研究目的

口腔潜在恶性病变和口腔鳞癌包括了从上皮单纯增生、轻中重度异常增生再到癌变恶性转化的一系列分子事件。目前在精准评估口腔黏膜上皮癌变风险方面值得深入研究。m6ARNA甲基化是真核生物编码mRNA和非编码ncRNA最普遍的修饰方式。通过影响mRNA命运，调节m6ARNA甲基化基因表达，参与调控全身多种恶性肿瘤发生与发展。然而，其在口腔上皮异常增生和鳞癌中的作用及其机制尚不清楚。同时，除了分子病理诊断之外，基于机器学习的计算机辅助诊断手段有助于口腔潜在恶性病变和口腔鳞癌诊断的标准化和自动化，最终有益于疾病的精准诊疗和预后评估。因此，本研究一方面从表观遗传学角度预测口腔潜在恶性病变的癌变风险；另一方面开发一种高效率的Ki-67细胞增殖指数的机器学习模型，作为计算机辅助病理诊断一个组成部分。

研究方法

第一部分 口腔黏膜上皮异常增生和鳞癌中m6A甲基化相关分子筛选及其表达

通过挖掘数据库信息，检索常见的23个m6A甲基化调节因子在头颈部鳞癌中的表达及其与预后的关系，结合临床队列样本(包括276例上皮单纯增生、轻中重度异常增生和口腔鳞癌)，通过免疫组化探究其在口腔鳞癌和口腔上皮异常增生中的表达，通过采用非参数检验Mann-Whitney检验、采用χ2检验和Spearman相关系数进行统计分析。

第二部分 口腔黏膜上皮异常增生和鳞癌中m6A甲基化修饰谱和表达谱分析

借助激光显微切割富集上皮异常增生和口腔鳞癌样本的上皮区域，通过MeRIP-Seq和RNA-Seq检测，建立m6A甲基化的修饰谱和表达谱，筛选差异修饰和差异表达mRNA，并进行GO和KEGG功能分析。

第三部分 无监督定量细胞增殖指数模型的初步建立

选择口腔鳞癌Ki-67免疫组化染色数字切片。采用基于局部统计的可变阈值方法去除无关浅色背景区域，保留胞核部分。在L^* a^* b^*颜色空间中采用阈值方法对蓝色的苏木素染色和棕色Ki-67染色进行分离。计算增殖指数并通过配对t检验和Spearman相关系数将本研究提出模型与人工计数和机器学习中常用的颜色反卷积方法进行比较分析。

 

 

研究结果

1. 本研究通过公共数据库进行生信分析，检索常见的23个m6A甲基化调节因子在头颈部鳞癌中的表达，发现IGF2BP2和IGF2BP3在头颈部鳞癌中的表达显著升高（P<0.01），FTO、HNRNPC、HNRNPA2B1、LRPPRC、IGF2BP1、IGF2BP2、IGF2BP3高表达患者预后较差，IGF2BP2在头颈部鳞癌中存在较高突变率，其表达与肿瘤纯度呈显著正相关，与B细胞、CD8+T细胞的浸润水平显著负相关；IGF2BP3的表达与肿瘤纯度和CD4+T细胞呈显著正相关。

2.利用免疫组化方法，发现IGF2BP2和IGF2BP3蛋白在口腔鳞癌中均高表达，且在口腔上皮单纯增生、上皮异常增生和口腔鳞癌中表达递增，与病理学分级存在相关性，是口腔上皮异常增生和鳞癌的潜在生物学预后指标。

3.MeRIP-Seq结果显示，在口腔鳞癌、中重度异常增生、轻度异常增中均存在差异甲基化位点，其中有4个高甲基化基因，11个低甲基化基因在三组中共同存在。RNA-Seq结果显示，在口腔鳞癌、中重度异常增生、轻度异常增中均存在差异表达mRNA，在三组比较分析发现存在共同表达上调基因107个，下调基因37个。

4.结合患者临床病理资料及病史，发现C4B、DNAH9、NCALD在稳定组与进展组比较和稳定组与正常组比较中均存在高甲基化和表达上调；结合公共数据库分析，C4B、DNAH9、NCALD高表达患者总生存率高于低表达患者，提示在口腔鳞癌患者和上皮异常增生患者中，C4B、DNAH9、NCALD高表达患者预后较好。

5. 建立了一种新的胞核检测和分类模型，可以处理不同大小的病理图像，并有效地检测出免疫组化棕色阳性细胞和阴性细胞。此算法结果与人工计数结果无显著差异（P>0.05），但计算速度较快，在处理较大尺寸图像时计算效率优势更加明显，并且检测结果优于常用的颜色反卷积方法（P<0.05）。

