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pmid:35982906

Development and Validation of a DNA Methylation-related Classifier of Circulating Tumour Cells to Predict Prognosis and to provide a therapeutic strategy in Lung Adenocarcinoma.

Xuyu Gu · Xianting Huang · Xiuxiu Zhang · Cailian Wang

International journal of biological sciences · 2022 doi:10.7150/ijbs.75284

Paper

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Experiment

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Data

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Development and Validation of a DNA Methylation-related Classifier of Circulating Tumour Cells to Predict Prognosis and to provide a therapeutic strategy in Lung Adenocarcinoma.
doi
10.7150/ijbs.75284
pmid
35982906
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Xuyu Gu
[1]
Xianting Huang
[2]
Xiuxiu Zhang
[3]
Cailian Wang
journal
International journal of biological sciences
year
2022
abstract
Background: A significant factor influencing the prognosis of lung adenocarcinoma (LUAD) is tumor metastasis. Studies have shown that abnormal DNA methylation in circulating tumor cells (CTCs) is associated with tumour metastasis. Based on the genes expressed in CTCs that play an important role in DNA methylation, we hope to build a risk model to predict prognosis and provide a therapeutic strategy in LUAD. Methods: The CTC sequencing data for LUAD were obtained from GSE74639, which contains 10 CTC samples and 6 primary tumour samples. To carefully assess the clinical value, functional status, involvement of the tumor microenvironment (TME) based on the risk model, and genetic variants based on based on data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO), a reliable risk model was successfully built. Results: Three differentially methylated genes (DMGs) of CTCs for LUAD, including mitochondrial ribosomal protein L51 (MRPL51), STE20-like kinase (SLK), and protein regulator of cytokinesis 1(PRC1), were effectively used to construct a risk model. Both the training and validation cohorts' stability and accuracy of the risk model were evaluated. Each patient in the TCGA-LUAD cohort received a risk score, and based on the median score, they were divided into high- and low-risk groups. The tumors in the high-risk group in this study were classified as "cold" and immunosuppressed, which may be linked to a poor prognosis. The tumors in the low-risk group, however, were deemed "hot" and had immune hyperfunction linked to a positive prognosis. Additionally, patients in the low-risk group showed greater sensitivity to immunotherapy than those in the high-risk group. Conclusions: Based on DMGs of CTCs from LUAD, we successfully developed a predictive risk model and discovered differences in biological function, TME, genetic variation, and clinical outcomes between those at high and low risk group.
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Additionally, by examining the correlation between gene expression and methylation level using R<0 and p<0.05 as criteria, differential methylation-driven genes (DMGs) were found.
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sections[4] "Screening of methylation-driven genes" paragraph 2
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Additionally, by examining the correlation between gene expression and methylation level using R<0 and p<0.05 as criteria, differential methylation-driven genes (DMGs) were found.
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The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.
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Three differentially methylated genes (DMGs) of CTCs for LUAD, including mitochondrial ribosomal protein L51 (MRPL51), STE20-like kinase (SLK), and protein regulator of cytokinesis 1(PRC1), were effectively used to construct a risk model.
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Three differentially methylated genes (DMGs) of CTCs for LUAD, including mitochondrial ribosomal protein L51 (MRPL51), STE20-like kinase (SLK), and protein regulator of cytokinesis 1(PRC1), were effectively used to construct a risk model.
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Three differentially methylated genes (DMGs) of CTCs for LUAD, including mitochondrial ribosomal protein L51 (MRPL51), STE20-like kinase (SLK), and protein regulator of cytokinesis 1(PRC1), were effectively used to construct a risk model.
