Search

Oncogene : including Oncogene reviews 40(5), 899-908 (2021). doi:10.1038/s41388-020-01578-4, Published by Springer Nature, London

Cancers 14(9), 2190 (2022). doi:10.3390/cancers14092190 special issue: "Special Issue "Perihilar Cholangiocarcinoma" / Special Issue Editors: Dr. Bas Groot Koerkamp, Guest Editor; Dr. Stefan Büttner, Guest Editor; Dr. Pim B. Olthof, Guest Editor", Published by MDPI, Basel

The binding of T cell immune checkpoint proteins programmed death 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) to their ligands allows immune evasion by tumours. The development of therapeutic antibodies, termed checkpoint inhibitors, that bind these molecules or their ligands, has provided a means to release this brake on the host anti-tumour immune response. However, these drugs are costly, are associated with potentially severe side effects, and only benefit a small subset of patients. It is therefore important to identify biomarkers that discriminate between responders and non-responders. This review discusses the determinants for a successful response to antibodies that bind PD-1 or its ligand PD-L1, dividing them into markers found in the tumour biopsy and those in non-tumour samples. It provides an update on the established predictive biomarkers (tumour PD-L1 expression, tumour mismatch repair deficiency and tumour mutational burden) and assesses the evidence for new potential biomarkers.

BackgroundPancreatic cancer continues to have an extremely poor prognosis in part due to late diagnosis. 25% of pancreatic cancer patients have a prior diagnosis of diabetes, and hence identifying individuals at risk of pancreatic cancer in those with recently diagnosed type 2 diabetes may be a useful opportunity to identify candidates for screening and early detection. In this study, we will comparatively evaluate regression and machine learning-based clinical prediction models for estimating individual risk of developing pancreatic cancer two years after type 2 diabetes diagnosis.MethodsIn the development dataset, we will include adults aged 30-84 years with incident type-2 diabetes registered with QResearch primary care database. Patients will be followed up from type-2 diabetes diagnosis to first diagnosis of pancreatic cancer as recorded in any one of primary care records, hospital episode statistics, cancer registry data, or death records. Cox-proportional hazards models will be used to develop a risk prediction model for estimating individual risk of developing pancreatic cancer during up to 2 years of follow-up. We will perform variable selection using a combination of clinical and statistical significance approach i.e. HR 1.1 and pInternal-external cross-validation (IECV) framework across geographical regions within England will be used to assess performance and pooled using random effects meta-analysis using: (i) model fit in terms of variation explained by the model Royston & Sauerbrei’s R2D, (ii) calibration slope and calibration-in-the-large, and (iii) discrimination measured in terms of Harrell’s C and Royston & Sauerbrei’s D-statistic.Further, we will evaluate machine learning (ML) approaches for the clinical prediction model using neural networks (NN) and XGBoost. The model predictors and performance of these will be compared with the results of those derived from the regression-based strategy.DiscussionThe proposed study will develop and validate a novel risk prediction model to aid early diagnosis of pancreatic cancer in patients with new-onset diabetes in primary care. With an enhanced decision-risk tool for use at point-of care by general practitioners to assess pancreatic cancer risk, it may improve decision-making so that at-risk patients are rapidly prioritised to aid early diagnosis of pancreatic cancer in patients with newly diagnosed diabetes.

Immune modulators play a crucial role in carcinogenesis and cancer progression by impairing cancer cell-targeted immune responses. T-cell immunoreceptor with immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domains (TIGIT) regulates T-cell function and cancer cell recognition and was therefore identified as a promising target for cancer immunotherapy. TIGIT is expressed in T cells and natural killer (NK) cells and has three ligands: CD155, CD112 and CD113. CD155 binds TIGIT with the highest affinity and promotes direct and indirect downregulation of T-cell response. TIGIT signalling further inhibits NK function and secretion of proinflammatory cytokines. An association between TIGIT expression and poor survival was identified in multiple cancer entities. Blocking TIGIT with monoclonal antibodies, and a combination of TIGIT and programmed cell death protein 1 blockade in particular, prevented tumour progression, distant metastasis and tumour recurrence in in vivo models. Inhibition of TIGIT is currently evaluated in first clinical trials.

