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Journal of Gastroenterology
Research and Practice


Research Article - Open Access, Volume 4

Molecular characteristics of left-sided, advanced stage colorectal cancer: A Mexican perspective

Lizardo-Thiebaud Maria José1; Martínez-Benítez Braulio1; Martínez-Nava Jean M2; Medrano Guzmán Rafael 3; María Guadalupe Jazmín De Anda González 1,2*

1Department of Anatomical Pathology, National Institute of Medical Sciences and Nutrition Salvador Zubirán, Mexico City, Mexico.

2Department of Anatomical Pathology, Oncology Hospital, National Medical Center Siglo XXI, IMSS, Mexico City, Mexico.

3Department of Surgery, Oncology Hospital, National Medical Center Siglo XXI, IMSS, Mexico City, Mexico.

*Corresponding Author : De Anda González MGJ
Department of Anatomical Pathology, Oncology Hospital, National Medical Center Siglo XXI, IMSS, Cuauhtémoc 333, Neighborhood Doctores, Delegation Cuauhtémoc, PC 06720 Mexico City, Mexico.
Email: deandajaz@hotmail.com

Received : Feb 13, 2024

Accepted : Mar 21, 2024

Published : Mar 28, 2024

Archived : www.jjgastro.com

Copyright : © De Anda González MGJ (2024).

Abstract

Background: Predictive molecular markers based on the consensus molecular classification of colorectal carcinoma are tested following expert recommendations. Specifically, they are tested when target molecular therapy is being considered for treatment. Their presence depends on biology but their frequency seems to be increased in advanced stages.

Objective: We developed a study of cases of left-sided CRC in advanced clinical stages from a cohort of Mexican patients to evaluate the presence of predictive molecular markers.

Method: Predictive molecular markers were analyzed, including BRAF, KRAS, NRAS and mismatch repair genes, in cases of advanced, left-sided colorectal carcinoma.

Results: An alteration was found in more than a half of cases. KRAS was the most frequently mutated gene, in more than a third of cases. No BRAF mutation was found.

Conclusion: The main determinants of predictive molecular markers appear to be staging, location and methodology. More studies need to be done to determine the variability given by race.

Keywords: Advanced colorectal cancer; KRAS; NRAS; BRAF; MSI.

Abbreviations: CRC: Colorectal Carcinoma; CMS: Consensus Molecular Subtypes; CAP: College of American Pathologists; MMR: Mismatch Repair Genes; Advanced CRC (Stage III and IV; Mcrc); MSS: Microsatellite Stable.

Keywords: Pharmacobezoar; Modified release venlafaxine; Overdose; Endoscopic decontamination.

Citation: Lizardo-Thiebaud MJ, Martínez-Benítez B, Martínez-Nava JM, Rafael MG, De Anda González MGJ. Molecular characteristics of left-sided advanced stage colorectal cancer: A Mexican perspective. J Gastroenterol Res Pract. 2024; 4(3): 1190.

Introduction

Colorectal Carcinoma (CRC) is a neoplasia with a doubleedge sword. Effective secondary prevention has been key to its management. Though its mortality rate varies depending on the population studied, data shows more than 50% of patients develop metastasis [1,2]. The changing epidemiological trend towards diagnoses in younger ages is also a matter of concern.

The epidemiology of CRC is best explained by its associated risk factors. Diet, obesity, the microbiota and the immune response contribute to the metabolic alterations seen in CRC [3,4]. Many molecules interact in the carcinogenesis of CRC. There are molecular signatures that have been identified as being different in the sequence of events, molecular interactions and biology of CRC. The main drivers are oncogenes and tumor suppressor genes, including KRAS, BRAF, PIK3CA, APC and p53 [3,5]. Accordingly, a molecular classification of CRC has been developed.

Historically, the molecular classification was based on the genetic model of CRC [6,7]. CRC arises from a precursor lesion, a dysplastic polyp. It was believed that these clonal cells had specific genetic alterations that followed a relatively constant pathway towards carcinoma.

In recent times, the CRC Subtyping Consortium analyzed published data on CRC subtyping. Four Consensus Molecular Subtypes (CMS) were identified [7-9].

CMS 1 corresponds to microsatellite unstable tumors. They harbor alterations in BRAF and overexpress genes associated with inflammation. CMS2 show higher chromosomal alterations, specially at oncogenes. They upregulate CMYC and WNT pathways. CMS3 show lower chromosomal alterations, higher prevalence of CpG island methylator phenotype-low clusters. They are associated with mutations in KRAS and metabolic alterations. CMS4 is associated with epithelial-mesenchymal transition and alterations in genes associated with the biology of metastasis [8].

