Pancreatic cancer subtypes: a roadmap for precision medicine

Pancreatic ductal adenocarcinoma: the latest on diagnosis, molecular profiling, and systemic treatments

Pancreatic ductal adenocarcinoma (PDAC) is currently the fourth leading cause of death in the United States and is expected to be ranked second in the next 10 years due to poor prognosis and a rising incidence. Distant metastatic PDAC is associated with the worst prognosis among the different phases of PDAC. The diagnostic options for PDAC are convenient and available for staging, tumor response evaluation, and management of resectable or borderline resectable PDAC. However, imaging is crucial in PDAC diagnosis, monitoring, resectability appraisal, and response evaluation. The advancement of medical technologies is evolving, hence the use of imaging in PDAC treatment options has grown as well as the utilization of ctDNA as a tumor marker. Treatment options for metastatic PDAC are minimal with the primary goal of therapy limited to symptom relief or palliation, especially in patients with low functional capacity at the point of diagnosis. Molecular profiling has shown promising potential solutions that would push the treatment boundaries for patients with PDAC. In this review, we will discuss the latest updates from evidence-based guidelines regarding diagnosis, therapy response evaluation, prognosis, and surveillance, as well as illustrating novel therapies that have been recently investigated for PDAC, in addition to discussing the molecular profiling advances in PDAC.

KRT17high/CXCL8+ Tumor Cells Display Both Classical and Basal Features and Regulate Myeloid Infiltration in the Pancreatic Cancer Microenvironment

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is generally divided in two subtypes, classical and basal. Recently, single-cell RNA sequencing has uncovered the coexistence of basal and classical cancer cells, as well as intermediary cancer cells, in individual tumors. The latter remains poorly understood; here, we sought to characterize them using a multimodal approach.

EXPERIMENTAL DESIGN

We performed subtyping on a single-cell RNA sequencing dataset containing 18 human PDAC samples to identify multiple intermediary subtypes. We generated patient-derived PDAC organoids for functional studies. We compared single-cell profiling of matched blood and tumor samples to measure changes in the local and systemic immune microenvironment. We then leveraged longitudinally patient-matched blood to follow individual patients over the course of chemotherapy.

RESULTS

We identified a cluster of KRT17-high intermediary cancer cells that uniquely express high levels of CXCL8 and other cytokines. The proportion of KRT17high/CXCL8+ cells in patient tumors correlated with intratumoral myeloid abundance, and, interestingly, high protumor peripheral blood granulocytes, implicating local and systemic roles. Patient-derived organoids maintained KRT17high/CXCL8+ cells and induced myeloid cell migration in a CXCL8-dependent manner. In our longitudinal studies, plasma CXCL8 decreased following chemotherapy in responsive patients, while CXCL8 persistence portended worse prognosis.

CONCLUSIONS

Through single-cell analysis of PDAC samples, we identified KRT17high/CXCL8+ cancer cells as an intermediary subtype, marked by a unique cytokine profile and capable of influencing myeloid cells in the tumor microenvironment and systemically. The abundance of this cell population should be considered for patient stratification in precision immunotherapy. See related commentary by Faraoni and McAllister, p. 2297.

Unlocking the Pancreatic Cancer Puzzle: Using Intermediate Cells to Target Treatment

KRT17-high intermediate cell population with elevated CXCL8 expression informed elevated myeloid infiltration status in tumors and associated with protumorigenic signatures in peripheral granulocytes from patients with pancreatic cancer. Furthermore, CXCL8 plasma levels were found to resemble KRT17+/CXCL8+ abundance in tumors, in which higher levels predicted worse patient outcomes. See related article by Carpenter et al., p. 2497.

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

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

Current Status and Future Directions: The Application of Artificial Intelligence/Machine Learning for Precision Medicine

Technological innovations, such as artificial intelligence (AI) and machine learning (ML), have the potential to expedite the goal of precision medicine, especially when combined with increased capacity for voluminous data from multiple sources and expanded therapeutic modalities; however, they also present several challenges. In this communication, we first discuss the goals of precision medicine, and contextualize the use of AI in precision medicine by showcasing innovative applications (e.g., prediction of tumor growth and overall survival, biomarker identification using biomedical images, and identification of patient population for clinical practice) which were presented during the February 2023 virtual public workshop entitled "Application of Artificial Intelligence and Machine Learning for Precision Medicine," hosted by the US Food and Drug Administration (FDA) and University of Maryland Center of Excellence in Regulatory Science and Innovation (M-CERSI). Next, we put forward challenges brought about by the multidisciplinary nature of AI, particularly highlighting the need for AI to be trustworthy. To address such challenges, we subsequently note practical approaches, viz., differential privacy, synthetic data generation, and federated learning. The proposed strategies - some of which are highlighted presentations from the workshop - are for the protection of personal information and intellectual property. In addition, methods such as the risk-based management approach and the need for an agile regulatory ecosystem are discussed. Finally, we lay out a call for action that includes sharing of data and algorithms, development of regulatory guidance documents, and pooling of expertise from a broad-spectrum of stakeholders to enhance the application of AI in precision medicine.

GraphPath: a graph attention model for molecular stratification with interpretability based on the pathway-pathway interaction network

MOTIVATION

Studying the molecular heterogeneity of cancer is essential for achieving personalized therapy. At the same time, understanding the biological processes that drive cancer development can lead to the identification of valuable therapeutic targets. Therefore, achieving accurate and interpretable clinical predictions requires paramount attention to thoroughly characterizing patients at both the molecular and biological pathway levels.

RESULTS

Here, we present GraphPath, a biological knowledge-driven graph neural network with multi-head self-attention mechanism that implements the pathway-pathway interaction network. We train GraphPath to classify the cancer status of patients with prostate cancer based on their multi-omics profiling. Experiment results show that our method outperforms P-NET and other baseline methods. Besides, two external cohorts are used to validate that the model can be generalized to unseen samples with adequate predictive performance. We reduce the dimensionality of latent pathway embeddings and visualize corresponding classes to further demonstrate the optimal performance of the model. Additionally, since GraphPath's predictions are interpretable, we identify target cancer-associated pathways that significantly contribute to the model's predictions. Such a robust and interpretable model has the potential to greatly enhance our understanding of cancer's biological mechanisms and accelerate the development of targeted therapies.

AVAILABILITY AND IMPLEMENTATION

https://github.com/amazingma/GraphPath.

Combining prognostic value of serum carbohydrate antigen 19-9 and tumor size reduction ratio in pancreatic ductal adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is a common cancer with increasing morbidity and mortality due to changes of social environment.

AIM

To evaluate the significance of serum carbohydrate antigen 19-9 (CA19-9) and tumor size changes pre- and post-neoadjuvant therapy (NAT).

METHODS

This retrospective study was conducted at the Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer Hospital. This study specifically assessed CA19-9 levels and tumor size before and after NAT.

RESULTS

A total of 156 patients who completed NAT and subsequently underwent tumor resection were included in this study. The average age was 65.4 ± 10.6 years and 72 (46.2%) patients were female. Before survival analysis, we defined the post-NAT serum CA19-9 level/pre-NAT serum CA19-9 level as the CA19-9 ratio (CR). The patients were divided into three groups: CR < 0.5, CR > 0.5 and < 1 and CR > 1. With regard to tumor size measured by both computed tomography and magnetic resonance imaging, we defined the post-NAT tumor size/pre-NAT tumor size as the tumor size ratio (TR). The patients were then divided into three groups: TR < 0.5, TR > 0.5 and < 1 and TR > 1. Based on these groups divided according to CR and TR, we performed both overall survival (OS) and disease-free survival (DFS) analyses. Log-rank tests showed that both OS and DFS were significantly different among the groups according to CR and TR (P < 0.05). CR and TR after NAT were associated with increased odds of achieving a complete or near-complete pathologic response. Moreover, CR (hazard ratio: 1.721, 95%CI: 1.373-3.762; P = 0.006), and TR (hazard ratio: 1.435, 95%CI: 1.275-4.363; P = 0.014) were identified as independent factors associated with OS.

