Body mass index and risk of colorectal carcinoma subtypes classified by tumor differentiation status

Akiko Hanyuda; Yin Cao; Tsuyoshi Hamada; Jonathan A Nowak; Zhi Rong Qian; Yohei Masugi; Annacarolina da Silva; Li Liu; Keisuke Kosumi; T Rinda Soong; Iny Jhun; Kana Wu; Xuehong Zhang; Mingyang Song; Jeffrey A Meyerhardt; Andrew T Chan; Charles S Fuchs; Edward L Giovannucci; Shuji Ogino; Reiko Nishihara

doi:10.1007/s10654-017-0254-y

. Author manuscript; available in PMC: 2018 May 16.

Published in final edited form as: Eur J Epidemiol. 2017 May 16;32(5):393–407. doi: 10.1007/s10654-017-0254-y

Body mass index and risk of colorectal carcinoma subtypes classified by tumor differentiation status

Akiko Hanyuda ¹, Yin Cao ¹, Tsuyoshi Hamada ¹, Jonathan A Nowak ¹, Zhi Rong Qian ¹, Yohei Masugi ¹, Annacarolina da Silva ¹, Li Liu ¹, Keisuke Kosumi ¹, T Rinda Soong ¹, Iny Jhun ¹, Kana Wu ¹, Xuehong Zhang ¹, Mingyang Song ¹, Jeffrey A Meyerhardt ¹, Andrew T Chan ¹, Charles S Fuchs ¹, Edward L Giovannucci ¹, Shuji Ogino ¹, Reiko Nishihara ¹

¹Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA (A.H., Y.C., L.L., M.S., E.L.G., R.N.); Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA (Y.C., M.S., A.T.C.); Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA (Y.C., M.S., A.T.C.); Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA (Y.C., M.S., A.T.C.); Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA (T.H., Z.R.Q., Y.M., A.dS., L.L., K.K., J.A.M., C.S.F., S.O.); Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA (J.A.N., T.R.S., I.J., S.O., R.N.); Department of Oncologic Pathology, Dana-Farber Cancer Institute, Boston, MA, USA (Z.R.Q., S.O., R.N.); Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA (X.Z., A.T.C., C.S.F., E.L.G.); Broad Institute of MIT and Harvard (A.T.C., R.N.); Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA (E.L.G., S.O., R.N.); Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA (R.N.); Department of Ophthalmology, Keio University School of Medicine, Tokyo, Japan (A.H.)

^✉

Co-corresponding authors: Shuji Ogino, MD, PhD, MS, Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital, 450 Brookline Ave., Room M422, Boston, MA 02215 USA, Telephone: +1-617-632-1972; Fax: +1-617-582-8558, shuji_ogino@dfci.harvard.edu

Reiko Nishihara, PhD, Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital, 450 Brookline Ave., Room M422, Boston, MA 02215 USA, Telephone: +1-617-432-1838; Fax: +1-617-432-2435, rnishiha@hsph.harvard.edu

A.H., Y.C., T.H., and J.A.N. contributed equally as co-first authors. C.S.F., E.L.G., S.O., and R.N. contributed equally as co-last authors.

PMCID: PMC5507723 NIHMSID: NIHMS873354 PMID: 28510098

Abstract

Background

Previous studies suggest that abnormal energy balance status may dysregulate intestinal epithelial homeostasis and promote colorectal carcinogenesis, yet little is known about how host energy balance and obesity influence enterocyte differentiation during carcinogenesis. We hypothesized that the association between high body mass index (BMI) and colorectal carcinoma incidence might differ according to tumor histopathologic differentiation status.

Methods

Using databases of the Nurses' Health Study and Health Professionals Follow-up Study, and duplication-method Cox proportional hazards models, we prospectively examined an association between BMI and the incidence of colorectal carcinoma subtypes classified by differentiation features.

Results

120,813 participants were followed for 26 or 32 years and 1,528 rectal and colon cancer cases with available tumor pathological data were documented. The association between BMI and colorectal cancer risk significantly differed depending on the presence or absence of poorly-differentiated foci (P_{heterogeneity}=0.006). Higher BMI was associated with a higher risk of colorectal carcinoma without poorly-differentiated foci (≥30.0kg/m² vs. 18.5-22.4kg/m²: multivariable-adjusted hazard ratio, 1.87; 95% confidence interval, 1.49-2.34; P_trend<0.001), but not with risk of carcinoma with poorly-differentiated foci (P_trend=0.56). This differential association appeared to be consistent in strata of tumor microsatellite instability (MSI) or FASN expression status, although the statistical power was limited. The association between BMI and colorectal carcinoma risk did not significantly differ by overall tumor differentiation, mucinous differentiation, or signet ring cell component (P_{heterogeneity}>0.03, with the adjusted α of 0.01).

Conclusions

High BMI was associated with risk of colorectal cancer subtype containing no poorly-differentiated focus. Our findings suggest that carcinogenic influence of excess energy balance might be stronger for tumors that retain better intestinal differentiation throughout the tumor areas.

Keywords: epigenetics, glandular epithelium, metabolism, molecular pathological epidemiology, overweight, stem cell

Introduction

Obesity represents a growing global concern in public health.[1–4] Although epidemiologic studies have shown an association between obesity or high body mass index (BMI) with increased colorectal cancer incidence[5,6] and mortality,[7,8] the underlying pathogenic mechanisms remain unclear.

Accumulating evidence suggests that excess energy balance may not only influence enterocyte differentiation but also contribute to colorectal carcinogenesis.[9–15] Experimental studies suggest that excess fat intake may increase both the number of intestinal stem cells, which may serve as the cell-of-origin for the development of cancer, and the proliferation rate of these intestinal stem cells.[14,16] Excess fat intake may also enhance the ability of more differentiated enterocytes (“transit-amplifying cells”), which are derived from intestinal stem cells, to initiate tumor development.[14,15] This effect appears to be mediated by PPARD activation in colorectal epithelial cells.[14,16] This activation may induce colonic inflammation and inflammation-associated tumorigenesis,[16] although the underlying mechanism of tumorigenesis has not been fully elucidated. Colorectal carcinoma is a tumor type with highly heterogeneous histopathological and molecular characteristics,[17–19] and previous studies suggest that excess energy balance likely affects enterocyte differentiation.[9–15] Thus, comprehensive analyses that take tumor histopathological variation into account are critical to elucidate the pathogenic influence of obesity on colorectal cancer development.

