Unraveling the role of molecular profiling in predicting treatment response in stage III colorectal cancer patients: Insights from the IDEA International Study

1. Introduction

Colorectal cancer (CRC) is one of the most common malignancies and the second most common cause of death from cancer[1]. In 2020, 1.9 million new cases of CRC and approximately 935,000 deaths were reported[2]. By 2030, the global burden of CRC is predicted to be 60%, with more than 2.2 million new cases and 1.1 million deaths. By 2035, the total number of deaths from rectal and colon cancer is estimated to increase by 60% and 71.5%, respectively[2]. Depending on the stage of the disease at the time of diagnosis, both the treatment and prognosis differ. Patients with stage III CRC have an overall 5-year survival rate of 60%. Adjuvant chemotherapy aims to increase this rate and extend both the overall and disease-free survival[3]. Since 2004, folinic acid, fluorouracil, and oxaliplatin (FOLFOX) or capecitabine and oxaliplatin) for six months has been the standard treatment regimen[3,4]. However, oxaliplatin can lead to adverse effects, particularly peripheral sensory neuropathy[5].

Considering the increased incidence of the disease, toxicity of the treatment, cost, and efforts to reduce the duration of treatment for all the aforementioned reasons[5], the international IDEA study was designed to evaluate the hypothesis of non-inferiority of the 3-month vs. 6-month adjuvant chemotherapy with FOLFOX or CAPOX[6].

Although strong, AJCC/UICC-TNM staging (American Joint Committee on Cancer/Union Internationale Contre le Cancer—extent of primary tumor, regional lymph node involvement, presence of distant metastases) often fails to provide complete prognostic information because the outcome varies even among patients of the same stage[7]. Therefore, there is an urgent need to identify new tools that can contribute to CRC prognosis. The aim of the current study was to investigate the molecular profile of surgical specimens from stage III CRC patients enrolled in the international IDEA study, for whom paraffin-embedded cancer tissue was available. Following genetic profiling, correlations were performed with clinicopathological characteristics, as well as with patient outcomes. Additionally, the patients were tested for vitamin D receptor (VDR) and toll-like receptor (TLR) gene polymorphisms in peripheral blood, as our previous studies have demonstrated the role of such polymorphisms in tumor development and progression[8,9,10].

2. Patients and methods

2.1. Patient enrollment

The Hellenic Oncology Research Group (HORG) enrolled 708 patients with CRC in the international IDEA study (ClinicalTrials.gov Identifier: NCT01308086). Of these, 237 stage III patients with formalin-fixed paraffin-embedded (FFPE) tissues were included in the current study (Supplementary Table S1). All patients were aged > 18 years and received adjuvant chemotherapy with FOLFOX or CAPOX. None of the enrolled subjects had any other documented malignancies.

2.2. Formalin-Fixed Paraffin-embedded (FFPE) tissues

All surgical materials were evaluated by a specialized pathologist at the Department of Pathology of the University General Hospital of Heraklion, Crete, and the most representative and enriched tumor areas were selected for dissection. Healthy tissue was used as the control tissue. The specifications of the FFPE sections used for DNA extraction were as follows: tissue surface area, 25 mm², section thickness, 10 μm; c. At least 10 sections with >50% cancer cells, d. Cancer cells were collected from areas rich in cancerous tissue and avoiding healthy tissue, adipose tissue, necrotic areas, and lymphocytes that decrease the content of cancer DNA. To facilitate the collection of appropriate cells from the 10 sections, an additional section was stained with hematoxylin-eosin to locate the cancerous areas.

2.3. TLR and VDR genotyping in blood samples

A total of 5 ml of peripheral blood in EDTA was collected from each patient, and DNA was extracted using the QIAamp DNA Blood Mini kit (QIAGEN, Hilden, Germany) according to the manufacturer’s instructions. The DNA concentration was determined using a NanoDrop ND-1000 v3.3 spectrophotometer (Thermo Fisher Scientific, Wilmington, DE, USA).

