Novel targets identified by integrated cancer-stromal interactome analysis of pancreatic adenocarcinoma

Spatial transcriptomics reveals prognosis-associated cellular heterogeneity in the papillary thyroid carcinoma microenvironment

BACKGROUND

Papillary thyroid carcinoma (PTC) is the most common malignant endocrine tumour, and its incidence and prevalence are increasing considerably. Cellular heterogeneity in the tumour microenvironment is important for PTC prognosis. Spatial transcriptomics is a powerful technique for cellular heterogeneity study.

METHODS

In conjunction with a clinical pathologist identification method, spatial transcriptomics was employed to characterise the spatial location and RNA profiles of PTC-associated cells within the tissue sections. The spatial RNA-clinical signature genes for each cell type were extracted and applied to outlining the distribution regions of specific cells on the entire section. The cellular heterogeneity of each cell type was further revealed by ContourPlot analysis, monocle analysis, trajectory analysis, ligand-receptor analysis and Gene Ontology enrichment analysis.

RESULTS

The spatial distribution region of tumour cells, typical and atypical follicular cells (FCs and AFCs) and immune cells were accurately and comprehensively identified in all five PTC tissue sections. AFCs were identified as a transitional state between FCs and tumour cells, exhibiting a higher resemblance to the latter. Three tumour foci were shared among all patients out of the 13 observed. Notably, tumour foci No. 2 displayed elevated expression levels of genes associated with lower relapse-free survival in PTC patients. We discovered key ligand-receptor interactions, including LAMB3-ITGA2, FN1-ITGA3 and FN1-SDC4, involved in the transition of PTC cells from FCs to AFCs and eventually to tumour cells. High expression of these patterns correlated with reduced relapse-free survival. In the tumour immune microenvironment, reduced interaction between myeloid-derived TGFB1 and TGFBR1 in tumour focus No. 2 contributed to tumourigenesis and increased heterogeneity. The spatial RNA-clinical analysis method developed here revealed prognosis-associated cellular heterogeneity in the PTC microenvironment.

CONCLUSIONS

The occurrence of tumour foci No. 2 and three enhanced ligand-receptor interactions in the AFC area/tumour foci reduced the relapse-free survival of PTC patients, potentially leading to improved prognostic strategies and targeted therapies for PTC patients.

A study on the role of Taxifolin in inducing apoptosis of pancreatic cancer cells: screening results using weighted gene co-expression network analysis

Pancreatic adenocarcinoma (PAAD) is a frequent malignant tumor in the pancreas. The incomplete understanding of cancer etiology and pathogenesis, as well as the limitations in early detection and diagnostic methods, have created an urgent need for the discovery of new therapeutic targets and drugs to control this disease. As a result, the current therapeutic options are limited. In this study, the weighted gene co-expression network analysis (WGCNA) method was employed to identify key genes associated with the progression and prognosis of pancreatic adenocarcinoma (PAAD) patients in the Gene Expression Profiling Interactive Analysis (GEPIA) database. To identify small molecule drugs with potential in the treatment of pancreatic adenocarcinoma (PAAD), we compared key genes to the reference dataset in the CMAP database. First, we analyzed the antitumor properties of small molecule drugs using cell counting kit-8 (CCK-8), AO/EB and Transwell assays. Subsequently, we integrated network pharmacology with molecular docking to explore the potential mechanisms of the identified molecules' anti-tumor effects. Our findings indicated that the progression and prognosis of PAAD patients in pancreatic cancer were associated with 11 genes, namely, DKK1, S100A2, CDA, KRT6A, ITGA3, GPR87, IL20RB, ZBED2, PMEPA1, CST6, and MUC16. These genes were filtered based on their therapeutic potential through comparing them with the reference dataset in the CMAP database. Taxifolin, a natural small molecule drug with the potential for treating PAAD, was screened by comparing it with the reference dataset in the CMAP database. Cell-based experiments have validated the potential of Taxifolin to facilitate apoptosis in pancreatic cancer cells while restraining their invasion and metastasis. This outcome is believed to be achieved via the HIF-1 signaling pathway. In conclusion, this study provided a theoretical basis for screening genes related to the progression of pancreatic cancer and discovered potentially active small molecule drugs. The experimental results confirm that Taxifolin has the ability to promote apoptosis in pancreatic cancer cells.

