Spatially restricted drivers and transitional cell populations cooperate with the microenvironment in untreated and chemo-resistant pancreatic cancer

The fibro-adipogenic progenitor APOD+DCN+LUM+ cell population in aggressive carcinomas

We identified a progenitor cell population highly enriched in samples from invasive and chemo-resistant carcinomas, characterized by a well-defined multigene signature including APOD, DCN, and LUM. This cell population has previously been labeled as consisting of inflammatory cancer-associated fibroblasts (iCAFs). The same signature characterizes naturally occurring fibro-adipogenic progenitors (FAPs) as well as stromal cells abundant in normal adipose tissue. Our analysis of human gene expression databases provides evidence that adipose stromal cells (ASCs) are recruited by tumors and undergo differentiation into CAFs during cancer progression to invasive and chemotherapy-resistant stages.

Single-cell analysis of chemotherapy-resistant microenvironment identifies a chemo-response biomarker for pancreatic cancer

Background

Pancreatic ductal adenocarcinoma (PDAC) is a highly fatal, aggressive cancer due to limited response chemotherapy. The tumor microenvironment (TME) has emerged as a key player in the development of chemoresistance and in malignant progression. In this study, we hypothesized that chemotherapy response is predictable by chemotherapy-related cell types and their differentially expressed genes (DEGs).

Methods

DEGs of chemoresistance cell types were identified via single cell analysis and Wilcoxon test. A chemotherapy response signature was established using a random forest model and validated with public datasets. Bulk cell fraction was analyzed using BayesPrism algorithms. Log-rank test was used to analyze survival of PDAC patients.

Results

We found that natural killer (NK) cells, myeloid cells, and erythroid cells were highly infiltrated in chemo-resistant TME. A total of 36 chemoresistance-related DEGs of chemo-resistant cells were identified in chemo-resistant PDAC. Functional enrichment analysis showed that chemoresistance upregulated various inflammation-related pathways, including TGF-β signaling. Based on these features, we constructed a random forest model to predict the response and survival for PDAC patients, which accurately distinguished high-risk and chemoresistant patients with significantly poorer prognosis in both the training and independent validation datasets. Cox regression analysis indicated that predicted labels were an independent prognostic factor in PDAC. Moreover, deconvolution of TME confirmed higher infiltration levels of M2 macrophage and NK cells in predicted chemoresistance. When combined with chemotherapy response related tumor mutations, the model showed excellent ability in predicting chemotherapy response and survival.

Conclusions

The TME was closely associated with the chemotherapy response and prognosis of PDAC. Our TME-based random forest model predicted chemotherapy response with complementary knowledge to the response-related genetic mutations.

PanIN and CAF transitions in pancreatic carcinogenesis revealed with spatial data integration

This study introduces a new imaging, spatial transcriptomics (ST), and single-cell RNA-sequencing integration pipeline to characterize neoplastic cell state transitions during tumorigenesis. We applied a semi-supervised analysis pipeline to examine premalignant pancreatic intraepithelial neoplasias (PanINs) that can develop into pancreatic ductal adenocarcinoma (PDAC). Their strict diagnosis on formalin-fixed and paraffin-embedded (FFPE) samples limited the single-cell characterization of human PanINs within their microenvironment. We leverage whole transcriptome FFPE ST to enable the study of a rare cohort of matched low-grade (LG) and high-grade (HG) PanIN lesions to track progression and map cellular phenotypes relative to single-cell PDAC datasets. We demonstrate that cancer-associated fibroblasts (CAFs), including antigen-presenting CAFs, are located close to PanINs. We further observed a transition from CAF-related inflammatory signaling to cellular proliferation during PanIN progression. We validate these findings with single-cell high-dimensional imaging proteomics and transcriptomics technologies. Altogether, our semi-supervised learning framework for spatial multi-omics has broad applicability across cancer types to decipher the spatiotemporal dynamics of carcinogenesis.

Cell-cell communication: new insights and clinical implications

Multicellular organisms are composed of diverse cell types that must coordinate their behaviors through communication. Cell-cell communication (CCC) is essential for growth, development, differentiation, tissue and organ formation, maintenance, and physiological regulation. Cells communicate through direct contact or at a distance using ligand-receptor interactions. So cellular communication encompasses two essential processes: cell signal conduction for generation and intercellular transmission of signals, and cell signal transduction for reception and procession of signals. Deciphering intercellular communication networks is critical for understanding cell differentiation, development, and metabolism. First, we comprehensively review the historical milestones in CCC studies, followed by a detailed description of the mechanisms of signal molecule transmission and the importance of the main signaling pathways they mediate in maintaining biological functions. Then we systematically introduce a series of human diseases caused by abnormalities in cell communication and their progress in clinical applications. Finally, we summarize various methods for monitoring cell interactions, including cell imaging, proximity-based chemical labeling, mechanical force analysis, downstream analysis strategies, and single-cell technologies. These methods aim to illustrate how biological functions depend on these interactions and the complexity of their regulatory signaling pathways to regulate crucial physiological processes, including tissue homeostasis, cell development, and immune responses in diseases. In addition, this review enhances our understanding of the biological processes that occur after cell-cell binding, highlighting its application in discovering new therapeutic targets and biomarkers related to precision medicine. This collective understanding provides a foundation for developing new targeted drugs and personalized treatments.

Aging- and alcohol-associated spatial transcriptomic signature in mouse acute pancreatitis reveals heterogeneity of inflammation and potential pathogenic factors

The rapidly aging population is consuming more alcohol, leading to increased alcohol-associated acute pancreatitis (AAP) with high mortality. However, the mechanisms remain undefined, and currently there are no effective therapies available. This study aims to elucidate aging- and alcohol-associated spatial transcriptomic signature by establishing an aging AAP mouse model and applying Visium spatial transcriptomics for understanding of the mechanisms in the context of the pancreatic tissue. Upon alcohol diet feeding and caerulein treatment, aging mice (18 months) developed significantly more severe AAP with 5.0-fold increase of injury score and 2.4-fold increase of amylase compared to young mice (3 months). Via Visium spatial transcriptomics, eight distinct tissue clusters were revealed from aggregated transcriptomes of aging and young AAP mice: five acinar, two stromal, and one islet, which were then merged into three clusters: acinar, stromal, and islet for the comparative analysis. Compared to young AAP mice, > 1300 differentially expressed genes (DEGs) and approximately 3000 differentially regulated pathways were identified in aging AAP mice. The top five DEGs upregulated in aging AAP mice include Mmp8, Ppbp, Serpina3m, Cxcl13, and Hamp with heterogeneous distributions among the clusters. Taken together, this study demonstrates spatial heterogeneity of inflammatory processes in aging AAP mice, offering novel insights into the mechanisms and potential drivers for AAP development. KEY MESSAGES: Mechanisms regarding high mortality of AAP in aging remain undefined. An aging AAP mouse model was developed recapturing clinical exhibition in humans. Spatial transcriptomics identified contrasted DEGs in aging vs. young AAP mice. Top five DEGs were Mmp8, Ppbp, Serpina3m, Cxcl13, and Hamp in aging vs. young AAP mice. Our findings shed insights for identification of molecular drivers in aging AAP.

Kinase activities in pancreatic ductal adenocarcinoma with prognostic and therapeutic avenues

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

Current computational methods for spatial transcriptomics in cancer biology

Cells in multicellular organisms constitute a self-organizing society by interacting with their neighbors. Cancer originates from malfunction of cellular behavior in the context of such a self-organizing system. The identities or characteristics of individual tumor cells can be represented by the hallmark of gene expression or transcriptome, which can be addressed using single-cell dissociation followed by RNA sequencing. However, the dissociation process of single cells results in losing the cellular address in tissue or neighbor information of each tumor cell, which is critical to understanding the malfunctioning cellular behavior in the microenvironment. Spatial transcriptomics technology enables measuring the transcriptome which is tagged by the address within a tissue. However, to understand cellular behavior in a self-organizing society, we need to apply mathematical or statistical methods. Here, we provide a review on current computational methods for spatial transcriptomics in cancer biology.

