Introduction
Colorectal Cancer (CRC) is a malignant tumor that originates from the mucosal epithelial cells of the colorectal tract, including colon cancer and rectal cancer.1 The pathological type of CRC is most commonly adenocarcinoma, which is mainly caused by the combined effect of genetic and environmental factors.2,3 The lesion often gradually develops from adenomatous polyps of the colorectal mucosal epithelium. At present, globally, the incidence rate of colorectal cancer ranks third and the mortality rate ranks second.4 The incidence and mortality rates of CRC in developing countries are both on a rapid upward trend, CRC is the second most common type of cancer in China.5,6
Distant metastasis of CRC refers to the process in which cancer cells break through the local tissue barrier of the colon and rectum, spread to distant organs of the body through the blood circulation, lymphatic system or directly, and form new tumor lesions.7 The common distant metastasis sites of CRC include organs such as the liver, lungs, bones, and brain.8,9 Distant metastasis of CRC means that tumor cells establish a new growth environment in distant organs, which greatly increases the difficulty and complexity of treatment.10,11 Distant metastasis has a significant adverse effect on the prognosis of CRC. Studies have shown that the survival rate of CRC patients with distant metastasis is significantly lower than that of patients without distant metastasis.12,13 In addition, distant metastasis not only directly affects the survival of CRC patients, but also triggers a series of serious clinical symptoms.13,14
Distant metastasis of CRC is jointly affected by multiple risk factors. Distant metastasis of CRC is influenced by the pathological characteristics of the tumor and molecular biological factors.15,16 In addition, factors such as the patient’s age and physical condition can also affect the risk of distant metastasis.17,18 Elderly patients and those with underlying diseases are more prone to distant metastasis due to their weakened immune systems.19 Meanwhile, unhealthy lifestyles such as smoking, excessive drinking, as well as obesity, which can cause metabolic abnormalities, also promote the occurrence and development of distant metastasis of CRC to a certain extent.20 Clarifying the risk factors of distant metastasis of CRC is of great significance for the early identification of high-risk populations and the formulation of individualized prevention and treatment strategies.
In the research field of risk factors for distant metastasis of CRC, the inflammatory state and nutritional level of the body have attracted much attention in recent years. The inflammatory environment can have a significant impact on the occurrence and development of tumors.21 Studies have found that chronic inflammation can promote the proliferation, survival, invasion, and metastasis of tumor cells by activating key signaling pathways such as nuclear factor κB (NF-κB) and signal transducer and activator of transcription 3 (STAT3).22,23 In addition, chronic inflammation can also reshape the tumor microenvironment, promote angiogenesis, and create conditions for tumor cells to enter the bloodstream and colonize at a distance.21 Nutritional status also plays an important role in the process of distant metastasis of CRC. On the one hand, malnutrition can weaken the immune function of the body, reducing the immune system’s ability to monitor and kill tumor cells, and providing conditions for the distant metastasis of tumor cells.24 On the other hand, abnormal metabolism of nutrients may affect the proliferation, apoptosis and metastasis-related signaling pathways of tumor cells, promoting the occurrence of distant metastasis of CRC.25
Pan-immune inflammation value (PIV), as an emerging biomarker, can comprehensively and intuitively assess the systemic inflammatory and immune status by integrating the counts of neutrophils, monocytes, lymphocytes, and platelets in the circulating blood (monocyte×neutrophil×platelet/lymphocyte).26 PIV is a comprehensive immunoinflammatory biomarker associated with the clinical stage,27,28 and prognosis26 of CRC. Prognostic nutritional index (PNI) is calculated by the formula: serum albumin + 5 × lymphocyte count. It combines the serum albumin level, which reflects the nutritional status, and the lymphocyte count, which reflects the immune function, and can better represent the overall nutritional and immune status of patients.29 PNI is often used to predict the incidence and prognosis of malignant tumors.30 Are PIV and PNI levels associated with the risk of distant metastasis of CRC? Kirsten rat sarcoma viral oncogene homologue (KRAS) is a key molecule in the EGFR-dependent RAS/RAF/MAPK pathway, KRAS mutations can lead to the continuous activation of this signaling pathway and induce the progression of CRC.31 Are there any differences in the relationship between PIV and PNI and the risk of distant metastasis in CRC patients with KRAS mutations and those without KRAS mutations? To solve this problem, this study was carried out.
