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

Cancer Cell International volume 25, Article number: 21 (2025) Cite this article

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.

Introduction

Colorectal cancer (CRC) is one of the major health malignancies of the colon and rectum and is responsible for severe health problems and death worldwide. CRC is estimated that CRC is the third most diagnosed cancer worldwide and the second leading cause of cancer-related deaths due to cancers [1, 2]. Even with advancements in diagnosis and medical facilities in recent years, people worldwide are more frequently affected by this disease, and the pattern has shown that morbidity and mortality are on the rise for CRC. Approximately 19 million new cases are registered, with 10 million deaths reported worldwide in 2020 [1, 3]. In Saudi Arabia, the situation seems to be worse, where CRC accounts for the second highest cancer incidence (12.3%) overall, highest in the males (15.6%), and third highest in females (9.7%) [4]. Moreover, owing to the heterogeneous nature of CRC involving different molecular subtypes and the lack of well-developed early detection biomarkers, many patients develop metastatic colorectal cancer (mCRC) [5, 6].

Based on histological classification, CRC is generally classified into three primary histological subtypes: adenocarcinoma, mucinous adenocarcinoma, and signet ring cell carcinoma [2]. Adenocarcinomas are the most widespread form of CRC, while the remaining two subtypes, mucinous adenocarcinoma and signet ring cell carcinomas, are generally less frequent but present distinctive features. Among these features are the onset at an early age, symptoms appearing when cancer reaches a more advanced stage, peritoneal metastasis, and increased chances of lymph node presence [7].

Different approaches are being utilized to guide treatment modalities in patients and the selection of biomarkers for efficient diagnosis of first- and second-line metastatic CRCs, such as mutational analysis of MAPK pathway genes. KRAS, NRAS gene exon 2,3 and 4, and BRAF, along with analysis of mismatch repair pathway gene deficiencies and microsatellite instability testing [8, 9]. Therefore, at the time of treatment selection in patients with mCRC, heterogeneity of the underlying molecular changes at the intratumoral level plays a significant role. Hence, the selection of samples for molecular analysis (blood or tumor tissue) and the locality of the chosen sample, such as primary tumor, metastasized tumor, and/or circulatory tumor DNA (ctDNA), may affect the results and subsequently affect the treatment outcomes. Consequently, more focus has shifted to in-depth study of the molecular characteristics of this complex disease, which will eventually help in better management, improved clinical outcomes, and improved personalized medicine.

Thus, in this study, our aim was to study the mutational spectrum of the NRAS gene in Saudi patients with CRC and broaden our understanding of the molecular involvement of NRAS genes in CRCs.

Materials & methods

Patients’ recruitment

In this study, we collected 80 tissues of CRC patients with CRC undergoing surgery at King Abdulaziz University Hospital, Jeddah. The surgery was performed by specialized surgeon, and he made sure to provide the proper tumor sample for further research by thorough inspection. This study was approved by the ethical committee of the Center of Excellence in Genomic Medicine Research (012-CEGMR-ETH-5). Written informed consent was obtained from all participants prior to the start of the study, according to the Declaration of Helsinki. Patient data were retrieved from the hospital database and medical records.

DNA extraction

After surgery, fresh tumor samples were immediately transferred to research facilities at the Center of Excellence in Genomic Medicine Research. The samples were stored at -20 °C until DNA extraction. DNA was extracted from the tissue samples using the DNeasy® Blood & Tissue Kit (Qiagen, Cat. No. 69504) according to the manufacturer’s protocol. Briefly, 20 mg of tissue was cut into small pieces for efficient lysis. The prepared Proteinase K–Buffer ATL working solution (20 µl Proteinase K mixed with 180 µl Buffer ATL) was poured into each collection microtube containing tissue samples, which were sealed with a clear cover and mixed by inverting the microtubes. The microtubes were centrifuged at 3000 rpm and incubated overnight at 56 °C. Next, we added 410 µl of premixed Buffer AL-ethanol to each sample, placed DNeasy 96 plates on top of S-Blocks, marked for sample identification, transferred the lysate into a Dneasy plate, sealed with an AirPore tape sheet, and centrifuged for 10 min at 6000 rpm. Thereafter added 500 µl Buffer AW1 and centrifuged for 5 min at 6000 rpm and then added 500 µl Buffer AW2 and centrifuged for 15 min at 6000 rpm. Then, we placed the plates on elution microtubes RS and added 200 µl Buffer AE, incubated for 1 min at room temperature, and centrifuged for 2 min at 6000 rpm to elute DNA.