Single cell transcriptomic analyses implicate an immunosuppressive tumor microenvironment in pancreatic cancer liver metastasis

Pancreatic ductal adenocarcinoma (PDAC) is a highly metastatic disease refractory to all targeted and immune therapies. However, our understanding of PDAC microenvironment especially the metastatic microenvironment is very limited partly due to the inaccessibility to metastatic tumor tissues. Here, we present the single-cell transcriptomic landscape of synchronously resected PDAC primary tumors and matched liver metastases. We perform comparative analysis on both cellular composition and functional phenotype between primary and metastatic tumors. Tumor cells exhibit distinct transcriptomic profile in liver metastasis with clearly defined evolutionary routes from cancer cells in primary tumor. We also identify specific subtypes of stromal and immune cells critical to the formation of the pro-tumor microenvironment in metastatic lesions, including RGS5+ cancer-associated fibroblasts, CCL18+ lipid-associated macrophages, S100A8+ neutrophils and FOXP3+ regulatory T cells. Cellular interactome analysis further reveals that the lack of tumor-immune cell interaction in metastatic tissues contributes to the formation of the immunosuppressive microenvironment. Our study provides a comprehensive characterization of the transcriptional landscape of PDAC liver metastasis.

PDAC, the Influencer Cancer: Cross-Talk with Tumor Microenvironment and Connected Potential Therapy Strategies

Pancreatic ductal adenocarcinoma (PDAC) is among the leading causes of death by cancer in the world. What makes this pathological condition particularly lethal is a combination of clinical and molecular heterogeneity, lack of early diagnostic indexes, and underwhelming results from current therapeutic protocols. A major cause of PDAC chemoresistance seems to lie in the ability of cancer cells to spread out and fill the pancreatic parenchyma, exchanging nutrients, substrates, and even genetic material with cells from the surrounding tumor microenvironment (TME). Several components can be found in the TME ultrastructure, including collagen fibers, cancer-associated fibroblasts, macrophages, neutrophils, mast cells, and lymphocytes. Cross-talk between PDAC and TME cells results in the latter being converted into cancer-favoring phenotypes; this behavior could be compared to an influencer guiding followers into supporting his activity. Moreover, TME could be a potential target for some of the newest therapeutic strategies; these include the use of pegvorhyaluronidase-α and CAR-T lymphocytes against HER2, FAP, CEA, MLSN, PSCA, and CD133. Other experimental therapy options are being currently studied, aiming to interfere with the KRAS pathway, DNA-repairing proteins, and apoptosis resistance in PDAC cells. Hopefully these new approaches will grant better clinical outcomes in future patients.

New thoughts and findings on invasion and metastasis of pancreatic ductal adenocarcinoma (PDAC) from comparative proteomics: multi-target therapy

As one of the most aggressive malignant tumors, pancreatic ductal adenocarcinoma (PDAC) ranks as the fourth cancer-related mortality in the world. The extremely low survival rate is closely related to early invasion and distant metastasis. However, effective target therapy for weakening its malignant behavior remains limited. Over the past decades, many proteins correlating with invasion and metastasis of PDAC have been discovered using proteomics. The discovery of these proteins gives us a deeper understanding of the invasive and migratory processes of PDAC. This review is a systemic integration of these proteomics findings over the past 10 years. The discovered proteins were typically associated with the glycolytic process, hypoxic microenvironment, post-translational modification, extracellular matrix, exosomes, cancer stem cells, and immune escape. Some proteins were found to have multiple functions, and, cooperation between different proteins in the invasive and metastatic processes was found. This cooperation, and not just single protein function, may play a more significant role in the poor prognosis of PDAC. Therefore, multi-target therapy against these cooperative networks should be a primary choice in the future.