CONCLUSION

This study demonstrated that post-NAT serum CA19-9 level/pre-NAT serum CA19-9 level and post-NAT tumor size/pre-NAT tumor size were independent factors associated with OS in patients with PDAC who received NAT and subsequent surgical resection.

Epigenetic therapeutic strategies in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal solid malignancies, characterized by its aggressiveness and metastatic potential, with a 5-year survival rate of only 8-11%. Despite significant improvements in PDAC treatment and management, therapeutic alternatives are still limited. One of the main reasons is its high degree of intra- and inter-individual tumor heterogeneity which is established and maintained through a complex network of transcription factors and epigenetic regulators. Epigenetic drugs, have shown promising preclinical results in PDAC and are currently being evaluated in clinical trials both for their ability to sensitize cancer cells to cytotoxic drugs and to counteract the immunosuppressive characteristic of PDAC tumor microenvironment. In this review, we discuss the current status of epigenetic treatment strategies to overcome molecular and cellular PDAC heterogeneity in order to improve response to therapy.

Involvement of CCCTC-binding factor in epigenetic regulation of cancer

A major global health burden continues to be borne by the complex and multifaceted disease of cancer. Epigenetic changes, which are essential for the emergence and spread of cancer, have drawn a huge amount of attention recently. The CCCTC-binding factor (CTCF), which takes part in a wide range of cellular processes including genomic imprinting, X chromosome inactivation, 3D chromatin architecture, local modifications of histone, and RNA polymerase II-mediated gene transcription, stands out among the diverse array of epigenetic regulators. CTCF not only functions as an architectural protein but also modulates DNA methylation and histone modifications. Epigenetic regulation of cancer has already been the focus of plenty of studies. Understanding the role of CTCF in the cancer epigenetic landscape may lead to the development of novel targeted therapeutic strategies for cancer. CTCF has already earned its status as a tumor suppressor gene by acting like a homeostatic regulator of genome integrity and function. Moreover, CTCF has a direct effect on many important transcriptional regulators that control the cell cycle, apoptosis, senescence, and differentiation. As we learn more about CTCF-mediated epigenetic modifications and transcriptional regulations, the possibility of utilizing CTCF as a diagnostic marker and therapeutic target for cancer will also increase. Thus, the current review intends to promote personalized and precision-based therapeutics for cancer patients by shedding light on the complex interplay between CTCF and epigenetic processes.

Introductory Chapter: Pancreatic Cancer – How to Prevent, Screen, and Detect?

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[Heterogeneity analysis of pancreatic cancer and identification of molecular subtypes of tumor cells based on CEACAM5, LGALS1 and CENPF gene expression]

OBJECTIVE

To explore the heterogeneity of pancreatic cancer and new methods for tumor cell molecular subtyping and identify the signature genes in pancreatic cancer progression.

METHODS

Based on the single-cell sequencing data of 16 pancreatic cancer tissues from the GSE155698 dataset, the single pancreatic cancer cells were classified according to EPCAM gene expression after preliminary clustering, re-clustering, and subgrouping to identify the signature genes, followed by pathway enrichment analysis and pseudo-time analysis. The key genes identified were validated using the clinical and tissue gene and protein expression data from 179 pancreatic cancer patients and 171 healthy controls. The impact of CEACAM5, LGALS1, and CENPF on proliferation, migration and invasion of pancreatic cancer cells were analyzed.

RESULTS

Analysis of 48 570 cells from 16 pancreatic cancer samples revealed a total of 22 clusters, including 5 clusters of pancreatic cancer cells, which were classified into Subtype 1, Subtype 2, and Subtype 3, each exhibiting distinct gene expression patterns and functions. The signature genes were enriched in negatively regulated protein metabolic processes, ferroptosis, and antigen processing and presentation-related pathways in Subtype 1 pancreatic cancer cells; in peptide synthesis processes, translation, and ribosome-related pathways in Subtype 2; and in ATP metabolic processes, glycolysis/gluconeogenesis, and cell cyclerelated pathways in Subtype 3. Subtypes 2 and 3 were potentially derived from Subtype 1, and Subtype 3 possibly represented the final developmental stage of pancreatic cancer cells. The key signature genes (CEACAM5, LGALS1, and CENPF) also exhibited different expression patterns in the developmental trajectory and showed high expressions in pancreatic cancer in association with poor prognoses. In pancreatic cancer cells, downregulation of CEACAM5, LGALS1, and CENPF significantly inhibited the proliferation, migration, and invasion abilities of the cells (P<0.05).

CONCLUSION

Pancreatic cancer cells exhibit significant heterogeneity, and CEACAM5, LGALS1, and CENPF gene expressions, which affect pancreatic cancer cell proliferation, invasion, and metastasis, can be used to identify distinct molecular subtypes during tumor cell development.

Exploiting the molecular subtypes and genetic landscape in pancreatic cancer: the quest to find effective drugs

Pancreatic Ductal Adenocarcinoma (PDAC) is a very lethal disease that typically presents at an advanced stage and is non-compliant with most treatments. Recent technologies have helped delineate associated molecular subtypes and genetic variations yielding important insights into the pathophysiology of this disease and having implications for the identification of new therapeutic targets. Drug repurposing has been evaluated as a new paradigm in oncology to accelerate the application of approved or failed target-specific molecules for the treatment of cancer patients. This review focuses on the impact of molecular subtypes on key genomic alterations in PDAC, and the progress made thus far. Importantly, these alterations are discussed in light of the potential role of drug repurposing in PDAC.

Pancreatic Cancer: Updates in Pathogenesis and Therapies

Despite the progress in pancreatic cancer (PC) chemo/radiotherapies, immunotherapies, and novel targeted therapies and the improvement in its peri-operative management policies, it still has a dismal catastrophic prognosis due to delayed detection, early neural and vascular invasions, early micro-metastatic spread, tumour heterogeneities, drug resistance either intrinsic or acquired, unique desmoplastic stroma, and tumour microenvironment (TME). Understanding tumour pathogenesis at the detailed genetic/epigenetic/metabolic/molecular levels as well as studying the tumour risk factors and its known precancerous lesions aggressively is required for getting a more successful therapy for this challenging tumour. For a better outcome of this catastrophic tumour, it should be diagnosed early and treated through multidisciplinary teams of surgeons, gastroenterologists/interventional upper endoscopists, medical/radiation oncologists, diagnostic/intervention radiologists, and pathologists at high-volume centres. Moreover, surgical resection with a negative margin (R0) is the only cure for it. In this chapter; we discuss the recently updated knowledge of PC pathogenesis, risk factors, and precancerous lesions as well as its different management tools (i.e. surgery, chemo/radiotherapies, immunotherapies, novel targeted therapies, local ablative therapies, etc.).

