De novo discovery of phenotypic intratumour heterogeneity using imaging mass spectrometry
An essential and so far unresolved factor influencing the evolution of cancer and the clinical management of patients is intratumour clonal and phenotypic heterogeneity. However, the de novo identification of tumour subpopulations is so far both a challenging and an unresolved task. Here we present...
Saved in:
| Published in: | The Journal of pathology Vol. 235; no. 1; pp. 3 - 13 |
|---|---|
| Main Authors: | , , , , , , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Chichester, UK
John Wiley & Sons, Ltd
01-01-2015
Wiley Subscription Services, Inc |
| Subjects: | |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | An essential and so far unresolved factor influencing the evolution of cancer and the clinical management of patients is intratumour clonal and phenotypic heterogeneity. However, the de novo identification of tumour subpopulations is so far both a challenging and an unresolved task. Here we present the first systematic approach for the de novo discovery of clinically detrimental molecular tumour subpopulations. In this proof‐of‐principle study, spatially resolved, tumour‐specific mass spectra were acquired, using matrix‐assisted laser desorption/ionization (MALDI) imaging mass spectrometry, from tissues of 63 gastric carcinoma and 32 breast carcinoma patients. The mass spectra, representing the proteomic heterogeneity within tumour areas, were grouped by a corroborated statistical clustering algorithm in order to obtain segmentation maps of molecularly distinct regions. These regions were presumed to represent different phenotypic tumour subpopulations. This was confirmed by linking the presence of these tumour subpopulations to the patients' clinical data. This revealed several of the detected tumour subpopulations to be associated with a different overall survival of the gastric cancer patients (p = 0.025) and the presence of locoregional metastases in patients with breast cancer (p = 0.036). The procedure presented is generic and opens novel options in cancer research, as it reveals microscopically indistinct tumour subpopulations that have an adverse impact on clinical outcome. This enables their further molecular characterization for deeper insights into the biological processes of cancer, which may finally lead to new targeted therapies. Copyright © 2014 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. |
|---|---|
| Bibliography: | Ministry of Education and Research ZonMW Zenith project - No. 93512002 Wilhelm Sander-Stiftung - No. 2012.028.1 Deutsche Forschungsgemeinschaft - No. SFB 824 TP Z02; No. WA 1656/3-1 ark:/67375/WNG-PNRT7TGP-T Marie Curie Action of the European Union - No. SITH FP7-PEOPLE-2012-IEF 331866 FigureS1. Tumour diversity and clinical impact of each cluster across k was assessed. Ellipses represent the clusters that can be identified through their ID (nomenclature: first digit = k, last two/three digits = clusters) or border colour. While the size of the ellipses is proportional to the level-wise amount of patients assigned to the cluster, the thickness of arrows represents the strength of correlation (0-1) between two clusters of consecutive segmentation maps. Additionally, the percentages of metastatic samples (pN1) in each cluster were calculated level-wise and used as fill colour for the ellipses (red for higher percentage of metastatic samples). As can be observed, the cluster associated with the metastatic status of breast cancer patients (starting with 202) remained robust along a changing parameter kFigureS2. Frozen lymph node metastases (M) from two gastric cancer patients (nos 29 and 61) and their corresponding primary tumours (PT) were submitted to the agreement analysis in order to assess spectral similarities between the subpopulations in the primary tumours and their metastases (A). For k = 3 (but only two clusters were found), proteomic similarities between primary tumours and their metastases were found to be higher within the patients than between the patients (B). For k = 4, regions similar to metastases were found in the PTs (C), including the one indicating poor survival (cluster 1 in PT61). For higher k values, PTs and their metastases are becoming separated, confirming their expected natural molecular differences (D)FigureS3. Comparison of results between our previous study (average pixels of each patient) on the identification of prognostic markers in gastric cancer (2 ) and the current study (1), which uses the information of all pixels (no averaging)FigureS4. Determination of the accurate mass of m/z 4156 by MALDI-FTICR high-resolution measurements, taken from the epithelial layer of a normal stomach mucosa which is rich in this mass signalFigureS5. Top-down fragmentation spectra of two m/z species around 4151.35 (±0.7 Da) by both ETD and HCDProtocolS1. Assignment of m/z species of interestProtocolS2. Optimization of the cluster presence threshold for comparison with clinical endpointsTableS1. Multivariate survival analysis of components returned by agreement analysis on gastric cancer using Cox regression modelTableS2. Top-down protein identification of tissue extractsTableS3. Correlation of molecular subtype in breast cancer with differences in heterogeneity or presence of a certain cluster (tumour subpopulation) ArticleID:PATH4436 Federal Republic of Germany - No. 0315505A; No. 01IB10004E SYS-STOMACH istex:095446947C82F9A26C5B36FE79FEAA5FA3587C0B ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 0022-3417 1096-9896 |
| DOI: | 10.1002/path.4436 |