To determine the genetic variants of TLRs and VDRs, Polymerase chain reaction and restriction fragment length polymorphism (PCR-RFLP) were used to determine the genetic variants of TLRs and VDRs. For TLR2 196-to-174 Ins/Del genetic variants, PCR was used, while TLR4 (Asp299Gly and Thr399Ile) and TLR9 (T1237C and T1486C) genetic variants were determined using PCR-RFLP. The materials and conditions for each gene target have been previously described[8,9]. Similarly, for genotyping of VDR genetic variants at the TaqI, ApaI, FokI, and BsmI positions, PCR-RFLP was used. The reagents and PCR conditions have been previously described, in detail[8,9,10]. The patients were classified as wild-type, heterozygous, or homozygous for each single nucleotide polymorphism, based on the absence or presence of the restriction site in both alleles.

2.4. Whole Exome Sequencing (WES)

The Illumina DNA Prep with Enrichment kit (Illumina, San Diego, CA 92122) was used for library preparation and enrichment, and sequencing of both tumor and normal tissues was conducted using the NovaSeq 6000 system (Illumina). For each sample, at least 250 ng of high-quality DNA was quantified using a Qubit Fluorometer (Thermo Fisher Scientific, Paisley, UK), was used. Following the WES, two files (. fastq) containing sequencing data were extracted from each tissue (tumor and normal) using forward and reverse reads.

2.5. Bioinformatic analysis

After obtaining the raw data from the WES analysis, a bioinformatics pipeline was used to process the data and generate interpretations. This included alignment to the human genome, variant calling, variant filtering, and annotation of the variants. The processed data were analyzed to identify somatic variants and evaluate their functional significance, particularly those associated with CRC (Figure 1). Initially, the raw sequences were aligned to the human genome (version hg19/GRCh37)[11], and variant calling was conducted using the genome analysis toolkit (GATK) for SNPs and insertion/deletions (INDELs). This generates two variant call format files (VCF) for each patient, one for the tumor and one for the normal tissue, respectively[12]. The somatic variants were isolated by subtracting the germline variants from the tumor, and a custom gene panel composed of 62 genes associated with 11 signaling pathways was utilized based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database on CRC-correlated genes[13] (Table 1 and Table 2). Subsequently, ANNOVAR software was employed to annotate the SNPs and INDELs, providing functional information that can determine the biological significance of each variant and identify CRC-associated variants[14].

To identify clinically significant variants and the signaling pathways involved, a filtering strategy was employed based on the functional position of the variants. Variants located in exons and splice sites are isolated as they are more likely to cause diseases[15]. In addition, the variants located in exons were further filtered based on their functional consequences, excluding variants causing synonymous mutations. This step was considered synonymous mutations that do not affect the amino acid sequence of proteins and are therefore less likely to be clinically relevant. All analyses were run in the Anaconda Powershell Prompt (Anaconda3, Inc.) on Ubuntu 20.04.3 LTS.

2.6. Statistical analysis

After characterizing the patients’ molecular profiles, the clinical, pathological, and epidemiological characteristics were examined to determine their association with patient outcomes. Disease-free (DFS) and overall survival (OS) were calculated from the day of tumor excision until the first documented recurrence or death, respectively. Recurrence was defined as the presence of metastatic disease, local recurrence, or a second primary tumor. The possible associations between baseline characteristics, recurrence, and individual or concurrent mutations were compared using the 2-sided Fisher exact test for categorical variables. The association between risk factors and time-to-event endpoints was evaluated using the log-rank test, and the Kaplan-Meier method was used to generate DFS and OS curves. Univariate and multivariate Cox regression analyses were conducted to evaluate the correlation between the potential prognostic factors and DFS or OS. Statistical significance was defined as p ≤ 0.05, and the statistical tool used was SPSS v. 26.

3. Results

3.1. Patients

The current investigation enrolled 237 patients with stage III CRC, and their characteristics are displayed in Table 3 and Supplementary Table S1. Among these patients, 151 (63.7%) were male, 159 (67.1%) were <70 years old (median:64 years, range:18-84), 158 (66.7%) had tumor localization in the left colon, and 132 (55.7%) patients underwent CAPOX as adjuvant chemotherapy. Of the entire patient population, 116 (48.9%) were administered a 3-month treatment regimen, while 121 (51.1%) were administered a 6-month treatment regimen. Moreover, 84 patients were analyzed for VDR and TLR gene polymorphisms. Regarding VDRs, 10 (11.9%), 7 (8.2%), 5 (6.0%), and 17 (20.2%) patients presented TaqI, ApaI, FokI, and BsmI homozygous phenotypes, respectively. Moreover, regarding TLRs, 48 (57.1%), 38 (46.4%), 38 (46.4%), 37 (44.0%), and 37 (44.0%) patients presented TLR2 196-to-174, TLR4—Asp299Gly, TLR4—Thr399Ile), TLR9—T1237C and TLR9—T1486C homozygous phenotype, respectively.