Poorly-differentiated colorectal carcinoma, characterized by 50% or greater poorly-differentiated areas, has been associated with distinct morphological and molecular characteristics including high level microsatellite instability (MSI), FASN overexpression, and the presence of mucinous or signet ring cell components.[20–22] MSI-high colorectal cancer has a deficient DNA mismatch repair system[23] and has been associated with poorly-differentiated tumors,[21] although the underlying mechanism remains unclear. FASN, a key enzyme involved in de novo lipogenesis, is commonly overexpressed in human tumors,[24,25] including colorectal carcinoma.[20,26] FASN overexpression has been associated with an increased risk of metastatic disease and worse prognosis.[27] Notably, studies using recently developed FASN inhibitors provide evidence that FASN downregulation can cause cell apoptosis and may suppress tumor proliferation in certain cancer types.[28,29]

Consistent with this accumulating evidence for the tumor-promoting effects of obesity, several studies have shown an association between higher BMI and the incidence of colorectal carcinoma, especially those with microsatellite stable (MSS) subtype (but not MSI-high subtype).[30–32] Nonetheless, other studies do not support this differential association.[33–35] Our previous study has shown an association between BMI and the incidence of colorectal carcinoma without FASN overexpression (but not FASN-overexpressed carcinoma).[36] Although there may be a relationship between BMI and the incidence of specific histopathological subtypes of colorectal carcinoma, no study has investigated the influence of excess energy balance on the risk of colorectal cancer according to tumor morphological features. Given the possible association between obesity and MSS colorectal carcinoma,[30–32] or FASN-negative carcinoma,[36] which are rarely associated with poorly-differentiated tumors,[20,21] we hypothesized that higher BMI might be associated with a greater incidence of well-differentiated colorectal carcinoma or colorectal carcinoma with no poorly-differentiated foci.

A prospective study was conducted using a molecular pathological epidemiology[37–40] database based on two U.S.-nationwide prospective cohort studies. In secondary analyses, we assessed the hypothesis in strata of relevant molecular phenotypes of colorectal cancer, including MSI and FASN expression status.

Methods

Study population

We utilized two large prospective cohort studies in U.S.; the Nurses' Health Study (NHS, 121,700 female nurses aged 30-55 were enrolled in 1976) and the Health Professionals Follow-up Study (HPFS, 51,529 male health professionals aged 40-75 were enrolled in 1986).[41,42] The cohorts have mailed questionnaires at enrollment and every two years thereafter to collect data on demographics, lifestyle factors, medical history, and disease outcomes. Information on dietary intake was collected every four years. Written informed consent was obtained from all individuals. The institutional review boards at the Harvard T.H. Chan School of Public Health and Partners' Healthcare approved this study. We excluded participants who had a history of cancer (except for non-melanoma skin cancer) or inflammatory bowel disease, or those with incomplete data on weight or height at baseline. We also excluded participants with a baseline BMI less than 18.5 kg/m² since these individuals might be underweight due to their preclinical disease or unhealthy condition. Participants were followed from the month of the baseline questionnaire return to the month of colorectal cancer diagnosis, death, or censoring date (June 1, 2010 for the NHS and January 31, 2010 for the HPFS), whichever came first. We treated colorectal carcinoma cases without tumor tissue data as censored cases at the month of the diagnosis.

Assessment of weight and height

To calculate average of BMI from study baseline to the time period of risk, we used height information reported at enrollment (1976 for the NHS and 1986 for the HPFS) and the average weight information up to time period at risk, using weight information collected every two years. In both cohorts, the validity and the reproducibility of the self-reported weight information was reasonable as previously described.[43] Participants were followed by trained technicians twice during the study, approximately 6 months apart to incorporate seasonal variability, and measured current their weight. Pearson correlation coefficient between self-reported weight and the average of the two weights measured by the technicians was 0.97 for both women and men.[43] Based on the World Health Organization (WHO) classification, we categorized BMI (kg/m²) into 5 categories: 18.5-22.4, 22.5-24.9, 25.0-27.4, 27.5-29.9, ≥30.0 kg/m².[44] To capture the change of BMI in each individual during the follow-up period, we have performed a Pearson correlation between the baseline BMI and the BMI of each biennial questionnaire cycle in each cohort. The Pearson correlation coefficients for BMI one decade apart was about 0.85, and for two decades apart, it was about 0.75, suggesting that the participants' weights were fairly constant over time (data were not shown).

Assessment of colorectal cancer cases

We requested written permission to obtain medical records and pathology reports when participants reported colorectal cancer on biennial questionnaires. Unreported fatal colorectal cases were identified through the National Death Index and next-of-kin. Medical and pathological records were reviewed by study physicians, who were blinded to exposure information, to collect data on colorectal cancer including tumor anatomic location, and disease stage.

Tumor histopathological, immunohistochemical, and molecular evaluation

We collected formalin-fixed paraffin-embedded (FFPE) archival tissue specimens of colorectal carcinoma resections from hospitals and laboratories. Hematoxylin and eosin-stained tissue sections from all colorectal carcinoma cases in this study were evaluated under a light microscope by a single pathologist (S.O.) who was unaware of other data. Overall tumor differentiation was categorized as well/moderate vs. poor (≥50% vs. <50% glandular area, respectively) according to the WHO classification system.[45] A poorly-differentiated focus was defined as an area with (1) solid tumor cell nest without glandular differentiation, or (2) any number of signet ring cells. The extent of each feature of poorly-differentiated foci, mucinous component, and signet ring cell component was scaled as 0% to 100%. For FASN immunohistochemistry assay, mouse monoclonal antihuman FASN antibody (clone 23, BD Biosciences, Mississauga, ON, Canada) (dilution 1:100) was used as primary antibody, following with Multilink secondary antibody (BioGenex) and streptavidin horseradish peroixidase (BioGenex), as described previously.[36] Tumor expression levels were compared with normal colonic mucosa as an internal negative control, and adipose tissue as an internal positive control. In addition, we included a negative control reaction omitting the primary antibody. Tumor FASN expression levels were categorized as negative vs. positive (no or weak expression vs. moderate or strong expression, respectively) as previously described.[36] DNA was extracted from archival tumor tissue. MSI analysis was performed utilizing 10 microsatellite markers (D2S123, D5S346, D17S250, BAT25, BAT26, BAT40, D18S55, D18S56, D18S67, and D18S487) and polymerase chain reaction as previously described.[46] We defined MSI-high as the presence of instability in ≥30% of these markers, and MSI-low/MSS otherwise.

