ArticleBeijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences2023
[Activation of JAK/STAT in ovarian high-grade serous cancers and its prognostic significance].
Article in Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Immunohistochemical expression of JAK2, STAT3, POLH, UBE2T, and REV7 in serous ovarian carcinoma: clinicopathological associations and co-expression patterns.Journal of molecular histology · 2026Article
- The Active Ingredients and Mechanisms of Xuefuzhuyu Pills in Treating Hyperprolactinemia Caused by Antipsychotics based on UHPLCQ-TOF-MS/MS, Network Pharmacology, and Molecular Docking Validation.Current computer-aided drug design · 2026Article
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
objectiveThe activation of Janus kinase (JAK) and signal transducers and activators of transcription (STAT) plays an important role in the prognosis and targeted therapy of ovarian high-grade serous carcinoma (HGSC). Utilizing simple and practicable technique, this study aimed to evaluate the activation of JAK/STAT signaling pathway in ovarian HGSC patients, and investigated the correlation between the activation of JAK/STAT signaling pathway and the prognosis of the HGSC patients.
methodsWe performed immunohistochemistry of phosphorylated STAT3 (pSTAT3) and phosphorylated STAT5 (pSTAT5) on paraffin imbedded slides of 73 ovarian HGSC patients, and evaluated the expression level and range of both markers. According to the grading score of the immunostaining of pSTAT3 and pSTAT5, we divided the 73 ovarian HGSC cases into STAT3 low/high expression and STAT5 low/high expression groups, and analyzed the prognosis of the patients in different groups, in order to explore the relationship between the expression of pSTAT3 and pSTAT5 proteins and the prognosis of the HGSC patients.
resultsSome of the ovarian HGSC cases showed high expression of pSTAT3 and pSTAT5 protein level, which was related to the poorer prognosis of the HGSC patients. There was a significant difference in the expression level of pSTAT3 and pSTAT5 between the patients with better prognosis (survival time ≥3 years) and poorer prognosis (survival time < 3 years). The patients with higher protein expression of pSTAT3, pSTAT5 or both markers might have poorer prognosis, with significant shorter progression-free survival time and overall survival time (
conclusionImmunostaining of pSTAT3 and pSTAT5 proteins might be helpful to evaluate and predict the prognosis of the ovarian HGSC patients, and to identify the patients who might have higher chances to respond to the STAT inhibitors and anti-angiogenesis therapy.
Indexed as
Identifiers
37042137PMC10091257What 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.