ArticleOncotarget2016
KCNN4 and S100A14 act as predictors of recurrence in optimally debulked patients with serous ovarian cancer.
Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled 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.
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
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.
- Prognostic and clinicopathological significance of S100A14 expression in cancer patients: A meta-analysis.Medicine · 2019Pooled it
- A diagnostic miRNA panel to detect recurrence of ovarian cancer through artificial intelligence approaches.Journal of cancer research and clinical oncology · 2023Article
- A machine learning approach to identify predictive molecular markers for cisplatin chemosensitivity following surgical resection in ovarian cancer.Scientific reports · 2021Article
- S100A14 inhibits cell growth and epithelial-mesenchymal transition (EMT) in prostate cancer through FAT1-mediated Hippo signaling pathway.Human cell · 2021Article
- Identification of 5-methylcytosine-related signature for predicting prognosis in ovarian cancer.Biological research · 2021Article
- Research Progress in Prognostic Factors and Biomarkers of Ovarian Cancer.Journal of Cancer · 2021Review
- Proteomic analysis enables distinction of early- versus advanced-stage lung adenocarcinomas.Clinical and translational medicine · 2020Article
- KCNN4 induces multiple chemoresistance in breast cancer by regulating BCL2A1.American journal of cancer research · 2020Article
- Recurrence-Associated Multi-RNA Signature to Predict Disease-Free Survival for Ovarian Cancer Patients.BioMed research international · 2020Article
- Ion Channels Orchestrate Pancreatic Ductal Adenocarcinoma Progression and Therapy.Frontiers in pharmacology · 2020Review
- KCancers · 2019Article
- Identification of S100A14 as a metastasis-promoting molecule in a murine organotropic metastasis model.Clinical & experimental metastasis · 2019Article
- Expression profile and functional role of S100A14 in human cancer.Oncotarget · 2019Review
- Prognostic values of S100 family members in ovarian cancer patients.BMC cancer · 2018Article
- Overexpression of S100A14 contributes to malignant progression and predicts poor prognosis of lung adenocarcinoma.Thoracic cancer · 2018Article
- A Clinicopathological Analysis of S100A14 Expression in Colorectal Cancer.In vivo (Athens, Greece)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Approximately 50-75% of patients with serous ovarian carcinoma (SOC) experience recurrence within 18 months after first-line treatment. Current clinical indicators are inadequate for predicting the risk of recurrence. In this study, we used 7 publicly available microarray datasets to identify gene signatures related to recurrence in optimally debulked SOC patients, and validated their expressions in an independent clinic cohort of 127 patients using immunohistochemistry (IHC). We identified a two-gene signature including KCNN4 and S100A14 which was related to recurrence in optimally debulked SOC patients. Their mRNA expression levels were positively correlated and regulated by DNA copy number alterations (CNA) (KCNN4: p=1.918e-05) and DNA promotermethylation (KCNN4: p=0.0179; S100A14: p=2.787e-13). Recurrence prediction models built in the TCGA dataset based on KCNN4 and S100A14 individually and in combination showed good prediction performance in the other 6 datasets (AUC:0.5442-0.9524). The independent cohort supported the expression difference between SOC recurrences. Also, a KCNN4 and S100A14-centered protein interaction subnetwork was built from the STRING database, and the shortest regulation path between them, called the KCNN4-UBA52-KLF4-S100A14 axis, was identified. This discovery might facilitate individualized treatment of SOC.
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.