【摘要】：目的:研究胃癌患者血清中小分子代謝產(chǎn)物與淋巴結(jié)轉(zhuǎn)移狀態(tài)的相關(guān)性;初步研究小分子代謝產(chǎn)物預測胃癌淋巴結(jié)轉(zhuǎn)移狀態(tài)的相關(guān)機制;嘗試利用小分子代謝產(chǎn)物與臨床病理資料建立預測胃癌淋巴結(jié)轉(zhuǎn)移的風險評分模型。方法:1、LC-MS分析:應(yīng)用液相色譜-質(zhì)譜儀分析血清樣本代謝產(chǎn)物譜;2、應(yīng)用酶聯(lián)免疫法測定各組血清樣本中VEGF-C、VEGF-D含量;3、應(yīng)用免疫組織化學染色技術(shù)檢測各組癌組織樣本中VEGF-C、VEGF-D的表達、癌旁組織淋巴管密度(LVD);4、數(shù)據(jù)分析:運用主成分分析、t檢驗、支持向量機判別分析等統(tǒng)計學方法進行數(shù)據(jù)分析,尋找T1-2N1-3組與T3N0組胃癌患者血清中的差異性代謝產(chǎn)物;并以差異性代謝產(chǎn)物為分組依據(jù)對獨立樣本進行分組;而后運用t-檢驗、卡方檢驗比較獨立樣本分組后的組間VEGF-C、D水平和癌旁組織淋巴管密度;單因素、多因素邏輯回歸選出與淋巴結(jié)轉(zhuǎn)移相關(guān)的獨立危險因素;進一步結(jié)合臨床病理資料和代謝產(chǎn)物建立預測胃癌淋巴結(jié)轉(zhuǎn)移的風險評分模型。結(jié)果:1.第一部分:血清樣本的代謝組研究中,從Peakview軟件得出的血清總離子流圖中,可明顯觀察出組間代謝產(chǎn)物的差異。PCA得分圖結(jié)果提示組T1-2N1-3組與T3N0胃癌之間能很好區(qū)分開,t檢驗可篩選出T1-2N1-3組與T3N0組之間差異的代謝產(chǎn)物共31種,進一步運用支持向量機方法進行判別分析,選出權(quán)重值為100%的代謝產(chǎn)物3種。聚類分析的熱圖結(jié)果表明這3種差異性代謝產(chǎn)物能將t1-2n1-3組與t3n0區(qū)分開。2.第二部分:以3種差異性代謝產(chǎn)物為依據(jù)對另一35例獨立樣本進行聚類分析,再次驗證其對t1-2n1-3組與t3n0組血清的區(qū)分結(jié)果。結(jié)果表明獨立樣本仍能區(qū)分為a組和b組。a、b兩組間血清樣本的vegf-c、vegf-d濃度,差異有統(tǒng)計學意義(p值分別為0.032、0.047);癌組織中vegf-c、vegf-d表達,a組顯著高于b組(p值分別為0.046、0.025);癌旁組織淋巴管密度測定a組顯著高于b組(p=0.007);生存分析亦存在顯著差異。3.第三部分:對年齡、性別、分化程度、腫瘤大小、3種差異性代謝物等資料進行邏輯回歸,結(jié)果表明:年齡、phenylpyruvicacid、threoninyl-isoleucine為胃癌淋巴結(jié)轉(zhuǎn)移的獨立危險因素,結(jié)合性別和2種代謝產(chǎn)物建立預測胃癌淋巴結(jié)轉(zhuǎn)移的風險評分模型,該模型能夠?qū)⒘馨徒Y(jié)轉(zhuǎn)移陰性與陽性樣本區(qū)分開,隨著評分的增加,淋巴結(jié)轉(zhuǎn)移陽性病例占組內(nèi)病例的百分比也增高,此模型作為診斷性實驗的roc曲線圖顯示相比于單個獨立危險因素,其能夠更好的預測淋巴結(jié)轉(zhuǎn)移。結(jié)論:1.不同淋巴就轉(zhuǎn)移狀態(tài)的胃癌患者血清中,代謝產(chǎn)物存在差異;2.通過液相色譜-質(zhì)譜技術(shù)篩選出的差異性代謝物對不同淋巴結(jié)轉(zhuǎn)移狀態(tài)的胃癌患者有較強的區(qū)分能力;代謝產(chǎn)物與淋巴結(jié)轉(zhuǎn)移之間有一定的相關(guān)性;3.基于差異性代謝產(chǎn)物對另一35例獨立樣本行聚類分析后,仍能有效分組,組間血清VEGF-C、D濃度水平、癌組織VEGF-C、D表達、癌旁組織淋巴管密度均存在差異,差異有統(tǒng)計學意義;4.代謝產(chǎn)物是可能是通過促進癌組織高表達VEGF-C、D,促進癌旁組織新生淋巴管形成,進而促進淋巴結(jié)轉(zhuǎn)移;也可能是VEGF-C、D的高表達,造成了血清中代謝產(chǎn)物的差異;5.邏輯回歸結(jié)果確定了年齡、Phenylpyruvic acid、Threoninyl-Isoleucine為胃癌淋巴結(jié)轉(zhuǎn)移的3個獨立危險因素,以該3個危險因素建立的預測胃癌淋巴結(jié)轉(zhuǎn)移的風險評分模型可能成為臨床預測淋巴結(jié)轉(zhuǎn)移的有效手段。
[Abstract]:Objective: To study the correlation between small molecular metabolites and lymph node metastases in patients with gastric cancer, and to study the mechanism of small molecular metabolites to predict lymph node metastasis in gastric cancer, and to establish a risk scoring model for predicting the metastasis of gastric cancer by using small molecule metabolites and clinicopathological data. Method: 1, LC-MS Analysis: using liquid chromatography mass spectrometry to analyze the metabolites of serum samples; 2, VEGF-C, VEGF-D content in serum samples were measured by ELISA; 3, the expression of VEGF-C, VEGF-D, and lymphatic density (LVD) in the para cancer tissue samples were detected by immunohistochemistry. 4, data analysis: using principal component analysis T test, support vector machine discriminant analysis and other statistical methods for data analysis to find the differential metabolites in the serum of patients with gastric cancer in group T1-2N1-3 and T3N0, and group the independent samples on the basis of the differential metabolites, and then using the t- test to compare the VEGF-C and D levels of the group after the independent sample grouping. And the lymph node density in the paracancerous tissue; single factor, multiple factor logic regression to select independent risk factors associated with lymph node metastasis; further combined with clinicopathological data and metabolites to establish a risk scoring model for predicting lymph node metastasis of gastric cancer. Results: 1. Part 1: in the metabolic group study of serum samples, from Peakview software In the serum total ion flow chart, the difference of.PCA score between groups was clearly observed. The results of.PCA score showed that the group T1-2N1-3 group was well separated from the T3N0 gastric cancer. The t test could screen out a total of 31 different metabolites between the T1-2N1-3 group and the T3N0 group, and the discriminant analysis was carried out by the support vector machine method. The weight value was selected to be 100. 