| Literature DB >> 32723394 |
Achraf El Asri1,2, Btissame Zarrouq3,4, Khaoula El Kinany3, Laila Bouguenouch5, Karim Ouldim5,6, Karima El Rhazi3.
Abstract
BACKGROUND: Between 30 and 50% of colon tumors have mutations in the Kirsten-ras (KRAS) gene, which have a large nutritional attributable risk. Despite its high frequency in colorectal cancer (CRC), data to support specific associations between KRAS mutations in CRC and diet are sparse. Here, we conducted a systematic review to summarize the current epidemiological evidence on the association between various dietary factors and KRAS mutations.Entities:
Keywords: Colorectal cancer; Diet; Foods; KRAS mutations; Nutrients
Year: 2020 PMID: 32723394 PMCID: PMC7388532 DOI: 10.1186/s12885-020-07189-2
Source DB: PubMed Journal: BMC Cancer ISSN: 1471-2407 Impact factor: 4.430
Fig. 1Flow diagram of process of systematic literature search in accordance with PRISMA guidelines
Quality assessment of published papers on nutritional factors and KRAS mutations in colorectal cancer worldwide
| Author, Year, and Reference Number | Relevant to This Review | Aims Clearly Stated | Appropriate Study Method | Sample Representative of Target Population | Confounding and Bias Considered | Good Response Rate | Were Questions Piloted | Were Tables and Figures Understandable | Can Results Be Applied to Local Situation? | Accepted as Type IV Evidence |
|---|---|---|---|---|---|---|---|---|---|---|
| He et al., 2019 [ | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No (Type III) |
| Keum et al., 2019 [ | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No (Type III) |
| Mehta et al., 2017 [ | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No (Type III) |
| Carr et al., 2017 [ | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No (Type III) |
| Hogervorst et al., 2014 [ | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No (Type III) |
| Jung et al., 2014 [ | Yes | Yes | Yes | No | Yes | Yes | Yes | Yes | Yes | No (Type III) |
| Gilsing et al., 2013 [ | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No (Type III) |
| Kamal et al., 2012 [ | Yes | Yes | Yes | No | No | Yes | No | Yes | Yes | No (Type III) |
| Razzak et al., 2012 [ | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No (Type III) |
| Ottini et al., 2011 [ | No | Yes | Yes | No | – | – | – | – | No | No (Type V) |
| Naguib et al., 2010 [ | Yes | Yes | Yes | No | No | Yes | Yes | Yes | No | No (Type V) |
| Slattery et al., 2010 [ | Yes | Yes | Yes | No | Yes | No | Yes | Yes | Yes | No (Type III) |
| Schernhammer et al., 2008 [ | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No (Type III) |
| Weijenberg et al., 2007 [ | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No (Type III) |
| Bongaerts et al., 2006 [ | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No (Type III) |
| Wark et al., 2006 [ | Yes | Yes | Yes | No | Yes | Yes | Yes | Yes | Yes | No (Type III) |
| Brink et al., 2005 [ | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No (Type III) |
| Brink et al., 2005 [ | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No (Type III) |
| Brink et al., 2004 [ | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No (Type III) |
| Howsam et al., 2004 [ | Yes | Yes | Yes | No | Yes | Yes | Yes | Yes | Yes | No (Type III) |
| Laso et al., 2004 [ | Yes | Yes | Yes | No | No | Yes | Yes | Yes | Yes | No (Type III) |
| Slattery et al., 2002 [ | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No (Type III) |
| Slattery et al., 2001 [ | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No (Type III) |
| Slattery et al., 2000 [ | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No (Type III) |
| Kampman et al., 2000 [ | Yes | Yes | Yes | No | Yes | Yes | Yes | Yes | Yes | No (Type III) |
| O’Brien et al., 2000 [ | Yes | Yes | Yes | No | No | Yes | Yes | Yes | Yes | No (Type V) |
| Martinez et al., 1999 [ | Yes | Yes | Yes | No | Yes | Yes | Yes | Yes | No | No (Type V) |
| Bautista et al., 1997 [ | Yes | Yes | Yes | No | Yes | Yes | Yes | Yes | Yes | No (Type III) |