Multiplexed Imaging Mass Cytometry Analysis Characterizes the Vascular Niche in Pancreatic Cancer

Oncogenesis and progression of pancreatic ductal adenocarcinoma (PDAC) are driven by complex interactions between the neoplastic component and the tumor microenvironment, which includes immune, stromal, and parenchymal cells. In particular, most PDACs are characterized by a hypovascular and hypoxic environment that alters tumor cell behavior and limits the efficacy of chemotherapy and immunotherapy. Characterization of the spatial features of the vascular niche could advance our understanding of inter- and intratumoral heterogeneity in PDAC. In this study, we investigated the vascular microenvironment of PDAC by applying imaging mass cytometry using a 26-antibody panel on 35 regions of interest across 9 patients, capturing more than 140,000 single cells. The approach distinguished major cell types, including multiple populations of lymphoid and myeloid cells, endocrine cells, ductal cells, stromal cells, and endothelial cells. Evaluation of cellular neighborhoods identified 10 distinct spatial domains, including multiple immune and tumor-enriched environments as well as the vascular niche. Focused analysis revealed differential interactions between immune populations and the vasculature and identified distinct spatial domains wherein tumor cell proliferation occurs. Importantly, the vascular niche was closely associated with a population of CD44-expressing macrophages enriched for a proangiogenic gene signature. Taken together, this study provides insights into the spatial heterogeneity of PDAC and suggests a role for CD44-expressing macrophages in shaping the vascular niche. Significance: Imaging mass cytometry revealed that pancreatic ductal cancers are composed of 10 distinct cellular neighborhoods, including a vascular niche enriched for macrophages expressing high levels of CD44 and a proangiogenic gene signature.

Understanding the Conundrum of Pancreatic Cancer in the Omics Sciences Era

Pancreatic cancer (PC) is an increasing cause of cancer-related death, with a dismal prognosis caused by its aggressive biology, the lack of clinical symptoms in the early phases of the disease, and the inefficacy of treatments. PC is characterized by a complex tumor microenvironment. The interaction of its cellular components plays a crucial role in tumor development and progression, contributing to the alteration of metabolism and cellular hyperproliferation, as well as to metastatic evolution and abnormal tumor-associated immunity. Furthermore, in response to intrinsic oncogenic alterations and the influence of the tumor microenvironment, cancer cells undergo a complex oncogene-directed metabolic reprogramming that includes changes in glucose utilization, lipid and amino acid metabolism, redox balance, and activation of recycling and scavenging pathways. The advent of omics sciences is revolutionizing the comprehension of the pathogenetic conundrum of pancreatic carcinogenesis. In particular, metabolomics and genomics has led to a more precise classification of PC into subtypes that show different biological behaviors and responses to treatments. The identification of molecular targets through the pharmacogenomic approach may help to personalize treatments. Novel specific biomarkers have been discovered using proteomics and metabolomics analyses. Radiomics allows for an earlier diagnosis through the computational analysis of imaging. However, the complexity, high expertise required, and costs of the omics approach are the main limitations for its use in clinical practice at present. In addition, the studies of extracellular vesicles (EVs), the use of organoids, the understanding of host-microbiota interactions, and more recently the advent of artificial intelligence are helping to make further steps towards precision and personalized medicine. This present review summarizes the main evidence for the application of omics sciences to the study of PC and the identification of future perspectives.

Unbiasedly decoding the tumor microenvironment with single-cell multiomics analysis in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a poor prognosis and limited therapeutic options. Research on the tumor microenvironment (TME) of PDAC has propelled the development of immunotherapeutic and targeted therapeutic strategies with a promising future. The emergence of single-cell sequencing and mass spectrometry technologies, coupled with spatial omics, has collectively revealed the heterogeneity of the TME from a multiomics perspective, outlined the development trajectories of cell lineages, and revealed important functions of previously underrated myeloid cells and tumor stroma cells. Concurrently, these findings necessitated more refined annotations of biological functions at the cell cluster or single-cell level. Precise identification of all cell clusters is urgently needed to determine whether they have been investigated adequately and to identify target cell clusters with antitumor potential, design compatible treatment strategies, and determine treatment resistance. Here, we summarize recent research on the PDAC TME at the single-cell multiomics level, with an unbiased focus on the functions and potential classification bases of every cellular component within the TME, and look forward to the prospects of integrating single-cell multiomics data and retrospectively reusing bulk sequencing data, hoping to provide new insights into the PDAC TME.

Senescence Defines a Distinct Subset of Myofibroblasts That Orchestrates Immunosuppression in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) therapeutic resistance is largely attributed to a unique tumor microenvironment embedded with an abundance of cancer-associated fibroblasts (CAF). Distinct CAF populations were recently identified, but the phenotypic drivers and specific impact of CAF heterogeneity remain unclear. In this study, we identify a subpopulation of senescent myofibroblastic CAFs (SenCAF) in mouse and human PDAC. These SenCAFs are a phenotypically distinct subset of myofibroblastic CAFs that localize near tumor ducts and accumulate with PDAC progression. To assess the impact of endogenous SenCAFs in PDAC, we used an LSL-KRASG12D;p53flox;p48-CRE;INK-ATTAC (KPPC-IA) mouse model of spontaneous PDAC with inducible senescent cell depletion. Depletion of senescent stromal cells in genetic and pharmacologic PDAC models relieved immune suppression by macrophages, delayed tumor progression, and increased responsiveness to chemotherapy. Collectively, our findings demonstrate that SenCAFs promote PDAC progression and immune cell dysfunction. Significance: CAF heterogeneity in PDAC remains poorly understood. In this study, we identify a novel subpopulation of senescent CAFs that promotes PDAC progression and immunosuppression. Targeting CAF senescence in combination therapies could increase tumor vulnerability to chemo or immunotherapy. See related article by Ye et al., p. 1302.

Gastric cancer immunosuppressive microenvironment heterogeneity: implications for therapy development

Although immunotherapy has revolutionized solid tumor treatment, durable responses in gastric cancer (GC) remain limited. The heterogeneous tumor microenvironment (TME) facilitates immune evasion, contributing to resistance to conventional and immune therapies. Recent studies have highlighted how specific TME components in GC acquire immune escape capabilities through cancer-specific factors. Understanding the underlying molecular mechanisms and targeting the immunosuppressive TME will enhance immunotherapy efficacy and patient outcomes. This review summarizes recent advances in GC TME research and explores the role of the immune-suppressive system as a context-specific determinant. We also provide insights into potential treatments beyond checkpoint inhibition.

Advances in spatial transcriptomics and its applications in cancer research

Malignant tumors have increasing morbidity and high mortality, and their occurrence and development is a complicate process. The development of sequencing technologies enabled us to gain a better understanding of the underlying genetic and molecular mechanisms in tumors. In recent years, the spatial transcriptomics sequencing technologies have been developed rapidly and allow the quantification and illustration of gene expression in the spatial context of tissues. Compared with the traditional transcriptomics technologies, spatial transcriptomics technologies not only detect gene expression levels in cells, but also inform the spatial location of genes within tissues, cell composition of biological tissues, and interaction between cells. Here we summarize the development of spatial transcriptomics technologies, spatial transcriptomics tools and its application in cancer research. We also discuss the limitations and challenges of current spatial transcriptomics approaches, as well as future development and prospects.

The Advancement and Application of the Single-Cell Transcriptome in Biological and Medical Research

Single-cell RNA sequencing technology (scRNA-seq) has been steadily developing since its inception in 2009. Unlike bulk RNA-seq, scRNA-seq identifies the heterogeneity of tissue cells and reveals gene expression changes in individual cells at the microscopic level. Here, we review the development of scRNA-seq, which has gone through iterations of reverse transcription, in vitro transcription, smart-seq, drop-seq, 10 × Genomics, and spatial single-cell transcriptome technologies. The technology of 10 × Genomics has been widely applied in medicine and biology, producing rich research results. Furthermore, this review presents a summary of the analytical process for single-cell transcriptome data and its integration with other omics analyses, including genomes, epigenomes, proteomes, and metabolomics. The single-cell transcriptome has a wide range of applications in biology and medicine. This review analyzes the applications of scRNA-seq in cancer, stem cell research, developmental biology, microbiology, and other fields. In essence, scRNA-seq provides a means of elucidating gene expression patterns in single cells, thereby offering a valuable tool for scientific research. Nevertheless, the current single-cell transcriptome technology is still imperfect, and this review identifies its shortcomings and anticipates future developments. The objective of this review is to facilitate a deeper comprehension of scRNA-seq technology and its applications in biological and medical research, as well as to identify avenues for its future development in alignment with practical needs.

