Article Search
검색
검색 팝업 닫기

Metrics

Help

  • 1. Aims and Scope

    Gut and Liver is an international journal of gastroenterology, focusing on the gastrointestinal tract, liver, biliary tree, pancreas, motility, and neurogastroenterology. Gut atnd Liver delivers up-to-date, authoritative papers on both clinical and research-based topics in gastroenterology. The Journal publishes original articles, case reports, brief communications, letters to the editor and invited review articles in the field of gastroenterology. The Journal is operated by internationally renowned editorial boards and designed to provide a global opportunity to promote academic developments in the field of gastroenterology and hepatology. +MORE

  • 2. Editorial Board

    Editor-in-Chief + MORE

    Editor-in-Chief
    Yong Chan Lee Professor of Medicine
    Director, Gastrointestinal Research Laboratory
    Veterans Affairs Medical Center, Univ. California San Francisco
    San Francisco, USA

    Deputy Editor

    Deputy Editor
    Jong Pil Im Seoul National University College of Medicine, Seoul, Korea
    Robert S. Bresalier University of Texas M. D. Anderson Cancer Center, Houston, USA
    Steven H. Itzkowitz Mount Sinai Medical Center, NY, USA
  • 3. Editorial Office
  • 4. Articles
  • 5. Instructions for Authors
  • 6. File Download (PDF version)
  • 7. Ethical Standards
  • 8. Peer Review

    All papers submitted to Gut and Liver are reviewed by the editorial team before being sent out for an external peer review to rule out papers that have low priority, insufficient originality, scientific flaws, or the absence of a message of importance to the readers of the Journal. A decision about these papers will usually be made within two or three weeks.
    The remaining articles are usually sent to two reviewers. It would be very helpful if you could suggest a selection of reviewers and include their contact details. We may not always use the reviewers you recommend, but suggesting reviewers will make our reviewer database much richer; in the end, everyone will benefit. We reserve the right to return manuscripts in which no reviewers are suggested.

    The final responsibility for the decision to accept or reject lies with the editors. In many cases, papers may be rejected despite favorable reviews because of editorial policy or a lack of space. The editor retains the right to determine publication priorities, the style of the paper, and to request, if necessary, that the material submitted be shortened for publication.

Search

Search

Year

to

Article Type

Original Article

Split Viewer

Impact of Visceral Fat on Survival and Metastasis of Stage III Colorectal Cancer

Jung Won Park1 , Soo Yeon Chang2 , Joon Seok Lim3 , Soo Jung Park1 , Jae Jun Park1,4 , Jae Hee Cheon1 , Won Ho Kim1 , Tae Il Kim1,4,5

1Department of Internal Medicine and Institute of Gastroenterology, Yonsei University College of Medicine, 2Health Promotion Center, Severance Hospital, Yonsei University College of Medicine, 3Department of Radiology, Yonsei University College of Medicine, 4Yonsei Cancer Prevention Center, Severance Hospital, Yonsei University College of Medicine, and 5Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, Seoul, Korea

Correspondence to: Tae Il Kim
ORCID https://orcid.org/0000-0003-4807-890X
E-mail taeilkim@yuhs.ac

Received: August 21, 2020; Revised: January 8, 2021; Accepted: January 19, 2021

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Gut Liver 2022;16(1):53-61. https://doi.org/10.5009/gnl20266

Published online July 28, 2021, Published date January 15, 2022

Copyright © Gut and Liver.

Background/Aims: Previous studies have investigated the relationship between visceral obesity and the risk of colorectal tumors. Visceral obesity may affect the outcome of colorectal cancer (CRC), including survival and metastasis. We investigated the associations between visceral adipose tissue and oncologic outcomes in stage III CRC.
Methods: Four hundred seventy-two patients with stage III CRC were identified. Subcutaneous and visceral adipose tissue areas were measured volumetrically via computed tomography for each patient at different levels of the lumbar spine. After adjusting for age, sex, and other clinical factors, the effects of visceral adipose tissue area on mortality and recurrence were assessed using Cox proportional hazard regression.
Results: In univariate and multivariate analyses, a higher visceral adipose tissue to total adipose tissue (VT) ratio (hazard ratio [HR], 1.041; 95% CI, 1.008 to 1.075; p=0.015) and higher visceral adipose tissue to subcutaneous adipose tissue (VS) ratio (HR, 1.016; 95% CI, 1.005 to 1.028; p=0.006) were both associated with poor CRC-specific survival. Interestingly, in the evaluation of each site of recurrence, a higher VT ratio (HR, 1.069; 95% CI, 1.010 to 1.131; p=0.020) and higher VS ratio (HR, 1.024; 95% CI, 1.003 to 1.045; p=0.023) were both related to a higher risk of peritoneal seeding and tumor recurrence. The VT ratio at the L3–L4 level was significantly associated with a higher risk of peritoneal seeding and tumor recurrence (HR, 4.969; 95% CI, 1.303 to 18.949; p=0.019), while other levels showed no such relationship.
Conclusions: Visceral obesity is closely related to increased risks of CRC-specific mortality and peritoneal seeding metastasis in stage III CRC patients.

Keywords: Obesity, Fat, Visceral, Colorectal neoplasms, Outcome

Obesity and cancer are the two most serious emerging health problems, and their interrelationship has also been known.1 Obesity is a well-known risk factor for the development of colorectal cancer (CRC) and is also associated with higher risks of postoperative complication rates and recurrence after adjuvant chemotherapy.2,3 Although the underlying mechanisms of their interaction remain unclear, recent data suggests an important role of visceral fat in this relationship.4,5 Visceral adipose tissue (VAT) has higher hormonal and metabolic activities than subcutaneous adipose tissue (SAT).6 Visceral adipocyte-induced insulin-like growth factor, inflammatory adipokines like interleukin-6 and tumor necrosis factor-α, and angiogenic factors are reported as mediators related with the tumorigenesis of obesity-related tumors.7-9 Furthermore, insulin resistance, commonly found in obesity, results in compensatory hyperinsulinemia. As key growth factors for colonic epithelial cells, insulin and C-peptide are well known mitogens of tumor cell growth.10-12

Previous studies have revealed the relationship between CRC and visceral obesity (VO). However, most studies have focused on the risk of complications after surgery, rather than recurrence or survival of CRC patients.13-16 A few studies have shown the oncologic outcomes of CRC in viscerally obese patients; however, the results and conclusions of such studies vary. Some studies have shown that VO is related to poor progression-free survival and poor response to adjuvant chemotherapy17-19 while other studies have argued that there is no convincing relationship between VO and survival or tumor stage of CRC.20,21 The role of VAT in CRC progression and recurrence remains to be elucidated and the numbers of studies concerning the association between metastasis and recurrence of CRC and VAT are very few.

We investigated the associations between VAT and oncologic outcomes, including overall survival, CRC-specific survival, progression-free survival, and metastasis sites, such as the liver, lung, or peritoneum, in stage III CRC.

1. Patients and data collection

The medical records of patients with colon or rectal cancer, who had undergone surgical bowel resection on account of CRC, and who had been seen at Severance Hospital, Yonsei University, Seoul, Korea, between January 1, 2007, and December 31, 2009, were identified. Among those identified, patients with metastasis at the time of diagnosis were excluded, as they were likely to have undergone significant weight loss, thus lowering the reliability of estimates on obesity and fat distribution. Patients were also excluded from the study if preoperative abdominal computed tomography (CT) could not be evaluated or if patients were diagnosed with any other type of cancer prior to the diagnosis of CRC. Finally, 472 patients diagnosed with stage III CRC were included.

Patient demographics and clinical characteristics, including age at diagnosis, gender, tumor stage at diagnosis and surgical diagnosis, and underlying medical conditions were obtained from medical records. Data regarding the history of use of drugs, family history of CRC, smoking history, drinking history, date of death and recurrence, cause of death, and received treatment were also obtained. The date of CRC diagnosis was defined as the day of pathologic diagnosis. Deaths were identified through medical records, and cause of death was determined in all cases. Height and weight recorded before surgery were used to calculate body mass index (BMI; weight in kg divided by height in m2). BMI was stratified into “underweight” (BMI <18.5 kg/m2), “normal” (BMI 18.5–24.9 kg/m2), “overweight” (BMI 25.0–29.9 kg/m2), and “obese” (BMI ≥30.0 kg/m2) based on the World Health Organization BMI classification.22

The Institutional Review Board of Severance Hospital, Yonsei University, Seoul, Korea, approved this study in accordance with the Declaration of Helsinki, and IRB review and informed consent were exempted after review of study design.

2. Measurements of abdominal adipose tissue

Preoperative abdomen CT (Siemens Medical Systems, Forchheim, Germany) was performed on all patients. VAT and SAT areas were retrospectively measured from three axial slices at the L3–L4, L4–L5, and L5–S1 intervertebral space. The CT attenuation level was set between –190 to –30 Hounsfield units, regions of adipose tissue were delineated, and areas of total adipose tissue, VAT, and SAT were calculated. The VAT area referred to the intra-abdominal fat bound by the parietal peritoneum or transversalis fascia, excluding the vertebral column and paraspinal muscles (Supplementary Fig. 1A). SAT area was the fat superficial to the abdominal and back muscles (Supplementary Fig. 1B). Free hand-driving mode program was used to measure fat volume. Automated fat segmentation was performed after adjusting the boundaries for subcutaneous and visceral compartments at each level. Then, we manipulated the fat segments to either include or exclude focal regions as required. A skilled radiologist, blinded to the patient’s data, measured all data.

The VAT to SAT ratio (VS ratio) and VAT to TAT ratio (VT ratio) were calculated to provide a single representative measure of abdominal fat.

3. Assessment of CRC staging and treatment

All patients with pathologically confirmed CRC were evaluated for appropriate staging based on 7th version of the American Joint Committee on Cancer TNM staging system. Treatment modality was determined based on the tumor extent and location at diagnosis and recurrence during follow-up. According to the National Comprehensive Cancer Network guideline, patients with locally advanced stage III CRC or recurrent advanced tumors with resectable metastatic lesions were treated by surgical resection, followed by adjuvant chemotherapy (FOLFOX regimen). Some patients with recurrent advanced tumors with metastasis were treated by neoadjuvant chemotherapy (FOLFIRI or FOLFOX with cetuximab or bevacizumab, based on primary tumor location and the result of KRAS mutation), followed by surgery. In case of rectal cancer, preoperative chemoradiation or postoperative radiation were added. Recurrent unresectable metastatic CRC were treated by palliative chemotherapy (FOFIRI or FOLFOX regimens) with target agent, such as cetuximab or bevacizumab, according to primary tumor location and the result of KRAS mutation analysis.

