A Multi-disciplinary Approach to Investigating Canine Diffuse Large B cell Lymphoma

研究犬弥漫性大 B 细胞淋巴瘤的多学科方法

• 批准号: 2726000
• 金额: --
• 依托单位: Royal Veterinary College
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2726000
• 关键词: Multi; disciplinary; Approach; Investigating; Canine

RATIONALE: In humans, DLBCL has been shown to demonstrate genetic heterogeneity and miRNA profiles predicting disease prognosis. In dogs there are limited studies and relatively little genetic characterisation of lymphoma, meaning that it is difficult to find correlation with the human disease. Nevertheless, in both humans and dogs, there is a significant subset of lymphomas that are refractory to treatment. OVERALL AIM: We propose to better define genetic subtypes of canine lymphoma and characterising response to treatment of the different subtypes through a combination of more accurate phenotyping of lymphomas by integrating a) advanced image analysis b) genome sequencing, and c) total RNA sequencing (including micro-RNA sequencing).HYPOTHESIS: Canine lymphoma can be more accurately diagnosed, treated and prognosticated through a synergistic molecular, genetics, and image based analysis.SPECIFIC PROJECT OBJECTIVESOBJECTIVE 1: Define morphometric characteristics of canine lymphoma through image analysis of digital whole slide images (WSIs) via machine learning and artificial intelligence methodsOBJECTIVE 2: Identify genetic markers for DLBCL susceptibility through genome wide association studies and CNV analysesOBJECTIVE 3: Define mRNA and miRNA expression profiles in canine DLBCL through mRNAseq and small RNA-seq, and investigate if tumour-associated miRNA can be detected in peripheral blood serumOBJECTIVE 4: Genetic and morphological signatures from 1-3 will be compared between cases that show good response to chemotherapy and those that are refractory to treatment.

理由：在人类中，DLBCL 已被证明具有遗传异质性，并且 miRNA 谱可预测疾病预后。在狗身上，淋巴瘤的研究有限，遗传特征也相对较少，这意味着很难找到与人类疾病的相关性。然而，在人类和狗中，有很大一部分淋巴瘤是难以治疗的。总体目标：我们建议通过整合 a) 高级图像分析 b) 基因组测序和 c) 全 RNA 测序（包括 micro-RNA 测序），结合更准确的淋巴瘤表型分析，更好地定义犬淋巴瘤的遗传亚型并描述不同亚型治疗的反应。假设：通过以下方式可以更准确地诊断、治疗和预测犬淋巴瘤： 具体项目目标 目标 1：通过机器学习和人工智能方法对数字全玻片图像 (WSI) 进行图像分析，定义犬淋巴瘤的形态特征 目标 2：通过全基因组关联研究和 CNV 分析，识别 DLBCL 易感性的遗传标记 目标 3：定义犬的 mRNA 和 miRNA 表达谱 通过 mRNAseq 和小 RNA-seq 检测 DLBCL，并研究是否可以在外周血清中检测到肿瘤相关 miRNA 目标 4：将比较对化疗显示良好反应的病例和治疗难治性病例之间的遗传和形态学特征 1-3。