Abstract
Objective
Colorectal cancer is typically classified into proximal colon, distal colon, and rectal cancer. Tumor genetic and epigenetic features differ by tumor location. Considering a possible role of bowel contents (including microbiome) in carcinogenesis, we hypothesized that tumor molecular features might gradually change along bowel subsites, rather than abruptly change at splenic flexure.
Design
Utilizing 1443 colorectal cancers in two U.S. nationwide prospective cohort studies, we examined the frequencies of molecular features [CpG island methylator phenotype (CIMP), microsatellite instability (MSI), LINE-1 methylation, and BRAF, KRAS, and PIK3CA mutations] along bowel subsites (rectum, rectosigmoid junction, sigmoid, descending colon, splenic flexure, transverse colon, hepatic flexure, ascending colon, and cecum). Linearity and non-linearity of molecular relations along subsites were statistically tested by multivariate logistic or linear regression analysis.
Results
The frequencies of CIMP-high, MSI-high, and BRAF mutation gradually increased from rectum (<2.3%) to ascending colon (36–40%), followed by falls in the cecum (12–22%). By linearity tests, these molecular relations were significantly linear from rectum to ascending colon (p<0.0001), and there was little evidence for non-linearity (p>0.09). Cecal cancers exhibited the highest frequency of KRAS mutations (52% vs. 27–35% in other sites; p<0.0001).
Conclusions
The frequencies of CIMP-high, MSI-high, and BRAF mutation in cancer increased gradually along colorectum subsites from rectum to ascending colon. Our novel data challenge the common conception of discrete molecular features of proximal vs. distal colorectal cancers, and have substantial impact on clinical, translational, and epidemiology research, which has typically been performed with dichotomous classification of proximal vs. distal tumors.
Keywords: colon cancer, epigenetics, genomic instability, continuum, RAS, RAF, PI3K
INTRODUCTION
Over the past decades, clinical, pathologic or epidemiologic investigations on the large bowel have semi-automatically divided colorectum into 3 compartments, namely, rectum, distal colon and proximal colon.[1–3] In 1990, Bufill proposed the existence of two distinct genetic categories of colorectal cancers according to tumor location in the proximal or distal segment of the large bowel, divided at splenic flexure.[1] This concept of distinct molecular features of proximal cancer vs. distal cancer has repeatedly been discussed.[2, 3]
Colorectal cancers encompass a heterogeneous group of diseases with complex genetic and epigenetic alterations.[4] Thus, molecular classification is increasingly important for clinical decision making.[5] Microsatellite instability (MSI) represents a distinct form of genomic instability.[5, 6] The CpG island methylator phenotype (CIMP) is a distinct form of epigenomic instability,[7–17] which causes most sporadic MSI-high colorectal cancers through epigenetic inactivation of MLH1.[18–21] Independent of MSI, CIMP-high colorectal cancer is associated with proximal tumor location, old age of onset, female sex, and BRAF mutation.[18, 19]
Accumulating evidence suggests that proximal colon cancer and distal colon cancer differ in various molecular features including CIMP and MSI.[22–25] However, it remains uncertain whether the tumor molecular features change abruptly at splenic flexure. Considering a possible role of bowel contents (including microbiome) in colorectal carcinogenesis,[26] we hypothesized that tumor molecular characteristics might change gradually along the large bowel. This hypothesis is not inconsistent with the differences between proximal vs. distal cancers, as long as tumor molecular features change along the large bowel.
To test the hypothesis, we conducted this study utilizing a database of 1443 colorectal cancers in two prospective cohort studies. We examined the frequencies of relevant molecular features along the bowel subsites (rectum, rectosigmoid, sigmoid colon, descending colon, splenic flexure, transverse colon, hepatic flexure, ascending colon, and cecum), and statistically assessed the linearity and non-linearity of molecular relations along the bowel subsites. Our novel findings of gradual increases of CIMP-high, MSI-high, and BRAF mutation from rectum to ascending colon challenge the common conception of discrete dichotomy of tumor molecular features in proximal colon vs. distal colorectum.
MATERIALS AND METHODS
Study group
We utilized the database of two independent, prospective cohort studies; the Nurses’ Health Study (N=121,701 women followed since 1976), and the Health Professionals Follow-up Study (N=51,529 men followed since 1986).[27, 28] Every 2 years, participantshave been sent follow-up questionnaires to update informationon potential risk factors and to identify newly diagnosed cancers in themselves and their first degree relatives. In addition, we searched the National Death Index for those who died of colorectal cancer. Our study physicians reviewed medical records and obtained information on disease stage and tumor location (rectum, rectosigmoid, sigmoid colon, descending colon, splenic flexure, transverse colon, hepatic flexure, ascending colon, and cecum). We collected paraffin-embedded tissue blocks from hospitals where patients underwent tumor resections. We collected diagnostic biopsy specimens for rectal cancer patients who received preoperative treatment, in order to avoid artifacts or bias introduced by treatment. Based on availability of adequate tissue specimens and follow-up data, a total of 1443 colorectal cancer cases (diagnosed up to 2006) were included (Tables 1–2). Among our cohort studies, there was no significant difference in demographic features between cases with tissue available and those without available tissue.[27] This current study represents a new analysis of tumor molecular features along the detailed bowel subsites on the existing colorectal cancer database that has been previously characterized for CIMP, MSI, LINE-1 methylation and BRAF and KRAS mutations.[29, 30] Informed consent was obtained from all study subjects. This study was approved by the Harvard School of Public Health and Brigham and Women’s Hospital Institutional Review Boards.
