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Polyphenols have been shown to exert biological activity in experimental models of colon cancer; however, human data linking specific polyphenols to colon cancer is limited. We assessed the relationship between pre‐diagnostic plasma polyphenols and colon cancer risk in a case–control study nested within the European Prospective Investigation into Cancer and Nutrition study. Using high pressure liquid chromatography coupled to tandem mass spectrometry, we measured concentrations of 35 polyphenols in plasma from 809 incident colon cancer cases and 809 matched controls. We used multivariable adjusted conditional logistic regression models that included established colon cancer risk factors. The false discovery rate (q values) was computed to control for multiple comparisons. All statistical tests were two‐sided. After false discovery rate correction and in continuous log2‐transformed multivariable models, equol (odds ratio [OR] per log2‐value, 0.86, 95% confidence interval [95% CI] = 0.79–0.93; q value = 0.01) and homovanillic acid (OR per log2‐value, 1.46, 95% CI = 1.16–1.84; q value = 0.02) were associated with colon cancer risk. Comparing extreme fifths, equol concentrations were inversely associated with colon cancer risk (OR = 0.61, 95% CI = 0.41–0.91, p trend = 0.003), while homovanillic acid concentrations were positively associated with colon cancer development (OR = 1.72, 95% CI = 1.17–2.53, p trend, What's new? Polyphenols are antioxidants abundant in food, and some polyphenols have demonstrated an anti‐cancer effect. Here, the authors looked for an association between polyphenols and colon cancer risk by conducting a nested case–control analysis within the EPIC cohort. Rather than employing questionnaires that rely on participant memories of their diet, this study directly measured 35 polyphenols in plasma samples and compared them with colon cancer risk. Only 2 chemicals showed any association. Concentrations of equol, which is metabolized from soy foods, were inversely associated with colon cancer risk. Higher levels of homovanillic acid, on the other hand, were associated with increased risk.

Background Chronic inflammation plays a critical role in the pathogenesis of the two major types of gastric cancer. Several foods, nutrients, and non-nutrient food components seem to be involved in the regulation of chronic inflammation. Objective To assess the association between the inflammatory potential of the diet and the risk of gastric carcinoma, overall and for the two major subsites: cardia cancers and non-cardia cancers. Design A total 476160 subjects (30% males, 70% females) from the European Investigation into Cancer and Nutrition (EPIC) study were followed for 14 years, during which 913 incident cases of gastric carcinoma were identified, including 236 located in the cardia, 341 in the distal part of the stomach (non-cardia), and 336 with overlapping or unknown tumor site. The dietary inflammatory potential was assessed by means of an inflammatory score of the diet (ISD), calculated using 28 dietary components and their corresponding inflammatory scores. The association between the ISD and gastric cancer risk was estimated by hazard ratios (HR) and 95%-confidence intervals (CI) calculated by multivariate Cox regression models adjusted for confounders. Results The inflammatory potential of diet was associated with an increased risk of gastric cancer. The HR (95% CI) for each increase in one standard deviation of the ISD were 1.25 (1.12, 1.39) for all gastric cancers, 1.30 (1.06, 1.59) for cardia cancers, and 1.07 (0.89, 1.28) for non-cardia cancers. The corresponding values for the highest compared to the lowest quartiles of the ISD were 1.66 (1.26, 2.20), 1.94 (1.14, 3.30), and 1.07 (0.70, 1.70) respectively. Conclusions Our results suggest that low-grade chronic inflammation induced by the diet may be associated with gastric cancer risk. This pattern seems to be more consistent for gastric carcinomas located in the cardia than for those located in the distal stomach.

