| 1. |
- Borgmästars, Emmy, et al.
(författare)
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Multi-omics profiling to identify early plasma biomarkers in pre-diagnostic pancreatic ductal adenocarcinoma : a nested case-control study
- 2024
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Ingår i: Translational Oncology. - : Elsevier. - 1944-7124 .- 1936-5233. ; 48
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Tidskriftsartikel (refereegranskat)abstract
- Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease with poor survival. Novel biomarkers are urgently needed to improve the outcome through early detection. Here, we aimed to discover novel biomarkers for early PDAC detection using multi-omics profiling in pre-diagnostic plasma samples biobanked after routine health examinations.A nested case-control study within the Northern Sweden Health and Disease Study was designed. Pre-diagnostic plasma samples from 37 future PDAC patients collected within 2.3 years before diagnosis and 37 matched healthy controls were included. We analyzed metabolites using liquid chromatography mass spectrometry and gas chromatography mass spectrometry, microRNAs by HTG edgeseq, proteins by multiplex proximity extension assays, as well as three clinical biomarkers using milliplex technology. Supervised and unsupervised multi-omics integration were performed as well as univariate analyses for the different omics types and clinical biomarkers. Multiple hypothesis testing was corrected using Benjamini-Hochberg's method and a false discovery rate (FDR) below 0.1 was considered statistically significant.Carbohydrate antigen (CA) 19-9 was associated with PDAC risk (OR [95 % CI] = 3.09 [1.31–7.29], FDR = 0.03) and increased closer to PDAC diagnosis. Supervised multi-omics models resulted in poor discrimination between future PDAC cases and healthy controls with obtained accuracies between 0.429–0.500. No single metabolite, microRNA, or protein was differentially altered (FDR < 0.1) between future PDAC cases and healthy controls.CA 19-9 levels increase up to two years prior to PDAC diagnosis but extensive multi-omics analysis including metabolomics, microRNAomics and proteomics in this cohort did not identify novel early biomarkers for PDAC.
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| 2. |
- Lindberg, Margaretha, et al.
(författare)
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Postoperative pain after colorectal surgery
- 2020
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Ingår i: International Journal of Colorectal Disease. - : Springer. - 0179-1958 .- 1432-1262. ; 35:7, s. 1265-1272
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Postoperative pain is a keystone in perioperative programs, as pain negatively impacts recovery. This study aimed to evaluate pain after elective colorectal surgery and to identify risk factors for postoperative pain.Methods: This prospective cohort study comprised consecutive patients undergoing elective colorectal surgery within the Enhanced Recovery after Surgery (ERAS) perioperative program between March 2013 and April 2017. The numeric rating scale (NRS) was used to estimate maximum pain. Logistic regression was used to model associations with the type of surgery, age, gender, and comorbidities.Results: The cohort comprised 434 of 459 eligible patients. On the day of surgery to postoperative day 3, 50-64% of patients reported moderate to severe pain (NRS 4-10). Postoperative pain was similar for open and minimally invasive rectal surgery, while patients undergoing minimally invasive colonic surgery experienced more pain on the day of surgery and less pain on postoperative days 2 and 3 vs. open colonic surgery. Younger age was associated with more pain every postoperative day and by 0.7 NRS/10 years (95% CI 0.5-0.9, P < 0.001) on the day of surgery, while having diabetes type 2 was associated with less postoperative pain by - 1.3 NRS (95% CI - 2.4 to - 0.2) on the day of surgery.Conclusions: The majority, and young patients in particular, experience moderate to severe pain after open and minimally invasive colorectal surgery, despite following ERAS perioperative program. There is a need for effective and individualized analgesia after colorectal surgery, since the individual pain response to surgery is difficult to predict.
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| 3. |
- Molnár, Adrienne, et al.
