Lipid levels and insulin resistance markers in patients with colorectal cancer: Propensity score matching analysis

Abstract

BACKGROUND

Colorectal cancer (CRC) is a prevalent malignant neoplasm characterized by subtle early manifestations.

AIM

To investigate the correlation among serum lipid profiles, the triglyceride-glucose (TyG) index, and the atherosclerotic index (AI) in patients with CRC. Furthermore, it explored the clinical diagnostic utility of combining serum lipids with cancer antigens in the context of CRC.

METHODS

A retrospective analysis encompassed 277 patients with CRC and 1034 healthy individuals.

RESULTS

Following propensity score matching, patients with CRC exhibited significantly reduced levels of serum triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol (LDL-C), as well as a diminished TyG index. Conversely, they displayed elevated AI levels compared to their healthy counterparts. Patients in advanced stages exhibited lower serum levels of TG, TC, and LDL-C compared to those in early stages. Patients with positive lymph node metastasis demonstrated reduced levels of TG, LDL-C, and the TyG index. Receiver operating characteristic analysis revealed that the combination of the TyG index, carcinoembryonic antigen, and carbohydrate antigen 19-9 yielded the highest positive prediction rate for CRC at 75.3%.

CONCLUSION

Preoperative serum lipid profiles exhibit a robust association with patients with CRC. The concurrent assessment of multiple serum lipids and cancer antigens effectively enhances the diagnostic accuracy for CRC.

Key Words: Colorectal cancer; Serum lipids; Triglyceride-glucose index; Atherosclerotic index; Diagnostic marker

Core Tip: Timely identification of colorectal cancer (CRC) is essential in lowering both the occurrence and death rates linked to the illness. It has been shown that serum lipids and insulin resistance (IR) markers can be useful biomarkers for detecting CRC in patients. This article retrospectively analyzed 277 patients with CRC and investigated the clinical diagnostic value of a combination of IR indicators, including the triglyceride-glucose index and atherosclerotic index, with cancer antigens as a novel diagnostic marker for CRC.

INTRODUCTION

Colorectal cancer (CRC) is one of the most common malignant tumors in the world, with 1.9 million new cases per year, and ranking as the second most commonly diagnosed cancer. The prognosis of CRC critically hinges upon the cancer stage determined during diagnosis[1]. Timely detection of CRC is imperative to reduce both its incidence and mortality rates associated with the disease.

Several methods are currently being proposed and used to identify the location of tumors. These methods include the fecal occult blood test, colonoscopy, and computed tomography. Currently, the most widely used diagnostic approach for CRC is colonoscopy, which has high sensitivity and specificity for identifying polyps and cancers[2]. However, it is an invasive, high-cost, and time-consuming procedure that requires complex implementation. Blood-based biomarkers such as carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA 19-9) have been recognized and accepted as noninvasive diagnostic procedures established to detect CRC[3].

Metabolic syndrome, consisting of impaired glucose tolerance, dyslipidemia, obesity, and hypertension, is associated with insulin resistance (IR)[4]. Dyslipidemia is an integral part of metabolic syndrome and is characterized by an alteration of serum lipids. In recent years, growing evidence has shown that serum lipids play an important role in tumor development and progression[5]. In particular, it has been shown that serum lipids can be a useful biomarker for detecting CRC in patients[6,7]. However, the limited knowledge of the relationship between serum lipids and the clinical parameters of CRC has obstructed the optimized use for serum lipids when obtaining more accurate and meaningful information for CRC diagnosis and treatment outcomes. Furthermore, there has been no research conducted using propensity score matching (PSM) to investigate the relationship between serum lipids and CRC.

Current evidence has confirmed that IR is a relevant risk factor for the morbidity and mortality of various cancers, including CRC[8,9]. Recently, the triglyceride-glucose (TyG) index and the atherosclerotic index (AI [TC−HDLC]/HDLC]), which are closely related to IR, diabetes, and metabolic syndrome, have attracted extensive attention and medical research. Previous studies have demonstrated that the TyG index may serve as a marker of CRC[7,10]. However, the role of the TyG index in cancer risk remains controversial, and its relationship has not been demonstrated in patients with CRC[11]. The AI is widely regarded as a predictor of cardiovascular disease. However, the association between AI and CRC still needs further exploration.

