Sinegugu Dubazana, Ekene Nweke, Sharol Ngwenya, Previn Naicker, Nnenna Elebo, Sindisiwe Buthelezi, Jones O. Omoshoro-Jones
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DNA and Total RNA were subsequently extracted from 28 tissues (14 paired tumours and normal tissues) and Whole exome and RNA sequencing were performed, respectively. Results: The Pixul+Sonication method yielded the highest number of identified proteins (20,804.5 peptides and 3,349.5 protein groups) followed by the Pixul-only method with 20,769,5 peptides and 3,300.5 protein groups). The difference between methods was insignificant; we chose the Pixul-only workflow for its high-throughput efficiency and minimal steps, reducing error probability. From the FFPE PDAC tissues, a total of 39 dysregulated proteins (17 downregulated and 22 upregulated) were identified. Key pathways such as extracellular matrix organization, platelet activation and fibrosis-related pathways were identified. Conclusion: Utilizing this optimized method, key proteins and pathways associated with PDAC progression were demonstrated. These findings underscore the potential of archived tissue-based proteomic analysis for biomarker discovery, providing critical insights into PDAC pathophysiology and novel therapeutic targets. The analyses of the sequencing data are ongoing. Citation Format: Sinegugu Dubazana, Ekene Nweke, Sharol Ngwenya, Previn Naicker, Nnenna Elebo, Sindisiwe Buthelezi, Jones O. Omoshoro-Jones. Multi-omic Analyses Of The Tumour Microenvironment Of South African Pancreatic Ductal Adenocarcinoma Patients [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research—Emerging Science Driving Transformative Solutions; Boston, MA; 2025 Sep 28-Oct 1; Boston, MA. 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This study conducted multi-omic analyses of archived FFPE tissues to identify potential biomarkers and elucidate molecular mechanisms of disease progression in our patient population. Methods: For the proteomics aspect, a comparison of sample preparation methods (Barocycler, Pixul+DTT, Pixul+Sonication and Pixul-only) was conducted for optimal protein extraction. Using the selected optimised method, 78 FFPE PDAC (22 paired tumour and normal, 34 unpaired tumour) tissues were processed to determine differentially expressed proteins. Limma was used for the differential expression analyses. DNA and Total RNA were subsequently extracted from 28 tissues (14 paired tumours and normal tissues) and Whole exome and RNA sequencing were performed, respectively. Results: The Pixul+Sonication method yielded the highest number of identified proteins (20,804.5 peptides and 3,349.5 protein groups) followed by the Pixul-only method with 20,769,5 peptides and 3,300.5 protein groups). The difference between methods was insignificant; we chose the Pixul-only workflow for its high-throughput efficiency and minimal steps, reducing error probability. From the FFPE PDAC tissues, a total of 39 dysregulated proteins (17 downregulated and 22 upregulated) were identified. Key pathways such as extracellular matrix organization, platelet activation and fibrosis-related pathways were identified. Conclusion: Utilizing this optimized method, key proteins and pathways associated with PDAC progression were demonstrated. These findings underscore the potential of archived tissue-based proteomic analysis for biomarker discovery, providing critical insights into PDAC pathophysiology and novel therapeutic targets. The analyses of the sequencing data are ongoing. Citation Format: Sinegugu Dubazana, Ekene Nweke, Sharol Ngwenya, Previn Naicker, Nnenna Elebo, Sindisiwe Buthelezi, Jones O. Omoshoro-Jones. Multi-omic Analyses Of The Tumour Microenvironment Of South African Pancreatic Ductal Adenocarcinoma Patients [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research—Emerging Science Driving Transformative Solutions; Boston, MA; 2025 Sep 28-Oct 1; Boston, MA. 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引用次数: 0
摘要