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[271]
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[272]
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[274]
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[279]
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[280]
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[281]
GSM1855078
[282]
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[283]
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[284]
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[285]
GSM1855082
[286]
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[287]
GSM1855084
[288]
GSM1855085
[289]
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[290]
GSM1855087
[291]
GSM1855088
[292]
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[293]
GSM1855090
[294]
GSM1855091
[295]
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[296]
GSM1855093
[297]
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[298]
GSM1855095
[299]
GSM1855096
[300]
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[301]
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[302]
GSM1855099
[303]
GSM1855100
[304]
GSM1855101
[305]
GSM1855102
[306]
GSM1855103
[307]
GSM1855104
[308]
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[309]
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[310]
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[311]
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[312]
GSM1855109
[313]
GSM1855110
[314]
GSM1855111
[315]
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[316]
GSM1855113
[317]
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[318]
GSM1855115
[319]
GSM1855116
[320]
GSM1855117
[321]
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[322]
GSM1855119
[323]
GSM1855120
[324]
GSM1855121
[325]
GSM1855122
[326]
GSM1855123
[327]
GSM1855124
[328]
GSM1855125
[329]
GSM1855126
[330]
GSM1855127
[331]
GSM1855128
[332]
GSM1855129
[333]
GSM1855130
[334]
GSM1855131
[335]
GSM1855132
[336]
GSM1855133
[337]
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[338]
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[339]
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[340]
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[341]
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[342]
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[343]
GSM1855140
[344]
GSM1855141
[345]
GSM1855142
[346]
GSM1855143
[347]
GSM1855144
[348]
GSM1855145
[349]
GSM1855146
[350]
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[351]
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[352]
GSM1855149
[353]
GSM1855150
[354]
GSM1855151
[355]
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[356]
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[357]
GSM1855154
[358]
GSM1855155
[359]
GSM1855156
[360]
GSM1855157
[361]
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[362]
GSM1855159
[363]
GSM1855160
[364]
GSM1855161
[365]
GSM1855162
[366]
GSM1855163
[367]
GSM1855164
[368]
GSM1855165
[369]
GSM1855166
[370]
GSM1855167
[371]
GSM1855168
[372]
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[373]
GSM1855170
[374]
GSM1855171
[375]
GSM1855172
[376]
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[377]
GSM1855174
[378]
GSM1855175
[379]
GSM1855176
[380]
GSM1855177
[381]
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[382]
GSM1855179
[383]
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[384]
GSM1855181
[385]
GSM1855182
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[387]
GSM1855184
[388]
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[389]
GSM1855186
[390]
GSM1855187
[391]
GSM1855188
[392]
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[393]
GSM1855190
[394]
GSM1855191
[395]
GSM1855192
[396]
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[397]
GSM1855194
[398]
GSM1855195
[399]
GSM1855196
[400]
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[401]
GSM1855198
[402]
GSM1855199
[403]
GSM1855200
[404]
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[405]
GSM1855202
[406]
GSM1855203
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GSM1855204
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GSM1855205
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GSM1855206
[410]
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GSM1855208
[412]
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[413]
GSM1855210
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[415]
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GSM1855214
[418]
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[420]
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[421]
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[423]
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[425]
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[431]
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[432]
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[433]
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[434]
GSM1855231
[435]
GSM1855232
[436]
GSM1855233
[437]
GSM1855234
[438]
GSM1855235
[439]
GSM1855236
[440]
GSM1855237
[441]
GSM1855238
sample_count
442
group_sizes
null
group_sizes_basis
null
platform
15048
taxon
Homo sapiens
title
KRAS mutation-associated gene expression, p53 and STK11 mutations, proliferation and immune surveillance in lung adenocarcinoma
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[3] object · 15 fields
id
data:geo:GSE74639
role
raw
format
geo-series
media_type
application/vnd.ncbi.geo-series+json
uri
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE74639
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE74639
version
null
note
The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.