Heterogeneity of myeloid cells in common cancers: Single cell insights and targeting strategies

Tumor microenvironment (TME), is characterized by a complex and heterogenous composition involving a substantial population of immune cells. Myeloid cells comprising over half of the solid tumor mass, are undoubtedly one of the most prominent cell populations associated with tumors. Studies have unambiguously established that myeloid cells play a key role in tumor development, including immune suppression, pro-inflammation, promote tumor metastasis and angiogenesis, for example, tumor-associated macrophages promote tumor progression in a variety of common tumors, including lung cancer, through direct or indirect interactions with the TME. However, due to previous technological constraints, research on myeloid cells often tended to be conducted as studies with low throughput and limited resolution. For example, the conventional categorization of macrophages into M1-like and M2-like subsets based solely on their anti-tumor and pro-tumor roles has disregarded their continuum of states, resulting in an inadequate analysis of the high heterogeneity characterizing myeloid cells. The widespread adoption of single-cell RNA sequencing (scRNA-seq) in tumor immunology has propelled researchers into a new realm of understanding, leading to the establishment of novel subsets and targets. In this review, the origin of myeloid cells in high-incidence cancers, the functions of myeloid cell subsets examined through traditional and single-cell perspectives, as well as specific targeting strategies, are comprehensively outlined. As a result of this endeavor, we will gain a better understanding of myeloid cell heterogeneity, as well as contribute to the development of new therapeutic approaches.

Progress of single-cell RNA sequencing combined with spatial transcriptomics in tumour microenvironment and treatment of pancreatic cancer

In recent years, single-cell analyses have revealed the heterogeneity of the tumour microenvironment (TME) at the genomic, transcriptomic, and proteomic levels, further improving our understanding of the mechanisms of tumour development. Single-cell RNA sequencing (scRNA-seq) technology allow analysis of the transcriptome at the single-cell level and have unprecedented potential for exploration of the characteristics involved in tumour development and progression. These techniques allow analysis of transcript sequences at higher resolution, thereby increasing our understanding of the diversity of cells found in the tumour microenvironment and how these cells interact in complex tumour tissue. Although scRNA-seq has emerged as an important tool for studying the tumour microenvironment in recent years, it cannot be used to analyse spatial information for cells. In this regard, spatial transcriptomics (ST) approaches allow researchers to understand the functions of individual cells in complex multicellular organisms by understanding their physical location in tissue sections. In particular, in related research on tumour heterogeneity, ST is an excellent complementary approach to scRNA-seq, constituting a new method for further exploration of tumour heterogeneity, and this approach can also provide unprecedented insight into the development of treatments for pancreatic cancer (PC). In this review, based on the methods of scRNA-seq and ST analyses, research progress on the tumour microenvironment and treatment of pancreatic cancer is further explained.

Spatial transcriptomics in cancer research and potential clinical impact: a narrative review

Spatial transcriptomics (ST) provides novel insights into the tumor microenvironment (TME). ST allows the quantification and illustration of gene expression profiles in the spatial context of tissues, including both the cancer cells and the microenvironment in which they are found. In cancer research, ST has already provided novel insights into cancer metastasis, prognosis, and immunotherapy responsiveness. The clinical precision oncology application of next-generation sequencing (NGS) and RNA profiling of tumors relies on bulk methods that lack spatial context. The ability to preserve spatial information is now possible, as it allows us to capture tumor heterogeneity and multifocality. In this narrative review, we summarize precision oncology, discuss tumor sequencing in the clinic, and review the available ST research methods, including seqFISH, MERFISH (Vizgen), CosMx SMI (NanoString), Xenium (10x), Visium (10x), Stereo-seq (STOmics), and GeoMx DSP (NanoString). We then review the current ST literature with a focus on solid tumors organized by tumor type. Finally, we conclude by addressing an important question: how will spatial transcriptomics ultimately help patients with cancer?

Dendritic cell subsets and implications for cancer immunotherapy

Dendritic cells (DCs) play a central role in the orchestration of effective T cell responses against tumors. However, their functional behavior is context-dependent. DC type, transcriptional program, location, intratumoral factors, and inflammatory milieu all impact DCs with regard to promoting or inhibiting tumor immunity. The following review introduces important facets of DC function, and how subset and phenotype can affect the interplay of DCs with other factors in the tumor microenvironment. It will also discuss how current cancer treatment relies on DC function, and survey the myriad ways with which immune therapy can more directly harness DCs to enact antitumor cytotoxicity.

Novel Approach for Pancreas Transcriptomics Reveals the Cellular Landscape in Homeostasis and Acute Pancreatitis

BACKGROUND & AIMS

Acinar cells produce digestive enzymes that impede transcriptomic characterization of the exocrine pancreas. Thus, single-cell RNA-sequencing studies of the pancreas underrepresent acinar cells relative to histological expectations, and a robust approach to capture pancreatic cell responses in disease states is needed. We sought to innovate a method that overcomes these challenges to accelerate study of the pancreas in health and disease.

METHODS

We leverage FixNCut, a single-cell RNA-sequencing approach in which tissue is reversibly fixed with dithiobis(succinimidyl propionate) before dissociation and single-cell preparation. We apply FixNCut to an established mouse model of acute pancreatitis, validate findings using GeoMx whole transcriptome atlas profiling, and integrate our data with prior studies to compare our method in both mouse and human pancreas datasets.

RESULTS

FixNCut achieves unprecedented definition of challenging pancreatic cells, including acinar and immune populations in homeostasis and acute pancreatitis, and identifies changes in all major cell types during injury and recovery. We define the acinar transcriptome during homeostasis and acinar-to-ductal metaplasia and establish a unique gene set to measure deviation from normal acinar identity. We characterize pancreatic immune cells, and analysis of T-cell subsets reveals a polarization of the homeostatic pancreas toward type-2 immunity. We report immune responses during acute pancreatitis and recovery, including early neutrophil infiltration, expansion of dendritic cell subsets, and a substantial shift in the transcriptome of macrophages due to both resident macrophage activation and monocyte infiltration.

CONCLUSIONS

FixNCut preserves pancreatic transcriptomes to uncover novel cell states during homeostasis and following pancreatitis, establishing a broadly applicable approach and reference atlas for study of pancreas biology and disease.

Netrin G1 Ligand is a new stromal immunomodulator that promotes pancreatic cancer

Understanding pancreatic cancer biology is fundamental for identifying new targets and for developing more effective therapies. In particular, the contribution of the stromal microenvironment to pancreatic cancer tumorigenesis requires further exploration. Here, we report the stromal roles of the synaptic protein Netrin G1 Ligand (NGL-1) in pancreatic cancer, uncovering its pro-tumor functions in cancer-associated fibroblasts and in immune cells. We observed that the stromal expression of NGL-1 inversely correlated with patients' overall survival. Moreover, germline knockout (KO) mice for NGL-1 presented decreased tumor burden, with a microenvironment that is less supportive of tumor growth. Of note, tumors from NGL-1 KO mice produced less immunosuppressive cytokines and displayed an increased percentage of CD8 + T cells than those from control mice, while preserving the physical structure of the tumor microenvironment. These effects were shown to be mediated by NGL-1 in both immune cells and in the local stroma, in a TGF-β-dependent manner. While myeloid cells lacking NGL-1 decreased the production of immunosuppressive cytokines, NGL-1 KO T cells showed increased proliferation rates and overall polyfunctionality compared to control T cells. CAFs lacking NGL-1 were less immunosuppressive than controls, with overall decreased production of pro-tumor cytokines and compromised ability to inhibit CD8 + T cells activation. Mechanistically, these CAFs downregulated components of the TGF-β pathway, AP-1 and NFAT transcription factor families, resulting in a less tumor-supportive phenotype. Finally, targeting NGL-1 genetically or using a functionally antagonistic small peptide phenocopied the effects of chemotherapy, while modulating the immunosuppressive tumor microenvironment (TME), rather than eliminating it. We propose NGL-1 as a new local stroma and immunomodulatory molecule, with pro-tumor roles in pancreatic cancer.