3 kinds of metabolites were found. The results of cluster analysis showed that the 3 different metabolites could separate the t1-2n1-3 group and the T3N0 region from the second part of.2.: 3 different metabolites were used to cluster analysis of the other 35 independent samples, and the results of the difference between the t1-2n1-3 group and the T3N0 group were verified again. The results showed that the independent sample was independent. The VEGF-C and VEGF-D concentration of serum samples between group A and group B, B two were statistically significant (P value was 0.032,0.047), VEGF-C, VEGF-D expression, a group were significantly higher than that of B group, and lymphatic density in paracancerous tissue was significantly higher than that in group two; survival analysis was also significantly worse. The third part of.3.: age, sex, degree of differentiation, tumor size, and 3 different metabolites. The results show that age, phenylpyruvicacid, threoninyl-isoleucine are independent risk factors for lymph node metastasis of gastric cancer, and the risk scoring model for predicting lymph node metastasis of gastric cancer combined with sex and 2 kinds of metabolites is established. The model can separate the negative lymph node metastasis from the positive sample area. As the score increases, the percentage of lymph node metastasis positive cases also increases. As a diagnostic test, the model shows that compared with a single independent risk factor, the model can predict lymph node metastasis better than a single independent risk factor. Conclusion: 1. different types of lymph node metastasis can be predicted. Conclusion: 1. different lymphatic vessels can be used to predict lymph node metastasis. The metabolic products were different in the serum of patients with gastric cancer with metastatic state; 2. the differential metabolites screened by liquid chromatography mass spectrometry had a strong distinguishing ability for gastric cancer patients with different lymph node metastases; there was a certain correlation between the metabolites and lymph node metastasis; and 3. based on the difference of metabolic products to the other 35. After cluster analysis, the serum VEGF-C, D concentration level, VEGF-C, D expression and lymphatic density in the para cancerous tissue were different, and the difference was statistically significant. 4. the metabolites could promote the high expression of VEGF-C, D, promote the formation of lymphatic tube in the paracancerous tissues, and then promote the drenching. The high expression of VEGF-C and D resulted in the difference in the metabolites in the serum; 5. the logical regression results confirmed the age, Phenylpyruvic acid, Threoninyl-Isoleucine as 3 independent risk factors for lymph node metastasis of gastric cancer, and the risk score model for predicting lymph node metastasis of gastric cancer by the 3 risk factors It is an effective means to predict lymph node metastasis in clinical practice.
【學位授予單位】：吉林大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：R735.2

