Objectives: The number of composite tissue allotransplant procedures is increasing and has gained popularity. As with other transplant procedures, early detection of possible pathologies is as important as clinical follow-up. The present study investigated the correlation between microRNA expression levels and clinical follow-up of individuals undergoing composite tissue transplant.
Materials and Methods: Whole microRNA expression levels were analyzed from peripheral blood mononuclear cells obtained from preoperative and postoperative blood of patients who underwent facial transplant. Analyses were performed using microRNA levels from patients’ preoperative blood samples.
Results: The clinical findings of patients with facial transplant were correlated with individual miRNA expression level changes. The expression of miR-31, the high expression of which has been linked to rejection, was significantly low in our patients. No expression changes were observed in other rejection-related microRNAs. Grade 1 rejection was generally seen in our patients, and these findings are consistent with the degree and frequency of rejection episodes in our cases. In addition, immunosuppression-associated diseases such as squamous cell carcinoma, posttransplant lymphoproliferative disorders, and aspergillosis, which are encountered clinically, were found to correlate with expression changes in microRNAs such as miR-150-5p, miR-21-5p, miR-17-5p, miR-20a-5p, and miR-3607-5p.
Conclusions: Defining the clinical findings and immunosuppression-associated pathologies encountered in composite tissue transplant using biomarkers such as microRNA can play an important role in the improvement of these transplant procedures and in predicting patient morbidity. Therefore, the use of microRNAs may be useful in the clinical follow-up of patients who have received composite tissue allotransplant.
Key words : Aspergillosis, Posttransplant lymphoproliferative disorders, Squamous cell carcinoma
Composite tissue allotransplantations (CTAs) have lately been performed for the purpose of form and function restoration and for improving quality of life in patients who have composite tissue losses due to congenital anomalies or external injuries that impair physical integrity and cause function loss, which do not directly affect vital activities but nevertheless reduce quality of life.1
Because immunological properties of transplanted tissues differ, the severity of the immunological response generated against the transplanted tissue also differs. The immunological response to the transplanted tissue is more severe in some transplants due to their immunological components. However, because transplanted tissues in CTAs are visible, rejection findings can be detected earlier through visual inspection and clinical findings before functional loss occurs. This greatly facilitates the transfer follow-up process.
Despite the advantage of earlier awareness of rejection episodes, CTA entails all of the other complications of solid-organ transplant procedures. Side effects from immunosuppressant agents used in organ transplant, such as infections (especially fungal and viral) and cancer, are also seen in CTAs. These complications are difficult to treat and generally fatal. Therefore, it is of great importance to diagnose these side effects early before clinical signs, loss of function, and progression.
Although many solid-organ transplants are today successfully performed, the number of effective biomarkers permitting efficient monitoring of pretransplant and posttransplant prognosis is limited. Biomarker studies are widely used in the transplantation field, particularly for the purpose of revealing molecular changes using noninvasive methods, without such changes being reflected in the clinical manifestation. Such molecular changes may be related to the fate of the allograft or responses to treatment. Time after transplant is a significant factor in the examination of biomarkers that can be used. Allograft damage occurs over time, and changes are observed in biomarkers after transplant.2
There are also no known specific biomarkers for CTAs, which have a more limited global application than solid-organ transplants. Biomarker studies are increasingly integrating information from multiple platforms, such as genotype analyses of single-nucleotide polymorphisms, epigenetic studies, and analyses of mRNA and microRNA (miRNA), as well as protein, peptide, antibody, and metabolite profiling.2-7
MicroRNAs are small regulator RNA molecules that are coded from highly protected DNA regions and are not translated. These molecules bond to the mRNAs through targets and enable gene expression control through translational suppression or mRNA destruction.
MicroRNAs are being examined as potential biomarkers for the diagnosis and prognosis of diseases and may play a role in cellular events, such as the cell cycle, immune response, and apoptosis.8 They also regulate inflammation, T- and B-cell differentiation, and signal mechanisms required for immune responses. Because of these characteristics, they may be effective in organ rejection or tolerance development. Numerous studies have reported miRNA expression profiles in organ transplant patients,9-11 including examining their potential target mRNAs, and posttransplant regulations have been demonstrated.