Table 1.
Clinical characteristics of colorectal cancer according to tumor location bowel subsite
| Clinical feature | Total N | Cecum | Ascending colon | Hepatic flexure | Transverse colon | Splenic flexure | Descending colon | Sigmoid colon | Rectosigmoid | Rectum | P value |
|---|---|---|---|---|---|---|---|---|---|---|---|
| All cases | 1443 | 243 | 295 | 46 | 91 | 33 | 83 | 314 | 106 | 232 | |
| Sex | <0.0001 | ||||||||||
| Male (HPFS) | 649 (45%) | 129 (53%) | 95 (32%) | 28 (61%) | 34 (37%) | 18 (55%) | 34 (41%) | 149 (47%) | 51 (48%) | 111 (48%) | |
| Female (NHS) | 794 (55%) | 114 (47%) | 200 (68%) | 18 (39%) | 57 (63%) | 15 (46%) | 49 (59%) | 165 (53%) | 55 (52%) | 121 (52%) | |
| Mean age ± SD | 68.4 ± 8.9 | 69.2 ± 8.6 | 70.9 ± 8.4 | 71.3 ± 8.8 | 67.0 ± 8.4 | 67.2 ± 9.6 | 65.8 ± 8.8 | 67.4 ± 8.3 | 67.4 ± 9.1 | 67.4 ± 9.6 | <0.0001 |
| Body mass index | 0.35 | ||||||||||
| <30 kg/m2 | 1161 (81%) | 209 (86%) | 241 (83%) | 35 (76%) | 72 (79%) | 24 (75%) | 65 (78%) | 246 (79%) | 83 (81%) | 186 (81 %) | |
| ≥30 kg/m2 | 269 (19%) | 33 (14%) | 48 (17%) | 11 (24%) | 19 (21%) | 8 (25%) | 18 (22%) | 67 (21%) | 20 (19%) | 45 (19%) | |
| Year of diagnosis | 0.0024 | ||||||||||
| Prior to 1995 | 459 (32%) | 65 (27%) | 75 (25%) | 10 (22%) | 32 (35%) | 13 (39%) | 29 (35%) | 124 (39%) | 28 (26%) | 83 (36%) | |
| 1995 to 2006 | 984 (68%) | 178 (73%) | 220 (75%) | 36 (78%) | 59 (65%) | 20 (61%) | 54 (65%) | 190 (61%) | 78 (74%) | 149 (64%) | |
| Family history of colorectal cancer in any first-degree relative | 0.15 | ||||||||||
| Absent | 1162 (81%) | 190 (79%) | 225 (78%) | 38 (83%) | 73 (80%) | 23 (72%) | 69 (83%) | 254 (81%) | 90 (87%) | 200 (87%) | |
| Present | 270 (19%) | 52 (21%) | 65 (22%) | 8 (17%) | 18 (20%) | 9 (28%) | 14 (17%) | 59 (19%) | 14 (13%) | 31 (13%) | |
| Pre-diagnosis physical activity (MET-hours/week) | 0.058 | ||||||||||
| <18 | 803 (59%) | 129 (55%) | 184 (65%) | 20 (43%) | 44 (53%) | 18 (60%) | 50 (63%) | 182 (63%) | 56 (55%) | 120 (57%) | |
| ≥18 | 550 (41%) | 104 (45%) | 97 (35%) | 26 (57%) | 39 (47%) | 12 (40%) | 29 (37%) | 108 (37%) | 45 (45%) | 90 (43%) | |
| Pre-diagnosis smoking status | 0.16 | ||||||||||
| Never | 571 (41%) | 108 (45%) | 108 (38%) | 19 (41%) | 36 (40%) | 12 (38%) | 24 (29%) | 141 (45%) | 38 (38%) | 85 (38%) | |
| Former/current smokers | 839 (60%) | 131 (55%) | 178 (62%) | 27 (59%) | 54 (60%) | 20 (63%) | 59 (71%) | 169 (55%) | 62 (62%) | 139 (62%) | |
| Pre-diagnosis alcohol consumption | 0.50 | ||||||||||
| No | 468 (33%) | 84 (35%) | 104 (36%) | 12 (26%) | 31 (34%) | 14 (44%) | 18 (22%) | 98 (31%) | 32 (31%) | 75 (33%) | |
| <15 g/day | 661 (46%) | 113 (47%) | 132 (46%) | 21 (46%) | 44 (48%) | 11 (34%) | 45 (54%) | 146 (47%) | 52 (50%) | 95 (43%) | |
| ≥15 g/day | 298 (21%) | 45 (19%) | 52 (18%) | 13 (28%) | 16 (18%) | 7 (22%) | 20 (24%) | 69 (22%) | 20 (19%) | 56 (25%) | |
(%) indicates the proportion of cases with a specific clinical feature among cancers located in each subsite (cecum, ascending colon, hepatic flexure, transverse colon, splenic flexure, descending colon, sigmoid colon, rectosigmoid or rectum). P values were calculated by chi-square test, except for age (one-way ANOVA test).
