Molecular subtypes of pancreatic cancer

IGFBP2 Drives Regulatory T Cell Differentiation through STAT3/IDO Signaling Pathway in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) represents one of the deadliest malignancies. Elevated regulatory T cell (Treg) infiltration has a potent immunosuppressive function in tumor biology, which contributes to low survival in PDAC. Nonetheless, the crosstalk between malignant cells and tumor-infiltrating Tregs in PDAC is not well understood. Here, clinical data demonstrates that the insulin-like growth factor binding protein 2 (IGFBP2) is associated with Treg accumulation in the microenvironment of PDAC in humans. Additionally, IGFBP2 increases Treg infiltration in the tumor microenvironment and promotes disease progression in mouse PDAC. Bioinformatic analysis and mechanistic assessment reveals IGFBP2 upregulated indoleamine 2, 3-dioxygenase (IDO) by activating signal transducer and activator of transcription 3 (STAT3) signaling in PDAC cells, thus inducing Treg differentiation and an immunosuppressive tumor microenvironment. These findings provide mechanistic insights into an important molecular pathway that promotes an immunosuppressive microenvironment, which suggests the IGFBP2 axis as a potential target for improved immune response in PDAC.

Integrative characterization of intraductal tubulopapillary neoplasm (ITPN) of the pancreas and associated invasive adenocarcinoma

Pancreatic intraductal tubulopapillary neoplasm (ITPN) is a recently recognized intraductal neoplasm. This study aimed to clarify the clinicopathologic and molecular features of this entity, based on a multi-institutional cohort of 16 pancreatic ITPNs and associated adenocarcinomas. The genomic profiles were analyzed using histology-driven multi-regional sequencing to provide insight on tumor heterogeneity and evolution. Furthermore, an exploratory transcriptomic characterization was performed on eight invasive adenocarcinomas. The clinicopathologic parameters and molecular alterations were further analyzed based on survival indices. The main findings were as follows: 1) the concomitant adenocarcinomas, present in 75% of cases, were always molecularly associated with the intraductal components. These data definitively establish ITPN as origin of invasive pancreatic adenocarcinoma; 2) alterations restricted to infiltrative components included mutations in chromatin remodeling genes ARID2, ASXL1, and PBRM1, and ERBB2-P3H4 fusion; 3) pancreatic ITPN can arise in the context of genetic syndromes, such as BRCA-germline and Peutz-Jeghers syndrome; 4) mutational profile: mutations in the classical PDAC drivers are present, but less frequently, in pancreatic ITPN; 5) novel genomic alterations were observed, including amplification of the Cyclin and NOTCH family genes and ERBB2, fusions involving RET and ERBB2, and RB1 disruptive variation; 6) chromosomal alterations: the most common was 1q gain (75% of cases); 7) by transcriptome analysis, ITPN-associated adenocarcinomas clustered into three subtypes that correlate with the activation of signaling mechanism pathways and tumor microenvironment, displaying squamous features in their majority; and 8) TP53 mutational status is a marker for adverse prognosis. ITPNs are precursor lesions of pancreatic cancer with a high malignant transformation risk. A personalized approach for patients with ITPN should recognize that such neoplasms could arise in the context of genetic syndromes. BRCA alterations, ERBB2 and RET fusions, and ERBB2 amplification are novel targets in precision oncology. The TP53 mutation status can be used as a prognostic biomarker.

Challenges in precision medicine in pancreatic cancer: A focus in cancer stem cells and microbiota

Pancreatic cancer adenocarcinoma (PDAC) is a lethal disease, with the lowest 5-years survival rate of all cancers due to late diagnosis. Despite the advance and success of precision oncology in gastrointestinal cancers, the frequency of molecular-informed therapy decisions in PDAC is currently neglectable. The reasons for this dismal situation are mainly the absence of effective early diagnostic biomarkers and therapy resistance. PDAC cancer stem cells (PDAC-SC), which are regarded as essential for tumor initiation, relapse and drug resistance, are highly dependent on their niche i.e. microanatomical structures of the tumor microenvironment. There is an altered microbiome in PDAC patients embedded within the highly desmoplastic tumor microenvironment, which is known to determine therapeutic responses and affecting survival in PDAC patients. We consider that understanding the communication network that exists between the microbiome and the PDAC-SC niche by co-culture of patient-derived organoids (PDOs) with TME microbiota would recapitulate the complexity of PDAC paving the way towards a precision oncology treatment-response prediction.

Mechanisms of PDAC subtype heterogeneity and therapy response

Pancreatic ductal adenocarcinoma (PDAC) is clinically challenging due to late diagnosis and resistance to therapy. Two major PDAC subtypes have been defined based on malignant epithelial cell gene expression profiles; the basal-like/squamous subtype is associated with a worse prognosis and therapeutic resistance as opposed to the classical subtype. Subtype specification is not binary, consistent with plasticity of malignant cell phenotype. PDAC heterogeneity and plasticity reflect partly malignant cell-intrinsic transcriptional and epigenetic regulation. However, the stromal and immune compartments of the tumor microenvironment (TME) also determine disease progression and therapy response. It is evident that integration of intrinsic and extrinsic factors can dictate subtype heterogeneity, and thus, delineating the pathways involved can help to reprogram PDAC towards a classical/druggable subtype.

hENT1 Expression Predicts Response to Gemcitabine and Nab-Paclitaxel in Advanced Pancreatic Ductal Adenocarcinoma

PURPOSE

Modified FOLFIRINOX (mFFX) and gemcitabine/nab-paclitaxel (GnP) remain standard first-line options for patients with advanced pancreatic ductal adenocarcinoma (PDAC). Human equilibrative nucleoside transporter 1 (hENT1) was hypothesized to be a biomarker of gemcitabine in the adjuvant setting, with conflicting results. In this study, we explore hENT1 mRNA expression as a predictive biomarker in advanced PDAC.

EXPERIMENTAL DESIGN

COMPASS was a prospective observational trial of patients with advanced PDAC. A biopsy was required prior to initiating chemotherapy, as determined by treating physician. Biopsies underwent laser capture microdissection prior to whole genome and RNA sequencing. The cut-off thresholds for hENT1 expression were determined using the maximal χ2 statistic.

RESULTS

253 patients were included in the analyses with a median follow-up of 32 months, with 138 patients receiving mFFX and 92 receiving GnP. In the intention to treat population, median overall survival (OS) was 10.0 months in hENT1high versus 7.9 months in hENT1low (P = 0.02). In patients receiving mFFX, there was no difference in overall response rate (ORR; 35% vs. 28%, P = 0.56) or median OS (10.6 vs. 10.5 months, P = 0.45). However, in patients treated with GnP, the ORR was significantly higher in hENT1high compared with hENT1low tumors (43% vs. 21%, P = 0.038). Median OS in this GnP-treated cohort was 10.6 months in hENT1high versus 6.7 months hENT1low (P < 0.001). In an interaction analysis, hENT1 was predictive of treatment response to GnP (interaction P = 0.002).

CONCLUSIONS

In advanced PDAC, hENT1 mRNA expression predicts ORR and OS in patients receiving GnP.

Efficient Selection of Enhancers and Promoters from MIA PaCa-2 Pancreatic Cancer Cells by ChIP-lentiMPRA

A library of active genome regulatory elements (putative promoters and enhancers) from MIA PaCa-2 pancreatic adenocarcinoma cells was constructed using a specially designed lentiviral vector and a massive parallel reporter assay (ChIP-lentiMPRA). Chromatin immunoprecipitation of the cell genomic DNA by H3K27ac antibodies was used for primary enrichment of the library for regulatory elements. Totally, 11,264 unique genome regions, many of which are capable of enhancing the expression of the CopGFP reporter gene from the minimal CMV promoter, were identified. The regions tend to be located near promoters. Based on the proximity assay, we found an enrichment of highly expressed genes among those associated with three or more mapped distal regions (2 kb distant from the 5'-ends of genes). It was shown significant enrichment of genes related to carcinogenesis or Mia PaCa-2 cell identity genes in this group. In contrast, genes associated with 1-2 distal regions or only with proximal regions (within 2 kbp of the 5'-ends of genes) are more often related to housekeeping functions. Thus, ChIP-lentiMPRA is a useful strategy for creating libraries of regulatory elements for the study of tumor-specific gene transcription.

