Integrated genomic and transcriptomic analysis reveals unique characteristics of hepatic metastases and pro-metastatic role of complement C1q in pancreatic ductal adenocarcinoma

Comparative analysis of the mutational landscape and evolutionary patterns of pancreatic ductal adenocarcinoma metastases in the liver or peritoneum

Background

Pancreatic ductal adenocarcinoma (PDAC) often presents with liver or peritoneal metastases at diagnosis. Despite similar treatment approaches, patient outcomes vary between these metastatic sites. To improve targeted therapies for metastatic PDAC, a comprehensive analysis of the genetic profiles and evolutionary patterns at these distinct metastatic locations is essential.

Methods

We performed whole exome sequencing on 44 tissue samples from 27 PDAC patients, including primary tumours and matched liver or peritoneal metastases. We analysed somatic mutation profiles, signatures, and affected pathways for each group, and examined clonal evolution using subclonal architectures and phylogenetic trees.

Results

KRAS mutations remained the predominant driver alteration, with a prevalence of 89 % across all tumours. Notably, we observed site-specific differences in mutation frequencies, with KRAS alterations detected in 77.8 % (7/9) of peritoneal metastases and 87.5 % (7/8) of liver metastases. TP53 mutations exhibited a similar pattern, occurring in 55.6 % (5/9) of peritoneal and 37.5 % (3/8) of liver metastases. Intriguingly, we identified site-specific alterations in DNA repair pathway genes, including ATM and BRCA1, with distinct mutational profiles in liver versus peritoneal metastases. Furthermore, liver metastases demonstrated a significantly higher tumor mutational burden (TMB) compared to peritoneal metastases (median [IQR]: 2.14 [1.77-2.71] vs. 1.29 [1.21-1.69] mutations/Mb; P = 0.048).

Conclusions

In conclusion, metastasis of pancreatic cancer may be influenced by variables other than KRAS mutations, such as TP53. PDAC peritoneal and liver metastases may differ in potential therapeutic biomarkers. Further inquiry is needed on the biological mechanisms underlying metastasis and the treatment of diverse metastases.

Single-cell Atlas of Penile Cancer Reveals TP53 Mutations as a Driver of an Aggressive Phenotype, Irrespective of Human Papillomavirus Status, and Provides Clues for Treatment Personalization

BACKGROUND AND OBJECTIVE

TP53 loss-of-function (TP53LOF) mutations might be a driver of poor prognosis and chemoresistance in both human papillomavirus (HPV)-independent (HPV-) and HPV-associated (HPV+) penile squamous cell carcinoma (PSCC). Here, we aim to describe transcriptomic differences in the PSCC microenvironment stratified by TP53LOF and HPV status.

METHODS

We used single-cell RNA sequencing (scRNA-seq) and T-cell receptor sequencing to obtain a comprehensive atlas of the cellular architecture of PSCC. TP53LOF and HPV status were determined by targeted next-generation sequencing and sequencing HPV-DNA reads. Six HPV+ TP53 wild type (WT), six HPV- TP53WT, and four TP53LOF PSCC samples and six controls were included. Immunohistochemistry and hematoxylin-eosin confirmed the morphological context of the observed signatures. Prognostic differences between patient groups were validated in 541 PSCC patients using Kaplan-Meier survival estimates.

KEY FINDINGS AND LIMITATIONS

Patients with aberrant p53 staining fare much worse than patients with either HPV- or HPV+ tumors and WT p53 expression. Using scRNA-seq, we revealed 65 cell subtypes within 83 682 cells. TP53LOF tumors exhibit a partial epithelial-to-mesenchymal transition, immune-excluded, angiogenic, and morphologically invasive environment, underlying their aggressive phenotype. HPV- TP53WT tumors show stemness and immune exhaustion. HPV+ TP53WT tumors mirror normal epithelial maturation with upregulation of antibody-drug-conjugate targets and activation of innate immunity. Inherent to the scRNA-seq analysis, low sample size is a limitation and validation of signatures in large PSCC cohorts is needed.