HPFS, Health Professionals Follow-up Study; MET, metabolic equivalent task; NHS, Nurses’ Health Study; SD, standard deviation.
Table 2.
Pathologic characteristics of colorectal cancer according to tumor location bowel subsite
| Pathologic feature | Total N | Cecum | Ascending colon | Hepatic flexure | Transverse colon | Splenic flexure | Descending colon | Sigmoid colon | Rectosigmoid | Rectum | P value |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Disease stage | <0.0001 | ||||||||||
| I | 339 (26%) | 53 (24%) | 59 (22%) | 12 (29%) | 16 (18%) | 7 (22%) | 12 (16%) | 84 (31%) | 33 (34%) | 63 (33%) | |
| II | 403 (31%) | 75 (34%) | 108 (40%) | 15 (36%) | 35 (40%) | 9 (28%) | 32 (43%) | 67 (25%) | 24 (25%) | 38 (20%) | |
| III | 357 (28%) | 57 (26%) | 61 (22%) | 9 (21%) | 21 (24%) | 9 (28%) | 25 (34%) | 77 (28%) | 30 (31%) | 68 (36%) | |
| IV | 187 (15%) | 36 (16%) | 44 (16%) | 6 (14%) | 16 (18%) | 7 (22%) | 5 (6.8%) | 44 (16%) | 9 (9.4%) | 20 (11%) | |
| Tumor differentiation | <0.0001 | ||||||||||
| Well to moderate | 1286 (90%) | 214 (88%) | 234 (80%) | 37 (80%) | 77 (86%) | 28 (85%) | 81 (98%) | 298 (96%) | 103 (98%) | 214 (96%) | |
| Poor | 140 (9.8%) | 28 (12%) | 58 (20%) | 9 (20%) | 13 (14%) | 5 (15%) | 2 (2.4%) | 13 (4.2%) | 2 (1.9%) | 10 (4.5%) | |
| Mucinous component | <0.0001 | ||||||||||
| 0% | 836 (62%) | 116 (49%) | 138 (48%) | 18 (45 %) | 41 (48%) | 17 (52%) | 57 (71%) | 217 (75%) | 71 (75%) | 161 (79%) | |
| 1–49% | 340 (25%) | 82 (35%) | 93 (33%) | 10 (25%) | 27 (31%) | 12 (36%) | 16 (20%) | 52 (18%) | 19 (20%) | 29 (14%) | |
| ≥50% | 175 (13%) | 39 (16%) | 55 (19%) | 12 (30%) | 18 (21%) | 4 (12%) | 7 (8.8%) | 22 (7.6%) | 5 (5.3%) | 13 (6.4%) | |
| Signet ring cell component | <0.0001 | ||||||||||
| 0% | 1201 (89%) | 207 (88%) | 224 (79%) | 33 (83%) | 70 (82%) | 32 (97%) | 75 (94%) | 278 (96%) | 94 (99%) | 189 (93%) | |
| 1–49% | 123 (9.1%) | 27 (11%) | 50 (18%) | 7 (18%) | 12 (14%) | 1 (3.0%) | 5 (6.3%) | 10 (3.4%) | 1 (1.1%) | 10 (4.9%) | |
| ≥50% | 23 (1.7%) | 2 (0.9%) | 11 (3.9%) | 0 | 3 (3.5%) | 0 | 0 | 3 (1.0%) | 0 | 4 (2.0%) | |
(%) indicates the proportion of cases with a specific pathologic feature among cancers located in each subsite (cecum, ascending colon, hepatic flexure, transverse colon, splenic flexure, descending colon, sigmoid colon, rectosigmoid or rectum). P values were calculated by chi-square test.
Assessment of physical activity
Leisure-time physical activity has been assessed every two years. Subjects reported duration of participation (ranging from 0 to 11 or more hours per week) on walking (along with usual pace); jogging; running; bicycling; swimming laps; racket sports; other aerobic exercises; lower intensity exercise (yoga, toning, stretching); or other vigorous activities. Each activity on the questionnaire was assigned a metabolic equivalent task (MET) score. One MET is the energy expenditure for sitting quietly. MET scores are defined as the ratio of the metabolic rate associated with specific activities divided by the resting metabolic rate. The values from the individual activities were summed for a total MET-hours per week score.
Assessment of cigarette smoking and alcohol consumption
Cigarette smoking has been assessed every two years in both cohorts. Alcohol consumption was the sum of the values for three types of beverages: beer, wine, and spirits. We assumed an ethanol content of 13.1 g for a 12-ounce (38-dl) can or bottle of beer, 11.0 g for a 4-ounce (12-dl) glass of wine, and 14.0 g for a standard portion of spirits.
