MALDI TOF Peptide and Glycan Mass Spectrometry Imaging as Diagnostic Tool in Cancer Research

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1 MALDI TOF Peptide and Glycan Mass Spectrometry Imaging as Diagnostic Tool in Cancer Research Prof Peter Hoffmann University of South Australia RCPA Introduction to Proteomics in Pathology Future Industries Institute, Sydney the 2 nd of November 2017

2 Introduction Mass spectrometry Imaging analysis of Endometrial cancer FFPE tissue to distinguish tumours with and without lymph node metastasis N-Glycan MALDI Imaging Mass Spectrometry on FFPE Tissue Enables the Delineation of Ovarian Cancer Tissues

3 Mass spectrometry Imaging analysis of Endometrial cancer Parul Mittal Peter Hoffmann, Manuela Klingler-Hoffmann, Martin K. Oehler

Clinical relevance Endometrial cancer (EC) is the most frequent malignant tumour occurring in the female reproductive system Affects approximately every 1/75 Australian women by the age of 75 5 year

4 Clinical relevance Endometrial cancer (EC) is the most frequent malignant tumour occurring in the female reproductive system Affects approximately every 1/75 Australian women by the age of 75 5 year survival rate Stage I ~ 85% Stage II ~ 75% Stage III ~ 45% Stage IV ~ 25% No metastasis Metastasis Most patients with endometrial cancer routinely undergo a lymph node dissection as part of the cancer operation and postoperative lower extremity (only 10% will have lymph node metastasis) Could Lymphadenectomy be safely omitted for low risk EC patients? adelaide.edu.au 4

5 The hunt for a molecular signature What if we would find a molecular signature in the primary tumour which can be used to predict the metastatic potential of the tumour? This would change the treatment regime for patients with endometrial cancer Overtreatment would be prevented adelaide.edu.au 5

6 Number of genomics and proteomic approaches have identified primary tumour signatures that could predict the presence of LNM in various cancers Metastatic potential of EC at the proteomics level, using MALDI mass spectrometry imaging (MALDI-MSI) and LC-MS/MS label free quantification. adelaide.edu.au 6

MALDI-ToF Mass spectrometry Laser Laser H + Koichi

Ionisation Nobel price in chemistry, 2002 "for the

structure analyses of biological macromolecules"

7 MALDI-ToF Mass spectrometry Laser Laser H + Koichi Tanaka Franz Hillenkamp Michael Karas Desorption Ionisation Nobel price in chemistry, 2002 "for the development of methods for identification and structure analyses of biological macromolecules" Target plate Matrix MALDI- Ionisation Sample d n Source (MALDI) U adelaide.edu.au Analyser (ToF) Time of Flight mass spectrometry Detector Mass spectrum m 2 2eU t 2 z d 7 m/z

8 Data Analysis Sample Preparation MALDI-MSI (Matrix Assisted Laser Desorption Ionisation Mass Spectrometry Imaging) 8

9 Histology compared to MALDI-Imaging adelaide.edu.au 9

10 MALD Imaging of FFPE tissue sections Control Normal DDA and DIA With LNM Without LNM adelaide.edu.au 10

11 MALDI Imaging of FFPE TMA s Control Normal DDA and DIA With LNM Without LNM adelaide.edu.au 11

12 TMA construction ITO Slide H&E IHC PEN Slide ITO Slide EC patient samples (n=57) n = 16 with LNM n = 27 without LNM n = 14 excluded 12

13 H&E stained annotated TMA1 Black: Annotated tumour region Red: With Metastasis Green: Without Metastasis Blue: Excluded adelaide.edu.au 13

14 MALDI MSI data was acquired on an ultraflextreme MALDI-TOF/TOF instrument Peak groups (intact mass, intensity) were generated from the MALDI-MSI data and then ranked using a CCA (Canonical Correlation Analysis ) based method for their ability to distinguish between the primary carcinomas with and without LNM (Lyron Winderbaum) A classification accuracy of 38 out of 43 patients (88.4%) was achieved adelaide.edu.au 14