Integrated bioinformatics analysis shows integrin alpha 3 is a prognostic biomarker for pancreatic cancer

Integrin subunit alpha 3 (ITGA3) expression correlates with the development and prognosis of human cancers. This study aimed to investigate the association of ITGA3 expression with pancreatic cancer (PCa) prognosis. The ITGA3 gene expression data were extracted from The Cancer Genome Atlas (TCGA) pancreatic adenocarcinoma (PAAD) cohort and 14 Gene Expression Omnibus microarray datasets. The differences in ITGA3 expression levels between tumor and non-tumor tissues were compared using the Mann-Whitney U test. Cox regression analysis and meta-analysis were performed to detect the association of ITGA3 expression with PCa prognosis. ITGA3 expression was higher in tumors than in controls. Tumors with advanced grades (3/4) had higher ITGA3 levels compared with early-grade tumors (1/2). The meta-analysis of the TCGA PAAD cohort and seven microarray datasets (GSE28735, GSE62452, GSE79668, GSE71729, GSE57495, GSE78229, and GSE21501) showed that ITGA3 was a prognostic biomarker in PCa (hazard ratio (HR) = 1.38, 95% confidence interval (CI) 1.26-1.51, p < 0.00001). Five ITGA3-related genes, including ITGB1 (HR = 1.6), ITGB5 (HR = 1.6), ITGB6 (HR = 1.6), LAMA3 (HR = 2.1), and CD9 (HR = 2.3), correlated with PCa prognosis significantly (p < 0.05). Functional enrichment analysis showed that ITGA3 was related to "hsa04151: PI3K-Akt signaling pathway" and "hsa04510: Focal adhesion." We concluded that high ITGA3 expression was a potential prognostic biomarker in PCa.

Laser Capture Microdissection: A Gear for Pancreatic Cancer Research

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

Establishing and characterizing a novel doxorubicin-resistant acute myeloid leukaemia cell line

Drug resistance is a major setback in cancer treatment, thus models to study its mechanisms are needed. Our work aimed to establish and characterize a resistant cell line from a sensitive acute myeloid leukaemia (AML) cell line - HL60 - by treating the sensitive cells with increasing concentrations of doxorubicin. We confirmed (cell viability assays) that the established subline, HL60-CDR, was resistant to doxorubicin for at least 30 days without drug treatment. The HL60-CDR cells were also resistant to three other drugs (cisplatin, etoposide and daunorubicin), exhibiting a multidrug resistant (MDR) profile. We verified (Western Blotting) that the MDR cells do not express drug efflux pumps, nor present altered expression of apoptotic proteins, when compared with the parental cell line. HL60-CDR cells presented alterations in the cell cycle profile, and in the expression levels of proteins involved in DNA repair mechanisms and drug metabolism, when compared with their drug sensitive counterpart. Proteomic analysis revealed that HL60-CDR cells presented an upregulation of proteins involved in oncogenic pathways, such as TSC2, PDPK1, Annexin A2, among others. Overall, we established an AML MDR subline - HL60-CDR - which presents several resistance mechanisms, providing an in vitro model to test new compounds to circumvent MDR in AML.

Cancer proteogenomics: current impact and future prospects

Genomic analyses in cancer have been enormously impactful, leading to the identification of driver mutations and development of targeted therapies. But the functions of the vast majority of somatic mutations and copy number variants in tumours remain unknown, and the causes of resistance to targeted therapies and methods to overcome them are poorly defined. Recent improvements in mass spectrometry-based proteomics now enable direct examination of the consequences of genomic aberrations, providing deep and quantitative characterization of tumour tissues. Integration of proteins and their post-translational modifications with genomic, epigenomic and transcriptomic data constitutes the new field of proteogenomics, and is already leading to new biological and diagnostic knowledge with the potential to improve our understanding of malignant transformation and therapeutic outcomes. In this Review we describe recent developments in proteogenomics and key findings from the proteogenomic analysis of a wide range of cancers. Considerations relevant to the selection and use of samples for proteogenomics and the current technologies used to generate, analyse and integrate proteomic with genomic data are described. Applications of proteogenomics in translational studies and immuno-oncology are rapidly emerging, and the prospect for their full integration into therapeutic trials and clinical care seems bright.

