FuncPEP v20: An Updated Database of Functional Short Peptides Translated from Non-Coding RNAs

Over the past decade, there have been reports of short novel functional peptides (less than 100 aa in length) translated from so-called non-coding RNAs (ncRNAs) that have been characterized using mass spectrometry (MS) and large-scale proteomics studies. Therefore, understanding the bivalent functions of some ncRNAs as transcripts that encode both functional RNAs and short peptides, which we named ncPEPs, will deepen our understanding of biology and disease. In 2020, we published the first database of functional peptides translated from non-coding RNAs-FuncPEP. Herein, we have performed an update including the newly published ncPEPs from the last 3 years along with the categorization of host ncRNAs. FuncPEP v2.0 contains 152 functional ncPEPs, out of which 40 are novel entries. A PubMed search from August 2020 to July 2023 incorporating specific keywords was performed and screened for publications reporting validated functional peptides derived from ncRNAs. We did not observe a significant increase in newly discovered functional ncPEPs, but a steady increase. The novel identified ncPEPs included in the database were characterized by a wide array of molecular and physiological parameters (i.e., types of host ncRNA, species distribution, chromosomal density, distribution of ncRNA length, identification methods, molecular weight, and functional distribution across humans and other species). We consider that, despite the fact that MS can now easily identify ncPEPs, there still are important limitations in proving their functionality

The Immune Checkpoint Landscape in Tumor Cells of Pancreatic Ductal Adenocarcinoma

Immune checkpoint therapy (ICT) has shown promising potential in the treatment of multiple solid tumors. However, the role of ICT in pancreatic ductal adenocarcinoma (PDAC) remains limited. Patterns of immune checkpoints (ICs) in PDAC represent the basis for establishing a potent ICT. The aim of this study is to create a profile of IC expression and its prognostic relevance in cancer cells of PDAC. Therefore, tumor cells from peripheral and central tissue microarray (TMA) spots from histologically confirmed PDAC of 68 patients after tumor resection were investigated in terms of expressions of TIM3, IDO, B7H4, LAG3, VISTA, and PD-L1 using immunohistochemistry. The presence of the respective ICs was compared to overall survival (OS). The presence of VISTA and PD-L1 significantly correlates with shorter OS (median OS: 22 months vs. 7 months and 22 months vs. 11 months, respectively, p 0.05). The analysis of OS of combined subgroups for VISTA and PD-L1 (VISTA and PD-L1 neg., VISTA pos. and PD-L1 neg., VISTA neg. and PD-L1 pos., and VISTA and PD-L1 pos.) yielded overall statistical significance difference (p = 0.02). These results suggest that the presence of VISTA and PD-L1 is of prognostic relevance and potentially qualifies them as targets for ICT

Construction and validation of prognostic nomogram for metaplastic breast cancer

In this study we aimed to develop nomogram models for predicting the overall survival (OS) and cancer-specific survival (CSS) of patients with metaplastic breast cancer (MBC). Data of patients diagnosed with MBC from 1973 to 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox analyses were performed to identify independent prognostic factors for OS and CSS of MBC patients. The obtained prognostic variables were combined to construct nomogram models for predicting OS and CSS in patients with MBC. Model performance was evaluated using concordance index (C-index) and calibration plots. Data from 1125 patients were collected and divided into a training (750) and a validation (375) cohort. The multivariate Cox model identified age, TNM stage, tumor size, and radiotherapy as independent covariates associated with OS and CSS. The nomogram constructed based on these covariates demonstrated excellent accuracy in estimating 3-, and 5-year OS and CSS, with a C-index of 0.769 (95% CI, 0.731-0.808) for OS and 0.761 (95% CI, 0.713-0.809) for CSS in the training cohort. In the validation cohort, the nomogram-predicted C-index was 0.738 (95%CI, 0.676-0.800) for OS and 0.747 (95%CI, 0.667-0.827) for CSS. All calibration curves exhibited good consistency between predicted and actual survival. The nomogram models established in this study may enhance the accuracy of prognosis prediction and therefore may improve individualized assessment of survival risks and enable constructive therapeutic suggestions

Rethinking the TNM Classification Regarding Direct Lymph Node Invasion in Pancreatic Ductal Adenocarcinoma

