Prognostic implications of tumor mutation burden in postoperative patients with colorectal cancer who received capecitabine-based adjuvant chemotherapy: a retrospective exploratory study

Prognostic implications of tumor mutation burden in postoperative patients with colorectal cancer who received capecitabine-based adjuvant chemotherapy: a retrospective exploratory study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prognostic implications of tumor mutation burden in postoperative patients with colorectal cancer who received capecitabine-based adjuvant chemotherapy: a retrospective exploratory study Yuanzeng Zhu, Han Zhang, Yang Zhou, Wenchao Chen, Di Lu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4357440/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: This study aimed to investigate the prognostic implications of tumor mutation burden (TMB) in patients with colorectal cancer (CRC) who underwent surgical resection and capecitabine-based adjuvant chemotherapy. Methods : A total of 82 patients with CRC who underwent surgical resection and capecitabine-based adjuvant chemotherapy were included in this study retrospectively. Tumor tissue specimens were collected for DNA extraction after surgical resection. Somatic mutation detection and TMB analysis were performed using next-generation sequencing (NGS) of tumor-related genes. The recurrence status of the patients was assessed in the hospital during the adjuvant chemotherapy period, and the long-term survival data of patients were obtained by telephone follow-up. The univariate analysis between TMB status and prognosis was carried out by Kaplan-Meier survival analysis and adjusted by multivariate Cox regression analysis subsequently. Results : The median follow-up period of this study was 5.3 years (range: 0.25-9.6 years). The median disease-free survival (DFS) of the 82 patients was 4.5 years, the median overall survival (OS) was 5.7 years. The results of NGS analysis demonstrated that the most common mutated somatic genes among the 82 patients were TP53 , APC , RAS , PIK3CA and EGFR , and the prevalence was 62.2%, 58.5%, 47.6%, 34.1% and 30.4%, respectively. Other somatic mutant genes were of relatively low frequency (<30%). Regarding the TMB analysis, the overall somatic mutation burden of the 82 patients was comparatively low [median: 3.9/Mb (range: 1.6-48.6/Mb)]. TMB status was divided into TMB-L (≤3.9/Mb) and TMB-H (>3.9/Mb) according to the median TMB threshold. And the patients with TMB-L and TMB-H were observed in 42 cases and 40 cases, respectively. Prognostic analysis according to TMB status demonstrated that the median OS of patients with TMB-L and TMB-H was 6.5 and 4.5 years, respectively ( P =0.009). Additionally, in order to adjust the confounding factors that might influence OS, a multivariate Cox regression analysis was introduced and the results exhibited that TMB status was an independent factor for OS (HR=0.71, P =0.011). Conclusion : TMB might be considered as a potential biomarker for predicting the prognosis of patients with CRC who underwent surgical resection and capecitabine-based adjuvant chemotherapy. Results of this study should be elucidated in large-scale prospective clinical trial subsequently. colorectal cancer adjuvant chemotherapy tumor mutation burden prognosis capecitabine Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Background Colorectal cancer (CRC) is one of the most common gastrointestinal tumors worldwide. Recently, the incidence of CRC in China is increasing rapidly. It is estimated that there are approximately 1800,000 new cases of CRC and 860,000 new deaths annually all over the world [ 1 ]. And there are approximately 560,000 new cases and 290,000 new deaths of CRC in China according to the recent epidemiological data [ 2 ]. Although surgical resection was the only way to cure patients with CRC for decades, approximately 25% of the patients were presented with clinical evidence of distant metastases at initial diagnosis, thus making the surgical resection unachievable [ 3 ]. Although immunotherapy made dramatical breakthroughs in a number of tumors recently [ 4 ], unfortunately, it had been proved that only patients with highly unstable microsatellites (MSI-H) were of the opportunity to benefit from immunotherapy in the field of metastatic CRC and majority of patients with metastatic CRC was unable to benefit from immunotherapy except the conventional chemoradiotherapy regimens [ 5 ]. Similarly, the promising research progress in early-stage and resected patients with CRC treatment was also limited relatively. Only IDEA trial was proved to be the significant breakthrough with clinical implications recently, which suggested that 3 months rather than 6 months of adjuvant chemotherapy was recommended for low-risk stage Ⅲ colon cancer [ 6 ]. Conclusions in IDEA trial helped to attenuate the unnecessary adverse reactions of chemotherapy, given that 6 months adjuvant chemotherapy regimens had been established to be the standard of care for stage Ⅲ patients with CRC for decades [ 7 ]. Furthermore, with the adequate development of the more sensitive detection techniques, ctDNA had established to be the potential predictive value in the recurrence risk assessment for patients with CRC after surgical resection [ 8 ]. Unfortunately, the predictive role regarding ctDNA for the intensity or duration of adjuvant chemotherapy among patients with CRC was still controversial and no standardized and unified criteria was available for the corresponding detection of ctDNA currently [ 9 ]. Therefore, it was still needed further exploration of ctDNA for clinical application extensively [ 10 ]. Capecitabine-based adjuvant chemotherapy had been established as the standard of care for the patients with CRC after surgical resection for decades, which improved 5-year survival rates of approximately 10% [ 11 ]. However, the benefits of capecitabine–based adjuvant chemotherapy for patients with stage Ⅱ CRC regarding reducing recurrence and prolonging survival remained controversial currently [ 12 ]. Furthermore, large individual differences were still observed in the clinical application of capecitabine-based adjuvant chemotherapy, which suggested that many factors might compromise the prognosis of this regimen clinically. Mismatch repair (MMR) status was a valuable predictor for the indication of adjuvant chemotherapy with fluorouracil-based regimen in stage II/III colon cancer [ 13 ]. Additionally, tumor mutation burden (TMB) was defined as the density of the distribution of non-synonymous mutations in the protein coding region, which was calculated by proportion between the total number of non-synonymous mutation in the protein coding region and the total length of the protein coding region and the unit was the number of mutations/MB [ 14 ]. Recent years had witnessed great progress of immune checkpoint inhibitors that brought new insight for the therapeutic strategy of anti-tumor therapy [ 15 ]. However, it should be noted that immune checkpoint inhibitors were only useful in a small number of the patients with the objective response rate (ORR) of approximately 20% [ 16 ], which suggested that the potential biomarkers such as PD-L1 expression and TMB were of urgent value to be explored for PD-1/PD-L1 checkpoint blockade therapy clinically [ 17 ]. Previous study indicated that higher TMB level was correlated with more neoantigens produced by tumor cells, thus contributing to the chances for T cell recognition, which might effectively enhance the probability of being recognized by the immune system [ 18 ]. And once PD-1 blockades activated the body's own anti-tumor immune response, the probability of killing tumor cells was higher and the efficacy of PD-1/PD-L1 blockades could be better eventually [ 19 ]. Additional evidences exhibited that TMB was also a potential biomarker to predict efficacy of immunotherapy in patients with CRC and TMB status was correlated with survival outcomes in patients with metastatic CRC receiving immune checkpoint inhibitors [ 20 ]. However, the relevance between TMB status and the prognosis of patients with postoperative CRC who received capecitabine-based adjuvant chemotherapy instead of immunotherapy was still unknown and if TMB status could be used as a potential biomarker for the surgical resection patients with CRC who received conventional adjuvant therapy was unclear currently [ 21 ]. Interestingly, a previous study initiated by DW Lee and colleagues reported the association between TMB status and the prognosis of patients with CRC receiving 5-FU combined with oxaliplatin as adjuvant treatment regimen and concluded that 10.7% of TMB-H patients conferred a superior 5-year RFS rate [ 22 ]. Additionally, AG Pai and colleagues explored the relationship between TMB status and the prognosis of patients with CRC receiving chemotherapy [ 23 ]. And the results demonstrated that there was no difference between TMB status and the prognosis of the patients. Consequently, the aim of this study was to identify the somatic gene mutation landscape and prognostic significance of TMB among patients with CRC who received surgical resection and capecitabine-based adjuvant chemotherapy. Methods Study design and eligibility criteria This study was designed as a retrospective study, patients with CRC who underwent surgical resection were collected and reviewed in the Department of Gastrointestinal Surgery of Henan Provincial People’s Hospital from June 2011 to December 2022. Baseline characteristics of the patients were obtained from the hospitals electronic medical record system. Patients who fulfilled the eligibility criteria were included in the study retrospectively. Inclusion criteria were: (1) aged ≥ 18 years; (2) ECOG performance status of 0–2 score; (3) normal cardiac function, renal function and bone marrow function to receive adjuvant chemotherapy appropriately; (4) pathological diagnosis of colon cancer or rectal cancer with histological type of adenocarcinoma and the patients received R0 surgical resection and postoperative adjuvant chemotherapy; (5) pathological staging of Ⅱ or Ⅲ. The exclusion criteria included: (1) patients failed to receive capecitabine-based adjuvant chemotherapy (capecitabine monotherapy or capecitabine-based regimens) after R0 resection; (2) cancer tissue specimens were not available for tumor genomic DNA extraction; (3) diagnosed of familial adenomatous polyposis or hereditary CRC; (4) concomitant with another tumor or serious diseases that might compromise the survival of the patients. Flow chart of present study was illustrated in Fig. 1 . Finally, a total of 82 patients with CRC patients met the eligibility criteria were enrolled in this study. The primary endpoint of present study was the prognostic significance between overall survival (OS) and tumor mutation burdern (TMB) status. The study was approved by the ethics committee of Henan Provincial People’s Hospital. Informed consent was signed by each enrolled patient in accordance with the recommendation of the declaration of Helsinki. Therapeutic regimens and follow up protocol All the patients with CRC included in this study were treated with capecitabine-based adjuvant chemotherapy. The chemotherapy regimens included capecitabine monotherapy and CAPEOX combination therapy. And the specific usage and dosage of capecitabine monotherapy was as follows: 3–4 weeks after surgical treatment, capecitabine, 1000–1250 mg/m 2 , twice daily, day 1–14, every 21 days as one cycle. Additionally, the detailed usage of CAPEOX regimen manifested as: capecitabine 1000mg/m 2 , twice daily, day 1–14, every 21 days as one cycle, combined with oxaliplatin, 80–130 mg/m 2 , iv. infusion, day 1. The adjuvant chemotherapy period was performed as 8 cycles or depended on the actual situation of the patients. Each patient was followed up at the onset of adjuvant chemotherapy administration. Initial follow-up was implemented when the patient received adjuvant chemotherapy in the hospital, where the baseline characteristics and the date of disease recurrence could be obtained through the electronic medical record system detailedly, and the recurrent status was determined by radiological assessment every three months and then every half year. Subsequent follow-up was performed mainly by telephone. Patients were followed up every three months for the date of recurrence and treatment after recurrence and the death status were mainly inquired. Furthermore, when a patient was recurrence or death, it must be confirmed by at least two research colleagues before it could be confirmed as a recurrence events or death events. Collection of tumor tissue specimen and sequencing analysis of targeted DNA Tumor tissue specimens of patients with CRC were collected after the surgical resection, and were stored in liquid nitrogen subsequently. Additionally, DNA was extracted using DNA FFPE tissue kit (QIAGEN, Valencia, CA) from the tumor tissue specimen and DNA concentration was measured by Qubitds DNA assay to make sure that A260/A280 was within the range of 1.8 to 2.0. Simultaneously, approximately 5 mL of peripheral blood was collected and incubated at room temperature for 2 hours. Then the supernatant was transferred to 15 mL centrifuge tubes and centrifuged to obtain the supernatant. Circulating cfDNA was recovered from 4 to 5 mL of plasma by using the QIAamp Circulating Nucleic Acid kit (Qiagen) accordingly. And then approximately 50 ng of cell free DNA is required for construction of an NGS library. Targeted DNA sequencing was performed when the DNA from tumor tissue specimens was extracted. DNA was profiled by using a capture-based targeted sequencing panel (Burning Rock Biotech. China) for sequencing analysis, which included part of the human genome region and 40 common tumor-related genes in colorectal cancer. 