Evidence map›Paper›PMID 35586489›Full record

ArticleFrontiers in oncology2022

ACYP1 Is a Pancancer Prognostic Indicator and Affects the Immune Microenvironment in LIHC.

Lingyi Zhou, Zheng Fu, Shuai Wang, Jing Jia, Yumeng Cheng, Yunxiang Zheng, Ningning Zhang, Wei Lu, Zhi Yao

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 37% 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

5 citing papers in PubMed, 7 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

9 authors at 3 institutions in 1 country.

Lingyi ZhouDepartment of Immunology, Key Laboratory of Immune Microenvironment and Disease of the Educational Ministry of China, Tianjin Key Laboratory of Cellular and Molecular Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
Zheng FuDepartment of Immunology, Key Laboratory of Immune Microenvironment and Disease of the Educational Ministry of China, Tianjin Key Laboratory of Cellular and Molecular Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
Shuai WangDepartment of Hepatobiliary Oncology, Liver Cancer Center, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University, Tianjin, China.
Jing JiaDepartment of Immunology, Key Laboratory of Immune Microenvironment and Disease of the Educational Ministry of China, Tianjin Key Laboratory of Cellular and Molecular Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
Yumeng ChengDepartment of Clinical Pharmacy, Tianjin Medical University, Tianjin, China.
Yunxiang ZhengDepartment of Clinical Pharmacy, Tianjin Medical University, Tianjin, China.
Ningning ZhangDepartment of Hepatobiliary Oncology, Liver Cancer Center, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University, Tianjin, China.
Wei LuDepartment of Hepatobiliary Oncology, Liver Cancer Center, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University, Tianjin, China.
Zhi YaoDepartment of Immunology, Key Laboratory of Immune Microenvironment and Disease of the Educational Ministry of China, Tianjin Key Laboratory of Cellular and Molecular Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
Tianjin Medical University · CNTianjin Medical University Cancer Institute and Hospital · CNTianjin Institute of Pharmaceutical Research (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: ACYP1 plays important physiological and metabolic roles in glycolysis and membrane ion pump activity by catalyzing acyl phosphate hydrolysis. ACYP1 is related to tumorigenesis and progression and poor prognosis in gastrointestinal cancer. However, its pancancer roles and mechanisms are unclear. Our study aimed to understand the ACYP1 expression signature and prognostic value across cancers and investigate immune infiltration patterns in liver hepatocellular carcinoma (LIHC) and verify them in LIHC samples. Methods: Transcriptional expression profiles of ACYP1 across cancers were analyzed using Oncomine and TIMER. The prognostic value of ACYP1 was assessed across PrognoScan, Kaplan-Meier Plotter, and GEPIA. Significant pathways associated with ACYP1 in LIHC were obtained Results: ACYP1 was overexpressed across cancers. High expression of ACYP1 correlated with a poor prognosis in most tumor types, especially in LIHC. ACYP1 was significantly implicated in immune and metabolic related pathways. High ACYP1 expression showed significant correlations with the abundances of Th2 cells, Tregs, macrophages, dendritic cells, and myeloid-derived suppressor cells in LIHC. LIHC patients with high ACYP1 expression showed significantly shorter overall survival and relapse-free survival rates concomitant with increased infiltration of CD4+ T cells. Mouse subcutaneous tumors with ACYP1 overexpression exhibited significantly accelerated tumor progression with increased aggregation of CD4+ T cells. Conclusion: Overall, ACYP1 may serve as a vital prognostic biomarker and play an immunoregulatory role in LIHC.

Indexed as

ACYP1biomarkerimmune infiltrationLIHCliver hepatocellular carcinomapancancerprognosis

Identifiers

PMID35586489
PMCPMC9108903
OpenAlexW4225275635

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.