15 adelaide.edu.au 15

16 Top ranked m/z peak groups as ranked by the CCA Ranked m/z values by CCA Protein Accession Name PLEC_HUMAN CPNE1_human ACTA_HUMAN no match RL11_human HS90B_human ACTA_HUMAN HNRPM_human CLH1_human RS9_human PGM1_human CPNE3_human ACTA_HUMAN SAMP_human EF2_human EIF3E_human H2A1D_human No match HSPB1_human COCOA1_human Mittal et al. 2016, Proteomics. Mittal, M. Klingler-Hoffmann, G. Arentz, L. Winderbaum, N.A. Lokman, C. Zhang, L. Anderson, J. Scurry, Y. Leung, C.J.R. Stewart, J. Carter, G. Kaur, M.K. Oehler, P. Hoffmann, ymph node metastasis of primary endometrial cancers: Associated proteins revealed by MALDI imaging, Proteomics, 2016 Jun;16(11-12): doi: /pmic

17 Relative intensity H&E stain With LNM Ion intensity images H&E stain Without LNM Ion intensity images m/z Mittal et al. 2016, Proteomics 17

18 MALDI Imaging of FFPE TMA s Control Normal DDA and DIA With LNM Without LNM adelaide.edu.au 18

Relative Intensity Relative quantification by targeted LC-MS/MS of α-actin2 Actin 2.0 1.5 n = 5 with LNM n = 5 without LNM 1.0 0.5 0.0 With LNM Without LNM Mittal et al. 2016, Proteomics P. Mittal, M.

19 Relative Intensity Relative quantification by targeted LC-MS/MS of α-actin2 Actin n = 5 with LNM n = 5 without LNM With LNM Without LNM Mittal et al. 2016, Proteomics P. Mittal, M. Klingler-Hoffmann, G. Arentz, L. Winderbaum, N.A. Lokman, C. Zhang, L. Anderson, J. Scurry, Y. Leung, C.J.R. Stewart, J. Carter, G. Kaur, M.K. Oehler, P. Hoffmann, Lymph node metastasis of primary endometrial cancers: Associated proteins revealed by MALDI imaging, Proteomics, 2016 Jun;16(11-12): doi: /pmic

Winderbaum, N.A. Lokman, C. Zhang, L. Anderson, J. Scurry, Y. Leung, C.J.R. Stewart, J. Carter, G. Kaur, M.K. Oehler, P.

20 Validation by Immunohistochemistry Without LNM With LNM Without With With LNM Without LNM 2 1 Chart Title 0% 20% 40% 60% 80% 100% 0% 20% 40% 60% 80% 100% 0% 20% 40% 60% 80% High positive Positive Low positive Negative Mittal et al. 2016, Proteomics P. Mittal, M. Klingler-Hoffmann, G. Arentz, L. Winderbaum, N.A. Lokman, C. Zhang, L. Anderson, J. Scurry, Y. Leung, C.J.R. Stewart, J. Carter, G. Kaur, M.K. Oehler, P. Hoffmann, Lymph node metastasis of primary endometrial cancers: Associated proteins revealed by MALDI imaging, Proteomics, 2016 Jun;16(11-12): doi: /pmic

21 adelaide.edu.au 21

22 TCGA The Cancer Genome Atlas, established in 2005 High throughput data for genomic and proteomic analysis Databank contained 514 EC patients, with RNA sequencing data available for 333 patients (n=54 with LNM and n=279 without LNM) From the analysis, we have chosen eleven differentially expressed genes: six most significant up- and five down-regulated genes Following extensive literature review the list has grown to 60 target proteins, which might be differentially expressed in primary tumours with and without LNM adelaide.edu.au 22

23 Using traditional form of LC-MS/MS, we were able to detect 23 of these proteins in EC tissue cohort (n=5 with LNM and n=5 without LNM) Using targeted LC-MS/MS, we confirmed the differential expression of 5 of the proteins (more than 2 peptides and p value < 0.05) Annexin A2 Annexin A1 Alpha actinin 4 EGFR ERBB2 adelaide.edu.au 23

