Globally, colorectal cancer is the fourth most frequent cause of cancer-related deaths and the third most common cancer, resulting in a serious public health problem [1-3]. In 2020, the CRC was responsible for 9% of cancer deaths and approximately 10% of cancer incidence [3]. In Uganda, most CRC patients are young and present at an advanced stage [4] resulting in poor survival [5]. These effects may be due to the unavailability of screening programs, a lack of awareness of CRC among the Ugandan population, and generally limited surgical and oncological infrastructure in Sub-Saharan Africa [5].

There has been a steady increase in the incidence of CRC recorded in the Kampala Cancer Registry, with the highest change in CRC incidence cases recorded between 2011 and 2015 [6]. This period tends to coincide with the increasing availability of CRC care as well as an improvement in CRC diagnostic capacity in Uganda. This includes the availability of more oncological care and the deployment of more surgeons in the district rural hospitals [5].

Differences in molecular characteristics and genetic background have been reported in cancer between other races and Africans [7,8]. Differences in somatic mutations and microsatellite instability status have been documented between African races and other races [8-10]. In African ancestry, the APC and KRAS driver genes have been reported to be more altered compared to other races [9]. In CRC development, APC is a key gatekeeper gene and a tumour suppressor gene [10,11]. In CRC, Schell reported that APC may play a prognostic role and CRC outcome may be predicted by routine clinical assessment of APC together with BRAF, KRAS, and TP53 [10].

In CRC, PIK3CA is one of the most frequently mutated genes. Approximately 80% of mutation hotspots occur in the helicase and kinase domains of exon 20 and exon 9, respectively [12,13]. Stimulation of AKT signalling, resulting in the promotion of cancer cell migration and proliferation, may result from PIK3CA mutations that activate the p110a enzyme, the key catalytic subunit of PI3 [14]. A crucial kinase that plays an important role in the proliferation, growth, and survival of solid tumours in the PI3K/AKT1/MTOR pathway is phosphatidylinositol-4, 5-bisphosphate 3-kinase (PI3K) [15,16].

Some studies have shown no association between PIK3CA mutations and survival; however, other studies have shown significantly better survival with PIK3CA mutations [17-21]. In Uganda, the relationship between demographic and clinicopathological features of PIK3CA remains unknown. Day et al. found that there was no relation between tumour stage and PIK3CA mutation, while Palomba reported an association of PIK3CA mutations with late tumour CRC stage [22,23]. There are currently no studies in Uganda that have determined the association between clinicopathological features and PIK3CA mutations in CRC. Therefore, understanding the influence of PIK3CA mutations on the clinicopathological characteristics of CRC will aid in identifying the characteristics of Ugandan patients with mutated PIK3CA-mutated CRC.

In the development of CRC, an important regulator of molecular processes is the transforming growth factor (TGF-β) signalling pathway [24]. In colorectal carcinogenesis, the SMAD4 tumour suppressor gene is important among its downstream effectors. An autosomal dominant inherited predisposition to colorectal polyps and CRC resulting in juvenile polyposis syndrome results from germ line mutations in SMAD4 [25]. SMAD4 mutations have been associated with a poor prognosis due to distant metastasis in some studies but not others, and this mutation has been reported in 5-20% of sporadic colorectal adenocarcinomas [26-30]. SMAD4 mutations have been found in high-grade colorectal tumours and also in tumours with mucinous differentiation [26,31-34]. The study aimed to characterize the distinctive clinicopathological features of APC, PIK3CA, and SMAD-4 mutated colorectal adenocarcinomas in Ugandan patients.

The design was a cross-sectional study between 2008 and 2021. Retrospective CRC FFPE blocks were obtained from the archives of the Department of Pathology, School of Biomedical Sciences, College of Health Sciences, Makerere University, from 1^st January 2008 to 15^th September 2021. Prospective participants were recruited consecutively from the Accident & Emergency Departments, Surgical Outpatient/Inpatient Departments, and Colonoscopy Departments of Masaka Regional Referral Hospital, Mulago National Referral Hospital, Uganda Martyrs’ Hospital Lubaga, and Mengo Hospital from 16^th September, 2019 to 16^th September, 2021. Two consultant pathologists confirmed the histopathologic diagnosis as colorectal adenocarcinoma: one pathologist at the Department of Pathology, School of Biomedical Sciences, College of Health Sciences, Makerere University, and another pathologist at the Institute of Genetics and Cancer at the University of Edinburgh.

