title":"TKI type switching overcomes ROS1 L2086F in ROS1 fusion-positive cancers","authors":"Rajat Thawani, Matteo Repetto, Clare Keddy, Katelyn Nicholson, Kristen Jones, Kevin Nusser, Catherine Z. Beach, Guilherme Harada, Alexander Drilon, Monika A. Davare","doi":"10.1038/s41698-024-00663-1","DOIUrl":"10.1038/s41698-024-00663-1","url":null,"abstract":"The grammar in this abstract is generally correct, but there’s a minor issue with sentence structure in one part. Here’s a slightly revised version with improved grammar and flow: ROS1 tyrosine kinase inhibitors (TKIs) are highly effective in ROS1-positive non-small cell lung cancer, but resistance remains a challenge. We investigated the activity of various TKIs against wildtype and mutant ROS1, focusing on the emerging L2086F resistance mutation. Using Ba/F3 and NIH3T3 cell models, CRISPR/Cas9-edited isogenic wildtype and mutant patient-derived cell lines, and in vivo tumor growth studies, we compared type I TKIs (crizotinib, entrectinib, taletrectinib, lorlatinib, and repotrectinib) to type II TKIs (cabozantinib and merestinib) and the type I FLT3 inhibitor gilteritinib. The ROS1 L2086F mutant kinase showed resistance to type I TKIs, while type II TKIs retained activity. Gilteritinib inhibited both wildtype and L2086F mutant ROS1 but was ineffective against the G2032R mutation. Structural analyses revealed distinct binding poses for cabozantinib and gilteritinib, explaining their efficacy against L2086F. Clinical cases demonstrated cabozantinib’s effectiveness in patients with TKI-resistant, ROS1 L2086F mutant NSCLCs. This study provides the first comprehensive report of ROS1 L2086F in the context of later-generation TKIs, including macrocyclic inhibitors. While cabozantinib effectively inhibits ROS1 L2086F, its multi-kinase inhibitor nature highlights the need for more selective and better-tolerated TKIs to overcome kinase-intrinsic resistance. Gilteritinib may offer an alternative for targeting ROS1 L2086F with distinct off-target toxicities, but further studies are required to fully evaluate its potential in this setting.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":null,"pages":null},"PeriodicalIF":6.8,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11310217/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141907292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-05DOI: 10.1038/s41698-024-00665-z
Ariane Lozac’hmeur, Tyler Danek, Qidi Yang, Mario G. Rosasco, John S. Welch, William Y. Go, Eric W. Ng, Armen Mardiros, David G. Maloney, Edward B. Garon, Kedar Kirtane, Diane M. Simeone, Julian R. Molina, Ameen A. Salahudeen, Michelle M. Stein, J. Randolph Hecht
To enable interrogation of tumor HLA LOH as a clinical diagnostic for precision oncology, we developed and validated an assay that detects HLA LOH within the context of an FDA-approved clinical diagnostic test, Tempus xT CDx. Validation was conducted via: (1) analytical evaluation of 17 archival patient samples and 42 cell line admixtures and (2) independent clinical evaluation of LOH prevalence in the HLA-A gene (HLA-A LOH) across 10,982 patients. To evaluate the prognostic relevance of HLA-A LOH we assessed 256 immunotherapy-treated non-small cell lung cancer (NSCLC) patients. To determine the feasibility of prospectively identifying and enrolling HLA-A LOH patients into a clinical trial, we established BASECAMP-1 (NCT04981119). We observed a positive predictive agreement of 97% and a negative predictive agreement of 100% in samples with ≥ 40% tumor purity. We observed HLA-A LOH in 16.1% of patients (1771/10,982), comparable to previous reports. HLA-A LOH was associated with longer survival among NSCLC adenocarcinoma patients (HR = 0.60, 95% CI [0.37, 0.96], p = 0.032) with a trend towards shorter survival among squamous cell patients (HR = 1.64, 95% CI [0.80, 3.41], p = 0.183). In 20 months, we prospectively screened 1720 subjects using the Tempus AWARE program, identifying 26 HLA-A*02 LOH patients at 8 sites, with 14 (54%) enrolled into BASECAMP-1. In conclusion, we developed and validated an investigational assay that detects tumor HLA LOH within an FDA-approved clinical diagnostic test, enabling HLA LOH utilization in diagnostic, prognostic, and therapeutic applications.
