Plasma and Tissue Specific miRNA Expression Pattern and Functional Analysis Associated to Colorectal Cancer Patients
<p>Summary of common miRNAs which are differentially expressed in plasma samples in colon, rectal, and colorectal cancer, respectively, versus healthy controls, displayed as heatmap and Venn diagrams. (<b>A</b>–<b>C</b>) Heatmap of miRNA microarray expression data for (<b>A</b>) colon, (<b>B</b>) rectal, (<b>C</b>) colorectal cancer versus healthy subjects. (<b>D</b>) The common miRNAs are presented by overlapping downregulated miRNAs in the three analyzed groups. (<b>E</b>) Biological processes affected, identification of target genes for the downregulated miRNAs using miRnet connected with KEEG database. <b>(F</b>) The common miRNAs are presented by overlapping overexpressed miRNAs in the three analyzed groups. (<b>G</b>) Biological processes affected, identification of target genes for the upregulated miRNAs using miRnet connected with KEEG database.</p> "> Figure 2
<p>Common miRNA expression profile pattern in TCGA (tumor versus normal tissue) and plasma (tumor samples versus healthy controls) data on colon, rectal and colorectal cancer. The diagrams present the overlapping TCGA and plasma miRNA signatures in the case of upregulated (<b>A</b>) and downregulated transcripts (<b>B</b>) for the case of colon cancer, similarly for the case of downregulated (<b>C</b>) and overexpressed miRNAs (<b>D</b>). We also present the overlapping of the downregulated (<b>E</b>) and overexpressed miRNAs (<b>F</b>) transcripts for colon, rectal and colorectal cancer.</p> "> Figure 3
<p>miRNA profile and pathway analysis affected by chemotherapy. (<b>A</b>) Heatmap detailing miRNA expression patterns from chemo-treated versus no chemotherapy plasma samples; (<b>B</b>) Venn diagram for the overexpressed miRNAs in colorectal and rectal cancer, emphasizing the common and specific signatures; (<b>C</b>) Venn diagram for the downregulated miRNAs in colorectal and rectal cancer; (<b>D</b>) cellular processes related to the target genes of the 25 most common overexpressed miRNA signatures in colorectal and rectal cancer. miRNA–mRNA integration was generated using miRNET and KEGG (Kyoto Encyclopedia of Genes and Genomes) classification of the target genes, based on statistical significance and strength of association; (<b>E</b>) miRNA–mRNA integration related to TP53 signaling; (<b>F</b>) cellular processes related to the target genes of the five most common downregulated miRNA signatures in colorectal and rectal cancer. (<b>G</b>) miRNA–mRNA integration was generated using miRNET and KEGG classification of the target genes based on statistical significance and strength of association.</p> "> Figure 4
<p>Tissue and plasma qRT-PCR data validation, the evaluation of the miRNA expression level shows relevant differences. (<b>A</b>) Expression level of miR-1228-3p, miR-642b-3p, miR-195-5p and miR-4741 in tumor tissue and normal tissue, and receiver operating characteristic (ROC) curve; (<b>B</b>) Circos plot of the integrated miRNA spatial signature showing the heterogeneity of the expression level; (<b>C</b>) miR-1228-3p expression level in plasma colorectal patients and healthy controls and ROC curve; (<b>D</b>) miR-1228-3p direct target, generated using miRtargetlink; (* <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> ≤ 0.001, **** <span class="html-italic">p</span> ≤ 0.0001).</p> "> Figure 5