Epithelial to Mesenchymal Transition as Mechanism of Progression of Pancreatic Cancer: From Mice to Men

Owed to its aggressive yet subtle nature, pancreatic cancer remains unnoticed till an advanced stage so that in most cases the diagnosis is made when the cancer has already spread to other organs with deadly efficiency. The progression from primary tumor to metastasis involves an intricate cascade of events comprising the pleiotropic process of epithelial to mesenchymal transition (EMT) facilitating cancer spread. The elucidation of this pivotal phenotypic change in cancer cell morphology, initially heretic, moved from basic studies dissecting the progression of pancreatic cancer in animal models to move towards human disease, although no clinical translation of the concept emerged yet. Despite this transition, a full-blown mesenchymal phenotype may not be accomplished; rather, the plasticity of the program and its dependency on heterotopic signals implies a series of fluctuating modifications of cancer cells encompassing mesenchymal and epithelial features. Despite the evidence supporting the activation of EMT and MET during cancer progression, our understanding of the relationship between tumor microenvironment and EMT is not yet mature for a clinical application. In this review, we attempt to resume the knowledge on EMT and pancreatic cancer, aiming to include the EMT among the hallmarks of cancer that could potentially modify our clinical thinking with the purpose of filling the gap between the results pursued in basic research by animal models and those achieved in translational research by surrogate biomarkers, as well as their application for prognostic and predictive purposes.

Laser Capture Microdissection: A Gear for Pancreatic Cancer Research

The advancement in molecular techniques has been attributed to the quality and significance of cancer research. Pancreatic cancer (PC) is one of the rare cancers with aggressive behavior and a high mortality rate. The asymptomatic nature of the disease until its advanced stage has resulted in late diagnosis as well as poor prognosis. The heterogeneous character of PC has complicated cancer development and progression studies. The analysis of bulk tissues of the disease was insufficient to understand the disease, hence, the introduction of the single-cell separating technique aided researchers to decipher more about the specific cell population of tumors. This review gives an overview of the Laser Capture Microdissection (LCM) technique, one of the single-cell separation methods used in PC research.

Assessment of spatial transcriptomics for oncology discovery

Tumor heterogeneity is a major challenge for oncology drug discovery and development. Understanding of the spatial tumor landscape is key to identifying new targets and impactful model systems. Here, we test the utility of spatial transcriptomics (ST) for oncology discovery by profiling 40 tissue sections and 80,024 capture spots across a diverse set of tissue types, sample formats, and RNA capture chemistries. We verify the accuracy and fidelity of ST by leveraging matched pathology analysis, which provides a ground truth for tissue section composition. We then use spatial data to demonstrate the capture of key tumor depth features, identifying hypoxia, necrosis, vasculature, and extracellular matrix variation. We also leverage spatial context to identify relative cell-type locations showing the anti-correlation of tumor and immune cells in syngeneic cancer models. Lastly, we demonstrate target identification approaches in clinical pancreatic adenocarcinoma samples, highlighting tumor intrinsic biomarkers and paracrine signaling.

Unified epigenomic, transcriptomic, proteomic, and metabolomic taxonomy of Alzheimer's disease progression and heterogeneity

Alzheimer's disease (AD) is a heterogeneous disorder with abnormalities in multiple biological domains. In an advanced machine learning analysis of postmortem brain and in vivo blood multi-omics molecular data (N = 1863), we integrated epigenomic, transcriptomic, proteomic, and metabolomic profiles into a multilevel biological AD taxonomy. We obtained a personalized multilevel molecular index of AD dementia progression that predicts severity of neuropathologies, and identified three robust molecular-based subtypes that explain much of the pathologic and clinical heterogeneity of AD. These subtypes present distinct patterns of alteration in DNA methylation, RNA, proteins, and metabolites, identifiable in the brain and subsequently in blood. In addition, the genetic variations that predispose to the various AD subtypes in brain predict distinct spatial patterns of alteration in cell types, suggesting a unique influence of each putative AD variant on neuropathological mechanisms. These observations support that an individually tailored multi-omics molecular taxonomy of AD may represent distinct targets for preventive or treatment interventions.

Construction of a Prognostic Model Based on Cuproptosis-Related lncRNA Signatures in Pancreatic Cancer

Aim

The aim of this study is to identify cuproptosis-related lncRNAs and construct a prognostic model for pancreatic cancer patients for clinical use.

Methods

The expression profile of lncRNAs was downloaded from The Cancer Genome Atlas database, and cuproptosis-related lncRNAs were identified. The prognostic cuproptosis-related lncRNAs were obtained and used to establish and validate a prognostic risk score model in pancreatic cancer.

Results

In total, 181 cuproptosis-related lncRNAs were obtained. The prognostic risk score model was constructed based on five lncRNAs (AC025257.1, TRAM2-AS1, AC091057.1, LINC01963, and MALAT1). Patients were assigned to two groups according to the median risk score. Kaplan-Meier survival curves showed that the difference in the prognosis between the high- and low-risk groups was statistically significant. Multivariate Cox analysis showed that our risk score was an independent risk factor for pancreatic cancer patients. Receiver operator characteristic curves revealed that the cuproptosis-related lncRNA model can effectively predict the prognosis of pancreatic cancer. The principal component analysis showed a difference between the high- and low-risk groups intuitively. Functional enrichment analysis showed that different genes were involved in cancer-related pathways in patients in the high- and low-risk groups.

Conclusion

The risk model based on five prognostic cuproptosis-related lncRNAs can well predict the prognosis of pancreatic cancer patients. Cuproptosis-related lncRNAs could be potential biomarkers for pancreatic cancer diagnosis and treatment.

Opposite Effects of Src Family Kinases on YAP and ERK Activation in Pancreatic Cancer Cells: Implications for Targeted Therapy

Pancreatic ductal adenocarcinoma (PDAC) remains an aggressive disease that is expected to become the second cause of cancer fatalities during the next decade. As therapeutic options are limited, novel targets, and agents for therapeutic intervention are urgently needed. Previously, we identified potent positive crosstalk between insulin/IGF-1 receptors and G protein-coupled (GPCR) signaling systems leading to mitogenic signaling in PDAC cells. Here, we show that a combination of insulin and the GPCR agonist neurotensin induced rapid activation of Src family of tyrosine kinases (SFK) within PANC-1 cells, as shown by FAK phosphorylation at Tyr576/577 and Tyr861, sensitive biomarkers of SFK activity within intact cells and Src416 autophosphorylation. Crucially, SFKs promoted YAP nuclear localization and phosphorylation at Tyr357, as shown by using the SFK inhibitors dasatinib, saracatinib, the preferential YES1 inhibitor CH6953755, siRNA-mediated knockdown of YES1, and transfection of epitogue-tagged YAP mutants in PANC-1 and Mia PaCa-2 cancer cells, models of the aggressive squamous subtype of PDAC. Surprisingly, our results also demonstrate that exposure to SFK inhibitors, including dasatinib or knockdown of YES and Src induces ERK overactivation in PDAC cells. Dasatinib-induced ERK activation was completely abolished by exposure to the FDA-approved MEK inhibitor trametinib. A combination of dasatinib and trametinib potently and synergistically inhibited colony formation by PDAC cells and suppressed the growth of Mia PaCa-2 cells xenografted into the flank of nude mice. The results provide rationale for considering a combination(s) of FDA-approved SFK (dasatinib) and MEK (e.g., trametinib) inhibitors in prospective clinical trials for the treatment of PDAC.

Facts and Hopes in Immunotherapy of Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most challenging cancers to treat. For patients with advanced and metastatic disease, chemotherapy has yielded only modest incremental benefits, which are not durable. Immunotherapy has revolutionized the treatment of other solid tumors by leading to cures where none existed only a decade ago, yet it has made few inroads with PDAC. A host of trials with promising preclinical data have failed, except for in a small minority of patients with selected biomarkers. There is, however, a glimmer of hope, which we seek to cultivate. In this review, we discuss recent advances in the understanding of the uniquely immunosuppressive tumor microenvironment (TME) in PDAC, learnings from completed trials of checkpoint inhibitors, TME modifiers, cellular and vaccine therapies, oncolytic viruses, and other novel approaches. We go on to discuss our expectations for improved preclinical models of immunotherapy in PDAC, new approaches to modifying the TME including the myeloid compartment, and emerging biomarkers to better select patients who may benefit from immunotherapy. We also discuss improvements in clinical trial design specific to immunotherapy that will help us better measure success when we find it. Finally, we discuss the urgent imperative to better design and execute bold, but rational, combination trials of novel agents designed to cure patients with PDAC.