Statement of Significance

Here we uncovered the pro-tumor roles of the synaptic protein NGL-1 in the tumor microenvironment of pancreatic cancer, defining a new target that simultaneously modulates tumor cell, fibroblast, and immune cell functions. This study reports a new pathway where NGL-1 controls TGF-β, AP-1 transcription factor members and NFAT1, modulating the immunosuppressive microenvironment in pancreatic cancer. Our findings highlight NGL-1 as a new stromal immunomodulator in pancreatic cancer.

Cellular collusion: cracking the code of immunosuppression and chemo resistance in PDAC

Despite the efforts, pancreatic ductal adenocarcinoma (PDAC) is still highly lethal. Therapeutic challenges reside in late diagnosis and establishment of peculiar tumor microenvironment (TME) supporting tumor outgrowth. This stromal landscape is highly heterogeneous between patients and even in the same patient. The organization of functional sub-TME with different cellular compositions provides evolutive advantages and sustains therapeutic resistance. Tumor progressively establishes a TME that can suit its own needs, including proliferation, stemness and invasion. Cancer-associated fibroblasts and immune cells, the main non-neoplastic cellular TME components, follow soluble factors-mediated neoplastic instructions and synergize to promote chemoresistance and immune surveillance destruction. Unveiling heterotypic stromal-neoplastic interactions is thus pivotal to breaking this synergism and promoting the reprogramming of the TME toward an anti-tumor milieu, improving thus the efficacy of conventional and immune-based therapies. We underscore recent advances in the characterization of immune and fibroblast stromal components supporting or dampening pancreatic cancer progression, as well as novel multi-omic technologies improving the current knowledge of PDAC biology. Finally, we put into context how the clinic will translate the acquired knowledge to design new-generation clinical trials with the final aim of improving the outcome of PDAC patients.

Enhanced Complement Expression in the Tumor Microenvironment Following Neoadjuvant Therapy: Implications for Immunomodulation and Survival in Pancreatic Ductal Adenocarcinoma

Background

Neoadjuvant therapy (NAT) is increasingly being used for pancreatic ductal adenocarcinoma (PDAC) treatment. However, its specific effects on carcinoma cells and the tumor microenvironment (TME) are not fully understood. This study aims to investigate how NAT differentially impacts PDAC's carcinoma cells and TME.

Methods

Spatial transcriptomics was used to compare gene expression profiles in carcinoma cells and the TME between 23 NAT-treated and 13 NAT-naïve PDAC patients, correlating with their clinicopathologic features. Analysis of an online single-nucleus RNA sequencing (snRNA-seq) dataset was performed for validation of the specific cell types responsible for NAT-induced gene expression alterations.

Results

NAT not only induces apoptosis and inhibits proliferation in carcinoma cells but also significantly remodels the TME. Notably, NAT induces a coordinated upregulation of multiple key complement genes (C3, C1S, C1R, C4B and C7) in the TME, making the complement pathway one of the most significantly affected pathways by NAT. Patients with higher TME complement expression following NAT exhibit improved overall survival. These patients also exhibit increased immunomodulatory and neurotrophic cancer-associated fibroblasts (CAFs); more CD4+ T cells, monocytes, and mast cells; and reduced immune exhaustion gene expression. snRNA-seq analysis demonstrates C3 complement was specifically upregulated in CAFs but not in other stroma cell types.

Conclusions

NAT can enhance complement production and signaling within the TME, which is associated with reduced immunosuppression in PDAC. These findings suggest that local complement dynamics could serve as a novel biomarker for prognosis, evaluating treatment response and resistance, and guiding therapeutic strategies in NAT-treated PDAC patients.

Single-cell transcriptome analysis reveals subtype-specific clonal evolution and microenvironmental changes in liver metastasis of pancreatic adenocarcinoma and their clinical implications

BACKGROUND

Intratumoral heterogeneity (ITH) and tumor microenvironment (TME) of pancreatic ductal adenocarcinoma (PDAC) play important roles in tumor evolution and patient outcomes. However, the precise characterization of diverse cell populations and their crosstalk associated with PDAC progression and metastasis is still challenging.

METHODS

We performed single-cell RNA sequencing (scRNA-seq) of treatment-naïve primary PDAC samples with and without paired liver metastasis samples to understand the interplay between ITH and TME in the PDAC evolution and its clinical associations.

RESULTS

scRNA-seq analysis revealed that even a small proportion (22%) of basal-like malignant ductal cells could lead to poor chemotherapy response and patient survival and that epithelial-mesenchymal transition programs were largely subtype-specific. The clonal homogeneity significantly increased with more prevalent and pronounced copy number gains of oncogenes, such as KRAS and ETV1, and losses of tumor suppressor genes, such as SMAD2 and MAP2K4, along PDAC progression and metastasis. Moreover, diverse immune cell populations, including naïve SELLhi regulatory T cells (Tregs) and activated TIGIThi Tregs, contributed to shaping immunosuppressive TMEs of PDAC through cellular interactions with malignant ductal cells in PDAC evolution. Importantly, the proportion of basal-like ductal cells negatively correlated with that of immunoreactive cell populations, such as cytotoxic T cells, but positively correlated with that of immunosuppressive cell populations, such as Tregs.

CONCLUSION

We uncover that the proportion of basal-like subtype is a key determinant for chemotherapy response and patient outcome, and that PDAC clonally evolves with subtype-specific dosage changes of cancer-associated genes by forming immunosuppressive microenvironments in its progression and metastasis.

Fibroblast subtypes in pancreatic cancer and pancreatitis: from mechanisms to therapeutic strategies

Excessive fibrosis is a predominant feature of pancreatic stroma and plays a crucial role in the development and progression of pancreatic ductal adenocarcinoma (PDAC) and chronic pancreatitis (CP). Emerging evidence showed diversity and heterogeneity of fibroblasts play crucial and somewhat contradictory roles, the interactions between fibroblasts and pancreatic cells or infiltrating immune cells are of great importance during PDAC and CP progression, with some promising therapeutic strategies being tested. Therefore, in this review, we describe the classification of fibroblasts and their functions in PDAC and pancreatitis, the mechanisms by which fibroblasts mediate the development and progression of PDAC and CP through direct or indirect interaction between fibroblast and pancreatic parenchymal cells, or by remodeling the pancreatic immune microenvironment mediates the development and progression of PDAC and CP. Finally, we summarized the current therapeutic strategies and agents that directly target subtypes of fibroblasts or interfere with their essential functions.

Clonal dominance defines metastatic dissemination in pancreatic cancer

Tumors represent ecosystems where subclones compete during tumor growth. While extensively investigated, a comprehensive picture of the interplay of clonal lineages during dissemination is still lacking. Using patient-derived pancreatic cancer cells, we created orthotopically implanted clonal replica tumors to trace clonal dynamics of unperturbed tumor expansion and dissemination. This model revealed the multifaceted nature of tumor growth, with rapid changes in clonal fitness leading to continuous reshuffling of tumor architecture and alternating clonal dominance as a distinct feature of cancer growth. Regarding dissemination, a large fraction of tumor lineages could be found at secondary sites each having distinctive organ growth patterns as well as numerous undescribed behaviors such as abortive colonization. Paired analysis of primary and secondary sites revealed fitness as major contributor to dissemination. From the analysis of pro- and nonmetastatic isogenic subclones, we identified a transcriptomic signature able to identify metastatic cells in human tumors and predict patients' survival.

In Neoadjuvant FOLFIRINOX Chemotherapy for Pancreatic Ductal Adenocarcinoma, Which Response is the More Reliable Indicator for Prognosis, Radiologic or Biochemical?

BACKGROUND

In this era of increasing neoadjuvant chemotherapy, methods for evaluating responses to neoadjuvant chemotherapy are still diverse among institutions. Additionally, the efficacy of adjuvant chemotherapy for patients undergoing neoadjuvant chemotherapy remains unclear. Therefore, this retrospective study was performed to evaluate the effectiveness of methods for assessing response to neoadjuvant chemotherapy and the need for adjuvant chemotherapy in treating patients with non-metastatic pancreatic ductal adenocarcinoma.

