Single-nucleus and spatial transcriptome profiling of pancreatic cancer identifies multicellular dynamics associated with neoadjuvant treatment

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.

Spatial Biology of Breast Cancer

Spatial findings have shaped on our understanding of breast cancer. In this review, we discuss how spatial methods, including spatial transcriptomics and proteomics and the resultant understanding of spatial relationships, have contributed to concepts regarding cancer progression and treatment. In addition to discussing traditional approaches, we examine how emerging multiplex imaging technologies have contributed to the field and how they might influence future research.

Early Immune Remodeling Steers Clinical Response to First-Line Chemoimmunotherapy in Advanced Gastric Cancer

Adding anti-programmed cell death protein 1 (anti-PD-1) to 5-fluorouracil (5-FU)/platinum improves survival in some advanced gastroesophageal adenocarcinomas (GEA). To understand the effects of chemotherapy and immunotherapy, we conducted a phase II first-line trial (n = 47) sequentially adding pembrolizumab to 5-FU/platinum in advanced GEA. Using serial biopsy of the primary tumor at baseline, after one cycle of 5-FU/platinum, and after the addition of pembrolizumab, we transcriptionally profiled 358,067 single cells to identify evolving multicellular tumor microenvironment (TME) networks. Chemotherapy induced early on-treatment multicellular hubs with tumor-reactive T-cell and M1-like macrophage interactions in slow progressors. Faster progression featured increased MUC5A and MSLN containing treatment resistance programs in tumor cells and M2-like macrophages with immunosuppressive stromal interactions. After pembrolizumab, we observed increased CD8 T-cell infiltration and development of an immunity hub involving tumor-reactive CXCL13 T-cell program and epithelial interferon-stimulated gene programs. Strategies to drive increases in antitumor immune hub formation could expand the portion of patients benefiting from anti-PD-1 approaches.

SIGNIFICANCE

The benefit of 5-FU/platinum with anti-PD-1 in first-line advanced gastric cancer is limited to patient subgroups. Using a trial with sequential anti-PD-1, we show coordinated induction of multicellular TME hubs informs the ability of anti-PD-1 to potentiate T cell-driven responses. Differential TME hub development highlights features that underlie clinical outcomes. This article is featured in Selected Articles from This Issue, p. 695.

GATA6 identifies an immune-enriched phenotype linked to favorable outcomes in patients with pancreatic cancer undergoing upfront surgery

This study underscores GATA6's role in distinguishing classical and basal-like pancreatic ductal adenocarcinoma (PDAC) phenotypes. Retrospective studies associate GATA6 immunohistochemistry (IHC) expression with survival outcomes, warranting prospective validation. In a prospective treatment-naive cohort of patients with resected PDAC, GATA6 IHC proves a prognostic discriminator, associating high GATA6 expression with extended survival and the classical PDAC phenotype. However, GATA6's prognostic significance is numerically lower after gemcitabine-based neoadjuvant chemoradiotherapy compared to its significance in patients treated with upfront surgery. Furthermore, GATA6 is implicated in immunomodulation, although a comprehensive investigation of its immunological role is lacking. Treatment-naive PDAC tumors with varying GATA6 expression yield distinct immunological landscapes. Tumors highly expressing GATA6 show reduced infiltration of immunosuppressive regulatory T cells and M2 macrophages but increased infiltration of immune-stimulating, antigen-presenting, and activated T cells. Our findings caution against solely relying on GATA6 for molecular subtyping in clinical trials and open avenues for exploring immune-based combination therapies.

Axon guidance cue SEMA3A promotes the aggressive phenotype of basal-like PDAC

OBJECTIVE

The dysregulation of the axon guidance pathway is common in pancreatic ductal adenocarcinoma (PDAC), yet our understanding of its biological relevance is limited. Here, we investigated the functional role of the axon guidance cue SEMA3A in supporting PDAC progression.

DESIGN

We integrated bulk and single-cell transcriptomic datasets of human PDAC with in situ hybridisation analyses of patients' tissues to evaluate SEMA3A expression in molecular subtypes of PDAC. Gain and loss of function experiments in PDAC cell lines and organoids were performed to dissect how SEMA3A contributes to define a biologically aggressive phenotype.

RESULTS

In PDAC tissues, SEMA3A is expressed by stromal elements and selectively enriched in basal-like/squamous epithelial cells. Accordingly, expression of SEMA3A in PDAC cells is induced by both cell-intrinsic and cell-extrinsic determinants of the basal-like phenotype. In vitro, SEMA3A promotes cell migration as well as anoikis resistance. At the molecular level, these phenotypes are associated with increased focal adhesion kinase signalling through canonical SEMA3A-NRP1 axis. SEMA3A provides mouse PDAC cells with greater metastatic competence and favours intratumoural infiltration of tumour-associated macrophages and reduced density of T cells. Mechanistically, SEMA3A functions as chemoattractant for macrophages and skews their polarisation towards an M2-like phenotype. In SEMA3Ahigh tumours, depletion of macrophages results in greater intratumour infiltration by CD8+T cells and better control of the disease from antitumour treatment.

CONCLUSIONS

Here, we show that SEMA3A is a stress-sensitive locus that promotes the malignant phenotype of basal-like PDAC through both cell-intrinsic and cell-extrinsic mechanisms.

Spatial genomics: mapping human steatotic liver disease

Metabolic dysfunction-associated steatotic liver disease (MASLD, formerly known as non-alcoholic fatty liver disease) is a leading cause of chronic liver disease worldwide. MASLD can progress to metabolic dysfunction-associated steatohepatitis (MASH, formerly known as non-alcoholic steatohepatitis) with subsequent liver cirrhosis and hepatocellular carcinoma formation. The advent of current technologies such as single-cell and single-nuclei RNA sequencing have transformed our understanding of the liver in homeostasis and disease. The next frontier is contextualizing this single-cell information in its native spatial orientation. This understanding will markedly accelerate discovery science in hepatology, resulting in a further step-change in our knowledge of liver biology and pathobiology. In this Review, we discuss up-to-date knowledge of MASLD development and progression and how the burgeoning field of spatial genomics is driving exciting new developments in our understanding of human liver disease pathogenesis and therapeutic target identification.

Tuft cells transdifferentiate to neural-like progenitor cells in the progression of pancreatic cancer

Pancreatic ductal adenocarcinoma (PDA) is partly initiated through the transdifferentiation of acinar cells to metaplastic ducts that act as precursors of neoplasia and cancer. Tuft cells are solitary chemosensory cells not found in the normal pancreas but arise in metaplasia and neoplasia, diminishing as neoplastic lesions progress to carcinoma. Metaplastic tuft cells (mTCs) function to suppress tumor progression through communication with the tumor microenvironment, but their fate during progression is unknown. To determine the fate of mTCs during PDA progression, we have created a lineage tracing model that uses a tamoxifen-inducible tuft-cell specific Pou2f3CreERT/+ driver to induce transgene expression, including the lineage tracer tdTomato or the oncogene Myc. mTC lineage trace models of pancreatic neoplasia and carcinoma were used to follow mTC fate. We found that mTCs, in the carcinoma model, transdifferentiate into neural-like progenitor cells (NRPs), a cell type associated with poor survival in PDA patients. Using conditional knock-out and overexpression systems, we found that Myc activity in mTCs is necessary and sufficient to induce this Tuft-to-Neuroendocrine-Transition (TNT).

