Identification of binding sites for C-terminal pro-gastrin-releasing peptide (GRP)-derived peptides in renal cell carcinoma: a potential target for future therapy

Evaluation of a tumor marker gastrin-releasing peptide precursor in the patients with kidney injuries

Gastrin-releasing peptide precursor (ProGRP) is a bioactive precursor of GRP and might play an important role as an emerging tumor marker in early cancer diagnosis. It might also be abnormal in the nonmalignant disease and renal function abnormalities. The present study was undertaken to investigate the changes of ProGRP levels in patients with kidney injuries, especially with chronic kidney disease (CKD), determine the upper reference intervals and clinical diagnostic value of ProGRP in CKD, and thus help oncologists in interpreting ProGRP levels and making clinical judgments of malignances. 676 individuals were enrolled in this cross-sectional study and divided into five groups: healthy control (n=194), CKD (n=272), nephrotic syndrome (NS) (n=137), antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) (n=41), and urinary tract infection (UTI) (n=32). A total of 27 features including age, gender, and 25 laboratory markers were analyzed. Machine learning algorithms were built for the diagnostic models of CKD. Statistical analysis was performed by R software. It was shown that serum ProGRP level in CKD was significantly higher than that in healthy controls, UTI and NS (P < 0.01). The upper reference limit of ProGRP was 188.42 pg/ml for CKD, 245.40 pg/ml for CKD IV-V, and 97.25 pg/ml for NS. Compared with the healthy control, the level of serum ProGRP in CKD stages II, III, IV-V was significantly increased and elevated progressively with CKD grade (P < 0.01). Random Forest (RF) model works best among 4 building machine learning algorithms. 5 vital indicators, ProGRP, estimated glomerular filtration rate (eGFR), urea, albumin (ALB), and direct bilirubin (DBIL), were selected to establish RF model for diagnosing CKD with an area under the curve (AUC) of 0.96 (95% confidence interval [CI]: 0.94-0.97) and high sensitivity (0.89) and specificity (0.92). This study demonstrates that the level of ProGRP in patients with CKD, nephrotic syndrome or AAV, was significantly higher than that in the healthy population. The machine learning model of ProGRP with DBIL, eGFR, ALB, and urea, could provide good clinical value for CKD evaluation.

Genetic and pharmacological inhibition of GRPR protects against acute kidney injury via attenuating renal inflammation and necroptosis

Gastrin-releasing peptide (GRP) binds to its receptor (GRP receptor [GRPR]) to regulate multiple biological processes, but the function of GRP/GRPR axis in acute kidney injury (AKI) remains unknown. In the present study, GRPR is highly expressed by tubular epithelial cells (TECs) in patients or mice with AKI, while histone deacetylase 8 may lead to the transcriptional activation of GRPR. Functionally, we uncovered that GRPR was pathogenic in AKI, as genetic deletion of GRPR was able to protect mice from cisplatin- and ischemia-induced AKI. This was further confirmed by specifically deleting the GRPR gene from TECs in GRPRFlox/Flox//KspCre mice. Mechanistically, we uncovered that GRPR was able to interact with Toll-like receptor 4 to activate STAT1 that bound the promoter of MLKL and CCL2 to induce TEC necroptosis, necroinflammation, and macrophages recruitment. This was further confirmed by overexpressing STAT1 to restore renal injury in GRPRFlox/Flox/KspCre mice. Concurrently, STAT1 induced GRP synthesis to enforce the GRP/GRPR/STAT1 positive feedback loop. Importantly, targeting GRPR by lentivirus-packaged small hairpin RNA or by treatment with a novel GRPR antagonist RH-1402 was able to inhibit cisplatin-induced AKI. In conclusion, GRPR is pathogenic in AKI and mediates AKI via the STAT1-dependent mechanism. Thus, targeting GRPR may be a novel therapeutic strategy for AKI.

knnAUC: an open-source R package for detecting nonlinear dependence between one continuous variable and one binary variable

BACKGROUND

Testing the dependence of two variables is one of the fundamental tasks in statistics. In this work, we developed an open-source R package (knnAUC) for detecting nonlinear dependence between one continuous variable X and one binary dependent variables Y (0 or 1).

RESULTS

We addressed this problem by using knnAUC (k-nearest neighbors AUC test, the R package is available at https://sourceforge.net/projects/knnauc/ ). In the knnAUC software framework, we first resampled a dataset to get the training and testing dataset according to the sample ratio (from 0 to 1), and then constructed a k-nearest neighbors algorithm classifier to get the yhat estimator (the probability of y = 1) of testy (the true label of testing dataset). Finally, we calculated the AUC (area under the curve of receiver operating characteristic) estimator and tested whether the AUC estimator is greater than 0.5. To evaluate the advantages of knnAUC compared to seven other popular methods, we performed extensive simulations to explore the relationships between eight different methods and compared the false positive rates and statistical power using both simulated and real datasets (Chronic hepatitis B datasets and kidney cancer RNA-seq datasets).

CONCLUSIONS

We concluded that knnAUC is an efficient R package to test non-linear dependence between one continuous variable and one binary dependent variable especially in computational biology area.

Insights into bombesin receptors and ligands: Highlighting recent advances

This following article is written for Prof. Abba Kastin's Festschrift, to add to the tribute to his important role in the advancement of the role of peptides in physiological, as well as pathophysiological processes. There have been many advances during the 35 years of his prominent role in the Peptide field, not only as editor of the journal Peptides, but also as a scientific investigator and editor of two volumes of the Handbook of Biological Active Peptides [146,147]. Similar to the advances with many different peptides, during this 35 year period, there have been much progress made in the understanding of the pharmacology, cell biology and the role of (bombesin) Bn receptors and their ligands in various disease states, since the original isolation of bombesin from skin of the European frog Bombina bombina in 1970 [76]. This paper will briefly review some of these advances over the time period of Prof. Kastin 35 years in the peptide field concentrating on the advances since 2007 when many of the results from earlier studies were summarized [128,129]. It is appropriate to do this because there have been 280 articles published in Peptides during this time on bombesin-related peptides and it accounts for almost 5% of all publications. Furthermore, 22 Bn publications we have been involved in have been published in either Peptides [14,39,55,58,81,92,93,119,152,216,225,226,231,280,302,309,355,361,362] or in Prof. Kastin's Handbook of Biological Active Peptides [137,138,331].