Identification and prognostic analysis of biomarkers to predict the progression of pancreatic cancer patients

BACKGROUND

Pancreatic cancer (PC) is a malignancy with a poor prognosis and high mortality. Surgical resection is the only "curative" treatment. However, only a minority of patients with PC can obtain surgery. Improving the overall survival (OS) rate of patients with PC is still a major challenge. Molecular biomarkers are a significant approach for diagnostic and predictive use in PCs. Several prediction models have been developed for patients newly diagnosed with PC that is operable or patients with advanced and metastatic PC; however, these models require further validation. Therefore, precise biomarkers are urgently required to increase the efficiency of predicting a disease-free survival (DFS), OS, and sensitivity to immunotherapy in PC patients and to improve the prognosis of PC.

METHODS

In the present study, we first evaluated the highly and selectively expressed targets in PC, using the GeoMxTM Digital Spatial Profiler (DSP) and then, we analyzed the roles of these targets in PCs using TCGA database.

RESULTS

LAMB3, FN1, KRT17, KRT19, and ANXA1 were defined as the top five upregulated targets in PC compared with paracancer. The TCGA database results confirmed the expression pattern of LAMB3, FN1, KRT17, KRT19, and ANXA1 in PCs. Significantly, LAMB3, FN1, KRT19, and ANXA1 but not KRT17 can be considered as biomarkers for survival analysis, univariate and multivariate Cox proportional hazards model, and risk model analysis. Furthermore, in combination, LAMB3, FN1, KRT19, and ANXA1 predict the DFS and, in combination, LAMB3, KRT19, and ANXA1 predict the OS. Immunotherapy is significant for PCs that are inoperable. The immune checkpoint blockade (ICB) analysis indicated that higher expressions of FN1 or ANXA1 are correlated with lower ICB response. In contrast, there are no significant differences in the ICB response between high and low expression of LAMB3 and KRT19.

CONCLUSIONS

In conclusion, LAMB3, FN1, KRT19, and ANXA1 are good predictors of PC prognosis. Furthermore, FN1 and ANXA1 can be predictors of immunotherapy in PCs.

Tumor Microenvironment in Pancreatic Intraepithelial Neoplasia

Simple Summary

Pancreatic ductal adenocarcinoma (PDAC) is a very aggressive neoplasm with a poor survival rate. This is mainly due to late detection, which substantially limits therapy options. A better understanding of the early phases of pancreatic carcinogenesis is fundamental for improving patient prognosis in the future. In this article, we focused on the tumor microenvironment (TME), which provides the biological niche for the development of PDAC from its most common precursor lesions, PanIN (pancreatic intraepithelial neoplasias).

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive tumors with a poor prognosis. A characteristic of PDAC is the formation of an immunosuppressive tumor microenvironment (TME) that facilitates bypassing of the immune surveillance. The TME consists of a desmoplastic stroma, largely composed of cancer-associated fibroblasts (CAFs), immunosuppressive immune cells, immunoregulatory soluble factors, neural network cells, and endothelial cells with complex interactions. PDAC develops from various precursor lesions such as pancreatic intraepithelial neoplasia (PanIN), intraductal papillary mucinous neoplasms (IPMN), mucinous cystic neoplasms (MCN), and possibly, atypical flat lesions (AFL). In this review, we focus on the composition of the TME in PanINs to reveal detailed insights into the complex restructuring of the TME at early time points in PDAC progression and to explore ways of modifying the TME to slow or even halt tumor progression.

