7Present address: Institute for Advanced Studies, University of Montenegro, Cetinjska 2, 81000 Podgorica, Montenegro
Despite recent advances in diagnosis and treatment, colorectal cancer (CRC) remains the third most common cancer worldwide, and has both a poor prognosis and a high recurrence rate, thus indicating the need for new, sensitive and specific biomarkers. MicroRNAs (miRNAs/miRs) are important regulators of gene expression, which are involved in numerous biological processes implicated in tumorigenesis. The objective of the present study was to investigate the expression of miRNAs in plasma and tissue samples from patients with CRC, and to examine their potential as CRC biomarkers. Using reverse transcription-quantitative PCR, it was revealed that miR-29a, miR-101, miR-125b, miR-146a and miR-155 were dysregulated in the formalin-fixed paraffin-embedded tissues of patients with CRC, compared with the surrounding healthy tissue, and these miRNAs were associated with several pathological features of the tumor. Bioinformatics analysis of overlapping target genes identified AGE-RAGE signaling as a putative joint regulatory pathway. miR-146a was also upregulated in the plasma of patients with CRC, compared with the healthy control group, and had a fair discriminatory power (area under the curve, 0.7006), with 66.7% sensitivity and 77.8% specificity. To the best of our knowledge, this distinct five-miRNA deregulation pattern in tumor tissue, and upregulation of plasma miR-146a, were shown for the first time in patients with CRC; however, studies on larger patient cohorts are warranted to confirm their potential to be used as CRC diagnostic biomarkers.
Colorectal cancer (CRC) is the third most commonly diagnosed cancer globally (10.0%), and the second most important cause of cancer death (9.4%). More than 1.9 million new CRC cases and 935,000 deaths were estimated to occur in 2020 (
Research on microRNAs (miRNAs) as new reliable biomarkers of tumor development and progression is emerging. MiRNAs are short, non-coding RNA sequences, 21–25 nucleotides in length that negatively regulate the expression of protein-coding genes (
In CRC, a current literature review identified over 230 potential candidate miRNAs in various biological fluids, with some level of association to the pathology (
The study protocol was approved by the Ethical Committee of the Clinical Center of Montenegro (approval no. 03/01-11417/1) and by the Committee for Medical Ethics and Bioethics of the Faculty of Medicine of the University of Montenegro (approval no. 3824/4). All the procedures were conducted in accordance with the Declaration of Helsinki and all participants signed an informed consent before any study procedures were performed. All participants completed a standardized questionnaire, in order to obtain demographic (age, gender), and basic health information, including eventual comorbidities and frequency of habits associated with an increased risk for CRC (BMI, hypertension, hyperlipidemia, diabetes mellitus, history of smoking, coffee and alcohol consumption, and physical activity). Peripheral blood samples were also collected from all participants.
CRC patients were recruited at the Center for Digestive Surgery of the Clinical Center of Montenegro, between November 2019 and November 2021. All patients were subjected to standard clinical practice. Peripheral blood sampling was performed during preoperative preparation on 24 patients who were admitted for surgical resection of colon tumors previously diagnosed by colonoscopy. Patients who received preoperative adjuvant therapy, those who have clinically diagnosed hereditary adenomatous polyposis or hereditary non-polyposis CRC, with a previous medical history of malignancy, poorly controlled systemic disease, and/or current acute disease, were not included in the study. In addition, paired CRC and surrounding normal colon tissue samples were obtained from CRC patients during the surgical treatment.
Healthy volunteers were recruited at the Faculty of Medicine, University of Montenegro. We have recruited 34 age- and sex-matched healthy volunteers. Inclusion criteria for the healthy group of participants were negative history of cancer, uncontrolled chronic systemic disease, including inflammatory bowel disease (IBD), and/or current acute disease.