Statistical analysis

We utilized a duplication-method Cox proportional cause-specific hazards regression model to examine whether the association of BMI with risk of colorectal carcinoma cases by tumor subgroups based on histopathologic features (poorly-differentiated foci, overall tumor differentiation, mucinous differentiation, or signet ring cell component).[47] To analyze the association specific to one tumor subtype, we have treated other subgroups as competing events, and tumors of unknown subgroup (such as those without histopathological data) were censored as previously described.[48] Age-adjusted and multivariable-adjusted hazard ratio (HR) was computed. In multivariable models, we adjusted for the following potential confounders: family history of colorectal cancer in any first-degree relative (yes vs. no), history of colonoscopy or sigmoidoscopy (yes vs. no), smoking status (never, <5, 5-19, 20-39, ≥40 cumulative pack-years), physical activity (quintiles of metabolic equivalent task score [METS]-hours per week), red and processed meat intake (quintiles of servings per day), alcohol consumption (0, 1-4,5-14, 15-29, ≥30 gram per day), current multivitamin use (yes vs. no), regular use of aspirin (yes vs. no), regular use of non-steroidal anti-inflammatory drugs (NSAIDs, yes vs. no), total energy intake (quintiles of kcal per day), folate intake (quintiles of μg per day), calcium intake (quintiles of mg per day), Alternate Healthy Eating Index (AHEI)-2010 (quintiles of the overall AHEI-2010 score without alcohol intake) and (for women participants) menopause/postmenopausal hormone-replacement therapy use status (premenopausal, postmenopausal never hormone use, postmenopausal past hormone use, or postmenopausal current hormone use). We used the most recent available information for all covariates prior to each biennial questionnaire cycle. The cumulative average of each relevant variable, which was the mean of all available data up to each biennial follow-up cycle, was used to decrease within-individual variation and to optimally estimate long-term influence. For missing variables, we used the most recent available information from the past questionnaires. We treated all variables as time-varying to take into account potential changes over follow-up time. Trend tests across categories of BMI were performed by using the median value for each category as a continuous variable in the regression model. We initially performed the analyses in each cohort separately and did not detect substantial heterogeneity between cohorts (P_{heterogeneity}>0.05 for Cochran's Q test); thus, we conducted a pooled analysis using the sex-stratified Cox regression model to maximize statistical power.

As our primary hypothesis testing, we examined the heterogeneity in the association between BMI and the colorectal cancer incidence according to tumor histologic subtypes using a likelihood ratio test with one degree of freedom (represented as P_{heterogeneity}).[47,49] We evaluated four morphological features (overall tumor differentiation, the presence of poorly-differentiated foci, or mucinous component, and signet ring cells) and therefore, adjusted the statistical significance level to 0.01 (≈0.05/4) based on Bonferroni correction for multiple hypothesis testing. All other assessments were secondary analyses. For secondary analyses, we interpreted the results cautiously in addition to use of the adjusted α level of 0.01. For example, as secondary analyses, we stratified cases by MSI or FASN status and examined the association between BMI and colorectal carcinoma risk according to histological subtypes after stratification by MSI or FASN status. All analyses were performed using SAS software (Version 9.3, SAS Institute, Cary, NC, USA) and all P values were two-sided.

Results

Among 120,813 participants (75,812 women and 45,001 men) during the 32 or 26 years of follow-up (3,346,671 person-years), we documented 1,528 incident colorectal carcinoma cases with and 1,446 cases without available FFPE tumor tissue and histopathologic records. Demographic characteristics and clinical features were similar between patients with and without tissue data, except that stage IV cancers were relatively under-represented in those with tissue data (Table S1). In both cohorts, individuals with higher BMI were more likely to have a history of diabetes, regularly use of NSAIDs or aspirin, consume more alcohol and red and processed meat, exercise less, and take more multivitamins, calcium, and folate (Table 1). Postmenopausal women with lower BMI tended to use menopausal hormone therapy, compared with those with higher BMI. The interrelationship between the subtypes based on each of the four morphological features (overall tumor differentiation, the presence of poorly-differentiated foci, or mucinous component, and signet ring cells) were shown in Table S2. In agreement with our previous study,[20] colorectal carcinoma with poor differentiation or those with the presence of poorly-differentiated focus were associated with tumors with high abundance of mucinous or signet ring cell components (Table S2).

Table 1. Age-standardized characteristics of the Nurses' Health Study (NHS) (1980-2010) and the Health Professionals Follow-up Study(HPFS) (1986-2010) participants according to body mass index (person-years)^*.

Characteristics	Women (NHS)					Men (HPFS)

	Body mass index (kg/m²)

	18.5-22.4	22.5-24.9	25.0-27.4	27.5-29.9	≥30	18.5-22.4	22.5-24.9	25.0-27.4	27.5-29.9	≥30
Participants, person-years	352576	323576	228396	135304	173152	59433	161809	154675	73416	45684
Age, year^†	57.6 (11.3)	60.0 (10.8)	61.3 (10.6)	62.1 (10.4)	61.2 (10.2)	63.7 (12.1)	63.4 (11.4)	63.5 (10.9)	63.4 (10.3)	63.0 (9.9)
Family history of colorectal cancer, %	12.5	12.9	13.1	13.2	13.4	12.1	12.0	12.3	12.2	12.5
History of diabetes, %	2.2	3.4	6.5	10.6	20.4	3.9	4.8	6.6	9.9	18.0
Body mass index, kg/m²	21.0 (1.0)	23.7 (0.7)	26.2 (0.7)	28.7 (0.7)	34.0 (3.8)	21.5 (0.9)	23.8 (0.7)	26.1 (0.7)	28.5 (0.7)	32.9 (4.0)
Postmenopause, %	73.7	77.1	78.6	79.5	78.6	-	-	-	-	-
Current hormone therapy use, %	32.1	30.2	27.1	24.9	20.3	-	-	-	-	-
History of colonoscopy/sigmoidoscopy, %	36.7	38.0	37.6	38.0	36.9	51.7	52.5	51.5	51.2	51.2
Current use of multivitamin, %	52.7	51.2	50.4	49.4	47.6	50.8	48.3	45.4	43.2	42.0
Regular use of nonsteroidal anti-inflammatory drugs(NSAIDs), %	14.3	17.0	18.4	19.9	21.5	11.3	13.7	15.3	17.5	19.3
Regular use of aspirin, %	32.2	33.5	35.3	36.2	37.8	41.2	45.6	47.6	49.1	49.7
Pack-years among ever smokers	23.8 (20.5)	23.7 (20.1)	24.2 (20.2)	24.0 (20.1)	23.4 (20.5)	23.6 (19.9)	23.1 (18.7)	24.9 (18.8)	26.7 (19.6)	28.1 (20.2)
Ever smokers, %	58.1	56.7	55.4	53.9	51.9	50.1	54.8	59.1	60.1	61.6
Total calorie, kcal/day	1665 (442)	1662 (435)	1667 (441)	1682 (447)	1716 (460)	2002 (544)	1967 (544)	1964 (561)	1977 (571)	2001 (586)
Alcohol intake, g/day	7.5 (10.2)	6.7 (9.6)	5.6 (9.0)	4.7 (8.3)	3.4 (7.2)	10.3 (13.4)	11.2 (13.5)	11.3 (14.1)	11.2 (14.5)	9.9 (14.3)
Physical activity, metabolic equivalent task score (METS)-hours/week	19.9 (20.7)	17.6 (17.8)	15.5 (15.6)	13.8 (14.7)	11.5 (12.7)	34.0 (33.3)	32.8 (29.4)	29.6 (28.4)	26.7 (25.9)	22.0 (23.5)
Red and processed meat, servings/week	6.3 (3.6)	6.5 (3.6)	6.7 (3.6)	6.9 (3.6)	7.4 (3.9)	5.5 (4.5)	5.8 (4.2)	6.6 (4.4)	7.1 (4.5)	7.8 (4.8)
Calcium, mg/day	927 (367)	926 (353)	919 (347)	914 (344)	896 (340)	948 (389)	935 (378)	918 (368)	920 (366)	927 (374)
Folate, μg/day	427 (217)	421 (212)	416 (206)	411 (217)	405 (205)	565 (265)	551 (257)	528 (250)	512 (237)	507 (243)
Alternate Healthy Eating Index (AHEI)-2010^‡	46.4 (10.1)	46.4 (9.7)	46.3 (9.4)	46.1 (9.2)	45.2 (9.3)	49.7 (11.0)	48.9 (10.2)	47.6 (9.8)	46.9 (9.5)	46.2 (9.6)