Upregulated Matrisomal Proteins and Extracellular Matrix Mechanosignaling Underlie Obesity-Associated Promotion of Pancreatic Ductal Adenocarcinoma

Diet-induced obesity (DIO) promotes pancreatic ductal adenocarcinoma (PDAC) in mice expressing KRasG12D in the pancreas (KC mice), but the precise mechanisms remain unclear. Here, we performed multiplex quantitative proteomic and phosphoproteomic analysis by liquid chromatography-tandem mass spectrometry and further bioinformatic and spatial analysis of pancreas tissues from control-fed versus DIO KC mice after 3, 6, and 9 months. Normal pancreatic parenchyma and associated proteins were steadily eliminated and the novel proteins, phosphoproteins, and signaling pathways associated with PDAC tumorigenesis increased until 6 months, when most males exhibited cancer, but females did not. Differentially expressed proteins and phosphoproteins induced by DIO revealed the crucial functional role of matrisomal proteins, which implies the roles of upstream regulation by TGFβ, extracellular matrix-receptor signaling to downstream PI3K-Akt-mTOR-, MAPK-, and Yap/Taz activation, and crucial effects in the tumor microenvironment such as metabolic alterations and signaling crosstalk between immune cells, cancer-associated fibroblasts (CAFs), and tumor cells. Staining tissues from KC mice localized the expression of several prognostic PDAC biomarkers and elucidated tumorigenic features, such as robust macrophage infiltration, acinar-ductal metaplasia, mucinous PanIN, distinct nonmucinous atypical flat lesions (AFLs) surrounded by smooth muscle actin-positive CAFs, invasive tumors with epithelial-mesenchymal transition arising close to AFLs, and expanding deserted areas by 9 months. We next used Nanostring GeoMX to characterize the early spatial distribution of specific immune cell subtypes in distinct normal, stromal, and PanIN areas. Taken together, these data richly contextualize DIO promotion of Kras-driven PDAC tumorigenesis and provide many novel insights into the signaling pathways and processes involved.

Cancer-associated fibroblasts: a versatile mediator in tumor progression, metastasis, and targeted therapy

Tumor microenvironment (TME) has been demonstrated to play a significant role in tumor initiation, progression, and metastasis. Cancer-associated fibroblasts (CAFs) are the major component of TME and exhibit heterogeneous properties in their communication with tumor cells. This heterogeneity of CAFs can be attributed to various origins, including quiescent fibroblasts, mesenchymal stem cells (MSCs), adipocytes, pericytes, endothelial cells, and mesothelial cells. Moreover, single-cell RNA sequencing has identified diverse phenotypes of CAFs, with myofibroblastic CAFs (myCAFs) and inflammatory CAFs (iCAFs) being the most acknowledged, alongside newly discovered subtypes like antigen-presenting CAFs (apCAFs). Due to these heterogeneities, CAFs exert multiple functions in tumorigenesis, cancer stemness, angiogenesis, immunosuppression, metabolism, and metastasis. As a result, targeted therapies aimed at the TME, particularly focusing on CAFs, are rapidly developing, fueling the promising future of advanced tumor-targeted therapy.

Mapping functional to morphological variation reveals the basis of regional extracellular matrix subversion and nerve invasion in pancreatic cancer

Intratumor morphological heterogeneity of pancreatic ductal adenocarcinoma (PDAC) predicts clinical outcomes but is only partially understood at the molecular level. To elucidate the gene expression programs underpinning intratumor morphological variation in PDAC, we investigated and deconvoluted at single cell level the molecular profiles of histologically distinct clusters of PDAC cells. We identified three major morphological and functional variants that co-exist in varying proportions in all PDACs, display limited genetic diversity, and are associated with a distinct organization of the extracellular matrix: a glandular variant with classical ductal features; a transitional variant displaying abortive ductal structures and mixed endodermal and myofibroblast-like gene expression; and a poorly differentiated variant lacking ductal features and basement membrane, and showing neuronal lineage priming. Ex vivo and in vitro evidence supports the occurrence of dynamic transitions among these variants in part influenced by extracellular matrix composition and stiffness and associated with local, specifically neural, invasion.

Single-cell characterization of infiltrating T cells identifies novel targets for gallbladder cancer immunotherapy

Gallbladder cancer (GBC) is among the most common malignancies of biliary tract system due to its limited treatments. The immunotherapeutic targets for T cells are appealing, however, heterogeneity of T cells hinds its further development. We systematically construct T cell atlas by single-cell RNA sequencing; and utilized the identified gene signatures of high_CNV_T cells to predict molecular subtyping towards personalized therapeutic treatments for GBC. We identified 12 T cell subtypes, where exhausted CD8+ T cells, activated/exhausted CD8+ T cells, and regulatory T cells were predominant in tumors. There appeared to be an inverse relationship between Th17 and Treg populations with Th17 levels significantly reduced, whereas Tregs were concomitantly increased. Furthermore, we first established subtyping criterion to identify three subtypes of GBC based on their pro-tumorigenic microenvironments, e.g., the type 1 group shows more M2 macrophages infiltration, while the type 2 group is infiltrated by highly exhausted CD8+ T cells, B cells and Tregs with suppressive activities. Our study provides valuable insights into T cell heterogeneity and suggests that molecular subtyping based on T cells might provide a potential immunotherapeutic strategy to improve GBC treatment.

The emerging tumor microbe microenvironment: From delineation to multidisciplinary approach-based interventions

Intratumoral microbiota has become research hotspots, and emerges as a non-negligent new component of tumor microenvironments (TME), due to its powerful influence on tumor initiation, metastasis, immunosurveillance and prognosis despite in low-biomass. The accumulations of microbes, and their related components and metabolites within tumor tissues, endow TME with additional pluralistic features which are distinct from the conventional one. Therefore, it's definitely necessary to comprehensively delineate the sophisticated landscapes of tumor microbe microenvironment, as well as their functions and related underlying mechanisms. Herein, in this review, we focused on the fields of tumor microbe microenvironment, including the heterogeneity of intratumor microbiota in different types of tumors, the controversial roles of intratumoral microbiota, the basic features of tumor microbe microenvironment (i.e., pathogen-associated molecular patterns (PAMPs), typical microbial metabolites, autophagy, inflammation, multi-faceted immunomodulation and chemoresistance), as well as the multidisciplinary approach-based intervention of tumor microbiome for cancer therapy by applying wild-type or engineered live microbes, microbiota metabolites, antibiotics, synthetic biology and rationally designed biomaterials. We hope our work will provide valuable insight to deeply understand the interplay of cancer-immune-microbial, and facilitate the development of microbes-based tumor-specific treatments.

Applicability of Spatial Technology in Cancer Research

This review explores spatial mapping technologies in cancer research, highlighting their crucial role in understanding the complexities of the tumor microenvironment (TME). The TME, which is an intricate ecosystem of diverse cell types, has a significant impact on tumor dynamics and treatment outcomes. This review closely examines cutting-edge spatial mapping technologies, categorizing them into capture-, imaging-, and antibody-based approaches. Each technology was scrutinized for its advantages and disadvantages, factoring in aspects such as spatial profiling area, multiplexing capabilities, and resolution. Additionally, we draw attention to the nuanced choices researchers face, with capture-based methods lending themselves to hypothesis generation, and imaging/antibody-based methods that fit neatly into hypothesis testing. Looking ahead, we anticipate a scenario in which multi-omics data are seamlessly integrated, artificial intelligence enhances data analysis, and spatiotemporal profiling opens up new dimensions.