A spectrophotometer (Nanodrop 2000; https://www.thermofisher.com/order/catalog/product/ND2000CLAPTOP) was used to ensure the quantity and quality of DNA. The range of 1.7 upto 2 is considered to be of good quality by using the method of calculating the ratio of light absorbance at 260 nm divided by absorbance at 280 nm. Moreover, to check the integrity of the eluted DNA, we ran the sample on 1% agarose using a horizontal gel electrophoresis system with SYBR safe dye (Thermo Fisher, USA) and observed it.

Sanger’s sequencing

To analyze the spectrum of pathogenic mutations in the NRAS gene, we amplified exons 2 and 3 (Table 1), respectively [10]. For PCR the thermocycler conditions were set as initial denaturation at 94 °C for 5 min, followed by 25 cycles of 94 °C for 30 s, primer annealing at 60 °C for 45 s, extension at 72 °C for 45 s each, followed by final extension at 72 °C for 5 min. NRAS gene sequences were retrieved using the reference match sequence NM_002524.5. Sequencing was performed using an ABI XL3500 sequencer with a BIG Dye Terminator® according to the manufacturer’s protocol. Briefly, after PCR amplification, the product was purified using a mixture of 100% ethanol (2.5 volume), NaOAc (1:10 volume), and EDTA (1:10 volume) and added to sample tubes. Then, the mixture was vortexed and centrifuged for 45 min at 4000 rpm and the resultant supernatant was discarded. The tubes were dried for 20 min at 50 °C, and nuclease-free water was added to elute the purified product. Subsequently, for cycle sequencing, we prepared a mixture of 5x sequencing buffer 2 µl, Primers (forward and reverse) 1 µl each, Big Dye Terminator 1 µl, template DNA 1 µl and H2O 5 µl (total 10 µl) and run on a thermocycler using the following conditions: initial denaturation at 95 °C for 5 min, followed by 25 cycles of 95 °C for 10 s, 50 °C for 5 s, 60 °C for 4 min, and hold at 4 °C. The samples were then subjected to a second purification step as the first step, and the purified samples were dried and added 10–12 µl of Hi-Di formamide was added to each tube, denatured at 95 °C for 5 min, and immediately placed on ice. To read the sequencing peaks and analyze the results, we used BioEdit Sequence Alignment Editor Version 7.2.5 and generated chromatograms accordingly.

Table 1 Sanger sequencing primers used for NRAS gene sequencing
Full size table

NRAS WT and NRAS T model building

Template searches for both NRAS Wild Type (NRAS WT) and NRAS Truncated (NRAS T) amino acid sequences were performed using the SWISS-MODEL template library (SMTL) [11, 12]. The SMTL was last updated on April 3, 2024, and included the latest PDB release on March 29, 2024. The NRAS WT and NRAS T models were constructed using ProMod3 [13], based on target-template alignment. Conserved coordinates from the template were copied to the model, whereas insertions and deletions were remodeled using a fragment library. The side chains were then rebuilt and the final geometry of the NRAS WT and NRAS T models was regularized using a force field [14].

NRAS WT and NRAS T models quality estimation

The global and per-residue model qualities for both wild-type and mutant NRAS proteins were evaluated using the QMEAN scoring function [15]. Quaternary structure annotation of the template was utilized to model the oligomeric form of the target sequence. The method was based on a supervised machine learning algorithm, Support Vector Machines (SVM), which integrates interface conservation, structural clustering, and other template features to provide a quaternary structure quality estimate (QSQE) [16]. The following models were constructed using the SWISSMODEL server for wild-type and mutant NRAS proteins.