However, studies of miRNAs in terms of CTAs are limited12 and have mainly involved animal studies, with scarce details of their clinical implications. In this study, our aim was to correlate the clinical findings of patients who received face transplants in our clinic with miRNA analyses. Ours is the first study in the literature to investigate miRNA profile changes in patients with face CTAs. In addition, there have been no cohort studies, and the present research will occupy an important place in the literature in terms of analyzing miRNA changes versus each patient’s preoperative values.
Materials and Methods
Face transplant recipients were recruited from the Akdeniz University Medical School Department of Plastic, Reconstructive, and Aesthetic Surgery (Turkey) and provided written informed consent. The study was approved by the local ethical committee (Akdeniz University Medical School, Clinical Research Ethics Committee). The study included 3 patients who had undergone face transplant procedures at the Akdeniz University Medical School Hospital Department of Plastic Surgery between July and December 2013 (Table 1, Figure 1).13,14
Blood samples were collected from patients once during the preoperative period and at 4 different times in the postoperative period (at day 3, week 3, month 3, and month 6 postoperatively).
Peripheral blood mononuclear cell isolation from blood
Blood samples in heparin-containing vacutainers were used for peripheral blood mononuclear cell isolation. Approximately 5 mL of blood, diluted at a ratio of 1:1 with 1× phosphate buffered saline (PBS) (137 mM NaCl [Merck], 2.7 mM KCl [Sigma], 10 mM Na2HPO4.2H2O [Merck], 1.8 mM KH2PO4 [Merck]), was slowly released onto 3 mL Biocoll separating solution (number 1077, Biochrom AG) with a Pasteur pipette. The mixture was centrifuged for 30 minutes at 1600 revolutions/min (rpm) at 25 °C. Blood cells separated into layers under the effects of the Biocoll solution, which created a density gradient. Mononuclear cells in the nebulous layer were picked up using a glass Pasteur pipette and transferred to another tube. Sterile 1× PBS was added for a total volume 10 mL, and the content was mixed by turning it upside down. The mixture was then centrifuged for 10 minutes at 2000 rpm at 25 °C. The pellet was dissolved with 1× PBS and made up to 10 mL. The pellet was dissolved by pipetting 350 µL of RLT buffer solution (miRNeasy Mini Kit, Qiagen) and stored at -80 °C until used for miRNA isolation.
MicroRNA isolation from lymphocytes
MicroRNA isolation was performed from peripheral blood mononuclear cells using a miRNeasy Mini Kit (number 217004, Qiagen) according to the manufacturer’s specifications.
MicroRNA expression profiling with real-time polymerase chain reaction
Briefly, 2 µL RNA (from 20 µL total eluted volume) was reversed-transcribed using HiSpec buffer with a miScriptII reverse transcriptase kit (Qiagen). A whole miRNome preamplification step was required before performing the quantitative polymerase chain reaction (qPCR) arrays. MicroRNA profiling with the human miRnome miScript miRNA qPCR arrays (version 16, no. 1066 miRNAs, Qiagen) and subsequent data analyses were performed according to the manufacturer’s instructions. A real-time PCR reaction was then performed using a miScript SYBR green PCR kit (number 218075, Qiagen) according to the manufacturer’s specifications.
From miRBase version 16 (miRBase Release 16, www.mirbase.org), 1008 miRNAs have been defined. The miRNome miScript miRNA PCR array (Qiagen) consists of Rotor-Disc 100, each of which contains primers specific to the defined miRNAs. The spike-in controls and the target miRNAs were analyzed in parallel for each sample. All samples were assayed in triplicate.
