Unsupervised class discovery in pancreatic ductal adenocarcinoma reveals cell-intrinsic mesenchymal features and high concordance between existing classification systems

Transcriptome-based classification to predict FOLFIRINOX response in a real-world metastatic pancreatic cancer cohort

Pancreatic ductal adenocarcinoma (PDAC) is often diagnosed at metastatic stage and typically treated with fluorouracil, leucovorin, irinotecan and oxaliplatin (FOLFIRINOX). Few patients benefit from this treatment. Molecular subtypes are prognostic in particularly resectable PDAC and might predict treatment response. This study aims to correlate molecular subtypes in metastatic PDAC with FOLFIRINOX responses using real-world data, providing assistance in counselling patients. We collected 131 RNA-sequenced metastatic biopsies and applied a network-based meta-analysis using published PDAC classifiers. Subsequent survival analysis was performed using the most suitable classifier. For validation, we developed an immunohistochemistry (IHC) classifier using GATA6 and keratin-17 (KRT17), and applied it to 86 formalin-fixed paraffin-embedded samples of advanced PDAC. Lastly, GATA6 knockdown models were generated in PDAC organoids and cell lines. We showed that the PurIST classifier was the most suitable classifier. With this classifier, classical tumors had longer PFS and OS than basal-like tumors (PFS: 216 vs. 78 days, p = 0.0002; OS: 251 vs. 195 days, p = 0.049). The validation cohort showed a similar trend. Importantly, IHC GATA6low patients had significantly shorter survival with FOLFIRINOX (323 vs. 746 days, p = 0.006), but no difference in non-treated patients (61 vs. 54 days, p = 0.925). This suggests that GATA6 H-score predicts therapy response. GATA6 knockdown models did not lead to increased FOLFIRINOX responsiveness. These data suggest a predictive role for subtyping (transcriptomic and GATA6 IHC), though no direct causal relationship was found between GATA6 expression and chemoresistance. GATA6 immunohistochemistry should be seamlessly added to current diagnostics and integrated into upcoming clinical trials.

Cell-specific models reveal conformation-specific RAF inhibitor combinations that synergistically inhibit ERK signaling in pancreatic cancer cells

Pancreatic ductal adenocarcinoma (PDAC) presents significant challenges for targeted clinical interventions due to prevalent KRAS mutations, rendering PDAC resistant to RAF and MEK inhibitors (RAFi and MEKi). In addition, responses to targeted therapies vary between patients. Here, we explored the differential sensitivities of PDAC cell lines to RAFi and MEKi and developed an isogenic pair comprising the most sensitive and resistant PDAC cells. To simulate patient- or tumor-specific variations, we constructed cell-line-specific mechanistic models based on protein expression profiling and differential properties of KRAS mutants. These models predicted synergy between two RAFi with different conformation specificity (type I½ and type II RAFi) in inhibiting phospho-ERK (ppERK) and reducing PDAC cell viability. This synergy was experimentally validated across all four studied PDAC cell lines. Our findings underscore the need for combination approaches to inhibit the ERK pathway in PDAC.

Transcriptomic subtyping of gastrointestinal malignancies

Gastrointestinal (GI) cancers are highly heterogeneous at multiple levels. Tumor heterogeneity can be captured by molecular profiling, such as genetic, epigenetic, proteomic, and transcriptomic classification. Transcriptomic subtyping has the advantage of combining genetic and epigenetic information, cancer cell-intrinsic properties, and the tumor microenvironment (TME). Unsupervised transcriptomic subtyping systems of different GI malignancies have gained interest because they reveal shared biological features across cancers and bear prognostic and predictive value. Importantly, transcriptomic subtypes accurately reflect complex phenotypic states varying not only per tumor region, but also throughout disease progression, with consequences for clinical management. Here, we discuss methodologies of transcriptomic subtyping, proposed taxonomies for GI malignancies, and the challenges posed to clinical implementation, highlighting opportunities for future transcriptomic profiling efforts to optimize clinical impact.

Kinase activities in pancreatic ductal adenocarcinoma with prognostic and therapeutic avenues

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with a limited number of known driver mutations but considerable cancer cell heterogeneity. Phosphoproteomics provides a direct read-out of aberrant signaling and the resultant clinically relevant phenotype. Mass spectrometry (MS)-based proteomics and phosphoproteomics were applied to 42 PDAC tumors. Data encompassed over 19 936 phosphoserine or phosphothreonine (pS/T; in 5412 phosphoproteins) and 1208 phosphotyrosine (pY; in 501 phosphoproteins) sites and a total of 3756 proteins. Proteome data identified three distinct subtypes with tumor intrinsic and stromal features. Subsequently, three phospho-subtypes were apparent: two tumor intrinsic (Phos1/2) and one stromal (Phos3), resembling known PDAC molecular subtypes. Kinase activity was analyzed by the Integrative iNferred Kinase Activity (INKA) scoring. Phospho-subtypes displayed differential phosphorylation signals and kinase activity, such as FGR and GSK3 activation in Phos1, SRC kinase family and EPHA2 in Phos2, and EGFR, INSR, MET, ABL1, HIPK1, JAK, and PRKCD in Phos3. Kinase activity analysis of an external PDAC cohort supported our findings and underscored the importance of PI3K/AKT and ERK pathways, among others. Interestingly, unfavorable patient prognosis correlated with higher RTK, PAK2, STK10, and CDK7 activity and high proliferation, whereas long survival was associated with MYLK and PTK6 activity, which was previously unknown. Subtype-associated activity profiles can guide therapeutic combination approaches in tumor and stroma-enriched tissues, and emphasize the critical role of parallel signaling pathways. In addition, kinase activity profiling identifies potential disease markers with prognostic significance.

A Histone Methylation-MAPK Signaling Axis Drives Durable Epithelial-Mesenchymal Transition in Hypoxic Pancreatic Cancer

The tumor microenvironment in pancreatic ductal adenocarcinoma (PDAC) plays a key role in tumor progression and response to therapy. The dense PDAC stroma causes hypovascularity, which leads to hypoxia. Here, we showed that hypoxia drives long-lasting epithelial-mesenchymal transition (EMT) in PDAC primarily through a positive-feedback histone methylation-MAPK signaling axis. Transformed cells preferentially underwent EMT in hypoxic tumor regions in multiple model systems. Hypoxia drove a cell autonomous EMT in PDAC cells, which, unlike EMT in response to growth factors, could last for weeks. Furthermore, hypoxia reduced histone demethylase KDM2A activity, suppressed PP2 family phosphatase expression, and activated MAPKs to post-translationally stabilize histone methyltransferase NSD2, leading to an H3K36me2-dependent EMT in which hypoxia-inducible factors played only a supporting role. Hypoxia-driven EMT could be antagonized in vivo by combinations of MAPK inhibitors. Collectively, these results suggest that hypoxia promotes durable EMT in PDAC by inducing a histone methylation-MAPK axis that can be effectively targeted with multidrug therapies, providing a potential strategy for overcoming chemoresistance.

SIGNIFICANCE

Integrated regulation of histone methylation and MAPK signaling by the low-oxygen environment of pancreatic cancer drives long-lasting EMT that promotes chemoresistance and shortens patient survival and that can be pharmacologically inhibited. See related commentary by Wirth and Schneider, p. 1739.