【相似文獻】

相關(guān)期刊論文 前10條

1 胡佳;王莉;;腎血管平滑肌脂肪瘤伴周圍淋巴結(jié)轉(zhuǎn)移1例[J];華西醫(yī)學;2006年01期

2 張德賢;孫菊杰;蔡淑萍;;腎血管平滑肌脂肪瘤伴多處淋巴結(jié)轉(zhuǎn)移1例報告[J];山東醫(yī)藥;2009年42期

3 夏作云;;試析乳腺浸潤性微乳頭狀癌的病理學特征與淋巴結(jié)轉(zhuǎn)移的關(guān)系[J];中外醫(yī)學研究;2013年18期

4 楊成;新生血管和腫瘤的淋巴結(jié)轉(zhuǎn)移[J];國外醫(yī)學.口腔醫(yī)學分冊;1997年06期

5 付興國,楊華,陳桂秋;男性乳腺浸潤性導管癌伴淋巴結(jié)轉(zhuǎn)移1例[J];中國實驗診斷學;2000年06期

6 周志明,趙錚錚,劉永欣,王澤學;128例肺癌患者手術(shù)切除淋巴結(jié)轉(zhuǎn)移分析[J];中國肺癌雜志;2001年02期

7 江珊;宋琳琳;張曉曉;詹維偉;;超聲彈性成像技術(shù)預測甲狀腺微小乳頭狀癌中央組淋巴結(jié)轉(zhuǎn)移的價值[J];中華醫(yī)學超聲雜志(電子版);2014年05期

8 張真發(fā),李軍,尚文軍,張林;臨床Ⅰ期非小細胞肺癌淋巴結(jié)轉(zhuǎn)移的影響因素及臨床意義[J];中國肺癌雜志;2003年04期

9 郭曉靜;陳凌;郎榮剛;范宇;付麗;;乳腺浸潤性微乳頭狀癌的病理學特征與淋巴結(jié)轉(zhuǎn)移的關(guān)系[J];中華病理學雜志;2006年01期

10 吳楠;劉亞慶;王緒凱;盧利;;舌癌術(shù)后多次復發(fā)與淋巴結(jié)轉(zhuǎn)移1例[J];中國實用口腔科雜志;2011年12期

相關(guān)會議論文 前10條

1 劉一飛;田大宇;;影響進展期胃癌No.14淋巴結(jié)轉(zhuǎn)移因素的分析[A];第9屆全國胃癌學術(shù)會議暨第二屆陽光長城腫瘤學術(shù)會議論文匯編[C];2014年

2 張玉晶;Oh JL;Whitman G;Iyengar P;Yu TK;Tereffe W;Woodward W;Perkins G;Buchholz TA;Strom EA.;;局部進展期乳腺癌臨床顯見的內(nèi)乳淋巴結(jié)轉(zhuǎn)移:發(fā)生率和局部控制[A];中華醫(yī)學會放射腫瘤治療學分會六屆二次暨中國抗癌協(xié)會腫瘤放療專業(yè)委員會二屆二次學術(shù)會議論文集[C];2009年

3 付玉蘭;黃惠玲;韓軍;;宮頸癌術(shù)后淋巴結(jié)轉(zhuǎn)移相關(guān)因素分析[A];中國抗癌協(xié)會婦科腫瘤專業(yè)委員會第七次全國學術(shù)會議論文匯編[C];2003年

4 李端樹;張凌;渠寧;嵇慶海;;中央?yún)^(qū)淋巴結(jié)轉(zhuǎn)移比例及陽性數(shù)目對于側(cè)頸淋巴結(jié)轉(zhuǎn)移預測作用的研究[A];2014第六屆全國甲狀腺腫瘤學術(shù)大會論文集[C];2014年

5 張遜;David I Watson;Justin R Bessell;;食管腺癌淋巴結(jié)轉(zhuǎn)移與腫瘤侵及食管壁深度的關(guān)系和對生存率的影響[A];第四屆中國腫瘤學術(shù)大會暨第五屆海峽兩岸腫瘤學術(shù)會議論文集[C];2006年

6 葉建華;葉再元;屠世良;;直腸癌淋巴結(jié)轉(zhuǎn)移的相關(guān)因素分析[A];浙江省中西醫(yī)結(jié)合學會第二屆老年病專業(yè)委員會第一次年會學術(shù)論文集[C];2007年