The molecular landscape of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is predicted to become the second leading cause of cancer-related mortality within the next decade, with limited effective treatment options and a dismal long-term prognosis for patients. Surgical resection of early, localised disease provides the only chance for potentially curative treatment; however, most patients with PDAC present with advanced disease and are not suitable for surgery. Genomic analyses of PDAC tumour lesions have identified a small number of recurrent alterations that are detected across most tumours, and beyond that a large number that either occur at a low (<5%) prevalence or are patient-specific in nature. This molecular heterogeneity has presented a significant challenge for the characterisation of tumour subtypes and effective molecular biomarkers, which have not yet manifested clinical benefits for diagnosis, treatment or prognosis in PDAC. These challenges are compounded by the overall lack of tumour biopsies for sequencing, the invasive nature of tissue sampling and the confounding effects of low tumour cellularity in many PDAC biopsy specimens, which have limited the applications of molecular profiling in unresectable patients and for longitudinal tumour monitoring. Further investigation into alternative sources of tumour analytes that can be sampled using minimally invasive methods and used to complement molecular analyses from tissue sequencing are required.

Prognostic biomarkers of pancreatic cancer identified based on a competing endogenous RNA regulatory network

BACKGROUND

Pancreatic cancer is an insidious and heterogeneous malignancy with poor prognosis that is often locally unresectable. Therefore, determining the underlying mechanisms and effective prognostic indicators of pancreatic cancer may help optimize clinical management. This study was conducted to develop a prognostic model for pancreatic cancer based on a competing endogenous RNA (ceRNA) network.

METHODS

We obtained transcriptomic data and corresponding clinicopathological information of pancreatic cancer samples from The Cancer Genome Atlas (TCGA) database (training set). Based on the ceRNA interaction network, we screened candidate genes to build prediction models. Univariate Cox regression analysis was performed to screen for genes associated with prognosis, and least absolute shrinkage and selection operator (LASSO) regression analysis was conducted to construct a predictive model. A receiver operating characteristic (ROC) curve was drawn, and the C-index was calculated to evaluate the accuracy of the prediction model. Furthermore, we downloaded transcriptomic data and related clinical information of pancreatic cancer samples from the Gene Expression Omnibus database (validation set) to evaluate the robustness of our prediction model.

RESULTS

Eight genes (ANLN, FHDC1, LY6D, SMAD6, ACKR4, RAB27B, AUNIP, and GPRIN3) were used to construct the prediction model, which was confirmed as an independent predictor for evaluating the prognosis of patients with pancreatic cancer through univariate and multivariate Cox regression analysis. By plotting the decision curve, we found that the risk score model is an independent predictor has the greatest impact on survival compared to pathological stage and targeted molecular therapy.

CONCLUSIONS

An eight-gene prediction model was constructed for effectively and independently predicting the prognosis of patients with pancreatic cancer. These eight genes identified show potential as diagnostic and therapeutic targets.

Mouse models of Kras activation in gastric cancer

Gastric cancer has one of the highest incidence rates and is one of the leading causes of cancer-related mortality worldwide. Sequential steps within the carcinogenic process are observed in gastric cancer as well as in pancreatic cancer and colorectal cancer. Kirsten rat sarcoma viral oncogene homolog (KRAS) is the most well-known oncogene and can be constitutively activated by somatic mutations in the gene locus. For over 2 decades, the functions of Kras activation in gastrointestinal (GI) cancers have been studied to elucidate its oncogenic roles during the carcinogenic process. Different approaches have been utilized to generate distinct in vivo models of GI cancer, and a number of mouse models have been established using Kras-inducible systems. In this review, we summarize the genetically engineered mouse models in which Kras is activated with cell-type and/or tissue-type specificity that are utilized for studying carcinogenic processes in gastric cancer as well as pancreatic cancer and colorectal cancer. We also provide a brief description of histological phenotypes and characteristics of those mouse models and the current limitations in the gastric cancer field to be investigated further.

Circ_0058058 Drives the Malignant Phenotypes and Immune Evasion of Pancreatic Cancer by the MicroRNA-557-Dependent Regulation of PDL1

OBJECTIVES

Pancreatic cancer (PC) is one of the most deadly malignancies in the world. Recently, circular RNAs play crucial roles in PC progression. However, the functions of circ_0058058 in PC are barely known.

METHODS

The expression of circ_0058058, microRNA-557-5p (miR-557), and programmed cell death receptor ligand 1 (PDL1) was detected by quantitative real-time polymerase chain reaction. Functional experiments were implemented to disclose the effect of circ_0058058 deficiency on PC cell proliferation, apoptosis, invasion, angiogenesis, and immune escape. The binding relationship between miR-557 and circ_0058058 or PDL1 was identified by dual-luciferase reporter assay and RNA immunoprecipitation assay. In vivo assay was used to disclose the impact of circ_0058058 silencing on tumor formation in vivo.

RESULTS

Circ_0058058 was highly expressed in PC tissues and cell lines. Knockdown of circ_0058058 repressed cell proliferation, invasion, angiogenesis, and immune escape while contributed to apoptosis in PC cells. Mechanically, circ_0058058 worked as a molecular sponge of miR-557 to regulate PDL1 expression. Moreover, circ_0058058 showed a promotional effect on tumor growth in vivo.

CONCLUSIONS

Our findings suggested that circ_0058058 served as miR-557 sponge to upregulate PDL1, thereby triggering PC proliferation, invasion, angiogenesis, and immune escape.

Systems biology and OMIC data integration to understand gastrointestinal cancers

Gastrointestinal (GI) cancers are a set of diverse diseases affecting many parts/ organs. The five most frequent GI cancer types are esophageal, gastric cancer (GC), liver cancer, pancreatic cancer, and colorectal cancer (CRC); together, they give rise to 5 million new cases and cause the death of 3.5 million people annually. We provide information about molecular changes crucial to tumorigenesis and the behavior and prognosis. During the formation of cancer cells, the genomic changes are microsatellite instability with multiple chromosomal arrangements in GC and CRC. The genomically stable subtype is observed in GC and pancreatic cancer. Besides these genomic subtypes, CRC has epigenetic modification (hypermethylation) associated with a poor prognosis. The pathway information highlights the functions shared by GI cancers such as apoptosis; focal adhesion; and the p21-activated kinase, phosphoinositide 3-kinase/Akt, transforming growth factor beta, and Toll-like receptor signaling pathways. These pathways show survival, cell proliferation, and cell motility. In addition, the immune response and inflammation are also essential elements in the shared functions. We also retrieved information on protein-protein interaction from the STRING database, and found that proteins Akt1, catenin beta 1 (CTNNB1), E1A binding protein P300, tumor protein p53 (TP53), and TP53 binding protein 1 (TP53BP1) are central nodes in the network. The protein expression of these genes is associated with overall survival in some GI cancers. The low TP53BP1 expression in CRC, high EP300 expression in esophageal cancer, and increased expression of Akt1/TP53 or low CTNNB1 expression in GC are associated with a poor prognosis. The Kaplan Meier plotter database also confirmed the association between expression of the five central genes and GC survival rates. In conclusion, GI cancers are very diverse at the molecular level. However, the shared mutations and protein pathways might be used to understand better and reveal diagnostic/prognostic or drug targets.

Classification and Prognosis Analysis of Pancreatic Cancer Based on DNA Methylation Profile and Clinical Information

Pancreatic adenocarcinoma (PAAD) has a poor prognosis with high individual variation in the treatment response among patients; however, there is no standard molecular typing method for PAAD prognosis in clinical practice. We analyzed DNA methylation data from The Cancer Genome Atlas database, which identified 1235 differentially methylated DNA genes between PAAD and adjacent tissue samples. Among these, 78 methylation markers independently affecting PAAD prognosis were identified after adjusting for significant clinical factors. Based on these genes, two subtypes of PAAD were identified through consistent clustering. Fourteen specifically methylated genes were further identified to be associated with survival. Further analyses of the transcriptome data identified 301 differentially expressed cancer driver genes between the two PAAD subtypes and the degree of immune cell infiltration differed significantly between the subtypes. The 14 specific genes characterizing the unique methylation patterns of the subtypes were used to construct a Bayesian network-based prognostic prediction model for typing that showed good predictive value (area under the curve value of 0.937). This study provides new insight into the heterogeneity of pancreatic tumors from an epigenetic perspective, offering new strategies and targets for personalized treatment plan evaluation and precision medicine for patients with PAAD.

