Evaluation of the mir-126, mir-182, and mir-486-5p Expression Signature of Head and Neck Squamous Cell Carcinomas and Lung Squamous Cell Carcinomas
Gizem ISSIN1, Zafer KUCUKODACI2, Ismail YILMAZ2, Evren ERKUL3, Ersin TURAL4, Dilaver DEMIREL5, Atila GUNGOR6, Sukru YILDIRIM7
1Department of Pathology, Erzincan Binali Yildirim University, Mengucek Gazi Training and Research Hospital, ERZINCAN, TURKEY
2University of Health Sciences, Ýstanbul Sultan 2. Abdülhamid Han Training Hospital, ISTANBUL, TURKEY
3Department of Otorhinolaryngology, Gulhane Medical School, University of Health Sciences, Ýstanbul Sultan 2. Abdülhamid Han Training Hospital, ISTANBUL, TURKEY
4Department of Pediatrics, University of Health Sciences, Ýstanbul Sultan 2. Abdülhamid Han Training Hospital, ISTANBUL, TURKEY
5Department of Pathology, University of Health Sciences, Gaziosmanpasa-Taksim Health Application and Research Center, ISTANBUL, TURKEY
6Department of Otorhinolaryngology, Medical Park Goztepe Hospital, ISTANBUL, TURKEY
7Department of Pathology, Maltepe University, Faculty of Medicine, ISTANBUL, TURKEY
Keywords: Head and neck, Lung, Squamous cell carcinoma, mir-126, mir-182, mir-486-5p
Although squamous cell carcinomas (SCCs) originating from different anatomic localizations display a similar histological appearance
under light microscopy, they may differ in terms of epigenetic and genetic features. The aim of this study was to analyze mir-126, mir-182, and
mir-486-5p expression levels in head and neck SCCs and lung SCCs, and to identify localization-specific miRNA expression profiles.
Material and Method: The expression levels of mir-126, mir-182, and mir-486-5p were analyzed in lung, oral cavity, laryngeal, and hypopharyngeal
SCCs in 40 patients, using quantitative real-time polymerase chain reaction.
Results: The findings showed that lung, oral cavity, laryngeal, and hypopharyngeal SCCs have distinct mir-126 and mir-486-5p expression
profiles. It was also observed that mir-126 and mir-486-5p expression levels were highly specific to the tumor localization.
Conclusion: These findings highlighted that SCCs originating from different anatomic localizations have different miRNA expression profiles.
miRNA expression analysis can be used to predict the primary localizations of those SCCs.
Squamous cell carcinoma (SCC) is a tumor that originates
from mucosal or epidermal keratinocytes and can occur
in different localizations such as the head and neck, lung,
cervix, and skin 1
. SCCs arising from different anatomic
localizations often exhibit a similar histological appearance
under the light microscope and this may cause diagnostic
challenges in some cases, especially in the differential
diagnosis of SCC masses in the lungs of patients with head
and neck squamous cell carcinoma (HNSCC) 2-4
The epithelium overlying the upper aerodigestive tract is
continuous with the respiratory epithelium, so carcinogens
such as tobacco products may show similar carcinogenic
processes along the upper aerodigestive and respiratory
tracts at the same time. Therefore, a second primary
tumor may develop in the lungs of patients with HNSCC
5. In addition, the lung is the most common site of
visceral metastases in these patients 6. Histopathological examination often does not provide enough insight to
suggest the exact localization of the primary anatomic region
of the tumor. Therefore, differential diagnosis between
the second primary lung tumor and a lung metastasis is
challenging in patients with HNSCC. Although SCCs that
arise from different anatomic localization have a similar
histopathological appearance, tumors may differ in terms
of genetic and epigenetic features, such as the miRNA
expression profile, which are specific to the anatomic
miRNAs, which are single-stranded non-protein-coding
RNAs generally 18–24 nucleotides long, are capable of
controlling gene expression at the post-transcriptional
level 11. Studies have revealed that miRNAs in humans
have an essential function in regulating various biological
pathways, such as the cell cycle, proliferation, development,
and growth 12. Dysregulation in the expression profile of
miRNAs disrupts biofeedback and gene expression control mechanisms, which may lead to the development of cancer
13. Several studies have revealed that miRNAs show
different expression profiles according to tissue and tumor
types 14,15. This highly specific expression profile can be
used for diagnostic purposes, such as the discrimination of
primary cancers and their metastases 15.