MicroRNAs were extracted from plasma using Qiagen miRNeasy Serum/Plasma Advanced kit (cat. No. 217204, Qiagen, Hilden, Germany) essentially as described in (
The miRNA concentration was determined using Qubit microRNA Assay kit (Q32880, Invitrogen, Thermo Fisher Scientific) on a Qubit 3.0 fluorimeter (Q33216, Invitrogen, Thermo Fisher Scientific, USA). Two µl miRNA from each sample were reversely transcribed to cDNA using TaqMan Advanced miRNA cDNA Synthesis kit (A28007, Applied Biosystems, USA) and analyzed with TaqMan Advanced microRNA Assays (A25576, Applied Biosystems, USA) for miR-29a, miR-101, miR-125b, miR-146a, and miR-155. Context sequences of TaqMan probes were as follows: ACUGAUUUCUUUUGGUGUUCAG for miR-29a; CAGUUAUCACAGUGCUGAUGCU for miR-101; UCCCUGAGACCCUAACUUGUGA for miR-125b; UGAGAACUGAAUUCCAUGGGUU for miR-146a; and UUAAUGCUAAUCGUGAUAGGGGUU for miR-155. RT-qPCR was run on an Applied Biosystems 7300 Real Time PCR system (Applied Biosystems, USA), with the following thermocycling conditions: enzyme activation: 95°C, 20 sec; denaturation: 95°C, 3 sec; annealing: 60°C, 30 sec, for 40 cycles. The expression levels of target miRNAs were normalized by using the mean expression levels of miR-361-5p gene for plasma samples, and miR-186-5p for FFPE tissue samples, selected as the most stable internal control miRNA by the NormFinder algorithm (
Biopsy samples were fixed in 10% buffered formalin and embedded in paraffin. Serial sections, 5 µm thick, were cut using microtome (Leica SM 200R, Austria). After deparaffinization in xylene and hydration in descending order of alcohol, sections were stained with Mayer's hematoxylin and 1% eosin solution, then illuminated and mounted on slides using dibutylphtalate polystyrene xylene (DPX).
Morphological analysis and reporting were conducted by two independent pathologists using CAP protocols (Cancer Reporting Protocols-College of American Pathologists). For each sample tumor site and size, histological type and grade, tumor extent, presence of lymphovascular and perineural invasion, necrosis, mucus production, inflammatory infiltrate density and composition, status of margins, lymph nodes status, and disease stage were estimated. Representative FFPE tissue samples were selected for miRNA and DNA extraction. Representative image of hematoxylin and eosin stained FFPE tissue sample of the patient with CRC is given in
MiRNA purification from FFPE tissues was performed using miRNeasy FFPE kit (cat. no. 217504, Qiagen, Hilden, Germany), according to the manufacturer's instructions. Two to three 10 µm inner sections were aseptically collected in nuclease-free microcentrifuge tube and deparaffinization solution (cat. no. 19093) was used to remove all paraffin. The hematoxylin and eosin-stained slides were evaluated by pathologist who designated control and tumor samples, ensuring no cancer cells were present in the controls (
DNA extraction from the FFPE tissue samples was performed using QIAmp DNA FFPE Tissue kit (cat. No. 56404) from Qiagen. Two 10 µm sections of FFPE tissue samples were cut, treated with deparaffinization solution (cat. no. 19093), and DNA was extracted following the manufacturer's instructions.
Potential targets of five studied miRNAs were predicted by miRTarBase database (
All statistical analyses were performed using GraphPad Prism 9.3.1 (GraphPad Software, San Diego, CA, USA). The results were considered statistically significant when P<0.05. Continuous variables were first tested for normality of distribution by D'Agostino-Pearson and Shapiro-Wilk tests and analyzed with the unpaired t-test or an appropriate non-parametric test (Mann-Whitney). Normally distributed variables of tumor FFPE tissue samples were analyzed with the paired Student's t-test. Categorical variables were analyzed with the Fisher's exact test. Receiver operating characteristic (ROC) curve analysis was performed to evaluate potential diagnostic performance of studied miRNAs. The area under the curve (AUC) was estimated, along with the 95% CI. Correlations between miRNA expression and clinical variables were explored using the Spearman correlation coefficient. Logistic regression analysis was also performed to evaluate the association of the investigated variables with the CRC.
Out of a total of 24 CRC patients who were initially recruited for this prospective study, six were excluded due to postoperative pathohistological diagnosis of adenoma (n=3), ulcerative colitis (n=1), and two due to sample hemolysis (
There were no significant differences in prevalence of either gender. The range of ages of the participants enrolled in our study is given in the
In order to assess their role in the development of CRC, relative expression of five selected miRNAs: miR-29a, miR-101, miR-125b, miR-146a, and miR-155, was analyzed in plasma samples of patients with CRC and healthy individuals. No statistically significant differences were observed between groups for miR-29a, miR-101, miR-125b, and miR-155 (data not shown). However, expression levels of miR-146a were significantly higher (P=0.0402) in the plasma of patients with CRC, compared to healthy individuals, as shown in
miR-146a is one of the most important inflammatory miRNAs, shown to mediate both the innate and adaptive immune response (
The associations between all five investigated miRNAs levels and patient characteristics are presented in the
Only two associations were found to be statistically significant, namely, miR-146a expression was significantly higher in male in comparison to female CRC patients (P=0.0441); and lower levels of miR-101 expression were found in patients with a history of smoking (P=0.0307) (
Clinical characteristics of the CRC group of patients are given in
A majority of patients (89.5%) were TNM stage III; 57.9% had positive nodal status, and tumors were predominantly located in the right colon (68.4%).
