Patient characteristics
The clinicopathological data of 10 Hypopharyngeal carcinoma patients are summarized in Table 1. The collected clinical data mainly include age, clinical stage, tumor diameter, lymphatic metastasis, distant metastasis, tumor differentiation degree, etc.
Table 1
The clinicopathological data of 10 Hypopharyngeal carcinoma patients
Variable
|
|
No of patients N = 10 (%)
|
Age (years)
|
Mean ± SD
|
55.1 ± 9.42
|
|
Range
|
35–68
|
Clinical stage
|
I
|
0(0)
|
|
II
|
0(0)
|
|
III
|
7(70)
|
|
IV
|
1(10)
|
|
NA
|
2(20)
|
Tumor size
|
T1
|
0(0)
|
|
T2
|
4(40)
|
|
T3
|
1(10)
|
|
T4
|
3(30)
|
|
NA
|
2(20)
|
Lymph nodes status
|
N0
|
0(0)
|
|
N1
|
3(30)
|
|
N2
|
4(40)
|
|
N3
|
1(10)
|
|
NA
|
2(20)
|
Distant metastasis
|
M0
|
7(70)
|
|
M1
|
1(10)
|
|
NA
|
2(20)
|
tumor differentiation
|
low
|
3(30)
|
|
Medium
|
6(60)
|
|
high
|
1(10)
|
Gene Variation Spectrum
The detection of SNV and indel in 10 patients with Hypopharyngeal carcinoma was statistically analyzed. We found that A / G, C / T, G / A transitions were more common than other types of single nucleotide mutations in all patients with Hypopharyngeal carcinoma (Fig. 1. A). Exon mutations accounted for 4.72% of all mutations. The mutation types of single nucleotide mutations in the exon region were counted. The results showed that missense mutations account for 51.47% of all exon mutations. Stop gain/loss mutations account for 1.57% of all mutations, and nonsense mutations account for 45.33% of all mutations. In addition, there are 1.63% of unknown mutations (Fig. 1.B). In the detection of insertions and deletions, exon mutations accounted for 1.59%. Frameshift deletion and frameshift insertion accounted for 43.8% and 11.7% of all exon mutations, respectively. Nonframeshift deletion and nonframeshift insertion accounted for 32.72% and 7.01% of all exon mutations, and stop gain/loss accounted for 1.36% of all mutations. In addition, there are 3.41% of unknown mutations (Fig. 1.C). In order to better understand the genetic mutations of each patient, the number of SNP/indel in different regions of the genome of each patient and the distribution of the number of different types of SNP/indel in the coding region were counted (Figure S1-S2).
We identified 8113 non-synonymous mutations after screening, including 8096 missense mutations, 1 stop gain mutation and 16 unknown mutations in 5326 genes. There were 1066 mutated genes in two patients, 339 in three patients, 80 in four patients and 22 in five patients. Interestingly, 8 genes including MEGF8, ITPR1, DYSF, DNAH10, CUL7, MYH14, LRP1, and ASTN1 have mutations in six patients, 3 genes including TTN, ASH1L, and MYH11 have mutations in seven patients, and KMT2C has mutations in ten patients. We found that all of the 12 genes had new mutations except kmt2c by comparing the dbSNP database(Table 2, F1, F2).
Table 2
Mutations of mutated genes in at least 6 patients
Gene
|
Mutation proportion
|
Mutation information
|
MEGF8
|
60%
|
rs377748543,rs370522595,3 novel mutations
|
ITPR1
|
60%
|
rs752791333,rs773763162,3 novel mutation
|
DYSF
|
60%
|
rs573666770,4 novel mutations
|
DNAH10
|
60%
|
rs148844278,rs748343428,2 novel mutations
|
CUL7
|
60%
|
rs757730802,rs373305024,3 novel mutations
|
TTN
|
70%
|
rs372496072,rs35683768,rs878903962,rs373854384,rs371908649,3 novel mutations
|
MYH14
|
60%
|
rs762779652,rs140118363,4 novel mutations
|
LRP1
|
60%
|
rs199726731,9 novel mutations
|
ASTN1
|
60%
|
6 novel mutations
|
ASH1L
|
70%
|
6 novel mutations
|
MYH11
|
70%
|
rs751495086,rs757099566,4 novel mutations
|
KMT2C
|
100%
|
rs2479172,rs28522267,rs77735469,rs201062304,rs28522267
|
High-frequency mutation genes in hypopharyngeal carcinoma in TCGA database
The 20 oncogenes most frequently mutated in the TCGA database were compared with our screened data, and the results showed that 13 genes including TTN, TP53, ANK3, UPF2, C6, BRCA2, CD163L1, ZNF831, KRT85, MACF1, SYT6, TPO, and SLIT2 had mutations in our samples (Table 3). TTN (70%), ANK3 (40%), and TP53 (30%) have a higher mutation rate, which is also ranked in the top three in the TCGA database. It showed that our results are consistent with the results of the TCGA database.