The Future of Precision Oncology

Our understanding of the molecular mechanisms underlying cancer development and evolution have evolved rapidly over recent years, and the variation from one patient to another is now widely recognized. Consequently, one-size-fits-all approaches to the treatment of cancer have been superseded by precision medicines that target specific disease characteristics, promising maximum clinical efficacy, minimal safety concerns, and reduced economic burden. While precision oncology has been very successful in the treatment of some tumors with specific characteristics, a large number of patients do not yet have access to precision medicines for their disease. The success of next-generation precision oncology depends on the discovery of new actionable disease characteristics, rapid, accurate, and comprehensive diagnosis of complex phenotypes within each patient, novel clinical trial designs with improved response rates, and worldwide access to novel targeted anticancer therapies for all patients. This review outlines some of the current technological trends, and highlights some of the complex multidisciplinary efforts that are underway to ensure that many more patients with cancer will be able to benefit from precision oncology in the near future.

Targeted transcriptomic analysis of pancreatic adenocarcinoma in EUS-FNA samples by NanoString technology

Background: Integration of transcriptomic testing into EUS-FNA samples is a growing need for precision oncology in pancreatic ductal adenocarcinoma (PDAC). The NanoString platform is suitable for transcriptome profiling in low yield RNA samples. Methods: Inclusion of patients that underwent EUS-FNA cytological diagnosis of pancreatic ductal adenocarcinoma using 19G and/or 22G needles and subsequent surgical resection. Formalin-fixed, paraffin-embedded (FFPE) cytological and surgical samples underwent RNA extraction and transcriptomic analysis using a custom 52-gene NanoString panel of stromal PDAC features. Cell type abundance was quantified in FFPE specimens and correlated. Results: 18 PDAC patients were included. Mean EUS-FNA passes was 2 + 0.7. All FFPE passed the RNA quality control for genomic analysis. Hierarchical clustering on the global gene expression data showed that genes were differentially expressed between EUS and surgical samples. A more enriched cancer-associated fibroblasts and epithelial-mesenchymal transition transcriptomic profile was observed across surgical specimens whereas immunological biomarkers were more represented in EUS-FNA samples. Cytological examination confirmed a scanty representation of CAF and more immunological cell abundance in cytological samples in comparison to surgical specimens. Conclusion: Targeted transcriptomic NanoString profiling of PDAC samples obtained by EUS-FNA is a feasible approach for pre-surgical molecular analysis although stromal CAF/EMT mRNA biomarkers are underrepresented.

Tumor heterogeneity: An oncogenic driver of PDAC progression and therapy resistance under stress conditions

Pancreatic ductal adenocarcinoma (PDAC) is a clinically challenging disease usually diagnosed at advanced or metastasized stage. By this year end, there are an expected increase in 62,210 new cases and 49,830 deaths in the United States, with 90% corresponding to PDAC subtype alone. Despite advances in cancer therapy, one of the major challenges combating PDAC remains tumor heterogeneity between PDAC patients and within the primary and metastatic lesions of the same patient. This review describes the PDAC subtypes based on the genomic, transcriptional, epigenetic, and metabolic signatures observed among patients and within individual tumors. Recent studies in tumor biology suggest PDAC heterogeneity as a major driver of disease progression under conditions of stress including hypoxia and nutrient deprivation, leading to metabolic reprogramming. We therefore advance our understanding in identifying the underlying mechanisms that interfere with the crosstalk between the extracellular matrix components and tumor cells that define the mechanics of tumor growth and metastasis. The bilateral interaction between the heterogeneous tumor microenvironment and PDAC cells serves as another important contributor that characterizes the tumor-promoting or tumor-suppressing phenotypes providing an opportunity for an effective treatment regime. Furthermore, we highlight the dynamic reciprocating interplay between the stromal and immune cells that impact immune surveillance or immune evasion response and contribute towards a complex process of tumorigenesis. In summary, the review encapsulates the existing knowledge of the currently applied treatments for PDAC with emphasis on tumor heterogeneity, manifesting at multiple levels, impacting disease progression and therapy resistance under stress.

Translating precision medicine for autism spectrum disorder: A pressing need

Autism spectrum disorder (ASD) is a heterogenous group of neurodevelopmental disorders (NDDs) with a high unmet medical need. Currently, ASD is diagnosed according to behavior-based criteria that overlook clinical and genomic heterogeneity, thus repeatedly resulting in failed clinical trials. Here, we summarize the scientific evidence pointing to the pressing need to create a precision medicine framework for ASD and other NDDs. We discuss the role of omics and systems biology to characterize more homogeneous disease subtypes with different underlying pathophysiological mechanisms and to determine corresponding tailored treatments. Finally, we provide recent initiatives towards tackling the complexity in NDDs for precision medicine and cost-effective drug discovery.

Targeted therapy for pancreatic ductal adenocarcinoma: Mechanisms and clinical study

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive and lethal malignancy with a high rate of recurrence and a dismal 5-year survival rate. Contributing to the poor prognosis of PDAC is the lack of early detection, a complex network of signaling pathways and molecular mechanisms, a dense and desmoplastic stroma, and an immunosuppressive tumor microenvironment. A recent shift toward a neoadjuvant approach to treating PDAC has been sparked by the numerous benefits neoadjuvant therapy (NAT) has to offer compared with upfront surgery. However, certain aspects of NAT against PDAC, including the optimal regimen, the use of radiotherapy, and the selection of patients that would benefit from NAT, have yet to be fully elucidated. This review describes the major signaling pathways and molecular mechanisms involved in PDAC initiation and progression in addition to the immunosuppressive tumor microenvironment of PDAC. We then review current guidelines, ongoing research, and future research directions on the use of NAT based on randomized clinical trials and other studies. Finally, the current use of and research regarding targeted therapy for PDAC are examined. This review bridges the molecular understanding of PDAC with its clinical significance, development of novel therapies, and shifting directions in treatment paradigm.

The EPH/Ephrin System in Pancreatic Ductal Adenocarcinoma (PDAC): From Pathogenesis to Treatment

Pancreatic ductal adenocarcinoma (PDAC) is a major concern for health care systems worldwide, since its mortality remains unaltered despite the surge in cutting-edge science. The EPH/ephrin signaling system was first investigated in the 1980s. EPH/ephrins have been shown to exert bidirectional signaling and cell-to-cell communication, influencing cellular morphology, adhesion, migration and invasion. Recent studies have highlighted the critical role of the EPH/ephrin system in various physiologic processes, including cellular proliferation, survival, synaptic plasticity and angiogenesis. Thus, it has become evident that the EPH/ephrin signaling system may have compelling effects on cell homeostasis that contribute to carcinogenesis. In particular, the EPH/ephrins have an impact on pancreatic morphogenesis and development, whereas several EPHs and ephrins are altered in PDAC. Several clinical and preclinical studies have attempted to elucidate the effects of the EPH/ephrin pathway, with multilayered effects on PDAC development. These studies have highlighted its highly promising role in the diagnosis, prognosis and therapeutic management of PDAC. The aim of this review is to explore the obscure aspects of the EPH/ephrin system concerning the development, physiology and homeostasis of the pancreas.

Genetics, Genomics and Emerging Molecular Therapies of Pancreatic Cancer

The number of cases of pancreatic cancers in 2019 in Poland was 3852 (approx. 2% of all cancers). The course of the disease is very fast, and the average survival time from the diagnosis is 6 months. Only <2% of patients live for 5 years from the diagnosis, 8% live for 2 years, and almost half live for only about 3 months. A family predisposition to pancreatic cancer occurs in about 10% of cases. Several oncogenes in which somatic changes lead to the development of tumours, including genes BRCA1/2 and PALB2, TP53, CDKN2A, SMAD4, MLL3, TGFBR2, ARID1A and SF3B1, are involved in pancreatic cancer. Between 4% and 10% of individuals with pancreatic cancer will have a mutation in one of these genes. Six percent of patients with pancreatic cancer have NTRK pathogenic fusion. The pathogenesis of pancreatic cancer can in many cases be characterised by homologous recombination deficiency (HRD)-cell inability to effectively repair DNA. It is estimated that from 24% to as many as 44% of pancreatic cancers show HRD. The most common cause of HRD are inactivating mutations in the genes regulating this DNA repair system, mainly BRCA1 and BRCA2, but also PALB2, RAD51C and several dozen others.