<p>Common miRNA signatures for colon, rectal and colorectal cancers involved in drug resistance. (<b>A</b>) Heatmap of the four validated miRNAs. (<b>B</b>) Heatmap generated using DIANA-miRPath v3.0 (<a href="http://snf-515788.vm.okeanos.grnet.gr" target="_blank">http://snf-515788.vm.okeanos.grnet.gr</a>), showing miRNA targets associated with biological processes related to the validated miRNAs.</p> "> Figure 6
<p>miRNA networks generated using IPA (Ingenuity Pathway Analysis) for the altered plasma miRNAs in colorectal cancer. (<b>A</b>) <b>N</b>1: Inflammatory Disease, Inflammatory Response, Organismal Injury and Abnormalities. (<b>B</b>) <b>N</b>3: Cancer, Organismal Injury and Abnormalities, Reproductive System Disease. (<b>C</b>) <b>N</b>4: Cancer, Immunological Disease, Organismal Injury and Abnormalities. (<b>D</b>) Venn diagram for miRNA altered networks.</p> "> Figure 7
<p>Plasma miRNAs as key modulators of drug resistance, with altered expression in colon and rectal cancer, as well as for the global analysis comprising all colorectal cancers. (<b>A</b>) Venn diagram for the altered miRNAs which supposedly interfere with drug resistance in the analyzed groups; (<b>B</b>) heatmap generated using DIANA-miRPath v3.0, showing miRNA targets associated with biological processes related to the common miRNA signatures involved in drug resistance.</p> "> Figure 8
<p>Plasma overexpressed miRNAs as key modulators of drug resistance observed to be altered in the cases of the analysis of colorectal and rectal cancer chemo-treated versus untreated. (<b>A</b>) Venn diagram for the altered miRNAs which are supposed to interfere with drug resistance in the analyzed groups. (<b>B</b>) Heatmap generated using DIANA-miRPath v3.0 (<a href="http://snf-515788.vm.okeanos.grnet.gr" target="_blank">http://snf-515788.vm.okeanos.grnet.gr</a>), showing miR-21-5p, miR-34a-3p, miR-126-3p, miR-20a-5p, miR-106-5p, miR-17-5p and miR-93-5p targets associated with biological processes. (<b>C</b>) miRNET network for common miRNA signatures emphasizing an important number of target genes related to pathways in cancer and TP53 signaling.</p> ">
Abstract
:1. Introduction
2. Material and Methods
2.1. TCGA Data, Human Subjects and Clinical Data
2.2. Plasma Preparation and RNA Isolation for Colorectal Cancer Patients and Healthy Controls
2.3. miRNA Microarray Evaluation
2.4. Analysis of Microarray Data
2.5. miRNA RT-PCR
2.6. Integrated Analysis of the Altered Plasma miRNAs in Colorectal Cancer
3. Results
3.1. Differential miRNA Expression on Colorectal Cancer Based on TCGA Data
3.2. Differential miRNA Expression in Colorectal Plasma Samples
3.3. Plasma miRNA Pattern Affected by Chemotherapy
3.4. RT-PCR Tissue and Plasma Validation
3.5. Plasma miRNAs as Primordial Signaling Molecules in Colorectal Cancer, Evaluated Using IPA
3.6. Plasma miRNAs as Regulators for Drug Resistance Mechanisms
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Conflicts of Interest
Abbreviations
COAD | Colon adenocarcinoma |
CRC | colorectal cancer |
CT | Chemotherapy |
KEGG | Kyoto Encyclopedia of Genes and Genomes |
EDTA | Ethylenediaminetetraacetic acid |
EMT | epithelial to mesenchymal transition |
FC | fold-change |