CONCLUSIONS AND CLINICAL IMPLICATIONS

This first scRNA-seq atlas offers unprecedented in-depth insights into PSCC biology underlying prognostic differences based on TP53 and HPV status. Our findings provide clues for testing novel biomarker-driven therapies in PSCC.

PATIENT SUMMARY

Here, we analyzed tissues of penile cancer at the level of individual cells, which helps us understand why patients who harbor a deactivating mutation in the TP53 gene do much worse than patients lacking such a mutation. Such an analysis may help us tailor future therapies based on TP53 gene mutations and human papillomavirus status of these tumors.

The lncRNA LINC01605 promotes the progression of pancreatic ductal adenocarcinoma by activating the mTOR signaling pathway

BACKGROUND

This study investigated the molecular mechanism of long intergenic non-protein coding RNA 1605 (LINC01605) in the process of tumor growth and liver metastasis of pancreatic ductal adenocarcinoma (PDAC).

METHODS

LINC01605 was filtered out with specificity through TCGA datasets (related to DFS) and our RNA-sequencing data of PDAC tissue samples from Renji Hospital. The expression level and clinical relevance of LINC01605 were then verified in clinical cohorts and samples by immunohistochemical staining assay and survival analysis. Loss- and gain-of-function experiments were performed to estimate the regulatory effects of LINC01605 in vitro. RNA-seq of LINC01605-knockdown PDAC cells and subsequent inhibitor-based cellular function, western blotting, immunofluorescence and rescue experiments were conducted to explore the mechanisms by which LINC01605 regulates the behaviors of PDAC tumor cells. Subcutaneous xenograft models and intrasplenic liver metastasis models were employed to study its role in PDAC tumor growth and liver metastasis in vivo.

RESULTS

LINC01605 expression is upregulated in both PDAC primary tumor and liver metastasis tissues and correlates with poor clinical prognosis. Loss and gain of function experiments in cells demonstrated that LINC01605 promotes the proliferation and migration of PDAC cells in vitro. In subsequent verification experiments, we found that LINC01605 contributes to PDAC progression through cholesterol metabolism regulation in a LIN28B-interacting manner by activating the mTOR signaling pathway. Furthermore, the animal models showed that LINC01605 facilitates the proliferation and metastatic invasion of PDAC cells in vivo.

CONCLUSIONS

Our results indicate that the upregulated lncRNA LINC01605 promotes PDAC tumor cell proliferation and migration by regulating cholesterol metabolism via activation of the mTOR signaling pathway in a LIN28B-interacting manner. These findings provide new insight into the role of LINC01605 in PDAC tumor growth and liver metastasis as well as its value for clinical approaches as a metabolic therapeutic target in PDAC.

Tracing unknown tumor origins with a biological-pathway-based transformer model

Cancer of unknown primary (CUP) represents metastatic cancer where the primary site remains unidentified despite standard diagnostic procedures. To determine the tumor origin in such cases, we developed BPformer, a deep learning method integrating the transformer model with prior knowledge of biological pathways. Trained on transcriptomes from 10,410 primary tumors across 32 cancer types, BPformer achieved remarkable accuracy rates of 94%, 92%, and 89% in primary tumors and primary and metastatic sites of metastatic tumors, respectively, surpassing existing methods. Additionally, BPformer was validated in a retrospective study, demonstrating consistency with tumor sites diagnosed through immunohistochemistry and histopathology. Furthermore, BPformer was able to rank pathways based on their contribution to tumor origin identification, which helped to classify oncogenic signaling pathways into those that are highly conservative among different cancers versus those that are highly variable depending on their origins.