METHODS

The study identified 150 patients who underwent neoadjuvant FOLFIRINOX chemotherapy followed by curative-intent pancreatectomy. The patients were stratified by biochemical response based on the normalization of carbohydrate antigen 19-9 and by radiologic response based on size change at imaging.

RESULTS

The patients were classified into the following three groups based on their response to neoadjuvant chemotherapy and prognosis: biochemical responders (BR+), radiology-only responders (BR-/RR+), and non-responders (BR-/RR-). The 3-year overall survival rate was higher for BR+ (71.0%) than for BR-/RR+ (53.6%) or BR-/RR- (33.1%) (P < 0.001). Response to neoadjuvant chemotherapy also was identified as a significant risk factor for recurrence in a comparison between BR-/RR+ and BR+ (hazard ratio [HR], 2.15; 95% confidence interval [CI] 1.19-3.88; P = 0.011) and BR-/RR- (HR, 3.82; 95% CI 2.41-6.08; P < 0.001). Additionally, regardless of the response to neoadjuvant chemotherapy, patients who completed adjuvant chemotherapy had a significantly higher 3-year overall survival rate than those who did not.

CONCLUSIONS

This response evaluation criterion for neoadjuvant chemotherapy is feasible and can significantly predict prognosis. Additionally, completion of adjuvant chemotherapy could be helpful to patients who undergo neoadjuvant chemotherapy regardless of their response to neoadjuvant chemotherapy.

Integrative analysis of spatial and single-cell transcriptome data from human pancreatic cancer reveals an intermediate cancer cell population associated with poor prognosis

BACKGROUND

Recent studies using single-cell transcriptomic analysis have reported several distinct clusters of neoplastic epithelial cells and cancer-associated fibroblasts in the pancreatic cancer tumor microenvironment. However, their molecular characteristics and biological significance have not been clearly elucidated due to intra- and inter-tumoral heterogeneity.

METHODS

We performed single-cell RNA sequencing using enriched non-immune cell populations from 17 pancreatic tumor tissues (16 pancreatic cancer and one high-grade dysplasia) and generated paired spatial transcriptomic data from seven patient samples.

RESULTS

We identified five distinct functional subclusters of pancreatic cancer cells and six distinct cancer-associated fibroblast subclusters. We deeply profiled their characteristics, and we found that these subclusters successfully deconvoluted most of the features suggested in bulk transcriptome analysis of pancreatic cancer. Among those subclusters, we identified a novel cancer cell subcluster, Ep_VGLL1, showing intermediate characteristics between the extremities of basal-like and classical dichotomy, despite its prognostic value. Molecular features of Ep_VGLL1 suggest its transitional properties between basal-like and classical subtypes, which is supported by spatial transcriptomic data.

CONCLUSIONS

This integrative analysis not only provides a comprehensive landscape of pancreatic cancer and fibroblast population, but also suggests a novel insight to the dynamic states of pancreatic cancer cells and unveils potential therapeutic targets.

Reconstitution of human PDAC using primary cells reveals oncogenic transcriptomic features at tumor onset

Animal studies have demonstrated the ability of pancreatic acinar cells to transform into pancreatic ductal adenocarcinoma (PDAC). However, the tumorigenic potential of human pancreatic acinar cells remains under debate. To address this gap in knowledge, we expand sorted human acinar cells as 3D organoids and genetically modify them through introduction of common PDAC mutations. The acinar organoids undergo dramatic transcriptional alterations but maintain a recognizable DNA methylation signature. The transcriptomes of acinar organoids are similar to those of disease-specific cell populations. Oncogenic KRAS alone do not transform acinar organoids. However, acinar organoids can form PDAC in vivo after acquiring the four most common driver mutations of this disease. Similarly, sorted ductal cells carrying these genetic mutations can also form PDAC, thus experimentally proving that PDACs can originate from both human acinar and ductal cells. RNA-seq analysis reveal the transcriptional shift from normal acinar cells towards PDACs with enhanced proliferation, metabolic rewiring, down-regulation of MHC molecules, and alterations in the coagulation and complement cascade. By comparing PDAC-like cells with normal pancreas and PDAC samples, we identify a group of genes with elevated expression during early transformation which represent potential early diagnostic biomarkers.

Integration of Pan-Cancer Single-Cell and Spatial Transcriptomics Reveals Stromal Cell Features and Therapeutic Targets in Tumor Microenvironment

Stromal cells are physiologically essential components of the tumor microenvironment (TME) that mediates tumor development and therapeutic resistance. Development of a logical and unified system for stromal cell type identification and characterization of corresponding functional properties could help design antitumor strategies that target stromal cells. Here, we performed a pan-cancer analysis of 214,972 nonimmune stromal cells using single-cell RNA sequencing from 258 patients across 16 cancer types and analyzed spatial transcriptomics from 16 patients across seven cancer types, including six patients receiving anti-PD-1 treatment. This analysis uncovered distinct features of 39 stromal subsets across cancer types, including various functional modules, spatial locations, and clinical and therapeutic relevance. Tumor-associated PGF+ endothelial tip cells with elevated epithelial-mesenchymal transition features were enriched in immune-depleted TME and associated with poor prognosis. Fibrogenic and vascular pericytes (PC) derived from FABP4+ progenitors were two distinct tumor-associated PC subpopulations that strongly interacted with PGF+ tips, resulting in excess extracellular matrix (ECM) abundance and dysfunctional vasculature. Importantly, ECM-related cancer-associated fibroblasts enriched at the tumor boundary acted as a barrier to exclude immune cells, interacted with malignant cells to promote tumor progression, and regulated exhausted CD8+ T cells via immune checkpoint ligand-receptors (e.g., LGALS9/TIM-3) to promote immune escape. In addition, an interactive web-based tool (http://www.scpanstroma.yelab.site/) was developed for accessing, visualizing, and analyzing stromal data. Taken together, this study provides a systematic view of the highly heterogeneous stromal populations across cancer types and suggests future avenues for designing therapies to overcome the tumor-promoting functions of stromal cells.

SIGNIFICANCE

Comprehensive characterization of tumor-associated nonimmune stromal cells provides a robust resource for dissecting tumor microenvironment complexity and guiding stroma-targeted therapy development across multiple human cancer types.

Lineage Plasticity: The New Cancer Hallmark on the Block

Plasticity refers to the ability of cells to adopt a spectrum of states or phenotypes. In cancer, it is a critical contributor to tumor initiation, progression, invasiveness, and therapy resistance, and it has recently been recognized as an emerging cancer hallmark. Plasticity can occur as a result of cell-intrinsic factors (e.g., genetic, transcriptional, or epigenetic fluctuations), or through cell-extrinsic cues (e.g., signaling from components of the tumor microenvironment or selective pressure from therapy). Over the past decade, technological advances, analysis of patient samples, and studies in mouse model systems have led to a deeper understanding of how such plastic states come about. In this review, we discuss: (i) the definition of plasticity; (ii) methods to measure and quantify plasticity; (iii) the clinical relevance of plasticity; and (iv) therapeutic hypotheses to modulate plasticity in the clinic.

Spatial transcriptomic analysis drives PET imaging of tight junction protein expression in pancreatic cancer theranostics

We apply spatial transcriptomics and proteomics to select pancreatic cancer surface receptor targets for molecular imaging and theranostics using an approach that can be applied to many cancers. Selected cancer surfaceome epithelial markers were spatially correlated and provided specific cancer localization, whereas the spatial correlation between cancer markers and immune- cell or fibroblast markers was low. While molecular imaging of cancer-associated fibroblasts and integrins has been proposed for pancreatic cancer, our data point to the tight junction protein claudin-4 as a theranostic target. Claudin-4 expression increased ∼16 fold in cancer as compared with normal pancreas, and the tight junction localization conferred low background for imaging in normal tissue. We developed a peptide-based molecular imaging agent targeted to claudin-4 with accumulation to ∼25% injected activity per cc (IA/cc) in metastases and ∼18% IA/cc in tumors. Our work motivates a new approach for data-driven selection of molecular targets.