FDR | false discovery rate |
IPA | Ingenuity Pathway Analysis |
miRNA | microRNA |
READ | Rectum adenocarcinoma |
ROC | Receiver operating characteristic |
References
- Falzone, L.; Scola, L.; Zanghì, A.; Biondi, A.; Di Cataldo, A.; Libra, M.; Candido, S. Integrated analysis of colorectal cancer microRNA datasets: Identification of microRNAs associated with tumor development. Aging 2018, 10, 1000–1014. [Google Scholar] [CrossRef] [PubMed]
- Hofsli, E.; Sjursen, W.; Prestvik, W.S.; Johansen, J.; Rye, M.; Trano, G.; Wasmuth, H.H.; Hatlevoll, I.; Thommesen, L. Identification of serum microRNA profiles in colon cancer. Br. J. Cancer 2013, 108, 1712–1719. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ferlay, J.; Soerjomataram, I.; Dikshit, R.; Eser, S.; Mathers, C.; Rebelo, M.; Parkin, D.M.; Forman, D.; Bray, F. Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012. Int. J. Cancer 2015, 136, E359–E386. [Google Scholar] [CrossRef] [PubMed]
- Bochis, O.V.; Irimie, A.; Pichler, M.; Berindan-Neagoe, I. The role of Skp2 and its substrate CDKN1B (p27) in colorectal cancer. J. Gastrointestin. Liver Dis. 2015, 24, 225–234. [Google Scholar] [CrossRef]
- Moiel, D.; Thompson, J. Early detection of colon cancer-the kaiser permanente northwest 30-year history: How do we measure success? Is it the test, the number of tests, the stage, or the percentage of screen-detected patients? Perm. J. 2011, 15, 30–38. [Google Scholar] [CrossRef] [Green Version]
- Hammond, W.A.; Swaika, A.; Mody, K. Pharmacologic resistance in colorectal cancer: A review. Ther. Adv. Med. Oncol. 2016, 8, 57–84. [Google Scholar] [CrossRef] [Green Version]
- Berindan-Neagoe, I.; Braicu, C.; Pileczki, V.; Cojocneanu Petric, R.; Miron, N.; Balacescu, O.; Iancu, D.; Ciuleanu, T. 5-Fluorouracil potentiates the anti-cancer effect of oxaliplatin on Colo320 colorectal adenocarcinoma cells. J. Gastrointest. Liver Dis. 2013, 22, 37–43. [Google Scholar]
- Ionescu, C.; Braicu, C.; Chiorean, R.; Cojocneanu Petric, R.; Neagoe, E.; Pop, L.; Chira, S.; Berindan-Neagoe, I. TIMP-1 expression in human colorectal cancer is associated with SMAD3 gene expression levels: A pilot study. J. Gastrointest. Liver Dis. 2014, 23, 413–418. [Google Scholar] [CrossRef] [Green Version]
- Olimid, D.A.; Olimid, A.P.; Ifrim Chen, F. Ethical governance of the medical research: Clinical investigation and informed consent under the new EU Medical Devices Regulation (2017745). Rom. J. Morphol. Embryol. 2018, 59, 1305–1310. [Google Scholar]
- Harrison, S.; Benziger, H. The molecular biology of colorectal carcinoma and its implications: A review. Surg. J. R. Coll. Surg. Edinb. Irel. 2011, 9, 200–210. [Google Scholar] [CrossRef]
- Braicu, C.; Tudoran, O.; Balacescu, L.; Catana, C.; Neagoe, E.; Berindan-Neagoe, I.; Ionescu, C. The significance of PDGF expression in serum of colorectal carcinoma patients—correlation with Duke's classification. Can PDGF become a potential biomarker? Chirurgia 2013, 108, 849–854. [Google Scholar] [PubMed]
- Calin, G.A.; Croce, C.M. MicroRNA signatures in human cancers. Nat. Rev. Cancer 2006, 6, 857–866. [Google Scholar] [CrossRef] [PubMed]
- Braicu, C.; Catana, C.; Calin, G.A.; Berindan-Neagoe, I. NCRNA combined therapy as future treatment option for cancer. Curr. Pharm. Des. 2014, 20, 6565–6574. [Google Scholar] [CrossRef]
