Abstract
Background
Gastric cancer (GC) is regarded as the most prevalent malignancy with the high mortality rate, worldwide. However, gastroscopy, a biopsy of suspected sample, and detecting CEA, CA19-9, and CA72-4 are presently used, but these diagnostic approaches have several limitations. Recently, microRNAs as the most important member of noncoding RNAs (ncRNAs) have received attention; recent evidence demonstrates that they can be used as the promising candidate biomarkers for GC diagnosis. We aimed to investigate the association between the microRNA-29a, -101, and -103 expression and autotaxin (ATX) and lysophosphatidic acid receptor 2 (LPA2) expression in GC patients. Material and Methods. The present study was conducted on 40 paired samples of primary GC tissue and adjacent noncancerous tissue. The gene expression levels of miR-101, -103, -29, ATX, and LPA2 were analyzed by quantitative reverse-transcription PCR (qRT-PCR). Besides, the protein levels of ATX and LPA2 were evaluated using western blot.
Results
The expression levels of miR-29 and miR-101 were significantly lower (p value < 0.0001), but the miR-103 and LPA2 were significantly higher in gastric tumor samples compared to the corresponding nontumor tissues (p value < 0.0001). Moreover, the diagnostic accuracy of miRs to discrimine the GC patients from noncancerous controls was reliable (miR-101, sensitivity: 82.5% and specificity: 85%; miR-103, sensitivity: 72.5% and specificity: 90%; miR-29, sensitivity: 77.5% and specificity: 70%).
Conclusion
It seems that determining the expression level of miR-101, -103, and -29, as the novel diagnostic biomarkers, has diagnostic value to distinguish GC patients from healthy individuals.
1. Introduction
Gastric cancer (GC) is a heterogeneous disease. It is known as the fourth most prevalent cancer in men and the fifth in women; it has become the second leading cause of cancer-related death worldwide [1, 2]. Recently, it was found that the GC incidence in the western Asia countries is high. In Iran, GC has an annual incidence of 7300, which is the first cause of cancer-related death in both genders. Also, the 5-year survival rate is reported to be less than 25% [3]. GC is only diagnosed in the early stages in less than 10% of cases, so that late diagnosis may lead to disease progression and reduced survival rate. The high mortality and morbidity rates are due to the late diagnosis, unfavorable prognosis, and resistance to treatment [4–6].
Gastroscopy is considered as the golden standard method for GC diagnosis, but the false-negative rate results require looking for other strategies [7–9]. Nowadays, diverse molecules have been evaluated as promising biomarkers in GC patients. For instance, carcinoembryonic antigen (CEA) and cancer antigen 19-9 (CA19-9) are introduced as diagnostic biomarkers, which in turn are used for GC screening; they have low sensitivity, especially at the early stages [10–12]. Hence, the identification of a high sensitive noninvasive method is necessary.
MicroRNAs (miRNAs), as the most famous noncoding RNAs (ncRNAs), are implicated in different biological events. These multitasking molecules are epigenetics modulators, which regulate gene expression at the posttranscriptional levels [13–15]. Recently, compelling evidence introduced miRNAs as new tools to diagnosis different cancers including breast, lung, colorectal, esophageal, and GC at the early stage [16–18]. More importantly, miRNAs are detectable in different biological body fluids, including serum, urine, saliva, CSF, and semen; they are resistant to nucleolytic degradation and are stable against environmental conditions such as freeze and thaw [19, 20]. Hence, these small molecules can be regarded as noninvasive diagnostic biomarkers at the early stage of various cancers, mainly GC.
It was demonstrated that the circulating miRNA-17 and miRNA-25 were remarkably elevated in the serum sample of GC patients compared to the healthy individuals; this finding suggests the cited miRNAs as the diagnostic biomarkers for the early detection of GC [21].
Lysophosphatidic acid (LPA) as a simple lipid consists of an acyl chain of a glycerol backbone; it activates six G-coupled protein receptors (LPA1–6) at least, inducing various signaling pathways [22]. There is evidence that LPA2 is involved in proliferation, apoptosis, drug resistance, metastasis, and the invasion of numerous cancer cells, as well as expression increment in different tumor tissues, including breast, liver, gastric, and colorectal cancers [23–26].
LPA is generated by the autotoxin (ATX) hydrolysis of lysophosphatidylcholine. ATX is an important extracellular lysophospholipase D enzyme that is overexpressed in the renal cell carcinoma, breast and ovarian cancer, and bladder carcinoma [27, 28]. There is increasing data, showing miRNAs regulate ATX and LPA expression [29, 30]. It has been reported that miR-101-3p suppresses ATX expression; also, an inverse correlation was found between ATX and miR-101-3p levels in U87 (astrocytoma cell line) and HCT116 (colorectal carcinoma cell line) cancer cells [31]. Furthermore, it was illustrated that the ATX signaling axis was reduced in chronic obstructive pulmonary disease (COPD) patients. This reduction corresponded to an increase in miR-29 family members [32]. Respecting the crucial roles of ATX and LPA2 in cancer progression, evaluating specific miRNAs, which control ATX and LPA2 expression, can be helpful in the development of novel therapeutic strategies for GC patients.
