ArticleFrontiers in oncology2022
Construction of a prognostic signature for serous ovarian cancer based on lactate metabolism-related genes.
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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.
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.
Who cites it
12 citing papers in PubMed.
- A mechanistic study revealing that SLCO1B3 promotes gastric cancer development and metastasis through MAP1S expression downregulation.BMC cancer · 2026Article
- An Integrative Variant Scoring Function for Finding Novel Genes Associated with Ovarian and Thyroid Cancer.International journal of environmental research and public health · 2026Article
- Emerging insights into the role of BDH1 in the pathogenesis of human cancer.Frontiers in oncology · 2026Review
- Identification of a Novel Pyroptosis-Related lncRNAs Prognosis Model and Subtypes in Ovarian Cancer.Phenomics (Cham, Switzerland) · 2025Article
- Development of macrophage M2 relate signature for predicting prognosis and immunotherapy response in ovarian cancer.Discover oncology · 2025Article
- Identification and validation of a prognostic signature of drug resistance and mitochondrial energy metabolism-related differentially expressed genes for breast cancer.Journal of translational medicine · 2025Article
- piR-26441 inhibits mitochondrial oxidative phosphorylation and tumorigenesis in ovarian cancer through m6A modification by interacting with YTHDC1.Cell death & disease · 2025Article
- Establishment and Validation of Lactate Metabolism-Related Genes as a Prognostic Model for Gastric Cancer.Current molecular medicine · 2025Article
- Characteristics of Oxidative Phosphorylation-Related Subtypes and Construction of a Prognostic Signature in Ovarian Cancer.Current gene therapy · 2025Article
- Senescence-Related LncRNAs: Pioneering Indicators for Ovarian Cancer Outcomes.Phenomics (Cham, Switzerland) · 2024Review
- Glutamine metabolism prognostic index predicts tumour microenvironment characteristics and therapeutic efficacy in ovarian cancer.Journal of cellular and molecular medicine · 2024Article
- A macrophage related signature for predicting prognosis and drug sensitivity in ovarian cancer based on integrative machine learning.BMC medical genomics · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The key biochemical feature of malignant tumor is the conversion of energy metabolism from oxidative phosphorylation to glycolysis, which provides sufficient capacity and raw materials for tumor cell rapid growth. Our study aims to construct a prognostic signature for ovarian cancer based on lactate metabolism-related genes (LMRGs). Methods: Data of ovarian cancer and non-diseased ovarian data were downloaded from TCGA and the GTEx database, respectively. LMRGs were obtained from GeneCards and MSigDB databases, and the differentially expressed LMRGs were identified using limma and DESeq2 R packages. Cox regression analysis and LASSO were performed to determine the LMRGs associated with OS and develop the prognostic signature. Then, clinical significance of the prognostic signature in ovarian cancer was assessed. Results: A total of 485 differentially expressed LMRGs in ovarian tissue were selected for subsequent analysis, of which 324 were up-regulated and 161 were down regulated. We found that 22 LMRGs were most significantly associated with OS by using the univariate regression analysis. The prognostic scoring model was consisted of 12 LMRGs (SLCO1B3, ERBB4, SLC28A1, PDSS1, BDH1, AIFM1, TSFM, PPARGC1A, HGF, FGFR1, ABCC8, TH). Kaplan-Meier survival analysis indicated that poorer overall survival (OS) in the high-risk group patients (P<0.0001). This prognostic signature could be an independent prognostic indicator after adjusting to other clinical factors. The calibration curves of nomogram for the signature at 1, 2, and 3 years and the ROC curve demonstrated good agreement between the predicted and observed survival rates of ovarian cancer patients. Furthermore, the high-risk group patients have much lower expression level of immune checkpoint-TDO2 compared with the low-risk group (P=0.024). Conclusions: We established a prognostic signature based on LMRGs for ovarian cancer, and highlighted emerging evidence indicating that this prognostic signature is a promising approach for predicting ovarian cancer prognosis and guiding clinical therapy.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.