Exploiting a subtype-specific mitochondrial vulnerability for successful treatment of colorectal peritoneal metastases

Peritoneal metastases (PMs) from colorectal cancer (CRC) respond poorly to treatment and are associated with unfavorable prognosis. For example, the addition of hyperthermic intraperitoneal chemotherapy (HIPEC) to cytoreductive surgery in resectable patients shows limited benefit, and novel treatments are urgently needed. The majority of CRC-PMs represent the CMS4 molecular subtype of CRC, and here we queried the vulnerabilities of this subtype in pharmacogenomic databases to identify novel therapies. This reveals the copper ionophore elesclomol (ES) as highly effective against CRC-PMs. ES exhibits rapid cytotoxicity against CMS4 cells by targeting mitochondria. We find that a markedly reduced mitochondrial content in CMS4 cells explains their vulnerability to ES. ES demonstrates efficacy in preclinical models of PMs, including CRC-PMs and ovarian cancer organoids, mouse models, and a HIPEC rat model of PMs. The above proposes ES as a promising candidate for the local treatment of CRC-PMs, with broader implications for other PM-prone cancers.

STAT3 is a genetic modifier of TGF-beta induced EMT in KRAS mutant pancreatic cancer

Oncogenic mutations in KRAS are among the most common in cancer. Classical models suggest that loss of epithelial characteristics and the acquisition of mesenchymal traits are associated with cancer aggressiveness and therapy resistance. However, the mechanistic link between these phenotypes and mutant KRAS biology remains to be established. Here, we identify STAT3 as a genetic modifier of TGF-beta-induced epithelial to mesenchymal transition. Gene expression profiling of pancreatic cancer cells identifies more than 200 genes commonly regulated by STAT3 and oncogenic KRAS. Functional classification of the STAT3-responsive program reveals its major role in tumor maintenance and epithelial homeostasis. The signatures of STAT3-activated cell states can be projected onto human KRAS mutant tumors, suggesting that they faithfully reflect characteristics of human disease. These observations have implications for therapeutic intervention and tumor aggressiveness.

Pancreatic Cancer Treatment Targeting the HGF/c-MET Pathway: The MEK Inhibitor Trametinib

Pancreatic cancer is characterized by fibrosis/desmoplasia in the tumor microenvironment, which is primarily mediated by pancreatic stellate cells and cancer-associated fibroblasts. HGF/c-MET signaling, which is instrumental in embryonic development and wound healing, is also implicated for its mitogenic and motogenic properties. In pancreatic cancer, this pathway, along with its downstream signaling pathways, is associated with disease progression, prognosis, metastasis, chemoresistance, and other tumor-related factors. Other features of the microenvironment in pancreatic cancer with the HGF/c-MET pathway include hypoxia, angiogenesis, metastasis, and the urokinase plasminogen activator positive feed-forward loop. All these attributes critically influence the initiation, progression, and metastasis of pancreatic cancer. Therefore, targeting the HGF/c-MET signaling pathway appears promising for the development of innovative drugs for pancreatic cancer treatment. One of the primary downstream effects of c-MET activation is the MAPK/ERK (Ras, Ras/Raf/MEK/ERK) signaling cascade, and MEK (Mitogen-activated protein kinase kinase) inhibitors have demonstrated therapeutic value in RAS-mutant melanoma and lung cancer. Trametinib is a selective MEK1 and MEK2 inhibitor, and it has evolved as a pivotal therapeutic agent targeting the MAPK/ERK pathway in various malignancies, including BRAF-mutated melanoma, non-small cell lung cancer and thyroid cancer. The drug's effectiveness increases when combined with agents like BRAF inhibitors. However, resistance remains a challenge, necessitating ongoing research to counteract the resistance mechanisms. This review offers an in-depth exploration of the HGF/c-MET signaling pathway, trametinib's mechanism, clinical applications, combination strategies, and future directions in the context of pancreatic cancer.

Qualitative flow metabolic phenotype of pancreatic cancer. A new prognostic biomarker?

BACKGROUND

Retrospective analysis to investigate the relationship between the flow-metabolic phenotype and overall survival (OS) of pancreatic ductal adenocarcinoma (PDAC) and its potential clinical utility.

METHODS

Patients with histopathologically proven PDAC between 2005 and 2014 using tumor attenuation on routine pre-operative CECT as a surrogate for the vascularity and [18F]FDG-uptake as a surrogate for metabolic activity on [18F]FDG-PET.

RESULTS

In total, 93 patients (50 male, 43 female, median age 63) were included. Hypoattenuating PDAC with high [18F]FDG-uptake has the poorest prognosis (median OS 7 ± 1 months), compared to hypoattenuating PDAC with low [18F]FDG-uptake (median OS 11 ± 3 months; p = 0.176), iso- or hyperattenuating PDAC with high [18F]FDG-uptake (median OS 15 ± 5 months; p = 0.004) and iso- or hyperattenuating PDAC with low [18F]FDG-uptake (median OS 23 ± 4 months; p = 0.035). In multivariate analysis, surgery combined with tumor differentiation, tumor stage, systemic therapy and flow metabolic phenotype remained independent predictors for overall survival.

DISCUSSION

The novel qualitative flow-metabolic phenotype of PDAC using a combination of CECT and [18F]FDG-PET features, predicted significantly worse survival for hypoattenuating-high uptake pancreatic cancers compared to the other phenotypes.

Efficient computation of high-dimensional penalized generalized linear mixed models by latent factor modeling of the random effects

Modern biomedical datasets are increasingly high-dimensional and exhibit complex correlation structures. Generalized linear mixed models (GLMMs) have long been employed to account for such dependencies. However, proper specification of the fixed and random effects in GLMMs is increasingly difficult in high dimensions, and computational complexity grows with increasing dimension of the random effects. We present a novel reformulation of the GLMM using a factor model decomposition of the random effects, enabling scalable computation of GLMMs in high dimensions by reducing the latent space from a large number of random effects to a smaller set of latent factors. We also extend our prior work to estimate model parameters using a modified Monte Carlo Expectation Conditional Minimization algorithm, allowing us to perform variable selection on both the fixed and random effects simultaneously. We show through simulation that through this factor model decomposition, our method can fit high-dimensional penalized GLMMs faster than comparable methods and more easily scale to larger dimensions not previously seen in existing approaches.

Predicting Long-term Disease-free Survival After Resection of Pancreatic Ductal Adenocarcinoma: A Nationwide Cohort Study

OBJECTIVE

To develop a prediction model for long-term (≥5 years) disease-free survival (DFS) after the resection of pancreatic ductal adenocarcinoma (PDAC).

BACKGROUND

Despite high recurrence rates, ~10% of patients have long-term DFS after PDAC resection. A model to predict long-term DFS may aid individualized prognostication and shared decision-making.

METHODS

This nationwide cohort study included all consecutive patients who underwent PDAC resection in the Netherlands (2014-2016). The best-performing prognostic model was selected by Cox-proportional hazard analysis and Akaike's Information Criterion, presented by hazard ratios (HRs) with 95% confidence intervals (CIs). Internal validation was performed, and discrimination and calibration indices were assessed.

RESULTS

In all, 836 patients with a median follow-up of 67 months (interquartile range 51-79) were analyzed. Long-term DFS was seen in 118 patients (14%). Factors predictive of long-term DFS were low preoperative carbohydrate antigen 19-9 (logarithmic; HR 1.21; 95% CI 1.10-1.32), no vascular resection (HR 1.33; 95% CI 1.12-1.58), T1 or T2 tumor stage (HR 1.52; 95% CI 1.14-2.04, and HR 1.17; 95% CI 0.98-1.39, respectively), well/moderate tumor differentiation (HR 1.44; 95% CI 1.22-1.68), absence of perineural and lymphovascular invasion (HR 1.42; 95% CI 1.11-1.81 and HR 1.14; 95% CI 0.96-1.36, respectively), N0 or N1 nodal status (HR 1.92; 95% CI 1.54-2.40, and HR 1.33; 95% CI 1.11-1.60, respectively), R0 resection margin status (HR 1.25; 95% CI 1.07-1.46), no major complications (HR 1.14; 95% CI 0.97-1.35) and adjuvant chemotherapy (HR 1.74; 95% CI 1.47-2.06). Moderate performance (concordance index 0.68) with adequate calibration (slope 0.99) was achieved.