Based on the CMS, molecular targets are being used to treat CRC. Specifically, CRC with metastasis [10]. In 2017, the American Society for Clinical Pathology, College of American Pathologists (CAP), the Association for Molecular Pathology and the American Society of Clinical Oncology established recommendations for the molecular biomarker testing and their corresponding treatments [11]. In summary, they concluded predictive molecular markers for CRC include KRAS, NRAS, BRAF and Mismatch Repair genes (MMR).

The clinical utility of studying the molecular subtypes of CRC specimens is not debatable. Recommendations are still not strong enough, reflecting the need of robust studies analyzing predictive molecular markers in CRC. We developed a study of cases of left-sided CRC in advanced clinical stages from a cohort of Mexican patients to evaluate the clinical utility of predictive molecular markers.

Materials and methods

A retrospective cohort of cases from the Oncology Hospital, National Medical Center Siglo XXI in Mexico City was done including all cases of advanced stage, left-sided colorectal carcinoma with molecular analysis of NRAS, KRAS and BRAF, as well as immunohistochemical determination of microsatellite instability from the years 2022 to 2023. It included adult patients of both sexes. Cases without a complete biomarker analysis were excluded. The study was approved by the internal Research Ethics Committee.

DNA was extracted from formalin-fixed paraffin specimens of the primary CRC, using the Biocartis IdyllaTM System for KRAS (BCT005812), NRAS and BRAF (A0030/6) (Table 1). The system determines the presence of mutations through real-time PCR.

Immunohistochemistry assays for MMR were performed in the same samples, using the following antibodies: MLH1 (Mob430), PMS2 (PDM171), MSH2 (Mob585), and MSH6 (Mob429). Their results were interpreted according to the guideline from the College of American Pathologists.

The statistical analysis was performed using GraphPad Prism 10. The chi-squared test was used to compare categorical groups and Mann-Whitney test was used for continuous variables. A pvalue of <0.05 (two-tailed) was considered significant in all the statistical tests.

Results

A total of 98 cases were included (Table 2). Cases with inadequate tissue were eliminated (one). The mean age was of 59 years. The male-to-female ratio was of 1.64. A total of 58 cases had an abnormal predictive molecular marker. The most frequently mutated marker was KRAS (see Table 2). There were only 5 cases with mutations in NRAS, and 4 cases with altered MMR status. There were no cases with mutations in BRAF.

The most prevalent mutation in KRAS was in codon 12. The number of cases with mutations in NRAS were too small to determine a prevalence. Cases with altered MMR were of two profiles: loss of MLH1 only or loss of MLH1 paired with PMS2. None of these cases presented mutation in BRAF. Analysis of the age differences in the cases with KRAS mutation, NRAS mutation and deficient MMR yielded no information. However, the case numbers for the latter too are small.

Figure 1: Graphical representation of (a) the frequency of predictive molecular markers and (b) the frequency of mutations in each foci analyzed in KRAS.

To identify differences in the frequency of mutations, a search was done in PUBMED using the terms “advanced colorectal”, “KRAS” and “PCR”. The search yielded 117 results, of which only 26 were considered for the final analysis. The data retrieved includes the results for KRAS, NRAS and BRAF mutation for advanced CRC (stage III and IV; mCRC), left-sided CRC (descending colon, sigmoid colon and rectum), transverse CRC, and right-sided CRC (ileocecal valve, cecum, and ascending colon). The results are shown in Table 4 [12-37].

Table 1: Genes, codons and mutations analyzed.
Gene Number of mutations Exon Codons Mutations
KRAS/NRAS 2 12 G12C (c.34G>T)
G12R (c.34G>C)
G12S (c.34G>A)
G12A (c.35G>C)
G12D (c.35G>A)
G12V (c.35G>T)
13 G13D (c.38G>A)
3 59 A59E (c.176C>A)
A59G (c.176C>G)
A59T (c.175G>A)
4

