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pmid:34557343

Clinicopathological value of long non-coding RNA profiles in gastrointestinal stromal tumor.

Yan Zhao · Xinxin Liu · Keshuai Xiao · Liwen Wang · Yuping Li · Mingyun Kan · Zhiwei Jiang

PeerJ · 2021 doi:10.7717/peerj.11946

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complete

Experiment

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Data

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Analysis

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:34557343
kind
science-record
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sha256:1746aa4c3b0caad2042fb7ce703f62b051bcb5a1fc3d18847440352d87797e39
schema
https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json
created_at
2026-11-01T15:41:53Z
updated_at
2026-11-01T21:26:17Z
generator object · 2 fields
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paper object · 10 fields
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complete
title
Clinicopathological value of long non-coding RNA profiles in gastrointestinal stromal tumor.
doi
10.7717/peerj.11946
pmid
34557343
authors array · 7 items
[0]
Yan Zhao
[1]
Xinxin Liu
[2]
Keshuai Xiao
[3]
Liwen Wang
[4]
Yuping Li
[5]
Mingyun Kan
[6]
Zhiwei Jiang
journal
PeerJ
year
2021
abstract
BACKGROUND: Long non-coding RNAs (lncRNAs) have been implicated in diagnosis and prognosis in various cancers. However, few lncRNA signatures have been established for prediction of gastrointestinal stromal tumors (GIST). We aimed to explore a lncRNA signature profile that associated with clinical relevance by mining data from Gene Expression Ominus (GEO) and Surveillance, Epidemiology, and End Results (SEER) Program. METHODS: Using a lncRNA-mining approach, we performed non-negative matrix factorization (NMF) consensus algorithm in Gastrointestinal stromal tumors (GISTs) cohorts (61 patients from GSE8167 and GSE17743) to cluster LncRNA expression profiles. Comparative markers selection, and Gene Set Enrichment Analysis (GSEA) algorithm were performed between distinct molecular subtypes of GIST. The survival rate of GIST patients from SEER stratified by gender were compared by Kaplan-Meier method and log-rank analysis. lncRNA-mRNA co-expression analysis was performed by Pearson correlation coefficients (PCC) using R package LINC. Somatic copy number alterations of GIST patients (GSE40966) were analyzed via web server GenePattern GISTIC2 algorithm. RESULTS: A total of four lncRNA molecular subtypes of GIST were identified with distinct biological pathways and clinical characteristics. LncRNA expression profiles well clustered the GIST samples into small size (<5 mm) and large size tumors (>5 mm), which is a fundamental index for GIST malignancy diagnosis. Several lncRNAs with abundant expression (LRRC75A-AS1, HYMAI, NEAT1, XIST and FTX) were closely associated with tumor size, which may suggest to be biomarkers for the GIST malignancy. Particularly, LRRC75A-AS1 was positively associated with tumor diameters and suggested an oncogene in GIST. Co-expression analysis suggested that chromosome region 17p11.2-p12 may contribute to the oncogenic process in malignant GIST. Interestingly, the gender had a strong influence on clustering by lncRNA expression profile. Data from the Surveillance, Epidemiology, and End Results (SEER) Program were further explored and 7983 patients who were diagnosed with GISTs from 1973 to 2014 were enrolled for analysis. The results also showed the favorable prognosis for female patients. The survival rate between male and female with GIST was statistically significant (P < 0.0001). Gene set enrichment analysis (GSEA) indicated distinct pathways between female and male, and malignant GIST was associated with several cancer metabolism and cell cycle associated pathways. CONCLUSIONS: This lncRNAs-based classification for GISTs may provide a molecular classification applicable to individual GIST that has implications to influence lncRNA markers selection and prediction of tumor progression.
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The survival rate of GIST patients from SEER stratified by gender were compared by Kaplan–Meier method and log-rank analysis.
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methodological
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sections[0] "Abstract" paragraph 2
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The survival rate of GIST patients from SEER stratified by gender were compared by Kaplan–Meier method and log-rank analysis.
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The following information was supplied regarding data availability: The raw data is available in the Supplemental File and at NCBI GEO: GSE17743, GSE8167, GSE20709.
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sections[31] "Data Availability Statement" paragraphs 1-3