4. Statistical analysis

Descriptive statistics are presented as absolute (n) and relative (%) frequencies for categorical variables, and median or mean±standard deviation for quantitative variables. In comparison of covariates between non-overweight and overweight groups, the Pearson chi-square test or Student t-test were used for analyzing categorical or continuous data, respectively. Relationships between fat parameters and clinical outcomes were examined with Cox proportional hazards regression model, which was used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) after adjusting patient-related variables, including age at diagnosis, gender, and family history of CRC with medication, smoking, and alcohol history, when indicated. The Kaplan-Meier analysis was used for survival curves, which were compared by the log-rank test. Given well-known sex differences in fat distribution, we adjusted for sex in bivariate and multivariate analyses. Statistical analysis was performed using the software package SPSS 21.0 (IBM Corp., Armonk, NY, USA). A difference of p<0.05 was considered statistically significant.

1. Patients’ demographics and clinical characteristics

Four hundred and seventy-two patients diagnosed with stage III CRC underwent colorectal surgery. CT scans for evaluation of disease extent and staging were performed in all 472 patients. Among the enrolled, 154 patients were overweight, while 318 were not. Demographics and baseline clinical characteristics were mostly similar between the two groups, except for factors associated with fat distribution (Table 1). Median age at diagnosis was 59 years (range, 26 to 86 years), and 272 patients were men (57.6%). As for age, gender, family history of cancer, chronic disease, and medication status, smoking history, and drinking history, there was no significant difference between the two groups. Tumor location, T and N stage, histologic type, and treatment type also showed no difference between the two groups. Average VAT area (83.89±30.85 cm2 vs 57.62±26.53 cm2, p<0.001) and SAT area (178.01±66.22 cm2 vs 125.25±55.18 cm2, p<0.001) were both significantly higher in the overweight group than in the non-overweight group. However, the VT and VS ratios did not show significant differences between the two groups.

Table 1 Patient Demographics and Baseline Clinical Characteristics (n=472)

VariableTotal (n=472)Non-overweight
(BMI <25 kg/m2) (n=318)
Overweight
(BMI ≥25 kg/m2) (n=154)
p-value
Age, yr59 (26–86)59 (26–86)58 (29–80)0.355
Male sex272 (57.6)177 (55.7)95 (61.7)0.214
Smoking status0.836
Current smoker285 (60.4)191 (60.1)94 (61.0)
Former smoker91 (19.3)60 (18.9)31 (20.1)
Never smoker96 (20.3)67 (21.1)29 (18.8)
Daily drinker39 (8.3)28 (8.8)11 (7.1)0.539
Family history of colorectal cancer35 (7.4)23 (7.2)12 (7.8)0.828
Chronic disease and medication
Hypertension159 (33.7)103 (32.4)56 (36.4)0.392
Diabetes mellitus81 (17.2)56 (17.6)25 (16.2)0.710
Regular use of metformin44 (9.3)32 (10.1)12 (7.8)0.426
Regular use of low-dose aspirin94 (19.9)58 (18.2)36 (23.4)0.190
Fatty liver45 (9.5)20 (6.3)25 (16.2)0.001
Cancer location0.545
Colon285 (60.4)189 (59.4)96 (62.3)
Rectum187 (39.6)129 (40.6)56 (37.7)
T-stage0.090
Tis2 (0.4)02 (1.3)
T119 (4.0)11 (3.5)8 (5.2)
T246 (9.7)28 (8.8)18 (11.7)
T3346 (73.3)234 (73.5)112 (72.7)
T459 (12.5)45 (14.2)14 (9.1)
N-stage0.796
N01 (0.2)1 (0.3)0
N1a177 (37.5)123 (38.7)54 (35.1)
N1b150 (31.8)96 (30.2)54 (35.1)
N1c000
N2a92 (19.5)63 (19.8)29 (18.8)
N2b52 (11.0)35 (11.0)17 (11.0)
Histologic type0.497
Well differentiated45 (9.5)27 (8.5)18 (11.7)
Moderately differentiated388 (82.2)265 (83.3)123 (79.9)
Poorly/undifferentiated22 (4.7)14 (4.4)8 (5.2)
Unknown17 (3.6)12 (3.8)5 (3.2)
Treatment
Neoadjuvant CCRT32 (6.8)23 (7.2)9 (5.8)0.574
Adjuvant CTx460 (97.5)309 (97.2)151 (98.1)0.568
Adjuvant CCRT95 (20.1)63 (19.8)32 (20.8)0.806
Postoperative RT1 (0.2)01 (0.7)0.150
Measures of obesity*
VAT area, cm266.20±30.5757.62±26.5383.89±30.85<0.001
SAT area, cm2142.46±63.92125.25±55.18178.01±66.22<0.001
VAT to TAT ratio32.46±9.8132.32±9.8932.76±9.650.634
VAT to SAT ratio51.42±23.6051.13±23.5652.04±23.740.696

Data are presented as median (range), number (%), or mean±SD.

BMI, body mass index; CCRT, chemoradiation; CTx, chemotherapy; RT, radiation therapy; VAT, visceral adipose tissue; SAT, subcutaneous adipose tissue; TAT, total adipose tissue.

*VAT area and SAT area: the average value for area at each of the three vertebral levels: L3–L4, L4–L5, and L5–S1.



2. Fat distribution and survival analysis

Among the entire cohort, there were total of 111 deaths, of which 67 cases were CRC-related. There were 114 cases of recurrence, with the lung being the most frequent site of recurrence (34 cases), followed by the liver and peritoneum, with 33 and 25 cases of recurrence, respectively. The median follow-up duration was 60 months (range, 12 to 84 months).

Overall survival and CRC-specific survival were investigated according to the obesity index (Tables 2 and 3). The Cox hazard regression analysis for overall survival showed that BMI was an independent risk factor for overall mortality. Higher BMI tended to display a lower risk of overall mortality in univariate analysis (HR, 0.939; 95% CI, 0.884 to 0.998; p=0.043), and this result was consistent after adjusting for age at diagnosis, sex, and familial history of CRC (HR, 0.915; 95% CI, 0.840 to 0.997; p=0.044). Regarding CRC-specific survival analysis, BMI was not a significant independent factor associated with CRC-specific mortality (HR, 1.006; 95% CI, 0.904 to 1.120; p=0.908). Interestingly, neither average VAT nor SAT area was associated with overall mortality. Meanwhile, the VT ratio (HR, 1.020; 95% CI, 1.001 to 1.039; p=0.043) and VS ratio (HR, 1.008; 95% CI, 1.001 to 1.016; p=0.027) were both related to higher overall mortality in univariate analysis. However, after adjustment for clinical factors, the results were not statistically significant. Nonetheless, VT and VS ratios were both independent predictors for CRC-specific mortality in stage III CRC after surgical resection (Table 3). In univariate analysis, both VT ratio (HR, 1.031; 95% CI, 1.006 to 1.056; p=0.014) and VS ratio (HR, 1.013; 95% CI, 1.004 to 1.022; p=0.005) were significantly associated with higher cancer-specific mortality; after adjustment of clinically relevant factors, the results maintained statistical significance (VT ratio: HR, 1.041; 95% CI, 1.008 to 1.075; p=0.015 and VS ratio: HR, 1.016; 95% CI, 1.005 to 1.028; p=0.006).

Table 2 Cox Hazard Regression Analysis for Overall Mortality According to Obesity Index

Obesity indexUnivariate HR (95% CI)p-valueAdjusted HR (95% CI)*p-value
BMI0.939 (0.884–0.998)0.0430.915 (0.840–0.997)0.044
Average VAT area1.000 (0.994–1.006)0.8881.003 (0.995–1.011)0.506
Average SAT area0.999 (0.996–1.002)0.4051.002 (0.997–1.007)0.453
VAT to TAT ratio1.020 (1.001–1.039)0.0431.022 (0.997–1.049)0.091
VAT to SAT ratio1.008 (1.001–1.016)0.0271.009 (1.000–1.019)0.058

HR, hazard ratio; CI, confidence interval; BMI, body mass index; VAT, visceral adipose tissue; SAT, subcutaneous adipose tissue; TAT, total adipose tissue.

*Adjusted for age at diagnosis, sex, familial history of colorectal cancer.



Table 3 Cox Hazard Regression Analysis for Colorectal Cancer-Specific Mortality According to Obesity Index

Obesity indexUnivariate HR (95% CI)p-valueAdjusted HR (95% CI)*p-value
BMI0.980 (0.907–1.059)0.6131.006 (0.904–1.120)0.908
Average VAT1.001 (0.993–1.008)0.8951.004 (0.993–1.014)0.493
Average SAT0.997 (0.993–1.001)0.1970.996 (0.990–1.003)0.278
VAT to TAT ratio1.031 (1.006–1.056)0.0141.041 (1.008–1.075)0.015
VAT to SAT ratio1.013 (1.004–1.022)0.0051.016 (1.005–1.028)0.006

HR, hazard ratio; CI, confidence interval; BMI, body mass index; VAT, visceral adipose tissue; SAT, subcutaneous adipose tissue; TAT, total adipose tissue.

*Adjusted for age at diagnosis, sex, familial history of colorectal cancer.



Additionally, according to the VT ratios of each intervertebral level, overall survival, cancer-specific survival, and recurrence-free survival were analyzed. There were no significant results regarding the overall survival and recurrence-free survival (Supplementary Tables 1 and 2). However, all three VT ratios (at L3–L4, L4–L5, and L5–S1) showed significant results, as higher VT ratios were associated with higher cancer-specific mortality, in analyses both unadjusted and adjusted for clinically relevant factors (Supplementary Table 3).