Statistical analyses and assessment
With the use of real-time PCR, threshold cycle (CT) values were calculated at a threshold value of 0.05. The CT values were uploaded to http://pcrdata analysis.sabiosciences.com/mirna, which utilizes the 2-ΔΔCt method for the calculation of miRNA expression levels and statistical analyses. Normalization (ΔCT) was performed by subtracting the CT values for reference genes from the CT values calculated for miRNAs. Normalized gene expression was calculated using the 2-ΔCT formula. Ratios of the normalized gene expressions of postoperative and preoperative results yielded the (2-ΔΔCT) multiple variances. These values were calculated using the following formulas:
ΔCT = CT (target gene) – CT (reference gene) and 2-ΔΔCT = 2-ΔCT (post-op)/2-ΔCT (preoperative).
Results from multiple variant analyses higher than 1 provide the coefficient of increase in the expression. For results with values lower than 1, the coefficient of increase in the expression was calculated using the following formula: coefficient of increase in the expression = -1/multiple variance value. MicroRNAs with an adjusted fold change above 2 or below -2 were selected as significant.
Because of differences in postoperative procedures in patients with face transplant, statistical assessments were performed for each individual. Although the number of samples obtained from the 3 face transplant operations included in the study was not sufficient to allow assessment at the P value limit within the scope of statistical methodology, it may be possible that the results could be assessed as a case series recommended for a rarely seen patient group.
We used Venn diagrams to investigate the presence of common or patient-specific miRNA (https://bioinfogp.cnb.csic.es/tools/venny/index.html).
Common up- and down-regulated miRNAs shown in all 3 patients
In the first step in our study, we aimed to detect miRNA expression levels and compare preoperative and postoperative miRNA variations in the 3 patients. Individual examination of the miRNA analyses revealed that the number of down-regulated miRNAs was lower than the number of up-regulated miRNAs (Figure 2). We then compared the miRNA analysis results from the 3 patients with VENNY (https://bioinfogp.cnb.csic.es/tools/venny/ index.html), and 1 common down-regulated miRNA and one common up-regulated miRNA were detected. We found miR-31 to be down-regulated in common for all 3 patients. Although no miRNA down-regulation was observed specifically for patient 1, two miRNAs (hsa-miR-150 and hsa-miR-3607-5p) down-regulation specific to patient 2 and two miRNAs (hsa-miR-451 and hsa-miR-455-3p) specific to patient 3 were detected (Figure 3). In addition, examination of the data obtained showed that some miRNAs were down-regulated specifically in some patients. For example, down-regulation of miR150 and miR3607 specific to patient 2 was observed.
In terms of the up-regulated miRNAs, the situation was a little more complicated. Although patient 1 exhibited 33 specific miRNA up-regulations, patient 2 exhibited 117 and patient 3 exhibited 44 miRNAs. Sixty miRNAs exhibited common up-regulation in patients 1 and 2, whereas 7 miRNAs exhibited common up-regulation in patients 1 and 3. In addition, 8 miRNAs exhibited common up-regulation specifically for patients 2 and 3. We found that miR-501 was up-regulated in common in all 3 patients (Figure 4).
Although postoperative expression changed on day 3, miR-31 and miR-501 became common in week 3
We found that miR-31 exhibited a down-regulation pattern from the postoperative day 3 onward in all 3 patients. Although the change in expression levels on day 3 in patient 1 was approximately -462.5, it gradually returned to its average levels (Figure 5).
Likewise, in patient 3, although the level of miR-501 on postoperative day 3 was higher than in the other 2 patients, it decreased to the average value of the other 2 patients in week 3. In addition, in patient 2, although a negative pattern appeared in miR-501 expression level changes at month 3, this was up-regulated again at month 6 (Figure 6).
Analysis of microRNAs that were down-regulated specifically for patient 2 revealed that miR-150 expression fluctuates in a time-dependent manner
When only miR-150 level changes were examined in patient 2, on postoperative day 3, expression fold change (compared with preoperative level) was -10.2556, reaching -4.428 on week 3 (Figure 7). Although the greatest change from preoperative levels (expression fold change -16.4498) was observed in month 3, values returned to -4.7022 levels in month 6.
Another miRNA that was down-regulated only in patient 2, similarly to miR-150, was miR-3607-5p. Although this did not exhibit a marked time-dependent fluctuation, in contrast to miR-150, fold change in expression was approximately -1.7 compared with the preoperative level of miR-3607 (Figure 8).