quote
The following information was supplied regarding data availability: The raw data is available in the Supplemental File and at NCBI GEO: GSE17743, GSE8167, GSE20709.
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the published estimate and its evidence
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the source data with its repository provenance
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Run the published analysis
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Apply the paper's statistical method to the resolved series and compare the result with the published target.
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GEO
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The following information was supplied regarding data availability: The raw data is available in the Supplemental File and at NCBI GEO: GSE17743, GSE8167, GSE20709.
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title
Gene expression profiles differentiating gastrointestinal stromal tumours according to KIT mutations and expression
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The following information was supplied regarding data availability: The raw data is available in the Supplemental File and at NCBI GEO: GSE17743, GSE8167, GSE20709.
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GSM520413
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GSM520414
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GSM520415
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25
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null
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null
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6801
taxon
Homo sapiens
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Copy number data from GIST with KIT mutation
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2026-11-01T15:39:54Z
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The following information was supplied regarding data availability: The raw data is available in the Supplemental File and at NCBI GEO: GSE17743, GSE8167, GSE20709.
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GEO accession URL
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The following information was supplied regarding data availability: The raw data is available in the Supplemental File and at NCBI GEO: GSE17743, GSE8167, GSE20709.
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GSM202203
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GSM202204
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GSM202205
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GSM202206
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GSM202207
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GSM202209
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GSM202210
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GSM202211
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GSM202212
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GSM202213
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GSM202214
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GSM202215
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GSM202216
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GSM202218
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GSM202221
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GSM202225
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GSM202226
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GSM202227
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GSM202228
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32
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null
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null
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570
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Homo sapiens
title
Distinct gene-expression-defined classes of gastrointestinal stromal tumor (GIST).
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2026-11-01T15:39:55Z
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Association analysis of clinical characteristics of GIST patients and 4 subtypes clustered by lncRNA profile.
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pmcid
PMC8420874
section_index
12
section_title
LncRNAs clustering GIST subtypes were associated with tumor size and gender
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5
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label
Table 1
caption
Association analysis of clinical characteristics of GIST patients and 4 subtypes clustered by lncRNA profile.
rows array · 5 items
[0] array · 10 items
[0]
Subtypes
[1]
Cases
[2]
Age
[3]
F:M
[4]
Locationintestinal:gastric
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MutationKIT:WT:PDGRF