3. Fat distribution and recurrence

Recurrence-free survival analysis was also performed according to obesity index (Table 4); however, there were no statistically significant results. BMI (HR, 0.978; 95% CI, 0.898 to 1.065; p=0.612), VAT (HR, 0.995; 95% CI, 0.986 to 1.003; p=0.234), and VT ratio (HR, 0.989; 95% CI, 0.963 to 1.015; p=0.387) were not associated with recurrence after treatment of stage III CRC. We performed additional analyses concerning the location of tumor recurrence. First, we investigated the relationship between fatty liver and liver recurrence; however, no significant association was found between these two factors (Supplementary Fig. 2). Liver and lung metastases according to obesity index were also evaluated separately; however, the analysis showed no significant results (Supplementary Tables 4 and 5). Analysis regarding peritoneal seeding recurrence provided interesting results (Table 5). In the multivariate analysis for peritoneal seeding recurrence according to obesity index and after adjusting for clinically relevant factors, BMI, VT ratio, and VS ratio showed statistically significant results. Higher VT (HR, 1.069; 95% CI, 1.010 to 1.131; p=0.020) and VS ratio (HR, 1.024; 95% CI, 1.003 to 1.045; p=0.023) were both associated with a higher risk of peritoneal seeding recurrence, but higher BMI (HR, 0.877; 95% CI, 0.774 to 0.994; p=0.040) was associated with a lower risk of peritoneal seeding recurrence. When VT ratio was divided into two groups by the highest and lowest 25 percentile number, VT ratio of the highest 25 percentile group had a 5-time higher risk of peritoneal recurrence than the lowest 25 percentile group (HR, 5.587; 95% CI, 1.048 to 29.789; p=0.044). However, results regarding VS ratio showed an irrelevant outcome (HR, 2.206; 95% CI, 0.616 to 7.895; p=0.224).

Table 4 Cox Hazard Regression Analysis for Recurrence According to Obesity Index

Obesity indexUnivariate HR (95% CI)p-valueAdjusted HR (95% CI)*p-value
BMI0.971 (0.915–1.031)0.3420.978 (0.898–1.065)0.612
Average VAT0.996 (0.990–1.003)0.2490.995 (0.986–1.003)0.234
Average SAT0.999 (0.996–1.002)0.3721.002 (0.997–1.007)0.541
VAT to TAT ratio1.000 (0.981–1.019)0.9780.989 (0.963–1.015)0.387
VAT to SAT ratio1.000 (0.992–1.008)0.9760.996 (0.986–1.006)0.446

HR, hazard ratio; CI, confidence interval; BMI, body mass index; VAT, visceral adipose tissue; SAT, subcutaneous adipose tissue; TAT, total adipose tissue.

*Adjusted for age at diagnosis, sex, familial history of colorectal cancer.



Table 5 Cox Hazard Regression Analysis for Peritoneal Seeding According to Obesity Index

Obesity indexUnivariate HR (95% CI)p-valueAdjusted HR (95% CI)*p-value
BMI0.884 (0.780–1.002)0.0540.877 (0.774–0.994)0.040
Average VAT1.003 (0.990–1.016)0.6711.007 (0.991–1.021)0.369
Average SAT0.999 (0.992–1.006)0.7970.997 (0.990–1.004)0.393
VAT to TAT ratio1.017 (0.977–1.059)0.4131.069 (1.010–1.131)0.020
VAT to TAT ratio (top vs bottom 25th percentile)
≤24.53%1.0001.000
>38.85%1.657 (0.479–5.729)0.4255.587 (1.048–29.789)0.044
VAT to SAT ratio1.007 (0.991–1.024)0.3731.024 (1.003–1.045)0.023
VAT to SAT ratio (top vs bottom 25th percentile)
≤32.50%1.0001.000
>63.53%1.900 (0.564–6.395)0.3002.206 (0.616–7.895)0.224

HR, hazard ratio; CI, confidence interval; BMI, body mass index; VAT, visceral adipose tissue; SAT, subcutaneous adipose tissue; TAT, total adipose tissue.

*Adjusted for age at diagnosis, sex, familial history of colorectal cancer.



Since the VAT and SAT areas used in survival and recurrence analyses were the average values of three intervertebral levels, another subgroup analysis, comparing peritoneal recurrence risk of these three intervertebral levels, was performed. Peritoneal seeding recurrence rate according to VT ratio of each spine level in stage III CRC patients was best explained when applying the area of adipose tissue from the L3 to L4 intervertebral level (Fig. 1A). When VT ratio of the L3–L4 level was divided into two groups by 50 percentile number, VT ratio of higher than 50 percentile had almost a 5-time higher risk of peritoneal recurrence than the lower than 50 percentile group (HR, 4.969; 95% CI, 1.303 to 18.949; p=0.019). However, VT ratio of higher than 50 percentile at the L4–L5 level (HR, 0.514; 95% CI, 0.091 to 2.892; p=0.450) or L5–S1 level (HR, 2.617; 95% CI, 0.413 to 16.57; p=0.307) was not associated with a higher risk of peritoneal recurrence (Fig. 1B and C).

Figure 1.Peritoneal seeding rate according to the visceral adipose tissue to total adipose tissue area ratio at each level of the lumbar spine in stage III colorectal cancer patients. (A) Visceral to total adipose tissue (VT) ratio at the L3–L4 level, (B) VT ratio at the L4–L5 level, (C) VT ratio at the L5–S1 level.

Obesity is known to be a risk factor for the development of several cancers, including CRC. However, the influence of VAT distribution on the outcomes of patients with CRC remains controversial. The objective of this study was to examine the outcome of CRC patients according to obesity indices including BMI, VAT area, SAT area, and their corresponding ratios.

Compared to SAT, VAT is known to be more biologically active and therefore related to obesity-related diseases including cancer.7,15,23 Most of VAT is distributed within the omentum, mesentery, and retroperitoneum.24 Then, we considered CT scan as a better method for measurement of fat because CT scan is mandatory examination before treatment of all newly diagnosed CRC. We focused on VAT distribution and its relative ratio to total adipose tissue or SAT distribution.

The most interesting finding in our study was that a higher VT ratio and a higher VS ratio were both associated with a higher risk of peritoneal seeding recurrence. To our knowledge, this is the first study to find a relationship between peritoneal seeding recurrence and visceral fat. Several studies have provided evidence of the significant contribution of VO to cancer development and aimed to understand the role of omental fat in intraperitoneal tumorigenesis. Using coculture system to simulate the crosstalk between adipocytes and cancer cells, Xiang et al.25 showed that omental adipocytes induced a significant increase of lipid uptake in gastric cancer cells, and enhanced their invasiveness. Similarly, another study using coculture of adipocyte and ovarian cancer cells demonstrated the direct transfer of lipids from adipocytes to cancer cells and an increase of tumor growth.26 In addition to the adipocytes, stimulation of peritoneal tumors is also associated with omental adipose tissue-derived stem cells (ASCs). Nowicka et al.27 reported that ASCs significantly promoted proliferation, migration, and resistance to chemotherapy and radiation in ovarian cancer cell lines by providing cancer cells with lactose and ATP generated in the glycolytic pathway. Another series of experiments using ASCs isolated from mice showed that cells isolated from the visceral fat of obese animals were able to increase the development of intraperitoneal tumors, whereas cells obtained from SAT lacked this activity.28

Along with these reports, the traditional “insulin hypothesis” has also been used to explain the relationship between obesity or visceral adiposity and CRC.11,29 Prospective studies have shown an increased risk of CRC in individuals with higher levels of postprandial insulin,30 C-peptide,31 and fasting glucose.30 However, Renehan et al.32 showed that not only the insulin/insulin-like growth factor molecular pathway, but also metabolic syndrome, aging, endogenous sex hormones, adiponectin, and leptin are all very complexly connected with inter-related regulation. Therefore, the insulin hypothesis, sex hormones and adiponectin, adipocyte-promoted lipid internalization of cancer cells, and ASCs affect and regulate each other in the process of peritoneal metastasis.

However, our assessment regarding peritoneal seeding recurrence and overall survival has shown that higher BMI was related to a lower risk of peritoneal seeding recurrence and overall mortality. In a recent review article regarding BMI, obesity, and their association with cardiovascular diseases, the authors claimed that BMI does not explain fat distribution or degree of VO.33 The metabolically healthy obese phenotype refers to a subgroup of obese individuals in which high BMI is associated with a healthy metabolic profile, characterized by high insulin sensitivity, favorable lipid profile, low VAT, and high lean mass. The “metabolically health” with healthy obese phenotype was not considered in our study, but this might have affected the results of our study, showing a low risk of peritoneal seeding and overall mortality in patients with higher BMI.

Our study has some limitations. First, given the retrospective nature of this study, the results require cautious interpretation. In addition, there is currently no established threshold of VAT area or VS ratio for defining VO. However, our findings might provide additional supportive evidence in this research area. Further, although our study includes a very heterogeneous patient population, it also includes a large number of subjects with stage III CRC, which improves the reliability of the results. Finally, the results of this study should be confirmed among the general population because patients of this study were from a tertiary medical institute.

In conclusion, VO is closely related to the increased risk of CRC-specific mortality and, most intriguingly, to higher risk of peritoneal seeding metastasis in patients with stage III CRC. These findings could be useful in strategy making process of diet and physical care for the patient group in actual clinical field. Further studies are needed to clarify the physiologic and biologic mechanisms mediating the link between visceral adiposity and CRC metastasis. The assimilation of quantitative measures of VO and corresponding clinical studies is needed to integrate these results with therapeutic and epidemiologic studies.

This research was supported by a grant from the National R&D Program for Cancer Control, Ministry of Health and Welfare, Republic of Korea (grant number: 1631020).

This abstract was presented in a poster session at Asian Pacific Digestive Week 2018 (APDW 2018), on November 15-18, 2018, in Seoul, Korea.

S.J.P. and J.H.C. are editorial board members of the journal but were not involved in the peer reviewer selection, evaluation, or decision process of this article. No other potential conflicts of interest relevant to this article were reported.

Study concept and design: T.I.K. Data acquisition: J.W.P., S.Y.C., S.J.P., J.J.P., J.H.C., J.S.L., W.H.K. Data analysis and interpretation: J.W.P., S.Y.C., J.S.L., T.I.K. Statistical analysis: J.W.P., S.Y.C. Drafting of the manuscript: J.W.P., S.Y.C. Critical revision of the manuscript: S.J.P., J.J.P., J.H.C., W.H.K., T.I.K.

