Evidence map›Paper›PMID 36624406›Full record

ArticleBMC cancer2023

Clinical features and lipid metabolism genes as potential biomarkers in advanced lung cancer.

María Merino Salvador, Lara Paula Fernández, Juan Moreno-Rubio, Gonzalo Colmenarejo, Enrique Casado, Ana Ramírez de Molina, María Sereno

Abstract read
In one paragraph

Article in BMC cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Effect ofJournal of thoracic disease · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

María Merino SalvadorMedical Oncology Department, Infanta Sofía University Hospital. Infanta Sofia University Hospital and Henares University Hospital Foundation for Biomedical Research and Innovation (FIIB HUIS HHEN), Paseo de Europa 34, San Sebastián de los Reyes, CP 28702, Madrid, Spain. mariamesal@gmail.com.
Lara Paula FernándezMolecular Oncology Group, IMDEA Food Institute, CEI UAM + CSIC, Madrid, Spain.
Juan Moreno-RubioMedical Oncology Department, Infanta Sofía University Hospital. Infanta Sofia University Hospital and Henares University Hospital Foundation for Biomedical Research and Innovation (FIIB HUIS HHEN), Paseo de Europa 34, San Sebastián de los Reyes, CP 28702, Madrid, Spain.
Gonzalo ColmenarejoBiostatistics and Bioinformatics Unit, IMDEA Food Institute, CEI UAM + CSIC, Madrid, Spain.
Enrique CasadoMedical Oncology Department, Infanta Sofía University Hospital. Infanta Sofia University Hospital and Henares University Hospital Foundation for Biomedical Research and Innovation (FIIB HUIS HHEN), Paseo de Europa 34, San Sebastián de los Reyes, CP 28702, Madrid, Spain.
Ana Ramírez de MolinaMolecular Oncology Group, IMDEA Food Institute, CEI UAM + CSIC, Madrid, Spain.
María SerenoMedical Oncology Department, Infanta Sofía University Hospital. Infanta Sofia University Hospital and Henares University Hospital Foundation for Biomedical Research and Innovation (FIIB HUIS HHEN), Paseo de Europa 34, San Sebastián de los Reyes, CP 28702, Madrid, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung cancer is one of the most lethal tumors with a poor survival rate even in those patients receiving new therapies. Metabolism is considered one of the hallmarks in carcinogenesis and lipid metabolism is emerging as a significant contributor to tumor metabolic reprogramming. We previously described a profile of some lipid metabolism related genes with potential prognostic value in advanced lung cancer.

aimTo analyze clinical and pathological characteristics related to a specific metabolic lipid genomic signature from patients with advanced lung cancer and to define differential outcome.

methodsNinety samples from NSCLC (non-small cell lung cancer) and 61 from SCLC (small cell lung cancer) patients were obtained. We performed a survival analysis based on lipid metabolic genes expression and clinical characteristics. The primary end point of the study was the correlation between gene expression, clinical characteristics and survival.

resultsClinical variables associated with overall survival (OS) in NSCLC patients were clinical stage, adenocarcinoma histology, Eastern Cooperative Oncology Group (ECOG), number and site of metastasis, plasma albumin levels and first-line treatment with platinum. As for SCLC patients, clinical variables that impacted OS were ECOG, number of metastasis locations, second-line treatment administration and Diabetes Mellitus (DM). None of them was associated with gene expression, indicating that alterations in lipid metabolism are independent molecular variables providing complementary information of lung cancer patient outcome.

conclusionsSpecific clinical features as well as the expression of lipid metabolism-related genes might be potential biomarkers with differential outcomes.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsSmall Cell Lung CarcinomaBiomarkersHumansLipid MetabolismLipidsPrognosisRetrospective StudiesBiomarkersLipidsAdvanced stagesLipid metabolismLung cancerOverall survival

Identifiers

PMID36624406
PMCPMC9830782

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.