The GNAS gene mutations are detected in many tumour types as with KRAS mutations, and are detected in 4-7% of colorectal tumours, 15% in liver carcinoma and 41% in intraductal papillary neoplasms of the pancreas [1,2]. Out of all cancers, GNAS gene mutations have been altered in 3.21% [3]. In tumorigenesis, such as in CRC, the GNAS gene is among the top seven most frequently mutated genes, hence the importance of the functional contribution of the G-subunit genes in CRC progression. Other genes include epidermal growth factor receptor (EGFR), insulin-like growth factor receptor (IGFIR), CASP8, TCF7L2, KRAS and APC [4].

In this study, the aim was to determine the prevalence of GNAS gene mutations in CRC genomic profiling of CRC patients in Uganda. Confirmation and identification of biomarkers and prognostication factors may improve the management of CRC although the progression of CRC involves a multi-gene aberration of several biomarkers [3,5]. Among the eukaryotes, the G-protein-coupled receptors are regarded as the most diversified and broadest family of cell surface receptors [6-9]. For hormone regulation and the regulation of cell growth, G-protein-coupled receptors (GPCRs) are the most prevailing signal-regulating networks in mammalian cells [2]. The G-proteins interrelate with GPCRs, which consist of three subunits heterotrimeric G-proteins, namely the Gα-subunit Gsα, the Gβ-subunit Gsβ and the Gα-subunit Gsα.

The G-proteins have α-subunits which are further classified into four subfamilies namely Gq, Gs, Gi, and G12/13. The guanine-nucleotide-binding proteins bind to Gsα which is encoded by the GNAS complex locus, and this leads to a physiological response via the downstream regulation of gene transcription. Oncogenic transformation and cancer cell growth in CRC depends on the critical role of gene mutations such as nonsense mutations, missense mutations, silent mutations and frame shift insertions. The adenylate cyclase gene is activated by mutations occurring at codon 201 of GNAS and this leads to CAMP constitute signalling and metastasis [3]. In CRC the role of GNAS R201H and R201C in CRC tumorignesis is under the control of the Gpa 33-antigen promotor. Augmentation of both the Wnt and ERK ½ MAPK cascade is caused by R201C and R201H activating mutation of GNAS and accounts for 70-80% of GNAS mutation.

The aim of the study was to determine the prevalence of pathological GNAS gene mutation and compare to clinic pathological features of CRC in Ugandan patients.

From the 16^th of September 2019 to the 16^th of September 2021, we recruited prospectively, consecutive participants attending the Surgical Departments of Masaka Regional Referral Hospital, Mulago National Referral Hospital, Uganda Martyrs’ Hospital Lusaka and Mengo Hospital. From 1^st January 2008 to 15^th September 2019, retrospective CRC FFPE blocks were obtained from the archives of the Department of Pathology, School of Biomedical Sciences, College of Health Sciences, and Makerere University. The histopathologic diagnosis was confirmed as colorectal adenocarcinoma by one consultant pathologist at the Department of Pathology, School of Biomedical Sciences, College of Health Sciences, Makerere University, and another consultant pathologist at the Institute of Genetics and Cancer at the University of Edinburgh. Cases with a histologically proven diagnosis of colorectal adenocarcinoma were considered for inclusion. Cases with recurrent colorectal cancer and poor-quality FFPE tissue samples were excluded. Poor quality FFPE tissue samples included those having a low concentration of extracted DNA, poor quality DNA, or insufficient tissue for the extraction of DNA. All cases meeting the selection criteria during the study period were included. The stage of the CRC was radiological, obtained from the radiology reports in the participants’ medical case files. The radiological TNM staging (8th edition) was used to stage all the colorectal tumours. The CRC cases were graded using a three-tier grading system as follows: well-differentiated CRC (G1) with >95% glandular formation; moderately differentiated CRC (G2) with 50–95% glandular formation; and poorly differentiated CRC (G3) with <50% glandular formation [12]. Data were obtained from the clinical case files for demographics, radiological stage, and topography of the colorectal tumour.

Extraction of DNA

From formalin-fixed paraffin-embedded (FFPE) tissue blocks that contained at least 50% tumour, DNA was extracted. FFPE tissue blocks with DNA degradation were excluded The QIAamp DNA FFPE Advanced UNG kits (Qiagen GmbH, Hilden, Germany) were used for DNA extraction following the recommendations. The manufacturer. A Nano drop 1000 spectrophotometer (Thermo Fischer Scientific, Wilmington, CO, USA) was used to measure the concentration and quality of the extracted DNA. The quality of each sample was checked on the Qubit to make sure it fell within 100-250 ng of DNA required for the DNA protocol. In order to prevent degradation it was stored at -200C. All the 127 CRC DNA samples passed the quality check.

