Epithelial and stromal cell urokinase plasminogen activator receptor expression differentially correlates with survival in rectal cancer stages B and C patients

Use of a Recombinant Biomarker Protein DDA Library Increases DIA Coverage of Low Abundance Plasma Proteins

Credible detection and quantification of low abundance proteins from human blood plasma is a major challenge in precision medicine biomarker discovery when using mass spectrometry (MS). In this proof-of-concept study, we employed a mixture of selected recombinant proteins in DDA libraries to subsequently identify (not quantify) cancer-associated low abundance plasma proteins using SWATH/DIA. The exemplar DDA recombinant protein spectral library (rPSL) was derived from tryptic digestion of 36 recombinant human proteins that had been previously implicated as possible cancer biomarkers from both our own and other studies. The rPSL was then used to identify proteins from nondepleted colorectal cancer (CRC) EDTA plasmas by SWATH-MS. Most (32/36) of the proteins used in the rPSL were reliably identified from CRC plasma samples, including 8 proteins (i.e., BTC, CXCL10, IL1B, IL6, ITGB6, TGFα, TNF, TP53) not previously detected using high-stringency protein inference MS according to PeptideAtlas. The rPSL SWATH-MS protocol was compared to DDA-MS using MARS-depleted and postdigestion peptide fractionated plasmas (here referred to as a human plasma DDA library). Of the 32 proteins identified using rPSL SWATH, only 12 could be identified using DDA-MS. The 20 additional proteins exclusively identified using the rPSL SWATH approach were almost exclusively lower abundance (i.e., <10 ng/mL) proteins. To mitigate justified FDR concerns, and to replicate a more typical library creation approach, the DDA rPSL library was merged with a human plasma DDA library and SWATH identification repeated using such a merged library. The majority (33/36) of the low abundance plasma proteins added from the rPSL were still able to be identified using such a merged library when high-stringency HPP Guidelines v3.0 protein inference criteria were applied to our data set. The MS data set has been deposited to ProteomeXchange Consortium via the PRIDE partner repository (PXD022361).

Molecular imaging of the urokinase plasminogen activator receptor: opportunities beyond cancer

The urokinase plasminogen activator receptor (uPAR) plays a multifaceted role in almost any process where migration of cells and tissue-remodeling is involved such as inflammation, but also in diseases as arthritis and cancer. Normally, uPAR is absent in healthy tissues. By its carefully orchestrated interaction with the protease urokinase plasminogen activator and its inhibitor (plasminogen activator inhibitor-1), uPAR localizes a cascade of proteolytic activities, enabling (patho)physiologic cell migration. Moreover, via the interaction with a broad range of cell membrane proteins, like vitronectin and various integrins, uPAR plays a significant, but not yet completely understood, role in differentiation and proliferation of cells, affecting also disease progression. The implications of these processes, either for diagnostics or therapeutics, have received much attention in oncology, but only limited beyond. Nonetheless, the role of uPAR in different diseases provides ample opportunity to exploit new applications for targeting. Especially in the fields of oncology, cardiology, rheumatology, neurology, and infectious diseases, uPAR-targeted molecular imaging could offer insights for new directions in diagnosis, surveillance, or treatment options.

Tissue and plasma proteomics for early stage cancer detection

The pursuit of novel and effective biomarkers is essential in the struggle against cancer, which is a leading cause of mortality worldwide. Here we discuss the relative advantages and disadvantages of the most frequently used proteomics techniques, concentrating on the latest advances and application of tissue and plasma proteomics for novel cancer biomarker discovery.

Prognostic Impact of Urokinase Plasminogen Activator Receptor Expression in Pancreatic Cancer: Malignant Versus Stromal Cells

The urokinase plasminogen activator receptor (uPAR) has been proposed as a potential prognostic factor for various malignancies. The aim of this study is to assess the prognostic value of uPAR expression in neoplastic and stromal cells of patients with pancreatic adenocarcinoma. Urokinase plasminogen activator receptor expression was determined by immunohistochemistry in 122 pancreatic ductal adenocarcinomas. Kaplan-Meier and Cox regression analyses were used to determine the association with survival. Respectively 66%, 82% and 62% of patients with pancreatic cancer expressed uPAR in neoplastic cells, stromal, and in both combined. Multivariate analysis showed a significant inverse association between uPAR expression in both neoplastic and stromal cells and overall survival. The prognostic impact of uPAR in stromal cells is substantial, but not as pronounced as that of uPAR expression in neoplastic cells. This study suggests a role for uPAR as a biomarker to single out higher risk subgroups of patients with pancreatic cancer.

Preclinical uPAR-targeted multimodal imaging of locoregional oral cancer

OBJECTIVES

Establishing adequate resection margins and lymphatic mapping are crucial for the prognosis of oral cancer patients. Novel targeted imaging modalities are needed, enabling pre- and intraoperative detection of tumour cells, in combination with improved post-surgical examination by the pathologist. The urokinase-receptor (uPAR) is overexpressed in head and neck cancer, where it is associated with tumour progression and metastasis.

MATERIAL AND METHODS

To determine suitability of uPAR for molecular imaging of oral cancer surgery, human head and neck tumours were sectioned and stained for uPAR to evaluate the expression pattern compared to normal mucosa. Furthermore, metastatic oral squamous carcinoma cell line OSC-19 was used for targeting uPAR in in vivo mouse models. Using anti-uPAR antibody ATN-658, equipped with a multimodal label, the in vivo specificity was investigated and the optimal dose and time-window were evaluated.

RESULTS

All human oral cancer tissues expressed uPAR in epithelial and stromal cells. Hybrid ATN-658 clearly visualized tongue tumours in mice using either NIRF or SPECT imaging. Mean fluorescent TBRs over time were 4.3±0.7 with the specific tracer versus 1.7±0.1 with a control antibody. A significant difference in TBRs could be seen between 1nmol (150μg) and 0.34nmol (50μg) dose groups (n=4, p<0.05). Co-expression between BLI, GFP and the NIR fluorescent signals were seen in the tongue tumour, whereas human cytokeratin staining confirmed presence of malignant cells in the positive cervical lymph nodes.

CONCLUSION

This study shows the applicability of an uPAR specific multimodal tracer in an oral cancer model, combining SPECT with intraoperative guidance.