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Record W4221071186 · doi:10.3389/fmolb.2022.778857

Comprehensive Analysis on Prognosis and Immune Infiltration of Lysyl Oxidase Family Members in Pancreatic Adenocarcinoma With Experimental Verification

2022· article· en· W4221071186 on OpenAlexaff
Chao Jiang, Meng Wang, Weikai Yao, Guoyue Lv, Xueyan Liu, Guangyi Wang

Bibliographic record

VenueFrontiers in Molecular Biosciences · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial metabolism and enzyme function
Canadian institutionsUniversity Health Network
FundersDepartment of Finance of Jilin ProvinceChina Scholarship Council
KeywordsLysyl oxidaseKEGGExtracellular matrixTumor microenvironmentImmune systemCancer researchPancreatic cancerBiologyImmunohistochemistryMetastasisAdenocarcinomaGene expressionCancerTranscriptomeGeneImmunologyGenetics

Abstract

fetched live from OpenAlex

Background: Pancreatic adenocarcinoma (PDAC) is the most aggressive among all solid malignancies with delayed disease detection and limited effective treatment. However, due to the intricate heterogeneity and exclusive tumor microenvironment (TME), the development of effective therapy has been facing enormous challenges. The lysyl oxidases (LOXs) underpin the shaping of the TME to promote cancer growth, metastasis and modulate response to treatment. Materials and Methods: The mRNA expression, prognostic, and clinicopathological data for LOXs in PDAC from multiple open-access databases were summarized and analyzed. The protein expression was verified by immunohistochemistry (IHC). Co-expressed genes of LOXs were predicted and elaborated by LinkedOmics. Functional enrichment analysis of LOXs co-expressed genes was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). TIMER and TISIDB were applied to analyze the relationship between LOXs expression and immune infiltration. Results: The mRNA expression levels of LOX, LOXL1 and LOXL2 were significantly higher in PDAC, the expression levels of LOXL3 and LOXL4 were contrary in different databases. High mRNA levels of LOX and LOXL2 were associated with advanced PDAC stage, while elevated LOX and LOXL3 expression correlated with high tumor grade. The IHC staining showed higher expression levels of LOX, LOXL1 and LOXL2, lower expression level of LOXL3 in PDAC tissues, while the protein expression of LOXL4 made no difference. Functional enrichment analysis showed a close relationship with extracellular matrix (ECM) regulation, except that LOXL3 and its ligands were highly associated with immune-related functions. Further analysis suggested that LOX and LOXL3 strongly correlated with tumor-infiltrating lymphocytes (TILs), various immune signatures, and immune checkpoints. Finally, survival analysis revealed high LOX and LOXL2 expression predicted worse overall survival (OS), progression-free interval (PFI), and disease-specific survival (DSS). Conclusion: These findings indicated that the LOX family, especially LOX and LOXL2, might have a prospective value in PDAC oncogenesis, and they may become prognostic biomarkers, revealing a promising field in targeted therapy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.214
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2022
Admission routes1
Has abstractyes

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