背景:胰腺导管腺癌(Pancreatic ductal adencarcinoma, PDAC)是全球最具侵袭性的恶性肿瘤之一,其5年生存率仅为13%。本研究对存档的FFPE组织进行了多组学分析,以确定潜在的生物标志物并阐明患者群体中疾病进展的分子机制。方法:在蛋白质组学方面,比较样品制备方法(Barocycler、Pixul+DTT、Pixul+Sonication和Pixul-only),优选蛋白质提取方法。使用选定的优化方法,对78个FFPE PDAC(22个配对肿瘤和正常,34个未配对肿瘤)组织进行处理,以确定差异表达蛋白。采用Limma进行差异表达分析。随后从28个组织(14对肿瘤和正常组织)中提取DNA和总RNA,分别进行全外显子组和RNA测序。结果:Pixul+Sonication法鉴定出最多的蛋白(20,804.5个多肽,3,349.5个蛋白组),其次是Pixul-only法,鉴定出20,769,5个多肽,3,300.5个蛋白组)。两种方法的差异不显著;我们选择了Pixul-only工作流,因为它的高吞吐量效率和最小的步骤,减少了错误概率。从FFPE PDAC组织中,共鉴定出39个失调蛋白(17个下调,22个上调)。确定了细胞外基质组织、血小板活化和纤维化相关途径等关键途径。结论:利用优化后的方法,揭示了与PDAC进展相关的关键蛋白和通路。这些发现强调了基于组织的蛋白质组学分析在生物标志物发现方面的潜力,为PDAC病理生理学和新的治疗靶点提供了重要的见解。测序数据的分析正在进行中。引文格式:Sinegugu Dubazana, Ekene Nweke, Sharol Ngwenya, Previn Naicker, Nnenna Elebo, Sindisiwe Buthelezi, Jones O. Omoshoro-Jones。南非胰腺导管腺癌患者肿瘤微环境的多组学分析[摘要]。摘自:AACR癌症研究特别会议论文集:胰腺癌研究进展-新兴科学驱动变革解决方案;波士顿;2025年9月28日至10月1日;波士顿,MA。费城(PA): AACR;癌症研究2025;85(18_Suppl_3): nr A040。
Abstract A040: Multi-omic Analyses Of The Tumour Microenvironment Of South African Pancreatic Ductal Adenocarcinoma Patients
Background: Pancreatic ductal adenocarcinoma (PDAC) ranks among the most aggressive malignancies globally, with a 5-year survival rate of only 13%. This study conducted multi-omic analyses of archived FFPE tissues to identify potential biomarkers and elucidate molecular mechanisms of disease progression in our patient population. Methods: For the proteomics aspect, a comparison of sample preparation methods (Barocycler, Pixul+DTT, Pixul+Sonication and Pixul-only) was conducted for optimal protein extraction. Using the selected optimised method, 78 FFPE PDAC (22 paired tumour and normal, 34 unpaired tumour) tissues were processed to determine differentially expressed proteins. Limma was used for the differential expression analyses. DNA and Total RNA were subsequently extracted from 28 tissues (14 paired tumours and normal tissues) and Whole exome and RNA sequencing were performed, respectively. Results: The Pixul+Sonication method yielded the highest number of identified proteins (20,804.5 peptides and 3,349.5 protein groups) followed by the Pixul-only method with 20,769,5 peptides and 3,300.5 protein groups). The difference between methods was insignificant; we chose the Pixul-only workflow for its high-throughput efficiency and minimal steps, reducing error probability. From the FFPE PDAC tissues, a total of 39 dysregulated proteins (17 downregulated and 22 upregulated) were identified. Key pathways such as extracellular matrix organization, platelet activation and fibrosis-related pathways were identified. Conclusion: Utilizing this optimized method, key proteins and pathways associated with PDAC progression were demonstrated. These findings underscore the potential of archived tissue-based proteomic analysis for biomarker discovery, providing critical insights into PDAC pathophysiology and novel therapeutic targets. The analyses of the sequencing data are ongoing. Citation Format: Sinegugu Dubazana, Ekene Nweke, Sharol Ngwenya, Previn Naicker, Nnenna Elebo, Sindisiwe Buthelezi, Jones O. Omoshoro-Jones. Multi-omic Analyses Of The Tumour Microenvironment Of South African Pancreatic Ductal Adenocarcinoma Patients [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research—Emerging Science Driving Transformative Solutions; Boston, MA; 2025 Sep 28-Oct 1; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(18_Suppl_3): nr A040.
期刊介绍:
Cancer Research, published by the American Association for Cancer Research (AACR), is a journal that focuses on impactful original studies, reviews, and opinion pieces relevant to the broad cancer research community. Manuscripts that present conceptual or technological advances leading to insights into cancer biology are particularly sought after. The journal also places emphasis on convergence science, which involves bridging multiple distinct areas of cancer research.
With primary subsections including Cancer Biology, Cancer Immunology, Cancer Metabolism and Molecular Mechanisms, Translational Cancer Biology, Cancer Landscapes, and Convergence Science, Cancer Research has a comprehensive scope. It is published twice a month and has one volume per year, with a print ISSN of 0008-5472 and an online ISSN of 1538-7445.
Cancer Research is abstracted and/or indexed in various databases and platforms, including BIOSIS Previews (R) Database, MEDLINE, Current Contents/Life Sciences, Current Contents/Clinical Medicine, Science Citation Index, Scopus, and Web of Science.