研究结论

1. m6A甲基化调节因子在头颈部肿瘤进展中起着重要作用，IGF2BP2和 IGF2BP3有望成为口腔鳞癌免疫治疗的靶标和标志物。

2. m6A甲基化普遍存在于口腔上皮异常增生和鳞癌病变中，与正常黏膜上皮相比甲基化程度增高，且高甲基化基因mRNA表达多上调。口腔鳞癌和正常上皮相比存在发生差异甲基化和差异表达基因。上皮轻度异常增生、中重度异常增生和口腔鳞癌之间存在相同的差异表达基因，但其表达改变和m6A甲基化未发现直接相关性。

3. 本研究开发出的胞核自动定量分析模型，可以高效率地分析口腔鳞癌中胞核Ki-67染色情况，并计算相应的增殖指数，从而用于病理的辅助诊断。此方法可扩展至泛癌种胞核阳性免疫组化指标的定量计算。

Objectives

Oral potentially malignant disorders and oral squamous cell carcinoma include a series of molecular events including simple, mild, moderate, severe epithelial hyperplasia and malignant transformation of cancer. At present, it is worthy of further research to accurately assess the risk of oral mucosal epithelial carcinogenesis. m6A RNA methylation is the most common modification of both coding mRNA and non-coding ncRNA in eukaryotes. By influencing the fate of mRNA and regulating the expression of m6ARNA methylation gene, it participates in the regulation of the occurrence and development of various malignant tumors in the human. However, its role and mechanism in oral epithelial dysplasia and oral squamous cell carcinoma remain unclear. In addition to molecular pathological diagnosis, the computer-assisted diagnosis technology based on machine learning is conducive to standardize and automate the diagnosis of oral potentially malignant disorders and oral squamous cell carcinoma, and ultimately benefit the accurate diagnosis and treatment of diseases and prognosis evaluation.

Therefore, in this study, on the one hand, we predicted the cancer risk of oral potentially malignant disorders from the epigenetics. On the other hand, an efficient machine learning model of Ki-67 cell proliferation index was developed as a component of computer-assisted pathological diagnosis.

Methods

Part I Screening and expression of m6A methylation related molecules in oral epithelial dysplasia and oral squamous cell carcinoma

By mining database information, we retrieved the common 23 m6A methylation regulating factor in head and neck squamous cell carcinomas, and analyzed their relationship with prognosis. Combined with clinical cohort samples, 276 cases with simple, mild, moderate epithelial hyperplasia and oral squamous cell carcinomas were collected.

Part II m6A methylation and expression in oral epithelial dysplasia and oral squamous cell carcinoma

The epithelial regions of 20 cases of epithelial dysplasia or oral squamous cell carcinoma samples were enriched by laser capture microdissection technology, and the modification and expression profiles of m6A methylation were established by MeRIP-Seq and RNA-Seq detection. Then, the differential modification and expression mrnas were screened, and the GO and KEGG functions were analyzed.

Part III Preliminary establishment of unsupervised quantitative cell proliferation index model

Oral squamous cell carcinoma tissue samples were selected for Ki-67 immunohistochemical staining, and digital sections were made. A variable threshold method based on local statistics was used to remove the irrelevant light-colored background regions and retain the nucleus part. A threshold method was used to separate blue hematoxylin staining from brown Ki-67 staining in L^* a ^* b ^* color space. And the results of this model were compared and analyzed with the manual counting and the color deconvolution method commonly used in machine learning.

Results

1. In this study, a public database was used for bioinformatics analysis to search for the expression of 23 common m6A methylation regulators in head and neck squamous cell carcinoma, and the expression of IGF2BP2 and IGF2BP3 in head and neck squamous cell carcinoma was significantly increased (P <0.01). Patients with high expression of FTO、HNRNPC、HNRNPA2B1、LRPPRC、IGF2BP1、IGF2BP2、IGF2BP3 had a poor prognosis. IGF2BP2 had a relatively high mutation rate in head and neck squamous cell carcinoma, and its expression was significantly positively correlated with tumor purity, and significantly negatively correlated with the infiltration level of B cells and CD8+T cells. The expression of IGF2BP3 was significantly positively correlated with tumor purity and CD4+T cells.