  1. Renehan AG, Soerjomataram I, Tyson M, et al. Incident cancer burden attributable to excess body mass index in 30 European countries. Int J Cancer 2010;126:692-702.
    Pubmed CrossRef
  2. Bardou M, Barkun AN, Martel M. Obesity and colorectal cancer. Gut 2013;62:933-947.
    Pubmed CrossRef
  3. Gribovskaja-Rupp I, Kosinski L, Ludwig KA. Obesity and colorectal cancer. Clin Colon Rectal Surg 2011;24:229-243.
    Pubmed KoreaMed CrossRef
  4. Vucenik I, Stains JP. Obesity and cancer risk: evidence, mechanisms, and recommendations. Ann N Y Acad Sci 2012;1271:37-43.
    Pubmed KoreaMed CrossRef
  5. Otake S, Takeda H, Suzuki Y, et al. Association of visceral fat accumulation and plasma adiponectin with colorectal adenoma: evidence for participation of insulin resistance. Clin Cancer Res 2005;11:3642-3646.
    Pubmed CrossRef
  6. Ibrahim MM. Subcutaneous and visceral adipose tissue: structural and functional differences. Obes Rev 2010;11:11-18.
    Pubmed CrossRef
  7. Després JP, Lemieux I. Abdominal obesity and metabolic syndrome. Nature 2006;444:881-887.
    Pubmed KoreaMed CrossRef
  8. Bianchini F, Kaaks R, Vainio H. Overweight, obesity, and cancer risk. Lancet Oncol 2002;3:565-574.
    Pubmed CrossRef
  9. Donohoe CL, Doyle SL, Reynolds JV. Visceral adiposity, insulin resistance and cancer risk. Diabetol Metab Syndr 2011;3:12.
    Pubmed KoreaMed CrossRef
  10. DeFronzo RA, Ferrannini E. Insulin resistance: a multifaceted syndrome responsible for NIDDM, obesity, hypertension, dyslipidemia, and atherosclerotic cardiovascular disease. Diabetes Care 1991;14:173-194.
    Pubmed CrossRef
  11. Giovannucci E. Insulin and colon cancer. Cancer Causes Control 1995;6:164-179.
    Pubmed CrossRef
  12. Otani T, Iwasaki M, Sasazuki S, Inoue M, Tsugane S; Japan Public Health Center-based Prospective Study Group. Plasma C-peptide, insulin-like growth factor-I, insulin-like growth factor binding proteins and risk of colorectal cancer in a nested case-control study: the Japan public health center-based prospective study. Int J Cancer 2007;120:2007-2012.
    Pubmed CrossRef
  13. Cecchini S, Cavazzini E, Marchesi F, Sarli L, Roncoroni L. Computed tomography volumetric fat parameters versus body mass index for predicting short-term outcomes of colon surgery. World J Surg 2011;35:415-423.
    Pubmed CrossRef
  14. Goulart A, Malheiro N, Rios H, Sousa N, Leão P. Influence of visceral fat in the outcomes of colorectal cancer. Dig Surg 2019;36:33-40.
    Pubmed CrossRef
  15. Hiuge-Shimizu A, Kishida K, Funahashi T, et al. Absolute value of visceral fat area measured on computed tomography scans and obesity-related cardiovascular risk factors in large-scale Japanese general population (the VACATION-J study). Ann Med 2012;44:82-92.
    Pubmed CrossRef
  16. Tsujinaka S, Konishi F, Kawamura YJ, et al. Visceral obesity predicts surgical outcomes after laparoscopic colectomy for sigmoid colon cancer. Dis Colon Rectum 2008;51:1757-1765.
    Pubmed CrossRef
  17. Rickles AS, Iannuzzi JC, Mironov O, et al. Visceral obesity and colorectal cancer: are we missing the boat with BMI? J Gastrointest Surg 2013;17:133-143.
    Pubmed CrossRef
  18. Clark W, Siegel EM, Chen YA, et al. Quantitative measures of visceral adiposity and body mass index in predicting rectal cancer outcomes after neoadjuvant chemoradiation. J Am Coll Surg 2013;216:1070-1081.
    Pubmed KoreaMed CrossRef
  19. Guiu B, Petit JM, Bonnetain F, et al. Visceral fat area is an independent predictive biomarker of outcome after first-line bevacizumab-based treatment in metastatic colorectal cancer. Gut 2010;59:341-347.
    Pubmed CrossRef
  20. Mahamid A, Ashkenazi I, Shapira-Rootman M, et al. Impact of increased visceral fat measured by CT on colon adenocarcinoma stage. J Gastrointest Cancer 2017;48:347-352.
    Pubmed CrossRef
  21. Park SW, Lee HL, Doo EY, et al. Visceral obesity predicts fewer lymph node metastases and better overall survival in colon cancer. J Gastrointest Surg 2015;19:1513-1521.
    Pubmed KoreaMed CrossRef
  22. WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004;363:157-163.
    Pubmed CrossRef
  23. Matsuzawa Y, Nakamura T, Shimomura I, Kotani K. Visceral fat accumulation and cardiovascular disease. Obes Res 1995;3 Suppl 5:645S-647S.
    Pubmed CrossRef
  24. Bjørndal B, Burri L, Staalesen V, Skorve J, Berge RK. Different adipose depots: their role in the development of metabolic syndrome and mitochondrial response to hypolipidemic agents. J Obes 2011;2011:490650.
    Pubmed KoreaMed CrossRef
  25. Xiang F, Wu K, Liu Y, et al. Omental adipocytes enhance the invasiveness of gastric cancer cells by oleic acid-induced activation of the PI3K-Akt signaling pathway. Int J Biochem Cell Biol 2017;84:14-21.
    Pubmed CrossRef
  26. Nieman KM, Kenny HA, Penicka CV, et al. Adipocytes promote ovarian cancer metastasis and provide energy for rapid tumor growth. Nat Med 2011;17:1498-1503.
    Pubmed KoreaMed CrossRef
  27. Nowicka A, Marini FC, Solley TN, et al. Human omental-derived adipose stem cells increase ovarian cancer proliferation, migration, and chemoresistance. PLoS One 2013;8:e81859.
    Pubmed KoreaMed CrossRef
  28. Zhang Y, Nowicka A, Solley TN, et al. Stromal cells derived from visceral and obese adipose tissue promote growth of ovarian cancers. PLoS One 2015;10:e0136361.
    Pubmed KoreaMed CrossRef
  29. McKeown-Eyssen G. Epidemiology of colorectal cancer revisited: are serum triglycerides and/or plasma glucose associated with risk? Cancer Epidemiol Biomarkers Prev 1994;3:687-695.
    Pubmed
  30. Schoen RE, Tangen CM, Kuller LH, et al. Increased blood glucose and insulin, body size, and incident colorectal cancer. J Natl Cancer Inst 1999;91:1147-1154.
    Pubmed CrossRef
  31. Kaaks R, Toniolo P, Akhmedkhanov A, et al. Serum C-peptide, insulin-like growth factor (IGF)-I, IGF-binding proteins, and colorectal cancer risk in women. J Natl Cancer Inst 2000;92:1592-1600.
    Pubmed CrossRef
  32. Renehan AG, Frystyk J, Flyvbjerg A. Obesity and cancer risk: the role of the insulin-IGF axis. Trends Endocrinol Metab 2006;17:328-336.
    Pubmed CrossRef
  33. Vecchié A, Dallegri F, Carbone F, et al. Obesity phenotypes and their paradoxical association with cardiovascular diseases. Eur J Intern Med 2018;48:6-17.
    Pubmed CrossRef

Article

Original Article

Gut and Liver 2022; 16(1): 53-61

Published online January 15, 2022 https://doi.org/10.5009/gnl20266

Copyright © Gut and Liver.

Impact of Visceral Fat on Survival and Metastasis of Stage III Colorectal Cancer

Jung Won Park1 , Soo Yeon Chang2 , Joon Seok Lim3 , Soo Jung Park1 , Jae Jun Park1,4 , Jae Hee Cheon1 , Won Ho Kim1 , Tae Il Kim1,4,5

1Department of Internal Medicine and Institute of Gastroenterology, Yonsei University College of Medicine, 2Health Promotion Center, Severance Hospital, Yonsei University College of Medicine, 3Department of Radiology, Yonsei University College of Medicine, 4Yonsei Cancer Prevention Center, Severance Hospital, Yonsei University College of Medicine, and 5Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, Seoul, Korea

Correspondence to:Tae Il Kim
ORCID https://orcid.org/0000-0003-4807-890X
E-mail taeilkim@yuhs.ac

Received: August 21, 2020; Revised: January 8, 2021; Accepted: January 19, 2021

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background/Aims: Previous studies have investigated the relationship between visceral obesity and the risk of colorectal tumors. Visceral obesity may affect the outcome of colorectal cancer (CRC), including survival and metastasis. We investigated the associations between visceral adipose tissue and oncologic outcomes in stage III CRC.
Methods: Four hundred seventy-two patients with stage III CRC were identified. Subcutaneous and visceral adipose tissue areas were measured volumetrically via computed tomography for each patient at different levels of the lumbar spine. After adjusting for age, sex, and other clinical factors, the effects of visceral adipose tissue area on mortality and recurrence were assessed using Cox proportional hazard regression.
Results: In univariate and multivariate analyses, a higher visceral adipose tissue to total adipose tissue (VT) ratio (hazard ratio [HR], 1.041; 95% CI, 1.008 to 1.075; p=0.015) and higher visceral adipose tissue to subcutaneous adipose tissue (VS) ratio (HR, 1.016; 95% CI, 1.005 to 1.028; p=0.006) were both associated with poor CRC-specific survival. Interestingly, in the evaluation of each site of recurrence, a higher VT ratio (HR, 1.069; 95% CI, 1.010 to 1.131; p=0.020) and higher VS ratio (HR, 1.024; 95% CI, 1.003 to 1.045; p=0.023) were both related to a higher risk of peritoneal seeding and tumor recurrence. The VT ratio at the L3–L4 level was significantly associated with a higher risk of peritoneal seeding and tumor recurrence (HR, 4.969; 95% CI, 1.303 to 18.949; p=0.019), while other levels showed no such relationship.
Conclusions: Visceral obesity is closely related to increased risks of CRC-specific mortality and peritoneal seeding metastasis in stage III CRC patients.