Main results of included studies
| Author, Year, and Reference | Study Design | Country and Setting | Sample size | Ethnicity | Main Focus | Relevant Exposures | Confounder Factors | Comparison Groups | Main Findings and Effects |
|---|---|---|---|---|---|---|---|---|---|
| He et al., 2019 [ | Two large prospective cohort studies: Nurses’ Health Study (NHS), 1980–2012) and Health Professionals Follow-up Study (HPFS), (1986–2012). | USA: - Nurses’ Health Study (NHS): 11 US States (California, Connecticut, Florida, Maryland, Massachusetts, Michigan, New Jersey, New York, Ohio, Pennsylvania, and Texas). - Health Professionals Follow-up Study (HPFS): 50 US states. | - A total of 138,793 participants were included: 90,869 from the NHS and 47,924 from the HPFS. - 1337 cases with data for KRAS Mutation. | Unspecified | Dietary intake of fiber, whole grains and risk of colorectal cancer. | - Total fiber (per 5 g/day) - Cereal fiber (per 5 g/day) - Fruit fiber (per 5 g/day) - Vegetable fiber (per 5 g/day) - Whole grain (per 20 g/day). | Age, family history of CRC, history of lower gastrointestinal endoscopy, smoking, body mass index, physical activity, alcohol intake, regular aspirin use, regular multivitamin use, total folate intake, calcium intake, vitamin D intake, glycemic load, processed red meat intake, hormone use. | - Group I: KRAS+ - Group II: KRAS- | No association |
| Keum et al.,2019 [ | Two ongoing prospective cohort studies: the Nurses’ Health Study (NHS) (1980–2010), and the Health Professionals Follow-up Study (HPFS) (1986–2010). | USA: - NHS: 11 US States. - HPFS: 50 US states. | - 88,506 women and 47,733 men. - 853 colon cancer cases. | Unspecified | Calcium intake and colon cancer risk subtypes by tumor molecular characteristics. | Total calcium intake (mg/day). | Age, questionnaire cycle, sex; Caucasian (yes vs. no), family history of colorectal cancer, history of sigmoidoscopy/colonoscopy, regular aspirin use, smoking, BMI, physical activity, 25-hydroxyvitamin D scores, intakes of energy, alcohol, red and processed meat and folate. | - Group I: KRAS+ - Group II: KRAS- | No association |
| Mehta et al., 2017 [ | Two ongoing cohorts, the Health Professionals Follow-up Study (HPFS) and the Nurses’ Health Study (NHS). | USA: - NHS: 11 US States. - HPFS: 50 US states. | - 137,217 participants (47,449 men and 89,768 women). - 1285 tumors for KRAS mutation status. | Unspecified | Western and prudent dietary patterns and risk of CRC. | Western and prudent dietary patterns score. | Age, sex, CRC family history, history of previous lower gastrointestinal endoscopy, smoking, body mass index, physical activity, NSAID, and total caloric intake. | - Group I: KRAS+ - Group II: KRAS- | No association with tumors harboring KRAS mutation. |
| Carr et al., 2017 [ | Case–control study | Southwest of Germany | - 2449 cases and 2479 controls. | Unspecified | Associations of red and processed meat intake with major molecular pathological . | Red and processed meat (frequency: times/day). | Age, sex, school education, BMI, family history of colorectal cancer, history of large–bowel endoscopy, participation in health checkup, smoking, ever regular use of NSAIDs, fruit intake, and wholegrain intake. | - Group I: KRAS+ - Group II: KRAS- | Positive association with higher red and processed meat intake and KRAS mutation (OR > 1 time/day vs ≤ 1 time/week: 1.49, 95% CI 1.09–2.03). |
| Hogervorst et al., 2014 [ | Case cohort study embedded in the Netherlands Cohort Study on diet and cancer (NLCS). | Netherlands (204 municipalities with computerized population registries). | - 120,852 participants (58,279 men + 62,573 women) - Subcohort ( - 733 CRC cases were available for the molecular analysis. | Unspecified | Acrylamide and CRC risk characterized by mutations in | - Acrylamide intake (g/day). | Age, smoking, BMI, family history of CRC, total energy intake. | - Group I: - Group II: | - Positive association with acrylamide intake among men (HR [4th quartile vs. 1st] = 2.12; 95% CI, 1.16–3.87; |