40 genes were derived from 5 important signal pathways that related to the occurrence and development of colorectal cancer, including WNT pathway, P53 pathway, RTK-RAS pathway, TGF-β pathway and PI3K pathway [ 24 ]. Probe hybridization and high-throughput sequencing were used to detect hot-spot mutation regions (exon, intron or promoter regions) of related genes, thus detecting the mutations, amplification and rearrangement (fusion) of genes relevant to cancer comprehensively and accurately. TMB detection analysis The specific methods of sequencing data analysis were reported previously [ 25 ]. TMB was defined as the number of substitutions or insertions or deletions of coding area of the somatic cell per million genomes detected in present study. The fusion, copy number variation and non-coding region mutation are not counted as TMB. Furthermore, synonymous mutations were also taken into consideration in order to reduce sampling noise. Additionally, analysis of cell free DNA from plasma was used to filter germline mutation (for instance: genetic polymorphisms, etc.). Additionally, TMB status was divided into TMB high level group (TMB-H) and TMB low level group (TMB-L) according to the median TMB threshold value. Statistical Analysis SPSS statistical analysis software (version 25.0) was used for the statistical analysis in present study. In terms of the analysis of baseline characteristics, the correlation between proportions variable and TMB status was analyzed using chi-square test and Fisher’s exact test was adopted when data was rare. The association analysis between continuous variable and TMB status was carried out using Mann-Whitney U nonparametric test. With regard to the analysis of prognostic data, Kaplan-Meier curves were introduced using Stata software (version 14.0) to compare the differences between DFS or OS and TMB status. Log-rank test was used to compare the survival differences. DFS was defined as the time from the onset of surgical resection to the patients’ recurrence of disease or death from any cause. Overall survival (OS) was defined as the time from the onset of surgical resection to the date of patients’ death from any cause. Those without death event by the end of the study follow-up, survival end points were censored at the date of last follow-up. Additionally, Cox multivariable analysis was introduced for OS. P < 0.05 was denoted as statistical significance. Results Baseline characteristics of the 82 patients with CRC according to TMB status Baseline characteristics of 82 patients with CRC included in present study were exhibited in Table 1 . The median age was 56 years (range: 27–82 years). Male and female was observed in 47 and 35 patients, respectively. ECOG performance status score of 0 and 1–2 score was noted in 59 and 23 patients, respectively. Besides, color cancer and rector cancer was found in 57 and 25 patients. Majority of patients with pathological staging of Ⅲ was observed in 63 patients. Histological type of adenocarcinoma was noted in all the 82 patients. Regarding the status of mismatch repair gene (MMR), there were 9 patients (11.0%) with deficiency of mismatch repair (dMMR) and 73 patients with proficiency of mismatch repair (pMMR). Interestingly, a total of 15 patients (18.3%) received adjuvant radiotherapy along with adjuvant chemotherapy. Furthermore, capecitabine monotherapy was administered in 17 patients and CAPEOX (capecitabine combined with oxaliplatin) regimen was implemented in 65 patients. Additionally, it should be noted that he actual median completion cycle of capecitabine monotherapy regimen was 5 cycles (range: 3–8 cycles). And the actual median completion cycle of CAPEOX regimen was 4 cycles (range: 3–8 cycles). Table 1 Baseline characteristics of the 82 patients with CRC according to TMB status Baseline characteristics Total (n = 82, %) TMB status χ 2 P TMB-L (n = 42) TMB-H (n = 40) Age Median (range) 56 (27–82) 56 (27–78) 56 (29–82) NA 0.618 Gender Male Female 47 (57.3) 35 (42.7) 24 (57.1) 18 (42.9) 23 (57.5) 17 (42.5) 0.001 0.974 ECOG PS score 0 1–2 59 (71.9) 23 (28.1) 32 (76.2) 10 (23.8) 27 (67.5) 13 (32.5) 0.767 0.381 Tumor location Color cancer Rector cancer 57 (69.5) 25 (30.5) 29 (69.0) 13 (31.0) 28 (70.0) 12 (30.0) 0.009 0.925 Pathological staging Ⅱ Ⅲ 19 (23.2) 63 (76.8) 13 (31.0) 29 (69.0) 6 (15.0) 34 (85.0) 2.929 0.087 Histological type Adenocarcinoma 82 (100.0) 42 (100.0) 40 (100.0) NA 1.000 MMR status dMMR pMMR 9 (11.0) 73 (89.0) 4 (9.5) 38 (90.5) 5 (12.5) 35 (87.5) 0.186 0.666 Adjuvant radiotherapy Yes No 15 (18.3) 67 (81.7) 8 (19.0) 34 (81.0) 7 (17.5) 33 (82.5) 0.033 0.856 Adjuvant chemotherapy regimen Capecitabine monotherapy CAPEOX 17 (20.7) 65 (79.3) 9 (21.4) 33 (78.6) 8 (20.0) 32 (80.0) 0.025 0.873 Completion of scheduled chemotherapy Capecitabine completion cycle Median (range) CAPEOX completion cycle Median (range) 5 (3–8) 4 (3–8) 5 (3–8) 4 (3–8) 5 (3–8) 4 (3–8)) NA NA 0.611 0.732 Abbreviation : CRC: colorectal cancer; TMB: tumor mutation burden; ECOG: Eastern Cooperative Oncology Group; PS: performance status; MMR: mismatch repair; dMMR: deficiency of mismatch repair; pMMR: proficiency of mismatch repair; NA: not available. The TMB profile among the 82 patients with CRC was illustrated in Fig. 2 . The median TMB of the 82 patients with CRC was 3.9/Mb with the ranging from 0/Mb to 48.6/Mb. Interestingly, TMB status was divided into two groups according to the median TMB threshold value. Therefore, patients with TMB ranging from 0/Mb to 3.9/Mb were classified as TMB-Low (TMB-L) and patients with TMB upper than 3.9/Mb were divided into TMB-High (TMB-H). The prevalence of TMB-L and TMB-H were observed in 42 patients and 40 patients, respectively. As showed in Table 1 , patients with TMB-L and TMB-H shared a basically balanced baseline characteristics and no statistically significant difference was observed individually ( P > 0.05). Nevertheless, it should be noted that the proportion of patients with pathological stage of Ⅱ was higher in TMB-L than that in TMB-H (31.0% vs 15.0%), even the difference was not statistically significant ( P = 0.087). Somatic gene mutation landscape analysis among the 82 patients with CRC Present study investigated the somatic gene mutation profile among the 82 patients with CRC. Specifically, the somatic gene mutation analysis for TMB detection of this study was based on the 40 genes in 5 important signal pathways that related to tumorigenesis and development of colorectal cancer. The somatic gene mutation landscape was presented in Fig. 3 and the most common cancer-related mutated gene among the 82 patients with CRC was TP53 with the incidence of 62.2%. Additionally, the other most common mutated genes were APC , RAS , PIK3CA , EGFR , ARID1A , BRAF , IRS2 , AXIN2 , FBXW7 , SMAD4 , TCF7L2 and ARID1A . And the corresponding prevalence was 58.5%, 47.6%, 34.1%, 30.4%, 28.0%, 23.2%, 19.5%, 18.3%, 17.1%, 14.6%, 13.4% and 11.0%, respectively. Additionally, other somatic genes with a mutation frequency > 2 cases were exhibited in Fig. 3 as well. Clinical significance of TMB status among the 82 patients with CRC All the 82 patients with CRC included in this study were available for prognostic assessment. And the last follow-up date of present study was July 2023. The median follow-up duration from the patients included in this study to last follow-up date was 5.3 years (follow-up range: 0.25–9.6 years). Collectively, the prognostic data of the 82 patients with CRC was presented in Fig. 4 and Fig. 5 As shown in Fig. 4 , The median DFS of the 82 patients was 4.5 years [95% confidence interval (CI): 3.30–5.70], 3-year DFS rate was 61.97% (95%CI: 50.51%-71.52%) and 5-year DFS rate was 37.49% (95%CI: 26.47%-48.46%), respectively. Furthermore, as illustrated in Fig. 5 , the median OS of the 82-patient cohort was 5.7 years (95%CI: 4.82–6.58), the 3-year OS rate was 79.16% (95%CI: 68.63%-86.49%) and 5-year OS rate was 56.06% (95%CI: 44.17%-66.37%). As mentioned above, there were 42 and 40 patients with TMB-L and TMB-H, respectively. The revelance of TMB status to prognosis was implemented in this study. As illustrated in Fig. 6 . The median DFS of TMB-L and TMB-H patients were 5.0 years (95%CI: 4.44–5.56) and 2.5 years (95%CI: 0.73–4.27), respectively. Besides, the 3-year DFS rate of patients with TMB-L and TMB-H was 76.05% and 47.05%, the corresponding 5-year DFS rate was 41.56% and 33.64%, respectively, and the difference was statistical significant (χ 2 = 4.85, P = 0.028). Furthermore, as exhibited in Fig. 7 , the median OS of TMB-L and TMB-H patients were 6.5 years (95%CI: 5.60–7.40) and 4.5 years (95%CI: 3.55–5.45), respectively. Additionally, the 3-year OS rate of patients with TMB-L and TMB-H was 85.71% and 72.26%, the according 5-year OS rate was 70.61% and 39.38%, respectively. And the difference was statistically significant (χ 2 = 6.79, P = 0.009). In order to adjust the potential confounding factors, a multivariate Cox analysis was adopted accordingly. The univariate analysis results were presented in Table 2 , which suggested that age, ECOG performance status score, pathological stage and TMB status had a significant influence on OS. Therefore, these factors were incorporated into the multivariate Cox regression analysis. And the results were shown in Table 2 as well. After multivariate adjustment, the TMB status still coffered an independent influence on OS (HR = 0.71, P = 0.011). Furthermore, the other variables that had independent implication for OS were age (HR = 0.76, P = 0.026), ECOG performance status score (HR = 0.71, P = 0.016) and pathological stage (HR = 0.63, P = 0.009). Table 2 Univariate and multivariate analyses of OS in 82 patients with colorectal cancer Baseline characteristics Median OS (95%CI) P (univariate analysis) Multivariate analysis HR (95%CI) P Age < 54 ≥ 54 6.5 (4.98–8.02) 5.1 (4.33–5.87) 0.011 0.76 (0.44–0.93) 0.026 Gender Female Male 5.5 (4.24–6.76) 6.0 (4.97–7.03) 0.562 ECOG PS score 0 1–2 6.6 (5.02–8.18) 4.8 (3.98–5.62) 0.009 0.71 (0.41–0.91) 0.016 Tumor location Color cancer Rector cancer 5.7 (4.75–6.65) 5.7 (4.59–6.81) 0.636 Pathological staging Ⅱ Ⅲ 6.9 (5.43–8.37) 4.8 (3.78–5.82) 0.005 0.63 (0.35–0.82) 0.009 MMR status dMMR pMMR 5.1 (4.09–6.11) 5.9 (4.96–6.84) 0.095 Adjuvant radiotherapy Yes No 6.1 (5.11–7.09) 5.5 (4.55–6.45) 0.431 Adjuvant chemotherapy regimen Capecitabine monotherapy CAPEOX 5.9 (4.75–7.05) 5.6 (4.59–6.61) 0.615 TMB status TMB-L TMB-H 6.5 (5.60–7.40) 4.5 (3.55–5.45) 0.009 0.71 (0.42–0.88) 0.011 Abbreviation : CRC: colorectal cancer; ECOG: Eastern Cooperative Oncology Group; PS: performance status; MMR: mismatch repair; dMMR: deficiency of mismatch repair; pMMR: proficiency of mismatch repair; TMB: tumor mutation burden; CI: confidence interval; HR: hazard ratio. Discussion Our study provided and highlighted real-world medical evidence regarding the prognostic data of patients with CRC who were treated with surgical resection and capecitabine-based adjuvant chemotherapy in real-world. Simultaneously, the prognostic significance of TMB status suggested that TMB could be considered as a potential biomarker to predict the prognosis of patients with CRC who received capecitabine-based adjuvant chemotherapy clinically. CRC was defined as a highly heterogeneous digestive system malignancy [ 26 ]. Relatively limited research progresses that might dramatically improve the prognosis of the patients with CRC were observed in recent years [ 27 ]. At present, PD-1/PD-L1 blockades were proved to be efficacious for considerable patients with advanced stage of cancer which provided significant survival benefit to some extent [ 28 ]. Nevertheless, the availability of PD-1/PD-L1 blockades in advanced CRC was scanty, which demonstrated that only patients with dMMR might benefit from PD-1 blockade according to Keynote 177 clinical trial [ 29 ]. As a result, traditional chemotherapy still played an important role in the treatment for CRC. However, it shoud be noted that ORR of chemotherapy was comparatively limited, suggesting the urgent exploration of potential biomarkers that could predict the efficacy of traditional chemotherapy was an important research direction [ 30 ]. At present, biomarkers that might predict the sensitivity to traditional chemotherapy were predominately focused on genetic polymorphisms, ctDNA and somatic gene mutations [ 31 ]. Noteworthily, a recently reported polymorphism study initiated by JS Su and colleagues indicated that PD-L1 gene polymorphism 901T > C could be used as a potential biomarker to involve in the prognosis of patients with CRC who received capecitabine-based adjuvant chemotherapy through the mediation of the mRNA expression of PD-L1 [ 32 ]. Furthermore, another study initiated by JT and colleagues investigated the clinical significance of ctDNA for guiding the prognosis of patients with high-risk stage Ⅲ colon cancer, which indicated that the monitoring of ctDNA might make a difference to predict the prognosis of patients with high-risk stage Ⅲ colon cancer [ 33 ]. Additionally, AJ Li and colleagues performed a study to explore the predictive association between PIK3CA and TP53 somatic mutations status and OS for patients with stage Ⅱ and Ⅲ CRC [ 34 ]. And the results suggested that patients