CONCLUSIONS

The developed prediction model, readily available at www.pancreascalculator.com, can be used to estimate the probability of long-term DFS after resection of pancreatic ductal adenocarcinoma.

RBFOX2 deregulation promotes pancreatic cancer progression and metastasis through alternative splicing

RNA splicing is an important biological process associated with cancer initiation and progression. However, the contribution of alternative splicing to pancreatic cancer (PDAC) development is not well understood. Here, we identify an enrichment of RNA binding proteins (RBPs) involved in splicing regulation linked to PDAC progression from a forward genetic screen using Sleeping Beauty insertional mutagenesis in a mouse model of pancreatic cancer. We demonstrate downregulation of RBFOX2, an RBP of the FOX family, promotes pancreatic cancer progression and liver metastasis. Specifically, we show RBFOX2 regulates exon splicing events in transcripts encoding proteins involved in cytoskeletal remodeling programs. These exons are differentially spliced in PDAC patients, with enhanced exon skipping in the classical subtype for several RBFOX2 targets. RBFOX2 mediated splicing of ABI1, encoding the Abelson-interactor 1 adapter protein, controls the abundance and localization of ABI1 protein isoforms in pancreatic cancer cells and promotes the relocalization of ABI1 from the cytoplasm to the periphery of migrating cells. Using splice-switching antisense oligonucleotides (AONs) we demonstrate the ABI1 ∆Ex9 isoform enhances cell migration. Together, our data identify a role for RBFOX2 in promoting PDAC progression through alternative splicing regulation.

Relative expression of hormone receptors by endothelial and smooth muscle cells in proliferative and non-proliferative areas of congenital arteriovenous malformations

BACKGROUND

Episodic growth due to microvascular proliferations (MVP) has been reported in congenital arteriovenous malformations (AVM), which are normally quiescent lesions composed of mature malformed vessels. Since AVM also may worsen under conditions of hormonal dysregulation, we hypothesized that hormonal influences may stimulate this process of vasoproliferative growth through potential interactions with hormone receptors (HR).

METHODS

13 Cases of AVM tissue with histologically documented vasoproliferative growth were analyzed quantitatively for the presence and tissue localization of estrogen receptor (ER), progesterone receptor (PGR), growth hormone receptor (GHR) and follicle-stimulating hormone receptor (FSHR) in relation to resident cells of interest (endothelial cells (EC), smooth muscle cells (SMC) and mast cells (MC)) by applying multiplex immunohistochemistry (IHC) staining. Expression patterns in lesions with MVP and mature vessels were quantified and compared. Available fresh frozen tissues of 3 AVM samples were used to confirm the presence of HR using Reverse-Transcriptase quantitative Polymerase Chain Reaction (RT-qPCR).

RESULTS

All four HR studied were expressed in all cases within EC and SMC in areas of MVP and mature vessels, but not in normal skin tissue. ER, GHR, and FSHR showed more expression in EC of MVP and in SMC of mature vessels. RT-qPCR confirmed presence of all 4 HR in both areas.

CONCLUSION

Expression of ER, PGR, GHR, and FSHR in vasoproliferative areas of congenital AVM could explain onset of sudden symptomatic growth, as has observed in a subpopulation of patients. These findings may have implications for eventual anti-hormonal targeted therapy in the lesions involved.

Oncogenic dependency plays a dominant role in the immune response to cancer

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest human malignancies. Advanced PDAC is considered incurable. Nearly 90% of pancreatic cancers are caused by oncogenic KRAS mutations. The mechanisms of primary or acquired resistance to KRAS inhibition are currently unknown. Here, we propose that oncogenic dependency, rather than KRAS mutation per se, plays a dominant role in the immune response to cancer, including late-stage PDAC. Classifying tumor samples according to KRAS activity scores allows accurate prediction of tumor immune composition and therapy response. Dual RAS/MAPK pathway blockade combining KRAS and MEK inhibitors is more effective than the selective KRAS inhibitor alone in attenuating MAPK activation and unblocking the influx of T cells into the tumor. Lowering KRAS activity in established tumors promotes immune infiltration, but with a limited antitumor effect, whereas combining KRAS/MEK inhibition with immune checkpoint blockade achieves durable regression in preclinical models. The results are directly applicable to stratifying human PDAC based on KRAS dependency values and immune cell composition to improve therapeutic design.

STAT3 is a genetic modifier of TGF-beta induced EMT in KRAS mutant pancreatic cancer

Oncogenic mutations in KRAS are among the most common in cancer. Classical models suggest that loss of epithelial characteristics and the acquisition of mesenchymal traits are associated with cancer aggressiveness and therapy resistance. However, the mechanistic link between these phenotypes and mutant KRAS biology remains to be established. Here we identify STAT3 as a genetic modifier of TGF-beta-induced epithelial to mesenchymal transition. Gene expression profiling of pancreatic cancer cells identifies more than 200 genes commonly regulated by STAT3 and oncogenic KRAS. Functional classification of STAT3 responsive program reveals its major role in tumor maintenance and epithelial homeostasis. The signatures of STAT3-activated cell states can be projected onto human KRAS mutant tumors, suggesting that they faithfully reflect characteristics of human disease. These observations have implications for therapeutic intervention and tumor aggressiveness.

Phosphoproteomics guides effective low-dose drug combinations against pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with a limited set of known driver mutations but considerable cancer cell heterogeneity. Phosphoproteomics provides a readout of aberrant signaling and has the potential to identify new targets and guide treatment decisions. Using two-step sequential phosphopeptide enrichment, we generate a comprehensive phosphoproteome and proteome of nine PDAC cell lines, encompassing more than 20,000 phosphosites on 5,763 phospho-proteins, including 316 protein kinases. By using integrative inferred kinase activity (INKA) scoring, we identify multiple (parallel) activated kinases that are subsequently matched to kinase inhibitors. Compared with high-dose single-drug treatments, INKA-tailored low-dose 3-drug combinations against multiple targets demonstrate superior efficacy against PDAC cell lines, organoid cultures, and patient-derived xenografts. Overall, this approach is particularly more effective against the aggressive mesenchymal PDAC model compared with the epithelial model in both preclinical settings and may contribute to improved treatment outcomes in PDAC patients.

Single-cell profiling to explore pancreatic cancer heterogeneity, plasticity and response to therapy

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer entity characterized by a heterogeneous genetic landscape and an immunosuppressive tumor microenvironment. Recent advances in high-resolution single-cell sequencing and spatial transcriptomics technologies have enabled an in-depth characterization of both malignant and host cell types and increased our understanding of the heterogeneity and plasticity of PDAC in the steady state and under therapeutic perturbation. In this Review we outline single-cell analyses in PDAC, discuss their implications on our understanding of the disease and present future perspectives of multimodal approaches to elucidate its biology and response to therapy at the single-cell level.

The molecular biology of peritoneal metastatic disease

Peritoneal metastases are a common form of tumor cell dissemination in gastrointestinal malignancies. Peritoneal metastatic disease (PMD) is associated with severe morbidity and resistance to currently employed therapies. Given the distinct route of dissemination compared with distant organ metastases, and the unique microenvironment of the peritoneal cavity, specific tumor cell characteristics are needed for the development of PMD. In this review, we provide an overview of the known histopathological, genomic, and transcriptomic features of PMD. We find that cancers representing the mesenchymal subtype are strongly associated with PMD in various malignancies. Furthermore, we discuss the peritoneal niche in which the metastatic cancer cells reside, including the critical role of the peritoneal immune system. Altogether, we show that PMD should be regarded as a distinct disease entity, that requires tailored treatment strategies.