KRAS G12D targeted therapies for pancreatic cancer: Has the fortress been conquered?

KRAS mutations are among the most commonly occurring mutations in cancer. After being deemed undruggable for decades, KRAS G12C specific inhibitors showed that small molecule inhibitors can be developed against this notorious target. At the same time, there is still no agent that could target KRAS G12D which is the most common KRAS mutation and is found in the majority of KRAS-mutated pancreatic tumors. Nevertheless, significant progress is now being made in the G12D space with the development of several compounds that can bind to and inhibit KRAS G12D, most notably MRTX1133. Exciting advances in this field also include an immunotherapeutic approach that uses adoptive T-cell transfer to specifically target G12D in pancreatic cancer. In this mini-review, we discuss recent advances in KRAS G12D targeting and the potential for further clinical development of the various approaches.

Regulation of pancreatic cancer therapy resistance by chemokines

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy characterized by high resistance and poor response to chemotherapy. In addition, the poorly immunogenic pancreatic tumors constitute an immunosuppressive tumor microenvironment (TME) that render immunotherapy-based approaches ineffective. Understanding the mechanisms of therapy resistance, identifying new targets, and developing effective strategies to overcome resistance can significantly impact the management of PDAC patients. Chemokines are small soluble factors that are significantly deregulated during PDAC pathogenesis, contributing to tumor growth, metastasis, immune cell trafficking, and therapy resistance. Thus far, different chemokine pathways have been explored as therapeutic targets in PDAC, with some promising results in recent clinical trials. Particularly, immunotherapies such as immune check point blockade therapies and CAR-T cell therapies have shown promising results when combined with chemokine targeted therapies. Considering the emerging pathological and clinical significance of chemokines in PDAC, we reviewed major chemokine-regulated pathways leading to therapy resistance and the ongoing endeavors to target chemokine signaling in PDAC. This review discusses the role of chemokines in regulating therapy resistance in PDAC and highlights the continuing efforts to target chemokine-regulated pathways to improve the efficacy of various treatment modalities.

Diffuse Involvement of Pancreas is not Always Autoimmune Pancreatitis

RATIONALE AND OBJECTIVES

To determine the prevalence of diffuse involvement of pancreas and to identify the findings of malignancies using enhancement computed tomography (CT).

MATERIALS AND METHODS

A total of 1,0249 patients performed enhancement CT in our hospital over 62 months were investigated and the final study cohort includes 245 patients (170 males, 75 females; mean age, 56.94 ± 12.17 years). The reference standard is the final clinical/pathological diagnosis. The lesion-to-aorta enhancement ratio (LAR) on the pancreatic arterial phase, portal phase and delayed phase (DP) and the traditional CT findings were evaluated. Intergroup comparisons between malignancies and non-malignancies lesions were performed. Univariate and multivariate analyses were conducted to identify findings predicting malignancies.

RESULTS

The prevalence of malignancy was 45.3% (111/245) of diffuse enlargement of pancreas. All benign lesions were autoimmune pancreatitis 54.7% (n = 134). The most common malignant lesion was pancreatic ductal adenocarcinoma (n = 88, 35.9%). Other rare lesions with malignant potential included pancreatic neuroendocrine tumor (n = 11, 4.5%), lymphoma (n = 4, 1.6%), metastasis (n = 4, 1.6%), solid pseudopapillary neoplasm (n = 3, 1.2%) and acinar cell carcinoma (n = 1, 0.4%). Residual normal pancreas parenchyma, heterogeneity, short axis (cut-off value, 3.15 cm) and LARDP (cut-off value, 0.75) were independent predictors of malignancies. When the above predictors were combined, a sensitivity of 94.2%, a specificity of 90.8% were attained.

CONCLUSION

Diffuse involvement of the pancreas is rare and is not a specific sign of autoimmune pancreatitis, and it is associated with a wide spectrum of malignant conditions. Dynamic enhancement CT is helpful to identifying malignancies.

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.

Single Cell RNA Sequencing: A New Frontier in Pancreatic Ductal Adenocarcinoma

Simple Summary

Pancreatic cancer has a very low survival rate for several reasons. One of those is primarily due to the difficulty in diagnosing it at an early stage. For this reason, it is important to refine our understanding of this disease to guide the development of new diagnostic and therapeutic modalities to combat this fatal illness. Here we attempt to provide a review of current progress in utilizing single-cell RNA sequencing (scRNA-seq) techniques in the molecular profiling of pancreatic ductal adenocarcinoma.

Abstract

Pancreatic ductal adenocarcinoma is a malignancy with a high mortality rate. It exhibits significant heterogeneity in metabolic pathways which are associated with its progression. In this review, we discuss the role of single cell RNA sequencing in unraveling the metabolic and clinical features of these highly malignant tumors.

Role of the Tumor Microenvironment in Regulating Pancreatic Cancer Therapy Resistance

Pancreatic cancer has a notoriously poor prognosis, exhibits persistent drug resistance, and lacks a cure. Unique features of the pancreatic tumor microenvironment exacerbate tumorigenesis, metastasis, and therapy resistance. Recent studies emphasize the importance of exploiting cells in the tumor microenvironment to thwart cancers. In this review, we summarize the hallmarks of the multifaceted pancreatic tumor microenvironment, notably pancreatic stellate cells, tumor-associated fibroblasts, macrophages, and neutrophils, in the regulation of chemo-, radio-, immuno-, and targeted therapy resistance in pancreatic cancer. The molecular insight will facilitate the development of novel therapeutics against pancreatic cancer.

Ecoevolutionary biology of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC), the most common histological subtype of pancreatic cancer, is an aggressive disease predicted to be the 2nd cause of cancer mortality in the US by 2040. While first-line therapy has improved, 5-year overall survival has only increased from 5 to ∼10%, and surgical resection is only available for ∼20% of patients as most present with advanced disease, which is invariably lethal. PDAC has well-established highly recurrent mutations in four driver genes including KRAS, TP53, CDKN2A, and SMAD4. Unfortunately, these genetic drivers are not currently therapeutically actionable. Despite extensive sequencing efforts, few additional significantly recurrent and druggable drivers have been identified. In the absence of targetable mutations, chemotherapy remains the mainstay of treatment for most patients. Further, the role of the above driver mutations on PDAC initiation and early development is well-established. However, these mutations alone cannot account for PDAC heterogeneity nor discern early from advanced disease. Taken together, management of PDAC is an example highlighting the shortcomings of the current precision medicine paradigm. PDAC, like other malignancies, represents an ecoevolutionary process. Better understanding the disease through this lens can facilitate the development of novel therapeutic strategies to better control and cure PDAC. This review aims to integrate the current understanding of PDAC pathobiology into an ecoevolutionary framework.

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.