LYVE-1-expressing Macrophages Modulate the Hyaluronan-containing Extracellular Matrix in the Mammary Stroma and Contribute to Mammary Tumor Growth

Macrophages represent a heterogeneous myeloid population with diverse functions in normal tissues and tumors. While macrophages expressing the cell surface marker lymphatic vessel endothelial hyaluronan receptor 1 (LYVE-1) have been identified in stromal regions of the normal mammary gland and in the peritumoral stroma, their functions within these regions are not well understood. Using a genetic mouse model of LYVE-1+ macrophage depletion, we demonstrate that loss of LYVE-1+ macrophages is associated with altered extracellular matrix remodeling in the normal mammary gland and reduced mammary tumor growth in vivo. In further studies focused on investigating the functions of LYVE-1+ macrophages in the tumor microenvironment, we demonstrate that LYVE-1 expression correlates with an increased ability of macrophages to bind, internalize, and degrade hyaluronan. Consistent with this, we show that depletion of LYVE-1+ macrophages correlates with increased hyaluronan accumulation in both the normal mammary gland and in mammary tumors. Analysis of single-cell RNA sequencing of macrophages isolated from these tumors reveals that depletion of LYVE-1+ macrophages in tumors drives a shift in the majority of the remaining macrophages toward a proinflammatory phenotype, as well as an increase in CD8+ T-cell infiltration. Together, these findings indicate that LYVE-1+ macrophages represent a tumor-promoting anti-inflammatory subset of macrophages that contributes to hyaluronan remodeling in the tumor microenvironment.

SIGNIFICANCE

We have identified a macrophage subset in mouse mammary tumors associated with tumor structural components. When this macrophage subset is absent in tumors, we report a delay in tumor growth and an increase in antitumor immune cells. Understanding the functions of distinct macrophage subsets may allow for improved therapeutic strategies for patients with breast cancer.

A temporal perspective for tumor-associated macrophage identities and functions

Cancer is a progressive disease that can develop and evolve over decades, with inflammation playing a central role at each of its stages, from tumor initiation to metastasis. In this context, macrophages represent well-established bridges reciprocally linking inflammation and cancer via an array of diverse functions that have spurred efforts to classify them into subtypes. Here, we discuss the intertwines between macrophages, inflammation, and cancer with an emphasis on temporal dynamics of macrophage diversity and functions in pre-malignancy and cancer. By instilling temporal dynamism into the more static classic view of tumor-associated macrophage biology, we propose a new framework to better contextualize their significance in the inflammatory processes that precede and result from the onset of cancer and shape its evolution.

Specific lineage transition of tumor-associated macrophages elicits immune evasion of ascitic tumor cells in gastric cancer with peritoneal metastasis

BACKGROUND

Gastric cancer with peritoneal metastasis (PM-GC), recognized as one of the deadliest cancers. However, whether and how the tumor cell-extrinsic tumor microenvironment (TME) is involved in the therapeutic failure remains unknown. Thus, this study systematically assessed the immunosuppressive tumor microenvironment in ascites from patients with PM-GC, and its contribution to dissemination and immune evasion of ascites-disseminated tumor cells (aDTCs).

METHODS

Sixty-three ascites and 43 peripheral blood (PB) samples from 51 patients with PM-GC were included in this study. aDTCs in ascites and circulating tumor cells (CTCs) in paired PB were immunophenotypically profiled. Using single-cell RNA transcriptional sequencing (scRNA-seq), crosstalk between aDTCs and the TME features of ascites was inspected. Further studies on the mechanism underlying aDTCs-immune cells crosstalk were performed on in vitro cultured aDTCs.

RESULTS

Immune cells in ascites interact with aDTCs, prompting their immune evasion. Specifically, we found that the tumor-associated macrophages (TAMs) in ascites underwent a continuum lineage transition from cathepsinhigh (CTShigh) to complement 1qhigh (C1Qhigh) TAM. CTShigh TAM initially attracted the metastatic tumor cells to ascites, thereafter, transitioning terminally to C1Qhigh TAM to trigger overproliferation and immune escape of aDTCs. Mechanistically, we demonstrated that C1Qhigh TAMs significantly enhanced the expression of PD-L1 and NECTIN2 on aDTCs, which was driven by the activation of the C1q-mediated complement pathway.