Keywords: Obesity, Fat, Visceral, Colorectal neoplasms, Outcome

INTRODUCTION

Obesity and cancer are the two most serious emerging health problems, and their interrelationship has also been known.1 Obesity is a well-known risk factor for the development of colorectal cancer (CRC) and is also associated with higher risks of postoperative complication rates and recurrence after adjuvant chemotherapy.2,3 Although the underlying mechanisms of their interaction remain unclear, recent data suggests an important role of visceral fat in this relationship.4,5 Visceral adipose tissue (VAT) has higher hormonal and metabolic activities than subcutaneous adipose tissue (SAT).6 Visceral adipocyte-induced insulin-like growth factor, inflammatory adipokines like interleukin-6 and tumor necrosis factor-α, and angiogenic factors are reported as mediators related with the tumorigenesis of obesity-related tumors.7-9 Furthermore, insulin resistance, commonly found in obesity, results in compensatory hyperinsulinemia. As key growth factors for colonic epithelial cells, insulin and C-peptide are well known mitogens of tumor cell growth.10-12

Previous studies have revealed the relationship between CRC and visceral obesity (VO). However, most studies have focused on the risk of complications after surgery, rather than recurrence or survival of CRC patients.13-16 A few studies have shown the oncologic outcomes of CRC in viscerally obese patients; however, the results and conclusions of such studies vary. Some studies have shown that VO is related to poor progression-free survival and poor response to adjuvant chemotherapy17-19 while other studies have argued that there is no convincing relationship between VO and survival or tumor stage of CRC.20,21 The role of VAT in CRC progression and recurrence remains to be elucidated and the numbers of studies concerning the association between metastasis and recurrence of CRC and VAT are very few.

We investigated the associations between VAT and oncologic outcomes, including overall survival, CRC-specific survival, progression-free survival, and metastasis sites, such as the liver, lung, or peritoneum, in stage III CRC.

MATERIALS AND METHODS

1. Patients and data collection

The medical records of patients with colon or rectal cancer, who had undergone surgical bowel resection on account of CRC, and who had been seen at Severance Hospital, Yonsei University, Seoul, Korea, between January 1, 2007, and December 31, 2009, were identified. Among those identified, patients with metastasis at the time of diagnosis were excluded, as they were likely to have undergone significant weight loss, thus lowering the reliability of estimates on obesity and fat distribution. Patients were also excluded from the study if preoperative abdominal computed tomography (CT) could not be evaluated or if patients were diagnosed with any other type of cancer prior to the diagnosis of CRC. Finally, 472 patients diagnosed with stage III CRC were included.

Patient demographics and clinical characteristics, including age at diagnosis, gender, tumor stage at diagnosis and surgical diagnosis, and underlying medical conditions were obtained from medical records. Data regarding the history of use of drugs, family history of CRC, smoking history, drinking history, date of death and recurrence, cause of death, and received treatment were also obtained. The date of CRC diagnosis was defined as the day of pathologic diagnosis. Deaths were identified through medical records, and cause of death was determined in all cases. Height and weight recorded before surgery were used to calculate body mass index (BMI; weight in kg divided by height in m2). BMI was stratified into “underweight” (BMI <18.5 kg/m2), “normal” (BMI 18.5–24.9 kg/m2), “overweight” (BMI 25.0–29.9 kg/m2), and “obese” (BMI ≥30.0 kg/m2) based on the World Health Organization BMI classification.22

The Institutional Review Board of Severance Hospital, Yonsei University, Seoul, Korea, approved this study in accordance with the Declaration of Helsinki, and IRB review and informed consent were exempted after review of study design.

2. Measurements of abdominal adipose tissue

Preoperative abdomen CT (Siemens Medical Systems, Forchheim, Germany) was performed on all patients. VAT and SAT areas were retrospectively measured from three axial slices at the L3–L4, L4–L5, and L5–S1 intervertebral space. The CT attenuation level was set between –190 to –30 Hounsfield units, regions of adipose tissue were delineated, and areas of total adipose tissue, VAT, and SAT were calculated. The VAT area referred to the intra-abdominal fat bound by the parietal peritoneum or transversalis fascia, excluding the vertebral column and paraspinal muscles (Supplementary Fig. 1A). SAT area was the fat superficial to the abdominal and back muscles (Supplementary Fig. 1B). Free hand-driving mode program was used to measure fat volume. Automated fat segmentation was performed after adjusting the boundaries for subcutaneous and visceral compartments at each level. Then, we manipulated the fat segments to either include or exclude focal regions as required. A skilled radiologist, blinded to the patient’s data, measured all data.

The VAT to SAT ratio (VS ratio) and VAT to TAT ratio (VT ratio) were calculated to provide a single representative measure of abdominal fat.

3. Assessment of CRC staging and treatment

All patients with pathologically confirmed CRC were evaluated for appropriate staging based on 7th version of the American Joint Committee on Cancer TNM staging system. Treatment modality was determined based on the tumor extent and location at diagnosis and recurrence during follow-up. According to the National Comprehensive Cancer Network guideline, patients with locally advanced stage III CRC or recurrent advanced tumors with resectable metastatic lesions were treated by surgical resection, followed by adjuvant chemotherapy (FOLFOX regimen). Some patients with recurrent advanced tumors with metastasis were treated by neoadjuvant chemotherapy (FOLFIRI or FOLFOX with cetuximab or bevacizumab, based on primary tumor location and the result of KRAS mutation), followed by surgery. In case of rectal cancer, preoperative chemoradiation or postoperative radiation were added. Recurrent unresectable metastatic CRC were treated by palliative chemotherapy (FOFIRI or FOLFOX regimens) with target agent, such as cetuximab or bevacizumab, according to primary tumor location and the result of KRAS mutation analysis.

4. Statistical analysis

Descriptive statistics are presented as absolute (n) and relative (%) frequencies for categorical variables, and median or mean±standard deviation for quantitative variables. In comparison of covariates between non-overweight and overweight groups, the Pearson chi-square test or Student t-test were used for analyzing categorical or continuous data, respectively. Relationships between fat parameters and clinical outcomes were examined with Cox proportional hazards regression model, which was used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) after adjusting patient-related variables, including age at diagnosis, gender, and family history of CRC with medication, smoking, and alcohol history, when indicated. The Kaplan-Meier analysis was used for survival curves, which were compared by the log-rank test. Given well-known sex differences in fat distribution, we adjusted for sex in bivariate and multivariate analyses. Statistical analysis was performed using the software package SPSS 21.0 (IBM Corp., Armonk, NY, USA). A difference of p<0.05 was considered statistically significant.

RESULTS

1. Patients’ demographics and clinical characteristics

Four hundred and seventy-two patients diagnosed with stage III CRC underwent colorectal surgery. CT scans for evaluation of disease extent and staging were performed in all 472 patients. Among the enrolled, 154 patients were overweight, while 318 were not. Demographics and baseline clinical characteristics were mostly similar between the two groups, except for factors associated with fat distribution (Table 1). Median age at diagnosis was 59 years (range, 26 to 86 years), and 272 patients were men (57.6%). As for age, gender, family history of cancer, chronic disease, and medication status, smoking history, and drinking history, there was no significant difference between the two groups. Tumor location, T and N stage, histologic type, and treatment type also showed no difference between the two groups. Average VAT area (83.89±30.85 cm2 vs 57.62±26.53 cm2, p<0.001) and SAT area (178.01±66.22 cm2 vs 125.25±55.18 cm2, p<0.001) were both significantly higher in the overweight group than in the non-overweight group. However, the VT and VS ratios did not show significant differences between the two groups.

Table 1 . Patient Demographics and Baseline Clinical Characteristics (n=472).

VariableTotal (n=472)Non-overweight
(BMI <25 kg/m2) (n=318)
Overweight
(BMI ≥25 kg/m2) (n=154)
p-value
Age, yr59 (26–86)59 (26–86)58 (29–80)0.355
Male sex272 (57.6)177 (55.7)95 (61.7)0.214
Smoking status0.836
Current smoker285 (60.4)191 (60.1)94 (61.0)
Former smoker91 (19.3)60 (18.9)31 (20.1)
Never smoker96 (20.3)67 (21.1)29 (18.8)
Daily drinker39 (8.3)28 (8.8)11 (7.1)0.539
Family history of colorectal cancer35 (7.4)23 (7.2)12 (7.8)0.828
Chronic disease and medication
Hypertension159 (33.7)103 (32.4)56 (36.4)0.392
Diabetes mellitus81 (17.2)56 (17.6)25 (16.2)0.710
Regular use of metformin44 (9.3)32 (10.1)12 (7.8)0.426
Regular use of low-dose aspirin94 (19.9)58 (18.2)36 (23.4)0.190
Fatty liver45 (9.5)20 (6.3)25 (16.2)0.001
Cancer location0.545
Colon285 (60.4)189 (59.4)96 (62.3)
Rectum187 (39.6)129 (40.6)56 (37.7)
T-stage0.090
Tis2 (0.4)02 (1.3)
T119 (4.0)11 (3.5)8 (5.2)
T246 (9.7)28 (8.8)18 (11.7)
T3346 (73.3)234 (73.5)112 (72.7)
T459 (12.5)45 (14.2)14 (9.1)
N-stage0.796
N01 (0.2)1 (0.3)0
N1a177 (37.5)123 (38.7)54 (35.1)
N1b150 (31.8)96 (30.2)54 (35.1)
N1c000
N2a92 (19.5)63 (19.8)29 (18.8)
N2b52 (11.0)35 (11.0)17 (11.0)
Histologic type0.497
Well differentiated45 (9.5)27 (8.5)18 (11.7)
Moderately differentiated388 (82.2)265 (83.3)123 (79.9)
Poorly/undifferentiated22 (4.7)14 (4.4)8 (5.2)
Unknown17 (3.6)12 (3.8)5 (3.2)
Treatment
Neoadjuvant CCRT32 (6.8)23 (7.2)9 (5.8)0.574
Adjuvant CTx460 (97.5)309 (97.2)151 (98.1)0.568
Adjuvant CCRT95 (20.1)63 (19.8)32 (20.8)0.806
Postoperative RT1 (0.2)01 (0.7)0.150
Measures of obesity*
VAT area, cm266.20±30.5757.62±26.5383.89±30.85<0.001
SAT area, cm2142.46±63.92125.25±55.18178.01±66.22<0.001
VAT to TAT ratio32.46±9.8132.32±9.8932.76±9.650.634
VAT to SAT ratio51.42±23.6051.13±23.5652.04±23.740.696

Data are presented as median (range), number (%), or mean±SD..

BMI, body mass index; CCRT, chemoradiation; CTx, chemotherapy; RT, radiation therapy; VAT, visceral adipose tissue; SAT, subcutaneous adipose tissue; TAT, total adipose tissue..

