ArticleScientific reports2021
Transcriptome analysis of the procession from chronic pancreatitis to pancreatic cancer and metastatic pancreatic cancer.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed, 6 citations in OpenAlex.
- Multimodal profiling of pancreatic cancer reveals a TIMP-1-dominated secretory profile determining pro-tumor immunoinstruction in human cancers.Cell reports. Medicine · 2026Article
- Improved biomarker discovery through a plot twist in transcriptomic data analysis.BMC biology · 2022Article
- The research progress of anti-inflammatory and anti-fibrosis treatment of chronic pancreatitis.Frontiers in oncology · 2022Review
- Distinct Murine Pancreatic Transcriptomic Signatures during Chronic Pancreatitis Recovery.Mediators of inflammation · 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
8 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Exploring the underlying mechanisms of cancer development is useful for cancer treatment. In this paper, we analyzed the transcriptome profiles from the human normal pancreas, pancreatitis, pancreatic cancer and metastatic pancreatic cancer to study the intricate associations among pancreatic cancer progression. We clustered the transcriptome data, and analyzed the differential expressed genes. WGCNA was applied to construct co-expression networks and detect important modules. Importantly we selected the module in a different way. As the pancreatic disease deteriorates, the number of differentially expressed genes increases. The gene networks of T cells and interferon are upregulated in stages. In conclusion, the network-based study provides gradually activated gene networks in the disease progression of pancreatitis, pancreatic cancer, and metastatic pancreatic cancer. It may contribute to the rational design of anti-cancer drugs.
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.