The stage of the CRC was a radiological stage, which was obtained from the radiology reports in the participants’ medical case files. The radiological TNM staging (8^th edition) was used to stage all the colorectal tumours. A three-tier grading system was used to grade all the CRC cases. G1 was a well-differentiated CRC with >95% glandular formation; G2 was a moderately-differentiated CRC with 50-95% glandular formation; and G3 was a poorly differentiated CRC with <50% glandular formation [34]. The CRC tissue was confirmed as a colorectal adenocarcinoma, and the grade and LVI status were also obtained on H&E interpretation by the two consultant pathologists. The histopathological subtypes were classified as AC (classical adenocarcinoma), MAC (mucinous adenocarcinoma), and SRCC (signet-ring colorectal carcinoma). These histopathological subtypes were obtained from the interpretation of the H&E stains by the consultant pathologists. 

Extraction of DNA

DNA was extracted from formalin-fixed paraffin-embedded (FFPE) tissue blocks that contained at least 50% tumor. Following the recommendations of the manufacturer, the QIAamp DNA FFPE Advanced UNG kits (Qiagen GmbH, Hilden, Germany) were used. The concentration and quality of the extracted DNA were measured using a nanodrop 1000 spectrophotometer (Thermo Fischer Scientific, Wilmington, Co., USA). The 127 CRC FFPE tissue samples passed the quality check.

Library Preparation and NGS Sequencing

Library preparation was completed following the QIAseq targeted DNA Pro kit for Illumina (Qiagen GmbH, Hilden, Germany) along with a Qiagen custom design panel (QIAseq DNA panel catalog identifier: CPHS-43072Z-1294). The custom panel represented 56 genes with a total of 1,294 primer probes. It is designed to enrich selected genes and regions using 100 to 250 ng of FFPE DNA. A single controlled multienzyme 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 (i.e.., 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 cleanup after ligation and target enrichment PCRs. Following enzymatic cleanups, more consistent library construction was achieved, as there were no highly variable bead cleanups following ligation and target enrichent PCRs (Figure 1).

Figure 1: QIAseq Library Preparation Workflow (Adapted from QIAseq Targeted DNA Pro Handbook, Page 11).

Two unique indices were assigned to each sample to overcome errors due to image analysis, demultiplexing sequencing errors, and oligosynthesis contamination to reduce any real misassignment of incorrect samples. The library pool was sequenced on the Illumina MiSeq platform using a dual-indexed paired-end sequencing program of 2x149-bp reads. 

Data Analysis

The quality of the raw fastq files was first assessed using FastQC and Multi QC software, which generated HTML quality reports. Any bases below a phred score of 25, as well as adapter sequences, were trimmed using the Trim Galore tool [35]. 

The processed reads were aligned to the human genome reference version 38 (hg38) using BWA-MEM (Burrows-Wheeler Aligner) [36], generating the alignment files. The GATK4 (Genome Analysis Toolkit Version 4) pipeline using the best practices guideline [35,36] was used for variant discovery using the Haplotype Caller option. Only variants with an overall read depth greater than 20x and a variant allele depth of at least 10x were filtered for downstream analysis. The resultant variants were annotated using ANNOVAR [37]. 

Variants classified to have an uncertain significance by ClinVar [38] were further subjected to [9] variant effect prioritization tools to confirm their pathogenicity effect: SIFT (Sorting Intolerant from Tolerant), LRT, Mutation Taster, Mutation Assessor, FATHMM, PROVEAN, ClinPred, MutPred, and MetaSVM. A variant was classified as deleterious (D) if predicted by at least five of the variant effect prioritization tools to have a damaging effect; otherwise, it was considered tolerated (T) if fewer than five (5) tools predicted it to have a damaging effect [39]. The novelty of a mutation was obtained by screening the absence of the mutation in the following major population and mutation databases: COSMIC, 1000 Genomes, dbSNP, ExAC, GnomAD, ClinVar, Varsome, and Mastermind.

Statistical Analysis

In descriptive analysis, age was summarized by median (interquartile range), while sex distribution, grade, stage, LVI status, histopathological subtypes, and topography were summarized by counts and percentages. The association of clinicopathological features with APC, PIK3CA, and SMAD4 mutation status was performed using the Chi-square test and Fischer’s exact test. A p-value of ≤0.05 was considered to be statistically significant.