Target MTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPTIEDSYRKQVVIDGETCLLDILDTAGQEEYSAMRDQYMRTGEGFLC

Q5RD87.1.AMTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPTIEDSYRKQVVIDGETCLLDILDTAGQEEYSAMRDQYMRTGEGLLC

Target VFAINNSKSFADINLYREQIKRVKDSDDVPMVLVGNKCDLPTRTVDTKQAHELAKSYGIPFIETSAKTRQGVEDAFYTLV

Q5RD87.1.AVFAINNSKSFADINLYREQIKRVKDSDDVPMVLVGNKCDLPTRTVDTKQAHELAKSYGIPFIETSAKTRQGVEDAFYTLV

Target

REIRQYRMKKLNSSDDGTQGCMGLPCVVM

Q5RD87.1.AREIRQYRMKKLNSSDDGTQGCMGLPCVVM

Target

MTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPTIEDSYRKQVVIDGRN–LFVGHT-G—YSWTRRVQCHERPIHED

W5PBT4.1.AMTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPTIEDSYRKQVVIDGETCLLDILDTAGQEEYS-AMRDQ-YMR-----

Target RRRLPLCICHQ

W5PBT4.1.A-----------

NRAS frame shift mutation analysis using mutation taster

NRAS frameshift mutations were examined using the Mutation Taster online tool (https://www.genecascade.org/MutationTaster2021/#) based on a single-base insertion in the coding sequence c. 145* insertion A using the Ensemble Transcript ID ENST00000369535 [17].

STRINGS analysis

To observe the protein-protein interaction network and generate functional enrichment analysis, we used STRING software version 12.0 ((https://string-db.org/). STRING facilitates the analysis of physical and functional associations using different arrays of computational predictions generated using multiple databases [18].

Results

In this study, we examined the molecular basis of the NRAS gene, ascertained 80 CRC patient samples were subjected to Sanger sequencing to acquire the spectrum of pathogenic mutations in the Saudi population. We found five different mutations in ten patients, G10R, E37K, E49R, Q61K, and Q61* (Fig. 1; Table 2). The most frequently identified mutation was E37K, which was found in five patients (6.25%), followed by G10R, which was found in two patients (2.5%). We found a single mutation, E49R, Q61K, and Q61*, in one patient each (1.25% each). The E49R mutation was identified for the first time in this study. This insertion mutation was found in exon 3 of NRAS (c.145 insertion A). These insertion mutations changed the amino acid sequence at position 49 and caused glutamic acid to be replaced with arginine p.49E > R (E49R). These insertion mutations subsequently lead to a frameshift from 49 amino acids onwards; eventually ending with a termination codon and making only an 85 amino acid protein (stop codon at c.256). This mutation is lethal and cuts the protein to less than half the size of the normal NRA S protein (189 amino acids).

Table 2 General characteristics, mutational spectrum, and amino acid alterations in NRAS
Full size table
Fig. 1
figure 1

Chromatograms showing the lethal insertion mutation at c.145, denoted by an arrow, along with the control sample

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NRAS homology modelling

To predict the lethality of the novel discovered mutation, we performed homology modeling of the NRAS WT and NRAS T proteins. The QSQE score was between 0 and 1, reflecting the expected accuracy of the interchain contacts for a model built based on a given alignment and template. Higher numbers indicated greater reliability. This complements the GMQE score, which estimates the accuracy of the tertiary structure of the resulting model. The GMQE score of the NRAS WT was 0.92 (Table 3), and that of the NRAS T was 0.72 (Table 4). The results showed that the MolProbity score for the NRAS WT was 1.31, with a Clash Score of 0.34, Ramachandran Favored percentage of 94.12, Ramachandran outlier percentage of 2.14, and Rotamer outlier percentage of 2.42 (Fig. 2D). In contrast, the MolProbity score for the NRAS T mutant was 2.09, with a Clash Score of 4.54, Ramachandran Favored percentage of 92.54, Ramachandran Outlier percentage of 2.99, and Rotamer Outlier percentage of 3.33 (Fig. 3D). MutationTaster analysis indicated that the c.145 insertion of A in the NRAS T protein caused a frameshift mutation that resulted in truncation of the NRAS protein to only 85 amino acids (Fig. 3). This truncation leads to the loss of essential NRAS protein features, as listed in Table 5 (See Fig. 3).

