CAJ | 학술논문

目的：通过前列腺癌（PCa）蛋白组学与基因组学文献，挖掘与 PCa 存在相关性并缺乏具体研究的差异基因，并分析其参与的生物过程与通路。方法计算机检索 PubMed 数据库，检索策略：“（prostate cancer[Title]） AND Proteomics”“（prostate cancer[Title]）AND Genomics”，时间限定为建库至2015年1月。按照 PCa 与前列腺增生（BPH）组织（A 组）、PCa 与邻近良性组织（B 组）、PCa 高 Gleason 评分与低 Gleason 评分（C 组）蛋白谱和基因谱的比较提取差异蛋白或基因，输入“ The Protein Information Resource （ PIR，Georgetown University Medical Center， Washington，DC 20007，USA）”，按照“ official gene symbol”统一名称。采用“ DAVID Bioinformatics Resources 6.7（National Institute of Allergy and Infectious Diseases，NIH，USA）”在线工具对差异基因进行 GO（ Gene Ontology）、KEGG 等生物信息学分析。结果共纳入35篇文献，提取差异基因764个，其中 A 组差异基因162个，B 组差异基因423个，C 组差异基因209个，3组共同差异基因21个。A 组差异基因中 DES 报道最多，为6次；B 组差异基因 ACPP报道最多，为4次；C 组差异基因 ACTN1、HSPB1、LMNA 报道最多，均为3次。GO 分析结果显示，差异基因涉及的生物过程主要有细胞死亡调控、细胞增殖调控、创伤反应、蛋白质转运、稳态过程（差异基因频数≥72，频率≥9.4％），细胞成分主要涉及胞外区、膜封闭腔、细胞骨架、囊泡以及线粒体（差异基因频数≥85，频率≥11.1％），分子功能主要涉及核苷酸结合、钙离子结合、相同蛋白结合以及酶结合（差异基因频数≥60，频率≥7.9％）。KEGG通路分析发现，差异基因主要参与癌症通路、黏着斑、肌动蛋白细胞骨架调控、MAPK 信号等生物学通路（差异基因频数≥29，频率≥3.8％）。对各组差异基因进行 KEGG 通路分析结果显示，各组差异基因共同参与的 KEGG 通路主要有黏着斑、补体及凝血级联、ECM 受体相互作用等生物学通路。结论差异基因 DES、ACTN1、ATP5B、TLN1、COL6A2、MYH9、OGN、PGAM1报道次数较多，而其参与 PCa 发生发展的具体机制未见报道，值得进一步实验验证。黏着斑、肌动蛋白细胞骨架的调控以及 MAPK 信号通路可能在 PCa 发生发展过程中发挥重要作用，对其进一步分析将为临床治疗 PCa 提供新的靶点。目的：通過前列腺癌（PCa）蛋白組學與基因組學文獻，挖掘與 PCa 存在相關性併缺乏具體研究的差異基因，併分析其參與的生物過程與通路。方法計算機檢索 PubMed 數據庫，檢索策略：“（prostate cancer[Title]） AND Proteomics”“（prostate cancer[Title]）AND Genomics”，時間限定為建庫至2015年1月。按照 PCa 與前列腺增生（BPH）組織（A 組）、PCa 與鄰近良性組織（B 組）、PCa 高 Gleason 評分與低 Gleason 評分（C 組）蛋白譜和基因譜的比較提取差異蛋白或基因，輸入“ The Protein Information Resource （ PIR，Georgetown University Medical Center， Washington，DC 20007，USA）”，按照“ official gene symbol”統一名稱。採用“ DAVID Bioinformatics Resources 6.7（National Institute of Allergy and Infectious Diseases，NIH，USA）”在線工具對差異基因進行 GO（ Gene Ontology）、KEGG 等生物信息學分析。結果共納入35篇文獻，提取差異基因764箇，其中 A 組差異基因162箇，B 組差異基因423箇，C 組差異基因209箇，3組共同差異基因21箇。A 組差異基因中 DES 報道最多，為6次；B 組差異基因 ACPP報道最多，為4次；C 組差異基因 ACTN1、HSPB1、LMNA 報道最多，均為3次。GO 分析結果顯示，差異基因涉及的生物過程主要有細胞死亡調控、細胞增殖調控、創傷反應、蛋白質轉運、穩態過程（差異基因頻數≥72，頻率≥9.4％），細胞成分主要涉及胞外區、膜封閉腔、細胞骨架、囊泡以及線粒體（差異基因頻數≥85，頻率≥11.1％），分子功能主要涉及覈苷痠結閤、鈣離子結閤、相同蛋白結閤以及酶結閤（差異基因頻數≥60，頻率≥7.9％）。KEGG通路分析髮現，差異基因主要參與癌癥通路、黏著斑、肌動蛋白細胞骨架調控、MAPK 信號等生物學通路（差異基因頻數≥29，頻率≥3.8％）。對各組差異基因進行 KEGG 通路分析結果顯示，各組差異基因共同參與的 KEGG 通路主要有黏著斑、補體及凝血級聯、ECM 受體相互作用等生物學通路。結論差異基因 DES、ACTN1、ATP5B、TLN1、COL6A2、MYH9、OGN、PGAM1報道次數較多，而其參與 PCa 髮生髮展的具體機製未見報道，值得進一步實驗驗證。黏著斑、肌動蛋白細胞骨架的調控以及 MAPK 信號通路可能在 PCa 髮生髮展過程中髮揮重要作用，對其進一步分析將為臨床治療 PCa 提供新的靶點。
목적：통과전렬선암（PCa）단백조학여기인조학문헌，알굴여 PCa 존재상관성병결핍구체연구적차이기인，병분석기삼여적생물과정여통로。방법계산궤검색 PubMed 수거고，검색책략：“（prostate cancer[Title]） AND Proteomics”“（prostate cancer[Title]）AND Genomics”，시간한정위건고지2015년1월。안조 PCa 여전렬선증생（BPH）조직（A 조）、PCa 여린근량성조직（B 조）、PCa 고 Gleason 평분여저 Gleason 평분（C 조）단백보화기인보적비교제취차이단백혹기인，수입“ The Protein Information Resource （ PIR，Georgetown University Medical Center， Washington，DC 20007，USA）”，안조“ official gene symbol”통일명칭。채용“ DAVID Bioinformatics Resources 6.7（National Institute of Allergy and Infectious Diseases，NIH，USA）”재선공구대차이기인진행 GO（ Gene Ontology）、KEGG 등생물신식학분석。결과공납입35편문헌，제취차이기인764개，기중 A 조차이기인162개，B 조차이기인423개，C 조차이기인209개，3조공동차이기인21개。A 조차이기인중 DES 보도최다，위6차；B 조차이기인 ACPP보도최다，위4차；C 조차이기인 ACTN1、HSPB1、LMNA 보도최다，균위3차。GO 분석결과현시，차이기인섭급적생물과정주요유세포사망조공、세포증식조공、창상반응、단백질전운、은태과정（차이기인빈수≥72，빈솔≥9.4％），세포성분주요섭급포외구、막봉폐강、세포골가、낭포이급선립체（차이기인빈수≥85，빈솔≥11.1％），분자공능주요섭급핵감산결합、개리자결합、상동단백결합이급매결합（차이기인빈수≥60，빈솔≥7.9％）。KEGG통로분석발현，차이기인주요삼여암증통로、점착반、기동단백세포골가조공、MAPK 신호등생물학통로（차이기인빈수≥29，빈솔≥3.8％）。대각조차이기인진행 KEGG 통로분석결과현시，각조차이기인공동삼여적 KEGG 통로주요유점착반、보체급응혈급련、ECM 수체상호작용등생물학통로。결론차이기인 DES、ACTN1、ATP5B、TLN1、COL6A2、MYH9、OGN、PGAM1보도차수교다，이기삼여 PCa 발생발전적구체궤제미견보도，치득진일보실험험증。점착반、기동단백세포골가적조공이급 MAPK 신호통로가능재 PCa 발생발전과정중발휘중요작용，대기진일보분석장위림상치료 PCa 제공신적파점。
