Retrospective Study Open Access
Copyright ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Surg. Jul 27, 2021; 13(7): 689-701
Published online Jul 27, 2021. doi: 10.4240/wjgs.v13.i7.689
Novel parameter based on lipid indicators ratio improves prognostic value of plasma lipid levels in resectable colorectal cancer patients
Jun-Nan Gu, Ying-Hao Cao, Sheng-He Deng, Fu-Wei Mao, Hui-Li Li, Hang Li, Xing-Hua Liu, Ji-Liang Wang, Ke Wu, Kai-Lin Cai, Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, Hubei Province, China
Shuang Yao, Hong-Yu Jiang, Yang-Ting He, Xin-Ying Li, Song-Qing Ke, Department of Epidemiology and Biostatistics, The Ministry of Education Key Lab of Environment and Health, School of Public Health, Huazhong University of Science and Technology, Wuhan 430022, Hubei Province, China
Hong-Li Liu, Cancer Center, Huazhong University of Science and Technology, Wuhan 430022, Hubei Province, China
Li Liu, Department of Epidemiology and Biostatistics, School of Public Health, Huazhong University of Science and Technology, Wuhan 430022, Hubei Province, China
ORCID number: Jun-Nan Gu (0000-0003-4828-6514); Shuang Yao (0000-0002-9017-0446); Ying-Hao Cao (0000-0002-4825-1402); Sheng-He Deng (0000-0001-6184-1389); Fu-Wei Mao (0000-0002-3312-7513); Hong-Yu Jiang (0000-0001-5824-3038); Yang-Ting He (0000-0002-9458-6465); Xin-Ying Li (0000-0002-9799-689X); Song-Qing Ke (0000-0003-4862-2661); Hui-Li Li (0000-0001-7508-1122); Hang Li (0000-0003-1640-8409); Xing-Hua Liu (0000-0001-8783-0573); Hong-Li Liu (0000-0002-5263-8108); Ji-Liang Wang (0000-0001-6169-637X); Ke Wu (0000-0002-6376-0782); Li Liu (0000-0001-7455-1735); Kai-Lin Cai (0000-0002-2572-0907).
Author contributions: Gu JN was responsible for conceptualization, methodology, validation, and writing of the original draft; Yao S was responsible for conceptualization, methodology, software, and formal analysis; Cao YH, Deng SH, and Mao FW were responsible for investigation and resources; Jiang HY, He YT, Li XY, and Ke SQ were responsible for resources and data curation; Li HL was responsible for visualization, supervision, and manuscript writing, review, and editing; Li H and Liu XH were responsible for visualization and supervision; Liu HL, Wu K, and Wang JL were responsible for supervision and project administration; Liu L and Cai KL were responsible for manuscript writing, review, and editing, supervision, project administration, and funding acquisition, and should be regarded as co-corresponding authors.
Supported by the Graduates’ Innovation Fund, Huazhong University of Science and Technology, No. 2020yjsCXCY080; and the Free Innovation Pre-research Fund and Platform Scientific Research Fund in 2019, No. 02.03.2019-111.
Institutional review board statement: This study was reviewed and approved by the Ethics Committee of the Wuhan Union Hospital.
Informed consent statement: The analysis used clinical data that were obtained after each patient agreed to treatment by written consent.
Conflict-of-interest statement: The authors declare no conflicts of interest related to this manuscript.
Data sharing statement: The data that support the findings of this study are available from the corresponding author upon reasonable request.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Kai-Lin Cai, PhD, Doctor, Professor, Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Union Hospital, No. 1277 Jiefang Avenue, Jianghan District, Wuhan 430022, Hubei Province, China. caikailin@hust.edu.cn
Received: December 28, 2020
Peer-review started: December 28, 2020
First decision: February 23, 2021
Revised: March 11, 2021
Accepted: June 28, 2021
Article in press: June 28, 2021
Published online: July 27, 2021

Abstract
BACKGROUND

At present, the value of lipid indicators in evaluating the prognosis of colorectal cancer is still relatively limited.

AIM

To evaluate the value of a novel parameter for colorectal cancer (CRC) prognosis scoring based on preoperative serum lipid levels.

METHODS

Four key serum lipid factors, namely, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1 (ApoA1), and apolipoprotein B (ApoB), were detected. Two representative ratios, HDL-C-LDL-C ratio (HLR) and ApoA1-ApoB ratio (ABR) were calculated. The relationship of these parameters with the prognosis of CRC patients including progression-free survival (PFS) and overall survival (OS) was analyzed by Kaplan-Meier plot and Cox proportional hazards regression. A novel lipoprotein cholesterol-apolipoprotein (LA) score based on HLR and ABR was established and its value in prognosis evaluation for CRC patients was explored.

RESULTS

Multivariate Cox proportional hazards regression analysis of PFS and OS showed that HDL-C, ApoA1, HLR, and ABR were positively associated with the prognosis of CRC patients. LA score was independently associated with a good prognosis in resectable CRC patients. Data processing of a dummy variable showed that the prognosis of patients with higher LA scores is better than that with lower LA scores.

CONCLUSION

The newly established LA score might serve as a better predictor of the prognosis of resectable CRC patients.

Key Words: Colorectal cancer, High-density lipoprotein cholesterol-low-density lipoprotein cholesterol ratio, Apolipoprotein A1-apolipoprotein B ratio, Liptein cholesterol-apolipoprotein score, Prognosis

Core Tip: Although the diagnosis and treatment of colorectal cancer are constantly improving, the prognosis of colorectal cancer still needs to be further improved. At present, the methods to evaluate the prognosis of colorectal cancer, whether imaging examination or endoscopic examination, are based on the judgment of tumor stage. Under the background that the relationship between lipid metabolism and cancer has been gradually explored, our research has further studied the relationship between some key lipid indicators and the prognosis of colorectal cancer, and has established a novel prognosis scoring system, namely, lipoprotein cholesterol-apolipoprotein score, based on lipid indicators, which is expected to have more application value in the future clinical work.



INTRODUCTION

Colorectal cancer (CRC) is the fourth most prevalent and second deadliest type of cancer worldwide[1]. The 5-year survival rates of CRC patients with local and distant metastasis are 71% and 14%, respectively, which remain unsatisfactory[2]. As such, early prediction of tumor progression is important[3-5]. The discovery of new indicators allows the identification and characterization of the initial steps of tumorigenesis and the prediction of disease prognosis[6,7].

At present, the prognostic assessment of CRC patients primarily includes imaging examination, such as computerized tomography/magnetic resonance imaging; endoscopic examination, such as colonoscopy/enteroscopy; and pathological examination[8,9]. These evaluation methods rely on the judgment of the tumor stage to predict the survival of patients[6,8]. To improve the oncology results of CRC patients, we explored prognostic indicators independent of tumor stage to establish a complete prognostic evaluation system for CRC.

