Elucidating the role of blood metabolites on pancreatic cancer risk using two-sample Mendelian randomization analysis

Pancreatic ductal adenocarcinoma (PDAC) is an uncommon but highly fatal malignancy. Identifying causal metabolite biomarkers offers an opportunity to facilitate effective risk assessment strategies for PDAC. In this study, we performed a two-sample Mendelian randomization (MR) study to characterize the potential causal effects of metabolites in plasma on PDAC risk. Genetic instruments were determined for a total of 506 metabolites from one set of comprehensive genome-wide association studies (GWAS) involving 913 individuals of European ancestry from the INTERVAL/EPIC-Norfolk cohorts. Another set of genetic instruments was developed for 483 metabolites from an independent GWAS conducted with 8299 individuals of European ancestry from the Canadian Longitudinal Study on Aging (CLSA) cohort. We analyzed GWAS data of the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4), comprising 8275 PDAC cases and 6723 controls of European ancestry. The association of metabolites with PDAC risk was assessed using the inverse-variance weighted (IVW) method, and complemented with sensitivity analyses of MR-Egger and MR-PRESSO tests. Potential side effects of targeting the identified metabolites for PDAC intervention were further evaluated by a phenome-wide MR (Phe-MR) analysis. Forty-four unique metabolites were identified to be significantly associated with PDAC risk, of which four top-ranking metabolites (X: 12798, X: 11787, X: 11308 and X: 19141) showed replication evidence when using instruments developed from both two cohorts. Our results highlight novel blood metabolites related to PDAC risk, which may help prioritize metabolic features for PDAC mechanistic research and further evaluation of their potential role in PDAC risk assessment.     

Patterns in metabolite profile are associated with risk of more aggressive prostate cancer: A prospective study of 3,057 matched case–control sets from EPIC

Metabolomics may reveal novel insights into the etiology of prostate cancer, for which few risk factors are established. We investigated the association between patterns in baseline plasma metabolite profile and subsequent prostate cancer risk, using data from 3,057 matched case–control sets from the European Prospective Investigation into Cancer and Nutrition (EPIC). We measured 119 metabolite concentrations in plasma samples, collected on average 9.4 years before diagnosis, by mass spectrometry (AbsoluteIDQ p180 Kit, Biocrates Life Sciences AG). Metabolite patterns were identified using treelet transform, a statistical method for identification of groups of correlated metabolites. Associations of metabolite patterns with prostate cancer risk (OR_1SD) were estimated by conditional logistic regression. Supplementary analyses were conducted for metabolite patterns derived using principal component analysis and for individual metabolites. Men with metabolite profiles characterized by higher concentrations of either phosphatidylcholines or hydroxysphingomyelins (OR_1SD = 0.77, 95% confidence interval 0.66–0.89), acylcarnitines C18:1 and C18:2, glutamate, ornithine and taurine (OR_1SD = 0.72, 0.57–0.90), or lysophosphatidylcholines (OR_1SD = 0.81, 0.69–0.95) had lower risk of advanced stage prostate cancer at diagnosis, with no evidence of heterogeneity by follow-up time. Similar associations were observed for the two former patterns with aggressive disease risk (the more aggressive subset of advanced stage), while the latter pattern was inversely related to risk of prostate cancer death (OR_1SD = 0.77, 0.61–0.96). No associations were observed for prostate cancer overall or less aggressive tumor subtypes. In conclusion, metabolite patterns may be related to lower risk of more aggressive prostate tumors and prostate cancer death, and might be relevant to etiology of advanced stage prostate cancer.     