The present study is aimed at investigating the serum levels of miRNA-101, -103, and -29a in GC patients, their correlation with clinicopathological characteristics, and ATX and LPA2 expression; it may help to find a new strategy in the diagnosis and treatment of GC patients.
2. Material and Methods
2.1. Study Population
Forty paired samples of primary GC tissue and adjacent noncancerous tissue (>3 cm from the tumor tissue) were collected from patients; they had been recruited during April 2019-July 2020 at the Iran National Tumor Bank, Cancer Institute, Imam Khomeini Hospital in Tehran, Iran. GC diagnosis was approved based on the clinical examination and histopathology tests conducted by an expert pathologist.
Exclusion criteria of the present study were as follows: patients with prior history of other malignancies, infection diseases, coagulation disorders, mental illness, or psychosis and those who had undergone chemotherapy, radiotherapy, and targeted therapy. All collected tissues, including GC and adjacent noncancerous tissues after removal from patients' bodies, were frozen and stored at -70 in liquid nitrogen until the final analysis. Also, clinicopathological characteristics of all patients were documented from the clinical and pathological records (Table 1). This study was confirmed by the Ethics Committee at Tehran University of Medical Sciences (IR.TUMS.MEDICINE.REC.1399.1087). All patients provided written informed consent through the Iran National Tumor bank.
Table 1.
Characteristics of included GC patients.
| Clinical parameters | N (%) | |
|---|---|---|
| Gender | Male | 34 (85) |
| Female | 6 (15) | |
| Site of primary | Cardian | 5 (12.5) |
| Antrum | 9 (22.5) | |
| Body | 26 (65) | |
| Necrosis invasion | Yes | 7 (16.6) |
| No | 20 (50) | |
| Unknown | 13 (32.4) | |
| Vascular invasion | Yes | 22 (55) |
| No | 17 (42.4) | |
| Unknown | 1 (2.6) | |
| Perineural invasion | Yes | 19 (47.6) |
| No | 19 (47.6) | |
| Unknown | 2 (4.8) | |
| Tumor size | <5 | 19 (47.6) |
| ≥5 | 21 (52.4) | |
| Histological grading | I + II | 22 (55) |
| III + IV + V | 18 (45) | |
| TNM staging | I + II | 19 (47.5) |
| III + IV | 21 (52.5) | |
| Pathological N | N0 | 15 (37.5) |
| N1 | 17 (42.5) | |
| N2 | 7 (17.5) | |
| N3 | 1 (2.5) | |
| Pathological M | M0 | 37 (92.5) |
| M1 | 3 (7.5) | |
| Pathological T | T1 + T2 | 15 (37.5) |
| T3 + T4 | 25 (62.5) | |
| Family history | Yes | 13 (32.5) |
| No | 27 (67.5) | |
2.2. RNA Extraction and cDNA Synthesis
Total RNA from tissues was extracted with Total RNA Purification Kit (Norgen Biotek, Canada) following the manufacturer's protocol. The quality and quantity of each isolated RNA were determined by OD260/280 using a NanoDrop spectrophotometer (Thermo Fisher Scientific). Afterward, for the cDNA synthesis of miRNA-101, -103, and -29a, purified RNA samples were polyadenylated by poly (A) polymerase; then, they were reverse transcribed to cDNA using a mixture of oligo (dT) adaptor provided in the kit (microScript microRNA cDNA Synthesis Kit, Norgen Biotek, Canada). Besides, cDNA synthesis of LPA2 and ATX was done by using 2 μg of total RNA and 1 μL of random hexamers as well as oligo (dT), 5× first-strand buffer, 1 μL dNTPs, and 0.5 μL RNasin and M-MLV for each sample.
2.3. Quantitative Reverse-Transcription PCR (qRT-PCR)
qRT-PCR was done using SYBR Premix Ex Taq II (Takara, Dalian, Liaoning, China) to detect the miRNA-101, -103, and -29a, ATX, and LRP2 expression as target genes; the β-actin was used as housekeeping gene for normalization. The real-time PCR cycler RotorGene Q (QIAGEN GmbH, Hilden, Germany) was used to perform the reactions. All reactions were performed in triplicate. Furthermore, the relative expression of miRNA-101, -103, -29a, ATX, and LRP2 primary GC tissue and adjacent noncancerous tissue was evaluated using the comparative cycle threshold (Ct) (2-ΔΔCt) method. The detailed sequences of primers for amplifying miRNA-101, -103, and -29a, ATX, and LRP2 have been presented in Table I of the supplementary file I.