Materials and Methods
Study Cohort
This study retrospectively analyzed 2408 patients with CRC who were treated at Meizhou People’s Hospital from December 2018 to March 2025. This study was performed under the guidance of the Declaration of Helsinki and approved by the Ethics Committee of Medicine, Meizhou People’s Hospital. Patients who met the following conditions were included in this study: (1) patients confirmed as CRC by pathological examination; (2) CRC patients without other malignant tumors; (3) no anti-tumor treatment was received before admission; and (4) the test records of laboratory indicators are complete. Patients with the following conditions were excluded from this study: (1) patients with a previous history of other malignant tumors; (2) patients with severe systemic underlying diseases and incomplete or failed functions of important organs; (3) CRC patients with other malignant tumors; and (4) clinical records incomplete.
Data Collection
The clinical data were collected, such as age, gender, body mass index (BMI), personal living habits (history of cigarette smoking and alcoholism), disease history (hypertension, diabetes mellitus, viral hepatitis), tumor stage (T stage and N stage), and the pathological and imaging examination results. The results of count of monocyte, neutrophil, platelet, and lymphocyte, and albumin were collected during the first hospital examination. The degree of obesity or emaciation is classified into three grades based on BMI: underweight (BMI <18.5 kg/m2), normal weight (BMI 18.5 to 23.9 kg/m2), and overweight (BMI 24.0 to 28.0 kg/m2).32
Calculation of PIV and PNI and Statistics Analysis
PIV and PNI were calculated according to the following formula:
● PIV = monocyte count (109/L) × neutrophil count (109/L) × platelet count (109/L) / lymphocyte count (109/L)
● PNI=serum albumin (g/L) + 5 × lymphocyte count (109/L)
In our study, we aimed to determine a moderate effect size with a significance level (α) set at 0.05 and a power (1-β) set at 0.80. The sample size required was approximately 500 patients as calculated using the G*Power software. Data analysis was performed using SPSS statistical software version 26.0 (IBM Inc., USA). Continuous variables are expressed as median and interquartile range (IQR) (25th to 75th percentiles), and are compared by Mann–Whitney U-test. Categorical variables are expressed as n (%), and analyzed using χ2 test. The optimal thresholds of PIV and PNI were evaluated by receiver operating characteristic (ROC) curve analysis. Logistic regression analysis was used to reveal the relationship of PIV and PNI and distant metastasis in CRC with and without KRAS mutation, respectively, adjusting for some influencing factors, such as age, gender, BMI, cigarette smoking, alcoholism, diabetes mellitus, family history of tumor, T stage, and N stage. p<0.05.
Results
The Clinical Features of the Patients with CRC
In this study cohort, there were 1502 (62.4%) male, 906 (37.6%) female, 783 (32.5%) <60 years old and 1625 (67.5%) aged ≥60, respectively. There were 294 (12.2%) cases with underweight and 729 (30.3%) cases with overweight respectively. The number of patients with a history of cigarette smoking, alcoholism, diabetes mellitus, and family history of tumor was 211 (8.8%), 95 (3.9%), 361 (15.0%), and 33 (1.4%), respectively. There were 308 (12.8%) and 2100 (87.2%) cases with T1-T2, and T3-T4 stage; 1813 (75.3%) and 595 (24.7%) cases with N0-N1 and N2-N3 stage, respectively. The number of patients with KRAS mutation and NRAS mutation was 1085 (45.1%) and 86 (3.6%), respectively. The average levels of PIV and PNI was 327.62 (183.19, 590.36) and 46.70 (43.10, 50.90), respectively. There were 825 (34.3%) patients with distant metastasis and 1583 (65.7%) without (Table 1).
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Table 1 The Clinical Features of the Patients with CRC
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Comparison of the Clinical Features Between Patients with and Without Distant Metastasis in CRC
The proportions of patients with stage T3-T4 (χ2=96.795, p<0.001), stage N2-N3 (χ2=377.441, p<0.001), and KRAS mutation (χ2=4.033, p=0.047) in CRC patients with distant metastasis were higher than those in patients without distant metastasis. There were no significant differences in other clinical features between the two groups (Table 2).