Multimodal, genome-wide characterization of epigenetic and genetic information in circulating cell-free DNA (cfDNA) could enable more sensitive early cancer detection, but it is technologically challenging. Recently, we developed TET-assisted pyridine borane sequencing (TAPS), which is a mild, bisulfite-free method for base-resolution direct DNA methylation sequencing. Here, we optimized TAPS for cfDNA (cfTAPS) to provide high-quality and high-depth whole-genome cell-free methylomes. We applied cfTAPS to 85 cfDNA samples from patients with hepatocellular carcinoma (HCC) or pancreatic ductal adenocarcinoma (PDAC) and noncancer controls. From only 10 ng of cfDNA (1 to 3 ml of plasma), we generated the most comprehensive cfDNA methylome to date. We demonstrated that cfTAPS provides multimodal information about cfDNA characteristics, including DNA methylation, tissue of origin, and DNA fragmentation. Integrated analysis of these epigenetic and genetic features enables accurate identification of early HCC and PDAC.

Cancers 13(15), 3661 (2021). doi:10.3390/cancers13153661, Published by MDPI, Basel

Liver cancer 10(3), 260-274 (2021). doi:10.1159/000515303, Published by Karger, Basel

Pancreatic ductal adenocarcinoma (PDAC) is the most common malignancy of the pancreas and has one of the highest mortality rates of any cancer type with a 5‐year survival rate of, What's new? While several transcriptomic classifications of pancreatic adenocarcinoma (PDAC) have been proposed, a unified classification would be valuable to inform future treatment strategies. Through an integrative meta‐analysis of 353 patients from four different studies, the authors found that the greatest prognostic value in independent cohorts could be achieved through stratification by gene expression signatures associated with tumour‐infiltrating immune cells across different pancreatic cancer subtypes. Recognising the existence of different tumour escape mechanisms (and indeed phenotypes) in pancreatic cancer may guide immunotherapeutic treatment plans and improve patient stratification for maximization of therapeutics.

TPS4183 Background: Overall survival remains low for pts with mPDAC despite approved therapies, highlighting the need for further innovative treatment options. Intra-tumoral fibrosis that characterizes PDAC has been associated with a state of immune exclusion and may constitute a mechanical obstacle to the intra-tumoral penetration of chemotherapy as well as contribute to the lack of efficacy of immunotherapy. TGF-β plays a key role in regulating the tumor microenvironment and emerging evidence points to its role as a pivotal activator of cancer-associated fibroblasts, leading to the development of fibrotic networks. Preclinical data in murine models have shown that TGF-β blockade augmented the antitumor activity of both NG and anti-PD-1 therapy, leading to tumor regression. These data provide the rationale for combining TGF-β-targeting agents with immunotherapy and chemotherapy. NIS793 is a human IgG2 mAb that binds to TGF-β. This study investigates NIS793 with and without spartalizumab (PD-1 antagonist) combined with NG in treatment naïve mPDAC. Methods: This is a phase II open-label, randomized, multicenter study (NCT04390763) beginning with a safety run-in period followed by randomization. Eligible pts are adults with previously untreated mPDAC and ECOG performance status score ≤1. Pts are excluded if they have a microsatellite-unstable tumor. The safety run-in data will be analyzed after ≥6 pts have received NIS793 (intravenously [IV] 2100 mg Q2W) + spartalizumab (IV 400 mg Q4W) + nab-paclitaxel (IV 125 mg/m2 on Days 1, 8 and 15) + gemcitabine (IV 1000 mg/m2 on Days 1, 8 and 15) for 1 cycle (28 days) to assess the safety and tolerability of the combination. In the randomized part, pts will be randomized 1:1:1 to NIS793 + spartalizumab + NG (n = 50) or NIS793 + NG (n = 50) or NG (n = 50). Treatment will continue until unacceptable toxicity, disease progression, discontinuation by investigator’s/pt’s choice, or withdrawal of consent. The primary objective is to evaluate the progression-free survival per RECIST 1.1, of NIS793 + NG ± spartalizumab versus NG alone. Secondary objectives include safety and tolerability, antitumor activity, overall survival, change in tumoral CD8 and PD-L1 status, and characterization of immunogenicity and pharmacokinetics. Efficacy will be assessed locally per RECIST v1.1 and iRECIST at screening, every 8 weeks for 1 year and then every 12 weeks until disease progression. Blood and tumor samples will be taken at baseline and during study treatment for pharmacokinetic, immunogenicity and biomarker assessments. This study is ongoing and will enroll pts from 31 sites across 14 countries. The first pt was treated on October 22, 2020. Enrollment for the randomized part of the study started on August 09, 2021. Clinical trial information: NCT04390763.