2.4. Western Blot Analysis
Total protein was extracted from homogenized GC and adjacent noncancerous tissues; it was done using modified radioimmunoprecipitation (RIPA) buffer. Then, equal amounts of proteins were resolved by 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and transferred onto a PVDF membrane. Afterward, membranes were incubated in 5% nonfat milk or bovine serum albumin (BSA) for 2 hours at room temperature and then incubated for 24 hours at 4C° with LPA2, ATX, and GAPDH primary antibodies. Next, they were exposed to the secondary antibody for 1 hour. Finally, labeled proteins were visualized using enhanced chemiluminescent substrate (ECL, Amersham). The bands intensity was assessed by densitometry via the ImageJ software.
3. Results
3.1. Evaluation of miR-101, -103, and -29 Expression in GC Tissues and Adjacent Nonneoplastic Tissues
As illustrated in Figure 1, the RT-qPCR findings demonstrated that the expression levels of miR-29 and miR-101 were significantly lower in GC specimens in comparison to the adjacent noncancerous tissues (p value < 0.0001). However, the miR-103 was overexpressed in gastric tumor samples compared to the corresponding nontumor tissues (p value < 0.0001) (Figure 1).
Figure 1.
Expression levels of miR-29 (a), miR-101 (b), and miR-103 (c) in GC tissues relative to the adjacent noncancerous tissues.
3.2. Comparison of ATX and LPA2 Expression in GC and Adjacent Nonneoplastic Tissues
The ATX and LPA2 expression was measured in the GC and noncancerous tissues. As presented in Figure 2, there was no any significant changes in the expression levels of ATX in GC tissues in comparison to the noncancerous tissues (p value = 0.2412). We observed that LPA2 expression was significantly higher in the GC samples (p value < 0.0001) (Figure 2).
Figure 2.
Expression levels of ATX (a) and LPA2 (b) in GC tissues relative to the adjacent noncancerous tissues.
3.3. Determination the ATX and LPA2 Protein Expression of GC and Adjacent Nonneoplastic Tissues
The protein expression levels of ATX were significantly higher in GC tissues (p value < 0.0002). Similarly, our data revealed a remarkable increase in protein levels of LPA2 in GC specimens compared to the noncancerous controls (p value < 0.0001) (Figure 3).
Figure 3.
Protein levels of ATX (a) and LPA2 (b) in GC tissues relative to the adjacent noncancerous tissues.
3.4. Correlation between the Gene Expression Levels of miRs, ATX, and LPA2 with Clinicopathological Properties
We next assessed the correlation of miR-103, miR-29, miR-101, ATX, and LPA2 expression with clinicopathological properties, including sex, site of primary, necrosis presence, vascular invasion, perineural invasion, TNM staging, tumor size, pathological grade, and family history in GC tissues. According to the findings presented in Table 2, there was no significant correlation between the expression of miRs, ATX, and LPA2 with none of the clinicopathological characterizations.
Table 2.
Comparison of diagnostic accuracy of microRNAs by ROC analysis for discrimination of the GC tissues of patients than adjacent noncancerous tissues.
| MicroRNAs | AUC (CI) | Sensitivity (%) | Specificity (%) | p value |
|---|---|---|---|---|
| miR-101 | 0.849 (0.755-0.942) | 82.5 | 85 | <0.001 |
| miR-29 | 0.834 (0.740-0.927) | 72.5 | 90 | <0.001 |
| miR-103 | 0.819 (0.726-0.912) | 77.5 | 70 | <0.001 |
AUC: area under the curve; CI: confidence interval.
3.5. Assessment of miR-101, -103, and -29 as Promising Candidate Biomarkers for GC Detection
To investigate whether the expression levels of miR-101, -103, and -29 have diagnostic value to discriminate GC patients from healthy individuals, the receiver operating characteristic (ROC) curves was depicted, and the area under the curve (AUC) values were computed. Given the ROC results, miR-101 (sensitivity: 82.5 and specificity: 85%), miR-103 (sensitivity: 72.5 and specificity: 90%), and miR-29 (sensitivity: 77.5 and specificity: 70%) with suitable sensitivity, specificity, and reasonable AUC had diagnostic accuracy for GC detection, as illustrated in Figure 4.
Figure 4.
Potential diagnostic accuracy of tissue miR-29, -101, and -103 to discriminate GC patients from adjacent noncancerous tissues.
4. Discussion
More recently, clinicians have focused on various invasive and noninvasive biomarkers to diagnose GC patients at the early stage. Gastroscopy, a biopsy of suspected samples, and detecting the serum biochemical tumor markers such as CEA, CA19-9, and CA72-4 are presently utilized. However, these diagnostic strategies have proven to be helpful, but they have some limitations. Hence, exploring noninvasive biomarkers with high sensitivity and specificity can help physicians for detecting the GC patients.
