Proteomic Biomarker Discovery in Breast Cancer

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1 Proteomic Biomarker Discovery in Breast Cancer Rob Baxter Laboratory for Cellular and Diagnostic Proteomics Kolling Institute, University of Sydney, Royal North Shore Hospital

2 Breast cancer is not a single disease Several different molecular subtypes, with different treatment options and response rates: Luminal A Luminal B HER2 enriched Basal-like Most basal-like cancers are negative for ER, PR and HER2 (triple-negative) TNBC is further divided into several different molecular subtypes*: Basal-like 1 Basal-like 2 Mesenchymal Luminal AR with different treatment response rates About 17,000 women in Australia are newly diagnosed with breast cancer each year, Of these, about 2500 have triple-negative breast cancer In general, TNBC has worse prognosis than other breast cancer types There are few prognostic markers available to aid in clinical decision-making for any form of breast cancer, and none for TNBC *Lehmann et al,

3 ER PR HER2 upa PAI-1 Chung & Baxter, Expert Rev Proteomics 9, , 2012

4 u Validation using a similar method, on an independent sample set of similar or greater size. v Verification on a large sample set by an alternative analytical method (e.g. IHC on tissue microarray; SRM and others). w Survival analysis to confirm clinical association with patient outcome. x Establishment of relationship to other pathological variables, such as receptor status, tumor stage and grade, lymphovascular invasion etc. y Determination of preanalytical variables (e.g. effect of age, gender, other disease status; sample collection and biomarker stability). z Determination of analytical precision and clinical decision points. { Finding commercial partner and seeking regulatory (e.g. FDA) approval. Chung & Baxter, Expert Rev Proteomics 9, , 2012

5 Two examples, using different discovery approaches u A novel prognostic marker for lymph nodepositive breast cancer v New prognostic markers in triple-negative breast cancer by MALDI MS imaging

6 u A novel prognostic marker for lymph node-positive breast cancer Protein-chip MALDI mass spectrometry (SELDI-TOF) was used to analyse 100 samples of breast tumours samples of adjacent unaffected breast tissue (Kolling Institute Breast Tumour Bank) Select peaks (clusters) over m/z ,000 which discriminate between cancer and unaffected tissue with high ROC AUC Using most discriminatory peaks, build a multivariate model by stepwise binary logistic regression (Note: this technology is now regarded as obsolete) Adsorptive protein chips with selective surface (ion-exchange, hydrophobic etc) Chung et al, Br J Cancer 108: , 2013

7 u A novel prognostic marker for lymph node-positive breast cancer Protein-chip MALDI mass spectrometry (SELDI-TOF) was used to analyse 100 samples of breast tumours samples of adjacent unaffected breast tissue (Kolling Institute Breast Tumour Bank) Select peaks (clusters) over m/z ,000 which discriminate between cancer and unaffected tissue with high ROC AUC Using most discriminatory peaks, build a multivariate model by stepwise binary logistic regression Peak Intensity m/z (mass/charge) Sensitivity ROC AUC = Specificity Chung et al, Br J Cancer 108: , 2013

8 u A novel prognostic marker for lymph node-positive breast cancer Multivariate analysis of several differentially expressed proteins showed that the levels one protein allowed us to distinguish between normal breast and breast cancer tissue with high sensitivity and specificity We then verified the results by analysing a further 100 breast cancer tissue normal breast tissue samples (Australian Breast Cancer Tissue Bank) Chung et al, Br J Cancer 108: , 2013 Br J Cancer 108: (2013) Liping Chung m/z 9226 = truncated form of calcium binding protein S100P (proteins bound to immobilised S100P antibody)

9 The S100P protein identified as prognostic for breast cancer (9.2 kda) is C-terminally truncated compared to normal S100P (10.4 kda) S100P Chung et al, Cancer Lett 368: 64-70, 2015

10 Clinicopathological characteristics of patients Chung et al, Cancer Lett 368: 64-70, 2015

11 Truncated S100P levels in breast tumour tissue classified according to pathological variables LN = lymph node involvement ER = estrogen receptor PR = progesterone receptor HER2 = human EGF receptor-2 Chung et al, Cancer Lett 368: 64-70, 2015

12 High breast tumour tissue levels of truncated S100P predict poor disease-free survival P=0.005 P=0.017 P=0.786 P=0.007 Chung et al, Cancer Lett 368: 64-70, 2015