- Braicu, C.; Calin, G.A.; Berindan-Neagoe, I. MicroRNAs and cancer therapy - from bystanders to major players. Curr. Med. Chem. 2013, 20, 3561–3573. [Google Scholar] [CrossRef]
- Jurj, A.; Braicu, C.; Pop, L.A.; Tomuleasa, C.; Gherman, C.D.; Berindan-Neagoe, I. The new era of nanotechnology, an alternative to change cancer treatment. Drug Des. Dev. 2017, 11, 2871–2890. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Oliveto, S.; Mancino, M.; Manfrini, N.; Biffo, S. Role of microRNAs in translation regulation and cancer. World J. Biol. Chem. 2017, 8, 45–56. [Google Scholar] [CrossRef]
- Seles, M.; Hutterer, G.C.; Kiesslich, T.; Pummer, K.; Berindan-Neagoe, I.; Perakis, S.; Schwarzenbacher, D.; Stotz, M.; Gerger, A.; Pichler, M. Current Insights into Long Non-Coding RNAs in Renal Cell Carcinoma. Int. J. Mol. Sci. 2016, 17, 573. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Irimie, A.I.; Braicu, C.; Sonea, L.; Zimta, A.A.; Cojocneanu-Petric, R.; Tonchev, K.; Mehterov, N.; Diudea, D.; Buduru, S.; Berindan-Neagoe, I. A Looking-Glass of Non-coding RNAs in oral cancer. Int. J. Mol. Sci. 2017, 18, 2620. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Catana, C.S.; Calin, G.A.; Berindan-Neagoe, I. Inflamma-miRs in Aging and Breast Cancer: Are They Reliable Players? Front. Med. 2015, 2, 85. [Google Scholar] [CrossRef] [Green Version]
- Tomuleasa, C.; Braicu, C.; Irimie, A.; Craciun, L.; Berindan-Neagoe, I. Nanopharmacology in translational hematology and oncology. Int. J. Nanomed. 2014, 9, 3465–3479. [Google Scholar] [CrossRef] [Green Version]
- Braicu, C.; Raduly, L.; Morar-Bolba, G.; Cojocneanu, R.; Jurj, A.; Pop, L.A.; Pileczki, V.; Ciocan, C.; Moldovan, A.; Irimie, A.; et al. Aberrant miRNAs expressed in HER-2 negative breast cancers patient. J. Exp. Clin. Cancer Res. 2018, 37, 257. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Jurj, A.; Zanoaga, O.; Braicu, C.; Lazar, V.; Tomuleasa, C.; Irimie, A.; Berindan-Neagoe, I. A Comprehensive Picture of Extracellular Vesicles and Their Contents. Molecular Transfer to Cancer Cells. Cancers 2020, 12, 298. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ling, H.; Pickard, K.; Ivan, C.; Isella, C.; Ikuo, M.; Mitter, R.; Spizzo, R.; Bullock, M.D.; Braicu, C.; Pileczki, V.; et al. The clinical and biological significance of MIR-224 expression in colorectal cancer metastasis. Gut 2015. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sonea, L.; Buse, M.; Gulei, D.; Onaciu, A.; Simon, I.; Braicu, C.; Berindan-Neagoe, I. Decoding the Emerging Patterns Exhibited in Non-coding RNAs Characteristic of Lung Cancer with Regard to their Clinical Significance. Curr. Genom. 2018, 19, 258–278. [Google Scholar] [CrossRef] [PubMed]
- Braicu, C.; Buiga, R.; Cojocneanu, R.; Buse, M.; Raduly, L.; Pop, L.A.; Chira, S.; Budisan, L.; Jurj, A.; Ciocan, C.; et al. Connecting the dots between different networks: miRNAs associated with bladder cancer risk and progression. J. Exp. Clin. Cancer Res. 2019, 38, 433. [Google Scholar] [CrossRef]
- Irimie, A.I.; Braicu, C.; Cojocneanu-Petric, R.; Berindan-Neagoe, I.; Campian, R.S. Novel technologies for oral squamous carcinoma biomarkers in diagnostics and prognostics. Acta Odontol. Scand. 2015, 73, 161–168. [Google Scholar] [CrossRef]