The gut microbiome is increasingly implicated in colorectal cancer (CRC) development. A subgroup of patients diagnosed with CRC show high antibody responses to Streptococcus gallolyticus subspecies gallolyticus (SGG). However, it is unclear whether the association is also present pre-diagnostically. We assessed the association of antibody responses to SGG proteins in pre-diagnostic serum samples with CRC risk in a case-control study nested within a prospective cohort. Pre-diagnostic serum samples from 485 first incident CRC cases (mean time between blood draw and diagnosis 3.4 years) and 485 matched controls in the European Prospective Investigation into Nutrition and Cancer (EPIC) study were analyzed for antibody responses to eleven SGG proteins using multiplex serology. Odds ratios (OR) and 95% confidence intervals (CI) were estimated using multivariable conditional logistic regression models. Antibody positivity for any of the eleven SGG proteins was significantly associated with CRC risk with 56% positive controls compared to 63% positive cases (OR: 1.36, 95% CI: 1.04-1.77). Positivity for two or more proteins of a previously identified SGG 6-marker panel with greater CRC-specificity was also observed among 9% of controls compared to 17% of CRC cases, corresponding to a significantly increased CRC risk (OR: 2.17, 95% CI: 1.44-3.27). In this prospective nested case-control study we observed a positive association between antibody responses to SGG and CRC development in serum samples taken pre-diagnostically. Further work is required to establish the possibly etiological significance of these observations and whether SGG serology may be applicable for CRC risk stratification. This article is protected by copyright. All rights reserved.

IMPORTANCE: There is an urgent need to improve lung cancer risk assessment because current screening criteria miss a large proportion of cases. OBJECTIVE: To investigate whether a lung cancer risk prediction model based on a panel of selected circulating protein biomarkers can outperform a traditional risk prediction model and current US screening criteria. DESIGN, SETTING, AND PARTICIPANTS: Prediagnostic samples from 108 ever-smoking patients with lung cancer diagnosed within 1 year after blood collection and samples from 216 smoking-matched controls from the Carotene and Retinol Efficacy Trial (CARET) cohort were used to develop a biomarker risk score based on 4 proteins (cancer antigen 125 [CA125], carcinoembryonic antigen [CEA], cytokeratin-19 fragment [CYFRA 21-1], and the precursor form of surfactant protein B [Pro-SFTPB]). The biomarker score was subsequently validated blindly using absolute risk estimates among 63 ever-smoking patients with lung cancer diagnosed within 1 year after blood collection and 90 matched controls from 2 large European population-based cohorts, the European Prospective Investigation into Cancer and Nutrition (EPIC) and the Northern Sweden Health and Disease Study (NSHDS). MAIN OUTCOMES AND MEASURES: Model validity in discriminating between future lung cancer cases and controls. Discrimination estimates were weighted to reflect the background populations of EPIC and NSHDS validation studies (area under the receiver-operating characteristics curve [AUC], sensitivity, and specificity). RESULTS: In the validation study of 63 ever-smoking patients with lung cancer and 90 matched controls (mean [SD] age, 57.7 [8.7] years; 68.6% men) from EPIC and NSHDS, an integrated risk prediction model that combined smoking exposure with the biomarker score yielded an AUC of 0.83 (95% CI, 0.76-0.90) compared with 0.73 (95% CI, 0.64-0.82) for a model based on smoking exposure alone (P = .003 for difference in AUC). At an overall specificity of 0.83, based on the US Preventive Services Task Force screening criteria, the sensitivity of the integrated risk prediction (biomarker) model was 0.63 compared with 0.43 for the smoking model. Conversely, at an overall sensitivity of 0.42, based on the US Preventive Services Task Force screening criteria, the integrated risk prediction model yielded a specificity of 0.95 compared with 0.86 for the smoking model. CONCLUSIONS AND RELEVANCE: This study provided a proof of principle in showing that a panel of circulating protein biomarkers may improve lung cancer risk assessment and may be used to define eligibility for computed tomography screening.