Pancreatic adenocarcinoma and pancreatic high-grade neuroendocrine carcinoma: two sides of the moon

Pancreatic adenocarcinoma is the seventh leading cause of cancer death in the world and the most common type pf pancreatic cancer. Unfortunately, less than 20% of patients are surgically resectable and the great majority of cases are treated with palliative chemotherapy with unsatisfactory results. No targeted agents or personalized approaches have been validated in the last decades. On the other side, neuroendocrine neoplasms of the pancreas are generally considered indolent tumours. However, high-grade neuroendocrine carcinoma is a rare subtype of neuroendocrine neoplasm of the pancreas (accounting up to 10% of the neuroendocrine neoplasms of the pancreas), with particularly aggressive behaviour and poor prognosis. Even in this case, the treatment is represented by palliative chemotherapy with dismal results and no personalized therapies are available, so far. Notably, the quality of life of these patients is disappointingly low and the future perspectives of more personalized diagnostic and therapeutic strategies are scarce. In this review, we discuss relevant and current information on epidemiology, pathology, diagnosis, clinical presentation, treatment and ongoing clinical trials of these two entities, in order to illustrate the two sides of the moon.

Occult polyclonality of preclinical pancreatic cancer models drives in vitro evolution

Heterogeneity is a hallmark of cancer. The advent of single-cell technologies has helped uncover heterogeneity in a high-throughput manner in different cancers across varied contexts. Here we apply single-cell sequencing technologies to reveal inherent heterogeneity in assumptively monoclonal pancreatic cancer (PDAC) cell lines and patient-derived organoids (PDOs). Our findings reveal a high degree of both genomic and transcriptomic polyclonality in monolayer PDAC cell lines, custodial variation induced by growing apparently identical cell lines in different laboratories, and transcriptomic shifts in transitioning from 2D to 3D spheroid growth models. Our findings also call into question the validity of widely available immortalized, non-transformed pancreatic lines as contemporaneous "control" lines in experiments. We confirm these findings using a variety of independent assays, including but not limited to whole exome sequencing, single-cell copy number variation sequencing (scCNVseq), single-nuclei assay for transposase-accessible chromatin with sequencing, fluorescence in-situ hybridization, and single-cell RNA sequencing (scRNAseq). We map scRNA expression data to unique genomic clones identified by orthogonally-gathered scCNVseq data of these same PDAC cell lines. Further, while PDOs are known to reflect the cognate in vivo biology of the parental tumor, we identify transcriptomic shifts during ex vivo passage that might hamper their predictive abilities over time. The impact of these findings on rigor and reproducibility of experimental data generated using established preclinical PDAC models between and across laboratories is uncertain, but a matter of concern.

Identification of Prognosis-Related Molecular Subgroups and Construction of a Prognostic Prediction Model Using Immune-Related Genes in Pancreatic Cancer

Background

Pancreatic cancer patients with similar clinicopathological status exhibit substantially different therapeutic responses, which might be caused by the vast molecular heterogeneity of tumors. In this study, we attempted to identify specific molecular subgroups and construct a prognostic prediction model based on the expression level of immune-related genes in pancreatic cancer. The transcriptome profiling, single nucleotide variation, copy number variation, clinicopathological information, and follow-up data of pancreatic cancer patients were obtained from The Cancer Genome Atlas database. Thereafter, the immune-related genes with prognostic significance were identified for further consensus cluster analysis. The molecular characteristics and clinicopathological information were compared between the identified subgroups, and a weighted correlation network analysis was performed to identify the hub genes associated with the subgroups. Finally, the prognostic prediction model based on immune-related genes was established using the least absolute shrinkage and selection operator (LASSO) analysis.

Results

A total of 67 immune-relevant genes with prognostic significance were selected and used for the consensus cluster analysis. The total samples were divided into two groups, C1 and C2. The subgroup C1 had a significantly worse prognosis than C2, as well as lower levels of immune cell infiltration, which indicate an immunosuppressed state. The mutational rate of the cancer-related genes including KRAS, TP53, and RNF43 was higher in the C1 subgroup. The C1 subgroup was associated with more advanced tumor grade and T stage and with higher mortality. Using LASSO regression, we developed a prognostic prediction model based on the expression levels of 19 immune-related genes, which we validated in three external data sets. In addition, we identified four potential therapeutic and prognostic biomarkers (TNNT1, KCNN4, SH2D3A, and PHLDA2).

Conclusion

We identified two novel molecular subgroups of pancreatic cancer and developed a prognostic prediction model based on the expression levels of immune-related genes, which could be used in a clinical setting and could aid in unraveling the molecular processes leading to the development of pancreatic cancer.

Aurora kinase a inhibitor MLN8237 suppresses pancreatic cancer growth

Pancreatic ductal adenocarcinoma (PDAC) is notorious for high mortality due to limited options of appropriate chemotherapy drugs. Here we report that Aurora kinase-A expression is elevated in both human and mouse PDAC samples. MLN8237, an inhibitor of Aurora kinase-A, efficiently reduced the proliferation and motility of PDAC cells in vitro as well as tumor growth in orthotropic xenograft model and genetic pancreatic cancer animal models (p53/LSL/Pdx-Cre mice) in vivo. MLN8237 exhibited tumor inhibitory effect through inhibiting proliferation and migration, and inducing apoptosis and senescence. These results provide the molecular basis for a novel chemotherapy strategy for PDAC patients.

The implication of liquid biopsies to predict chemoresistance in pancreatic cancer

Pancreatic cancer is one of the most aggressive diseases among solid tumors. Most patients are diagnosed with advanced or metastatic disease and are characterized by poor chemosensitivity. Therefore, earlier diagnosis and novel therapeutic possibilities for pancreatic cancer patients are urgently needed. Liquid biopsy is an emerging technology that allows the noninvasive sampling of tumor material. Nowadays, liquid biopsy has shown promising results as diagnostic, prognostic and predictive biomarkers, but it has not yet been universally adopted into regular use by clinicians. In this review, we describe different components of liquid biopsy, especially circulating tumor cells, circulating tumor DNA and exosomes and their potential clinical utility for pancreatic cancer patients.

The next wave of cellular immunotherapies in pancreatic cancer

Pancreatic cancer is an aggressive disease that is predicted to become the second leading cause of cancer-related death worldwide by 2030. The overall 5-year survival rate is around 10%. Pancreatic cancer typically presents late with locally advanced or metastatic disease, and there are limited effective treatments available. Cellular immunotherapy, such as chimeric antigen receptor (CAR) T cell therapy, has had significant success in treating hematological malignancies. However, CAR T cell therapy efficacy in pancreatic cancer has been limited. This review provides an overview of current and ongoing CAR T cell clinical studies of pancreatic cancer and the major challenges and strategies to improve CAR T cell efficacy. These strategies include arming CAR T cells; developing off-the-shelf allogeneic CAR T cells; using other immune CAR cells, like natural killer cells and tumor-infiltrating lymphocytes; and combination therapy. Careful incorporation of preclinical models will enhance management of affected individuals, assisting incorporation of cellular immunotherapies. A multifaceted, personalized approach involving cellular immunotherapy treatment is required to improve pancreatic cancer outcomes.

Subtypes in pancreatic ductal adenocarcinoma based on niche factor dependency show distinct drug treatment responses

Background

Pancreatic ductal adenocarcinoma (PDAC) is characterized by abundant stroma in which microenvironmental (niche) factors promote PDAC progression. In mouse models, reduction of the stroma increased the proportion of poorly differentiated PDAC with a worse prognosis. Here, we aimed to clarify the effects of stroma on PDAC that may define the PDAC phenotype and induce distinct therapeutic responses.

