Discovery of Prognostic Markers for Early-Stage High-Grade Serous Ovarian Cancer by Maldi-Imaging

With regard to relapse and survival, early-stage high-grade serous ovarian (HGSOC) patients comprise a heterogeneous group and there is no clear consensus on first-line treatment. Currently, no prognostic markers are available for risk assessment by standard targeted immunohistochemistry and novel approaches are urgently required. Here, we applied MALDI-imaging mass spectrometry (MALDI-IMS), a new method to identify distinct mass profiles including protein signatures on paraffin-embedded tissue sections. In search of prognostic biomarker candidates, we compared proteomic profiles of primary tumor sections from early-stage HGSOC patients with either recurrent (RD) or non-recurrent disease (N = 4; each group) as a proof of concept study. In total, MALDI-IMS analysis resulted in 7537 spectra from the malignant tumor areas. Using receiver operating characteristic (ROC) analysis, 151 peptides were able to discriminate between patients with RD and non-RD (AUC > 0.6 or < 0.4; p < 0.01), and 13 of them could be annotated to proteins. Strongest expression levels of specific peptides linked to Keratin type1 and Collagen alpha-2(I) were observed and associated with poor prognosis (AUC > 0.7). These results confirm that in using IMS, we could identify new candidates to predict clinical outcome and treatment extent for patients with early-stage HGSOC.

[1]  P. Boor,et al.  Sample preparation of formalin-fixed paraffin-embedded tissue sections for MALDI-mass spectrometry imaging , 2020, Analytical and Bioanalytical Chemistry.

[2]  M. Vaidya,et al.  Multifaceted role of keratins in epithelial cell differentiation and transformation , 2019, Journal of Biosciences.

[3]  Kristina Schwamborn,et al.  Site‐to‐Site Reproducibility and Spatial Resolution in MALDI–MSI of Peptides from Formalin‐Fixed Paraffin‐Embedded Samples , 2019, Proteomics. Clinical applications.

[4]  Carsten Denkert,et al.  MALDI‐Imaging for Classification of Epithelial Ovarian Cancer Histotypes from a Tissue Microarray Using Machine Learning Methods , 2018, Proteomics. Clinical applications.

[5]  Cassandra L Clift,et al.  Extracellular Matrix Imaging of Breast Tissue Pathologies by MALDI–Imaging Mass Spectrometry , 2018, Proteomics. Clinical applications.

[6]  Pei-Shan Lee,et al.  Surgical and survival outcomes of laparoscopic staging surgery for patients with stage I ovarian cancer. , 2018, Taiwanese journal of obstetrics & gynecology.

[7]  S. You,et al.  Survival benefit of patients with early-stage ovarian carcinoma treated with paclitaxel chemotherapeutic regimens , 2017, Journal of gynecologic oncology.

[8]  Wei Wei,et al.  Clinical outcome and prognostic factors of patients with early-stage epithelial ovarian cancer , 2016, Oncotarget.

[9]  M. Sherman,et al.  The Surveillance, Epidemiology, and End Results (SEER) Program and Pathology: Toward Strengthening the Critical Relationship , 2016, The American journal of surgical pathology.

[10]  R. Caprioli,et al.  Imaging mass spectrometry assists in the classification of diagnostically challenging atypical Spitzoid neoplasms. , 2016, Journal of the American Academy of Dermatology.

[11]  M. Nowicki,et al.  Increased Expression of Several Collagen Genes is Associated with Drug Resistance in Ovarian Cancer Cell Lines , 2016, Journal of Cancer.

[12]  A. Jemal,et al.  Cancer statistics, 2016 , 2016, CA: a cancer journal for clinicians.

[13]  A. Walch,et al.  MALDI Imaging mass spectrometry: current frontiers and perspectives in pathology research and practice , 2015, Laboratory Investigation.

[14]  A. Walch,et al.  Discussion point: reporting guidelines for mass spectrometry imaging , 2015, Analytical and Bioanalytical Chemistry.

[15]  N. Packer,et al.  MALDI imaging mass spectrometry of N-linked glycans on formalin-fixed paraffin-embedded murine kidney , 2014, Analytical and Bioanalytical Chemistry.

[16]  By O. Klein MALDI imaging mass spectrometry: Discrimination of pathophysiological regions in traumatized skeletal muscle by characteristic peptide signatures , 2014 .

[17]  J. Oetjen,et al.  MALDI imaging mass spectrometry: Discrimination of pathophysiological regions in traumatized skeletal muscle by characteristic peptide signatures , 2014, Proteomics.

[18]  B. Cillero-Pastor,et al.  Matrix-assisted laser desorption ionization mass spectrometry imaging for peptide and protein analyses: a critical review of on-tissue digestion. , 2014, Journal of proteome research.

[19]  Jaime Prat,et al.  Staging classification for cancer of the ovary, fallopian tube, and peritoneum , 2014, International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics.

[20]  Peter Hoffmann,et al.  Tryptic peptide reference data sets for MALDI imaging mass spectrometry on formalin-fixed ovarian cancer tissues. , 2013, Journal of proteome research.