Previous studies have shown that abnormal lipid metabolism plays an important role in tumor progression and may be associated with a poor prognosis in esophageal squamous cell carcinoma[10], nasopharyngeal carcinoma[11], and CRC[12]. A lipid profile includes lipid molecules [cholesterol (CHO), triglycerides, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1 (ApoA1), and apolipoprotein B (ApoB)], and lipid-based biomarkers [namely, HDL-C-LDL-C ratio (HLR) and ApoB-ApoA1 ratio (ABR)]. Epidemiological evidence has indicated an inverse relationship between plasma HDL-C and ApoA1 levels and adenoma risk[13]. Functional studies have revealed important roles of ApoA1 in the development and progression of cancer, such as renal cell carcinoma[14], esophageal squamous cell carcinoma[15], and nasopharyngeal carcinoma[11]. However, the values of lipid molecules in the prognosis of CRC are still under discussion. Hence, the current retrospective cohort study was designed to detect the association of individual lipid molecules and an integrated lipid score with the survival rate of CRC patients.

MATERIALS AND METHODS
Patients

A total of 1696 CRC patients from the Wuhan Union Hospital were enrolled in this study between January 2013 and December 2017. All patients were pathologically identified with primary CRC. The exclusion criteria were as follows: (1) Patients treated with medication or undergoing hormone replacement therapy or curative resection; (2) Patients with concomitant diseases that were associated with increasing serum lipids and proteins levels (i.e., diabetes, hyperlipidemia, or metabolic syndrome); and (3) Other types of malignancy. The present study was approved by the ethics committee of Wuhan Union Hospital and was conducted in accordance with the ethical standards of the World Medical Association Declaration of Helsinki.

Follow-up

All CRC patients were followed after completion of tumor resection according to clinical guidelines. The patients were generally followed every 3 mo by the outpatient service with ultrasound in the first 2 years and then annually for the next 3 to 5 years when no evidence of recurrence was observed. For the patients who did not visit our hospital as scheduled, telephone interviews were conducted to obtain treatment information and progression status. The end of follow-up was in August 2018. The outcomes of this study were progression-free survival (PFS) and overall survival (OS). PFS was calculated as the interval between cancer diagnosis and the first documentation of disease recurrence, metastasis, death, or end of follow-up, whichever came first. OS was defined as the time from the diagnosis of CRC to the date of death, follow-up, or end of follow-up, whichever came first.

Laboratory measurements

Laboratory measurements of lipid-related factors in routine blood tests were collected. Blood samples from each patient were obtained within 1 wk prior to the surgical resection of their primary tumors. On the basis of previous studies on the relationship between lipid metabolism and CRC, we identified four key serum lipid factors, namely, HDL-C, LDL-C, ApoA1, and ApoB.

Statistical analysis

tContinuous variables are expressed as the mean ± SD, and the Student’s t test was used for comparison between groups. Categorical variables are represented by the number of cases (percentage), and the chi-square test was used for comparison between groups. We used the inflexion value of the receiver operating characteristic (ROC) curve to transform the continuous variables into categorical variables. Kaplan-Meier (KM) method and log-rank test were applied to compare the survival difference between groups. Cox proportional hazards regression was used to calculate hazard ratios (HRs) and the corresponding 95% confidence intervals (95%CIs). In addition, subgroup analyses were conducted by age, sex, tumor node metastasis (TNM) stage, tumor location, tumor size, and pathological differentiation. Statistical analyses were performed using SAS 9.4 (SAS Institute Inc, Cary, North Carolina, United States) and R 3.5.1 (R Foundation for Statistical Computing, Vienna, Austria). All analyses were two-sided, and P values < 0.05 were considered statistically significant.

RESULTS
Clinicopathological characteristics of CRC patients

A total of 1696 patients with CRC, 1016 of which were male and 680 were female, were included in the final analysis. Demographic characteristics are described in Table 1. Of the patients included, 979 (57.72%) had tumors located in the colon and 717 (42.28%) in the rectum. TNM stages I, II, III, and IV were observed in 223 (13.15%), 573 (33.79%), 654 (38.56%), and 246 (14.50%) of the patients, respectively. Compared with 1673 (98.64%) CRC patients with a negative circumferential margin, only 23 (1.36%) patients had a positive margin. A total of 367 (21.64%) and 1329 (78.36%) CRC patients were with and without vascular invasion, respectively. In addition, 370 (21.82%) and 1326 (78.18%) patients presented neural invasion and absence of neural invasion, respectively. Supplementary Table 1 shows the baseline clinicopathologic characteristics of patients without serum ApoA1 and ApoB data.

Table 1 Baseline patient clinicopathologic characteristics.
Progression-free survival
1P value
Overall survival
1P value
No progression
Progression
Survival
Death
(n = 1388) (%)
(n = 308) (%)
(n = 1494) (%)
(n = 202) (%)
Age (yr) (mean ± SD)58.61 ± 11.7158.48 ± 12.640.86158.64 ± 11.7558.19 ± 12.810.618
SexMale821 (59.15)195 (63.31)0.199880 (58.90)136 (67.33)0.022
Female567 (40.85)113 (36.69)614 (41.10)66 (32.67)
Tumor locationColon801 (57.71)178 (57.79)0.999861 (57.63)118 (58.42)0.880
Rectum587 (42.29)130 (42.21)633 (42.37)84 (41.58)
TNM stageI216 (15.56)7 (2.27)< 0.001219 (14.66)4 (1.98)< 0.001
II522 (37.61)51 (16.56)536 (35.88)37 (18.32)
III561 (40.42)93 (30.19)570 (38.15)84 (41.58)
IV89 (6.41)157 (50.97)169 (11.31)77 (38.12)
Tumor size (cm)d < 261 (4.39)12 (3.90)0.86367 (4.48)6 (2.97)0.246
2 ≤ d < 5886 (63.83)201 (65.26)964 (64.52)123 (60.89)
d > 5441 (31.77)95 (30.84)463 (31.00)73 (36.14)
DifferentiationLow186 (13.40)36 (11.69)0.586192 (12.85)30 (14.85)0.648
Medium1104 (79.54)253 (82.14)1197 (80.12)160 (79.21)
High98 (7.06)19 (6.17)105 (7.03)12 (5.94)
Circumferential marginNo1372 (98.85)301 (97.73)0.1671477 (98.86)196 (97.03)0.047
Yes16 (1.15)7 (2.27)17 (1.14)6 (2.97)
Vascular tumor thrombusNo1111 (80.04)218 (70.78)0.0011180 (78.98)149 (73.76)0.101
Yes277 (19.96)90 (29.22)314 (21.02)53 (26.24)
Nerve invasionNo1098 (79.11)228 (74.03)0.0571177 (78.78)149 (73.76)0.122
Yes290 (20.89)80 (25.97)317 (21.22)53 (26.24)
ChemotherapyNo606 (43.66)87 (28.25)< 0.001603 (40.36)90 (44.55)0.254
Yes782 (56.34)221 (71.75)891 (59.64)112 (55.45)
RadiotherapyNo1315 (94.74)275 (89.29)0.0011400 (93.71)190 (94.06)0.999
Yes73 (5.26)33 (10.71)94 (6.29)12 (5.94)
ApoA1 (G/L)1.22 ± 0.251.12 ± 0.27< 0.0011.20 ± 0.251.12 ± 0.280.010
ApoB (G/L)0.94 ± 0.230.91 ± 0.240.1700.93 ± 0.230.92 ± 0.250.628
HDL-C (mmol/L)1.22 ± 0.331.20 ± 0.340.2081.22 ± 0.331.20 ± 0.370.440
LDL-C (mmol/L)2.62 ± 0.752.60 ± 0.840.8072.61 ± 0.752.64 ± 0.900.664
Prognostic association of lipid-related indicators in CRC patients