A systems approach identifies time-dependent associations of multimorbidities with pancreatic cancer risk

BackgroundPancreatic ductal adenocarcinoma (PDAC) is usually diagnosed in late adulthood; therefore, many patients suffer or have suffered from other diseases. Identifying disease patterns associated with PDAC risk may enable a better characterization of high-risk patients.MethodsMultimorbidity patterns (MPs) were assessed from 17 self-reported conditions using hierarchical clustering, principal component, and factor analyses in 1705 PDAC cases and 1084 controls from a European population. Their association with PDAC was evaluated using adjusted logistic regression models. Time since diagnosis of morbidities to PDAC diagnosis/recruitment was stratified into recent (<3 years) and long term (≥3 years). The MPs and PDAC genetic networks were explored with DisGeNET bioinformatics-tool which focuses on gene-diseases associations available in curated databases.ResultsThree MPs were observed: gastric (heartburn, acid regurgitation, Helicobacter pylori infection, and ulcer), metabolic syndrome (obesity, type-2 diabetes, hypercholesterolemia, and hypertension), and atopic (nasal allergies, skin allergies, and asthma). Strong associations with PDAC were observed for ≥2 recently diagnosed gastric conditions [odds ratio (OR), 6.13; 95% confidence interval CI 3.01–12.5)] and for ≥3 recently diagnosed metabolic syndrome conditions (OR, 1.61; 95% CI 1.11–2.35). Atopic conditions were negatively associated with PDAC (high adherence score OR for tertile III, 0.45; 95% CI, 0.36–0.55). Combining type-2 diabetes with gastric MP resulted in higher PDAC risk for recent (OR, 7.89; 95% CI 3.9–16.1) and long-term diagnosed conditions (OR, 1.86; 95% CI 1.29–2.67). A common genetic basis between MPs and PDAC was observed in the bioinformatics analysis.ConclusionsSpecific multimorbidities aggregate and associate with PDAC in a time-dependent manner. A better characterization of a high-risk population for PDAC may help in the early diagnosis of this cancer. The common genetic basis between MP and PDAC points to a mechanistic link between these conditions.     

Do pancreatic cancer and chronic pancreatitis share the same genetic risk factors? A PANcreatic Disease ReseArch (PANDoRA) consortium investigation

Pancreatic ductal adenocarcinoma (PDAC) is a very aggressive tumor with a five‐year survival of less than 6%. Chronic pancreatitis (CP), an inflammatory process in of the pancreas, is a strong risk factor for PDAC. Several genetic polymorphisms have been discovered as susceptibility loci for both CP and PDAC. Since CP and PDAC share a consistent number of epidemiologic risk factors, the aim of this study was to investigate whether specific CP risk loci also contribute to PDAC susceptibility. We selected five common SNPs (rs11988997, rs379742, rs10273639, rs2995271 and rs12688220) that were identified as susceptibility markers for CP and analyzed them in 2,914 PDAC cases, 356 CP cases and 5,596 controls retrospectively collected in the context of the international PANDoRA consortium. We found a weak association between the minor allele of the PRSS1‐PRSS2‐rs10273639 and an increased risk of developing PDAC (OR_homozygous = 1.19, 95% CI 1.02–1.38, p = 0.023). Additionally all the SNPs confirmed statistically significant associations with risk of developing CP, the strongest being PRSS1‐PRSS2‐rs10273639 (OR_heterozygous = 0.51, 95% CI 0.39–0.67, p = 1.10 × 10⁻⁶) and MORC4‐rs 12837024 (OR_homozygous = 2.07 (1.55–2.77, p_trend = 0.7 × 10⁻¹¹). Taken together, the results from our study do not support variants rs11988997, rs379742, rs10273639, rs2995271 and rs12688220 as strong predictors of PDAC risk, but further support the role of these SNPs in CP susceptibility. Our study suggests that CP and PDAC probably do not share genetic susceptibility, at least in terms of high frequency variants.     

A prospective evaluation of serum methionine-related metabolites in relation to pancreatic cancer risk in two prospective cohort studies