{"title":"Detecting HLA loss of heterozygosity within a standard diagnostic sequencing workflow for prognostic and therapeutic opportunities","authors":"Ariane Lozac’hmeur, Tyler Danek, Qidi Yang, Mario G. Rosasco, John S. Welch, William Y. Go, Eric W. Ng, Armen Mardiros, David G. Maloney, Edward B. Garon, Kedar Kirtane, Diane M. Simeone, Julian R. Molina, Ameen A. Salahudeen, Michelle M. Stein, J. Randolph Hecht","doi":"10.1038/s41698-024-00665-z","DOIUrl":"10.1038/s41698-024-00665-z","url":null,"abstract":"To enable interrogation of tumor HLA LOH as a clinical diagnostic for precision oncology, we developed and validated an assay that detects HLA LOH within the context of an FDA-approved clinical diagnostic test, Tempus xT CDx. Validation was conducted via: (1) analytical evaluation of 17 archival patient samples and 42 cell line admixtures and (2) independent clinical evaluation of LOH prevalence in the HLA-A gene (HLA-A LOH) across 10,982 patients. To evaluate the prognostic relevance of HLA-A LOH we assessed 256 immunotherapy-treated non-small cell lung cancer (NSCLC) patients. To determine the feasibility of prospectively identifying and enrolling HLA-A LOH patients into a clinical trial, we established BASECAMP-1 (NCT04981119). We observed a positive predictive agreement of 97% and a negative predictive agreement of 100% in samples with ≥ 40% tumor purity. We observed HLA-A LOH in 16.1% of patients (1771/10,982), comparable to previous reports. HLA-A LOH was associated with longer survival among NSCLC adenocarcinoma patients (HR = 0.60, 95% CI [0.37, 0.96], p = 0.032) with a trend towards shorter survival among squamous cell patients (HR = 1.64, 95% CI [0.80, 3.41], p = 0.183). In 20 months, we prospectively screened 1720 subjects using the Tempus AWARE program, identifying 26 HLA-A*02 LOH patients at 8 sites, with 14 (54%) enrolled into BASECAMP-1. In conclusion, we developed and validated an investigational assay that detects tumor HLA LOH within an FDA-approved clinical diagnostic test, enabling HLA LOH utilization in diagnostic, prognostic, and therapeutic applications.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":null,"pages":null},"PeriodicalIF":6.8,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11300791/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141894006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tumor spread through air spaces (STAS) is a distinctive metastatic pattern affecting prognosis in lung adenocarcinoma (LUAD) patients. Several challenges are associated with STAS detection, including misdetection, low interobserver agreement, and lack of quantitative analysis. In this research, a total of 489 digital whole slide images (WSIs) were collected. The deep learning-based STAS detection model, named STASNet, was constructed to calculate semi-quantitative parameters associated with STAS density and distance. STASNet demonstrated an accuracy of 0.93 for STAS detection at the tiles level and had an AUC of 0.72–0.78 for determining the STAS status at the WSI level. Among the semi-quantitative parameters, T10S, combined with the spatial location information, significantly stratified stage I LUAD patients on disease-free survival. Additionally, STASNet was deployed into a real-time pathological diagnostic environment, which boosted the STAS detection rate and led to the identification of three easily misidentified types of occult STAS.