24 Relative Intensity Relative Intensity Relative Intensity Relative Intensity Relative quantification by targeted LC-MS/MS P value a 3 X ANXA2; A C T N 4 -o n ly tu m o u r A NAnnexin Xp Avalue 2 -o n ly tu= A2 m o u r ACTN4; p value = P value b α-actin 4 2 X X X X X c 0 With LNM W ith L N M P value Without LNM E R B B 2 -o n ly tu m o u r ANXA1; A N Xp A 1value -o n ly tu= m o u r 2.0 ERBB2; p value = Annexin A1 8 P value X X X With LNM Without LNM W ith L N M W ith o u t L N M d 1.5 X X W ith o u t L N M 5 X X e 0 With LNM W ith L N M Without LNM P value W ith o u t L N M 0 With LNM W ith L N M Without LNM EGFR; E Gp F Rvalue -o n ly tu= m o u r metastatic potential of primary endometrial cancer, Biochimica et Biophysica Acta (BBA), Submitted for publication on 15/06/2016 P. Mittal, M. Klingler-Hoffmann, G. Arentz, L.J. Winderbaum, G. Kaur, M.K. Oehler, P. Hoffmann, Annexin A2 and alpha actinin 4 expression correlates with 4 X 10 6 W ith o u t L N M

25 Spatial localization by MALDI MSI The tissue localization of peptides from the differentially expressed proteins were visualized using MALDI MSI in whole tissue sections (n=5 with LNM and n=5 without LNM) as well as TMAs (n=16 with LNM and n=27 without LNM) adelaide.edu.au 25

26 True True positive positive True rate positive rate (sensitivity) (sensitivity) rate (sensitivity) True positive rate (sensitivity) True True positive positive True rate positive rate (sensitivity) (sensitivity) rate (sensitivity) True positive rate (sensitivity) True True positive positive True rate positive rate (sensitivity) (sensitivity) rate (sensitivity) True positive rate (sensitivity) Annexin A2 α-actin 4 Annexin A1d a a a b b b c c c d d d Tumour With LNM Tumour Tumour Normal Tumour Normal Normal Normal Tumour Without LNM Tumour Normal Tumour Normal Tumour Normal AUC = 0.780, m/z ± Da 1 AUC = 0.780, m/z ± Da Normal 0.8 1AUC = 0.780, m/z ± Da AUC = 0.780, m/z ± Da False positive rate (1-specificity) False 0.2 AUC 0.2 = 0.229, positive rate 0.6(1-specificity) m/z 0.8± Da False 0 positive rate (1-specificity) 1 AUC 0= 0.229, m/z ± Da 1 False positive rate (1-specificity) 0.8AUC = 0.229, m/z ± Da AUC = 0.229, m/z ± Da False 0.4 positive rate (1-specificity) False 0.2positive 0.4 rate 0.6(1-specificity) AUC False = , positive rate (1-specificity) m/z ± Da False positive rate (1-specificity) AUC = 0.240, m/z ± Da 0.8 AUC = 0.240, m/z ± Da 1 1 AUC = 0.240, m/z ± Da False positive rate (1-specificity) 0 P. Mittal, M. Klingler-Hoffmann, G. Arentz, L.J. Winderbaum, G. Kaur, M.K. Oehler, P. Hoffmann, Annexin A2 0.4 and alpha 0.6 actinin expression correlates with metastatic potential of primary endometrial cancer, Biochimica et Biophysica Acta (BBA), Submitted 0 False for 0.2publication positive 0.4 rate 0.6(1-specificity) 0.8 on 15/06/

27 Validation by Immunohistochemistry The proteins identified were further validated by immunohistochemistry This allowed the simultaneous analysis of 43 patients (n=16 with LNM and n=27 without LNM) of which 39 had not been analysed by relative quantification LC- MS/MS. adelaide.edu.au 27