Tumor immune microenvironment-based therapies in pancreatic ductal adenocarcinoma: time to update the concept

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal solid tumors. The tumor immune microenvironment (TIME) formed by interactions among cancer cells, immune cells, cancer-associated fibroblasts (CAF), and extracellular matrix (ECM) components drives PDAC in a more immunosuppressive direction: this is a major cause of therapy resistance and poor prognosis. In recent years, research has advanced our understanding of the signaling mechanism by which TIME components interact with the tumor and the evolution of immunophenotyping. Through revolutionary technologies such as single-cell sequencing, we have gone from simply classifying PDACs as "cold" and "hot" to a more comprehensive approach of immunophenotyping that considers all the cells and matrix components. This is key to improving the clinical efficacy of PDAC treatments. In this review, we elaborate on various TIME components in PDAC, the signaling mechanisms underlying their interactions, and the latest research into PDAC immunophenotyping. A deep understanding of these network interactions will contribute to the effective combination of TIME-based therapeutic approaches, such as immune checkpoint inhibitors (ICI), adoptive cell therapy, therapies targeting myeloid cells, CAF reprogramming, and stromal normalization. By selecting the appropriate integrated therapies based on precise immunophenotyping, significant advances in the future treatment of PDAC are possible.

Combining the Tyrosine Kinase Inhibitor Cabozantinib and the mTORC1/2 Inhibitor Sapanisertib Blocks ERK Pathway Activity and Suppresses Tumor Growth in Renal Cell Carcinoma

Current treatment approaches for renal cell carcinoma (RCC) face challenges in achieving durable tumor responses due to tumor heterogeneity and drug resistance. Combination therapies that leverage tumor molecular profiles could offer an avenue for enhancing treatment efficacy and addressing the limitations of current therapies. To identify effective strategies for treating RCC, we selected ten drugs guided by tumor biology to test in six RCC patient-derived xenograft (PDX) models. The multitargeted tyrosine kinase inhibitor (TKI) cabozantinib and mTORC1/2 inhibitor sapanisertib emerged as the most effective drugs, particularly when combined. The combination demonstrated favorable tolerability and inhibited tumor growth or induced tumor regression in all models, including two from patients who experienced treatment failure with FDA-approved TKI and immunotherapy combinations. In cabozantinib-treated samples, imaging analysis revealed a significant reduction in vascular density, and single-nucleus RNA sequencing (snRNA-seq) analysis indicated a decreased proportion of endothelial cells in the tumors. SnRNA-seq data further identified a tumor subpopulation enriched with cell-cycle activity that exhibited heightened sensitivity to the cabozantinib and sapanisertib combination. Conversely, activation of the epithelial-mesenchymal transition pathway, detected at the protein level, was associated with drug resistance in residual tumors following combination treatment. The combination effectively restrained ERK phosphorylation and reduced expression of ERK downstream transcription factors and their target genes implicated in cell-cycle control and apoptosis. This study highlights the potential of the cabozantinib plus sapanisertib combination as a promising treatment approach for patients with RCC, particularly those whose tumors progressed on immune checkpoint inhibitors and other TKIs.

SIGNIFICANCE

The molecular-guided therapeutic strategy of combining cabozantinib and sapanisertib restrains ERK activity to effectively suppress growth of renal cell carcinomas, including those unresponsive to immune checkpoint inhibitors.

A Mutation-driven oncofetal regression fuels phenotypic plasticity in colorectal cancer

Targeting cancer stem cells (CSCs) is crucial for effective cancer treatment 1 . However, the molecular mechanisms underlying resistance to LGR5 + CSCs depletion in colorectal cancer (CRC) 2,3 remain largely elusive. Here, we unveil the existence of a primitive cell state dubbed the oncofetal (OnF) state, which works in tandem with the LGR5 + stem cells (SCs) to fuel tumor evolution in CRC. OnF cells emerge early during intestinal tumorigenesis and exhibit features of lineage plasticity. Normally suppressed by the Retinoid X Receptor (RXR) in mature SCs, the OnF program is triggered by genetic deletion of the gatekeeper APC. We demonstrate that diminished RXR activity unlocks an epigenetic circuity governed by the cooperative action of YAP and AP1, leading to OnF reprogramming. This high-plasticity state is inherently resistant to conventional chemotherapies and its adoption by LGR5 + CSCs enables them to enter a drug-tolerant state. Furthermore, through phenotypic tracing and ablation experiments, we uncover a functional redundancy between the OnF and stem cell (SC) states and show that targeting both cellular states is essential for sustained tumor regression in vivo . Collectively, these findings establish a mechanistic foundation for developing effective combination therapies with enduring impact on CRC treatment.

Single-cell sequencing in pancreatic cancer research: A deeper understanding of heterogeneity and therapy

Pancreatic cancer, including pancreatic ductal adenocarcinomas (PDACs), is a malignant tumor with characteristics of tumor-stroma interactions. Patients often have a poor prognosis and a poor long-term survival rate. In recent years, rapidly-developing single-cell sequencing techniques have been used to analyze cell populations at a single-cell resolution, so that it is now possible to have a more in-depth and clearer understanding of the genetic composition of pancreatic cancer. In this review, we provide an overview of the current single-cell sequencing techniques and their applications in the exploration of intratumoral heterogeneity, the tumor microenvironment, therapy resistance, and novel treatments. Our hope is to provide new insight into the potential of precision therapy, which will perhaps one day lead to significant advances in PDAC treatment.

Single-cell transcriptomics reveals long noncoding RNAs associated with tumor biology and the microenvironment in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is highly heterogeneous and lethal. Long noncoding RNAs (lncRNAs) are an important class of genes regulating tumorigenesis and progression. Prior bulk transcriptomic studies in PDAC have revealed the dysregulation of lncRNAs but lack single-cell resolution to distinguish lncRNAs in tumor-intrinsic biology and the tumor microenvironment (TME). We analyzed single-cell transcriptome data from 73 multiregion samples in 21 PDAC patients to evaluate lncRNAs associated with intratumoral heterogeneity and the TME in PDAC. We found 111 cell-specific lncRNAs that reflected tumor, immune and stromal cell contributions, associated with outcomes, and validated across orthogonal datasets. Single-cell analysis of tumor cells revealed lncRNAs associated with TP53 mutations and FOLFIRINOX treatment that were obscured in bulk tumor analysis. Lastly, tumor subcluster analysis revealed widespread intratumor heterogeneity and intratumoral lncRNAs associated with cancer hallmarks and tumor processes such as angiogenesis, epithelial-mesenchymal transition, metabolism and immune signaling. Intratumoral subclusters and lncRNAs were validated across six datasets and showed clinically relevant associations with patient outcomes. Our study provides the first comprehensive assessment of the lncRNA landscape in PDAC using single-cell transcriptomic data and can serve as a resource, PDACLncDB (accessible at https://www.maherlab.com/pdaclncdb-overview), to guide future functional studies.

Improving the prognosis of pancreatic cancer: insights from epidemiology, genomic alterations, and therapeutic challenges

Pancreatic cancer, notorious for its late diagnosis and aggressive progression, poses a substantial challenge owing to scarce treatment alternatives. This review endeavors to furnish a holistic insight into pancreatic cancer, encompassing its epidemiology, genomic characterization, risk factors, diagnosis, therapeutic strategies, and treatment resistance mechanisms. We delve into identifying risk factors, including genetic predisposition and environmental exposures, and explore recent research advancements in precursor lesions and molecular subtypes of pancreatic cancer. Additionally, we highlight the development and application of multi-omics approaches in pancreatic cancer research and discuss the latest combinations of pancreatic cancer biomarkers and their efficacy. We also dissect the primary mechanisms underlying treatment resistance in this malignancy, illustrating the latest therapeutic options and advancements in the field. Conclusively, we accentuate the urgent demand for more extensive research to enhance the prognosis for pancreatic cancer patients.