3.2. Annotated variants for each position

The KEGG CRC panel detected 85,871 uniquely annotated variants. Of these, 602 were detected in exonic positions, including 25 splice variants. The remaining variants were non-coding, with 81,555 intronic variants being the most common, followed by 2,184 UTR variants, 788 downstream variants, and 742 upstream variants.

3.3. Identification of mutated genes

Mutated genes within the KEGG CRC gene panel for each patient were identified. On average, the patients exhibited eight mutated genes (range, 2–21 genes). The frequencies of mutations in each gene, specifically in exons and splicing sites, are presented in Table 4 and Figure 2.

From this analysis, it was observed that certain groups of patients had a higher mutation frequency in specific genes (Table 5). In brief, males had a significantly higher frequency of mutations in the JUN and MAPK3 genes than females (p=0.05, p=0.05, respectively). In terms of age groups, patients below 70 years of age had a higher frequency of mutations in TGFBR1 than those ≥70 years of age (p=0.012). Similarly, patients between 51-70 years old had more frequent mutations in BAD (p<0.001), RAC (p=0.016), AKT, AKT2, AKT3, APC, APPL1, AXIN1, AXIN2, BIRC5, DCC, GSK3B, KRAS, MAPK1, MAPK8, MAPK9, MAPK10, MLH1, MSH6, PΙK3CA, PIK3R1, PIK3R2, PIK3R5, RAF1, RALGDS, SMAD2, SMAD3, TCF7L2, TGFB1 and TGFB2 genes ( p=0.037). Moreover, mutation rates in ARAF, MAPK10, CASP, TCF7, and TGFΒ3 genes were significantly higher in patients relapsed after adjuvant treatment (p=0.027, p=0.044, p=0.003, and p=0.037, respectively).

Subsequently, it was demonstrated that patients with tumors located in the transverse colon, homozygous for mutated VDR alleles (TaqI, ApaI, FokI, BsmI) and homozygous for mutated TLR9 alleles (T1237C and T1486C), had mutations in genes that are mainly involved in the apoptosis, PIK3-AKT, Wnt and MAPK signaling pathways (Table 6).

3.4. Clinical outcome based on molecular profile and patients’ characteristics

Regarding disease-free survival (DFS), it was demonstrated that patients with ARAF mutations had a significantly shorter DFS (74 months, 95% CI:29.3 – 154.9 months) compared to those with wild-type ARAF mutations (133 months, 95% CI:101 – 138 months, p=0.017) (Figure 3A). Similarly, patients with MAPK10 mutations exhibit a significantly shorter DFS compared to those wild-type (12.5 months, 95% CI:0.0 – 29 months vs 108 months, 95% CI:101 – 114 months; p<0.001) (Figure 3B).

Similarly, it was demonstrated that patients with right-sided tumors experienced a significantly shorter overall survival (OS) compared to patients with left-sided tumors (92.1 months, 95% CI:82.5 – 122 months vs 111.3 months, 95% CI:104 – 135 months; p=0.011) (Figure 4A). Moreover, relapsed patients demonstrated a significantly shorter OS compared to those non-relapsed (81.1 months, 95% CI:70.4 – 118 months vs 104.3 months, 95% CI:93.9 – 130 months; p=0.008) (Figure 4Β). Moreover, patients with AKT1, APC2, ARAF, BAD, MAPK10, RAC3, RHOA, TGFB2 and TGFB3 mutations exhibited a significantly shorter OS compared to wild-type patients (68.9 vs 107.9 months, p=0.03; 89.7 vs 109.4 months, p=0.001; 43.3 vs 109.4 months, p<0.001; 34 vs 107.7 months, p=0.011; 19.3 vs 108.6, p>0.001; 55.6 vs 109, p<0.001; 45.2 vs 108.5 months, p=0.004; 69.5 vs 109.7 months, p=0.032 και 30.5 vs 108.1 months p<0.001, respectively) (Figures 4C-K). Finally, patients with MSH6 gene mutations had a significantly longer OS compared to those wild-type (120.7 months, 95% CI:111.3 – 130.1 months vs 100.9 months, 95% CI:93.7 – 108.1 108.1 months; p=0.008) (Figure 4L).