28 With With LNM With LNM LNM Without Without LNM LNM LNM With With LNM With LNM LNM Without Without LNM LNM LN a WithoutLNM WithoutLNM WithoutLNM Annexin A2 With LNM With LNM With LNM 20% 40% 60% 80% 100% b Without LNM Without LNM 0% High Positive 20% Positive 40% Low 60% Positive80% Negative 100% Chart Title 0% High Positive 20% 40% Positive Low 60% Positive80% Negative 100% High Positive Positive Chart Low Title positive Negative 0% High Positive 20% Positive 40% Low 60% Positive80% Negative 100% Chart Title High Positive Positive Low positive Negative High Positive Positive Low positive Negative Without LNM α-actin 4 With LNM With LNM c With With LNM LNM Without Without LNM LNM With LNM Without Without Without 20% 40% 60% 80% 100% High Positive IHC-TMA1B-Annexin Positive Low A1 Positive Negative IHC-TMA1B-Annexin A1 High Positive IHC-TMA1B-Annexin Positive Low A1 Positive Negative 20% 40% 60% 80% 100% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Low 0% High 10% Positive 20% High positive Positive 40% Positive positive Negative 60% 70% Low Positive 90% 100% Negative 30% 50% 80% High positive Positive Low positive Negative 20% 40% 60% 80% 100% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% High positive Positive Low positive Negative Annexin A1 With With LNM Without LNM With With 20% 40% 60% 80% 100% High Positive 20% Positive 40% Low 60% Positive80% Negative 100% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% High Positive 20% Positive 40% Low 60% Positive80% Negative 100% P. Mittal, M. Klingler-Hoffmann, G. Arentz, L.J. Winderbaum, G. 0% Kaur, 10% M.K. High 20% Oehler, Positive 30% P. 40% Hoffmann, 50% Low Positive 60% Annexin 70% Negative80% A2 and 90% alpha 100% High Positive Positive actinin 4 expression correlates with Low Positive Negative metastatic potential of primary endometrial cancer, Biochimica0% et Biophysica 10% High 20% Positive Acta 30% (BBA), Positive 40% 50% Submitted Low Positive 60% 70% Negative for publication 80% 90% 100% on 15/06/2016

29 Our study indicates that annexin A2 is increased in abundance, whereas annexin A1 and α actinin 4 are markedly decreased in primary tumours with LNM compared to those without P. Mittal, M. Klingler-Hoffmann, G. Arentz, L.J. Winderbaum, G. Kaur, M.K. Oehler, P. Hoffmann, ANNEXIN A2 AND ALPHA ACTININ 4 EXPRESSION CORRELATES WITH METASTATIC POTENTIAL OF PRIMARY ENDOMETRIAL CANCER, Biochimica et Biophysica Acta (BBA), Submitted for publication on 15/06/2016 adelaide.edu.au 29

30 Logistic Regression Model to fit IHC results adelaide.edu.au 30

31 Nomogram using clinical variables From the 43 patients analysed, we had 35 patients for which all the following clinical variables have been recorded: age, tumour grade, tumour size, tumour extent, and lymphovascular space invasion (LVSI) Fitting a logistic regression model based on all these clinical variables and iteratively removing the least significant of them Resulted in only one significant clinical variable: LVSI, and this agrees with recently published results adelaide.edu.au 31

32 Model to fit clinical variables adelaide.edu.au 32

33 Model to fit LVSI and IHC results adelaide.edu.au 33

34 Model to fit MALDI-MSI variables alone adelaide.edu.au 34

35 Adding MALDI-MSI Variables with LVSI adelaide.edu.au 35

36 Nomogram for Endometrial Cancer LNM: LVSI + v4 + v adelaide.edu.au 36

37 Summary LVSI information not available when women are diagnosed with EC as they have only small biopsy taken Would be great to have a model to guide the surgeons whether to remove the lymph nodes before the surgery. MALDI MSI in combination with LVSI performs better to predict LNM from primary tumours for endometrial cancer than anything else available adelaide.edu.au 37

38 Conclusion MALDI-MSI can be used in the clinics to guide the surgeons Without knowing the protein, we were able to classify the EC patients with and without LNM with 88% accuracy Moreover the logistic regression model of MALDI-MSI data perform better than IHC data After surgery a combination of LVSI and MALDI-MSI data could confirm the decision not to remove Lymph nodes adelaide.edu.au 38

39 N-Glycan MALDI Imaging Mass Spectrometry on Formalin-Fixed Paraffin-Embedded Tissue Enables the Delineation of Ovarian Cancer Tissues Matthew T. Briggs, Arun V. Everest-Dass, Gurjeet Kaur, Martin K. Oehler, Nicolle H. Packer, Peter Hoffmann