HMGA2 alleviates ferroptosis by promoting GPX4 expression in pancreatic cancer cells

Pancreatic cancer is one of the most malignant tumor types and is characterized by high metastasis ability and a low survival rate. As a chromatin-binding protein, HMGA2 is widely overexpressed and considered an oncogene with various undefined regulatory mechanisms. Herein, we demonstrated that HMGA2 is highly expressed in pancreatic cancer tissues, mainly distributed in epithelial cells, and represents a subtype of high epithelial-mesenchymal transition. Deletion of HMGA2 inhibits tumor malignancy through cell proliferation, metastasis, and xenograft tumor growth in vivo. Moreover, HMGA2 enhanced the cellular redox status by inhibiting reactive oxygen species and promoting glutathione production. Importantly, ferroptotic cell death was significantly ameliorated in cells overexpressing HMGA2. Conversely, HMGA2 deletion exacerbated ferroptosis. Mechanistically, HMGA2 activated GPX4 expression through transcriptional and translational regulation. HMGA2 binds and promotes cis-element modification in the promoter region of the GPX4 gene by enhancing enhancer activity through increased H3K4 methylation and H3K27 acetylation. Furthermore, HMGA2 stimulated GPX4 protein synthesis via the mTORC1-4EBP1 and -S6K signaling axes. The overexpression of HMGA2 alleviated the decrease in GPX4 protein levels resulting from the pharmacologic inhibition of mTORC1. Conversely, compared with the control, HMGA2 deletion more strongly reduced the phosphorylation of 4EBP1 and S6K. A strong positive correlation between HMGA2 and GPX4 expression was confirmed using immunohistochemical staining. We also demonstrated that HMGA2 mitigated the sensitivity of cancer cells to combination treatment with a ferroptosis inducer and mTORC1 inhibition or gemcitabine. In summary, our results revealed a regulatory mechanism by which HMGA2 coordinates GPX4 expression and underscores the potential value of targeting HMGA2 in cancer treatment.

The impacts of active and self-supervised learning on efficient annotation of single-cell expression data

A crucial step in the analysis of single-cell data is annotating cells to cell types and states. While a myriad of approaches has been proposed, manual labeling of cells to create training datasets remains tedious and time-consuming. In the field of machine learning, active and self-supervised learning methods have been proposed to improve the performance of a classifier while reducing both annotation time and label budget. However, the benefits of such strategies for single-cell annotation have yet to be evaluated in realistic settings. Here, we perform a comprehensive benchmarking of active and self-supervised labeling strategies across a range of single-cell technologies and cell type annotation algorithms. We quantify the benefits of active learning and self-supervised strategies in the presence of cell type imbalance and variable similarity. We introduce adaptive reweighting, a heuristic procedure tailored to single-cell data-including a marker-aware version-that shows competitive performance with existing approaches. In addition, we demonstrate that having prior knowledge of cell type markers improves annotation accuracy. Finally, we summarize our findings into a set of recommendations for those implementing cell type annotation procedures or platforms. An R package implementing the heuristic approaches introduced in this work may be found at https://github.com/camlab-bioml/leader .

Pancreatic cancer tumor microenvironment is a major therapeutic barrier and target

Pancreatic Ductal Adenocarcinoma (PDAC) is projected to become the 2nd leading cause of cancer-related deaths in the United States. Limitations in early detection and treatment barriers contribute to the lack of substantial success in the treatment of this challenging-to-treat malignancy. Desmoplasia is the hallmark of PDAC microenvironment that creates a physical and immunologic barrier. Stromal support cells and immunomodulatory cells face aberrant signaling by pancreatic cancer cells that shifts the complex balance of proper repair mechanisms into a state of dysregulation. The product of this dysregulation is the desmoplastic environment that encases the malignant cells leading to a dense, hypoxic environment that promotes further tumorigenesis, provides innate systemic resistance, and suppresses anti-tumor immune invasion. This desmoplastic environment combined with the immunoregulatory events that allow it to persist serve as the primary focus of this review. The physical barrier and immune counterbalance in the tumor microenvironment (TME) make PDAC an immunologically cold tumor. To convert PDAC into an immunologically hot tumor, tumor microenvironment could be considered alongside the tumor cells. We discuss the complex network of microenvironment molecular and cellular composition and explore how they can be targeted to overcome immuno-therapeutic challenges.

Engrailed-1 Promotes Pancreatic Cancer Metastasis

Engrailed-1 (EN1) is a critical homeodomain transcription factor (TF) required for neuronal survival, and EN1 expression has been shown to promote aggressive forms of triple negative breast cancer. Here, it is reported that EN1 is aberrantly expressed in a subset of pancreatic ductal adenocarcinoma (PDA) patients with poor outcomes. EN1 predominantly repressed its target genes through direct binding to gene enhancers and promoters, implicating roles in the activation of MAPK pathways and the acquisition of mesenchymal cell properties. Gain- and loss-of-function experiments demonstrated that EN1 promoted PDA transformation and metastasis in vitro and in vivo. The findings nominate the targeting of EN1 and downstream pathways in aggressive PDA.

Spatial Transcriptomics Suggests That Alterations Occur in the Preneoplastic Breast Microenvironment of BRCA1/2 Mutation Carriers

Breast cancer is the most common cancer in females, affecting one in every eight women and accounting for the majority of cancer-related deaths in women worldwide. Germline mutations in the BRCA1 and BRCA2 genes are significant risk factors for specific subtypes of breast cancer. BRCA1 mutations are associated with basal-like breast cancers, whereas BRCA2 mutations are associated with luminal-like disease. Defects in mammary epithelial cell differentiation have been previously recognized in germline BRCA1/2 mutation carriers even before cancer incidence. However, the underlying mechanism is largely unknown. Here, we employ spatial transcriptomics to investigate defects in mammary epithelial cell differentiation accompanied by distinct microenvironmental alterations in preneoplastic breast tissues from BRCA1/2 mutation carriers and normal breast tissues from noncarrier controls. We uncovered spatially defined receptor-ligand interactions in these tissues for the investigation of autocrine and paracrine signaling. We discovered that β1-integrin-mediated autocrine signaling in BRCA2-deficient mammary epithelial cells may differ from BRCA1-deficient mammary epithelial cells. In addition, we found that the epithelial-to-stromal paracrine signaling in the breast tissues of BRCA1/2 mutation carriers is greater than in control tissues. More integrin-ligand pairs were differentially correlated in BRCA1/2-mutant breast tissues than noncarrier breast tissues with more integrin receptor-expressing stromal cells.

IMPLICATIONS

These results suggest alterations in the communication between mammary epithelial cells and the microenvironment in BRCA1 and BRCA2 mutation carriers, laying the foundation for designing innovative breast cancer chemo-prevention strategies for high-risk patients.