The areas under the ROC curves of HDL-C, LDL-C, ApoA1, and ApoB for PFS and OS are presented in Table 2. As shown in the KM curve (Supplementary Figure 1), higher serum levels of HDL-C, ApoA1, and ApoB were associated with a better PFS and OS than those with lower levels. By contrast, the patients with higher serum LDL-C levels showed a worse PFS and OS than those with lower LDL-C levels. Multivariate Cox proportional hazards regression revealed that the HRs of PFS were 0.696 (95%CI: 0.528-0.918) and 0.617 (95%CI: 0.442-0.863) for high levels of HDL-C and ApoA1, respectively. Similarly, HDL-C and ApoA1 were associated with a low risk for OS, with HRs of 0.505 (95%CI: 0.363-0.702) and 0.625 (95%CI: 0.410-0.955), respectively, whereas LDL-C was associated with a high risk for OS (HR: 1.503, 95%CI: 1.001-2.258).

Table 2 Cox proportional hazards regression analyses for basic lipid indicators for progression-free survival and overall survival.
AUCCut-pointPFS
Univariate
P value
Multivariate1
P value
HR (95%CI)
HR (95%CI)
HDL-C (mmol/L)0.5190.9200.699 (0.530-0.920)0.011b0.696 (0.528-0.918)0.010a
LDL-C (mmol/L)0.5132.1600.865 (0.679-1.103)0.2420.878 (0.689-1.119)0.295
ApoA1 (G/L)0.6101.0300.520 (0.374-0.725)< 0.001b0.617 (0.442-0.863)0.005a
ApoB (G/L)0.5470.8600.743 (0.537-1.029)0.0740.796 (0.574-1.103)0.170
OS
AUCCut-pointUnivariateP valueMultivariate2P value
HR (95%CI)HR (95%CI)
HDL-C (mmol/L)0.5190.9000.492 (0.354-0.685)< 0.001b0.505 (0.363-0.702)< 0.001a
LDL-C (mmol/L)0.4993.6501.645 (1.096-2.468)0.016b1.503 (1.001-2.258)0.050
ApoA1 (G/L)0.5781.1300.572 (0.375-0.873)0.010b0.625 (0.410-0.955)0.030a
ApoB (G/L)0.5270.8600.744 (0.487-1.136)0.1710.807 (0.528-1.234)0.323

The areas under the ROC curves of two hallmarks comprising the ratio of lipid biomarkers, HLR and ABR, for PFS and OS are shown in Table 3. The KM curves for the two hallmarks are shown in Figure 1, which indicated that higher levels of HLR and ABR were associated with a better PFS and OS than those with lower levels. In the multivariate Cox proportional hazards regression analyses, high levels of HLR and ABR were associated with a decreased risk of disease progression, with HRs of 0.710 (95%CI: 0.528-0.955) and 0.501 (95%CI: 0.324-0.775), respectively. High levels of HLR and ABR were associated with a decreased risk of overall mortality, with HRs of 0.619 (95%CI: 0.434-0.882) and 0.481 (95%CI: 0.271-0.853), respectively. At the same time, we made subgroup analysis of lipid indicators and found some significant results (Supplementary Tables 2-7).

Figure 1
Figure 1 Kaplan-Meier curves for progression-free survival and overall survival of colorectal cancer patients according to two hallmarks consisting of the ratio of lipid biomarkers (high-density lipoprotein cholesterol/low-density lipoprotein cholesterol ratio and apolipoprotein A1/apolipoprotein B ratio). A: Kaplan-Meier curves for progression-free survival (PFS) of colorectal cancer patients according to high-density lipoprotein cholesterol/low-density lipoprotein cholesterol (HDL-C/LDL-C) ratio; B: Kaplan-Meier curves for overall survival (OS) of colorectal cancer patients according to HDL-C/LDL-C ratio; C: Kaplan-Meier curves for PFS of colorectal cancer patients according to ApoA1/ApoB ratio; and D: The Kaplan-Meier curves for OS of colorectal cancer patients according to ApoA1/ApoB ratio.
Table 3 Cox proportional hazards regression analyses for lipid-based indicators for progression-free survival and overall survival.
AUCCut-pointPFS
Univariate
P value
Multivariate1
P value
HR (95%CI)
HR (95%CI)
HDL-C/LDL-C0.4970.3230.672 (0.500-0.904)0.009b0.710 (0.528-0.955)0.024a
ApoA1/ApoB0.5280.9090.465 (0.302-0.715)0.001b0.501 (0.324-0.775)0.002a
OS
AUCCut-pointUnivariateP valueMultivariate2P value
HR (95%CI)HR (95%CI)
HDL-C/LDL-C0.5060.3230.573 (0.402-0.815)0.002b0.619 (0.434-0.882)0.008a
ApoA1/ApoB0.5270.8710.411 (0.232-0.729)0.002b0.481 (0.271-0.853)0.012a
Prospects for the newly established scoring system

Given that HLR and ABR presented inverse associations with CRC mortality, an integrated lipid score, that is, lipoprotein cholesterol-apolipoprotein score (LA score), was developed as a novel prognostic indicator for CRC survival. HLR and ABR were dichotomized with the inflection point of the corresponding ROC curve on OS (Table 3). This LA score was generated as follows: Score 0: 0 < HLR < 0.323 and 0 < ABR < 0.871; score 1: HLR > 0.323 and 0 < ABR < 0.871, or 0 < HLR < 0.323 and ABR > 0.871; and score 2: HLR > 0.323 and ABR > 0.871. As shown in Figure 2, KM log-rank survival analysis suggested that PFS was good for CRC patients at the same survival time point with per point increase in LA score (P = 0.00058). According to the multivariate Cox regression analysis, resectable CRC patients with an LA score of 2 had a better PFS than patients with an LA score of 0 through data processing of dummy variable quantification (HR: 0.427, 95%CI: 0.256-0.713, P = 0.001, Table 4). Furthermore, the analysis of continuous variables suggested that LA score had a protective effect on the prognosis of patients with resectable CRC (HR: 0.654, 95%CI: 0.512-0.836, P = 0.001, Table 4).