| Jung et al., 2014 [ | Two cohorts, the Health Professionals Follow-up Study (HPFS) and the Nurses’ Health Study (NHS) (1986–2008). | USA: - NHS: 11 US States. - HPFS: 50 US states. | - 140,418 participants. - 1059 incident CRC cases with tumor molecular data. | Unspecified | Association between vitamin D and CRC risk. | - Predicted vitamin D score (ng/mL) | Age, sex, family, history of endoscopy, aspirin use, smoking, intake of total fruits and vegetables, total calories. | - Group I: - Group II: | Negative association between higher predicted vitamin D score and |
| Gilsing et al., 2013 [ | Cohort Study initiated in September 1986. | Netherlands (204 municipalities with computerized population registries). | - Case subjects were enumerated from the entire cohort (120,852 men and women). - the accumulated person years of the entire cohort were estimated from a random subcohort of 5000 men and women. - 733 CRC cases were available for the molecular analysis. | Unspecified | Dietary heme iron intake and risk of CRC with mutations in | - Heme iron intake (g/day) | Age, sex, BMI, family history of CRC, smoking, nonoccupational physical activity, total energy intake, alcohol consumption, total vegetable consumption | - Group I: wild-type - Group II: activating mutant | Positive association with heme iron intake (HR = 1.71; 95% CI, 1.15–2.57; |
| Kamal et al., 2012 [ | Retrospective cohort study | Egypt. Kasr El Aini Hospital, Cairo University. | 80 CRC patients (56 males and 24 females). | Unspecified | Associations between | - Meat, green leafy vegetables, tea, and coffee at < 3 times/week versus more than 3 times/week. - Red blood cell folic acid (ng/mL). | not mentioned | - Group I: - Group II: | Potential link between folic acid and - OR for folic acid was 0.983 for each 1 ng/mL higher folate. |
| Razzak et al., 2012 [ | Cohort study from the Iowa Women’s Health Study. | Iowa, USA. | - - 514 incident CRC cases were available for the molecular marker assays. | Caucasian women. | Associations between dietary folate, vitamin B6, vitamin B12, and methionine with different pathways in CRC. | - Folate (μg/day) - Vitamin B6 (mg/day) - Vitamin B12 (μg/day) - Methionine (g/day). | Age,, BMI, waist-to-hip ratio, smoking status, exogenous estrogen use, physical activity level, and daily intake of total energy, total fat, sucrose, red meat, calcium, methionine, vitamin E, alcohol. | - Group I: - Group II: | None of the dietary exposures were associated with |
| Ottini et al., 2011 [ | Case study | Italy | 1 individual (King Ferrante I of Aragon). | Caucasian | Explanation of the death of King Ferrante I | Carbon (δ-13C) and nitrogen (δ-15N) isotope analysis. | not mentioned | – | Possible abundance of dietary carcinogens, related to meat consumption, could explain |
| Naguib et al., 2010 [ | Case series. | Norfolk, United Kingdom. | −25,639 from The EPIC Norfolk cohort (1993–1997). - 202 CRC cases were tested for Kras mutations. | Unspecified | Associations between | - Alcohol (g/day) - Meat (g/day), including red meat, red processed meat, white meat, white fish, fatty fish - Fruit and vegetables - Fat, total fat, PUFA, MUFA, SFA -Vitamins B2, B3, B6, B9, B12, C, and D - Fiber and macronutrients: total energy (MJ/day), carbohydrates (g/day), protein (g/day), nonstarch polysaccharide (g/day), calcium (mg/day). | Not mentioned | - Group I: Patients with - Group II: Patients with | - - |