Leveraging spatial omics for the development of precision sarcoma treatments

Sarcomas are rare and heterogeneous cancers that arise from bone or soft tissue, and are the second most prevalent solid cancer in children and adolescents. Owing to the complex nature of pediatric sarcomas, the development of therapeutics for pediatric sarcoma has seen little progress in the past decades. Existing treatments are largely limited to chemotherapy, radiation, and surgery. Limited knowledge of the sarcoma tumor microenvironment (TME) and of well-defined target antigens in the different subtypes necessitates an alternative investigative approach to improve treatments. Recent advances in spatial omics technologies have enabled a more comprehensive study of the TME in multiple cancers. In this opinion article we discuss advances in our understanding of the TME of some cancers enabled by spatial omics technologies, and we explore how these technologies might advance the development of precision treatments for sarcoma, especially pediatric sarcoma.

Pan-Cancer Single-Nucleus Total RNA Sequencing Using snHH-Seq

Tumor heterogeneity and its drivers impair tumor progression and cancer therapy. Single-cell RNA sequencing is used to investigate the heterogeneity of tumor ecosystems. However, most methods of scRNA-seq amplify the termini of polyadenylated transcripts, making it challenging to perform total RNA analysis and somatic mutation analysis.Therefore, a high-throughput and high-sensitivity method called snHH-seq is developed, which combines random primers and a preindex strategy in the droplet microfluidic platform. This innovative method allows for the detection of total RNA in single nuclei from clinically frozen samples. A robust pipeline to facilitate the analysis of full-length RNA-seq data is also established. snHH-seq is applied to more than 730 000 single nuclei from 32 patients with various tumor types. The pan-cancer study enables it to comprehensively profile data on the tumor transcriptome, including expression levels, mutations, splicing patterns, clone dynamics, etc. New malignant cell subclusters and exploring their specific function across cancers are identified. Furthermore, the malignant status of epithelial cells is investigated among different cancer types with respect to mutation and splicing patterns. The ability to detect full-length RNA at the single-nucleus level provides a powerful tool for studying complex biological systems and has broad implications for understanding tumor pathology.

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.

Omics-based molecular classifications empowering in precision oncology

BACKGROUND

In the past decades, cancer enigmatical heterogeneity at distinct expression levels could interpret disparities in therapeutic response and prognosis. It built hindrances to precision medicine, a tactic to tailor customized treatment informed by the tumors' molecular profile. Single-omics analysis dissected the biological features associated with carcinogenesis to some extent but still failed to revolutionize cancer treatment as expected. Integrated omics analysis incorporated tumor biological networks from diverse layers and deciphered a holistic overview of cancer behaviors, yielding precise molecular classification to facilitate the evolution and refinement of precision medicine.

CONCLUSION

This review outlined the biomarkers at multiple expression layers to tutor molecular classification and pinpoint tumor diagnosis, and explored the paradigm shift in precision therapy: from single- to multi-omics-based subtyping to optimize therapeutic regimens. Ultimately, we firmly believe that by parsing molecular characteristics, omics-based typing will be a powerful assistant for precision oncology.

ADGRE5-centered Tsurv model in T cells recognizes responders to neoadjuvant cancer immunotherapy

Background

Neoadjuvant immunotherapy with anti-programmed death-1 (neo-antiPD1) has revolutionized perioperative methods for improvement of overall survival (OS), while approaches for major pathologic response patients' (MPR) recognition along with methods for overcoming non-MPR resistance are still in urgent need.

Methods

We utilized and integrated publicly-available immune checkpoint inhibitors regimens (ICIs) single-cell (sc) data as the discovery datasets, and innovatively developed a cell-communication analysis pipeline, along with a VIPER-based-SCENIC process, to thoroughly dissect MPR-responding subsets. Besides, we further employed our own non-small cell lung cancer (NSCLC) ICIs cohort's sc data for validation in-silico. Afterward, we resorted to ICIs-resistant murine models developed by us with multimodal investigation, including bulk-RNA-sequencing, Chip-sequencing and high-dimensional cytometry by time of flight (CYTOF) to consolidate our findings in-vivo. To comprehensively explore mechanisms, we adopted 3D ex-vivo hydrogel models for analysis. Furthermore, we constructed an ADGRE5-centered Tsurv model from our discovery dataset by machine learning (ML) algorithms for a wide range of tumor types (NSCLC, melanoma, urothelial cancer, etc.) and verified it in peripheral blood mononuclear cells (PBMCs) sc datasets.

Results

Through a meta-analysis of multimodal sequential sc sequencing data from pre-ICIs and post-ICIs, we identified an MPR-expanding T cells meta-cluster (MPR-E) in the tumor microenvironment (TME), characterized by a stem-like CD8+ T cluster (survT) with STAT5-ADGRE5 axis enhancement compared to non-MPR or pre-ICIs TME. Through multi-omics analysis of murine TME, we further confirmed the existence of survT with silenced function and immune checkpoints (ICs) in MPR-E. After verification of the STAT5-ADGRE5 axis of survT in independent ICIs cohorts, an ADGRE5-centered Tsurv model was then developed through ML for identification of MPR patients pre-ICIs and post-ICIs, both in TME and PBMCs, which was further verified in pan-cancer immunotherapy cohorts. Mechanistically, we unveiled ICIs stimulated ADGRE5 upregulation in a STAT5-IL32 dependent manner in a 3D ex-vivo system (3D-HYGTIC) developed by us previously, which marked Tsurv with better survival flexibility, enhanced stemness and potential cytotoxicity within TME.

Conclusion

Our research provides insights into mechanisms underlying MPR in neo-antiPD1 and a well-performed model for the identification of non-MPR.

Gene panel selection for targeted spatial transcriptomics

Targeted spatial transcriptomics hold particular promise in analyzing complex tissues. Most such methods, however, measure only a limited panel of transcripts, which need to be selected in advance to inform on the cell types or processes being studied. A limitation of existing gene selection methods is their reliance on scRNA-seq data, ignoring platform effects between technologies. Here we describe gpsFISH, a computational method performing gene selection through optimizing detection of known cell types. By modeling and adjusting for platform effects, gpsFISH outperforms other methods. Furthermore, gpsFISH can incorporate cell type hierarchies and custom gene preferences to accommodate diverse design requirements.

Intratumoral Cell Neighborhoods Coordinate Outcomes in Pancreatic Ductal Adenocarcinoma

BACKGROUND & AIMS

Pancreatic ductal adenocarcinoma (PDA) is a highly lethal disease characterized by a spatially heterogeneous tumor microenvironment. Within the PDA microenvironment, cells organize into communities where cell fate is influenced by neighboring cells of diverse ontogeny and function. However, it remains unclear how cell neighborhoods in the tumor microenvironment evolve with treatment and impact clinical outcomes.

METHODS

Here, using automated chromogenic multiplex immunohistochemistry and unsupervised computational image analysis of human PDA tumors, we investigated cell neighborhoods in surgically resected tumors from patients with chemotherapy-naïve PDA (n = 59) and neoadjuvant chemotherapy-treated PDA (n = 57). Single cells were defined by lineage markers (CD3, CD8, Foxp3, CD68, CK19), proliferation (Ki67), and neighboring cells.

RESULTS

Distinct intratumoral immune and tumor cell subsets were defined by neighboring cells. Higher content of stromal-associated macrophages was seen in chemotherapy-naïve tumors from long-term survivors (overall survival >3 years) compared with short-term survivors (overall survival <1 year), whereas immune-excluded tumor cells were higher in short-term survivors. Chemotherapy-treated vs -naïve tumors showed lower content of tumor-associated T cells and macrophages but similar densities of stromal-associated immune cells. However, proliferating tumor cell subsets with immune-rich neighborhoods were higher in chemotherapy-treated tumors. In a blinded analysis of tumors from patients treated with neoadjuvant chemotherapy, a composite index comprising lower quantities of immune-excluded tumor cells and higher spatially distinct immune cell subsets was associated with prolonged survival.