Simple Summary Pancreatic cancer has the worst survival of any human cancer. Checkpoint blockade has not yielded much benefit in pancreatic cancer. We explored immune cell phenotypes with this disease to identify new targets for checkpoint blockade therapy. We created a checkpoint-focused panel to analyse immune cells from eight pancreatic cancer patients. This showed us the majority of T-cells are senescent. Further T-cell investigation demonstrated the majority of cytotoxic T-cells have intermediate to low PD1 expression suggesting why PD1 may not work as a pancreatic cancer therapy strategy. Our data has also highlighted a regulatory T-cell population which is highly activated and can mediate immunosuppression. The checkpoints that are highly expressed on these cells are TIGIT, ICOS and CD39, suggesting inhibition of these may be a viable therapeutic strategy. Furthermore, we showed that Tregs were retained amongst the fibroblast stroma of the tumour. Our work suggests there are key checkpoints on Tregs that may help guide therapeutic strategies in pancreatic cancer. Abstract Pancreatic cancer has one of the worst prognoses of any human malignancy and leukocyte infiltration is a major prognostic marker of the disease. As current immunotherapies confer negligible survival benefits, there is a need to better characterise leukocytes in pancreatic cancer to identify better therapeutic strategies. In this study, we analysed 32 human pancreatic cancer patients from two independent cohorts. A multi-parameter mass-cytometry analysis was performed on 32,000 T-cells from eight patients. Single-cell RNA sequencing dataset analysis was performed on a cohort of 24 patients. Multiplex immunohistochemistry imaging and spatial analysis were performed to map immune infiltration into the tumour microenvironment. Regulatory T-cell populations demonstrated highly immunosuppressive states with high TIGIT, ICOS and CD39 expression. CD8+ T-cells were found to be either in senescence or an exhausted state. The exhausted CD8 T-cells had low PD-1 expression but high TIGIT and CD39 expression. These findings were corroborated in an independent pancreatic cancer single-cell RNA dataset. These data suggest that T-cells are major players in the suppressive microenvironment of pancreatic cancer. Our work identifies multiple novel therapeutic targets that should form the basis for rational design of a new generation of clinical trials in pancreatic ductal adenocarcinoma.

Journal of Clinical Medicine 10(3), 490 (2021). doi:10.3390/jcm10030490 special issue: "Special Issue "Pancreatic Cancer: Challenges and Breakthroughs" / Special Issue Editor: Dr. Maria Del Pilar Acedo Nunez, Guest Editor", Published by MDPI, Basel

BackgroundB cells and tertiary lymphoid structures (TLS) are reported to be important in the improvement of survival of cancer patients. These secondary lymphoid organs have been associated with the generation of an anti-tumor response. Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancer types and the stromal architecture shapes the intratumoral heterogeneity. The stroma of PDAC is a complex system in which crosstalk takes place between cancer-associated fibroblasts, immune cells, endothelial cells and the cancer cells. Besides immune cells and fibroblasts, there is some limited data about the influence of nerve fibers on cancer progression.Patients and methodsNerve Fiber Density (NFD) was analysed in our cohort of 188 patients with Pancreatic Ductal Adenocarcinoma who underwent pancreatic surgery. We used immunohistochemistry and multiplex imaging to phenotype the immune cell infiltrate. The cell detection classifier measured distance from immune cell to cancer gland and with a heat map we could count TLS. By using Machine learning we were able to define the spatial distribution and counting Tertiary Lymphoid Structures.ResultsHigh NFD is significantly associated with prolonged overall survival (HR 1.676 (95%CI 1.126,2.495) for low vs. high NFD, p-value 0.0109). The immune cells surrounding the nerve fibers were phenotyped in B cells, T cells and dendritic follicular cells, matching a TLS. Here we show that small nerve fibers are located at the TLS in Pancreatic Cancer and a high Nerve Fiber Density combined with more than 5 TLS is associated with a better survival (HR 0.388 (95%CI 0.218, 0.689).ConclusionThe co-localization of small nerve fibers with TLS is a new finding which has not been described before. However the precise roles of these TLS and nerve fibers remains unknown. These findings unravel future pathways and has the potential to reach new directions into already existing targeted therapy.