Deficiencies in methyl donor status may render DNA methylation changes and DNA damage, leading to carcinogenesis. Epidemiological studies reported that higher dietary intake of choline is associated with lower risk of pancreatic cancer, but no study has examined the association of serum choline and its metabolites with risk of pancreatic cancer. Two parallel case–control studies, one nested within the Shanghai Cohort Study (129 cases and 258 controls) and the other within the Singapore Chinese Health Study (58 cases and 104 controls), were conducted to evaluate the associations of baseline serum concentrations of choline, betaine, methionine, total methyl donors (i.e., sum of choline, betaine and methionine), dimethylglycine and trimethylamine N-oxide (TMAO) with pancreatic cancer risk. In the Shanghai cohort, odds ratios and 95% confidence intervals of pancreatic cancer for the highest quartile of choline, betaine, methionine, total methyl donors and TMAO were 0.27 (0.11–0.69), 0.57 (0.31–1.05), 0.50 (0.26–0.96), 0.37 (0.19–0.73) and 2.81 (1.37–5.76), respectively, compared to the lowest quartile. The corresponding figures in the Singapore cohort were 0.85 (0.23–3.17), 0.50 (0.17–1.45), 0.17 (0.04–0.68), 0.33 (0.10–1.16) and 1.42 (0.50–4.04). The inverse associations of methionine and total methyl donors including choline, betaine and methionine with pancreatic cancer risk in both cohorts support that DNA repair and methylation play an important role against the development of pancreatic cancer. In the Shanghai cohort, TMAO, a gut microbiota-derived metabolite of dietary phosphatidylcholine, may contribute to higher risk of pancreatic cancer, suggesting a modifying role of gut microbiota in the dietary choline-pancreatic cancer risk association.     

Serum levels of iCAF-derived osteoglycin predict favorable outcome in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is characterized by abundant stroma, the main cellular constituents of which are cancer-associated fibroblasts (CAFs). Stroma-targeting agents have been proposed to improve the poor outcome of current treatments. However, clinical trials using these agents showed disappointing results. Heterogeneity in the PDAC CAF population was recently delineated demonstrating that both tumor-promoting and tumor-suppressive activities co-exist in the stroma. Here, we aimed to identify biomarkers for the CAF population that contribute to a favorable outcome. RNA-sequencing reads from patient-derived xenografts (PDXs) were mapped to the human and mouse genome to allocate the expression of genes to the tumor or stroma. Survival meta-analysis for stromal genes was performed and applied to human protein atlas data to identify circulating biomarkers. The candidate protein was perturbed in co-cultures and assessed in existing and novel single-cell gene expression analysis from control, pancreatitis, pancreatitis-recovered and PDAC mouse models. Serum levels of the candidate biomarker were measured in two independent cohorts totaling 148 PDAC patients and related them to overall survival. Osteoglycin (OGN) was identified as a candidate serum prognostic marker. Single-cell analysis indicated that Ogn is derived from a subgroup of inflammatory CAFs. Ogn-expressing fibroblasts are distinct from resident healthy pancreatic stellate cells and arise during pancreatitis. Serum OGN levels were prognostic for favorable overall survival in two independent PDAC cohorts (HR = 0.47, P = .042 and HR = 0.53, P = .006). Altogether, we conclude that high circulating OGN levels inform on a previously unrecognized subgroup of CAFs and predict favorable outcomes in resectable PDAC.     

Alterations in the gut microbiota and metabolite profiles of thyroid carcinoma patients

The aim of our study was to investigate the relationship among the gut microbiota community, metabolite profiles and thyroid carcinoma (TC). First, 30 TC patients and 35 healthy controls (HCs) fecal samples were applied to characterize the gut microbial community using 16S rRNA gene sequencing. Differential microbiota compositions were observed, with significant enrichment of 19 and depletion of 8 genera in TC samples compared to those in HCs (Q value <0.05), and some genera were correlated with various clinical parameters, such as lipoprotein A and apolipoprotein B. Furthermore, 6 different genera distinguished TC patients from HCs with the AUC of 0.94. The PICRUSt analysis showed 12 remarkably different metabolic pathways (Q value <0.05). Subsequently, we systematically analyzed the gut microbiota and metabolites in the same TC patients (n = 15) and HCs (n = 15). The characteristics of the gut microbiota community were mostly consistent with the above results (30 TC patients and 35 HCs), and liquid chromatography mass spectrometry analysis was performed to characterize the metabolite profiles. In total, 21 different genera (Q value <0.05) and 72 significantly changed metabolites (VIP > 1.0 and p < 0.05) were observed and correlated to each other. Eight metabolites combined with 5 genera were more effective in distinguishing TC patients from HCs (AUC = 0.97). In conclusion, our study presents a comprehensive landscape of the gut microbiota and metabolites in TC patients, and provides a research direction of the mechanism of interaction between gut microbiota alteration and TC pathogenesis.     