| Slattery et al., 2010 [ | Case control study of participants in Kaiser Permanente Medical Care Program study | Northern California and Utah, USA. | - 951 cases - 1205 controls | 82% white, non-Hispanic, 4.1% African American, 7.6% Hispanic, 4.6% Asian, 0.7% American Indian, and 1% multiple races/ethnicity. | Diet, physical activity, and body size associations with rectal tumor mutations and epigenetic changes. | - Foods and dietary patterns involving dairy high fat, low fat, fruit, vegetables, red meat, fish, whole grains, refined grains, Western diet, prudent diet. - Nutrients: calories, PUFA, MUFA, SFA, trans fats, omega-3 fats, animal protein, vegetable protein, carbohydrates, dietary fiber. | Age, sex, recent aspirin use, long-term activity level, pack-years of cigarette smoking, dietary calcium, energy intake. | - Group I: CpG Island methylator phenotype CIMP+ - Group II: TP53 mutation - Group III: - Group IV: controls. | - High levels of vegetable intake reduced risk of KRAS mutations (OR = 0.60; 95% CI, 0.40–0.89; - Dietary fiber was associated with reduced risk of KRAS rectal tumor mutations - Prudent dietary pattern significantly reduced the - No significant result for the other factors. |
| Schernhammer et al., 2008 [ | Two prospective cohort studies: NHS and HPFS. | USA: - NHS: 11 US States. - HPFS: 50 US states. | - 88,691 women and 47,371 men. - 669 incident cases of CRC were available for the molecular analysis. | Unspecified | Association between dietary folate intake, vitamin B, and incidence of | - Folate (μg/day). | Age, sex, energy intake, screening sigmoidoscopy, family history, aspirin use, smoking, physical activity, BMI in 5 categories, colon polyps, beef intake, calcium intake, multivitamin use, alcohol use, and intake of vitamin B6, B12, and methionine. | - Group I: - Group II: | Low folate and vitamin B6 intakes were associated an increased risk of colon cancer, but these effects did not differ significantly by |
| Weijenberg et al., 2007 [ | Cohort study: Netherlands Cohort Study on diet and cancer (NLCS). | Netherlands (204 municipalities with computerized population registries). | - 531 incident cases of CRC were available for the molecular analysis. | Unspecified | Baseline fat intake versus risk of colon and rectal tumors with some gene alterations. | - Fat variables (g/day), including total fat, SFA, MUFA, PUFA, linolenic acid, linoleic acid. | Age, sex, BMI, family history of CRC, daily energy intake, daily linoleic acid intake, daily calcium intake, smoking. | - Group I: colon cancer with no gene aberrations - Group II: colon cancer with activating | - No association with total, saturated, MUFA, and PUFA - Linoleic acid showed a positive association with |
| Bongaerts et al., 2006 [ | Prospective Cohort study: Netherlands Cohort Study on diet and cancer (NLCS). | Netherlands (204 municipalities with computerized population registries). | - The cohort included 58,279 men and 62,573 women. - 578 incident cases of CRC were available for the molecular analysis. | Unspecified | Associations between consumption of alcohol and alcoholic beverages and risk of CRC without and with specific | - Alcohol consumption: total alcohol (g/day), beer (glasses/week), wine (glasses/week), liquor (glasses/week). | Age, family history of CRC, BMI, calcium intake, linoleic intake, smoking, total alcohol consumption. | - Group I: colon cancer, - Group II: colon cancer, - Group III: rectal cancer, - Group IV: rectal cancer, - Men and women analyzed separately. | - No association between alcohol and - Positive association with beer drinking (RR: 3.48; 95% CI, 1.1–11.0). |
| Wark et al., 2006 [ | Case-control study | Netherlands (outpatient clinics of 10 hospitals). | - 658 cases - 709 controls | Unspecified | Associations between diet, lifestyle, and | - Foods (g/day): dairy products, red meat, tea - Macronutrients (g/day): total dietary fat, PUFA, MUFA, protein - Micronutrients (mg/day): calcium, vitamin B2. | Sex, age, total energy. | - Group I: patients with - Group II: patients with - Group III: controls. | No significant results: - Red meat OR = 1.70 (95% CI, 0.94–3.09), potential risk, not statistically significant result - Total dietary fat OR = 0.55 (95% CI, 0.28–1.06) - PUFA OR = 0.58 (95% CI, 0.31–1.10) - No differences versus risk of KRAS adenomas could be detected for other factors. |