Poor-prognosis molecular subtypes in adenocarcinomas of pancreato-biliary and gynecological origin: A systematic review

Pancreato-biliary and gynecological adenocarcinomas need better tools to predict clinical outcome. Potential prognostic mesenchymal(-like) transcriptome-based subtypes have been identified in these cancers. In this systematic review, we include studies into molecular subtyping and summarize biological and clinical features of the subtypes within and across sites of origin, searching for suggestions to improve classification and prognostication. PubMed and Embase were searched for original research articles describing potential mesenchymal(-like) mRNA-based subtypes in pancreato-biliary or gynecological adenocarcinomas. Studies limited to supervised clustering were excluded. Fourty-four studies, discussing cholangiocarcinomas, gallbladder, ampullary, pancreatic, ovarian, and endometrial adenocarcinomas were included. There was overlap in molecular and clinical features in mesenchymal(-like) subtypes across all adenocarcinomas. Approaches including microdissection were more likely to identify prognosis-associating subtypes. To conclude, molecular subtypes in pancreato-biliary and gynecological adenocarcinomas share biological and clinical characteristics. Furthermore, separation of stromal and epithelial signals should be applied in future studies into biliary and gynecological adenocarcinomas.

Serum levels of iCAF-derived osteoglycin predict favorable outcome in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is characterized by abundant stroma, the main cellular constituents of which are cancer-associated fibroblasts (CAFs). Stroma-targeting agents have been proposed to improve the poor outcome of current treatments. However, clinical trials using these agents showed disappointing results. Heterogeneity in the PDAC CAF population was recently delineated demonstrating that both tumor-promoting and tumor-suppressive activities co-exist in the stroma. Here, we aimed to identify biomarkers for the CAF population that contribute to a favorable outcome. RNA-sequencing reads from patient-derived xenografts (PDXs) were mapped to the human and mouse genome to allocate the expression of genes to the tumor or stroma. Survival meta-analysis for stromal genes was performed and applied to human protein atlas data to identify circulating biomarkers. The candidate protein was perturbed in co-cultures and assessed in existing and novel single-cell gene expression analysis from control, pancreatitis, pancreatitis-recovered and PDAC mouse models. Serum levels of the candidate biomarker were measured in two independent cohorts totaling 148 PDAC patients and related them to overall survival. Osteoglycin (OGN) was identified as a candidate serum prognostic marker. Single-cell analysis indicated that Ogn is derived from a subgroup of inflammatory CAFs. Ogn-expressing fibroblasts are distinct from resident healthy pancreatic stellate cells and arise during pancreatitis. Serum OGN levels were prognostic for favorable overall survival in two independent PDAC cohorts (HR = 0.47, P = .042 and HR = 0.53, P = .006). Altogether, we conclude that high circulating OGN levels inform on a previously unrecognized subgroup of CAFs and predict favorable outcomes in resectable PDAC.

An Immunogenic Cell Death-Related Gene Signature Reflects Immune Landscape and Predicts Prognosis in Melanoma Independently of BRAF V600E Status

Immunogenic cell death (ICD) is a type of regulated cell death that can activate adaptive immune response, and its ability to reshape the tumor microenvironment via multiple mechanisms may contribute to immunotherapy. The treatment options for patients with skin cutaneous melanoma (SKCM) vary based on BRAF V600E statuses. However, all standard treatments include immunotherapy. Therefore, it is critical to identify ICD-associated signatures that can help classify patients according to benefits from ICD immunotherapy. In this study, data on melanoma samples with BRAF V600E mutation (BRAF V600E-mutant melanoma) and melanoma samples with wild-type BRAF V600E alleles (BRAF V600E WT melanoma) were collected from The Cancer Genome Atlas (TCGA) database. The ICD-related (ICD-high and ICD-low) subgroups of patients with BRAF V600E WT melanoma were established via consensus clustering. The analyses of survival, differentially expressed genes (DEGs), functional annotation, and immune landscape were performed in these two subgroups. Results showed that ICD-high subgroup was correlated with a positive overall survival (OS) and active tumor immune landscape. A model comprising seven prognosis ICD-related gene biomarkers was developed. Survival analysis and receiver operating characteristic (ROC) curve evaluation in both cohorts with BRAF V600E WT and BRAF V600E-mutant melanoma showed an accurate prognostic estimation of ICD-related risk signature. There was a correlation between immune cell infiltration and immunotherapy response and risk score. Thus, the ICD risk signature was closely associated with the tumor's immune microenvironment. Our results may provide insights to further individualize and improve precision therapeutic decision-making in BRAF V600E-mutant and WT melanoma.

XDec-CHI reveals immunosuppressive interactions in pancreatic ductal adenocarcinoma

Most cancers harbor a diverse collection of cell types including a typically heterogeneous cancer cell fraction. To reconstruct cell-intrinsic and heterotypic interactions driving tumor progression, we combine the XDec deconvolution method with cell-type-specific gene expression correlation analysis into the XDec-CHI method. XDec-CHI identifies intra- and inter-cellular pathways using correlation and places them in the context of specific tumor subtypes, as defined by the state of constituent cancer cells. We make the method web-accessible for analysis of publicly accessible pancreatic ductal adenocarcinoma, breast, head and neck, glioblastoma, and glioma tumors. We apply the method to TCGA and ICGC datasets to identify immune-suppressive interactions within PDAC tumors that are relevant for immunotherapies targeting PD-L1. Subtype-specific interactions derived from correlative analyses validated in co-culture experiments suggest PDAC subtypes have distinct therapeutic weaknesses, with Basal-like and MSLN-high Classical B tumors most likely to respond to therapies targeting PD-L1.

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.

Establishment of a reference single-cell RNA sequencing dataset for human pancreatic adenocarcinoma

Single-cell RNA sequencing (scRNAseq) has been used to assess the intra-tumor heterogeneity and microenvironment of pancreatic ductal adenocarcinoma (PDAC). However, previous knowledge is not fully universalized. Here, we built a single cell atlas of PDAC from six datasets containing over 70 samples and >130,000 cells, and demonstrated its application to the reanalysis of the previous bulk transcriptomic cohorts and inferring cell-cell communications. The cell decomposition of bulk transcriptomics using scRNAseq data showed the cellular heterogeneity of PDAC; moreover, high levels of tumor cells and fibroblasts were indicative of poor-prognosis. Refined tumor subtypes signature indicated the tumor cell dynamics in intra-tumor and their specific regulatory network. We further identified functionally distinct tumor clusters that had close interaction with fibroblast subtypes via different signaling pathways dependent on subtypes. Our analysis provided a reference dataset for PDAC and showed its utility in research on the microenvironment of intra-tumor heterogeneity.

Multi-Omics-Based Autophagy-Related Untypical Subtypes in Patients with Cerebral Amyloid Pathology

Recent multi-omics analyses paved the way for a comprehensive understanding of pathological processes. However, only few studies have explored Alzheimer's disease (AD) despite the possibility of biological subtypes within these patients. For this study, unsupervised classification of four datasets (genetics, miRNA transcriptomics, proteomics, and blood-based biomarkers) using Multi-Omics Factor Analysis+ (MOFA+), along with systems-biological approaches following various downstream analyses are performed. New subgroups within 170 patients with cerebral amyloid pathology (Aβ+) are revealed and the features of them are identified based on the top-rated targets constructing multi-omics factors of both whole (M-TPAD) and immune-focused models (M-IPAD). The authors explored the characteristics of subtypes and possible key-drivers for AD pathogenesis. Further in-depth studies showed that these subtypes are associated with longitudinal brain changes and autophagy pathways are main contributors. The significance of autophagy or clustering tendency is validated in peripheral blood mononuclear cells (PBMCs; n = 120 including 30 Aβ- and 90 Aβ+), induced pluripotent stem cell-derived human brain organoids/microglia (n = 12 including 5 Aβ-, 5 Aβ+, and CRISPR-Cas9 apolipoprotein isogenic lines), and human brain transcriptome (n = 78). Collectively, this study provides a strategy for precision medicine therapy and drug development for AD using integrative multi-omics analysis and network modelling.