Emerging evidence elucidated that several miRNAs can act as diagnostic biomarkers in GC; they are measurable in various body fluids such as serum, urine, gastric juice, and CSF [33]. Also, regarding their resistance to RNases, boiling, pH changes, and extended storage [34], they can be beneficial markers for GC diagnosis. Our results exhibited that expression levels of miR-29 and miR-101 significantly reduced, whereas miR-103 and LPA2 expression remarkably increased in GC tissues compared to the corresponding noncancerous tissues. Although, the gene expression level of ATX was not altered between the GC and normal tissues.
Interestingly, compared with adjacent nontumor groups, the protein level of ATX and LPA2 was substantially higher in GC specimens. It has been reported that miR-29 as a tumor-suppressive miRNA is downregulated in different cancers, including osteosarcoma, glioblastoma, hepatocellular carcinoma, bladder, prostate, renal, lung, and ovarian cancers [35, 36]. Following our results, several studies revealed that the expression level of miR-29 was elevated in GC tissues compared to the normal tissues; they also suggested that the miR expression level can be possibly employed as a new diagnostic biomarker in GC patients [37].
On the other hand, there are controversial data about expression levels of miR-101 in various cancers. However, most reports demonstrated that this miRNA is a tumor suppressor gene with lower expression in diverse cancers [38, 39]. Two studies reported its upregulation in prostate cancer tissue HepG2 cells [40, 41]. Recently, Dong and Liu found that the expression level of miR-101 was reduced in GC tissues. It correlated with the pathological differentiation degree of the tumor, lymph node metastasis, and depth of infiltration [42]. In addition, similar to our results, several studies reported that this miRNA reduced in GC samples in comparison to the cancer-adjacent normal tissues [43, 44].
Another important miRNA in the pathogenesis of GC is miR-103, which is considered oncogenic in different types of cancers [45, 46]. It has been found that miR-103 is overexpressed in the animal model of diffuse-type GC [47]. There are conflicting reports regarding tissue expression levels of miR-103 in different types of GC patients. So, Parvaee and colleagues exhibited that miR-103 expression was not significantly changed between the intestinal-type of GC compared to the healthy individuals [48].
Moreover, in another study, the observed plasma expression of miR-103 in different GC cases with or without any intestinal components was not remarkable. This miRNA was not appropriate for diffuse-type GC screening [49]. By contrast, similar to our findings, it was elucidated that the expression level of miR-103 was elevated in advanced GC tissues in comparison to the normal gastric mucosa of cancer-free subjects [50]. It seems that sample type is the reason for these controversial reports.
Many in vitro and in vivo researches have revealed elevated LPA/ATX signaling participates in cancer initiation and development. LPA2, as a G protein-coupled receptor, is extensively expressed in several tumors, including breast, ovarian, thyroid, and colorectal cancers [23]. This study observed that LPA2 gene and protein expression was enhanced in tumoral tissues toward adjacent nontumor tissues, which align with Yamashita's study [26]. They reported LPA2 elevation in intestinal-type GC; its expression is linked to an increased rate of lymphatic and venous invasion metastasis. Due to the fact that LPA2 is involved in the pathogenesis of GC, its inhibition by drugs can be a good treatment for patients.
ATX with lysophospholipase D activity implicates in LPA signaling pathway. This innovative molecule has crucial functions in angiogenesis, invasion, and metastasis. There is accumulating data that increased ATX has been detected in malignancies such as breast, pancreatic, non-small-cell lung, colorectal, and thyroid cancers [51–53]. In following with our findings, it has been demonstrated that serum activity of ATX enhanced in pancreatic cancer patients but not in GC ones [54, 55]. Nonetheless, related to the ATX protein, it was higher in GC tissue samples than the paired nontumor tissue specimens.
It seems, that miR-103, miR-29, and miR-101 with suitable sensitivity and specificity have good diagnostic performance for distinguishing GC patients from normal individuals. Several studies have shown that numerous miRNAs are reliable markers for diagnosis, prognosis, and clinical applications in GC at the early stages. In this way, following observation, Wang and coworkers reported that the cut of value 0.69 miR-29 fold change with 70% sensitivity and 68% specificity has appropriate diagnostic accuracy in the tumor tissue [56, 57]. Also, despite disagreements about using miR-103 as a diagnostic biomarker in GC, we found this miRNA helpful to detect GC patients with sensible AUC, sensitivity, and specificity. This disagreement probably is due to the sample size, inclusion and exclusion criteria, individual characterization, and analytical procedures.
Besides, miR-101 has been introduced as a diagnostic biomarker for GC discrimination by two studies [38, 58]. The clinical utility of serum miRNAs as promising diagnostic and prognostic biomarkers for GC needs more explorations. Indeed, the therapeutic applications of miRNAs as diagnostic and prognostic biomarkers for GC are not still completely determined, and further studies are necessary.
