Spontaneous metastasis in congenic mice with transgenic breast cancer is unaffected by plasminogen gene ablation

Comprehensive analysis of subtypes and risk model based on complement system associated genes in ccRCC

BACKGROUND

Immune therapy is widely used in treating clear cell renal cell carcinoma (ccRCC), yet identifying patient subgroups that are expected to response remains challenging. As complement system can mediate immune effects, including the progression of tumors, a correlation between complement system and immune therapy may exist.

METHODS

Based on 11 complement system associated genes (CSAGs) identified from The Cancer Genome Atlas (TCGA), we performed unsupervised clustering and classified the tumors into two different complement system (CS) patterns. The clinical significance, tumor microenvironment (TME), functional enrichment, and immune infiltration were further analyzed. A novel scoring system named CSscore was developed based on the expression levels of the 11 CSAGs.

RESULTS

Two distinct CS patterns were identified, classified as Cluster1 and Cluster2, and Cluster1 showed poor clinical outcome. Further analysis of functional enrichment, immune cell infiltration, and genetic variation revealed that Cluster1 had high infiltration of TME immune cells, but also exhibited high immune escape. The novel prognostic model, CSscore could act as an independent prognostic factor and effectively predict patients' prognosis and distinguish the therapeutic efficacy of different immune treatment strategies. The pan-cancer analysis of the CSscore indicates its potential to be further generalized to other types of cancer.

CONCLUSIONS

Two distinct CS patterns were identified and were further analyzed in terms of infiltration of TME immune cells and immune escape, providing potential explanations for the impact on prognosis of ccRCC. Our CSscore prognostic model may offer a novel perspective in the management of ccRCC patients, and potentially other types of cancer as well.

Plasmin and Plasminogen System in the Tumor Microenvironment: Implications for Cancer Diagnosis, Prognosis, and Therapy

Simple Summary

In this review, we present a detailed discussion of how the plasminogen-activation system is utilized by tumor cells in their unrelenting attack on the tissues surrounding them. Plasmin is an enzyme which is responsible for digesting several proteins that hold the tissues surrounding solid tumors together. In this process tumor cells utilize the activity of plasmin to digest tissue barriers in order to leave the tumour site and spread to other parts of the body. We specifically focus on the role of plasminogen receptor—p11 which is an important regulatory protein that facilitates the conversion of plasminogen to plasmin and by this means promotes the attack by the tumour cells on their surrounding tissues.

Abstract

The tumor microenvironment (TME) is now being widely accepted as the key contributor to a range of processes involved in cancer progression from tumor growth to metastasis and chemoresistance. The extracellular matrix (ECM) and the proteases that mediate the remodeling of the ECM form an integral part of the TME. Plasmin is a broad-spectrum, highly potent, serine protease whose activation from its precursor plasminogen is tightly regulated by the activators (uPA, uPAR, and tPA), the inhibitors (PAI-1, PAI-2), and plasminogen receptors. Collectively, this system is called the plasminogen activation system. The expression of the components of the plasminogen activation system by malignant cells and the surrounding stromal cells modulates the TME resulting in sustained cancer progression signals. In this review, we provide a detailed discussion of the roles of plasminogen activation system in tumor growth, invasion, metastasis, and chemoresistance with specific emphasis on their role in the TME. We particularly review the recent highlights of the plasminogen receptor S100A10 (p11), which is a pivotal component of the plasminogen activation system.

Construction of a novel gene-based model for prognosis prediction of clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) comprises the majority of kidney cancer death worldwide, whose incidence and mortality are not promising. Identifying ideal biomarkers to construct a more accurate prognostic model than conventional clinical parameters is crucial.

METHODS

Raw count of RNA-sequencing data and clinicopathological data were acquired from The Cancer Genome Atlas (TCGA). Tumor samples were divided into two sets. Differentially expressed genes (DEGs) were screened in the whole set and prognosis-related genes were identified from the training set. Their common genes were used in LASSO and best subset regression which were performed to identify the best prognostic 5 genes. The gene-based risk score was developed based on the Cox coefficient of the individual gene. Time-dependent receiver operating characteristic (ROC) and Kaplan-Meier (KM) survival analysis were used to assess its prognostic power. GSE29609 dataset from GEO (Gene Expression Omnibus) database was used to validate the signature. Univariate and multivariate Cox regression were performed to screen independent prognostic parameters to construct a nomogram. The predictive power of the nomogram was revealed by time-dependent ROC curves and the calibration plot and verified in the validation set. Finally, Functional enrichment analysis of DEGs and 5 novel genes were performed to suggest the potential biological pathways.

RESULTS

PADI1, ATP6V0D2, DPP6, C9orf135 and PLG were screened to be significantly related to the prognosis of ccRCC patients. The risk score effectively stratified the patients into high-risk group with poor overall survival (OS) based on survival analysis. AJCC-stage, age, recurrence and risk score were regarded as independent prognostic parameters by Cox regression analysis and were used to construct a nomogram. Time-dependent ROC curves showed the nomogram performed best in 1-, 3- and 5-year survival predictions compared with AJCC-stage and risk score in validation sets. The calibration plot showed good agreement of the nomogram between predicted and observed outcomes. Functional enrichment analysis suggested several enriched biological pathways related to cancer.

