Abstract A040: Multi-omic Analyses Of The Tumour Microenvironment Of South African Pancreatic Ductal Adenocarcinoma Patients

Abstract 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):Abstract nr A040.

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Journal
Cancer Research
Published
2025-09-28
DOI
https://doi.org/10.1158/1538-7445.pancreatic25-a040
Primary Topic
Cancer Genomics and Diagnostics
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article

Abstract A040: Multi-omic Analyses Of The Tumour Microenvironment Of South African Pancreatic Ductal Adenocarcinoma Patients

Previn Naicker, Sharol Ngwenya, Ekene Emmanuel Nweke, Sindisiwe Buthelezi et al.
Cancer Research
Cancer Genomics and Diagnostics
article

Abstract A040: Multi-omic Analyses Of The Tumour Microenvironment Of South African Pancreatic Ductal Adenocarcinoma Patients

Previn Naicker, Sharol Ngwenya, Ekene Emmanuel Nweke, Sindisiwe Buthelezi, J. Omoshoro–Jones, Sinegugu Dubazana, Nnenna Elebo
article en

Abstract

Abstract 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):Abstract nr A040.

Cancer ResearchVol. 85(18_Supplement_3)
University of the Witwatersrand (ZA), University of Pretoria (ZA)
Openalex Percentile: Top 67%
Cancer Genomics and Diagnostics
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