Identification and validation of a prognostic model for HER2-low breast cancer based on unfolded protein response-related genes

The prognostic model based on UPR related genes, COPS5, DKC1, NOP56, and EIF4G1, could predict the prognosis of HER2-low breast cancer patients.

Authors

Institutions

Publication Details

Journal
Discover Oncology
Published
2025-10-14
DOI
https://doi.org/10.1007/s12672-025-03718-2
Primary Topic
Endoplasmic Reticulum Stress and Disease
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Identification and validation of a prognostic model for HER2-low breast cancer based on unfolded protein response-related genes

Hui Yan, Yuanyuan Gao, Ping Hu, Yanjiao Zhao
Discover Oncology
Endoplasmic Reticulum Stress and Disease
article

Identification and validation of a prognostic model for HER2-low breast cancer based on unfolded protein response-related genes

Hui Yan, Yuanyuan Gao, Ping Hu, Yanjiao Zhao
article en

Abstract

The prognostic model based on UPR related genes, COPS5, DKC1, NOP56, and EIF4G1, could predict the prognosis of HER2-low breast cancer patients.

Discover OncologyVol. 16(1)
Ningxia Medical University (CN), Ningxia Medical University General Hospital (CN)
Ningxia Medical University, Natural Science Foundation of Ningxia Province
Openalex Percentile: Top 69%
Endoplasmic Reticulum Stress and Disease
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.