Impact of classical and basal-like molecular subtypes on overall survival in resected pancreatic cancer in the SPACIOUS-2 multicentre study

BACKGROUND

The recently identified classical and basal-like molecular subtypes of pancreatic cancer impact on overall survival (OS). However, the added value of routine subtyping in both clinical practice and randomized trials is still unclear, as most studies do not consider clinicopathological parameters. This study examined the clinical prognostic value of molecular subtyping in patients with resected pancreatic cancer.

METHODS

Subtypes were determined on fresh-frozen resected pancreatic cancer samples from three Dutch centres using the Purity Independent Subtyping of Tumours classification. Patient, treatment, and histopathological variables were compared between subtypes. The prognostic value of subtyping in (simulated) pre- and postoperative settings was assessed using Kaplan-Meier and Cox regression analyses.

RESULTS

Of 199 patients with resected pancreatic cancer, 164 (82.4 per cent) were classified as the classical and 35 (17.6 per cent) as the basal-like subtype. Patients with a basal-like subtype had worse OS (11 versus 16 months (HR 1.49, 95 per cent c.i. 1.03 to 2.15; P = 0.035)) than patients with a classical subtype. In multivariable Cox regression analysis, including only clinical variables, the basal-like subtype was a statistically significant predictor for poor OS (HR 1.61, 95 per cent c.i. 1.11 to 2.34; P = 0.013). When histopathological variables were added to this model, the prognostic value of subtyping decreased (HR 1.49, 95 per cent c.i. 1.01 to 2.19; P = 0.045).

CONCLUSION

The basal-like subtype was associated with worse OS in patients with resected pancreatic cancer. Adding molecular classification to inform on tumor biology may be used in patient stratification.

Modeling Obesity-Driven Pancreatic Carcinogenesis-A Review of Current In Vivo and In Vitro Models of Obesity and Pancreatic Carcinogenesis

Pancreatic ductal adenocarcinoma (PDAC) is the most common pancreatic malignancy with a 5-year survival rate below 10%, thereby exhibiting the worst prognosis of all solid tumors. Increasing incidence together with a continued lack of targeted treatment options will cause PDAC to be the second leading cause of cancer-related deaths in the western world by 2030. Obesity belongs to the predominant risk factors for pancreatic cancer. To improve our understanding of the impact of obesity on pancreatic cancer development and progression, novel laboratory techniques have been developed. In this review, we summarize current in vitro and in vivo models of PDAC and obesity as well as an overview of a variety of models to investigate obesity-driven pancreatic carcinogenesis. We start by giving an overview on different methods to cultivate adipocytes in vitro as well as various in vivo mouse models of obesity. Moreover, established murine and human PDAC cell lines as well as organoids are summarized and the genetically engineered models of PCAC compared to xenograft models are introduced. Finally, we review published in vitro and in vivo models studying the impact of obesity on PDAC, enabling us to decipher the molecular basis of obesity-driven pancreatic carcinogenesis.

A novel angiogenesis-based molecular signature related to prognosis and tumor immune interactions of pancreatic cancer

Angiogenesis, a hallmark of cancer, is related to prognosis, tumor progression, and treatment response. Nevertheless, the correlation of angiogenesis-based molecular signature with clinical outcome and immune cell infiltration has not been thoroughly studied in pancreatic cancer. In this study, multiple bioinformatics methods were combined to evaluate prognosis, immune cell infiltration, and the alterations of angiogenesis-related genes (ARGs) in PC samples, and further establish a novel angiogenesis-related gene signature. Moreover, the protein and mRNA expression levels of four angiogenesis risk genes were determined by Human Protein Atlas (HPA) database and qPCR analysis, respectively. Here, we recognized two distinct angiogenesis subtypes and two gene subtypes, and revealed the critical roles of ARGs in the tumor immune microenvironment (TIME), clinical features, and prognosis. Consequently, we established an ARGs score to predict prognosis and therapeutic response of PC patients, and validated its robust predictive ability. Additionally, the ARGs score was markedly associated with clinical outcomes, tumor mutation burden (TMB), and chemotherapeutic drug sensitivity. In brief, our findings imply that the ARGs score is a robust prognostic indicator and may contribute to the development of effective individualized therapies for PC.

The roles of intratumour heterogeneity in the biology and treatment of pancreatic ductal adenocarcinoma

Intratumour heterogeneity (ITH) has become an important focus of cancer research in recent years. ITH describes the cellular variation that enables tumour evolution, including tumour progression, metastasis and resistance to treatment. The selection and expansion of genetically distinct treatment-resistant cancer cell clones provides one explanation for treatment failure. However, tumour cell variation need not be genetically encoded. In pancreatic ductal adenocarcinoma (PDAC) in particular, the complex tumour microenvironment as well as crosstalk between tumour and stromal cells result in exceptionally variable tumour cell phenotypes that are also highly adaptable. In this review we discuss four different types of phenotypic heterogeneity within PDAC, from morphological to metabolic heterogeneity. We suggest that these different types of ITH are not independent, but, rather, can inform one another. Lastly, we highlight recent findings that suggest how therapeutic efforts may halt PDAC progression by constraining cellular heterogeneity.

Metabolism-Based Molecular Subtyping Endows Effective Ketogenic Therapy in p53-Mutant Colon Cancer

Although targeting cancer metabolism is a promising therapeutic strategy, clinical success depends on accurate molecular and metabolic subtyping. Here, this study reports two metabolism-based molecular subtypes associated with the ketogenic treatment of colon cancer: glycolytic (glycolysis+ /ketolysis- ) and ketolytic (glycolysis+ /ketolysis+ ), which are manifested by distinct profiles of metabolic enzymes and mitochondrial dysfunction, and by different responses to ketone-containing interventions in vitro and in vivo. Notably, the glycolytic subtype is able to be transformed into the ketolytic subtype in p53-mutated tumors upon glucose limitation, rendering resistance to ketogenic therapy associated with upregulation of ketolytic enzymes, such as OXCT1 by mutant p53. The allosteric activator of mutant p53 effectively blocks the rewired molecular expression and the reprogrammed metabolism, leading to the suppression of tumor growth. The findings highlight the utility of metabolic subtyping to guide ketogenic therapy in colon cancer and identify mutant p53 as a synthetic lethality target for ketogenic treatment.

Pancreatic Ductal Adenocarcinoma: Molecular Pathology and Predictive Biomarkers

Pancreatic ductal adenocarcinoma (PDAC) has an extremely poor prognosis due to the lack of methods or biomarkers for early diagnosis and its resistance to conventional treatment modalities, targeted therapies, and immunotherapies. PDACs are a heterogenous group of malignant epithelial neoplasms with various histomorphological patterns and complex, heterogenous genetic/molecular landscapes. The newly proposed molecular classifications of PDAC based on extensive genomic, transcriptomic, proteomic and epigenetic data have provided significant insights into the molecular heterogeneity and aggressive biology of this deadly disease. Recent studies characterizing the tumor microenvironment (TME) have shed light on the dynamic interplays between the tumor cells and the immunosuppressive TME of PDAC, which is essential to disease progression, as well as its resistance to chemotherapy, newly developed targeted therapy and immunotherapy. There is a critical need for the development of predictive markers that can be clinically utilized to select effective personalized therapies for PDAC patients. In this review, we provide an overview of the histological and molecular heterogeneity and subtypes of PDAC, as well as its precursor lesions, immunosuppressive TME, and currently available predictive molecular markers for patients.