*VAT area and SAT area: the average value for area at each of the three vertebral levels: L3–L4, L4–L5, and L5–S1..



2. Fat distribution and survival analysis

Among the entire cohort, there were total of 111 deaths, of which 67 cases were CRC-related. There were 114 cases of recurrence, with the lung being the most frequent site of recurrence (34 cases), followed by the liver and peritoneum, with 33 and 25 cases of recurrence, respectively. The median follow-up duration was 60 months (range, 12 to 84 months).

Overall survival and CRC-specific survival were investigated according to the obesity index (Tables 2 and 3). The Cox hazard regression analysis for overall survival showed that BMI was an independent risk factor for overall mortality. Higher BMI tended to display a lower risk of overall mortality in univariate analysis (HR, 0.939; 95% CI, 0.884 to 0.998; p=0.043), and this result was consistent after adjusting for age at diagnosis, sex, and familial history of CRC (HR, 0.915; 95% CI, 0.840 to 0.997; p=0.044). Regarding CRC-specific survival analysis, BMI was not a significant independent factor associated with CRC-specific mortality (HR, 1.006; 95% CI, 0.904 to 1.120; p=0.908). Interestingly, neither average VAT nor SAT area was associated with overall mortality. Meanwhile, the VT ratio (HR, 1.020; 95% CI, 1.001 to 1.039; p=0.043) and VS ratio (HR, 1.008; 95% CI, 1.001 to 1.016; p=0.027) were both related to higher overall mortality in univariate analysis. However, after adjustment for clinical factors, the results were not statistically significant. Nonetheless, VT and VS ratios were both independent predictors for CRC-specific mortality in stage III CRC after surgical resection (Table 3). In univariate analysis, both VT ratio (HR, 1.031; 95% CI, 1.006 to 1.056; p=0.014) and VS ratio (HR, 1.013; 95% CI, 1.004 to 1.022; p=0.005) were significantly associated with higher cancer-specific mortality; after adjustment of clinically relevant factors, the results maintained statistical significance (VT ratio: HR, 1.041; 95% CI, 1.008 to 1.075; p=0.015 and VS ratio: HR, 1.016; 95% CI, 1.005 to 1.028; p=0.006).

Table 2 . Cox Hazard Regression Analysis for Overall Mortality According to Obesity Index.

Obesity indexUnivariate HR (95% CI)p-valueAdjusted HR (95% CI)*p-value
BMI0.939 (0.884–0.998)0.0430.915 (0.840–0.997)0.044
Average VAT area1.000 (0.994–1.006)0.8881.003 (0.995–1.011)0.506
Average SAT area0.999 (0.996–1.002)0.4051.002 (0.997–1.007)0.453
VAT to TAT ratio1.020 (1.001–1.039)0.0431.022 (0.997–1.049)0.091
VAT to SAT ratio1.008 (1.001–1.016)0.0271.009 (1.000–1.019)0.058

HR, hazard ratio; CI, confidence interval; BMI, body mass index; VAT, visceral adipose tissue; SAT, subcutaneous adipose tissue; TAT, total adipose tissue..

*Adjusted for age at diagnosis, sex, familial history of colorectal cancer..



Table 3 . Cox Hazard Regression Analysis for Colorectal Cancer-Specific Mortality According to Obesity Index.

Obesity indexUnivariate HR (95% CI)p-valueAdjusted HR (95% CI)*p-value
BMI0.980 (0.907–1.059)0.6131.006 (0.904–1.120)0.908
Average VAT1.001 (0.993–1.008)0.8951.004 (0.993–1.014)0.493
Average SAT0.997 (0.993–1.001)0.1970.996 (0.990–1.003)0.278
VAT to TAT ratio1.031 (1.006–1.056)0.0141.041 (1.008–1.075)0.015
VAT to SAT ratio1.013 (1.004–1.022)0.0051.016 (1.005–1.028)0.006

HR, hazard ratio; CI, confidence interval; BMI, body mass index; VAT, visceral adipose tissue; SAT, subcutaneous adipose tissue; TAT, total adipose tissue..

*Adjusted for age at diagnosis, sex, familial history of colorectal cancer..



Additionally, according to the VT ratios of each intervertebral level, overall survival, cancer-specific survival, and recurrence-free survival were analyzed. There were no significant results regarding the overall survival and recurrence-free survival (Supplementary Tables 1 and 2). However, all three VT ratios (at L3–L4, L4–L5, and L5–S1) showed significant results, as higher VT ratios were associated with higher cancer-specific mortality, in analyses both unadjusted and adjusted for clinically relevant factors (Supplementary Table 3).

3. Fat distribution and recurrence

Recurrence-free survival analysis was also performed according to obesity index (Table 4); however, there were no statistically significant results. BMI (HR, 0.978; 95% CI, 0.898 to 1.065; p=0.612), VAT (HR, 0.995; 95% CI, 0.986 to 1.003; p=0.234), and VT ratio (HR, 0.989; 95% CI, 0.963 to 1.015; p=0.387) were not associated with recurrence after treatment of stage III CRC. We performed additional analyses concerning the location of tumor recurrence. First, we investigated the relationship between fatty liver and liver recurrence; however, no significant association was found between these two factors (Supplementary Fig. 2). Liver and lung metastases according to obesity index were also evaluated separately; however, the analysis showed no significant results (Supplementary Tables 4 and 5). Analysis regarding peritoneal seeding recurrence provided interesting results (Table 5). In the multivariate analysis for peritoneal seeding recurrence according to obesity index and after adjusting for clinically relevant factors, BMI, VT ratio, and VS ratio showed statistically significant results. Higher VT (HR, 1.069; 95% CI, 1.010 to 1.131; p=0.020) and VS ratio (HR, 1.024; 95% CI, 1.003 to 1.045; p=0.023) were both associated with a higher risk of peritoneal seeding recurrence, but higher BMI (HR, 0.877; 95% CI, 0.774 to 0.994; p=0.040) was associated with a lower risk of peritoneal seeding recurrence. When VT ratio was divided into two groups by the highest and lowest 25 percentile number, VT ratio of the highest 25 percentile group had a 5-time higher risk of peritoneal recurrence than the lowest 25 percentile group (HR, 5.587; 95% CI, 1.048 to 29.789; p=0.044). However, results regarding VS ratio showed an irrelevant outcome (HR, 2.206; 95% CI, 0.616 to 7.895; p=0.224).

Table 4 . Cox Hazard Regression Analysis for Recurrence According to Obesity Index.

Obesity indexUnivariate HR (95% CI)p-valueAdjusted HR (95% CI)*p-value
BMI0.971 (0.915–1.031)0.3420.978 (0.898–1.065)0.612
Average VAT0.996 (0.990–1.003)0.2490.995 (0.986–1.003)0.234
Average SAT0.999 (0.996–1.002)0.3721.002 (0.997–1.007)0.541
VAT to TAT ratio1.000 (0.981–1.019)0.9780.989 (0.963–1.015)0.387
VAT to SAT ratio1.000 (0.992–1.008)0.9760.996 (0.986–1.006)0.446

HR, hazard ratio; CI, confidence interval; BMI, body mass index; VAT, visceral adipose tissue; SAT, subcutaneous adipose tissue; TAT, total adipose tissue..

*Adjusted for age at diagnosis, sex, familial history of colorectal cancer..



Table 5 . Cox Hazard Regression Analysis for Peritoneal Seeding According to Obesity Index.

Obesity indexUnivariate HR (95% CI)p-valueAdjusted HR (95% CI)*p-value
BMI0.884 (0.780–1.002)0.0540.877 (0.774–0.994)0.040
Average VAT1.003 (0.990–1.016)0.6711.007 (0.991–1.021)0.369
Average SAT0.999 (0.992–1.006)0.7970.997 (0.990–1.004)0.393
VAT to TAT ratio1.017 (0.977–1.059)0.4131.069 (1.010–1.131)0.020
VAT to TAT ratio (top vs bottom 25th percentile)
≤24.53%1.0001.000
>38.85%1.657 (0.479–5.729)0.4255.587 (1.048–29.789)0.044
VAT to SAT ratio1.007 (0.991–1.024)0.3731.024 (1.003–1.045)0.023
VAT to SAT ratio (top vs bottom 25th percentile)
≤32.50%1.0001.000
>63.53%1.900 (0.564–6.395)0.3002.206 (0.616–7.895)0.224

HR, hazard ratio; CI, confidence interval; BMI, body mass index; VAT, visceral adipose tissue; SAT, subcutaneous adipose tissue; TAT, total adipose tissue..

*Adjusted for age at diagnosis, sex, familial history of colorectal cancer..



Since the VAT and SAT areas used in survival and recurrence analyses were the average values of three intervertebral levels, another subgroup analysis, comparing peritoneal recurrence risk of these three intervertebral levels, was performed. Peritoneal seeding recurrence rate according to VT ratio of each spine level in stage III CRC patients was best explained when applying the area of adipose tissue from the L3 to L4 intervertebral level (Fig. 1A). When VT ratio of the L3–L4 level was divided into two groups by 50 percentile number, VT ratio of higher than 50 percentile had almost a 5-time higher risk of peritoneal recurrence than the lower than 50 percentile group (HR, 4.969; 95% CI, 1.303 to 18.949; p=0.019). However, VT ratio of higher than 50 percentile at the L4–L5 level (HR, 0.514; 95% CI, 0.091 to 2.892; p=0.450) or L5–S1 level (HR, 2.617; 95% CI, 0.413 to 16.57; p=0.307) was not associated with a higher risk of peritoneal recurrence (Fig. 1B and C).

Figure 1. Peritoneal seeding rate according to the visceral adipose tissue to total adipose tissue area ratio at each level of the lumbar spine in stage III colorectal cancer patients. (A) Visceral to total adipose tissue (VT) ratio at the L3–L4 level, (B) VT ratio at the L4–L5 level, (C) VT ratio at the L5–S1 level.

DISCUSSION

Obesity is known to be a risk factor for the development of several cancers, including CRC. However, the influence of VAT distribution on the outcomes of patients with CRC remains controversial. The objective of this study was to examine the outcome of CRC patients according to obesity indices including BMI, VAT area, SAT area, and their corresponding ratios.

