Evidence map›Paper›PMID 42678551›Full record

ArticleNaunyn-Schmiedeberg's archives of pharmacology2026

Multiomics, pharmacogenomic, and structural characterization of NCCRP1 as a candidate therapeutic target in ovarian cancer.

Dahlak Daniel Solomon, Yung-Kuo Lee, Sachin Kumar, Kai-Fu Chang, Chung-Hsien Lin, Ching-Chung Ko, Ngoc Uyen Nhi Nguyen, Do Thi Minh Xuan, Neethu Palekkode, Chih-Yang Wang and 1 more

Abstract read
PubMed Publisher
In one paragraph

Article in Naunyn-Schmiedeberg's archives of pharmacology, 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

11 authors.

Dahlak Daniel Solomon *Ph.D. Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science, Taipei Medical University, Taipei, 11031, Taiwan.
Yung-Kuo Lee *School of Medicine, National Defense Medical University, Taipei, 11490, Taiwan.
Sachin KumarPh.D. Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science, Taipei Medical University, Taipei, 11031, Taiwan.
Kai-Fu ChangMedical Laboratory, Medical Education and Research Center, Kaohsiung Armed Forces General Hospital, Kaohsiung, 80284, Taiwan.
Chung-Hsien LinMedical Laboratory, Medical Education and Research Center, Kaohsiung Armed Forces General Hospital, Kaohsiung, 80284, Taiwan.
Ching-Chung KoDepartment of Medical Imaging, Chi-Mei Medical Center, Tainan, 710402, Taiwan.
Ngoc Uyen Nhi NguyenCenter for Regenerative Medicine, University of South Florida Health Heart Institute, Tampa, FL, 33602, USA.
Do Thi Minh XuanFaculty of Pharmacy, Van Lang University, 69/68 Dang Thuy Tram Street, Binh Loi Trung Ward, Ho Chi Minh City, 70000, Vietnam.
Neethu PalekkodePh.D. Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science, Taipei Medical University, Taipei, 11031, Taiwan.
Chih-Yang WangPh.D. Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science, Taipei Medical University, Taipei, 11031, Taiwan. chihyang@tmu.edu.tw.
Hui-Ru LinInstitute of Medical Science and Technology, National Sun Yat-Sen University, Kaohsiung, 80424, Taiwan. linlulu0805@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian cancer is characterized by extensive molecular heterogeneity and poor clinical outcomes, highlighting the need to identify biologically relevant therapeutic targets. NCCRP1 remains poorly characterized in ovarian cancer, and its molecular and therapeutic significance is largely unknown. In this study, we applied an integrative multiomics framework incorporating transcriptomic profiling, survival analysis, immune microenvironment characterization, pathway and network analyses, pharmacogenomic assessment, structural modeling, and single-cell RNA sequencing to investigate the role of NCCRP1 in ovarian cancer. Family-wide screening of the TCGA-OV cohort identified NCCRP1 as the only member significantly associated with overall survival. Elevated NCCRP1 expression was enriched in tumor tissues and associated with adverse clinical outcomes. Functional analyses demonstrated that NCCRP1-high tumors exhibit activation of epithelial-mesenchymal transition, cytoskeletal remodeling, adhesion signaling, and hypoxia-associated pathways, suggesting involvement in tumor plasticity and progression. Network-based analyses further positioned NCCRP1 within regulatory programs linked to structural reorganization and aggressive tumor phenotypes. Single-cell RNA sequencing confirmed that NCCRP1 expression is predominantly localized to malignant epithelial populations, supporting a tumor-intrinsic role. Pharmacogenomic analyses identified NCCRP1-associated transcriptional states linked to distinct drug sensitivity patterns, while structural modeling suggested the presence of a surface-accessible cavity capable of accommodating small molecules. Although these findings require experimental validation, they provide preliminary evidence supporting the potential druggability of NCCRP1. Our findings provide a comprehensive molecular characterization of NCCRP1 and support its prioritization as a candidate therapeutic target in ovarian cancer. This study demonstrates the utility of integrating multiomics, pharmacogenomic, structural, and single-cell approaches for therapeutic target discovery and prioritization in cancer.

Indexed as

NCCRP1Ovarian cancerPharmacogenomicsSingle-cell RNA sequencingStructural bioinformaticsTherapeutic target

Identifiers

PMID42678551

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.