There were 127 CRC participants in this study. The median (IQR) age was 54 [45-67] years, and the male–female ratio was 1.2:1. The commonest location of CRC was the rectum, which constituted 57 (44.9%) participants. There were 33 (25.9%) right-sided colon tumours and 94 (74%) left-sided colon tumours. Stage III CRC tumours consisted of 56 (44.1%), while there were 20 (15.8%) stage IV CRC tumours. Grade II CRC consisted of 96 (75.6%) tumours, while 14 (11%) were grade III tumours. There were 114 (89.8%) CRC tumours with lymphovascular invasion, while 13 (10.2%) had no lymphovascular invasion.

 Table 1: Demographic and Clinicopathological Characteristics of All Ugandan CRC Participants.

Association between Clinicopathological Characteristics and APC Mutations in Ugandan CRC Participants

The association between age and APC mutations was also investigated in this study. There was no association between age and APC mutation status (p = 0.109) (Table 2). There were more APC-positive mutations in male and female participants compared to APC-negative CRC tumours (p = 0.047). The positive APC mutation rate was 77 (60.6%) in this study.

Table 2: Analysis of the Association between Clinicopathological Features and APC Mutation in Ugandan CRC Participants.

*Fischer’s exact test

There were 40 (70.2%) female participants with APC positive mutations compared to 17 (29.8%) female participants with APC negative mutations, and this reached statistical significance (p = 0.047). A higher stage of CRC was not associated with APC mutation status (p = 0.13). The associations between APC mutation status and tumour depth (T-stage) (p = 0.824*), lymph node status (N-stage) (p = 0.234), and metastasis (M-stage) (p = 0.239) were also not statistically significant. There was no difference in the grade of CRC and APC mutation status (p = 0.07171). There were 65 (57%) positive APC tumours that were LVI positive compared to 49(42.9%) negative APC tumours that were LVI positive, and this reached statistical significance (p = 0.015).

There were more left-sided colon tumours that were APC positive (58, 75.3%) compared to right-sided colon tumours (19, 24.7%); however, this did not reach statistical significance (p = 0.676).

Association between Clinicopathological Characteristics and PIK3CA Mutations in Ugandan CRC Participants

This study investigated the association between age and the overall PIK3CA mutation. The association did not reach statistical significance (p = 0.449) (Table 3). There were 23 (62.2%) female CRC participants that had a PIK3CA mutation, while there were 56 (62.2%) male CRC participants that had no PIK3CA mutation, and this reached statistical significance (p = 0.012). PIK3CA pathogenic mutations were detected in 37 (29.1%) of all the CRC participants.

Table 3: Analysis of the Association between Clinicopathological Features and PIK3CA Mutation in Ugandan CRC Participants.

*Fischer’s exact test

One hundred and twenty-seven CRC participants were analysed for the association between overall PIK3CA mutations and disease stage. A higher stage of CRC was not associated with PIK3CA overall mutation status (p = 0.509). With an increasing T stage, there were more participants who were PIK3CA negative, and this reached statistical significance (p = 0.018). The overall PIK3CA mutations, however, were not associated with advanced lymph node involvement (p = 0.152) or metastatic stages (p = 0.228).

The relationship between PIK3CA mutations and tumour sites was also analysed. The results showed that there was no association in PIK3CA mutation status between right-sided and left-sided colon cancers. There were 25 (26.6%) PIK3CA positive mutations compared to 69 (73.4%) PIK3CA negative mutations in left colon tumours. While there were 12 (36.4%) PIK3CA positive mutations and 21 (63.6%) PIK3CA negative mutations in right colon tumours (p = 0.288).

There was no difference between the degree of tumour differentiation (grade) and PIK3CA mutation status (p = 0.055). No association between the LVI status and the PIK3CA mutation status was found (p = 1.000). 

Association between Clinicopathological Characteristics and SMAD4 Mutations in Ugandan CRC Participants

The association between age and SMAD4 mutations was investigated in this study. The positive SMAD4 mutation rate was 68 (53.5%). There were 34 (54.8%) participants <54 years of age that had a positive SMAD4 mutation, while there were 28 (45.2%) SMAD4-negative participants <54 years of age. There was no association between age and SMAD4 mutation status (p = 0.775). Twenty-eight (49.1%) male participants had a positive SMAD4 mutation, while 29 (50.9%) male participants had a negative SMAD4 mutation. Therefore, there was no association between gender and SMAD4 mutation status (p = 0.367). 