3.5. Univariate and multivariate Cox-regression analysis

Univariate analysis revealed that tumor localization in the right colon, and ARAF and MAPK10 mutations were associated with reduced DFS (Table 7). Multivariate analysis confirmed that tumor localization and ARAF and MAPK10 mutations were independent predictive factors of reduced DFS (HR=2.1; 95% CI:1.1-4.0; p=0.019; HR=3.9 ; 95% CI:1.2-13.1; p=0.027; HR=49; 95% CI:9.8-244.1; p<0.001 (Table 7).

Similarly, right-sided tumors and AKT1, APC2, ARAF, BAD, MAPK10, RAC3, RHOA, TGFB2, and TGFB3 were associated with an increased risk of shorter OS. In contrast, MSH6 mutations were demonstrated to be a good prognostic factor, as they were associated with a reduced risk for shorter OS. Multivariate analysis revealed that right-sided tumors and RAC3 and RHOA gene mutations emerged as independent predictors of reduced OS (HR=2.2; 95% CI:1.0-4.5; p=0.043; HR=3.5; 95% CI:1.1-10.7; p=0.029 and HR=9.5; 95% CI:1.9-47.7; p=0.006 (Table 7).

4. Discussion

Despite the potential benefits of presymptomatic screening and available treatments, CRC continues to be a significant public health concern[16]. Understanding the processes involved in CRC development and progression can help to identify new targets for treatment. Structural and functional changes in the DNA can offer vital insights into patient management[17,18]. As the normal colonic epithelium transforms into cancerous tissue, various mutations occur, leading to adenoma formation[19,20,21,22,23,24,25,26]. Extensive cancer cell proliferation through the RAS-RAF-MEK-ERK signaling pathway drives carcinogenesis, tumor invasion, and metastasis[27]. Moreover, the immune responses to cancer cells differ among patients with mutations[28,29,30,31,32,33,34].

The objective of this study was to analyze genetic changes in surgical samples from patients with stage III CRC. The study included 237 patients, and the WES and KEGG gene panel for CRC revealed 59 mutated genes belonging to 11 distinct signaling pathways. Of these, mutations in APC2, BRAF, MAPK10, MLH1, MSH6, RHOA, TGFβ, and TGFβ2 have been linked to a significant impact on patient survival. APC, TP53, KRAS, and MSH3 were the most commonly observed mutations in this study.

APC encodes an anti-tumor protein that competes with the Wnt signaling pathway and is involved in cell migration, adhesion, and apoptosis. APC mutations are responsible for familial adenomatous polyposis (FAP), an autosomal dominant precancerous disease that typically leads to malignancy. APC mutations are commonly observed in CRC cases[35]. Similarly, APC2 mutations, which are directly associated with APC’s tumor-suppressive function[36], have been linked to worse prognosis in CRC patients[37,38]. This study confirms that APC2 mutations in patients with stage III CRC are associated with lower overall survival but do not represent an independent prognostic factor. TP53 encodes an anti-tumor protein that regulates the expression of target genes, leading to cell cycle arrest, apoptosis, senescence, DNA repair, or metabolic changes. Similar to APC, TP53 are frequently observed in CRC cases[35]. Furthermore, mutations in the APC2 gene, which is directly linked to APC’s tumor-suppressive function[36], are also associated with worse prognosis in CRC patients[37,39]. This study confirms that while APC2 mutations in stage III CRC patients are linked to lower overall survival, they do not represent an independent prognostic factor. Various human cancers, including approximately 60% of CRC, are associated with mutations in the TP53 gene[40,41]. Prior studies have shown that mutations in TP53 resulting in the loss of its transcriptional activity, can lead to uncontrolled cellular proliferation in multiple organs, including the colon[42]. Similarly, KRAS mutations are the primary indicators of gastrointestinal cancers and are found in approximately 40% of patients with CRC (stage II-IV)[43]. They serve as negative prognostic factors for carcinogenesis and anti-EGFR therapy[44] because intracellular signal interruption leads to uncontrolled cellular proliferation and cancer. MSH3 mutations have been mainly linked to endometrial cancer, but there are reports of its relationship with inflammatory processes, such as ulcerative colitis and Crohn’s disease, which considerably increase the likelihood of CRC development[45,46]. MSH3-associated CRC seems to follow the classic APC pathway, as patients with adenomas and CRC carrying APC mutations showed MSH3 deficiency[47], as confirmed in this study. In addition to the common mutations detected in the patient group, mutations in AKT1, ARAF, BAD, MAPK10, RAC3, RHOA, TGFB2, and TGFB3 were associated with worse prognosis in this study. Furthermore, mutations in ARAF and MAPK10 were identified as independent prognostic factors for DFS, whereas mutations in RAC3 and RHOA were identified as independent prognostic factors for decreased OS.