Figure 2
Figure 2 Kaplan-Meier curves for progression-free survival and overall survival of colorectal cancer patients according to lipoprotein cholesterol-apolipoprotein score. A: Kaplan-Meier curves for progression-free survival of colorectal cancer patients according to lipoprotein cholesterol-apolipoprotein (LA) score; B: Kaplan-Meier curves for overall survival of colorectal cancer patients according to LA score.
Table 4 Cox proportional hazards regression analyses for lipoprotein-cholesterol-apolipoprotein score for progression-free survival and overall survival.
Continuous variable

PFS

Univariate
P value
Multivariate1
P value

HR (95%CI)
HR (95%CI)
LA score30.625 (0.490-0.797)< 0.001b0.654 (0.512-0.836)0.001a
OS
UnivariateP valueMultivariate2P value
HR (95%CI)HR (95%CI)
LA score30.616 (0.453-0.838)0.002b0.677 (0.500-0.917)0.012a
Dummy variable
PFS
UnivariateP valueMultivariate1P value
HR (95%CI)HR (95%CI)
LA score3 10.598 (0.280-1.277)0.1840.646 (0.302-1.383)0.261
LA score3 20.387 (0.233-0.643)< 0.001b0.427 (0.256-0.713)0.001a
OS
UnivariateP valueMultivariate2P value
HR (95%CI)HR (95%CI)
LA score3 10.973 (0.370-2.561)0.9561.508 (0.507-3.992)0.408
LA score3 20.413 (0.213-0.802)0.009b0.524 (0.269-1.019)0.057

In further subgroup analysis (Table 5), for CRC patients with TNM stage III/IV, patients with rectal tumor, or those with a tumor size (cm) of 2 ≤ d < 5, the increased LA score had a stronger protective effect on PFS, with HRs of 0.632 (95%CI: 0.485-0.824), 0.582 (95%CI: 0.411-0.826), and 0.575 (95%CI: 0.435-0.761), respectively. For CRC patients younger than 65 years, female patients, patients with TNM stage III/IV, patients with a tumor size (cm) of 2 ≤ d < 5, or patients with low tumor differentiation, the increased LA score was associated with a decreased risk of OS, with HRs of 0.626 (95%CI: 0.424-0.924), 0.572 (95%CI: 0.333-0.981), 0.676 (95%CI: 0.490-0.932), 0.636 (95%CI: 0.445-0.908), and 0.298 (95%CI: 0.149-0.594), respectively.

Table 5 Association between lipoprotein-cholesterol-apolipoprotein score with overall survival and progression-free survival in patients with colorectal cancer among different subgroups.
LA score
PFS
OS
n
Progression
HR (95%CI)
n
Death
HR (95%CI)
Age (yr)< 65330900.725 (0.532-0.987)330490.626 (0.424-0.924)
≥ 65191580.540 (0.358-0.814)191380.724 (0.437-1.199)
SexMale321970.671 (0.500-0.901)321580.756 (0.520-1.101)
Female200510.592 (0.366-0.956)200290.572 (0.333-0.981)
TNM stageI/II243350.805 (0.421-1.538)243150.678 (0.265-1.735)
III/IV2781130.632 (0.485-0.824)278720.676 (0.490-0.932)
Tumor locationColon320910.793 (0.557-1.128)320530.686 (0.454-1.036)
Rectum201570.582 (0.411-0.826)201340.710 (0.450-1.121)
Tumor size (cm)d < 212201220
2 ≤ d < 53741080.575 (0.435-0.761)374610.636 (0.445-0.908)
d ≥ 5135380.792 (0.485-1.294)135240.634 (0.354-1.137)
DifferentiationLow56180.504 (0.286-0.890)56110.298 (0.149-0.594)
Medium4151180.722 (0.534-0.977)415680.781 (0.528-1.155)
High50120.534 (0.261-1.093)5080.704 (0.313-1.586)
DISCUSSION

Recently, abnormal lipid metabolism has been linked with cancer risk and progression in several malignancies[16,17] and validated to be a vital metabolic reprogramming process in cancer cells[18,19]. However, the role of lipid-related molecules in evaluating the prognosis of resectable CRC is not very clear. Therefore, the establishment of intuitive, sensitive, and specific lipid-derived markers that can be used to clinically predict cancer prognosis is required. In the present study, the prognostic effects of various lipid-related indicators were systematically and comprehensively studied, and several important findings were discovered. First, the protective effects of certain lipid indicators, such as HDL-C, ApoA1, HLR, and ABR, on PFS and OS in patients with resectable CRC were validated. Second, the combination of HLR along with ABR, defined as LA score, was statistically significant in relation to the prognosis of CRC and is more intuitive than other lipid-based indicators. Third, the clinical feasibility of the newly established LA score was evaluated and accordingly confirmed as a prognostic factor.