Recently, we identified unique processing patterns of apolipoprotein A2 (ApoA2) in patients with pancreatic cancer. This study provides a first prospective evaluation of an ApoA2 isoform ("ApoA2-ATQ/AT"), alone and in combination with carbohydrate antigen 19-9 (CA19-9), as an early detection biomarker for pancreatic cancer. We performed ELISA measurements of CA19-9 and ApoA2-ATQ/AT in 156 patients with pancreatic cancer and 217 matched controls within the European EPIC cohort, using plasma samples collected up to 60 months prior to diagnosis. The detection discrimination statistics were calculated for risk scores by strata of lag-time. For CA19-9, in univariate marker analyses, C-statistics to distinguish future pancreatic cancer patients from cancer-free individuals were 0.80 for plasma taken ≤6 months before diagnosis, and 0.71 for >6-18 months; for ApoA2-ATQ/AT, C-statistics were 0.62, and 0.65, respectively. Joint models based on ApoA2-ATQ/AT plus CA19-9 significantly improved discrimination within >6-18 months (C = 0.74 vs. 0.71 for CA19-9 alone, p = 0.022) and ≤18 months (C = 0.75 vs. 0.74, p = 0.022). At 98% specificity, and for lag times of ≤6, >6-18 or ≤18 months, sensitivities were 57%, 36% and 43% for CA19-9 combined with ApoA2-ATQ/AT, respectively, vs. 50%, 29% and 36% for CA19-9 alone. Compared to CA19-9 alone, the combination of CA19-9 and ApoA2-ATQ/AT may improve detection of pancreatic cancer up to 18 months prior to diagnosis under usual care, and may provide a useful first measure for pancreatic cancer detection prior to imaging. This article is protected by copyright. All rights reserved.

Background Obesity is positively associated with colorectal cancer. Recently, body size subtypes categorised by the prevalence of hyperinsulinaemia have been defined, and metabolically healthy overweight/obese individuals (without hyperinsulinaemia) have been suggested to be at lower risk of cardiovascular disease than their metabolically unhealthy (hyperinsulinaemic) overweight/obese counterparts. Whether similarly variable relationships exist for metabolically defined body size phenotypes and colorectal cancer risk is unknown. Methods and Findings The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case–control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of, Gunter and colleagues analyse a large European dataset to determine how body size and metabolic profile associates with the risk of developing colorectal cancer., Editors' Summary Background Colorectal cancer is the third most common cancer worldwide and is a leading cause of cancer-related death, killing around 700,000 people every year. It develops when cells in the colon (the final part of the digestive system, which is also known as the large intestine or large bowel) or the rectum (the lower end of the colon) acquire genetic changes that allow them to divide uncontrollably to form a tumor and to move around the body (metastasize). Symptoms of colorectal cancer include blood in the stool, a change in bowel habits, and unexplained weight loss. Treatments for colorectal cancer include surgery, chemotherapy, and radiation. As with other types of cancer, these treatments are more likely to be successful if started when the tumor is very small. Consequently, many countries run screening programs that use colonoscopy, the fecal occult blood test, and other tests to detect the earliest signs of colorectal cancer in apparently healthy people. Why Was This Study Done? Being obese—having too much body fat—is associated with an increased colorectal cancer risk (other risk factors include age, having a family history of colorectal cancer, and eating a high-fat, low-fiber diet). Obesity is also associated with several other chronic diseases, and recent evidence suggests that some obese individuals have a higher risk of developing these diseases than others. For example, overweight/obese individuals who have hyperinsulinemia (abnormally high blood levels of insulin; “metabolically unhealthy”) seem to have a higher risk of cardiovascular disease than their non-hyperinsulinemic (“metabolically healthy”) overweight counterparts. If certain combinations of metabolic health status and body size (“metabolically defined body size phenotypes”) are also associated with colorectal cancer, measurement of insulin levels in conjunction with body fat (adiposity) measurements such as body mass index (BMI; an indicator of body fat calculated by dividing a person’s weight in kilograms by their height in meters squared) might improve colorectal cancer risk assessment. In this nested case–control study, the researchers assess the associations between metabolically defined body size phenotypes and colorectal cancer risk. A nested case–control study identifies everyone in a group (here, participants in the European Prospective Investigation into Cancer and Nutrition [EPIC] study) who has a specific condition, identifies