Table 3 NRAS WT homology model parameters based on the Swiss-Model server
Full size table
Table 4 NRAS T homology model parameters were based on the Swiss-model server
Full size table
Table 5 The impact of the frameshift mutation c. 145* insertion A in the NRAS gene on the protein structure was determined using mutation taster
Full size table
Fig. 2
figure 2

Homology modeling of NRAS Willd Type (NRAS WT) protein. (A). Secondary structure (B). Confidence (Class) (C). Confidence (Gradient). (D). Ramachandran plots based on NRAS WT homology model for general aminoacid composition, glycine, proline, and pre-proline. (E). MolProbity results for NRAS WT homology model

Full size image
Fig. 3
figure 3

Homology Modeling of NRAS Truncated (NRAS T) protein. (A). Secondary structure (B). Confidence (Class) (C). Confidence (Gradient). (D). Ramachandran plots based on NRAS T homology model for general aminoacid composition, glycine, proline, and pre-proline. (E). MolProbity results for NRAS T homology model

Full size image

Furthermore, we performed gene-gene interactions and functional analyses using STRING, which utilizes multiple databases and computational predictions. STRING analysis showed that this NRAS gene is crucial for the normal functioning of cells and performing crucial functions (Fig.  4). The NRAS gene has been shown to clearly interact with other major player genes such as EGFR, BRAF, HRAS, and MAP2K2, which are important for cells to carry out important tasks related to cell integrity and signal transduction. The majority of these genes are part of the RAS/MAPK pathway, which controls vital cell functions such as proliferation, differentiation, migration, and apoptosis. Mutations in these genes can cause cancer and lead to abnormal cell function.

Fig. 4
figure 4

STRING generated map showing the protein-protein interaction map of the NRAS gene with other important proteins (https://string-db.org/)

Full size image

Discussion

CRC remains one of the most prevalent malignancies worldwide [3, 19]. The median age at CRC diagnosis is approximately 60 years, with most cases presented in the 50–69 age groups. Recently, concerns have risen as the younger population has become more effective than in the past, particularly in high-income countries with better healthcare facilities such as the United States, where the percentage of new diagnosis cases below 55 years of age increased from 11 to 20% between 1995 and 2019 [20]. Even CRC is on the rise below 39 years of age, which is alarming [21, 22].

The development and progression of CRC is a multistep process involving genetic mutations, chromosomal aberrations, and epigenetic modifications [21, 23]. Much of the current focus is on gene mutations, as many oncogenes have been established to play key roles in CRC carcinogenesis [24]. The most significant of these are mutations in the rat sarcoma virus (RAS) family and b-RAF murine sarcoma viral oncogene B (BRAF), which are involved in the activation of mitogen-activated protein kinase (MAPK) signaling pathways [25]. Therefore, it has been proposed that these types of gene mutations may be important for early diagnosis and can be used as biomarkers. He et al. (2022) recommended the use of fecal KRAS and TP53 as specific biomarkers for CRC diagnosis, screening, and recurrence monitoring. However, these assays are still in their infancy [26].

Although the understanding of CRC, its pathophysiology and molecular mechanisms are well studied now, and great breakthroughs have been made in the clinical investigations and treatment of CRC in the past few years but due to the fact that the CRC is very complex and heterogeneous disease with different prognosis and treatment responses, hence its utmost important to identify molecular markers with real predictive and prognostic values [27]. One of the main approaches for the treatment of CRC is to target epidermal growth factor (EGFR) and KRAS gene mutations, which play a major role in resistance to EGFR inhibitors. In addition, there are some other mechanisms that are suggested to add-on in this resistance such as ligand expression, BRAF gene mutations, elevated EGFR copy numbers and some other signaling pathways activation [28]. Consequently, mutations in RAS family genes, particularly in KRAS and NRAS genes (in exons 2, 3, and 4), BRAF (exon 15), and PIK3CA (exon 20), are gaining importance for their predictive value in anti-EGFR targeted therapies [29]. The RAS family remains a focal point in CRC studies, and is the most frequently studied malignant gene family, among which KRAS is the most analyzed and researched gene [3]. Although the presence of pathogenic mutations differs widely regionally, they are present in approximately 50–55% of mCRCs [30, 31].