- Braicu, C.; Zimta, A.A.; Gulei, D.; Olariu, A.; Berindan-Neagoe, I. Comprehensive analysis of circular RNAs in pathological states: Biogenesis, cellular regulation, and therapeutic relevance. Cell Mol. Life Sci. 2019, 76, 1559–1577. [Google Scholar] [CrossRef]
- Wang, Z.; Jensen, M.A.; Zenklusen, J.C. A Practical Guide to The Cancer Genome Atlas (TCGA). Methods Mol. Biol. 2016, 1418, 111–141. [Google Scholar] [CrossRef]
- Zanutto, S.; Pizzamiglio, S.; Ghilotti, M.; Bertan, C.; Ravagnani, F.; Perrone, F.; Leo, E.; Pilotti, S.; Verderio, P.; Gariboldi, M.; et al. Circulating miR-378 in plasma: A reliable, haemolysis-independent biomarker for colorectal cancer. Br. J. Cancer 2014, 110, 1001–1007. [Google Scholar] [CrossRef]
- Wikberg, M.L.; Myte, R.; Palmqvist, R.; van Guelpen, B.; Ljuslinder, I. Plasma miRNA can detect colorectal cancer, but how early? Cancer Med. 2018, 7, 1697–1705. [Google Scholar] [CrossRef]
- Gaedcke, J.; Grade, M.; Camps, J.; Sokilde, R.; Kaczkowski, B.; Schetter, A.J.; Difilippantonio, M.J.; Harris, C.C.; Ghadimi, B.M.; Moller, S.; et al. The rectal cancer microRNAome—microRNA expression in rectal cancer and matched normal mucosa. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2012, 18, 4919–4930. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Gulei, D.; Magdo, L.; Jurj, A.; Raduly, L.; Cojocneanu-Petric, R.; Moldovan, A.; Moldovan, C.; Florea, A.; Pasca, S.; Pop, L.A.; et al. The silent healer: miR-205-5p up-regulation inhibits epithelial to mesenchymal transition in colon cancer cells by indirectly up-regulating E-cadherin expression. Cell Death Dis. 2018, 9, 66. [Google Scholar] [CrossRef] [PubMed]
- Guo, J.; Yang, Y.; Yang, Y.; Linghu, E.; Zhan, Q.; Brock, M.V.; Herman, J.G.; Zhang, B.; Guo, M. RASSF10 suppresses colorectal cancer growth by activating P53 signaling and sensitizes colorectal cancer cell to docetaxel. Oncotarget 2015, 6, 4202–4213. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Papachristou, D.J.; Korpetinou, A.; Giannopoulou, E.; Antonacopoulou, A.G.; Papadaki, H.; Grivas, P.; Scopa, C.D.; Kalofonos, H.P. Expression of the ribonucleases Drosha, Dicer, and Ago2 in colorectal carcinomas. Virchows Arch. Int. J. Pathol. 2011, 459, 431–440. [Google Scholar] [CrossRef]
- Gibbings, D.; Mostowy, S.; Jay, F.; Schwab, Y.; Cossart, P.; Voinnet, O. Selective autophagy degrades DICER and AGO2 and regulates miRNA activity. Nat. Cell Biol. 2012, 14, 1314–1321. [Google Scholar] [CrossRef] [Green Version]
- Bian, X.J.; Zhang, G.M.; Gu, C.Y.; Cai, Y.; Wang, C.F.; Shen, Y.J.; Zhu, Y.; Zhang, H.L.; Dai, B.; Ye, D.W. Down-regulation of Dicer and Ago2 is associated with cell proliferation and apoptosis in prostate cancer. Tumour Biol. J. Int. Soc. Oncodev. Biol. Med. 2014, 35, 11571–11578. [Google Scholar] [CrossRef]
- Prodromaki, E.; Korpetinou, A.; Giannopoulou, E.; Vlotinou, E.; Chatziathanasiadou, M.; Papachristou, N.I.; Scopa, C.D.; Papadaki, H.; Kalofonos, H.P.; Papachristou, D.J. Expression of the microRNA regulators Drosha, Dicer and Ago2 in non-small cell lung carcinomas. Cell. Oncol. 2015, 38, 307–317. [Google Scholar] [CrossRef]
- Gibbings, D.; Mostowy, S.; Voinnet, O. Autophagy selectively regulates miRNA homeostasis. Autophagy 2013, 9, 781–783. [Google Scholar] [CrossRef] [Green Version]
- Hummel, R.; Hussey, D.J.; Haier, J. MicroRNAs: Predictors and modifiers of chemo- and radiotherapy in different tumour types. Eur. J. Cancer 2010, 46, 298–311. [Google Scholar] [CrossRef]