CONCLUSIONS

Together, these data provide new insights into discrete cell communities in PDA and show their clinical relevance.

ROR2 regulates cellular plasticity in pancreatic neoplasia and adenocarcinoma

Cellular plasticity is a hallmark of pancreatic ductal adenocarcinoma (PDAC) starting from the conversion of normal cells into precancerous lesions to the progression of carcinoma subtypes associated with aggressiveness and therapeutic response. We discovered that normal acinar cell differentiation, maintained by the transcription factor Pdx1, suppresses a broad gastric cell identity that is maintained in metaplasia, neoplasia, and the classical subtype of PDAC in mouse and human. We have identified the receptor tyrosine kinase Ror2 as marker of a gastric metaplasia (SPEM)-like identity in the pancreas. Ablation of Ror2 in a mouse model of pancreatic tumorigenesis promoted a switch to a gastric pit cell identity that largely persisted through progression to the classical subtype of PDAC. In both human and mouse pancreatic cancer, ROR2 activity continued to antagonize the gastric pit cell identity, strongly promoting an epithelial to mesenchymal transition, conferring resistance to KRAS inhibition, and vulnerability to AKT inhibition.

A spatial cell atlas of neuroblastoma reveals developmental, epigenetic and spatial axis of tumor heterogeneity

Neuroblastoma is a pediatric cancer arising from the developing sympathoadrenal lineage with complex inter- and intra-tumoral heterogeneity. To chart this complexity, we generated a comprehensive cell atlas of 55 neuroblastoma patient tumors, collected from two pediatric cancer institutions, spanning a range of clinical, genetic, and histologic features. Our atlas combines single-cell/nucleus RNA-seq (sc/scRNA-seq), bulk RNA-seq, whole exome sequencing, DNA methylation profiling, spatial transcriptomics, and two spatial proteomic methods. Sc/snRNA-seq revealed three malignant cell states with features of sympathoadrenal lineage development. All of the neuroblastomas had malignant cells that resembled sympathoblasts and the more differentiated adrenergic cells. A subset of tumors had malignant cells in a mesenchymal cell state with molecular features of Schwann cell precursors. DNA methylation profiles defined four groupings of patients, which differ in the degree of malignant cell heterogeneity and clinical outcomes. Using spatial proteomics, we found that neuroblastomas are spatially compartmentalized, with malignant tumor cells sequestered away from immune cells. Finally, we identify spatially restricted signaling patterns in immune cells from spatial transcriptomics. To facilitate the visualization and analysis of our atlas as a resource for further research in neuroblastoma, single cell, and spatial-omics, all data are shared through the Human Tumor Atlas Network Data Commons at www.humantumoratlas.org.

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.

SORC: an integrated spatial omics resource in cancer

The interactions between tumor cells and the microenvironment play pivotal roles in the initiation, progression and metastasis of cancer. The advent of spatial transcriptomics data offers an opportunity to unravel the intricate dynamics of cellular states and cell-cell interactions in cancer. Herein, we have developed an integrated spatial omics resource in cancer (SORC, http://bio-bigdata.hrbmu.edu.cn/SORC), which interactively visualizes and analyzes the spatial transcriptomics data in cancer. We manually curated currently available spatial transcriptomics datasets for 17 types of cancer, comprising 722 899 spots across 269 slices. Furthermore, we matched reference single-cell RNA sequencing data in the majority of spatial transcriptomics datasets, involving 334 379 cells and 46 distinct cell types. SORC offers five major analytical modules that address the primary requirements of spatial transcriptomics analysis, including slice annotation, identification of spatially variable genes, co-occurrence of immune cells and tumor cells, functional analysis and cell-cell communications. All these spatial transcriptomics data and in-depth analyses have been integrated into easy-to-browse and explore pages, visualized through intuitive tables and various image formats. In summary, SORC serves as a valuable resource for providing an unprecedented spatially resolved cellular map of cancer and identifying specific genes and functional pathways to enhance our understanding of the tumor microenvironment.

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.

FOLFIRINOX chemotherapy modulates the peripheral immune landscape in pancreatic cancer: Implications for combination therapies and early response prediction

BACKGROUND

FOLFIRINOX chemotherapy has improved outcomes for pancreatic cancer patients, but poor long-term survival outcomes and high toxicity remain challenges. This study investigates the impact of FOLFIRINOX on plasma proteins and peripheral immune cells to guide immune-based combination therapies and, ideally, to identify a potential biomarker to predict early disease progression during FOLFIRINOX.

METHODS

Blood samples were collected from 86 pancreatic cancer patients before and two weeks after the first FOLFIRINOX cycle and subjected to comprehensive immune cell and proteome profiling. Principal Component Analysis and Linear Mixed Effect Regression models were used for data analysis. FOLFIRINOX efficacy was radiologically evaluated after the fourth cycle.

RESULTS

One cycle of FOLFIRINOX diminished tumour-cell-related pathways and enhanced pathways related to immune activation, illustrated by an increase in pro-inflammatory IL-18, IL-15, and TNFRSF4. Similarly, FOLFIRINOX promoted the activation of CD4 + and CD8 + T cells, the proliferation of NK(T), and the activation of antigen-presenting cells. Furthermore, high pre-treatment levels of VEGFA and PRDX3 and an elevation in FCRL3 levels after one cycle predicted early progression under FOLFIRINOX. Finally, patients with progressive disease exhibited high levels of inhibitory markers on B cells and CD8 + T cells, while responding patients exhibited high levels of activation markers on CD4 + and CD8 + T cell subsets.

CONCLUSION

FOLFIRINOX has immunomodulatory effects, providing a foundation for clinical trials exploring immune-based combination therapies that harness the immune system to treat pancreatic cancer. In addition, several plasma proteins hold potential as circulating predictive biomarkers for early prediction of FOLFIRINOX response in patients with pancreatic cancer.

High-resolution and quantitative spatial analysis reveal intra-ductal phenotypic and functional diversification in pancreatic cancer

A 'classical' and a 'basal-like' subtype of pancreatic cancer have been reported, with differential expression of GATA6 and different dosages of mutant KRAS. We established in situ detection of KRAS point mutations and mRNA panels for the consensus subtypes aiming to project these findings to paraffin-embedded clinical tumour samples for spatial quantitative analysis. We unveiled that, next to inter-patient and intra-patient inter-ductal heterogeneity, intraductal spatial phenotypes exist with anti-correlating expression levels of GATA6 and KRASG12D . The basal-like mRNA panel better captured the basal-like cell states than widely used protein markers. The panels corroborated the co-existence of the classical and basal-like cell states in a single tumour duct with functional diversification, i.e. proliferation and epithelial-to-mesenchymal transition respectively. Mutant KRASG12D detection ascertained an epithelial origin of vimentin-positive cells in the tumour. Uneven spatial distribution of cancer-associated fibroblasts could recreate similar intra-organoid diversification. This extensive heterogeneity with functional cooperation of plastic tumour cells poses extra challenges to therapeutic approaches. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

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.