Diagnostic performance of the investigated miRNAs for CRC was evaluated by computing AUC values of the ROC curves for each miRNA. The results presented in the
To investigate whether there is any correlation between CRC tissue and plasma levels, we performed an analysis for each individual miRNA, but no significant correlation was found (data not shown). We have also compared miRNA expression levels in the FFPE samples of the healthy surrounding tissue with miRNA expression levels in CRC plasma samples, and we did not find any significant correlation.
Next, we analyzed miRNA expression levels in correlation with clinical and pathological features of patients with CRC (
We found that there is a negative correlation between miR-101 levels in tumor tissue and the lymphovascular invasion (r=−0.4901, P=0.0389). We have also analyzed each individual miRNA in two different groups for all investigated demographic and clinical variables, as shown in the
In order to better understand the consequences of this identified five-miRNA deregulation, we performed a bioinformatic analysis on the genes regulated by miR-29a, miR-101, miR-125b, miR-146a, and miR-155. A total of 174 genes were found to be regulated by at least two out of five studied miRNAs (
The enrichment analysis revealed that the targets of candidate miRNAs were involved in pathways of several different cancers, including pancreatic, bladder, chronic myeloid leukemia, melanoma, and NSCLC, but also in EGFR tyrosine kinase inhibitor resistance and interestingly enough, the AGE-RAGE signaling pathway (
Binding of advanced glycation end products (AGEs) to their receptors (RAGEs) activate several different signaling pathways, such as MAPK, p53, PI3K/Akt/mTOR, JAK-STAT, and NF-κB, involved in the proliferation of cancer cells, angiogenesis, and invasion (
The present pilot study determined the pattern of miRNAs deregulation in CRC patients in Montenegro for the first time, with the aim of contributing new information to the current knowledge of which specific miRNA signature could be used in clinical setting. We have shown that all five of the investigated candidate miRNAs were deregulated in FFPE tissue samples of patients with CRC, compared to the healthy surrounding colonic mucosa (
Our bioinformatic analysis identified the AGE-RAGE signaling pathway as one of the putative jointly affected pathways by all five of the investigated miRNAs. AGEs are predominantly formed as a result of chronic hyperglycemic conditions/diabetes or aging (
miR-146a is one of the most prominent inflammatory miRNAs, with a key modulatory role both in the innate and adaptive immune response (
Serum miR-146a was shown to have a significant diagnostic ability in CRC, as a member of a three-miRNA panel, together with miR-30e-3p, and miR-148a-3p (
miR-29a expression was found to be up-regulated in FFPE tissue samples of the patients with CRC (
We found significantly lower miR-101 expression in FFPE tissue samples of patients with CRC, compared to the normal surrounding colonic mucosa (
miR-125b was found to be upregulated in both CRC tumors and metastatic sites, compared to adjacent normal tissues, and miR-125b overexpression enhanced CRC cells migration and invasion (
miR-155 was found to be over-expressed in CRC (
A major limitation of this study that needs to be considered when interpreting its results is a small sample size, thus a follow-up study on a larger prospective cohort of patients is warranted. In general, many potential miRNA biomarkers are still not utilized in the clinical setting, partially due to inconsistent findings. The discovery and validation of a novel miRNA signature in a specific population could potentially aid in the timely diagnosis of patients at risk. Since the development and progression of CRC is a multi-step process which involves mutations in many genes, future combination biomarkers will better reflect the complexity and heterogeneity of CRC. Further analysis of miRNAs in various CRC stages, and the various targets of selected miRNAs is necessary. Circulating miRNAs could potentially be a novel, noninvasive CRC screening tool, which could be utilized along with fecal occult blood testing and colonoscopy. Analysis of specific miRNAs identified in this study, in combination with other CRC diagnostic biomarkers, such as carcinoembryonic antigen, and carbohydrate antigen 19-9 could further increase their sensitivity and specificity.
In conclusion, our study identified statistically significant up-regulation of circulating miR-146a in patients with CRC in the Montenegrin population for the first time. miR-146a was shown to have the potential to be used as a diagnostic biomarker for CRC. This was further corroborated by the finding that its expression was altered in both FFPE tissues and in plasma of patients with CRC. We have also shown for the first time that the distinct five-miRNA (miR-29a, miR-101, miR-125b, miR-146a, and miR-155) pattern of expression is highly involved in CRC carcinogenesis, contributing to the current understanding of which miRNA signature can be potentially used in a clinical setting. Bioinformatics analysis identified the AGE-RAGE signaling axis as a common potentially deregulated pathway. Better understanding of the interaction between the oncogenic effect of the AGE-RAGE axis and the inflammatory tumor microenvironment, and their regulation, could lead to the development of new cancer prevention and treatment methods.
