Molecular Signatures of Biologic Behavior in Pediatric Osteosarcoma

儿童骨肉瘤生物学行为的分子特征

• 批准号: 10588388
• 负责人: Kelly M Makielski
• 金额: $ 12.53万
• 依托单位: UNIVERSITY OF MINNESOTA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-01 至 2027-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10588388
• 关键词: Address; Adolescent and Young Adult; Affect; Award; Behavior; Binding; Bioinformatics; Biological; Biological Markers; Biology; Blood; Blood Tests; Bone neoplasms; Categories; Child; Childhood Osteosarcoma; Clinical; Clinical Trials; Data; Dedications; Development; Diagnosis; Diagnostic tests; Disease; Disease Progression; Disease remission; Funding; Future; Gene Cluster; Genes; Goals; Human; Immune response; Incidence; Knowledge; Leadership; Machine Learning; Malignant Neoplasms; Membrane; Mentors; Messenger RNA; Methods; Molecular Profiling; Morbidity - disease rate; Neoplasm Metastasis; Noise; Normal Cell; Operative Surgical Procedures; Outcome; Patients; Pattern; Pediatric cohort; Probability; Prognosis; Progression-Free Survivals; Research; Resources; Risk Marker; Sampling; Scientist; Second Primary Cancers; Sensitivity and Specificity; Serum; Severities; Survivors; Systemic Therapy; Testing; Time; Toxic effect; Treatment Failure; Tumor Biology; Work; Xenograft Model; Xenograft procedure; aggressive therapy; bioinformatics pipeline; biomarker discovery; biomarker identification; biomarker selection; biomarker signature; career; chemotherapy; clinically relevant; differential expression; exosome; experience; experimental study; genetic signature; improved; machine learning algorithm; microvesicles; minimally invasive; mouse model; multidisciplinary; negative affect; next generation sequencing; novel; osteosarcoma; patient stratification; patient subsets; predictive marker; predictive signature; predictive test; primary bone cancer; prognostic indicator; risk minimization; skills; standard of care; transcriptome sequencing; translational model; translational scientist; treatment response; treatment risk; tumor; tumor behavior; young adult

PROJECT SUMMARY/ABSTRACT Osteosarcoma, the most common primary tumor of bone, primarily affects children, adolescents, and young adults. A diagnosis of osteosarcoma is devastating, as approximately half of pediatric osteosarcoma patients experience metastasis and ultimately succumb to the disease within 10 years of their diagnosis. Currently there is no diagnostic test to predict prognosis, so all patients are treated with aggressive surgery and intense chemotherapy with high rates of toxicity. However, a subset of patients may not require as aggressive therapy to achieve remission. Additionally, those that survive have a high incidence of lifelong morbidities, including treatment-related secondary malignancies. Accurate prognostic indicators could be integrated into the standard of care for osteosarcoma to guide therapy. Children with more favorable prognoses could be treated more conservatively, reducing the need for aggressive surgery, and decreasing the intensity of systemic therapy. This would decrease the likelihood and severity of long-term morbidities, and reduce the probability of secondary, treatment-related malignancies without negatively affecting prognosis. Conversely, patients with a worse prognosis could receive more aggressive treatments or be guided to experimental clinical trials to improve their long-term survival. In this project, we will develop a serum exosomal gene signature associated with prognosis in pediatric osteosarcoma. Exosomes are membrane-bound microvesicles containing cargo associated with tumor biology and disease state. We will first identify biomarkers by sequencing serum exosomes from a large cohort of pediatric osteosarcoma patients with known clinical outcomes. We will then identify genes associated with metastatic propensity using xenograft mouse models established from pediatric osteosarcomas with distinct biologic behavior. We will analyze co-regulated gene clusters and apply machine learning, improving sensitivity and specificity, and ultimately resulting in a more robust gene signature. The osteosarcoma gene signature developed in this project can be utilized in the clinical setting to predict prognosis, stratifying patients into more appropriate treatment categories, and having the potential to improve management of this devastating disease. Additionally, these biomarkers will contribute to our understanding of the biological behavior and progression of osteosarcoma, allowing us to infer mechanisms of host response, metastasis, and response to therapy. Importantly, this K01 is critical to advancing my career as a translational scientist by providing the necessary protected time and dedicated resources to perform high-quality, clinically relevant research, under the guidance of an exceptional multidisciplinary mentor team. This award will facilitate my transition to independence, as the data procured in this project will allow me to be competitive for future independent funding applications. Additionally, as I complete these aims, I will develop the necessary knowledge and leadership skills of a successful independent research scientist specializing in exosome biology and translational models of pediatric osteosarcoma and ultimately expanding to other cancers.

项目摘要/摘要 骨肉瘤是最常见的原发骨肿瘤，主要影响儿童、青少年和青少年。 成年人。骨肉瘤的诊断是毁灭性的，因为大约一半的儿童骨肉瘤患者 经历转移，并最终在确诊后10年内死于这种疾病。目前 没有预测预后的诊断测试，因此所有患者都接受积极的手术和强化治疗。 化疗毒副作用大。然而，一部分患者可能不需要积极的治疗。 以达到缓解的目的。此外，那些幸存下来的人终身患病的发生率很高，包括 与治疗相关的继发性恶性肿瘤。准确的预后指标可以被纳入标准 对骨肉瘤的护理指导治疗。预后较好的儿童可以接受更多治疗 保守治疗，减少侵袭性手术的需要，降低系统治疗的强度。 这将降低长期患病的可能性和严重性，并降低 第二，与治疗相关的恶性肿瘤，不会对预后产生负面影响。相反，患有 预后较差的患者可能会接受更积极的治疗，或被引导进行实验性临床试验 提高他们的长期生存能力。在这个项目中，我们将开发一种与血清外切体基因标志相关的 对儿童骨肉瘤预后的影响。Exosome是含有货物的膜结合的微囊 与肿瘤生物学和疾病状态有关。我们将首先通过对血清进行测序来鉴定生物标记物 已知临床结果的一大群儿童骨肉瘤患者的外切体。到时候我们会的 利用从儿科动物建立的异种移植小鼠模型识别与转移倾向相关的基因 骨肉瘤具有明显的生物学行为。我们将分析共同调控的基因簇并应用机器 学习，提高敏感度和特异度，最终产生更健壮的基因签名。这个 该项目开发的骨肉瘤基因特征可用于临床环境预测 预后，将患者分成更合适的治疗类别，并有改善的潜力 对这种毁灭性疾病的管理。此外，这些生物标志物将有助于我们理解 骨肉瘤的生物学行为和进展，使我们能够推断宿主反应的机制， 转移和对治疗的反应。重要的是，这款K01对于提升我作为翻译的职业生涯至关重要 科学家通过提供必要的保护时间和专用资源来执行高质量的临床 相关研究，在杰出的多学科导师团队的指导下。这项裁决将有助于 我向独立的过渡，因为在这个项目中获得的数据将使我在未来具有竞争力 独立的资金申请。此外，随着我完成这些目标，我将制定必要的 擅长外显体生物学的成功独立研究科学家的知识和领导技能 和儿童骨肉瘤的翻译模型，并最终扩展到其他癌症。