Pancreatic cancer has the worst prognosis of any human malignancy and leukocyte infiltration is a major prognostic marker of the disease. As current immunotherapies confer negligible survival benefits, there is a need to better characterise leukocytes in pancreatic cancer to identify better therapeutic strategies.In this study, we analysed 32 human pancreatic cancer patients from two independent cohorts. A multi-parameter mass-cytometry analysis was performed on 32,000 T-cells from eight patients. Single-cell RNA sequencing dataset analysis was performed on a cohort of 24 patients. Multiplex immunohistochemistry imaging and spatial analysis were performed to map immune infiltration into the tumour microenvironment.Regulatory T-cell populations demonstrated highly immunosuppressive states with high TIGIT, ICOS and CD39 expression. CD8+ T-cells were found to be either in senescence or an exhausted state. The exhausted CD8 T-cells had low PD-1 expression but high TIGIT and CD39 expression. These findings were corroborated in an independent pancreatic cancer single-cell RNA dataset from additional 24 patients.These data suggest that T-cells are major players in the suppressive microenvironment of pancreatic cancer. Our work identifies novel therapeutic targets that should form the basis for rational design of a new generation of clinical trials in pancreatic ductal adenocarcinoma.

Introduction In this study (PRECISE), we assess the clinical utility of a germline DNA sequencing‐based test (ToxNav) for mutations in DPYD and ENOSF1 genes to alter clinician‐prescribed fluoropyrimidine doses and the use of a digital application (PROMinet) to record patient‐reported chemotherapy toxicity. Materials and methods Adult patients with a histological diagnosis of colorectal cancer (CRC) who consented to fluoropyrimidine‐based chemotherapy were recruited prospectively and given a digital application to monitor and record associated toxicities. Patient samples were analyzed for 18 germline coding variants in DPYD and 1 ENOSF1 variant. Results Genetic testing was performed for 60 patients and identified one patient at increased risk of fluoropyrimidine‐based toxicities. Uptake of genetic testing was high and results were available on average 17 days from initial clinical encounter. Patient‐reported chemotherapy toxicity identified differences in 5‐fluorouracil vs capecitabine regime profiles and identified profiles associated with subsequent need for chemotherapy dose reduction and hospital admission. Discussion The PRECISE clinical trial demonstrated that a germline DNA sequencing‐based test can provide clinically relevant information to alter clinicians' fluoropyrimidine prescription. The study also obtained high volume, high granularity patient‐reported toxicity data that might allow the improvement and personalization of chemotherapy management., In the PRECISE study, we assess the clinical utility of a germline DNA sequencing‐based test to alter clinician‐prescribed fluoropyrimidine doses and the use of a digital application to record patient‐reported chemotherapy toxicity. Genetic testing identified one patient at increased risk of fluoropyrimidine‐based toxicities and patient‐reported toxicity identified differences in chemotherapy regime profiles and association with subsequent need for chemotherapy dose reduction and hospital admission. The study demonstrated the clinical utility of a germline DNA sequencing‐based test for providing information to alter clinicians' fluoropyrimidine prescription and obtained high volume, high granularity patient‐reported toxicity data.

