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Cited by 16Colorectal Cancer Treatments and StudiesAdvanced Proteomics Techniques and ApplicationsAdvanced Biosensing Techniques and Applications

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Targeted multiplex proteomics for molecular prescreening and biomarker discovery in metastatic colorectal cancer

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Serna, Garazi, Ruiz-Pace, Fiorella, Cecchi, Fabiola, Fasani, Roberta, Jimenez, Jose, Thyparambil, Sheeno, Landolfi, Stefania, Elez, Elena, Vivancos, Ana, Hembrough, Todd, Tabernero, Josep, Dienstmann, Rodrigo, Nuciforo, Paolo·2019·Scientific Reports
DOI 10.1038/s41598-019-49867-7PMC PMC6753065
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Abstract

Protein biomarkers are widely used in cancer diagnosis, prognosis, and prediction of treatment response. Here we introduce the use of targeted multiplex proteomics (TMP) as a tool to simultaneously measure a panel of 54 proteins involved in oncogenic, tumour suppression, drug metabolism and resistance, in patients with metastatic colorectal cancer (mCRC). TMP provided valuable diagnostic information by unmasking an occult neuroendocrine differentiation and identifying a misclassified case based on abnormal proteins phenotype. No significant differences in protein levels between unpaired primary and metastatic samples were observed. Four proteins were found differentially expressed in KRAS-mutant as compared to wild-type tumours (overexpressed in mutant: KRAS, EGFR; overexpressed in wild-type: TOPO1, TOP2A). Survival analyses revealed the association between mesothelin expression and poor overall survival, whereas lack of PTEN protein expression associated with lower progression-free survival with anti-EGFR-based therapy in the first-line setting for patients with RAS wild-type tumour. Finally, outlier analysis identified putative targetable proteins in 65% of patients lacking a targetable genomic alteration. Our data show that TMP constitutes a promising, novel molecular prescreening tool in mCRC to identify protein expression alterations that may impact on patient outcomes and more precisely guide patient eligibility to clinical trials with novel targeted experimental therapies.

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Figure 1 Targeted multiplex proteomics heatmap. Individual samples are plotted in columns (case IDs are indicated at the bottom of each column). Proteins are plotted in rows. Each cell shows the protein level in amol/μg. For each protein, levels of expression are shown on a colour scale from the lowest (light grey) to the highest (red) value. ND indicates non-detectable levels. Percentage of ND for each protein is shown in the rightmost column. RAS and PIK3CA status (MUT, mutation; WT, wild type), tissue (PRIM, primary sample; MET, metastasis), and site are indicated; NA: not applicable.
Figure 1 Targeted multiplex proteomics heatmap. Individual samples are plotted in columns (case IDs are indicated at the bottom of each column). Proteins are plotted in rows. Each cell shows the protein level in amol/μg. For each protein, levels of expression are shown on a colour scale from the lowest (light grey) to the highest (red) value. ND indicates non-detectable levels. Percentage of ND for each protein is shown in the rightmost column. RAS and PIK3CA status (MUT, mutation; WT, wild type), tissue (PRIM, primary sample; MET, metastasis), and site are indicated; NA: not applicable.CC BY · PubMed Central
Figure 2 Mesothelin (MSLN) expression in colorectal cancer. (A) Kaplan-Meier analysis of overall survival in the metastatic setting according to MSLN expression levels quantified by mass spectrometry (MS). (B) Correlation between MS (x-axis, amol/ug) and immunohistochemistry (y-axis, H-score). Pearson correlation coefficient, 95% confidence interval and p-value are indicated. (C) Representative immunohistochemistry staining of a MS MSLN-negative (upper panel; ID-79, liver metastasis, H-score = 0) and –positive (lower panel; ID-72, primary CRC, H-score = 210) cases. Digital magnification: 0.5 × (left) and 20 × (right).
Figure 2 Mesothelin (MSLN) expression in colorectal cancer. (A) Kaplan-Meier analysis of overall survival in the metastatic setting according to MSLN expression levels quantified by mass spectrometry (MS). (B) Correlation between MS (x-axis, amol/ug) and immunohistochemistry (y-axis, H-score). Pearson correlation coefficient, 95% confidence interval and p-value are indicated. (C) Representative immunohistochemistry staining of a MS MSLN-negative (upper panel; ID-79, liver metastasis, H-score = 0) and –positive (lower panel; ID-72, primary CRC, H-score = 210) cases. Digital magnification: 0.5 × (left) and 20 × (right).CC BY · PubMed Central
Figure 3 Distribution of genomic targetable alterations (inner circle). Detailed proteomic targetable alterations for non-genomics targetable samples (outer ring).
Figure 3 Distribution of genomic targetable alterations (inner circle). Detailed proteomic targetable alterations for non-genomics targetable samples (outer ring).CC BY · PubMed Central