2. The expressions of IGF2BP2 and IGF2BP3 in oral squamous cell carcinoma and oral epithelial dysplasia were detected by immunohistochemistry. These results indicated that both IGF2BP2 and IGF2BP3 were highly expressed in oral squamous cell carcinoma, and gradually increased in oral simple epithelial hyperplasia, epithelial dysplasia and oral squamous cell carcinoma, which were correlated with pathological grade. IGF2BP2 and IGF2BP3 were the potential biological prognostic indicators of oral epithelial dysplasia and oral squamous cell carcinoma.

3. MeRIP-Seq results showed that there were differential methylation sites in oral squamous cell carcinoma, moderate and severe epithelial dysplasia and mild epithelial dysplasia, among which 4 hypermethylated genes and 11 hypomethylated genes co-existed in the three groups. RNA-seq results indicated that there were differentially expressed mRNA, and 107 up-regulated genes and 37 down-regulated genes were found to be co-expressed in the three groups.

4. Based on the clinicopathological data and medical history of the patients, the patients were grouped according to the history of oral mucosal epithelial disorders. It was found that the hypermethylation and up-regulated expression of C4B, DNAH9 and NCALD were between the stable group and the progressive group, and between the stable group and the normal group. Based on the public database analysis, the overall survival rate of patients with high expression of C4B, DNAH9, and NCALD was higher than that of patients with low expression of them, which suggesting that patients with high expression of C4B, DNAH9, and NCALD had a better prognosis in patients with oral squamous cell carcinoma and oral epithelial dysplasia.

5. A new model for nucleus detection and classification was established, which can process pathological images of different sizes and effectively detect detect brown positive and negative cells by immunohistochemistry. There was no significant difference between the results of this algorithm and the manual counting results (P>0.05), but the calculation speed was faster, and the computational efficiency advantage was more obvious when processing larger images. In addition, the detection results were better than the commonly used color deconvolution methods (P<0.05).

Conclusions

1. m6A methylation regulators play an important role in the progression of head and neck tumors, and IGF2BP2 and IGF2BP3 are expected to be targets and markers for immunotherapy of oral squamous cell carcinoma.

2. m6A methylation is commonly found in oral epithelial dysplasia and oral squamous cell carcinoma. Compared with normal oral mucosal epithelium, the degree of methylation is increased, and the mRNA with hypermethylated genes is mostly up-regulated. Moreover, differentially methylated and differentially expressed genes were found in oral squamous cell carcinoma compared with normal oral mucosal epithelium. There were co-expressed genes between mild, moderate and severe epithelial dysplasia and oral squamous cell carcinoma, but the expression changes were not directly related to m6A methylation.

3. The nuclear automatic quantitative analysis model developed in this study can efficiently analyze the Ki-67 staining f nuclei in oral squamous cell carcinoma and calculate the corresponding proliferation index, so as to be used for the auxiliary diagnosis of pathology. This method can be extended to the automatic quantitative calculation of nuclear positive immunohistochemical index of the pan-carcinomatous species.

第一章 文献综述 1
第二章 引言 9
第三章 口腔上皮异常增生和鳞癌中m6A甲基化相关分子筛选及其表达 11
3.1 材料和方法 11
3.1.1 样本、试剂、仪器和耗材 11
3.1.2 实验方法 11
3.2 实验结果 14
3.2.1 生信分析 14
3.2.3 免疫组化结果 21
3.3 讨论 28
第四章 口腔黏膜上皮异常增生和鳞癌中m6A甲基化修饰谱和表达谱分析 32
4.1 材料和方法 32
4.1.1 样本、试剂、仪器和耗材 32
4.1.2 实验方法 33
4.2 实验结果 35
4.2.1 病例基本情况 35
4.2.2 MeRIP-Seq和RNA-Seq测序序列统计与质控 36
4.2.3 上皮异常增生和口腔鳞癌m6A修饰谱和表达谱建立 37
4.2.4 稳定组、进展组患者m6A修饰谱和表达谱建立 49
4.3 讨论 51
第五章 无监督定量细胞增殖指数模型的初步建立 54
5.1 材料和方法 54
5.1.1 样本、试剂、仪器和耗材 54
5.1.2 实验方法 55
5.2 实验结果 58
5.2.1 图像处理分析结果 59
5.2.2 不同尺寸病理图像分析结果 60
5.2.3不同算法结果 60
5.3讨论 63
第六章 结论及展望 65
参考文献 67
致谢 77
北京大学学位论文原创性声明和使用授权说明 78
学位论文答辩委员会名单 79
答辩委员会决议书 80
个人简历、在学期间发表的学术论文与研究成果 81

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