access_statement_kind
data_availability_statement
sample_accessions array · 16 items
[0]
GSM1924814
[1]
GSM1924815
[2]
GSM1924816
[3]
GSM1924817
[4]
GSM1924818
[5]
GSM1924819
[6]
GSM1924820
[7]
GSM1924821
[8]
GSM1924822
[9]
GSM1924823
[10]
GSM1924824
[11]
GSM1924825
[12]
GSM1924826
[13]
GSM1924827
[14]
GSM1924828
[15]
GSM1924829
sample_count
16
group_sizes
null
group_sizes_basis
null
platform
16288
taxon
Homo sapiens
title
RNA-Seq of Single Lung Circulating Tumor Cells (CTCs) and primary Tumor Cells from an orthotopic lung xenograft model
resolution_checked_at
2026-11-01T18:06:44Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
gaps array · 6 items
[0]
asset:data:geo:GSE42127 not downloaded
[1]
asset:data:geo:GSE42127 licence not read
[2]
asset:data:geo:GSE72094 not downloaded
[3]
asset:data:geo:GSE72094 licence not read
[4]
asset:data:geo:GSE74639 not downloaded
[5]
asset:data:geo:GSE74639 licence not read
analysis object · 4 fields
state
partial
methods array · 7 items
[0] object · 10 fields
id
method-1
family
group_comparison
specific
wilcoxon
label
Group comparison
dsl_operations array · 0 items
missing_operations array · 1 item
[0]
group_comparison_wilcoxon
expressible
false
parameters object · 0 fields
data_shapes array · 1 item
[0]
two_or_more_groups_continuous
evidence object · 3 fields
score
0.8
band
high
quote
Wilcoxon
[1] object · 10 fields
id
method-2
family
survival_analysis
specific
kaplan_meier
label
Survival analysis
dsl_operations array · 1 item
[0]
survival_km
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
score
0.8
band
high
quote
Kaplan-Meier
[2] object · 10 fields
id
method-3
family
survival_analysis
specific
cox_proportional_hazards
label
Survival analysis
dsl_operations array · 1 item
[0]
cox_ph
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
score
0.8
band
high
quote
Cox regression
[3] object · 10 fields
id
method-4
family
survival_analysis
specific
log_rank_test
label
Survival analysis
dsl_operations array · 1 item
[0]
logrank_test
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
score
0.8
band
high
quote
log-rank
[4] object · 10 fields
id
method-5
family
correlation_analysis
specific
spearman
label
Correlation analysis
dsl_operations array · 1 item
[0]
spearman_rho
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
paired_numeric_columns
evidence object · 3 fields
score
0.8
band
high
quote
Spearman correlation
[5] object · 10 fields
id
method-6
family
contingency_analysis
specific
chi_square
label
Categorical (contingency table) analysis
dsl_operations array · 1 item
[0]
chi_square_test
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
categorical_cross_tabulation
evidence object · 3 fields
score
0.8
band
high
quote
chi-square
[6] object · 10 fields
id
method-7
family
null
specific
null
label
correlation analysis
dsl_operations array · 0 items
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 0 items
evidence object · 3 fields
score
1
band
verbatim
quote
Additionally, by examining the correlation between gene expression and methylation level using R<0 and p<0.05 as criteria, differential methylation-driven genes (DMGs) were found.
targets array · 0 items
gaps array · 2 items
[0]
method.reader_named_unmapped
[1]
method.group_comparison_wilcoxon
capability object · 3 fields
state
complete
requirements array · 1 item
[0] object · 6 fields
capability_id
capability:computational_analysis
label
Computational analysis platform
assay_families array · 9 items
[0]
meta_analysis
[1]
machine_learning
[2]
survival_analysis
[3]
statistical_regression
[4]
pca
[5]
molecular_docking
[6]
network_analysis
[7]
differential_expression
[8]
gwas
candidate
Automated Assays Laravel application and simulated adapters
gaps array · 0 items
readiness object · 8 fields
state
complete
tier
R1
blocked_on
nothing:replicable_now
axes object · 3 fields
method object · 5 fields
tier
R1
expressible
false
required_operations array · 0 items
missing_operations array · 1 item
[0]
group_comparison_wilcoxon
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: wilcoxon.