(författare)
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Portomesenteric venous contact ≤180° and overall survival in resectable head and body pancreatic adenocarcinoma treated with upfront surgery
- 2023
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Ingår i: European Journal of Surgical Oncology. - : Elsevier. - 0748-7983 .- 1532-2157. ; 49:11
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Upfront surgery is the standard of care for resectable pancreatic cancer, defined as the absence of or ≤180° tumour contact with the portal/superior mesenteric vein. We hypothesized that portomesenteric venous contact is prognostically unfavourable and aimed to assess whether it is associated with poorer outcomes compared with no venous contact in resectable head and body pancreatic cancer.Methods: This single-centre retrospective study included patients undergoing upfront surgery for resectable head and body pancreatic cancer in 2010–2020 at Umeå University Hospital, Sweden. No venous contact was compared with portomesenteric venous contact of ≤180° based on preoperative imaging. Survival on an intention-to-treat basis was compared with Kaplan-Meier curves, a log-rank test and Cox proportional hazards models.Results: The final study cohort included 39 patients with portomesenteric venous contact and 144 patients without venous contact. Patients with portomesenteric tumour contact had a median overall survival of 15.3 months compared to 23.0 months (log rank P = 0.059). Portomesenteric venous contact was an independent negative prognostic factor for survival in the multivariable Cox model (HR 1.68; 95% CI 1.11–2.55, P = 0.014) and was associated with higher rates of microscopically non-radical resections (R1) (50% vs 26.1%, P = 0.012) and pathological lymph node metastasis (76.7% vs 56.8%, P = 0.012). There was no difference in adjuvant chemotherapy receipt or postoperative complications between the groups.Conclusions: Portomesenteric venous contact is associated with poorer overall survival and higher rates of R1 resections and lymph node metastasis in patients with resectable head and body pancreatic cancer treated with upfront surgery.
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| 4. |
- Borgmästars, Emmy, et al.
(författare)
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Circulating tissue polypeptide-specific antigen in pre-diagnostic pancreatic cancer samples
- 2021
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Ingår i: Cancers. - : MDPI. - 2072-6694. ; 13:21
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Tidskriftsartikel (refereegranskat)abstract
- Early detection of pancreatic ductal adenocarcinoma (PDAC) is challenging, and late diagnosis partly explains the low 5-year survival. Novel and sensitive biomarkers are needed to enable early PDAC detection and improve patient outcomes. Tissue polypeptide specific antigen (TPS) has been studied as a biomarker in PDAC diagnostics, and it has previously been shown to reflect clinical status better than the ‘golden standard’ biomarker carbohydrate antigen 19-9 (CA 19-9) that is most widely used in the clinical setting. In this cross-sectional case-control study using pre-diagnostic plasma samples, we aim to evaluate the potential of TPS as a biomarker for early PDAC detection. Furthermore, in a subset of individuals with multiple samples available at different time points before diagnosis, a longitudinal analysis was used. We assessed plasma TPS levels using enzyme-linked immunosorbent assay (ELISA) in 267 pre-diagnostic PDAC plasma samples taken up to 18.8 years before clinical PDAC diagnosis and in 320 matched healthy controls. TPS levels were also assessed in 25 samples at PDAC diagnosis. Circulating TPS levels were low both in pre-diagnostic samples of future PDAC patients and in healthy controls, whereas TPS levels at PDAC diagnosis were significantly increased (odds ratio 1.03; 95% confidence interval: 1.01–1.05) in a logistic regression model adjusted for age. In conclusion, TPS levels increase late in PDAC progression and hold no potential as a biomarker for early detection.
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| 5. |
- Borgmästars, Emmy, 1990-
(författare)
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In search of early biomarkers in pancreatic ductal adenocarcinoma using multi-omics and bioinformatics
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Background: Pancreatic ductal adenocarcinoma (PDAC) is a very aggressive malignancy with a 5-year survival of 10 %. Surgery is the only curative treatment. Unfortunately, few patients are eligible for surgery due to late detection. Thus, we need ways to detect the disease at an earlier stage and for that good screening biomarkers could be used. Previous studies have analyzed circulating analytes in prospective studies to identify early PDAC signals. One such class is microRNAs (miRNAs). MicroRNAs are non-coding RNAs of around 22 nucleotides that act as post- transcriptional regulators by interaction with messenger RNAs (mRNAs). The function of a miRNA can be elucidated by target prediction, to identify its potential targets, followed by enrichment analysis of the predicted targets. Challenges with this approach includes a lot of false positives being generated and that miRNAs can perform their role in a tissue- or disease-specific manner. Other classes of analytes that have previously been studied in prospective PDAC cohorts are metabolites and proteins. Aims: This thesis has three aims. First, to build a miRNA functional analysis pipeline with correlation support between miRNA and its predicted target genes. Second, to identify potential