This study sheds light on the association between mutations in genes involved in signaling pathways such as PI3K-Akt, MAPK, apoptosis, and CRC. To the best of our knowledge, this is the first report of its kind in the literature. The reactivation of embryonic self-renewal pathways, such as Hedgehog, Notch, and TGFβ/Stat3, is characteristic of most tumors, including CRC. The Wnt pathway is also essential in most CRC. Targeting embryonic pathways directly is likely to be more effective against stem and differentiated cancer cells [48,49,50]. Tumors that are addicted to increased regulated activity of the embryonic pathway, in combination with high tumor heterogeneity, may be more vulnerable to such therapies [51,52,53]. Patients with VDR polymorphisms had concurrent mutations in genes involved in cell cycle, apoptosis, PI3K-Akt, WNT, MAPK, ErbB, MSI, and RAS. Similarly, TLR9 polymorphisms were associated with mutations in genes involved in apoptotic signaling pathways, PI3K-Akt, and Wnt. Previous studies from our group have demonstrated that higher detection of TLR and VDR polymorphisms in CRC patients, especially advanced-stage patients, highlights the role of these polymorphisms in carcinogenesis, disease progression, and ultimately, patient survival[9,10,54]. Regarding DFS, tumors in the sigmoid or right colon and mutations in the ARAF and/or MAPK10 genes were associated with shorter DFS, a fact that has been confirmed in previous studies[55,56,57]. To our knowledge, this is the first study to highlight the role of ARAF and MAPK10 mutations as independent prognostic factors for decreased DFS.

The observation of statistically lower OS in patients with right colon tumors and gene mutations has been confirmed in the literature. Borakati et al. conducted A retrospective study and found that tumors in the right colon were independent prognostic factors for reduced OS after hepatic metastasectomy, regardless of the higher rates of liver metastases and larger metastases in the left colon[58]. Patients with mutations in genes, such as AKT1, APC2, ARAF, BAD, MAPK10, RAC3, RHOA, TGFB2, and TGFB3 had significantly reduced OS, as reported in other studies that also linked APC2, RHOA, and TGFB mutations to worse prognosis[37,38,59]. Conversely, studies have shown that mutations in MSH6 are associated with a lower risk of developing CRC, and patients with such mutations have a milder clinical presentation[60,61]. In the present study, patients with MSH6 mutations had a significantly longer OS, confirming MSH6 mutations are good prognostic factors. Concurrent mutations (co-mutations) are a significant factor that have been minimally investigated in CRC. Studies in patients with non-small cell lung cancer have shown distinct biological behavior and prognosis in KRAS/LKB1, KRAS/TP53, or KRAS/p16 mutated tumors[62]. Additionally, our group has previously reported the importance of evaluating the loss of LKB1 through immunohistochemistry in early stage CRC, particularly in BRAF^V600E mutated tumors[63]. In the present study, several concurrent mutations were detected in patients, but no correlation was found with clinical/pathological characteristics or patient prognosis.

5. Conclusions

In conclusion, molecular characterization of cancer cells can enhance our understanding of the biological progression of this disease[64,65]. The findings of this study suggest that mutations are promising prognostic biomarkers. As personalized medicine has become the primary mode of therapy, knowledge of the precise mutation status of patients with CRC can lead to better therapeutic choices. However, further research is necessary with a larger patient cohort and international collaborations to confirm the correlation between patients’ molecular profiles, clinicopathological and epidemiological characteristics, and outcomes. Such research is expected to contribute to more precise clinical decision-making, personalized and improved care, and reduced toxicity of treatment, costs to patients, and burden on health systems.