- Gulei, D.; Irimie, A.I.; Cojocneanu-Petric, R.; Schultze, J.L.; Berindan-Neagoe, I. Exosomes—Small Players, Big Sound. Bioconjug. Chem. 2018. [Google Scholar] [CrossRef]
- Law, J.; Salla, M.; Zare, A.; Wong, Y.; Luong, L.; Volodko, N.; Svystun, O.; Flood, K.; Lim, J.; Sung, M.; et al. Modulator of apoptosis 1 (MOAP-1) is a tumor suppressor protein linked to the RASSF1A protein. J. Biol. Chem. 2015, 290, 24100–24118. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Available online: https://www.proteinatlas.org/ENSG00000165943-MOAP1/pathology/tissue/colorectal+cancer (accessed on 26 June 2019).
- Volodko, N.; Salla, M.; Zare, A.; Abulghasem el, A.; Vincent, K.; Benesch, M.G.; McMullen, T.P.; Bathe, O.F.; Postovit, L.; Baksh, S. RASSF1A Site-Specific Methylation Hotspots in Cancer and Correlation with RASSF1C and MOAP-1. Cancers 2016, 8, 55. [Google Scholar] [CrossRef] [PubMed]
- Allen, W.L.; Stevenson, L.; Coyle, V.M.; Jithesh, P.V.; Proutski, I.; Carson, G.; Gordon, M.A.; Lenz, H.J.; Van Schaeybroeck, S.; Longley, D.B.; et al. A systems biology approach identifies SART1 as a novel determinant of both 5-fluorouracil and SN38 drug resistance in colorectal cancer. Mol. Cancer Ther. 2012, 11, 119–131. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Izeradjene, K.; Douglas, L.; Delaney, A.; Houghton, J.A. Casein kinase II (CK2) enhances death-inducing signaling complex (DISC) activity in TRAIL-induced apoptosis in human colon carcinoma cell lines. Oncogene 2005, 24, 2050–2058. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Demographics | COAD (n = 444) | READ (n = 161) | Total CRC (n = 605) | |
---|---|---|---|---|
Sex | Males | 231 | 86 | 317 |
Females | 211 | 74 | 285 | |
Unknown | 2 | 1 | 3 | |
Age | Median, Range | 68, 31–90 | 65.5, 31–90 | 68, 31–90 |
Median, Range ♂ | 69, 31–90 | 64, 33–87 | 68, 31–90 | |
Median, Range ♀ | 68, 34–90 | 67, 31–87 | 68, 31–90 | |
Relevant family history | Yes | 56 | 15 | 71 |
No | 319 | 121 | 440 | |
Unknown | 69 | 25 | 94 | |
TNM | T1 | 11 | 9 | 20 |
T2 | 74 | 27 | 101 | |
T3 | 301 | 110 | 411 | |
T4 | 55 | 13 | 68 | |
Tis | 1 | - | 1 | |
T unknown | 2 | 2 | 4 | |
N0 | 257 | 80 | 337 | |
N1 | 104 | 44 | 148 | |
N2 | 81 | 33 | 114 | |
Nx | - | 2 | 2 | |
N unknown | 2 | 2 | 4 | |
M0 | 320 | 121 | 441 | |
M1 | 65 | 23 | 88 | |
Mx | 50 | 14 | 64 | |
M unknown | 9 | 3 | 12 | |
Tumor stage | I | 73 | 29 | 102 |
II | 169 | 48 | 217 | |
III | 125 | 50 | 175 | |
IV | 65 | 24 | 89 | |
Unknown | 12 | 10 | 22 | |
Microsatellites | MSI high | 76 | 4 | 80 |
MSI low | 78 | 19 | 97 | |
MSS | 277 | 136 | 413 | |
Unknown | 13 | 2 | 15 |
Demographics | Without CT (n = 38) | With CT (n = 17) | Controls (n = 16) | |
---|---|---|---|---|
Sex | Males | 18 | 12 | 9 |
Females | 20 | 5 | 7 | |
Age | Median, Range | 63, 41–77 | 61, 42–79 | 54.5, 41–63 |
Median, Range ♂ | 60, 50–75 | 63, 42–79 | 55, 51–63 | |
Median, Range ♀ | 64, 41–77 | 58, 49–64 | 54, 41–58 | |
Origin | Urban | 26 | 10 | 16 |
Rural | 12 | 7 | - | |
Relevant family history | Yes | 5 | 2 | - |
No | 33 | 15 | - | |
Unknown | - | - | - | |
TNM | T1 | 3 | 1 | - |
T2 | 6 | 6 | - | |
T3 | 26 | 10 | - | |
T4 | 3 | 0 | - | |
N0 | 22 | 12 | - | |
N1 | 7 | 5 | - | |
N2 | 9 | 0 | - | |
M0 | 33 | 15 | - | |
M1 | 5 | 2 | - | |
M - unknown | - | - | - | |
AJCC Staging | I | 7 | 4 | - |