Therefore, we retrospectively analyzed 277 patients with CRC and investigated the clinical diagnostic value of a combination of IR indicators, including the TyG index and AI, with cancer antigens as a novel diagnostic marker for CRC.

MATERIALS AND METHODS

Study population

Patients with histologically confirmed CRC at the Department of Gastrointestinal Surgery of Shanghai East Hospital (Shanghai, China) between 2021 and 2022 were retrospectively reviewed. To evaluate the link between CRC and the lipid profile found in the serum, a control group was retrospectively examined from a cohort initially collected at the health promotion center. Patients had a previous history of malignancy. Participants who did not undergo lipid profile assessment in the laboratory or were lost during the follow-up period were excluded from the study. Ultimately, a total of 277 individuals diagnosed with CRC and 1034 healthy control subjects were included in the analysis (Figure 1). All participants provided written informed consent. The methods used in this study were conducted in compliance with the Declaration of Helsinki and other applicable guidelines. The study was approved by the Human Research Ethics Committee of Shanghai East Hospital.

Figure 1 Flow of included participants. CRC: Colorectal cancer; PSM: Propensity score matching.

Data collection

The participants in the study were required to fill out a questionnaire that collected information regarding any current or previous illnesses, both acute and chronic, as well as any medications they were currently taking. Peripheral blood was collected for routine hematological tests and cancer antigens such as CEA and CA19-9. The clinicopathological classification of CRC was performed according to the 8th American Joint Committee on Cancer tumor-node-metastasis (TNM) staging system. The serum lipid profiles of all subjects were measured in the study. The levels of serum lipids, such as triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), were assessed utilizing the Roche Cobas e801 chemistry analyzer (Roche Diagnostics, Mannheim, Germany). The TyG index was calculated as Ln (fasting TG [mg/dL] × fasting plasma glucose [mg/dL]/2). AI was analytically calculated from (TC-HDL-C)/HDL-C.

Statistical analyses

The data are expressed as the mean ± standard deviation in cases of normal distribution, and as the median with the interquartile range for nonparametric distribution. To analyze categorical variables, χ² or Fisher exact tests were employed, while continuous variables were assessed using the Student's t-test or one-way analysis of variance. To evaluate the discriminatory ability of the variables in predicting the incidence of CRC, a receiver operating characteristic (ROC) curve was constructed. We calculated the corresponding area under the curve, along with its 95% confidence interval (CI). The statistical software Statistical Package for the Social Sciences (version 26.0; IBM, Armonk, NY, United States) was utilized for data analysis, with statistical significance defined as P < 0.05 (two-sided). The effect of serum lipids was evaluated by one-to-one PSM to adjust for factors including sex, body mass index (BMI), coronary heart disease, cerebral infarction, and hypertension.

RESULTS

Serum lipid levels, TyG, and AI are strongly associated with CRC before and after PSM

We identified 277 patients with CRC and 1034 healthy participants. Table 1 presents the fundamental data of the patients with CRC. There were significant differences between groups in terms of BMI, white blood cells, red blood cells, hemoglobin, and platelets (Table 2). The serum levels of TG, TC, HDL-C, and LDL-C, and the TyG index were significantly lower in patients with CRC than in healthy participants (P < 0.01), whereas AI was significantly higher in patients with CRC than in healthy participants (P < 0.01) (Figure 2A and B). The patients with CRC and healthy participants were subsequently divided into two subgroups depending on sex. Our results indicated that TG, TC, HDL-C, LDL-C, and TyG index were also significantly lower in both male and female patients compared with the same sex group in healthy participants (Figure 2C-F).