{"title":"Deep learning-based detection and semi-quantitative model for spread through air spaces (STAS) in lung adenocarcinoma","authors":"Yipeng Feng, Hanlin Ding, Xing Huang, Yijian Zhang, Mengyi Lu, Te Zhang, Hui Wang, Yuzhong Chen, Qixing Mao, Wenjie Xia, Bing Chen, Yi Zhang, Chen Chen, Tianhao Gu, Lin Xu, Gaochao Dong, Feng Jiang","doi":"10.1038/s41698-024-00664-0","DOIUrl":"10.1038/s41698-024-00664-0","url":null,"abstract":"Tumor spread through air spaces (STAS) is a distinctive metastatic pattern affecting prognosis in lung adenocarcinoma (LUAD) patients. Several challenges are associated with STAS detection, including misdetection, low interobserver agreement, and lack of quantitative analysis. In this research, a total of 489 digital whole slide images (WSIs) were collected. The deep learning-based STAS detection model, named STASNet, was constructed to calculate semi-quantitative parameters associated with STAS density and distance. STASNet demonstrated an accuracy of 0.93 for STAS detection at the tiles level and had an AUC of 0.72–0.78 for determining the STAS status at the WSI level. Among the semi-quantitative parameters, T10S, combined with the spatial location information, significantly stratified stage I LUAD patients on disease-free survival. Additionally, STASNet was deployed into a real-time pathological diagnostic environment, which boosted the STAS detection rate and led to the identification of three easily misidentified types of occult STAS.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":null,"pages":null},"PeriodicalIF":6.8,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11300827/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141894005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-03DOI: 10.1038/s41698-024-00657-z
Ferdinand W. Janssen, Nathalie S. M. Lak, Claudia Y. Janda, Lennart A. Kester, Michael T. Meister, Johannes H. M. Merks, Marry M. van den Heuvel-Eibrink, Max M. van Noesel, Jozsef Zsiros, Godelieve A. M. Tytgat, Leendert H. J. Looijenga
Liquid biopsies are emerging as an alternative source for pediatric cancer biomarkers with potential applications during all stages of patient care, from diagnosis to long-term follow-up. While developments within this field are reported, these mainly focus on dedicated items such as a specific liquid biopsy matrix, analyte, and/or single tumor type. To the best of our knowledge, a comprehensive overview is lacking. Here, we review the current state of liquid biopsy research for the most common non-central nervous system pediatric solid tumors. These include neuroblastoma, renal tumors, germ cell tumors, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma and other soft tissue sarcomas, and liver tumors. Within this selection, we discuss the most important or recent studies involving liquid biopsy-based biomarkers, anticipated clinical applications, and the current challenges for success. Furthermore, we provide an overview of liquid biopsy-based biomarker publication output for each tumor type based on a comprehensive literature search between 1989 and 2023. Per study identified, we list the relevant liquid biopsy-based biomarkers, matrices (e.g., peripheral blood, bone marrow, or cerebrospinal fluid), analytes (e.g., circulating cell-free and tumor DNA, microRNAs, and circulating tumor cells), methods (e.g., digital droplet PCR and next-generation sequencing), the involved pediatric patient cohort, and proposed applications. As such, we identified 344 unique publications. Taken together, while the liquid biopsy field in pediatric oncology is still behind adult oncology, potentially relevant publications have increased over the last decade. Importantly, steps towards clinical implementation are rapidly gaining ground, notably through validation of liquid biopsy-based biomarkers in pediatric clinical trials.
{"title":"A comprehensive overview of liquid biopsy applications in pediatric solid tumors","authors":"Ferdinand W. Janssen, Nathalie S. M. Lak, Claudia Y. Janda, Lennart A. Kester, Michael T. Meister, Johannes H. M. Merks, Marry M. van den Heuvel-Eibrink, Max M. van Noesel, Jozsef Zsiros, Godelieve A. M. Tytgat, Leendert H. J. Looijenga","doi":"10.1038/s41698-024-00657-z","DOIUrl":"10.1038/s41698-024-00657-z","url":null,"abstract":"Liquid biopsies are emerging as an alternative source for pediatric cancer biomarkers with potential applications during all stages of patient care, from diagnosis to long-term follow-up. While developments within this field are reported, these mainly focus on dedicated items such as a specific liquid biopsy matrix, analyte, and/or single tumor type. To the best of our knowledge, a comprehensive overview is lacking. Here, we review the current state of liquid biopsy research for the most common non-central nervous system pediatric solid tumors. These include neuroblastoma, renal tumors, germ cell tumors, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma and other soft tissue sarcomas, and liver tumors. Within this selection, we discuss the most important or recent studies involving liquid biopsy-based biomarkers, anticipated clinical applications, and the current challenges for success. Furthermore, we provide an overview of liquid biopsy-based biomarker publication output for each tumor type based on a comprehensive literature search between 1989 and 2023. Per study identified, we list the relevant liquid biopsy-based biomarkers, matrices (e.g., peripheral blood, bone marrow, or cerebrospinal fluid), analytes (e.g., circulating cell-free and tumor DNA, microRNAs, and circulating tumor cells), methods (e.g., digital droplet PCR and next-generation sequencing), the involved pediatric patient cohort, and proposed applications. As such, we identified 344 unique publications. Taken together, while the liquid biopsy field in pediatric oncology is still behind adult oncology, potentially relevant publications have increased over the last decade. Importantly, steps towards clinical implementation are rapidly gaining ground, notably through validation of liquid biopsy-based biomarkers in pediatric clinical trials.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":null,"pages":null},"PeriodicalIF":6.8,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11297996/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141889807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-02DOI: 10.1038/s41698-024-00667-x
