Radioresistance remains a significant challenge in treating pancreatic ductal adenocarcinoma (PDAC), contributing to the poor survival rates of this cancer. MicroRNAs (miRs) are small non-coding RNA ...molecules that may play an essential role in regulating radioresistance by altering the levels of oxidative stress. In this study, we investigated the role and potential mechanisms linking miR-31 to PDAC radioresistance. A pCMV-miR vector containing a miR-31 mimic was stably expressed into a miR-31-deficient PDAC cell line, BxPC-3. Additionally, a pmiRZip lentivector suppressing miR-31 was stably expressed in a miR-31 abundant PDAC cell line, Panc-1. Clonogenic assays were conducted to explore the role of miR-31 manipulation on radiosensitivity. Fluorometric ROS assays were performed to quantify ROS levels. The expression of potential miR-31 targets was measured by Western blot analysis. It was found that the manipulation of miR-31 altered the radiosensitivity in PDAC cells by regulating oxidative stress. Using online bioinformatics tools, we identified the 3'UTR of
as a predicted target of miR-31. Our study demonstrates, for the first time, that manipulating miR-31 alters GPx8 expression, regulating ROS detoxification and promoting either a radioresistant or radiosensitive phenotype. MiR-31 may represent a promising therapeutic target for altering radiosensitivity in PDAC cells.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Pancreatic cancer (PC) is regarded as one of the most lethal malignant diseases in the world, with GLOBOCAN 2020 estimates indicating that PC was responsible for almost half a million deaths ...worldwide in 2020. Pancreatic cystic lesions (PCLs) are fluid-filled structures found within or on the surface of the pancreas, which can either be pre-malignant or have no malignant potential. While some PCLs are found in symptomatic patients, nowadays many PCLs are found incidentally in patients undergoing cross-sectional imaging for other reasons-so called 'incidentalomas'. Current methods of characterising PCLs are imperfect and vary hugely between institutions and countries. As such, there is a profound need for improved diagnostic algorithms. This could facilitate more accurate risk stratification of those PCLs that have malignant potential and reduce unnecessary surveillance. As PC continues to have such a poor prognosis, earlier recognition and risk stratification of PCLs may lead to better treatment protocols. This review will focus on the importance of biomarkers in the context of PCLs and PCand outline how current 'omics'-related work could contribute to the identification of a novel integrated biomarker profile for the risk stratification of patients with PCLs and PC.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Glioblastoma multiforme (GBM) is the most common adult primary brain malignancy, with dismal survival rates of ~14.6 months. The current standard-of-care consists of surgical resection and ...chemoradiotherapy, however the treatment response is limited by factors such as tumour heterogeneity, treatment resistance, the blood-brain barrier, and immunosuppression. Several immunotherapies have undergone clinical development for GBM but demonstrated inadequate efficacy, yet future combinatorial approaches are likely to hold more promise. Olaparib is FDA-approved for BRCA-mutated advanced ovarian and breast cancer, and clinical studies have revealed its utility as a safe and efficacious radio- and chemo-sensitiser in GBM. The ability of Olaparib to enhance natural killer (NK) cell-mediated responses has been reported in prostate, breast, and lung cancer. This study examined its potential combination with NK cell therapies in GBM by firstly investigating the susceptibility of the GBM cell line T98G to NK cells and, secondly, examining whether Olaparib can sensitise T98G cells to NK cell-mediated responses. Here, we characterise the NK receptor ligand profile of T98G cells and demonstrate that Olaparib does not dampen T98G susceptibility to NK cells or elicit immunomodulatory effects on the function of NK cells. This study provides novel insights into the potential combination of Olaparib with NK cell therapies for GBM.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Pancreatic ductal adenocarcinoma (PDAC) has a 5-year survival rate below 5%. Carbohydrate antigen 19-9 (CA19-9) is the most commonly used blood-based biomarker for PDAC in current clinical practice, ...despite having been shown repeatedly to be inaccurate and have poor diagnostic performance. This review aims to assess the reported diagnostic accuracy of all blood-based biomarkers investigated to date in PDAC, by directly comparing individual biomarkers and multi-biomarker panels, both containing CA19-9 and not (novel). A systematic review was conducted in accordance with PRISMA standards in July 2020. Individualized search strategies for three academic databases identified 5,885 studies between the years 1973 and 2020. After two rounds of screening, 250 studies were included. Data were extracted and assessed for bias. A multivariate three-level meta-analysis with subgroup moderators was run in R using AUC values as effect size. On the basis of this model, the pooled AUC value for all multi-biomarker panels (AUC = 0.898; 95% confidence interval (CI): 0.88-0.91) was significantly higher than all single biomarkers (AUC = 0.803; 95% CI: 0.78-0.83;
< 0.0001). The pooled AUC value for CA19-9 alone was significantly lower compared with the multi-biomarker panels containing CA19-9 (
< 0.0001). For the novel biomarkers, the pooled AUC for single biomarkers was also significantly lower compared with multi-biomarker panels (
< 0.0001). Novel biomarkers that have been repeatedly examined across the literature, such as TIMP-1, CEA, and CA125, are highlighted as promising. These results suggest that CA19-9 may be best used as an addition to a panel of biomarkers rather than alone, and that multi-biomarker panels generate the most robust results in blood-based PDAC diagnosis.
