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pmid:34838035

Prognostic value and immunological role of AXL gene in clear cell renal cell carcinoma associated with identifying LncRNA/RBP/AXL mRNA networks.

Yi Wang · Ye Tian · Shouyong Liu · Zengjun Wang · Qianwei Xing

Cancer cell international · 2021 doi:10.1186/s12935-021-02322-y

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:34838035
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title
Prognostic value and immunological role of AXL gene in clear cell renal cell carcinoma associated with identifying LncRNA/RBP/AXL mRNA networks.
doi
10.1186/s12935-021-02322-y
pmid
34838035
authors array · 5 items
[0]
Yi Wang
[1]
Ye Tian
[2]
Shouyong Liu
[3]
Zengjun Wang
[4]
Qianwei Xing
journal
Cancer cell international
year
2021
abstract
BACKGROUNDS: This article aimed to explore the prognostic and immunological roles of AXL gene in clear cell renal cell carcinoma (ccRCC) for overall survival (OS) and to identify the LncRNA/RBP/AXL mRNA networks. METHODS: AXL-related gene expression matrix and clinical data were obtained from The Cancer Genome Atlas (TCGA) dataset and AXL-related pathways were identified by gene set enrichment analysis (GSEA). We performed univariate/multivariate Cox regression analysis to evaluate independent prognostic factors and the relationships between AXL and immunity were also investigated. RESULTS: The outcomes of us indicated that the AXL mRNA expression was up-regulated in ccRCC samples and high expression of AXL was associated with worse OS in TCGA dataset (P < 0.01). Further external verification results from HPA, UALCAN, ICGC dataset, GSE6344, GSE14994, and qRT-PCR remained consistent (all P < 0.05). AXL was also identified as an independent prognostic factor for ccRCC by univariate/multivariate Cox regression analysis (both P < 0.05). A nomogram including AXL expression and clinicopathological factors was established by us and GSEA results found that elevated AXL expression was associated with the JAK-STAT, P53, WNT, VEGF and MAPK signaling pathways. In terms of immunity, AXL was dramatically linked to tumor microenvironment, immune cells, immune infiltration, immune checkpoint molecules and tumor mutational burden (TMB). As for its potential mechanisms, we also identified several LncRNA/RBP/AXL mRNA axes. CONCLUSIONS: AXL was revealed to play prognostic and immunological roles in ccRCC and LncRNA/RBP/AXL mRNA axes were also identified by us for its potential mechanisms.
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Univariate/multivariate Cox hazard regression analysis were employed to the ccRCC patients from TCGA database by R package to identify whether eight clinicopathological parameters (race, gender, age, grade, T, M, N, stage) and AXL could be independent factors correlated with OS.
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sections[7] "Univariate/multivariate Cox hazard regression analysis and nomogram establishment" paragraph 2
quote
Univariate/multivariate Cox hazard regression analysis were employed to the ccRCC patients from TCGA database by R package to identify whether eight clinicopathological parameters (race, gender, age, grade, T, M, N, stage) and AXL could be independent factors correlated with OS.
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The RNA-sequencing data and corresponding clinical information were downloaded from the Cancer Genome Atlas (TCGA) database (https://portal.gdc.cancer.gov/) and the International Cancer Genome Consortium (ICGC) database (https://icgc.org/).
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sections[28] "Availability of data and materials" paragraph 2
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The RNA-sequencing data and corresponding clinical information were downloaded from the Cancer Genome Atlas (TCGA) database (https://portal.gdc.cancer.gov/) and the International Cancer Genome Consortium (ICGC) database (https://icgc.org/).
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AXL was revealed to play prognostic and immunological roles in ccRCC.
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Taken together, our results indicated that AXL was revealed to play prognostic and immunological roles in ccRCC.
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AXL was revealed to play prognostic and immunological roles in ccRCC.
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Patterns of gene expression and copy-number alterations in VHL disease-associated and sporadic ccRCC
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paper
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pmid:34838035
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manuscript
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PMID 34838035 full text
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data:geo:GSE14994
type
dataset
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GEO GSE14994
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agent:corpus-assay-engine
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activity-read-34838035
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extraction
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source:pmid:34838035
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agent:minimax-reader
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activity-resolve-GSE14994
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accession_resolution
used array · 1 item
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data:geo:GSE14994
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agent:corpus-assay-engine
agents array · 2 items
[0] object · 3 fields
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agent:corpus-assay-engine
type
software
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Corpus assay engine
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agent:minimax-reader
type
software
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MiniMax literature reader
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343fb30756ba6ec3
capability_table_fingerprint