Histopathologic evaluations
Tissue sections from all colorectal cancer cases were reviewed by a pathologist (S.O.) unaware of other data. Tumor differentiation was categorized as well-moderate vs. poor (>50% vs. ≤50% glandular area). Extent of mucin and signet ring cells were recorded.
Sequencing of BRAF, KRAS and PIK3CA, and Microsatellite instability (MSI) analysis
DNA was extracted from tumor and PCR and Pyrosequencing targeted for BRAF (codon 600),[31] KRAS (codons 12 and 13),[32] and PIK3CA (exons 9 and 20) were performed as previously described.[33] MSI analysis was performed, using 10 microsatellite markers (BAT25, BAT26, BAT40, D2S123, D5S346, D17S250, D18S55, D18S56, D18S67 and D18S487).[30] MSI-high was defined as the presence of instability in ≥30% of the markers. MSI-low (1–29% unstable markers) tumors were grouped into microsatellite stable (MSS) tumors (no unstable markers) because those showed similar features.
Methylation analyses for CpG islands and LINE-1
Using real-time PCR (MethyLight[34]) on bisulfite-treated DNA,[35] we quantified DNA methylation in eight CIMP-specific promoters [CACNA1G, CDKN2A (p16), CRABP1, IGF2, MLH1, NEUROG1, RUNX3 and SOCS1].[9, 18, 36] CIMP-high was defined as the presence of ≥6/8 methylated promoters, and CIMP-low/0 as 0/8–5/8 methylated promoters, according to the previously established criteria.[18, 36] In order to accurately quantify methylation levels in LINE-1 repetitive elements, we utilized Pyrosequencing as previously described.[37, 38]
Analysis of gene expression
RNA was extracted and gene expression profiling was performed according to the complementary DNA-mediated annealing, selection, extension and ligation (DASL) assay (Illumina, San Diego, CA) as previously described.[39]
Statistical analysis
For all statistical analyses, we used SAS software (Version 9.1.3, SAS Institute, Cary, NC). All p values were two-sided. For categorical data, the chi-square test was performed. One-way ANOVA was used to compare mean age or mean LINE-1 methylation level across bowel subsites. Kruskal-Wallis test was used to compare the ABCB1 expression levels across bowel subsites.
To test linearity and non-linearity of the relationship of tumor location-molecular feature along bowel subsites, multivariate logistic regression analysis (or linear regression analysis for LINE-1 methylation level) was performed. First, a numeric subsite location variable which represented an average distance (cm) from anal verge to each subsite was made, utilizing recent CT (computed tomography) colonography data.[40] In the logistic or linear regression model with a tumor molecular variable as an outcome variable, a significant p value by the Wald test on the bowel subsite variable indicated a linear relationship of the molecular variable along the bowel subsites, but a non-linear relationship might be present. To test non-linearity of the relationship along the bowel subsites, we used likelihood ratio test (LRT) comparing the model with squared and/or cubic subsite variables to the model without squared or cubic subsite variable. With a significant p value by the Wald test (mentioned above), a non-significant LRT p value would support a linear relationship excluding non-linearity, while a significant LRT p value would indicate the presence of non-linearity. All logistic and linear regression models were adjusted for age (continuous), sex, year of diagnosis (continuous), family history of colorectal cancer in any first-degree relative (present vs. absent), body mass index (BMI; <30 vs. ≥30 kg/m2), physical activity (<18 vs. ≥18 MET-hours/week), smoking (never vs. former/current smokers), and alcohol consumption (no vs. <15 vs. ≥15 g/day). For cases with missing information in any of the covariates [family history of colorectal cancer (0.9%), BMI (0.8%), physical activity (5.1%), smoking (1.1%)], we included those cases in a majority category of a given covariate to avoid overfitting. We confirmed that excluding cases with missing information in any of the covariates did not substantially alter results (data not shown).
RESULTS
Colorectal cancer molecular features along bowel subsites
To assess the frequencies of various tumor molecular features along the bowel subsites (rectum, rectosigmoid, sigmoid colon, descending colon, splenic flexure, transverse colon, hepatic flexure, ascending colon, and cecum), we examined the database of 1443 colorectal cancer cases (excluding appendiceal cancers) in the two prospective cohort studies. Table 3 and Supplementary Tables 1–2 show the frequencies of various clinical, pathologic or molecular features along the bowel subsites in our subject population. The frequencies of CIMP-high, MSI-high, and BRAF mutation gradually increased from rectum (<2.3%) to ascending colon (36–40%) (Figure 1), supporting our hypothesis that these tumor molecular features might change gradually along the large bowel. There was no abrupt change at splenic flexure. Cecal cancers showed lower frequencies of CIMP-high, MSI-high, and BRAF mutation (12–22%) than ascending colon cancers. Notably, cecal cancers showed a higher frequency of KRAS mutations (52%) than any other sites (27–35%; p<0.0001).