Methods

The molecular features of PDAC based on differentiation grade were clarified by genome and transcriptome analysis using PDAC organoids (PDOs). We identified the dependency on niche factors that might regulate the differentiation grade. A three-dimensional co-culture model with cancer-associated fibroblasts (CAFs) was generated to determine whether CAFs provide niche factors essential for differentiated PDAC. PDOs were subtyped based on niche factor dependency, and the therapeutic responses for each subtype were compared.

Results

The expression profiles of PDOs differed depending on the differentiation grade. Consistent with the distinct profiles, well differentiated types showed high niche dependency, while poorly differentiated types showed low niche dependency. The three-dimensional co-culture model revealed that well differentiated PDOs were strongly dependent on CAFs for growth, and moderately differentiated PDOs showed plasticity to change morphology depending on CAFs. Differentiated PDOs upregulated the expression of mevalonate pathway-related genes correlated with the niche dependency and were more sensitive to simvastatin than poorly differentiated PDOs.

Conclusions

Our findings suggest that CAFs maintain the differentiated PDAC phenotype through secreting niche factors and induce distinct drug responses. These results may lead to the development of novel subtype-based therapeutic strategies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-022-02301-9.

NOXA expression drives synthetic lethality to RUNX1 inhibition in pancreatic cancer

Recent evidence demonstrated the existence of molecular subtypes in pancreatic ductal adenocarcinoma (PDAC), which resist all current therapies. The paucity of therapeutic options, including a complete lack of targeted therapies, underscores the urgent and unmet medical need for the identification of targets and novel treatment strategies for PDAC. Our study unravels a function of the transcription factor RUNX1 in apoptosis regulation in PDAC. We show that pharmacological RUNX1 inhibition in PDAC is feasible and leads to NOXA-dependent apoptosis. The development of targeted therapies that influence the transcriptional landscape of PDAC might have great benefits for patients who are resistant to conventional therapies. RUNX1 inhibition as a new therapeutic intervention offers an attractive strategy for future therapies.

Evasion from drug-induced apoptosis is a crucial mechanism of cancer treatment resistance. The proapoptotic protein NOXA marks an aggressive pancreatic ductal adenocarcinoma (PDAC) subtype. To identify drugs that unleash the death-inducing potential of NOXA, we performed an unbiased drug screening experiment. In NOXA-deficient isogenic cellular models, we identified an inhibitor of the transcription factor heterodimer CBFβ/RUNX1. By genetic gain and loss of function experiments, we validated that the mode of action depends on RUNX1 and NOXA. Of note is that RUNX1 expression is significantly higher in PDACs compared to normal pancreas. We show that pharmacological RUNX1 inhibition significantly blocks tumor growth in vivo and in primary patient-derived PDAC organoids. Through genome-wide analysis, we detected that RUNX1-loss reshapes the epigenetic landscape, which gains H3K27ac enrichment at the NOXA promoter. Our study demonstrates a previously unknown mechanism of NOXA-dependent cell death, which can be triggered pharmaceutically. Therefore, our data show a way to target a therapy-resistant PDAC, an unmet clinical need.

3,5-Bis(trifluoromethyl)phenylsulfonamides, a novel pancreatic cancer active lead. Investigation of the terminal aromatic moiety

Virtual screening identified N-(6-((4-bromobenzyl)amino)hexyl)-3,5-bis(trifluoromethyl)benzenesulfonamide (1) a lead compound that bound to the S100A2-p53 binding groove. S100A2 is a Ca²⁺ binding protein with implications in cell signaling and is known to be upregulated in pancreatic cancer. It is a validated pancreatic cancer drug target. Lead 1, inhibited the growth of the MiaPaCa-2 pancreatic cancer cell line (GI₅₀ = 2.97 μM). Focused compound libraries were developed to explore the SAR of this compound class with 4 libraries and 43 compounds total. Focused library (Library 1) development identified lipophillic sulfonamides as preferred for MiaPaCa-2 activity, with -CF₃ and -C(CH₃)₃ substituents well tolerated (MiaPaCa-2 GI₅₀ < 6 μM). Contraction of the hexylamino spacer to ethyl (Library 2) and propyl (Library 3) proved beneficial to activity against a broad spectrum panel of cancer cell lines: HT29 (lung), MCF-7 (breast), A2780 (ovarian), H460 (colon), A431 (skin), Du145 (prostate), BE2-C (neuroblastoma), U87 and SJ-G2 (glioblastoma) (cohort-1); and a pancreatic cancer cell line panel: MiaPaCa-2, BxPC-3, AsPC-1, Capan-2, HPAC and PANC-1 (cohort-2). With a marked preference for a propyl linker the observed GI₅₀ values ranged from 1.4 - 18 μM against cohort-1 and 1.4-18 μM against cohort-2 cell lines. In Library 4 the terminal aromatic moiety was explored with 4-substituted analogues preferred (with activity of 48 (4-Cl) >47 (3-Cl) >46 (2-Cl)) against the cell lines examined. The introduction of bulky aromatic moieties was well tolerated, e.g. dihydrobenzo[b]^1,4dioxine (51) returned cohort-2 GI₅₀ values of 1.7 - 3.4 μM. In all instances the observed docked binding poses and binding scores were consistent with the observed cytotoxicity. This in turn supports, but does not prove, that these analogues function via S100A2-p53 binding groove inhibition.

Pancreatic Cancer Organoids in the Field of Precision Medicine: A Review of Literature and Experience on Drug Sensitivity Testing with Multiple Readouts and Synergy Scoring

Simple Summary

New treatments are urgently needed for pancreatic ductal adenocarcinoma because it is one of the most aggressive and lethal cancers, detected too late and resistant to conventional chemotherapy. Tumors in most patients feature a similar set of core mutations but so far it has not been possible to design a one-fits-all treatment strategy. Instead, efforts are underway to personalize the therapies. To find the treatments that might work the best for each patient, entirely new experimental platforms based on living miniature tumors, organoids, have been developed. We review here the latest international findings in designing personalized treatments pancreatic cancer patients using organoids as testing beds. Our own work adds important clues about how such testing could, and perhaps should, be conducted.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is a silent killer, often diagnosed late. However, it is also dishearteningly resistant to nearly all forms of treatment. New therapies are urgently needed, and with the advent of organoid culture for pancreatic cancer, an increasing number of innovative approaches are being tested. Organoids can be derived within a short enough time window to allow testing of several anticancer agents, which opens up the possibility for functional precision medicine for pancreatic cancer. At the same time, organoid model systems are being refined to better mimic the cancer, for example, by incorporation of components of the tumor microenvironment. We review some of the latest developments in pancreatic cancer organoid research and in novel treatment design. We also summarize our own current experiences with pancreatic cancer organoid drug sensitivity and resistance testing (DSRT) in 14 organoids from 11 PDAC patients. Our data show that it may be necessary to include a cell death read-out in ex vivo DSRT assays, as metabolic viability quantitation does not capture actual organoid killing. We also successfully adapted the organoid platform for drug combination synergy discovery. Lastly, live organoid culture 3D confocal microscopy can help identify individual surviving tumor cells escaping cell death even during harsh combination treatments. Taken together, the organoid technology allows the development of novel precision medicine approaches for PDAC, which paves the way for clinical trials and much needed new treatment options for pancreatic cancer patients.

Understanding pancreatic cancer stem cells and their role in carcinogenesis: a narrative review

OBJECTIVE

The purpose of this review article is to describe the pathogenesis of pancreatic cancer and to better understand the role of abnormal stem cells in the development of pancreatic cancer.

