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Impact of a haplotype (composed of the APC, KRAS, and TP53 genes) on colorectal adenocarcinoma differentiation and patient prognosis

  • Author Footnotes
    1 Equal contributors.
    Xinyu Peng
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    Department of Gastrointestinal Surgery,Affiliated Hospital of Hebei University, No.212 Yuhua East Road, Baoding City, Hebei Province, PR China 071000
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    1 Equal contributors.
    Tao Zhang
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    1 Equal contributors.
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    Department of Gastrointestinal Surgery,Affiliated Hospital of Hebei University, No.212 Yuhua East Road, Baoding City, Hebei Province, PR China 071000
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  • Xiongjie Jia
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    Department of Gastrointestinal Surgery,Affiliated Hospital of Hebei University, No.212 Yuhua East Road, Baoding City, Hebei Province, PR China 071000
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  • Tong Wang
    Affiliations
    General Surgery Department, Laiyuan County Hospital, No. 299, Zhongxin Road, Laiyuan County, Baoding City, Hebei Province, PR China 074399
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  • Hengxue Lin
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    Department of Gastrointestinal Surgery,Affiliated Hospital of Hebei University, No.212 Yuhua East Road, Baoding City, Hebei Province, PR China 071000
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  • Gang Li
    Affiliations
    Department of Gastrointestinal Surgery,Affiliated Hospital of Hebei University, No.212 Yuhua East Road, Baoding City, Hebei Province, PR China 071000
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  • Riheng Li
    Correspondence
    Correspondence author at: Department of Gastrointestinal Surgery, Affiliated Hospital of Hebei University, Baoding 071000, Hebei province, China.
    Affiliations
    Department of Gastrointestinal Surgery,Affiliated Hospital of Hebei University, No.212 Yuhua East Road, Baoding City, Hebei Province, PR China 071000
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  • Aimin Zhang
    Correspondence
    Correspondence author at: Department of Gastrointestinal Surgery, Affiliated Hospital of Hebei University, Baoding 071000, Hebei province, China.
    Affiliations
    Department of Gastrointestinal Surgery,Affiliated Hospital of Hebei University, No.212 Yuhua East Road, Baoding City, Hebei Province, PR China 071000
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Open AccessPublished:October 13, 2022DOI:https://doi.org/10.1016/j.cancergen.2022.10.002

      Highlights

      • The APC, KRAS, and TP53 gene mutations predicted the outcome of XELOX treatment.
      • The APC, KRAS, and TP53 gene mutations are correlated with the prognosis of CRC.
      • A specific sequential mutations in APC, KRAS, and TP53 always co-occur in the same samples
      • A specific sequential mutations in APC, KRAS, and TP53 can assemble a haplotype
      • The indicated haplotype are correlated with the differentiation of CRC

      Abstract

      Background

      Many types of gene mutation are associated with the drug resistance of cancer cells. XELOX is a new and efficient surgical adjuvant chemotherapy for colorectal adenocarcinoma. However, drug-resistant related genetic mutations associated with this treatment remain unknown.

      Methods

      Next-generation sequencing (NGS) was performed on 36 colorectal cancer patients to identify mutations among patients with residual tumors following preoperative chemotherapy. Enrichment and prognosis of these mutations were evaluated in a TCGA cohort. The pathology of cases with poor prognosis-related mutations was also determined.

      Results

      A sequence of SNPs associated with the APC, KRAS, and TP53 genes in 13 of 19 subjects with residual tumors after preoperative chemotherapy was identified. Using survival analysis data from 317 cases in the TCGA database, a prognosis-related haplotype composed of SNPs from APC, KRAS, and TP53 was assembled. Colorectal cancer patients with these mutations had a lower 5-year tumor-specific survival rate than those without (p < 0.05). Most patients with these mutations were at a higher clinical stage (III-IV) of disease. Enrolled subjects with the identified haplotype tended to have poor cancer cell differentiation.

      Conclusions

      The prognosis-related haplotype can be used as a marker of drug resistance and prognosis in colorectal cancer patients after preoperative chemotherapy.