Relationship between posttransplant lymphoproliferative disorders (B-cell lymphoma) and up-regulated miRNAs in patient 2
We generated a Venn diagram using the datasets of validated genes related to posttransplant lymphoproliferative disorders (PTLD), such as B-cell lymphoma, on the miRWALk site. When we compared against validated PTLD-related miRNAs and miRNAs seen in patient 2, we encountered 3 specific miRNAs: miR-21-5p, miR-17-5p, and miR-20a-5p (Figure 9).
The miR-21-5p level appeared to be 2.5169 times up-regulated compared with the preoperative level on day 3. Although a change of 3.9 was observed at week 3, a decrease in expression of -1.0353 occurred in month 3. This downward trend was limited to month 3, and the month 6 level was 3.9 times up-regulated versus that shown preoperatively (Figure 10).
The miR-17-5p and miR-20a-5p expression fold changes followed a similar pattern. Although the expression levels at day 3 and week 3 were high, levels at months 3 and 6 decreased slightly compared with other time points (Figure 10).
Composite tissue allotransplantation is not a life-saving procedure but is important for improving quality of life. It has gained attention worldwide, and the number of operations performed has increased considerably.
Composite tissue allotransplant differs from solid-organ transplant because it involves heterogeneous tissue content such as skin, muscle, vascular, nerve, bone, and bone marrow and therefore has high immunogenicity. Despite this difference, CTA has complications similar to those seen in solid-organ transplants. These complications can be grouped immunologically and depend on the immunosuppressive agents used. Immunologically, the main complications are rejection episodes of the transplanted organ. Likewise, it is known to increase susceptibility to infections and have increased risk of malignancy due to immunosuppressive treatments. The immune system plays a critical role in transplant, and, similar to that shown in other organ transplants, immune-mediated rejection of CTA may occur.1
Biomarkers are needed to ensure effective monitoring of prognosis after transplant. For transplant patients, diagnosing complications that may occur without any clinical symptoms and starting treatment immediately thereafter are highly important. Numerous biomarkers for diagnosing graft rejection have been proposed. However, whether these biomarkers are able to accurately monitor antidonor immune status or simply diagnose a temporary condition unrelated to the rejection potential is unclear since only a few have been externally validated. Furthermore, good monitoring tools should help predict outcomes, such as allograft function and survival, rather than simply diagnose allograft rejection.3,4,7,15
In this context, the number of studies on miRNAs as biomarkers for early diagnosis is growing, and numerous studies have investigated the use of miRNA for early diagnosis of complications in organ transplant.16-18 However, these studies also have their limitations. Generally, research has involved groups with and without complications. This means that some individual-based changes may be overlooked. In our study, each patient was evaluated both individually and within the group using preoperative blood. This adds particular significance to our results. In addition, it is also possible to overlook changes occurring during complications, since other studies have investigated samples taken when clinical findings are observed. In our study, blood collected at regular intervals (regardless of whether or not any clinical finding was present) was associated with subsequent clinical findings. This permitted a more accurate analysis of the association between the complication development process and the biomarkers.
MicroRNA studies performed with CTAs have generally involved experimental animals.12,19 Studies have shown that miR-146a, miR-155, and miR-182 are related to acute rejection episodes in limb transplant.12-19 In the present study, no change was observed in terms of miRNAs. There may be various reasons for this. First, although grade 1 and grade 2 rejections were observed according to the BANFF criteria during follow-up of our patients, acute rejection episodes were not observed during our study period (Table 1). Another possible reason is that previous studies were conducted in animals, and humans may differ from the miRNA biogenesis seen in that research. Additionally, tacrolimus was administered as an immunosuppressant regimen for the first 7 days in animal studies, and rejection-related miRNA levels were observed on days 10 to 14. Because the immunosuppressant regimen for our patients has more content (antithymocyte globulin, mycophenolate mofetil, etc) than those used in animal studies, the formation of biogenesis in rejection episodes may be more easily suppressed. Rejection episodes have been predominantly grade 2 and grade 3 according to the BANFF criteria at skin biopsies in previous comparable studies. In our study, the highest rejection was grade 2. We therefore may not have seen the change in these miRNAs. Finally, limb and face transplants may differ in the their immunological responses.
