Evidence map›Paper›PMID 39659524›Full record

ReviewFrontiers in cell and developmental biology2024

Targeting the JAK-STAT pathway in colorectal cancer: mechanisms, clinical implications, and therapeutic potential.

Penghui Li, Di Huang

Abstract readReview
In one paragraph

Review in Frontiers in cell and developmental biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Penghui LiDepartment of Gastrointestinal Surgery, The First Affiliated Hospital, College of Clinical Medicine, Henan University of Science and Technology, Luoyang, Henan, China.
Di HuangDepartment of Child Health Care, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colorectal cancer (CRC) remains one of the most prevalent and fatal malignancies worldwide, consistently ranking among the top three in terms of incidence and mortality. Despite notable advancements in early detection and therapeutic interventions, survival outcomes for advanced-stage CRC are still dismal, largely due to issues such as drug resistance and metastasis. Recent research has increasingly implicated the JAK-STAT signaling pathway as a pivotal contributor to CRC pathogenesis. This evolutionarily conserved pathway plays a key role in transmitting extracellular signals to the nucleus, thereby modulating gene expression involved in numerous fundamental biological processes. In CRC, dysregulation of the JAK-STAT pathway is frequently observed and is strongly associated with tumor progression, including processes such as cellular proliferation, apoptosis, metastasis, immune evasion, and the sustenance of cancer stem cells. Given its integral role in CRC advancement, the JAK-STAT pathway has gained recognition as a viable therapeutic target. Extensive evidence from preclinical and clinical models supports the efficacy and safety of targeting components of the JAK-STAT pathway, presenting new therapeutic possibilities for patients with CRC, particularly in addressing drug resistance and enhancing treatment outcomes. This review offers a detailed exploration of the JAK-STAT pathway, focusing on its regulatory mechanisms in CRC-related malignancies. Moreover, it examines the association between JAK-STAT protein expression, clinical features, prognosis, and its therapeutic potential in CRC management.

Indexed as

colorectal cancerJAK-STATmechanismprognosistherapeutic potential

Identifiers

PMID39659524
PMCPMC11628519

What OpenQuestion holds

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Registered trials

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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.