Library Preparation and NGS Sequencing

Library preparation was completed following the QIAseq targeted DNA Pro kit for Illumina (QiagenGmbH, Hilden, Germany) along with a Qiagen custom design panel (QIAseq DNA panel catalogue identifier: CPHS-43072Z-1294) [13]. The custom panel represented 56 genes with a total of 1,294 primer probes. It is designed to enrich selected genes and regions using100 to 250ng FFPE DNA. A single controlled multi-enzyme reaction was responsible for the fragmentation of the DNA samples, end repair, and A-tailing. A sequencing platform-specific adapter containing UMI prepared DNA fragments was used which ligated their 5’ ends. To generate more FFPE DNA molecules for library construction, a repair step was carried out. The repaired FFPE DNA was placed directly into the fragmentation reaction in the same tube. An adaptor containing a 12-base fully random sequence (ie. UMI) was used to ligate the fragmented DNA. A unique sequence was used for each DNA molecule in the sample.

Following the UMI assignment, target enrichment was performed to ensure that DNA molecules with UMIs in the sequenced library were sufficiently enriched. Several cycles of targeted PCR using one universal primer complementary to the adaptor and one region-specific primer were subjected to ligated DNA molecules for enrichment. Amplification of the library and addition of platform-specific adaptor sequences and sample indices were carried out using universal PCR. An enzymatic reaction was used for clean up after ligation and target enrichment PCRs. Following enzymatic clean-ups, more consistent library construction was achieved, as there were no highly variable bead clean-ups following ligation and target enrichment PCRs [14]. Two unique indices were assigned to each sample to overcome errors due to image analysis, demultiplexing sequencing error, and oligo synthesis contamination to reduce any real misassignment to incorrect samples. The library pool was sequenced on the Illumina MiSeqplatform using a dual indexed paired-end sequencing program of 2 × 149-bp reads.

Data Analysis

The quality of the raw FASTQ files was first assessed using FastQC and MultiQC software [15-17], which generated HTML quality reports. Bases with a Phred quality score below 25 and adapter sequences were trimmed using Trim Galore [18]. The processed reads were aligned to the human genome reference version 38 (hg38) using BWA-MEM [19], generating the alignment files. Variant discovery was performed using the GATK4 (Genome Analysis Tool Kit version 4) pipeline following the best practices guide-lines [20], employing the Haplotype Caller option. Variants were filtered for downstream analysis based on an overall read depth greater than 20X and a variant allele depth of at least 10X.

The resultant variants were annotated using ANNOVAR (18). Variants of uncertain significance (VUS) according to ClinVar [21] were subjected to further analysis using nine variant effect prioritization tools: SIFT [22], LRT [23], Mutation Taster [24], Mutation Assessor (Reva 2011), FATHMM [17], PROVEAN [17], ClinPred [15], MutPred [19], and MetaSVM [25]. A variant was classified as deleterious (D) if at least five out of these nine tools predicted it to have a damaging effect. This threshold was chosen based on the consensus approach used in previous studies to minimize false positives and ensure a high confidence in pathogenicity classification [20,22,23]. Variants predicted to be damaging by fewer than five tools were considered tolerated (T).

Statistical Data Analysis

The data consisted of categorical and numerical types. Using agreeable cutoffs, the numerical data was translated into categorical type. Using the median age as a cutoff, the data on age was translated to categorical data. The mean age for the participants corresponding to the GNAS mutation status was estimated. Using proportions and frequencies, categorical data was summarized corresponding to the GNAS mutation status. Using means (standard deviations) and medians (interquartile range), continuous variables were summarized. Categorical and continuous variables were analyzed using the Fischer’s exact tests and chi-square tests. P-values were used to determine the statistical significance of the correlations. A p-value of ≤0.05 was considered statistically significant.