Consensus Statement on Mandatory Measurements for Pancreatic Cancer Trials for Patients With Resectable or Borderline Resectable Disease (COMM-PACT-RB): A Systematic Review and Delphi Consensus Statement

Importance

Pancreatic cancer is the third most common cause of cancer death; however, randomized clinical trials (RCTs) of survival in patients with resectable pancreatic cancer lack mandatory measures for reporting baseline and prognostic factors, which hampers comparisons between outcome measures.

Objective

To develop a consensus on baseline and prognostic factors to be used as mandatory measurements in RCTs of resectable and borderline resectable pancreatic cancer.

Evidence Review

We performed a systematic literature search of the Cochrane Central Register of Controlled Trials (CENTRAL), PubMed, and Embase for RCTs on resectable and borderline resectable pancreatic cancer with overall survival as the primary outcome. We produced a systematic summary of all baseline and prognostic factors identified in the RCTs. A Delphi panel that included 13 experts was surveyed to reach a consensus on mandatory and recommended baseline and prognostic factors.

Findings

The 42 RCTs that met inclusion criteria reported a total of 60 baseline and 19 prognostic factors. After 2 Delphi rounds, agreement was reached on 50 mandatory baseline and 20 mandatory prognostic factors for future RCTs, with a distinction between studies of neoadjuvant vs adjuvant treatment.

Conclusion and Relevance

This findings of this systematic review and international expert consensus have produced this Consensus Statement on Mandatory Measurements in Pancreatic Cancer Trials for Resectable and Borderline Resectable Disease (COMM-PACT-RB). The baseline and prognostic factors comprising the mandatory measures will facilitate better comparison across RCTs and eventually will enable improved clinical practice among patients with resectable and borderline resectable pancreatic cancer.

Selective multi-kinase inhibition sensitizes mesenchymal pancreatic cancer to immune checkpoint blockade by remodeling the tumor microenvironment

KRAS-mutant pancreatic ductal adenocarcinoma (PDAC) is highly immunosuppressive and resistant to targeted and immunotherapies. Among the different PDAC subtypes, basal-like mesenchymal PDAC, which is driven by allelic imbalance, increased gene dosage and subsequent high expression levels of oncogenic KRAS, shows the most aggressive phenotype and strongest therapy resistance. In the present study, we performed a systematic high-throughput combination drug screen and identified a synergistic interaction between the MEK inhibitor trametinib and the multi-kinase inhibitor nintedanib, which targets KRAS-directed oncogenic signaling in mesenchymal PDAC. This combination treatment induces cell-cycle arrest and cell death, and initiates a context-dependent remodeling of the immunosuppressive cancer cell secretome. Using a combination of single-cell RNA-sequencing, CRISPR screens and immunophenotyping, we show that this combination therapy promotes intratumor infiltration of cytotoxic and effector T cells, which sensitizes mesenchymal PDAC to PD-L1 immune checkpoint inhibition. Overall, our results open new avenues to target this aggressive and therapy-refractory mesenchymal PDAC subtype.

HDAC2 Facilitates Pancreatic Cancer Metastasis

The mortality of patients with pancreatic ductal adenocarcinoma (PDAC) is strongly associated with metastasis, a multistep process that is incompletely understood in this disease. Although genetic drivers of PDAC metastasis have not been defined, transcriptional and epigenetic rewiring can contribute to the metastatic process. The epigenetic eraser histone deacetylase 2 (HDAC2) has been connected to less differentiated PDAC, but the function of HDAC2 in PDAC has not been comprehensively evaluated. Using genetically defined models, we show that HDAC2 is a cellular fitness factor that controls cell cycle in vitro and metastasis in vivo, particularly in undifferentiated, mesenchymal PDAC cells. Unbiased expression profiling detected a core set of HDAC2-regulated genes. HDAC2 controlled expression of several prosurvival receptor tyrosine kinases connected to mesenchymal PDAC, including PDGFRα, PDGFRβ, and EGFR. The HDAC2-maintained program disabled the tumor-suppressive arm of the TGFβ pathway, explaining impaired metastasis formation of HDAC2-deficient PDAC. These data identify HDAC2 as a tractable player in the PDAC metastatic cascade. The complexity of the function of epigenetic regulators like HDAC2 implicates that an increased understanding of these proteins is needed for implementation of effective epigenetic therapies.

SIGNIFICANCE

HDAC2 has a context-specific role in undifferentiated PDAC and the capacity to disseminate systemically, implicating HDAC2 as targetable protein to prevent metastasis.

Analysis of the glyco-code in pancreatic ductal adenocarcinoma identifies glycan-mediated immune regulatory circuits

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most aggressive malignancies with a 5-year survival rate of only 9%. Despite the fact that changes in glycosylation patterns during tumour progression have been reported, no systematic approach has been conducted to evaluate its potential for patient stratification. By analysing publicly available transcriptomic data of patient samples and cell lines, we identified here two specific glycan profiles in PDAC that correlated with progression, clinical outcome and epithelial to mesenchymal transition (EMT) status. These different glycan profiles, confirmed by glycomics, can be distinguished by the expression of O-glycan fucosylated structures, present only in epithelial cells and regulated by the expression of GALNT3. Moreover, these fucosylated glycans can serve as ligands for DC-SIGN positive tumour-associated macrophages, modulating their activation and inducing the production of IL-10. Our results show mechanisms by which the glyco-code contributes to the tolerogenic microenvironment in PDAC.

Rodriguez et al. present a transcriptomic analysis of glycosylation associated gene profiles, including bulk patient sequencing, sc-RNA seq, cell lines and organoids, to examine glycosylation in PDAC. They find 2 specific glycan profiles correlating with progression, clinical outcome and EMT, and conclude that the glyco-code contributes to the tolerogenic microenvironment in PDAC.

Robust deep learning model for prognostic stratification of pancreatic ductal adenocarcinoma patients

A major challenge for treating patients with pancreatic ductal adenocarcinoma (PDAC) is the unpredictability of their prognoses due to high heterogeneity. We present Multi-Omics DEep Learning for Prognosis-correlated subtyping (MODEL-P) to identify PDAC subtypes and to predict prognoses of new patients. MODEL-P was trained on autoencoder integrated multi-omics of 146 patients with PDAC together with their survival outcome. Using MODEL-P, we identified two PDAC subtypes with distinct survival outcomes (median survival 10.1 and 22.7 months, respectively, log rank p = 1 × 10⁻⁶), which correspond to DNA damage repair and immune response. We rigorously validated MODEL-P by stratifying patients in five independent datasets into these two survival groups and achieved significant survival difference, which is superior to current practice and other subtyping schemas. We believe the subtype-specific signatures would facilitate PDAC pathogenesis discovery, and MODEL-P can provide clinicians the prognoses information in the treatment decision-making to better gauge the benefits versus the risks.

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We developed DL-based MODEL-P to identify prognosis-correlated PDAC subtypes

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The identified subtypes related to DNA damage repair and immune response processes

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MODEL-P stratified patients from independent datasets into distinct survival groups

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MODEL-P could be used in clinics to aid treatment decision-making

HSP90 Inhibition Synergizes with Cisplatin to Eliminate Basal-like Pancreatic Ductal Adenocarcinoma Cells

Simple Summary

Pancreatic cancer is currently difficult to treat, but the drug cisplatin represents one of the most important therapeutic options. We find that cells derived from this cancer fall into two classes regarding their sensitivity towards cisplatin, and we observe that cells with high expression levels of GATA6 and microRNA 200 are mostly sensitive. However, those cells that respond poorly to cisplatin can be sensitized by drugs that inhibit HSP90, a protein that helps other proteins to fold properly. This was also found in a mouse model of pancreatic cancer. Our results suggest that the combination of cisplatin with HSP90-inhibitory drugs might improve the treatment of pancreatic cancer.