5. Conclusion
In summary, our result implied that gene expression levels of miR-101, -29, -103, and LPA2 increased in GC tissues toward adjacent noncancerous tissues. Moreover, compared to matched nontumor tissues, the protein status of LPA2 and ATX was higher in GC tissue samples. Meanwhile, all three miRNAs had diagnostic value with reliable AUC, sensitivity, and specificity to distinguish GC patients from healthy subjects.
5.1. Limitation Study
In future studies, it is better to investigate the relationship between miRs expression and patients' response to treatment. It is also necessary to evaluate the effect of different drugs, to select the most appropriate ones to regulate the expression of these genes, and ultimately increase patient survival.
Acknowledgments
This research was supported by a grant (grant 99-3-101-51122) from the Deputy of Research, Tehran University of Medical Sciences and Health Services.
Data Availability
The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.
Ethical Approval
All the procedures performed in the studies involving human participants were in accordance with ethical standards of the local ethics committee of Tehran University of Medical Sciences (IR.TUMS.MEDICINE.REC.1399.1087), as well as 1964 Helsinki declaration.
Conflicts of Interest
The authors declare that they have no conflict of interest.
Authors' Contributions
R.Sh. conceived the manuscript and revised it. S.T. and S.A. designed the research study and performed the research. S.T., S.A., Gh. P., M.Z., and A.E R. analyzed the data and wrote the manuscript. Sara Tutunchi and Saeedeh Akhavan contributed equally to this work and are co-first authors.
Supplementary Materials
Table I: SeqTences of primers for qRT-PCR.
References
- 1.Thrift A. P., El-Serag H. B. Burden of gastric cancer. Clinical Gastroenterology and Hepatology . 2020;18(3):534–542. doi: 10.1016/j.cgh.2019.07.045. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Zebardast A., Tehrani S. S., Latifi T., Sadeghi F. Critical review of Epstein–Barr virus microRNAs relation with EBV‐associated gastric cancer. Journal of Cellular Physiology . 2021;236(9):6136–6153. doi: 10.1002/jcp.30297. [DOI] [PubMed] [Google Scholar]
- 3.Farmanfarma K. K., Mahdavifar N., Hassanipour S., Salehiniya H. Epidemiologic study of gastric cancer in Iran: a systematic review. Clinical and Experimental Gastroenterology . 2020;Volume 13:511–542. doi: 10.2147/CEG.S256627. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Rawla P., Barsouk A. Epidemiology of gastric cancer: global trends, risk factors and prevention. Przeglad gastroenterologiczny . 2019;14(1):26–38. doi: 10.5114/pg.2018.80001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Pasechnikov V., Chukov S., Fedorov E., Kikuste I., Leja M. Gastric cancer: prevention, screening and early diagnosis. World Journal of Gastroenterology: WJG . 2014;20(38):p. 13842. doi: 10.3748/wjg.v20.i38.13842. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Paracetamol (acetaminophen) IARC monographs on the evaluation of carcinogenic risks to humans . 1990;50:307–332. [PMC free article] [PubMed] [Google Scholar]
- 7.Vradelis S., Maynard N., Warren B. F., Keshav S., Travis S. P. L. Quality control in upper gastrointestinal endoscopy: detection rates of gastric cancer in Oxford 2005–2008. Postgraduate Medical Journal . 2011;87(1027):335–339. doi: 10.1136/pgmj.2010.101832. [DOI] [PubMed] [Google Scholar]
- 8.Stefan-van Staden R.-I., Ilie-Mihai R. M., Pogacean F., Pruneanu S. M. Needle stochastic sensors for on-site fast recognition and quantification of biomarkers for gastric cancer in biological samples. New Journal of Chemistry . 2020;44(46):20203–20211. doi: 10.1039/D0NJ03847D. [DOI] [Google Scholar]
- 9.Stefan-van Staden R. I., Ilie-Mihai R. M., Gurzu S. The fast screening method of biological samples for early diagnosis of gastric cancer. Cancer Investigation . 2020;4(3):25–30. doi: 10.30699/mci.4.3.25. [DOI] [Google Scholar]