A total of 127 CRC patients diagnosed between 1^st January 2008 to 15^th September 2021 were analyzed for GNAS mutation status and MSI status. The mean (SD) age was 54.9 (16.0) years. There were 58 (45.7%) females and 69 (54.3%) males with CRC. AJCC late-stage (III+IV) CRC was found in 109 (85.8%) CRC patients, while early-stage (I+II) CRC constituted 18 (14.2%) CRC patients. There were 14 (11%) patients with poorly differentiated CRC, 96 (75.6%) patients with moderately differentiated CRC and 17 (13.4%) with well-differentiated CRC. Tumours with positive lymphovascular invasion (LVI) constituted 114 (89.8%) and 12 (10.2%) tumours had no LVI.

The majority of tumours were found in the rectum, 57 (44.8%), followed by the sigmoid colon 19 (14.9%), ascending colon 16(12.6%), caecum 12 (9.5%), descending colon 10 (7.8%), recto sigmoid 7 (5.5%), hepatic flexure 3 (2.36%), transverse colon 2 (1.6%) and splenic flexure 1 (0.8%). There were 94 (74.0%) left-sided colon tumours and 33 (25.9%) right-sided colon tumours.

Prevalence of GNAS Mutations

There were 36 (28.3%) colorectal tumours that had a pathologically mutated GNAS gene.

MSI and MSS Molecular Subtypes of CRC

There were 52 (40.9%) MSI positive colorectal tumours followed by 75 (59.1%) MSS colorectal tumours.

Table 1: Clincopathological characteristics of GNAS positive and GNAS negative CRC.

Compared to 17 (47.2%) CRC tumours which were GNAS mutation positive there were 45(49.5%) CRC tumours which were GNAS mutation negative in participants ≤54 years (p=0.821) (Table 1). Although there were 19 (52.8%) participants with GNAS positive CRC, there were 46 (50.6%) participants with GNAS negative CRC that were ≤54 years (p=0.821) (Table 1). There was no difference in GNAS mutation status between male and female participants (p=0.950).

There were 20 (55.6%) GNAS positive tumours compared to 36 39.6%) GNAS negative tumours that had stage III disease (p=0.301). Whilst there were 4 (11.1%) GNAS positive tumours compared to 16 (17.6%) GNAS negative tumours with stage IV CRC (p=0.301) (Table 1).

There were 27 (75%) GNAS positive tumours compared to 69 (75.8%) GNAS negative tumours with grade II CRC (p=0.299). Whilst there were 6 (16.7%) GNAS positive tumours compared to 8 (8.8%) GNAS negative tumours with grade III CRC (p=0.299). GNAS mutation positive tumours were found in 18 (50%) MSI positive tumours whilst 34 (37.4%) GNAS negative tumours were MSI positive (p=0.192) (Table 1).

Relation between GNAS Mutation Positive Tumours and KRAS Mutation Positive Tumours

There were only 8 (6.3%) KRAS mutations of which 4 (3.1%) were GNAS mutation positive and 4 (3.1%) were GNAS mutation negative. Out of those tumours that were GNAS mutation positive, 40 (31.5%) were KRAS mutation negative and 4 (3.1%) were KRAS mutation positive. Whilst out of those tumours that were GNAS mutation negative, 79 (62.2%) were KRAS mutation negative and 4 (3.1%) were KRAS mutation positive. There was no relation between GNAS mutated tumours and KRAS mutated tumours (p=0.447).

Ethical Approval

Mutations in the RAS family of genes, particularly the activation of heterotrimeric G-protein α-subunits (Gsα), is responsible for a third of all cancers caused by mutations in the RAS family of genes. Early onset of organ metastases in CRC and a lack of early occurring signs result in a small number of patients being good candidates to receive curative surgery at the time of diagnosis in hospital [26]. Based on the cancer type, the occurrence of these mutations varies and is approximately 5-7% in CRC and 21% in pancreatic cancer [27]. The risk of mortality and recurrence from CRC is correlated with the stage of CRC at diagnosis. Therefore, there is a need for a biomarker predicting prognosis [28-30].

Cytotoxic drugs which include monoclonal antibodies targeting EGF receptor have been used for treating CRC, however the GNAS gene mutation is a prominent factor contributing to treatment failure [31].