[21]  Figo Guidelines Staging classification for cancer of the ovary, fallopian tube, and peritoneum☆ , 2013 .

[22]  I. Floriani,et al.  Conservative management of early-stage epithelial ovarian cancer: results of a large retrospective series. , 2013, Annals of oncology : official journal of the European Society for Medical Oncology.

[23]  N. Cho,et al.  In situ identification and localization of IGHA2 in the breast tumor microenvironment by mass spectrometry. , 2012, Journal of proteome research.

[24]  Stefan Heldmann,et al.  Exploring three-dimensional matrix-assisted laser desorption/ionization imaging mass spectrometry data: three-dimensional spatial segmentation of mouse kidney. , 2012, Analytical chemistry.

[25]  Natalie I. Tasman,et al.  A Cross-platform Toolkit for Mass Spectrometry and Proteomics , 2012, Nature Biotechnology.

[26]  Michel Salzet,et al.  The C-terminal fragment of the immunoproteasome PA28S (Reg alpha) as an early diagnosis and tumor-relapse biomarker: evidence from mass spectrometry profiling , 2012, Histochemistry and Cell Biology.

[27]  Horst Zitzelsberger,et al.  Tumor classification of six common cancer types based on proteomic profiling by MALDI imaging. , 2012, Journal of proteome research.

[28]  Orlando Guntinas-Lichius,et al.  MALDI-imaging segmentation is a powerful tool for spatial functional proteomic analysis of human larynx carcinoma , 2012, Journal of Cancer Research and Clinical Oncology.

[29]  R. Casadonte,et al.  Proteomic analysis of formalin-fixed paraffin-embedded tissue by MALDI imaging mass spectrometry , 2011, Nature Protocols.

[30]  Kenneth P. Nephew,et al.  Rethinking ovarian cancer: recommendations for improving outcomes , 2011, Nature Reviews Cancer.

[31]  E. Steyerberg,et al.  [Regression modeling strategies]. , 2011, Revista espanola de cardiologia.

[32]  A. Schneider,et al.  Recommendations of the Fertility Task Force of the European Society of Gynecologic Oncology About the Conservative Management of Ovarian Malignant Tumors , 2011, International Journal of Gynecologic Cancer.

[33]  R. Caprioli,et al.  Detergent enhancement of on-tissue protein analysis by matrix-assisted laser desorption/ionization imaging mass spectrometry. , 2011, Rapid communications in mass spectrometry : RCM.

[34]  Theodore Alexandrov,et al.  Spatial segmentation of imaging mass spectrometry data with edge-preserving image denoising and clustering. , 2010, Journal of proteome research.

[35]  Peter Hoffmann,et al.  Citric acid antigen retrieval (CAAR) for tryptic peptide imaging directly on archived formalin-fixed paraffin-embedded tissue. , 2010, Journal of proteome research.

[36]  E. Popa,et al.  TOF-secondary ion mass spectrometry imaging of polymeric scaffolds with surrounding tissue after in vivo implantation. , 2010, Analytical chemistry.

[37]  M. Castiglione,et al.  Newly diagnosed and relapsed epithelial ovarian carcinoma: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. , 2010, Annals of oncology : official journal of the European Society for Medical Oncology.

[38]  Fred A Hamprecht,et al.  Concise representation of mass spectrometry images by probabilistic latent semantic analysis. , 2008, Analytical chemistry.

[39]  R. Whittal,et al.  Interferences and contaminants encountered in modern mass spectrometry. , 2008, Analytica chimica acta.

[40]  Pierre P Massion,et al.  High‐throughput proteomic analysis of formalin‐fixed paraffin‐embedded tissue microarrays using MALDI imaging mass spectrometry , 2008, Proteomics.

[41]  Sandra Rauser,et al.  MALDI imaging mass spectrometry for direct tissue analysis: a new frontier for molecular histology , 2008, Histochemistry and Cell Biology.

[42]  B. Monk,et al.  Prognostic factors for high‐risk early‐stage epithelial ovarian cancer , 2008, Cancer.

[43]  D. Querleu,et al.  Surgical staging of early invasive epithelial ovarian tumors. , 2000, Seminars in surgical oncology.

[44]  M. Gore,et al.  Natural history and prognosis of untreated stage I epithelial ovarian carcinoma. , 1996, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[45]  V. Torri,et al.  Adjuvant treatment for early epithelial ovarian cancer: Results of two randomised clinical trials comparing cisplatin to no further treatment or chromic phosphate (32P) , 1995 .

[46]  N. Le,et al.  ‘Moderate-risk’ ovarian cancer (stage I, grade 2; stage II, grade 1 or 2) treated with cisplatin chemotherapy (single agent or combination) and pelvi-abdominal irradiation , 1993, International Journal of Gynecologic Cancer.

[47]  V. Abeler,et al.  Randomized trial comparing cisplatin with radioactive phosphorus or whole‐abdomen irradiation as adjuvant treatment of Ovarian cancer , 1992, Cancer.