Research based on the integrated analysis of The Cancer
Genome Atlas (TCGA) database data has revealed that
mir-126, mir-182 and mir-486-5p were the consistently
and significantly dysregulated miRNAs in lung cancer
16-19. Research has also indicated that profile analysis of
this miRNA expression could differentiate lung carcinoma
patients from healthy tissue or patients with lung metastasis
of tumor 20-25. In this study, mir-126, mir-486-5p and
mir-182 expression levels were analyzed in lung, oral cavity,
hypopharynx, and laryngeal SCC, and evaluations were
made of the association of tumor anatomic localization
with the mir-126, mir-486-5p, and mir-182 expression
A total of 40 subjects were enrolled from patients who
underwent surgical resection for oral cavity, laryngeal,
hypopharyngeal, or lung SCC between January 2012 and December 2015 in the Department of Thoracic and
Otorhinolaryngology Surgery, 2nd Sultan Abdulhamid Han
Training and Research Hospital. Analyses were conducted
on the formalin-fixed, paraffin-embedded tissues from 40
cases comprising five each from glottic and supraglottic
laryngeal SCC cases, and 10 each from oral cavity,
hypopharyngeal, and lung SCC cases. None of the patients
had a known history of surgery for recurrent cancer, nor
had they received neoadjuvant chemo/radiotherapy.
Clinical data were gathered from all patients. The details
of the clinical and pathological data are presented in Table
. Approval for the study was granted by the Local Medical
Ethics Committee (approval No. 29.01.2016/1491-17-
16/1539). All study procedures were performed according
to the Declaration of Helsinki principles.
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|Table I: Clinicopathological characteristics of the patients in this study.
Selection of miRNA
The selection of miRNA was based on a literature review
of the research based on the integrated analysis of the
Cancer Genome Atlas (TCGA) database data of miRNA
expression profiles in lung SCCs 16-25. To identify
miRNAs with a predictive potential to differentiate lung
SCCs and HNSCCs, the research focused on miRNAs that
play a critical role in lung carcinogenesis, lung tissue, or
tumor specificity. miRNAs accepted as oncoMÝR (e.g.,
miR-21, mir-30) and miRNAs whose expression levels were highly associated with squamous epithelia-containing
tissues, such as mir-205, mir-31 and mir-203, were not
selected 26-29. Three miRNAs (mir-126, mir-182 and
mir-486) that could differentiate lung carcinoma patients
from healthy tissue or patients with lung metastasis were
selected for the study.
RNA Extraction from Tissue Samples and Quantitative
Real-Time Polymerase Chain Reaction (PCR) of miRNAs
The slides of each patient were re-examined to determine
the areas where tumor cells were most dense. Tumors
and corresponding non-neoplastic squamous epithelium
were manually micro-dissected from 5μm- thick paraffin
sections and placed in 1.5 mL microcentrifuge tubes.
After deparaffinization and rehydration, total RNA was
isolated using Recover All Total Nucleic Acid Isolation
Kit for FFPE tissue in accordance with the manufacturer’s
instructions. The RNA concentration was measured with
a NanoDrop 1000 Spectrophotometer (Thermo Scientific,
USA). Ten nanograms of total RNA were reversetranscribed
for RNU6b, mir-126, mir-182, and mir-486-
5p using the Taqman MicroRna Reverse Transcription
Kit. Reverse transcription was performed under the
following conditions: 16°C for 30 min, 42°C for 30 min,
and 85°C for 5 min with a sample volume of 15 μl. The
real-time PCR was performed in the 7500 Real-Time PCR
system (ABI, Applied Biosystems, USA) using TaqMan
MicroRNA Assays and TaqMan Universal PCR Master
Mix with a sample volume of 20 μl (7.67 μL nuclease-free
water, 10 μl TaqMan Universal PCR Master Mix, 1 μl
TaqMan Small RNA Assay, and 1.33 μl product from the
reverse transcription reaction). All reagents used in this
study were purchased from Thermo Fisher Scientific Inc.
(Thermo Scientific/Ambion, USA). All the samples were
run in triplicate, and no-template controls were tested
alongside actual samples in each experiment. After initial
enzyme activation at 95°C for 10 min and 40 cycles of 15
s denaturation at 95°C were performed, 1 min annealing
and extension at 60°C was carried out. Raw RT-qPCR data
were obtained using Applied Biosystems7500 Real-Time
PCR Software version 2.0, and the cycle threshold (Ct)
values were used to analyze the expression levels of targeted
miRNAs. The expression levels were normalized to the
RNU6B (endogenous control) expression. The miRNA
relative amounts were determined using the comparative
Ct method (ΔΔCT = ΔCT [the tumor tissue sample] – ΔCT
[the corresponding non-neoplastic squamous epithelium]).