Abstract

To improve the treatment of pancreatic ductal adenocarcinoma (PDAC), a promising strategy consists of personalized chemotherapy based on gene expression profiles. Investigating a panel of PDAC-derived human cell lines, we found that their sensitivities towards cisplatin fall in two distinct classes. The platinum-sensitive class is characterized by the expression of GATA6, miRNA-200a, and miRNA-200b, which might be developable as predictive biomarkers. In the case of resistant PDAC cells, we identified a synergism of cisplatin with HSP90 inhibitors. Mechanistic explanations of this synergy include the degradation of Fanconi anemia pathway factors upon HSP90 inhibition. Treatment with the drug combination resulted in increased DNA damage and chromosome fragmentation, as we have reported previously for ovarian cancer cells. On top of this, HSP90 inhibition also enhanced the accumulation of DNA-bound platinum. We next investigated an orthotopic syngeneic animal model consisting of tumors arising from KPC cells (LSL-KrasG12D/+; LSL-Trp53R172H/+; Pdx-1-Cre, C57/BL6 genetic background). Here again, when treating established tumors, the combination of cisplatin with the HSP90 inhibitor onalespib was highly effective and almost completely prevented further tumor growth. We propose that the combination of platinum drugs and HSP90 inhibitors might be worth testing in the clinics for the treatment of cisplatin-resistant PDACs.

Clinical Impact of Molecular Subtyping of Pancreatic Cancer

Pancreatic ductal adenocarcinoma is a highly lethal malignancy, which has now become the seventh most common cause of cancer death in the world, with the highest mortality rates in Europe and North America. In the past 30 years, there has been some progress in 5-year survival (rates increasing from 2.5 to 10%), but this is still extremely poor compared to all other common cancer types. Targeted therapies for advanced pancreatic cancer based on actionable mutations have been disappointing, with only 3–5% showing even a short clinical benefit. There is, however, a molecular diversity beyond mutations in genes responsible for producing classical canonical signaling pathways. Pancreatic cancer is almost unique in promoting an excess production of other components of the stroma, resulting in a complex tumor microenvironment that contributes to tumor development, progression, and response to treatment. Various transcriptional subtypes have also been described. Most notably, there is a strong alignment between the Classical/Pancreatic progenitor and Quasi-mesenchymal/Basal-like/Squamous subtype signatures of Moffit, Collinson, Bailey, Puleo, and Chan-Seng-Yue, which have potential clinical impact. Sequencing of epithelial cell populations enriched by laser capture microscopy combined with single-cell RNA sequencing has revealed the potential genomic evolution of pancreatic cancer as being a consequence of a gene expression continuum from mixed Basal-like and Classical cell populations within the same tumor, linked to allelic imbalances in mutant KRAS, with metastatic tumors being more copy number-unstable compared to primary tumors. The Basal-like subtype appears more chemoresistant with reduced survival compared to the Classical subtype. Chemotherapy and/or chemoradiation will also enrich the Basal-like subtype. Squamous/Basal-like programs facilitate immune infiltration compared with the Classical-like programs. The immune infiltrates associated with Basal and Classical type cells are distinct, potentially opening the door to differential strategies. Single-cell and spatial transcriptomics will now allow single cell profiling of tumor and resident immune cell populations that may further advance subtyping. Multiple clinical trials have been launched based on transcriptomic response signatures and molecular subtyping including COMPASS, Precision Promise, ESPAC6/7, PREDICT-PACA, and PASS1. We review several approaches to explore the clinical relevance of molecular profiling to provide optimal bench-to-beside translation with clinical impact.

Bayesian log-normal deconvolution for enhanced in silico microdissection of bulk gene expression data

Deconvolution of bulk gene expression profiles into the cellular components is pivotal to portraying tissue's complex cellular make-up, such as the tumor microenvironment. However, the inherently variable nature of gene expression requires a comprehensive statistical model and reliable prior knowledge of individual cell types that can be obtained from single-cell RNA sequencing. We introduce BLADE (Bayesian Log-normAl Deconvolution), a unified Bayesian framework to estimate both cellular composition and gene expression profiles for each cell type. Unlike previous comprehensive statistical approaches, BLADE can handle > 20 types of cells due to the efficient variational inference. Throughout an intensive evaluation with > 700 simulated and real datasets, BLADE demonstrated enhanced robustness against gene expression variability and better completeness than conventional methods, in particular, to reconstruct gene expression profiles of each cell type. In summary, BLADE is a powerful tool to unravel heterogeneous cellular activity in complex biological systems from standard bulk gene expression data.

Genomic Heterogeneity of Pancreatic Ductal Adenocarcinoma and Its Clinical Impact

Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer death due to limited advances in recent years in early diagnosis and personalized therapy capable of overcoming tumor resistance to chemotherapy. In the last decades, significant advances have been achieved in the identification of recurrent genetic and molecular alterations of PDAC including those involving the KRAS, CDKN2A, SMAD4, and TP53 driver genes. Despite these common genetic traits, PDAC are highly heterogeneous tumors at both the inter- and intra-tumoral genomic level, which might contribute to distinct tumor behavior and response to therapy, with variable patient outcomes. Despite this, genetic and genomic data on PDAC has had a limited impact on the clinical management of patients. Integration of genomic data for classification of PDAC into clinically defined entities-i.e., classical vs. squamous subtypes of PDAC-leading to different treatment approaches has the potential for significantly improving patient outcomes. In this review, we summarize current knowledge about the most relevant genomic subtypes of PDAC including the impact of distinct patterns of intra-tumoral genomic heterogeneity on the classification and clinical and therapeutic management of PDAC.

New Insights Into Pancreatic Cancer: Notes from a Virtual Meeting

Pancreatic ductal adenocarcinoma remains a major challenge in cancer medicine. Given the increase in incidence and mortality, interdisciplinary research is necessary to translate basic knowledge into therapeutic strategies improving the outcome of patients. On the 4th and 5th of February 2021, three German pancreatic cancer research centers, the Clinical Research Unit 5002 from Göttingen, the Collaborative Research Center 1321 from Munich, and Clinical Research Unit 325 from Marburg organized the 1st Virtual Göttingen-Munich-Marburg Pancreatic Cancer Meeting in order to foster scientific exchange. This report summarizes current research and proceedings presented during that meeting.

The recurring features of molecular subtypes in distinct gastrointestinal malignancies-A systematic review

In colorectal cancer (CRC), pancreatic ductal adenocarcinoma (PDAC) and gastric cancer (GC) multiple studies of inter-tumor heterogeneity have identified molecular subtypes, which correlate with clinical features. Our aim was to investigate the attributes of molecular subtypes across three different gastrointestinal cancer types. We performed a systematic search for publications on molecular subtypes or classifications in PDAC and GC and compared the described subtypes with the established consensus molecular subtypes of CRC. Examining the characteristics of subtypes across CRC, PDAC and GC resulted in four categories of subtypes. We describe uniting and distinguishing features within a mesenchymal, an epithelial, an immunogenic and a metabolic and digestive subtype category. We conclude that molecular subtypes of CRC, PDAC and GC display relevant overlap in molecular features and clinical outcomes. This finding encourages quantitative studies on subtypes across different cancer types and could lead to a paradigm shift in future treatment strategies.

Identification and Validation of Immune Molecular Subtypes in Pancreatic Ductal Adenocarcinoma: Implications for Prognosis and Immunotherapy

Background

Pancreatic ductal adenocarcinoma (PDAC) remains treatment refractory. Immunotherapy has achieved success in the treatment of multiple malignancies. However, the efficacy of immunotherapy in PDAC is limited by a lack of promising biomarkers. In this research, we aimed to identify robust immune molecular subtypes of PDAC to facilitate prognosis prediction and patient selection for immunotherapy.