BACKGROUND

Pancreatic cancer is a highly fatal disease that is caused by the uncontrolled proliferation of pancreatic exocrine or neuroendocrine glands. It is believed that pancreatic cancers arise from a small population of abnormal cancer stem cells (CSCs) that promote tumorigenesis, tumor metastasis and therapeutic resistance. The molecular markers CD133, CXCR4, DCLK1, c-MET, ABCG2 and Lgr5 are routinely used to detected and observe the behaviours of pancreatic cancer stem cells (PCSCs).

METHODS

A comprehensive search was performed on PubMed, Google Scholar, Scopus, Clinicaltrials.gov and Web of Science using related keywords. Articles focusing on PCSCs and pancreatic cancer pathogenesis, biochemistry and clinical trials were selected.

CONCLUSIONS

Although very little is known about the exact cause of pancreatic cancer, PCSCs seem to play an important role in carcinogenesis. Mutated biochemical cascades include Sonic Hedgehog, K-RAS-JNK, DLL4/Notch and Nodal/Activin. Several clinical trials are trying to determine if the transplantation of hematopoietic stem cell or peripheral stem cells could be useful for the treatment of such an aggressive tumor.

Pancreatic stromal Gremlin 1 expression during pancreatic tumorigenesis

Chronic pancreatitis (CP) is a major risk factor of pancreatic ductal adenocarcinoma (PDAC). How CP promotes pancreatic oncogenesis remains unclear. A characteristic feature of PDAC is its prominent desmoplasia in the tumor microenvironment, composed of activated fibroblasts and macrophages. Macrophages can be characterized as M1 or M2, with tumor-inhibiting or -promoting functions, respectively. We reported that Gremlin 1 (GREM1), a key pro-fibrogenic factor, is upregulated in the stroma of CP. The current study aimed to investigate the expression of GREM1 and correlation between GREM1 and macrophages within the pancreas during chronic inflammation and the development of PDAC. By mRNA in situ hybridization, we detected GREM1 mRNA expression within α-smooth muscle actin (SMA)-positive fibroblasts of the pancreatic stroma. These designated FibroblastsGrem1+ marginally increased from CP to pancreatic intraepithelial neoplasia (PanIN) and PDAC. Within PDAC, FibroblastsGrem1+ increased with higher pathological tumor stages and in a majority of PDAC subtypes screened. Additionally, FibroblastsGrem1+ positively correlated with total macrophages (MacCD68+) and M2 macrophages (M2CD163+) in PDAC. To begin exploring potential molecular links between FibroblastsGrem1+ and macrophages in PDAC, we examined the expression of macrophage migration inhibitory factor (MIF), an endogenous counteracting molecule of GREM1 and an M1 macrophage promoting factor. By IHC staining of MIF, we found MIF to be expressed by tumor cells, positively correlated with GREM1; by IHC co-staining, we found MIF to be negatively correlated with M2CD163+ expression. Our findings suggest that GREM1 expression by activated fibroblasts may promote PDAC development, and GREM1/MIF may play an important role in macrophage phenotype.

Hippo Pathway in Regulating Drug Resistance of Glioblastoma

Glioblastoma (GBM) represents the most common and malignant tumor of the Central Nervous System (CNS), affecting both children and adults. GBM is one of the deadliest tumor types and it shows a strong multidrug resistance (MDR) and an immunosuppressive microenvironment which remain a great challenge to therapy. Due to the high recurrence of GBM after treatment, the understanding of the chemoresistance phenomenon and how to stimulate the antitumor immune response in this pathology is crucial. The deregulation of the Hippo pathway is involved in tumor genesis, chemoresistance and immunosuppressive nature of GBM. This pathway is an evolutionarily conserved signaling pathway with a kinase cascade core, which controls the translocation of YAP (Yes-Associated Protein)/TAZ (Transcriptional Co-activator with PDZ-binding Motif) into the nucleus, leading to regulation of organ size and growth. With this review, we want to highlight how chemoresistance and tumor immunosuppression work in GBM and how the Hippo pathway has a key role in them. We linger on the role of the Hippo pathway evaluating the effect of its de-regulation among different human cancers. Moreover, we consider how different pathways are cross-linked with the Hippo signaling in GBM genesis and the hypothetical mechanisms responsible for the Hippo pathway activation in GBM. Furthermore, we describe various drugs targeting the Hippo pathway. In conclusion, all the evidence described largely support a strong involvement of the Hippo pathway in gliomas progression, in the activation of chemoresistance mechanisms and in the development of an immunosuppressive microenvironment. Therefore, this pathway is a promising target for the treatment of high grade gliomas and in particular of GBM.

Identification of Hypoxia-Related Molecular Classification and Associated Gene Signature in Oral Squamous Cell Carcinoma

The high heterogeneity of oral squamous cell carcinoma (OSCC) is the main obstacle for individualized treatment. Recognizing the characteristics of different subtypes and investigating the promising strategies for each subclass are of great significance in precise treatment. In this study, we systematically evaluated hypoxia-mediated patterns together with immune characteristics of 309 OSCC patients in the TCGA training set and 97 patients in the GSE41613 testing set. We further identified two different hypoxia subtypes with distinct immune microenvironment traits and provided treatment programs for the two subclasses. In order to assess hypoxia level individually, we finally constructed a hypoxia-related risk score, which could predict the clinical outcome and immunotherapy response of OSCC patients. In summary, the recognition of different hypoxia patterns and the establishment of hypoxia-related risk score might enhance our understanding of the tumor microenvironment of OSCC and provide more personalized treatment strategies in the future.

A personalized approach to pancreatic ductal adenocarcinoma and its application in surgical practice

Pancreatic duct adenocarcinoma is an aggressive tumor which constitutes the fourth leading cause of cancer-related mortality in the USA. Despite the fact that surgery is an integral part of treatment, 5-year survival rates remain unfavorable, partly because of the complex genetic background, delayed diagnosis and also the absence of effective therapeutic approaches. To optimize surgery's results in recent years, the use of patients' genetic profile has been implemented through classification into subtypes; subtypes based on mutations which could efficiently lead oncologists to the path of targeted novel neoadjuvant regimens. This approach aims to achieve the most effective selection of patients undergoing surgery, to increase the number of potentially resectable tumors and also control micro-metastases, aiming to extend overall survival.

Down-regulation of metabolic pathways could offset the poor prognosis conferred by co-existent diabetes mellitus in pancreatic (head) adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) patients with diabetes mellitus (DM) have poor overall survival. Underlying mechanisms have not been fully clarified. This presents an opportunity for precision-oncology for which we systematically analysed publicly-available PDAC transcriptome data.

METHODS

PDAC TCGA RNASeq data were used. Analyses were restricted to only 'high purity' and 'head' as anatomical site. Patients were characterised by: (1) Gene expression classification, and (2) Weighted gene correlation network analysis (WGCNA) to identify co-expression patterns of genes. Newly identified gene signature subclasses of pancreatic head PDAC were associated with clinical and functional characteristics of patients.

RESULTS

Consensus clustering identified two patient subclasses within PDAC involving pancreatic head. WGCNA identified 11 distinct networks of gene expression patterns across two sub-classes. Class 1 patients demonstrated a significant upregulation of Module 5 and Module 6 gene expression compared to Class 2. Class 1 predominantly expressed the acinar, ductal and islet cell gene signatures. There were significantly less patients with DM in Class 1 subclass compared to Class 2 (p < 0.037). Patients with DM had significant downregulation of pathways involved in cellular metabolism, hormone secretion and paucity of islet cell markers with no reduced survival compared with non-diabetics.