13 Truncated S100P is predominantly found within the nucleus MCF-7 cytoplasm MCF-7 nucleus tumour cytoplasm t-s100p S100P tumour nucleus Chung et al, Cancer Lett 368: 64-70, 2015

14 SUMMARYu A novel prognostic marker for lymph node-positive breast cancer We analysed 400 breast cancer and unaffected adjacent tissue samples using protein-chip MALDI (SELDI-TOF) MS A novel truncated form of calcium-binding protein S100P was found to discriminate highly between cancer and unaffected tissue We propose that nuclear t-s100p is a significant prognostic indicator for poor survival in women with lymph node-positive breast cancer

15 v New prognostic markers in triple-negative breast cancer by MALDI MS imaging

16 Background MALDI-TOF MS imaging (MSI) captures mass spectra at multiple locations across a tissue section and integrates them into images of ion distribution Laser Tissue section on conductive glass slide, coated in matrix m/z (mass/charge) Small molecules (e.g. lipids, drugs), peptides (up to ~5000 Da) or intact proteins (up to ~25,000 Da) can be imaged

17 Background MALDI-TOF MS imaging (MSI) captures mass spectra at multiple locations across a tissue section and integrates them into images of ion distribution Laser m/z m/z Tissue section on conductive glass slide, coated in matrix m/z m/z (mass/charge) m/z (mass/charge)

18 Methods This study used MSI to discover proteins capable of distinguishing TNBC tumour tissue from non-cancer tissue, with the goal of evaluating them for their prognostic potential in women with TNBC µm sections from ten FFPE TNBC tumours were mounted onto ITO-treated glass slides, and marked for regions of tumour and non-tumour tissue Sections were deparaffinised, antigen-retrieved, and sprayed with trypsin to generate peptides, then CHCA matrix, using the ImagePrep workstation. Imaging data was acquired using a Bruker UltrafleXtreme TOF-TOF MS in positive ion reflectron mode. Mass spectra were collected in the m/z range at 50 µm raster resolution. In parallel, tissue samples were extracted, trypsin-digested, and peptides identified by LC-MALDI-MS/MS to generate a reference library. Data were processed and analysed using SciLS Lab software, and distinguishing peptides were characterised by their ROC-AUC values. Leo Phillips

19 Analysis of tryptic peptides: SOX11 Tissue: 08P-3105 m/z= Receiver Operating Characteristic (ROC) Curves Sensitivity (true positives) 1.0 AUC = Specificity (false positives) Benign Cancer Cancer Benign Tissue: 08P-9220 m/z= Sensitivity AUC = Specificity Benign Cancer

20 m/z= Analysis of tryptic peptides: MUC Sensitivity AUC = AUC = Tissue: 08P Tissue: 08P Specificity Sensitivity Specificity Tissue: 08P m/z= Sensitivity AUC = Tissue: 08P Specificity Benign Cancer Cancer Benign 1.0 Tissue: 08P-9361 Sensitivity AUC = Tissue: 08P Specificity Benign Cancer

21 SOX11 immunohistochemistry in TNBC tissue microarrays

22 Kaplan-Meier survival analysis for basal-like TNBC (Public gene expression data kmplot.com) Probability of recurrence-free survival HR = 2.14 ( ) logrank P = HR = ( ) ( ) logrank P = Probability Low High SOX Time (months) Probability Low High ATIC/PURH COL6A Time (months) HR = 2.14 ( ) logrank P = HR HR = ( ) ( ) logrank P P = Probability Low High COL1A2 Probability Time (months) Time (months) Low High ZSWIM8 UBR4

23 SUMMARY New prognostic markers in triple-negative breast cancer by MALDI MS imaging v We have used MALDI-MS imaging to identify candidate proteins that distinguish TNBC tissue from non-cancer tissue with high ROC-AUC values, with potential prognostic value in women with TNBC Other highly discriminatory proteins remain to be identified Some of the identified proteins can be shown by gene expression analysis to be prognostic for patient survival (RFS) Validation of the prognostic value of identified proteins is being undertaken using immunohistochemical analysis of TNBC tissue microarrays

24 Acknowledgements Liping Chung Leo Phillips Clinical collaborators: Fran Boyle (Mater) and Katrina Moore (RNSH) Kolling Tumour Bank and Australian Breast Cancer Tissue Bank for the breast cancer tissue samples and follow-up data Anthony Gill and Loretta Sioson (Surgical Pathology, RNSH/Kolling) for providing TNBC TMAs and for assistance with IHC