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pmid:38540240

Immune Gene Networks from Lung Cancer Patients Treated with Immune Checkpoint Inhibitors.

Kyung Soo Kim · Taewon Kang · Dong Wook Jekarl

Biomedicines · 2024 doi:10.3390/biomedicines12030628

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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title
Immune Gene Networks from Lung Cancer Patients Treated with Immune Checkpoint Inhibitors.
doi
10.3390/biomedicines12030628
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38540240
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Kyung Soo Kim
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Taewon Kang
[2]
Dong Wook Jekarl
journal
Biomedicines
year
2024
abstract
The association between immune checkpoint inhibitors (ICIs) and immune gene networks in squamous lung cancer (LUSC) and lung adenocarcinoma (LUAD) was studied. Immune gene networks were constructed using RNA-seq data from the gene expression omnibus (GEO) database. Datasets with more than 10 samples of normal control and tumor tissues were selected; of these, GSE87340, GSE120622, and GSE111907 were suitable for analysis. Gene set enrichment for pathway analysis was performed. For immune gene network construction, 998 unique immune genes were selected from 21 pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG). Gene function annotation was performed based on the KEGG, Gene Ontology, and Reactome databases. Tumor tissues showed decreased coagulation, hematopoiesis, and innate immune pathways, whereas complement- and coagulation-related genes were prominent in the tumor immune gene network. The average numbers of neighbors, clustering coefficients, network diameters, path lengths, densities, and heterogeneities were highest for normal tissue, followed by LUAD and LUSC. Decreased coagulation genes, which were prominent in tumor immune networks, imply functional attenuation. LUAD was deviated from normal tissue, based on network parameters. Tumor tissues showed decreased immune function, and the deviation of LUSC from normal tissue might explain LUSC's better therapeutic response to ICI treatment.
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After selecting normal controls and an equal number of tumor tissues, gene set enrichment for pathway analysis was performed using the GAGE R package [26], which utilizes the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways [18,27].
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sections[3] "2.1. Gene Set Enrichment for Pathway Analysis" paragraph 2
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After selecting normal controls and an equal number of tumor tissues, gene set enrichment for pathway analysis was performed using the GAGE R package [26], which utilizes the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways [18,27].
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sections[15] "Data Availability Statement" paragraph 2
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Data are contained within the article and Supplementary Materials.
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LUSC tissues deviated more from normal samples than LUAD tissues based on Euclidean, Manhattan, and cosine distances.
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sections[7] "3. Results" paragraph 19
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These analysis results indicate that LUAD tissues are closer to normal tissues compared with LUSC, and LUSC tissues deviated more from the normal samples.
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null
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null
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null
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2026-11-01T20:16:09Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[7] object · 15 fields
id
data:geo:SRP255477
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raw
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geo-series
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application/vnd.ncbi.geo-series+json
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=SRP255477
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null
bytes
null
access
open
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resolved
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null
reader_status
reader_required
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SRP255477
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null
note
Data are contained within the article and Supplementary Materials.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
Data are contained within the article and Supplementary Materials.
access_statement_kind
data_availability_statement
sample_accessions array · 0 items
sample_count
null
group_sizes
null
group_sizes_basis
null
platform
null
taxon
null
title
null
resolution_checked_at
2026-11-01T20:16:09Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
gaps array · 14 items
[0]
asset:data:geo:GSE111907 not downloaded
[1]
asset:data:geo:GSE111907 licence not read
[2]
asset:data:geo:GSE120622 not downloaded
[3]
asset:data:geo:GSE120622 licence not read
[4]
asset:data:geo:GSE87340 not downloaded
[5]
asset:data:geo:GSE87340 licence not read
[6]
asset:data:geo:PRJNA438518 not downloaded
[7]
asset:data:geo:PRJNA438518 licence not read
[8]
asset:data:geo:PRJNA463790 not downloaded
[9]
asset:data:geo:PRJNA463790 licence not read
[10]
asset:data:geo:SRP162843 not downloaded
[11]
asset:data:geo:SRP162843 licence not read
[12]
asset:data:geo:SRP255477 not downloaded
[13]
asset:data:geo:SRP255477 licence not read
analysis object · 4 fields
state
partial
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[0] object · 10 fields
id
method-1
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sequence_alignment
specific
read_mapping
label
Sequence alignment / homology
dsl_operations array · 2 items
[0]
sequence_align
[1]
alignment_identity
missing_operations array · 0 items
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data_shapes array · 1 item
[0]
sequence_records
evidence object · 3 fields
score
0.8
band
high
quote
HISAT2
[1] object · 10 fields
id
method-2
family
null
specific
null
label
Gene set enrichment for pathway analysis using the GAGE R package, followed by immune gene correlation-network analysis using Pearson’s correlation coefficient.
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
After selecting normal controls and an equal number of tumor tissues, gene set enrichment for pathway analysis was performed using the GAGE R package [26], which utilizes the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways [18,27].
targets array · 0 items
gaps array · 1 item
[0]
method.reader_named_unmapped
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
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true
required_operations array · 2 items
[0]
sequence_align
[1]
alignment_identity
missing_operations array · 0 items
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: read_mapping.
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 · 7 items
[0]
GSE87340
[1]
GSE120622
[2]
PRJNA463790
[3]
SRP162843
[4]
GSE111907
[5]
PRJNA438518
[6]
SRP255477
resolved_accessions array · 3 items
[0]
GSE87340
[1]
GSE120622
[2]
GSE111907
statements array · 1 item
[0]
Data are contained within the article and Supplementary Materials.
basis
The paper names GSE87340, GSE120622, GSE111907 in Gene Expression Omnibus (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 · 2 items
[0]
sequence_align
[1]
alignment_identity
assets array · 2 items
[0]
source:pmid:38540240
[1]
data:geo:GSE111907
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[0]
run_analysis
must_build object · 5 fields
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readers array · 0 items
capabilities array · 0 items
