Association of alternative splicing and tumor immune in gastric cancer based on TCGA data set

doi:10.3969/j.issn.1674-8115.2021.04.006

Abstract

Abstract: Objective

· To investigate the association of alternative splicing and tumor immune in gastric cancer based on The Cancer Genome Atlas (TCGA) data set.

Methods

· Transcriptomic data, genomic data and corresponding clinical information of 375 tumor tissues and 32 paired adjacent normal tissues from gastric cancer patients were separately downloaded from TCGA portal. Percent-spliced-in matrix containing 452 gastric cancer tissues and paired normal tissues were downloaded from Spliceseq database. The microarray transcriptomic data GSE15459 including 192 gastric cancer patients were downloaded from Gene Expression Omnibus (GEO). ConcensusClusterPlus package was used for classifying the samples based on splicing events. Competitive Gene Set Test Accounting for Inter-gene Correlation (CAMERA) and Gene Set Variation Analysis (GSVA) were used to apply pathway and gene set analysis. CIBERSORT was used to interrogate the condition of tumor microenvironment of samples through deconvolution of profiling of mRNA expression.

Results

· Four hundred and forty-five gastric cancer tissues and paired adjacent normal tissues were included into the study after filtering, involving 4 051 genes and 8 649 splicing events. There were aberrant splicing events existing in gastric cancer tissues compared to adjacent normal tissues. The gastric cancer samples could be divided into 4 subtypes based on different high-frequency splicing events. Many clinical characteristics like T stage, M stage, age, Lauren classification, pathological stage and histological stage among the 4 subtypes were significantly different (P<0.05). The tumor hallmark characteristics and condition of microenvironment were also marked different among the 4 subtypes. The high expression of certain splicing factors were responsible for clustering of the subtypes (log₂FC > 1 and FDR < 0.05), and gene set of core splicing factors was strongly correlated to antigen presentation in tumor (Pearson R = 0.44, P = 0.000).

Conclusion

· The variation of splicing events was closely related to clinical characteristics and tumor microenvironment in gastric cancer. Expression of splicing factors dominates the variation of alternative splicing events. Certain splicing factors were expected to be biomarkers for classification of gastric cancer, and targets for improving the efficacy of immunotherapy.

Key words: alternative splicing, gastric cancer, bioinformatics, tumor microenvironment, The Cancer Genome Atlas (TCGA)

CLC Number:

R735.2

Qi-sheng GU, Mi-li ZHANG, Can CAO, Ji-kun LI. Association of alternative splicing and tumor immune in gastric cancer based on TCGA data set[J]. JOURNAL OF SHANGHAI JIAOTONG UNIVERSITY (MEDICAL SCIENCE), 2021, 41(4): 448-458.

Figures/Tables 10

TrendMD

References 26

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Item	C1 (n=199)	C2 (n=144)	C3 (n=31)	C4 (n=35)	P value	Missing data/%
Mean age at Initial pathological diagnosis/year	65.74±10.69	66.2±10.20	71.13±9.87	59.51± 10.47	0.000	1.2
M stage/n (%)					0.020	5.1
M0	181 (96.3)	125 (91.2)	24 (82.8)	33 (97.1)
M1	7 (3.7)	12 (8.8)	5 (17.2)	1 (2.9)
T stage/n (%)					0.007	2.2
T1	18 (9.0)	3 (2.1)	1 (3.8)	0 (0)
T2	30 (15.1)	41 (29.3)	9 (34.6)	8 (22.9)
T3	97 (48.7)	59 (42.1)	8 (30.8)	14 (40.0)
T4	54 (27.1)	37 (26.4)	8 (30.8)	13 (37.1)
N stage/n (%)					0.636	4.5
N0	59 (30.4)	47 (33.8)	6 (25.0)	10 (30.3)
N1	50 (25.8)	44 (31.7)	10 (41.7)	7 (21.2)
N2	43 (22.2)	22 (15.8)	5 (20.8)	8 (24.2)
N3	42 (21.6)	26 (18.7)	3 (12.5)	8 (24.2)
AJCC pathological stage /n (%)					0.000	5.9
Ⅰ	30 (15.5)	19 (14.0)	5 (22.7)	3 (8.8)
Ⅱ	55 (28.5)	51 (37.5)	4 (18.2)	12 (35.3)
Ⅲ	95 (49.2)	49 (36.0)	4 (18.2)	18 (52.9)
Ⅳ	13 (6.7)	17 (12.5)	9 (40.9)	1 (2.9)
Lauren classification /n (%)					0.000	38.6
Diffuse	36 (25.0)	16 (23.9)	3 (23.1)	21 (77.8)
Intestinal	108 (75.0)	51 (76.1)	10 (76.9)	6 (22.2)
Histological grade/n (%)					0.000	2.2
G1	6 (3.1)	2 (1.4)	2 (6.5)	1 (3.1)
G2	87 (44.8)	51 (35.7)	9 (29.0)	1 (3.1)
G3	101 (52.1)	90 (62.9)	20 (64.5)	30 (93.8)
Gender /n (%)					0.186	0
Female	60 (30.2)	54 (37.5)	14 (45.2)	15 (42.9)
Male	139 (69.8)	90 (62.5)	17 (54.8)	20 (57.1)
Race /n (%)					0.045	13.7
Asian	55 (30.1)	21 (17.2)	1 (7.7)	9 (25.7)
Black	9 (4.9)	3 (2.5)	0 (0)	0 (0)
White	119 (65.0)	98 (80.3)	12 (92.3)	26 (74.3)

