Evidence map›Paper›PMID 40433925›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

Single-Cell Analysis Reveals that Vitamin C Inhibits Bone Metastasis of Renal Cancer via Cell Cycle Arrest and Microenvironment Remodeling.

Jianye Zhang, Qi Zhang, Gang Lin, Ying Wang, Juan Li, Ping Wang, Jie Qi, Yuan Liang, Shiming He, Yanqing Gong and 8 more

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
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

18 authors.

Jianye ZhangDepartment of Urology, Peking University First Hospital, Beijing, 100034, P. R. China.
Qi ZhangChina National Center for Bioinformation, Beijing, 100101, P. R. China.
Gang LinDepartment of Thoracic Surgery, Peking University First Hospital, Peking University, Beijing, 100034, P. R. China.
Ying WangChina National Center for Bioinformation, Beijing, 100101, P. R. China.
Juan LiChina National Center for Bioinformation, Beijing, 100101, P. R. China.
Ping WangChina National Center for Bioinformation, Beijing, 100101, P. R. China.
Jie QiChina National Center for Bioinformation, Beijing, 100101, P. R. China.
Yuan LiangChina National Center for Bioinformation, Beijing, 100101, P. R. China.
Shiming HeDepartment of Urology, Peking University First Hospital, Beijing, 100034, P. R. China.
Yanqing GongDepartment of Urology, Peking University First Hospital, Beijing, 100034, P. R. China.
Ninghan FengDepartment of Urology, Affiliated Wuxi No. 2 Hospital of Nanjing Medical University, Wuxi, 214002, P. R. China.
Yang WangDepartment of Urology, Affiliated Wuxi No. 2 Hospital of Nanjing Medical University, Wuxi, 214002, P. R. China.
Yuanyuan MaAnimal Center, Peking University First Hospital, Beijing, 100034, P. R. China.
Mei ZhangChina National Center for Bioinformation, Beijing, 100101, P. R. China.
Yue ShiChina National Center for Bioinformation, Beijing, 100101, P. R. China.
Xuesong LiDepartment of Urology, Peking University First Hospital, Beijing, 100034, P. R. China.
Weimin CiChina National Center for Bioinformation, Beijing, 100101, P. R. China.ORCID https://orcid.org/0000-0002-4111-5360
Liqun ZhouDepartment of Urology, Peking University First Hospital, Beijing, 100034, P. R. China.

Funding

Beijing Natural Science Foundation J230017Beijing Natural Science Foundation L248017Capital Health Research and Development of Special Fund 2022-1-4072Clinical Features Research of Capital Z211100002921070National High Level Hospital Clinical Research Funding 2022CR73National High Level Hospital Clinical Research Funding 2025SF032National Natural Science Foundation of China 82173216National Natural Science Foundation of China 82341030National Natural Science Foundation of China 82372951
6 · The paper itself

Abstract

Bone metastasis is the second most common site of distant metastatic spread in renal cell carcinoma (RCC) patients, significantly contributing to cancer-related mortality. The metastatic process is driven by both intrinsic tumor cell properties, such as cancer stem cell-like characteristics, and the bone microenvironment. Understanding the complex interactions between cancer cells and their niche is crucial for identifying therapeutic targets to eliminate metastasis-initiating cells and prevent overt metastasis. In this study, a murine bone metastasis model is developed using renal cancer cells derived from fibrin gel-induced 3D tumor spheres, which exhibit stem-like phenotypes. It is found that a stable form of vitamin C, L-ascorbic acid 2-phosphate sesquimagnesium (APM), significantly inhibits the growth of renal cancer stem-like cells in vitro and the progression of RCC bone metastasis in vivo. Single-cell RNA sequencing revealed that APM induces cell cycle arrest and reduces the metastatic potential of cancer cells. Furthermore, APM remodels the tumor microenvironment by suppressing osteoclast differentiation and neutrophil recruitment. Combining APM with a CXCR2 antagonist, SB225002, further inhibits bone metastasis progression. This study provides a high-resolution profile of vitamin C's antitumor effects in the bone metastatic microenvironment and supports the rationale for clinical trials of vitamin C in bone metastatic RCC.

Indexed as

Ascorbic AcidBone NeoplasmsCarcinoma, Renal CellCell Cycle CheckpointsKidney NeoplasmsTumor MicroenvironmentAnimalsCell Line, TumorHumansMiceSingle-Cell AnalysisAscorbic AcidAPMbone metastasismicroenvironmentrenal cancertreatment

Identifiers

PMID40433925
PMCPMC12376498

What OpenQuestion holds

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Registered trials

None linked

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.