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Table 2 Comparison of the Clinical Features Between Patients with and Without Without Distant Metastasis in CRC Patients
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The average levels of PIV and PNI was 296.25 (171.62, 500.02) and 47.20 (43.60, 51.15) in patients without distant metastasis, 405.94 (214.04, 852.33) and 46.00 (42.08, 50.05) in patients without distant metastasis, respectively. The differences in PIV and PNI levels between the two groups were statistically significant (p<0.001) (Table 2).
When distant metastasis was set as the endpoint of PIV and PNI in ROC analysis, the cutoff value of PIV was 339.50 (sensitivity 58.9%, specificity 62.5%, area under the ROC curve (AUC): 0.627), and the PNI cutoff value was 45.53 (sensitivity 47.3%, specificity 66.4%, AUC: 0.590) (Figure 1).
 |
Figure 1 The ROC curve analysis of PIV (A) and PNI (B) to distinguish distant metastasis. Abbreviations: PIV, pan-immune-inflammation value; PNI, prognostic nutritional index.
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Comparison of the Clinical Features Between Distant Metastasis Patients and No Distant Metastasis Patients in CRC Patients Without and with KRAS Mutation, Respectively
In CRC patients without KRAS mutation, the proportions of patients with stage T3-T4 (χ2=39.267, p<0.001), and stage N2-N3 (χ2=176.372, p<0.001) in CRC patients with distant metastasis were higher than those in patients without distant metastasis. In CRC patients with KRAS mutation, the proportions of patients with stage T3-T4 (χ2=59.593, p<0.001), stage N2-N3 (χ2=205.034, p<0.001), high PIV (≥339.50) (χ2=97.343, p<0.001), and low PNI (<45.53) (χ2=29.400, p<0.001) in CRC patients with distant metastasis were higher than those in patients without distant metastasis (Table 3).
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Table 3 Comparison of the Clinical Features Between Distant Metastasis Patients and No Distant Metastasis Patients in CRC Patients Without and with KRAS Mutation, Respectively
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Logistic Regression Analysis of Risk Factors Associated with Distant Metastasis in CRC
Univariate analysis showed that stage T3-T4 (odds ratio (OR): 5.873, 95% confidence interval (CI): 3.967–8.695, p<0.001), and stage N2-N3 (OR: 6.628, 95% CI: 5.413–8.116, p<0.001), KRAS mutation (OR: 1.189, 95% CI: 1.004–1.408, p=0.045), high PIV (OR: 1.938, 95% CI: 1.634–2.299, p<0.001), and low PNI (OR: 1.457, 95% CI: 1.229–1.727, p<0.001) were significantly associated with distant metastasis in CRC (Table 4).
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Table 4 Logistic Regression Analysis of Risk Factors Associated with Distant Metastasis in CRC
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Multivariate logistic regression analysis showed that stage T3-T4 (OR: 3.827, 95% CI: 2.549–5.746, p<0.001), and stage N2-N3 (OR: 5.797, 95% CI: 4.705–7.144, p<0.001), KRAS mutation (OR: 1.400, 95% CI: 1.151–1.702, p=0.001), high PIV (OR: 1.713, 95% CI: 1.407–2.086, p<0.001), and low PNI (OR: 1.236, 95% CI: 1.013–1.50, p=0.037) were independently associated with distant metastasis in CRC (Table 4).
Logistic Regression Analysis of Risk Factors Associated with Distant Metastasis in CRC Without and with KRAS Mutation, Respectively
In CRC without KRAS mutation, multivariate regression analysis showed that stage T3-T4 (OR: 2.967, 95% CI: 1.804–4.880, p<0.001), and stage N2-N3 (OR: 5.109, 95% CI: 3.886–6.717, p<0.001) were associated with distant metastasis (Table 5).
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Table 5 Logistic Regression Analysis of Risk Factors Associated with Distant Metastasis in CRC Without and with KRAS Mutation, Respectively
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In CRC with KRAS mutation, multivariate regression analysis showed that stage T3-T4 (OR: 5.963, 95% CI: 2.897–12.273, p<0.001), and stage N2-N3 (OR: 7.094, 95% CI: 5.070–9.926, p<0.001), high PIV (OR: 2.867, 95% CI: 2.119–3.879, p<0.001), and low PNI (OR: 1.620, 95% CI: 1.184–2.215, p=0.003) were associated with distant metastasis (Table 5).