 61 Q61K (c.181C>A; c.180_181delinsAA)
Q61L (c.182A>T)
Q61R (c.182A>G)
Q61H (c.183A>C; c.183A>T)
117 K117N (c.351A>C; c.351A>T)
146 A146P (c.436G>C)
A146T (c.436G>A)
A146V (c.437C>T)
BRAF 5 600 V600E (c.1799T>A; c.1799_1800delinsAA)
V600D (c.1799_1800delinsAC)
V600K (c.1798_1799delinsAA)
V600R (c.1798_1799delinsAG)
Table 2: Results of the systematic analysis.
Year Anthors Method Exons Total n n Stage Age M.F Laterality KRAS % NRAS % BRAF %
2013 Rosty et al.. KRAS-RT PCR
BRAF allele
specific PCR 		KRAS exon 2, BRAF
V600E 		776 all 6818 1.09 all 28.00 n/a 16.00
295 advanced all 29.10 n/a 19.60
210 all right 32.30 n/a 30.40
63 all transverse 28.50 n/a 20.60
463 all left 26.70 n/a 9.20
2015 Mans et al. RT-PCR; dye
terminator
sequencing for
BRAF 		KRAS exon 2 431 advanced 61 (27-92) 1.37 all 42.00 n/a 8.00
161 advanced right 48.40 n/a 15.00
239 advanced left 42.60 n/a 4.60
2016 Nam et al. RT-PCR KRAS codons 12, 13, 61;
BRAF V600E 		191 all 60 (28-93) 1.17 all 54.40 n/a 3.10
170 advanced all 56.40 3.50
49 all right 71.40 n/a 8.20
142 all left 48.50 n/a 1.40
2016 Sharma et al. RT-PCR KRAS exon 2 461 advanced 61 (26-89) 1.17 all 37.30 n/a n/a
2017 Lee et al. RT-PCR KRAS codon 12, 13,61 262 advanced 62 (32-93) 1.56 all 46.60 n/a n/a
2017 Hua Gae et al. RT-PCR KRAS exon 2,3,4; BRAF
exon 15 		289 all 59.6 1.8 all 42.70 n/a 2.30
43 all right 37.20 n/a 7.00
179 all left 43.50 n/a 1.10
2019 Franczak et al. RT-PCR RAS exon 2,3,4; BRAF
exon 15 		50 advanced all 44.00 7.00 11.00
2019 Wojas- Krawc-
zyk et al. 		RT-PCR RAS exon 2,3,4; BRAF
exon 15 		102 advanced 64+/- 9.41 2.09 all 30.30 3.90 6.87
32 advanced right
(A,T,D)		 19.00 6.25 6.25
63 advanced left 32.00 1.50 8.00
2020 Van Tactal RT-PCR RAS codon 12, 13, 61;
BRAF exon 15 		156 79 advanced 59.5 1.1 all 44.00 14.00 10.00
2020 Bourhis et al. RT-PCR RAS codon 12, 13, 61;
BRAF exon 15 		20 advanced 45-90 0.87 55.00 5.00 15.00
2021 Alharbi et al. RT-PCR RAS codon 12, 13, 61;
BRAF exon 15 		248 all 63 1 14 1.62 all 50.00 2.00 0.40
65 right 65.00
117 left 45.00
2021 Delatkhah et al. RT-PCR RAS 173 advanced 58 + 12.95 1.27 all 44.00 1.30 2.50
20 right 35.00 n/a n/a
87 left 44.00 n/a n/a
2022 Makutani et al. RT-PCR RAS codon 12, 13, 61;
BRAF exon 15 		253 all 72 (32- 92) 1.11 all 44.00 3.60 18.00
2022 Alghamdi et al. RT-PCR KRAS exon 2,3,4 194 all 58 1 13 1.12 all 50.00 n/a n/a
47 right 76.00
135 left 45.00
2022 Bezyk et al. RT-PCR RAS exon 2,3,4; BRAF
exon 15 		500 advanced 66 1.5 all 38.00 4.00 4.80
89 advanced right 52.00 3.40 10.00
17 advanced transverse 47.00 0.00 23.50
337 advanced left 32.60 4.70 2.70
2023 Mahdi et al. RT-PCR RAS exon 2,3,4 414 advanced 59 + 16 1.08 all 52.00 3.00 n/a
105 right 60.00 2.00 n/a
299 left 50.00 3.40 n/a
2023 Radanova et al. RT-PCR KRAS exon 2,3,4 236 advanced 63.92 +
10.52		 1.4 all 47.00 n/a n/a
70 advanced right 54.20 n/a n/a
166 advanced left 44.00 n/a n/a
Present study RT-PCR RAS exon 2,3,4; BRAF
exon 15 		98 advanced 59 1.64 left 49.00 5.00 0.00

Discussion

Predictive molecular markers for CRC include KRAS, NRAS, BRAF and mismatch repair genes. The American Society for Clinical Pathology, CAP, the Association for Molecular Pathology and the American Society of Clinical Oncology have established recommendations based on expert opinion [11]. The expert consensus opinion considers formalin fixed paraffin embedded tissue acceptable for molecular analysis. Both metastatic and recurrent are the preferred CRC tissues for testing.