Methods

A training cohort of 149 PDAC samples from The Cancer Genome Atlas (TCGA) with mRNA expression data was analyzed. By means of non-negative matrix factorization (NMF), we virtually dissected the immune-related signals from bulk gene expression data. Detailed immunogenomic and survival analyses of the immune molecular subtypes were conducted to determine their biological and clinical relevance. Validation was performed in five independent datasets on a total of 615 samples.

Results

Approximately 31% of PDAC samples (46/149) had higher immune cell infiltration, more active immune cytolytic activity, higher activation of the interferon pathway, a higher tumor mutational burden (TMB), and fewer copy number alterations (CNAs) than the other samples (all P < 0.001). This new molecular subtype was named Immune Class, which served as an independent favorable prognostic factor for overall survival (hazard ratio, 0.56; 95% confidence interval, 0.33-0.97). Immune Class in cooperation with previously reported tumor and stroma classifications had a cumulative effect on PDAC prognostic stratification. Moreover, programmed cell death-1 (PD-1) inhibitors showed potential efficacy for Immune Class (P = 0.04). The robustness of our immune molecular subtypes was further verified in the validation cohort.

Conclusions

By capturing immune-related signals in the PDAC tumor microenvironment, we reveal a novel molecular subtype, Immune Class. Immune Class serves as an independent favorable prognostic factor for overall survival in PDAC patients.

Tumor-Associated Macrophages in Pancreatic Ductal Adenocarcinoma: Therapeutic Opportunities and Clinical Challenges

Simple Summary

Macrophages are a major component of the pancreatic tumor microenvironment, and their increased abundance is associated with poor patient survival. Given the multi-faceted role of macrophages in promoting pancreatic tumor development and progression, these cells represent promising targets for anti-cancer therapy.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignant disease with a 5-year survival rate of less than 10%. Macrophages are one of the earliest infiltrating cells in the pancreatic tumor microenvironment, and are associated with an increased risk of disease progression, recurrence, metastasis, and shorter overall survival. Pre-clinical studies have demonstrated an unequivocal role of macrophages in PDAC by contributing to chronic inflammation, cancer cell stemness, desmoplasia, immune suppression, angiogenesis, invasion, metastasis, and drug resistance. Several macrophage-targeting therapies have also been investigated in pre-clinical models, and include macrophage depletion, inhibiting macrophage recruitment, and macrophage reprogramming. However, the effectiveness of these drugs in pre-clinical models has not always translated into clinical trials. In this review, we discuss the molecular mechanisms that underpin macrophage heterogeneity within the pancreatic tumor microenvironment, and examine the contribution of macrophages at various stages of PDAC progression. We also provide a comprehensive update of macrophage-targeting therapies that are currently undergoing clinical evaluation, and discuss clinical challenges associated with these treatment modalities in human PDAC patients.

Identification of the Neurokinin-1 Receptor as Targetable Stratification Factor for Drug Repurposing in Pancreatic Cancer

The SP/NK1R-complex plays an important role in tumor proliferation. Targeting of the neurokinin-1 receptor in previous studies with its antagonist aprepitant (AP) resulted in anti-tumoral effects in colorectal cancer and hepatoblastoma. However, there is still a lack of knowledge regarding its effects on pancreatic cancer. Therefore, we treated human pancreatic ductal adenocarcinoma (PDAC) cell lines (Capan-1, DanG, HuP-T3, Panc-1, and MIA PaCa-2) and their cancer stem cell-like cells (CSCs) with AP and analyzed functional effects by MTT-, colony, and sphere formation assays, respectively; moreover, we monitored downstream mechanisms by flow cytometry. NK1R inhibition resulted in dose-dependent growth reduction in both CSCs and non-CSCs without induction of apoptosis in most PDAC cell lines. More importantly, we identified striking AP dependent cell cycle arrest in all parental cells. Furthermore, gene expression and the importance of key genes in PDAC tumorigenesis were analyzed combining RT-qPCR in eight PDAC cell lines with publicly available datasets (TCGA, GEO, CCLE). Surprisingly, we found a better overall survival in patients with high NK1R levels, while at the same time, NK1R was significantly decreased in PDAC tissue compared to normal tissue. Interestingly, there is currently no differentiation between the isoforms of NK1R (truncated and full; NK1R-tr and -fl) in any of the indicated public transcriptomic records, although many publications already emphasize on important regulatory differences between the two isoforms of NK1R in many cancer entities. In conclusion, analysis of splice variants might potentially lead to a stratification of PDAC patients for NK1R-directed therapies. Furthermore, we presume PDAC patients with high expressions of NK1R-tr might benefit from treatment with AP to improve chemoresistance. Therefore, analysis of splice variants might potentially lead to a stratification of PDAC patients for NK1R-directed therapies.

MicroRNA-sensitive oncolytic measles virus for chemovirotherapy of pancreatic cancer

Advanced pancreatic cancer is characterized by few treatment options and poor outcomes. Oncolytic virotherapy and chemotherapy involve complementary pharmacodynamics and could synergize to improve therapeutic efficacy. Likewise, multimodality treatment may cause additional toxicity, and new agents have to be safe. Balancing both aims, we generated an oncolytic measles virus for 5-fluorouracil-based chemovirotherapy of pancreatic cancer with enhanced tumor specificity through microRNA-regulated vector tropism. The resulting vector encodes a bacterial prodrug convertase, cytosine deaminase-uracil phosphoribosyl transferase, and carries synthetic miR-148a target sites in the viral F gene. Combination of the armed and targeted virus with 5-fluorocytosine, a prodrug of 5-fluorouracil, resulted in cytotoxicity toward both infected and bystander pancreatic cancer cells. In pancreatic cancer xenografts, a single intratumoral injection of the virus induced robust in vivo expression of prodrug convertase. Based on intratumoral transgene expression kinetics, we devised a chemovirotherapy regimen to assess treatment efficacy. Concerted multimodality treatment with intratumoral virus and systemic prodrug administration delayed tumor growth and prolonged survival of xenograft-bearing mice. Our results demonstrate that 5-fluorouracil-based chemovirotherapy with microRNA-sensitive measles virus is an effective strategy against pancreatic cancer at a favorable therapeutic index that warrants future clinical translation.

Delineating copy number and clonal substructure in human tumors from single-cell transcriptomes

Single-cell transcriptomic analysis is widely used to study human tumors. However, it remains challenging to distinguish normal cell types in the tumor microenvironment from malignant cells and to resolve clonal substructure within the tumor. To address these challenges, we developed an integrative Bayesian segmentation approach called copy number karyotyping of aneuploid tumors (CopyKAT) to estimate genomic copy number profiles at an average genomic resolution of 5 Mb from read depth in high-throughput single-cell RNA sequencing (scRNA-seq) data. We applied CopyKAT to analyze 46,501 single cells from 21 tumors, including triple-negative breast cancer, pancreatic ductal adenocarcinoma, anaplastic thyroid cancer, invasive ductal carcinoma and glioblastoma, to accurately (98%) distinguish cancer cells from normal cell types. In three breast tumors, CopyKAT resolved clonal subpopulations that differed in the expression of cancer genes, such as KRAS, and signatures, including epithelial-to-mesenchymal transition, DNA repair, apoptosis and hypoxia. These data show that CopyKAT can aid in the analysis of scRNA-seq data in a variety of solid human tumors.