PFS and OS in CRC patients with a high preoperative serum HDL-C concentration were higher than those with a low serum HDL-C concentration. Previous studies have reported that the levels of HDL-C are inversely related to the risk of CRC[13,20]. Unlike previous studies, a large cohort of CRC patients was included in the present study to further demonstrate the validity of this conclusion. In addition, a total of 1696 patients with CRC after surgical operation from Wuhan Union Hospital were included in this multivariate Cox proportional hazards regression analysis. The primary role of HDL-C, as the only atherosclerotic protective lipid, is to transport excess CHO from the periphery to the liver for excretion. Moreover, HDL-C has been shown to exhibit antioxidant, anti-inflammatory, and antithrombotic effects and is inversely associated with cancer[21-23]. However, the function of HDL-C in carcinogenesis is not fully understood. Cancer is a pro-inflammatory state, including tumor cell proliferation, survival, and migration, and inflammatory cells actively participate in the development of tumors[24]. HDL-C may influence certain pro-inflammatory mediators involved in carcinogenesis[21]. Su et al[25] suggested that HDL-C mimetic peptides may considerably reduce colon cancer cell proliferation in BALB/c mice through antioxidant and anti-inflammatory mechanisms. In addition, HDL-C may affect immune cells in the tumor microenvironment rather than directly kill tumor cells[26]. HDL-C inhibits the progression of CRC through anti-inflammatory and immune mechanisms probably via the aforementioned mechanisms; hence, CRC patients with a high preoperative serum HDL-C presented a better OS, as shown in the present study (HR: 0.505, 95%CI: 0.363-0.702, P < 0.001). Several studies have reported elevated LDL-C levels in several types of cancer, such as breast cancer[27] and CRC[28]. The present study revealed that CRC patients with high blood LDL-C had a worse OS (HR: 1.503, 95%CI: 1.001-2.258, P = 0.050), which is consistent with the findings reported in the literature. This result indicates that LDL-C might be an independent predictor of CRC prognosis. Montel et al[29] and Song et al[30] reported that cancer cells can express an LDL receptor-related protein that can promote the growth and invasion of cancer cells. This process may be one of the mechanisms by which LDL-C in blood affects cancer progression. On the basis of this evidence, we proposed that HLR, a lipid-based hallmark, is linked to the prognosis of CRC. This retrospective cohort study confirmed that high levels of HLR were associated with a better postoperative OS (HR: 0.619, 95%CI: 0.434-0.882, P = 0.008). Although previous work has clarified the role of LDL-C-to-HDL-C ratio in the evaluation of cardiovascular disease[31,32], few have linked a similar ratio to the prognosis of CRC. The present study confirmed that HLR is helpful in assessing the prognosis of patients with resectable CRC. Furthermore, HLR is worthy of further study and may be clinically applied in the future.

Serum ApoA1 also exhibited protective effects on PFS and OS in CRC patients according to multivariate Cox proportional hazards regression analysis. Among the 522 CRC patients who had been measured for preoperative serum ApoA1, those with high serum ApoA1 levels showed a better prognosis after surgical operation. Apolipoprotein A1, which is encoded by a gene located on chromosome 11q23-q24, is a member of the apolipoprotein family[33,34]. As a major protein constituent of high-density lipoproteins, ApoA1 is synthesized predominantly in the liver and small intestine and is part of the apolipoprotein A1/A4/E family[35]. ApoA1 is widely recognized and validated in various cancers as a prognostic factor[36,37]. However, researchers have different opinions on how ApoA1 plays a role in cancer patients, and the pathogenesis is still under exploration. Recent studies have found that ApoA1 has a negative effect on tumor microenvironment in terms of overall metastasis reduction and accumulation of tumor-associated macrophages[38]. Moreover, ApoA1 can inhibit tumor-associated angiogenesis and then decrease protein expression of MMP9, which is a critical matrix-degrading enzyme needed for metastasis[36]. Georgila et al[36] demonstrated that ApoA1 may function as a potent immunomodulator in tumor microenvironment, transforming tumor-related macrophages from pro-tumor into antitumor phenotypes. These findings imply that ApoA1 may play an important role in the tumorigenesis and progression of CRC. Consistent with previous studies, the present study showed that a low ApoA1 level was correlated with a poor OS and may act as an independent prognostic factor for survival (HR: 0.625, 95%CI: 0.410-0.955, P = 0.030). However, further research is required to clarify the underlying mechanisms. Furthermore, consistent with some previous studies[39,40], the present study found no statistically significant association between serum ApoB levels and CRC prognosis. Therefore, the predictive importance of ABR is positive. Previous studies have found that the ratio of ApoB to ApoA1 is useful for assessing not only cardiovascular diseases[41,42] but also the risk of osteonecrosis[43]. By contrast, few studies have reported that the ratio may be associated with the prognosis of CRC. In this retrospective cohort study, the CRC patients with low preoperative ABR had a worse OS than those with high ABR (HR: 0.481, 95%CI: 0.271-0.853, P = 0.012). Therefore, preoperative measurement of ABR may provide pivotal information for the stratified assessment of prognostic risk in patients who had undergone CRC radical correction.

According to the results of the above study, this cohort study supports the conclusion that HLR and ABR are independent prognostic factors for CRC patients. In the past decade, the Glasgow prognostic score has been widely used in assessing the inflammatory state and risk of cancer prognosis[44-47]. A lipid-related scoring system similar to the GPS was built considering the evidence reported in the literature. This novel CRC prognostic scoring system, called “LA score”, is achieved by combining dichotomized HLR and ABR based on the optimal cut-off threshold from the corresponding RUC curves. Moreover, LA score remarkably correlated with the prognosis of CRC patients. Multivariate Cox proportional hazards regression analysis showed that LA score was an independent prognostic factor for patients with resectable CRC. Patients with an LA score of 2 had a better PFS than those with an LA score of 0 based on data processing of dummy variable quantification (HR: 0.427, 95%CI: 0.256-0.713, P = 0.001, Table 4). As a newly established scoring system, the combination of HLR and ABR reduces the deviation that might be caused by a single ratio hallmark as a predictor and reflects a better prediction effect than either of the two ratios alone (HRs: 0.427 vs 0.710 and 0.501). Such a combination leads to intuitive and convenient evaluation of the prognosis. Notably, the relative stability of lipid indicators in the human body would result in stronger clinical application value of LA score than that of markers or scores composed of inflammatory indicators that considerably vary during the perioperative period. As treatment plans are becoming individualized for each patient, a prognostic scoring system, such as LA score, can be of great help in identifying high-risk populations that require close follow-up surveillance or postoperative adjuvant radiotherapy and chemotherapy to prevent disease recurrence and improve oncological outcomes.

Subgroup analyses provided additional information for the prognostic value of lipid hallmarks. For patients with TNM stage III/IV CRC, high preoperative HLR, ABR levels, and LA scores had protective effects on PFS and OS (Table 5; Supplementary Tables 4 and 7). These findings suggest that HLR, ABR, and LA scores were prognostic indicators independent of TNM stage for postoperative CRC patients. For example, based on the protective effect of LA scores, the preoperative or postoperative LA scores can be increased to improve the prognosis of TNM stage III CRC patients who plan to undergo surgical operations. These clinically important hypotheses deserve further study. Furthermore, these issues require retrospective, multicenter research. Subgroup analysis may be useful and important when used properly despite of data misjudgments. In conclusion, the subgroup analysis also supports the statistical results reported by previous studies.

However, the current research has several limitations. Although the clinical feasibility of lipid-related research factors had been verified as prognostic factors, the quantification and clinical application of such factors still require further research. The results must be validated in a large-scale and multicenter retrospective study because the number of patients included in this cohort study was not sufficiently large and the patients came from a single source. Detailed and definitive mechanisms and the biological importance of HDL-C and ApoA1 in CRC should be elucidated.