TPS4173 Background: Overall survival remains low for pts with mPDAC despite approved therapies, highlighting the need for further innovative treatment options. Intra-tumoral fibrosis that characterizes PDAC has been associated with a state of immune exclusion and may constitute a mechanical obstacle to the penetration of chemotherapy into the tumor as well as contribute to the lack of efficacy of immunotherapy. TGF-β plays a key role in regulating the tumor microenvironment and emerging evidence points to TGF-β as a pivotal activator of cancer-associated fibroblasts, leading to the development of fibrotic networks. Preclinical data in murine models have shown that TGF-β blockade augmented the benefit of both NG and anti-PD-1 therapy, leading to tumor regression. These data provide the rationale for combining TGF-β-targeting agents with immunotherapy and chemotherapy. NIS793 is a human IgG2 mAb that binds to TGF-β. This study investigates NIS793 with and without spartalizumab combined with NG in treatment naïve mPDAC. Methods: This is a phase II open-label, randomized, multicenter study (NCT04390763) beginning with a safety run-in period followed by randomization. Eligible pts are adults with previously untreated mPDAC and an ECOG performance status ≤1. Pts are excluded if they have a tumor histology other than adenocarcinoma or microsatellite instability-high tumor. The safety run-in data will be analyzed after ≥6 pts have received NIS793 (intravenously [IV] 2100 mg Q2W) + spartalizumab (IV 400 mg Q4W) + nab-paclitaxel (IV 125 mg/m2 on Days 1, 8 and 15) + gemcitabine (IV 1000 mg/m2 on Days 1, 8 and 15) for 1 cycle (28 days) to assess the safety and tolerability of the combination and confirm the dose for the randomized part. Pts will be randomized 1:1:1 to NIS793 + spartalizumab + NG (n=50) or NIS793 + NG (n=50) or NG (n=50). Treatment will continue until unacceptable toxicity, disease progression, discontinuation by investigator’s or pt’s choice, or withdrawal of consent. The primary objective is to evaluate the progression-free survival of NIS793 + NG ± spartalizumab versus NG alone. Secondary objectives include safety and tolerability, antitumor activity, overall survival, change in CD8 and PD-L1 status, and characterization of immunogenicity and pharmacokinetics. Efficacy will be assessed locally per RECIST v1.1 and iRECIST at screening, every 8 weeks for 1 year and then every 12 weeks until disease progression. Blood and tumor samples will be taken at baseline and during study treatment for pharmacokinetic, immunogenicity and biomarker assessments. This study is ongoing and will enroll pts from 30 sites across 15 countries. The first pt was treated on October 22, 2020. Clinical trial information: NCT04390763.

Simple Summary Pancreatic ductal adenocarcinoma (PDAC) has a poor 5-year survival rate and is the 7th leading cause of cancer-related deaths in the world. The high mortality for this disease is partly due to late presentation rendering therapeutics ineffective. Since a majority of patients are diagnosed at advanced stages due to the lack of specific symptoms, and the prognosis is linked to the stage of detection, there is a need for robust early detection methods for PDAC. Here, we review the potential use of circulating tumour DNA (ctDNA) as a non-invasive biomarker in the early detection of pancreatic cancer. In brief ctDNA levels in blood correlate with disease progression but its widespread application for early PDAC detection requires further investigation and potentially, a combination of ctDNA sequence and methylome analysis with other, protein-based biomarkers. Abstract Pancreatic cancer is a lethal disease, with mortality rates negatively associated with the stage at which the disease is detected. Early detection is therefore critical to improving survival outcomes. A recent focus of research for early detection is the use of circulating cell-free tumour DNA (ctDNA). The detection of ctDNA offers potential as a relatively non-invasive method of diagnosing pancreatic cancer by using genetic sequencing technology to detect tumour-specific mutational signatures in blood samples before symptoms manifest. These technologies are limited by a number of factors that lower sensitivity and specificity, including low levels of detectable ctDNA in early stage disease and contamination with non-cancer circulating cell-free DNA. However, genetic and epigenetic analysis of ctDNA in combination with other standard diagnostic tests may improve early detection rates. In this review, we evaluate the genetic and epigenetic methods under investigation in diagnosing pancreatic cancer and provide a perspective for future developments.

Background The COVID-19 pandemic required a rapid response and need for real-world data in cancer patients. The nationwide, real-time coordinated UKCCMP reporting network provided an immediate solution. Methods The ability to set up an interdisciplinary multi-organisational team quickly, covering expert knowledge from clinical, legal, statistical, and computer science was essential. The technical infra-structure allows clinician-led anonymised data entry and rapid dissemination of results with a clinical (RedCap) database as core. However the development of a national cancer reporting network was crucial for the viability of the project. From its inception in March 2020 the reporting network was established via 4 iterative phases. Results Within the first 4 weeks, >50 centres were involved with coverage throughout the UK. Expansion has continued with >70 centres within 6 weeks reporting over 1200 COVID positive cancer patients. This was achieved through a 4-phase approach: phase 1 - Outline: This involved project protocol development where key data and timelines were confirmed by a small project team followed by whole-team sign-off. phase 2 - Engagement: This involved identification and engagement of existing groups to establish an initial network. Professional body endorsement led to increased recognition and utilisation of their membership networks. Finally regional leads were identified. phase 3 - Invitation: The third phase involved the distribution of a formal invite letter via identified networks. Project specific email and standard mailing lists were created to enhance network identity and communication. phase 4 - Consolidation: Early development of an interactive project website and focus on communication via social media with varied content consolidated interest and led to further extension. Conclusions Real-time reporting of real world data can be achieved with clearly defined project phases, standardised documentation and an iterative recruitment process. The COVID-19 pandemic necessitated a rapid response, proving that similar reporting networks can be set up quickly and robustly to react to the evidence-based needs of the oncology community in the drive for implementation of change. Legal entity responsible for the study The authors. Funding Has not received any funding. Disclosure A.C. Olsson-Brown: Honoraria (self): Roche; Honoraria (institution): Roche; Honoraria (self): Bristol Myers Squibb; Research grant/Funding (institution): Bristol Myers Squibb; Research grant/Funding (institution): USB Pharma; Research grant/Funding (institution): Eli Lily; Research grant/Funding (institution): Novartis. D.J. Hughes: Honoraria (self): Novartis; Research grant/Funding (self): NanoMab Technology LtD. S. Sivakumar: Research grant/Funding (self): Celgene. All other authors have declared no conflicts of interest.