Figure 2 Serum lipid, triglyceride-glucose index, and atherosclerotic index in patients with colorectal cancer and healthy participants. A: Serum lipids including total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C); B: Triglyceride-glucose (TyG) index and atherosclerotic index (AI) in all research subjects; C: Serum lipids; D: TyG index and AI in male subjects; E and F: Serum lipids; TyG index, and AI in female subjects. Data are presented as the mean ± standard deviation and analyzed by the Student’s t-test. ^aP < 0.05; ^bP < 0.01; ^cP < 0.001. CRC: Colorectal cancer.

Table 1 Basic information of patients with colorectal cancer before and after propensity score matching.

Characteristics	All CRC, n = 277	Propensity-matched CRC, n = 207
Ascending colon	55 (11.4)	42 (8.7)
Transverse colon	11 (2.3)	8 (1.7)
Descending colon	18 (3.7)	14 (2.9)
Sigmoid colon	68 (14)	49 (10.1)
Rectum	125 (25.8)	94 (19.4)
T. stage
T1	28 (5.8)	23 (4.8)
T2	36 (7.4)	25 (5.2)
T3	196 (40.5)	148 (30.6)
T4	17 (3.5)	11 (2.3)
N. stage
N0	156 (32.2)	119 (24.6)
N1	71 (14.7)	53 (11)
N2	50 (10.3)	35 (7.2)
M. stage
M0	251 (51.9)	190 (39.3)
M1	26 (5.4)	17 (3.5)
Blood vessels
-	199 (41.1)	150 (31)
+	78 (16.1)	57 (11.8)
Nerve
-	210 (43.4)	159 (32.9)
+	67 (13.8)	48 (9.9)
Size, median (IQR)	4 (3, 5)	4 (3, 5)
Differentiation
Low grade	94 (19.4)	69 (14.3)
High grade	183 (37.8)	138 (28.5)
Stage
I	55 (11.4)	41 (8.2)
II	95 (19.6)	72 (14.9)
III	100 (20.7)	73 (15.1)
IV	27 (5.6)	19 (3.9)

Data are n (%) unless otherwise indicated. CRC: Colorectal cancer; IQR: Interquartile range.

Table 2 Characteristics of study participants.

Characteristics	All patients			Propensity-matched patients
	Control, n = 1034	CRC, n = 277	P value	Controls, n = 207	CRC, n = 207	P value
Age in years	66.53 ± 7.41	66.54 ± 10.91	0.989	68.89 ± 5.53	65.58 ± 11.12	0.053
Sex as male/female	466/568	176/101	< 0.001	96/111	122/85	0.010
Hypertension in %	10.25	43.68	< 0.001	34.78	28.99	0.206
Diabetes in %	1.64	14.80	< 0.001	7.73	5.80	0.434
Coronary heart disease or Cerebral infarction in %	0.48%	12.64	< 0.001	2.24	2.24	1
BMI	25.09 ± 5.25	23.78 ± 3.27	< 0.001	24.40 ± 3.77	23.84 ± 3.29	0.106
WBC as × 109/L	6.49 ± 1.58	6.16 ± 1.84	0.003	6.64 ± 1.66	6.14 ± 1.84	0.004
RBC as × 109/L	4.70 ± 0.43	4.19 ± 0.61	< 0.001	4.66 ± 0.40	4.21 ± 0.58	< 0.001
Hb in g/L	143.23 ± 13.24	120.63 ± 25.73	< 0.001	141.89 ± 12.61	121.47 ± 25.08	< 0.001
PLT as × 109/L	216.94 ± 52.78	240.59 ± 83.72	< 0.001	224.17 ± 51.69	240.94 ± 78.97	0.011
ALT in U/L	21.36 ± 7.75	18.50 ± 31.60	0.144	20.33 ± 7.63	17.65 ± 18.27	0.057
AST in U/L	21.40 ± 12.65	21.24 ± 35.77	0.908	19.36 ± 12.60	19.73 ± 11.93	0.758
TC in mmol/L	4.81 ± 0.98	4.23 ± 0.97	< 0.001	4.80 ± 1.02	4.34 ± 0.94	< 0.001
TG in mmol/L	1.65 ± 1.21	1.35 ± 0.73	< 0.001	1.84 ± 1.87	1.33 ± 0.65	< 0.001
HDL-C in mmol/L	1.38 ± 0.36	1.14 ± 0.32	< 0.001	1.41 ± 0.41	1.17 ± 0.32	< 0.001
LDL-C in mmol/L	3.10 ± 0.87	2.66 ± 0.85	< 0.001	3.01 ± 0.86	2.76 ± 0.83	0.003
UA in mmol/L	319.84 ± 77.29	315.62 ± 81.37	0.430	324.75 ± 80.97	312.42 ± 78.70	0.121
SCR in mmoI/L	74.63 ± 22.89	76.67 ± 21.08	0.190	78.29 ± 26.10	73.84 ± 19.89	0.056
CEA in ng/mL	1.91 ± 1.51	35.67 ± 176.15	0.002	2.80 ± 1.54	26.62 ± 95.89	0.001
CA199 in U/mL	11.26 ± 7.64	176.16 ± 1013.41	0.009	12.00 ± 8.77	159.62 ± 929.85	0.027
AI	2.65 ± 1.05	35.67 ± 176.15	0.002	2.64 ± 1.35	2.89 ± 1.14	0.042
TyG index	8.81 ± 0.58	8.58 ± 0.55	< 0.001	8.86 ± 0.59	8.55 ± 0.51	< 0.001