Mechanisms of lymph node invasion seem to play a prognostic role in pancreatic ductal adenocarcinoma (PDAC) after resection. However, the 8th edition of the TNM classification of the American Joint Committee on Cancer (AJCC) does not consider this. The aim of this study was to analyse the prognostic role of different mechanisms of lymph node invasion on PDAC. One hundred and twenty-two patients with resected PDAC were examined. We distinguished three groups: direct (per continuitatem, Nc) from the main tumour, metastasis (Nm) without any contact to the main tumour, and a mixed mechanism (Ncm). Afterwards, the prognostic power of the different groups was analysed concerning overall survival (OS). In total, 20 patients displayed direct lymph node invasion (Nc = 16.4%), 44 were classed as Nm (36.1%), and 21 were classed as Ncm (17.2%). The difference in OS was not statistically significant between N0 (no lymph node metastasis, n = 37) and Nc (p = 0.134), while Nm had worse OS than N0 (p < 0.001). Direct invasion alone had no statistically significant effect on OS (p = 0.885). Redefining the N0 stage by including Nc patients showed a more precise OS prediction among N stages (p = 0.001 vs. p = 0.002). Nc was more similar to N0 than to Nm; hence, we suggest a rethinking of TNM classification based on the mechanisms of lymph node metastases in PDAC. Overall, this novel classification is more precise

DNA Methylation-Based Classifier Differentiates Intrahepatic Pancreato-Biliary Tumours

BACKGROUND: Differentiating intrahepatic cholangiocarcinomas (iCCA) from hepatic metastases of pancreatic ductal adenocarcinoma (PAAD) is challenging. Both tumours have similar morphological and immunohistochemical pattern and share multiple driver mutations. We hypothesised that DNA methylation-based machine-learning algorithms may help perform this task. METHODS: We assembled genome-wide DNA methylation data for iCCA (n = 259), PAAD (n = 431), and normal bile duct (n = 70) from publicly available sources. We split this cohort into a reference (n = 399) and a validation set (n = 361). Using the reference cohort, we trained three machine learning models to differentiate between these entities. Furthermore, we validated the classifiers on the technical validation set and used an internal cohort (n = 72) to test our classifier. FINDINGS: On the validation cohort, the neural network, support vector machine, and the random forest classifiers reached accuracies of 97.68%, 95.62%, and 96.5%, respectively. Filtering by anomaly detection and thresholds improved the accuracy to 99.07% (37 samples excluded by filtering), 96.22% (17 samples excluded), and 100% (44 samples excluded) for the neural network, support vector machine and random forest, respectively. Because of best balance between accuracy and number of predictable cases we tested the neural network with applied filters on the in-house cohort, obtaining an accuracy of 95.45%. INTERPRETATION: We developed a classifier that can differentiate between iCCAs, intrahepatic metastases of a PAAD, and normal bile duct tissue with high accuracy. This tool can be used for improving the diagnosis of pancreato-biliary cancers of the liver

Combined miRNA and SERS urine liquid biopsy for the point-of-care diagnosis and molecular stratification of bladder cancer

Background: Bladder cancer (BC) has the highest per-patient cost of all cancer types. Hence, we aim to develop a non-invasive, point-of-care tool for the diagnostic and molecular stratification of patients with BC based on combined microRNAs (miRNAs) and surface-enhanced Raman spectroscopy (SERS) profiling of urine. Methods: Next-generation sequencing of the whole miRNome and SERS profiling were performed on urine samples collected from 15 patients with BC and 16 control subjects (CTRLs). A retrospective cohort (BC = 66 and CTRL = 50) and RT-qPCR were used to confirm the selected differently expressed miRNAs. Diagnostic accuracy was assessed using machine learning algorithms (logistic regression, naive Bayes, and random forest), which were trained to discriminate between BC and CTRL, using as input either miRNAs, SERS, or both. The molecular stratification of BC based on miRNA and SERS profiling was performed to discriminate between high-grade and low-grade tumors and between luminal and basal types. Results: Combining SERS data with three differentially expressed miRNAs (miR-34a-5p, miR-205-3p, miR-210-3p) yielded an Area Under the Curve (AUC) of 0.92 +/- 0.06 in discriminating between BC and CTRL, an accuracy which was superior either to miRNAs (AUC = 0.84 +/- 0.03) or SERS data (AUC = 0.84 +/- 0.05) individually. When evaluating the classification accuracy for luminal and basal BC, the combination of miRNAs and SERS profiling averaged an AUC of 0.95 +/- 0.03 across the three machine learning algorithms, again better than miRNA (AUC = 0.89 +/- 0.04) or SERS (AUC = 0.92 +/- 0.05) individually, although SERS alone performed better in terms of classification accuracy. Conclusion: miRNA profiling synergizes with SERS profiling for point-of-care diagnostic and molecular stratification of BC. By combining the two liquid biopsy methods, a clinically relevant tool that can aid BC patients is envisaged

