Suppr超能文献

比较转录组分析定量评估骨肉瘤中的免疫细胞转录水平、转移进展和生存情况。

Comparative Transcriptome Analysis Quantifies Immune Cell Transcript Levels, Metastatic Progression, and Survival in Osteosarcoma.

机构信息

Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota.

Animal Cancer Care and Research Program, University of Minnesota, St. Paul, Minnesota.

出版信息

Cancer Res. 2018 Jan 15;78(2):326-337. doi: 10.1158/0008-5472.CAN-17-0576. Epub 2017 Oct 24.

Abstract

Overall survival of patients with osteosarcoma (OS) has improved little in the past three decades, and better models for study are needed. OS is common in large dog breeds and is genetically inducible in mice, making the disease ideal for comparative genomic analyses across species. Understanding the level of conservation of intertumor transcriptional variation across species and how it is associated with progression to metastasis will enable us to more efficiently develop effective strategies to manage OS and to improve therapy. In this study, transcriptional profiles of OS tumors and cell lines derived from humans ( = 49), mice ( = 103), and dogs ( = 34) were generated using RNA sequencing. Conserved intertumor transcriptional variation was present in tumor sets from all three species and comprised gene clusters associated with cell cycle and mitosis and with the presence or absence of immune cells. Further, we developed a novel gene cluster expression summary score (GCESS) to quantify intertumor transcriptional variation and demonstrated that these GCESS values associated with patient outcome. Human OS tumors with GCESS values suggesting decreased immune cell presence were associated with metastasis and poor survival. We validated these results in an independent human OS tumor cohort and in 15 different tumor data sets obtained from The Cancer Genome Atlas. Our results suggest that quantification of immune cell absence and tumor cell proliferation may better inform therapeutic decisions and improve overall survival for OS patients. This study offers new tools to quantify tumor heterogeneity in osteosarcoma, identifying potentially useful prognostic biomarkers for metastatic progression and survival in patients. .

摘要

骨肉瘤(OS)患者的总体存活率在过去三十年中几乎没有改善,因此需要更好的研究模型。OS 在大型犬种中很常见,并且可以在小鼠中遗传诱导,这使得该疾病非常适合跨物种进行比较基因组分析。了解跨物种肿瘤间转录变异性的保守程度及其与转移进展的关系,将使我们能够更有效地制定有效的策略来管理 OS 并改善治疗效果。在这项研究中,使用 RNA 测序生成了来自人类(= 49)、小鼠(= 103)和犬(= 34)的 OS 肿瘤和细胞系的转录谱。所有三种物种的肿瘤组中均存在保守的肿瘤间转录变异性,并且包含与细胞周期和有丝分裂以及免疫细胞存在或不存在相关的基因簇。此外,我们开发了一种新的基因簇表达摘要评分(GCESS)来量化肿瘤间转录变异性,并证明这些 GCESS 值与患者的预后相关。GCESS 值提示免疫细胞存在减少的人类 OS 肿瘤与转移和不良生存相关。我们在一个独立的人类 OS 肿瘤队列和来自癌症基因组图谱的 15 个不同肿瘤数据集的验证了这些结果。我们的研究结果表明,定量评估免疫细胞缺失和肿瘤细胞增殖可能会更好地为治疗决策提供信息,并提高 OS 患者的总体生存率。这项研究提供了用于量化骨肉瘤肿瘤异质性的新工具,为转移性进展和生存的预后生物标志物提供了潜在的有用信息。

相似文献

1
Comparative Transcriptome Analysis Quantifies Immune Cell Transcript Levels, Metastatic Progression, and Survival in Osteosarcoma.
Cancer Res. 2018 Jan 15;78(2):326-337. doi: 10.1158/0008-5472.CAN-17-0576. Epub 2017 Oct 24.
2
A novel prognostic signature related to programmed cell death in osteosarcoma.
Front Immunol. 2024 Jul 1;15:1427661. doi: 10.3389/fimmu.2024.1427661. eCollection 2024.
6
Heterotypic mouse models of canine osteosarcoma recapitulate tumor heterogeneity and biological behavior.
Dis Model Mech. 2016 Dec 1;9(12):1435-1444. doi: 10.1242/dmm.026849. Epub 2016 Nov 3.
8
miRNA-449a is downregulated in osteosarcoma and promotes cell apoptosis by targeting BCL2.
Tumour Biol. 2015 Sep;36(10):8221-9. doi: 10.1007/s13277-015-3568-y. Epub 2015 May 23.
10
Comprehensive analysis of prognostic tumor microenvironment-related genes in osteosarcoma patients.
BMC Cancer. 2020 Aug 27;20(1):814. doi: 10.1186/s12885-020-07216-2.

引用本文的文献

1
Barking up the right tree: Immune checkpoint signatures of human and dog cancers.
PLoS Comput Biol. 2025 Aug 11;21(8):e1013270. doi: 10.1371/journal.pcbi.1013270. eCollection 2025 Aug.
2
Risk score model with two immune infiltration-related long non-coding RNAs to predict prognosis in patients with osteosarcoma.
Oncol Lett. 2025 Jul 15;30(3):443. doi: 10.3892/ol.2025.15189. eCollection 2025 Sep.
3
Consistently processed RNA sequencing data from 50 sources enriched for pediatric data.
Sci Data. 2025 Jul 2;12(1):1134. doi: 10.1038/s41597-025-05376-z.
6
Techniques for Validating CRISPR Changes Using RNA-Sequencing Data.
Genes (Basel). 2025 Mar 24;16(4):369. doi: 10.3390/genes16040369.
10
Bayesian unsupervised clustering identifies clinically relevant osteosarcoma subtypes.
Brief Bioinform. 2024 Nov 22;26(1). doi: 10.1093/bib/bbae665.

本文引用的文献

1
Understanding the Osteosarcoma Pathobiology: A Comparative Oncology Approach.
Vet Sci. 2016 Jan 18;3(1):3. doi: 10.3390/vetsci3010003.
2
RNA sequencing validation of the Complexity INdex in SARComas prognostic signature.
Eur J Cancer. 2016 Apr;57:104-11. doi: 10.1016/j.ejca.2015.12.027. Epub 2016 Feb 23.
4
Integrated analysis of gene expression and genomic aberration data in osteosarcoma (OS).
Cancer Gene Ther. 2015 Nov;22(11):524-9. doi: 10.1038/cgt.2015.48. Epub 2015 Oct 2.
5
Aberrant Retinoblastoma (RB)-E2F Transcriptional Regulation Defines Molecular Phenotypes of Osteosarcoma.
J Biol Chem. 2015 Nov 20;290(47):28070-28083. doi: 10.1074/jbc.M115.679696. Epub 2015 Sep 16.
7
Robust enumeration of cell subsets from tissue expression profiles.
Nat Methods. 2015 May;12(5):453-7. doi: 10.1038/nmeth.3337. Epub 2015 Mar 30.
8
Complementary genomic approaches highlight the PI3K/mTOR pathway as a common vulnerability in osteosarcoma.
Proc Natl Acad Sci U S A. 2014 Dec 23;111(51):E5564-73. doi: 10.1073/pnas.1419260111. Epub 2014 Dec 15.
10
OptiType: precision HLA typing from next-generation sequencing data.
Bioinformatics. 2014 Dec 1;30(23):3310-6. doi: 10.1093/bioinformatics/btu548. Epub 2014 Aug 20.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验