AI: Atherosclerotic index; ALT: Alanine aminotransferase; AST: Aspartate transaminase; BMI: Body mass index; CEA: Carcinoembryonic antigen; CRC: Colorectal cancer; Hb: Hemoglobin; HDL-C: High-density lipoprotein cholesterol; LDL-C: Low-density lipoprotein cholesterol; PLT: Platelet; RBCs: Red blood cells; SCR: Serum creatinine; TC: Total cholesterol; TG: Triglyceride; TyG: Triglyceride-glucose; UA: Uric acid; WBCs: White blood cells.

Based on these findings, we implemented PSM using a modified 1:1 ratio. We achieved successful matching of 414 participants, evenly distributed with 207 individuals in each group. Post PSM, both groups demonstrated robust balance across all variables. Analysis of matched patients showed similar results (Figure 3).

Figure 3 Serum lipid, triglyceride-glucose index, and atherosclerotic index in patients with colorectal cancer and healthy participants after propensity score matching. A and B: Serum lipids, triglyceride-glucose (TyG) index and atherosclerotic index (AI) in all research subjects after propensity score matching (PSM); C and D: Serum lipids, TyG index, and AI in male subjects after PSM; E and F: Serum lipids, TyG index, and AI in female subjects after PSM. Data are presented as the mean ± standard deviation and analyzed by the Student’s t-test. ^aP < 0.05; ^bP < 0.01; ^cP < 0.001. CRC: Colorectal cancer; HDL-C: High-density lipoprotein cholesterol; LDL-C: Low-density lipoprotein cholesterol; TC: Total cholesterol; TG: Triglyceride.

Relationships between serum lipid levels and the malignancy and invasiveness of CRC

To evaluate the relationship between serum lipids and tumor stage, all patients were stratified into two groups: those with relatively early-stage tumors (stages I and II) and those with advanced-stage tumors (stages III and IV). We found that TC and LDL-C were significantly lower in patients with advanced-stage tumors (Figure 4A and B). The levels of TG and LDL-C and the TyG index in patients with CRC with lymph node metastasis were significantly lower than those in patients without lymph node metastasis (Figure 4C and D). The levels of TG and the TyG index were associated with poor differentiation in patients with CRC (Figure 4E and F).

Figure 4 Relationships between serum lipid levels and the malignancy and invasiveness of colorectal cancer. A and B: Serum lipids, triglyceride-glucose (TyG) index, and atherosclerotic index (AI) in different tumor stage of colorectal cancer (CRC); C and D: Serum lipids, TyG index, and AI in patients with CRC with or without with lymph node metastasis; E and F: Serum lipids, TyG index, and AI in patients with CRC with different differentiations. Data are presented as the mean ± standard deviation and analyzed by the Student’s t-test. ^aP < 0.05; ^bP < 0.01; ^cP < 0.001. HDL-C: High-density lipoprotein cholesterol; LDL-C: Low-density lipoprotein cholesterol; TC: Total cholesterol; TG: Triglyceride.