Differential spatial distribution of HNF4α isoforms during dysplastic progression of intraductal papillary mucinous neoplasms of the pancreas

Hepatocyte Nuclear Factor 4-alpha (HNF4α) comprises a nuclear receptor superfamily of ligand-dependent transcription factors that yields twelve isoforms in humans, classified into promoters P1 or P2-associated groups with specific functions. Alterations in HNF4α isoforms have been associated with tumorigenesis. However, the distribution of its isoforms during progression from dysplasia to malignancy has not been studied, nor has it yet been studied in intraductal papillary mucinous neoplasms, where both malignant and pre-malignant forms are routinely clinically identified. We examined the expression patterns of pan-promoter, P1-specific, and P2-specific isoform groups in normal pancreatic components and IPMNs. Pan-promoter, P1 and P2 nuclear expression were weakly positive in normal pancreatic components. Nuclear expression for all isoform groups was increased in low-grade IPMN, high-grade IPMN, and well-differentiated invasive adenocarcinoma. Poorly differentiated invasive components in IPMNs showed loss of all forms of HNF4α. Pan-promoter, and P1-specific HNF4α expression showed shifts in subnuclear and sub-anatomical distribution in IPMN, whereas P2 expression was consistently nuclear. Tumor cells with high-grade dysplasia at the basal interface with the stroma showed reduced expression of P1, while P2 was equally expressed in both components. Additional functional studies are warranted to further explore the mechanisms underlying the spatial and differential distribution of HNF4α isoforms in IPMNs.

Epigenetic regulation during cancer transitions across 11 tumour types

Chromatin accessibility is essential in regulating gene expression and cellular identity, and alterations in accessibility have been implicated in driving cancer initiation, progression and metastasis1-4. Although the genetic contributions to oncogenic transitions have been investigated, epigenetic drivers remain less understood. Here we constructed a pan-cancer epigenetic and transcriptomic atlas using single-nucleus chromatin accessibility data (using single-nucleus assay for transposase-accessible chromatin) from 225 samples and matched single-cell or single-nucleus RNA-sequencing expression data from 206 samples. With over 1 million cells from each platform analysed through the enrichment of accessible chromatin regions, transcription factor motifs and regulons, we identified epigenetic drivers associated with cancer transitions. Some epigenetic drivers appeared in multiple cancers (for example, regulatory regions of ABCC1 and VEGFA; GATA6 and FOX-family motifs), whereas others were cancer specific (for example, regulatory regions of FGF19, ASAP2 and EN1, and the PBX3 motif). Among epigenetically altered pathways, TP53, hypoxia and TNF signalling were linked to cancer initiation, whereas oestrogen response, epithelial-mesenchymal transition and apical junction were tied to metastatic transition. Furthermore, we revealed a marked correlation between enhancer accessibility and gene expression and uncovered cooperation between epigenetic and genetic drivers. This atlas provides a foundation for further investigation of epigenetic dynamics in cancer transitions.

Emerging Prognostic and Predictive Factors in Pancreatic Cancer

Pancreatic cancer is a lethal disease with increasing incidence and high recurrence rates and is currently resistant to conventional therapies. Moreover, it displays extensive morphologic and molecular intratumoral and intertumoral heterogeneity and a mostly low mutational burden, failing to induce significant antitumor immunity. Thus, immunotherapy has shown limited effect in pancreatic cancer, except in rare tumors with microsatellite instability, constituting <1% of the cases. Currently, new methods, including single-cell and single-nucleus RNA sequencing, have refined and expanded the 2-group molecular classification based on bulk RNA sequencing (classical and basal-like subtypes), identifying hybrid forms and providing us with a comprehensive map of the tumor cell subsets that drive gene expression during tumor evolution, simultaneously giving us insight into therapy resistance and metastasis. Additionally, deeper profiling of the tumor microenvironment of pancreatic cancer by using spatial analyses and multiplex imaging techniques has improved our understanding of the heterogeneous distribution of both adaptive and innate immune components with their protumor and antitumor properties. By integrating host immune response patterns, as defined by spatial transcriptomic and proteomic analysis and multiplex immunofluorescence, with molecular and morphologic features of the tumors, we can increasingly understand the genetic, immunologic, and morphologic background of pancreatic cancer and recognize the potential predictors for different treatment modalities.

High-dimensional deconstruction of pancreatic cancer identifies tumor microenvironmental and developmental stemness features that predict survival

Numerous cell states are known to comprise the pancreatic ductal adenocarcinoma (PDAC) tumor microenvironment (TME). However, the developmental stemness and co-occurrence of these cell states remain poorly defined. Here, we performed single-cell RNA sequencing (scRNA-seq) on a cohort of treatment-naive PDAC time-of-diagnosis endoscopic ultrasound-guided fine needle biopsy (EUS-FNB) samples (n = 25). We then combined these samples with surgical resection (n = 6) and publicly available samples to increase statistical power (n = 80). Following annotation into 25 distinct cell states, cells were scored for developmental stemness, and a customized version of the Ecotyper tool was used to identify communities of co-occurring cell states in bulk RNA-seq samples (n = 268). We discovered a tumor microenvironmental community comprised of aggressive basal-like malignant cells, tumor-promoting SPP1+ macrophages, and myofibroblastic cancer-associated fibroblasts associated with especially poor prognosis. We also found a developmental stemness continuum with implications for survival that is present in both malignant cells and cancer-associated fibroblasts (CAFs). We further demonstrated that high-dimensional analyses predictive of survival are feasible using standard-of-care, time-of-diagnosis EUS-FNB specimens. In summary, we identified tumor microenvironmental and developmental stemness characteristics from a high-dimensional gene expression analysis of PDAC using human tissue specimens, including time-of-diagnosis EUS-FNB samples. These reveal new connections between tumor microenvironmental composition, CAF and malignant cell stemness, and patient survival that could lead to better upfront risk stratification and more personalized upfront clinical decision-making.

Spatially Resolved Multi-Omics Single-Cell Analyses Inform Mechanisms of Immune Dysfunction in Pancreatic Cancer

BACKGROUND & AIMS

As pancreatic ductal adenocarcinoma (PDAC) continues to be recalcitrant to therapeutic interventions, including poor response to immunotherapy, albeit effective in other solid malignancies, a more nuanced understanding of the immune microenvironment in PDAC is urgently needed. We aimed to unveil a detailed view of the immune micromilieu in PDAC using a spatially resolved multimodal single-cell approach.

METHODS

We applied single-cell RNA sequencing, spatial transcriptomics, multiplex immunohistochemistry, and mass cytometry to profile the immune compartment in treatment-naïve PDAC tumors and matched adjacent normal pancreatic tissue, as well as in the systemic circulation. We determined prognostic associations of immune signatures and performed a meta-analysis of the immune microenvironment in PDAC and lung adenocarcinoma on single-cell level.

RESULTS

We provided a spatially resolved fine map of the immune landscape in PDAC. We substantiated the exhausted phenotype of CD8 T cells and immunosuppressive features of myeloid cells, and highlighted immune subsets with potentially underappreciated roles in PDAC that diverged from immune populations within adjacent normal areas, particularly CD4 T cell subsets and natural killer T cells that are terminally exhausted and acquire a regulatory phenotype. Differential analysis of immune phenotypes in PDAC and lung adenocarcinoma revealed the presence of extraordinarily immunosuppressive subtypes in PDAC, along with a distinctive immune checkpoint composition.

CONCLUSIONS

Our study sheds light on the multilayered immune dysfunction in PDAC and presents a holistic view of the immune landscape in PDAC and lung adenocarcinoma, providing a comprehensive resource for functional studies and the exploration of therapeutically actionable targets in PDAC.

Single-cell dissection of tumor microenvironmental response and resistance to cancer therapy

Cancer treatment strategies have evolved significantly over the years, with chemotherapy, targeted therapy, and immunotherapy as major pillars. Each modality leads to unique treatment outcomes by interacting with the tumor microenvironment (TME), which imposes a fundamental selective pressure on cancer progression. The advent of single-cell profiling technologies has revolutionized our understanding of the intricate and heterogeneous nature of the TME at an unprecedented resolution. This review delves into the commonalities and differential manifestations of how cancer therapies reshape the microenvironment in diverse cancer types. We highlight how groundbreaking immune checkpoint blockade (ICB) strategies alone or in combination with tumor-targeting treatments are endowed with comprehensive mechanistic insights when decoded at the single-cell level, aiming to drive forward future research directions on personalized treatments.

