Evidence map›Paper›PMID 42841377›Full record

ArticleMolecular oncology2026

Unique circulating miRNAome signatures captured with distinct molecular states in Lynch syndrome and sporadic colorectal cancer.

Ramadhani Salum Chambuso, Md Shohel Ul Islam, Rosa M Xicola, Raj Ramesar, Xavier Llor, Sinclair Steele

Abstract read
In one paragraph

Article in Molecular oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

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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

6 authors.

Ramadhani Salum ChambusoDepartment of Pathological Sciences, College of Medicine, Ajman University, UAE.ORCID https://orcid.org/0000-0001-8794-604X
Md Shohel Ul IslamDepartment of Genetic Engineering and Biotechnology, Faculty of Biological Science and Technology, Jashore University of Science and Technology, Bangladesh.ORCID https://orcid.org/0000-0001-7725-3899
Rosa M XicolaSection of Digestive Diseases, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA.ORCID https://orcid.org/0000-0001-6466-1885
Raj RamesarDivision of Human Genetics, Department of Pathology, University of Cape Town, South Africa.ORCID https://orcid.org/0000-0001-5688-1634
Xavier LlorSection of Digestive Diseases, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA.ORCID https://orcid.org/0000-0002-6259-185X
Sinclair SteeleDepartment of Pathological Sciences, College of Medicine, Ajman University, UAE.ORCID https://orcid.org/0000-0002-0409-8039

Funding

Ajman University AU-DRG 501/2025
6 · The paper itself

Abstract

Hereditary nonpolyposis colorectal cancer (HNPCC), usually termed Lynch syndrome (LS), is the most prevalent hereditary colorectal cancer syndrome, yet molecular biomarkers to differentiate nonmalignant from malignant LS cases remain limited. We performed a secondary analysis of the circulating miRNAome in 155 individuals, including healthy controls (CTRL), nonmalignant LS (H-LS), cancer-associated LS (C-LS), and sporadic colorectal cancer (CRC). We observed that LS variant heterozygotes, especially those without overt cancer, exhibit a transitional miRNAomic architecture distinct from both healthy controls and CRC patients in different age groups. Age-stratified differential expression and miRNA-mRNA network analyses revealed distinct regulatory hubs across groups. Group-specific miRNAs targeted oncogenic, immune, and DNA repair pathways. The analysis suggested that nonmalignant LS variant heterozygotes occupy a circulating miRNAome state distinct from both healthy controls and overt CRC, whereas C-LS and sporadic CRC shared selected malignant-associated miRNA features. To assess external concordance, we performed orthogonal validation of a prespecified six-miRNA panel in the independent GSE30454 primary colorectal tissue cohort, comprising normal, LS, sporadic MSI, and MSS samples. The composite panel preserved disease-axis structure across the external cohort, with strongest discrimination in biologically relevant mismatch repair-related contrasts. These findings suggest candidate circulating miRNA molecular states across LS and sporadic colorectal cancer.

Indexed as

age‐stratified transcriptomicscirculating microRNAscolorectal cancer risk profilingLynch syndrome biomarkersmiRNA‐mRNA regulatory networksorthogonal validation

Identifiers

PMID42841377
PMCPMC13643886

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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.