Siyuan Cheng, Lin Li, Yunshin Yeh, Yingli Shi, Omar Franco, Eva Corey, Xiuping Yu
Recent advancements in single-cell RNA sequencing (scRNAseq) have facilitated the discovery of previously unrecognized subtypes within prostate cancer (PCa), offering new insights into cancer heterogeneity and progression. In this study, we integrated scRNAseq data from multiple studies, comprising publicly available cohorts and data generated by our research team, and established the Human Prostate Single cell Atlas (HuPSA) and Mouse Prostate Single cell Atlas (MoPSA) datasets. Through comprehensive analysis, we identified two novel double-negative PCa populations: KRT7 cells characterized by elevated KRT7 expression and progenitor-like cells marked by SOX2 and FOXA2 expression, distinct from NEPCa, and displaying stem/progenitor features. Furthermore, HuPSA-based deconvolution re-classified human PCa specimens, validating the presence of these novel subtypes. We then developed a user-friendly web application, “HuPSA–MoPSA” ( https://pcatools.shinyapps.io/HuPSA-MoPSA/ ), for visualizing gene expression across all newly established datasets. Our study provides comprehensive tools for PCa research and uncovers novel cancer subtypes that can inform clinical diagnosis and treatment strategies.
{"title":"Unveiling novel double-negative prostate cancer subtypes through single-cell RNA sequencing analysis","authors":"Siyuan Cheng, Lin Li, Yunshin Yeh, Yingli Shi, Omar Franco, Eva Corey, Xiuping Yu","doi":"10.1038/s41698-024-00667-x","DOIUrl":"10.1038/s41698-024-00667-x","url":null,"abstract":"Recent advancements in single-cell RNA sequencing (scRNAseq) have facilitated the discovery of previously unrecognized subtypes within prostate cancer (PCa), offering new insights into cancer heterogeneity and progression. In this study, we integrated scRNAseq data from multiple studies, comprising publicly available cohorts and data generated by our research team, and established the Human Prostate Single cell Atlas (HuPSA) and Mouse Prostate Single cell Atlas (MoPSA) datasets. Through comprehensive analysis, we identified two novel double-negative PCa populations: KRT7 cells characterized by elevated KRT7 expression and progenitor-like cells marked by SOX2 and FOXA2 expression, distinct from NEPCa, and displaying stem/progenitor features. Furthermore, HuPSA-based deconvolution re-classified human PCa specimens, validating the presence of these novel subtypes. We then developed a user-friendly web application, “HuPSA–MoPSA” ( https://pcatools.shinyapps.io/HuPSA-MoPSA/ ), for visualizing gene expression across all newly established datasets. Our study provides comprehensive tools for PCa research and uncovers novel cancer subtypes that can inform clinical diagnosis and treatment strategies.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":null,"pages":null},"PeriodicalIF":6.8,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11297170/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141879216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1038/s41698-024-00658-y
Han Gong, Peihe Zhang, Qiang Liu, Yuxuan Tian, Fuxin Chen, Siyi Qian, Chaofeng Tu, Yueqiu Tan, Xingming Hu, Bin Zhang
Lung adenocarcinoma (LUAD) is a leading cause of cancer mortality, with many patients facing poor prognosis, particularly those with metastatic or drug-resistant tumors. Homologous recombination genes (HRGs) are crucial in tumor progression and therapy resistance, but their clinical significance in LUAD is not well understood. In this study, we systematically characterize key HRGs in LUAD patients, identifying two distinct HR subtypes associated with different outcomes and biological functions. We establish a 5-gene scoring system (XRCC2, RAD51, BRCA1, FANCA, and CHEK1) that reliably predicts patient outcomes and immunotherapy responses in LUAD. Bioinformatics analysis and clinical validation highlight XRCC2 as a crucial biomarker in LUAD. Functional investigations through in vivo and in vitro experiments reveal the role of XRCC2 in promoting lung cancer migration and invasion. Mechanistically, XRCC2 stabilizes vimentin (VIM) protein expression through deubiquitylation. We predict c-MYC as a potential regulator of XRCC2 and demonstrate that inhibiting c-MYC with compound 10058-F4 reduces XRCC2 and VIM expression. Preclinical studies show the synergistic inhibition of metastasis in vivo when combining 10058-F4 with doxorubicin (Dox). Our findings present a potential personalized predictive tool for LUAD prognosis, identifying XRCC2 as a critical biomarker. The c-Myc-XRCC2-VIM axis emerges as a promising therapeutic target for overcoming lung metastasis. This study provides valuable insights into LUAD, proposing a prognostic tool for further clinical validation and unveiling a potential therapeutic strategy for combating lung metastasis by targeting c-Myc-XRCC2-VIM.