The authors would like to thank Dr Katarina Popović (University of Montenegro, Faculty of Medicine) for English language editing.
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
MŽ, NP, JR, LV, IRD, AT, NG, and SG conceived the study. MŽ, JR, MR, FM, SG, and AT designed the methodology. MŽ, NP, BV, and IRD recruited patients. MŽ, JR, BV, VT, FV and LV performed formal analysis and data curation. MŽ prepared the original draft and data visualization. All authors reviewed and edited the manuscript. MR, VT, and FV performed project administration. MŽ and JR confirm the authenticity of all the raw data. All authors read and approved the final manuscript.
The study was conducted according to the guidelines of the Declaration of Helsinki and was approved by the Ethical Committee of the Clinical Center of Montenegro (approval no. 03/01-11417/1 on 24.06.2019.) and by the Committee for Medical Ethics and Bioethics of the Faculty of Medicine of the University of Montenegro (approval no. 3824/4 on 13.12.2018.). Written informed consent was obtained from all study subjects.
Written informed consent has been obtained from all the study subjects to publish this paper.
The authors declare that they have no competing interests.
Flow chart of study participant recruitment. Number of screened, excluded and analyzed (A) healthy participants, (B) patients with CRC (with plasma samples) and (C) patients with CRC (with FFPE samples). CRC, colorectal cancer; FFPE, formalin-fixed paraffin-embedded; miRNA, microRNA.
(A) Relative expression and (B) ROC curve of circulatory miR-146a in patients with CRC and healthy control subjects. *P=0.0402. CRC, colorectal cancer; miR, microRNA.
miRNA expression is deregulated in FFPE tissues of CRC patients. Relative expression of (A) miR-29a, (B) miR-125b, (C) miR-146a, (D) miR-155 and (E) miR-101. *P<0.015, **P=0.0068, ***P=0.0007, ****P<0.0001. CRC, colorectal cancer; FFPE, formalin-fixed paraffin-embedded; miR, microRNA.
Protein network encoded by jointly regulated genes. Evidenced in red are the proteins involved in the AGE-RAGE signalling pathway (made with the STRING database). Number of nodes: 174; number of edges: 2,206; average node degree: 25.4; avg. local clustering coefficient: 0.602; expected number of edges: 741; PPI enrichment P-value: <1.0×10−16.
Demographic and clinical characteristics of the study cohorts (plasma samples).
Characteristic | Colon cancer (n=18) | Healthy controls (n=18) | P-value |
---|---|---|---|
Sex | >0.999 | ||
Female (%) | 7 (38.9) | 7 (38.9) | |
Male (%) | 11 (61.1) | 11 (61.1) | |
Age at diagnosis, years | |||
Mean ± SD | 66.89±9.64 | 65.44±8.12 | 0.599 |
Median (range) | 66.0 (55.0-87.0) | 65.0 (55.0-77.0) | |
Mean ± SD BMI, kg/m2 | 26.88±3.67 | 27.17±3.96 | 0.7842 |
Hypertension (%) | 9 ( |
8 (44.4) | >0.999 |
Hyperlipidemia (%) | 2 (11.1) | 7 (38.9) | 0.1212 |
Diabetes mellitus (%) | 3 (16.7) | 3 (16.7) | >0.999 |
Physical activity (%) | 16 (88.9) | 11 (61.1) | 0.1212 |
History of smoking (%) | 10 (55.6) | 10 (55.6) | >0.999 |
Coffee consumption (%) | 0 (0) | 7 (38.9) | 0.0076 |
Alcohol consumption (%) | 5 (27.8) | 9 ( |
0.3053 |
SD, standard deviation; Physical activity, walking ≥30 min at least 5 days per week; History of smoking, current or former smokers; Coffee consumption, consumption of 3 or more cups daily.
P<0.05.
Demographic and clinical characteristics of the study cohort (FFPE samples).
Characteristic | Colon cancer (n=19) |
---|---|
Female (%) | 7 (36.8) |
Male (%) | 12 (63.2) |
Age at diagnosis | |
Mean ± SD | 66.84±9.37 |
Median (range) | 66.0 (55.0-87.0) |
TNM stage | |
I (%) | 0 (0) |
II (%) | 1 (5.3) |
III (%) | 17 (89.5) |
IV (%) | 1 (5.3) |
Nodal status | |
Positive (%) | 11 (57.9) |
Negative (%) | 8 (42.1) |
Tumor location | |
Left (%) | 6 (31.6) |
Right (%) | 13 (68.4) |
Positive (%) | 5 (45.45%) |
Negative (%) | 6 (54.54%) |
Patients with lymph node metastasis.