matched individuals in the same group without the condition, and asks whether these controls and the cases differ in terms of a specific characteristic or outcome. What Did the Researchers Do and Find? The researchers matched 737 participants in the EPIC study who developed colorectal cancer after study enrollment with 737 controls and used serum concentrations of C-peptide, a marker of insulin secretion, and BMI measurements to classify each individual as metabolically healthy/normal weight, metabolically healthy/overweight, metabolically unhealthy/normal weight, or metabolically unhealthy/overweight. Specifically, the researchers categorized people as metabolically unhealthy if they had a C-peptide level above an arbitrarily chosen cut-off value based on the distribution of C-peptide levels in the control participants and as overweight if they had a BMI of ≥25 kg/m2 (the standard definition of overweight). Compared to metabolically healthy normal weight individuals, metabolically unhealthy normal weight and overweight individuals had an increased colorectal cancer risk; metabolically healthy overweight individuals had a similar colorectal cancer risk to metabolically healthy normal weight individuals. Among overweight individuals, metabolically healthy individuals had a lower colorectal cancer risk than metabolically unhealthy individuals. Finally, similar associations were seen when the researchers used waist circumference instead of BMI as the measure of adiposity. What Do These Findings Mean? These findings suggest that normal weight individuals with hyperinsulinemia (the metabolically unhealthy normal weight phenotype) have a higher risk of colorectal cancer than normal weight individuals without hyperinsulinemia. They also suggest that metabolically unhealthy overweight individuals have a higher risk of colorectal cancer than metabolically healthy overweight individuals. The accuracy of these findings may be limited by the method the researchers used to classify individuals as hyperinsulinemic—there is no universally accepted clinical definition for using C-peptide level to diagnose hyperinsulinemia. Nevertheless, these findings suggest that the assessment of insulin levels in conjunction with adiposity measures might be a better way to assess an individual’s colorectal cancer risk than simply measuring adiposity, and might help to identify those individuals at high risk of colorectal cancer who are most likely to benefit from targeted interventions designed to prevent the onset of clinical disease. Additional Information This list of resources contains links that can be accessed when viewing the PDF on a device or via the online version of the article at http://dx.doi.org/10.1371/journal.pmed.1001988. The US National Cancer Institute provides information for patients about all aspects of colorectal cancer; it also provides more detailed information colorectal cancer for health professionals and information on cancer risk and obesity The UK National Health Service Choices website has information and personal stories about colorectal cancer and information on obesity The not-for-profit organization Cancer Research UK provides information about colorectal cancer and about the association between cancer and obesity MedlinePlus provides links to further resources about colorectal cancer and about obesity Wikipedia has a page on hyperinsulinemia (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages) More information about the EPIC study is available

BACKGROUND: Higher coffee intake has been purportedly related to a lower risk of liver cancer. However, it remains unclear whether this association may be accounted for by specific biological mechanisms.OBJECTIVE: We aimed to evaluate the potential mediating roles of inflammatory, metabolic, liver injury, and iron metabolism biomarkers on the association between coffee intake and the primary form of liver cancer-hepatocellular carcinoma (HCC).DESIGN: We conducted a prospective nested case-control study within the European Prospective Investigation into Cancer and Nutrition among 125 incident HCC cases matched to 250 controls using an incidence-density sampling procedure. The association of coffee intake with HCC risk was evaluated by using multivariable-adjusted conditional logistic regression that accounted for smoking, alcohol consumption, hepatitis infection, and other established liver cancer risk factors. The mediating effects of 21 biomarkers were evaluated on the basis of percentage changes and associated 95% CIs in the estimated regression coefficients of models with and without adjustment for biomarkers individually and in combination.RESULTS: The multivariable-adjusted RR of having ≥4 cups (600 mL) coffee/d compared with CONCLUSION: These data suggest that the inverse association of coffee intake with HCC risk was partly accounted for by biomarkers of inflammation and hepatocellular injury.