Evidence map›Paper›PMID 22848304›Full record

ArticleOncology letters2011

HSulf-1 suppresses cell growth and down-regulates Hedgehog signaling in human gastric cancer cells.

Hui-Yan Ma, Fang Zhang, Jie Li, Min-Li Mo, Zhao Chen, Lili Liu, Hai-Meng Zhou, Qing Sheng

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.4field-weighted citation impact, top 38% of its field
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

7 citing papers in PubMed, 12 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

Hui-Yan MaCollege of Life Sciences, Zhejiang Sci-Tech University, Hangzhou 310018.
Fang Zhang
Jie Li
Min-Li Mo
Zhao Chen
Lili Liu
Hai-Meng Zhou
Qing Sheng
Tsinghua University · CNZhejiang Sci-Tech University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gastric cancer is the second most lethal cancer worldwide. Despite the current surgical and adjuvant therapies, 5-year survival remains less than 20-25% in the US, Europe and China. Therefore, there is an urgent need to identify new therapeutic targets for treating this malignant disease. Accumulating evidence has supported that aberrant activation of the Hedgehog signaling pathway plays a crucial role in tumorigenesis and progression of gastric cancer. Human sulfatase-1 (HSulf-1) is a recently identified enzyme that desulfates cell surface heparan sulfate proteoglycans (HSPGs), which is critical for Hedgehog signal transduction under a highly sulfated state. HSulf-1 has recently emerged as a tumor suppressor gene in certain types of cancer, including ovarian, breast, myeloma and hepatocellular carcinoma; however, its role in gastric cancer remains to be elucidated. Therefore, we established HSulf-1-expressing monoclonal MKN28 gastric cancer cells to investigate its function in gastric cancer. Expression of HSulf-1 significantly suppressed cellular proliferation and growth in MKN28 gastric cancer cells. Notably, HSulf-1 inhibits Gli-mediated transcription and down-regulates the expression of Hedgehog target genes, including GLI1, PTCH1/2, HHIP, CCND1, C-MYC and BCL-2. Collectively, the study provides evidence that HSulf-1 may function as a tumor suppressor in gastric cancer. It suppresses gastric cancer cell proliferation, possibly through abrogating the Hedgehog signaling pathway. The study provides new mechanistic insight into HSulf-1- mediated tumor suppression, and supports the use of HSulf-1 as a potential new therapeutic target in treating gastric cancer.

Identifiers

PMID22848304
PMCPMC3406501
OpenAlexW2026957368

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.