A comprehensive review of pancreatic cancer and its therapeutic challenges

Pancreatic cancer is a devastating and lethal human malignancy with no curable chemo-treatments available thus far. More than 90% of pancreatic tumors are formed from ductal epithelium as pancreatic ductal adenocarcinoma (PDAC), which often accompany with the expression of mutant K-ras. The incidences of pancreatic cancer are expected to increase rapidly worldwide in the near future, due to environmental pollution, obesity epidemics and etc. The dismal prognosis of this malignancy is contributed to its susceptibility to tumor micro-metastasis from inception and the lack of methods to detect precursor lesions at very early stages of the onset until clinical symptoms occur. In recent years, basic and clinical studies have been making promising progresses for discovering markers to determine the subtypes or stages of this malignancy, which allow effectively implementing personalized therapeutic interventions. The purpose of this review is to discuss the existing knowledge of the molecular mechanisms of pancreatic cancer and the current state of treatment options with the emphasis on targeting therapeutic approaches. The specific focuses are on the molecular mechanisms of the disease, identifications of drug resistance, establishment of immune escaping mechanisms as well as potential of targeting identified pathways in combinations with existing chemo-drugs.

Management of Advanced Pancreatic Cancer through Stromal Depletion and Immune Modulation

Pancreatic cancer is one of the leading causes of cancer-related deaths worldwide. Unfortunately, therapeutic gains in the treatment of other cancers have not successfully translated to pancreatic cancer treatments. Management of pancreatic cancer is difficult due to the lack of effective therapies and the rapid development of drug resistance. The cytotoxic agent gemcitabine has historically been the first-line treatment, but combinations of other immunomodulating and stroma-depleting drugs are currently undergoing clinical testing. Moreover, the treatment of pancreatic cancer is complicated by its heterogeneity: analysis of genomic alterations and expression patterns has led to the definition of multiple subtypes, but their usefulness in the clinical setting is limited by inter-tumoral and inter-personal variability. In addition, various cell types in the tumor microenvironment exert immunosuppressive effects that worsen prognosis. In this review, we discuss current perceptions of molecular features and the tumor microenvironment in pancreatic cancer, and we summarize emerging drug options that can complement traditional chemotherapies.

Spatiotemporal dynamics of self-organized branching in pancreas-derived organoids

The development dynamics and self-organization of glandular branched epithelia is of utmost importance for our understanding of diverse processes ranging from normal tissue growth to the growth of cancerous tissues. Using single primary murine pancreatic ductal adenocarcinoma (PDAC) cells embedded in a collagen matrix and adapted media supplementation, we generate organoids that self-organize into highly branched structures displaying a seamless lumen connecting terminal end buds, replicating in vivo PDAC architecture. We identify distinct morphogenesis phases, each characterized by a unique pattern of cell invasion, matrix deformation, protein expression, and respective molecular dependencies. We propose a minimal theoretical model of a branching and proliferating tissue, capturing the dynamics of the first phases. Observing the interaction of morphogenesis, mechanical environment and gene expression in vitro sets a benchmark for the understanding of self-organization processes governing complex organoid structure formation processes and branching morphogenesis.

Prognosis of pancreatic head cancer with different patterns of lymph node metastasis

BACKGROUND

The nodal stage of pancreatic ductal adenocarcinoma (PDAC) is revised in the AJCC 8th edition. Studies on the prognosis of PDAC according to lymph node metastasis (LNM) are still ongoing. We attempted to find the patterns of nodal involvement and to reveal its clinical significance to overall survival (OS).

METHODS

We analyzed 585 patients who received pancreatic head cancer surgery diagnosed as PDAC from January 2007 to December 2016. Patients were classified into three groups: Group 1 (G1, patients without LNM), Group 2 (G2, those with LNM only in the peripancreatic area), and Group 3 (G3 those with LNM in the other area and/or peripancreatic LNM). Risk factors were analyzed by Cox-regression test and overall survival was compared by Kaplan-Meier analysis.

RESULTS

LNM in peripancreatic area was the most common (88.7%). In the multivariate analysis, T stage, nuclear differentiation, adjuvant treatment, and the G2 and G3 were independent risk factors for OS (G2 over G1, HR 1.384, 95% CI 1.046-1.802; P = .036 and G3 over G1, HR 2.383, 95% CI 1.378-4.103; P = .001). G3 showed worse OS than G2 (P = .006). In the N1 status, LNM to the pericholedochal (PC) and superior mesenteric artery (SMA) areas resulted in worse OS than the G2 (P = .011 and P = .019).

CONCLUSIONS

We found that LNM beyond the peripancreatic area significantly affects OS in pancreatic head cancer patients. Depending on the station of the LNM, different risk-stratification and treatment strategies will need to be considered.

Cytotoxicity of combinations of the pan-KRAS SOS1 inhibitor BAY-293 against pancreatic cancer cell lines

KRAS is mutated in approximately 25% of cancer patients and first KRAS G12C-specific inhibitors showed promising responses. Pancreatic cancer has the highest frequency of KRAS mutations but the prevailing KRAS G12D mutation is difficult to target. Inhibition of the GTP exchange factor (GEF) SOS1-KRAS interaction impairs oncogenic signaling independently of the specific KRAS mutations. In general, cell lines exhibiting KRAS mutations show specific alterations in respect to glucose utilization, signal transduction and stress survival. The aim of this investigation was to check the putative synergy of the SOS1 inhibitor BAY-293 with modulators targeting specific vulnerabilities of KRAS-mutated cell lines in vitro. The cytotoxicity of BAY-293 combinations was tested against MIA PaCa-2 (G12C), AsPC1 (G12D) and BxPC3 (KRAS wildtype) cell lines using MTT tests and calculation of the combination indices (CI) according to the Chou-Talalay method. The results show that BAY-293 synergizes with modulators of glucose utilization, inhibitors of the downstream MAPK pathway and several chemotherapeutics in dependence of the specific KRAS status of the cell lines. In particular, divergent responses for BAY-293 combinations between pancreatic and NSCLC cell lines were observed for linsitinib, superior inhibitory effects of trametinib and PD98059 in NSCLC, and lack of activity with doxorubicin in case of the pancreatic cell lines. Phosphoproteome analysis revealed inhibition of distinct signaling pathways by BAY-293 for MIA PaCa-2 on the one hand and for Aspc1 and BH1362 on the other hand. In conclusion, BAY-293 exhibits synergy with drugs in dependence of the tumor type and specific KRAS mutation.

Invasive IPMN relapse later and more often in lungs in comparison to pancreatic ductal adenocarcinoma

BACKGROUND

The different oncological outcomes of invasive intraductal papillary mucinous neoplasm (I-IPMN) and pancreatic ductal adenocarcinoma (PDAC) are debated. This study aimed to compare disease recurrence patterns and histopathological characteristics in patients with resected I-IPMN and PDAC.

METHODS

Consecutive patients undergoing surgical resection for stage I-III I-IPMN or PDAC between 2010 and 2016 were retrospectively analyzed. Patients treated with neoadjuvant therapy or resected for Tis neoplasia were excluded. All surgical specimens were re-staged according to AJCC-8th-edition.

RESULTS

A total of 330 patients were included, of whom 43 had I-IPMN and 287 had PDAC. Median follow-up time was 26.7 (1.3-92.3) months and estimated median disease-free survival (DFS) was 60.3 months (47.2-73.4) for I-IPMN and 23.8 (19.3-28.2) months for PDAC (p < 0.001). During follow-up, 32.6% of I-IPMN and 67.9% of PDAC patients experienced recurrence (p < 0.001). The sites of first recurrence were the lungs (38.5% vs 13.1%, p = 0.027), liver (28.6% vs 45.0%, p = 0.180) and local (15.4% vs 36.6%, p = 0.101) for I-IPMN and PDAC, respectively. At multivariate analysis, I-IPMN histology remained an independent predictive factor for longer DFS (OR 0.528, CI 95% 0.278-1.000, p = 0.050), regardless of stage or adjuvant chemotherapy. I-IPMN and PDAC differed in rates of neuroinvasion (51.2% vs 97.2%) and positive lymph node status (N+) (46.5% vs 82.7%), especially in patients with lower T status.

CONCLUSION

I-IPMN showed a different recurrence pattern compared to PDAC, with a higher lung tropism, and longer DFS. This different biological behavior is associated with lower rates of neuroinvasion and nodal involvement, especially in early-stage disease.

