Banking Pancreas Samples

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Banking Pancreas Samples NIHR Liverpool Pancreas Biomedical Research Unit Pancreatic Cancer Biobank Tissue Blood Juice Liverpool Cancer Tissue Bank Clinical Trials Samples : Good Clinical Practice

1 Banking Pancreas Samples NIHR Liverpool Pancreas Biomedical Research Unit Pancreatic Cancer Biobank Tissue Blood Juice Liverpool Cancer Tissue Bank Clinical Trials Samples : Good Clinical Practice for laboratories Urine Saliva Acute Pancreatitis Biobank Chronic Pancreatitis Biobank OMICS techniques: transcriptomic, proteomic, genomic, other Aim: to develop new diagnostic approaches, therapies and treatments for patients with pancreatitis and pancreatic cancer.

NIHR Liverpool Pancreas Biomedical Research Unit Severely debilitating disease Inflammation of the Pancreas Dysregulation of digestive enzyme secretion Incidence 150-420 cases per million

2 NIHR Liverpool Pancreas Biomedical Research Unit Severely debilitating disease Inflammation of the Pancreas Dysregulation of digestive enzyme secretion Incidence cases per million population/year in the UK Severity Mild AP may require brief hospitalization and has very low mortality rate Severe AP can result in patients being critically ill with multiple organ dysfunction requiring intensive care monitoring. Mortality rate between 10-30% depending on the presence of sterile versus infected necrosis Transcriptomic Approach Jane Armstrong, Brian Lane Proteomic Approach Vickie Elliott

1 126 251 376 501 626 751 876 1001 1126 1251 1376 1501 1626 1751 1876 2001 2126 2251 2376 2501 2626 2751 2876 3001 3126 3251 3376 3501 3626 3751 3876 4001 4126 Mutation Screening Approach in Chronic

3 Mutation Screening Approach in Chronic Pancreatitis Aim: to find SNPs associated with chronic pancreatitis in genes linked to Fatty Acid Ethyl Ester metabolism 97 CP, 98 Ctrl 0.18 Mb sequenced per patient SNP 26 top hits selected for further analysis

4 Imaging of tissue Confocal imaging Electron micrograph imaging Confocal image: (a) mouse pancreatic acinar cells, (b) human pancreatic tissue section Electron micrograph of human pancreatic tissue Awais Muhammad Diane Latawiec

5 EPC-TM-NET The aim of EPC-TM-NET is to improve survival of pancreatic cancer patients by development and validation of better therapeutic strategies targeting the tumour microenvironment rather than the tumour cell alone Neoptolemos, Greenhalf, Costello

6 Pancreatic tumours are stoma rich Alpha-Smooth muscle actin Myofibroblasts in pancreatic tumour

Stroma impairs delivery of drugs to pancreatic tumour cells Sub-cutaneous transplanted KPC tumors KPC pancreatic tumors Confocal microscopy of doxorubicin delivery to mouse

7 Stroma impairs delivery of drugs to pancreatic tumour cells Sub-cutaneous transplanted KPC tumors KPC pancreatic tumors Confocal microscopy of doxorubicin delivery to mouse pancreatic tumors Olive KP, Jacobetz MA, Davidson CJ, et al. Inhibition of Hedgehog signaling enhances delivery of chemotherapy in a mouse model of pancreatic cancer. Science 2009;324:

EPC-TM-NET The aim of EPC-TM-NET is to improve survival of pancreatic cancer patients by development and validation of better therapeutic strategies targeting

8 EPC-TM-NET The aim of EPC-TM-NET is to improve survival of pancreatic cancer patients by development and validation of better therapeutic strategies targeting the tumour microenvironment rather than the tumour cell alone Aims: 1. Quantify stroma 2. Correlate stroma with serum markers Neoptolemos, Greenhalf, Costello

9 Quantifying Stroma Developed a prtocol for profiling stromal levels using Tissue Micro Arrays This involves quantification of the following components: 1. Epithelia component (Cytokeratin) 2. Fibrotic component (Alpha SMA) 3. Lymphocytes (CD3, CD8) 4. Endothelial component (vascular CD31; lymphatic D2-40) 5. Macrophage component (CD68, CD206, CD204, HLA-DR) Quantification is both manual and automated (Definiens Tissue Studio)

10 Protocol for analysis Cut into ~190 x 3µm depth sections Analyse sections at 4 levels within the TMA (n=44 patients) 15 antibodies were tested for specificity and quality of staining 6 antibodies were selected that gave greatest information regarding stromal level Cytokine analysis was undertaken for these 44 patients by analysing matching serum samples using Luminex

11 Automation using Definiens Tissue Studio 11

12 COMPARISON OF DEFINIENS AND MANUAL SCORING By eye Definiens 50% 62.52% 60% 63.63% Dr Katharine hand

13 LYMPHATIC VESSEL CLASSIFICATION Small lymphatic vessels Large lymphatic vessels Tumour associated lymphatic vessels Stroma associated lymphatic vessels [D2-40/ haematoxylin] 13

14 Pan Macrophage (CD68) M1 Macrophage (CD68 & HLA-DR) M2 Macrophage (CD206) 14

15 STROMAL CORRELATIONS WITH SERUM PROTEINS DETECTION OF CYTOKINES USING LUMINEX 15

16 VALIDATION 48 pt TMA has been constructed to validate the stromal-cytokine associations observed TMA sectioned at 4μm and stained at 4 sections with antibodies Matched serum samples have been analysed using 27-panel Luminex

17 Acknowledgements Katharine Hand Awais Muhammad Jane Armstrong Diane Latawiec Vicki Elliott Claire Jenkinson Anthony Evans Fiona Campbell Brian Lane Victoria Shaw Christopher Halloran Paula Ghaneh Bill Greenhalf Robert Sutton Dan Palmer Syed Hussain Ross Sibson John Neoptolemos

Supplemental Table 1. Primer sequences for transcript analysis

Supplemental Table 1. Primer sequences for transcript analysis Primer Sequence (5 3 ) Primer Sequence (5 3 ) Mmp2 Forward CCCGTGTGGCCCTC Mmp15 Forward CGGGGCTGGCT Reverse GCTCTCCCGGTTTC Reverse CCTGGTGTGCCTGCTC