Compared to SAT, VAT is known to be more biologically active and therefore related to obesity-related diseases including cancer.7,15,23 Most of VAT is distributed within the omentum, mesentery, and retroperitoneum.24 Then, we considered CT scan as a better method for measurement of fat because CT scan is mandatory examination before treatment of all newly diagnosed CRC. We focused on VAT distribution and its relative ratio to total adipose tissue or SAT distribution.

The most interesting finding in our study was that a higher VT ratio and a higher VS ratio were both associated with a higher risk of peritoneal seeding recurrence. To our knowledge, this is the first study to find a relationship between peritoneal seeding recurrence and visceral fat. Several studies have provided evidence of the significant contribution of VO to cancer development and aimed to understand the role of omental fat in intraperitoneal tumorigenesis. Using coculture system to simulate the crosstalk between adipocytes and cancer cells, Xiang et al.25 showed that omental adipocytes induced a significant increase of lipid uptake in gastric cancer cells, and enhanced their invasiveness. Similarly, another study using coculture of adipocyte and ovarian cancer cells demonstrated the direct transfer of lipids from adipocytes to cancer cells and an increase of tumor growth.26 In addition to the adipocytes, stimulation of peritoneal tumors is also associated with omental adipose tissue-derived stem cells (ASCs). Nowicka et al.27 reported that ASCs significantly promoted proliferation, migration, and resistance to chemotherapy and radiation in ovarian cancer cell lines by providing cancer cells with lactose and ATP generated in the glycolytic pathway. Another series of experiments using ASCs isolated from mice showed that cells isolated from the visceral fat of obese animals were able to increase the development of intraperitoneal tumors, whereas cells obtained from SAT lacked this activity.28

Along with these reports, the traditional “insulin hypothesis” has also been used to explain the relationship between obesity or visceral adiposity and CRC.11,29 Prospective studies have shown an increased risk of CRC in individuals with higher levels of postprandial insulin,30 C-peptide,31 and fasting glucose.30 However, Renehan et al.32 showed that not only the insulin/insulin-like growth factor molecular pathway, but also metabolic syndrome, aging, endogenous sex hormones, adiponectin, and leptin are all very complexly connected with inter-related regulation. Therefore, the insulin hypothesis, sex hormones and adiponectin, adipocyte-promoted lipid internalization of cancer cells, and ASCs affect and regulate each other in the process of peritoneal metastasis.

However, our assessment regarding peritoneal seeding recurrence and overall survival has shown that higher BMI was related to a lower risk of peritoneal seeding recurrence and overall mortality. In a recent review article regarding BMI, obesity, and their association with cardiovascular diseases, the authors claimed that BMI does not explain fat distribution or degree of VO.33 The metabolically healthy obese phenotype refers to a subgroup of obese individuals in which high BMI is associated with a healthy metabolic profile, characterized by high insulin sensitivity, favorable lipid profile, low VAT, and high lean mass. The “metabolically health” with healthy obese phenotype was not considered in our study, but this might have affected the results of our study, showing a low risk of peritoneal seeding and overall mortality in patients with higher BMI.

Our study has some limitations. First, given the retrospective nature of this study, the results require cautious interpretation. In addition, there is currently no established threshold of VAT area or VS ratio for defining VO. However, our findings might provide additional supportive evidence in this research area. Further, although our study includes a very heterogeneous patient population, it also includes a large number of subjects with stage III CRC, which improves the reliability of the results. Finally, the results of this study should be confirmed among the general population because patients of this study were from a tertiary medical institute.

In conclusion, VO is closely related to the increased risk of CRC-specific mortality and, most intriguingly, to higher risk of peritoneal seeding metastasis in patients with stage III CRC. These findings could be useful in strategy making process of diet and physical care for the patient group in actual clinical field. Further studies are needed to clarify the physiologic and biologic mechanisms mediating the link between visceral adiposity and CRC metastasis. The assimilation of quantitative measures of VO and corresponding clinical studies is needed to integrate these results with therapeutic and epidemiologic studies.

SUPPLEMENTARY MATERIALS

Supplementary materials can be accessed at https://doi.org/10.5009/gnl20266.

gnl-16-1-53-supple.pdf

ACKNOWLEDGEMENTS

This research was supported by a grant from the National R&D Program for Cancer Control, Ministry of Health and Welfare, Republic of Korea (grant number: 1631020).

This abstract was presented in a poster session at Asian Pacific Digestive Week 2018 (APDW 2018), on November 15-18, 2018, in Seoul, Korea.

CONFLICTS OF INTEREST

S.J.P. and J.H.C. are editorial board members of the journal but were not involved in the peer reviewer selection, evaluation, or decision process of this article. No other potential conflicts of interest relevant to this article were reported.

AUTHOR CONTRIBUTIONS

Study concept and design: T.I.K. Data acquisition: J.W.P., S.Y.C., S.J.P., J.J.P., J.H.C., J.S.L., W.H.K. Data analysis and interpretation: J.W.P., S.Y.C., J.S.L., T.I.K. Statistical analysis: J.W.P., S.Y.C. Drafting of the manuscript: J.W.P., S.Y.C. Critical revision of the manuscript: S.J.P., J.J.P., J.H.C., W.H.K., T.I.K.

Fig 1.

Figure 1.Peritoneal seeding rate according to the visceral adipose tissue to total adipose tissue area ratio at each level of the lumbar spine in stage III colorectal cancer patients. (A) Visceral to total adipose tissue (VT) ratio at the L3–L4 level, (B) VT ratio at the L4–L5 level, (C) VT ratio at the L5–S1 level.
Gut and Liver 2022; 16: 53-61https://doi.org/10.5009/gnl20266

Table 1 Patient Demographics and Baseline Clinical Characteristics (n=472)

VariableTotal (n=472)Non-overweight
(BMI <25 kg/m2) (n=318)
Overweight
(BMI ≥25 kg/m2) (n=154)
p-value
Age, yr59 (26–86)59 (26–86)58 (29–80)0.355
Male sex272 (57.6)177 (55.7)95 (61.7)0.214
Smoking status0.836
Current smoker285 (60.4)191 (60.1)94 (61.0)
Former smoker91 (19.3)60 (18.9)31 (20.1)
Never smoker96 (20.3)67 (21.1)29 (18.8)
Daily drinker39 (8.3)28 (8.8)11 (7.1)0.539
Family history of colorectal cancer35 (7.4)23 (7.2)12 (7.8)0.828
Chronic disease and medication
Hypertension159 (33.7)103 (32.4)56 (36.4)0.392
Diabetes mellitus81 (17.2)56 (17.6)25 (16.2)0.710
Regular use of metformin44 (9.3)32 (10.1)12 (7.8)0.426
Regular use of low-dose aspirin94 (19.9)58 (18.2)36 (23.4)0.190
Fatty liver45 (9.5)20 (6.3)25 (16.2)0.001
Cancer location0.545
Colon285 (60.4)189 (59.4)96 (62.3)
Rectum187 (39.6)129 (40.6)56 (37.7)
T-stage0.090
Tis2 (0.4)02 (1.3)
T119 (4.0)11 (3.5)8 (5.2)
T246 (9.7)28 (8.8)18 (11.7)
T3346 (73.3)234 (73.5)112 (72.7)
T459 (12.5)45 (14.2)14 (9.1)
N-stage0.796
N01 (0.2)1 (0.3)0
N1a177 (37.5)123 (38.7)54 (35.1)
N1b150 (31.8)96 (30.2)54 (35.1)
N1c000
N2a92 (19.5)63 (19.8)29 (18.8)
N2b52 (11.0)35 (11.0)17 (11.0)
Histologic type0.497
Well differentiated45 (9.5)27 (8.5)18 (11.7)
Moderately differentiated388 (82.2)265 (83.3)123 (79.9)
Poorly/undifferentiated22 (4.7)14 (4.4)8 (5.2)
Unknown17 (3.6)12 (3.8)5 (3.2)
Treatment
Neoadjuvant CCRT32 (6.8)23 (7.2)9 (5.8)0.574
Adjuvant CTx460 (97.5)309 (97.2)151 (98.1)0.568
Adjuvant CCRT95 (20.1)63 (19.8)32 (20.8)0.806
Postoperative RT1 (0.2)01 (0.7)0.150
Measures of obesity*
VAT area, cm266.20±30.5757.62±26.5383.89±30.85<0.001
SAT area, cm2142.46±63.92125.25±55.18178.01±66.22<0.001
VAT to TAT ratio32.46±9.8132.32±9.8932.76±9.650.634
VAT to SAT ratio51.42±23.6051.13±23.5652.04±23.740.696

Data are presented as median (range), number (%), or mean±SD.

BMI, body mass index; CCRT, chemoradiation; CTx, chemotherapy; RT, radiation therapy; VAT, visceral adipose tissue; SAT, subcutaneous adipose tissue; TAT, total adipose tissue.

*VAT area and SAT area: the average value for area at each of the three vertebral levels: L3–L4, L4–L5, and L5–S1.


Table 2 Cox Hazard Regression Analysis for Overall Mortality According to Obesity Index

Obesity indexUnivariate HR (95% CI)p-valueAdjusted HR (95% CI)*p-value
BMI0.939 (0.884–0.998)0.0430.915 (0.840–0.997)0.044
Average VAT area1.000 (0.994–1.006)0.8881.003 (0.995–1.011)0.506
Average SAT area0.999 (0.996–1.002)0.4051.002 (0.997–1.007)0.453
VAT to TAT ratio1.020 (1.001–1.039)0.0431.022 (0.997–1.049)0.091
VAT to SAT ratio1.008 (1.001–1.016)0.0271.009 (1.000–1.019)0.058

HR, hazard ratio; CI, confidence interval; BMI, body mass index; VAT, visceral adipose tissue; SAT, subcutaneous adipose tissue; TAT, total adipose tissue.

*Adjusted for age at diagnosis, sex, familial history of colorectal cancer.


Table 3 Cox Hazard Regression Analysis for Colorectal Cancer-Specific Mortality According to Obesity Index

Obesity indexUnivariate HR (95% CI)p-valueAdjusted HR (95% CI)*p-value
BMI0.980 (0.907–1.059)0.6131.006 (0.904–1.120)0.908
Average VAT1.001 (0.993–1.008)0.8951.004 (0.993–1.014)0.493
Average SAT0.997 (0.993–1.001)0.1970.996 (0.990–1.003)0.278
VAT to TAT ratio1.031 (1.006–1.056)0.0141.041 (1.008–1.075)0.015
VAT to SAT ratio1.013 (1.004–1.022)0.0051.016 (1.005–1.028)0.006

HR, hazard ratio; CI, confidence interval; BMI, body mass index; VAT, visceral adipose tissue; SAT, subcutaneous adipose tissue; TAT, total adipose tissue.