capability object · 4 fields
tier
R1
capability_id
capability:computational_analysis
availability_state
owned
basis
The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
R1
reachable
true
accessions array · 3 items
[0]
GSE74639
[1]
GSE72094
[2]
GSE42127
resolved_accessions array · 3 items
[0]
GSE74639
[1]
GSE72094
[2]
GSE42127
statements array · 1 item
[0]
The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.
basis
The paper names GSE74639, GSE72094, GSE42127 in GEO and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
dsl_operations array · 0 items
assets array · 2 items
[0]
source:pmid:35982906
[1]
data:geo:GSE42127
steps array · 0 items
must_build object · 5 fields
dsl_operations array · 1 item
[0] object · 3 fields
operation
group_comparison_wilcoxon
priority
null
converters array · 0 items
readers array · 0 items
capabilities array · 0 items
data_gaps array · 1 item
[0]
data:geo:GSE42127
gaps array · 0 items
review object · 5 fields
state
partial
machine_critique object · 5 fields
kind
extraction_review
reader object · 5 fields
model
MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-11-01T18:00:30Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
calls
5
usage object · 3 fields
prompt_tokens
15583
completion_tokens
2503
cached_tokens
256
stages array · 1 item
[0] object · 4 fields
id
extraction
state
complete
reader
MiniMax-M3.1-Flash
provider
minimax
gaps array · 3 items
[0]
review.independent_reader
[1]
review.machine_critique
[2]
review.human_critique
execution object · 5 fields
state
absent
status
not_run
mode
null
runs array · 0 items
gaps array · 1 item
[0]
execution.not_run
provenance object · 7 fields
entities array · 3 items
[0] object · 3 fields
id
pmid:35982906
type
paper
label
pmid:35982906
[1] object · 3 fields
id
source:pmid:35982906
type
manuscript
label
PMID 35982906 full text
[2] object · 3 fields
id
data:geo:GSE42127
type
dataset
label
GEO GSE42127
activities array · 3 items
[0] object · 4 fields
id
activity-reading-sci-2026-11-01
type
classification
used array · 3 items
[0] object · 3 fields
id
pmid:35982906
type
paper
label
pmid:35982906
[1] object · 3 fields
id
source:pmid:35982906
type
manuscript
label
PMID 35982906 full text
[2] object · 3 fields
id
data:geo:GSE42127
type
dataset
label
GEO GSE42127
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-35982906
type
extraction
used array · 1 item
[0]
source:pmid:35982906
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE42127
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE42127
agent
agent:corpus-assay-engine
agents array · 2 items
[0] object · 3 fields
id
agent:corpus-assay-engine
type
software
label
Corpus assay engine
[1] object · 3 fields
id
agent:minimax-reader
type
software
label
MiniMax literature reader
source_run_id
reading-sci-2026-11-01
dsl_catalogue_fingerprint
343fb30756ba6ec3
capability_table_fingerprint
2cb3e42f047d2ecf
snapshot_id
ba34b49490d9bfaf
lineage object · 4 fields
parent_id
pmid:35982906
parent_hash
sha256:8fb6d81faf3a890c110cc32bcf843bb8633819d16584200d678f6918344bb812
fork_of
null
gaps array · 13 items
[0]
asset:data:geo:GSE42127 licence not read
[1]
asset:data:geo:GSE42127 not downloaded
[2]
asset:data:geo:GSE72094 licence not read
[3]
asset:data:geo:GSE72094 not downloaded
[4]
asset:data:geo:GSE74639 licence not read
[5]
asset:data:geo:GSE74639 not downloaded
[6]
execution.not_run
[7]
method.group_comparison_wilcoxon
[8]
method.reader_named_unmapped
[9]
review.human_critique
[10]
review.independent_reader
[11]
review.machine_critique
[12]
step:run_analysis blocked on method:group_comparison_wilcoxon
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[0] object · 11 fields
role
analysis
definition_id
group_comparison
definition_version
f2132e96ae6c7a4e
required_operations array · 0 items
support_state
partial
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
Wilcoxon
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assay:1