Relationships between serum lipid levels and tumor location

Of the 277 patients with CRC, 152 (54.9%) had CRC and 125 (45.1%) had rectal cancer. The serum HDL-C level in patients with CRC was significantly lower than that in patients with rectal cancer (P < 0.01) (Figure 5A and B). We divided patients with CRC into right-sided CRC (RSCC) and left-sided CRC (LSCC) subgroups. The serum TC level in patients with RSCC was significantly lower than that in patients with LSCC (P < 0.05) (Figure 5C and D).

Figure 5 Relationships between serum lipid levels and tumor location. A and B: Serum lipids, triglyceride-glucose (TyG) index, and atherosclerotic index (AI) in patients with colorectal cancer (CRC) and rectal cancer; C and D: Serum lipids, TyG index, and AI in patients with right-sided CRC (RCSS) and left-sided CRC (LCSS). Data are presented as the mean ± standard deviation and analyzed by the Student’s t-test. ^aP < 0.05; ^bP < 0.01; ^cP < 0.001. HDL-C: High-density lipoprotein cholesterol; LDL-C: Low-density lipoprotein cholesterol; TC: Total cholesterol; TG: Triglyceride.

Serum lipid levels in patents with CRC with normal CEA and CA19-9 levels

Of all patients with CRC, 136 had normal preoperative serum CEA and CA19-9 levels. Serum lipid levels were associated with CRC with normal CEA and CA19-9 levels. The levels of TG, TC, HDL-C, and LDL-C and the TyG index in the CRC group were significantly lower than those in healthy participants, whereas AI was higher in the CRC group (Figure 6A and B). After PSM, analysis of matched patients showed similar results (Figure 6C and D).

Figure 6 Serum lipid levels in patients with colorectal cancer with normal carcinoembryonic antigen and carbohydrate antigen 19-9. A and B: Serum lipids, triglyceride-glucose (TyG) index, and atherosclerotic index (AI) in patients with colorectal cancer (CRC) with normal carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 before propensity score matching (PSM); C and D: Serum lipids, TyG index, and AI in patients with CRC with normal CEA and CA19-9 after PSM. Data are presented as the mean ± standard deviation and analyzed by the Student’s t-test. ^aP < 0.05; ^bP < 0.01; ^cP < 0.001. HDL-C: High-density lipoprotein cholesterol; LDL-C: Low-density lipoprotein cholesterol; TC: Total cholesterol; TG: Triglyceride.

Enhanced diagnostic value of serum lipid levels and serum cancer antigens in patients with CRC

Given the abnormal rates of serum lipid levels and serum cancer antigens in patients with CRC, the TyG index, CEA, and CA19-9 were combined to examine whether the combination can enhance the diagnostic rate in patients with CRC. Our results showed that the combination of the TyG index and cancer antigens can be used as a new diagnostic marker for CRC (Figure 7). The combination of the TyG index, CEA, and CA19-9 had the highest positive prediction rate for CRC (75.3%) by ROC analysis. The remaining serum lipids and cancer antigens are shown in Table 3. Based on this candidate model, we developed a nomogram to visualize CRC diagnosis. Utilizing the patient’s blood lipids, CEA, CA19-9, and TyG index, we can predict the likelihood of the patient having CRC (Figure 8).

Figure 7 Various combined diagnostic indicators for patients with colorectal cancer. AI: Atherosclerotic index; AUC: Area under the curve; CEA: Carcinoembryonic antigen; HDL-C: High-density lipoprotein cholesterol; LDL-C: Low-density lipoprotein cholesterol; TC: Total cholesterol; TG: Triglyceride; TyG: Triglyceride-glucose.