data_gaps array · 1 item
[0]
data:geo:GSE111907
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
2026-11-01T19:13:28Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
calls
5
usage object · 3 fields
prompt_tokens
11707
completion_tokens
1643
cached_tokens
264
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[0] object · 4 fields
id
extraction
state
complete
reader
MiniMax-M3.1-Flash
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minimax
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review.independent_reader
[1]
review.machine_critique
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review.human_critique
execution object · 5 fields
state
absent
status
not_run
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null
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gaps array · 1 item
[0]
execution.not_run
provenance object · 7 fields
entities array · 3 items
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id
pmid:38540240
type
paper
label
pmid:38540240
[1] object · 3 fields
id
source:pmid:38540240
type
manuscript
label
PMID 38540240 full text
[2] object · 3 fields
id
data:geo:GSE111907
type
dataset
label
GEO GSE111907
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:38540240
type
paper
label
pmid:38540240
[1] object · 3 fields
id
source:pmid:38540240
type
manuscript
label
PMID 38540240 full text
[2] object · 3 fields
id
data:geo:GSE111907
type
dataset
label
GEO GSE111907
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-38540240
type
extraction
used array · 1 item
[0]
source:pmid:38540240
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE111907
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accession_resolution
used array · 1 item
[0]
data:geo:GSE111907
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:38540240
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sha256:706475974fb9ac47d077007a06c6f28ed730c60d1efdd36b9c79bea082505e61
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null
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[0]
asset:data:geo:GSE111907 licence not read
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[3]
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[4]
asset:data:geo:GSE87340 licence not read
[5]
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[6]
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[7]
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[8]
asset:data:geo:PRJNA463790 licence not read
[9]
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[10]
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[11]
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[12]
asset:data:geo:SRP255477 licence not read
[13]
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[14]
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[0] object · 11 fields
role
data_generation
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rna_seq
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99e1195c7d6f
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assay_lexicon
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[0]
Immune gene networks were constructed using RNA-seq data from the gene expression omnibus (GEO)
[1]
y the SRA database, was utilized to download RNA-seq fastq files. HISAT2 was utilized to align ra
[2]
profiling by high throughput sequencing, and RNA sequencing, which resulted in 493 datasets. Among them,
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paper_text_order:250
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assay:1
[1] object · 11 fields
role
analysis
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sequence_alignment
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f2132e96ae6c7a4e
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dsl_catalogue
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38540240", "kind": "science-record", "revision": 4, "content_hash": "sha256:fba70f90baf25b8383675134445a40442eaba9a2f70d21917380a4847ec76591", "created_at": "2026-11-01T19:20:29Z", "updated_at": "2026-11-01T22:11:32Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Immune Gene Networks from Lung Cancer Patients Treated with Immune Checkpoint Inhibitors.", "doi": "10.3390/biomedicines12030628", "pmid": "38540240", "authors": ["Kyung Soo Kim", "Taewon Kang", "Dong Wook Jekarl"], "journal": "Biomedicines", "year": 2024, "abstract": "The association between immune checkpoint inhibitors (ICIs) and immune gene networks in squamous lung cancer (LUSC) and lung adenocarcinoma (LUAD) was studied. Immune gene networks were constructed using RNA-seq data from the gene expression omnibus (GEO) database. Datasets with more than 10 samples of normal control and tumor tissues were selected; of these, GSE87340, GSE120622, and GSE111907 were suitable for analysis. Gene set enrichment for pathway analysis was performed. For immune gene network construction, 998 unique immune genes were selected from 21 pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG). Gene function annotation was performed based on the KEGG, Gene Ontology, and Reactome databases. Tumor tissues showed decreased coagulation, hematopoiesis, and innate immune pathways, whereas complement- and coagulation-related genes were prominent in the tumor immune gene network. The average numbers of neighbors, clustering coefficients, network diameters, path lengths, densities, and heterogeneities were highest for normal tissue, followed by LUAD and LUSC. Decreased coagulation genes, which were prominent in tumor immune networks, imply functional attenuation. LUAD was deviated from normal tissue, based on network parameters. Tumor tissues showed decreased immune function, and the deviation of LUSC from normal tissue might explain LUSC's better therapeutic response to ICI treatment.", "claims": [{"id": "claim-method", "statement": "After selecting normal controls and an equal number of tumor tissues, gene set enrichment for pathway analysis was performed using the GAGE R package [26], which utilizes the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways [18,27].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38540240", "locator": "sections[3] \"2.1. Gene Set Enrichment for Pathway Analysis\" paragraph 2", "quote": "After selecting normal controls and an equal number of tumor tissues, gene set enrichment for pathway analysis was performed using the GAGE R package [26], which utilizes the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways [18,27]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Data are contained within the article and Supplementary Materials.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38540240", "locator": "sections[15] \"Data Availability Statement\" paragraph 2", "quote": "Data are contained within the article and Supplementary Materials."}], "state": "complete"}, {"id": "claim-target-result", "statement": "LUSC tissues deviated more from normal samples than LUAD tissues based on Euclidean, Manhattan, and cosine distances.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38540240", "locator": "sections[7] \"3. Results\" paragraph 19", "quote": "These analysis results indicate that LUAD tissues are closer to normal tissues compared with LUSC, and LUSC tissues deviated more from the normal samples."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "LUSC tissues deviated more from normal samples than LUAD tissues based on Euclidean, Manhattan, and cosine distances.", "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:38540240"], "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. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE111907"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE111907"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38540240", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3390/biomedicines12030628", "sha256": 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