Table 3
Comparison of the TOP20 genes of hypopharyngeal carcinoma in the TCGA database and the samples in this research
|
1
|
2
|
3
|
4
|
5
|
6
|
7
|
8
|
9
|
10
|
Mutation proportion
|
TTN
|
-
|
+
|
+
|
-
|
+
|
+
|
+
|
-
|
+
|
+
|
70%
|
TP53
|
-
|
-
|
+
|
-
|
+
|
-
|
-
|
+
|
-
|
-
|
30%
|
ANK3
|
+
|
+
|
-
|
-
|
-
|
+
|
-
|
-
|
+
|
-
|
40%
|
UPF2
|
-
|
+
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
10%
|
MFAP3
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
0%
|
DST
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
0%
|
C6
|
-
|
+
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
10%
|
BRCA2
|
-
|
+
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
10%
|
CD163L1
|
-
|
-
|
+
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
10%
|
MUC16
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
0%
|
ZNF831
|
-
|
-
|
-
|
-
|
-
|
-
|
+
|
-
|
-
|
-
|
10%
|
KRT85
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
+
|
-
|
10%
|
MACF1
|
-
|
-
|
-
|
-
|
-
|
+
|
-
|
+
|
-
|
-
|
20%
|
CCDC146
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
0%
|
SYT6
|
-
|
+
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
10%
|
ANO7
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
0%
|
TPO
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
+
|
-
|
10%
|
RBAK-RB
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
0%
|
GRM8
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
0%
|
SLIT2
|
+
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
+
|
-
|
20%
|
+mutate in the sample -not mutate in the sample |
Screening pathogenic genes based on ACMG guidelines
72 pathogenic or possibly pathogenic mutations were identified in 53 genes according to the ACMG guidelines, including SNVs or INDELs (Table F3). There were 2 pathogenic or possibly pathogenic mutations in BIVM-ERCC5, FBN2, MYH11, SCN2A, S4CNA and SDHA, 3 pathogenic or possibly pathogenic mutations in RYR1 and SCN5A, and 4 pathogenic or possibly pathogenic mutations in LDLR, TP53 and TTN. 4 unreported mutations were found by comparison to the dbSNP database, and these mutations may cause disease, including two mutations in BIVM-ERCC5 (exon6:c.C640T:p.R214C), (exon14:c. C2002T:p.R668C), GJA3 (exon2:c.C56T:p.T19M), SPG7 (exon9:c.C1198T:p.R400W), these mutations may be related to the pathogenesis of hypopharyngeal carcinoma.
GO annotation of pathogenic and possibly pathogenic genes
Gene ontology annotation and pathway analyses were performed on 53 pathogenic genes and possibly pathogenic genes. The BP of these genes is related to muscle contraction, visual perception, cell proliferation, positive regulation of transcription, DNA-templated, multicellular organism development, sodium ion transmembrane transport, positive regulation of gene expression, nervous system development, transport, etc. The main cellular components of these genes involve integral component of membrane, integral component of plasma membrane, mitochondrion, dendrite, intracellular membrane-bounded organelle, Z disc, mitochondrial matrix, voltage-gated sodium channel complex, apical part of cell, etc. GP-MF annotation showed that these genes are related to some molecular functions, including protein binding, ATP binding, calcium ion binding, calmodulin binding, enzyme binding, protein binding, ubiquitin protein ligase binding, voltage-gated sodium channel activity ATPase activity, coupled to transmembrane movement of substances, flavin adenine dinucleotide binding (Fig. 2, table F4).
Altered pathways
53 pathogenic or potentially pathogenic genes were analyzed by KEGG enrichment, and the results showed that these genes were highly enriched in some cancers and cancer-related pathways (Table 4). Enrichment pathways mainly include: (a). Various cancers, including thyroid cancer, bladder cancer, endometrial cancer, non-small cell lung cancer, melanoma, pancreatic cancer, colorectal cancer, small cell lung cancer, etc. (b) some signaling pathways closely related to cancer, such as MAPK signaling pathway, HIF-1 signaling pathway, central carbon metabolism in cancer, etc. We constructed a PPI network of 53 pathogenic genes to understand the interaction between 53 pathogenic genes (Fig. 3). The figure shows that these genes include 52 nodes and 62 edges.