      Keywords

      Introduction

      Colorectal cancer (CRC) is one of the leading causes of cancer-related mortality in both men and women worldwide. The survival rate of patients with metastatic CRC (mCRC) remains at ≤10% [
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      Colorectal cancer statistics, 2017.
      ]. Patients with high-grade (stages III or IV) CRC have an elevated risk of recurrence and are typically treated with both surgery and adjuvant chemotherapy [
      • Mizushima T
      • Ikeda M
      • Kato T
      • Ikeda A
      • Nishimura J
      • Hata T
      • et al.
      Postoperative XELOX therapy for patients with curatively resected high-risk stage II and stage III rectal cancer without preoperative chemoradiation: a prospective, multicenter, open-label, single-arm phase II study.
      ]. Several chemo-reagent-based therapies for CRC have been developed, including CAP, 5-FU, XELOX, and FOLFOX, and relevant data and treatment outcomes are gaining more attention [
      • Kuebler JP
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      Oxaliplatin combined with weekly bolus fluorouracil and leucovorin as surgical adjuvant chemotherapy for stage II and III colon cancer: results from NSABP C-07.
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      Capecitabine plus oxaliplatin compared with fluorouracil and folinic acid as adjuvant therapy for stage III colon cancer.
      ,
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      Multicenter International Study of Oxaliplatin/5-Fluorouracil/Leucovorin in the Adjuvant Treatment of Colon Cancer I. Oxaliplatin, fluorouracil, and leucovorin as adjuvant treatment for colon cancer.
      ]. XELOX is a particularly convenient chemotherapeutic agent with similar efficacy to FOLFOX. However, the mechanism of resistance to this drug and its impact on disease outcomes remain unclear [
      • Mizushima T
      • Ikeda M
      • Kato T
      • Ikeda A
      • Nishimura J
      • Hata T
      • et al.
      Postoperative XELOX therapy for patients with curatively resected high-risk stage II and stage III rectal cancer without preoperative chemoradiation: a prospective, multicenter, open-label, single-arm phase II study.
      ,
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      Does adjuvant fluoropyrimidine-based chemotherapy provide a benefit for patients with resected rectal cancer who have already received neoadjuvant radiochemotherapy? A systematic review of randomized trials.
      ,
      • Levine AJ
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      The roles of initiating Truncal mutations in human cancers: the order of mutations and tumor cell type matters.
      ].
      CRC chemotherapy resistance-related mutations have been identified in many genes, including APC, EFGR, KRAS, TP53, BRAF, and ERCC2 [
      • Levine AJ
      • Jenkins NA
      • Copeland NG.
      The roles of initiating Truncal mutations in human cancers: the order of mutations and tumor cell type matters.
      ,
      • Kent DG
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      Order matters: the order of somatic mutations influences cancer evolution.
      ]. Mutations in APC, KRAS, and TP53 are shown to co-occur in the same samples [
      • Schell MJ
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      A multigene mutation classification of 468 colorectal cancers reveals a prognostic role for APC.
      ]. APC is a large scaffold protein that is ubiquitously expressed in several tissues, including the brain and gastrointestinal tract [
      • Wachsmannova L
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      Novel strategies for comprehensive mutation screening of the APC gene.
      ], and serves as a key regulator of the oncogenic protein, beta-catenin, in the Wnt signaling pathway [
      • Cheng X
      • Xu X
      • Chen D
      • Zhao F
      • Wang W
      Therapeutic potential of targeting the Wnt/β-catenin signaling pathway in colorectal cancer.
      ]. TP53 is a tumor suppressor gene with a spectrum of mutations in CRC samples [
      • Liebl MC
      • Hofmann TG.
      The role of p53 signaling in colorectal cancer.
      ]. KRAS is defined as a ‘switch’ in cancer cell signal transduction [
      • Janssen KP
      • Alberici P
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      • Franken P
      • et al.
      APC and oncogenic KRAS are synergistic in enhancing Wnt signaling in intestinal tumor formation and progression.
      ] that regulates malignant behavior. A series of KRAS mutations serve as prognosis markers for Bevacizumab resistance [
      • Wong CC
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      • Wu JL
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      • Qian Y
      • et al.
      In colorectal cancer cells with mutant KRAS, SLC25A22-mediated glutaminolysis reduces DNA demethylation to increase WNT signaling, stemness, and drug resistance.
      ]. Most of these mutations were reported in 5-FU or other reagent-treated samples but the combined effect remains unknown. This study sought to investigate the combined effect of APC, KRAS, and TP53 mutations on XELOX-based chemo-resistance in CRC.

