Evidence map›Paper›PMID 38730450›Full record

ArticleBiomarker research2024

Deciphering metabolic heterogeneity in retinoblastoma unravels the role of monocarboxylate transporter 1 in tumor progression.

Junjie Tang, Yaoming Liu, Yinghao Wang, Zhihui Zhang, Jiahe Nie, Xinyue Wang, Siming Ai, Jinmiao Li, Yang Gao, Cheng Li and 5 more

Abstract read
In one paragraph

Article in Biomarker research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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  10. SOX4 as a Key Oncogene Driving Tumor Invasion in Retinoblastoma.Investigative ophthalmology & visual science · 2025
    Article
  11. Article
  12. Review
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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

15 authors.

Junjie Tang *State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Yaoming Liu *State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Yinghao WangState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Zhihui ZhangState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Jiahe NieState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Xinyue WangState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Siming AiState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Jinmiao LiState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Yang GaoState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Cheng LiState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Chao ChengState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Shicai SuState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Shuxia ChenState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Ping ZhangState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Rong LuState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China. lurong@gzzoc.com.

Funding

National Natural Science Foundation of China 82203175Ocular Tumor Platform of Zhongshan Ophthalmic Center 303010406Science and Technology Program of Guangzhou 2024A03J0266Science and Technology Program of Guangzhou 2024A03J0267
6 · The paper itself

Abstract

backgroundTumors exhibit metabolic heterogeneity, influencing cancer progression. However, understanding metabolic diversity in retinoblastoma (RB), the primary intraocular malignancy in children, remains limited.

methodsThe metabolic landscape of RB was constructed based on single-cell transcriptomic sequencing from 11 RB and 5 retina samples. Various analyses were conducted, including assessing overall metabolic activity, metabolic heterogeneity, and the correlation between hypoxia and metabolic pathways. Additionally, the expression pattern of the monocarboxylate transporter (MCT) family in different cell clusters was examined. Validation assays of MCT1 expression and function in RB cell lines were performed. The therapeutic potential of targeting MCT1 was evaluated using an orthotopic xenograft model. A cohort of 47 RB patients was analyzed to evaluate the relationship between MCT1 expression and tumor invasion.

resultsDistinct metabolic patterns in RB cells, notably increased glycolysis, were identified. This metabolic heterogeneity correlated closely with hypoxia. MCT1 emerged as the primary monocarboxylate transporter in RB cells. Disrupting MCT1 altered cell viability and energy metabolism. In vivo studies using the MCT1 inhibitor AZD3965 effectively suppressed RB tumor growth. Additionally, a correlation between MCT1 expression and optic nerve invasion in RB samples suggested prognostic implications.

conclusionsThis study enhances our understanding of RB metabolic characteristics at the single-cell level, highlighting the significance of MCT1 in RB pathogenesis. Targeting MCT1 holds promise as a therapeutic strategy for combating RB, with potential prognostic implications.

Indexed as

AZD3965Cancer metabolismMonocarboxylate transporter 1Retinoblastoma

Identifiers

PMID38730450
PMCPMC11088057

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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.