{"title":"XRCC2 driven homologous recombination subtypes and therapeutic targeting in lung adenocarcinoma metastasis","authors":"Han Gong, Peihe Zhang, Qiang Liu, Yuxuan Tian, Fuxin Chen, Siyi Qian, Chaofeng Tu, Yueqiu Tan, Xingming Hu, Bin Zhang","doi":"10.1038/s41698-024-00658-y","DOIUrl":"10.1038/s41698-024-00658-y","url":null,"abstract":"Lung adenocarcinoma (LUAD) is a leading cause of cancer mortality, with many patients facing poor prognosis, particularly those with metastatic or drug-resistant tumors. Homologous recombination genes (HRGs) are crucial in tumor progression and therapy resistance, but their clinical significance in LUAD is not well understood. In this study, we systematically characterize key HRGs in LUAD patients, identifying two distinct HR subtypes associated with different outcomes and biological functions. We establish a 5-gene scoring system (XRCC2, RAD51, BRCA1, FANCA, and CHEK1) that reliably predicts patient outcomes and immunotherapy responses in LUAD. Bioinformatics analysis and clinical validation highlight XRCC2 as a crucial biomarker in LUAD. Functional investigations through in vivo and in vitro experiments reveal the role of XRCC2 in promoting lung cancer migration and invasion. Mechanistically, XRCC2 stabilizes vimentin (VIM) protein expression through deubiquitylation. We predict c-MYC as a potential regulator of XRCC2 and demonstrate that inhibiting c-MYC with compound 10058-F4 reduces XRCC2 and VIM expression. Preclinical studies show the synergistic inhibition of metastasis in vivo when combining 10058-F4 with doxorubicin (Dox). Our findings present a potential personalized predictive tool for LUAD prognosis, identifying XRCC2 as a critical biomarker. The c-Myc-XRCC2-VIM axis emerges as a promising therapeutic target for overcoming lung metastasis. This study provides valuable insights into LUAD, proposing a prognostic tool for further clinical validation and unveiling a potential therapeutic strategy for combating lung metastasis by targeting c-Myc-XRCC2-VIM.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":null,"pages":null},"PeriodicalIF":6.8,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11294482/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141875525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1038/s41698-024-00643-5
Abdelrahman H. Elsayed, Xueyuan Cao, Richard J. Marrero, Nam H. K. Nguyen, Huiyun Wu, Yonhui Ni, Raul C. Ribeiro, Herold Tobias, Peter J. Valk, François Béliveau, Guillaume Richard-Carpentier, Josée Hébert, C. Michel Zwaan, Alan Gamis, Edward Anders Kolb, Richard Aplenc, Todd A. Alonzo, Soheil Meshinchi, Jeffrey Rubnitz, Stanley Pounds, Jatinder K. Lamba
In this study, we leveraged machine-learning tools by evaluating expression of genes of pharmacological relevance to standard-AML chemotherapy (ara-C/daunorubicin/etoposide) in a discovery-cohort of pediatric AML patients (N = 163; NCT00136084 ) and defined a 5-gene-drug resistance score (ADE-RS5) that was predictive of outcome (high MRD1 positivity p = 0.013; lower EFS p < 0.0001 and OS p < 0.0001). ADE-RS5 was integrated with a previously defined leukemic-stemness signature (pLSC6) to classify patients into four groups. ADE-RS5, pLSC6 and integrated-score was evaluated for association with outcome in one of the largest assembly of ~3600 AML patients from 10 independent cohorts (1861 pediatric and 1773 adult AML). Patients with high ADE-RS5 had poor outcome in validation cohorts and the previously reported pLSC6 maintained strong significant association in all validation cohorts. For pLSC6/ADE-RS5-integrated-score analysis, using Group-1 (low-scores for ADE-RS5 and pLSC6) as reference, Group-4 (high-scores for ADE-RS5 and pLSC6) showed worst