Diagnostic value of serum miR-144-3p for the detection of acute cellular rejection in heart transplant patients

Bioinformatic and experimental analyses of GATA3 and its regulatory miRNAs in breast Cancer

BACKGROUND

GATA binding protein 3 (GATA3) is a transcription factor that plays a critical role in the differentiation and function of luminal epithelial cells in the breast. MicroRNAs (miRNAs) are small non-coding RNAs that modulate gene expression and their dysregulation has been implicated in cancer. The purpose of this study was to investigate the expression of GATA3 and its corresponding targeting miRNAs in breast cancer.

MATERIALS AND METHODS

In this study, we used bioinformatic tools, including the miRWalk database and RNA Hybrid online tool, to identify potential miRNAs that target the GATA3 mRNA. Then, we collected frozen tissue specimens from 67 breast cancer patients and 67 adjacent normal breast tissue samples and evaluated the expression levels of GATA3, hsa-miR-433-3p, and hsa-miR-144-3p using quantitative RT-PCR.

RESULTS

We found that hsa-miR-433-3p and hsa-miR-144-3p are potential miRNAs that target the GATA3 mRNA, and we found that both were significantly downregulated in breast cancer tissues relative to adjacent normal breast tissues (P < 0.0001). We also observed a significant upregulation of the GATA3 mRNA in breast cancer tissues (P < 0.0001). Additionally, we found that their dysregulation was associated with clinicopathological features such as invasive carcinoma and carcinoma in situ subtypes, tumor grade, estrogen receptor status, progesterone receptor status, and HER2 status.

CONCLUSIONS

Our study represents the first attempt to investigate the expression of GATA3 and its targeting miRNAs simultaneously in breast cancer. Our findings suggest that dysregulation of these genes may contribute to breast cancer development and progression.

Validation of the clinical utility of microRNA as noninvasive biomarkers of cardiac allograft rejection: A prospective longitudinal multicenter study

While studies have shown an association between microRNAs and cardiac rejection, the clinical relevance of a preidentified miRNA signature as a noninvasive biomarker has never been assessed in prospective multicentric unselected cohorts. To address this unmet need, we designed a prospective study (NCT02672683) including recipients from 11 centers between August 2016 to March 2018. The objective was to validate the association between 3 previously identified circulating microRNA (10a, 92a, 155) and the histopathological diagnosis of rejection. Both relative and absolute (sensitivity analysis) quantifications of microRNAs were performed. Overall, 461 patients were included (831 biopsies, 79 rejections). A per-protocol interim analysis (258 biopsies, 49 rejections) did not find any association between microRNA and rejection (microRNA 10a: odds ratio (OR) = 1.05, 95% confidence intervals (CI) = 0.87-1.27, p = 0.61; 92a: OR = 0.98, 95%CI = 0.87-1.10, p = 0.68; 155: OR = 0.91, 95%CI = 0.76-1.10, p = 0.33). These results were confirmed in the sensitivity analysis. The analysis of the remaining sera was stopped for futility. This study shows no clinical utility of circulating microRNAs 10a, 92a, and 155 monitoring in heart allograft recipients.

Novel ceRNA network construction associated with programmed cell death in acute rejection of heart allograft in mice

Background

T cell-mediated acute rejection(AR) after heart transplantation(HT) ultimately results in graft failure and is a common indication for secondary transplantation. It's a serious threat to heart transplant recipients. This study aimed to explore the novel lncRNA-miRNA-mRNA networks that contributed to AR in a mouse heart transplantation model.

Methods

The donor heart from Babl/C mice was transplanted to C57BL/6 mice with heterotopic implantation to the abdominal cavity. The control group was syngeneic heart transplantation with the same kind of mice donor. The whole-transcriptome sequencing was performed to obtain differentially expressed mRNAs (DEmRNAs), miRNAs (DEmiRNAs) and lncRNAs (DElncRNAs) in mouse heart allograft. The biological functions of ceRNA networks was analyzed by GO and KEGG enrichment. Differentially expressed ceRNA involved in programmed cell death were further verified with qRT-PCR testing.

Results

Lots of DEmRNAs, DEmiRNAs and DElncRNAs were identified in acute rejection and control after heart transplantation, including up-regulated 4754 DEmRNAs, 1634 DElncRNAs, 182 DEmiRNAs, and down-regulated 4365 DEmRNAs, 1761 DElncRNAs, 132 DEmiRNAs. Based on the ceRNA theory, lncRNA-miRNA-mRNA regulatory networks were constructed in allograft acute rejection response. The functional enrichment analysis indicate that the down-regulated mRNAs are mainly involved in cardiac muscle cell contraction, potassium channel activity, etc. and the up-regulated mRNAs are mainly involved in T cell differentiation and mononuclear cell migration, etc. The KEGG pathway enrichment analysis showed that the down-regulated DEmRNAs were mainly enriched in adrenergic signaling, axon guidance, calcium signaling pathway, etc. The up-regulated DEmRNAs were enriched in the adhesion function, chemokine signaling pathway, apoptosis, etc. Four lncRNA-mediated ceRNA regulatory pathways, Pvt1/miR-30c-5p/Pdgfc, 1700071M16Rik/miR-145a-3p/Pdgfc, 1700071M16Rik/miR-145a-3p/Tox, 1700071M16Rik/miR-145a-3p/Themis2, were finally validated. In addition, increased expression of PVT1, 1700071M16Rik, Tox and Themis2 may be considered as potential diagnostic gene biomarkers in AR.