Figure 8 Nomogram for colorectal cancer diagnosis. AUC: Area under the curve; CEA: Carcinoembryonic antigen; HDL-C: High-density lipoprotein cholesterol; LDL-C: Low-density lipoprotein cholesterol; TC: Total cholesterol; TG: Triglyceride; TyG: Triglyceride-glucose.

Table 3 Various combined diagnostic indicators for patients with colorectal cancer.

Indicator	AUC	95%CI	Cut-off value	P value
TC	0.6243	0.5709-0.6777	4.325	< 0.0001
TG	0.6406	0.5873-0.6938	1.345	< 0.0001
HDL-C	0.6802	0.6292-0.7311	1.165	< 0.0001
LDL-C	0.5812	0.5263-0.6360	3.035	0.0043
CEA	0.6429	0.5882-0.6976	5.15	< 0.0001
CA19-9	0.5623	0.5057-0.6190	23.225	0.0305
AI	0.5748	0.5199-0.6298	2.655	0.0085
TyG index	0.6572	0.6048-0.7097	8.635	< 0.0001
CEA + CA199 + TYG index	0.7525	0.7052-0.7997		< 0.0001

AI: Atherosclerotic index; AUC: Area under the curve; CEA: Carcinoembryonic antigen; CI: Confidence interval; HDL-C: High-density lipoprotein cholesterol; LDL-C: Low-density lipoprotein cholesterol; SCR: Serum creatinine; TG: Triglyceride; TC: Total cholesterol; TyG: Triglyceride-glucose.

DISCUSSION

Identifying simple, feasible, and low-cost markers of CRC is of great significance for the treatment and prognosis of patients with CRC. However, due to the absence of distinct symptoms and restricted detection techniques, CRC is frequently misdiagnosed, resulting in the disease being detected in its advanced stages when noticeable symptoms emerge. The present retrospective study analyzed the relationship between dyslipidemia and CRC. We also explored whether the combination of serum lipids or the TyG index and AI can enhance the diagnostic rate of CRC. Of interest, our results showed that preoperative serum lipids were significantly lower in patients with CRC than in healthy participants, even after PSM. In addition, the TyG index and AI as IR markers were associated with CRC. Our study found that various factors such as lymphatic metastasis, vascular invasion, nerve infiltration, and pathologic TNM stage can impact the levels of serum lipids. Therefore, we suggest that measuring serum lipid levels, along with the TyG index and AI, can serve as biomarkers for both diagnosing CRC and predicting its characteristics such as lymph node metastasis, vascular invasion, neural infiltration, and staging. These findings highlight the potential of utilizing these biomarkers for improved understanding and management of CRC. Moreover, the use of these biomarkers can contribute to early detection and intervention strategies, ultimately enhancing outcomes for patients with CRC. Moreover, detection of the TyG index and cancer antigens can effectively improve the diagnosis of CRC.

The routine lipid panel consists of TG, TC, HDL-C, and LDL-C. Accumulating evidence suggests that lipid imbalance may contribute to CRC risk through inflammation, oxidative stress, IR, and protein function alteration[12]. A recent study suggested that serum lipids may serve as a potential marker for CRC[5,12]. However, no research has been conducted on the association of the lipid derivative TyG index and AI with patients with CRC, especially by using PSM analysis. Several studies have demonstrated the association of serum lipid levels and cardiovascular diseases. In recent years, evidence has shown that serum lipid components are associated with the occurrence and development of various types of cancer and thus can be used to evaluate cancer. However, data on the relationship of serum lipid levels with CRC are contradictory[13,14]. PSM analysis is a statistical technique designed to address confounding bias and mimic a randomized clinical trial, improving the level of evidence in studies[15]. It was found that the CRC group had lower serum lipid levels before and after PSM. It is hypothesized that the association of low serum lipids and lipoproteins with CRC results from the metabolic, competitive, and rapid consumption of nutrients by cancer cells, rather than increased levels as a protective factor.