with PIK3CA and TP53 double mutations were correlated with worse OS. Collectively, all the above findings demonstrated that the related DNA status of colon cancer or rectal cancer might predict the prognosis of patients with CRC who were treated with conventional chemotherapy to some extent. Although this study was designed as a retrospective analysis, we still carried out the prognostic analysis of the 82 patients with CRC who received capecitabine-based adjuvant chemotherapy. And the results showed that the median DFS of the 82 patients was 4.5 years and the median OS of the 82-patient cohort was 5.7 years. The DFS and OS data in our study seemed to be lower than that in NO16968 study which was implemented to identify the feasibility of oxaliplatin combined with capecitabine as adjuvant therapy for stage Ⅲ CRC [ 35 ]. The discrepancy between the two study could be attributed to the fact that more patients with an ECOG performance status of 2 score were included in our study than that in the NO16968 study and the results of the Cox analysis suggested that patients with ECOG of 2 score conferred a worse prognosis, which was consistent with the previous study [ 36 ]. Besides, it should be noted that this study was designed as a retrospective analysis. Management of the patients in retrospective study was not sufficient and normative compared with well-designed phase Ⅲ clinical trial. And the actual completion of capecitabine monotherapy regimen in this study was only 5 cycles, and the CAPEOX regimen was only 4 cycles. The insufficient adjuvant chemotherapy might stand a good chance to compromise the survival of the patients to some extent [ 37 ]. The somatic mutation and TMB analysis in this study was based on the targeted next-generation sequencing technology, which was proved to be an accurate and available approach for measuring targeted gene mutation with a greater depth and less time compared with whole exome sequencing [ 38 ]. Consequently, it was a useful and crucial method for the somatic mutation detection and TMB analysis in view of the wide genetic heterogeneity of CRC [ 39 ]. Therefore, the NGS technique could accurately analysis somatic mutation genes that related to CRC incidence and identify the accurate TMB analysis. In this study, somatic mutation results based on NGS analysis indicated that TP53 gene was of the highest mutation frequency in postsurgical CRC tissue (62.2%), which was basically consistent with the results of the research initiated by the DW Lee and colleagues investigated TMB in patients with CRC [ 22 ]. They identified that APC gene was of highest mutation frequency, TP53 gene was the second most common mutated gene with the prevalence of approximately 63.8%. These results exhibited that the essential function of TP53 gene in tumorigenesis. TP53 gene was a tumor suppressor gene that regulated cell division by keeping cells from growing and proliferating., thus playing an important regulatory role in the development and recurrence of colon cancer or rectal cancer [ 40 ]. Furthermore, present study confirmed that APC , RAS , PIK3CA and EGFR were closely related to the tumorigenesis and development of CRC, and the incidence among the 82 patients with CRC was 58.5%, 47.6%, 34.1% and 30.4%, respectively. The somatic mutation profile was basically consistent with the results of the previous study initiated by MAV Cavagnari and colleagues [ 41 ]. They also used NGS technique to implement the relevant somatic mutant genes based on the DNA extracted from frozen or paraffin-embedded tumor tissues. Interestingly, we also found a 4.9% and 2.4% incidence of ERBB2 and MTOR genes, which might be attributed to the heterogeneity of the development of CRC to some extent and some rare gene mutations could also contribute to the tumorigenesis of colon cancer or rectal cancer [ 42 ]. With regard to the TMB analysis, the results of this study exhibited that the overall somatic mutation burden of the 82 patients was relatively low with a median TMB of 3.9/Mb (range: 0-48.6/Mb), which was similar with two colorectal cancer studies reported previously [ 22 , 41 ]. The median TMB in 516 patients with CRC patients of the DW’s study was 4.5/Mb, while the median TMB in 29 patients with CRC of the MG’s study was approximately 5.0/Mb. Previous study published in the journal of Nature explored the TMB in various solid tumors [ 43 ], and the results indicated that the TMB in melanoma and lung cancer was of the highest incidence of median TMB with approximately 10/Mb. However, TMB in colorectal cancer was almost 3/Mb, which were basically consistent with the TMB results in our study. Furthermore, it should be noted that the prognostic analysis exhibited that patients with TMB-H conferred a worse OS, which contradicted the results of a previous study initiated by DW Lee and colleagues. They found that patients with TMB-H were associated with superior RFS and OS. The discrepancy could be attributed to the threshold value of TMB-H and TMB-L. The TMB in DW Lee's team was distinguished by 7/Mb, and the proportion of patients with TMB-H was only 10.7%, which might contribute to the difference in prognosis [ 22 ]. However, TMB analysis of our study was basically consistent with that of the previous study initiated by MAV C and colleagues, which exhibited that the median OS of patients with TMB ≥ 5 and TMB 0.05) [ 41 ]. Furthermore, a recent study by LB Xu and colleagues found that soft tissue sarcoma patients with high TMB conferred a worse prognosis when received conventional adjuvant chemotherapy, which was consistent with the results of our study as well [ 25 ]. Interestingly, the definition of TMB threshold in their study was the same as that in our study using the median threshold to distinguish TMB high and TMB low. Collectively, our study preliminarily demonstrated that patients with CRC of higher TMB were associated with worse prognosis when received capecitabine-based adjuvant chemotherapy. And the conclusion needed to be confirmed in large-scale clinical trials subsequently. The limitions of this study were as follows: firstly, the sample size of the study was relatively small, and the clinical significance of TMB in patient with CRC needed to be further evaluated in a in a larger population. Secondly, the TMB analysis in this study was restricted to only 40 genes in 5 signaling pathways that related to CRC tumorigenesis and development. Further study based on more genes was needed to clarify the function in all exons. Conclusions Collectively, our study provided and highlighted real-world medical evidence regarding the prognostic data of patients with CRC who were treated with surgical resection and capecitabine-based adjuvant chemotherapy in real-world. Furthermore, the prognostic significance of TMB status suggested that TMB could be considered as a potential biomarker to predict the prognosis of patients with CRC who received capecitabine-based adjuvant chemotherapy clinically. Declarations Ethical approval This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Henan Provincial People’s Hospital (2022-073-06). Consent to participate The written informed consent was obtained from all the patients. Consent for publication Not applicable. Availability of data and materials The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing Interests The authors have no relevant financial or non-financial interests to disclose. Funding This work was supported by grants from the Natural science foundation of Henan province (No. 162300410292) Author Contributions All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by YZZ, HZ, YZ and WCC. The study was conceived and supervised by DL, The first draft of the manuscript was written by YZZ and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Acknowledgements All authors would like to gratitude patients who participated in the present study. References Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A: Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018, 68(6):394-424. Bai M, Li ZG, Ba Y: Influence of KDR Genetic Variation on the Efficacy and Safety of Patients with Chemotherapy Refractory Metastatic CRC Who Received Apatinib Treatment. Int J Gen Med 2021, 14:1041-1055. Okuda H, Shimomura M, Ikeda S, Nakahara M, Miguchi M, Ishizaki Y, Saitoh Y, Toyota K, Sumitani D, Shimizu Y et al: A prospective feasibility study of uracil-tegafur and leucovorin as adjuvant chemotherapy for patients aged ≥ 80 years after curative resection of colorectal cancer, the HiSCO-03 study. Cancer Chemother Pharmacol 2023, 91(4):317-324. Kishore C, Bhadra P: Current advancements and future perspectives of immunotherapy in colorectal cancer research. Eur J Pharmacol 2021, 893:173819. Tintelnot J, Stein A: Immunotherapy in colorectal cancer: Available clinical evidence, challenges and novel approaches. World J Gastroenterol 2019, 25(29):3920-3928. Grothey A, Sobrero AF, Shields AF, Yoshino T, Paul J, Taieb J, Souglakos J, Shi Q, Kerr R, Labianca R et al: Duration of Adjuvant Chemotherapy for Stage III Colon Cancer. N Engl J Med 2018, 378(13):1177-1188. Yamazaki K, Yamanaka T, Shiozawa M, Manaka D, Kotaka M, Gamoh M, Shiomi A, Makiyama A, Munemoto Y, Rikiyama T et al: Oxaliplatin-based adjuvant chemotherapy duration (3 versus 6 months) for high-risk stage II colon cancer: the randomized phase III ACHIEVE-2 trial. Ann Oncol 2021, 32(1):77-84. Dasari A, Morris VK, Allegra CJ, Atreya C, Benson AB, 3rd, Boland P, Chung K, Copur MS, Corcoran RB, Deming DA et al: ctDNA applications and integration in colorectal cancer: an NCI Colon and Rectal-Anal Task Forces whitepaper. Nat Rev Clin Oncol 2020, 17(12):757-770. Osumi H, Shinozaki E, Yamaguchi K, Zembutsu H: Clinical utility of circulating tumor DNA for colorectal cancer. Cancer Sci 2019, 110(4):1148-1155. Luo H, Zhao Q, Wei W, Zheng L, Yi S, Li G, Wang W, Sheng H, Pu H, Mo H et al: Circulating tumor DNA methylation profiles enable early diagnosis, prognosis prediction, and screening for colorectal cancer. Sci Transl Med 2020, 12(524). Hamaguchi R, Tsuchiya T, Miyata G, Sato T, Takahashi K, Miura K, Oshio H, Ohori H, Ariyoshi K, Oyamada S et al: Efficacy of oral administration of cystine and theanine in colorectal cancer patients undergoing capecitabine-based adjuvant chemotherapy after surgery: a multi-institutional, randomized, double-blinded, placebo-controlled, phase II trial (JORTC-CAM03). Support Care Cancer 2020, 28(8):3649-3657. Yang L, Sun Y, Huang XE, Yu DS, Zhou JN, Zhou X, Li DZ, Guan X: Carcinoma microsatellite instability status as a predictor of benefit from fluorouracil-based adjuvant chemotherapy for stage II rectal cancer. Asian Pac J Cancer Prev 2015, 16(4):1545-1551. Taieb J, Shi Q, Pederson L, Alberts S, Wolmark N, Van Cutsem E, de Gramont A, Kerr R, Grothey A, Lonardi S et al: Prognosis of microsatellite instability and/or mismatch repair deficiency stage III colon cancer patients after disease recurrence following adjuvant treatment: results of an ACCENT pooled analysis of seven studies. Ann Oncol 2019, 30(9):1466-1471. Steuer CE, Ramalingam SS: Tumor Mutation Burden: Leading Immunotherapy to the Era of Precision Medicine? J Clin Oncol 2018, 36(7):631-632. Bagchi S, Yuan R, Engleman EG: Immune Checkpoint Inhibitors for the Treatment of Cancer: Clinical Impact and Mechanisms of Response and Resistance. Annu Rev Pathol 2021, 16:223-249. Guzik K, Tomala M, Muszak D, Konieczny M, Hec A, Blaszkiewicz U, Pustula M, Butera R, Domling A, Holak TA: Development of the Inhibitors that Target the PD-1/PD-L1 Interaction-A Brief Look at Progress on Small Molecules, Peptides and Macrocycles. Molecules 2019, 24(11). Berland L, Heeke S, Humbert O, Macocco A, Long-Mira E, Lassalle S, Lespinet-Fabre V, Lalvee S, Bordone O, Cohen C et al: Current views on tumor mutational burden in patients with non-small cell lung cancer treated by immune checkpoint inhibitors. J Thorac Dis 2019, 11(Suppl 1):S71-s80. Efremova M, Finotello F, Rieder D, Trajanoski Z: Neoantigens Generated by Individual Mutations and Their Role in Cancer Immunity and Immunotherapy. Front Immunol 2017, 8:1679. Lin C, Shi X, Zhao J, He Q, Fan Y, Xu W, Shao Y, Yu X, Jin Y: Tumor Mutation Burden Correlates With Efficacy of Chemotherapy/Targeted Therapy in Advanced Non-Small Cell Lung Cancer. Front Oncol 2020, 10:480. Schrock AB, Ouyang C, Sandhu J, Sokol E, Jin D, Ross JS, Miller VA, Lim D, Amanam I, Chao J et al: Tumor mutational burden is predictive of response to immune checkpoint inhibitors in MSI-high metastatic colorectal cancer. Ann Oncol 2019, 30(7):1096-1103. Innocenti F, Ou FS, Qu X, Zemla TJ, Niedzwiecki D, Tam R, Mahajan S, Goldberg RM, Bertagnolli MM, Blanke CD et al: Mutational Analysis of Patients With Colorectal Cancer in CALGB/SWOG 80405 Identifies New Roles of Microsatellite Instability and Tumor Mutational Burden for Patient Outcome. J Clin Oncol 2019, 37(14):1217-1227. Lee DW, Han SW, Bae JM, Jang H, Han H, Kim H, Bang D, Jeong SY, Park KJ, Kang GH et al: Tumor Mutation Burden and Prognosis in Patients with Colorectal Cancer Treated with Adjuvant Fluoropyrimidine and Oxaliplatin. Clin Cancer Res 2019, 25(20):6141-6147. Pai SG, Carneiro BA, Chae YK, Costa RL, Kalyan A, Shah HA, Helenowski I, Rademaker AW, Mahalingam D, Giles FJ: Correlation of tumor mutational burden and treatment outcomes in patients with colorectal cancer. J Gastrointest Oncol 2017, 8(5):858-866. Lee DW, Han SW, Cha Y, Bae JM, Kim HP, Lyu J, Han H, Kim H, Jang H, Bang D et al: Association between mutations of critical pathway genes and survival outcomes