The fold changes in the expression of the three miRNAs
between each tumor sample and its corresponding nonneoplastic
squamous epithelium were determined using
the the 2–ΔΔCT method.
Data obtained in the study were analyzed statistically using
SPSS version 20.0 software. Fold changes for miRNAs
were expressed graphically and numerically. Comparisons
among primary localizations were performed for Log2
transformed miRNA expression levels using one-way
ANOVA and Tukey’s honest significant difference tests
(Tukey’s HSD). Individual and combined Receiver
Operator Characteristics (ROC) curve analyses for
miRNAs with significant differences among SCC groups
were performed to assess the diagnostic accuracy. The
statistical confidence level was set at 0.95 (α = 0.05). Post
hoc power analysis was performed for miRNA levels with
a statically insignificant difference using G*Power version
188.8.131.52. Differences in expression profiles of miR-126 and
mir-486-5p among groups were significant, with powers of
0.95 and 0.93, respectively
The SCC samples and corresponding non-neoplastic
squamous epithelia of 40 patients were analyzed for mir-
126, mir-182 and mir-486-5p via RT-qPCR analysis. One
lung SCC and one laryngeal SCC patient were excluded
from the study because no expression for RNU6b was
detected. In an attempt to identify anatomical site-specific
miRNA expression patterns, the relative expression levels
of these miRNAs in the SCC subgroups were determined
and log2 transformed, as represented in the box plot
graphs (Figure 1A-C
). The results shown in Figure 1A-C
indicated that mir-126 was under-expressed in all groups.
mir-182 was overexpressed in lung and laryngeal SCCs
and underexpressed in oral and hypopharyngeal SCCs.
mir-486-5p was overexpressed in oral and hypopharyngeal
SCCs and underexpressed in lung and laryngeal SCCs.
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|Figure 1: A-C) Expression levels of the five candidate miRNAs
in lung, oral, hypopharyngeal and laryngeal SCCs. A; mir-126,
B; mir-182, C; mir-486-5p. Scale at y-axis represents fold change
values normalized to the corresponding squamous epithelium.
Line inside the box: median, box: interval between the 25th and
75th percentiles, whiskers: interval between the 10th and 90th
percentiles, circles: outliers.
There were no statistically significant differences in the
mir-126, mir-182 and mir-486-5p expression profiles
between keratinizing type SCCs and non-keratinizing type
SCCs in all anatomic localizations (p>0.05). The miRNA
expression profiles in the lung SCCs were compared with
the expression profiles in the oral cavity, laryngeal, and
hypopharyngeal SCCs. The results are summarized in
Table II. The findings showed that there were noticeably
different expression levels for mir-126, mir-182, and mir-
486-5p between the lung SCCs and hypopharyngeal SCCs
(p < 0.05); for mir-126, mir-182, and mir-486-5p between
the lung SCCs and oral SCCs (p < 0.05); and for mir-126
between the lung SCCs and laryngeal SCCs (p < 0.05).
Click Here to Zoom
|Table II: Analysis of variance (ANOVA) results for miRNA expression between lung, oral, hypopharyngeal, and laryngeal SCC.
ROC curve analysis was performed to assess the value of
these miRNA expression profiles as specific molecular
signatures for anatomic localization. The area under the curves (AUC) for mir-126, mir-182, and mir-486-5p
were 0.93, 0.84, and 0.95, respectively (p < 0.05). All three
miRNAs had good discriminative power in differentiating
lung SCCs from hypopharyngeal SCCs. The combination
signatures of mir-126 and mir-486-5p showed better
prediction than individual miRNA. The optimal cut-off
values of mir-126 and mir-486-5p were – 2.25 and 0.34,
respectively. These findings showed that the combined
expression profiles of mir-126 and mir-486-5p could distinguish lung SCCs from hypopharyngeal SCCs with
100% sensitivity and 100% specificity (Figure 2A).
Click Here to Zoom
|Figure 2: A) ROC curve analysis of the mir-126, mir486-5p and combination of mir-126
and mir-486-5p signature for differentiating lung SCCs from hypopharyngeal SCCs; mir-
126 revealed 80.0% specificity and 88.0% sensitivity with the cut-off point was -2.257 and
mir-486-5p revealed 90.0% specificity and 100.0% sensitivity with the cut-off point was
0.34. Combined expression profiles of mir-126 and mir-486-5p revealed an AUC of 1.00.
B) Analysis of the mir-126, mir486-5p and combination of mir-126 and mir-486-
5p signature for differentiating lung SCCs from oral SCCs; mir-126 revealed 90.0%
specificity and 88.0% sensitivity with the cut-off point was-2.1785 and mir-486-5p
revealed 80.0% specificity and 100.0% sensitivity with the cut-off point was -0.1122.