Recent epidemiological and clinical evidence points to a strong association of IR with cancer risk[8]. The TyG index, which relies on fasting levels of TGs and glucose, is gaining recognition as a credible and straightforward proxy for IR. The TyG index is associated with an increased risk of cancers of the digestive system. Limited research has explored the correlation between patients with CRC and the TyG index. Our investigation, however, reveals noteworthy findings: The TyG index maintains a significant correlation with patients with CRC, persisting even after PSM. This study found that as the TyG index decreased, the tumor stage of CRC increased, suggesting that the TyG index may be a valuable marker for predicting CRC. ROC analysis results indicated that the area under the ROC of the TyG index was 0.657, further supporting its potential as a reliable diagnostic tool for CRC. AI is also closely related to IR, diabetes, and metabolic syndrome. Compared to previous studies, we demonstrated for the first time that both the TyG index and AI are reliable blood-based biomarkers for patients with CRC.

Tumor location plays a vital role in determining the progression of the disease, prognosis, and the appropriate management. Various factors, such as the embryonic origin of the tumor, its vascular and nervous supplies, as well as its microbiotic burden, contribute to these differences[16]. When analyzed by anatomical site, the results indicated a positive and significant association between HDL-C and rectal cancer. At a physiological level, RSCC is more likely to exhibit advanced tumor stage and increased lymphovascular invasion[17] with poor prognosis and overall survival compared with LSCC[18]. When subgroup analysis was stratified by the left and right colons, TC levels were much lower in patients with RSCC than in those with LSCC.

Over the years, researchers have pursued tumor markers capable of detecting early stages of malignant cell transformation. These biomarkers, typically proteins associated with cancer, hold promise for clinical applications in patients with cancer. Several indicators of CRC, including CEA, CA 19-9, tissue polypeptide-specific antigen, tumor-associated glycoprotein 72, and hematopoietic growth factors, are widely established and routinely used in clinical practice[19]. Nevertheless, these assessments often lack outstanding diagnostic accuracy. Individual marker analyses for disease detection and prognosis are frequently limited by the modest sensitivity and specificity of conventional medical protocols. A more effective strategy involves simultaneous evaluation of multiple markers to improve diagnostic efficacy. The tumor markers CEA and CA19-9 are widely used for real-world opportunistic cancer screening, treatment response assessment, and recurrence monitoring in CRC. However, both tumor markers do not necessarily increase in all cases; sometimes none or only one of the two tumor markers increases. It is possible that patients with advanced stages may not exhibit elevated serum levels of CEA or CA19-9. A recent study suggested that serum lipids may serve as biomarkers for CRC. Nonetheless, there is a dearth of investigations that have delved into the possibility of utilizing serum lipids to diagnose patients with CRC displaying normal levels of CEA and CA19-9[6]. Our results showed that even in patients with normal CEA and CA19-9, serum lipids, TyG index, and AI had a strong association with CRC, even after PMS.

Due to the highly heterogeneous nature of CRC, a single tumor marker is unlikely to have sufficient sensitivity or specificity for use in diagnostic tests. Moreover, combinations of two or more types of biomarkers are often used in clinical practice to improve the accuracy and efficiency of disease diagnosis. In our study, combining serum lipids and tumor markers improved clinical sensitivity for the detection of CRC and could be a more effective marker.

Our study had several limitations. Initially, it should be noted that this study was conducted retrospectively at a solitary institution, which introduces the possibility of selection bias. To adequately assess the diagnostic efficacy of serum lipids, it is imperative to conduct prospective studies spanning multiple institutions. Additionally, due to the limited number of patients with CRC, our dataset cannot be split into separate training and test sets for statistical validation. The lack of a validation cohort hampers a thorough confirmation of our findings. Moving forward, we plan to collect additional data to facilitate validation efforts. Additionally, we failed to assess treatment response or perform survival analysis based on serum lipid levels. Nevertheless, our findings convincingly demonstrate that the amalgamation of serum lipids and tumor markers holds substantial diagnostic capability for patients with CRC.

CONCLUSION

In conclusion, the results of our study suggest that the serum lipids have strong association with CRC. The detection of TyG index and cancer antigens can effectively improve the diagnosis of CRC.