Discussion
Accurate prediction of distant metastasis of CRC can effectively assist clinical decision-making, create space for early intervention, and improve the survival rate and quality of life of patients. In this study, stage T3-T4 and stage N2-N3 were associated with distant metastasis in CRC with and without KRAS mutation. High PIV and low PNI were associated with distant metastasis in CRC patients with KRAS mutation, but not in patients without KRAS mutation.
The results of this study shows that the detection rate of KRAS gene mutations in CRC patients with distant metastasis is significantly higher than that in patients without distant metastasis, which is consistent with the conclusions of some previous studies.33–36 It indicates that KRAS gene mutation may be an important molecular event promoting distant metastasis of CRC. KRAS gene is a key node of the RAS-mitogen activated protein kinase (MAPK) signaling pathway, its mutation will lead to the continuous activation of this pathway.37,38 The continuously activated RAS-MAPK signaling pathway can enhance the proliferation ability of tumor cells, enabling tumor cells to gain a stronger survival advantage and thereby laying the cell quantity basis for distant metastasis.39 Meanwhile, the abnormal activation of this pathway can also affect the epithelial-mesenchymal transition (EMT) process of tumor cells, promoting the loss of polarity of epithelial cells, the acquisition of mesenchymal cell characteristics, changes in cell morphology, significantly enhanced invasion ability, and thus making it easier to break through the basement membrane, enter the blood circulation or lymphatic circulation, and undergo distant metastasis.40,41 In CRC without KRAS mutation, the RAS-MAPK signaling pathway is in a relatively normal regulatory state, and the invasion and metastasis ability of tumor cells is somewhat limited.
In addition, the influence of the tumor microenvironment on the difference in distant metastasis risk between patients with and without KRAS mutation cannot be ignored either.42 Mutations in the KRAS gene may alter the pattern of cytokine secretion by tumor cells, promoting the activation of tumor-associated fibroblasts (CAFs) and tumor angiogenesis.43,44 Activated CAFs can secrete transforming growth factor -β (TGF-β), inducing epithelial-mesenchymal transition (EMT) in tumor cells, enabling tumor cells to acquire the characteristics of mesenchymal cells, enhancing their motility and making them more prone to distant metastasis.45 Meanwhile, the abnormally generated tumor blood vessels provide a convenient channel for tumor cells to enter the bloodstream.46 In contrast, in the tumor microenvironment where the KRAS gene has not mutated, the interaction patterns between tumor cells and surrounding cells and the matrix are different, which is not conducive to the migration and distant colonization of tumor cells.
In terms of inflammation, KRAS mutations activate inflammatory signaling pathways such as nuclear factor-kappaB (NF-κB), and the persistent inflammatory microenvironment further intensifies this activation effect.47 Inflammatory cells such as macrophages and neutrophils accumulate in tumor tissues and secrete pro-inflammatory factors such as tumor necrosis factor -α (TNF-α) and interleukin-6 (IL-6).48 TNF-α can enhance the epithelial-mesenchymal transition (EMT) process of cells with KRAS mutation, enabling tumor cells to acquire stronger invasive ability.49 At the same time, TNF-α promotes angiogenesis, providing convenient conditions for tumor cells to enter the circulatory system and undergo distant metastasis.50 IL-6 can collaborate with the RAS-MAPK pathway activated by KRAS mutations through the JAK-STAT3 signaling pathway, enhancing the proliferation and survival ability of tumor cells and increasing the risk of distant metastasis.51 In addition, reactive oxygen species (ROS) produced under chronic inflammatory conditions may also induce mutations in other genes, forming a “secondary blow” with KRAS mutations, further intensifying the malignancy and metastasis potential of tumors.52 Liang et al found that the PIV level of CRC patients with KRAS mutations was significantly higher than that of patients without KRAS mutations.53 Xiong et al found that the PIV level of breast cancer patients with lymph node metastasis was significantly higher than that of patients without lymph node metastasis.54 Furthermore, some studies suggested that PIV was a promising biomarker to predict the prognosis of some tumors.55–57 In this study, high PIV is associated with distant metastasis in CRC patients with KRAS mutation, it enriches the data on the value of PIV in the assessment of tumor progression and prognosis.