However, NRAS is a less studied gene than KRAS; therefore, the aim of this study was to investigate NRAS in detail in the Saudi population, to establish a mutational spectrum, and to provide reference data for personalized therapy and clinical treatment. Previous studies have reported NRAS mutations to be 2.2 7% but differ greatly in different populations [3, 32, 33]. We analysed exons 2 and 3 of NRAS in 80 patients with CRC and found mutations in 10 patients (12.5%). This indicates that the NRAS gene is more involved in Saudi Arabia than in the rest of the world. Most hot spots were found to be E37K in five patients (6.25%), followed by G10R in two patients (2.5%), and E49R, Q61K, and Q61* in one patient each (1.25%). The E49R or c.145 insA (p.Glu49ArgTer85) insertion mutation is novel, as per our detailed search of the available databases. This novel lethal insertion mutation at c.145 (E49R) substituted glutamic acid with arginine and subsequently changed the entire amino acid sequence in the protein. Moreover, owing to the insertion and frameshift, the stop codon appears at c.256, resulting in early truncation and leaving the protein to be only 85 amino acids long. Hence, damaging the protein has proven to be detrimental for its proper functioning. We used in silico modelling to predict functional damage and found that the mutation was lethal using homology modelling and QSQE and GMQE scores. The MolProbity score for the wild-type protein was 1.31, while for that the mutant protein was 2.09. These results indicated that the c.145 insertion of A caused a frameshift mutation, leading to the loss of essential NRAS protein features and crucial cellular functions. Furthermore, we found that five of ten patients developed metastases, including two patients at a young age (30- and 36-years of age, respectively). Therefore, there is a critical need to develop innovative strategies to diagnose and improve personalized mCRC treatment in young patients [1, 6]. Our findings will help to establish a real mutational spectrum of the NRAS gene in Saudi patients and will lead to improved personalized targeted therapy for CRC patients.

Conclusions

In conclusion, we established a mutational spectrum of the NRAS gene in Saudi patients and found a novel lethal insertion mutation, E49R, that damages the NRAS protein and impairs cellular functions. The NRAS gene seems to be more common in Saudi patients (12.5%) than in the world. In the future, the authors intend to collaborate with different oncology centers to include larger patient datasets to further validate the present research findings.

Data availability

Data is provided within the manuscript.

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Acknowledgements

This research work was funded by Institutional Fund Projects under grant no (IFPRC-092-140-2020). Therefore, authors gratefully acknowledge technical and financial support from the Ministry of Education and King Abdulaziz University, Jeddah, Saudi Arabia.

Funding

This research work was funded by Institutional Fund Projects under grant no (IFPRC-092-140-2020).

Author information

Authors and Affiliations

  1. Institute of Genomic Medicine Sciences, King Abdulaziz University, Jeddah, Saudi Arabia

    Mahmood Rasool, Adeel G. Chaudhary, Sajjad Karim & Peter Natesan Pushparaj

  2. King Fahd Medical Research Center, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia

    Absarul Haque

  3. Faculty of Medicine, King Abdulaziz University Hospital, King Abdulaziz University, Jeddah, Saudi Arabia

    Mohammed Alharthi & Abdulrahman Sibiany

  4. Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia

    Mohammed Saad Alamri, Samer Mohammed Hassan Alqarni & Irfan A. Rather

Authors
  1. Mahmood Rasool
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  2. Absarul Haque
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  3. Mohammed Alharthi
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  4. Abdulrahman Sibiany
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  5. Mohammed Saad Alamri
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  6. Samer Mohammed Hassan Alqarni
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  7. Irfan A. Rather
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  8. Adeel G. Chaudhary
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  9. Sajjad Karim
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  10. Peter Natesan Pushparaj
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Contributions

M.R. and A.C. Supervised the study. M.A., A.S. provided patient samples. M.R., A.H., P.N.P., S.K. wrote the manuscript. M.S.A., S. M.H.A. did the experiments. I.R. M.R revised and edited the manuscript.

Corresponding author

Correspondence to Mahmood Rasool.

Ethics declarations

Human ethics and consent to participate

This study was approved by the ethical committee of the Center of Excellence in Genomic Medicine Research, King Abdulaziz University (012-CEGMR-ETH-5). Written informed consent was obtained from all participants prior to the start of the study, according to the Declaration of Helsinki.

Competing interests

The authors declare no competing interests.

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Rasool, M., Haque, A., Alharthi, M. et al. The mutational spectrum of NRAS gene discovers a novel frameshift mutation (E49R) in Saudi colorectal cancer patients. Cancer Cell Int 25, 21 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12935-025-03652-x

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  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12935-025-03652-x

Keywords

Cancer Cell International

ISSN: 1475-2867

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