High SIRT1 expression is a negative prognosticator in pancreatic ductal adenocarcinoma

Background: Several lines of evidence indicate that Sirt1, a class III histone deacetylase (HDAC) is implicated in the initiation and progression of malignancies and thus gained attraction as druggable target. Since data on the role of Sirt1 in pancreatic ductal adenocarcinoma (PDAC) are sparse, we investigated the expression profile and prognostic significance of Sirt1 in vivo as well as cellular effects of Sirt1 inhibition in vitro. Methods: Sirt1 expression was analyzed by immunohistochemistry in a large cohort of PDACs and correlated with clinicopathological and survival data. Furthermore, we investigated the impact of overexpression and small molecule inhibition on Sirt1 in pancreatic cancer cell culture models including combinatorial treatment with chemotherapy and EGFR-inhibition. Cellular events were measured quantitatively in real time and corroborated by conventional readouts including FACS analysis and MTT assays. Results: We detected nuclear Sirt1 expression in 36 (27.9%) of 129 PDACs. SIRT1 expression was significantly higher in poorly differentiated carcinomas. Strong SIRT1 expression was a significant predictor of poor survival both in univariate (p = 0.002) and multivariate (HR 1.65, p = 0.045) analysis. Accordingly, overexpression of Sirt1 led to increased cell viability, while small molecule inhibition led to a growth arrest in pancreatic cancer cells and impaired cell survival. This effect was even more pronounced in combinatorial regimens with gefitinib, but not in combination with gemcitabine. Conclusions: Sirt1 is an independent prognosticator in PDACs and plays an important role in pancreatic cancer cell growth, which can be levered out by small molecule inhibition. Our data warrant further studies on SIRT1 as a novel chemotherapeutic target in PDAC

Oncolytic virotherapy for metastatic breast cancer – a case report

BackgroundBreast cancer is one of the most common malignancies worldwide and remains incurable after metastasis, with a 3-year overall survival rate of <40%.Case presentationA 40-year-old, Caucasian patient with a grade-3 estrogen receptor-, progesterone receptor-, Her2-positive breast tumor and two lung nodules was treated with intramuscular targeted immunotherapy with trastuzumab and oral tamoxifen hormone therapy, together with customized intra-tumoral oncolytic virotherapy (IT-OV) over a 17-month period. PET/CT imaging at 3 and 6 months showed increased primary tumor size and metabolic glucose uptake in the primary tumor, axillary lymph nodes and lung nodules, which were paralleled by a hyperimmune reaction in the bones, liver, and spleen. Thereafter, there was a steady decline in both tumor size and metabolic activity until no radiographic evidence of disease was observed. The treatment regimen was well tolerated and good quality of life was maintained throughout.ConclusionIntegration of IT-OV immunotherapy in standard treatment protocols presents an attractive modality for late-stage primary tumors with an abscopal effect on metastases

Bcl3 Couples Cancer Stem Cell Enrichment With Pancreatic Cancer Molecular Subtypes