Table 4
Pathway annotation of pathogenic and likely pathogenic genes
ID
|
Description
|
Background number
|
P-Value
|
count
|
Gene ID
|
hsa01100
|
Metabolic pathways
|
1433
|
1.21×10− 4
|
9
|
PIGA|TK2|HOGA1|GUSB
|NDUFS1|COQ2|PPOX|MUT|SDHA
|
hsa05200
|
Pathways in cancer
|
530
|
8.35×10− 5
|
6
|
COL4A5|TP53|JAG1|EGFR|PAX8|AR
|
hsa01522
|
Endocrine resistance
|
98
|
1.14×10− 5
|
4
|
TP53|ABCB11|EGFR|JAG1
|
hsa05165
|
Human papillomavirus infection
|
330
|
1.08×10− 3
|
4
|
TP53|JAG1|COL4A5|EGFR
|
hsa04151
|
PI3K-Akt signaling pathway
|
354
|
1.40×10− 3
|
4
|
TP53|COL4A5|EGFR|INSR
|
hsa02010
|
ABC transporters
|
45
|
3.84×10− 5
|
3
|
ABCA4|ABCB11|ABCD1
|
hsa03420
|
Nucleotide excision repair
|
47
|
4.34×10− 5
|
3
|
ERCC2|ERCC5|BIVM-ERCC5
|
hsa05215
|
Prostate cancer
|
97
|
3.41×10− 4
|
3
|
TP53|AR|EGFR
|
hsa05224
|
Breast cancer
|
147
|
1.11×10− 3
|
3
|
TP53|JAG1|EGFR
|
hsa04932
|
Non-alcoholic fatty liver
disease (NAFLD)
|
149
|
1.15×10− 3
|
3
|
INSR|SDHA|NDUFS1
|
hsa05160
|
Hepatitis C
|
155
|
1.29×10− 3
|
3
|
TP53|LDLR|EGFR
|
hsa05016
|
Huntington disease
|
193
|
2.38×10− 3
|
3
|
TP53|SDHA|NDUFS1
|
hsa04010
|
MAPK signaling pathway
|
295
|
765×10− 3
|
3
|
TP53|EGFR|INSR
|
hsa00630
|
Glyoxylate and dicarboxylate metabolism
|
30
|
8.63×10− 4
|
2
|
HOGA1|MUT
|
hsa05216
|
Thyroid cancer
|
37
|
1.28×10− 3
|
2
|
TP53|PAX8
|
hsa05219
|
Bladder cancer
|
41
|
1.56×10− 3
|
2
|
TP53|EGFR
|
hsa00860
|
Porphyrin and chlorophyll
metabolism
|
42
|
1.63×10− 3
|
2
|
GUSB|PPOX
|
hsa04913
|
Ovarian steroidogenesis
|
49
|
2.18×10− 3
|
2
|
LDLR|INSR
|
hsa04979
|
Cholesterol metabolism
|
50
|
2.27×10− 3
|
2
|
ABCB11|LDLR
|
hsa05213
|
Endometrial cancer
|
58
|
3.00×10− 3
|
2
|
TP53|EGFR
|
hsa05223
|
Non-small cell lung cancer
|
66
|
3.84×10− 3
|
2
|
TP53|EGFR
|
hsa05230
|
Central carbon metabolism in cancer
|
69
|
4.18×10− 3
|
2
|
TP53|EGFR
|
hsa04520
|
Adherens junction
|
72
|
4.53×10− 3
|
2
|
EGFR|INSR
|
hsa04976
|
Bile secretion
|
72
|
4.53×10− 3
|
2
|
ABCB11|LDLR
|
hsa05218
|
Melanoma
|
72
|
4.53×10− 3
|
2
|
TP53|EGFR
|
hsa05212
|
Pancreatic cancer
|
75
|
4.89×10− 3
|
2
|
TP53|EGFR
|
hsa05214
|
Glioma
|
75
|
4.89×10− 3
|
2
|
TP53|EGFR
|
hsa00983
|
Drug metabolism - other enzymes
|
79
|
5.40×10− 3
|
2
|
GUSB|TK2
|
hsa05210
|
Colorectal cancer
|
86
|
6.34×10− 3
|
2
|
TP53|EGFR
|
hsa04540
|
Gap junction
|
88
|
6.63×10− 3
|
2
|
EGFR|TUBB3
|
hsa04211
|
Longevity regulating pathway
|
89
|
6.77×10− 3
|
2
|
TP53|INSR
|
hsa05410
|
Hypertrophic cardiomyopathy (HCM)
|
90
|
6.91×10− 3
|
2
|
TTN|SGCA
|
hsa05222
|
Small cell lung cancer
|
93
|
7.35×10− 3
|
2
|
TP53|COL4A5
|
hsa05414
|
Dilated cardiomyopathy (DCM)
|
96
|
7.81×10− 3
|
2
|
TTN|SGCA
|
hsa04928
|
Parathyroid hormone synthesis, secretion and action
|
106
|
9.41×10− 3
|
2
|
CASR|EGFR
|
hsa04066
|
HIF-1 signaling pathway
|
109
|
9.92×10− 3
|
2
|
EGFR|INSR
|