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Research works printed but not linked: 41

  1. Addona, T. A. et al. Multi-site assessment of the precision and reproducibility of multiple reaction monitoring–based measurements of proteins in plasma. Nat. Biotechnol. 27, 633–641 (2009). · DOI · Paper page
  2. Nilsson, T. et al. Mass spectrometry in high-throughput proteomics: ready for the big time. Nat. Methods 7, 681–685 (2010). · DOI · Paper page
  3. Prieto, D. A. et al. Liquid Tissue: proteomic profiling of formalin-fixed tissues. Biotechniques Suppl, 32–5 (2005). · DOI
  4. Bateman, N. W. et al. Differential Proteomic Analysis of Late-Stage and Recurrent Breast Cancer from Formalin-Fixed Paraffin-Embedded Tissues. J. Proteome Res. 10, 1323–1332 (2011). · DOI
  5. Hood, B. L. et al. Proteomic Analysis of Formalin-fixed Prostate Cancer Tissue. Mol. Cell. Proteomics 4, 1741–1753 (2005). · DOI
  6. Hembrough, T. et al. Application of Selected Reaction Monitoring for Multiplex Quantification of Clinically Validated Biomarkers in Formalin-Fixed, Paraffin-Embedded Tumor Tissue. J. Mol. Diagnostics 15, 454–465 (2013). · DOI
  7. Huang, S. K. et al. LC/MS-Based Quantitative Proteomic Analysis of Paraffin-Embedded Archival Melanomas Reveals Potential Proteomic Biomarkers Associated with Metastasis. PLoS One 4, e4430 (2009). · DOI
  8. DeSouza, L. V. et al. mTRAQ-based quantification of potential endometrial carcinoma biomarkers from archived formalin-fixed paraffin-embedded tissues. Proteomics 10, 3108–3116 (2010). · DOI
  9. Hembrough, T. et al. Selected Reaction Monitoring (SRM) Analysis of Epidermal Growth Factor Receptor (EGFR) in Formalin Fixed Tumor Tissue. Clin. Proteomics 9, 5 (2012). · DOI
  10. Nuciforo, P. et al. High HER2 protein levels correlate with increased survival in breast cancer patients treated with anti-HER2 therapy. Mol. Oncol. 10, 138–147 (2016). · DOI
  11. Catenacci, D. V. T. et al. Absolute Quantitation of Met Using Mass Spectrometry for Clinical Application: Assay Precision, Stability, and Correlation with MET Gene Amplification in FFPE Tumor Tissue. PLoS One 9, e100586 (2014). · DOI
  12. Catenacci, D. V. T. et al. Mass-spectrometry-based quantitation of Her2 in gastroesophageal tumor tissue: comparison to IHC and FISH. Gastric Cancer 19, 1066–1079 (2016). · DOI
  13. Maron, S. B. et al. Targeted Therapies for Targeted Populations: Anti-EGFR Treatment for EGFR -Amplified Gastroesophageal Adenocarcinoma. Cancer Discov. 8, 696–713 (2018). · DOI
  14. Moldvay, J. et al. The role of TTF-1 in differentiating primary and metastatic lung adenocarcinomas. Pathol. Oncol. Res. 10, 85–8 (2004). · DOI
  15. Compérat, E. et al. Variable sensitivity and specificity of TTF-1 antibodies in lung metastatic adenocarcinoma of colorectal origin. Mod. Pathol. 18, 1371–1376 (2005). · DOI
  16. Harbaum, L. et al. Keratin 7 expression in colorectal cancer - freak of nature or significant finding? Histopathology 59, 225–234 (2011). · DOI
  17. Choueiri, M. B. et al. ERCC1 and TS Expression as Prognostic and Predictive Biomarkers in Metastatic Colon Cancer. PLoS One 10, e0126898 (2015). · DOI
  18. Grimminger, P. P. et al. TS and ERCC-1 mRNA expressions and clinical outcome in patients with metastatic colon cancer in CONFIRM-1 and −2 clinical trials. Pharmacogenomics J. 12, 404–411 (2012). · DOI
  19. Li, P. et al. ERCC1, defective mismatch repair status as predictive biomarkers of survival for stage III colon cancer patients receiving oxaliplatin-based adjuvant chemotherapy. Br. J. Cancer 108, 1238–1244 (2013). · DOI
  20. Shirota, Y. et al. ERCC1 and Thymidylate Synthase mRNA Levels Predict Survival for Colorectal Cancer Patients Receiving Combination Oxaliplatin and Fluorouracil Chemotherapy. J. Clin. Oncol. 19, 4298–4304 (2001). · DOI
  21. Li, Z. et al. Predictive value of APE1, BRCA1, ERCC1 and TUBB3 expression in patients with advanced non-small cell lung cancer (NSCLC) receiving first-line platinum–paclitaxel chemotherapy. Cancer Chemother. Pharmacol. 74, 777–786 (2014). · DOI