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Updated information throughout follow-up was used to calculate the mean (standard deviation [SD]) for continuous variables and percentage for categorical variables.

^†

All values other than age have been directly standardized to age distribution (in 5-year age group) of all the participants.

^‡

Without alcohol intake.

AHEI, Alternate Healthy Eating Index; HPFS, Health Professionals Follow-up Study; METS, metabolic equivalent task score; NHS, Nurses' Health Study; NSAIDs, nonsteroidal anti-inflammatory drugs.

Higher BMI was significantly associated with a higher risk of overall colorectal cancer for both women and men (P_trend<0.001) (Tables 2 and 3). In our primary hypothesis testing, the association of BMI with risk of colorectal cancer differed significantly by presence vs. absence of poorly-differentiated foci (P_{heterogeneity}=0.006) (Table 4). The association between BMI and a higher risk of colorectal cancer appeared to be specific for cancer without poorly-differentiated foci (comparing participants with ≥30.0kg/m² to those with 18.5-22.4kg/m²; multivariable-adjusted HR=1.87; 95% CI, 1.49-2.34; P_trend<0.001). In contrast, BMI was not significantly associated with incidence of colorectal cancer with poorly-differentiated foci (comparing participants with ≥30.0kg/m² to those with 18.5-22.4kg/m²;multivariable-adjusted HR=1.17; 95% CI, 0.82-1.65; P_trend>0.50) (Table 4). Although the heterogeneity test did not reach statistical significance with Bonferroni correction, similar heterogeneity was observed in analyses of colorectal cancer subtypes classified by overall tumor differentiation (P_{heterogeneity}=0.04, with the adjusted α level of 0.01) (Table 4). These differential associations appeared consistent in both cohorts (Tables 2 and 3). On the contrary, we did not observe differential association of BMI with colorectal cancer incidence by subtypes classified by mucinous or signet ring cell components (P_{heterogeneity}>0.03)(Tables 4 and S5).

Table 2. Body mass index and risk of colorectal cancer overall and by tumor histopathological characteristics in the Nurses' Health Study (NHS).

	Body mass index (kg/m²)					P_trend	P_{heterogeneity}^†

	18.5-22.4	22.5-24.9	25.0-27.4	27.5-29.9	≥30
Total colorectal cancer
Person-years	699109	639958	450110	266076	339690
Cases, No. (n=860)	177	222	187	111	163
Age-adjusted HR (95% CI)	1 [Reference]	1.19 (0.98, 1.45)	1.34 (1.09, 1.64)	1.29 (1.02, 1.64)	1.58 (1.28, 1.96)	<0.001
Multivariable HR (95% CI)^*	1 [Reference]	1.18 (0.97, 1.45)	1.32 (1.07, 1.62)	1.27 (1.00, 1.62)	1.55 (1.24, 1.94)	<0.001

Poorly-differentiated foci
*Absent*
Cases, No. (n=592)	114	146	132	78	122
Age-adjusted HR (95% CI)	1 [Reference]	1.24 (0.97, 1.59)	1.50 (1.16, 1.93)	1.45 (1.09, 1.94)	1.87 (1.44, 2.41)	<0.001	0.02
Multivariable HR (95% CI)^*	1 [Reference]	1.23 (0.96, 1.58)	1.47 (1.14, 1.90)	1.42 (1.06, 1.91)	1.82 (1.40, 2.38)	<0.001	0.02
*Present*
Cases, No. (n=259)	60	74	52	33	40
Age-adjusted HR (95% CI)	1 [Reference]	1.13 (0.80, 1.59)	1.04 (0.72, 1.51)	1.06 (0.69, 1.63)	1.10 (0.74, 1.65)	0.77
Multivariable HR (95% CI)^*	1 [Reference]	1.12 (0.79, 1.57)	1.03 (0.71, 1.49)	1.04 (0.67, 1.59)	1.08 (0.72, 1.63)	0.86

Overall tumor differentiation
*Well/moderate*
Cases, No. (n=750)	150	187	169	98	146
Age-adjusted HR (95% CI)	1 [Reference]	1.19 (0.96, 1.48)	1.43 (1.15, 1.78)	1.35 (1.05, 1.75)	1.67 (1.33, 2.11)	<0.001	0.08
Multivariable HR (95% CI)^*	1 [Reference]	1.18 (0.95, 1.47)	1.41 (1.12, 1.76)	1.33 (1.03, 1.73)	1.64 (1.29, 2.09)	<0.001	0.08
*Poor*
Cases, No. (n=104)	26	33	16	13	16
Age-adjusted HR (95% CI)	1 [Reference]	1.16 (0.69, 1.94)	0.75 (0.40, 1.41)	0.98 (0.50, 1.91)	1.03 (0.55, 1.93)	0.82
Multivariable HR (95% CI)^*	1 [Reference]	1.15 (0.69, 1.93)	0.75 (0.40, 1.41)	0.95 (0.48, 1.86)	1.02 (0.54, 1.91)	0.77