      Materials and methods

      Clinical sample collection

      A total of 36 subjects (17 females and 19 males, 51–83 years of age) who had received a new CRC diagnosis based on pathology and medical imaging results (MRI) and completed XELOX-based preoperative treatment were enrolled in this study. All patients were admitted to the Affiliated Hospital of Hebei University from August 2018 to March 2019. This study received approval from the hospital review board. Patients with recurrent CRC, receipt of other treatments prior to admission, and the presence of other cancers or tumors of unknown origin were excluded. Survival follow-up data were included in the study. All patients were fully educated about the study and signed the informed consent. A total of 2 μg of genomic DNA from each patient was extracted and degraded into 300–500 bp fragments using the Covaris S220 single tube sonicator (Life Technologies, Carlsbad, CA). Targeted NGS of 24 high-frequency mutant genes in tumor samples before and after XELOX-based treatment is well documented. The target genes were enriched using a custom-designed set of target gene enrichment RNA oligonucleotides for in-solution hybrid selection (Agilent Technologies, Santa Clara, CA). Specific oligonucleotide probes were designed against the 24 CRC susceptibility genes, which spanned their entire non-repetitive genomic region. All coding regions had an average coverage of >95% and an overall coverage of 43%. Libraries were prepared according to the manufacturers’ protocols (NEBNext® and Illumina®, San Diego, California, USA) and sequenced using HiSeq 2500 (Illumina) (PE=125). Q30 >85 was used as the threshold for data quality control evaluated using FastQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Alignment of the qualified data to the human reference genome (hg19, NCBI build GRCh37) was performed using the Burrows-Wheeler aligner (BWA) (http://bio-bwa.sourceforge.net).

      Polymorphism selection

      The HapMap SNP database (http://www.ncbi.nlm.nih.gov/) and SNP data (http://snpinfo.niehs.nih.gov/) were used to identify functional SNPs in APC, KRAS, and TP53. The selection criteria included a minor allele frequency of ≥5% and a linkage disequilibrium (LD) coefficient r2 of <0.8. All SNPs were associated with CRC.

      TCGA data preparation

      Gene mutation data from 317 CRC samples with at least one mutation in the APC, KRAS, or TP53 genes, were downloaded from TCGA database. The annotated germline SNPs were screened out before downloading. CRC patient data were included if the diagnosis was stage III-IV according to the 7th edition of the AJCC Cancer Staging Manual. Corresponding CRC patient clinical information was obtained from TCGA database according to TCGA publication guidelines and data access policies. Patient data were excluded if there was evidence of recurrent cancer, therapies performed before admission, the presence of other CRC clinical stages, or additional clinical disorders. The top 25 mutated sites on the three genes were analyzed using the R “maftools” package.

      Haplotype analysis

      The assembled haplotype was estimated in the CRC patient cohort by case status. The R “haplo.stats” package was used to estimate posterior probabilities of haplotypes. STATA's haplologit command was used to model the association between haplotypes and case status as described previously [
      • Shih PC
      • Mei KC.
      Role of STAT3 signaling transduction pathways in cancer stem cell-associated chemoresistance.
      ]. Patients from TCGA who carried the SNP haplotype were included in subsequent experiments.

      H&E staining

      Samples were obtained from the patients (n = 36) who received surgery after XELOX-based preoperative treatment. Tumor localization was completed under the guidance of an MRI. Both CRC and para cancer tissues from each patient were collected. Histopathology was performed to identify all tissue samples. Tissue sections were dried at room temperature, fixed at room temperature for 30 s, dewaxed with xylene, and rehydrated in a gradient ethanol-water solution. The sections were washed in 1x PBS for 2 s, stained with hematoxylin (60℃) for 60 s, and immersed in PBS for 10 s, 1% hydrochloric acid alcohol differentiation solution for 3 s, and PBS for an additional 2 s. The sections were then subjected to eosin staining for 3 min, washed in PBS for 2 s, dehydrated with 70%, 80%, and 95% ethanol for 5 min each, and xylene coated 3 times for 5 min. Finally, the sections were transparently sealed with gum, and tissue morphology and structure were observed under a microscope (BX63, Olympus, Japan)

      Statistics

      R packages were used for bioinformatic analysis. Kaplan-Meier curves were used to assess the cumulative probability of CRC. Survival curves were created using K-M plotter and compared using the log-rank test. One-way ANOVA combined with the Tukey test was used to compare multiple groups. Chi-square analysis was used to determine the correlation between the frequency of SNPs or haplotypes in CRC tissues and patient clinical data. Univariate and multivariate analyses were performed using the Cox proportional hazards model to investigate the influence of genotypes on the risk of recurrence. The model was also adjusted for age, gender, and other related factors. The χ2 test was used to evaluate differences in gene mutation frequency between groups. p < 0.05 was considered statistically significant.