Table 4: Analysis of the Association between Clinicopathological Features and SMAD4 Mutation in Ugandan CRC Participants.

*Fischer’s exact test

There were 10 (14.7%) stage I participants with positive SMAD4 mutations, compared to 9 (15.3%) stage I participants with negative SMAD4 mutations. While there were 26 (38.2%) stage III participants with positive SMAD4 mutations compared to 30 (50.8%) stage III participants with negative SMAD4 mutations, 10 (14.7%) stage IV participants had positive SMAD4 mutations, while 10 (16.9%) stage IV participants had negative SMAD4 mutations. Therefore, there was no association between stage and SMAD4 mutation status (p = 0.238). The associations between SMAD4 mutation status and tumour depth (T-stage) (p=0.808*), lymph node status (N-stage) (p=0.186), and metastasis (M-stage) (p=0.57) were also not statistically significant.

There was no difference in the grade of CRC or SMAD4 mutation status (p = 0.875). There were 60 (52.6%) positive SMAD4 tumours that were LVI positive compared to 54 (47.4%) negative SMAD4 tumours that were LVI positive; however, this did not reach statistical significance (p = 0.542). There were forty-nine left-sided colon tumours that were SMAD4-positive compared to forty-five right-sided colon tumours. Therefore, there was no association between the location of the tumour and SMAD4 mutation status (p = 0.589).

Relationship between MSI-Positive Tumours and PIK3CA Mutation Status

There were thirty-seven mutation-positive PIK3CA tumours, while 90 CRC tumours were negative for the PIK3CA mutation. Out of all the MSI-positive tumours, fifteen (29.4%) were mutation-positive PIK3CA tumours while 36 (70.6%) were mutation-negative PIK3CA tumours. There were 77 (60.6%) MSI-negative tumours, while there were 51 (40.2%) MSI-positive tumours. Out of the MSI-negative tumours, 22 (28.9%) were mutation-positive PIK3CA tumours, while 54 (71.05%) were mutation-negative PIK3CA tumours. There was no significant difference between MSI tumours that were PIK3CA mutation-positive or negative (p = 0.955).

MAC tumours constituted 10 (7.9%), while AC tumours constituted 92.1% of all tumours. There were 4 (40%) MAC tumours that were PIK3CA positively mutated, while there were 6 (60%) MAC tumours that were PIK3CA mutation-negative. There was no difference in histopathological subtype between PIK3CA mutation-positive or negative tumours (p = 0.415).

Out of 127 CRC tumours, eight (6.3%) had the KRAS-positive mutation. There were 4 (3.2%) CRC tumours that had BRAF-positive mutations. There were only 3 (2.4%) CRC tumours in this study with a triple combination of APC/KRAS/PIK3CA mutations. Double mutations of APC/KRAS were 7 (5.5%) in this study.

In CRC tumour development, the tumour suppressor gene APC plays an important role. Tumour progression results from the accumulation of beta-catenin in the cytoplasm resulting from the absence of the APC protein, resulting in the constitutive transcriptional activation of TCF-responsive genes [40,41]. Studies have shown that the APC mutation frequency rate in Western patients is 44.8%, while the frequency rate in Asian countries is 32.4% and in Middle Eastern countries is 33% [42]. The differences in mutation frequencies in Western countries, Asian countries, Middle Eastern countries, and our population may be due to environmental factors.

Consistent with previous studies conducted globally, where the APC mutation rate in CRC patients is reported to be between 34 and 80%, in our study, the APC exon 15 mutation frequency, which includes codons 1227–1724, was 60.6% [43,44]. The high prevalence of APC mutations in our study increases the need to perform mutation analysis for APC in the detection of CRC. APC mutations, especially in the mutation cluster region, may be considered diagnostic and prognostic biomarkers [45,46].

Among triple combinations of APC/KRAS/PIK3CA mutations, there have been only three participants in our study, while the most common double mutations were APC/KRAS mutations, where seven patients presented. Other studies have shown that the most common observed combinations of mutations were KRAS/p53 and APC/KRAS [47,48]. KRAS and BRAF mutations tend to be mutually exclusive, and the co-existence of these mutations is relatively rare in the CRC [49,50]. In our study, KRAS and BRAF did not coexist in any participant. The CRC is associated with a more severe type of disease when KRAS and BRAF co-exist and have been associated with a high T-stage (T3 and T4) [51,52].

