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

Single-cell multi-omics in the study of digestive system cancers

Digestive system cancers are prevalent diseases with a high mortality rate, posing a significant threat to public health and economic burden. The diagnosis and treatment of digestive system cancer confront conventional cancer problems, such as tumor heterogeneity and drug resistance. Single-cell sequencing (SCS) emerged at times required and has developed from single-cell RNA-seq (scRNA-seq) to the single-cell multi-omics era represented by single-cell spatial transcriptomics (ST). This article comprehensively reviews the advances of single-cell omics technology in the study of digestive system tumors. While analyzing and summarizing the research cases, vital details on the sequencing platform, sample information, sampling method, and key findings are provided. Meanwhile, we summarize the commonly used SCS platforms and their features, as well as the advantages of multi-omics technologies in combination. Finally, the development trends and prospects of the application of single-cell multi-omics technology in digestive system cancer research are prospected.

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.

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?

Current and future immunotherapeutic approaches in pancreatic cancer treatment

Pancreatic cancer is a major cause of cancer-related death, but despondently, the outlook and prognosis for this resistant type of tumor have remained grim for a long time. Currently, it is extremely challenging to prevent or detect it early enough for effective treatment because patients rarely exhibit symptoms and there are no reliable indicators for detection. Most patients have advanced or spreading cancer that is difficult to treat, and treatments like chemotherapy and radiotherapy can only slightly prolong their life by a few months. Immunotherapy has revolutionized the treatment of pancreatic cancer, yet its effectiveness is limited by the tumor's immunosuppressive and hard-to-reach microenvironment. First, this article explains the immunosuppressive microenvironment of pancreatic cancer and highlights a wide range of immunotherapy options, including therapies involving oncolytic viruses, modified T cells (T-cell receptor [TCR]-engineered and chimeric antigen receptor [CAR] T-cell therapy), CAR natural killer cell therapy, cytokine-induced killer cells, immune checkpoint inhibitors, immunomodulators, cancer vaccines, and strategies targeting myeloid cells in the context of contemporary knowledge and future trends. Lastly, it discusses the main challenges ahead of pancreatic cancer immunotherapy.

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.

Pancreatic cancer environment: from patient-derived models to single-cell omics

Pancreatic cancer (PC) is a highly malignant cancer characterized by poor prognosis, high heterogeneity, and intricate heterocellular systems. Selecting an appropriate experimental model for studying its progression and treatment is crucial. Patient-derived models provide a more accurate representation of tumor heterogeneity and complexity compared to cell line-derived models. This review initially presents relevant patient-derived models, including patient-derived xenografts (PDXs), patient-derived organoids (PDOs), and patient-derived explants (PDEs), which are essential for studying cell communication and pancreatic cancer progression. We have emphasized the utilization of these models in comprehending intricate intercellular communication, drug responsiveness, mechanisms underlying tumor growth, expediting drug discovery, and enabling personalized medical approaches. Additionally, we have comprehensively summarized single-cell analyses of these models to enhance comprehension of intercellular communication among tumor cells, drug response mechanisms, and individual patient sensitivities.

Genetically predicted blood metabolites mediate the association between circulating immune cells and pancreatic cancer: A Mendelian randomization study

BACKGROUND

Pancreatic cancer is characterized by metabolic dysregulation and unique immunological profiles. Nevertheless, the comprehensive understanding of immune and metabolic dysregulation of pancreatic cancer remains unclear. In the present study, we aimed to investigate the causal relationship of circulating immune cells and pancreatic cancer and identify the blood metabolites as potential mediators.

METHODS

The exposure and outcome genome-wide association studies (GWAS) data used in the present study were obtained from the GWAS open-access database (https://gwas.mrcieu.ac.uk). The study used 731 circulating immune cell features, 1400 types of blood metabolites and pancreatic cancer from GWAS. We then performed bidirectional Mendelian randomization (MR) analyses to explore the causal relationships between the circulating immune cells and pancreatic cancer, and two-step MR to discover potential mediating blood metabolites in this process. All statistical analyses were performed in R software. The STROBE-MR (i.e. Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization) checklist for the reporting of MR studies was also used.