Table 3.
Molecular characteristics of colorectal cancer according to tumor location bowel subsite
| Molecular feature | Total N | Cecum | Ascending colon | Hepatic flexure | Transverse colon | Splenic flexure | Descending colon | Sigmoid colon | Rectosigmoid | Rectum | P value |
|---|---|---|---|---|---|---|---|---|---|---|---|
| CIMP status | <0.0001 | ||||||||||
| CIMP-low/0 | 1010 (83%) | 160 (78%) | 152 (60%) | 24 (65%) | 54 (70%) | 24 (86%) | 68 (92%) | 266 (96%) | 85 (98%) | 177 (98%) | |
| CIMP-high | 208 (17%) | 44 (22%) | 102 (40%) | 13 (35%) | 23 (30%) | 4 (14%) | 6 (8.1%) | 10 (3.6%) | 2 (2.3%) | 4 (2.2%) | |
| MSI status | <0.0001 | ||||||||||
| MSS | 1061 (84%) | 163 (78%) | 165 (63%) | 27 (71%) | 64 (80%) | 25 (81%) | 70 (93%) | 275 (97%) | 87 (97%) | 183 (98%) | |
| MSI-high | 196 (16%) | 46 (22%) | 98 (37%) | 11 (29%) | 16 (20%) | 6 (19%) | 5 (6.7%) | 8 (2.8%) | 3 (3.3%) | 3 (1.6%) | |
| BRAF mutation | <0.0001 | ||||||||||
| (−) | 1093 (86%) | 186 (88%) | 172 (64%) | 25 (68%) | 62 (78%) | 25 (81%) | 68 (89%) | 276 (96%) | 90 (96%) | 189 (98%) | |
| (+) | 183 (14%) | 26 (12%) | 95 (36%) | 12 (32%) | 18 (23%) | 6 (19%) | 8 (11%) | 11 (3.8%) | 4 (4.3%) | 3 (1.6%) | |
| KRAS mutation | <0.0001 | ||||||||||
| (−) | 819 (64%) | 101 (48%) | 182 (68%) | 26 (70%) | 59 (73%) | 21 (66%) | 50 (66%) | 186 (65%) | 63 (68%) | 131 (68%) | |
| (+) | 458 (36%) | 111 (52%) | 85 (32%) | 11 (30%) | 22 (27%) | 11 (34%) | 26 (34%) | 101 (35%) | 30 (32%) | 61 (32%) | |
| PIK3CA mutation | 0.0016 | ||||||||||
| (−) | 962 (82%) | 146 (75%) | 191 (78%) | 31 (84%) | 62 (85%) | 18 (64%) | 57 (80%) | 220 (83%) | 77 (90%) | 160 (89%) | |
| (+) | 217 (18%) | 49 (25%) | 54 (22%) | 6 (16%) | 11 (15%) | 10 (36%) | 14 (20%) | 44 (17%) | 9 (10%) | 20 (11%) | |
| LINE-1 methylation level (mean ± SD) | |||||||||||
| 62.7 ± 9.5 | 63.7 ± 9.0 | 64.7 ± 9.4 | 62.4 ± 8.7 | 62.5 ± 10.0 | 61.9 ± 10.2 | 60.2 ± 11.7 | 61.3 ± 9.1 | 61.0 ± 10.1 | 63.2 ± 8.5 | 0.0003 | |
| ABCB1 expression level (log2 intensity) | |||||||||||
| Median (interquartile range) | 6.47 (6.35–6.81) | 6.46 (6.35–6.71) | 6.43 (6.35–6.73) | 6.43 (6.35–6.68) | 6.44 (6.35–6.67) | 6.48 (6.38–6.91) | 6.60 (6.36–6.84) | 6.51 (6.37–6.91) | 6.53 (6.35–6.82) | 6.51 (6.39–6.80) | 0.19 |
(%) indicates the proportion of cases with a specific molecular feature among cancers located in each subsite (cecum, ascending colon, hepatic flexure, transverse colon, splenic flexure, descending colon, sigmoid colon, rectosigmoid or rectum). P values were calculated by chi-square test, except for LINE-1 (one-way ANOVA test) and ABCB1 (Kruskal-Wallis test).
CIMP, CpG island methylator phenotype; MSI, microsatellite instability; MSS, microsatellite stable; SD, standard deviation.
Figure 1.
Frequencies of CIMP-high, MSI-high, and BRAF mutation in colorectal cancer along bowel subsites. The frequencies of these molecular features increase gradually from rectum to ascending colon. Formal multivariate statistical analyses for linearity and non-linearity were performed as described in MATERIALS AND METHODS and results are shown in Table 4.
CIMP, CpG island methylator phenotype; MSI, microsatellite instability.
Although there was no striking pattern of PIK3CA mutation frequency along bowel subsites, it was generally low in rectum and rectosigmoid (10–11%) and higher proximally (p=0.0016).