The RING finger protein family in health and disease

Ubiquitination is a highly conserved and fundamental posttranslational modification (PTM) in all eukaryotes regulating thousands of proteins. The RING (really interesting new gene) finger (RNF) protein, containing the RING domain, exerts E3 ubiquitin ligase that mediates the covalent attachment of ubiquitin (Ub) to target proteins. Multiple reviews have summarized the critical roles of the tripartite-motif (TRIM) protein family, a subgroup of RNF proteins, in various diseases, including cancer, inflammatory, infectious, and neuropsychiatric disorders. Except for TRIMs, since numerous studies over the past decades have delineated that other RNF proteins also exert widespread involvement in several diseases, their importance should not be underestimated. This review summarizes the potential contribution of dysregulated RNF proteins, except for TRIMs, to the pathogenesis of some diseases, including cancer, autoimmune diseases, and neurodegenerative disorder. Since viral infection is broadly involved in the induction and development of those diseases, this manuscript also highlights the regulatory roles of RNF proteins, excluding TRIMs, in the antiviral immune responses. In addition, we further discuss the potential intervention strategies targeting other RNF proteins for the prevention and therapeutics of those human diseases.

Correlation of transcriptional subtypes with a validated CT radiomics score in resectable pancreatic ductal adenocarcinoma

OBJECTIVES

Transcriptional classifiers (Bailey, Moffitt and Collison) are key prognostic factors of pancreatic ductal adenocarcinoma (PDAC). Among these classifiers, the squamous, basal-like, and quasimesenchymal subtypes overlap and have inferior survival. Currently, only an invasive biopsy can determine these subtypes, possibly resulting in treatment delay. This study aimed to investigate the association between transcriptional subtypes and an externally validated preoperative CT-based radiomic prognostic score (Rad-score).

METHODS

We retrospectively evaluated 122 patients who underwent resection for PDAC. All treatment decisions were determined at multidisciplinary tumor boards. Tumor Rad-score values from preoperative CT were dichotomized into high or llow categories. The primary endpoint was the correlation between the transcriptional subtypes and the Rad-score using multivariable linear regression, adjusting for clinical and histopathological variables (i.e., tumor size). Prediction of overall survival (OS) was secondary endpoint.

RESULTS

The Bailey transcriptional classifier significantly associated with the Rad-score (coefficient = 0.31, 95% confidence interval [CI]: 0.13-0.44, p = 0.001). Squamous subtype was associated with high Rad-scores while non-squamous subtype was associated with low Rad-scores (adjusted p = 0.03). Squamous subtype and high Rad-score were both prognostic for OS at multivariable analysis with hazard ratios (HR) of 2.79 (95% CI: 1.12-6.92, p = 0.03) and 4.03 (95% CI: 1.42-11.39, p = 0.01), respectively.

CONCLUSIONS

In patients with resectable PDAC, an externally validated prognostic radiomic model derived from preoperative CT is associated with the Bailey transcriptional classifier. Higher Rad-scores were correlated with the squamous subtype, while lower Rad-scores were associated with the less lethal subtypes (immunogenic, ADEX, pancreatic progenitor).

KEY POINTS

• The transcriptional subtypes of PDAC have been shown to have prognostic importance but they require invasive biopsy to be assessed. • The Rad-score radiomic biomarker, which is obtained non-invasively from preoperative CT, correlates with the Bailey squamous transcriptional subtype and both are negative prognostic biomarkers. • The Rad-score is a promising non-invasive imaging biomarker for personalizing neoadjuvant approaches in patients undergoing resection for PDAC, although additional validation studies are required.

Heterogeneity of Cancer-Associated Fibroblasts and the Tumor Immune Microenvironment in Pancreatic Cancer

Simple Summary

Stroma-targeting therapy in pancreatic ductal adenocarcinoma (PDAC) has been extensively investigated, but no candidates have shown efficacy at the clinical trial stage. Studies of cancer-associated fibroblast (CAF) depletion in a mouse model suggested that CAFs have not only tumor-promoting function but also tumor-suppressive activity. Recently, single-cell RNA sequencing (scRNA-seq) has revealed the complex tumor microenvironment within PDAC, and subpopulations of functionally distinct CAFs and their association with tumor immunity have been reported. However, the existence of tumor suppressive CAFs and CAFs involved in the maintenance of PDAC differentiation has also been reported. In the future, therapeutic strategies should be developed considering these CAF subpopulations, with the hope of improving the prognosis of PDAC.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers, with a 5-year survival rate of 9%. Cancer-associated fibroblasts (CAFs) have historically been considered tumor-promoting. However, multiple studies reporting that suppression of CAFs in PDAC mouse models resulted in more aggressive tumors and worse prognosis have suggested the existence of a tumor-suppressive population within CAFs, leading to further research on heterogeneity within CAFs. In recent years, the benefits of cancer immunotherapy have been reported in various carcinomas. Unfortunately, the efficacy of immunotherapies in PDAC has been limited, and the CAF-driven cancer immunosuppressive microenvironment has been suggested as the cause. Thus, clarification of heterogeneity within the tumor microenvironment, including CAFs and tumor immunity, is urgently needed to establish effective therapeutic strategies for PDAC. In this review, we report the latest findings on the heterogeneity of CAFs and the functions of each major CAF subtype, which have been revealed by single-cell RNA sequencing in recent years. We also describe reports of tumor-suppressive CAF subtypes and the existence of CAFs that maintain a differentiated PDAC phenotype and review the potential for targeted therapy.

A ubiquitin-related gene signature for predicting prognosis and constructing molecular subtypes in osteosarcoma

Background: Ubiquitination is medicated by three classes of enzymes and has been proven to involve in multiple cancer biological processes. Moreover, dysregulation of ubiquitination has received a growing body of attention in osteosarcoma (OS) tumorigenesis and treatment. Therefore, our study aimed to identify a ubiquitin-related gene signature for predicting prognosis and immune landscape and constructing OS molecular subtypes.

Methods: Therapeutically Applicable Research to Generate Effective Treatments (TARGET) was regarded as the training set through univariate Cox regression, Lasso Cox regression, and multivariate Cox regression. The GSE21257 and GSE39055 served as the validation set to verify the predictive value of the signature. CIBERSORT was performed to show immune infiltration and the immune microenvironment. The NMF algorithm was used to construct OS molecular subtypes.

Results: In this study, we developed a ubiquitin-related gene signature including seven genes (UBE2L3, CORO6, DCAF8, DNAI1, FBXL5, UHRF2, and WDR53), and the gene signature had a good performance in predicting prognosis for OS patients (AUC values at 1/3/5 years were 0.957, 0.890, and 0.919). Multivariate Cox regression indicated that the risk score model and prognosis stage were also independent prognostic prediction factors. Moreover, analyses of immune cells and immune-related functions showed a significant difference in different risk score groups and the three clusters. The drug sensitivity suggested that IC50 of proteasome inhibitor (MG-132) showed a notable significance between the risk score groups (p < 0.05). Through the NMF algorithm, we obtained the three clusters, and cluster 3 showed better survival outcomes. The expression of ubiquitin-related genes (CORO6, UBE2L3, FBXL5, DNAI1, and DCAF8) showed an obvious significance in normal and osteosarcoma tissues.

Conclusion: We developed a novel ubiquitin-related gene signature which showed better predictive prognostic ability for OS and provided additional information on chemotherapy and immunotherapy. The OS molecular subtypes would also give a useful guide for individualized therapy.

Pre-Training on In Vitro and Fine-Tuning on Patient-Derived Data Improves Deep Neural Networks for Anti-Cancer Drug-Sensitivity Prediction

Large-scale databases that report the inhibitory capacities of many combinations of candidate drug compounds and cultivated cancer cell lines have driven the development of preclinical drug-sensitivity models based on machine learning. However, cultivated cell lines have devolved from human cancer cells over years or even decades under selective pressure in culture conditions. Moreover, models that have been trained on in vitro data cannot account for interactions with other types of cells. Drug-response data that are based on patient-derived cell cultures, xenografts, and organoids, on the other hand, are not available in the quantities that are needed to train high-capacity machine-learning models. We found that pre-training deep neural network models of drug sensitivity on in vitro drug-sensitivity databases before fine-tuning the model parameters on patient-derived data improves the models’ accuracy and improves the biological plausibility of the features, compared to training only on patient-derived data. From our experiments, we can conclude that pre-trained models outperform models that have been trained on the target domains in the vast majority of cases.