The mutation status of CRC can be tested through direct Sanger sequencing, Polymerase Chain Reaction (PCR) or pyrosequencing. The DNA extraction may be done from paraffin-embedded tissue followed by dissection of the tumor. Pathology reporting protocols from the CAP recommend identifying every method used accordingly [38].

One of the best non-NGS methods for the identification of RAS-BRAF mutations in CRC is indeed PCR. Considering the Idylla platform, a French meta-analysis calculated a sensibility of 99.3% and specificity of 96.8% with a positive predictive value of 97.4% and negative predictive value of 99.1% for KRAS. Similarly, they reported a sensibility of 96.7% and 98.8%, a specificity of 99.7% and 99.3%, a PPV of 99% and 98%, with a NPP of 98.9% and 99.6% for NRAS and BRAF respectively [39]. Investigating the frequency of RAS-BRAF mutations using the Idylla platform, we found fourteen studies for CRC from which nine reported relevant statistics (Table 3) [40-48]. The frequency of KRAS mutations is similar (especially considering studies with mCRC), most being higher than 40%. Likewise, the presence of NRAS mutations is low, most studies reporting a frequency lower than 5%. The presence of BRAF mutation is variable. The impact of race cannot be analyzed.

Numerous PCR-based methods have been validated to test for predictive molecular markers. Their sensibility is higher than that of Sanger sequencing. The frequency of mutations, however, varies according to specific variables. For instance, age and sex are not associated to mutations [36,37]. Nor are the degree of differentiation, the presence of lymphovascular invasion or perineural invasion [37]. Race could be important; however, the main determinants appear to be staging, location and methodology (Table 3).

The frequency of mutations in predictive molecular markers are found in more than 50% of cases with CRC, a similar rate as found in the cohort (59%). KRAS is the most mutated gene (in 35-40% of cases as found in the literature; 49% of cases in our cohort). This remains true independently of the population studied (Table 3).

KRAS is highly associated to right-sided CRC. Nevertheless, left-sided CRC may present alterations in KRAS, even if Microsatellite Stable (MSS). The frequency is lower but depends on the staging of the disease (Table 4). NRAS is mutated less often, and there is no association to sidedness (Table 3).

According to the CMS of CRC, right-sided CRC are commonly unstable. Left-sided CRC are less frequently associated to MMR, but not an impossibility. In our cohort of left-sided CRC, cases lacking only MLH1 may reflect methylation of MLH1, which is associated to BRAF mutations. However, none had mutation in BRAF. mCRC tumors present BRAF mutation in 5-10% of cases (Table 3). When comparing MSS, right-sided and left-sided CRC, BRAF mutations are statistically more frequent in MSS right-sided CRC [49,50]. Sidedness may thus explain our unanticipated result for BRAF.

Mutations in genes from the MAPK pathway (specifically KRAS and NRAS) not only predict resistance to tyrosine kinase inhibitors but also seem to predict survival [37,51-53]. Clinical decision-making depends on the exhaustiveness of their study. Though there is a low rate of concomitant mutations (NRAS/ KRAS and KRAS/BRAF), their existence may be relevant [36,37]. The low rate may be explained by studies analyzing tumor heterogeneity in mCRC, which have identified small clones having mutations at other exons of KRAS [54,55]. Their presence may affect the effectiveness on target therapy. With this understanding, PCR-based studies have, through time, increased the number of exons being studied in both genes (KRAS and NRAS) (Table 3).

Conclusion

For population/race to be considered a variant in the presence of predictive molecular markers, the techniques used, the staging reported, and the location of CRC is adamant. In present times, RAS mutant CRC is thoroughly studied by PCR-based platforms. As long as protocols are updated and followed correctly, the identification of predictive molecular markers remains beneficial.

Declarations

Author contributions: MGJDA provided the conceptualization, data curation, project administration and resources and review and editing; MJLT provided with methodology, formal analysis and writing of original draft; RMG and BMB provided conceptualization, investigation, supervision, review and editing; JMMN provided with resources, project administration and supervision.

Conflict of interest: The authors declare no potential conflicts of interest.

Ethics approval and consent to participate: The study has been reviewed by the appropriate ethics committee.

Availability of data and materials: The data generated in this study are available upon request from the corresponding author. Raw data for this study were generated at the Molecular Biology laboratory at the Hospital. Derived data supporting the findings of this study are available from the corresponding author upon request. All data analyzed during this study are included in this published article. The raw data generated at the core facilities may be accessed by the corresponding author upon request.

Funding: Not applicable.

Acknowledgements: The study did not receive fundings.

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