Serum and tissue metallome of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) patients have late presentation at the time of diagnosis and a poor prognosis. Metal dyshomeostasis is known to play a role in cancer progression. However, the blood and tissue metallome of PDAC patients has not been assessed. This study aimed to determine the levels of essential and toxic metals in the serum and pancreatic tissue from PDAC patients. Serum samples were obtained from PDAC patients before surgical resection. Tissue (tumor and adjacent normal pancreas) were obtained from the surgically resected specimen. Inductively coupled plasma–mass spectrometry (ICP-MS) analysis was performed to quantify the levels of 10 essential and 3 toxic metals in these samples. Statistical analysis was performed to identify dysregulated metals in PDAC and their role as potential diagnostic and prognostic biomarkers. Significantly decreased serum levels of magnesium, potassium, calcium, iron, zinc, selenium, arsenic, and mercury and increased levels of molybdenum were shown to be associated with PDAC. There were significantly decreased levels of zinc, manganese and molybdenum, and increased levels of calcium and selenium in the pancreatic tumor tissue compared with the adjacent normal pancreas. Notably, lower serum levels of calcium, iron, and selenium, and higher levels of manganese, were significantly associated with a poor prognosis (i.e., overall survival) in PDAC patients. In conclusion, this is the first study to comprehensively assess the serum and tissue metallome of PDAC patients. It identified the association of metals with PDAC diagnosis and prognosis.     

Prospective study of blood metabolites associated with colorectal cancer risk

Few prospective studies, and none in Asians, have systematically evaluated the relationship between blood metabolites and colorectal cancer risk. We conducted a nested case–control study to search for risk‐associated metabolite biomarkers for colorectal cancer in an Asian population using blood samples collected prior to cancer diagnosis. Conditional logistic regression was performed to assess associations of metabolites with cancer risk. In this study, we included 250 incident cases with colorectal cancer and individually matched controls nested within two prospective Shanghai cohorts. We found 35 metabolites associated with risk of colorectal cancer after adjusting for multiple comparisons. Among them, 12 metabolites were glycerophospholipids including nine associated with reduced risk of colorectal cancer and three with increased risk [odds ratios per standard deviation increase of transformed metabolites: 0.31–1.98; p values: 0.002–1.25 × 10^?10]. The other 23 metabolites associated with colorectal cancer risk included nine lipids other than glycerophospholipid, seven aromatic compounds, five organic acids and four other organic compounds. After mutual adjustment, nine metabolites remained statistically significant for colorectal cancer. Together, these independently associated metabolites can separate cancer cases from controls with an area under the curve of 0.76 for colorectal cancer. We have identified that dysregulation of glycerophospholipids may contribute to risk of colorectal cancer.     

Metabolomic analysis of prostate cancer risk in a prospective cohort: The alpha‐tocopherol,beta‐carotene cancer prevention (ATBC) study