Background: Pancreatic cancer has the worst prognosis of any human malignancy. We have shown using transcriptomics and histopathology that immune infiltrate in resection samples from a Whipple’s operation is predictive of prognosis. In particular, lymphocytes appear to be a major prognostic marker. With promising immunotherapies being proposed for other cancers, there is a need for a deeper understanding of the immune landscape of pancreatic cancer to identify points of intervention. Methods: We have developed a 37-marker mass cytometry staining panel to characterize the dominant immune populations within primary pancreatic cancer. Our panel further analyzes T-cell subpopulations and their functional status, including a host of clinically relevant checkpoint markers and immunosuppressive signatures. Results: The degree of immune infiltration we observe is highly variable between patients, but all patients equivocally show a complex immune microenvironment consistent of macrophages, neutrophils, and different lymphocytes. The T cells infiltrating the tumor, both CD4 and CD8 T cells, appear to be dysfunctional with hardly any activation signature. A highly suppressive phenotype also characterizes the regulatory T-cell population. Our data suggest that the microenvironment of pancreatic cancer is extremely suppressive and could be a major driver of poor prognosis. Yet, this work identifies potential therapeutic targets and avenues that should be further investigated and may inspire future clinical trials. Future Work: We are planning to investigate the behavior of T-regs from PDAC using in vitro assays. To that end, we will use a recently developed advanced 3D culture system to visualize their interactions with CD8s and the functional consequences of those interactions on CD8-mediated killing. Citation Format: Shivan Sivakumar, Enas Abu-Shah, David Ahern, Nagina Mangal, Srikanth Reddy, Aniko Rendek, Zahir Soonawalla, Michael Silva, Mark Middleton, Michael L. Dustin. T-cell regulation in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2019 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(3 Suppl):Abstract nr A91.

Pancreatic cancer has the worst prognosis of any human malignancy. Our recent work has shown that immune infiltrate by transcriptomics and histopathology can predict prognosis after a Whipple’s operation, with lymphocyte infiltration being the most important prognostic marker. We have profiled T cells within primary pancreatic cancer to understand the T-cell architecture within the tumor. We have used a 37-marker T cell-focused panel to study the immune infiltrate. We see a diverse immunosuppressive immune microenvironment within the primary tumor. There is a complex architecture of macrophages, neutrophils, and T cells. The commonest CD4 T cells in the microenvironment are Tregs. There are potential novel therapeutic strategies for Tregs using unique checkpoint inhibitors. The CD8 T cells have PD-1 activity but are not activated or proliferating. The poor prognosis of pancreatic cancer could be explained by the immunosuppressive microenvironment, but there are opportunities to drug Tregs in this disease. Citation Format: Shivan Sivakumar, Enas Abu Shah, David Ahern, Nagina Mangal, Srikanth Reddy, Aniko Rendek, Zahir Soonawalla, Michael Silva, Mark Middleton, Michael Dustin. The T-cell architecture of pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2019 Sept 6-9; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2019;79(24 Suppl):Abstract nr B52.