according to the tumor location in colorectal cancer. Cancer 2017, 123(18):3513-3523. Xu LB, Zhao ZG, Xu SF, Zhang XX, Liu T, Jing CY, Zhang SG, Yu SJ: The landscape of gene mutations and clinical significance of tumor mutation burden in patients with soft tissue sarcoma who underwent surgical resection and received conventional adjuvant therapy. Int J Biol Markers 2020, 35(3):14-22. Zhang Y, Song J, Zhao Z, Yang M, Chen M, Liu C, Ji J, Zhu D: Single-cell transcriptome analysis reveals tumor immune microenvironment heterogenicity and granulocytes enrichment in colorectal cancer liver metastases. Cancer Lett 2020, 470:84-94. Hermann, Brenner, Chen: The colorectal cancer epidemic: challenges and opportunities for primary, secondary and tertiary prevention. British Journal of Cancer 2018. Ai L, Chen J, Yan H, He Q, Luo P, Xu Z, Yang X: Research Status and Outlook of PD-1/PD-L1 Inhibitors for Cancer Therapy. Drug Des Devel Ther 2020, 14:3625-3649. André T, Shiu KK, Kim TW, Jensen BV, Jensen LH, Punt C, Smith D, Garcia-Carbonero R, Benavides M, Gibbs P et al: Pembrolizumab in Microsatellite-Instability-High Advanced Colorectal Cancer. N Engl J Med 2020, 383(23):2207-2218. Malla SB, Fisher DJ, Domingo E, Blake A, Hassanieh S, Redmond KL, Richman SD, Youdell M, Walker SM, Logan GE et al: In-depth Clinical and Biological Exploration of DNA Damage Immune Response as a Biomarker for Oxaliplatin Use in Colorectal Cancer. Clin Cancer Res 2021, 27(1):288-300. Reece M, Saluja H, Hollington P, Karapetis CS, Vatandoust S, Young GP, Symonds EL: The Use of Circulating Tumor DNA to Monitor and Predict Response to Treatment in Colorectal Cancer. Front Genet 2019, 10:1118. Su J, Dai B, Yuan W, Wang G, Zhang Z, Li Z, Liu J, Song J: The influence of PD-L1 genetic variation on the prognosis of R0 resection colorectal cancer patients received capecitabine-based adjuvant chemotherapy: a long-term follow-up, real-world retrospective study. Cancer Chemother Pharmacol 2020, 85(5):969-978. Tie J, Cohen JD, Wang Y, Christie M, Simons K, Lee M, Wong R, Kosmider S, Ananda S, McKendrick J et al: Circulating Tumor DNA Analyses as Markers of Recurrence Risk and Benefit of Adjuvant Therapy for Stage III Colon Cancer. JAMA Oncol 2019, 5(12):1710-1717. Li AJ, Li HG, Tang EJ, Wu W, Chen Y, Jiang HH, Lin MB, Yin L: PIK3CA and TP53 mutations predict overall survival of stage II/III colorectal cancer patients. World J Gastroenterol 2018, 24(5):631-640. Schmoll HJ, Tabernero J, Maroun J, de Braud F, Price T, Van Cutsem E, Hill M, Hoersch S, Rittweger K, Haller DG: Capecitabine Plus Oxaliplatin Compared With Fluorouracil/Folinic Acid As Adjuvant Therapy for Stage III Colon Cancer: Final Results of the NO16968 Randomized Controlled Phase III Trial. J Clin Oncol 2015, 33(32):3733-3740. Yang J, Xu H, Guo X, Zhang J, Ye X, Yang Y, Ma X: Pretreatment Inflammatory Indexes as Prognostic Predictors for Survival in Colorectal Cancer Patients Receiving Neoadjuvant Chemoradiotherapy. Sci Rep 2018, 8(1):3044. Iveson TJ, Sobrero AF, Yoshino T, Souglakos I, Ou FS, Meyers JP, Shi Q, Grothey A, Saunders MP, Labianca R et al: Duration of Adjuvant Doublet Chemotherapy (3 or 6 months) in Patients With High-Risk Stage II Colorectal Cancer. J Clin Oncol 2021, 39(6):631-641. Borowka P, Pulaski L, Marciniak B, Borowska-Struginska B, Dziadek J, Zadzinska E, Lorkiewicz W, Strapagiel D: Screening methods for detection of ancient Mycobacterium tuberculosis complex fingerprints in next-generation sequencing data derived from skeletal samples. Gigascience 2019, 8(6). Zhang H, Deng YM, Chen ZC, Tang YC, Yang S, Zhang SD, Liang JM, Wang YG, Wu X, Zhang RW et al: Clinical significance of tumor mutation burden and DNA damage repair in advanced stage non-small cell lung cancer patients. Eur Rev Med Pharmacol Sci 2020, 24(14):7664-7672. Li C, Bu J, Liao Y, Zhang J, Han J, Zhang H, Xing H, Li Z, Wu H, Liang L et al: High Expressions of CUL4A and TP53 in Colorectal Cancer Predict Poor Survival. Cell Physiol Biochem 2018, 51(6):2829-2842. Cavagnari MAV, Silva TD, Pereira MAH, Sauer LJ, Shigueoka D, Saad SS, Barão K, Ribeiro CCD, Forones NM: Impact of genetic mutations and nutritional status on the survival of patients with colorectal cancer. BMC Cancer 2019, 19(1):644. Dunlop MG, Dobbins SE, Farrington SM, Jones AM, Palles C, Whiffin N, Tenesa A, Spain S, Broderick P, Ooi LY et al: Common variation near CDKN1A, POLD3 and SHROOM2 influences colorectal cancer risk. Nat Genet 2012, 44(7):770-776. Lawrence MS, Stojanov P, Polak P, Kryukov GV, Cibulskis K, Sivachenko A, Carter SL, Stewart C, Mermel CH, Roberts SA et al: Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature 2013, 499(7457):214-218. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4357440","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":299290814,"identity":"8e82796b-570a-49ed-9c24-123163afe1c6","order_by":0,"name":"Yuanzeng Zhu","email":"","orcid":"","institution":"Henan Provincial People’s Hospital, Zhengzhou University People’s Hospital, Henan University People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuanzeng","middleName":"","lastName":"Zhu","suffix":""},{"id":299290815,"identity":"b05e2ecf-b25b-48e0-9363-6a7f5d5478ee","order_by":1,"name":"Han 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07:26:01","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4357440/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4357440/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":56280450,"identity":"e08dfea6-8924-4d4d-9ab4-3dff7aeb3d23","added_by":"auto","created_at":"2024-05-10 20:57:05","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":483623,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of this retrospective study of clinical significance for tumor mutation burden among 82 patients with colorectal cancer who received capecitabine-based adjuvant chemotherapy\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4357440/v1/093774fe3028b83f9a41221c.jpg"},{"id":56280285,"identity":"0074b4ef-dda8-400b-9d8d-322ee13f9c34","added_by":"auto","created_at":"2024-05-10 20:54:52","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":150896,"visible":true,"origin":"","legend":"\u003cp\u003eThe tumor mutation burden profile of the 82 patients with colorectal cancer who received capecitabine-based adjuvant chemotherapy\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4357440/v1/a8519d52506774176b87bf59.jpg"},{"id":56280452,"identity":"752a9ef6-97b8-47ab-9519-48800ce7847d","added_by":"auto","created_at":"2024-05-10 20:57:16","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":392952,"visible":true,"origin":"","legend":"\u003cp\u003eThe somatic mutation landscape of the 82 patients with colorectal cancer who received capecitabine-based adjuvant chemotherapy by targeted next generation sequencing\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4357440/v1/6df4fdfa2530fca0a6776ec3.jpg"},{"id":56280190,"identity":"c258b923-33c3-449a-98bd-178dccfbd96a","added_by":"auto","created_at":"2024-05-10 20:52:08","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":218071,"visible":true,"origin":"","legend":"\u003cp\u003eDisease free survival of the 82 patients with colorectal cancer who received capecitabine-based adjuvant chemotherapy\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4357440/v1/cac935efd8106608b360d2a7.jpg"},{"id":56280180,"identity":"b0a1c5fa-668c-4676-8dfd-f5c37ac432b7","added_by":"auto","created_at":"2024-05-10 20:51:59","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":213245,"visible":true,"origin":"","legend":"\u003cp\u003eOverall survival of the 82 patients with colorectal cancer who received capecitabine-based adjuvant chemotherapy\u003c/p\u003e","description":"","filename":"Picture5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4357440/v1/86affc8bf5b3b569889c62ef.jpg"},{"id":56280437,"identity":"a94ab402-39fe-4118-bf0f-47d9742666cf","added_by":"auto","created_at":"2024-05-10 20:56:41","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":225384,"visible":true,"origin":"","legend":"\u003cp\u003eDisease-free survival of the 82 patients with colorectal cancer according to tumor mutation burden status\u003c/p\u003e","description":"","filename":"Picture6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4357440/v1/9e5f2ca5932500def50803a6.jpg"},{"id":56280453,"identity":"0b5ac616-23a7-4286-97cd-42788269f049","added_by":"auto","created_at":"2024-05-10 20:57:18","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":220883,"visible":true,"origin":"","legend":"\u003cp\u003eOverall survival of the 82 patients with colorectal cancer according to tumor mutation burden status\u003c/p\u003e","description":"","filename":"Picture7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4357440/v1/0d4f8403c05ac968bf458ebe.jpg"},{"id":60565741,"identity":"f5c5883f-71f6-4767-93da-72c0ed49d616","added_by":"auto","created_at":"2024-07-18 08:32:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2647310,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4357440/v1/693dae54-93ca-4493-a45c-aec53c16b988.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prognostic implications of tumor mutation burden in postoperative patients with colorectal cancer who received capecitabine-based adjuvant chemotherapy: a retrospective exploratory study","fulltext":[{"header":"Background","content":"\u003cp\u003eColorectal cancer (CRC) is one of the most common gastrointestinal tumors worldwide. Recently, the incidence of CRC in China is increasing rapidly. It is estimated that there are approximately 1800,000 new cases of CRC and 860,000 new deaths annually all over the world [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. And there are approximately 560,000 new cases and 290,000 new deaths of CRC in China according to the recent epidemiological data [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Although surgical resection was the only way to cure patients with CRC for decades, approximately 25% of the patients were presented with clinical evidence of distant metastases at initial diagnosis, thus making the surgical resection unachievable [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Although immunotherapy made dramatical breakthroughs in a number of tumors recently [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], unfortunately, it had been proved that only patients with highly unstable microsatellites (MSI-H) were of the opportunity to benefit from immunotherapy in the field of metastatic CRC and majority of patients with metastatic CRC was unable to benefit from immunotherapy except the conventional chemoradiotherapy regimens [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Similarly, the promising research progress in early-stage and resected patients with CRC treatment was also limited relatively. Only IDEA trial was proved to be the significant breakthrough with clinical implications recently, which suggested that 3 months rather than 6 months of adjuvant chemotherapy was recommended for low-risk stage Ⅲ colon cancer [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Conclusions in IDEA trial helped to attenuate the unnecessary adverse reactions of chemotherapy, given that 6 months adjuvant chemotherapy regimens had been established to be the standard of care for stage Ⅲ patients with CRC for decades [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Furthermore, with the adequate development of the more sensitive detection techniques, ctDNA had established to be the potential predictive value in the recurrence risk assessment for patients with CRC after surgical resection [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Unfortunately, the predictive role regarding ctDNA for the intensity or duration of adjuvant chemotherapy among patients with CRC was still controversial and no standardized and unified criteria was available for the corresponding detection of ctDNA currently [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Therefore, it was still needed further exploration of ctDNA for clinical application extensively [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Capecitabine-based adjuvant chemotherapy had been established as the standard of care for the patients with CRC after surgical resection for decades, which improved 5-year survival rates of approximately 10% [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, the benefits of capecitabine\u0026ndash;based adjuvant chemotherapy for patients with stage Ⅱ CRC regarding reducing recurrence and prolonging survival remained controversial currently [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Furthermore, large individual differences were still observed in the clinical application of capecitabine-based adjuvant chemotherapy, which suggested that many factors might compromise the prognosis of this regimen clinically.