*Adjusted for age at diagnosis, sex, familial history of colorectal cancer.


Table 4 Cox Hazard Regression Analysis for Recurrence According to Obesity Index

Obesity indexUnivariate HR (95% CI)p-valueAdjusted HR (95% CI)*p-value
BMI0.971 (0.915–1.031)0.3420.978 (0.898–1.065)0.612
Average VAT0.996 (0.990–1.003)0.2490.995 (0.986–1.003)0.234
Average SAT0.999 (0.996–1.002)0.3721.002 (0.997–1.007)0.541
VAT to TAT ratio1.000 (0.981–1.019)0.9780.989 (0.963–1.015)0.387
VAT to SAT ratio1.000 (0.992–1.008)0.9760.996 (0.986–1.006)0.446

HR, hazard ratio; CI, confidence interval; BMI, body mass index; VAT, visceral adipose tissue; SAT, subcutaneous adipose tissue; TAT, total adipose tissue.

*Adjusted for age at diagnosis, sex, familial history of colorectal cancer.


Table 5 Cox Hazard Regression Analysis for Peritoneal Seeding According to Obesity Index

Obesity indexUnivariate HR (95% CI)p-valueAdjusted HR (95% CI)*p-value
BMI0.884 (0.780–1.002)0.0540.877 (0.774–0.994)0.040
Average VAT1.003 (0.990–1.016)0.6711.007 (0.991–1.021)0.369
Average SAT0.999 (0.992–1.006)0.7970.997 (0.990–1.004)0.393
VAT to TAT ratio1.017 (0.977–1.059)0.4131.069 (1.010–1.131)0.020
VAT to TAT ratio (top vs bottom 25th percentile)
≤24.53%1.0001.000
>38.85%1.657 (0.479–5.729)0.4255.587 (1.048–29.789)0.044
VAT to SAT ratio1.007 (0.991–1.024)0.3731.024 (1.003–1.045)0.023
VAT to SAT ratio (top vs bottom 25th percentile)
≤32.50%1.0001.000
>63.53%1.900 (0.564–6.395)0.3002.206 (0.616–7.895)0.224

HR, hazard ratio; CI, confidence interval; BMI, body mass index; VAT, visceral adipose tissue; SAT, subcutaneous adipose tissue; TAT, total adipose tissue.

*Adjusted for age at diagnosis, sex, familial history of colorectal cancer.


References

  1. Renehan AG, Soerjomataram I, Tyson M, et al. Incident cancer burden attributable to excess body mass index in 30 European countries. Int J Cancer 2010;126:692-702.
    Pubmed CrossRef
  2. Bardou M, Barkun AN, Martel M. Obesity and colorectal cancer. Gut 2013;62:933-947.
    Pubmed CrossRef
  3. Gribovskaja-Rupp I, Kosinski L, Ludwig KA. Obesity and colorectal cancer. Clin Colon Rectal Surg 2011;24:229-243.
    Pubmed KoreaMed CrossRef
  4. Vucenik I, Stains JP. Obesity and cancer risk: evidence, mechanisms, and recommendations. Ann N Y Acad Sci 2012;1271:37-43.
    Pubmed KoreaMed CrossRef
  5. Otake S, Takeda H, Suzuki Y, et al. Association of visceral fat accumulation and plasma adiponectin with colorectal adenoma: evidence for participation of insulin resistance. Clin Cancer Res 2005;11:3642-3646.
    Pubmed CrossRef
  6. Ibrahim MM. Subcutaneous and visceral adipose tissue: structural and functional differences. Obes Rev 2010;11:11-18.
    Pubmed CrossRef
  7. Després JP, Lemieux I. Abdominal obesity and metabolic syndrome. Nature 2006;444:881-887.
    Pubmed KoreaMed CrossRef
  8. Bianchini F, Kaaks R, Vainio H. Overweight, obesity, and cancer risk. Lancet Oncol 2002;3:565-574.
    Pubmed CrossRef
  9. Donohoe CL, Doyle SL, Reynolds JV. Visceral adiposity, insulin resistance and cancer risk. Diabetol Metab Syndr 2011;3:12.
    Pubmed KoreaMed CrossRef
  10. DeFronzo RA, Ferrannini E. Insulin resistance: a multifaceted syndrome responsible for NIDDM, obesity, hypertension, dyslipidemia, and atherosclerotic cardiovascular disease. Diabetes Care 1991;14:173-194.
    Pubmed CrossRef
  11. Giovannucci E. Insulin and colon cancer. Cancer Causes Control 1995;6:164-179.
    Pubmed CrossRef
  12. Otani T, Iwasaki M, Sasazuki S, Inoue M, Tsugane S; Japan Public Health Center-based Prospective Study Group. Plasma C-peptide, insulin-like growth factor-I, insulin-like growth factor binding proteins and risk of colorectal cancer in a nested case-control study: the Japan public health center-based prospective study. Int J Cancer 2007;120:2007-2012.
    Pubmed CrossRef
  13. Cecchini S, Cavazzini E, Marchesi F, Sarli L, Roncoroni L. Computed tomography volumetric fat parameters versus body mass index for predicting short-term outcomes of colon surgery. World J Surg 2011;35:415-423.
    Pubmed CrossRef
  14. Goulart A, Malheiro N, Rios H, Sousa N, Leão P. Influence of visceral fat in the outcomes of colorectal cancer. Dig Surg 2019;36:33-40.
    Pubmed CrossRef
  15. Hiuge-Shimizu A, Kishida K, Funahashi T, et al. Absolute value of visceral fat area measured on computed tomography scans and obesity-related cardiovascular risk factors in large-scale Japanese general population (the VACATION-J study). Ann Med 2012;44:82-92.
    Pubmed CrossRef
  16. Tsujinaka S, Konishi F, Kawamura YJ, et al. Visceral obesity predicts surgical outcomes after laparoscopic colectomy for sigmoid colon cancer. Dis Colon Rectum 2008;51:1757-1765.
    Pubmed CrossRef
  17. Rickles AS, Iannuzzi JC, Mironov O, et al. Visceral obesity and colorectal cancer: are we missing the boat with BMI? J Gastrointest Surg 2013;17:133-143.
    Pubmed CrossRef
  18. Clark W, Siegel EM, Chen YA, et al. Quantitative measures of visceral adiposity and body mass index in predicting rectal cancer outcomes after neoadjuvant chemoradiation. J Am Coll Surg 2013;216:1070-1081.
    Pubmed KoreaMed CrossRef
  19. Guiu B, Petit JM, Bonnetain F, et al. Visceral fat area is an independent predictive biomarker of outcome after first-line bevacizumab-based treatment in metastatic colorectal cancer. Gut 2010;59:341-347.
    Pubmed CrossRef
  20. Mahamid A, Ashkenazi I, Shapira-Rootman M, et al. Impact of increased visceral fat measured by CT on colon adenocarcinoma stage. J Gastrointest Cancer 2017;48:347-352.
    Pubmed CrossRef
  21. Park SW, Lee HL, Doo EY, et al. Visceral obesity predicts fewer lymph node metastases and better overall survival in colon cancer. J Gastrointest Surg 2015;19:1513-1521.
    Pubmed KoreaMed CrossRef
  22. WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004;363:157-163.
    Pubmed CrossRef
  23. Matsuzawa Y, Nakamura T, Shimomura I, Kotani K. Visceral fat accumulation and cardiovascular disease. Obes Res 1995;3 Suppl 5:645S-647S.
    Pubmed CrossRef
  24. Bjørndal B, Burri L, Staalesen V, Skorve J, Berge RK. Different adipose depots: their role in the development of metabolic syndrome and mitochondrial response to hypolipidemic agents. J Obes 2011;2011:490650.
    Pubmed KoreaMed CrossRef
  25. Xiang F, Wu K, Liu Y, et al. Omental adipocytes enhance the invasiveness of gastric cancer cells by oleic acid-induced activation of the PI3K-Akt signaling pathway. Int J Biochem Cell Biol 2017;84:14-21.
    Pubmed CrossRef
  26. Nieman KM, Kenny HA, Penicka CV, et al. Adipocytes promote ovarian cancer metastasis and provide energy for rapid tumor growth. Nat Med 2011;17:1498-1503.
    Pubmed KoreaMed CrossRef
  27. Nowicka A, Marini FC, Solley TN, et al. Human omental-derived adipose stem cells increase ovarian cancer proliferation, migration, and chemoresistance. PLoS One 2013;8:e81859.
    Pubmed KoreaMed CrossRef
  28. Zhang Y, Nowicka A, Solley TN, et al. Stromal cells derived from visceral and obese adipose tissue promote growth of ovarian cancers. PLoS One 2015;10:e0136361.
    Pubmed KoreaMed CrossRef
  29. McKeown-Eyssen G. Epidemiology of colorectal cancer revisited: are serum triglycerides and/or plasma glucose associated with risk? Cancer Epidemiol Biomarkers Prev 1994;3:687-695.
    Pubmed
  30. Schoen RE, Tangen CM, Kuller LH, et al. Increased blood glucose and insulin, body size, and incident colorectal cancer. J Natl Cancer Inst 1999;91:1147-1154.
    Pubmed CrossRef
  31. Kaaks R, Toniolo P, Akhmedkhanov A, et al. Serum C-peptide, insulin-like growth factor (IGF)-I, IGF-binding proteins, and colorectal cancer risk in women. J Natl Cancer Inst 2000;92:1592-1600.
    Pubmed CrossRef
  32. Renehan AG, Frystyk J, Flyvbjerg A. Obesity and cancer risk: the role of the insulin-IGF axis. Trends Endocrinol Metab 2006;17:328-336.
    Pubmed CrossRef
  33. Vecchié A, Dallegri F, Carbone F, et al. Obesity phenotypes and their paradoxical association with cardiovascular diseases. Eur J Intern Med 2018;48:6-17.
    Pubmed CrossRef
Gut and Liver

Vol.18 No.5
September, 2024

pISSN 1976-2283
eISSN 2005-1212

qrcode
qrcode

Supplementary

Share this article on :

  • line

Popular Keywords

Gut and LiverQR code Download
qr-code

Editorial Office