CONCLUSIONS

A significant proportion of patients with PDAC of pancreatic head and DM exhibit downregulation of pathways involved in cellular metabolism, hormone secretion and signalling accompanied by a paucity of islet expression. Investigating the relationship between DM and gene expression profiles in patients with PDAC presents opportunities to improve overall survival in diabetics with PDAC.

Peripheral Blood Lymphocyte Percentage May Predict Chemotolerance and Survival in Patients with Advanced Pancreatic Cancer. Association between Adaptive Immunity and Nutritional State

Pancreatic Carcinoma (PC) cells have the ability to induce patient immunosuppression and to escape immunosurveillance. Low circulating lymphocytes are associated with an advanced stage of PC and reduced survival. Blood lymphocytes expressed as a percentage of Total White Blood Cells (L% TWBC) could predict chemotolerance (n° of tolerated cycles), survival time and Body Weight (BW) more effectively than lymphocytes expressed as an absolute value (LAB > 1500 n°/mm3) or lymphocytes >22%, which is the lowest limit of normal values in our laboratory. Forty-one patients with advanced PC, treated with chemotherapy, were selected for this observational retrospective study. Patients were evaluated at baseline (pre-chemotherapy), and at 6, 12 and 18 months, respectively, after diagnosis of PC. The study found L ≥ 29.7% to be a better predictor of survival (COX model, using age, sex, BW, serum creatinine, bilirubin and lymphocytes as covariates), chemotolerance (r = +0.50, p = 0.001) and BW (r = +0.35, p = 0.027) than LAB > 1500 or L > 22%. BW did not significantly correlate with chemotolerance or survival. The preliminary results of this study suggest that L ≥ 29.7% is more effective than LAB > 1500 or L > 22% at predicting chemotolerance, survival time and nutritional status. A possible impact of nutritional status on chemotherapy and survival seems to be lymphocyte-mediated given the association between BW and L%. This study may serve as the basis for future research to explore whether nutritional interventions can improve lymphopenia, and if so, how this may be possible.

Molecular Subtypes of Oral Squamous Cell Carcinoma Based on Immunosuppression Genes Using a Deep Learning Approach

Background: The mechanisms through which immunosuppressed patients bear increased risk and worse survival in oral squamous cell carcinoma (OSCC) are unclear. Here, we used deep learning to investigate the genetic mechanisms underlying immunosuppression in the survival of OSCC patients, especially from the aspect of various survival-related subtypes. Materials and methods: OSCC samples data were obtained from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and OSCC-related genetic datasets with survival data in the National Center for Biotechnology Information (NCBI). Immunosuppression genes (ISGs) were obtained from the HisgAtlas and DisGeNET databases. Survival analyses were performed to identify the ISGs with significant prognostic values in OSCC. A deep learning (DL)-based model was established for robustly differentiating the survival subpopulations of OSCC samples. In order to understand the characteristics of the different survival-risk subtypes of OSCC samples, differential expression analysis and functional enrichment analysis were performed. Results: A total of 317 OSCC samples were divided into one inferring cohort (TCGA) and four confirmation cohorts (ICGC set, GSE41613, GSE42743, and GSE75538). Eleven ISGs (i.e., BGLAP, CALCA, CTLA4, CXCL8, FGFR3, HPRT1, IL22, ORMDL3, TLR3, SPHK1, and INHBB) showed prognostic value in OSCC. The DL-based model provided two optimal subgroups of TCGA-OSCC samples with significant differences (p = 4.91E-22) and good model fitness [concordance index (C-index) = 0.77]. The DL model was validated by using four external confirmation cohorts: ICGC cohort (n = 40, C-index = 0.39), GSE41613 dataset (n = 97, C-index = 0.86), GSE42743 dataset (n = 71, C-index = 0.87), and GSE75538 dataset (n = 14, C-index = 0.48). Importantly, subtype Sub1 demonstrated a lower probability of survival and thus a more aggressive nature compared with subtype Sub2. ISGs in subtype Sub1 were enriched in the tumor-infiltrating immune cells-related pathways and cancer progression-related pathways, while those in subtype Sub2 were enriched in the metabolism-related pathways. Conclusion: The two survival subtypes of OSCC identified by deep learning can benefit clinical practitioners to divide immunocompromised patients with oral cancer into two subpopulations and give them target drugs and thus might be helpful for improving the survival of these patients and providing novel therapeutic strategies in the precision medicine area.

Biomarkers for early detection of pancreatic cancer - miRNAs as a potential diagnostic and therapeutic tool?

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignancies, with poor prognosis resulting mostly from late diagnosis. Surgery remains the most effective treatment and early detection significantly increases the overall survival. Biomarkers used for diagnosis and to monitor the response to treatment, such as carbohydrate antigen 19-9 (CA19-9) and carcinoembryonic antigen (CEA), are not adequate as early detection markers of PDAC, partly due to low sensitivity/specificity. Therefore, new biomarkers for PDAC are critically needed. This review aims at recent advancements in the identification and characterization of new biomarkers, microRNAs, which might prove useful in the early detection of PDAC.

Role of stromal activin A in human pancreatic cancer and metastasis in mice

Pancreatic ductal adenocarcinoma (PDAC) has extensive stromal involvement and remains one of the cancers with the highest mortality rates. Activin A has been implicated in colon cancer and its stroma but its role in the stroma of PDAC has not been elucidated. Activin A expression in cancer and stroma was assessed in human PDAC tissue microarrays (TMA). Activin A expression in human TMA is significantly higher in cancer samples, with expression in stroma correlated with shorter survival. Cultured pancreatic stellate cells (PSC) were found to secrete high levels of activin A resulting in PDAC cell migration that is abolished by anti-activin A neutralizing antibody. KPC mice treated with anti-activin A neutralizing antibody were evaluated for tumors, lesions and metastases quantified by immunohistochemistry. KPC mice with increased tumor burden express high plasma activin A. Treating KPC mice with an activin A neutralizing antibody does not reduce primary tumor size but decreases tumor metastases. From these data we conclude that PDAC patients with high activin A expression in stroma have a worse prognosis. PSCs secrete activin A, promoting increased PDAC migration. Inhibition of activin A in mice decreased metastases. Hence, stroma-rich PDAC patients might benefit from activin A inhibition.

The Latest Advancement in Pancreatic Ductal Adenocarcinoma Therapy: A Review Article for the Latest Guidelines and Novel Therapies

Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer deaths in the US, and it is expected to be the second leading cause of cancer deaths by 2030. The lack of effective early screening tests and alarming symptoms with early undetectable micro-metastasis at the time of presentation play a vital role in the high death rate from pancreatic cancer. In addition to this, the low mutation burden in pancreatic cancer, low immunological profile, dense tumorigenesis stroma, and decreased tumor sensitivity to cytotoxic drugs contribute to the low survival rates in PDAC patients. Despite breakthroughs in chemotherapeutic and immunotherapeutic drugs, pancreatic cancer remains one of the solid tumors that exhibit meager curative rates. Therefore, researchers must dedicate more effort to understanding the pathology and immunological behavior of PDAC, in addition to properly utilizing more advanced screening modalities and new therapeutic agents. In our review, we focus mainly on the latest updates from clinical guidelines and novel therapies that have been recently investigated or are under investigation for PDAC. We used PubMed as a search tool for finding original research articles addressing the latest developments in diagnosing and treating PDAC. Additionally, we also used the clinical trials published on clinicaltrialsgov as sources for our data.