In a systematic review and three-level multivariate meta-analysis, it is shown for the first time that blood-based multi-biomarker panels for the diagnosis of PDAC exhibit superior performance in comparison with single biomarkers. CA19-9 is demonstrated to have limited utility alone, and to perform poorly in patient control cohorts of both healthy and benign individuals. Multi-biomarker panels containing CA19-9 produce the best diagnostic performance overall.
Abstract
Background: Pancreatic cancer was responsible for almost 500,000 deaths globally in 2020 according to GLOBOCAN 2020. Pancreatic cystic lesions (PCLs) are fluid-filled protrusions either on ...or inside the pancreas. PCLs can either be benign or pre-malignant, however, current guidelines based on clinical features are limited in their ability to accurately stratify patients based on cancer risk. Multi-omic profiling of the pancreatic cyst fluid (PCF) could aid in the identification of a novel biomarker panel of patient cancer risk. Methods: PCF was collected from 40 patients by EUS-FNA. Patients were stratified using the 2018 European evidence-based guidelines into low-risk (n=15), high risk (n=15) and no-risk/pseudocyst (n=10). PCF was sonicated and subsequently processed using a single-pot solid-phase-enhanced sample preparation (SP3) protocol with Sera-Mag SpeedBead carboxylate-modified beads prior to LC-MS. Samples were run on a Thermo Scientific Q Exactive mass spectrometer coupled to a Dionex Ultimate 3000 (RSLCnano) chromatography system. MS-generated proteomic data were analysed in Perseus (v1.6.13). HTG microRNA whole transcriptome sequencing was run on whole PCF. Transcriptomic data were analysed using HTG EdgeSeq Reveal (v3.1). Results: MS-analysis revealed 1,266 proteins present across all PCF samples. Proteins were filtered based on potential contaminants and valid values. Only proteins expressed in a minimum of six PCF samples were included in the analysis. After data clean-up, 465 proteins were examined for differential expression. A total of eight proteins were upregulated in high-risk PCF compared to low-risk (p<0.05, FDR=0.05, s0=0.1). Among them, seven have been shown to be upregulated in pancreatic cancer. Conversely, one protein which is reported to be downregulated in pancreatic cancer, was significantly upregulated in the high-risk patient cohort. A total of 2,096 miRNAs were identified across all PCF samples. MiRNAs were filtered based on fold-change > ±2 between the groups, with 202 miRNAs meeting this criteria. Forty-six miRNAs were significantly upregulated in high-risk PCF compared to low-risk PCF (adj-p<0.05, FDR=0.05, s0=0.1). Five of these miRNAs are known to be upregulated in pancreatic ductal adenocarcinoma (PDAC) tissues. Furthermore, three of the miRNAs are upregulated in the circulation of PDAC patients. Importantly, seven miRNAs identified as being upregulated in high-risk PCF have been shown to be downregulated in PDAC tissues. Differentially expressed proteins and miRNAs are currently being utilised to create an integrated, multi-omic predictive algorithm for patient risk. Conclusion: Multi-omic profiling of pancreatic cyst fluid provides an abundance of potential biomarkers that could be utilised for the stratification of patients into high-and low-risk groups for malignancy. Integration of multi-omic data has the potential to provide more robust biomarker panels of patient risk. Validation of biomarkers in independent patient cohorts will be key to the development of novel clinical biomarkers.
Citation Format: Laura E. Kane, Gregory S. Mellotte, Simone Marcone, Barbara M. Ryan, Stephen G. Maher. Multi-omic profiling of patient pancreatic cyst fluid for the identification of a novel biomarker panel of patient cancer risk abstract. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2021 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2021;81(22 Suppl):Abstract nr PO-009.
