Novel Molecular Characterization of Colorectal Primary Tumors Based on miRNAs
Abstract
:1. Introduction
2. Results
2.1. Identification of Tissue miRNAs Differentially Expressed in Colorectal Tumours Based on Age and MMR Defect
- (1)
- One non-tumour colonic mucosae as a control.
- (2)
- Sporadic CRC-diagnosed patients less than 45 years of age and without Lynch syndrome.
- (3)
- CRC patients with Lynch syndrome.
- (4)
- Sporadic CRC-diagnosed patients over 45 years of age and without Lynch syndrome.
2.2. Selection of miRNAs for qRT-PCR Validation in a Larger Patient Cohort
2.3. miRNAs Associated with Sporadic CRC Patient Age at Diagnosis and Discriminate Sporadic CRC vs. Lynch Syndrome Patients
2.4. miRNAs Can Be Associated with Histopathological Features in CRC Patients
2.5. miRNAs Can Indicate CRC Progression: Association to Tumour Staging and Invasion
2.6. miRNAs Can Be Useful for Prognosis in CRC: Association with Overall Survival and Progression Free Survival
2.7. Functional Significance of miRNAs
2.7.1. Age and Lynch Syndrome
2.7.2. Histopathological Features
2.7.3. Tumour Progression
2.8. miRNAs Expression Could Regroup CRC Patients
3. Discussion
4. Material and Methods
4.1. Colorectal Cancer Biopsies Collection: Ethics Statement
4.2. microRNA Array Profiling
4.3. Validation of Selected miRNAs: Total RNA Extraction and RT-qPCR
4.4. Bioinformatics Studies
4.5. Statistical Analysis
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Transcript Profiling
Abbreviations
CRC | Colorectal cancer |
MiRNAs | microRNAs |
CIN | Chromosomal instability |
MSI | Microsatellite instability |
CIMP | CpG island methylator phenotype |
MMR | DNA mismatch repair |
CMS | Consensus molecular subtype |
TNM | Tumour-node-metastasis |
FFPE | Formalin-Fixed Paraffin-Embedded |
LNA | Locked Nucleic Acid |
Cq | quantitation cycle |
GO | Gene ontology |
NSCLC | Non-small-cell lung carcinoma |
EMT | Epithelial to mesenchymal transition |
BP | Biological process |
CC | Cellular component |
MF | Molecular function |
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Patient | Group | Age | Staging | Tumour Site | Histologic Grade |
---|---|---|---|---|---|
1 | Control | 51 | NA | NA | NA |
2 | <45 Non Lynch | 27 | IIA | Left | - |
3 | <45 Non Lynch | 35 | IIA | Right | Well differentiated |
4 | Lynch | 46 | - | - | Moderately differentiated |
5 | Lynch | 47 | IIIB | Transverse | Moderately differentiated |
6 | Lynch | 41 | IIA | Left | Well differentiated |
7 | >45 Non Lynch | 70 | IVA | Left | Well differentiated |
8 | >45 Non Lynch | 64 | IIIB | Left | Well differentiated |
miRNA ID | Accession Number | <45 Non Lynch | Lynch | >45 Non Lynch |
---|---|---|---|---|
logFC | logFC | logFC | ||
hsa-miR-1-3p | MIMAT0000416 | 0.02 | −0.22 | 3.13 |
hsa-miR-10a-5p | MIMAT0000253 | −0.43 | −0.50 | 2.55 |
hsa-miR-16-5p | MIMAT0000069 | 1.97 | 2.99 | 4.47 |