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35982906", "kind": "science-record", "revision": 4, "content_hash": "sha256:1039b8f70229dff67b3d3f292bdee03693fd52ba5ce37639e333e9b895779a20", "created_at": "2026-11-01T18:15:07Z", "updated_at": "2026-11-01T22:07:18Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Development and Validation of a DNA Methylation-related Classifier of Circulating Tumour Cells to Predict Prognosis and to provide a therapeutic strategy in Lung Adenocarcinoma.", "doi": "10.7150/ijbs.75284", "pmid": "35982906", "authors": ["Xuyu Gu", "Xianting Huang", "Xiuxiu Zhang", "Cailian Wang"], "journal": "International journal of biological sciences", "year": 2022, "abstract": "Background: A significant factor influencing the prognosis of lung adenocarcinoma (LUAD) is tumor metastasis. Studies have shown that abnormal DNA methylation in circulating tumor cells (CTCs) is associated with tumour metastasis. Based on the genes expressed in CTCs that play an important role in DNA methylation, we hope to build a risk model to predict prognosis and provide a therapeutic strategy in LUAD. Methods: The CTC sequencing data for LUAD were obtained from GSE74639, which contains 10 CTC samples and 6 primary tumour samples. To carefully assess the clinical value, functional status, involvement of the tumor microenvironment (TME) based on the risk model, and genetic variants based on based on data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO), a reliable risk model was successfully built. Results: Three differentially methylated genes (DMGs) of CTCs for LUAD, including mitochondrial ribosomal protein L51 (MRPL51), STE20-like kinase (SLK), and protein regulator of cytokinesis 1(PRC1), were effectively used to construct a risk model. Both the training and validation cohorts' stability and accuracy of the risk model were evaluated. Each patient in the TCGA-LUAD cohort received a risk score, and based on the median score, they were divided into high- and low-risk groups. The tumors in the high-risk group in this study were classified as \"cold\" and immunosuppressed, which may be linked to a poor prognosis. The tumors in the low-risk group, however, were deemed \"hot\" and had immune hyperfunction linked to a positive prognosis. Additionally, patients in the low-risk group showed greater sensitivity to immunotherapy than those in the high-risk group. Conclusions: Based on DMGs of CTCs from LUAD, we successfully developed a predictive risk model and discovered differences in biological function, TME, genetic variation, and clinical outcomes between those at high and low risk group.", "claims": [{"id": "claim-method", "statement": "Additionally, by examining the correlation between gene expression and methylation level using R<0 and p<0.05 as criteria, differential methylation-driven genes (DMGs) were found.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35982906", "locator": "sections[4] \"Screening of methylation-driven genes\" paragraph 2", "quote": "Additionally, by examining the correlation between gene expression and methylation level using R<0 and p<0.05 as criteria, differential methylation-driven genes (DMGs) were found."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35982906", "locator": "sections[24] \"Data Availability Statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Three differentially methylated genes (DMGs) of CTCs for LUAD, including mitochondrial ribosomal protein L51 (MRPL51), STE20-like kinase (SLK), and protein regulator of cytokinesis 1(PRC1), were effectively used to construct a risk model.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35982906", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Three differentially methylated genes (DMGs) of CTCs for LUAD, including mitochondrial ribosomal protein L51 (MRPL51), STE20-like kinase (SLK), and protein regulator of cytokinesis 1(PRC1), were effectively used to construct a risk model."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "Three differentially methylated genes (DMGs) of CTCs for LUAD, including mitochondrial ribosomal protein L51 (MRPL51), STE20-like kinase (SLK), and protein regulator of cytokinesis 1(PRC1), were effectively used to construct a risk model.", "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:35982906"], "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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