When common changes were investigated, miR-31 exhibited a down-regulation pattern compared with preoperative blood levels in all 3 patients. These findings differ significantly from the previous literature. One cohort study involving heart transplant recipients reported increased miR-31 expression in the group exhibiting T-cell-mediated rejection and antibody-mediated rejection compared with a group without rejection.20 The absence of rejection episodes in our patients is consistent with this previously reported low miR-31 level. Therefore, miR-31 may be also useful as a rejection marker in CTAs.
Similarly, miR-501 levels increased in all 3 patients compared with preoperative values. Zheng and associates21 identified Myd88 and cFos as target genes for miR-501. Downregulation of miR-501 may cause increased Myd88 and cFos expression. In addition, increased cFos expression has been shown to be correlated with the presence of chronic rejection in facial transplants.22 We observed an increase in miR-501 expression in our patients, and thus cFos expression should therefore decrease. These data are consistent with the absence of chronic rejection in our clinical findings. Similarly, high Myd88 expression has been reported in kidney patients with antibody-mediated rejection.23 Similarly to cFos, it may be concluded that high expression of miR-501 may be related to low expression of Myd88, and this relationship is consistent with the absence of rejection in our clinical findings.
miR-150-5p, a down-regulation miRNA specific to patient 2, has been associated with squamous cell carcinoma (SCC). Yokobori and associates24 showed a relationship between miR-150-5p and esophageal SCC, whereas Kolenda and associates25 observed an association with head and neck SCC. Another study reported that miR-150-5p exhibited antitumor characteristics in SCC.26 In contrast to other patients, patient 2 (Table 1) exhibited decreased expression of miR-150 postoperatively, suggesting that down-regulation of miR-150 may be a predisposing factor for SCC in our patients. Consistent with these results, monitoring of miR-150-5p expression levels may be important for early diagnosis of SCC complications developing after transplant.
One important finding involving patient 2 is related to PTLDs. miR-21-5p, miR-17-5p, and miR-20a-5p expressions increased compared with the patient’s preoperative levels, and these 3 miRNAs have already been associated with B-cell lymphoma according to miRWALK database. These findings differ from those of the other 2 patients. Our analyses showed that the expression fold change in miR-21-5p was particularly higher than that shown in the other 2 miRNAs. Examination of the relationship between miRNA and cancer has shown that dysregulation of miR-21 promotes lymph node and distant metastases, as well as invasion of blood vessels when overexpressed.27 miR-21 can also down-regulate the Spry2 gene,28 and this downregulation/loss of function has been reported to result in hyperactivated MAPK-ERK signaling and increased B-cell proliferation.29 Therefore, as invalidated on the miRWALK site, miR-21 expression change is closely related to PTLD, and the fact that no change in this miRNA was observed in the other 2 patients suggests that it can be used as a biomarker to monitor posttransplant complications. An association has also been shown between miR-21-5p expression changes and development of laryngeal SCC.30 miR-21-5p follow-up may therefore be clinically important for early diagnosis and follow-up of malignancy, one of the complications of immunosuppressive agents used posttransplant.
The 4 miRNAs described (miR-150-5p, miR-21-5p, miR-17-5p, and miR-20a-5p) changed only in patient 2, with no changes detected in patients 1 and 3. In addition, we observed no evidence of malignancy secondary to immunosuppression treatment during the 7-year follow-up of patients 1 and 3 (Table 1). These data reinforce the hypothesis of a link between these 4 miRNAs and immunosuppressive therapy-associated cancer formation.