- 10.Căinap C., Nagy V., Gherman A., et al. Classic tumor markers in gastric cancer. Current standards and limitations. Current standards and limitations. Clujul Medical . 2015;88(2):111–115. doi: 10.15386/cjmed-409. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Sekiguchi M., Matsuda T. Limited usefulness of serum carcinoembryonic antigen and carbohydrate antigen 19-9 levels for gastrointestinal and whole-body cancer screening. Scientific Reports . 2020;10(1):1–10. doi: 10.1038/s41598-020-75319-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Comnea-Stancu I. R., Stefan-van Staden R. I., van Staden J. F., Stanciu-Gavan C. Stochastic sensors based on maltodextrins for screening of whole blood for neuron specific enolase, carcinoembryonic antigen and epidermal growth factor receptor. Microsystem Technologies . 2016;22(1):25–29. doi: 10.1007/s00542-015-2635-z. [DOI] [Google Scholar]
- 13.Abolghasemi M., Tehrani S. S., Yousefi T., et al. MicroRNAs in breast cancer: roles, functions, and mechanism of actions. Journal of Cellular Physiology . 2020;235(6):5008–5029. doi: 10.1002/jcp.29396. [DOI] [PubMed] [Google Scholar]
- 14.Maniati M. S., Maniati M., Yousefi T., Ahmadi-Ahangar A., Tehrani S. S. New insights into the role of microRNAs and long noncoding RNAs in most common neurodegenerative diseases. Journal of Cellular Biochemistry . 2019;120(6):8908–8918. doi: 10.1002/jcb.28361. [DOI] [PubMed] [Google Scholar]
- 15.Zadeh F. J., Akbari T., zayeri Z. D., Samimi A., Davari N., Rezaeeyan H. The role of molecular mechanism of ten-eleven translocation 2 (TET2) family proteins in pathogenesis of cardiovascular diseases (CVDs) Molecular Biology Reports . 2020;47(7):5503–5509. doi: 10.1007/s11033-020-05602-4. [DOI] [PubMed] [Google Scholar]
- 16.Jamali L., Tofigh R., Tutunchi S., et al. Circulating microRNAs as diagnostic and therapeutic biomarkers in gastric and esophageal cancers. Journal of Cellular Physiology . 2018;233(11):8538–8550. doi: 10.1002/jcp.26850. [DOI] [PubMed] [Google Scholar]
- 17.Jang J. Y., Kim Y. S., Kang K. N., Kim K. H., Park Y. J., Kim C. W. Multiple microRNAs as biomarkers for early breast cancer diagnosis. Molecular and clinical oncology . 2021;14(2):p. 1. doi: 10.3892/mco.2020.2193. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Haybar H., Rezaeeyan H., Shahjahani M., Shirzad R., Saki N. T-bet transcription factor in cardiovascular disease: attenuation or inflammation factor? Journal of Cellular Physiology . 2019;234(6):7915–7922. doi: 10.1002/jcp.27935. [DOI] [PubMed] [Google Scholar]
- 19.Matias-Garcia P. R., Wilson R., Mussack V., et al. Impact of long-term storage and freeze-thawing on eight circulating microRNAs in plasma samples. PLoS One . 2020;15(1, article e0227648) doi: 10.1371/journal.pone.0227648. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Hoshino I. The usefulness of microRNA in urine and saliva as a biomarker of gastroenterological cancer. International Journal of Clinical Oncology . 2021;26:1431–1440. doi: 10.1007/s10147-021-01911-1. [DOI] [PubMed] [Google Scholar]
- 21.ZiaSarabi P., Sorayayi S., Hesari A. R., Ghasemi F. Circulating microRNA-133, microRNA-17 and microRNA-25 in serum and its potential diagnostic value in gastric cancer. Journal of Cellular Biochemistry . 2019;120(8):12376–12381. doi: 10.1002/jcb.28503. [DOI] [PubMed] [Google Scholar]
- 22.Brindley D. N. Lysophosphatidic acid signaling in cancer. Cancers . 2020;12(12):p. 3791. doi: 10.3390/cancers12123791. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Leblanc R., Peyruchaud O. New insights into the autotaxin/LPA axis in cancer development and metastasis. Experimental Cell Research . 2015;333(2):183–189. doi: 10.1016/j.yexcr.2014.11.010. [DOI] [PubMed] [Google Scholar]
- 24.Song X., Shi Y., You J., et al. D-4F, an apolipoprotein A-I mimetic, suppresses IL-4 induced macrophage alternative activation and pro-fibrotic TGF-β1 expression. Pharmaceutical Biology . 2019;57(1):470–476. doi: 10.1080/13880209.2019.1640747. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Enooku K., Uranbileg B., Ikeda H., et al. Higher LPA2 and LPA6 mRNA levels in hepatocellular carcinoma are associated with poorer differentiation, microvascular invasion and earlier recurrence with higher serum autotaxin levels. PLoS One . 2016;11(9, article e0161825) doi: 10.1371/journal.pone.0161825. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Yamashita H., Kitayama J., Shida D., et al. Differential expression of lysophosphatidic acid receptor-2 in intestinal and diffuse type gastric cancer. Journal of Surgical Oncology . 2006;93(1):30–35. doi: 10.1002/jso.20397. [DOI] [PubMed] [Google Scholar]