RESULTS

MR analysis identified seven types of circulating immune cells causally associated with pancreatic cancer. Furthermore, there was no strong evidence that genetically predicted pancreatic cancer had an effect on these seven types of circulating immune cells. Further two-step MR analysis found 10 types of blood metabolites were causally associated with pancreatic cancer and the associations between circulating CD39+CD8+ T cells and pancreatic cancer were mediated by blood orotates with proportions of 5.18% (p = 0.016).

CONCLUSIONS

The present study provides evidence supporting the causal relationships between various circulating immune cells, especially CD39+CD8+ T cells, and pancreatic cancer, with a potential effect mediated by blood orotates. Further research is needed on additional risk factors as potential mediators and establish a comprehensive immunity-metabolism network in pancreatic cancer.

Identifying the Spatial Architecture That Restricts the Proximity of CD8+ T Cells to Tumor Cells in Pancreatic Ductal Adenocarcinoma

The anti-tumor function of CD8+ T cells is dependent on their proximity to tumor cells. Current studies have focused on the infiltration level of CD8+ T cells in the tumor microenvironment, while further spatial information, such as spatial localization and inter-cellular communication, have not been defined. In this study, co-detection by indexing (CODEX) was designed to characterize PDAC tissue regions with seven protein markers in order to identify the spatial architecture that regulates CD8+ T cells in human pancreatic ductal adenocarcinoma (PDAC). The cellular neighborhood algorithm was used to identify a total of six conserved and distinct cellular neighborhoods. Among these, one unique spatial architecture of CD8+ T and CD4+ T cell-enriched neighborhoods enriched the majority of CD8+ T cells, but heralded a poor prognosis. The proximity analysis revealed that the CD8+ T cells in this spatial architecture were significantly closer to themselves and the CD4+ T cells than to the tumor cells. Collectively, we identified a unique spatial architecture that restricted the proximity of CD8+ T cells to tumor cells in the tumor microenvironment, indicating a novel immune evasion mechanism of pancreatic ductal adenocarcinoma in a topologically regulated manner and providing new insights into the biology of PDAC.

The immunological landscape in pancreatic ductal adenocarcinoma and overcoming resistance to immunotherapy

Pancreatic ductal adenocarcinoma is associated with a poor prognosis and there are few treatment options. The development of immunotherapy in pancreatic ductal adenocarcinoma has been difficult, and immune checkpoint inhibitors are only effective in a very small subset of patients. Most obstacles for treatment have been related to intertumoural and intratumoural heterogeneity, the composition of tumour stroma, and crosstalk with cancer cells. Improved molecular characterisation of pancreatic ductal adenocarcinoma and a better understanding of its microenvironment have paved the way for novel immunotherapy strategies, including the identification of predictive biomarkers, the development of rational combinations to optimise effectiveness, and the targeting of new mechanisms. Future immunotherapy strategies should consider individual characteristics to move beyond the traditional immune targets and circumvent the resistance to therapies that have been developed so far.

Local Delivery of SBRT and IL12 by mRNA Technology Overcomes Immunosuppressive Barriers to Eliminate Pancreatic Cancer

The immunosuppressive milieu in pancreatic cancer (PC) is a significant hurdle to treatments, resulting in survival statistics that have barely changed in 5 decades. Here we present a combination treatment consisting of stereotactic body radiation therapy (SBRT) and IL-12 mRNA lipid nanoparticles delivered directly to pancreatic murine tumors. This treatment was effective against primary and metastatic models, achieving cures in both settings. IL-12 protein concentrations were transient and localized primarily to the tumor. Depleting CD4 and CD8 T cells abrogated treatment efficacy, confirming they were essential to treatment response. Single cell RNA sequencing from SBRT/IL-12 mRNA treated tumors demonstrated not only a complete loss of T cell exhaustion, but also an abundance of highly proliferative and effector T cell subtypes. SBRT elicited T cell receptor clonal expansion, whereas IL-12 licensed these cells with effector function. This is the first report demonstrating the utility of SBRT and IL-12 mRNA in PC.

Statement of significance

This study demonstrates the use of a novel combination treatment consisting of radiation and immunotherapy in murine pancreatic tumors. This treatment could effectively treat local and metastatic disease, suggesting it may have the potential to treat a cancer that has not seen a meaningful increase in survival in 5 decades.