CONCLUSION

Through a systematic and comprehensive analysis, HDL-C, HLR, ApoA1, and ABR were demonstrated to be protective factors for the prognosis in patients with resectable CRC. Moreover, a novel prognostic scoring system, namely, LA score, for CRC was established. The high correlation between the novel scoring system and the prognosis of CRC patients and its intuitiveness and convenience make it a promising prognostic marker, but its specific clinical value remains to be further explored. Lipid indicators are feasible and promising prognostic biomarkers for CRC, and their quantification may be helpful in the diagnosis and treatment of CRC.

ARTICLE HIGHLIGHTS
Research background

Abnormal lipid metabolism has been considered to be associated with the oncogenesis, development, and prognosis in cancer.

Research motivation

Although the association between abnormal lipid metabolism and cancer progression is widely recognized, the value of lipid indicators in evaluating the prognosis of colorectal cancer (CRC) is still relatively limited.

Research objectives

The present study aimed to evaluate the association between preoperative serum lipid conditions and the prognosis in patients with CRC.

Research methods

This study included 1696 colorectal cancer patients. Four key lipid factors and two lipid ratio indicators were calculated to analyze the association between these parameters and prognosis of CRC by Kaplan-Meier plot and Cox proportional hazards regression.

Research results

High-density lipoprotein cholesterol (HDL-C), apolipoprotein A1, HDL-C-low-density lipoprotein cholesterol ratio, and ApoA1-apolipoprotein B ratio were positively associated with the prognosis of CRC patients. Lipoprotein cholesterol-apolipoprotein (LA) score was independently associated with a good prognosis in resectable CRC patients.

Research conclusions

The current study indicated that serum lipid parameters, particularly the newly established LA score, might serve as candidate predictors of the prognosis of resectable CRC patients.

Research perspectives

We have identified the value of several lipid parameters and a newly constructed score in assessing the prognosis of resectable CRC patients in a retrospective study. Compared with more volatile inflammatory factors, these more stable lipid parameters can provide a great help to improve the prognostic evaluation of CRC.