[Background & Aims]: The existence of different subtypes of pancreatic ductal adenocarcinoma (PDAC) and their correlation with patient outcome have shifted the emphasis on patient classification for better decision-making algorithms and personalized therapy. The contribution of mechanisms regulating the cancer stem cell (CSC) population in different subtypes remains unknown. [Methods]: Using RNA-seq, we identified B-cell CLL/lymphoma 3 (BCL3), an atypical nf-κb signaling member, as differing in pancreatic CSCs. To determine the biological consequences of BCL3 silencing in vivo and in vitro, we generated bcl3-deficient preclinical mouse models as well as murine cell lines and correlated our findings with human cell lines, PDX models, and 2 independent patient cohorts. We assessed the correlation of bcl3 expression pattern with clinical parameters and subtypes. [Results]: Bcl3 was significantly down-regulated in human CSCs. Recapitulating this phenotype in preclinical mouse models of PDAC via BCL3 genetic knockout enhanced tumor burden, metastasis, epithelial to mesenchymal transition, and reduced overall survival. Fluorescence-activated cell sorting analyses, together with oxygen consumption, sphere formation, and tumorigenicity assays, all indicated that BCL3 loss resulted in CSC compartment expansion promoting cellular dedifferentiation. Overexpression of BCL3 in human PDXs diminished tumor growth by significantly reducing the CSC population and promoting differentiation. Human PDACs with low BCL3 expression correlated with increased metastasis, and BCL3-negative tumors correlated with lower survival and nonclassical subtypes. [Conclusions]: We demonstrate that bcl3 impacts pancreatic carcinogenesis by restraining CSC expansion and by curtailing an aggressive and metastatic tumor burden in PDAC across species. Levels of BCL3 expression are a useful stratification marker for predicting subtype characterization in PDAC, thereby allowing for personalized therapeutic approaches.This work was supported by the Deutsche Forschungsgemeinschaft (grants AL 1174/4-1, AL1174/4-2, and Collaborative Research Center 1321 “Modeling and Targeting Pancreatic Cancer” to Hana Algül; SFB824 Z2 to Katja Steiger), the Deutsche Krebshilfe (grant 111646 to Hana Algül), a Ramon y Cajal Merit Award from the Ministerio de Economía y Competitividad, Spain (to Bruno Sainz Jr), a Coordinated Grant from Fundación Asociación Española Contra el Cáncer (GC16173694BARB to Bruno Sainz Jr), funding from The Fero Foundation (to Bruno Sainz Jr), and a Proyecto de Investigacion de Salud, ISCIII, Spain (no. PI18/00757 to Bruno Sainz Jr). Jiaoyu Ai is supported by the “China Scholarship Council” grant program

Aggressive PDACs show hypomethylation of repetitive elements and the execution of an intrinsic IFN program linked to a ductal cell of origin

Pancreatic ductal adenocarcinoma (PDAC) is characterized by extensive desmoplasia, which challenges the molecular analyses of bulk tumor samples. Here we FACS-purified epithelial cells from human PDAC and normal pancreas and derived their genome-wide transcriptome and DNA methylome landscapes. Clustering based on DNA methylation revealed two distinct PDAC groups displaying different methylation patterns at regions encoding repeat elements. Methylation(low) tumors are characterized by higher expression of endogenous retroviral (ERV) transcripts and dsRNA sensors which leads to a cell intrinsic activation of an interferon signature (IFNsign). This results in a pro-tumorigenic microenvironment and poor patient outcome. Methylation(low)/IFNsign(high) and Methylation(high)/IFNsign(low) PDAC cells preserve lineage traits, respective of normal ductal or acinar pancreatic cells. Moreover, ductal-derived Kras(G12D)/Trp53(−/−) mouse PDACs show higher expression of IFNsign compared to acinar-derived counterparts. Collectively, our data point to two different origins and etiologies of human PDACs, with the aggressive Methylation(low)/IFNsign(high) subtype potentially targetable by agents blocking intrinsic IFN-signaling

Neoadjuvant chemotherapy is associated with suppression of the B cell-centered immune landscape in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is typically diagnosed at advanced stages and associated with early distant metastasis and poor survival. Besides clinical factors, the tumor microenvironment (TME) emerged as a crucial determinant of patient survival and therapy response in many tumors, including PDAC. Thus, the presence of tumor-infiltrating lymphocytes and the formation of tertiary lymphoid structures (TLS) is associated with longer survival in PDAC. Although neoadjuvant therapy (NeoTx) has improved the management of locally advanced tumors, detailed insight into its effect on various TME components is limited. While a remodeling towards a proinflammatory state was reported for PDAC-infiltrating T cells, the effect of NeoTx on B cell subsets, including plasma cells, and TLS formation is widely unclear. We thus investigated the frequency, composition, and spatial distribution of PDAC-infiltrating B cells in primary resected (PR) versus neoadjuvant-treated patients using a novel multiplex immunohistochemistry panel. The NeoTx group displayed significantly lower frequencies of pan B cells, GC B cells, plasmablasts, and plasma cells, accompanied by a reduced abundance of TLS. This finding was supported by bulk RNA-sequencing analysis of an independent fresh frozen tissue cohort, which revealed that major B cell pathways were downregulated in the NeoTx group. We further observed that plasma cells frequently formed aggregates that localized close to TLS and that TLS+ patients displayed significantly higher plasma cell frequencies compared to TLS- patients in the PR group. Additionally, high densities of CD20+ intratumoral B cells were significantly associated with longer overall survival in the PR group. While CD20+ B cells held no prognostic value for NeoTx patients, an increased frequency of proliferating CD20+Ki67+ B cells emerged as an independent prognostic factor for longer survival in the NeoTx group. These results indicate that NeoTx differentially affects PDAC-infiltrating immune cells and may have detrimental effects on the existing B cell landscape and the formation of TLS. Gaining further insight into the underlying molecular mechanisms is crucial to overcome the intrinsic immunotherapy resistance of PDAC and develop novel strategies to improve the long-term outcome of PDAC patients

