Evidence map›Paper›PMID 35473935›Full record

ArticleBiomarker research2022

SRTdb: an omnibus for human tissue and cancer-specific RNA transcripts.

Qili Shi, Teng Liu, Wei Hu, Zhiao Chen, Xianghuo He, Shengli Li

Registry-linked trialAbstract read
In one paragraph

Article in Biomarker research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07319949 (Evaluative Study on Predicting the Primary Site of Metastatic Tumors Using Transcriptomic Profiling for Tumor Tissue Origin Identification), which is not on this map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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.

NCT07319949 not yet recruitingnot on this mapstarted 2026, after this paper: background citation

Evaluative Study on Predicting the Primary Site of Metastatic Tumors Using Transcriptomic Profiling for Tumor Tissue Origin Identification

TypeobservationalSponsorFudan UniversityRan2026 to 2026Enrolled30ConditionsMalignant Tumor With Metastasis, CUP
3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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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

6 authors.

Qili Shi *Fudan University Shanghai Cancer Center and Institute of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
Teng Liu *Precision Research Center for Refractory Diseases, Institute for Clinical Research, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201620, China.
Wei HuPrecision Research Center for Refractory Diseases, Institute for Clinical Research, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201620, China.
Zhiao ChenFudan University Shanghai Cancer Center and Institute of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
Xianghuo HeFudan University Shanghai Cancer Center and Institute of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai, 200032, China. xhhe@fudan.edu.cn.
Shengli LiPrecision Research Center for Refractory Diseases, Institute for Clinical Research, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201620, China. shengli.li@shsmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The production of functional mature RNA transcripts from genes undergoes various pre-transcriptional regulation and post-transcriptional modifications. Accumulating studies demonstrated that gene transcription carries out in tissue and cancer type-dependent ways. However, RNA transcript-level specificity analysis in large-scale transcriptomics data across different normal tissue and cancer types is lacking. We applied reference-based de novo transcript assembly and quantification of 27,741 samples across 33 cancer types, 29 tissue types, and 25 cancer cell line types. We totally identified 231,836 specific RNA transcripts (SRTs) across various tissue and cancer types, most of which are found independent of specific genes. Almost half of tumor SRTs are also tissue-specific but in different tissues. Furthermore, we found that 10 ~ 20% of tumor SRTs in most tumor types were testis-specific. The SRT database (SRTdb) was constructed based on these resources. Taking liver cancer as an example, we showed how SRTdb resource is utilized to optimize the identification of RNA transcripts for more precision diagnosis of particular cancers. Our results provide a useful resource for exploring transcript specificity across various cancer and tissue types, and boost the precision medicine for tumor patients.

Indexed as

Pan-cancer analysisPrecision tumor diagnosisRNA transcriptTissue specificity analysisTranscriptional diversity

Identifiers

PMID35473935
PMCPMC9044872

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