hsa-miR-20a-5p | MIMAT0000075 | 0.71 | 1.83 | 3.66 |
hsa-miR-23b-3p | MIMAT0000418 | 2.83 | 2.96 | 6.05 |
hsa-miR-24-3p | MIMAT0000080 | 1.82 | 2.31 | 5.15 |
hsa-miR-27b-3p | MIMAT0000419 | 0.68 | 1.07 | 3.93 |
hsa-miR-29c-3p | MIMAT0000681 | 1.29 | 1.92 | 4.16 |
hsa-miR-99a-5p | MIMAT0000097 | −0.54 | −1.46 | 0.38 |
hsa-miR-143-3p | MIMAT0000435 | 0.17 | −0.35 | 4.59 |
hsa-miR-145-5p | MIMAT0000437 | −0.03 | −0.02 | 4.45 |
hsa-miR-193b-5p | MIMAT0004767 | −0.23 | −0.59 | 0.36 |
hsa-miR-320a | MIMAT0000510 | −1.68 | −1.60 | 0.05 |
hsa-miR-326 | MIMAT0000756 | −1.38 | −1.89 | −2.89 |
hsa-miR-642b-3p | MIMAT0018444 | −1.46 | −1.57 | −3.05 |
hsa-Let7a-5p | MIMAT0000062 | 1.14 | 1.58 | 3.68 |
SNORD4A | NR_000010.1 | −0.42 | 1.00 | 2.10 |
Characteristics | Patients |
---|---|
Gender (m:f) absolute numbers | 115:77 |
Lynch syndrome | |
Lynch | 20 |
Sporadic | 170 |
Age, years at diagnosis | |
Under 50 | 59 |
Over 50 | 132 |
Under 60 | 87 |
Over 60 | 103 |
Tumour site | |
Right | 71 |
Left | 101 |
Unknown | 20 |
T stage | |
Tis | 2 |
T1 | 1 |
T2 | 29 |
T3 | 126 |
T4 | 27 |
Tx | 7 |
N stage | |
N0 | 80 |
N1 | 44 |
N2 | 58 |
Nx | 10 |
M stage | |
M0 | 166 |
M1 | 16 |
NS/NC | 10 |
AJCC staging 7th ed | |
Stage 0 | 2 |
Stage I | 25 |
Stage IIA | 50 |
Stage IIB | 4 |
Stage IIC | 2 |
Stage IIIA | 3 |
Stage IIIB | 53 |
Stage IIIC | 29 |
Stage IVA | 13 |
Stage IVB | 3 |
Characteristics | Patients |
---|---|
Histologic grade | |
Well differentiated | 92 |
Moderately differentiated | 54 |
Poorly differentiated | 35 |
Undifferentiated | 0 |
Unknown | 11 |
Stroma | |
Abundant | 33 |
Moderate | 57 |
Poor | 59 |
Unknown | 43 |
Mucinus component | |
Mucinus | 17 |
No mucinus | 142 |
Unknown | 33 |
Peritumoral inflammatory infiltrate | |
Marked | 24 |
Moderate | 40 |
Poor | 86 |
Unknown | 42 |
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Share and Cite
Conde, E.; Pascual, A.; Prieto-Cuadra, D.; Laza, V.F.; Molina-Cerrillo, J.; Ramos-Muñoz, M.E.; Rodríguez-Serrano, E.M.; Soto, J.L.; Carrato, A.; García-Bermejo, M.L.; et al. Novel Molecular Characterization of Colorectal Primary Tumors Based on miRNAs. Cancers 2019, 11, 346. https://doi.org/10.3390/cancers11030346
Conde E, Pascual A, Prieto-Cuadra D, Laza VF, Molina-Cerrillo J, Ramos-Muñoz ME, Rodríguez-Serrano EM, Soto JL, Carrato A, García-Bermejo ML, et al. Novel Molecular Characterization of Colorectal Primary Tumors Based on miRNAs. Cancers. 2019; 11(3):346. https://doi.org/10.3390/cancers11030346
Chicago/Turabian StyleConde, Elisa, Alejandro Pascual, Daniel Prieto-Cuadra, Val F. Laza, Javier Molina-Cerrillo, Miren Edurne Ramos-Muñoz, Esperanza Macarena Rodríguez-Serrano, José Luis Soto, Alfredo Carrato, María Laura García-Bermejo, and et al. 2019. "Novel Molecular Characterization of Colorectal Primary Tumors Based on miRNAs" Cancers 11, no. 3: 346. https://doi.org/10.3390/cancers11030346