Combined expression profiles of mir-126 and mir-486-5p revealed an AUC of 1.00
(100% sensitivity and 100% specificity).
C) Analysis of the mir-126 signature for differentiating lung SCCs from laryngeal SCCs;
mir-126 revealed 100.0% specificity and 100.0% sensitivity with the cut-off point was-
ROC: Receiver operating characteristic, AUC: Area under the curve, CI: Confidence interval
mir-126 and mir-486-5p were differentially expressed
between the lung SCCs and oral SCCs. ROC curve analysis
indicated that these miRNA expression profiles were a
significant discriminant factor between lung SCCs and oral
SCCs. The AUCs for mir-126 and mir-486 were 0.93 and
0.96, respectively, and when combined, the AUC was 1.00
(p < 0.05). The optimal cut-off values of mir-126 and mir-486 were – 2.17 and – 0.11, respectively. In addition to the
hypopharyngeal SCC, the combined expression profiles of
mir-126 and mir-486 could distinguish lung SCCs from
oral SCCs with 100% sensitivity and 100% specificity
Only mir-126 was differentially expressed between lung
SCCs and laryngeal SCCs. ROC curve analyses revealed
that the optimal cut-off value of mir-126 was – 1.63, and mir-126 was sufficiently effective to differentiate between
lung SCCs and laryngeal SCCs (AUC = 1.00) (Figure 2C).
The laryngeal SCCs group included five glottic laryngeal
SCC cases and four supraglottic laryngeal SCC cases that
predominantly located in the epiglottis without false
cord involvement. There were no statistically significant
differences in the mir-126 expression profile between the
supraglottic laryngeal SCCs and the glottic laryngeal SCCs
cases. (p > 0.05).
Oral and hypopharyngeal SCCs originate from squamous
cells in the mucosal lining of the upper aerodigestive tract
. At the third month of prenatal development, the larynx
is lined entirely by pseudostratified epithelium 30
age, this epithelium is gradually replaced by stratified
squamous epithelium except for the ventricle, the subglottic,
and rare microscopic patches in the supraglottic region 30,31
. The glottic and some of the supraglottic laryngeal SCCs
arises from the stratified squamous epithelium. However,
the rest of the laryngeal SCCs arises from the metaplastic
squamous epithelium 32,33
Lung SCCs originate in the lower respiratory tract
epithelium, and unlike the upper aerodigestive tract, this
epithelium does not normally contain squamous cells.
Long-term exposure to irritants causes epithelial changes in
the bronchial epithelium, creating a reparative reaction that
causes squamous metaplasia and epithelial dysplasia 34,35. Lung SCCs develop from these metaplastic-dysplastic
cells 34. SCCs arising from keratinocytes or metaplastic
cells often exhibit similar histological appearance under the
Considering the differences in the developmental stages
of these tumors, SCCs may differ in terms of genetic and
epigenetic features. Many studies have shown that tumors
with similar histological appearance originating from
different anatomic localizations have genetic and epigenetic
differences specific to the localization 8,10,34.
Studies have also emphasized that tumors carry specific
genetic and epigenetic features to metastatic foci and the
localization of tumors can be predicted by evaluating these
properties 14,15. In this study, the expression patterns of
mir-126, mir-182 and mir-486-5p were analyzed in lung,
oral cavity, hypopharyngeal, and laryngeal SCCs, which
have been shown to be highly significant and consistently
dysregulated miRNAs in lung cancer. The study findings
revealed that the lung, oral cavity, hypopharyngeal, and
laryngeal SCCs had distinct miRNA expression profiles.
Munoz-Largacha et al. also showed that lung SCCs and
HNSCCs had distinct miRNA expression profiles 10
in a study which demonstrated that 48 miRNAs were
differentially expressed between lung SCCs and HNSCCs.