In the present study the prevalence of the pathogenic GNAS gene mutation was found to be 28.3% in Uganda. Globally, the overall prevalence of GNAS gene mutations is 4.8%. The GNAS gene mutation functions as the most common cancer-initiating mutation across the heterotrimeric Gγ proteins, the Gα -subunit cascade of the MAPK-ERK pathway and is the most comprehensively investigated mutation in many cancers. It is also an active oncogene found in several tumour types such as CRC in 3.5-7% and 15-21% of intraductal pancreas and liver cancer cases globally [28,29], however in Uganda the prevalence of this mutation is higher. This prevalence rate reported in our study is higher to the figures reported in the USA (5.4%), [32], UK (1.0%), [28], Spain (4.7%) [33], India (3.2%) [34], Taiwan (4.0%) [35]. The GNAS mutation prevalence differs or is not present in available data from the UAE [36], Korea [37], Tokyo [38] and Turkey [39]. There are multiple reasons which may include geographical settings, route of specimen collection, and racial predilection to lifestyle. The prevalence of the GNAS gene mutation was lowest in Italy (0.4%) and the United Kingdom (0.5%) and highest among patients screened in Japan (26.8%) and Norway (12.9%). The prevalence of the GNAS gene mutation in Uganda is similar to that found in Japan (26.8%).

It is well known that the incidence of epigenetic and genomic alterations leading to tumorigenesis in CRC is dynamic [40,41]. The clinicopathologic data from our study was reviewed to determine whether GNAS mutant tumours are associated with unique morphologic or clinical phenotypes.

In our study there was an equal distribution of patients with GNAS mutations that were above or below the median age of 54 years. However, in other studies from the West, the majority of CRC patients were over 50 years old, suggesting that the adult population GNAS gene mutations are more predominant. These outcome findings were in keeping with Western literature which shows that ageing is associated with a higher risk of CRC [42]. Our study did not show any difference in sex in these individuals that had GNAS mutated CRC, although there were more male CRC patients with GNAS mutations compared to female patients. Globally, other studies have shown that male patients have a higher predisposition (57%) to CRC compared to their female counterparts [43,44].

Our study showed that whilst more patients presented with advanced stage CRC, there was no difference in the GNAS mutation status between early stage (stage I, II) and advanced stage (III,IV) CRC, whilst other studies around the world, showed that late-stage (III, IV) CRC has more GNAS gene mutations (68%) compared to early stage (I,II) CRC (27%). Although the majority were rectal tumours in our study, there was no difference in the GNAS mutation status between right-sided and left-sided colon cancers. In Uganda, the majority of rectal and colon cancers, present at a late-stage and hence this may explain the lack of difference in the GNAS mutation status. In CRC, microsatellite instability (MSI), right-sided tumours, KRAS mutations and villous colon cancers have been found to be linked to GNAS mutations, particularly at codon 201 [45]. However, the findings in our study do not show a relationship between the GNAS status and the MSI status, KRAS status or topography of the tumour.

Other studies from developed high-income countries have reported a higher GNAS mutation rate among colon cancers as these tumours tend to present with late-stage CRC [46]. Studies have shown that GNAS mutant villous adenomas arise throughout the colon, whereas GNAS mutant cancers are not present in the distal colon. This raises the possibility of GNAS mutant adenomas becoming symptomatic and being more easily detected in the distal colon. However, they progress more rapidly in the proximal colon [45]. In Western populations, villous adenomas have been divided into two groups, one group consists of the villous adenomas that arise from the GNAS mutation pathway and another set of villous adenomas that arise from the alternative pathway.

In cancer, the GNAS codon 201 aberrations are frequently detected, as they lead to autonomous cyclic-AMP release due to activation of Gsα. In many studies, the two most identified codons of the GNAS gene mutation are R201H and R201C. The majority of GNAS mutations have been reported in codon R201H (39.7%) and R201C (40.7%). In the US, 83% of GNAS mutations are found in codons R201H with 5% of individuals having GNAS mutations [47]. GNAS mutations in codons 201 have been found in 91.3% of individuals in the Republic of Korea [49]. In Australia, a study reported a synergistic detection of GNAS along with KRAS mutation in CRC, and 87% of the GNAS codons are mainly in codons R201H and R201C [48]. There were no GNAS mutations reported in some studies in CRC [49-50]. Only two studies have reported other GNAS codons in CRC mainly R201S and Q227H mutations [32,51]. The R201H and R201C codons are the most commonly detected GNAS codon in CRC and their presence may have therapeutic implications [52].