circulating biomarkers for early detection of PDAC using multi-omics. Third, to identify potential prognostic metabolites in a prospective PDAC cohort.Methods: We used publicly available data from the cancer genome atlas-pancreatic adenocarcinoma (TCGA-PAAD) and pre-diagnostic plasma samples from the Northern Sweden Health and Disease Study. We built a pipeline in R including miRNA, mRNA, and protein expression data from TCGA-PAAD for in silico miRNA functional analysis. Pre- diagnostic plasma samples from future PDAC patients as well as matched healthy controls were analyzed using multi- omics. Tissue polypeptide specific antigen (TPS) was analyzed by enzyme linked immunosorbent assay in 267 future PDAC samples and 320 healthy controls. Metabolomics and clinical biomarkers (carbohydrate antigen (CA) 19-9, carcinoembryonic antigen (CEA), and CA 15-3) were profiled in 100 future PDAC samples and 100 healthy controls using liquid chromatography-mass spectrometry (MS), gas chromatography-MS, and multi-plex technology. Of these, a subset of 39 future PDAC patients and 39 healthy controls were profiled for 2083 microRNAs using targeted sequencing and 644 proteins using proximity extension assays. Circulating levels of multi-omics analytes were analyzed using conditional or unconditional logistic regression. Least absolute shrinkage and selection operator (LASSO) in combination with 500 bootstrap iterations identified the most informative variables. The prognostic value of metabolites was assessed using cox regression. Multi-omics factor analysis (MOFA) and data integration analysis for biomarker discovery using latent components (DIABLO) were used for multi-omics integration analyses.Results: An automated pipeline was built consisting of 1) miRNA target prediction, 2) correlation analyses between miRNA and its targets on mRNA and protein expression levels, and 3) functional enrichment of correlated targets to identify enriched Kyoto encyclopedia of genes and genomes (KEGG) pathways and gene ontology (GO) terms for a specific miRNA. The pipeline was run for all microRNAs (~700) detected in the TCGA-PAAD cohort. These results can be downloaded from a shiny app (https://emmbor.shinyapps.io/mirfa/). TPS was not altered in pre-diagnostic PDAC patients up to 24 years prior to diagnosis, but increased at diagnosis (OR = 1.03, 95 % CI: 1.01-1.05). Internal area under curves of 0.74, 0.80, and 0.88 were achieved for five metabolites, two proteins, and two miRNAs that were selected by LASSO and bootstrap iterations, in combination with CA 19-9. Neither MOFA nor DIABLO separated well between future PDAC cases and healthy controls. Conclusions: Our bioinformatics pipeline for in silico functional analysis of microRNAs successfully identifies enriched KEGG pathways and GO terms for miRNA isoforms. The investigated plasma samples are heterogeneous, but among the analyzed variables, we identified five metabolites, two proteins, and two microRNAs with highest potential for early PDAC detection. CA 19-9 levels increased closer to diagnosis. We identified five fatty acids that could be studied in a diagnostic PDAC cohort as prognostic biomarkers.
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| 6. |
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| 7. |
- Borgmästars, Emmy, et al.
(författare)
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Metabolomics for early pancreatic cancer detection in plasma samples from a Swedish prospective population-based biobank
- 2024
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Ingår i: Journal of Gastrointestinal Oncology. - : AME Publishing Company. - 2078-6891 .- 2219-679X. ; 15:2, s. 755-767
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Tidskriftsartikel (refereegranskat)abstract
- Background: Pancreatic ductal adenocarcinoma (pancreatic cancer) is often detected at late stages resulting in poor overall survival. To improve survival, more patients need to be diagnosed early when curative surgery is feasible. We aimed to identify circulating metabolites that could be used as early pancreatic cancer biomarkers.Methods: We performed metabolomics by liquid and gas chromatography-mass spectrometry in plasma samples from 82 future pancreatic cancer patients and 82 matched healthy controls within the Northern Sweden Health and Disease Study (NSHDS). Logistic regression was used to assess univariate associations between metabolites and pancreatic cancer risk. Least absolute shrinkage and selection operator (LASSO) logistic regression was used to design a metabolite-based risk score. We used receiver operating characteristic (ROC) analyses to assess the discriminative performance of the metabolite-based risk score.Results: Among twelve risk-associated metabolites with a nominal P value <0.05, we defined a risk score of three metabolites [indoleacetate, 3-hydroxydecanoate (10:0-OH), and retention index (RI): 2,745.4] using LASSO. A logistic regression model containing these three metabolites, age, sex, body mass index (BMI), smoking status, sample date, fasting status, and carbohydrate antigen 19-9 (CA 19-9) yielded an internal area under curve (AUC) of 0.784 [95% confidence interval (CI): 0.714–0.854] compared to 0.681 (95% CI: 0.597–0.764) for a model without these metabolites (P value =0.007). Seventeen metabolites were significantly associated with pancreatic cancer survival [false discovery rate (FDR) <0.1].Conclusions: Indoleacetate, 3-hydroxydecanoate (10:0-OH), and RI: 2,745.4 were identified as the top candidate biomarkers for early detection. However, continued efforts are warranted to determine the usefulness of these metabolites as early pancreatic cancer biomarkers.
