Proteomics Reveals Cell‐Surface Urokinase Plasminogen Activator Receptor Expression Impacts Most Hallmarks of Cancer

PLAUR facilitates the progression of clear cell renal cell carcinoma by activating the PI3K/AKT/mTOR signaling pathway

Background

PLAUR has been found upregulated in various tumors and closely correlated with the malignant phenotype of tumor cells. The aim of this study was to investigate the relationship between PLAUR and clear cell renal cell carcinoma (ccRCC) and its potential mechanism of promoting tumor progression.

Methods

The expression levels and clinical significance of PLAUR, along with the associated signaling pathways, were extensively investigated in ccRCC samples obtained from The Cancer Genome Atlas (TCGA). PLAUR expression in 20 pairs of ccRCC tumor tissues and the adjacent tissues was assessed using qRT-PCR and IHC staining. Additionally, a series of in vitro experiments were conducted to investigate the impact of PLAUR suppression on cellular proliferation, migration, invasion, cell cycle progression, and apoptosis in ccRCC. The Western blot analysis was employed to investigate the expression levels of pivotal genes associated with the PI3K/AKT/mTOR signaling pathway.

Results

The expression of PLAUR was significantly upregulated in ccRCC compared to normal renal tissues, and higher PLAUR expression in ccRCC was associated with a poorer prognosis than low expression. The in-vitro functional investigations demonstrated that knockdown of PLAUR significantly attenuated the proliferation, migration, and invasion capabilities of ccRCC cells. Concurrently, PLAUR knockdown effectively induced cellular apoptosis, modulated the cell cycle, inhibited the EMT process, and attenuated the activation of the PI3K/AKT/mTOR signaling pathway. PLAUR may represent a key mechanism underlying ccRCC progression.

Conclusions

The involvement of PLAUR in ccRCC progression may be achieved through the activation of the PI3K/AKT/mTOR signaling pathway, making it a reliable biomarker for the identification and prediction of ccRCC.

Prospective Phase II Trial of Prognostication by 68Ga-NOTA-AE105 uPAR PET in Patients with Neuroendocrine Neoplasms: Implications for uPAR-Targeted Therapy

The clinical course for patients with neuroendocrine neoplasms (NENs) ranges from indolent to highly aggressive. Noninvasive tools to improve prognostication and guide decisions on treatment are warranted. Expression of urokinase plasminogen activator receptor (uPAR) is present in many cancer types and associated with a poor outcome. Therefore, using an in-house-developed uPAR PET tracer [⁶⁸Ga]Ga-NOTA-Asp-Cha-Phe-D-Ser-D-Arg-Tyr-Leu-Trp-Ser-OH (⁶⁸Ga-NOTA-AE105), we aimed to assess uPAR expression in NENs. We hypothesized that uPAR expression was detectable in a significant proportion of patients and associated with a poorer outcome. In addition, as uPAR-targeted radionuclide therapy has previously proven effective in preclinical models, the study would also indicate the potential for uPAR-targeted radionuclide therapy in NEN patients. Methods: In a prospective clinical phase II trial, we included 116 patients with NENs of all grades, of whom 96 subsequently had uPAR PET/CT performed with evaluable lesions. PET/CT was performed 20 min after injection of approximately 200 MBq of ⁶⁸Ga-NOTA-AE105. uPAR target-to-liver ratio was used to define lesions as uPAR-positive when lesion SUV_max-to-liver SUV_mean ratio was at least 2. Patients were followed for at least 1 y to assess progression-free and overall survival. Results: Most patients had small intestinal NENs (n = 61) and metastatic disease (n = 86). uPAR-positive lesions were seen in 68% (n = 65) of all patients and in 75% (n = 18) of patients with high-grade (grade 3) NENs. During follow-up (median, 28 mo), 59 patients (62%) experienced progressive disease and 28 patients (30%) died. High uPAR expression, defined as a uPAR target-to-liver ratio above median, had a hazard ratio of 1.87 (95% CI, 1.11-3.17) and 2.64 (95% CI, 1.19-5.88) for progression-free and overall survival, respectively (P < 0.05 for both). Conclusion: When ⁶⁸Ga-NOTA-AE105 PET was used to image uPAR in patients with NENs, uPAR-positive lesions were seen in most patients, notably in patients with both low-grade and high-grade NENs. Furthermore, uPAR expression was associated with a worse prognosis. We suggest that uPAR PET is relevant for risk stratification and that uPAR may be a promising target for therapy in patients with NENs.