With regard to tumor LINE-1 methylation level [mean ± standard deviation (SD)], it gradually decreased from rectum (63.2 ± 8.5) to descending colon (60.2 ± 11.7), and then increased from descending colon to ascending colon (64.7 ± 9.4) (p=0.0003). Again, there was no abrupt change at splenic flexure.
There was no significant relationship between bowel subsites and ABCB1 expression level (p=0.19).
Considering the importance of molecular classification based on combined CIMP and MSI status,[41] we also examined the frequency of each CIMP/MSI subtype along bowel subsites (Figure 2). The frequency of CIMP-high MSI-high tumors increased gradually along the bowel subsites from rectum to ascending colon, while the frequency of CIMP-low/0 MSS tumors decreased from rectum to ascending colon. There was no abrupt change at splenic flexure.
Figure 2.
Frequencies of CIMP/MSI subtypes of colorectal cancer along bowel subsites. The frequency of CIMP-high MSI-high tumors increased gradually from rectum to ascending colon, while that of CIMP-low/0 MSS tumors decreased gradually from rectum to ascending colon.
CIMP, CpG island methylator phenotype; MSI, microsatellite instability; MSS, microsatellite stable.
Assessment of linearity of tumor location-molecular relationship
We assessed the linearity of tumor location-molecular relationship along the bowel subsites by multivariate logistic regression model (or linear regression model for LINE-1 methylation) (Table 4). In our multivariate analysis strategy, we could assess whether data presented in Table 3 and Figure 1 were independent of other variables. We used bowel subsite as a predictor (independent) variable, and a molecular feature as an outcome (dependent) variable. When we assessed the relationship between subsite (rectum to ascending colon) and CIMP, bowel subsite was significantly linearly associated with CIMP-high (p<0.0001). To assess non-linearity, we performed likelihood ratio test (LRT) comparing a model with squared and/or cubic subsite variable(s) to a model without squared or cubic variable. As a result, LRT yielded p>0.09, excluding non-linear relationship and supporting a linear relationship of bowel subsites with CIMP-high.
Table 4.
Assessment of linearity and non-linearity on subsite-molecular relationship in colorectal cancer by multivariate logistic or linear regression model
| Multivariate regression model | Outcome variable (molecular feature) | Bowel subsite variable (from rectum to ascending colon) | Squared subsite variable | Cubic subsite variable | Likelihood ratio test (LRT) | |||
|---|---|---|---|---|---|---|---|---|
| P value (Wald test) | Included | P value (Wald test) | Included | P value (Wald test) | degrees of freedom | P value^ | ||
| Logistic | CIMP | <0.0001 | No | - | No | - | - | Referent |
| 0.0017 | Yes | 0.17 | No | - | 1 | 0.17 | ||
| 0.68 | Yes | 0.15 | Yes | 0.096 | 2 | 0.098 | ||
| Logistic | MSI | <0.0001 | No | - | No | - | - | Referent |
| 0.020 | Yes | 0.56 | No | - | 1 | 0.56 | ||
| 0.93 | Yes | 0.48 | Yes | 0.42 | 2 | 0.61 | ||
| Logistic | BRAF mutation | <0.0001 | No | - | No | - | - | Referent |
| 0.0041 | Yes | 0.26 | No | - | 1 | 0.26 | ||
| 0.56 | Yes | 0.76 | Yes | 0.63 | 2 | 0.47 | ||
| Logistic | KRAS mutation | 0.66 | No | - | No | - | - | Referent |
| 0.48 | Yes | 0.42 | No | - | 1 | 0.42 | ||
| 0.16 | Yes | 0.19 | Yes | 0.23 | 2 | 0.35 | ||
| Logistic | PIK3CA mutation | 0.0034 | No | - | No | - | - | Referent |
| 0.070 | Yes | 0.20 | No | - | 1 | 0.20 | ||
| 0.096 | Yes | 0.23 | Yes | 0.30 | 2 | 0.26 | ||
| Linear | LINE-1 methylation level | 0.020 | No | - | No | - | - | Referent |
| 0.0070 | Yes | 0.0006 | No | - | 1 | 0.0036 | ||
| 0.036 | Yes | 0.0022 | Yes | <0.0001 | 2 | <0.0001 | ||
A multivariate regression model included age, sex, year of diagnosis, family history of colorectal cancer, body mass index, physical activity, smoking, alcohol consumption and the bowel subsite variable with or without the squared and cubic subsite variables, as indicated in the table.
A significant p value by the likelihood ratio test (LRT) indicates a non-linearity, and a combination of insignificant p values by LRT and a significant p value by Wald test on the subsite variable in the model without the squared or cubic location variable indicates a linear relationship.
CIMP, CpG island methylator phenotype; LRT, likelihood ratio test; MSI, microsatellite instability.