MiR-543 regulates the epigenetic landscape of myelofibrosis by targeting TET1 and TET2

Myelofibros is (MF) is a myeloproliferative neoplasm characterized by cytopenia and extramedullary hematopoiesis, resulting in splenomegaly. Multiple pathological mechanisms (e.g., circulating cytokines and genetic alterations, such as JAK(V617F) mutation) have been implicated in the etiology of MF, but the molecular mechanism causing resistance to JAK(V617F) inhibitor therapy remains unknown. Among MF patients who were treated with the JAK inhibitor ruxolitinib, we compared noncoding RNA profiles of ruxolitinib therapy responders versus nonresponders and found miR-S43 was significantly upregulated in non responders. We validated these findings by reverse transcription-quantitative PCR. in this same cohort, in 2 additional independent MF patient cohorts from the United States and Romania, and in a JAK2(V617F) mouse model of MF. Both in vitro and in vivo models were used to determine the underlying molecular mechanism of miR-543 in MF. Here, we demonstrate that miR-543 targets the dioxygenases ten-eleven translocation 1 (TET1) and 2 (TET2) in patients and in vitro, causing increased levels of global 5-methylcytosine, while decreasing the acetylation of histone 3, STAT3, and tumor protein p53. Mechanistically, we found that activation of STAT3 by JAKs epigenetically controls miR-543 expression via binding the promoter region of miR-543. Furthermore, miR-543 upregulation promotes the expression of genes related to drug metabolism, including CYP3A4, which is involved in ruxolitinib metabolism. Our findings suggest miR-543 as a potentially novel biomarker for the prognosis of MF patients with a high risk of treatment resistance and as a potentially new target for the development of new treatment options

17β-estradiol promotes extracellular vesicle release and selective miRNA loading in ERα-positive breast cancer

The causes and consequences of abnormal biogenesis of extracellular vesicles (EVs) are not yet well understood in malignancies, including in breast cancers (BCs). Given the hormonal signaling dependence of estrogen receptor–positive (ER+) BC, we hypothesized that 17β-estradiol (estrogen) might influence EV production and microRNA (miRNA) loading. We report that physiological doses of 17β-estradiol promote EV secretion specifically from ER+ BC cells via inhibition of miR-149-5p, hindering its regulatory activity on SP1, a transcription factor that regulates the EV biogenesis factor nSMase2. Additionally, miR-149-5p downregulation promotes hnRNPA1 expression, responsible for the loading of let-7’s miRNAs into EVs. In multiple patient cohorts, we observed increased levels of let-7a-5p and let-7d-5p in EVs derived from the blood of premenopausal ER+ BC patients, and elevated EV levels in patients with high BMI, both conditions associated with higher levels of 17β-estradiol. In brief, we identified a unique estrogen-driven mechanism by which ER+ BC cells eliminate tumor suppressor miRNAs in EVs, with effects on modulating tumor-associated macrophages in the microenvironment

Anti-miR-93-5p Therapy Prolongs Sepsis Survival by Restoring the Peripheral Immune Response

Sepsis remains a leading cause of death for humans and currently has no pathogenesis-specific therapy. Hampered progress is partly due to a lack of insight into deep mechanistic processes. In the past decade, deciphering the functions of small noncoding miRNAs in sepsis pathogenesis became a dynamic research topic. To screen for new miRNA targets for sepsis therapeutics, we used samples for miRNA array analysis of PBMCs from patients with sepsis and control individuals, blood samples from 2 cohorts of patients with sepsis, and multiple animal models: mouse cecum ligation puncture-induced (CLP-induced) sepsis, mouse viral miRNA challenge, and baboon Gram+ and Gram- sepsis models. miR-93-5p met the criteria for a therapeutic target, as it was overexpressed in baboons that died early after induction of sepsis, was downregulated in patients who survived after sepsis, and correlated with negative clinical prognosticators for sepsis. Therapeutically, inhibition of miR-93-5p prolonged the overall survival of mice with CLP-induced sepsis, with a stronger effect in older mice. Mechanistically, anti-miR-93-5p therapy reduced inflammatory monocytes and increased circulating effector memory T cells, especially the CD4+ subset. AGO2 IP in miR-93-KO T cells identified important regulatory receptors, such as CD28, as direct miR-93-5p target genes. In conclusion, miR-93-5p is a potential therapeutic target in sepsis through the regulation of both innate and adaptive immunity, with possibly a greater benefit for elderly patients than for young patients