- 27.Xu A., Khan A. K., Chen F., Zhong Z., Chen H. C., Song Y. Overexpression of autotaxin is associated with human renal cell carcinoma and bladder carcinoma and their progression. Medical Oncology . 2016;33(11):1–8. doi: 10.1007/s12032-016-0836-7. [DOI] [PubMed] [Google Scholar]
- 28.Seo E. J., Kwon Y. W., Jang I. H., et al. Autotaxin regulates maintenance of ovarian cancer stem cells through lysophosphatidic acid-mediated autocrine mechanism. Stem Cells . 2016;34(3):551–564. doi: 10.1002/stem.2279. [DOI] [PubMed] [Google Scholar]
- 29.Murph M. M. MicroRNA regulation of the autotaxin-lysophosphatidic acid signaling Axis. Cancers . 2019;11(9):p. 1369. doi: 10.3390/cancers11091369. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Ma X., Feng J., Lu M., et al. microRNA-501-5p promotes cell proliferation and migration in gastric cancer by downregulating LPAR1. Journal of Cellular Biochemistry . 2020;121(2):1911–1922. doi: 10.1002/jcb.29426. [DOI] [PubMed] [Google Scholar]
- 31.Wang Y., Lyu L., Zhang X., Zhang J. Autotaxin is a novel target of microRNA-101-3p. FEBS Open Bio . 2019;9(4):707–716. doi: 10.1002/2211-5463.12608. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Naz S., Kolmert J., Yang M., et al. Metabolomics analysis identifies sex-associated metabotypes of oxidative stress and the autotaxin–lysoPA axis in COPD. European Respiratory Journal . 2017;49(6):p. 1602322. doi: 10.1183/13993003.02322-2016. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Yuan H.-L., Wang T., Zhang K.-H. MicroRNAs as potential biomarkers for diagnosis, therapy and prognosis of gastric cancer. Onco Targets and therapy . 2018;Volume 11:3891–3900. doi: 10.2147/OTT.S156921. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Wang W., Luo Y. P. MicroRNAs in breast cancer: oncogene and tumor suppressors with clinical potential. Journal of Zhejiang University-Science B . 2015;16(1):18–31. doi: 10.1631/jzus.B1400184. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Kwon J. J., Factora T. D., Dey S., Kota J. A systematic review of miR-29 in cancer. Molecular Therapy-Oncolytics . 2019;12:173–194. doi: 10.1016/j.omto.2018.12.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Alizadeh M., Safarzadeh A., Beyranvand F., et al. The potential role of miR-29 in health and cancer diagnosis, prognosis, and therapy. Journal of Cellular Physiology . 2019;234(11):19280–19297. doi: 10.1002/jcp.28607. [DOI] [PubMed] [Google Scholar]
- 37.Zhao X., Hou Y., Tuo Z., Wei F. Application values of miR-194 and miR-29 in the diagnosis and prognosis of gastric cancer. Experimental and Therapeutic Medicine . 2018;15(5):4179–4184. doi: 10.3892/etm.2018.5931. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Imamura T., Komatsu S., Ichikawa D., et al. Low plasma levels of miR-101 are associated with tumor progression in gastric cancer. Oncotarget . 2017;8(63):106538–106550. doi: 10.18632/oncotarget.20860. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Wang C.-Z., Deng F., Li H., et al. MiR-101: a potential therapeutic target of cancers. American Journal of Translational Research . 2018;10(11):3310–3321. [PMC free article] [PubMed] [Google Scholar]
- 40.Li Q., Wang G., Shan J. L., et al. MicroRNA-224 is upregulated in HepG2 cells and involved in cellular migration and invasion. Journal of Gastroenterology and Hepatology . 2010;25(1):164–171. doi: 10.1111/j.1440-1746.2009.05971.x. [DOI] [PubMed] [Google Scholar]
- 41.Lee K.-H., Chen Y. L., Yeh S. D., et al. MicroRNA-330 acts as tumor suppressor and induces apoptosis of prostate cancer cells through E2F1-mediated suppression of Akt phosphorylation. Oncogene . 2009;28(38):3360–3370. doi: 10.1038/onc.2009.192. [DOI] [PubMed] [Google Scholar]
- 42.Dong X., Liu Y. Expression and significance of miR-24 and miR-101 in patients with advanced gastric cancer. Oncology Letters . 2018;16(5):5769–5774. doi: 10.3892/ol.2018.9324. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Wang H.-J., Ruan H. J., He X. J., et al. MicroRNA-101 is down-regulated in gastric cancer and involved in cell migration and invasion. European Journal of Cancer . 2010;46(12):2295–2303. doi: 10.1016/j.ejca.2010.05.012. [DOI] [PubMed] [Google Scholar]