PIK3CA mutation status was not associated with factors affecting prognosis such as tumour grade, CRC stage, or distant metastases. PIK3CA has an important role in CRC tumorigenesis and development; however, this study, similar to other studies, showed a remarkable lack of association between key clinicopathologic characteristics and PIK3CA mutations [53-55]. A meta-analysis by Mei et al. in 2016 showed that the pooled hazard ratios of wild-type and PIK3CA-mutated CRC for disease-free survival and overall survival were 1.20 (95% CI: 0.98–1.46) and 0.96 (95% CI: 0.83–1.12), respectively [56]. Therefore, PIK3CA mutations have shown no association with CRC tumour progression. The absence of any association with the main clinic-pathologic characteristics may be due to the fact that in CRC, the PIK3CA gene has a high mutation rate. As opposed to other gene mutations, the PIK3CA mutations may not be the crucial molecular alteration [56,57]. In vitro experiments have shown that the influence of mutations in PIK3CA on the growth of cancer cells may not be sufficiently potent, and to effectively influence tumour behaviour, these mutations need to cooperate with the other mutations of PIK3CA pathway kinases [58,59]. In addition, CRC has distinct molecular backgrounds with high heterogeneity [60].

A study by Smeby et al. showed that the rate of genetic alterations is dependent on the molecular background. Therefore, distinct molecular contexts may be responsible for the association of clincopathologic characteristics with PIK3CA mutations [61]. In KRAS-wild CRC, there are many studies that have shown the predictive and prognostic value of the PIK3CA mutation [57,62,63]. In wild-type KRAS, the association between clinicopathologic features and PIK3CA mutations may differ from that in unselected CRC patients [57,62,63].

Studies have shown that higher PIK3CA mutation rates are found in the proximal colon compared to the distal colon and rectum. This finding shows that there is a difference in molecular features between distal and proximal colorectal tumours [64]. Mucinous adenocarcinomas have been found to be closely associated with PIK3CA mutations [65]. However, in our study, there was no association between mucinous adenocarcinomas and PIK3CA mutations. The cause of this association in other studies is not clear [65]. Other studies have also shown that MSI and KRAS mutations were associated with KRAS and PIK3CA mutations; however, our study found no associations [66].

The findings from other studies show that at the molecular level, there is a significant difference between wild-type and PIK3CA-mutated patients. However, alterations in the clinicopathologic phenotypes were not possible with molecular events associated with PIK3CA mutations.

In vitro experiments have shown that mutations in exons 20 and 9 transform CRC cells in independent and different pathways [67]. However, in our study, we did not investigate the associations between PIK3CA mutations and exons 20 and 9. In metastatic CRC, KRAS mutations have been shown to be strongly associated with PIK3CA exon 20 and 9 mutations. In metastatic CRC, KRAS mutations have been shown to be strongly associated with PIK3CA exon 20 and 9 mutations [66]. In our study, there was no association between BRAF and PIK3CA mutations; however, other studies have shown that BRAF is negatively associated with PIK3CA exon 9 mutations, while BRAF mutations were positively associated with PIK3CA exon 20 mutations. Therefore, it appears that one should consider separately the effect of PIK3CA exon 20 and exon 9 mutations. In our study, due to the small sample size, the relationship between PIK3CA and several clinicopathologic features could not be determined, especially in terms of sub-group analysis of exon 20 and exon 9 mutations. Our study involved mutation detection assays, which may be different from those of other studies. This may have also affected the precision and accuracy of the results of our study [53].

A study by Fleming et al. reported a mutation frequency of SMAD4 at 8.6% with sporadic CRC in western patients [68]. CRC cells evade the inhibitory effect of TGF-beta due to mutations in SMAD4, and this contributes to the progression of CRC [69,70]. In our study, the rate of SMAD4 mutation in Ugandan patients was 53.5%. The differences in SMAD4 mutation frequency rates may be due to differences in the geographical distribution, ethnicities, and sample size. In the Ugandan population, this is the first report of a SMAD4 gene mutation.

In CRC progression and development, EGFR signalling plays a significant role. It is particularly important to identify molecular alterations that affect anti-EGFR treatment. In chemotherapy-resistant metastatic CRC patients, De Roock et al. found that PIK3CA, BRAF, and KRAS mutations also affect the anti-EGFR treatment outcome [57]. While this study did not examine the effects of anti-EGFR treatment with PIK3CA, BRAF, and KRAS mutations, future studies in Uganda will be necessary to investigate the effect of this treatment.