\u003c/p\u003e \u003cp\u003eMismatch repair (MMR) status was a valuable predictor for the indication of adjuvant chemotherapy with fluorouracil-based regimen in stage II/III colon cancer [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Additionally, tumor mutation burden (TMB) was defined as the density of the distribution of non-synonymous mutations in the protein coding region, which was calculated by proportion between the total number of non-synonymous mutation in the protein coding region and the total length of the protein coding region and the unit was the number of mutations/MB [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Recent years had witnessed great progress of immune checkpoint inhibitors that brought new insight for the therapeutic strategy of anti-tumor therapy [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, it should be noted that immune checkpoint inhibitors were only useful in a small number of the patients with the objective response rate (ORR) of approximately 20% [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], which suggested that the potential biomarkers such as \u003cem\u003ePD-L1\u003c/em\u003e expression and TMB were of urgent value to be explored for \u003cem\u003ePD-1/PD-L1\u003c/em\u003e checkpoint blockade therapy clinically [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Previous study indicated that higher TMB level was correlated with more neoantigens produced by tumor cells, thus contributing to the chances for T cell recognition, which might effectively enhance the probability of being recognized by the immune system [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. And once \u003cem\u003ePD-1\u003c/em\u003e blockades activated the body's own anti-tumor immune response, the probability of killing tumor cells was higher and the efficacy of \u003cem\u003ePD-1/PD-L1\u003c/em\u003e blockades could be better eventually [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Additional evidences exhibited that TMB was also a potential biomarker to predict efficacy of immunotherapy in patients with CRC and TMB status was correlated with survival outcomes in patients with metastatic CRC receiving immune checkpoint inhibitors [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. However, the relevance between TMB status and the prognosis of patients with postoperative CRC who received capecitabine-based adjuvant chemotherapy instead of immunotherapy was still unknown and if TMB status could be used as a potential biomarker for the surgical resection patients with CRC who received conventional adjuvant therapy was unclear currently [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Interestingly, a previous study initiated by DW Lee and colleagues reported the association between TMB status and the prognosis of patients with CRC receiving 5-FU combined with oxaliplatin as adjuvant treatment regimen and concluded that 10.7% of TMB-H patients conferred a superior 5-year RFS rate [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Additionally, AG Pai and colleagues explored the relationship between TMB status and the prognosis of patients with CRC receiving chemotherapy [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. And the results demonstrated that there was no difference between TMB status and the prognosis of the patients.\u003c/p\u003e \u003cp\u003eConsequently, the aim of this study was to identify the somatic gene mutation landscape and prognostic significance of TMB among patients with CRC who received surgical resection and capecitabine-based adjuvant chemotherapy.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and eligibility criteria\u003c/h2\u003e \u003cp\u003e This study was designed as a retrospective study, patients with CRC who underwent surgical resection were collected and reviewed in the Department of Gastrointestinal Surgery of Henan Provincial People\u0026rsquo;s Hospital from June 2011 to December 2022. Baseline characteristics of the patients were obtained from the hospitals electronic medical record system. Patients who fulfilled the eligibility criteria were included in the study retrospectively. Inclusion criteria were: (1) aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years; (2) ECOG performance status of 0\u0026ndash;2 score; (3) normal cardiac function, renal function and bone marrow function to receive adjuvant chemotherapy appropriately; (4) pathological diagnosis of colon cancer or rectal cancer with histological type of adenocarcinoma and the patients received R0 surgical resection and postoperative adjuvant chemotherapy; (5) pathological staging of Ⅱ or Ⅲ. The exclusion criteria included: (1) patients failed to receive capecitabine-based adjuvant chemotherapy (capecitabine monotherapy or capecitabine-based regimens) after R0 resection; (2) cancer tissue specimens were not available for tumor genomic DNA extraction; (3) diagnosed of familial adenomatous polyposis or hereditary CRC; (4) concomitant with another tumor or serious diseases that might compromise the survival of the patients. Flow chart of present study was illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Finally, a total of 82 patients with CRC patients met the eligibility criteria were enrolled in this study. The primary endpoint of present study was the prognostic significance between overall survival (OS) and tumor mutation burdern (TMB) status. The study was approved by the ethics committee of Henan Provincial People\u0026rsquo;s Hospital. Informed consent was signed by each enrolled patient in accordance with the recommendation of the declaration of Helsinki.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eTherapeutic regimens and follow up protocol\u003c/h2\u003e \u003cp\u003eAll the patients with CRC included in this study were treated with capecitabine-based adjuvant chemotherapy. The chemotherapy regimens included capecitabine monotherapy and CAPEOX combination therapy. And the specific usage and dosage of capecitabine monotherapy was as follows: 3\u0026ndash;4 weeks after surgical treatment, capecitabine, 1000\u0026ndash;1250 mg/m\u003csup\u003e2\u003c/sup\u003e, twice daily, day 1\u0026ndash;14, every 21 days as one cycle. Additionally, the detailed usage of CAPEOX regimen manifested as: capecitabine 1000mg/m\u003csup\u003e2\u003c/sup\u003e, twice daily, day 1\u0026ndash;14, every 21 days as one cycle, combined with oxaliplatin, 80\u0026ndash;130 mg/m\u003csup\u003e2\u003c/sup\u003e, iv. infusion, day 1. The adjuvant chemotherapy period was performed as 8 cycles or depended on the actual situation of the patients.\u003c/p\u003e \u003cp\u003eEach patient was followed up at the onset of adjuvant chemotherapy administration. Initial follow-up was implemented when the patient received adjuvant chemotherapy in the hospital, where the baseline characteristics and the date of disease recurrence could be obtained through the electronic medical record system detailedly, and the recurrent status was determined by radiological assessment every three months and then every half year. Subsequent follow-up was performed mainly by telephone. Patients were followed up every three months for the date of recurrence and treatment after recurrence and the death status were mainly inquired. Furthermore, when a patient was recurrence or death, it must be confirmed by at least two research colleagues before it could be confirmed as a recurrence events or death events.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eCollection of tumor tissue specimen and sequencing analysis of targeted DNA\u003c/h2\u003e \u003cp\u003eTumor tissue specimens of patients with CRC were collected after the surgical resection, and were stored in liquid nitrogen subsequently. Additionally, DNA was extracted using DNA FFPE tissue kit (QIAGEN, Valencia, CA) from the tumor tissue specimen and DNA concentration was measured by Qubitds DNA assay to make sure that A260/A280 was within the range of 1.8 to 2.0. Simultaneously, approximately 5 mL of peripheral blood was collected and incubated at room temperature for 2 hours. Then the supernatant was transferred to 15 mL centrifuge tubes and centrifuged to obtain the supernatant. Circulating cfDNA was recovered from 4 to 5 mL of plasma by using the QIAamp Circulating Nucleic Acid kit (Qiagen) accordingly. And then approximately 50 ng of cell free DNA is required for construction of an NGS library.\u003c/p\u003e \u003cp\u003eTargeted DNA sequencing was performed when the DNA from tumor tissue specimens was extracted. DNA was profiled by using a capture-based targeted sequencing panel (Burning Rock Biotech. China) for sequencing analysis, which included part of the human genome region and 40 common tumor-related genes in colorectal cancer. 40 genes were derived from 5 important signal pathways that related to the occurrence and development of colorectal cancer, including \u003cem\u003eWNT\u003c/em\u003e pathway, \u003cem\u003eP53\u003c/em\u003e pathway, \u003cem\u003eRTK-RAS\u003c/em\u003e pathway, \u003cem\u003eTGF-β\u003c/em\u003e pathway and \u003cem\u003ePI3K\u003c/em\u003e pathway [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Probe hybridization and high-throughput sequencing were used to detect hot-spot mutation regions (exon, intron or promoter regions) of related genes, thus detecting the mutations, amplification and rearrangement (fusion) of genes relevant to cancer comprehensively and accurately.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eTMB detection analysis\u003c/h2\u003e \u003cp\u003eThe specific methods of sequencing data analysis were reported previously [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. TMB was defined as the number of substitutions or insertions or deletions of coding area of the somatic cell per million genomes detected in present study. The fusion, copy number variation and non-coding region mutation are not counted as TMB. Furthermore, synonymous mutations were also taken into consideration in order to reduce sampling noise. Additionally, analysis of cell free DNA from plasma was used to filter germline mutation (for instance: genetic polymorphisms, etc.). Additionally, TMB status was divided into TMB high level group (TMB-H) and TMB low level group (TMB-L) according to the median TMB threshold value.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eSPSS statistical analysis software (version 25.0) was used for the statistical analysis in present study. In terms of the analysis of baseline characteristics, the correlation between proportions variable and TMB status was analyzed using chi-square test and Fisher\u0026rsquo;s exact test was adopted when data was rare. The association analysis between continuous variable and TMB status was carried out using Mann-Whitney U nonparametric test. With regard to the analysis of prognostic data, Kaplan-Meier curves were introduced using Stata software (version 14.0) to compare the differences between DFS or OS and TMB status. Log-rank test was used to compare the survival differences. DFS was defined as the time from the onset of surgical resection to the patients\u0026rsquo; recurrence of disease or death from any cause. Overall survival (OS) was defined as the time from the onset of surgical resection to the date of patients\u0026rsquo; death from any cause. Those without death event by the end of the study follow-up, survival end points were censored at the date of last follow-up. Additionally, Cox multivariable analysis was introduced for OS. \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was denoted as statistical significance.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics of the 82 patients with CRC according to TMB status\u003c/h2\u003e \u003cp\u003eBaseline characteristics of 82 patients with CRC included in present study were exhibited in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The median age was 56 years (range: 27\u0026ndash;82 years). Male and female was observed in 47 and 35 patients, respectively. ECOG performance status score of 0 and 1\u0026ndash;2 score was noted in 59 and 23 patients, respectively. Besides, color cancer and rector cancer was found in 57 and 25 patients. Majority of patients with pathological staging of Ⅲ was observed in 63 patients. Histological type of adenocarcinoma was noted in all the 82 patients. Regarding the status of mismatch repair gene (MMR), there were 9 patients (11.0%) with deficiency of mismatch repair (dMMR) and 73 patients with proficiency of mismatch repair (pMMR). Interestingly, a total of 15 patients (18.3%) received adjuvant radiotherapy along with adjuvant chemotherapy. Furthermore, capecitabine monotherapy was administered in 17 patients and CAPEOX (capecitabine combined with oxaliplatin) regimen was implemented in 65 patients. Additionally, it should be noted that he actual median completion cycle of capecitabine monotherapy regimen was 5 cycles (range: 3\u0026ndash;8 cycles). And the actual median completion cycle of CAPEOX regimen was 4 cycles (range: 3\u0026ndash;8 cycles).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of the 82 patients with CRC according to TMB status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBaseline characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;82, %)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eTMB status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTMB-L (n\u0026thinsp;=\u0026thinsp;42)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTMB-H (n\u0026thinsp;=\u0026thinsp;40)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003cp\u003eMedian (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56 (27\u0026ndash;82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (27\u0026ndash;78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56 (29\u0026ndash;82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.618\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47 (57.3)\u003c/p\u003e \u003cp\u003e35 (42.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (57.1)\u003c/p\u003e \u003cp\u003e18 (42.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23 (57.5)\u003c/p\u003e \u003cp\u003e17 (42.