They found mir-10a expression was greater (-3.5 to - 5.3-
fold) in lung SCCs and miR-10b expression was greater
(1.7-fold) in HNSCCs; the expression ratio of mir-10a to
mir-10b had a strong predictive power of tumor anatomical
site in the training and the validation data sets (AUC: 0.92-
0.98). They also stated that expression profile of several
miRNA may be useful for discriminating between HNSCC and lung SCC. The fold change of mir-126, mir-182 and
mir-486 between HNSCC and lung SCC were – 1.63, 1.03
and 1.33, respectively, in their data sets. In addition to those
findings, from the current study results it was observed
that mir-126, mir-182, and mir-486-5p were differentially
expressed between the lung SCCs and hypopharyngeal
SCCs, mir-126 and mir-486-5p were differentially
expressed between the lung SCCs and oral SCCs, and mir-
126 was differentially expressed between the lung SCCs and
laryngeal SCCs. The most important findings of this study
were that the expression profiles of mir-126 and mir-486-
5p were strongly correlated with tumor localization.
mir-126 has a role in the regulation of 81 genes such as
MAPK1, VEGFA, PIK3CA, PIK3CD, AKT1, and STK1119.
Target pathway prediction has shown that most of these
genes are involved in the regulation of proliferation 36,37. mir-126 plays an important role in lung tumorigenesis
by influencing the PI3K/Akt pathway and MAPK signaling
pathway via regulation of AKT1, PIK3CA, and MAPK1 36,38. Crawford et al. also observed that alteration of mir-
126 expression affected adhesion, and the migratory and
invasive capacity of lung cancer, through Crk regulation
39. Several studies have indicated that mir-126 is
significantly downregulated miRNA in lung cancer 17,20,39. The current study findings showed that although mir-
126 was downregulated in all SCC groups, the expression of
mir-126 was significantly lower in lung SCCs than in other
Studies have indicated that mir-126 is also an important
biomarker in the diagnosis of lung cancer 17,20,21,38,39.
Song et al. revealed that combinations of mir-126, mir-182,
and mir-205 have good accuracy in the prediction of lung
carcinoma 21. Zhu et al. and Sanfienzo et al. reported that
analysis of serum and plasma miRNAs expression profiles,
including mir-126, could distinguish lung carcinoma
patients from healthy volunteers 22,40. Furthermore,
Barshack et al. compared the mir-126 expression profile
of lung tumors and metastases of the tumors to the lungs,
and observed that mir-126 expression was downregulated
in primary lung tumor and expression analyses could
distinguish primary lung tumor from lung metastases 20.
The current study findings showed that mir-126 expression
profile was highly specific for tumor anatomic localization
and analysis of expression levels proved to be a promising
method with the potential to differentiate between lung
SCCs and laryngeal SCCs (p < 0.0001, 95% CI).
mir-486-5p is another important miRNA, involved in lung
tumorigenesis, which induces translation of numerous
validated genes, such as PTEN, CDK4, ARHGAP, and PIK3R1 36,37. The interaction between mir-486-5p and
these genes influences cell cycle progression, apoptosis,
and the PI3K/Akt pathway 36,37. Yu et al. showed that
mir-486-5p inhibited the development and invasion
of lung tumors through the repression of GAB2, while
Wang et al. showed that the downregulation of miR-
486-5p contributed to the development of lung cancer
by regulating ARHGAP5 41,42. Several studies have
shown that mir-486-5p acts as a tumor suppressor and is
one of the most significantly downregulated miRNAs in
lung cancer 18,41,42. mir-486-5p could also provide a
diagnostic approach for detecting lung cancer 23,24. In
meta-analyses by Tian et al., it was indicated that mir-486
expression analyses of tissue, plasma, blood, and serum
could provide a biomarker for lung cancer diagnosis 18,25. In addition to this result, the current study findings
suggested that mir-486-5p expression levels were also
highly specific for tumor localization and mir486-5p
has great potential to be a novel, sensitive, and reliable
biomarker for differential diagnosis. It was determined that
mir-486-5p was down-regulated in lung SCCs and laryngeal
SCCs, and up-regulated in hypopharyngeal and oral cavity
SCCs. The analysis of mir-486-5p expression profiles can
differentiate lung SCCs from hypopharyngeal SCCs with
90% sensitivity and 100% specificity and can differentiate
lung SCCs from oral SCCs with 80% sensitivity and 100%
specificity. In addition, the combined expression profiles of
mir-126 and mir-486-5p could distinguish lung SCCs from
hypopharyngeal SCCs and oral SCCs with 100% sensitivity
and 100% specificity.
mir-182 can affect 2105 genes and plays an important
role in carcinogenesis in various cancer tissues 36,37. It
has been reported that the target genes of mir-182-5p are
enriched in 42 KEGG pathways such as ‘NSCLC’, ‘cell cycle’,
‘apoptosis’, ‘p53 signaling pathway’, and ‘Wnt signaling
pathway’ 37. Lou et al. analyzed the TCGA database and
observed that mir-182 regulated 81 gene functions in lung
SCCs by repressing these gene functions 19. In addition,
analyses of TCGA data have revealed that mir-182, whose
over expression has been reported recently to be associated
with overall poor survival in patients with lung SCC, was
one of the most upregulated miRNAs in lung SCCs 19,43. Compatible with this research, the current study
results showed that mir-182 was upregulated in the oral,
hypopharyngeal, laryngeal, and lung SCC.