Several studies have investigated the role of SMAD4 mutations in the clinicopathological parameters and prognosis of CRC. The results are inconsistent. A meta-analysis by Fang T et al. from China showed that a poor prognosis was associated with SMAD4 mutations in CRC [71]. A worse overall- and disease-free survival was associated with SMAD4 mutations compared to SMAD-4 wild-type controls [71]. The results from this meta-analysis showed distant metastasis and higher pathological TNM stages occur more frequently in CRC patients with SMAD4 mutations [71]. Lymph node metastasis and mucinous differentiation were more likely to occur in SMAD4 mutant patients [71]. These SMAD4 mutant CRC patients were more likely to concurrently have RAS mutations. In our study, SMAD4 mutations were not associated with a poorer T stage, metastasis, poor grade, or lymphovascular invasion. Therefore, the SMAD4 status in CRC was not associated with a poorer prognosis. Consistent with the results from our study, SMAD4 gene mutations were not associated with sex, age, tumour grade, BRAF, or MSI status [71]. Another meta-analysis by Huang D et al. showed that there was a higher risk of distant metastasis in SMAD4-mutated CRC patients [72].

Many studies over the last twenty years have shown that the SMAD4 mutation may promote tumour progression caused by other genes; however, by itself, it does not cause tumorignesis [73]. Compared to tumours without liver metastasis, the frequency of SMAD4 mutations was higher in CRC with liver metastasis (74). SMAD4-deficient CRC tumour cells secrete more CCL15 and CCL9 and, through the CCL15-CCR1 and CCL9-CCR1 axes, recruit CCR1+myeloid cells, which are responsible for metastasis [75]. Due to recurrent CRC after initial resection of the tumour, patients with SMAD4 mutations are less likely to undergo hepatic resection [76]. In CRC patients, Alhopuro have shown that SMAD4-mutation-positive tumours are sensitive to 5-FU-based chemotherapy [77]. A novel mechanism discovered by Zhang et al. is the inhibition of the PIK3/Akt/CDC2/suruivin cascade by SMAD4, triggering the chemo sensitivity of 5-FU through cell cycle arrest [78]. Lin et al. found that a high expression of SMAD4 is beneficial to cetuximab-based chemotherapy and that there is a reduction in the sensitivity of CRC cells to cetuximab by silencing SMAD4 and promoting epithelial-mesenchymal transition [79]. Following liver resection, Mizuno T et al. showed that significantly poor overall survival was found with the SMAD4-positive CRC mutation, which was independent of the RAS mutation status [80]. Therefore, these findings show that SMAD4 pathogenic variants play a major role in the progression of CRC and the efficacy of target therapy.

Loss of SMAD4 expression in CRC results in disruption of canonical TGF-β signalling as it is a signalling transcription factor [81]. Studies have shown that a reduction in disease-free survival and overall survival of advanced-stage CRC patients is associated with a loss of SMAD4 function [82,83].

In the early stages, the canonical TGF-β/SMAD4 signalling pathway is a tumour suppressor, resulting in an increased ability to induce apoptosis and having anti-proliferative activity. TGF-β stimulates the development of advanced tumours and acts as a promoter of metastasis [84]. Invasive potential of CRC was not obtained with the TGF-β-dependent EMT, in a study by Siraj et al., however, the activated RAS would alter the reaction, resulting in invasive and tumorigenic potential. The synergistic effect of TGF-β/SMAD4 and Ras-Raf-MAPK cascades was necessary for the tumour to acquire an aggressive phenotype [85].

Currently, RAS is a tumour driver gene, biomarker, and target for treatment in CRC. An aggressive phenotype of CRC is produced when the expression of RAS up-regulates the expression of phosphotyrosine kinase receptors ERRB2 (HER2) and ERBB1 (EGFR). SMAD4-dependent signal transduction has an antiproliferative effect by negatively regulating and inhibiting Ras-induced up regulation of ERBB2 and EGFR. The abnormal expression of ERBB2 and EGFR is synergistically up regulated by the loss of oncogenic SMAD4 and RAS signals, leading to the spread and metastasis of the primary tumour [86,87]. The RAS and ERK pathways may be quickly activated by TGF-β. However, the TGF-β/SMAD4 pathway is inhibited by the ERK pathway by phosphorylating SMAD3 and SMAD2, resulting in tumour cells with RAS mutations exhibiting a loss of TGF-β antiproliferative activity [88].