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.974\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eECOG PS score\u003c/p\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e1\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59 (71.9)\u003c/p\u003e \u003cp\u003e23 (28.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (76.2)\u003c/p\u003e \u003cp\u003e10 (23.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (67.5)\u003c/p\u003e \u003cp\u003e13 (32.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.767\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.381\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor location\u003c/p\u003e \u003cp\u003eColor cancer\u003c/p\u003e \u003cp\u003eRector cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57 (69.5)\u003c/p\u003e \u003cp\u003e25 (30.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (69.0)\u003c/p\u003e \u003cp\u003e13 (31.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 (70.0)\u003c/p\u003e \u003cp\u003e12 (30.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.925\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathological staging\u003c/p\u003e \u003cp\u003eⅡ\u003c/p\u003e \u003cp\u003eⅢ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (23.2)\u003c/p\u003e \u003cp\u003e63 (76.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (31.0)\u003c/p\u003e \u003cp\u003e29 (69.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (15.0)\u003c/p\u003e \u003cp\u003e34 (85.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.929\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistological type\u003c/p\u003e \u003cp\u003eAdenocarcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMMR status\u003c/p\u003e \u003cp\u003edMMR\u003c/p\u003e \u003cp\u003epMMR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (11.0)\u003c/p\u003e \u003cp\u003e73 (89.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (9.5)\u003c/p\u003e \u003cp\u003e38 (90.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (12.5)\u003c/p\u003e \u003cp\u003e35 (87.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.666\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdjuvant radiotherapy\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (18.3)\u003c/p\u003e \u003cp\u003e67 (81.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (19.0)\u003c/p\u003e \u003cp\u003e34 (81.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (17.5)\u003c/p\u003e \u003cp\u003e33 (82.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.856\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdjuvant chemotherapy regimen\u003c/p\u003e \u003cp\u003eCapecitabine monotherapy\u003c/p\u003e \u003cp\u003eCAPEOX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (20.7)\u003c/p\u003e \u003cp\u003e65 (79.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (21.4)\u003c/p\u003e \u003cp\u003e33 (78.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (20.0)\u003c/p\u003e \u003cp\u003e32 (80.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.873\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompletion of scheduled chemotherapy\u003c/p\u003e \u003cp\u003eCapecitabine completion cycle\u003c/p\u003e \u003cp\u003eMedian (range)\u003c/p\u003e \u003cp\u003eCAPEOX completion cycle\u003c/p\u003e \u003cp\u003eMedian (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (3\u0026ndash;8)\u003c/p\u003e \u003cp\u003e4 (3\u0026ndash;8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (3\u0026ndash;8)\u003c/p\u003e \u003cp\u003e4 (3\u0026ndash;8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (3\u0026ndash;8)\u003c/p\u003e \u003cp\u003e4 (3\u0026ndash;8))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.611\u003c/p\u003e \u003cp\u003e0.732\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eAbbreviation\u003c/b\u003e: CRC: colorectal cancer; TMB: tumor mutation burden; ECOG: Eastern Cooperative Oncology Group; PS: performance status; MMR: mismatch repair; dMMR: deficiency of mismatch repair; pMMR: proficiency of mismatch repair; NA: not available.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe TMB profile among the 82 patients with CRC was illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The median TMB of the 82 patients with CRC was 3.9/Mb with the ranging from 0/Mb to 48.6/Mb. Interestingly, TMB status was divided into two groups according to the median TMB threshold value. Therefore, patients with TMB ranging from 0/Mb to 3.9/Mb were classified as TMB-Low (TMB-L) and patients with TMB upper than 3.9/Mb were divided into TMB-High (TMB-H). The prevalence of TMB-L and TMB-H were observed in 42 patients and 40 patients, respectively. As showed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, patients with TMB-L and TMB-H shared a basically balanced baseline characteristics and no statistically significant difference was observed individually (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Nevertheless, it should be noted that the proportion of patients with pathological stage of Ⅱ was higher in TMB-L than that in TMB-H (31.0% vs 15.0%), even the difference was not statistically significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.087).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSomatic gene mutation landscape analysis among the 82 patients with CRC\u003c/h2\u003e \u003cp\u003ePresent study investigated the somatic gene mutation profile among the 82 patients with CRC. Specifically, the somatic gene mutation analysis for TMB detection of this study was based on the 40 genes in 5 important signal pathways that related to tumorigenesis and development of colorectal cancer. The somatic gene mutation landscape was presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and the most common cancer-related mutated gene among the 82 patients with CRC was \u003cem\u003eTP53\u003c/em\u003e with the incidence of 62.2%. Additionally, the other most common mutated genes were \u003cem\u003eAPC\u003c/em\u003e, \u003cem\u003eRAS\u003c/em\u003e, \u003cem\u003ePIK3CA\u003c/em\u003e, \u003cem\u003eEGFR\u003c/em\u003e, \u003cem\u003eARID1A\u003c/em\u003e, \u003cem\u003eBRAF\u003c/em\u003e, \u003cem\u003eIRS2\u003c/em\u003e, \u003cem\u003eAXIN2\u003c/em\u003e, \u003cem\u003eFBXW7\u003c/em\u003e, \u003cem\u003eSMAD4\u003c/em\u003e, \u003cem\u003eTCF7L2\u003c/em\u003e and \u003cem\u003eARID1A\u003c/em\u003e. And the corresponding prevalence was 58.5%, 47.6%, 34.1%, 30.4%, 28.0%, 23.2%, 19.5%, 18.3%, 17.1%, 14.6%, 13.4% and 11.0%, respectively. Additionally, other somatic genes with a mutation frequency\u0026thinsp;\u0026gt;\u0026thinsp;2 cases were exhibited in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e as well.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eClinical significance of TMB status among the 82 patients with CRC\u003c/h2\u003e \u003cp\u003eAll the 82 patients with CRC included in this study were available for prognostic assessment. And the last follow-up date of present study was July 2023. The median follow-up duration from the patients included in this study to last follow-up date was 5.3 years (follow-up range: 0.25\u0026ndash;9.6 years). Collectively, the prognostic data of the 82 patients with CRC was presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, The median DFS of the 82 patients was 4.5 years [95% confidence interval (CI): 3.30\u0026ndash;5.70], 3-year DFS rate was 61.97% (95%CI: 50.51%-71.52%) and 5-year DFS rate was 37.49% (95%CI: 26.47%-48.46%), respectively. Furthermore, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, the median OS of the 82-patient cohort was 5.7 years (95%CI: 4.82\u0026ndash;6.58), the 3-year OS rate was 79.16% (95%CI: 68.63%-86.49%) and 5-year OS rate was 56.06% (95%CI: 44.17%-66.37%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs mentioned above, there were 42 and 40 patients with TMB-L and TMB-H, respectively. The revelance of TMB status to prognosis was implemented in this study. As illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. The median DFS of TMB-L and TMB-H patients were 5.0 years (95%CI: 4.44\u0026ndash;5.56) and 2.5 years (95%CI: 0.73\u0026ndash;4.27), respectively. Besides, the 3-year DFS rate of patients with TMB-L and TMB-H was 76.05% and 47.05%, the corresponding 5-year DFS rate was 41.56% and 33.64%, respectively, and the difference was statistical significant (χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;4.85, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.028). Furthermore, as exhibited in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, the median OS of TMB-L and TMB-H patients were 6.5 years (95%CI: 5.60\u0026ndash;7.40) and 4.5 years (95%CI: 3.55\u0026ndash;5.45), respectively. Additionally, the 3-year OS rate of patients with TMB-L and TMB-H was 85.71% and 72.26%, the according 5-year OS rate was 70.61% and 39.38%, respectively. And the difference was statistically significant (χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;6.79, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn order to adjust the potential confounding factors, a multivariate Cox analysis was adopted accordingly. The univariate analysis results were presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, which suggested that age, ECOG performance status score, pathological stage and TMB status had a significant influence on OS. Therefore, these factors were incorporated into the multivariate Cox regression analysis. And the results were shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e as well. After multivariate adjustment, the TMB status still coffered an independent influence on OS (HR\u0026thinsp;=\u0026thinsp;0.71, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.011). Furthermore, the other variables that had independent implication for OS were age (HR\u0026thinsp;=\u0026thinsp;0.76, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.026), ECOG performance status score (HR\u0026thinsp;=\u0026thinsp;0.71, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.016) and pathological stage (HR\u0026thinsp;=\u0026thinsp;0.63, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and multivariate analyses of OS in 82 patients with colorectal cancer\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBaseline characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMedian OS (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e (univariate analysis)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;54\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.5 (4.98\u0026ndash;8.02)\u003c/p\u003e \u003cp\u003e5.1 (4.33\u0026ndash;5.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.76 (0.44\u0026ndash;0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.5 (4.24\u0026ndash;6.76)\u003c/p\u003e \u003cp\u003e6.0 (4.97\u0026ndash;7.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eECOG PS score\u003c/p\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e1\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.6 (5.02\u0026ndash;8.18)\u003c/p\u003e \u003cp\u003e4.8 (3.98\u0026ndash;5.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.71 (0.41\u0026ndash;0.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor location\u003c/p\u003e \u003cp\u003eColor cancer\u003c/p\u003e \u003cp\u003eRector cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.7 (4.75\u0026ndash;6.65)\u003c/p\u003e \u003cp\u003e5.7 (4.59\u0026ndash;6.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathological staging\u003c/p\u003e \u003cp\u003eⅡ\u003c/p\u003e \u003cp\u003eⅢ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.9 (5.43\u0026ndash;8.37)\u003c/p\u003e \u003cp\u003e4.8 (3.78\u0026ndash;5.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.63 (0.35\u0026ndash;0.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMMR status\u003c/p\u003e \u003cp\u003edMMR\u003c/p\u003e \u003cp\u003epMMR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.1 (4.09\u0026ndash;6.11)\u003c/p\u003e \u003cp\u003e5.9 (4.96\u0026ndash;6.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdjuvant radiotherapy\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.1 (5.11\u0026ndash;7.09)\u003c/p\u003e \u003cp\u003e5.5 (4.55\u0026ndash;6.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.431\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdjuvant chemotherapy regimen\u003c/p\u003e \u003cp\u003eCapecitabine monotherapy\u003c/p\u003e \u003cp\u003eCAPEOX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.9 (4.75\u0026ndash;7.05)\u003c/p\u003e \u003cp\u003e5.6 (4.59\u0026ndash;6.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTMB status\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTMB-L\u003c/p\u003e \u003cp\u003eTMB-H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.5 (5.60\u0026ndash;7.40)\u003c/p\u003e \u003cp\u003e4.5 (3.55\u0026ndash;5.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.71 (0.42\u0026ndash;0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eAbbreviation\u003c/b\u003e: CRC: colorectal cancer; ECOG: Eastern Cooperative Oncology Group; PS: performance status; MMR: mismatch repair; dMMR: deficiency of mismatch repair; pMMR: proficiency of mismatch repair; TMB: tumor mutation burden; CI: confidence interval; HR: hazard ratio.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e Our study provided and highlighted real-world medical evidence regarding the prognostic data of patients with CRC who were treated with surgical resection and capecitabine-based adjuvant chemotherapy in real-world. Simultaneously, the prognostic significance of TMB status suggested that TMB could be considered as a potential biomarker to predict the prognosis of patients with CRC who received capecitabine-based adjuvant chemotherapy clinically.