Evidence map›Paper›PMID 39249558›Full record

ArticleClinical and experimental medicine2024

APOBEC family reshapes the immune microenvironment and therapy sensitivity in clear cell renal cell carcinoma.

Guiying Huang, Xianlin Zhan, Lihong Shen, Luping Lou, Yuehong Dai, Aiming Jiang, Yuzhen Gao, Yanzhong Wang, Xinyou Xie, Jun Zhang

Abstract read
In one paragraph

Article in Clinical and experimental medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

10 authors.

Guiying Huang *Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Xianlin Zhan *Department of Clinical Laboratory, PLA Navy Medical Center, Shanghai, China.
Lihong ShenDepartment of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Luping LouDepartment of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Yuehong DaiDepartment of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Aiming JiangDepartment of Urology, Changhai Hospital, Naval Medical University (Second Military Medical University), Shanghai, China.
Yuzhen GaoDepartment of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Yanzhong WangDepartment of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Xinyou XieDepartment of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China. srrshoffice@163.com.
Jun ZhangDepartment of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China. jameszhang2000@zju.edu.cn.

Funding

The China National Key Research and Development Program Stem Cell and Translational Research Key Projects 2018YFA0108300The National Natural Science Foundation of China 81902560,81730073, 81872074
6 · The paper itself

Abstract

Emerging evidence suggests that the APOBEC family is implicated in multiple cancers and might be utilized as a new target for cancer detection and treatment. However, the dysregulation and clinical implication of the APOBEC family in clear cell renal cell cancer (ccRCC) remain elusive. TCGA multiomics data facilitated a comprehensive exploration of the APOBEC family across cancers, including ccRCC. Remodeling analysis classified ccRCC patients into two distinct subgroups: APOBEC family pattern cancer subtype 1 (APCS1) and subtype 2 (APCS2). The study investigated differences in clinical parameters, tumor immune microenvironment, therapeutic responsiveness, and genomic mutation landscapes between these subtypes. An APOBEC family-related risk model was developed and validated for predicting ccRCC patient prognosis, demonstrating good sensitivity and specificity. Finally, the overview of APOBEC3B function was investigated in multiple cancers and verified in clinical samples. APCS1 and APCS2 demonstrated considerably distinct clinical features and biological processes in ccRCC. APCS1, an aggressive subtype, has advanced clinical stage and a poor prognosis. APCS1 exhibited an oncogenic and metabolically active phenotype. APCS1 also exhibited a greater tumor mutation load and immunocompromised condition, resulting in immunological dysfunction and immune checkpoint treatment resistance. The genomic copy number variation of APCS1, including arm gain and loss, was much more than that of APCS2, which may help explain the tired immune system. Furthermore, the two subtypes have distinct drug sensitivity patterns in clinical specimens and matching cell lines. Finally, we developed a predictive risk model based on subtype biomarkers that performed well for ccRCC patients and validated the clinical impact of APOBEC3B. Aberrant APOBEC family expression patterns might modify the tumor immune microenvironment by increasing the genome mutation frequency, thus inducing an immune-exhausted phenotype. APOBEC family-based molecular subtypes could strengthen the understanding of ccRCC characterization and guide clinical treatment. Targeting APOBEC3B may be regarded as a new therapeutic target for ccRCC.

Indexed as

APOBEC DeaminasesCarcinoma, Renal CellKidney NeoplasmsTumor MicroenvironmentBiomarkers, TumorHumansMinor Histocompatibility AntigensMutationPrognosisAPOBEC DeaminasesBiomarkers, TumorMinor Histocompatibility AntigensAPOBEC familyClear cell renal cell carcinomaMachine learningMolecular subtypesMultiomicsTumor immunity

Identifiers

PMID39249558
PMCPMC11383847

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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.