A Resource for Retrieving and Visualizing Human GPCR–Cancer Association Information: GPCR-PEnDB 2.0

Background/Objectives: G protein-coupled receptors (GPCRs) form the largest group of cell surface receptors, with approximately 800 genes encoded in the human genome. Many GPCRs are therapeutic targets for major human diseases, including cancer. However, information describing their connections with cancer remains scattered across publications and online resources. GPCR-PEnDB is a database established in 2020 to provide structural and functional information on GPCRs. The present study introduces an expanded version of the original database with an additional module focused on literature-reported associations between human GPCRs and cancer. Methods: A systematic PubMed mining workflow was developed using 832 human GPCRs and 33 cancer types in TCGA. Current and historical GPCR gene symbols, receptor names, and synonyms were collected from UniProt and the HUGO Gene Nomenclature Committee and assessed using PubMed records. Terms likely to retrieve unrelated publications were excluded or further scrutinized in a receptor-specific context. The retained GPCR search terms were combined with predefined cancer names and synonyms to retrieve human-related, non-review publications. Titles and abstracts were screened for the intended receptor and cancer type. Retained publications were classified using association categories that were initially defined manually and expanded using OpenAI, GPT-5.6 Sol. Results: GPCR-PEnDB 2.0 contains 458 unique human GPCRs with published connections to one or more of the 33 TCGA cancer types. Interactive network visualizations summarize the number of publications supporting each GPCR–cancer association. Users can search by GPCR or cancer type, with each association displaying supporting PubMed records, matched terms, extracted sentences, and assigned categories. Conclusions: GPCR-PEnDB 2.0 provides a centralized resource for examining published GPCR–cancer connections and their reported biological, clinical, and therapeutic contexts.

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Publication Details

Journal
Biomedicines
Published
2026-11-08
DOI
https://doi.org/10.3390/biomedicines14112565
Primary Topic
Receptor Mechanisms and Signaling
Type
article
Field-Weighted Citation Impact
0.00
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article

A Resource for Retrieving and Visualizing Human GPCR–Cancer Association Information: GPCR-PEnDB 2.0

Jonathon E. Mohl, Ming‐Ying Leung, Khodeza Begum Mitchell
Biomedicines
Receptor Mechanisms and Signaling
article

A Resource for Retrieving and Visualizing Human GPCR–Cancer Association Information: GPCR-PEnDB 2.0

Jonathon E. Mohl, Ming‐Ying Leung, Khodeza Begum Mitchell
article en

Abstract

Background/Objectives: G protein-coupled receptors (GPCRs) form the largest group of cell surface receptors, with approximately 800 genes encoded in the human genome. Many GPCRs are therapeutic targets for major human diseases, including cancer. However, information describing their connections with cancer remains scattered across publications and online resources. GPCR-PEnDB is a database established in 2020 to provide structural and functional information on GPCRs. The present study introduces an expanded version of the original database with an additional module focused on literature-reported associations between human GPCRs and cancer. Methods: A systematic PubMed mining workflow was developed using 832 human GPCRs and 33 cancer types in TCGA. Current and historical GPCR gene symbols, receptor names, and synonyms were collected from UniProt and the HUGO Gene Nomenclature Committee and assessed using PubMed records. Terms likely to retrieve unrelated publications were excluded or further scrutinized in a receptor-specific context. The retained GPCR search terms were combined with predefined cancer names and synonyms to retrieve human-related, non-review publications. Titles and abstracts were screened for the intended receptor and cancer type. Retained publications were classified using association categories that were initially defined manually and expanded using OpenAI, GPT-5.6 Sol. Results: GPCR-PEnDB 2.0 contains 458 unique human GPCRs with published connections to one or more of the 33 TCGA cancer types. Interactive network visualizations summarize the number of publications supporting each GPCR–cancer association. Users can search by GPCR or cancer type, with each association displaying supporting PubMed records, matched terms, extracted sentences, and assigned categories. Conclusions: GPCR-PEnDB 2.0 provides a centralized resource for examining published GPCR–cancer connections and their reported biological, clinical, and therapeutic contexts.

BiomedicinesVol. 14(11)
The University of Texas at El Paso (US)
Receptor Mechanisms and Signaling
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A Resource for Retrieving and Visualizing Human GPCR–Cancer Association Information: GPCR-PEnDB 2.0 — Jonathon E. Mohl, Ming‐Ying Leung, et al. · Biomedicines (2026) | TGRS Research Map | TGRS