CONCLUSIONS

In our study, we constructed a gene-based model integrating clinical prognostic parameters to predict prognosis of ccRCC well, which might provide a reliable prognosis assessment tool for clinician and aid treatment decision-making in the clinic.

Plasminogen-binding proteins as an evasion mechanism of the host's innate immunity in infectious diseases

Pathogens have developed particular strategies to infect and invade their hosts. Amongst these strategies’ figures the modulation of several components of the innate immune system participating in early host defenses, such as the coagulation and complement cascades, as well as the fibrinolytic system. The components of the coagulation cascade and the fibrinolytic system have been proposed to be interfered during host invasion and tissue migration of bacteria, fungi, protozoa, and more recently, helminths. One of the components that has been proposed to facilitate pathogen migration is plasminogen (Plg), a protein found in the host’s plasma, which is activated into plasmin (Plm), a serine protease that degrades fibrin networks and promotes degradation of extracellular matrix (ECM), aiding maintenance of homeostasis. However, pathogens possess Plg-binding proteins that can activate it, therefore taking advantage of the fibrin degradation to facilitate establishment in their hosts. Emergence of Plg-binding proteins appears to have occurred in diverse infectious agents along evolutionary history of host–pathogen relationships. The goal of the present review is to list, summarize, and analyze different examples of Plg-binding proteins used by infectious agents to invade and establish in their hosts. Emphasis was placed on mechanisms used by helminth parasites, particularly taeniid cestodes, where enolase has been identified as a major Plg-binding and activating protein. A new picture is starting to arise about how this glycolytic enzyme could acquire an entirely new role as modulator of the innate immune system in the context of the host–parasite relationship.

Epsilon-aminocaproic acid prevents high glucose and insulin induced-invasiveness in MDA-MB-231 breast cancer cells, modulating the plasminogen activator system

Obesity and type II diabetes mellitus have contributed to the increase of breast cancer incidence worldwide. High glucose concentration promotes the proliferation of metastatic cells, favoring the activation of the plasminogen/plasmin system, thus contributing to tumor progression. The efficient formation of plasmin is dependent on the binding of plasminogen to the cell surface. We studied the effect of ε-aminocaproic acid (EACA), an inhibitor of the binding of plasminogen to cell surface, on proliferation, migration, invasion, epithelial-mesenchymal transition (EMT), and plasminogen activation system, in metastatic MDA-MB-231 breast cancer cells grown in a high glucose microenvironment and treated with insulin. MDA-MB-231 cells were treated with EACA 12.5 mmol/L under high glucose 30 mmol/L (HG) and high glucose and insulin 80 nmol/L (HG-I) conditions, evaluating: cell population growth, % of viability, migratory, and invasive abilities, as well as the expression of uPA, its receptor (uPAR), and its inhibitor (PAI-1), by real-time reverse transcription-polymerase chain reaction (RT-PCR) and Western blot, MMP-2 and MMP-9 mRNAs were evaluated by RT-PCR. Markers of EMT were evaluated by Western blot. Additionally, the presence of active uPA was studied by gel zymography, using casein-plasminogen as substrates. EACA prevented the increase in cell population, migration and invasion induced by HG and insulin, which was associated with the inhibition of EMT and the attenuation of HG- and insulin-dependent expression of uPA, uPAR, PAI-1, MMP-2, MMP-9, α-enolase (ENO A), and HCAM. The interaction of plasminogen to the cell surface and plasmin formation are mediators of the prometastasic action of hyperglycemia and insulin, potentially, EACA can be employed in the prevention and as adjuvant treatment of breast tumorigenesis promoted by hyperglycemia and insulin.

Spontaneous lung and lymph node metastasis in transgenic breast cancer is independent of the urokinase receptor uPAR

Urokinase-type plasminogen activator (uPA) is an extracellular protease that plays a pivotal role in tumor progression. uPA activity is spatially restricted by its anchorage to high-affinity uPA receptors (uPAR) at the cell surface. High tumor tissue expression of uPA and uPAR is associated with poor prognosis in lung, breast, and colon cancer patients in clinical studies. Genetic deficiency of uPA leads to a significant reduction in metastases in the murine transgenic MMTV-PyMT breast cancer model, demonstrating a causal role for uPA in cancer dissemination. To investigate the role of uPAR in cancer progression, we analyze the effect of uPAR deficiency in the same cancer model. uPAR is predominantly expressed in stromal cells in the mouse primary tumors, similar to human breast cancer. In a cohort of MMTV-PyMT mice [uPAR-deficient (n = 31) or wild type controls (n = 33)], tumorigenesis, tumor growth, and tumor histopathology were not significantly affected by uPAR deficiency. Lung and lymph node metastases were also not significantly affected by uPAR deficiency, in contrast to the significant reduction seen in uPA-deficient mice. Taken together, our data show that the genetic absence of uPAR does not influence the outcome of the MMTV-PyMT cancer model.