Compared to patients with both mutations, patients with SMAD4 wild-type and RAS wild-type tumours have longer overall survival [89]. Regardless of RAS mutation status or clinicopathological features, SMAD4 mutations were associated with poorer overall survival. Further investigations are required for the precise mechanisms of SMAD4 and other influential genes.

The frequency of APC mutations in Uganda was similar to reported frequencies in Western populations except for the PIK3CA and SMAD4 mutations, where higher frequencies were reported compared to the Western world. Overall, APC mutations in Uganda were associated with a positive LVI status. However, APC, PIK3CA, and SMAD4 mutations were not associated with most clinicopathologic parameters.

There was no association between clinicopathologic parameters and overall PIK3CA mutation status. PIK3CA mutations were not found to be associated with right-sided colon tumours in CRC Ugandan patients. Further studies are needed to investigate the implications of PIK3CA mutations when combined with BRAF and KRAS. Evaluation of PIK3CA exon 20 and exon 9 mutations is required in Ugandan CRC patients. SMAD4 was not associated with a poor prognosis in Ugandan CRC patients and was not related to tumour grade, BRAF status, or MSI status. Further studies will be needed in Uganda to evaluate these findings and the clinical significance of SMAD4 status in CRC.

Optimizing personalized cancer therapy in this population is necessary by identifying molecular markers that may provide insights into the pathogenic process of CRC.

Study Limitations

Compared to developed high-income countries, difficulty was encountered in obtaining complete data from the medical records retrospectively. During the collection of secondary data from the Kampala Cancer Registry, selection bias could have possibly been introduced, as patients with no clinical data or missing demographic clinical data were excluded.

Underestimating the stage was another major limitation, as it was radiological and not pathological, and some cases were not staged with a CT scan but by ultrasound. Since the lymph node assessment in this study was radiological and not pathological, this could have overestimated or underestimated the extent of lymph node involvement for TNM staging.

Since we only used colorectal cancer tissues for analyses, we could not confirm whether the genetic mutations and/or variations were present in the germline or were purely somatic. In this part of the study, we did not perform immunohistochemical staining or functional studies to further investigate the effect of the described mutations on the expression levels of the corresponding proteins. To overcome the influence of antigen degradation on archival material, a high standard of laboratory testing was followed, along with the maintenance of a short period of storage of specimens. 

Ethical Approval and Consent to Participate in the Study

This study was approved by the Higher Degrees Research and Ethics Committee, School of Biomedical Sciences, College of Health Sciences, Makerere University (Approval No. SBS-630), and the Ugandan National Council for Science and Technology (Approval No. HS-2574). All participants who were recruited prospectively were informed of the purpose of the study, and they endorsed the informed consent forms prior to participation in this study. 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 Higher Degrees 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 was accessed from the medical case files in the respective hospitals, was anonymized and maintained with confidentiality. The conduct of the study was in accordance with the Declaration of Helsinki.

Consent for Publication

Not Applicable

Authors’ Contributions

Richard Wismayer conceived the concept, collected data, participated in the analysis, and wrote the paper. Rosie Mathews 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 carried out the statistical analysis. Henry Wabinga, Michael Odida, and Ian Tomlinson carried out critical reviews of the manuscript for intellectual content. All authors approved the final manuscript.

Competing Interests

The authors declare that they have no competing interests.

Acknowledgements

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 at 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.

Data Sharing Statement

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

Funding

This colorectal cancer study was part of a collaboration between Makerere University and the University of Edinburgh. Professor Ian Tomlinson is acknowledged for funding the laboratory experiments in this study.

Abbreviations

ANNOVAR – a software tool to utilize update-to-date information to functionally annotate genetic variants detected from diverse genomes

APC – adenomatous polyposis coli

COSMIC – catalogue of somatic mutations in cancer

CLINVAR – interpretation of clinically relevant variants

CRC – colorectal cancer

DNA – deoxyribonucleic acid

FFPE – formalin-fixed, paraffin-embedded

PCR – polymerase chain reaction

PIK3CA – phosphatidylinositol-4, 5-bisphosphate 3-kinase catalytic unit alpha

SD – standard deviation

TGF-β – trabsforming growth factor-beta

TP53 – tumour protein p53 gene

UMI – unique molecular identifier

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