Traces of trauma – a multivariate pattern analysis of childhood trauma, brain structure and clinical phenotypes

Background: Childhood trauma (CT) is a major yet elusive psychiatric risk factor, whose multidimensional conceptualization and heterogeneous effects on brain morphology might demand advanced mathematical modeling. Therefore, we present an unsupervised machine learning approach to characterize the clinical and neuroanatomical complexity of CT in a larger, transdiagnostic context. Methods: We used a multicenter European cohort of 1076 female and male individuals (discovery: n = 649; replication: n = 427) comprising young, minimally medicated patients with clinical high-risk states for psychosis; patients with recent-onset depression or psychosis; and healthy volunteers. We employed multivariate sparse partial least squares analysis to detect parsimonious associations between combinations of items from the Childhood Trauma Questionnaire and gray matter volume and tested their generalizability via nested cross-validation as well as via external validation. We investigated the associations of these CT signatures with state (functioning, depressivity, quality of life), trait (personality), and sociodemographic levels. Results: We discovered signatures of age-dependent sexual abuse and sex-dependent physical and sexual abuse, as well as emotional trauma, which projected onto gray matter volume patterns in prefronto-cerebellar, limbic, and sensory networks. These signatures were associated with predominantly impaired clinical state- and trait-level phenotypes, while pointing toward an interaction between sexual abuse, age, urbanicity, and education. We validated the clinical profiles for all three CT signatures in the replication sample. Conclusions: Our results suggest distinct multilayered associations between partially age- and sex-dependent patterns of CT, distributed neuroanatomical networks, and clinical profiles. Hence, our study highlights how machine learning approaches can shape future, more fine-grained CT research

KRT81 and HNF1A expression in pancreatic ductal adenocarcinoma: investigation of predictive and prognostic value of immunohistochemistry‐based subtyping

Abstract Even after decades of research, pancreatic ductal adenocarcinoma (PDAC) remains a highly lethal disease and responses to conventional treatments remain mostly poor. Subclassification of PDAC into distinct biological subtypes has been proposed by various groups to further improve patient outcome and reduce unnecessary side effects. Recently, an immunohistochemistry (IHC)‐based subtyping method using cytokeratin‐81 (KRT81) and hepatocyte nuclear factor 1A (HNF1A) could recapitulate some of the previously established molecular subtyping methods, while providing significant prognostic and, to a limited degree, also predictive information. We refined the KRT81/HNF1A subtyping method to classify PDAC into three distinct biological subtypes. The prognostic value of the IHC‐based method was investigated in two primary resected cohorts, which include 269 and 286 patients, respectively. In the second cohort, we also assessed the predictive effect for response to erlotinib + gemcitabine. In both PDAC cohorts, the new HNF1A‐positive subtype was associated with the best survival, the KRT81‐positive subtype with the worst, and the double‐negative with an intermediate survival (p < 0.001 and p < 0.001, respectively) in univariate and multivariate analyses. In the second cohort (CONKO‐005), the IHC‐based subtype was additionally found to have a potential predictive value for the erlotinib‐based treatment effect. The revised IHC‐based subtyping using KRT81 and HNF1A has prognostic significance for PDAC patients and may be of value in predicting treatment response to specific therapeutic agents

A machine learning algorithm predicts molecular subtypes in pancreatic ductal adenocarcinoma with differential response to gemcitabine-based versus FOLFIRINOX chemotherapy.