Mucinous component
*Absent (0%)*
Cases, No. (n=491)	108	119	108	60	96
Age-adjusted HR (95% CI)	1 [Reference]	1.08 (0.83, 1.40)	1.30 (0.99, 1.70)	1.21 (0.88, 1.66)	1.59 (1.21, 2.10)	<0.001	0.74
Multivariable HR (95% CI)^*	1 [Reference]	1.07 (0.82, 1.39)	1.28 (0.98, 1.68)	1.19 (0.86, 1.63)	1.56 (1.17, 2.07)	0.002	0.75
*1% to 49%*
Cases, No. (n=225)	48	62	44	32	39
Age-adjusted HR (95% CI)	1 [Reference]	1.20 (0.82, 1.75)	1.13 (0.75, 1.70)	1.29 (0.82, 2.02)	1.34 (0.87, 2.05)	0.19
Multivariable HR (95% CI)^*	1 [Reference]	1.20 (0.82, 1.75)	1.12 (0.74, 1.69)	1.26 (0.80, 1.98)	1.32 (0.86, 2.03)	0.24
*≥50%*
Cases, No. (n=104)	17	26	23	14	24
Age-adjusted HR (95% CI)	1 [Reference]	1.36 (0.74, 2.52)	1.58 (0.84, 2.96)	1.51 (0.74, 3.08)	2.21 (1.18, 4.12)	0.01
Multivariable HR (95% CI)^*	1 [Reference]	1.35 (0.73, 2.49)	1.54 (0.82, 2.89)	1.48 (0.73, 3.02)	2.15 (1.15, 4.03)	0.02

Signet ring cell component
*Absent*
Cases, No. (n=750)	155	191	164	96	144
Age-adjusted HR (95% CI)	1 [Reference]	1.19 (0.96, 1.47)	1.36 (1.09, 1.69)	1.30 (1.01, 1.68)	1.63 (1.29, 2.04)	<0.001	0.39
Multivariable HR (95% CI)^*	1 [Reference]	1.18 (0.95, 1.46)	1.34 (1.07, 1.67)	1.28 (0.99, 1.66)	1.60 (1.26, 2.03)	<0.001	0.38
*Present*
Cases, No. (n=110)	22	31	23	15	19
Age-adjusted HR (95% CI)	1 [Reference]	1.23 (0.71, 2.13)	1.19 (0.66, 2.15)	1.21 (0.62, 2.34)	1.28 (0.69, 2.38)	0.51
Multivariable HR (95% CI)^*	1 [Reference]	1.21 (0.70, 2.10)	1.18 (0.66, 2.13)	1.17 (0.61, 2.27)	1.26 (0.68, 2.34)	0.55

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Adjusted for family history of colorectal cancer (yes/no), history of colonoscopy/sigmoidoscopy (yes/no), smoking in pack-years (never, <5,5-19, 20-39, 40+ pack-years), physical activity (quintiles of metabolic equivalent task score [METS]-hours per week), red and processed meat intake (quintiles of servings per day), alcohol consumption (0, <5, 5-<15, 15-<30, 30+ gram per day), current multivitamin use (yes or no), regular use of aspirin (yes or no), regular use of non-steroidal anti-inflammatory drugs (NSAIDs [yes or no]), total energy intake (quintiles of calories per day), folate intake (quintiles of μg per day), calcium intake (quintiles of mg per day), and Alternate Healthy Eating Index (AHEI)-2010 (quintiles of the overall AHEI-2010 score without alcohol intake). For women, we additionally adjusted for menopause/postmenopausal hormone use status (premenopausal, postmenopausal never use, postmenopausal past use, postmenopausal current hormone use).

^†

We assessed whether the magnitude of the subtype-specific associations had an increasing or decreasing ordinal trend according to the subtyping marker using a likelihood ratio test with one degree of freedom, and the statistical significance of this trend was presented as P_{heterogeneity}.

CI, confidence interval; HR, hazard ratio; NHS, Nurses' Health Study.

Table 3. Body mass index and risk of colorectal cancer overall and by tumor histopathological characteristics in the Health Professionals Follow-up Study (HPFS).

	Body mass index (kg/m²)					P_trend	P_{heterogeneity}^†

	18.5-22.4	22.5-24.9	25.0-27.4	27.5-29.9	≥30
Total colorectal cancer
Person-years	59433	161809	154675	73416	45684
Cases, No. (n=668)	58	202	221	117	70
Age-adjusted HR (95% CI)	1 [Reference]	1.34 (1.00, 1.80)	1.55 (1.16, 2.08)	1.77 (1.28, 2.43)	1.76 (1.24, 2.51)	<0.001
Multivariable HR (95% CI)^*	1 [Reference]	1.33 (0.99, 1.79)	1.52 (1.13, 2.04)	1.70 (1.23, 2.35)	1.71 (1.19, 2.46)	<0.001

Poorly-differentiated foci
*Absent*
Cases, No. (n=477)	40	140	156	89	52
Age-adjusted HR (95% CI)	1 [Reference]	1.37 (0.96, 1.95)	1.62 (1.14, 2.30)	1.98 (1.36, 2.89)	1.95 (1.28, 2.97)	<0.001	0.18
Multivariable HR (95% CI)^*	1 [Reference]	1.36 (0.95, 1.93)	1.58 (1.11, 2.25)	1.90 (1.29, 2.78)	1.89 (1.24, 2.90)	<0.001	0.19
*Present*
Cases, No. (n=178)	18	58	59	25	18
Age-adjusted HR (95% CI)	1 [Reference]	1.19 (0.70, 2.04)	1.30 (0.76, 2.22)	1.17 (0.63, 2.16)	1.39 (0.71, 2.69)	0.42
Multivariable HR (95% CI)^*	1 [Reference]	1.20 (0.70, 2.05)	1.26 (0.74, 2.16)	1.14 (0.61, 2.10)	1.36 (0.70, 2.66)	0.51

Overall tumor differentiation
*Well/moderate*
Cases, No. (n=616)	55	181	204	109	67
Age-adjusted HR (95% CI)	1 [Reference]	1.27 (0.94, 1.72)	1.52 (1.13, 2.06)	1.76 (1.26, 2.44)	1.79 (1.25, 2.57)	<0.001	0.26
Multivariable HR (95% CI)^*	1 [Reference]	1.26 (0.93, 1.71)	1.48 (1.09, 2.00)	1.68 (1.20, 2.34)	1.73 (1.19, 2.51)	<0.001	0.31
*Poor*
Cases, No. (n=45)	3	18	14	7	3
Age-adjusted HR (95% CI)	1 [Reference]	2.21 (0.65, 7.55)	1.77 (0.50, 6.20)	1.77 (0.45, 6.91)	1.41 (0.28, 7.08)	0.90
Multivariable HR (95% CI)^*	1 [Reference]	2.30 (0.67, 7.90)	1.83 (0.52, 6.47)	1.85 (0.47, 7.28)	1.45 (0.29, 7.31)	0.93

