Evidence map›Paper›PMID 41386760›Full record

ArticleCancer reports (Hoboken, N.J.)2025

A New Radiotranscriptomic Approach to Analyze Combined Sets of T3b Stage-Specific Genes and Radiomic Features in Prostate Cancer.

Qian Yang, Peng Tang, Jiao Mo, Qiuyang Li, Jiahui Huang, Xiaoyu Han, Hao Xu, Xi Liu, Jie Tang

Abstract read
In one paragraph

Article in Cancer reports (Hoboken, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

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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.

Qian YangDepartment of Ultrasound, Air Force Medical Center, Air Force Military Medical University, Beijing, China.ORCID 0000-0003-4401-1257
Peng TangDepartment of Orthopedics, China Rehabilitation Research Center, Beijing Charity Hospital, Beijing, China.ORCID 0000-0001-9985-8522
Jiao MoDepartment of Ultrasound, Air Force Medical Center, Air Force Military Medical University, Beijing, China.ORCID 0009-0008-7905-8948
Qiuyang LiDepartment of Ultrasound, First Medical Center, Chinese PLA General Hospital, Beijing, China.ORCID 0000-0002-7818-3842
Jiahui HuangDepartment of Ultrasound, Air Force Medical Center, Air Force Military Medical University, Beijing, China.ORCID 0009-0001-4826-1600
Xiaoyu HanDepartment of Ultrasound, Air Force Medical Center, Air Force Military Medical University, Beijing, China.ORCID 0009-0008-0218-8672
Hao XuDepartment of Ultrasound, Air Force Medical Center, Air Force Military Medical University, Beijing, China.ORCID 0009-0009-7460-7140
Xi LiuDepartment of Ultrasound, Air Force Medical Center, Air Force Military Medical University, Beijing, China.ORCID 0000-0002-6179-3695
Jie TangDepartment of Ultrasound, First Medical Center, Chinese PLA General Hospital, Beijing, China.ORCID 0000-0002-6882-4044

Funding

National Key Research and Development Program of China 2024YFB3214400National Social Science Fund of China 2024-SKJJ-B-047Natural Science Basic Research Program of Shaanxi Province 2023-JC-QN-0912
6 · The paper itself

Abstract

backgroundCurrent clinical staging of prostate cancer (PCa) using the tumor-node-metastasis (TNM) system and serum biomarkers remains limited in distinguishing locally advanced (T3b) PCa from organ-confined (T2c) disease.

aimsBuilding on our previous biomarker discovery in differentiating PCa from that of benign prostatic hyperplasia, this study pioneers a radiotranscriptomic model to distinguish T3b stage PCa from T2c stage PCa by integrating contrast-enhanced ultrasound (CEUS) radiomics with stage-specific transcriptomic signatures, addressing a critical knowledge gap in precision staging. METHODS AND

resultsThis prospective study was approved by the review board of Chinese PLA General Hospital (S2021-565-01), and all participants provided written informed consent. Transrectal B-mode ultrasound images and contrast-enhanced ultrasound images on two imaging planes were prospectively analyzed in 48 patients with biopsy-confirmed PCa (35 patients with stage T2c and 13 with stage T3b). Textural features were evaluated using microvascular ultrasonography and contrast-enhanced ultrasound. Radiomic data were then retrieved from all modes. An across-the-board investigation of mRNA and miRNA expressions was also performed in the two PCa stages. Six biomarkers (frizzled 4, ribosomal protein S7, ribosomal protein L29, miR-374c, miR-9, and miR-6510) were identified to differentiate T3b stage from T2c stage. The area under the curve (AUC) values of the combined set (AUC = 0.887, 0.956, and 0.996 for random forest, naïve Bayes, and support vector machine, respectively) and radiomic features alone (AUC = 0.921, 0.957, and 0.998, respectively) were found to be more accurate than those of the transcriptomic data alone (AUC = 0.583, 0.716, and 0.898, respectively) or clinical features alone (AUC = 0.585, 0.675, and 0.953, respectively). The PCa gene regulatory network comprised of four miRNAs (miR-148, miR-141, miR-342, and miR-210) may contribute to accelerating tumor progression.

conclusionWe established the new radiotranscriptomic signatures specifically optimized for differentiating T3b stage from T2c stage by decoding stage-specific imaging-genomic crosstalk. This new approach may overcome TNM staging limitations.

Indexed as

Biomarkers, TumorProstatic NeoplasmsTranscriptomeAgedContrast MediaGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMaleMiddle AgedNeoplasm StagingProspective StudiesRadiomicsUltrasonographyBiomarkers, TumorContrast Mediaprostate cancerradiomicsradiotranscriptomicstexture analysisultrasound

Identifiers

PMID41386760
PMCPMC12700717

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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.