Despite decades of concerted epidemiological research, relatively little is known about the etiology of prostate cancer. As genome‐wide association studies have identified numerous genetic variants, so metabolomic profiling of blood and other tissues represents an agnostic, “broad‐spectrum” approach for examining potential metabolic biomarkers of prostate cancer risk. To this end, we conducted a prospective analysis of prostate cancer within the Alpha‐Tocopherol, Beta‐Carotene Cancer Prevention Study cohort based on 200 cases (100 aggressive) and 200 controls (age‐ and blood collection date‐matched) with fasting serum collected up to 20 years prior to case diagnoses. Ultrahigh performance liquid chromatography/mass spectroscopy and gas chromatography/mass spectroscopy identified 626 compounds detected in >95% of the men and the odds ratio per 1‐standard deviation increase in log‐metabolite levels and risk were estimated using conditional logistic regression. We observed strong inverse associations between energy and lipid metabolites and aggressive cancer (p = 0.018 and p = 0.041, respectively, for chemical class over‐representation). Inositol‐1‐phosphate showed the strongest association (OR = 0.56, 95% CI = 0.39–0.81, p = 0.002) and glycerophospholipids and fatty acids were heavily represented; e.g., oleoyl‐linoleoyl‐glycerophosphoinositol (OR = 0.64, p = 0.004), 1‐stearoylglycerophosphoglycerol (OR=0.65, p = 0.025), stearate (OR=0.65, p = 0.010) and docosadienoate (OR = 0.66, p = 0.014). Both alpha‐ketoglutarate and citrate were associated with aggressive disease risk (OR = 0.69, 95% CI = 0.51–0.94, p = 0.02; OR = 0.69, 95% CI = 0.50–0.95, p = 0.02), as were elevated thyroxine and trimethylamine oxide (OR = 1.65, 95% CI = 1.08–2.54, p = 0.021; and OR = 1.36, 95% CI = 1.02–1.81, p = 0.039). Serum PSA adjustment did not alter the findings. Our data reveal several metabolomic leads that may have pathophysiological relevance to prostate carcinogenesis and should be examined through additional research.     

Metabonomic changes from pancreatic intraepithelial neoplasia to pancreatic ductal adenocarcinoma in tissues from rats

Pancreatic ductal adenocarcinoma (PDAC) is one of the most malignant tumors and is difficult to diagnose in the early phase. This study was aimed at obtaining the metabolic profiles and characteristic metabolites of pancreatic intraepithelial neoplasia (PanIN) and PDAC tissues from Sprague–Dawley (SD) rats to establish metabonomic methods used in the early diagnosis of PDAC. In the present study, the animal models were established by embedding 7,12‐dimethylbenzanthracene (DMBA) in the pancreas of SD rats to obtain PanIN and PDAC tissues. After the preprocessing of tissues, ¹H nuclear magnetic resonance (NMR) spectroscopy combined with multivariate and univariate statistical analysis was applied to identify the potential metabolic signatures and the corresponding metabolic pathways. Pattern recognition models were successfully established and differential metabolites, including glucose, amino acids, carboxylic acids and coenzymes, were screened out. Compared with the control, the trends in the variation of several metabolites were similar in both PanIN and PDAC. Kynurenate and methionine levels were elevated in PanIN but decreased in PDAC, thus, could served as biomarkers to distinguish PanIN from PDAC. Our results suggest that NMR‐based techniques combined with multivariate statistical analysis can distinguish the metabolic differences among PanIN, PDAC and normal tissues, and, therefore, present a promising approach for physiopathologic metabolism investigations and early diagnoses of PDAC.     

Association between a polymorphic variant in the CDKN2B-AS1/ANRIL gene and pancreatic cancer risk

Genes carrying high-penetrance germline mutations may also be associated with cancer susceptibility through common low-penetrance genetic variants. To increase the knowledge on genetic pancreatic ductal adenocarcinoma (PDAC) aetiology, the common genetic variability of PDAC familial genes was analysed in our study. We conducted a multiphase study analysing 7745 single nucleotide polymorphisms (SNPs) from 29 genes reported to harbour a high-penetrance PDAC-associated mutation in at least one published study. To assess the effect of the SNPs on PDAC risk, a total of 14 666 PDAC cases and 221 897 controls across five different studies were analysed. The T allele of the rs1412832 polymorphism, that is situated in the CDKN2B-AS1/ANRIL, showed a genome-wide significant association with increased risk of developing PDAC (OR = 1.11, 95% CI = 1.07-1.15, P = 5.25 × 10⁻⁹). CDKN2B-AS1/ANRIL is a long noncoding RNA, situated in 9p21.3, and regulates many target genes, among which CDKN2A (p16) that frequently shows deleterious somatic and germline mutations and deregulation in PDAC. Our results strongly support the role of the genetic variability of the 9p21.3 region in PDAC aetiopathogenesis and highlight the importance of secondary analysis as a tool for discovering new risk loci in complex human diseases.     