Mucinous component
*Absent (0%)*
Cases, No. (n=384)	34	125	125	64	36
Age-adjusted HR (95% CI)	1 [Reference]	1.44 (0.98, 2.11)	1.48 (1.01, 2.18)	1.69 (1.11, 2.58)	1.57 (0.97, 2.52)	0.06	0.18
Multivariable HR (95% CI)^*	1 [Reference]	1.43 (0.97, 2.10)	1.44 (0.98, 2.12)	1.60 (1.04, 2.45)	1.52 (0.94, 2.46)	0.11	0.18
*1% to 49%*
Cases, No. (n=175)	15	51	60	33	16
Age-adjusted HR (95% CI)	1 [Reference]	1.28 (0.72, 2.29)	1.70 (0.96, 3.01)	1.98 (1.07, 3.67)	1.51 (0.73, 3.10)	0.06
Multivariable HR (95% CI)^*	1 [Reference]	1.25 (0.70, 2.23)	1.61 (0.91, 2.86)	1.87 (1.01, 3.48)	1.42 (0.69, 2.95)	0.09
*≥50%*
Cases, No. (n=60)	4	18	20	6	12
Age-adjusted HR (95% CI)	1 [Reference]	1.84 (0.62, 5.48)	2.20 (0.74, 6.50)	1.27 (0.35, 4.53)	4.63 (1.46, 14.7)	0.02
Multivariable HR (95% CI)^*	1 [Reference]	1.91 (0.64, 5.68)	2.21 (0.75, 6.55)	1.22 (0.34, 4.38)	4.67 (1.46, 14.9)	0.03

Signet ring cell component
*Absent*
Cases, No. (n=603)	53	183	200	108	59
Age-adjusted HR (95% CI)	1 [Reference]	1.32 (0.97, 1.80)	1.54 (1.13, 2.09)	1.79 (1.28, 2.49)	1.64 (1.12, 2.39)	<0.001	0.45
Multivariable HR (95% CI)^*	1 [Reference]	1.32 (0.97, 1.80)	1.50 (1.10, 2.05)	1.72 (1.23, 2.41)	1.59 (1.08, 2.34)	0.003	0.43
*Present*
Cases, No. (n=65)	5	19	21	9	11
Age-adjusted HR (95% CI)	1 [Reference]	1.51 (0.56, 4.05)	1.73 (0.65, 4.63)	1.56 (0.52, 4.71)	2.95 (1.01, 8.61)	0.05
Multivariable HR (95% CI)^*	1 [Reference]	1.46 (0.54, 3.94)	1.65 (0.62, 4.42)	1.49 (0.49, 4.50)	2.86 (0.98, 8.40)	0.06

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Adjusted for the same set of covariates as in Table 2.

^†

CI, confidence interval; HPFS, Health Professionals Follow-up Study; HR, hazard ratio.

Table 4. Body mass index and risk of colorectal cancer overall and by tumor histopathological characteristics in the pooled cohorts.

	Body mass index (kg/m²)					P_trend	P_{heterogeneity}^†

	18.5-22.4	22.5-24.9	25.0-27.4	27.5-29.9	≥30
Total colorectal cancer
Person-years	812884	951694	747717	407217	427160
Cases, No. (n=1528)	235	424	408	228	233
Age-adjusted HR (95% CI)	1 [Reference]	1.22 (1.04, 1.44)	1.39 (1.18, 1.64)	1.46 (1.21, 1.75)	1.62 (1.35, 1.95)	<0.001
Multivariable HR (95% CI)^*	1 [Reference]	1.22 (1.04, 1.43)	1.38 (1.17, 1.63)	1.43 (1.19, 1.73)	1.61 (1.33, 1.95)	<0.001

Poorly-differentiated foci
*Absent*
Cases, No. (n=1069)	154	286	288	167	174
Age-adjusted HR (95% CI)	1 [Reference]	1.27 (1.04, 1.55)	1.52 (1.24, 1.85)	1.65 (1.32, 2.07)	1.88 (1.51, 2.35)	<0.001	0.006
Multivariable HR (95% CI)^*	1 [Reference]	1.27 (1.04, 1.55)	1.50 (1.23, 1.84)	1.63 (1.30, 2.04)	1.87 (1.49, 2.34)	<0.001	0.006
*Present*
Cases, No. (n=437)	78	132	111	58	58
Age-adjusted HR (95% CI)	1 [Reference]	1.13 (0.85, 1.50)	1.13 (0.84, 1.52)	1.08 (0.77, 1.53)	1.17 (0.83, 1.65)	0.51
Multivariable HR (95% CI)^*	1 [Reference]	1.13 (0.85, 1.50)	1.11 (0.83, 1.49)	1.06 (0.75, 1.50)	1.17 (0.82, 1.65)	0.56

Overall tumor differentiation
*Well/moderate*
Cases, No. (n=1366)	205	368	373	207	213
Age-adjusted HR (95% CI)	1 [Reference]	1.21 (1.01, 1.44)	1.45 (1.21, 1.72)	1.51 (1.24, 1.84)	1.70 (1.40, 2.07)	<0.001	0.03
Multivariable HR (95% CI)^*	1 [Reference]	1.20 (1.01, 1.43)	1.43 (1.20, 1.70)	1.48 (1.22, 1.81)	1.69 (1.38, 2.06)	<0.001	0.04
*Poor*
Cases, No. (n=149)	29	51	30	20	19
Age-adjusted HR (95% CI)	1 [Reference]	1.28 (0.81, 2.03)	0.91 (0.54, 1.54)	1.06 (0.59, 1.90)	1.06 (0.59, 1.90)	0.79
Multivariable HR (95% CI)^*	1 [Reference]	1.28 (0.80, 2.03)	0.92 (0.55, 1.55)	1.05 (0.59, 1.87)	1.07 (0.59, 1.91)	0.80

Mucinous component
*Absent (0%)*
Cases, No. (n=875)	142	244	233	124	132
Age-adjusted HR (95% CI)	1 [Reference]	1.19 (0.97, 1.47)	1.33 (1.07, 1.65)	1.37 (1.07, 1.75)	1.58 (1.24, 2.00)	<0.001	0.36
Multivariable HR (95% CI)^*	1 [Reference]	1.19 (0.97, 1.47)	1.32 (1.06, 1.64)	1.34 (1.05, 1.72)	1.56 (1.23, 2.00)	<0.001	0.36
*1% to 49%*
Cases, No. (n=400)	63	113	104	65	55
Age-adjusted HR (95% CI)	1 [Reference]	1.18 (0.86, 1.61)	1.32 (0.96, 1.82)	1.51 (1.06, 2.14)	1.38 (0.95, 1.98)	0.03
Multivariable HR (95% CI)^*	1 [Reference]	1.18 (0.86, 1.61)	1.31 (0.95, 1.80)	1.48 (1.04, 2.11)	1.36 (0.94, 1.97)	0.04
*≥50%*
Cases, No. (n=164)	21	44	43	20	36
Age-adjusted HR (95% CI)	1 [Reference]	1.45 (0.86, 2.45)	1.70 (1.00, 2.88)	1.36 (0.73, 2.53)	2.65 (1.54, 4.57)	0.001
Multivariable HR (95% CI)^*	1 [Reference]	1.46 (0.86, 2.46)	1.68 (0.99, 2.86)	1.34 (0.72, 2.49)	2.63 (1.53, 4.54)	0.001