Integrative multi-omic cancer profiling reveals DNA methylation patterns associated with therapeutic vulnerability and cell-of-origin

DNA methylation plays a critical role in establishing and maintaining cellular identity. However, it is frequently dysregulated during tumor development and is closely intertwined with other genetic alterations. Here, we leveraged multi-omic profiling of 687 tumors and matched non-involved adjacent tissues from the kidney, brain, pancreas, lung, head and neck, and endometrium to identify aberrant methylation associated with RNA and protein abundance changes and build a Pan-Cancer catalog. We uncovered lineage-specific epigenetic drivers including hypomethylated FGFR2 in endometrial cancer. We showed that hypermethylated STAT5A is associated with pervasive regulon downregulation and immune cell depletion, suggesting that epigenetic regulation of STAT5A expression constitutes a molecular switch for immunosuppression in squamous tumors. We further demonstrated that methylation subtype-enrichment information can explain cell-of-origin, intra-tumor heterogeneity, and tumor phenotypes. Overall, we identified cis-acting DNA methylation events that drive transcriptional and translational changes, shedding light on the tumor's epigenetic landscape and the role of its cell-of-origin.

Fibrosis induced by resident macrophages has divergent roles in pancreas inflammatory injury and PDAC

Tissue-resident macrophages (TRMs) are long-lived cells that maintain locally and can be phenotypically distinct from monocyte-derived macrophages. Whether TRMs and monocyte-derived macrophages have district roles under differing pathologies is not understood. Here, we showed that a substantial portion of the macrophages that accumulated during pancreatitis and pancreatic cancer in mice had expanded from TRMs. Pancreas TRMs had an extracellular matrix remodeling phenotype that was important for maintaining tissue homeostasis during inflammation. Loss of TRMs led to exacerbation of severe pancreatitis and death, due to impaired acinar cell survival and recovery. During pancreatitis, TRMs elicited protective effects by triggering the accumulation and activation of fibroblasts, which was necessary for initiating fibrosis as a wound healing response. The same TRM-driven fibrosis, however, drove pancreas cancer pathogenesis and progression. Together, these findings indicate that TRMs play divergent roles in the pathogenesis of pancreatitis and cancer through regulation of stromagenesis.

Pan-cancer proteogenomics connects oncogenic drivers to functional states

Cancer driver events refer to key genetic aberrations that drive oncogenesis; however, their exact molecular mechanisms remain insufficiently understood. Here, our multi-omics pan-cancer analysis uncovers insights into the impacts of cancer drivers by identifying their significant cis-effects and distal trans-effects quantified at the RNA, protein, and phosphoprotein levels. Salient observations include the association of point mutations and copy-number alterations with the rewiring of protein interaction networks, and notably, most cancer genes converge toward similar molecular states denoted by sequence-based kinase activity profiles. A correlation between predicted neoantigen burden and measured T cell infiltration suggests potential vulnerabilities for immunotherapies. Patterns of cancer hallmarks vary by polygenic protein abundance ranging from uniform to heterogeneous. Overall, our work demonstrates the value of comprehensive proteogenomics in understanding the functional states of oncogenic drivers and their links to cancer development, surpassing the limitations of studying individual cancer types.

The spatial coexistence of TIGIT/CD155 defines poorer survival and resistance to adjuvant chemotherapy in pancreatic ductal adenocarcinoma

Background: Targeting emerging T cell immunoreceptor with immunoglobulin and ITIM domain (TIGIT)/CD155 axis shows promise for restoring anti-tumor immunity, but its immune phenotypes and prognostic significance in a large cohort of pancreatic ductal adenocarcinoma (PDAC) are limited. Methods: Three seven-color multispectral panels were rationally designed to investigate the protein expression, immune-microenvironmental feature, prognostic value, and the response to adjuvant chemotherapy of TIGIT/CD155 in 272 PDAC specimens using multiplex immunohistochemistry. Results: We revealed low immunogenicity and high heterogeneity of the PDAC immune microenvironment featured by abundant CD3+ T cells and CD68+ macrophages and low infiltration of activated cytotoxic T lymphocytes. TIGIT and CD155 were highly expressed in PDAC tissues compared to paracancerous tissues. Tumor-infiltrating lymphocytes expressing TIGIT were correlated with high densities of CD45RO+ T cells; TIGTI+CD8+ T cells were associated with high infiltration of CD3+CD45RO+FOXP3+. CD155+CK+ were significantly related to high densities of CD3+ and CD3+CD8+CD45RO+ T cells. High positive rates for TIGIT in TCs, CD8+ T cells, and CD155 in macrophages were correlated with poor progression-free and disease-specific survival, respectively, and their clinical significance was correlated with PD-L1 status. Notably, spatial co-existence of TIGIT+CK+ or TIGIT+CD8+ and CD155+CD68+ indicated poor survival and resistance to adjuvant chemotherapy response in patients with PDAC. Conclusion: Our findings suggest that targeting TIGIT/CD155 immunosuppressive axis may guide patient stratification and improve the clinical outcome of PDAC.

Therapy-associated remodeling of pancreatic cancer revealed by single-cell spatial transcriptomics and optimal transport analysis

In combination with cell intrinsic properties, interactions in the tumor microenvironment modulate therapeutic response. We leveraged high-plex single-cell spatial transcriptomics to dissect the remodeling of multicellular neighborhoods and cell-cell interactions in human pancreatic cancer associated with specific malignant subtypes and neoadjuvant chemotherapy/radiotherapy. We developed Spatially Constrained Optimal Transport Interaction Analysis (SCOTIA), an optimal transport model with a cost function that includes both spatial distance and ligand-receptor gene expression. Our results uncovered a marked change in ligand-receptor interactions between cancer-associated fibroblasts and malignant cells in response to treatment, which was supported by orthogonal datasets, including an ex vivo tumoroid co-culture system. Overall, this study demonstrates that characterization of the tumor microenvironment using high-plex single-cell spatial transcriptomics allows for identification of molecular interactions that may play a role in the emergence of chemoresistance and establishes a translational spatial biology paradigm that can be broadly applied to other malignancies, diseases, and treatments.

Single-cell omics: a new perspective for early detection of pancreatic cancer?

Pancreatic cancer is one of the most lethal cancers, mostly due to late diagnosis and limited treatment options. Early detection of pancreatic cancer in high-risk populations bears the potential to greatly improve outcomes, but current screening approaches remain of limited value despite recent technological advances. This review explores the possible advantages of liquid biopsies for this application, particularly focusing on circulating tumour cells (CTCs) and their subsequent single-cell omics analysis. Originating from both primary and metastatic tumour sites, CTCs provide important information for diagnosis, prognosis and tailoring of treatment strategies. Notably, CTCs have even been detected in the blood of subjects with pancreatic precursor lesions, suggesting their suitability as a non-invasive tool for the early detection of malignant transformation in the pancreas. As intact cells, CTCs offer comprehensive genomic, transcriptomic, epigenetic and proteomic information that can be explored using rapidly developing techniques for analysing individual cells at the molecular level. Studying CTCs during serial sampling and at single-cell resolution will help to dissect tumour heterogeneity for individual patients and among different patients, providing new insights into cancer evolution during disease progression and in response to treatment. Using CTCs for non-invasive tracking of cancer features, including stemness, metastatic potential and expression of immune targets, provides important and readily accessible molecular insights. Finally, the emerging technology of ex vivo culturing of CTCs could create new opportunities to study the functionality of individual cancers at any stage and develop personalised and more effective treatment approaches for this lethal disease.

Acinar-to-Ductal Metaplasia (ADM): On the Road to Pancreatic Intraepithelial Neoplasia (PanIN) and Pancreatic Cancer

Adult pancreatic acinar cells show high plasticity allowing them to change in their differentiation commitment. Pancreatic acinar-to-ductal metaplasia (ADM) is a cellular process in which the differentiated pancreatic acinar cells transform into duct-like cells. This process can occur as a result of cellular injury or inflammation in the pancreas. While ADM is a reversible process allowing pancreatic acinar regeneration, persistent inflammation or injury can lead to the development of pancreatic intraepithelial neoplasia (PanIN), which is a common precancerous lesion that precedes pancreatic ductal adenocarcinoma (PDAC). Several factors can contribute to the development of ADM and PanIN, including environmental factors such as obesity, chronic inflammation and genetic mutations. ADM is driven by extrinsic and intrinsic signaling. Here, we review the current knowledge on the cellular and molecular biology of ADM. Understanding the cellular and molecular mechanisms underlying ADM is critical for the development of new therapeutic strategies for pancreatitis and PDAC. Identifying the intermediate states and key molecules that regulate ADM initiation, maintenance and progression may help the development of novel preventive strategies for PDAC.