The results of this study demonstrated that SCCs arising
from different anatomic localizations in the oral,
hypopharyngeal, laryngeal, and lung regions had mir-126 and mir486-5p expression profiles specific to the
localization and these expression profiles were strongly
associated with tumor localization. The weakest point of this
study was the small sample size. Nevertheless, the findings
of this study will provide a basis for further investigations
into miRNA-based differential diagnosis. Further research
of larger samples may help to clarify the diagnostic utility
of these miRNAs as a predictive tool.
In conclusion, recent studies have revealed that the
miRNAs expressed differentially between different tissue
and tumor types and their highly specific expression
profiles can be used for diagnosis through the classification
of primary cancers and their metastases. The results of
this study revealed that the SCCs arising from the oral,
hypopharyngeal, laryngeal, and lung regions had distinct
mir-126 and mir-486-5p expression profiles, and mir-126
and mir-486-5p expression analysis may provide potential
biological markers for the prediction of the primary
localization of SCCs.
The authors would like to thank Aptullah Haholu for his
contribution to the histopathologic analyses.
CONFLICT of INTEREST
The authors declare that they have no conflict of interest.
This study was supported by the Gulhane Military Medical
Academy, Haydarpasa Training Hospital Epidemiology
Concept: GI, ZK, ÝY, Design: GI, ZK, ÝY, Data collection
or processing: GI, ÝY, EE, Analysis or Interpretation: GI,
ÝY, ET, Literature search: GI, ZK, ÝY, EE, Writing: GI,
Approval: GI, ZK, ÝY, EE, ET, DD, AG, ÞY.
1) Thompson L. World Health Organization classification of
tumours: pathology and genetics of head and neck tumours. Ear
Nose Throat J. 2006;85:74.
2) Pereira TC, Share SM, Magalhães AV, Silverman JF. Can we tell
the site of origin of metastatic squamous cell carcinoma? An
immunohistochemical tissue microarray study of 194 cases. Appl
Immunohistochem Mol Morphol. 2011; 19:10-4.
3) Hainsworth JD, Fizazi K. Treatment for patients with unknown
primary cancer and favorable prognostic factors. Semin Oncol.
2009; 36: 44-51.
4) Geurts TW, Nederlof PM, van den Brekel MW, van’t Veer LJ,
de Jong D, Hart AA, van Zandwijk N, Klomp H, Balm AJ, van
Velthuysen ML. Pulmonary squamous cell carcinoma following
head and neck squamous cell carcinoma: Metastasis or second
primary? Clin Cancer Res. 2005; 11: 6608-14.
5) Slaughter DP, Southwick HW, Smejkal W. Field cancerization
in oral stratified squamous epithelium; Clinical implications of
multicentric origin. Cancer. 1953; 6: 963-8.
6) Ferlito A, Shaha AR, Silver CE, Rinaldo A, Mondin V. Incidence
and sites of distant metastases from head and neck cancer. ORL J
Otorhinolaryngol Relat Spec. 2001; 63: 202-7.
7) Yilmaz I, Erkul BE, Ozturk Sari S, Issin G, Tural E, Terzi Kaya
Terzi N, Karatay H, Celik M, Ulusan M, Bilgic B. Promoter
region mutations of the telomerase reverse transcriptase (TERT)
gene in head and neck squamous cell carcinoma. Oral Surg Oral
Med Oral Pathol Oral Radiol. 2020; 130: 63-70.
8) Talbot SG, Estilo C, Maghami E, Sarkaria IS, Pham DK,
O-charoenrat P, Socci ND, Ngai I, Carlson D, Ghossein R,
Viale A, Park BJ, Rusch VW, Singh B. Gene expression profiling
allows distinction between primary and metastatic squamous cell
carcinomas in the lung. Cancer Res. 2005; 65: 3063-71.