  22. Motulsky, H. J. & Brown, R. E. Detecting outliers when fitting data with nonlinear regression-a new method based on robust nonlinear regression and the false discovery rate, https://doi.org/10.1186/1471-2105-7-123 (2006). · DOI · Paper page
  23. Hong, D. S. et al. Phase IB Study of Vemurafenib in Combination with Irinotecan and Cetuximab in Patients with Metastatic Colorectal Cancer with BRAFV600E Mutation. Cancer Discov. 6, 1352–1365 (2016). · DOI · Paper page
  24. Hainsworth, J. D. et al. Targeted Therapy for Advanced Solid Tumors on the Basis of Molecular Profiles: Results From MyPathway, an Open-Label, Phase IIa Multiple Basket Study. J. Clin. Oncol. 36, 536–542 (2018). · DOI · Paper page
  25. Poulsen, T. T. et al. Sym015: A Highly Efficacious Antibody Mixture against MET -Amplified Tumors. Clin. Cancer Res. 23, 5923–5935 (2017). · DOI
  26. El-Deiry, W. S. et al. Molecular profiling of 6,892 colorectal cancer samples suggests different possible treatment options specific to metastatic sites. Cancer Biol. Ther. 16, 1726–1737 (2015). · DOI
  27. Dienstmann, R. et al. Analysis of mutant allele fractions in driver genes in colorectal cancer - biological and clinical insights. Mol. Oncol. 11, 1263–1272 (2017). · DOI
  28. Overman, M. J. et al. Utility of a molecular prescreening program in advanced colorectal cancer for enrollment on biomarker-selected clinical trials. Ann. Oncol. 27, 1068–1074 (2016). · DOI
  29. Morello, A., Sadelain, M. & Adusumilli, P. S. Mesothelin-Targeted CARs: Driving T Cells to Solid Tumors. Cancer Discov. 6, 133–46 (2016). · DOI
  30. Foda, A. A. M., El-Hawary, A. K. & Hamed, H. Aberrant Expression of Calretinin, D2–40 and Mesothelin in Mucinous and Non-Mucinous Colorectal Carcinomas and Relation to Clinicopathological Features and Prognosis. Pathol. Oncol. Res. 22, 725–732 (2016). · DOI
  31. Li, S. et al. Plasma Mesothelin as a Novel Diagnostic and Prognostic Biomarker in Colorectal Cancer. J. Cancer 8, 1355–1361 (2017). · DOI
  32. Loupakis, F. et al. PTEN Expression and KRAS Mutations on Primary Tumors and Metastases in the Prediction of Benefit From Cetuximab Plus Irinotecan for Patients With Metastatic Colorectal Cancer. J. Clin. Oncol. 27, 2622–2629 (2009). · DOI · Paper page
  33. Sartore-Bianchi, A. et al. PIK3CA Mutations in Colorectal Cancer Are Associated with Clinical Resistance to EGFR-Targeted Monoclonal Antibodies. Cancer Res. 69, 1851–1857 (2009). · DOI · Paper page
  34. Razis, E. et al. Potential value of PTEN in predicting cetuximab response in colorectal cancer: An exploratory study. BMC Cancer 8, 234 (2008). · DOI
  35. Sawai, H. et al. Loss of PTEN expression is associated with colorectal cancer liver metastasis and poor patient survival. BMC Gastroenterol. 8, 56 (2008). · DOI
  36. Laurent-Puig, P. et al. Analysis of PTEN, BRAF, and EGFR Status in Determining Benefit From Cetuximab Therapy in Wild-Type KRAS Metastatic Colon Cancer. J. Clin. Oncol. 27, 5924–5930 (2009). · DOI · Paper page
  37. Personeni, N. et al. FOLFIRI and Cetuximab Every Second Week for First-Line Treatment of KRAS Wild-Type Metastatic Colorectal Cancer According to Phosphatase and Tensin Homolog Expression: A Phase II Study. Clin. Colorectal Cancer 14, 162–169 (2015). · DOI
  38. Takashima, A. & Faller, D. V. Targeting the RAS oncogene. Expert Opin. Ther. Targets 17, 507–531 (2013). · DOI
  39. Desmedt, C. et al. Multifactorial Approach to Predicting Resistance to Anthracyclines. J. Clin. Oncol. 29, 1578–1586 (2011). · DOI
  40. Bartlett, J. M. S. et al. Predicting Anthracycline Benefit: TOP2A and CEP17—Not Only but Also. J. Clin. Oncol. 33, 1680–1687 (2015). · DOI
  41. Thress, K. S. et al. Acquired EGFR C797S mutation mediates resistance to AZD9291 in non–small cell lung cancer harboring EGFR T790M. Nat. Med. 21, 560–562 (2015). · DOI · Paper page