uPAR: An Essential Factor for Tumor Development

Tumorigenesis is closely related to the loss of control of many genes. Urokinase-type plasminogen activator receptor (uPAR), a glycolipid-anchored protein on the cell surface, is controlled by many factors in tumorigenesis and is expressed in many tumor tissues. In this review, we summarize the regulatory effects of the uPAR signaling pathway on processes and factors related to tumor progression, such as tumor cell proliferation, adhesion, metastasis, glycolysis, tumor microenvironment and angiogenesis. Overall, the evidence accumulated to date suggests that uPAR induction by tumor progression may be one of the most important factors affecting therapeutic efficacy. An improved understanding of the interactions between uPAR and its coreceptors in cancer will provide critical biomolecular information that may help to better predict the disease course and response to therapy.

Proteomics, Personalized Medicine and Cancer

As of 2020 the human genome and proteome are both at >90% completion based on high stringency analyses. This has been largely achieved by major technological advances over the last 20 years and has enlarged our understanding of human health and disease, including cancer, and is supporting the current trend towards personalized/precision medicine. This is due to improved screening, novel therapeutic approaches and an increased understanding of underlying cancer biology. However, cancer is a complex, heterogeneous disease modulated by genetic, molecular, cellular, tissue, population, environmental and socioeconomic factors, which evolve with time. In spite of recent advances in treatment that have resulted in improved patient outcomes, prognosis is still poor for many patients with certain cancers (e.g., mesothelioma, pancreatic and brain cancer) with a high death rate associated with late diagnosis. In this review we overview key hallmarks of cancer (e.g., autophagy, the role of redox signaling), current unmet clinical needs, the requirement for sensitive and specific biomarkers for early detection, surveillance, prognosis and drug monitoring, the role of the microbiome and the goals of personalized/precision medicine, discussing how emerging omics technologies can further inform on these areas. Exemplars from recent onco-proteogenomic-related publications will be given. Finally, we will address future perspectives, not only from the standpoint of perceived advances in treatment, but also from the hurdles that have to be overcome.

Key Matrix Remodeling Enzymes: Functions and Targeting in Cancer

Tissue functionality and integrity demand continuous changes in distribution of major components in the extracellular matrices (ECMs) under normal conditions aiming tissue homeostasis. Major matrix degrading proteolytic enzymes are matrix metalloproteinases (MMPs), plasminogen activators, atypical proteases such as intracellular cathepsins and glycolytic enzymes including heparanase and hyaluronidases. Matrix proteases evoke epithelial-to-mesenchymal transition (EMT) and regulate ECM turnover under normal procedures as well as cancer cell phenotype, motility, invasion, autophagy, angiogenesis and exosome formation through vital signaling cascades. ECM remodeling is also achieved by glycolytic enzymes that are essential for cancer cell survival, proliferation and tumor progression. In this article, the types of major matrix remodeling enzymes, their effects in cancer initiation, propagation and progression as well as their pharmacological targeting and ongoing clinical trials are presented and critically discussed.

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).

The status of proteomics as we enter the 2020s: Towards personalised/precision medicine

The last decade has seen many major advances in proteomics, with over 70,000 publications in the field since 2010. A comprehensive omics toolbox has been developed facilitating rapid in depth analysis of the human proteome. Such studies are advancing our understanding of the biology of both health and disease. The combination of proteomics with other omics platforms (the omics pipeline), in particular proteogenomics, is giving important insights to the molecular changes leading to disease, covering the spectrum from genotype to phenotype and identifying potential biomarkers for disease detection, surveillance and monitoring, and revealing potential new drug targets. Discovery-based finding are now being translated to clinical application, supporting the rollout of precision/personalised medicine. This perspective has focused on twelve areas of importance that have fuelled the field. Recent exemplars are given to illustrate this and show how, together with some emerging technologies, they are anticipated to lead to further advances in the field. However, hurdles still remain to be overcome, especially in the area of Big Data analysis.