Saturated fatty acid intake,genetic risk and colorectal cancer incidence: A large-scale prospective cohort study

Previous investigations mainly focused on the associations of dietary fatty acids with colorectal cancer (CRC) risk, which ignored gene-environment interaction and mechanisms interpretation. We conducted a case-control study (751 cases and 3058 controls) and a prospective cohort study (125 021 participants) to explore the associations between dietary fatty acids, genetic risks, and CRC. Results showed that high intake of saturated fatty acid (SFA) was associated with a higher risk of CRC than low SFA intake (HR =1.22, 95% CI:1.02-1.46). Participants at high genetic risk had a greater risk of CRC with the HR of 2.48 (2.11-2.91) than those at low genetic risk. A multiplicative interaction of genetic risk and SFA intake with incident CRC risk was found (P_Interaction = 7.59 × 10⁻²⁰), demonstrating that participants with high genetic risk and high SFA intake had a 3.75-fold greater risk of CRC than those with low genetic risk and low SFA intake. Furthermore, incorporating PRS and SFA into traditional clinical risk factors improved the discriminatory accuracy for CRC risk stratification (AUC from 0.706 to 0.731). Multi-omics data showed that exposure to SFA-rich high-fat dietary (HFD) can responsively induce epigenome reprogramming of some oncogenes and pathological activation of fatty acid metabolism pathway, which may contribute to CRC development through changes in gut microbiomes, metabolites, and tumor-infiltrating immune cells. These findings suggest that individuals with high genetic risk of CRC may benefit from reducing SFA intake. The incorporation of SFA intake and PRS into traditional clinical risk factors will help improve high-risk sub-populations in individualized CRC prevention.     

Urinary estrogens and estrogen metabolites and subsequent risk of breast cancer among premenopausal women

Endogenous estrogens and estrogen metabolism are hypothesized to be associated with premenopausal breast cancer risk but evidence is limited. We examined 15 urinary estrogens/estrogen metabolites and breast cancer risk among premenopausal women in a case-control study nested within the Nurses' Health Study II (NHSII). From 1996 to 1999, urine was collected from 18,521 women during the mid-luteal menstrual phase. Breast cancer cases (N = 247) diagnosed between collection and June 2005 were matched to two controls each (N = 485). Urinary estrogen metabolites were measured by liquid chromatography-tandem mass spectrometry and adjusted for creatinine level. Relative risks (RR) and 95% confidence intervals (CI) were estimated by multivariate conditional logistic regression. Higher urinary estrone and estradiol levels were strongly significantly associated with lower risk (top vs. bottom quartile RR: estrone = 0.52; 95% CI, 0.30-0.88; estradiol = 0.51; 95% CI, 0.30-0.86). Generally inverse, although nonsignificant, patterns also were observed with 2- and 4-hydroxylation pathway estrogen metabolites. Inverse associations generally were not observed with 16-pathway estrogen metabolites and a significant positive association was observed with 17-epiestriol (top vs. bottom quartile RR = 1.74; 95% CI, 1.08-2.81; P(trend) = 0.01). In addition, there was a significant increased risk with higher 16-pathway/parent estrogen metabolite ratio (comparable RR = 1.61; 95% CI, 0.99-2.62; P(trend) = 0.04). Other pathway ratios were not significantly associated with risk except parent estrogen metabolites/non-parent estrogen metabolites (comparable RR = 0.58; 95% CI, 0.35-0.96; P(trend) = 0.03). These data suggest that most mid-luteal urinary estrogen metabolite concentrations are not positively associated with breast cancer risk among premenopausal women. The inverse associations with parent estrogen metabolites and the parent estrogen metabolite/non-parent estrogen metabolite ratio suggest that women with higher urinary excretion of parent estrogens are at lower risk.     