Hierarchical and automated cell-type annotation and inference of cancer cell of origin with Census

MOTIVATION

Cell-type annotation is a time-consuming yet critical first step in the analysis of single-cell RNA-seq data, especially when multiple similar cell subtypes with overlapping marker genes are present. Existing automated annotation methods have a number of limitations, including requiring large reference datasets, high computation time, shallow annotation resolution, and difficulty in identifying cancer cells or their most likely cell of origin.

RESULTS

We developed Census, a biologically intuitive and fully automated cell-type identification method for single-cell RNA-seq data that can deeply annotate normal cells in mammalian tissues and identify malignant cells and their likely cell of origin. Motivated by the inherently stratified developmental programs of cellular differentiation, Census infers hierarchical cell-type relationships and uses gradient-boosted \decision trees that capitalize on nodal cell-type relationships to achieve high prediction speed and accuracy. When benchmarked on 44 atlas-scale normal and cancer, human and mouse tissues, Census significantly outperforms state-of-the-art methods across multiple metrics and naturally predicts the cell-of-origin of different cancers. Census is pretrained on the Tabula Sapiens to classify 175 cell-types from 24 organs; however, users can seamlessly train their own models for customized applications.

AVAILABILITY AND IMPLEMENTATION

Census is available at Zenodo https://zenodo.org/records/7017103 and on our Github https://github.com/sjdlabgroup/Census.

Cancer-Associated Fibroblasts in Gastrointestinal Cancers: Unveiling Their Dynamic Roles in the Tumor Microenvironment

Gastrointestinal cancers are highly aggressive malignancies with significant mortality rates. Recent research emphasizes the critical role of the tumor microenvironment (TME) in these cancers, which includes cancer-associated fibroblasts (CAFs), a key component of the TME that have diverse origins, including fibroblasts, mesenchymal stem cells, and endothelial cells. Several markers, such as α-SMA and FAP, have been identified to label CAFs, and some specific markers may serve as potential therapeutic targets. In this review article, we summarize the literature on the multifaceted role of CAFs in tumor progression, including their effects on angiogenesis, immune suppression, invasion, and metastasis. In addition, we highlight the use of single-cell transcriptomics to understand CAF heterogeneity and their interactions within the TME. Moreover, we discuss the dynamic interplay between CAFs and the immune system, which contributes to immunosuppression in the TME, and the potential for CAF-targeted therapies and combination approaches with immunotherapy to improve cancer treatment outcomes.

Single-Cell Analysis Differentiates the Effects of p53 Mutation and p53 Loss on Cell Compositions of Oncogenic Kras-Driven Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is a devastating malignant disease with a dismal prognosis. In the past decades, a plethora of genetically engineered mouse models (GEMMs) with autochthonous pancreatic tumor development have greatly facilitated studies of pancreatic cancer. Commonly used GEMMs of PDAC often harbor the oncogenic KRAS driver mutation (KrasG12D), in combination with either p53 mutation by knock-in strategy (Trp53R172H) or p53 loss by conditional knockout (Trp53cKO) strategy, in pancreatic cell lineages. However, the systematic comparison of the tumor microenvironment between KrasG12D; Trp53R172H (KPmut) mouse models and KrasG12D; Trp53cKO (KPloss) mouse models is still lacking. In this study, we conducted cross-dataset single-cell RNA-sequencing (scRNA-seq) analyses to compare the pancreatic tumor microenvironment from KPmut mouse models and KPloss mouse models, especially focusing on the cell compositions and transcriptomic phenotypes of major cell types including cancer cells, B cells, T cells, granulocytes, myeloid cells, cancer-associated fibroblasts, and endothelial cells. We identified the similarities and differences between KPmut and KPloss mouse models, revealing the effects of p53 mutation and p53 loss on oncogenic KRAS-driven pancreatic tumor progression.

Dissecting mammalian reproduction with spatial transcriptomics

BACKGROUND

Mammalian reproduction requires the fusion of two specialized cells: an oocyte and a sperm. In addition to producing gametes, the reproductive system also provides the environment for the appropriate development of the embryo. Deciphering the reproductive system requires understanding the functions of each cell type and cell-cell interactions. Recent single-cell omics technologies have provided insights into the gene regulatory network in discrete cellular populations of both the male and female reproductive systems. However, these approaches cannot examine how the cellular states of the gametes or embryos are regulated through their interactions with neighboring somatic cells in the native tissue environment owing to tissue disassociations. Emerging spatial omics technologies address this challenge by preserving the spatial context of the cells to be profiled. These technologies hold the potential to revolutionize our understanding of mammalian reproduction.

OBJECTIVE AND RATIONALE

We aim to review the state-of-the-art spatial transcriptomics (ST) technologies with a focus on highlighting the novel biological insights that they have helped to reveal about the mammalian reproductive systems in the context of gametogenesis, embryogenesis, and reproductive pathologies. We also aim to discuss the current challenges of applying ST technologies in reproductive research and provide a sneak peek at what the field of spatial omics can offer for the reproduction community in the years to come.

SEARCH METHODS

The PubMed database was used in the search for peer-reviewed research articles and reviews using combinations of the following terms: 'spatial omics', 'fertility', 'reproduction', 'gametogenesis', 'embryogenesis', 'reproductive cancer', 'spatial transcriptomics', 'spermatogenesis', 'ovary', 'uterus', 'cervix', 'testis', and other keywords related to the subject area. All relevant publications until April 2023 were critically evaluated and discussed.

OUTCOMES

First, an overview of the ST technologies that have been applied to studying the reproductive systems was provided. The basic design principles and the advantages and limitations of these technologies were discussed and tabulated to serve as a guide for researchers to choose the best-suited technologies for their own research. Second, novel biological insights into mammalian reproduction, especially human reproduction revealed by ST analyses, were comprehensively reviewed. Three major themes were discussed. The first theme focuses on genes with non-random spatial expression patterns with specialized functions in multiple reproductive systems; The second theme centers around functionally interacting cell types which are often found to be spatially clustered in the reproductive tissues; and the thrid theme discusses pathological states in reproductive systems which are often associated with unique cellular microenvironments. Finally, current experimental and computational challenges of applying ST technologies to studying mammalian reproduction were highlighted, and potential solutions to tackle these challenges were provided. Future directions in the development of spatial omics technologies and how they will benefit the field of human reproduction were discussed, including the capture of cellular and tissue dynamics, multi-modal molecular profiling, and spatial characterization of gene perturbations.

WIDER IMPLICATIONS

Like single-cell technologies, spatial omics technologies hold tremendous potential for providing significant and novel insights into mammalian reproduction. Our review summarizes these novel biological insights that ST technologies have provided while shedding light on what is yet to come. Our review provides reproductive biologists and clinicians with a much-needed update on the state of art of ST technologies. It may also facilitate the adoption of cutting-edge spatial technologies in both basic and clinical reproductive research.

The immune microenvironment after neoadjuvant therapy compared to upfront surgery in patients with pancreatic cancer

BACKGROUND

Patients with resectable and borderline resectable pancreatic ductal adenocarcinoma increasingly receive neoadjuvant therapy prior to surgery. However, the effect of neoadjuvant therapy on the immune microenvironment remains largely unknown. We analyzed the immune microenvironment in pancreatic cancer tumor tissue samples from patients treated with neoadjuvant therapy compared to patients after upfront surgery to gain knowledge about the immunological environment after therapy.