Cited by

Sorted by citations

  • EGFR Blockade Reverts Resistance to KRASG12C Inhibition in Colorectal Cancer.

    Amodio, V., Yaeger, R., Arcella, P., Cancelliere, C., Lamba, S., Lorenzato, A., Arena, S., Montone, M., Mussolin, B., Bian, Y., et al. (2020) · Cancer Discovery · doi:10.1158/2159-8290.cd-20-0187 · Cited by 504

    “Basal EGFR expression, as measured by IHC or mass spectrometry (28, 29), has not been associated with EGFR inhibitor sensitivity in colorectal cancer, and indeed we find no clear difference between receptor expression levels by lineage or in the subset of patients with colorectal cancer and NSCLC treated with AMG510.”
    BackgroundSelf-citation

Metadata

Authors
Serna, G., Ruiz-Pace, F., Cecchi, F., Fasani, R., Jimenez, J., Thyparambil, S., Landolfi, S., Elez, E., Vivancos, A., Hembrough, T., Tabernero, J., Dienstmann, R., & Nuciforo, P.
Affiliations
  • Vall d'Hebron Institute of Oncology (ES)
  • NantOmics LLC (United States) (US)
  • Vall d'Hebron Hospital Universitari (ES)
Corresponding author
Nuciforo, Paolo
ORCID
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2019-09-19
Volume
9
Issue
1
Pages
13568-13568
ISSN
2045-2322 (ISSN-L)
DOI
10.1038/s41598-019-49867-7
PMC
PMC6753065
OpenAlex
W2974810552
Cited by
16
References
3
Citations by year
2024: 1 · 2023: 6 · 2021: 3 · 2020: 6
FWCI
0.94
Type
journal article
Language
en
Open access
Licence
Locations
  • Scientific Reports (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • RECERCAT (Consorci de Serveis Universitaris de Catalunya) (submittedVersion, cc-by)
Funders
Fundación Cellex
Topics
  • Health Sciences › Medicine › Oncology › Colorectal Cancer Treatments and Studies
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Advanced Biosensing Techniques and Applications
Keywords
metastatic colorectal cancer, protein biomarkers, neuroendocrine differentiation, KRAS mutation, EGFR, TOP2A, mesothelin, PTEN, anti-EGFR therapy, progression-free survival, overall survival, drug resistance, drug metabolism, inclusion and exclusion criteria
MeSH terms
Mesothelin, Adult, Aged, Female, Humans, Male, Middle Aged, Mutation, Neoplasm Metastasis, Prognosis, Colorectal Neoplasms, Biomarkers, Gene Expression Regulation, Neoplastic, Survival Analysis, Proto-Oncogene Proteins p21(ras), Proteomics, PTEN Phosphohydrolase, GPI-Linked Proteins

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