Metabolic Pathways as a Novel Landscape in Pancreatic Ductal Adenocarcinoma

Metabolism plays a fundamental role in both human physiology and pathology, including pancreatic ductal adenocarcinoma (PDAC) and other tumors. Anabolic and catabolic processes do not only have energetic implications but are tightly associated with other cellular activities, such as DNA duplication, redox reactions, and cell homeostasis. PDAC displays a marked metabolic phenotype and the observed reduction in tumor growth induced by calorie restriction with in vivo models supports the crucial role of metabolism in this cancer type. The aggressiveness of PDAC might, therefore, be reduced by interventions on bioenergetic circuits. In this review, we describe the main metabolic mechanisms involved in PDAC growth and the biological features that may favor its onset and progression within an immunometabolic context. We also discuss the need to bridge the gap between basic research and clinical practice in order to offer alternative therapeutic approaches for PDAC patients in the more immediate future.

Single-nucleus and spatial transcriptome profiling of pancreatic cancer identifies multicellular dynamics associated with neoadjuvant treatment

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal and treatment-refractory cancer. Molecular stratification in pancreatic cancer remains rudimentary and does not yet inform clinical management or therapeutic development. Here, we construct a high-resolution molecular landscape of the cellular subtypes and spatial communities that compose PDAC using single-nucleus RNA sequencing and whole-transcriptome digital spatial profiling (DSP) of 43 primary PDAC tumor specimens that either received neoadjuvant therapy or were treatment naive. We uncovered recurrent expression programs across malignant cells and fibroblasts, including a newly identified neural-like progenitor malignant cell program that was enriched after chemotherapy and radiotherapy and associated with poor prognosis in independent cohorts. Integrating spatial and cellular profiles revealed three multicellular communities with distinct contributions from malignant, fibroblast and immune subtypes: classical, squamoid-basaloid and treatment enriched. Our refined molecular and cellular taxonomy can provide a framework for stratification in clinical trials and serve as a roadmap for therapeutic targeting of specific cellular phenotypes and multicellular interactions.

Histone Deacetylase Inhibitors Restore Cancer Cell Sensitivity towards T Lymphocytes Mediated Cytotoxicity in Pancreatic Cancer

Despite medical advancements, the prognosis of pancreatic ductal adenocarcinoma (PDAC) has not improved significantly over the past 50 years. By utilising the large-scale genomic datasets available from the Australia Pancreatic Cancer Project (PACA-AU) and The Cancer Genomic Atlas Project (TCGA-PAAD), we studied the immunophenotype of PDAC in silico and identified that tumours with high cytotoxic T lymphocytes (CTL) killing activity were associated with favourable clinical outcomes. Using the STRING protein-protein interaction network analysis, the identified differentially expressed genes with low CTL killing activity were associated with TWIST/IL-6R, HDAC5, and EOMES signalling. Following Connectivity Map analysis, we identified 44 small molecules that could restore CTL sensitivity in the PDAC cells. Further high-throughput chemical library screening identified 133 inhibitors that effectively target both parental and CTL-resistant PDAC cells in vitro. Since CTL-resistant PDAC had a higher expression of histone proteins and its acetylated proteins compared to its parental cells, we further investigated the impact of histone deacetylase inhibitors (HDACi) on CTL-mediated cytotoxicity in PDAC cells in vitro, namely SW1990 and BxPC3. Further analyses revealed that givinostat and dacinostat were the two most potent HDAC inhibitors that restored CTL sensitivity in SW1990 and BxPC3 CTL-resistant cells. Through our in silico and in vitro studies, we demonstrate the novel role of HDAC inhibition in restoring CTL resistance and that combinations of HDACi with CTL may represent a promising therapeutic strategy, warranting its further detailed molecular mechanistic studies and animal studies before embarking on the clinical evaluation of these novel combined PDAC treatments.

Mitophagy-mediated molecular subtypes depict the hallmarks of the tumour metabolism and guide precision chemotherapy in pancreatic adenocarcinoma

Background: Mitophagy is closely related to cancer initiation and progression. However, heterogeneity with reference to mitophagy remains unexplored in pancreatic adenocarcinoma (PAAD).

Materials and methods: We used Reactome database to download the mitophagy-related, glycolysis-related and cholesterol biosynthesis-related signaling pathways. Unsupervised clustering using the “ConsensusClusterPlus” R package was performed to identify molecular subtypes related to mitophagy and metabolism. Prognosis-related mitophagy regulators were identified by univariate Cox regression analysis. Receiver operating characteristics (ROC) and Kaplan-Meier (K-M) survival analyses were used to assess the diagnostic and prognostic role of the hub genes and prognosis risk model. Weighted gene co-expression network analysis (WGCNA) was utilized for screening the mitophagy subtype-related hub genes. Metascape was utilized to carry out functional enrichment analysis. The “glmnet” R package was utilised for LASSO, and the “e1071” R package was utilised for SVM. Chemotherapeutic drug sensitivity was estimated using the R package “pRRophetic” and Genomics of Drug Sensitivity in Cancer (GDSC) database. The nomogram was established by the “rms” R package.

Results: Three distinct mitophagy subtypes (low, high and intermediate) of PAAD were identified based on the landscape of mitophagy regulators. The high mitophagy subtype had the worst prognosis, highest mRNA expression-based stemness index scores and most hypoxic environment compared to the other subtypes. Additionally, glycolysis and cholesterol biosynthesis were significantly elevated. Three mitophagy subtype-specific gene signatures (CAST, CCDC6, and ERLIN1) were extracted using WGCNA and machine learning. Moreover, PAAD tumours were insensitive to Erlotinib, Sunitinib and Imatinib in the high mitophagy subtype and high CAST, CCDC6, and ERLIN1 expressed subtypes. Furthermore, CAST, CCDC6, and ERLIN1 affected immune cell infiltration (M1 and CD8Tcm), resulting in the altered prognosis of patients with PAAD. A nomogram was constructed to screen patients with the low mitophagy subtype, which showed a higher sensitivity to chemotherapeutic agents.

Conclusion: Based on various bioinformatics tools and databases, the PAAD heterogeneity regarding mitophagy was systematically examined. Three different PAAD subtypes having different outcomes, metabolism patterns and chemosensitivity were observed. Moreover, three novel biomarkers that are closely associated with mitophagy and have the potential to guide individualised treatment regimens in PAAD were obtained.

High enhancer activity is an epigenetic feature of HPV negative atypical head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous disease with significant mortality and frequent recurrence. Prior efforts to transcriptionally classify HNSCC into groups of varying prognoses have identified four accepted molecular subtypes of the disease: Atypical (AT), Basal (BA), Classical (CL), and Mesenchymal (MS). Here, we investigate the active enhancer landscapes of these subtypes using representative HNSCC cell lines and identify samples belonging to the AT subtype as having increased enhancer activity compared to the other 3 HNSCC subtypes. Cell lines belonging to the AT subtype are more resistant to enhancer-blocking bromodomain inhibitors (BETi). Examination of nascent transcripts reveals that both AT TCGA tumors and cell lines express higher levels of enhancer RNA (eRNA) transcripts for enhancers controlling BETi resistance pathways, such as lipid metabolism and MAPK signaling. Additionally, investigation of higher-order chromatin structure suggests more enhancer-promoter (E-P) contacts in the AT subtype, including on genes identified in the eRNA analysis. Consistently, known BETi resistance pathways are upregulated upon exposure to these inhibitors. Together, our results identify that the AT subtype of HNSCC is associated with higher enhancer activity, resistance to enhancer blockade, and increased signaling through pathways that could serve as future targets for sensitizing HNSCC to BET inhibition.