METHODS

Multispectral imaging was performed on tissue from resected specimens from patients with PDAC who underwent upfront surgery (n = 10), neoadjuvant FOLFIRINOX (n = 10) or gemcitabine + radiotherapy (gem-RT) (n = 9) followed by surgery. The samples were selected by a dedicated pancreas pathologist from both the central part and the invasive front of the tumor (by the resected vein or venous surface) and subsequently analyzed using the Vectra Polaris.

RESULTS

Patients receiving neoadjuvant FOLFIRINOX display a more pro-inflammatory immune profile, with less regulatory T cells and more CD8 T cells in the tumor tissue compared to patients receiving neoadjuvant gem-RTgem-RT or undergoing upfront surgery. Furthermore, CD163+ macrophages were decreased, and a higher CD163- macrophages versus CD163+ macrophages ratio was found in patients with neoadjuvant FOLFIRINOX. In all treatment groups, percentage of FoxP3+ B cells was significantly higher in tumor tissue compared to adjacent tissue. Furthermore, an increase in regulatory T cells in the tumor tissue was found in patients undergoing upfront surgery or receiving neoadjuvant gem-RT. In the gem-RT group, less CD8 T cells and a higher CD163+ macrophages to CD8 ratio were noted in the tumor tissue, suggesting a more immune suppressive profile in the tumor tissue.

CONCLUSION

Patients receiving neoadjuvant FOLFIRINOX display a more pro-inflammatory immune profile compared to patients receiving neoadjuvant gem-RT or undergoing upfront surgery. Furthermore, in all treatment groups, a more immune suppressive microenvironment was found in the tumor tissue compared to the adjacent non-tumorous tissue.

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.

Genetic alterations in the neuronal development genes are associated with changes of the tumor immune microenvironment in pancreatic cancer

Background

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis and is highly metastatic. Our prior studies have demonstrated the critical role of axon guidance pathway genes in PDAC and the connection between neuronal development and the tumor microenvironment. A recent study newly identified 20 neuronal development genes [disks large homolog 2 (DLG2), neuron-glial-related cell adhesion molecule (NRCAM), neurexin3 (NRXN3), mitogen-activated protein kinase 10 (MAPK10), platelet-derived growth factor D (PDGFD), protein kinase C epsilon (PRKCE), potassium calcium-activated channel subfamily M alpha 1 (KCNMA1), polycystic kidney and hepatic disease 1 (PKHD1), neural cell adhesion molecule 1 (NCAM1), neuregulin-1 (NRG1), zinc finger protein 667 (ZNF667), cystic fibrosis transmembrane conductance regulator (CFTR), acyl-CoA medium-chain synthetase-3 (ACSM3), complement 6 (C6), protein tyrosine phosphatase receptor type M (PTPRM), hypoxia-inducible factor 1 alpha (HIF1A), adenylyl cyclase 5 (ADCY5), adherens junctions-associated protein 1 (AJAP1), neurobeachin (NBEA), sodium voltage-gated channel alpha subunit 9 (SCN9A)] that are associated with perineural invasion and poor prognosis of PDAC. The relationship between genetic alterations in these 20 genes and tumor immune microenvironment (TME) has not previously been investigated.

Methods

We hence applied the sequential multiplex immunohistochemistry results of biopsy specimens from 63 PDAC patients to investigate this relationship.

Results

We found that, except for PTPRM and NBEA, genetic alterations involving these 20 genes are associated with significant changes in the densities of major immune cell subtypes. Except for AJAP1, the copy number loss involving this panel of neuronal development genes is significantly associated with changes in immune cell infiltrates. In contrast, the copy number gain in fewer genes, including NRXN3, ZNF667, ACSM3, C6, ADCY5, SCN9A, and PRKCE, is significantly associated with changes in immune cell infiltrates.

Conclusions

Our study suggested that neuronal development genes play a role in modulating TME in a pancreatic cancer setting.

Tumor- and Nerve-Derived Axon Guidance Molecule Promotes Pancreatic Ductal Adenocarcinoma Progression and Metastasis through Macrophage Reprogramming

Axon guidance molecules were found to be the gene family most frequently altered in pancreatic ductal adenocarcinoma (PDA) through mutations and copy number changes. However, the exact molecular mechanism regarding PDA development remained unclear. Using genetically engineered mouse models to examine one of the axon guidance molecules, semaphorin 3D (SEMA3D), we found a dual role for tumor-derived SEMA3D in malignant transformation of pancreatic epithelial cells and a role for nerve-derived SEMA3D in PDA development. This was demonstrated by the pancreatic-specific knockout of the SEMA3D gene from the KRAS G12D and TP53 R 172 H mutation knock-in, PDX1-Cre (KPC) mouse model which demonstrated a delayed tumor initiation and growth comparing to the original KPC mouse model. Our results showed that SEMA3D knockout skews the macrophages in the pancreas away from M2 polarization, providing a potential mechanistic role of tumor-derived SEMA3D in PDA development. The KPC mice with the SEMA3D knockout remained metastasis-free, however, died from primary tumor growth. We then tested the hypothesis that a potential compensation mechanism could result from SEMA3D which is naturally expressed by the intratumoral nerves. Our study further revealed that nerve-derived SEMA3D does not reprogram macrophages directly, but reprograms macrophages indirectly through ARF6 signaling and lactate production in PDA tumor cells. SEMA3D increases tumor-secreted lactate which is sensed by GPCR132 on macrophages and subsequently stimulates pro-tumorigenic M2 polarization in vivo. Tumor intrinsic- and extrinsic-SEMA3D induced ARF6 signaling through its receptor Plexin D1 in a mutant KRAS-dependent manner. Consistently, RNA sequencing database analysis revealed an association of higher KRAS MUT expression with an increase in SEMA3D and ARF6 expression in human PDAs. Moreover, multiplex immunohistochemistry analysis showed an increased number of M2-polarized macrophages proximal to nerves in human PDA tissue expressing SEMA3D. Thus, this study suggests altered expression of SEMA3D in tumor cells lead to acquisition of cancer-promoting functions and the axon guidance signaling originating from nerves is "hijacked" by tumor cells to support their growth. Other axon guidance and neuronal development molecules may play a similar dual role which is worth further investigation.

One sentence summary

Tumor- and nerve-derived SEMA3D promotes tumor progression and metastasis through macrophage reprogramming in the tumor microenvironment.

STATEMENT OF SIGNIFICANCE

This study established the dual role of axon guidance molecule, SEMA3D, in the malignant transformation of pancreatic epithelial cells and of nerve-derived SEMA3D in PDA progression and metastasis. It revealed macrophage reprogramming as the mechanism underlying bothroles. Together, this research elucidated how inflammatory responses promote invasive PDA progression and metastasis through an oncogenic process.