Abstract
Background: Pancreatic ductal adenocarcinoma (PDAC) is the most lethal form of pancreatic cancer, being responsible for ~90% of all pancreatic cancers and having a 5-year survival rate of ...~8.5%. The current clinical gold-standard for diagnosis of PDAC is the blood-based biomarker CA19-9. However, many studies have highlighted the limitations of CA19-9, specifically its relatively low sensitivity and specificity, and its inaccuracy in patients with certain underlying conditions. As such, there is an unmet need for robust diagnostic biomarkers for PDAC. Here, the diagnostic accuracy of all blood-based biomarkers examined in PDAC, reporting specifically on CA19-9, multi-marker panels containing CA19-9, novel single markers, and novel multi-marker panels for the diagnosis of PDAC. Methods: A systematic review of blood-based biomarkers for the diagnosis of PDAC was conducted in accordance with PRISMA standards. Individual search strategies using medical subject headings (MeSH) and ‘text words’ were developed for three academic databases: Medline, EMBASE and Web of Science. The 5,885 studies identified were subjected to two rounds of screening by two independent reviewers, with 250 studies being included in the meta-analysis. Data were extracted and assessed for bias using the QUADAS-2 Risk of Bias tool. Data were separated into two subgroups: those including CA19-9, and those without CA19-9 (novel). Patient cohorts examined were classified as “PDAC vs healthy”, “PDAC vs benign” and “PDAC vs mixed”. A multivariate three-level meta-analysis with subgroup moderators was run in R (v1.3.959) on all CA19-9 containing biomarker studies and subsequently on all novel biomarker studies, using reported AUC values as effect size. Results: Based on the three-level meta-analytic model, the pooled AUC value for CA19-9 alone (AUC=0.8473, 95% CI: 0.82-0.87) was significantly lower compared to the multi-marker panels containing CA19-9 (AUC=0.91, 95% CI:0.90-0.93) (p<0.0001). The estimated between-study variance in the model was I2Level 3= 63.55%, and the within-study variance was I2Level 2=36.45%. For the novel markers, the pooled AUC for single markers (AUC=0.79, 95% CI:0.75-0.83) was also significantly lower compared to novel multi-marker panels (AUC=0.87, 95% CI:0.85-0.89) (p<0.0001). Marker robustness was also influenced by the patient cohort examined, with CA19-9 markers performing best in all cohorts compared to novel markers; PDAC vs healthy (AUC=0.91, 95% CI:0.88-0.94), PDAC vs benign (AUC=0.85, 95% CI:0.84-0.87), and PDAC vs mixed (AUC=0.87, 95% CI:0.82-0.91) (p<0.0001). Conclusion: Overall, multi-marker panels show higher pooled AUC values than single markers, for both CA19-9 and novel datasets. Multi-marker panels containing CA19-9 demonstrate the most promising pooled AUC value, with CA19-9 alone performing inferiorly to novel multi-marker panels. These results indicate that CA19-9 may be best used as an addition to a panel of markers rather than alone, and that multi-marker panels ultimately generate the most robust results in a diagnostic capacity.
Citation Format: Laura E. Kane, Gregory S. Mellotte, Eimear Mylod, Rebecca O'Brien, Fiona O'Connell, Khanh Nguyen, Croí E. Buckley, Jennifer Arlow, David Mockler, Aidan D. Meade, Barbara M. Ryan, Stephen G. Maher. Diagnostic accuracy of blood-based multi-omic biomarkers for pancreatic adenocarcinoma: A systematic review and meta-analysis abstract. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2021 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2021;81(22 Suppl):Abstract nr PO-008.
Abstract
Introduction: Pancreatic cancer was responsible for almost 500,000 deaths globally in 2020 according to GLOBOCAN. Pancreatic cystic lesions (PCLs) are fluid-filled protrusions either on or ...inside the pancreas and can either be benign or pre-malignant. Current clinical guidelines to risk stratify PCL patients are imperfect. Multi-omic profiling of pancreatic cyst fluid (PCF) could aid in the identification of a novel biomarker panel to improve PCL risk stratification.
Methods: PCF was collected from 40 patients by EUS-FNA, with matched serum collected prior to EUS. Patients were stratified using the 2018 European evidence-based guidelines into low-risk (n=15), high risk (n=15) and no-risk or pseudocyst (n=10). PCF was sonicated and subsequently processed using an SP3 paramagnetic bead protocol prior to LC-MS. MS-generated LFQ intensity data were analyzed in Perseus (v1.6.13.0) and STRING (v11.5). HTG microRNA whole transcriptome sequencing was run on whole PCF. MiRNA sequencing data were analyzed using HTG EdgeSeq Reveal (v3.1.0). Spearman correlations were generated using R packages ‘Hmisc’ (v4.5-0) and ‘corrplot’ (v0.90).