outcome (EFS: p < 0.0001 and OS: p < 0.0001). Groups-2/3 (one high and one low-score) showed intermediate outcome (p < 0.001). Integrated score groups remained an independent predictor of outcome in multivariable-analysis after adjusting for established prognostic factors (EFS: Group 2 vs. 1, HR = 4.68, p < 0.001, Group 3 vs. 1, HR = 3.22, p = 0.01, and Group 4 vs. 1, HR = 7.26, p < 0.001). These results highlight the significant prognostic value of transcriptomics-based scores capturing disease aggressiveness through pLSC6 and drug resistance via ADE-RS5. The pLSC6 stemness score is a significant predictor of outcome and associates with high-risk group features, the ADE-RS5 drug resistance score adds further value, reflecting the clinical utility of simultaneous testing of both for optimizing treatment strategies.
在本研究中，我们利用机器学习工具，评估了儿科急性髓细胞性白血病患者发现队列（N = 163；NCT00136084）中与标准急性髓细胞性白血病化疗（阿糖胞苷/大柔比星/依托泊苷）药理学相关的基因表达，并定义了可预测预后的 5 基因耐药评分（ADE-RS5）（高 MRD1 阳性 p = 0.013；较低 EFS p = 0.013；较低 EFS p = 0.013）。
{"title":"Integrated drug resistance and leukemic stemness gene-expression scores predict outcomes in large cohort of over 3500 AML patients from 10 trials","authors":"Abdelrahman H. Elsayed, Xueyuan Cao, Richard J. Marrero, Nam H. K. Nguyen, Huiyun Wu, Yonhui Ni, Raul C. Ribeiro, Herold Tobias, Peter J. Valk, François Béliveau, Guillaume Richard-Carpentier, Josée Hébert, C. Michel Zwaan, Alan Gamis, Edward Anders Kolb, Richard Aplenc, Todd A. Alonzo, Soheil Meshinchi, Jeffrey Rubnitz, Stanley Pounds, Jatinder K. Lamba","doi":"10.1038/s41698-024-00643-5","DOIUrl":"10.1038/s41698-024-00643-5","url":null,"abstract":"In this study, we leveraged machine-learning tools by evaluating expression of genes of pharmacological relevance to standard-AML chemotherapy (ara-C/daunorubicin/etoposide) in a discovery-cohort of pediatric AML patients (N = 163; NCT00136084 ) and defined a 5-gene-drug resistance score (ADE-RS5) that was predictive of outcome (high MRD1 positivity p = 0.013; lower EFS p < 0.0001 and OS p < 0.0001). ADE-RS5 was integrated with a previously defined leukemic-stemness signature (pLSC6) to classify patients into four groups. ADE-RS5, pLSC6 and integrated-score was evaluated for association with outcome in one of the largest assembly of ~3600 AML patients from 10 independent cohorts (1861 pediatric and 1773 adult AML). Patients with high ADE-RS5 had poor outcome in validation cohorts and the previously reported pLSC6 maintained strong significant association in all validation cohorts. For pLSC6/ADE-RS5-integrated-score analysis, using Group-1 (low-scores for ADE-RS5 and pLSC6) as reference, Group-4 (high-scores for ADE-RS5 and pLSC6) showed worst outcome (EFS: p < 0.0001 and OS: p < 0.0001). Groups-2/3 (one high and one low-score) showed intermediate outcome (p < 0.001). Integrated score groups remained an independent predictor of outcome in multivariable-analysis after adjusting for established prognostic factors (EFS: Group 2 vs. 1, HR = 4.68, p < 0.001, Group 3 vs. 1, HR = 3.22, p = 0.01, and Group 4 vs. 1, HR = 7.26, p < 0.001). These results highlight the significant prognostic value of transcriptomics-based scores capturing disease aggressiveness through pLSC6 and drug resistance via ADE-RS5. The pLSC6 stemness score is a significant predictor of outcome and associates with high-risk group features, the ADE-RS5 drug resistance score adds further value, reflecting the clinical utility of simultaneous testing of both for optimizing treatment strategies.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":null,"pages":null},"PeriodicalIF":6.8,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11294346/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141875523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1038/s41698-024-00654-2