9) Shimizu S, Yatabe Y, Koshikawa T, Haruki N, Hatooka S, Shinoda
M, Suyama M, Ogawa M, Hamajima N, Ueda R, Takahashi T,
Mitsudomi T. High frequency of clonally related tumors in cases
of multiple synchronous lung cancers as revealed by molecular
diagnosis. Clin Cancer Res. 2000; 6: 3994-9.
10) Muñoz-Largacha JA, Gower AC, Sridhar P, Deshpande A,
O’Hara CJ, Yamada E, Godfrey TE, Fernando HC, Litle VR.
miRNA profiling of primary lung and head and neck squamous
cell carcinomas: Addressing a diagnostic dilemma. J Thorac
Cardiovasc Surg. 2017; 154: 714-27.
11) Lee RC, Ambros V. An extensive class of small RNAs in
Caenorhabditis elegans. Science. 2001; 294: 862-4.
12) He L, Hannon GJ. MicroRNAs: small RNAs with a big role in
gene regulation. Nat Rev Genet. 2004; 5: 522-31.
13) Croce CM. Causes and consequences of microRNA dysregulation
in cancer. Nat Rev Genet. 2009; 10: 704-14.
14) Lu J, Getz G, Miska EA, Alvarez-Saavedra E, Lamb J, Peck D,
Sweet-Cordero A, Ebert BL, Mak RH, Ferrando AA, Downing
JR, Jacks T, Horvitz HR, Golub TR. MicroRNA expression
profiles classify human cancers. Nature. 2005; 435: 834-8.
15) Barker EV, Cervigne NK, Reis PP, Goswami RS, Xu W, Weinreb
I, Irish JC, Kamel-Reid S. microRNA evaluation of unknown
primary lesions in the head and neck. Mol Cancer. 2009;8:127.
16) Võsa U, Vooder T, Kolde R, Vilo J, Metspalu A, Annilo T. Metaanalysis
of microRNA expression in lung cancer. Int J Cancer.
2013; 132: 2884-93.
17) Li C, Yin Y, Liu X, Xi X, Xue W, Qu Y. Non-small cell lung
cancer associated microRNA expression signature: Integrated
bioinformatics analysis, validation and clinical significance.
Oncotarget. 2017; 8: 24564-78.
18) Tian F, Wang J, Ouyang T, Lu N, Lu J, Shen Y, Bai Y, Xie X,
Ge Q. MiR-486-5p serves as a good biomarker in nonsmall cell
lung cancer and suppresses cell growth with the involvement of a
target PIK3R1. Front Genet. 2019;10: 688.
19) Luo J, Shi K, Yin SY, Tang RX, Chen WJ, Huang LZ, Gan TQ,
Cai ZW, Chen G. Clinical value of miR-182-5p in lung squamous
cell carcinoma: A study combining data from TCGA, GEO, and
RT-qPCR validation. World J Surg Oncol. 2018;16:76.
20) Barshack I, Lithwick-Yanai G, Afek A, Rosenblatt K, Tabibian-
Keissar H, Zepeniuk M, Cohen L, Dan H, Zion O, Strenov
Y, Polak-Charcon S, Perelman M. MicroRNA expression
differentiates between primary lung tumors and metastases to
the lung. Pathol Res Pract. 2010; 206: 578-84.
21) Song R, Liu Q, Hutvagner G, Nguyen H, Ramamohanarao K,
Wong L, Li J. Rule discovery and distance separation to detect
reliable miRNA biomarkers for the diagnosis of lung squamous
cell carcinoma. BMC Genomics. 2014; 15: S16.
22) Zhu W, Zhou K, Zha Y, Chen D, He J, Ma H, Liu X, Le H, Zhang
Y. Diagnostic value of serum miR-182, miR-183, miR-210, and
miR-126 levels in patients with early-stage non-small cell lung
cancer. PLoS One. 2016; 11: e0153046.
23) Yu S, Geng S, Hu Y. miR-486-5p inhibits cell proliferation and
invasion through repressing GAB2 in non-small cell lung cancer.
Oncol Lett. 2018;16: 3525-30.
24) Wang J, Tian X, Han R, Zhang X, Wang X, Shen H, Xue L, Liu
Y, Yan X, Shen J, Mannoor K, Deepak J, Donahue JM, Stass SA,
Xing L, Jiang F. Downregulation of miR-486-5p contributes to
tumor progression and metastasis by targeting protumorigenic
ARHGAP5 in lung cancer. Oncogene. 2014;33:1181-9.
25) Tian F, Shen Y, Chen Z, Li R, Lu J, Ge Q. Aberrant miR-181b-5p
and miR-486-5p expression in serum and tissue of non-small cell
lung cancer. Gene. 2016; 591: 338-43.