When we assessed the relationship between subsite (rectum to ascending colon) and MSI (or BRAF mutation) by logistic regression models (Table 4), results were similar to those on the relationship between bowel subsite and CIMP. Tumor location bowel subsite (from rectum to ascending colon) was significantly linearly associated with MSI-high or BRAF mutation (p<0.0001). In addition, bowel subsite was also linearly associated with PIK3CA mutation (p=0.0034). When assessing non-linearity, LRT comparing a model with squared and/or cubic subsite variable(s) to a model without squared or cubic variable yielded non-significant p values (p>0.19), excluding non-linearity and supporting a linear relationship between subsite and MSI (or BRAF mutation or PIK3CA mutation).
To exclude a potential influence of differential selection bias due to preoperative treatment for rectal cancers, we excluded cancers in rectum and rectosigmoid, and performed a linearity test. Tumor location bowel subsite (sigmoid colon to ascending colon) was significantly linearly associated with CIMP-high, MSI-high, or BRAF mutation (p<0.0001), but not with PIK3CA mutation (p=0.13), and there was no evidence for non-linearity (LRT p>0.05).
DISCUSSION
We performed this study to test the hypothesis that molecular features of colorectal cancer change gradually along bowel subsites, rather than change abruptly at splenic flexure. Accumulating evidence suggests that proximal colon cancers differ in clinical, pathologic and molecular features from distal cancers.[22–25] However, it has remained uncertain whether those features change abruptly at splenic flexure. Utilizing the tumor database in the two prospective cohort studies, our current study is unique in examining tumor molecular features along the detailed bowel subsites (rectum, rectosigmoid, sigmoid colon, descending colon, splenic flexure, transverse colon, hepatic flexure, ascending colon, and cecum). Notably, we found that the frequencies of CIMP-high, MSI-high, and BRAF mutation increased (statistically) linearly along the bowel from rectum to ascending colon. These data support our hypothesis of gradual changes in tumor molecular features along the bowel subsites, rather than abrupt changes at splenic flexure. Importantly, our hypothesis and data are not inconsistent with repeated observations of differences in molecular features (such as CIMP and MSI) between proximal colon cancer and distal colorectal cancer,[22–25] so long as molecular features change along the bowel subsites.
Examining molecular changes in colorectal neoplasias is increasingly important for better understanding of the carcinogenic process.[42–44] In the past decades, colorectal cancers were typically divided into 3 compartments, rectum, distal colon (sigmoid to splenic flexure) and proximal colon (transverse colon to cecum) in most clinical, pathologic and epidemiologic publications.[1–3] As a result, our epidemiologic, clinical and molecular pathologic knowledge on colorectal cancer in detailed bowel subsites is currently deficient. Therefore, our data demonstrating gradual changes in tumor molecular features along the bowel may have considerable implications in clinical, epidemiologic and pathologic research. We would propose that future studies on colorectal neoplasia should include information on detailed bowel subsites (beyond proximal colon, distal colon and rectum), which will further improve our understanding of the mechanisms of colorectal carcinogenesis.
Colorectal epithelial cells are constantly in contact with bowel contents, which may play a critical role in cellular transformation and tumor development and progression. Bowel contents (food debris, microbiome and bacterial fermentation products) and their interactions with host cells (epithelial and immune cells) may directly cause cellular molecular changes, or alternatively, may influence tumor progression differentially according to molecular features in pre-neoplastic or pre-malignant cells.[45, 46] In fact, bowel contents gradually change along the bowel subsites, and this fact may explain why tumor molecular features change gradually along the bowel subsites. In support of this hypothesis, studies on synchronous primary colorectal cancers have shown that CIMP-high (or MSI-high or BRAF-mutated) proximal cancer may coexist with CIMP-negative (or MSS or BRAF-wild-type) distal cancer,[47–50] and another study has shown a gradual gradient of CpG island methylation along normal bowel mucosa.[51] Together with these data, our current study supports the role of bowel contents in predisposing colon epithelial cells to certain molecular insults. However, further investigations such as identifying components of bowel contents or factors participating in the host-bacterial interactions are needed to understand how colorectal cancer develops.
The ATP-binding cassette (ABC) transporters constitute a large family of active transporter molecules, and play a role in the process of absorption. Because of the diverse substrates that can be transported, ABC proteins are found to be expressed in a number of specialized cell types.[52] ABCB1 has been known to play a critical role in host-bacterial interactions in the gastrointestinal tract,[53] and has been implicated in colorectal cancer development and progression.[54] Potocnik et al.[55] have shown that ABCB1 gene polymorphisms may be associated with MSI-high cancer. Although our current study did not show that bowel subsite was significantly associated with ABCB1 expression in colorectal cancer, ABC transporters may play roles in modifying risks of colorectal epithelial cells for neoplastic transformation/progression differentially according to cellular molecular status.
Interestingly, our data indicate that cecal cancers have unique molecular features different from cancers in other subsites. The frequency of KRAS mutation was highest in cecal cancers among all subsites. In addition, for the relations of bowel subsites with the frequencies of CIMP-high, MSI-high and BRAF mutation, cecal cancers did not follow the trend of the increase from rectum to ascending colon. Kucherlapati et al. have shown that loss of Rb1 in the gastrointestinal tract of Apc1638N mice promotes cecal tumor formation.[56] Loss of RB1 (retinoblastoma protein) has been found specifically in cecal cancers.[57] Taken together, cecal cancer may arise through somewhat unique carcinogenic mechanisms different from cancers in other subsites.