Pre-analytical factors can significantly affect circulating cell-free DNA (cfDNA) analysis. However, there are few robust methods to rapidly assess sample quality and the impact of pre-analytical processing. To address this gap and to evaluate effects of DNA extraction methods and blood collection tubes on cfDNA yield and fragment size, we developed a multiplexed droplet digital PCR (ddPCR) assay with 5 short and 4 long amplicons targeting single copy genomic loci. Using this assay, we compared 7 cfDNA extraction kits and found cfDNA yield and fragment size vary significantly. We also compared 3 blood collection protocols using plasma samples from 23 healthy volunteers (EDTA tubes processed within 1 hour and Cell-free DNA Blood Collection Tubes processed within 24 and 72 hours) and found no significant differences in cfDNA yield, fragment size and background noise between these protocols. In 219 clinical samples, cfDNA fragments were shorter in plasma samples processed immediately after venipuncture compared to archived samples, suggesting contribution of background DNA by lysed peripheral blood cells. In summary, we have described a multiplexed ddPCR assay to assess quality of cfDNA samples prior to downstream molecular analyses and we have evaluated potential sources of pre-analytical variation in cfDNA studies.

Pancreatic ductal adenocarcinoma (PDAC) is the most common malignancy of the pancreas and has one of the highest mortality rates of any cancer type with a 5-year survival rate of < 5% and median overall survival of typically six months from diagnosis. Recent transcriptional studies of PDAC have provided several competing stratifications of the disease. However, the development of therapeutic strategies will depend on a unique and coherent classification of PDAC. Here, we use an integrative meta-analysis of four different PDAC gene expression studies to derive the consensus PDAC classification. Despite the fact that immunotherapies have yet to have an impact in treatment of PDAC, the gene expression signatures that stratify PDAC across studies are immunologic. We define these as “adaptive”, “innate” and “immune-exclusion” immunologic signatures, which are prognostic across independent cohorts. An appreciation of the immune composition of PDAC with prognostic significance is an opportunity to understand distinct immune escape mechanisms in development of the disease and design novel immune-oncology therapeutic strategies to overcome current barriers.

Pre-analytical factors can significantly affect circulating cell-free DNA (cfDNA) analysis. However, there are few robust methods to rapidly assess sample quality and the impact of pre-analytical processing. To address this gap and to evaluate effects of DNA extraction methods and blood collection tubes on cfDNA yield and fragment size, we developed a multiplexed droplet digital PCR (ddPCR) assay with 5 short and 4 long amplicons targeting single copy genomic loci (mean amplicon size: 71 bp and 471 bp respectively). Using this assay, we compared performance of 7 cfDNA extraction kits and found cfDNA yield and fragment size varies significantly between them. We also compared 3 blood collection protocols used to collect plasma samples from 23 healthy volunteers (EDTA tubes processed within 1 hour and Cell-free DNA BCT tubes at ambient temperature processed within 24 hours and 72 hours of collection). To assess whether cell-stabilizing preservative in BCT tubes introduced noise in cfDNA, we performed digital targeted sequencing. We found no significant differences in cfDNA yield, fragment size and background sequencing noise between these protocols. In 219 clinical samples tested for quality using the ddPCR assay, cfDNA fragment size was significantly shorter in plasma samples immediately processed for ctDNA analysis compared to archived samples, suggesting background DNA contributed by lysed peripheral blood cells. In summary, we describe a multiplexed ddPCR approach that enables cfDNA quality assessment and could inform the design of future circulating tumor DNA studies.Gene namesNone

Translational medicine bridges the gap between discoveries in biomedical science and their safe and effective clinical application. Despite the gross opportunity afforded by modern research for unparalleled advances in this field, the process of translation remains protracted. Efforts to expedite science translation have included the facilitation of interdisciplinary collaboration within both academic and clinical environments in order to generate integrated working platforms fuelling the sharing of knowledge, expertise, and tools to align biomedical research with clinical need. However, barriers to scientific translation remain, and further progress is urgently required. Collective intelligence and crowdsourcing applications offer the potential for global online networks, allowing connection and collaboration between a wide variety of fields. This would drive the alignment of biomedical science with biotechnology, clinical need, and patient experience, in order to deliver evidence-based innovation which can revolutionize medical care worldwide. Here we discuss the critical steps towards implementing collective intelligence in translational medicine using the experience of those in other fields of science and public health.

A survey of 764 medical undergraduates explored their preferred careers information sources. Students wished to access careers information from a variety of sources but most valued face-to-face interviews with both trained careers counsellors and senior medical colleagues.