Similar to KRAS, the GNAS gene is part of the RAS-RAF-MEK-ERK pathway (or MAPK/ERK pathway) family. Activation of the GNAS gene mutation, results in tumorigenesis by activating the ERK1/1 MAPK pathway or the Wnt/β-catenin pathway, however compared to KRAS mutations, the GNAS mutations are less frequent [54]. However, in transmutated cells, whole genomic analysis has shown that aberrations affecting GPCRs and G-proteins occur more frequently. GNAS-activating mutations are mainly exclusive to CRC progression in late stages. These mutations are associated with a poor prognosis and account for 5-10% of mCRC cases [52]. There is a constant stimulation of the mitogen-activating proteiun kinase MAPK-pathway due to this mutation, which controls the transcriptase activity of regulatory genes in the cell cycle by modulating cell growth stimuli [52].

The genetic classification of CRC and molecular subtypes may be determined from genetic mutations using Next Generation Sequencing (NGS). This may offer patients a more precise diagnosis and hence a more specialized course of treatment. Early identification of sub-codon mutation and mutations tends to increase the sensitivity of finding low-frequency aberrations or variations. This will also ensure a thorough screening of broad genomic coverage and a quicker turnaround of large numbers of patient samples.

To the best of our knowledge this is the first study in Uganda and in East Africa which has reported on the prevalence of GNAS gene mutations in CRC patients.

The prevalence of GNAS mutations in CRC patients in Uganda is 28.3% which is similar to the prevalence from Japan, however different to the prevalence reported in other countries. Our findings showed no association between GNAS mutation and demographics, topography, stage, grade, LVI status, MSI status and K-ras mutation status in Ugandan CRC patients.

AC Classical adenocarcinoma

APC Adenomatous Polyposis Coli

AJCC American Joint Committee on Cancer

CRC Colorectal cancer

CIN Chromosomal instability

CSS Cancer specific survival

DNA Deoxyribonucleic acid

FAP Familial Adenomatous Polyposis

FFPE Formalin fixed paraffin embedded

REC Research and Ethics Committee

LVI Lymphovascular invasion

MAC Mucinous adenocarcinoma

MSI Microsatellite Instability

MMR Mismatch repair

MSS Microsatellite stability

PCR Polymerase chain reaction

SRCC Signet ring colorectal cancer

TNM Tumor Node Metastasis

Ethical Approval and Consent to Participate

This study was approved by the Research and Ethics Committee of the School of Biomedical Sciences, College of Health Sciences, and Makerere University for the corresponding author (SBS-HDREC-630). Final approval of this research study was obtained from the Uganda National Council for Science and Technology (HS-2574). Written informed consent was obtained from prospective participants included in the study before completing the Data Extraction Form. All the data and specimens pertaining to the research were kept confidential. For the retrospective arm of the study, data were abstracted from the case files in the respective hospitals. Therefore, a waiver of consent was obtained from the Research and Ethics Committee, School of Biomedical Sciences, College of Health Sciences, Makerere University, to access the data and perform the experiments on the tissue block samples. The patient data, which were accessed from the medical case files in the respective hospitals, were anonymized and maintained with confidentiality. The conduct of the study was in accordance with the Declaration of Helsinki.

Availability of Data and Materials

The data supporting the findings of this study are available from the corresponding author upon reasonable request.

Competing Interests

The authors declare that they have no competing interests.

Funding

The authors declare that they received no specific funding for this work. However, the corresponding author and grants from Professor Ian Tomlinson funded this part of the corresponding author’s research study. No payment was received by the authors to write and publish this part of the study.

Authors’ Contributions

Richard Wismayer conceived the concept and proposal, collected data, performed data analysis and wrote the paper.  Rosie Matthews extracted DNA from colorectal cancer tissue samples. Celina Whalley designed and performed mutation analysis and DNA sequencing. Fredrick Elishama Kakembo and Steve Thorn carried out bioinformatics analysis of the variant data. Julius Kiwanuka performed data analysis and provided statistical support. Henry Wabinga, Michael Odida and Ian Tomlinson carried out critical reviews of the manuscript for intellectual content. All authors approved the final manuscript.

This study was part of a collaboration between the University of Edinburgh and Makerere University. Professor Ian Tomlinson is acknowledged for funding the laboratory experiments of this study from grants pertaining to the 1000 Genomes Project. We thank all the staff and research assistants from the Institute of Genetics and Cancer, University of Edinburgh and the Institute of Cancer and Genomic Sciences, University of Birmingham.

We thank the Department of Pathology, Makerere University for using the database and retrieving the tissue block samples from the archives. Finally, we would like to thank the research assistants, staff and recruited patients from the Department of Surgery of Masaka Regional Referral Hospital, Mulago National Referral Hospital, Uganda Martyrs’ Hospital Lubaga and Mengo Hospital.

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