Spatial proteomics for understanding the tissue microenvironment

The human body comprises rich populations of cells, which are arranged into tissues and organs with diverse functionalities. These cells exhibit a broad spectrum of phenotypes and are often organized as a heterogeneous but sophisticatedly regulated ecosystem - tissue microenvironment, inside which every cell interacts with and is reciprocally influenced by its surroundings through its life span. Therefore, it is critical to comprehensively explore the cellular machinery and biological processes in the tissue microenvironment, which is best exemplified by the tumor microenvironment (TME). The past decade has seen increasing advances in the field of spatial proteomics, the main purpose of which is to characterize the abundance and spatial distribution of proteins and their post-translational modifications in the microenvironment of diseased tissues. Herein, we outline the achievements and remaining challenges of mass spectrometry-based tissue spatial proteomics. Exciting technology developments along with important biomedical applications of spatial proteomics are highlighted. In detail, we focus on high-quality resources built by scalpel macrodissection-based region-resolved proteomics, method development of sensitive sample preparation for laser microdissection-based spatial proteomics, and antibody recognition-based multiplexed tissue imaging. In the end, critical issues and potential future directions for spatial proteomics are also discussed.

Stroma Involvement in Pancreatic Ductal Adenocarcinoma: An Overview Focusing on Extracellular Matrix Proteins

Pancreatic cancer is the seventh leading cause of cancer-related deaths worldwide and is predicted to become second in 2030 in industrialized countries if no therapeutic progress is made. Among the different types of pancreatic cancers, Pancreatic Ductal Adenocarcinoma (PDAC) is by far the most represented one with an occurrence of more than 90%. This specific cancer is a devastating malignancy with an extremely poor prognosis, as shown by the 5-years survival rate of 2–9%, ranking firmly last amongst all cancer sites in terms of prognostic outcomes for patients. Pancreatic tumors progress with few specific symptoms and are thus at an advanced stage at diagnosis in most patients. This malignancy is characterized by an extremely dense stroma deposition around lesions, accompanied by tissue hypovascularization and a profound immune suppression. Altogether, these combined features make access to cancer cells almost impossible for conventional chemotherapeutics and new immunotherapeutic agents, thus contributing to the fatal outcomes of the disease. Initially ignored, the Tumor MicroEnvironment (TME) is now the subject of intensive research related to PDAC treatment and could contain new therapeutic targets. In this review, we will summarize the current state of knowledge in the field by focusing on TME composition to understand how this specific compartment could influence tumor progression and resistance to therapies. Attention will be paid to Tenascin-C, a matrix glycoprotein commonly upregulated during cancer that participates to PDAC progression and thus contributes to poor prognosis.

Role of targeted immunotherapy for pancreatic ductal adenocarcinoma (PDAC) treatment: An overview

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest solid tumors with a high mortality rate and poor survival rate. Depending on the tumor stage, PDAC is either treated by resection surgery, chemotherapies, or radiotherapies. Various chemotherapeutic agents have been used to treat PDAC, alone or in combination. Despite the combinations, chemotherapy exhibits many side-effects leading to an increase in the toxicity profile amongst the PDAC patients. Additionally, these standard chemotherapeutic agents have only a modest impact on patient survival due to their limited efficacy. PDAC was previously considered as an immunologically silent malignancy, but recent findings have demonstrated that effective immune-mediated tumor cell death can be used for its treatment. PDAC is characterized by an immunosuppressive tumor microenvironment accompanied by the major expression of myeloid-derived suppressor cells (MDSC) and M2 tumor-associated macrophages. In contrast, the expression of CD8⁺ T cells is significantly low. Additionally, infiltration of mast cells in PDAC correlates with the poor prognosis. Immunotherapeutic agents target the immunity mediators and empower them to suppress the tumor and effectively treat PDAC. Different targets are studied and exploited to induce an antitumor immune response in PDAC patients. In recent times, site-specific delivery of immunotherapeutics also gained attention among researchers to effectively treat PDAC. In the present review, existing immunotherapies for PDAC treatment along with their limitations are addressed in detail. The review also includes the pathophysiology, traditional strategies and significance of targeted immunotherapies to combat PDAC effectively. Separately, the identification of ideal targets for the targeted therapy of PDAC is also reviewed exhaustively. Additionally, the review also addresses the applications of targeted immunotherapeutics like checkpoint inhibitors, adoptive T-cell therapy etc.