There are advantages in utilising the database of the two U.S. nationwide prospective cohort studies to study molecular features of colorectal cancer along bowel subsites. Our large database readily enabled us to examine the frequencies of various molecular features in cancers in each bowel subsite with adequate statistical power, and test linearity of the molecular relations along the bowel subsites while adjusting for patient and clinical characteristics. In addition, cohort participants who developed cancer resided throughout the U.S., and thus were more representative colorectal cancer cases in the general U.S. population than highly-selected patients in one to a few academic hospitals. These facts increase generalisability of our study findings.
One limitation of our study is that a vast majority (94%) of our cohort participants were non-Hispanic Caucasians. Thus, it remains to be seen whether our findings can be applicable to other racial or ethnic groups. As another limitation, rectal cancer is commonly treated by preoperative radiation, which could cause bias or artifacts. Thus, we collected pretreatment biopsy materials to overcome this issue. In addition, as a secondary analysis, we excluded rectal and rectosigmoid cancers, and we obtained similar findings of statistically linear increases in the frequencies of CIMP-high, MSI-high and BRAF mutation from sigmoid colon to ascending colon.
In summary, our data suggest that the frequencies of CIMP-high, MSI-high and BRAF mutation in colorectal cancer do not change abruptly at splenic flexure. Instead, the frequencies of CIMP-high, MSI-high, and BRAF mutation appear to gradually (statistically linearly) increase along the bowel from rectum to ascending colon. In addition, cecal cancers represent a unique subtype characterized by high frequency of KRAS mutation, and cecal cancers do not follow the linearity trend in terms of CIMP, MSI and BRAF mutation. Our novel data indicate that future studies on colorectal cancers or neoplasias should include information on detailed bowel subsites (beyond proximal colon, distal colon and rectum), which will further improve our understanding of the mechanisms of colorectal carcinogenesis.
Supplementary Material
Significance of this study.
What is already known about this subject?
Colorectal cancer is typically classified into rectal, distal colon, and proximal colon cancers.
Proximal colon cancers and distal cancers differ in clinical, pathologic and molecular features.
Although it remains uncertain whether colorectal cancer molecular features change abruptly at splenic flexure, some investigators believe that there are distinct molecular features of proximal tumors and distal tumors.
What are the new findings?
The frequencies of CIMP-high, MSI-high, and BRAF mutation in colorectal cancer increase gradually (statistically linearly) along the bowel from rectum to ascending colon, rather than abruptly change at splenic flexure.
Cecal cancers represent a unique subtype characterized by a high frequency of KRAS mutation, and cecal cancers do not follow the linearity trend in terms of the frequencies of CIMP-high, MSI-high and BRAF mutation.
Mean tumor LINE-1 methylation levels show non-linear changes along the bowel subsites, and do not show an abrupt change at splenic flexure.
How might it impact on clinical practice in the foreseeable future?
Over the past decades, most clinical, translational, and epidemiologic studies have gathered and published colorectal tumor location data as proximal colon vs. distal colon (vs. rectum). Future studies on colorectal neoplastic diseases should include information on detailed bowel subsites (beyond proximal colon, distal colon and rectum), which will further improve our understanding of the mechanisms of colorectal carcinogenesis.
Acknowledgments
We 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.
FUNDING
This work was supported by U.S. National Institute of Health grants [P01CA87969 (to S.E. Hankinson), P01CA55075 (to W.C. Willett), P50CA127003 (to C.S.F.), R01CA151993 (to S.O.), and R01CA137178 (to A.T.C)]; the Bennett Family Fund for Targeted Therapies Research; and the Entertainment Industry Foundation through National Colorectal Cancer Research Alliance. T.M. was supported by a fellowship grant from the Japan Society for Promotion of Science. The content is solely the responsibility of the authors and does not necessarily represent the official views of NCI or NIH. Funding agencies did not have any role in the design of the study; the collection, analysis, or interpretation of the data; the decision to submit the manuscript for publication; or the writing of the manuscript.
Abbreviations
- ANOVA
analysis of variance
- CIMP
CpG island methylator phenotype
- HPFS
Health Professionals Follow-up Study
- LRT
likelihood ratio test
- MET
metabolic equivalent task
- MSI
microsatellite instability
- MSS
microsatellite stable
- NHS
Nurses’ Health Study
- SD
standard deviation
Footnotes
Competing interests: None
Author contribution
SO conceived the study. All authors contributed to data acquisition, analyses and interpretations. MY, TM, AK, SO drafted the manuscript. All authors critically revised the manuscript. All authors approved the final version. ATC, CSF, SO provided funding support.
The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, an exclusive licence (or non exclusive for government employees) on a worldwide basis to the BMJ Publishing Group Ltd and its Licensees to permit this article (if accepted) to be published in Gut editions and any other BMJPGL products to exploit all subsidiary rights, as set out in our licence.
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