Footnotes

Manuscript source: Invited manuscript

Specialty type: Gastroenterology and hepatology

Country/Territory of origin: China

Peer-review report’s scientific quality classification

Grade A (Excellent): 0

Grade B (Very good): 0

Grade C (Good): C

Grade D (Fair): 0

Grade E (Poor): 0

P-Reviewer: Mohamed SY S-Editor: Zhang L L-Editor: Wang TQ P-Editor: Li JH

References
1.  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;68:394-424.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 53206]  [Cited by in F6Publishing: 51512]  [Article Influence: 8585.3]  [Reference Citation Analysis (122)]
2.  Siegel RL, Miller KD, Fedewa SA, Ahnen DJ, Meester RGS, Barzi A, Jemal A. Colorectal cancer statistics, 2017. CA Cancer J Clin. 2017;67:177-193.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2526]  [Cited by in F6Publishing: 2757]  [Article Influence: 393.9]  [Reference Citation Analysis (2)]
3.  Miller KD, Nogueira L, Mariotto AB, Rowland JH, Yabroff KR, Alfano CM, Jemal A, Kramer JL, Siegel RL. Cancer treatment and survivorship statistics, 2019. CA Cancer J Clin. 2019;69:363-385.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2417]  [Cited by in F6Publishing: 2780]  [Article Influence: 556.0]  [Reference Citation Analysis (0)]
4.  Siegel RL, Jemal A, Wender RC, Gansler T, Ma J, Brawley OW. An assessment of progress in cancer control. CA Cancer J Clin. 2018;68:329-339.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 112]  [Cited by in F6Publishing: 117]  [Article Influence: 19.5]  [Reference Citation Analysis (0)]
5.  Wender RC, Brawley OW, Fedewa SA, Gansler T, Smith RA. A blueprint for cancer screening and early detection: Advancing screening's contribution to cancer control. CA Cancer J Clin. 2019;69:50-79.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 59]  [Cited by in F6Publishing: 67]  [Article Influence: 13.4]  [Reference Citation Analysis (0)]
6.  Dekker E, Tanis PJ, Vleugels JLA, Kasi PM, Wallace MB. Colorectal cancer. Lancet. 2019;394:1467-1480.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1570]  [Cited by in F6Publishing: 2182]  [Article Influence: 436.4]  [Reference Citation Analysis (2)]
7.  Smith RA, Andrews KS, Brooks D, Fedewa SA, Manassaram-Baptiste D, Saslow D, Brawley OW, Wender RC. Cancer screening in the United States, 2018: A review of current American Cancer Society guidelines and current issues in cancer screening. CA Cancer J Clin. 2018;68:297-316.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 305]  [Cited by in F6Publishing: 330]  [Article Influence: 55.0]  [Reference Citation Analysis (0)]
8.  Akin O, Brennan SB, Dershaw DD, Ginsberg MS, Gollub MJ, Schöder H, Panicek DM, Hricak H. Advances in oncologic imaging: update on 5 common cancers. CA Cancer J Clin. 2012;62:364-393.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 47]  [Cited by in F6Publishing: 46]  [Article Influence: 3.8]  [Reference Citation Analysis (0)]
9.  Volk RJ, Leal VB, Jacobs LE, Wolf AMD, Brooks DD, Wender RC, Smith RA. From guideline to practice: New shared decision-making tools for colorectal cancer screening from the American Cancer Society. CA Cancer J Clin. 2018;68:246-249.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 24]  [Cited by in F6Publishing: 26]  [Article Influence: 4.3]  [Reference Citation Analysis (0)]
10.  Mokany E, Bone SM, Young PE, Doan TB, Todd AV. MNAzymes, a versatile new class of nucleic acid enzymes that can function as biosensors and molecular switches. J Am Chem Soc. 2010;132:1051-1059.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 169]  [Cited by in F6Publishing: 175]  [Article Influence: 12.5]  [Reference Citation Analysis (0)]
11.  Chang H, Wei JW, Chen K, Zhang S, Han F, Lu LX, Xiao WW, Gao YH. Apolipoprotein A-I Is a Prognosticator of Nasopharyngeal Carcinoma in the Era of Intensity-modulated Radiotherapy. J Cancer. 2018;9:702-710.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 13]  [Cited by in F6Publishing: 18]  [Article Influence: 3.0]  [Reference Citation Analysis (0)]
12.  Zhang X, Zhao XW, Liu DB, Han CZ, Du LL, Jing JX, Wang Y. Lipid levels in serum and cancerous tissues of colorectal cancer patients. World J Gastroenterol. 2014;20:8646-8652.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in CrossRef: 57]  [Cited by in F6Publishing: 58]  [Article Influence: 5.8]  [Reference Citation Analysis (0)]
13.  Yang MH, Rampal S, Sung J, Choi YH, Son HJ, Lee JH, Kim YH, Chang DK, Rhee PL, Kim JJ, Rhee JC, Chun HK, Guallar E, Cho J. The association of serum lipids with colorectal adenomas. Am J Gastroenterol. 2013;108:833-841.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 51]  [Cited by in F6Publishing: 60]  [Article Influence: 5.5]  [Reference Citation Analysis (0)]
14.  Van Hemelrijck M, Garmo H, Hammar N, Jungner I, Walldius G, Lambe M, Holmberg L. The interplay between lipid profiles, glucose, BMI and risk of kidney cancer in the Swedish AMORIS study. Int J Cancer. 2012;130:2118-2128.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 38]  [Cited by in F6Publishing: 40]  [Article Influence: 3.1]  [Reference Citation Analysis (0)]
15.  Kelly P, Paulin F, Lamont D, Baker L, Clearly S, Exon D, Thompson A. Pre-treatment plasma proteomic markers associated with survival in oesophageal cancer. Br J Cancer. 2012;106:955-961.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 43]  [Cited by in F6Publishing: 44]  [Article Influence: 3.7]  [Reference Citation Analysis (0)]
16.  Nam SY, Park BJ, Nam JH, Kook MC. Effect of Helicobacter pylori eradication and high-density lipoprotein on the risk of de novo gastric cancer development. Gastrointest Endosc. 2019;90:448-456.e1.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 28]  [Cited by in F6Publishing: 30]  [Article Influence: 6.0]  [Reference Citation Analysis (0)]
17.  Borgquist S, Butt T, Almgren P, Shiffman D, Stocks T, Orho-Melander M, Manjer J, Melander O. Apolipoproteins, lipids and risk of cancer. Int J Cancer. 2016;138:2648-2656.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 101]  [Cited by in F6Publishing: 137]  [Article Influence: 17.1]  [Reference Citation Analysis (0)]
18.  Long J, Zhang CJ, Zhu N, Du K, Yin YF, Tan X, Liao DF, Qin L. Lipid metabolism and carcinogenesis, cancer development. Am J Cancer Res. 2018;8:778-791.  [PubMed]  [DOI]  [Cited in This Article: ]
19.  Liu Q, Luo Q, Halim A, Song G. Targeting lipid metabolism of cancer cells: A promising therapeutic strategy for cancer. Cancer Lett. 2017;401:39-45.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 184]  [Cited by in F6Publishing: 226]  [Article Influence: 32.3]  [Reference Citation Analysis (0)]
20.  Choi YJ, Lee DH, Han KD, Shin CM, Kim N. Abdominal obesity, glucose intolerance and decreased high-density lipoprotein cholesterol as components of the metabolic syndrome are associated with the development of colorectal cancer. Eur J Epidemiol. 2018;33:1077-1085.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 33]  [Cited by in F6Publishing: 36]  [Article Influence: 6.0]  [Reference Citation Analysis (0)]
21.  Ganjali S, Ricciuti B, Pirro M, Butler AE, Atkin SL, Banach M, Sahebkar A. High-Density Lipoprotein Components and Functionality in Cancer: State-of-the-Art. Trends Endocrinol Metab. 2019;30:12-24.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 35]  [Cited by in F6Publishing: 37]  [Article Influence: 7.4]  [Reference Citation Analysis (0)]
22.  Gomaraschi M. Role of Lipoproteins in the Microenvironment of Hormone-Dependent Cancers. Trends Endocrinol Metab. 2020;31:256-268.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 10]  [Cited by in F6Publishing: 12]  [Article Influence: 3.0]  [Reference Citation Analysis (0)]
23.  Jafri H, Alsheikh-Ali AA, Karas RH. Baseline and on-treatment high-density lipoprotein cholesterol and the risk of cancer in randomized controlled trials of lipid-altering therapy. J Am Coll Cardiol. 2010;55:2846-2854.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 113]  [Cited by in F6Publishing: 121]  [Article Influence: 8.6]  [Reference Citation Analysis (0)]
24.  Mantovani A, Allavena P, Sica A, Balkwill F. Cancer-related inflammation. Nature. 2008;454:436-444.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 6912]  [Cited by in F6Publishing: 7791]  [Article Influence: 486.9]  [Reference Citation Analysis (0)]