Results: MS-analysis of PCF revealed 8 proteins to be significantly upregulated in high-risk compared to low-risk (p<0.05, FDR=0.05, s0=0.1). All 8 proteins had significantly positive correlations with patient risk and expression of the other seven. LCN-2, REG1A, LGALS3, PIGR and S100A8 have been shown to be elevated in the blood of pancreatic cancer patients. PRSS8 is known to be elevated in the serum of ovarian cancer patients, while MUC6 and TCN1 have not been shown to be differentially expressed in the circulation of cancer patients. STRING analysis revealed 11.8% and 6.8% of the proteins identified to be involved in the innate and adaptive immune responses, respectively. Significant positive correlations were found between 11 immune-associated proteins and patient risk classification (p<0.05). Whole transcriptome sequencing revealed 3 miRNA (miR-216a-5p, miR-216b-5p and HK_SKORA66) to be significantly upregulated in high-risk PCF compared to low-risk, and 5 miRNA (miR-197-5p, miR-6741-5p, miR-3180-3p, miR-3180 and miR-6782-5p) to be significantly upregulated in matched high-risk serum compared to low-risk (adj-p<0.05, FDR=0.05, s0=0.1). Unsupervised hierarchical clustering of patients using the 8 differentially expressed proteins and 3 miRNA from the PCF gave a clustering accuracy of 95.8%, with just 1/24 patients being misclassified.
Conclusion: We have identified a putative multi-omic biomarker panel for PCL patient risk stratification. Practically, further refinement of this panel through the inclusion of additional biological compartments is required. These data will be validated in a larger patient cohort, with the aim of generating a less invasive blood-based panel that will aid in the improvement of risk stratification.
Citation Format: Laura E. Kane, Gregory S. Mellotte, Rebecca G. Lyons, Eimear Mylod, Simone Marcone, Paul F. Ridway, Finbar MacCarthy, Kevin C. Conlon, Joanne Lysaght, Barbara M. Ryan, Stephen G. Maher. Establishment of a novel multi-omic biomarker panel in cyst fluid and blood for stratifying patient risk of pancreatic cancer abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3381.
Social media has brought about a revolution in fan culture, from fan uprisings to save programs to groups and pages dedicated to mourning lost programs and characters. This edited collection examines ...how fans use social media in regard to television programming, characters, narrative, and various types of interactions, as well as how television uses social media to engage fan cultures.
Thyroxine (T4) seems to accelerate recovery from various forms of acute renal failure. The mechanisms of this effect are still debated. We decided to evaluate if thyroxine enhances the recovery of ...HgCl2 renal failure through an increment in the mitotic activity or through an increase in membrane phospholipid biosynthesis of the regenerating tubular cells. Male Wistar rats were allocated to four groups: one group received 0.4 mg/100g BW HgCl2 SC and saline IP (HgCl2 group); the second received the toxin and 24 and 48 h after it, T4 15 µg/100g BW IP (HgCl2 +T4 Diuretics in Acute Renal Failure group); a third group received saline SC and T4 IP (T4 group), and the last group received saline SC and IP (control group). On the third day GFR was evaluated by 24-h creatinine clearance and afterward rats were sacrificed and the kidneys removed. Some of them were studied histologically, evaluating the severity of the tubular lesion using a semiquantitative score (0-4) and the mitotic index (N mitotic figures per 10 high-power fields). In the other kidneys we studied phospholipid synthesis through the incorporation of 32 P into the different renal phospholipids of the several kidney regions. The T4-treated group had a better recovery of GFR after the toxin (HgCl2 + T4: 0.44 ±. 09 vs. HgCl2: 0.23 ±. 06, p <. 05). Both HgCl2-treated groups had similar lesional scores and mitotic indexes. Phospholipid synthesis, evaluated as the % change of 32 P incorporation to phosphatidylcholine compared to control rats, showed a 21% decrease in incorporation in the HgCl2 group and a 95% increase in the HgCl2 + T4 group in the outer medulla. We conclude that T4 accelerates the recover of HgCl2 through an increase in membrane phospholipid biosynthesis, and not through an increase in the replication of tubular cells.
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