IIA | 12 | 6 | - | |
IIB | 1 | - | - | |
III | 1 | - | - | |
IIIA | - | 3 | - | |
IIIB | 8 | 2 | - | |
IIIC | 4 | - | - | |
IV | 5 | 2 | - | |
Tumor grade | 1 | 11 | 4 | - |
2 | 24 | 11 | - | |
3 | 3 | 2 | - | |
Unknown | - | - | - | |
Tumor location | Colon | 25 | 0 | - |
Rectum | 12 | 13 | - | |
Junction | 1 | 4 | - | |
Chemotherapy | No | 38 | 0 | - |
Yes | 0 | 17 | - |
Clinical Features | Variable | Plasma | Tissue | |
---|---|---|---|---|
All Patients (n = 25) | Controls (n = 25) | All Patients (n = 30) | ||
Sex | Males | 13 | 17 | 15 |
Females | 12 | 8 | 15 | |
Age | Median, Range | 65, 37–86 | 44, 38–61 | 62, 19–79 |
Median, Range ♂ | 59, 37–84 | 42, 40–61 | 58, 19–74 | |
Median, Range ♀ | 72, 40–86 | 46.5, 38–54 | 66, 56–79 | |
Origin | Urban | 20 | 25 | 21 |
Rural | 5 | 0 | 9 | |
Relevant family history | Yes | 1 | - | 6 |
No | 16 | - | 24 | |
Unknown | 8 | - | - | |
TNM | T1 | 1 | - | 4 |
T2 | 0 | - | 3 | |
T3 | 14 | - | 19 | |
T4 | 10 | - | 4 | |
N0 | 11 | - | 20 | |
N1 | 10 | - | 4 | |
N2 | 4 | - | 6 | |
M0 | 14 | - | 26 | |
M1 | 6 | - | 4 | |
M – unknown | 5 | - | - | |
AJCC Staging | I | 1 | - | 7 |
II | 1 | - | 1 | |
IIA | 2 | - | 9 | |
IIB | - | - | 1 | |
III | 2 | - | 6 | |
IIIB | 7 | - | 2 | |
IIIC | 1 | - | - | |
IV | 5 | - | 4 | |
Uncertain | 6 | - | - | |
Tumor grade | 1 | 10 | - | 10 |
2 | 11 | - | 17 | |
3 | 3 | - | 3 | |
Unknown | 1 | - | - | |
Tumor location | Colon | 22 | - | 23 |
Rectum | 2 | - | 6 | |
Junction | 1 | - | 1 | |
Chemotherapy | No | 25 | - | 30 |
Yes | 0 | - | 0 |
Colon Cancer versus Healthy Patients | Rectal Cancer versus Healthy Patients | Colorectal Cancer versus Healthy Patients | ||||||
---|---|---|---|---|---|---|---|---|
Systematic Name | FC (abs) | p (Corr) | Systematic Name | FC (abs) | p (Corr) | Systematic Name | FC (abs) | p (Corr) |
miR-195-5p | −20.10 | 2.23 × 10−15 | miR-4530 | −28.78 | 2.59 × 10−6 | miR-4741 | −19.07 | 2.57 × 10−12 |
miR-363-3p | −19.81 | 3.28 × 10−7 | miR-6850-5p | −27.90 | 1.04 × 10−5 | miR-642b-3p | −18.98 | 4.89 × 10−10 |
miR-96-5p | −18.73 | 1.14 × 10−18 | miR-642b-3p | −26.12 | 6.43E × 10−11 | miR-195-5p | −16.93 | 2.50 × 10−16 |
miR-4741 | −14.42 | 8.34 × 10−8 | miR-5787 | −24.89 | 2.93 × 10−5 | miR-134-5p | −15.94 | 1.57 × 10−12 |
miR-374a-5p | −13.10 | 1.69 × 10−7 | miR-5703 | −23.46 | 7.31 × 10−5 | miR-5787 | −14.36 | 1.37 × 10−4 |
miR-660-5p | −12.87 | 7.03× 10−8 | miR-4741 | −22.70 | 7.13 × 10−11 | miR-96-5p | −14.27 | 1.88 × 10−16 |
miR-192-5p | −12.86 | 3.82 × 10−9 | miR-642a-3p | −22.42 | 1.47 × 10−14 | miR-4530 | −14.15 | 1.03 × 10−4 |
miR-642b-3p | −12.62 | 7.01 × 10−6 | miR-8072 | −21.87 | 1.21 × 10−11 | miR-6791-5p | −13.44 | 5.09 × 10−6 |
miR-151a-5p | −11.83 | 1.20 × 10−7 | miR-134-5p | −21.86 | 4.62 × 10−15 | miR-4534 | −13.13 | 6.24 × 10−6 |
miR-301a-3p | −11.82 | 1.45 × 10−9 | miR-630 | −21.33 | 1.12× 10−4 | miR-6850-5p | −13.03 | 3.22 × 10−4 |
miR-30b-5p | −11.08 | 3.17 × 10−6 | miR-6791-5p | −19.38 | 1.73× 10−7 | miR-6068 | −13.01 | 2.25 × 10−7 |
miR-134-5p | −10.93 | 8.58 × 10−7 | miR-3663-3p | −18.29 | 5.84 × 10−6 | miR-6728-5p | −12.91 | 2.24 × 10−13 |
miR-18a-5p | −10.83 | 2.55 × 10−8 | miR-4534 | −18.28 | 1.64 × 10−6 | miR-363-3p | −12.63 | 7.60 × 10−6 |
miR-126-5p | −10.81 | 5.37 × 10−9 | miR-6728-5p | −18.07 | 2.15 × 10−18 | miR-642a-3p | −11.93 | 7.58 × 10−4 |