      Results

      NGS results

      A target NGS panel of high-frequency mutant genes was used to identify gene mutations in CRC patients before preoperative chemotherapy and after surgery. Postoperative examination revealed no residual tumors in 17 of 36 patients.The Mutations of preoperative tumor samples were compared between patients with residual tumors and those without (Supplementary Table 1). Findings indicated that mutations in the APC, KRAS, and TP53 genes were more frequent in patients with residual tumors (Fig 1A). Few KRAS mutations were detected in patients without residual tumors (Fig 1B). Cox analysis was used to evaluate the association between patient clinical characteristics and the presence of mutations. Multivariate results showed that the prevalence of APC, KRAS, and TP53 mutations was significantly higher among patients with AJCC stage III/IV (p = 0.008) and TN stage III/IV (p = 0.015, p = 0.004) (Table 1).
      Fig 1
      Fig. 1Genomic variation of the target gene in the clinical subjects.
      (A)The total mutation rates of the APC, KRAS, and TP53 genes in subjects with and without residual tumors. (B) Individual APC, KRAS, and TP53 mutation rates in subjects with and without residual tumors. **indicates values with a p-value <0.05.
      Table 1. clinical-pathological characteristic in colorectal adenocarcinoma patients and their association with occurrence of APC, KRAS or Tp53 mutation
      VariableH RCl (95%)P
      Univariate analysis (n= 36)
      Age
      <601.000
      >601.0831.015–2.6520.141
      Gender
      male1.000
      female0.8760.247–1.5320.116
      T stage
      Tis,T1–21.000
      T3–42.1171.085–3.1810.015*
      N stage
      N01.000
      N1–32.1891.568–3.0810.004*
      M stage
      M01.000
      M11.4351.232–2.8790.253
      Clinical stage
      I–II1.000
      III–IV1.8541.012–3.7710.008*
      HR indicate the Hazard ratio; CI indicate the confident interval

      Mutation identification and enrichment analysis in TCGA data

      Mutation enrichment analysis was used to identify chemoresistant related SNPs in TCGA data. A waterfall plot showed the high frequency of CRC patients with APC, KRAS, and TP53 mutations (Fig. 2A). A total of 46,382 SNPs were identified. The top 10 genes with identified mutations were APC, TP53, KRAS, TTN, PIK3CA, MUC16, SYNE1, FAT4, ZFHX4, and DNAH5. The TCGA cohort was divided into two subgroups. Group I included co-occurrence mutations in APC, KRAS, and TP53 while Group II included those with only one mutation site in APC, KRAS, or TP53. Group I had a significantly lower 5-year survival rate than Group II (p = 0.0285, Fig. 2B-E). Particular tumor driver genes, including SYNE1, MUC16, ZFHX4, and DNAH5, also had a higher mutation rate in Group I (Fig. 2F-G). This finding indicates that co-occurrent mutations in APC, KRAS, and TP53 may predict poor CRC patient prognosis.
      Fig 2
      Fig. 2Mutation Identification and Enrichment Analysis using TCGA data.
      (A) A waterfall plot of the top 10 mutated genes in TCGA CRC cohort that carries at least one APC, KRAS, or TP53 mutation. (B-E) The correlation of Group I, APC, KRAS, or TP53 mutations with CRC patient survival. COX analysis was performed to get the adjusted HR. (Group I:p = 0.0285; APC:p = 0.0816; TP53:p = 0.0267; KRAS:p = 0.0767).(F) TCGA cohort subjects with the top 10 mutated genes. (G) The mean mutation rate of the top 10 mutated genes in TCGA cohort.