Nutritional factors also have profound impacts on distant metastasis of CRC with KRAS mutations. Tumor cells have abnormal metabolism, especially in the context of KRAS mutation, and have a more vigorous demand for nutrients. Cells with KRAS mutation up-regulate glucose transporters to take up more glucose and perform aerobic glycolysis (Warburg effect), providing energy and biosynthetic raw materials for cell proliferation and metastasis.58,59 Meanwhile, abnormal fatty acid metabolism is also associated with KRAS mutation.60 Tumor cells can utilize fatty acid β-oxidation to generate energy or de novo synthesize fatty acids for cell membrane construction and signal transduction.61 When the body is malnourished, tumor cells may reshape their own metabolic patterns by plundering the nutrients of the host’s normal tissues, thereby enhancing their ability to colonize and survive at a distance.62 Some studies have suggested that PNI was associated with distant metastasis,25,63 recurrence,64 and long-term outcome30 in patients with CRC. In this study, low PNI is associated with distant metastasis in CRC patients with KRAS mutation, this result enriches the information of PNI in related fields.
The clinical significance of this study lies in providing new biomarkers for the prognosis assessment of CRC patients with KRAS mutation. By detecting the levels of PIV and PNI, clinicians can more accurately determine the risk of distant metastasis in patients, thereby formulating more individualized treatment plans. For KRAS-mutated CRC patients with elevated PIV and decreased PNI, it may be necessary to strengthen anti-inflammatory treatment and nutritional support to improve the immune-inflammatory state and nutritional status of the patients, and reduce the risk of distant metastasis. Moreover, this discovery also provides a direction for the development of new therapeutic targets. By targeting the immune-inflammatory and nutritional metabolic abnormalities reflected by PIV and PNI, corresponding therapeutic drugs may be developed to improve the efficacy and survival rate of CRC patients with KRAS mutation.
Although this study has obtained some valuable information, there are still some deficiencies. First, as a single-center retrospective study, the subjects of this research all came from the same medical institution. The representativeness of the sample was to some extent limited, which might lead to potential selection bias. Therefore, the results of this study require more research findings to be verified. Second, the cutoff values of PIV and PNI in this study were determined through ROC analysis. Currently, there is no widely accepted and unified cutoff value, and the cutoff values may vary among different studies. The AUC of PIV and PNI (0.627 and 0.590, respectively) for predicting distant metastasis of CRC is relatively low in this study, suggesting that these two indicators have limited discriminatory power. It might be related to the complexity of tumor metastasis and the high heterogeneity of CRC patients, therefore, more studies are needed to verify this result in the future. Third, this study was limited to analyzing PIV and PNI before treatment, but failed to consider the relationship between the changes of PIV and PNI before and after chemotherapy and distant metastasis. Finally, this study did not combine the indicators of inflammation and nutritional statuses with imaging variables to assess the risk of distant metastasis of CRC. Despite the above limitations, since the indicators related to PIV and PNI indices can be easily obtained from laboratory tests. The levels of PIV and PNI have certain clinical application value in predicting distant metastasis in CRC patients, especially for CRC patients with KRAS mutation.
Conclusion
Stage T3-T4 and stage N2-N3 were associated with distant metastasis in CRC with and without KRAS mutation. High PIV and low PNI were associated with distant metastasis in CRC patients with KRAS mutation, but not in patients without KRAS mutation. Inflammation and nutritional status are closely related to distant metastasis of CRC. PIV and PNI can effectively predict the risk of distant metastasis of CRC, and the detection method has the advantages of simplicity, economy, and convenience. Of course, since this single-center retrospective study may introduce bias in the results, the findings of this study require further researches to be validated.
Data Sharing Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Ethics Approval
All participants were informed on the study procedures and goals and the study obtained written informed consent from all the participants. The study was performed under the guidance of the Declaration of Helsinki and approved by the Ethics Committee of Medicine, Meizhou People’s Hospital.
Acknowledgments
The authors thank their colleagues, who were not listed in the authorship for their helpful comments on the manuscript.
Author Contributions
All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.
Funding
This study was supported by the Project of Medical and Health Scientific Research of Meizhou City (Grant No.: 2025-B-11).
Disclosure
The authors declare that they have no competing interests in this work.
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