Serum high mobility group box-1 is a powerful diagnostic and prognostic biomarker for pancreatic ductal adenocarcinoma

Extracellular high mobility group box‐1 (HMGB1) contributes to tumor growth and invasiveness. We evaluated the diagnostic and prognostic ability of serum HMGB1 for pancreatic ductal adenocarcinoma (PDAC). Serum HMGB1 measured by enzyme‐linked immunosorbent assay (ELISA) were compared among normal, chronic pancreatitis, PDAC group in both training (n = 25, each group) and independent validation set (n = 45, each group). To determine the usability of serum HMGB1 as a diagnostic predictor of PDAC, receiver operating characteristic (ROC) curves with sensitivity/specificity and logistic regression were evaluated. To assess the HMGB1‐associated prognosis of PDAC, Kaplan–Meier survival and Cox proportional‐hazards regression were applied. Serum HMGB1 was correlated with presence and advanced‐stage of PDAC. Logistic regression exhibited serum HMGB1 was a remarkable biomarker to predict PDAC as a single or multiple‐markers; sensitivity/specificity of serum HMGB1 were superior to carbohydrate antigen (CA) 19‐9 or carcinoembryonic antigen (CEA) in both training and independent datasets. Kaplan–Meier survival analysis showed PDAC patients with high serum HMGB1 levels (>30 ng/mL; median survival, 192 days) had a worse prognosis than patients with low HMGB1 levels (≤30 ng/mL; 514 days) by log‐rank (P = 0.017). Cox proportional‐hazards model showed the relative hazard ratios in high‐serum HMGB1 group was 3.077 compared with the low‐serum HMGB1 group. In conclusion, serum HMGB1 is a desirable diagnostic and prognostic biomarker for PDAC compared with pre‐existing PDAC biomarkers, CA19‐9 and CEA.     

PAM4 enzyme immunoassay alone and in combination with CA 19‐9 for the detection of pancreatic adenocarcinoma

BACKGROUND:

The monoclonal antibody PAM4 has high specificity for pancreatic ductal adenocarcinoma (PDAC), as well as its precursor lesions, but has not been found to be reactive with normal and benign pancreatic tissues. The objective of the current study was to evaluate a PAM4‐based serum enzyme immunoassay alone and in combination with the carbohydrate antigen (CA) 19‐9 assay for the detection of PDAC, with particular attention to early stage disease.

METHODS:

Sera from patients with confirmed PDAC (N = 298), other cancers (N = 99), benign disease of the pancreas (N = 120), and healthy adults (N = 79) were evaluated by a specific enzyme immunoassay for the concentration of PAM4 and CA 19‐9 antigen levels by blinded analyses. All tests for statistical significance were 2‐sided.

RESULTS:

The overall sensitivity for PAM4 detection of PDAC was 76%, with 64% of patients with stage I disease also identified. The detection rate was considerably higher (85%) for patients with advanced disease. The assay demonstrated high specificity compared with benign pancreatic disease (85%), with a positive likelihood ratio of 4.93. CA 19‐9 provided an overall sensitivity of 77%, and was positive in 58% of patients with stage I disease; however, the specificity was significantly lower for CA 19‐9 (68%), with a positive likelihood ratio of 2.85 (P = .026 compared with PAM4). It is important to note that a combined PAM4 and CA 19‐9 biomarker serum assay demonstrated an improved sensitivity (84%) for the overall detection of PDAC without a significant loss of specificity (82%) compared with either arm alone.

CONCLUSIONS:

The PAM4 enzyme immunoassay identified approximately two‐thirds of patients with stage I PDAC with high discriminatory power with respect to benign, nonneoplastic pancreatic disease. These results provide a rationale for testing patient groups considered to be at high risk for PDAC with a combined PAM4 and CA 19‐9 biomarker serum assay for the detection of early stage PDAC. Cancer 2013. © 2012 American Cancer Society.     