      The combined effect of SNPs on CRC prognosis

      Using the mutation rate in TCGA dataset, the top 10 SNPs were selected (Table 2). TP53 SNP (CC/rs28934578), KRAS SNP (CG or CT/rs121913529), and APC SNP (CT/rs121913332) were shown to cooccur in the same CRC sample and assemble as a haplotype (Table 3). However, the significantly lower 5-year overall survival rate (OR=0.43) was only observed in patients with CG/rs121913529/KRAS (Fig 3A-C). To investigate the effect of these mutations on CRC prognosis, the 5-year survival rate of 102 patients with the combined haplotype-1 and 215 subjects without the haplotype was assessed (Fig 3D). Patients with haplotype-1 had a significantly higher HR index than those without the haplotype for survival time (HR=0.4487, 95% CI: 0.29–1.0; HR= 1.3725, 95% CI: 0.48–2.114). The haplotype was detected in 15 subjects (78%) with residual tumors and eight subjects (15%) without (Fig 3E, p < 0.05).
      Table 2The Top10 mutational SNPs in the TCGA dataset
      SNPscount
      rs121913529|KRAS86
      rs104886003|PIK3CA33
      rs112445441|KRAS27
      rs28934578|TP5325
      rs121913332|APC24
      rs121913530|KRAS18
      rs587781392|APC15
      rs121913333|APC15
      rs764719749|ACVR2A15
      rs113488022|BRAF14
      Table 3The top three coefficient haplotypes in this study
      HaplotypeAlternative nuclei acids
      The logistic regression model (multivariate regression) indicates a significant interaction term showing that the effect of SNPs of and vice versa.
      Coefficient(95% CI)
      Positive casesPositive ratio
      Haplotype-1CC/rs28934578;CT/rs121913332; CG/rs1219135290.86610232.2%
      Haplotype-2CC/rs28934578;CT/rs121913332;0.7128727.4%
      Haplotype-3CC/rs28934578;CT/rs121913332;CT/rs1219135290.6686219.5%
      low asterisk The logistic regression model (multivariate regression) indicates a significant interaction term showing that the effect of SNPs of and vice versa.
      Fig 3
      Fig. 3Combined effect of SNPs on CRC prognosis.
      (A-C) The Kaplan-Meier survival curve of subjects with different rs28934578/TP53, rs121913332/APC, and rs121913529/KRAS genotypes, respectively. CC/rs28934578, CT/rs121913332, and CG/ rs121913529 were associated with a poorer prognosis than other CRC genotypes. Only CG/rs121913529/KRAS represented a statistically significant difference (p = 0.278, p = 0.1837, and p = 0.0357). (D) The Kaplan-Meier survival curve of subjects with the haplotype (assembled from CC/rs28934578, CT/rs121913332, and CG/ rs121913529) and those without (p = 0.048). (E) The ratio of subjects with the haplotype who had residual tumors and those who did not (**p < 0.05).

      Relationship between clinical features and the haplotype

      To investigate the potential relationship between clinical features and the KRAS SNP (CG or CT/rs121913529), COX analysis was performed using TCGA data. The results showed that stage III-IV CRC patients had a significantly higher likelihood of having the haplotype (CC/rs28934578, CG or CT/rs121913529 and CT/rs121913332; Fig 4A-B, p < 0.05). At the same time, the haplotype (with CG/rs121913529, KRAS) was more frequently detected in the poorly differentiated CRC patient group (Fig 4B, p<0.05). The gene expression spectrum of CRC patients with the haplotype was also explored. The three KEGG enrichment scores indicated that these gene-related pathways were significantly enriched in cytokine-cytokine receptor interaction, immuno-response, and apoptosis pathways (Fig. 4C). These findings indicate that some immune cell types may be enriched in these patients.
      Fig 4
      Fig. 4Relationship between clinical features and the haplotype.
      Forest plot of the association between patient clinical characteristics and different genotypes of d CG/CT/rs121913529(A) and d CG/rs121913529. (B) The hazard ratio (HR) and 95% CI. (C) KEGG enrichment analysis of related mutations from the selected TCGA cohort. **The variable with a p-value < 0.05.

      The haplotype is associated with the CRC differentiation

      These results indicated that the mutation haplotype may correlate with poorer cancer cell differentiation. To explore this, the differentiation status of tumor tissues from CRC patients who underwent surgical resection was assessed. H&E staining results revealed poorer differentiation in patients with the haplotype (Fig. 5A, p < 0.05). Thirteen patients were found in both the haplotype and the residual tumor groups (Fig. 5B). The main histological characteristics of poorly differentiated CRC included the presence of small and closely arranged tumor cells and evidence of tumor cells falling off in clusters and forming a mulberry fruit-like structure (Fig. 5C).
      Fig 5
      Fig. 5The correlation between the haplotype and the differentiation of CRC.
      (A) The ratio of subjects with poorly differentiated tumor cells who had the haplotype and those who did not (**p < 0.05). (B) Venn diagram of 13 subjects who had both the haplotype and residual tumors. (C) H&E staining was used to evaluate the presence of histological characteristics of poorly differentiated CRC. H&E: hematoxylin and eosin. Scale bar=100 μM.

