Determination of Exploratory Metastasis Biomarkers in Cancer of Unknown Primary Using Metastatic Colon Cancer as a Model: RNA Sequencing Bioinformatics Analysis

We aimed to explore the real-world practice setting and identify common genetic signaling or patterns in cancer of unknown primary (CUP) using colon cancer as a model through RNA sequencing bioinformatics analysis. Data were retrieved and analyzed using the hospital information system. We compared the number of CUP patients involved in Medical Oncology services with those who were not, and used a bioinformatics approach to analyze RNA sequencing datasets from The Cancer Genome Atlas for metastatic colon cancer as a prototype and compare information between the primary tumor and its metastatic sites. Comparisons for identifying differentially expressed genes included liver metastases versus primary tumors, lymph node metastases versus primary tumors, and all colon tumors with metastasis versus those without. Over 20 years, the hospital identified 1193 CUP patients; 154 received Medical Oncology services. We sourced 37 primary and 9 metastatic (5 liver, 4 lymph node) colon cancer RNA sequencing datasets for bioinformatics analysis. Multigroup analysis identified ROPN1, Y_RNA, and OR4F4 as highly expressed in both metastatic types. High ROPN1 expression was associated with poor overall and disease-free survival rates. RNA sequencing bioinformatics is potentially useful for identifying exploratory metastasis biomarkers in CUP. ROPN1 may be linked to metastasis and unfavorable prognosis in colon cancer. Further analysis across paired primary/metastatic panels from multiple cancer types is warranted to determine the lineage-tracing utility in CUP.

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Journal
Current Issues in Molecular Biology
Published
2026-10-14
DOI
https://doi.org/10.3390/cimb48101058
Primary Topic
Cancer Diagnosis and Treatment
Type
article
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article

Determination of Exploratory Metastasis Biomarkers in Cancer of Unknown Primary Using Metastatic Colon Cancer as a Model: RNA Sequencing Bioinformatics Analysis

Jirapat Wonglhow, Pongsakorn Choochuen, Maliwan Songserm, Rawikant Kamolphiwong et al.
Current Issues in Molecular Biology
Cancer Diagnosis and Treatment
article

Determination of Exploratory Metastasis Biomarkers in Cancer of Unknown Primary Using Metastatic Colon Cancer as a Model: RNA Sequencing Bioinformatics Analysis

Jirapat Wonglhow, Pongsakorn Choochuen, Maliwan Songserm, Rawikant Kamolphiwong, Chirawadee Sathitruangsak, Patcharaporn Thongwatchara, Arunee Dechaphunkul, Patrapim Sunpaweravong
article en

Abstract

We aimed to explore the real-world practice setting and identify common genetic signaling or patterns in cancer of unknown primary (CUP) using colon cancer as a model through RNA sequencing bioinformatics analysis. Data were retrieved and analyzed using the hospital information system. We compared the number of CUP patients involved in Medical Oncology services with those who were not, and used a bioinformatics approach to analyze RNA sequencing datasets from The Cancer Genome Atlas for metastatic colon cancer as a prototype and compare information between the primary tumor and its metastatic sites. Comparisons for identifying differentially expressed genes included liver metastases versus primary tumors, lymph node metastases versus primary tumors, and all colon tumors with metastasis versus those without. Over 20 years, the hospital identified 1193 CUP patients; 154 received Medical Oncology services. We sourced 37 primary and 9 metastatic (5 liver, 4 lymph node) colon cancer RNA sequencing datasets for bioinformatics analysis. Multigroup analysis identified ROPN1, Y_RNA, and OR4F4 as highly expressed in both metastatic types. High ROPN1 expression was associated with poor overall and disease-free survival rates. RNA sequencing bioinformatics is potentially useful for identifying exploratory metastasis biomarkers in CUP. ROPN1 may be linked to metastasis and unfavorable prognosis in colon cancer. Further analysis across paired primary/metastatic panels from multiple cancer types is warranted to determine the lineage-tracing utility in CUP.

Current Issues in Molecular BiologyVol. 48(10)
Prince of Songkla University (TH)
Good health and well-being
Openalex Percentile: Top 18%
Cancer Diagnosis and Treatment
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