Conclusion

We speculated that Pvt1/miR-30c-5p/Pdgfc, 1700071M16Rik/miR-145a-3p/Pdgfc, 1700071M16Rik/miR-145a-3p/Tox and 1700071M16Rik/miR-145a-3p/Themis2 interaction pairs may serve as potential biomarkers in AR after HT.

Combining Serum miR-144-3p and miR-652-3p as Potential Biomarkers for the Early Diagnosis and Stratification of Acute Cellular Rejection in Heart Transplantation Patients

BACKGROUND

There is a dire need for specific, noninvasive biomarkers that can accurately detect cardiac acute cellular rejection (ACR) early. Previously, we described miR-144-3p as an excellent candidate for detecting grade ≥2R ACR. Now, we investigated the combination of miR-144-3p with miR-652-3p, other differentially expressed serum miRNA we previously described, to improve diagnostic accuracy mainly in mild rejection to avoid reaching severe stages.

METHODS

We selected miR-652-3p from a preliminary RNA-seq study to be validated by reverse transcription-quantitative polymerase chain reaction on 212 consecutive serum samples from transplantation recipients undergoing routine endomyocardial biopsies to subsequently combine them with miR-144-3p results and investigate their diagnostic capability.

RESULTS

We confirmed the miR-652-3p overexpression (P < 0.0001) and its capability to discriminate between patients with and without ACR of any grade (P < 0.0001). The combined serum levels of miR-144-3p and miR-652-3p were significantly higher in patients with rejection regardless of posttransplantation time (P < 0.0001). This combination resulted in a diagnostic efficacy for 1R (area under the curve = 0.794) and ≥2R (area under the curve = 0.892; P < 0.0001) that was superior to each biomarker alone. Furthermore, it was a strong independent predictor of ACR for 1R (odds ratio of 10.950; P < 0.0001) and ≥2R (odds ratio of 14.289; P < 0.01).

CONCLUSIONS

We demonstrated that an appropriate combination of blood-based biomarkers could exhibit greater efficiency for cardiac rejection diagnosis. The combined detection of abnormal expression of miR-144-3p and miR-652-3p in the serum of ACR patients can improve the diagnostic sensitivity of rejection at an early stage and contribute to increasing the diagnostic accuracy, mainly in the lower rejection grades.

Diagnostic accuracy of brain natriuretic peptide and N-terminal-pro brain natriuretic peptide to detect complications of cardiac transplantation in adults: A systematic review and meta-analysis

BACKGROUND

We aimed to evaluate the utility of BNP and NT-proBNP in identifying adverse recipient outcomes following cardiac transplantation.

METHODS

We searched MEDLINE (Ovid), Embase (Ovid), and the Cochrane Library from inception to February 2023. We included studies reporting associations between BNP or NT-proBNP and adverse outcomes following cardiac transplantation in adults. We calculated standardised mean differences (SMD) with 95% confidence intervals (CI); or confusion matrices with sensitivities and specificities. Where meta-analysis was inappropriate, studies were analysed descriptively.

RESULTS

Thirty-two studies involving 2,297 cardiac transplantation recipients were included. We report no significant association between BNP or NT-proBNP and significant acute cellular rejection of grade 3A or higher (SMD 0.40, 95% CI -0.06-0.86) as defined by the latest 2004 International Society for Heart and Lung Transplantation Guidelines. We also report no strong associations between BNP or NT-proBNP and cardiac allograft vasculopathy or antibody mediated rejection.

CONCLUSION

In isolation, serum BNP and NT-proBNP lack sufficient sensitivity and specificity to reliably predict adverse outcomes following cardiac transplantation.

Amplification of Plasma MicroRNAs for Non-invasive Early Detection of Acute Rejection after Heart Transplantation With Ultrasound-Targeted Microbubble Destruction

OBJECTIVE

Acute rejection (AR) screening has always been the focus of patient management in the first several years after heart transplantation (HT). As potential biomarkers for the non-invasive diagnosis of AR, microRNAs (miRNAs) are limited by their low abundance and complex origin. Ultrasound-targeted microbubble destruction (UTMD) technique could temporarily alter vascular permeability through cavitation. We hypothesized that increasing the permeability of myocardial vessels might enhance the abundance of circulating AR-related miRNAs, thus enabling the non-invasive monitoring of AR.

METHODS

The Evans blue assay was applied to determine efficient UTMD parameters. Blood biochemistry and echocardiographic indicators were used to ensure the safety of the UTMD. AR of the HT model was constructed using Brown-Norway and Lewis rats. Grafted hearts were sonicated with UTMD on postoperative day (POD) 3. The polymerase chain reaction was used to identify upregulated miRNA biomarkers in graft tissues and their relative amounts in the blood.

