Evidence map›Paper›PMID 39844204›Full record

ArticleCancer cell international2025

The mutational spectrum of NRAS gene discovers a novel frameshift mutation (E49R) in Saudi colorectal cancer patients.

Mahmood Rasool, Absarul Haque, Mohammed Alharthi, Abdulrahman Sibiany, Mohammed Saad Alamri, Samer Mohammed Hassan Alqarni, Irfan A Rather, Adeel G Chaudhary, Sajjad Karim, Peter Natesan Pushparaj

Abstract read
In one paragraph

Article in Cancer cell international, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
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

10 authors.

Mahmood RasoolInstitute of Genomic Medicine Sciences, King Abdulaziz University, Jeddah, Saudi Arabia. mahmoodrasool@yahoo.com.
Absarul HaqueKing Fahd Medical Research Center, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia.
Mohammed AlharthiFaculty of Medicine, King Abdulaziz University Hospital, King Abdulaziz University, Jeddah, Saudi Arabia.
Abdulrahman SibianyFaculty of Medicine, King Abdulaziz University Hospital, King Abdulaziz University, Jeddah, Saudi Arabia.
Mohammed Saad AlamriDepartment of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.
Samer Mohammed Hassan AlqarniDepartment of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.
Irfan A RatherDepartment of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.
Adeel G ChaudharyInstitute of Genomic Medicine Sciences, King Abdulaziz University, Jeddah, Saudi Arabia.
Sajjad KarimInstitute of Genomic Medicine Sciences, King Abdulaziz University, Jeddah, Saudi Arabia.
Peter Natesan PushparajInstitute of Genomic Medicine Sciences, King Abdulaziz University, Jeddah, Saudi Arabia.

Funding

Ministry of Education and King Abdulaziz University IFPRC-092-140-2020
6 · The paper itself

Abstract

Colorectal cancer (CRC) is a major health problem the world face currently and one of the leading causes of death worldwide. CRC is genetically heterogeneous and multiple genetic aberrations may appear on course of the disease throughout patient's lifetime. Genetic biomarkers such as BRAF, KRAS, and NRAS may provide early precision treatment options that are crucial for patient survival and well-being. The aim of this study was to identify pathogenic mutations in the NRAS gene causing colorectal cancer in the Saudi population. We enrolled 80 CRC tumor tissue samples and performed molecular analyses to establish the mutation spectrum status in the western region of Saudi Arabia. We identified 5 different mutations in 10 patients, 4 of whom were reported previously (G10R, E37K, Q61K, and Q61*) in the literature while we discovered one novel lethal insertion mutation (E49R). A novel identified insertion mutation was present in the third codon of the NRAS gene [c.145 insA (p.Glu49ArgTer85)], causing a frameshift in the amino acid sequence of the protein, and leading to an aberrant and truncated protein of 85 amino acids. Subsequent bioinformatics analysis showed that the mutation was highly deleterious and affected protein function to a greater extent. This identification may further improve the prognosis of CRC and benefit subsequent treatment choices.

Indexed as

Colorectal cancerGenetic landscapeNovel mutationNRAS gene

Identifiers

PMID39844204
PMCPMC11755827

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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.