25.  Su F, Grijalva V, Navab K, Ganapathy E, Meriwether D, Imaizumi S, Navab M, Fogelman AM, Reddy ST, Farias-Eisner R. HDL mimetics inhibit tumor development in both induced and spontaneous mouse models of colon cancer. Mol Cancer Ther. 2012;11:1311-1319.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 52]  [Cited by in F6Publishing: 56]  [Article Influence: 4.7]  [Reference Citation Analysis (0)]
26.  Zamanian-Daryoush M, DiDonato JA. Apolipoprotein A-I and Cancer. Front Pharmacol. 2015;6:265.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 55]  [Cited by in F6Publishing: 66]  [Article Influence: 7.3]  [Reference Citation Analysis (0)]
27.  Cedó L, Reddy ST, Mato E, Blanco-Vaca F, Escolà-Gil JC. HDL and LDL: Potential New Players in Breast Cancer Development. J Clin Med. 2019;8.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 54]  [Cited by in F6Publishing: 82]  [Article Influence: 16.4]  [Reference Citation Analysis (0)]
28.  van Duijnhoven FJ, Bueno-De-Mesquita HB, Calligaro M, Jenab M, Pischon T, Jansen EH, Frohlich J, Ayyobi A, Overvad K, Toft-Petersen AP, Tjønneland A, Hansen L, Boutron-Ruault MC, Clavel-Chapelon F, Cottet V, Palli D, Tagliabue G, Panico S, Tumino R, Vineis P, Kaaks R, Teucher B, Boeing H, Drogan D, Trichopoulou A, Lagiou P, Dilis V, Peeters PH, Siersema PD, Rodríguez L, González CA, Molina-Montes E, Dorronsoro M, Tormo MJ, Barricarte A, Palmqvist R, Hallmans G, Khaw KT, Tsilidis KK, Crowe FL, Chajes V, Fedirko V, Rinaldi S, Norat T, Riboli E. Blood lipid and lipoprotein concentrations and colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition. Gut. 2011;60:1094-1102.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 152]  [Cited by in F6Publishing: 165]  [Article Influence: 12.7]  [Reference Citation Analysis (0)]
29.  Montel V, Gaultier A, Lester RD, Campana WM, Gonias SL. The low-density lipoprotein receptor-related protein regulates cancer cell survival and metastasis development. Cancer Res. 2007;67:9817-9824.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 56]  [Cited by in F6Publishing: 61]  [Article Influence: 3.6]  [Reference Citation Analysis (0)]
30.  Song H, Li Y, Lee J, Schwartz AL, Bu G. Low-density lipoprotein receptor-related protein 1 promotes cancer cell migration and invasion by inducing the expression of matrix metalloproteinases 2 and 9. Cancer Res. 2009;69:879-886.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 129]  [Cited by in F6Publishing: 149]  [Article Influence: 9.9]  [Reference Citation Analysis (0)]
31.  Awano K. Is low-density lipoprotein/high-density lipoprotein (LDL/HDL)-cholesterol ratio a more important predictor of vulnerable plaque in coronary artery disease than LDL- or HDL-cholesterol? Circ J. 2010;74:1294-1295.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 5]  [Cited by in F6Publishing: 5]  [Article Influence: 0.4]  [Reference Citation Analysis (0)]
32.  Liem AH, van de Woestijne AP, Roeters van Lennep HW, Zwinderman AH, van der Steeg WA, Jukema JW. ApoB/A1 and LDL-C/HDL-C and the prediction of cardiovascular risk in statin-treated patients. Curr Med Res Opin. 2008;24:359-364.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 18]  [Cited by in F6Publishing: 18]  [Article Influence: 1.1]  [Reference Citation Analysis (0)]
33.  Das M, Wilson CJ, Mei X, Wales TE, Engen JR, Gursky O. Structural Stability and Local Dynamics in Disease-Causing Mutants of Human Apolipoprotein A-I: What Makes the Protein Amyloidogenic? J Mol Biol. 2016;428:449-462.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 39]  [Cited by in F6Publishing: 36]  [Article Influence: 4.0]  [Reference Citation Analysis (0)]
34.  Shoulders CC, Kornblihtt AR, Munro BS, Baralle FE. Gene structure of human apolipoprotein A1. Nucleic Acids Res. 1983;11:2827-2837.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 101]  [Cited by in F6Publishing: 120]  [Article Influence: 2.9]  [Reference Citation Analysis (0)]
35.  Brewer HB Jr, Fairwell T, LaRue A, Ronan R, Houser A, Bronzert TJ. The amino acid sequence of human APOA-I, an apolipoprotein isolated from high density lipoproteins. Biochem Biophys Res Commun. 1978;80:623-630.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 285]  [Cited by in F6Publishing: 303]  [Article Influence: 6.6]  [Reference Citation Analysis (0)]
36.  Georgila K, Vyrla D, Drakos E. Apolipoprotein A-I (ApoA-I), Immunity, Inflammation and Cancer. Cancers (Basel). 2019;11:1097.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 71]  [Cited by in F6Publishing: 118]  [Article Influence: 23.6]  [Reference Citation Analysis (0)]
37.  Sirniö P, Väyrynen JP, Klintrup K, Mäkelä J, Mäkinen MJ, Karttunen TJ, Tuomisto A. Decreased serum apolipoprotein A1 Levels are associated with poor survival and systemic inflammatory response in colorectal cancer. Sci Rep. 2017;7:5374.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 51]  [Cited by in F6Publishing: 66]  [Article Influence: 9.4]  [Reference Citation Analysis (0)]
38.  Neyen C, Mukhopadhyay S, Gordon S, Hagemann T. An apolipoprotein A-I mimetic targets scavenger receptor A on tumor-associated macrophages: A prospective anticancer treatment? Oncoimmunology. 2013;2:e24461.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 19]  [Cited by in F6Publishing: 19]  [Article Influence: 1.7]  [Reference Citation Analysis (0)]
39.  Ryoo JH, Park SK. Association of apolipoprotein B and incidence of metabolic syndrome in Korean men: a 5-years' follow-up study. Atherosclerosis. 2013;226:496-501.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 18]  [Cited by in F6Publishing: 20]  [Article Influence: 1.7]  [Reference Citation Analysis (0)]
40.  Seo MH, Bae JC, Park SE, Rhee EJ, Park CY, Oh KW, Park SW, Kim SW, Lee WY. Association of lipid and lipoprotein profiles with future development of type 2 diabetes in nondiabetic Korean subjects: a 4-year retrospective, longitudinal study. J Clin Endocrinol Metab. 2011;96:E2050-E2054.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 45]  [Cited by in F6Publishing: 53]  [Article Influence: 4.1]  [Reference Citation Analysis (0)]
41.  Thompson A, Danesh J. Associations between apolipoprotein B, apolipoprotein AI, the apolipoprotein B/AI ratio and coronary heart disease: a literature-based meta-analysis of prospective studies. J Intern Med. 2006;259:481-492.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 162]  [Cited by in F6Publishing: 217]  [Article Influence: 12.1]  [Reference Citation Analysis (0)]
42.  Lind L. Apolipoprotein B/A1 and risk of cardiovascular disease. Lancet. 2008;372:185-186.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 9]  [Cited by in F6Publishing: 9]  [Article Influence: 0.6]  [Reference Citation Analysis (0)]
43.  Miyanishi K, Yamamoto T, Irisa T, Noguchi Y, Sugioka Y, Iwamoto Y. Increased level of apolipoprotein B/apolipoprotein A1 ratio as a potential risk for osteonecrosis. Ann Rheum Dis. 1999;58:514-516.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 29]  [Cited by in F6Publishing: 29]  [Article Influence: 1.2]  [Reference Citation Analysis (0)]
44.  Ishizuka M, Nagata H, Takagi K, Horie T, Kubota K. Inflammation-based prognostic score is a novel predictor of postoperative outcome in patients with colorectal cancer. Ann Surg. 2007;246:1047-1051.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 199]  [Cited by in F6Publishing: 212]  [Article Influence: 12.5]  [Reference Citation Analysis (0)]
45.  Vashist YK, Loos J, Dedow J, Tachezy M, Uzunoglu G, Kutup A, Yekebas EF, Izbicki JR. Glasgow Prognostic Score is a predictor of perioperative and long-term outcome in patients with only surgically treated esophageal cancer. Ann Surg Oncol. 2011;18:1130-1138.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 83]  [Cited by in F6Publishing: 96]  [Article Influence: 6.9]  [Reference Citation Analysis (0)]
46.  McMillan DC. The systemic inflammation-based Glasgow Prognostic Score: a decade of experience in patients with cancer. Cancer Treat Rev. 2013;39:534-540.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 765]  [Cited by in F6Publishing: 911]  [Article Influence: 75.9]  [Reference Citation Analysis (0)]
47.  Hirashima K, Watanabe M, Shigaki H, Imamura Y, Ida S, Iwatsuki M, Ishimoto T, Iwagami S, Baba Y, Baba H. Prognostic significance of the modified Glasgow prognostic score in elderly patients with gastric cancer. J Gastroenterol. 2014;49:1040-1046.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 52]  [Cited by in F6Publishing: 62]  [Article Influence: 6.2]  [Reference Citation Analysis (0)]