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lineage object · 4 fields
parent_id
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gaps array · 9 items
[0]
asset:data:geo:GSE14994 licence not read
[1]
asset:data:geo:GSE14994 not downloaded
[2]
asset:data:geo:GSE6344 licence not read
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method.reader_named_unmapped
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review.human_critique
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review.independent_reader
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review.machine_critique
assays array · 2 items
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data_generation
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rna_seq
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support_state
partial
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assay_lexicon
99e1195c7d6f
confidence
0.93
evidence array · 1 item
[0]
eria. Availability of data and materials The RNA-sequencing data and corresponding clinical information
order_basis
paper_text_order:2715
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assay:1
[1] object · 11 fields
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analysis
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survival_analysis
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required_operations array · 1 item
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cox_ph
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34838035", "kind": "science-record", "revision": 4, "content_hash": "sha256:adec831e51a3cff459712969835e4cefdda4d2fc2078e006f427f5dfa2682b77", "created_at": "2026-11-01T17:36:32Z", "updated_at": "2026-11-01T22:05:15Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Prognostic value and immunological role of AXL gene in clear cell renal cell carcinoma associated with identifying LncRNA/RBP/AXL mRNA networks.", "doi": "10.1186/s12935-021-02322-y", "pmid": "34838035", "authors": ["Yi Wang", "Ye Tian", "Shouyong Liu", "Zengjun Wang", "Qianwei Xing"], "journal": "Cancer cell international", "year": 2021, "abstract": "BACKGROUNDS: This article aimed to explore the prognostic and immunological roles of AXL gene in clear cell renal cell carcinoma (ccRCC) for overall survival (OS) and to identify the LncRNA/RBP/AXL mRNA networks.\nMETHODS: AXL-related gene expression matrix and clinical data were obtained from The Cancer Genome Atlas (TCGA) dataset and AXL-related pathways were identified by gene set enrichment analysis (GSEA). We performed univariate/multivariate Cox regression analysis to evaluate independent prognostic factors and the relationships between AXL and immunity were also investigated.\nRESULTS: The outcomes of us indicated that the AXL mRNA expression was up-regulated in ccRCC samples and high expression of AXL was associated with worse OS in TCGA dataset (P < 0.01). Further external verification results from HPA, UALCAN, ICGC dataset, GSE6344, GSE14994, and qRT-PCR remained consistent (all P < 0.05). AXL was also identified as an independent prognostic factor for ccRCC by univariate/multivariate Cox regression analysis (both P < 0.05). A nomogram including AXL expression and clinicopathological factors was established by us and GSEA results found that elevated AXL expression was associated with the JAK-STAT, P53, WNT, VEGF and MAPK signaling pathways. In terms of immunity, AXL was dramatically linked to tumor microenvironment, immune cells, immune infiltration, immune checkpoint molecules and tumor mutational burden (TMB). As for its potential mechanisms, we also identified several LncRNA/RBP/AXL mRNA axes.\nCONCLUSIONS: AXL was revealed to play prognostic and immunological roles in ccRCC and LncRNA/RBP/AXL mRNA axes were also identified by us for its potential mechanisms.", "claims": [{"id": "claim-method", "statement": "Univariate/multivariate Cox hazard regression analysis were employed to the ccRCC patients from TCGA database by R package to identify whether eight clinicopathological parameters (race, gender, age, grade, T, M, N, stage) and AXL could be independent factors correlated with OS.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34838035", "locator": "sections[7] \"Univariate/multivariate Cox hazard regression analysis and nomogram establishment\" paragraph 2", "quote": "Univariate/multivariate Cox hazard regression analysis were employed to the ccRCC patients from TCGA database by R package to identify whether eight clinicopathological parameters (race, gender, age, grade, T, M, N, stage) and AXL could be independent factors correlated with OS."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The RNA-sequencing data and corresponding clinical information were downloaded from the Cancer Genome Atlas (TCGA) database (https://portal.gdc.cancer.gov/) and the International Cancer Genome Consortium (ICGC) database (https://icgc.org/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34838035", "locator": "sections[28] \"Availability of data and materials\" paragraph 2", "quote": "The RNA-sequencing data and corresponding clinical information were downloaded from the Cancer Genome Atlas (TCGA) database (https://portal.gdc.cancer.gov/) and the International Cancer Genome Consortium (ICGC) database (https://icgc.org/)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "AXL was revealed to play prognostic and immunological roles in ccRCC.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:34838035", "locator": "sections[21] \"Conclusions\" paragraph 2", "quote": "Taken together, our results indicated that AXL was revealed to play prognostic and immunological roles in ccRCC."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "AXL was revealed to play prognostic and immunological roles in ccRCC.", "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:34838035"], "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:GSE14994"], "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:GSE14994"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34838035", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12935-021-02322-y", "sha256": 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