Item	C1 (n=199)	C2 (n=144)	C3 (n=31)	C4 (n=35)	P value	Missing data/%
Mean age at Initial pathological diagnosis/year	65.74±10.69	66.2±10.20	71.13±9.87	59.51± 10.47	0.000	1.2
M stage/n (%)					0.020	5.1
M0	181 (96.3)	125 (91.2)	24 (82.8)	33 (97.1)
M1	7 (3.7)	12 (8.8)	5 (17.2)	1 (2.9)
T stage/n (%)					0.007	2.2
T1	18 (9.0)	3 (2.1)	1 (3.8)	0 (0)
T2	30 (15.1)	41 (29.3)	9 (34.6)	8 (22.9)
T3	97 (48.7)	59 (42.1)	8 (30.8)	14 (40.0)
T4	54 (27.1)	37 (26.4)	8 (30.8)	13 (37.1)
N stage/n (%)					0.636	4.5
N0	59 (30.4)	47 (33.8)	6 (25.0)	10 (30.3)
N1	50 (25.8)	44 (31.7)	10 (41.7)	7 (21.2)
N2	43 (22.2)	22 (15.8)	5 (20.8)	8 (24.2)
N3	42 (21.6)	26 (18.7)	3 (12.5)	8 (24.2)
AJCC pathological stage /n (%)					0.000	5.9
Ⅰ	30 (15.5)	19 (14.0)	5 (22.7)	3 (8.8)
Ⅱ	55 (28.5)	51 (37.5)	4 (18.2)	12 (35.3)
Ⅲ	95 (49.2)	49 (36.0)	4 (18.2)	18 (52.9)
Ⅳ	13 (6.7)	17 (12.5)	9 (40.9)	1 (2.9)
Lauren classification /n (%)					0.000	38.6
Diffuse	36 (25.0)	16 (23.9)	3 (23.1)	21 (77.8)
Intestinal	108 (75.0)	51 (76.1)	10 (76.9)	6 (22.2)
Histological grade/n (%)					0.000	2.2
G1	6 (3.1)	2 (1.4)	2 (6.5)	1 (3.1)
G2	87 (44.8)	51 (35.7)	9 (29.0)	1 (3.1)
G3	101 (52.1)	90 (62.9)	20 (64.5)	30 (93.8)
Gender /n (%)					0.186	0
Female	60 (30.2)	54 (37.5)	14 (45.2)	15 (42.9)
Male	139 (69.8)	90 (62.5)	17 (54.8)	20 (57.1)
Race /n (%)					0.045	13.7
Asian	55 (30.1)	21 (17.2)	1 (7.7)	9 (25.7)
Black	9 (4.9)	3 (2.5)	0 (0)	0 (0)
White	119 (65.0)	98 (80.3)	12 (92.3)	26 (74.3)

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