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Diameter (mm)
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Sig.(p)
[8]
Diameter (mm)
[9]
Sig.(p)
[1] array · 10 items
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11
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9.09 + 7.34
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0.995a
[8]
10.45 + 7.90*
[9]
0.000c
[2] array · 7 items
[0]
G2
[1]
20
[2]
63.6 + 12.4
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1:19
[4]
7:13
[5]
16:4:0
[6]
11.2 + 8.28
[3] array · 9 items
[0]
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[1]
11
[2]
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3:8
[4]
0:11
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6:1:4
[6]
48.73 + 25.16
[7]
0.921b
[8]
52.17 + 30.89*
[4] array · 7 items
[0]
G4
[1]
19
[2]
–
[3]
4:15
[4]
0:19
[5]
10:2:7
[6]
54.16 + 34.27
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section[12]/table-wrap[1]#table-1
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Equilibrium comparison of baseline characteristics of GIST patients before and after propensity score matching. stratified by gender (male vs. female).
structure object · 5 fields
pmcid
PMC8420874
section_index
13
section_title
Female GIST patients showed favorable survival time by SEER database
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35
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Table 2
caption
Equilibrium comparison of baseline characteristics of GIST patients before and after propensity score matching. stratified by gender (male vs. female).
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[0] array · 6 items
[0]
[1]
Before matching
[2]
[3]
[4]
After matching
[5]
[1] array · 8 items
[0]
Characteristics
[1]
Male
[2]
Female
[3]
p
[4]
[5]
Male
[6]
Female
[7]
p
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[0]
[1]
4,139 (51.8%)
[2]
3,844 (48.2%)
[3]
[4]
[5]
2,567 (50%)
[6]
2,567 (50%)
[7]
[3] array · 8 items
[0]
Tumor site
[1]
[2]
[3]
0.054
[4]
[5]
[6]
[7]
1.0
[4] array · 8 items
[0]
Stomach
[1]
2,192 (53.0%)
[2]
2,188 (56.9%)
[3]
[4]
[5]
1,467 (57.1%)
[6]
1,467 (57.1%)
[7]
[5] array · 8 items
[0]
Small intestine
[1]
1,177 (28.4%)
[2]
977 (25.4%)
[3]
[4]
[5]
716 (27.9%)
[6]
716 (27.9%)
[7]
[6] array · 8 items
[0]
Rectum
[1]
138 (3.3%)
[2]
85 (2.2%)
[3]
[4]
[5]
37 (1.4%)
[6]
37 (1.4%)
[7]
[7] array · 8 items
[0]
Colon
[1]
112 (2.7%)
[2]
107 (2.8%)
[3]
[4]
[5]
40 (1.6%)
[6]
40 (1.6%)
[7]
[8] array · 8 items
[0]
Others
[1]
520 (12.6%)
[2]
487 (12.7%)
[3]
[4]
[5]
307 (12.0%)
[6]
307 (12.0%)
[7]
[9] array · 8 items
[0]
Age
[1]
[2]
[3]
<0.001
[4]
[5]
[6]
[7]
1.0
[10] array · 8 items
[0]
≤60
[1]
1,958 (47.3%)
[2]
1,607 (41.8%)
[3]
[4]
[5]
1,259 (49.0%)
[6]
1,259 (49.0%)
[7]
[11] array · 8 items
[0]
>60
[1]
2,181 (52.7%)
[2]
2,237 (58.2%)
[3]
[4]
[5]
1,308 (51.0%)
[6]
1,308 (51.0%)
[7]
[12] array · 8 items
[0]
Therapy
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[2]
[3]
<0.001
[4]
[5]
[6]
[7]
1.0
[13] array · 8 items
[0]
Surgery
[1]
3,190 (77.1%)
[2]
3,086 (80.3%)
[3]
[4]
[5]
2,090 (81.4%)
[6]
2,090 (81.4%)
[7]
[14] array · 8 items
[0]
No surgery
[1]
911 (22.0%)
[2]
731 (19.0%)
[3]
[4]
[5]
473 (18.4%)
[6]
473 (18.4%)
[7]
[15] array · 8 items
[0]
Unknown
[1]
38 (0.9%)
[2]
27 (0.7%)
[3]
[4]
[5]
4 (0.2%)
[6]
4 (0.2%)
[7]
[16] array · 8 items
[0]
Marital status
[1]
[2]
[3]
<0.001
[4]
[5]
[6]
[7]
1.0
[17] array · 8 items
[0]
Married
[1]
2,751 (66.5%)
[2]
1,861 (48.4%)
[3]
[4]
[5]
1,675 (65.3%)
[6]
1,675 (65.3%)
[7]
[18] array · 8 items
[0]
Widowed
[1]
189 (4.6%)
[2]
773 (20.1%)
[3]
[4]
[5]
157 (6.1%)
[6]
157 (6.1%)
[7]
[19] array · 8 items
[0]
Single/unmarried
[1]
678 (16.4%)
[2]
636 (16.5%)
[3]
[4]
[5]
438 (17.1%)
[6]
438 (17.1%)
[7]
[20] array · 8 items
[0]
Divorced/separated
[1]
318 (7.7%)
[2]
386 (10.0%)
[3]
[4]
[5]
199 (7.8%)
[6]
199 (7.8%)
[7]
[21] array · 8 items
[0]
Unknown
[1]
203 (4.9%)
[2]
188 (4.9%)
[3]
[4]
[5]
98 (3.8%)
[6]
98 (3.8%)
[7]
[22] array · 8 items
[0]
Race
[1]
[2]
[3]
0.62
[4]
[5]
[6]
[7]
1.0
[23] array · 8 items
[0]
White
[1]
2,891 (69.8%)
[2]
2,578 (67.1%)
[3]
[4]
[5]
1,849 (72.0%)
[6]
1,849 (72.0%)
[7]
[24] array · 8 items
[0]
Black
[1]
680 (16.4%)
[2]
729 (19.0%)
[3]
[4]
[5]
399 (15.5%)
[6]
399 (15.5%)
[7]
[25] array · 8 items
[0]
Others
[1]
568 (13.7%)
[2]
537 (14.0%)
[3]
[4]
[5]
319 (12.4%)
[6]
319 (12.4%)
[7]
[26] array · 8 items
[0]
Grade
[1]
[2]
[3]
0.37
[4]
[5]
[6]
[7]
1.0
[27] array · 8 items
[0]
I/II
[1]
715 (17.3%)
[2]
765 (19.9%)
[3]
[4]
[5]
467 (18.2%)
[6]
467 (18.2%)
[7]
[28] array · 8 items
[0]
III/IV
[1]
482 (11.6%)
[2]
387 (10.1%)
[3]
[4]
[5]
230 (9.0%)
[6]
230 (9.0%)
[7]
[29] array · 8 items
[0]
Unknown
[1]
2942 (71.1%)
[2]
2692 (70.0%)
[3]
[4]
[5]
1,870 (72.8%)
[6]
1,870 (72.8%)
[7]
[30] array · 8 items
[0]
Tumor size
[1]
[2]
[3]
<0.001
[4]
[5]
[6]
[7]
1.0