Signet ring cell component
*Absent*
Cases, No. (n=1353)	208	374	364	204	203
Age-adjusted HR (95% CI)	1 [Reference]	1.22 (1.03, 1.45)	1.40 (1.18, 1.67)	1.48 (1.22, 1.80)	1.62 (1.34, 1.97)	<0.001	0.67
Multivariable HR (95% CI)^*	1 [Reference]	1.22 (1.02, 1.45)	1.39 (1.17, 1.66)	1.46 (1.20, 1.78)	1.61 (1.32, 1.97)	<0.001	0.67
*Present*
Cases, No. (n=175)	27	50	44	24	30
Age-adjusted HR (95% CI)	1 [Reference]	1.25 (0.78, 2.01)	1.30 (0.80, 2.12)	1.26 (0.72, 2.19)	1.60 (0.95, 2.71)	0.13
Multivariable HR (95% CI)^*	1 [Reference]	1.23 (0.77, 1.98)	1.28 (0.79, 2.09)	1.23 (0.70, 2.14)	1.58 (0.93, 2.67)	0.14

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Adjusted for the same set of covariates as in Table 2.

^†

CI, confidence interval; HR, hazard ratio.

In agreement with our previous studies,[35] there was no statistically significant heterogeneity in the associations between BMI and cancer subtypes according to MSI(P_{heterogeneity}=0.72) (Table S3). However, we observed a significant heterogeneity in the association of BMI with cancer subtypes by FASN expression status (P_{heterogeneity}=0.008) (Table S4). Because of the associations of MSI-high colorectal cancer with poor differentiation[21] and FASN overexpression,[22] as well as the association of obesity with FASN-negative colorectal cancer risk,[36] we further investigated whether the heterogeneous association according to the presence of poorly-differentiated foci was independent of MSI or FASN status. Although the statistical power was limited in the subsequent subgroup analyses, the differential association of BMI with colorectal cancer subtypes according to the presence of poorly-differentiated foci appeared to be consistent regardless of MSI or FASN expression status (Tables S3 and S4).

Discussion

A large prospective cohort study was conducted to assess the association between BMI and colorectal cancer risk according to subtypes defined by tumor histomorphological features. Accumulating evidence suggests that poor differentiation or the presence of poorly-differentiated focus is associated with colorectal carcinoma with MSI-high,[21] FASN overexpression,[22] and mucinous or signet ring cell components.[20] MSI-high, characterized by a deficient DNA mismatch repair system,[23] and overexpression of FASN, a key enzyme of de novo lipogenesis,[20,26] appeared to drive dysregulated cell proliferation, reducing gland-forming ability of neoplastic epithelial cells, independent of excess energy balance. Colorectal carcinoma with a high abundance of mucinous or signet ring cell components could potentially be poorly differentiated tumors or those with the presence of poorly-differentiated focus,[45] consistent with our previous study.[20] Collectively, obesity may influence colorectal carcinoma risk differentially according to tumor morphological characteristics. The current study suggests that higher BMI may be associated with an increased risk of colorectal cancer without poorly-differentiated foci. This heterogeneous association appeared to be present irrespective of MSI or FASN expression status, although the statistical power was limited. We also observed a possibly stronger association between BMI and well/moderately differentiated colorectal carcinoma as compared with the association between BMI and poor differentiation carcinoma, although the difference was not statistically significant. Our data suggest that excess body weight might contribute to the development of specific morphologic subtypes of colorectal cancer.

Accumulating evidence from epidemiological and animal studies suggests a causal link between obesity and colorectal cancer,[50–52] but little is known about how excess energy intake can drive carcinogenesis in the intestinal epithelium.[15,53–55] In a recent large population-based study of U.K. women, BMI was analyzed in relation to risks of mucinous and signet ring cell subtypes of colorectal carcinoma, but poor differentiation or poorly differentiated focus was not examined.[56] Notably, the classification system of neuroendocrine type vs. signet ring cell type vs. mucinous type (vs. other adenocarcinoma) is not optimal, because two or three of these features can co-exist in a given tumor. Moreover, their histopathological data were not based on centralized pathology review, but largely on pathological reports in community hospital settings.[56] In the current study, pathologic characteristics were examined by the single expert pathologist, and our multivariable analyses adjusting for potential confounders could demonstrate a vigorous heterogeneous association between BMI and colorectal cancer incidence according to tumor differentiation.

Previous studies have shown that excess energy balance and the resultant PPARD activation may play a critical role in tissue remodeling and cancer initiation in the intestine.[9,13,14,57–59] Recent studies in murine models have demonstrated that prolonged high-fat load can increase the proportion of intestinal stem cells (ISCs), augment stem cell self-renewal, and provide non-ISCs (differentiated intestinal cells) with stemness attributes through activation of PPARD signaling, all of which may contribute to tumor development.[14,15] Additional studies have shown that the number of ISCs may be reduced by fasting and increased by refeeding.[10] In contrast, one study has shown that prolonged energy restriction leads to an increase in ISC proliferation, and an enhancement of ISC activity in mice.[12] The present study provides evidence suggesting that higher BMI is associated with an increased risk of colorectal carcinoma that has an abundance of well-differentiated glandular epithelial cells (i.e., no poorly-differentiated focus). The data in the current study suggest that colorectal carcinoma containing fewer malfunctioning stem-like cells (which may fail to differentiate into glandular epithelial cells) may depend on excess energy balance for their growth, while carcinoma containing many such malfunctioning stem-like cells may be less dependent on systemic energy balance status. This hypothesis requires further investigation in future studies.

The results of epidemiologic studies are somewhat conflicting in terms of the association of BMI with incidence of colorectal cancer MSI-high and MSS subtypes. Although earlier case-control studies suggested the differential influence of obesity on MSS vs. MSI-high colorectal cancer risk,[30–32] subsequent prospective cohort studies did not fully support this differential association.[33–35] We can speculate that the previously-described association between BMI and MSS colorectal cancer might have been driven by the association between MSS and carcinoma without poorly-differentiated foci. Another possible explanation for the association between obesity and MSS colorectal cancer might be due to the higher prevalence of MSS status in FASN-negative colorectal cancer.[22,40] As we previously demonstrated, higher BMI might be associated with incidence of FASN-negative colorectal cancer, but not with FASN-positive cancer.[36] Together with experimental for the “metabolic oncogenic” role of tumor FASN,[26,60,61] it is conceivable that FASN-overexpressing colonic cells might initiate tumorigenesis independent of host energy balance status whereas FASN-negative cells might depend on excess energy balance for neoplastic development. Indeed in our exploratory analysis, FASN-negative colorectal carcinoma without poorly-differentiated foci appeared to be most strongly associated with high BMI.