7 石峰;秦昂;;~(125)I粒子治療惡性淋巴結(jié)轉(zhuǎn)移瘤臨床觀察[A];中華醫(yī)學會第九次全國核醫(yī)學學術(shù)會議論文摘要匯編[C];2011年

8 葉建華;葉再元;屠世良;;直腸癌淋巴結(jié)轉(zhuǎn)移的相關(guān)因素分析[A];2008年浙江省肛腸外科學術(shù)年會暨繼續(xù)教育培訓班資料匯編[C];2008年

9 李福根;許紹發(fā);劉志東;;淋巴結(jié)轉(zhuǎn)移與肺癌預后關(guān)系的研究[A];中華醫(yī)學會第六次全國胸心血管外科學術(shù)會議論文集（胸外科分冊）[C];2006年

10 任宇鵬;徐惠綿;;胃癌淋巴結(jié)轉(zhuǎn)移規(guī)律及其與生物學行為關(guān)系的研究[A];第四屆中國腫瘤學術(shù)大會暨第五屆海峽兩岸腫瘤學術(shù)會議論文集[C];2006年

相關(guān)重要報紙文章 前2條

1 健康時報特約記者 程守勤;3分鐘識別淋巴結(jié)轉(zhuǎn)移[N];健康時報;2007年

2 衣曉峰 李華虹;根治胃癌須把握淋巴結(jié)轉(zhuǎn)移規(guī)律[N];中國醫(yī)藥報;2005年

相關(guān)博士學位論文 前8條

1 韓嘯天;宮頸癌淋巴結(jié)轉(zhuǎn)移相關(guān)miRNA篩選及機制研究[D];復旦大學;2014年

2 周治國;基于計算智能和機器學習的胃癌淋巴結(jié)檢測及淋巴結(jié)轉(zhuǎn)移診斷方法研究[D];西安電子科技大學;2014年

3 丁文婧;子宮內(nèi)膜癌淋巴結(jié)轉(zhuǎn)移預測模型的初步建立[D];上海交通大學;2015年

4 戚曉通;食管鱗癌侵犯粘膜下層與淋巴結(jié)轉(zhuǎn)移規(guī)律研究[D];南京醫(yī)科大學;2016年

5 郭學光;CCL21/CCR7軸對肺腺癌A549細胞增殖、遷移、侵襲及淋巴結(jié)轉(zhuǎn)移的影響研究[D];第三軍醫(yī)大學;2007年

6 郭曉靜;乳腺浸潤性微乳頭狀癌病理學特征的相關(guān)研究[D];天津醫(yī)科大學;2007年

7 邵雁;甲狀腺乳頭狀癌淋巴結(jié)轉(zhuǎn)移的相關(guān)因素研究[D];浙江大學;2008年

8 李偉;胃癌淋巴結(jié)轉(zhuǎn)移信號傳導通路蛋白表達譜篩選和分析[D];吉林大學;2013年

相關(guān)碩士學位論文 前10條

1 徐剛;乳腺癌內(nèi)乳淋巴結(jié)轉(zhuǎn)移相關(guān)危險因素研究[D];蘇州大學;2015年

2 何建;拖出式適形切除在低位直腸癌中的應(yīng)用及相關(guān)因素分析[D];第二軍醫(yī)大學;2015年

3 高維鴿;術(shù)前外周血中性粒細胞與淋巴細胞比值測定與直腸癌預后的關(guān)系[D];新疆醫(yī)科大學;2015年

4 毛智軍;遠端胃癌淋巴結(jié)轉(zhuǎn)移規(guī)律的臨床研究[D];延安大學;2016年

5 張猛;CD44、HIF-1α在胃癌中的表達及臨床意義[D];廣西醫(yī)科大學;2016年

6 王福剛;進展期胃癌淋巴結(jié)轉(zhuǎn)移規(guī)律對放療靶區(qū)勾畫的指導[D];濟南大學;2016年

7 趙權(quán)權(quán);直腸癌新輔助放化療后淋巴結(jié)轉(zhuǎn)移的相關(guān)研究[D];第二軍醫(yī)大學;2016年

8 楊雄雯;下葉肺癌患者上葉12區(qū)淋巴結(jié)轉(zhuǎn)移規(guī)律及臨床分析[D];南昌大學;2016年

9 王鵬;524例肺癌患者淋巴結(jié)轉(zhuǎn)移影響因素及規(guī)律的研究[D];大連醫(yī)科大學;2016年

10 徐冬冬;血清小分子代謝產(chǎn)物與胃癌淋巴結(jié)轉(zhuǎn)移狀態(tài)的相關(guān)性研究[D];吉林大學;2017年

，

本文編號：2171875