Single-cell morphological and topological atlas reveals the ecosystem diversity of human breast cancer

Digital pathology allows computerized analysis of tumor ecosystem using whole slide images (WSIs). Here, we present single-cell morphological and topological profiling (sc-MTOP) to characterize tumor ecosystem by extracting the features of nuclear morphology and intercellular spatial relationship for individual cells. We construct a single-cell atlas comprising 410 million cells from 637 breast cancer WSIs and dissect the phenotypic diversity within tumor, inflammatory and stroma cells respectively. Spatially-resolved analysis identifies recurrent micro-ecological modules representing locoregional multicellular structures and reveals four breast cancer ecotypes correlating with distinct molecular features and patient prognosis. Further analysis with multiomics data uncovers clinically relevant ecosystem features. High abundance of locally-aggregated inflammatory cells indicates immune-activated tumor microenvironment and favorable immunotherapy response in triple-negative breast cancers. Morphological intratumor heterogeneity of tumor nuclei correlates with cell cycle pathway activation and CDK inhibitors responsiveness in hormone receptor-positive cases. sc-MTOP enables using WSIs to characterize tumor ecosystems at the single-cell level.

Delineating spatial cell-cell interactions in the solid tumour microenvironment through the lens of highly multiplexed imaging

The growth and metastasis of solid tumours is known to be facilitated by the tumour microenvironment (TME), which is composed of a highly diverse collection of cell types that interact and communicate with one another extensively. Many of these interactions involve the immune cell population within the TME, referred to as the tumour immune microenvironment (TIME). These non-cell autonomous interactions exert substantial influence over cell behaviour and contribute to the reprogramming of immune and stromal cells into numerous pro-tumourigenic phenotypes. The study of some of these interactions, such as the PD-1/PD-L1 axis that induces CD8+ T cell exhaustion, has led to the development of breakthrough therapeutic advances. Yet many common analyses of the TME either do not retain the spatial data necessary to assess cell-cell interactions, or interrogate few (<10) markers, limiting the capacity for cell phenotyping. Recently developed digital pathology technologies, together with sophisticated bioimage analysis programs, now enable the high-resolution, highly-multiplexed analysis of diverse immune and stromal cell markers within the TME of clinical specimens. In this article, we review the tumour-promoting non-cell autonomous interactions in the TME and their impact on tumour behaviour. We additionally survey commonly used image analysis programs and highly-multiplexed spatial imaging technologies, and we discuss their relative advantages and limitations. The spatial organization of the TME varies enormously between patients, and so leveraging these technologies in future studies to further characterize how non-cell autonomous interactions impact tumour behaviour may inform the personalization of cancer treatment.​.

Targeting neoadjuvant chemotherapy-induced metabolic reprogramming in pancreatic cancer promotes anti-tumor immunity and chemo-response

The molecular dynamics of pancreatic ductal adenocarcinoma (PDAC) under chemotherapy remain incompletely understood. The widespread use of neoadjuvant chemotherapy (NAC) provides a unique opportunity to investigate PDAC samples post-chemotherapy. Leveraging a cohort from Fudan University Shanghai Cancer Center, encompassing PDAC samples with and without exposure to neoadjuvant albumin-bound paclitaxel and gemcitabine (AG), we have compiled data from single-cell and spatial transcriptomes, proteomes, bulk transcriptomes, and metabolomes, deepening our comprehension of the molecular changes in PDACs in response to chemotherapy. Metabolic flux analysis reveals that NAC induces a reprogramming of PDAC metabolic patterns and enhances immunogenicity. Notably, NAC leads to the downregulation of glycolysis and the upregulation of CD36. Tissue microarray analysis demonstrates that high CD36 expression is linked to poorer survival in patients receiving postoperative AG. Targeting CD36 synergistically improves the PDAC response to AG both in vitro and in vivo, including patient-derived preclinical models.

Serum immune checkpoint profiling identifies soluble CD40 as a biomarker for pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) responds poorly to systemic treatment, including new immunotherapeutic approaches. Biomarkers are urgently needed for early disease detection, patient stratification for treatment, and response prediction. The role of soluble CD40 (sCD40) is unknown in PDAC. In this study, we performed a quantitative multiplex analysis of 17 immune checkpoint proteins in serum samples from patients with various stages of PDAC in a discovery study (n = 107) and analyzed sCD40 by ELISA in a validation study (n = 317). Youden's J statistic was used for diagnostic cut-off optimization. A Cox proportional hazards regression model was applied in an empiric approach for prognostic threshold optimization. Kaplan-Meier estimator and multivariable Cox regression analyses were used for survival analysis. sCD40 was significantly increased in the serum of patients with PDAC compared to healthy cohorts and patients with IPMN. In the validation cohort, the area under the receiver operating characteristic (ROC) c-statistic was 0.8, and combining sCD40 with CA19-9 yielded a c-statistic of 0.95. sCD40 levels were independent of the tumor stage. However, patients who received neoadjuvant chemotherapy had significantly lower sCD40 levels than those who underwent upfront surgery. Patients with a sCD40 level above the empirical threshold of 0.83 ng/ml had a significantly reduced overall survival with a hazard ratio of 1.4. This observation was pronounced in patients after neoadjuvant chemotherapy. Collectively, soluble CD40 may be considered as both a diagnostic and prognostic non-invasive biomarker in PDAC.

Currently Debated Topics on Surgical Treatment of Pancreatic Ductal Adenocarcinoma: A Narrative Review on Surgical Treatment of Borderline Resectable, Locally Advanced, and Synchronous or Metachronous Oligometastatic Tumor

BACKGROUND

Previously considered inoperable patients (borderline resectable, locally advanced, synchronous oligometastatic or metachronous pancreatic adenocarcinoma (PDAC)) are starting to become resectable thanks to advances in chemo/radiotherapy and the reduction in operative mortality.

METHODS

This narrative review presents a chosen literature selection, giving a picture of the current state of treatment of these patients.

RESULTS

Neoadjuvant therapy (NAT) is generally recognized as the treatment of choice before surgery. However, despite the increased efficacy, the best pathological response is still limited to 10.9-27.9% of patients. There are still limited data on the selection of possible NAT responders and how to diagnose non-responders early. Multidetector computed tomography has high sensitivity and low specificity in evaluating resectability after NAT, limiting the resection rate of resectable patients. Ca 19-9 and Positron emission tomography are giving promising results. The prediction of early recurrence after a radical resection of synchronous or metachronous metastatic PDAC, thus identifying patients with poor prognosis and saving them from a resection of little benefit, is still ongoing, although some promising data are available.

CONCLUSION

In conclusion, high-level evidence demonstrating the benefit of the surgical treatment of such patients is still lacking and should not be performed outside of high-volume centers with interdisciplinary teams of surgeons and oncologists.

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

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

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.

Spatially Resolved Transcriptomics Technology Facilitates Cancer Research

Single cell RNA sequencing (scRNA-seq) provides a great convenience for studying tumor occurrence and development for its ability to study gene expression at the individual cell level. However, patient-derived tumor tissues are composed of multiple types of cells including tumor cells and adjacent non-malignant cells such as stromal cells and immune cells. The spatial locations of various cells in situ tissues plays a pivotal role in the occurrence and development of tumors, which cannot be elucidated by scRNA-seq alone. Spatially resolved transcriptomics (SRT) technology emerges timely to explore the unrecognized relationship between the spatial background of a particular cell and its functions, and is increasingly used in cancer research. This review provides a systematic overview of the SRT technologies that are developed, in particular the more widely used cutting-edge SRT technologies based on next-generation sequencing (NGS). In addition, the main achievements by SRT technologies in precisely unveiling the underappreciated spatial locations on gene expression and cell function with unprecedented high-resolution in cancer research are emphasized, with the aim of developing more effective clinical therapeutics oriented to a deeper understanding of the interaction between tumor cells and surrounding non-malignant cells.