miR-425-5p | −10.58 | 5.28 × 10−5 | miR-1227-5p | −17.65 | 2.65 × 10−14 | miR-8072 | −11.71 | 1.13 × 10−6 |
miR-1228-3p | 27.70 | 6.85 × 10−9 | miR-1228-3p | 38.80 | 1.22 × 10−11 | miR-1228-3p | 33.80 | 1.03 × 10−13 |
miR-4730 | 25.41 | 1.61 × 10−12 | miR-1238-3p | 36.44 | 2.04 × 10−11 | miR-1238-3p | 30.58 | 6.37 × 10−13 |
miR-6716-3p | 24.99 | 6.11 × 10−12 | miR-6508-5p | 35.56 | 4.22 × 10−10 | miR-6069 | 30.11 | 2.96 × 10−13 |
miR-6069 | 24.44 | 1.15 × 10−8 | miR-6737-3p | 34.81 | 4.06 × 10−12 | miR-6800-3p | 29.83 | 2.08 × 10−11 |
miR-6800-3p | 24.09 | 6.46 × 10−8 | miR-6069 | 34.58 | 4.03 × 10−11 | miR-6508-5p | 29.39 | 1.6 0 × 10−11 |
miR-1238-3p | 23.90 | 2.31 × 10−8 | miR-1234-3p | 34.11 | 7.48 × 10−13 | miR-6737-3p | 28.55 | 5.39 × 10−14 |
miR-6737-3p | 21.77 | 7.00 × 10−9 | miR-6800-3p | 34.04 | 9.46 × 10−10 | miR-6716-3p | 27.72 | 3.38 × 10−17 |
miR-6508-5p | 21.64 | 9.66 × 10−8 | miR-191-3p | 33.43 | 2.20 × 10−11 | miR-4730 | 25.70 | 5.06 × 10−14 |
miR-451b | 20.37 | 1.71 × 10−7 | miR-6716-3p | 28.94 | 1.16 × 10−12 | miR-191-3p | 24.76 | 1.06 × 10−11 |
miR-5010-3p | 19.00 | 1.32 × 10−7 | miR-3162-3p | 27.82 | 5.99 × 10−17 | miR-451b | 24.16 | 1.81 × 10−10 |
miR-4433a-5p | 17.96 | 7.84 × 10−9 | miR-4433a-5p | 27.76 | 2.32 × 10−11 | miR-1234-3p | 24.01 | 9.15 × 10−12 |
miR-191-3p | 17.01 | 2.31 × 10−7 | miR-6797-3p | 27.48 | 1.92 × 10−13 | miR-4433a-5p | 23.76 | 1.55 × 10−13 |
miR-3162-3p | 16.21 | 3.08 × 10−9 | miR-1281 | 27.26 | 7.17 × 10−14 | miR-316-2-3p | 21.95 | 1.58 × 10−16 |
miR-1234-3p | 15.44 | 1.04 × 10−6 | miR-451b | 25.66 | 1.06 × 10−8 | miR-6797-3p | 20.71 | 2.22 × 10−13 |
miR-1281 | 14.80 | 1.69 × 10−7 | miR-1825 | 25.28 | 1.43 × 10−13 | miR-1281 | 20.66 | 3.25 × 10−13 |
ID | Associated Network Functions | Score | Focus Molecules | n |
---|---|---|---|---|
1 | Inflammatory Disease, Inflammatory Response, Organismal Injury and Abnormalities | 21 | 14 | N1 |
2 | Organismal Injury and Abnormalities, Reproductive System Disease, Inflammatory Disease | 20 | 13 | N2 |
3 | Cancer, Organismal Injury and Abnormalities, Reproductive System Disease | 20 | 13 | N3 |
4 | Cancer, Immunological Disease, Organismal Injury and Abnormalities | 13 | 9 | N4 |
5 | Organismal Injury and Abnormalities, Reproductive System Disease, Developmental Disorder | 7 | 6 | N5 |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Cojocneanu, R.; Braicu, C.; Raduly, L.; Jurj, A.; Zanoaga, O.; Magdo, L.; Irimie, A.; Muresan, M.-S.; Ionescu, C.; Grigorescu, M.; et al. Plasma and Tissue Specific miRNA Expression Pattern and Functional Analysis Associated to Colorectal Cancer Patients. Cancers 2020, 12, 843. https://doi.org/10.3390/cancers12040843
Cojocneanu R, Braicu C, Raduly L, Jurj A, Zanoaga O, Magdo L, Irimie A, Muresan M-S, Ionescu C, Grigorescu M, et al. Plasma and Tissue Specific miRNA Expression Pattern and Functional Analysis Associated to Colorectal Cancer Patients. Cancers. 2020; 12(4):843. https://doi.org/10.3390/cancers12040843
Chicago/Turabian StyleCojocneanu, Roxana, Cornelia Braicu, Lajos Raduly, Ancuta Jurj, Oana Zanoaga, Lorand Magdo, Alexandru Irimie, Mihai-Stefan Muresan, Calin Ionescu, Mircea Grigorescu, and et al. 2020. "Plasma and Tissue Specific miRNA Expression Pattern and Functional Analysis Associated to Colorectal Cancer Patients" Cancers 12, no. 4: 843. https://doi.org/10.3390/cancers12040843