Diagnostic performance of all investigated miRNAs in CRC tissue samples.
FFPE miRNA | AUC | Cutoff point | Sensitivity, % | Specificity, % |
---|---|---|---|---|
miR-29a | 0.8921 | >1.582 | 84.21 | 89.47 |
miR-101 | 0.8172 | <0.7511 | 73.68 | 73.68 |
miR-125b | 0.7313 | >1.421 | 68.42 | 78.95 |
miR-146a | 0.7535 | >1.683 | 63.16 | 94.74 |
miR-155 | 0.7341 | >1.347 | 73.68 | 89.47 |
AUC, area under the receiver operating characteristic curve.
The most strongly enriched GO processes and KEGG pathways-joint analysis.
A, Biological process (Gene Ontology) | ||||
---|---|---|---|---|
Term or pathway | Description | Count in network | Strength | False discovery rate |
GO:0006211 | 5-methylcytosine catabolic process | 3 of 3 | 2.05 | 0.00019 |
GO:1905460 | Negative regulation of vascular associated smooth muscle cell apoptotic process | 2 of 2 | 2.05 | 0.0044 |
GO:1905075 | Positive regulation of tight junction disassembly | 2 of 2 | 2.05 | 0.0044 |
GO:1904466 | Positive regulation of matrix metallopeptidase secretion | 2 of 2 | 2.05 | 0.0044 |
GO:0035622 | Intrahepatic bile duct development | 2 of 2 | 2.05 | 0.0044 |
GO:0032707 | Negative regulation of interleukin-23 production | 2 of 2 | 2.05 | 0.0044 |
GO:0014740 | Negative regulation of muscle hyperplasia | 2 of 2 | 2.05 | 0.0044 |
GO:0003169 | Coronary vein morphogenesis | 2 of 2 | 2.05 | 0.0044 |
GO:0002384 | Hepatic immune response | 2 of 2 | 2.05 | 0.0044 |
GO:0061419 | Positive regulation of transcription from RNA polymerase II promoter in response to hypoxia | 4 of 6 | 1.87 | 2.15×10−5 |
GO:0004517 | Nitric-oxide synthase activity | 3 of 3 | 2.05 | 0.00062 |
GO:0003886 | DNA (cytosine-5-)-methyltransferase activity | 3 of 3 | 2.05 | 0.00062 |
GO:0070579 | Methylcytosine dioxygenase activity | 3 of 4 | 1.93 | 0.00098 |
GO:0034617 | Tetrahydrobiopterin binding | 3 of 4 | 1.93 | 0.00098 |
GO:0043125 | Erb-3 class receptor binding | 3 of 4 | 1.93 | 0.00098 |
GO:0003958 | NADPH-hemoprotein reductase activity | 3 of 6 | 1.75 | 0.0021 |
GO:003958 | Type III transforming growth factor beta receptor binding | 2 of 4 | 1.75 | 0.0282 |
GO:0070878 | Primary miRNA binding | 4 of 10 | 1.65 | 0.00030 |
GO:0051525 | NFAT protein binding | 2 of 5 | 1.65 | 0.0375 |
GO:0046870 | Cadmium ion binding | 2 of 5 | 1.65 | 0.0375 |
hsa05212 | Pancreatic cancer | 26 of 73 | 1.6 | 1.37×10−29 |
hsa05219 | Bladder cancer | 13 of 41 | 1.55 | 7.98×10−15 |
hsa04933 | AGE-RAGE signaling pathway in diabetic complications | 28 of 98 | 1.51 | 1.37×10−29 |
hsa05220 | Chronic myeloid leukemia | 20 of 75 | 1.48 | 5.34× 0−21 |
hsa05218 | Melanoma | 19 of 72 | 1.47 | 5.88×10−20 |
hsa05223 | Non-small cell lung cancer | 17 of 68 | 1.45 | 1.09×10−17 |
hsa01521 | EGFR tyrosine kinase inhibitorresistance | 19 of 78 | 1.44 | 1.80×10−19 |
hsa05213 | Endometrial cancer | 14 of 57 | 1.44 | 1.22×10−14 |
hsa05214 | Glioma | 17 of 72 | 1.42 | 2.29×10−17 |
hsa05222 | Small cell lung cancer | 21 of 92 | 1.41 | 7.11×10−21 |