Dawoon E. Jung, Mi-Kyoung Seo, Jung Hyun Jo, Kahee Kim, Chanyang Kim, Hyundeok Kang, Soo Been Park, Hee Seung Lee, Sangwoo Kim, Si Young Song
Discovery and verification of diagnostic or therapeutic biomarkers for biliary tract cancer (BTC) is challenging owing to the low prevalence of the disease. Here, we identified and investigated the clinical impact of a fusion gene, Pumilio1-tumor necrosis factor receptor-associated factor 3 (PUM1-TRAF3), caused by 1;14 chromosomal translocation in BTC. PUM1-TRAF3 was initially identified in the RNA-sequencing of five BTC surgical tissues and confirmed by fluorescence in situ hybridization. Expression of the fusion gene was validated in an expanded cohort (5/55, 9.1%). Establishment and molecular assessment of PUM1-TRAF3 expressing BTC cells revealed that PUM1-TRAF3 activates non-canonical NF-κB signaling via NF-κB-inducing kinase (NIK). Abnormal TRAF3 activity, driven by competitive binding of PUM1-TRAF3 and TRAF3 to NIK, led to NIK rescue followed by P52/RelB nuclear translocation, all of which were reverted by an NIK inhibitor. The elevated expression of NIK and activated NF-κB signaling was observed in the PUM1-TRAF3-expressing regions of patient tissues. Expression of the PUM1-TRAF3 fusion was significantly correlated with strong NIK expression, which is associated with a poorer prognosis for patients with BTC. Overall, our study identifies a new fusion gene, PUM1-TRAF3, that activates NIK and non-canonical NF-κB signaling, which may be beneficial for developing precise treatment strategies for BTC.
{"title":"PUM1-TRAF3 fusion protein activates non-canonical NF-κB signaling via rescued NIK in biliary tract cancer","authors":"Dawoon E. Jung, Mi-Kyoung Seo, Jung Hyun Jo, Kahee Kim, Chanyang Kim, Hyundeok Kang, Soo Been Park, Hee Seung Lee, Sangwoo Kim, Si Young Song","doi":"10.1038/s41698-024-00654-2","DOIUrl":"10.1038/s41698-024-00654-2","url":null,"abstract":"Discovery and verification of diagnostic or therapeutic biomarkers for biliary tract cancer (BTC) is challenging owing to the low prevalence of the disease. Here, we identified and investigated the clinical impact of a fusion gene, Pumilio1-tumor necrosis factor receptor-associated factor 3 (PUM1-TRAF3), caused by 1;14 chromosomal translocation in BTC. PUM1-TRAF3 was initially identified in the RNA-sequencing of five BTC surgical tissues and confirmed by fluorescence in situ hybridization. Expression of the fusion gene was validated in an expanded cohort (5/55, 9.1%). Establishment and molecular assessment of PUM1-TRAF3 expressing BTC cells revealed that PUM1-TRAF3 activates non-canonical NF-κB signaling via NF-κB-inducing kinase (NIK). Abnormal TRAF3 activity, driven by competitive binding of PUM1-TRAF3 and TRAF3 to NIK, led to NIK rescue followed by P52/RelB nuclear translocation, all of which were reverted by an NIK inhibitor. The elevated expression of NIK and activated NF-κB signaling was observed in the PUM1-TRAF3-expressing regions of patient tissues. Expression of the PUM1-TRAF3 fusion was significantly correlated with strong NIK expression, which is associated with a poorer prognosis for patients with BTC. Overall, our study identifies a new fusion gene, PUM1-TRAF3, that activates NIK and non-canonical NF-κB signaling, which may be beneficial for developing precise treatment strategies for BTC.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":null,"pages":null},"PeriodicalIF":6.8,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11294552/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141875524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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