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| 8. |
- Borgmästars, Emmy, et al.
(författare)
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Metabolomics for early pancreatic cancer detection in plasma samples from a Swedish prospective population-based biobank
- 2024
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Ingår i: Journal of Gastrointestinal Oncology. - : AME Publishing Company. - 2078-6891 .- 2219-679X. ; 15:2, s. 755-767
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Tidskriftsartikel (refereegranskat)abstract
- Background: Pancreatic ductal adenocarcinoma (pancreatic cancer) is often detected at late stages resulting in poor overall survival. To improve survival, more patients need to be diagnosed early when curative surgery is feasible. We aimed to identify circulating metabolites that could be used as early pancreatic cancer biomarkers.Methods: We performed metabolomics by liquid and gas chromatography-mass spectrometry in plasma samples from 82 future pancreatic cancer patients and 82 matched healthy controls within the Northern Sweden Health and Disease Study (NSHDS). Logistic regression was used to assess univariate associations between metabolites and pancreatic cancer risk. Least absolute shrinkage and selection operator (LASSO) logistic regression was used to design a metabolite-based risk score. We used receiver operating characteristic (ROC) analyses to assess the discriminative performance of the metabolite-based risk score.Results: Among twelve risk-associated metabolites with a nominal P value <0.05, we defined a risk score of three metabolites [indoleacetate, 3-hydroxydecanoate (10:0-OH), and retention index (RI): 2,745.4] using LASSO. A logistic regression model containing these three metabolites, age, sex, body mass index (BMI), smoking status, sample date, fasting status, and carbohydrate antigen 19-9 (CA 19-9) yielded an internal area under curve (AUC) of 0.784 [95% confidence interval (CI): 0.714–0.854] compared to 0.681 (95% CI: 0.597–0.764) for a model without these metabolites (P value =0.007). Seventeen metabolites were significantly associated with pancreatic cancer survival [false discovery rate (FDR) <0.1].Conclusions: Indoleacetate, 3-hydroxydecanoate (10:0-OH), and RI: 2,745.4 were identified as the top candidate biomarkers for early detection. However, continued efforts are warranted to determine the usefulness of these metabolites as early pancreatic cancer biomarkers.
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| 9. |
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| 10. |
- Cayssials, Valerie, et al.
(författare)
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Inflammatory potential of diet and pancreatic cancer risk in the EPIC study
- 2022
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Ingår i: European Journal of Nutrition. - : Springer Nature. - 1436-6207 .- 1436-6215. ; 61, s. 2313-2320
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: There is existing evidence on the potential role of chronic inflammation in the pathogenesis of pancreatic cancer (PC) and on how risk may be modulated by dietary factors. Pro-inflammatory diets are suggested to be associated with increased risk of PC but, so far, evidence remains not conclusive. We examined the association between the dietary inflammatory potential and PC risk within the European Prospective Investigation into Cancer and Nutrition (EPIC) study, which includes 450,112 participants.Methods: After a 14-year follow-up, a total of 1239 incident PC cases were included in this study. The inflammatory potential of the diet was estimated using an Inflammatory Score of the Diet (ISD). Hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between the ISD and PC were estimated using multivariable Cox regression models, adjusted for known risk factors for PC.Results: Participants with higher ISDs had a higher risk of developing PCs. In the fully adjusted multivariate model, the risk of PC increased by 11% (HR 1.11, 95% CI 1.02–1.22) for 1 point each standard deviation increase in the ISD score. Neither obesity nor any other known risk factor for PC showed statistically significant interactions.Conclusion: To the best of our knowledge, this is the first prospective study reporting a positive relationship between the inflammatory potential of diet and PC. Since early diagnosis and treatment of pancreatic cancer might be challenging, prevention remains the major hope for reducing the burden of this disease.
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