PURPOSE:Development of a supervised machine-learning model capable of predicting clinically relevant molecular subtypes of pancreatic ductal adenocarcinoma (PDAC) from diffusion-weighted-imaging-derived radiomic features. METHODS:The retrospective observational study assessed 55 surgical PDAC patients. Molecular subtypes were defined by immunohistochemical staining of KRT81. Tumors were manually segmented and 1606 radiomic features were extracted with PyRadiomics. A gradient-boosted-tree algorithm was trained on 70% of the patients (N = 28) and tested on 30% (N = 17) to predict KRT81+ vs. KRT81- tumor subtypes. A gradient-boosted survival regression model was fit to the disease-free and overall survival data. Chemotherapy response and survival were assessed stratified by subtype and radiomic signature. Radiomic feature importance was ranked. RESULTS:The mean±STDEV sensitivity, specificity and ROC-AUC were 0.90±0.07, 0.92±0.11, and 0.93±0.07, respectively. The mean±STDEV concordance indices between the disease-free and overall survival predicted by the model based on the radiomic parameters and actual patient survival were 0.76±0.05 and 0.71±0.06, respectively. Patients with a KRT81+ subtype experienced significantly diminished median overall survival compared to KRT81- patients (7.0 vs. 22.6 months, HR 4.03, log-rank-test P = <0.001) and a significantly improved response to gemcitabine-based chemotherapy over FOLFIRINOX (10.14 vs. 3.8 months median overall survival, HR 2.33, P = 0.037) compared to KRT81- patients, who responded significantly better to FOLFIRINOX over gemcitabine-based treatment (30.8 vs. 13.4 months median overall survival, HR 2.41, P = 0.027). Entropy was ranked as the most important radiomic feature. CONCLUSIONS:The machine-learning based analysis of radiomic features enables the prediction of subtypes of PDAC, which are highly relevant for disease-free and overall patient survival and response to chemotherapy

Whole Exome Sequencing of Biliary Tubulopapillary Neoplasms Reveals Common Mutations in Chromatin Remodeling Genes

The molecular carcinogenesis of intraductal tubulopapillary neoplasms (ITPN), recently described as rare neoplasms in the pancreato-biliary tract with a favorable prognosis despite a high incidence of associated pancreato-biliary adenocarcinoma, is still poorly understood. To identify driver genes, chromosomal gains and losses, mutational signatures, key signaling pathways, and potential therapeutic targets, the molecular profile of 11 biliary and 6 pancreatic ITPNs, associated with invasive adenocarcinoma in 14/17 cases, are studied by whole exome sequencing (WES). The WES of 17 ITPNs reveals common copy number variants (CNVs) broadly distributed across the genome, with recurrent chromosomal deletions primarily in 1p36 and 9p21 affecting the tumor suppressors CHD5 and CDKN2A, respectively, and gains in 1q affecting the prominent oncogene AKT3. The identified somatic nucleotide variants (SNVs) involve few core signaling pathways despite high genetic heterogeneity with diverse mutational spectra: Chromatin remodeling, the cell cycle, and DNA damage/repair. An OncoKB search identifies putative actionable genomic targets in 35% of the cases (6/17), including recurrent missense mutations of the FGFR2 gene in biliary ITPNs (2/11, 18%). Our results show that somatic SNV in classical cancer genes, typically associated with pancreato-biliary carcinogenesis, were absent (KRAS, IDH1/2, GNAS, and others) to rare (TP53 and SMAD4, 6%, respectively) in ITPNs. Mutational signature pattern analysis reveals a predominance of an age-related pattern. Our findings highlight that biliary ITPN and classical cholangiocarcinoma display commonalities, in particular mutations in genes of the chromatin remodeling pathway, and appear, therefore, more closely related than pancreatic ITPN and classical pancreatic ductal adenocarcinoma