      Discussion

      Preoperative chemotherapy is an effective method for improving high-stage CRC patient outcomes [
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      ]. KRAS mutations have been associated with many tumor types and are shown to correlate with chemoresistance, brain metastasis, and vascular formation [
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      ]. Sequential or cooccurring somatic mutations play an important role in CRC-related chemoresistance [
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      ]. Compared to APC mutations, a different sequence of RAS and TP53 somatic mutations was more directly correlated with a tumor phenotype [
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      ]. In a study of Oxaliplatin-based combination chemotherapy, sequential KRAS and APC somatic mutations were associated with a significantly reduced 4-year recurrence-free survival (RFS) probability [
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      ]. The current study explored how the sequential order of APC, TP53, and KRAS somatic mutations contribute to cell differentiation.
      The adjuvant oxaliplatin plus capecitabine (XELOX) is recommended for use both before and after curative resection of advanced CRC [
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      • Hata T
      • et al.
      Postoperative XELOX therapy for patients with curatively resected high-risk stage II and stage III rectal cancer without preoperative chemoradiation: a prospective, multicenter, open-label, single-arm phase II study.
      ]. Preoperative XELOX plus bevacizumab is commonly used to treat high-stage CRC [
      • Haller DG
      • Tabernero J
      • Maroun J
      • de Braud F
      • Price T
      • Van Cutsem E
      • et al.
      Capecitabine plus oxaliplatin compared with fluorouracil and folinic acid as adjuvant therapy for stage III colon cancer.
      ] and the reported pathologic complete response rate is 4.3–13% [
      • Mizushima T
      • Ikeda M
      • Kato T
      • Ikeda A
      • Nishimura J
      • Hata T
      • et al.
      Postoperative XELOX therapy for patients with curatively resected high-risk stage II and stage III rectal cancer without preoperative chemoradiation: a prospective, multicenter, open-label, single-arm phase II study.
      ]. However, there is an absence of effective biomarkers to predict the XELOX-specific response in clinical practice. The current study identified a new haplotype and evaluated its prognosis value using TCGA data. In another aspect, the patients in residual tumor groups without haplotype also carry either individual KRAS, APC or TP53 mutations. But there was no any specific mutations significantly enriched in the residual tumor groups. We did not find any significant clinical or pathology correlation of these sparsely mutations. This haplotype may contribute to the infiltration of specific immune cells and correlate with poor cancer cell differentiation. A limitation of this study is that it involved a relatively small patient cohort. Future studies are needed to evaluate the prognostic value of this haplotype in a larger and more ethnically diverse cohort. In addition, the cross-talk mechanism between cancer cells that carry this haplotype and immune cells in the microenvironment requires further exploration.

      Conclusion

      The current study identified the clinical significance of a haplotype composed of an SNP sequence in the APC, TP53, and KRAS genes associated with CRC. A new mutational gene combination was identified in a patient cohort that received preoperative XELOX therapy. The haplotype composed of these mutant genes was associated with poor CRC-related outcomes. CRC patients with this haplotype were more likely to have poorly differentiated adenocarcinoma and to harbor residual tumor cells following treatment. Further studies are needed to assess the relationship between the haplotype and tumor recurrence by investigating recurrence in a larger cohort of patients with this mutant gene combination.

      Funding

      Not applicable.
      Consent for publication.
      Not applicable.

      Competing interests

      The authors declare that they have no competing interests.

      Ethics approval and consent to participate

      The present study was approved by the Ethics Committee of the Affiliated Hospital of Hebei University. The research was performed in accordance with the World Medical Association Declaration of Helsinki. All patients provided written informed consent prior to inclusion in the study.

      CRediT authorship contribution statement

      Xinyu Peng: Conceptualization, Methodology, Software, Writing – original draft. Tao Zhang: Conceptualization, Methodology, Visualization, Writing – original draft. Xiongjie Jia: Formal analysis, Visualization. Tong Wang: Formal analysis. Hengxue Lin: Investigation, Resources, Validation. Gang Li: Investigation, Resources, Validation. Riheng Li: Funding acquisition, Methodology, Project administration, Supervision, Writing – review & editing. Aimin Zhang: Funding acquisition, Project administration, Supervision, Writing – review & editing.

      Data Availability

      • Data will be made available on request.

      Declaration of competing interest

      ALL the authors declare that they have no competing interests.

      Appendix. Supplementary materials

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