26) Esquela-Kerscher A, Slack FJ. Oncomirs - microRNAs with a role
in cancer. Nat Rev Cancer. 2006; 6: 259-69.
27) Fletcher AM, Heaford AC, Trask DK. Detection of metastatic
head and neck squamous cell carcinoma using the relative
expression of tissue-specific mir-205. Transl Oncol. 2008;1:202-
28) Li N, Kaur S, Greshock J, Lassus H, Zhong X, Wang Y, Leminen
A, Shao Z, Hu X, Liang S, Katsaros D, Huang Q, Bützow R, Weber
BL, Coukos G, Zhang L. A combined array-based comparative
genomic hybridization and functional library screening approach
identifies mir-30d as an oncomir in cancer. Cancer Res. 2012; 72:
29) Yu T, Ma P, Wu D, Shu Y, Gao W. Functions and mechanisms of
microRNA-31 in human cancers. Biomed Pharmacother. 2018;
30) Tucker JA, Tucker GF, Vidic B, Stead J. Survey of the development
of laryngeal epithelium. Ann Otol Rhinol Laryngol. 1976;85:
31) Matthew RL, Laura WL. Larynx. In: Matthew RL, Laura WL,
editors. Diagnostic Pathology: Normal Histology. Salt Lake City,
UT: Elsevier; 2018. 190-3.
32) Thompson, Lester DR. Larynx. In: Noel W, Richard JC, Saul
S, Lawrence MW, editors. Modern Surgical Pathology. WB
Saunders: Elsevier; 2009. 208-45.
33) Lu B. Squamous metaplasia of the mucosa of the human laryngeal
ventricle: A clinicopathological study with reference to the
possibility of de novo carcinogenesis. Nihon Jibiinkoka Gakkai
Kaiho. 1992; 95: 360-72.
34) Auerbach O, Stout AP, Hammond EC, Garfinkel L. Changes
in bronchial epithelium in relation to cigarette smoking and in
relation to lung cancer. N Engl J Med. 1961;265: 253-67.
35) Sutherland KD, Berns A. Cell of origin of lung cancer. Mol Oncol.
2010; 4: 397-403.
36) Vlachos IS, Zagganas K, Paraskevopoulou MD, Georgakilas G,
Karagkouni D, Vergoulis T, Dalamagas T, Hatzigeorgiou AG.
DIANA-miRPath v3.0: deciphering microRNA function with
experimental support. Nucleic Acids Res. 2015; 43: W460-6.
37) Backes C, Kehl T, Stöckel D, Fehlmann T, Schneider L, Meese
E, Lenhof HP, Keller A. miRPathDB: a new dictionary on
microRNAs and target pathways. Nucleic Acids Res. 2017; 45:
38) Zheng W, Zhou Y, Lu J, Xu H, Lei L, Chen C, Zhao J, Xu L. The
prognostic value of miR-126 expression in non-small-cell lung
cancer: a meta-analysis. Cancer Cell Int. 2017; 17: 71.
39) Crawford M, Brawner E, Batte K, Yu L, Hunter MG, Otterson
GA, Nuovo G, Marsh CB, Nana-Sinkam SP. MicroRNA-126
inhibits invasion in non-small cell lung carcinoma cell lines.
Biochem Biophys Res Commun. 2008; 373: 607-12.
40) Sanfiorenzo C, Ilie MI, Belaid A, Barlési F, Mouroux J, Marquette
CH, Brest P, Hofman P. Two panels of plasma microRNAs
as non-invasive biomarkers for prediction of recurrence in
resectable NSCLC. PLoS One. 2013; 8: e54596.
41) Yu S, Geng S, Hu Y. miR-486-5p inhibits cell proliferation and
invasion through repressing GAB2 in non-small cell lung cancer.
Oncol Lett. 2018; 16: 3525-30.
42) Wang J, Tian X, Han R, Zhang X, Wang X, Shen H, Xue L, Liu
Y, Yan X, Shen J, Mannoor K, Deepak J, Donahue JM, Stass SA,
Xing L, Jiang F. Downregulation of miR-486-5p contributes to
tumor progression and metastasis by targeting protumorigenic
ARHGAP5 in lung cancer. Oncogene. 2014; 33: 1181-9.
43) Zhu W, Liu X, He J, Chen D, Hunag Y, Zhang YK. Overexpression
of members of the microRNA-183 family is a risk factor for lung
cancer: a case control study. BMC Cancer. 201; 11: 393.