| Brink et al., 2005 [ | Cohort study: Netherlands Cohort Study on diet and cancer (NLCS). | Netherlands (204 Dutch municipalities with computerised population registries). | − 2948 subcohort members. − 608 incident colon and rectal cancer cases were available for the molecular analysis. | Unspecified | Association between meat and | Meat (g/day): total fresh meat, beef, pork, minced meat, liver, chicken, other meat, meat product, fish. | Age, sex, Quetelet Index, smoking, energy intake, family history of CRC. | - Group I: patients with - Group II: patients with G > C or G > T activating - Group III: patients with G > A activating - Group IV: patients with | - For meat products, positive association shown (RR for highest vs lowest quartile of intake = 2.37; 95% CI, 0.75–7.51; - No clear associations were observed for total fresh meat, different types of fresh meat, meat products, and fish. |
| Brink et al., 2005 [ | Cohort study: Netherlands Cohort Study on diet and cancer (NLCS). | Netherlands (204 municipalities with computerized population registries). | - 3048 Subcohort members (1475 men and 1573 women). - 608 incident CRC cases were available for the molecular analysis. | Unspecified | Association between dietary folate and specific | - Folate (μg /day). | Age, sex, BMI, smoking, alcohol, fresh meat, energy intake, family history of CRC, vitamin C, iron, fiber. | - Group I: colon cancer, - Group II: colon cancer, - Group III: rectal cancer, - Group IV: rectal cancer, | - For women: folate intake was associated with an increased risk of - For men: folate intake was associated with decreased risk of |
| Brink et al., 2004 [ | Cohort study: Netherlands Cohort Study on diet and cancer (NLCS). | Netherlands (204 municipalities with computerized population registries). | - 2948 Subcohort members. - 608 incident CRC cases were available for the molecular analysis. | Unspecified | Associations between dietary intake of various fats and specific | Fat variables (g/day): - Total fat - SFA - MUFA - PUFA - Linolenic acid - Linoleic acid. | Age, sex, Quetelet Index, smoking, energy intake, family history of CRC. | - Group I: colon cancer, - Group II: colon cancer, - Group III: rectal cancer, - Group IV: rectal cancer, | - No association with intake of total fats, SFA, and MUFA - Positive association with high intake of PUFA and linoleic acid (RRs for 1 SD of increase of PUFA and linoleic acid = 1.21; 95% CI, 1.05–1.41; and 1.22; 95% CI, 1.05–1.42). |
| Howsam et al., 2004 [ | Case control study | Barcelona, Catalonia, Spain. | Subsample of cases ( | Unspecified | Association between risk of CRC and exposure to organochlorine compounds. | Different types of organochlorines: - p,p’-DDE (low, medium, high) - α-HCH (low, medium, high) - PCB-28 (low, medium, high) - PCB-118 (low, medium, high). | Age, sex, BMI, energy intake. | - Group I: - Group II: | - Exposure to mono-ortho PCB-28 and PCB-118 increased risk of tumor - PCB-28 OR = 2.83 (95% CI, 1.13–7.06). - PCB-118 OR = 1.64 (95% CI, 0.67–4.01). |
| Laso et al., 2004 [ | Case-control study | Catalonia, Spain. | - 246 cases - 296 controls | Unspecified | Association between specific micronutrient intake and CRC and | - Fiber (g/day) - Folate (μg/day) - Vitamins A (μg/day), B1 (mg/day), D (μg/day), E (mg/day) - Potassium (mg/day) - Calcium (mg/day) - Iron (g/day) | Not mentioned | - Group I: control - Group II: patients with CRC - Group III: patients with | - Low intake of vitamin E (OR = 2.3; 95%CI, 1.2–4.6) - Low intake of vitamin D OR = 2 (95% CI, 1.1–4.2) - Low intake of vitamin B1 OR = 2.5 (95% CI, 1.2–5.1) - Low intake of vitamin A OR = 2.5 (95% CI, 1.2–5.1) - Low intake of folate OR = 2 (95% CI, 1.1–3.9) - Low intake of fiber OR = 2.7 (95% CI, 1.4–5.1) - Low intake of calcium OR = 2.3 (95% CI, 1.1–4.6) - Low intake of vitamin A OR = 2.5 (95% CI, 1.2–5.1). |
| Slattery et al., 2002 [ | Case-control study | USA: Northern California, Utah, Minnesota. | - 1836 cases - 1958 controls | white, African-American Hispanic | Association between GSTM-1 and NAT2 and colon tumors | -Cruciferous vegetables (high, intermediate, low) -Red meat frequency/day (< 0.86, 0.86–3.5, > 3.5) | Age, sex. | - Group I: - Group II: - Group III: | No significant result: - Red meat OR = 0.7 (95% CI, 0.5–1.1) - Cruciferous vegetable OR = 0.7 (95% CI 0.5–1.2) |
