Evidence map›Paper›PMID 42146449›Full record

ArticlebioRxiv : the preprint server for biology2026

Solid Tumors Pan Cancer Transcriptome: Tissue/Cancer specific expression groups at the Isoform-Level.

Pallavi Surana, Matthew Obusan, Ramana V Davuluri

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Pallavi SuranaDepartment of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11794, USA.ORCID 0009-0004-4241-9181
Matthew ObusanDepartment of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11794, USA.
Ramana V DavuluriDepartment of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11794, USA.ORCID 0000-0002-7053-1064

Funding

Developing Novel Deep-Learning Based Methods for Deciphering Non-Coding Gene Regulatory CodeR01LM013722 · NLM · STATE UNIVERSITY NEW YORK STONY BROOK · PI RAMANA V DAVULURI · 2021 to 2026
$2.0M
NLM NIH HHS R01 LM013722
6 · The paper itself

Abstract

Most of the human genome is transcribed into diverse isoforms whose tissue specificity is profoundly disrupted in cancer, yet isoform-level dysregulation remains poorly characterized across solid tumors. Here, we introduce STPCaT (Solid Tumors Pan-Cancer Transcriptome), an isoform-centric analysis extending TransTEx to systematically classify transcript expression across TCGA solid tumors and GTEx normal tissues. STPCaT reveals a striking collapse of normal tissue-specific programs in cancer, accompanied by the emergence of two dominant expression groups: cancer-high (Can

Identifiers

PMID42146449
PMCPMC13174662

What OpenQuestion holds

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LicenceCC BY-NC
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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.