40 Protein Glycosylation

41 Glycosylation in apoptotic pathways Cell Death and Differentiation (2013) 20, ; doi: /cdd

42 α2-6 Sialylation prevents apoptosis Pro-apoptotic Anti-apoptotic Molecules 2015, 20, ; doi: /molecules

43 Sialylation in ovarian cell lines Mol Cell Proteomics Sep;13(9): doi: /mcp.M

44 Workflow of N-glycan Imaging

45 Workflow for N-glycan Imaging

46 H&E stain of stage III ovarian tumour section Tumour Stroma Adipose Necrotic

47 MALDI-MS sum spectra No N-Glycans Control 18 N-Glycans (confirmed by LC-MS/MS) PNGase F Glycoforms cannot be identified by MALDI-MS adelaide.edu.au 47

48 No high mass range N-Glycans No N-Glycans Control No high mass range N-Glycans PNGase F (i.e. tri-antennary or tetra-antennary)

49 Visualization of m/z Which glycoform?

50 Glycoform identified by LC-MS/MS

51 LC-MS is more sensitive than MALDI-MS 36 N-Glycans (including glycoforms identifed by LC-MS/MS) Glycoforms are not shown in this figure

52 High mass range N-Glycans identified by LC-MS/MS Tri-antennary and Tetra-antennary not identified in MALDI-MS

53 H&E stain of stage III ovarian tumour section Tumour Stroma Adipose Necrotic

54 Tissue types have distinguished glycan pattern

55 Sialylation in ovarian cell lines Mol Cell Proteomics Sep;13(9): doi: /mcp.M

56 Sialic acid linkages from tumor region Intens. x α2-3 linked 3 α2-6 linked Time [min]

57 Conclusion Glycan Imaging established for FFPE tumour tissue Cancer, stroma, necrotic and adipose tissue can be easily distinguished by the glycan pattern Different sialic acid linkages can be identified in the tumour tissue In the future we will chemically modify these linkages and will be able to map them spatially with MSI Glycan Imaging is a very promising tool for cancer diagnostic in the future

58 MALDI Imaging on N-glycans Gustafsson OJ, Briggs MT, Condina MR, Winderbaum LJ, Pelzing M, McColl SR, Everest- Dass AV, Packer NH, Hoffmann P. MALDI imaging mass spectrometry of N-linked glycans released from formalin-fixed murine kidney. Anal & Bioanal Chem., 2015, 407, M.T. Briggs, J.S. Kuliwaba, D. Muratovic, A.V. Everest-Dass, N.H. Packer, D.M. Findlay, Peter Hoffmann. MALDI mass spectrometry imaging of N-glycans on tibial cartilage and subchondral bone proteins in knee osteoarthritis. Proteomics, 2016, 16(11-12): A.V. Everest-Dass*, M.T. Briggs*, K. Gurjeet, M.K. Oehler, P. Hoffmann*, N.H. Packer*. N-glycan MALDI imaging mass spectrometry on formalin-fixed paraffin-embedded tissues enables the delineation of ovarian cancer tissues. MCP, 2016, 15(9): M.T. Briggs, Y.Y. Ho, G. Kaur, M.K. Oehler, A.V. Everest-Dass, N.H. Packer, P. Hoffmann. 2Nglycan matrix-assisted laser desorption/ionization mass spectrometry imaging protocol for formalin-fixed paraffin-embedded tissues. Rapid Communication in Mass Spectrometry May 30;31(10):

59 Acknowledgements Proteomics and MS group Dr. Georgia Arentz Dr. Mark Condina Dr. Manuela Klingler-Hoffmann Dr. Yin Ying Ho Dr. Noor Lackman Chris Cursaro Parul Mittal Chao Zhang Matthew Briggs Lyron Winderbaum Michelle Turvey Mitch Acland Brooke Dilmetz Royal Adelaide Hospital Prof. Martin K. Oehler Dr. Carmela Riccardelli X Building MM Building The University of Adelaide A/Prof. Inge Koch Macquarie Univervisty Prof. Nicolle Packer Dr. Arun Dass University Sains, Malaysia Prof Gurjeet Kaur

60 Thank you

61 adelaide.edu.au 61

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