| Slattery et al., 2001 [ | Case-control study | USA: Northern California, Utah, Minnesota. | - 1428 cases - 2410 control | White African American Hispanic | Association between lifestyle factors and | - caffeine (low, intermediate, and high) - Western diet and prudent diet patterns (low, intermediate, and high). | Age. | - Group I: patients with - Group II: patients with - Group III: controls. | - For Western diet pattern, low OR = 1.0, intermediate OR = 1.2 (95% CI, 0.95–1.6), and high OR = 1.5 (95% CI, 1.2–1.9) - Prudent diet pattern showed no clear association. |
| Slattery et al., 2000 [ | Case-control study | USA: Northern California, Utah, Minnesota. | - 1836 cases - 1958 controls | African-American, white, Hispanic. | Associations between dietary intake and | - Dietary fat (g/1000 kcal): fat, SFA, MUFA, PUFA, cholesterol - Insulin-related factors: Carbohydrate (g/1000 kcal), Refined grains (servings/day) - DNA methylation factors: folate (mg/1000 kcal), vitamin B6 (mg/1000 kcal), methionine (g/1000 kcal), alcohol (g/day) - Carcinogen detoxification: cruciferous vegetables. | Age, sex, energy intake, BMI, physical activity, dietary calcium, fiber. | - Group I: patients with - Group II: patients with - Group III: controls. | Low levels of vegetables OR = 0.6 (95% CI, 0.4–0.9; |
| Kampman et al., 2000 [ | Case control study | Netherlands | - 204 cases - 259 controls | Caucasian | Associations between animal product and | - Foods: total red meat, beef, processed meat, poultry, fish, dairy products - Nutrients: total fat, SFA, cholesterol, total protein, animal protein, calcium. | Age, sex, total energy intake | - Group I: patients with - Group II: patients with - Group III: controls. | - Animal protein OR = 1.5 (95% CI, 1–2.1) for codon 12 but OR = 0.4 (95% CI, 0.2–1) for codon 13 - Calcium OR = 1.2 (95% CI, 0.9–1.6) for codon 12 but OR = 0.6 (95% CI, 0.3–1.2) for codon 13. |
| O’Brien et al., 2000 [ | Case series | Norwich, United Kingdom. | 51 participants (26 males and 26 females). | Unspecified | Associations between | Red meat (g/day) | - Group I: - Group II: | No correlation between | |
| Martinez et al., 1999 [ | Case series | USA: Phoenix metropolitan area, Arizona. | 678 participants | 96% were white. | Associations between variables known or suspected to be related to risk of CRC and occurrence of | -Total fat, SFA, dietary fiber, red meat, alcohol (g/day) - Dietary calcium, total calcium, dietary folate, total folate (mg/day). | Age, sex, energy intake. | - Group I: - Group II: | - Only intake of total folate was associated with |
| Bautista et al., 1997 [ | Case control study | Spain, Island of Majorca. | - 286 cases and 295 controls. - 106 CRC cases were available for the molecular analysis. | Unspecified | Possible associations between dietary factors and KRAS mutation in CRC tumors | - Total fats, PUFA, MUFA, SFA - calcium | Age, physical activity, number of meals, total caloric intake; fats were also adjusted for calcium, and calcium was adjusted for MUFA | - Group I: KRAS+ - Group II: KRAS- - Group III: controls | -High calcium intake was associated with a decreased risk of KRAS-mutated tumors (OR = 0.36; 95% CI, 0.14–0.97) - No association between KRAS+ and other nutrients |
Abbreviations: ANOVA analysis of variance, APC adenomatous polyposis coli gene, BMI body mass index, CI confidence interval, CRC colorectal cancer, GST glutathione S-transferase, GSTM-1 Glutathione S-transferases mu form, HPFS Health Professionals Follow-Up Study, HR hazard ratio, MUFA monounsaturated fatty acids, MSI microsatellite instability, NAT N-acetyltransferase, NAT2 N-acetyltransferase 2, NHS Nurses’ Health Studies, NLCS Netherlands Cohort Study on diet and cancer, OR odds ratio, PUFA polyunsaturated fatty acids, RR risk ratio, SFA saturated fatty acids, USA United States of America