ArticleBioscience reports2019
Role of long non-coding RNA TP73-AS1 in cancer.
Article in Bioscience reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 16 citations in OpenAlex.
- Uncovering alterations in cancer epigenetics via trans-dimensional Markov chain Monte Carlo and hidden Markov models.Journal of the Royal Statistical Society. Series C, Applied statistics · 2026Article
- Long Non-Coding TP73-AS1: A Potential Biomarker and Therapeutic Target in Cancer.International journal of molecular sciences · 2025Review
- TP73-AS1 Regulates MPP+-Induced Cell Inflammation and Apoptosis in SH-SY5Y Cells.Degenerative neurological and neuromuscular disease · 2025Article
- Review
- A Pleiotropic Role of Long Non-Coding RNAs in the Modulation of Wnt/β-Catenin and PI3K/Akt/mTOR Signaling Pathways in Esophageal Squamous Cell Carcinoma: Implication in Chemotherapeutic Drug Response.Current oncology (Toronto, Ont.) · 2022Review
- Regulatory mechanisms and potential medical applications of HNF1A-AS1 in cancers.American journal of translational research · 2022Review
- RHO GTPase-Related Long Noncoding RNAs in Human Cancers.Cancers · 2021Review
- Comprehensive analysis of LncRNAs expression profiles in an in vitro model of steatosis treated with Exendin-4.Journal of translational medicine · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer incidence rate has increased so much that it is the second leading cause of deaths worldwide after cardiovascular diseases. Sensitive and specific biomarkers are needed for an early diagnosis of cancer and in-time treatment. Recent studies have found that long non-coding RNAs (lncRNAs) participate in cancer tumorigenesis. LncRNA P73 antisense RNA 1T (TP73-AS1), also known as KIAA0495 and p53-dependent apoptosis modulator (PDAM), is located in human chromosomal band 1p36.32 and plays a crucial role in many different carcinomas. This review summarizes current findings on the role of TP73-AS1 and its signaling pathways in various cancers, including glioma, esophageal squamous cell carcinoma (ESCC), hepatocellular carcinoma (HCC), colorectal cancer (CRC), osteosarcoma, gastric cancer (GC), clear cell renal cell carcinoma (ccRCC), breast cancer (BC), bladder cancer, ovarian cancer, cholangiocarcinoma (CCA), lung cancer, and pancreatic cancer. Its aberrant expression generally correlates with clinicopathological characterization of patients. Moreover, TP73-AS1 regulates proliferation, migration, invasion, apoptosis, and chemoresistance cancer mechanisms, both in vivo and in vitro, through different signaling pathways. Therefore, TP73-AS1 may be considered as a marker for diagnosis and prognosis, also as a target for cancer treatment.
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.