Evidence map›Paper›PMID 39822275›Full record

ArticleNAR cancer2025

The Atlas of Protein-Protein Interactions in Cancer (APPIC)-a webtool to visualize and analyze cancer subtypes.

Benjamin Ahn, Charissa Chou, Caden Chou, Jennifer Chen, Amelia Zug, Yigit Baykara, Jessica Claus, Sean M Hacking, Alper Uzun, Ece D Gamsiz Uzun

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NAR cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Benjamin AhnDepartment of Pathology and Laboratory Medicine, The Warren Alpert Medical School of Brown University, 593 Eddy Street, Providence, RI 02903, USA.
Charissa ChouDepartment of Pathology and Laboratory Medicine, Rhode Island Hospital, 593 Eddy Street, Providence, RI 02903, USA.
Caden ChouDepartment of Pathology and Laboratory Medicine, The Warren Alpert Medical School of Brown University, 593 Eddy Street, Providence, RI 02903, USA.
Jennifer ChenDepartment of Pathology and Laboratory Medicine, The Warren Alpert Medical School of Brown University, 593 Eddy Street, Providence, RI 02903, USA.
Amelia ZugDepartment of Pathology and Laboratory Medicine, The Warren Alpert Medical School of Brown University, 593 Eddy Street, Providence, RI 02903, USA.
Yigit BaykaraDepartment of Pathology and Laboratory Medicine, The Warren Alpert Medical School of Brown University, 593 Eddy Street, Providence, RI 02903, USA.
Jessica ClausDepartment of Pathology and Laboratory Medicine, The Warren Alpert Medical School of Brown University, 593 Eddy Street, Providence, RI 02903, USA.
Sean M HackingDepartment of Pathology, NYU Grossman School of Medicine, 550 1st Ave., New York, NY 10016, USA.
Alper UzunDepartment of Pathology and Laboratory Medicine, The Warren Alpert Medical School of Brown University, 593 Eddy Street, Providence, RI 02903, USA.ORCID 0000-0001-6489-8591
Ece D Gamsiz UzunDepartment of Pathology and Laboratory Medicine, The Warren Alpert Medical School of Brown University, 593 Eddy Street, Providence, RI 02903, USA.ORCID 0000-0003-4068-7153

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer is a complex disease with heterogeneous mutational and gene expression patterns. Subgroups of patients who share a phenotype might share a specific genetic architecture including protein-protein interactions (PPIs). We developed the Atlas of Protein-Protein Interactions in Cancer (APPIC), an interactive webtool that provides PPI subnetworks of 10 cancer types and their subtypes shared by cohorts of patients. To achieve this, we analyzed publicly available RNA sequencing data from patients and identified PPIs specific to 26 distinct cancer subtypes. APPIC compiles biological and clinical information from various databases, including the Human Protein Atlas, Hugo Gene Nomenclature Committee, g:Profiler, cBioPortal and Clue.io. The user-friendly interface allows for both 2D and 3D PPI network visualizations, enhancing the usability and interpretability of complex data. For advanced users seeking greater customization, APPIC conveniently provides all output files for further analysis and visualization on other platforms or tools. By offering comprehensive insights into PPIs and their role in cancer, APPIC aims to support the discovery of tumor subtype-specific novel targeted therapeutics and drug repurposing. APPIC is freely available at https://appic.brown.edu.

Indexed as

NeoplasmsProtein Interaction MappingProtein Interaction MapsSoftwareHumansInternet

Identifiers

PMID39822275
PMCPMC11734624

What OpenQuestion holds

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Registered trials

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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.