\u003c/p\u003e \u003cp\u003eCRC was defined as a highly heterogeneous digestive system malignancy [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Relatively limited research progresses that might dramatically improve the prognosis of the patients with CRC were observed in recent years [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. At present, \u003cem\u003ePD-1/PD-L1\u003c/em\u003e blockades were proved to be efficacious for considerable patients with advanced stage of cancer which provided significant survival benefit to some extent [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Nevertheless, the availability of \u003cem\u003ePD-1/PD-L1\u003c/em\u003e blockades in advanced CRC was scanty, which demonstrated that only patients with dMMR might benefit from PD-1 blockade according to Keynote 177 clinical trial [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. As a result, traditional chemotherapy still played an important role in the treatment for CRC. However, it shoud be noted that ORR of chemotherapy was comparatively limited, suggesting the urgent exploration of potential biomarkers that could predict the efficacy of traditional chemotherapy was an important research direction [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. At present, biomarkers that might predict the sensitivity to traditional chemotherapy were predominately focused on genetic polymorphisms, ctDNA and somatic gene mutations [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Noteworthily, a recently reported polymorphism study initiated by JS Su and colleagues indicated that \u003cem\u003ePD-L1\u003c/em\u003e gene polymorphism 901T\u0026thinsp;\u0026gt;\u0026thinsp;C could be used as a potential biomarker to involve in the prognosis of patients with CRC who received capecitabine-based adjuvant chemotherapy through the mediation of the mRNA expression of \u003cem\u003ePD-L1\u003c/em\u003e [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Furthermore, another study initiated by JT and colleagues investigated the clinical significance of ctDNA for guiding the prognosis of patients with high-risk stage Ⅲ colon cancer, which indicated that the monitoring of ctDNA might make a difference to predict the prognosis of patients with high-risk stage Ⅲ colon cancer [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Additionally, AJ Li and colleagues performed a study to explore the predictive association between \u003cem\u003ePIK3CA\u003c/em\u003e and \u003cem\u003eTP53\u003c/em\u003e somatic mutations status and OS for patients with stage Ⅱ and Ⅲ CRC [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. And the results suggested that patients with \u003cem\u003ePIK3CA\u003c/em\u003e and \u003cem\u003eTP53\u003c/em\u003e double mutations were correlated with worse OS. Collectively, all the above findings demonstrated that the related DNA status of colon cancer or rectal cancer might predict the prognosis of patients with CRC who were treated with conventional chemotherapy to some extent.\u003c/p\u003e \u003cp\u003eAlthough this study was designed as a retrospective analysis, we still carried out the prognostic analysis of the 82 patients with CRC who received capecitabine-based adjuvant chemotherapy. And the results showed that the median DFS of the 82 patients was 4.5 years and the median OS of the 82-patient cohort was 5.7 years. The DFS and OS data in our study seemed to be lower than that in NO16968 study which was implemented to identify the feasibility of oxaliplatin combined with capecitabine as adjuvant therapy for stage Ⅲ CRC [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The discrepancy between the two study could be attributed to the fact that more patients with an ECOG performance status of 2 score were included in our study than that in the NO16968 study and the results of the Cox analysis suggested that patients with ECOG of 2 score conferred a worse prognosis, which was consistent with the previous study [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Besides, it should be noted that this study was designed as a retrospective analysis. Management of the patients in retrospective study was not sufficient and normative compared with well-designed phase Ⅲ clinical trial. And the actual completion of capecitabine monotherapy regimen in this study was only 5 cycles, and the CAPEOX regimen was only 4 cycles. The insufficient adjuvant chemotherapy might stand a good chance to compromise the survival of the patients to some extent [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe somatic mutation and TMB analysis in this study was based on the targeted next-generation sequencing technology, which was proved to be an accurate and available approach for measuring targeted gene mutation with a greater depth and less time compared with whole exome sequencing [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Consequently, it was a useful and crucial method for the somatic mutation detection and TMB analysis in view of the wide genetic heterogeneity of CRC [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Therefore, the NGS technique could accurately analysis somatic mutation genes that related to CRC incidence and identify the accurate TMB analysis. In this study, somatic mutation results based on NGS analysis indicated that \u003cem\u003eTP53\u003c/em\u003e gene was of the highest mutation frequency in postsurgical CRC tissue (62.2%), which was basically consistent with the results of the research initiated by the DW Lee and colleagues investigated TMB in patients with CRC [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. They identified that APC gene was of highest mutation frequency, \u003cem\u003eTP53\u003c/em\u003e gene was the second most common mutated gene with the prevalence of approximately 63.8%. These results exhibited that the essential function of \u003cem\u003eTP53\u003c/em\u003e gene in tumorigenesis. \u003cem\u003eTP53\u003c/em\u003e gene was a tumor suppressor gene that regulated cell division by keeping cells from growing and proliferating., thus playing an important regulatory role in the development and recurrence of colon cancer or rectal cancer [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Furthermore, present study confirmed that \u003cem\u003eAPC\u003c/em\u003e, \u003cem\u003eRAS\u003c/em\u003e, \u003cem\u003ePIK3CA\u003c/em\u003e and \u003cem\u003eEGFR\u003c/em\u003e were closely related to the tumorigenesis and development of CRC, and the incidence among the 82 patients with CRC was 58.5%, 47.6%, 34.1% and 30.4%, respectively. The somatic mutation profile was basically consistent with the results of the previous study initiated by MAV Cavagnari and colleagues [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. They also used NGS technique to implement the relevant somatic mutant genes based on the DNA extracted from frozen or paraffin-embedded tumor tissues. Interestingly, we also found a 4.9% and 2.4% incidence of \u003cem\u003eERBB2\u003c/em\u003e and \u003cem\u003eMTOR\u003c/em\u003e genes, which might be attributed to the heterogeneity of the development of CRC to some extent and some rare gene mutations could also contribute to the tumorigenesis of colon cancer or rectal cancer [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWith regard to the TMB analysis, the results of this study exhibited that the overall somatic mutation burden of the 82 patients was relatively low with a median TMB of 3.9/Mb (range: 0-48.6/Mb), which was similar with two colorectal cancer studies reported previously [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The median TMB in 516 patients with CRC patients of the DW\u0026rsquo;s study was 4.5/Mb, while the median TMB in 29 patients with CRC of the MG\u0026rsquo;s study was approximately 5.0/Mb. Previous study published in the journal of Nature explored the TMB in various solid tumors [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], and the results indicated that the TMB in melanoma and lung cancer was of the highest incidence of median TMB with approximately 10/Mb. However, TMB in colorectal cancer was almost 3/Mb, which were basically consistent with the TMB results in our study. Furthermore, it should be noted that the prognostic analysis exhibited that patients with TMB-H conferred a worse OS, which contradicted the results of a previous study initiated by DW Lee and colleagues. They found that patients with TMB-H were associated with superior RFS and OS. The discrepancy could be attributed to the threshold value of TMB-H and TMB-L. The TMB in DW Lee's team was distinguished by 7/Mb, and the proportion of patients with TMB-H was only 10.7%, which might contribute to the difference in prognosis [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. However, TMB analysis of our study was basically consistent with that of the previous study initiated by MAV C and colleagues, which exhibited that the median OS of patients with TMB\u0026thinsp;\u0026ge;\u0026thinsp;5 and TMB\u0026thinsp;\u0026lt;\u0026thinsp;5 was 33.6 and 41.0 months, respectively, even the difference was not statistically significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Furthermore, a recent study by LB Xu and colleagues found that soft tissue sarcoma patients with high TMB conferred a worse prognosis when received conventional adjuvant chemotherapy, which was consistent with the results of our study as well [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Interestingly, the definition of TMB threshold in their study was the same as that in our study using the median threshold to distinguish TMB high and TMB low. Collectively, our study preliminarily demonstrated that patients with CRC of higher TMB were associated with worse prognosis when received capecitabine-based adjuvant chemotherapy. And the conclusion needed to be confirmed in large-scale clinical trials subsequently.\u003c/p\u003e \u003cp\u003eThe limitions of this study were as follows: firstly, the sample size of the study was relatively small, and the clinical significance of TMB in patient with CRC needed to be further evaluated in a in a larger population. Secondly, the TMB analysis in this study was restricted to only 40 genes in 5 signaling pathways that related to CRC tumorigenesis and development. Further study based on more genes was needed to clarify the function in all exons.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003e Collectively, our study provided and highlighted real-world medical evidence regarding the prognostic data of patients with CRC who were treated with surgical resection and capecitabine-based adjuvant chemotherapy in real-world. Furthermore, the prognostic significance of TMB status suggested that TMB could be considered as a potential biomarker to predict the prognosis of patients with CRC who received capecitabine-based adjuvant chemotherapy clinically.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of\u0026nbsp;Henan Provincial People\u0026rsquo;s Hospital\u0026nbsp;(2022-073-06).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe written informed consent was obtained from all the patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from the Natural science foundation of Henan province (No. 162300410292)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by YZZ, HZ, YZ and WCC. The study was conceived and supervised by DL, The first draft of the manuscript was written by YZZ and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors would like to gratitude patients who participated in the present study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A: Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018, 68(6):394-424.\u003c/li\u003e\n\u003cli\u003eBai M, Li ZG, Ba Y: Influence of KDR Genetic Variation on the Efficacy and Safety of Patients with Chemotherapy Refractory Metastatic CRC Who Received Apatinib Treatment. Int J Gen Med 2021, 14:1041-1055.\u003c/li\u003e\n\u003cli\u003eOkuda H, Shimomura M, Ikeda S, Nakahara M, Miguchi M, Ishizaki Y, Saitoh Y, Toyota K, Sumitani D, Shimizu Y et al: A prospective feasibility study of uracil-tegafur and leucovorin as adjuvant chemotherapy for patients aged\u0026thinsp;\u0026ge;\u0026thinsp;80 years after curative resection of colorectal cancer, the HiSCO-03 study. Cancer Chemother Pharmacol 2023, 91(4):317-324.\u003c/li\u003e\n\u003cli\u003eKishore C, Bhadra P: Current advancements and future perspectives of immunotherapy in colorectal cancer research. Eur J Pharmacol 2021, 893:173819.\u003c/li\u003e\n\u003cli\u003eTintelnot J, Stein A: Immunotherapy in colorectal cancer: Available clinical evidence, challenges and novel approaches. World J Gastroenterol 2019, 25(29):3920-3928.\u003c/li\u003e\n\u003cli\u003eGrothey A, Sobrero AF, Shields AF, Yoshino T, Paul J, Taieb J, Souglakos J, Shi Q, Kerr R, Labianca R et al: Duration of Adjuvant Chemotherapy for Stage III Colon Cancer. N Engl J Med 2018, 378(13):1177-1188.\u003c/li\u003e\n\u003cli\u003eYamazaki K, Yamanaka T, Shiozawa M, Manaka D, Kotaka M, Gamoh M, Shiomi A, Makiyama A, Munemoto Y, Rikiyama T et al: Oxaliplatin-based adjuvant chemotherapy duration (3 versus 6 months) for high-risk stage II colon cancer: the randomized phase III ACHIEVE-2 trial. Ann Oncol 2021, 32(1):77-84.\u003c/li\u003e\n\u003cli\u003eDasari A, Morris VK, Allegra CJ, Atreya C, Benson AB, 3rd, Boland P, Chung K, Copur MS, Corcoran RB, Deming DA et al: ctDNA applications and integration in colorectal cancer: an NCI Colon and Rectal-Anal Task Forces whitepaper. Nat Rev Clin Oncol 2020, 17(12):757-770.