[31] array · 8 items
[0]
≤2 cm
[1]
203 (4.9%)
[2]
276 (7.2%)
[3]
[4]
[5]
121 (4.7%)
[6]
121 (4.7%)
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1,388 (54.1%)
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lncRNA Markers selection and associated expression pattern between four subtypes
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{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34557343", "kind": "science-record", "revision": 6, "content_hash": "sha256:1746aa4c3b0caad2042fb7ce703f62b051bcb5a1fc3d18847440352d87797e39", "created_at": "2026-11-01T15:41:53Z", "updated_at": "2026-11-01T21:26:17Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Clinicopathological value of long non-coding RNA profiles in gastrointestinal stromal tumor.", "doi": "10.7717/peerj.11946", "pmid": "34557343", "authors": ["Yan Zhao", "Xinxin Liu", "Keshuai Xiao", "Liwen Wang", "Yuping Li", "Mingyun Kan", "Zhiwei Jiang"], "journal": "PeerJ", "year": 2021, "abstract": "BACKGROUND: Long non-coding RNAs (lncRNAs) have been implicated in diagnosis and prognosis in various cancers. However, few lncRNA signatures have been established for prediction of gastrointestinal stromal tumors (GIST). We aimed to explore a lncRNA signature profile that associated with clinical relevance by mining data from Gene Expression Ominus (GEO) and Surveillance, Epidemiology, and End Results (SEER) Program.\nMETHODS: Using a lncRNA-mining approach, we performed non-negative matrix factorization (NMF) consensus algorithm in Gastrointestinal stromal tumors (GISTs) cohorts (61 patients from GSE8167 and GSE17743) to cluster LncRNA expression profiles. Comparative markers selection, and Gene Set Enrichment Analysis (GSEA) algorithm were performed between distinct molecular subtypes of GIST. The survival rate of GIST patients from SEER stratified by gender were compared by Kaplan-Meier method and log-rank analysis. lncRNA-mRNA co-expression analysis was performed by Pearson correlation coefficients (PCC) using R package LINC. Somatic copy number alterations of GIST patients (GSE40966) were analyzed via web server GenePattern GISTIC2 algorithm.\nRESULTS: A total of four lncRNA molecular subtypes of GIST were identified with distinct biological pathways and clinical characteristics. LncRNA expression profiles well clustered the GIST samples into small size (<5 mm) and large size tumors (>5 mm), which is a fundamental index for GIST malignancy diagnosis. Several lncRNAs with abundant expression (LRRC75A-AS1, HYMAI, NEAT1, XIST and FTX) were closely associated with tumor size, which may suggest to be biomarkers for the GIST malignancy. Particularly, LRRC75A-AS1 was positively associated with tumor diameters and suggested an oncogene in GIST. Co-expression analysis suggested that chromosome region 17p11.2-p12 may contribute to the oncogenic process in malignant GIST. Interestingly, the gender had a strong influence on clustering by lncRNA expression profile. Data from the Surveillance, Epidemiology, and End Results (SEER) Program were further explored and 7983 patients who were diagnosed with GISTs from 1973 to 2014 were enrolled for analysis. The results also showed the favorable prognosis for female patients. The survival rate between male and female with GIST was statistically significant (P < 0.0001). Gene set enrichment analysis (GSEA) indicated distinct pathways between female and male, and malignant GIST was associated with several cancer metabolism and cell cycle associated pathways.\nCONCLUSIONS: This lncRNAs-based classification for GISTs may provide a molecular classification applicable to individual GIST that has implications to influence lncRNA markers selection and prediction of tumor progression.", "claims": [{"id": "claim-method", "statement": "The survival rate of GIST patients from SEER stratified by gender were compared by Kaplan–Meier method and log-rank analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34557343", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The survival rate of GIST patients from SEER stratified by gender were compared by Kaplan–Meier method and log-rank analysis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The following information was supplied regarding data availability:\nThe raw data is available in the Supplemental File and at NCBI GEO: GSE17743, GSE8167, GSE20709.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34557343", "locator": "sections[31] \"Data Availability Statement\" paragraphs 1-3", "quote": "The following information was supplied regarding data availability:\nThe raw data is available in the Supplemental File and at NCBI GEO: GSE17743, GSE8167, GSE20709."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:34557343"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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