Molecular and Metabolic Subtypes Correspondence for Pancreatic Ductal Adenocarcinoma Classification

Pancreatic ductal adenocarcinoma (PDAC), the most common form of pancreatic cancer, is an extremely lethal disease due to late diagnosis, aggressiveness and lack of effective therapies. Considering its intrinsic heterogeneity, patient stratification models based on transcriptomic and genomic signatures, with partially overlapping subgroups, have been established. Besides molecular alterations, PDAC tumours show a strong desmoplastic response, resulting in profound metabolic reprogramming involving increased glucose and amino acid consumption, as well as lipid scavenging and biosynthesis. Interestingly, recent works have also revealed the existence of metabolic subtypes with differential prognosis within PDAC, which correlated to defined molecular subclasses in patients: lipogenic subtype correlated with a classical/progenitor signature, while glycolytic tumours associated with the highly aggressive basal/squamous profile. Bioinformatic analyses have demonstrated that the representative genes of each metabolic subtype are up-regulated in PDAC samples and predict patient survival. This suggests a relationship between the genetic signature, metabolic profile, and aggressiveness of the tumour. Considering all this, defining metabolic subtypes represents a clear opportunity for patient stratification considering tumour functional behaviour independently of their mutational background.

Soluble Compounds Released by Hypoxic Stroma Confer Invasive Properties to Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is characterized by abundant stroma and a hypoxic microenvironment. Pancreatic stellate cells (PSC) are activated by hypoxia and promote excessive desmoplasia, further contributing to the development of hypoxia. We aimed to explore how hypoxia and stroma interact to contribute to invasive growth in PDAC. [¹⁸F]HX4 PET/CT was found to be a feasible non-invasive method to assess tumor hypoxia in 42 patients and correlated with HIF1α immunohistochemistry in matched surgical specimens. [¹⁸F]HX4 uptake and HIF1α were strong prognostic markers for overall survival. Co-culture and medium transfer experiments demonstrated that hypoxic PSCs and their supernatant induce upregulation of mesenchymal markers in tumor cells, and that hypoxia-induced stromal factors drive invasive growth in hypoxic PDACs. Through stepwise selection, stromal MMP10 was identified as the most likely candidate responsible for this. In conclusion, hypoxia-activated PSCs promote the invasiveness of PDAC through paracrine signaling. The identification of PSC-derived MMP10 may provide a lead to develop novel stroma-targeting therapies.

CCAAT/Enhancer-Binding Protein Delta (C/EBPδ): A Previously Unrecognized Tumor Suppressor that Limits the Oncogenic Potential of Pancreatic Ductal Adenocarcinoma Cells

Simple Summary

Here we show that a protein called C/EBPδ is present in healthy pancreas tissue but almost absent in pancreas tumors. Patients with less C/EBPδ in their tumors had the most metastases and the worst survival chances, showing that C/EBPδ has tumor-suppressive properties in pancreatic cancer. In this study, we reactivated C/EBPδ in pancreatic cancer cells in vitro and observed a reduction in cell proliferation in a 2-dimentional and 3-dimensional space. This implies that tumor cells grow slower when C/EBPδ is activated and they are likely also less capable to escape the primary tumor in order to form metastases. Conversely, when we deleted C/EBPδ in pancreatic cancer cells, we observed accelerated growth. We suggest that reactivating C/EBPδ can suppress tumor growth and formation of metastases, thereby improving patient survival.

Abstract

CCAAT/enhancer-binding protein δ (C/EBPδ) is a transcription factor involved in growth arrest and differentiation, which has consequently been suggested to harbor tumor suppressive activities. However, C/EBPδ over-expression correlates with poor prognosis in glioblastoma and promotes genomic instability in cervical cancer, hinting at an oncogenic role of C/EBPδ in these contexts. Here, we explore the role of C/EBPδ in pancreatic cancer. We determined C/EBPδ expression in biopsies from pancreatic cancer patients using public gene-expression datasets and in-house tissue microarrays. We found that C/EBPδ is highly expressed in healthy pancreatic ductal cells but lost in pancreatic ductal adenocarcinoma. Furthermore, loss of C/EBPδ correlated with increased lymph node involvement and shorter overall survival in pancreatic ductal adenocarcinoma patients. In accordance with this, in vitro experiments showed reduced clonogenic capacity and proliferation of pancreatic ductal adenocarcinoma cells following C/EBPδ re-expression, concurrent with decreased sphere formation capacity in soft agar assays. We thus report a previously unrecognized but important tumor suppressor role of C/EBPδ in pancreatic ductal adenocarcinoma. This is of particular interest since only few tumor suppressors have been identified in the context of pancreatic cancer. Moreover, our findings suggest that restoration of C/EBPδ activity could hold therapeutic value in pancreatic ductal adenocarcinoma, although the latter claim needs to be substantiated in future studies.

Microdissected pancreatic cancer proteomes reveal tumor heterogeneity and therapeutic targets

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a relative paucity of cancer cells that are surrounded by an abundance of nontumor cells and extracellular matrix, known as stroma. The interaction between stroma and cancer cells contributes to poor outcome, but how proteins from these individual compartments drive aggressive tumor behavior is not known. Here, we report the proteomic analysis of laser-capture microdissected (LCM) PDAC samples. We isolated stroma, tumor, and bulk samples from a cohort with long- and short-term survivors. Compartment-specific proteins were measured by mass spectrometry, yielding what we believe to be the largest PDAC proteome landscape to date. These analyses revealed that, in bulk analysis, tumor-derived proteins were typically masked and that LCM was required to reveal biology and prognostic markers. We validated tumor CALB2 and stromal COL11A1 expression as compartment-specific prognostic markers. We identified and functionally addressed the contributions of the tumor cell receptor EPHA2 to tumor cell viability and motility, underscoring the value of compartment-specific protein analysis in PDAC.

Basal-like and classical cells coexist in pancreatic cancer revealed by single-cell analysis on biopsy-derived pancreatic cancer organoids from the classical subtype

Pancreatic ductal adenocarcinoma (PDAC) is composed of stromal, immune, and cancerous epithelial cells. Transcriptomic analysis of the epithelial compartment allows classification into different phenotypic subtypes as classical and basal-like. However, little is known about the intra-tumor heterogeneity particularly in the epithelial compartment. Growing evidences suggest that this phenotypic segregation is not so precise and different cancerous cell types may coexist in a single tumor. To test this hypothesis, we performed single-cell transcriptomic analyses using combinational barcoding exclusively on epithelial cells from six different classical PDAC patients obtained by Endoscopic Ultrasound (EUS) with Fine Needle Aspiration (FNA). To purify the epithelial compartment, PDAC were grown as biopsy-derived pancreatic cancer organoids. Single-cell transcriptomic analysis allowed the identification of four main cell clusters present in different proportions in all tumors. Remarkably, although all these tumors were classified as classical, one cluster present in all corresponded to a basal-like phenotype. These results reveal an unanticipated high heterogeneity of pancreatic cancers and demonstrate that basal-like cells, which have a highly aggressive phenotype, are more widespread than expected.

High-grade mesenchymal pancreatic ductal adenocarcinoma drives stromal deactivation through CSF-1

Pancreatic ductal adenocarcinoma (PDAC) is characterized by an abundance of stroma. Multiple molecular classification efforts have identified a mesenchymal tumor subtype that is consistently characterized by high-grade growth and poor clinical outcome. The relation between PDAC stroma and tumor subtypes is still unclear. Here, we aimed to identify how PDAC cells instruct the main cellular component of stroma, the pancreatic stellate cells (PSCs). We found in primary tissue that high-grade PDAC had reduced collagen deposition compared to low-grade PDAC. Xenografts and organotypic co-cultures established from mesenchymal-like PDAC cells featured reduced collagen and activated PSC content. Medium transfer experiments using a large set of PDAC cell lines revealed that mesenchymal-like PDAC cells consistently downregulated ACTA2 and COL1A1 expression in PSCs and reduced proliferation. We identified colony-stimulating factor 1 as the mesenchymal PDAC-derived ligand that deactivates PSCs, and inhibition of its receptor CSF1R was able to counteract this effect. In conclusion, high-grade PDAC features stroma that is low in collagen and activated PSC content, and targeting CSF1R offers direct options to maintain a tumor-restricting microenvironment.