Immune‐complex level of cofilin‐1 in sera is associated with cancer progression and poor prognosis in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies. To improve its outcome, reliable biomarkers are urgently needed. In this study, we aimed to elucidate the key molecules involved in PDAC progression using proteomics approaches. First, we undertook 2‐D electrophoresis to identify the proteins overexpressed in PDAC tissues. Following the analysis of agarose gel spots, cofilin‐1 was identified and verified as a candidate protein commonly upregulated in PDAC tissues. In immunohistochemistry, cofilin‐1 was strongly expressed in the cytoplasm of PDAC cells. Samples were divided into two groups based on the level of cofilin‐1 expression. The high expression group showed significantly higher incidence of hematogenous dissemination in relapsed patients than the low expression group (P = 0.0083). In in vitro experiments, knockdown of cofilin‐1 significantly decreased chemotaxis in PDAC cell lines. After we confirmed that cofilin‐1 was secreted from PDAC cells, we established a detection system for the immune‐complex of cofilin‐1 in sera. Using this system, we measured the IC levels of cofilin‐1 in sera and observed that the IC levels of cofilin‐1 in PDAC patients were higher than those in healthy volunteers and patients with pancreatitis (PDAC vs. healthy volunteers, P < 0.0001; PDAC vs. patients with pancreatitis, P < 0.026). Notably, the IC levels of cofilin‐1 showed a stepwise increase during PDAC progression (P = 0.0034), and high IC levels of cofilin‐1 indicated poor prognosis of patients after surgery (P = 0.039). These results suggest that the IC of cofilin‐1 in sera is a potentially attractive serum biomarker for the prognosis of PDAC.     

Alteration of amino acid and biogenic amine metabolism in hepatobiliary cancers: Findings from a prospective cohort study

Perturbations in levels of amino acids (AA) and their derivatives are observed in hepatocellular carcinoma (HCC). Yet, it is unclear whether these alterations precede or are a consequence of the disease, nor whether they pertain to anatomically related cancers of the intrahepatic bile duct (IHBC), and gallbladder and extrahepatic biliary tract (GBTC). Circulating standard AA, biogenic amines and hexoses were measured (Biocrates AbsoluteIDQ‐p180Kit) in a case‐control study nested within a large prospective cohort (147 HCC, 43 IHBC and 134 GBTC cases). Liver function and hepatitis status biomarkers were determined separately. Multivariable conditional logistic regression was used to calculate odds ratios and 95% confidence intervals (OR; 95%CI) for log‐transformed standardised (mean = 0, SD = 1) serum metabolite levels and relevant ratios in relation to HCC, IHBC or GBTC risk. Fourteen metabolites were significantly associated with HCC risk, of which seven metabolites and four ratios were the strongest predictors in continuous models. Leucine, lysine, glutamine and the ratio of branched chain to aromatic AA (Fischer's ratio) were inversely, while phenylalanine, tyrosine and their ratio, glutamate, glutamate/glutamine ratio, kynurenine and its ratio to tryptophan were positively associated with HCC risk. Confounding by hepatitis status and liver enzyme levels was observed. For the other cancers no significant associations were observed. In conclusion, imbalances of specific AA and biogenic amines may be involved in HCC development.     

Mass profiling of serum to distinguish mice with pancreatic cancer induced by a transgenic Kras mutation

Mass spectrometry (MS) has the unique ability to profile, in an easily accessible body tissue (peripheral blood/serum,) the sizes and relative amounts of a wide variety of biomolecules in a single platform setting. Using electrospray ionization (ESI)‐MS, we distinguished individual serum from wild‐type control mice from serum of mice containing an oncogenic Kras mutation, which leads to development of pancreatic ductal adenocarcinoma (PDAC) similar to that observed in humans. Identification of differences in significant ESI‐MS sera mass peaks between Kras‐activated mice and control mice was performed using t tests and a “nested leave one out” cross‐validation procedure. Peak distributions in serum of control mice from mice with Kras‐mutant‐dependent PDAC were distinguished from those of pancreatic intraepithelial neoplasia (PanIN) lesions (p = 0.00024). In addition, Kras mutant mice with PDAC were distinguished from Kras mutant mice with PanIN alone (p = 0.0057). Test specificity, a measure of the false positives, was greater for the control vs. Kras mutated mice, and the test sensitivity, a measure of false negatives, was greater for the PDAC vs. PanIN containing mice. Receiver‐operating characteristic (ROC) curve discriminatory values were 0.85 for both comparisons. These studies indicate ESI‐MS serum mass profiling can detect physiological changes associated with pancreatic cancer initiation and development in a GEM (genetic engineered mouse) model that mimics pancreatic cancer development in humans. Such technology has the potential to aid in early detection of pancreatic cancer and in developing therapeutic drug interventions.