The Therapeutic Potential of Carnosine as an Antidote against Drug-Induced Cardiotoxicity and Neurotoxicity: Focus on Nrf2 Pathway

Different drug classes such as antineoplastic drugs (anthracyclines, cyclophosphamide, 5-fluorouracil, taxanes, tyrosine kinase inhibitors), antiretroviral drugs, antipsychotic, and immunosuppressant drugs are known to induce cardiotoxic and neurotoxic effects. Recent studies have demonstrated that the impairment of the nuclear factor erythroid 2–related factor 2 (Nrf2) pathway is a primary event in the pathophysiology of drug-induced cardiotoxicity and neurotoxicity. The Nrf2 pathway regulates the expression of different genes whose products are involved in antioxidant and inflammatory responses and the detoxification of toxic species. Cardiotoxic drugs, such as the anthracycline doxorubicin, or neurotoxic drugs, such as paclitaxel, suppress or impair the Nrf2 pathway, whereas the rescue of this pathway counteracts both the oxidative stress and inflammation that are related to drug-induced cardiotoxicity and neurotoxicity. Therefore Nrf2 represents a novel pharmacological target to develop new antidotes in the field of clinical toxicology. Interestingly, carnosine (β-alanyl-l-histidine), an endogenous dipeptide that is characterized by strong antioxidant, anti-inflammatory, and neuroprotective properties is able to rescue/activate the Nrf2 pathway, as demonstrated by different preclinical studies and preliminary clinical evidence. Starting from these new data, in the present review, we examined the evidence on the therapeutic potential of carnosine as an endogenous antidote that is able to rescue the Nrf2 pathway and then counteract drug-induced cardiotoxicity and neurotoxicity.

Activation of STING in the pancreatic tumor microenvironment: A novel therapeutic opportunity

Pancreatic ductal adenocarcinoma (PDAC) is a cancer of poor prognosis that presents with a dense desmoplastic stroma that contributes to therapeutic failure. PDAC patients are mostly unresponsive to immunotherapy. However, hopes to elicit response to immunotherapy have emerged with novel strategies targeting the Stimulator of Interferon Genes (STING) protein, which is a major regulator of tumor-associated inflammation. Combination of STING agonists with conventional immunotherapy approaches has proven to potentiate therapeutic benefits in several cancers. However, recent data underscore that the output of STING activation varies depending on the cellular and tissue context. This suggests that tumor heterogeneity, and in particular the heterogeneity of the tumor microenvironment (TME), is a key factor determining whether STING activation would bear benefits for patients. In this review, we discuss the potential benefits of STING activation in PDAC. To this aim, we describe the major components of the PDAC TME, and the expected consequences of STING activation.

Characterization of Immune-Related Molecular Subtypes and a Prognostic Signature Correlating With the Response to Immunotherapy in Patients With Gastric Cancer

Gastric cancer (GC) is a disease characterized by high molecular and phenotypic heterogeneity and represents a leading cause of cancer-related death worldwide. The tumor immune microenvironment (TIME) affects the response to immunotherapy and the prognosis of patients with GC. Explorations of the TIME in GC and characterization of molecular subtypes might enhance personalized treatment and facilitate clinical decision-making. In this study, two molecular subtypes were defined through unsupervised consensus clustering based on immune-related dysregulated genes. Then, patients with different molecular subtypes of GC were shown to have distinct differences in sensitivity to immune checkpoint blockers (ICBs). The immune-related prognostic signature was established utilizing least absolute shrinkage and selection operator (LASSO)-Cox regression analysis. Three independent external cohorts and the IMvigor210 cohort were introduced to validate the robustness of IPRS. scRNA-seq data of GC samples were used to decipher the underlying mechanisms of how IPRS contributes to the TIME. GC biospecimens were collected for RT-qPCR to further validate our findings. In summary, we characterized the abnormal TIME of GC and constructed a reliable immune-related prognostic signature correlating with the response to immunotherapy. This study may provide new strategies for developing individualized treatments for patients with GC.

A special subtype: Revealing the potential intervention and great value of KRAS wildtype pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is the predominant form of pancreatic cancer and has devastating consequences on affected families and society. Its dismal prognosis is attributed to poor specificity of symptoms during early stages. It is widely believed that PDAC patients with the wildtype (WT) KRAS gene benefit more from currently available treatments than those with KRAS mutations. The oncogenic genetic changes alternations generally found in KRAS wildtype PDAC are related to either the KRAS pathway or microsatellite instability/mismatch repair deficiency (MSI/dMMR), which enable the application of tailored treatments based on each patient's genetic characteristics. This review focuses on targeted therapies against alternative tumour mechanisms in KRAS WT PDAC.

GREM1 is required to maintain cellular heterogeneity in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) shows pronounced epithelial and mesenchymal cancer cell populations^1-4. Cellular heterogeneity in PDAC is an important feature in disease subtype specification^3-5, but how distinct PDAC subpopulations interact, and the molecular mechanisms that underlie PDAC cell fate decisions, are incompletely understood. Here we identify the BMP inhibitor GREM1^6,7 as a key regulator of cellular heterogeneity in pancreatic cancer in human and mouse. Grem1 inactivation in established PDAC in mice resulted in a direct conversion of epithelial into mesenchymal PDAC cells within days, suggesting that persistent GREM1 activity is required to maintain the epithelial PDAC subpopulations. By contrast, Grem1 overexpression caused an almost complete 'epithelialization' of highly mesenchymal PDAC, indicating that high GREM1 activity is sufficient to revert the mesenchymal fate of PDAC cells. Mechanistically, Grem1 was highly expressed in mesenchymal PDAC cells and inhibited the expression of the epithelial-mesenchymal transition transcription factors Snai1 (also known as Snail) and Snai2 (also known as Slug) in the epithelial cell compartment, therefore restricting epithelial-mesenchymal plasticity. Thus, constant suppression of BMP activity is essential to maintain epithelial PDAC cells, indicating that the maintenance of the cellular heterogeneity of pancreatic cancer requires continuous paracrine signalling elicited by a single soluble factor.

Exploring the Potential of Pyroptosis-Related Genes in Predicting Prognosis and Immunological Characteristics of Pancreatic Cancer From the Perspective of Genome and Transcriptome

Objective

To probe into the role of pyroptosis-related genes in pancreatic carcinoma.

Methods

Herein, we conducted a comprehensive bioinformatics analysis to evaluate tumor-immune infiltration and tumor mutation burden, the correlations between PRGs, and microsatellite instability and found that 33 PRGS were up- or down-regulated in PC. Then we built the PPI network, which was downloaded from the STRING database. Using TCGA cohort median risk score, PC subjects from the Gene Expression Composite cohort (GEO) data resource were stratified into two risk categories, with the low-PC risk group harboring a higher overall survival (OS) (P = 0.011). We employed the ssGSEA approach to quantify immune cell abundance in separate risk groups separated by risk signature while assessing variations in immune cell invasion. Chemotherapeutic drugs were retrieved from the Genomics of Drug Sensitivity in Cancer (GDSC) data resource.

Results

Eight prognostic PRG models (CASP4, GSDMC, IL-18, NLRP1, NLRP2, PLCG1, TIRAP, and TNF) were established via LASSO Cox regression to estimate the OS of PC subjects with medium-to-high accuracy.

Conclusion

Our study is the first to identify a pyroptotic-related prognostic gene feature for PC, providing more options for the prognostic prediction of PC.

Management of Pancreatic Cancer and Its Microenvironment: Potential Impact of Nano-Targeting

Simple Summary

The poor prognosis and survival rates associated with pancreatic cancer show that there is a clear unmet need for better disease management. The heterogeneity of the tumor and its microenvironment, including stroma and fibrosis, creates a challenge for current therapy. The pathogenesis of pancreatic cancer is mediated by several factors, such as severed communication between pancreatic stellate cells and stroma and the consequences of hypoxia-inducible factors that aid in the survival of the pancreatic tumor. Given the multiple limitations of molecular targeting, multiple functional nano-targeting offers a breakthrough in pancreatic cancer treatment through its ability to overcome the physical challenges posed by the tumor microenvironment, amongst many others.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is rare and difficult to treat, making it a complicated diagnosis for every patient. These patients have a low survival rate along with a poor quality of life under current pancreatic cancer therapies that adversely affect healthy cells due to the lack of precise drug targeting. Additionally, chemoresistance and radioresistance are other key challenges in PDAC, which might be due in part to the lack of tumor-targeted delivery of sufficient levels of different chemotherapies because of their low therapeutic index. Thus, instead of leaving a trail of off-target damage when killing these cancer cells, it is best to find a way that targets them directly. More seriously, metastatic relapse often occurs after surgery, and therefore, achieving improved outcomes in the management of PDAC in the absence of strategies preventing metastasis is likely to be impossible. Nano-targeting of the tumor and its microenvironment has shown promise for treating various cancers, which might be a promising approach for PDAC. This review updates the advancements in treatment modalities for pancreatic cancer and highlights future directions that warrant further investigation to increase pancreatic patients’ overall survival.