miR-3607-5p, which was down-regulated only in patient 2, could not be associated with a direct symptom when examined in the databases. However, detailed examination of the data validated from the miRWALK database showed that it is associated with the TNFRSF1B gene (according to miRWALK analysis, TNFRS1B appears to be a putative target of miR-3607-5p). TNFRSF1B has been shown to be associated with invasive pulmonary aspergillosis treated with chemotherapeutics.31,32 In light of these findings, the resistant renal aspergillosis seen in our patient may be related to this gene and miRNA, and more detailed molecular studies are needed for definitive confirmation of this relationship. The fact that no clinically opportunistic infection was encountered in our 2 patients who did not exhibit this miRNA change after 7 years of follow-up strengthens the possibility of a link between the miRNA concerned and opportunistic infection aspergillosis (Table 1). This observation may thus be useful for early diagnosis and treatment of aspergillosis, one of the most important mortal complications of both chemotherapeutics and immunosuppressive treatments.
Differently expressed miRNAs were detected in preoperative and postoperative samples from patients with CTA. Although several studies have shown a clear agreement between miRNA levels in samples in different states after transplant,33-35 no other studies have compared the miRNA expression profiles using preoperative versus postoperative samples. Our results suggest that miRNA expression profiles may be of diagnostic value and may be useful in the monitoring of early diagnosis of progression in posttransplant samples. Further studies with larger patient numbers are needed to determine the miRNA profiles in preoperative and postoperative samples to identify predictive biomarkers in CTA.
DOI : 10.6002/ect.2020.0177
From the 1Department of Plastic, Reconstructive, and Aesthetic Surgery, Akdeniz University School of Medicine, Antalya, Turkey; the 2Department of Molecular Biology and Genetics, Konya Food and Agriculture University, Konya, Turkey; and the 3Department of Medical Biology and Genetics, Akdeniz University School of Medicine, Antalya, Turkey
Acknowledgements: This study was supported by the Akdeniz University Scientific Research Project Coordination Unit (Grant No. 2014.01.0103.014). Experiments were carried out at the Akdeniz University Health Sciences Research and Application Center and ATQ Biotechnology Laboratory. We particularly thank Dr. Bala Gur Dedeoglu for her help with the bioinformatics analysis. Linguistic and grammatical editing of this publication was made by Carl Nino Rossini. The authors have no further potential conflicts of interest to disclose.
Orchid numbers are listed. M. G. Ertosun: 0000-0002-2557-7346; Ö. Özkan: 0000-0001-6744-9193; E. Çelen: 0000-0001-8606-4424; Ö. Özkan: 0000-0002-9031-5596; B. Yoldaş: 0000-0002-9491-3075.
MGE, OzO, EÇ, OmO, and BY participated in research design; MGE, BY, OzO, and OmO participated in the writing of the paper; MGE, BY, and EÇ participated in the performance of the research; MGE, BY, OzO, OmO, and EÇ participated in data analysis.
Corresponding author: Burçak Yoldaş, Department of Medical Biology and Genetics, Akdeniz University School of Medicine, Antalya, Turkey
Table 1. Details of the 3 Study Patients
Figure 1. Pictures of Patients in Specified Periods
Figure 2. List of Up-regulated and Down-regulated MicroRNAs Specific to Patients
Figure 3. Venn Diagram of MicroRNAs Showing Specific and Common Down-Regulation in the 3 Patients
Figure 4. Venn Diagram of MicroRNAs Showing Specific and Common Up-Regulation in the 3 Patients
Figure 5. Expression Fold Changes of miR-31-5p in the 3 Patients Compared With Preoperative Expression Levels
Figure 6. Expression Fold Changes of miR-501-5p in the 3 Patients Compared With Preoperative Expression Levels
Figure 7. Expression Fold Changes in miR-150-5p, Which Varied Specifically for Patient 2 Compared With Preoperative Level
Figure 8. Expression Fold Changes in miR-3607-5p, Which Varied Specifically for Patient 2 Compared With Preoperative Expression Level
Figure 9. A Venn Diagram Was Used to Visualize the Relationship Between Posttransplant Lymphoproliferative Disorders (B-Cell Lymphomas) on the miRWALK
Site and miRNAs With Change Specific to Patient 2
Figure 10. Expression Fold Changes in the 3 MicroRNAs Associated With Posttransplant Lymphoproliferative Disorders