- 44.Riquelme I., Tapia O., Leal P., et al. miR-101-2, miR-125b-2 and miR-451a act as potential tumor suppressors in gastric cancer through regulation of the PI3K/AKT/mTOR pathway. Cellular Oncology . 2016;39(1):23–33. doi: 10.1007/s13402-015-0247-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Zheng J., Liu Y., Qiao Y., Zhang L., Lu S. miR-103 promotes proliferation and metastasis by targeting KLF4 in gastric cancer. International Journal of Molecular Sciences . 2017;18(5):p. 910. doi: 10.3390/ijms18050910. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Han L.-L., Yin X.-R., Zhang S.-Q. miR-103 promotes the metastasis and EMT of hepatocellular carcinoma by directly inhibiting LATS2. International Journal of Oncology . 2018;53(6):2433–2444. doi: 10.3892/ijo.2018.4580. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Rotkrua P., Shimada S., Mogushi K., Akiyama Y., Tanaka H., Yuasa Y. Circulating microRNAs as biomarkers for early detection of diffuse-type gastric cancer using a mouse model. British Journal of Cancer . 2013;108(4):932–940. doi: 10.1038/bjc.2013.30. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Parvaee P., Sarmadian H., Khansarinejad B., Amini M., Mondanizadeh M. Plasma level of microRNAs, miR-107, miR-194 and miR-210 as potential biomarkers for diagnosis intestinal-type gastric cancer in human. Asian Pacific journal of cancer prevention: APJCP . 2019;20(5):1421–1426. doi: 10.31557/APJCP.2019.20.5.1421. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Oze I., Shimada S., Nagasaki H., et al. Plasma microRNA-103, microRNA-107, and microRNA-194 levels are not biomarkers for human diffuse gastric cancer. Journal of Cancer Research and Clinical Oncology . 2017;143(3):551–554. doi: 10.1007/s00432-016-2316-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Kim B. H., Hong S. W., Kim A., Choi S. H., Yoon S. O. Prognostic implications for high expression of oncogenic microRNAs in advanced gastric carcinoma. Journal of Surgical Oncology . 2013;107(5):505–510. doi: 10.1002/jso.23271. [DOI] [PubMed] [Google Scholar]
- 51.Peyruchaud O., Saier L., Leblanc R. Autotaxin implication in cancer metastasis and autoimunne disorders: functional implication of binding autotaxin to the cell surface. Cancers . 2020;12(1):p. 105. doi: 10.3390/cancers12010105. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Quan M., Cui J. J., Feng X., Huang Q. The critical role and potential target of the autotaxin/lysophosphatidate axis in pancreatic cancer. Tumor Biology . 2017;39(3):p. 1010428317694544. doi: 10.1177/1010428317694544. [DOI] [PubMed] [Google Scholar]
- 53.Sadeghzadeh-Bazargan A., Ghassemi M., Goodarzi A., Roohaninasab M., Najar Nobari N., Behrangi E. Systematic review of low-dose isotretinoin for treatment of acne vulgaris: focus on indication, dosage, regimen, efficacy, safety, satisfaction, and follow up, based on clinical studies. Dermatologic Therapy . 2021;34(1, article e14438) doi: 10.1111/dth.14438. [DOI] [PubMed] [Google Scholar]
- 54.Nakai Y., Ikeda H., Nakamura K., et al. Specific increase in serum autotaxin activity in patients with pancreatic cancer. Clinical Biochemistry . 2011;44(8-9):576–581. doi: 10.1016/j.clinbiochem.2011.03.128. [DOI] [PubMed] [Google Scholar]
- 55.Ghassemi M., Roohaninasab M., Kamani S. A., Sadeghzadeh-Bazargan A., Goodarzi A. Comparison of the efficacy and safety of intralesional injection of tranexamic acid and the topical application of Kligman combination drug in the treatment of macular amyloidosis. Dermatologic Therapy . 2022;35(1, article e15213) doi: 10.1111/dth.15213. [DOI] [PubMed] [Google Scholar]
- 56.Wang D., Fan Z., Liu F., Zuo J. Hsa-miR-21 and Hsa-miR-29 in tissue as potential diagnostic and prognostic biomarkers for gastric cancer. Cellular Physiology and Biochemistry . 2015;37(4):1454–1462. doi: 10.1159/000438514. [DOI] [PubMed] [Google Scholar]
- 57.Roohaninasab M., Sadeghzadeh-Bazargan A., Goodarzi A. Effects of laser therapy on periorbital hyperpigmentation: a systematic review on current studies. Lasers in Medical Science . 2021;36(9):1781–1789. doi: 10.1007/s10103-020-03241-6. [DOI] [PubMed] [Google Scholar]
- 58.Zeng W., Zhang S., Yang L., et al. Serum miR-101-3p combined with pepsinogen contributes to the early diagnosis of gastric cancer. BMC Medical Genetics . 2020;21(1):p. 28. doi: 10.1186/s12881-020-0967-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Table I: SeqTences of primers for qRT-PCR.
Data Availability Statement
The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.