RESULTS

Amounts of six kinds of plasma miRNA, including miR-142-3p, miR-181a-5p, miR-326-3p, miR-182, miR-155-5p and miR-223-3p, were 10.89 ± 1.36, 13.54 ± 2.15, 9.84 ± 0.70, 8.55 ± 2.00, 12.50 ± 3.96 and 11.02 ± 3.47 times higher in the UTMD group than those in the control group on POD 3. Plasma miRNA abundance in the allograft group without UTMD did not differ from that in the isograft group on POD 3. After FK506 treatment, no miRNAs increased in the plasma after UTMD.

CONCLUSION

UTMD can promote the transfer of AR-related miRNAs from grafted heart tissue to the blood, allowing non-invasive early detection of AR.

Non-invasive detection of cardiac allograft rejection among heart transplant recipients using an electrocardiogram based deep learning model

Aims

Current non-invasive screening methods for cardiac allograft rejection have shown limited discrimination and are yet to be broadly integrated into heart transplant care. Given electrocardiogram (ECG) changes have been reported with severe cardiac allograft rejection, this study aimed to develop a deep-learning model, a form of artificial intelligence, to detect allograft rejection using the 12-lead ECG (AI-ECG).

Methods and results

Heart transplant recipients were identified across three Mayo Clinic sites between 1998 and 2021. Twelve-lead digital ECG data and endomyocardial biopsy results were extracted from medical records. Allograft rejection was defined as moderate or severe acute cellular rejection (ACR) based on International Society for Heart and Lung Transplantation guidelines. The extracted data (7590 unique ECG-biopsy pairs, belonging to 1427 patients) was partitioned into training (80%), validation (10%), and test sets (10%) such that each patient was included in only one partition. Model performance metrics were based on the test set (n = 140 patients; 758 ECG-biopsy pairs). The AI-ECG detected ACR with an area under the receiver operating curve (AUC) of 0.84 [95% confidence interval (CI): 0.78-0.90] and 95% (19/20; 95% CI: 75-100%) sensitivity. A prospective proof-of-concept screening study (n = 56; 97 ECG-biopsy pairs) showed the AI-ECG detected ACR with AUC = 0.78 (95% CI: 0.61-0.96) and 100% (2/2; 95% CI: 16-100%) sensitivity.

Conclusion

An AI-ECG model is effective for detection of moderate-to-severe ACR in heart transplant recipients. Our findings could improve transplant care by providing a rapid, non-invasive, and potentially remote screening option for cardiac allograft function.

A Review of Biomarkers of Cardiac Allograft Rejection: Toward an Integrated Diagnosis of Rejection

Despite major advances in immunosuppression, allograft rejection remains an important complication after heart transplantation, and it is associated with increased morbidity and mortality. The gold standard invasive strategy to monitor and diagnose cardiac allograft rejection, based on the pathologic evaluation of endomyocardial biopsies, suffers from many limitations including the low prevalence of rejection, sample bias, high inter-observer variability, and international working formulations based on arbitrary cut-offs that simplify the landscape of rejection. The development of innovative diagnostic and prognostic strategies—integrating conventional histology, molecular profiling of allograft biopsy, and the discovery of new tissue or circulating biomarkers—is one of the major challenges of translational medicine in solid organ transplantation, and particularly in heart transplantation. Major advances in the field of biomarkers of rejection have paved the way for a paradigm shift in the monitoring and diagnosis of cardiac allograft rejection. We review the recent developments in the field, including non-invasive biomarkers to minimize the number of protocol endomyocardial biopsies and tissue biomarkers as companion tools of pathology to refine the diagnosis of cardiac rejection. Finally, we discuss the potential role of these biomarkers to provide an integrated bio-histomolecular diagnosis of cardiac allograft rejection.

Electron Microscopy Reveals Evidence of Perinuclear Clustering of Mitochondria in Cardiac Biopsy-Proven Allograft Rejection

Acute cellular rejection is a major complication in heart transplantation. We focus on the analysis of new ultrastructural findings in cardiac biopsy rejection based on mitochondrial intracellular organization. This study includes heart transplanted patients from a single center who were referred for endomyocardial biopsies as a scheduled routine screening. Participants were divided into two groups: patients transplanted without allograft rejection (Grade 0R), and patients with biopsy-proven allograft rejection (Grade ≥ 2R). Using electronic microscopy, we detected a significant increase in the volume density of mitochondria (p < 0.0001) and dense bodies (p < 0.01) in the rejection group. The most relevant finding was the presence of local accumulations of mitochondria close to the nuclear envelope, pressing and molding the morphology of this membrane in all rejection samples (100%). We identified this perinuclear clustering of mitochondria phenomenon in a 68 ± 27% of the total cardiac nucleus observed from rejection samples. We did not observe this phenomenon in any non-rejection samples, reflecting excellent sensitivity and specificity. We have identified a specific phenomenon affecting the architecture of the nuclear membrane—perinuclear clustering of mitochondria—in endomyocardial biopsies from patients with cardiac rejection. This ultrastructural approach might complement and improve the diagnosis of rejection.