Objective To mine differentially expressed genes which have strong correlation with prostate cancer (PCa)but have not been specifically covered through literatures about proteomics and genomics of PCa and analyze the biological processes and pathways in which these genes are involved. Methods With PubMed public database,we used the advanced search by inputting " (prostate cancer[Title])AND Proteomics" " (prostate cancer[Title])AND Genomics" for literatures before January 2015. We extracted differentially expressed proteins or genes according to the comparison of protein and gene expression profiles between PCa and benign prostatic hyperplasia(BPH)(Group A),between PCa and adjacent benign tissues (Group B)and between high and low Gleason scores of Pca( Group C). We input all the differentially expressed genes or proteins into " The Protein Information Resource( PIR,Georgetown University Medical Center,Washington,DC 20007, USA)" and unified all names according to " official gene symbol" . Then we conducted the bioinformatics analysis of Gene Ontology and KEGG pathway by DAVID Bioinformatics Resources 6. 7( National Institute of Allergy and Infectious Diseases, NIH,USA)online tool. Results A total of 35 articles were included. Through mining,we obtained 764 differentially expressed genes totally,of which 162 were in Group A,423 in Group B and 209 in Group C. In all the 3 groups,there were 21 common reported genes. DES was reported the most in Group A,which appeared 6 times. ACPP was reported the most in Group B,which appeared 4 times. ACTN1,HSPB1 and LMNA were reported the most in Group C,which all appeared 3 times. All these genes played important roles in biological processes of regulation of cell death,regulation of cell proliferation,response to wounding, protein transport and homeostatic process( genes count ≥ 72,percentage ≥ 9. 4% ),as well as in molecular function of nucleotide binding,calcium ion binding,identical protein binding and enzyme binding( genes count ≥ 60,percentage ≥7. 9% ). Their cellular components were mainly in extracellular region,membrane - enclosed lumen,cytoskeleton,vesicle and mitochondrion(genes count≥85,percentage≥11. 1% ). They were mainly involved in the biological pathways like pathways in cancer,focal adhesion,regulation of actin cytoskeleton and MAPK signaling(genes count≥29,percentage≥3. 8% ). The co- occurrence KEGG pathways from different groups were focal adhesion,complement and coagulation cascade and ECM -receptor interactions. Conclusion We found out there is strong association between DES,ACTN1,ATP5B,TLN1,COL6A2, MYH9,OGN,PGAM1 and PCa but without specific relevant reports,which means more experimental researches are needed to prove that. What's more,focal adhesion,regulation of actin cytoskeleton and MAPK signaling pathway may play important roles in the development of PCa. Further analysis will provide new targets for clinical prevention and treatment of PCa.