As the emerging field of epidemiology, molecular pathological epidemiology (MPE)facilitates integrative analyses on the associations of lifestyle, dietary or environmental factors with cancer incidence and mortality, taking into account tumor genetic, epigenetic, or histopathological variations.[62] The MPE approach[63,64] can take into account histopathologic characteristics as manifestations of molecular pathology. The current study exploiting this MPE approach can provide a unique insight into mechanisms of colorectal carcinogenesis associated with excess adiposity. Additionally, there are several strengths in this study. First, we avoided recall bias in weight reporting by using a prospective study design. Second, repeated collection of prediagnosis weight data over a prolonged follow-up period allowed us to evaluate the long-term effect of adiposity on colorectal cancer risk. To control for potential confounders, we adjusted for a number of dietary and environmental factors. In addition, tissue specimens of colorectal cancer were collected from a large number of hospitals in various settings throughout the U.S., which increases the generalizable of our findings.

There are several limitations in this study. First, tumor tissue specimens were not available for all colorectal cancer cases, leading to potential selection bias. However, we did not observe any considerable differences in demographic features between participants with and without available tissue data. In addition, we acknowledge possible bias due to intratumor heterogeneity in evaluating tumor histopathologic characteristics. Given the fact that we examined focal features of each tumor specimen, including poorly-differentiated focus, mucinous component, and signet ring cells, intratumor heterogeneity was indeed taken into account in our analyses. Second, as is the case with observational studies, there is the possibility of unmeasured confounding. Nonetheless, our multivariable risk estimates were computed with adjustment for many well-known risk factors for colorectal cancer. Third, the current data were derived from cohort studies of health care professionals who were mostly Caucasians. Hence, generalizability of our findings in other populations must be examined in additional studies. Fourth, there has been a debate on use of BMI as a surrogate for host energy balance status.[65] Therefore, future studies using different anthropometric factors would provide additional insights into excess energy intake and colorectal carcinogenesis. Fifth, because of the MPE research design, this study possesses specific caveats, which have been previously discussed.[37,38] In particular, recognizing multiple hypothesis testing in our current analyses, we used the adjusted α level, and interpreted our results cautiously. In addition, we emphasize the importance of validating our findings in independent population-based studies in the future.

In conclusion, our MPE study suggests that higher BMI might increase the risk of colorectal carcinoma without poorly-differentiated foci. Although a validation in independent datasets is needed, our findings may provide unique insights into the potential oncogenic role of obesity and excess energy balance status.

Supplementary Material

Supplementary materials

NIHMS873354-supplement-Supplementary_materials.docx^{(49KB, docx)}

Acknowledgments

We would like to thank the participants and staff of the Nurses' Health Study and the Health Professionals Follow-up Study for their valuable contributions as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, WY. The authors assume full responsibility for analyses and interpretation of these data.

Funding: This work was supported by U.S. National Institutes of Health (NIH) grants [UM1 CA186107 and P01 CA87969 to Meir J. Stampfer; P01 CA55075 and UM1 CA167552 to Walter C. Willett; K07 CA190673 to R.N.; R01 CA137178 and K24 DK098311 to A.T.C.; P50 CA127003 to C.S.F.; R01 CA151993 and R35 CA197735 to S.O.], by Nodal Award from the Dana-Farber Harvard Cancer Center (to S.O.); and by grants from the Project P Fund, the Friends of the Dana-Farber Cancer Institute, the Bennett Family Fund and the Entertainment Industry Foundation through National Colorectal Cancer Research Alliance. A.H. was supported by the Japan-United States Educational Exchange Promotion Foundation (Fulbright Foundation), Japan and the U.S. T.H. was supported by a fellowship grant from the Uehara Memorial Foundation and by a grant from the Mochida Memorial Foundation for Medical and Pharmaceutical Research. Y.M. was supported by a fellowship grant of the Keio Gijuku Fukuzawa Memorial Fund for the Advancement of Education and Research. A.T.C. was a Damon Runyon Clinical Investigator.

Abbreviations

AHEI: Alternate Healthy Eating Index
BMI: body mass index
CI: confidence interval
FFPE: formalin-fixed paraffin-embedded
HPFS: Health Professionals Follow-up Study
HR: hazard ratio
ISC: intestinal stem cells
METS: metabolic equivalent task score
MPE: Molecular Pathological Epidemiology
MSI: microsatellite instability
MSS: microsatellite stable
NHS: Nurses' Health Study
NSAIDs: non-steroidal anti-inflammatory drugs
SD: standard deviation
WHO: World Health Organization

Footnotes

Conflict of interest: A.T.C. previously served as a consultant for Bayer Healthcare, Pozen Inc, and Pfizer Inc. This study was not funded by Bayer Healthcare, Millennium Pharmaceuticals, or Pfizer Inc. All remaining authors have declared no conflicts of interest.

Use of standardized official symbols: We use HUGO (Human Genome Organisation)-approved official symbols for genes (italics) and gene products (non-italics), including CTNNB1, FASN, and PPARD; all of which are described at www.genenames.org.

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PERMALINK

Body mass index and risk of colorectal carcinoma subtypes classified by tumor differentiation status

Akiko Hanyuda

Yin Cao

Tsuyoshi Hamada

Jonathan A Nowak

Zhi Rong Qian

Yohei Masugi

Annacarolina da Silva

Li Liu

Keisuke Kosumi

T Rinda Soong

Iny Jhun

Kana Wu

Xuehong Zhang

Mingyang Song

Jeffrey A Meyerhardt

Andrew T Chan

Charles S Fuchs

Edward L Giovannucci

Shuji Ogino

Reiko Nishihara

Abstract

Background

Methods

Results

Conclusions

Introduction

Methods

Study population

Assessment of weight and height

Assessment of colorectal cancer cases

Tumor histopathological, immunohistochemical, and molecular evaluation

Statistical analysis

Results

Table 1. Age-standardized characteristics of the Nurses' Health Study (NHS) (1980-2010) and the Health Professionals Follow-up Study(HPFS) (1986-2010) participants according to body mass index (person-years)*.

Table 2. Body mass index and risk of colorectal cancer overall and by tumor histopathological characteristics in the Nurses' Health Study (NHS).

Table 3. Body mass index and risk of colorectal cancer overall and by tumor histopathological characteristics in the Health Professionals Follow-up Study (HPFS).

Table 4. Body mass index and risk of colorectal cancer overall and by tumor histopathological characteristics in the pooled cohorts.

Discussion

Supplementary Material

Acknowledgments

Abbreviations

Footnotes

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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Links to NCBI Databases

Table 1. Age-standardized characteristics of the Nurses' Health Study (NHS) (1980-2010) and the Health Professionals Follow-up Study(HPFS) (1986-2010) participants according to body mass index (person-years)^*.