Morphological Heterogeneity in Pancreatic Cancer Reflects Structural and Functional Divergence

Simple Summary

Pancreatic cancer has a poor prognosis, which is largely due to resistance to treatment. Tumor heterogeneity is a known cause for treatment failure and has been studied at the molecular level. Morphological heterogeneity is common but has not been investigated, despite the fact that pathology examination is an integral part of clinical diagnostics. This study assessed whether morphological heterogeneity reflects structural and functional diversity in key cancer biological processes. Using archival tissues from resected pancreatic cancer, we selected four common and distinct morphological phenotypes and demonstrated that these differed significantly for a panel of 26 structural and functional features of the cancer-cell and stromal compartments. The strong link between these features and morphological phenotypes allowed prediction of the latter based on the results for the panel of features. The findings of this study indicate that morphological heterogeneity reflects biological diversity and that its assessment may potentially provide clinically relevant information.

Abstract

Inter- and intratumor heterogeneity is an important cause of treatment failure. In human pancreatic cancer (PC), heterogeneity has been investigated almost exclusively at the genomic and transcriptional level. Morphological heterogeneity, though prominent and potentially easily assessable in clinical practice, remains unexplored. This proof-of-concept study aims at demonstrating that morphological heterogeneity reflects structural and functional divergence. From the wide morphological spectrum of conventional PC, four common and distinctive patterns were investigated in 233 foci from 39 surgical specimens. Twenty-six features involved in key biological processes in PC were analyzed (immuno-)histochemically and morphometrically: cancer cell proliferation (Ki67) and migration (collagen fiber alignment, MMP14), cancer stem cells (CD44, CD133, ALDH1), amount, composition and spatial arrangement of extracellular matrix (epithelial proximity, total collagen, collagen I and III, fibronectin, hyaluronan), cancer-associated fibroblasts (density, αSMA), and cancer-stroma interactions (integrins α2, α5, α1; caveolin-1). All features differed significantly between at least two of the patterns. Stromal and cancer-cell-related features co-varied with morphology and allowed prediction of the morphological pattern. In conclusion, morphological heterogeneity in the cancer-cell and stromal compartments of PC correlates with structural and functional diversity. As such, histopathology has the potential to inform on the operationality of key biological processes in individual tumors.

Proteomic analysis of pancreatic ductal adenocarcinoma

INTRODUCTION

Pancreatic ductal adenocarcinoma (PDAC), which represents approximately 80% of all pancreatic cancers, is a highly aggressive malignant disease and one of the most lethal among all cancers. Overall, the 5-year survival rate among all pancreatic cancer patients is less than 9%; these rates have shown little change over the past 30 years. A more comprehensive understanding of the molecular mechanisms underlying this complex disease is crucial to the development of new diagnostic tools for early detection and disease monitoring, as well as to identify new and more effective therapeutics to improve patient outcomes.

AREA COVERED

We summarize recent advances in proteomic strategies and mass spectrometry to identify new biomarkers for early detection and monitoring of disease progression, predict response to therapy, and to identify novel proteins that have the potential to be 'druggable' therapeutic targets. An overview of proteomic studies that have been conducted to further our mechanistic understanding of metastasis and chemotherapy resistance in PDAC disease progression will also be discussed.

EXPERT COMMENTARY

The results from these PDAC proteomic studies on a variety of PDAC sample types (e.g., blood, tissue, cell lines, exosomes, etc.) provide great promise of having a significant clinical impact and improving patient outcomes.