\u003c/li\u003e\n\u003cli\u003eOsumi H, Shinozaki E, Yamaguchi K, Zembutsu H: Clinical utility of circulating tumor DNA for colorectal cancer. Cancer Sci 2019, 110(4):1148-1155.\u003c/li\u003e\n\u003cli\u003eLuo H, Zhao Q, Wei W, Zheng L, Yi S, Li G, Wang W, Sheng H, Pu H, Mo H et al: Circulating tumor DNA methylation profiles enable early diagnosis, prognosis prediction, and screening for colorectal cancer. Sci Transl Med 2020, 12(524).\u003c/li\u003e\n\u003cli\u003eHamaguchi R, Tsuchiya T, Miyata G, Sato T, Takahashi K, Miura K, Oshio H, Ohori H, Ariyoshi K, Oyamada S et al: Efficacy of oral administration of cystine and theanine in colorectal cancer patients undergoing capecitabine-based adjuvant chemotherapy after surgery: a multi-institutional, randomized, double-blinded, placebo-controlled, phase II trial (JORTC-CAM03). Support Care Cancer 2020, 28(8):3649-3657.\u003c/li\u003e\n\u003cli\u003eYang L, Sun Y, Huang XE, Yu DS, Zhou JN, Zhou X, Li DZ, Guan X: Carcinoma microsatellite instability status as a predictor of benefit from fluorouracil-based adjuvant chemotherapy for stage II rectal cancer. Asian Pac J Cancer Prev 2015, 16(4):1545-1551.\u003c/li\u003e\n\u003cli\u003eTaieb J, Shi Q, Pederson L, Alberts S, Wolmark N, Van Cutsem E, de Gramont A, Kerr R, Grothey A, Lonardi S et al: Prognosis of microsatellite instability and/or mismatch repair deficiency stage III colon cancer patients after disease recurrence following adjuvant treatment: results of an ACCENT pooled analysis of seven studies. Ann Oncol 2019, 30(9):1466-1471.\u003c/li\u003e\n\u003cli\u003eSteuer CE, Ramalingam SS: Tumor Mutation Burden: Leading Immunotherapy to the Era of Precision Medicine? J Clin Oncol 2018, 36(7):631-632.\u003c/li\u003e\n\u003cli\u003eBagchi S, Yuan R, Engleman EG: Immune Checkpoint Inhibitors for the Treatment of Cancer: Clinical Impact and Mechanisms of Response and Resistance. Annu Rev Pathol 2021, 16:223-249.\u003c/li\u003e\n\u003cli\u003eGuzik K, Tomala M, Muszak D, Konieczny M, Hec A, Blaszkiewicz U, Pustula M, Butera R, Domling A, Holak TA: Development of the Inhibitors that Target the PD-1/PD-L1 Interaction-A Brief Look at Progress on Small Molecules, Peptides and Macrocycles. Molecules 2019, 24(11).\u003c/li\u003e\n\u003cli\u003eBerland L, Heeke S, Humbert O, Macocco A, Long-Mira E, Lassalle S, Lespinet-Fabre V, Lalvee S, Bordone O, Cohen C et al: Current views on tumor mutational burden in patients with non-small cell lung cancer treated by immune checkpoint inhibitors. J Thorac Dis 2019, 11(Suppl 1):S71-s80.\u003c/li\u003e\n\u003cli\u003eEfremova M, Finotello F, Rieder D, Trajanoski Z: Neoantigens Generated by Individual Mutations and Their Role in Cancer Immunity and Immunotherapy. Front Immunol 2017, 8:1679.\u003c/li\u003e\n\u003cli\u003eLin C, Shi X, Zhao J, He Q, Fan Y, Xu W, Shao Y, Yu X, Jin Y: Tumor Mutation Burden Correlates With Efficacy of Chemotherapy/Targeted Therapy in Advanced Non-Small Cell Lung Cancer. Front Oncol 2020, 10:480.\u003c/li\u003e\n\u003cli\u003eSchrock AB, Ouyang C, Sandhu J, Sokol E, Jin D, Ross JS, Miller VA, Lim D, Amanam I, Chao J et al: Tumor mutational burden is predictive of response to immune checkpoint inhibitors in MSI-high metastatic colorectal cancer. Ann Oncol 2019, 30(7):1096-1103.\u003c/li\u003e\n\u003cli\u003eInnocenti F, Ou FS, Qu X, Zemla TJ, Niedzwiecki D, Tam R, Mahajan S, Goldberg RM, Bertagnolli MM, Blanke CD et al: Mutational Analysis of Patients With Colorectal Cancer in CALGB/SWOG 80405 Identifies New Roles of Microsatellite Instability and Tumor Mutational Burden for Patient Outcome. J Clin Oncol 2019, 37(14):1217-1227.\u003c/li\u003e\n\u003cli\u003eLee DW, Han SW, Bae JM, Jang H, Han H, Kim H, Bang D, Jeong SY, Park KJ, Kang GH et al: Tumor Mutation Burden and Prognosis in Patients with Colorectal Cancer Treated with Adjuvant Fluoropyrimidine and Oxaliplatin. Clin Cancer Res 2019, 25(20):6141-6147.\u003c/li\u003e\n\u003cli\u003ePai SG, Carneiro BA, Chae YK, Costa RL, Kalyan A, Shah HA, Helenowski I, Rademaker AW, Mahalingam D, Giles FJ: Correlation of tumor mutational burden and treatment outcomes in patients with colorectal cancer. J Gastrointest Oncol 2017, 8(5):858-866.\u003c/li\u003e\n\u003cli\u003eLee DW, Han SW, Cha Y, Bae JM, Kim HP, Lyu J, Han H, Kim H, Jang H, Bang D et al: Association between mutations of critical pathway genes and survival outcomes according to the tumor location in colorectal cancer. Cancer 2017, 123(18):3513-3523.\u003c/li\u003e\n\u003cli\u003eXu LB, Zhao ZG, Xu SF, Zhang XX, Liu T, Jing CY, Zhang SG, Yu SJ: The landscape of gene mutations and clinical significance of tumor mutation burden in patients with soft tissue sarcoma who underwent surgical resection and received conventional adjuvant therapy. Int J Biol Markers 2020, 35(3):14-22.\u003c/li\u003e\n\u003cli\u003eZhang Y, Song J, Zhao Z, Yang M, Chen M, Liu C, Ji J, Zhu D: Single-cell transcriptome analysis reveals tumor immune microenvironment heterogenicity and granulocytes enrichment in colorectal cancer liver metastases. Cancer Lett 2020, 470:84-94.\u003c/li\u003e\n\u003cli\u003eHermann, Brenner, Chen: The colorectal cancer epidemic: challenges and opportunities for primary, secondary and tertiary prevention. British Journal of Cancer 2018.\u003c/li\u003e\n\u003cli\u003eAi L, Chen J, Yan H, He Q, Luo P, Xu Z, Yang X: Research Status and Outlook of PD-1/PD-L1 Inhibitors for Cancer Therapy. Drug Des Devel Ther 2020, 14:3625-3649.\u003c/li\u003e\n\u003cli\u003eAndr\u0026eacute; T, Shiu KK, Kim TW, Jensen BV, Jensen LH, Punt C, Smith D, Garcia-Carbonero R, Benavides M, Gibbs P et al: Pembrolizumab in Microsatellite-Instability-High Advanced Colorectal Cancer. N Engl J Med 2020, 383(23):2207-2218.\u003c/li\u003e\n\u003cli\u003eMalla SB, Fisher DJ, Domingo E, Blake A, Hassanieh S, Redmond KL, Richman SD, Youdell M, Walker SM, Logan GE et al: In-depth Clinical and Biological Exploration of DNA Damage Immune Response as a Biomarker for Oxaliplatin Use in Colorectal Cancer. Clin Cancer Res 2021, 27(1):288-300.\u003c/li\u003e\n\u003cli\u003eReece M, Saluja H, Hollington P, Karapetis CS, Vatandoust S, Young GP, Symonds EL: The Use of Circulating Tumor DNA to Monitor and Predict Response to Treatment in Colorectal Cancer. Front Genet 2019, 10:1118.\u003c/li\u003e\n\u003cli\u003eSu J, Dai B, Yuan W, Wang G, Zhang Z, Li Z, Liu J, Song J: The influence of PD-L1 genetic variation on the prognosis of R0 resection colorectal cancer patients received capecitabine-based adjuvant chemotherapy: a long-term follow-up, real-world retrospective study. Cancer Chemother Pharmacol 2020, 85(5):969-978.\u003c/li\u003e\n\u003cli\u003eTie J, Cohen JD, Wang Y, Christie M, Simons K, Lee M, Wong R, Kosmider S, Ananda S, McKendrick J et al: Circulating Tumor DNA Analyses as Markers of Recurrence Risk and Benefit of Adjuvant Therapy for Stage III Colon Cancer. JAMA Oncol 2019, 5(12):1710-1717.\u003c/li\u003e\n\u003cli\u003eLi AJ, Li HG, Tang EJ, Wu W, Chen Y, Jiang HH, Lin MB, Yin L: PIK3CA and TP53 mutations predict overall survival of stage II/III colorectal cancer patients. World J Gastroenterol 2018, 24(5):631-640.\u003c/li\u003e\n\u003cli\u003eSchmoll HJ, Tabernero J, Maroun J, de Braud F, Price T, Van Cutsem E, Hill M, Hoersch S, Rittweger K, Haller DG: Capecitabine Plus Oxaliplatin Compared With Fluorouracil/Folinic Acid As Adjuvant Therapy for Stage III Colon Cancer: Final Results of the NO16968 Randomized Controlled Phase III Trial. J Clin Oncol 2015, 33(32):3733-3740.\u003c/li\u003e\n\u003cli\u003eYang J, Xu H, Guo X, Zhang J, Ye X, Yang Y, Ma X: Pretreatment Inflammatory Indexes as Prognostic Predictors for Survival in Colorectal Cancer Patients Receiving Neoadjuvant Chemoradiotherapy. Sci Rep 2018, 8(1):3044.\u003c/li\u003e\n\u003cli\u003eIveson TJ, Sobrero AF, Yoshino T, Souglakos I, Ou FS, Meyers JP, Shi Q, Grothey A, Saunders MP, Labianca R et al: Duration of Adjuvant Doublet Chemotherapy (3 or 6 months) in Patients With High-Risk Stage II Colorectal Cancer. J Clin Oncol 2021, 39(6):631-641.\u003c/li\u003e\n\u003cli\u003eBorowka P, Pulaski L, Marciniak B, Borowska-Struginska B, Dziadek J, Zadzinska E, Lorkiewicz W, Strapagiel D: Screening methods for detection of ancient Mycobacterium tuberculosis complex fingerprints in next-generation sequencing data derived from skeletal samples. Gigascience 2019, 8(6).\u003c/li\u003e\n\u003cli\u003eZhang H, Deng YM, Chen ZC, Tang YC, Yang S, Zhang SD, Liang JM, Wang YG, Wu X, Zhang RW et al: Clinical significance of tumor mutation burden and DNA damage repair in advanced stage non-small cell lung cancer patients. Eur Rev Med Pharmacol Sci 2020, 24(14):7664-7672.\u003c/li\u003e\n\u003cli\u003eLi C, Bu J, Liao Y, Zhang J, Han J, Zhang H, Xing H, Li Z, Wu H, Liang L et al: High Expressions of CUL4A and TP53 in Colorectal Cancer Predict Poor Survival. Cell Physiol Biochem 2018, 51(6):2829-2842.\u003c/li\u003e\n\u003cli\u003eCavagnari MAV, Silva TD, Pereira MAH, Sauer LJ, Shigueoka D, Saad SS, Bar\u0026atilde;o K, Ribeiro CCD, Forones NM: Impact of genetic mutations and nutritional status on the survival of patients with colorectal cancer. BMC Cancer 2019, 19(1):644.\u003c/li\u003e\n\u003cli\u003eDunlop MG, Dobbins SE, Farrington SM, Jones AM, Palles C, Whiffin N, Tenesa A, Spain S, Broderick P, Ooi LY et al: Common variation near CDKN1A, POLD3 and SHROOM2 influences colorectal cancer risk. Nat Genet 2012, 44(7):770-776.\u003c/li\u003e\n\u003cli\u003eLawrence MS, Stojanov P, Polak P, Kryukov GV, Cibulskis K, Sivachenko A, Carter SL, Stewart C, Mermel CH, Roberts SA et al: Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature 2013, 499(7457):214-218.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"colorectal cancer, adjuvant chemotherapy, tumor mutation burden, prognosis, capecitabine","lastPublishedDoi":"10.21203/rs.3.rs-4357440/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4357440/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eThis study aimed to investigate the prognostic implications of tumor mutation burden (TMB) in patients with colorectal cancer (CRC) who underwent surgical resection and capecitabine-based adjuvant chemotherapy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: A total of 82 patients with CRC who underwent surgical resection and capecitabine-based adjuvant chemotherapy were included in this study retrospectively. Tumor tissue specimens were collected for DNA extraction after surgical resection. Somatic mutation detection and TMB analysis were performed using next-generation sequencing (NGS) of tumor-related genes. The recurrence status of the patients was assessed in the hospital during the adjuvant chemotherapy period, and the long-term survival data of patients were obtained by telephone follow-up. The univariate analysis between TMB status and prognosis was carried out by Kaplan-Meier survival analysis and adjusted by multivariate Cox regression analysis subsequently.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: The median follow-up period of this study was 5.3 years (range: 0.25-9.6 years). The median disease-free survival (DFS) of the 82 patients was 4.5 years, the median overall survival (OS) was 5.7 years. The results of NGS analysis demonstrated that the most common mutated somatic genes among the 82 patients were \u003cem\u003eTP53\u003c/em\u003e, \u003cem\u003eAPC\u003c/em\u003e, \u003cem\u003eRAS\u003c/em\u003e, \u003cem\u003ePIK3CA\u003c/em\u003e and \u003cem\u003eEGFR\u003c/em\u003e, and the prevalence was 62.2%, 58.5%, 47.6%, 34.1% and 30.4%, respectively. Other somatic mutant genes were of relatively low frequency (\u0026lt;30%). Regarding the TMB analysis, the overall somatic mutation burden of the 82 patients was comparatively low [median: 3.9/Mb (range: 1.6-48.6/Mb)]. TMB status was divided into TMB-L (≤3.9/Mb) and TMB-H (\u0026gt;3.9/Mb) according to the median TMB threshold. And the patients with TMB-L and TMB-H were observed in 42 cases and 40 cases, respectively. Prognostic analysis according to TMB status demonstrated that the median OS of patients with TMB-L and TMB-H was 6.5 and 4.5 years, respectively (\u003cem\u003eP\u003c/em\u003e=0.009). Additionally, in order to adjust the confounding factors that might influence OS, a multivariate Cox regression analysis was introduced and the results exhibited that TMB status was an independent factor for OS (HR=0.71, \u003cem\u003eP\u003c/em\u003e=0.011).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: TMB might be considered as a potential biomarker for predicting the prognosis of patients with CRC who underwent surgical resection and capecitabine-based adjuvant chemotherapy. Results of this study should be elucidated in large-scale prospective clinical trial subsequently.\u003c/p\u003e","manuscriptTitle":"Prognostic implications of tumor mutation burden in postoperative patients with colorectal cancer who received capecitabine-based adjuvant chemotherapy: a retrospective exploratory study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-10 20:47:06","doi":"10.21203/rs.3.rs-4357440/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e560cae4-d539-4c83-92a4-a4dfddfbceb4","owner":[],"postedDate":"May 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-07-18T08:32:02+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-10 20:47:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4357440","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4357440","identity":"rs-4357440","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}