CONCLUSIONS

For the first time, we identified an immunosuppressive macrophage transition from CTShigh to C1Qhigh TAM in ascites from patients with PM-GC. This may contribute to developing potential TAM-targeted immunotherapies for PM-GC.

Molecular and immune characterization of Chinese early-stage non-squamous non-small cell lung cancer: a multi-omics cohort study

Background

Albeit considered with superior survival, around 30% of the early-stage non-squamous non-small cell lung cancer (Ns-NSCLC) patients relapse within 5 years, suggesting unique biology. However, the biological characteristics of early-stage Ns-NSCLC, especially in the Chinese population, are still unclear.

Methods

Multi-omics interrogation of early-stage Ns-NSCLC (stage I-III), paired blood samples and normal lung tissues (n=76) by whole-exome sequencing (WES), RNA sequencing, and T-cell receptor (TCR) sequencing were conducted.

Results

An average of 128 exonic mutations were identified, and the most frequently mutant gene was EGFR (55%), followed by TP53 (37%) and TTN (26%). Mutations in MUC17, ABCA2, PDE4DIP, and MYO18B predicted significantly unfavorable disease-free survival (DFS). Moreover, cytobands amplifications in 8q24.3, 14q13.1, 14q11.2, and deletion in 3p21.1 were highlighted in recurrent cases. Higher incidence of human leukocyte antigen loss of heterozygosity (HLA-LOH), higher tumor mutational burden (TMB) and tumor neoantigen burden (TNB) were identified in ever-smokers than never-smokers. HLA-LOH also correlated with higher TMB, TNB, intratumoral heterogeneity (ITH), and whole chromosomal instability (wCIN) scores. Interestingly, higher ITH was an independent predictor of better DFS in early-stage Ns-NSCLC. Up-regulation of immune-related genes, including CRABP2, ULBP2, IL31RA, and IL1A, independently portended a dismal prognosis. Enhanced TCR diversity of peripheral blood mononuclear cells (PBMCs) predicted better prognosis, indicative of a noninvasive method for relapse surveillance. Eventually, seven machine-learning (ML) algorithms were employed to evaluate the predictive accuracy of clinical, genomic, transcriptomic, and TCR repertoire data on DFS, showing that clinical and RNA features combination in the random forest (RF) algorithm, with area under the curve (AUC) of 97.5% and 83.3% in the training and testing cohort, respectively, significantly outperformed other methods.

Conclusions

This study comprehensively profiled the genomic, transcriptomic, and TCR repertoire spectrums of Chinese early-stage Ns-NSCLC, shedding light on biological underpinnings and candidate biomarkers for prognosis development.

Advanced insights on tumor-associated macrophages revealed by single-cell RNA sequencing: The intratumor heterogeneity, functional phenotypes, and cellular interactions

Single-cell RNA sequencing (scRNA-seq) is an emerging technology used for cellular transcriptome analysis. The application of scRNA-seq has led to profoundly advanced oncology research, continuously optimizing novel therapeutic strategies. Intratumor heterogeneity extensively consists of all tumor components, contributing to different tumor behaviors and treatment responses. Tumor-associated macrophages (TAMs), the core immune cells linking innate and adaptive immunity, play significant roles in tumor progression and resistance to therapies. Moreover, dynamic changes occur in TAM phenotypes and functions subject to the regulation of the tumor microenvironment. The heterogeneity of TAMs corresponding to the state of the tumor microenvironment has been comprehensively recognized using scRNA-seq. Herein, we reviewed recent research and summarized variations in TAM phenotypes and functions from a developmental perspective to better understand the significance of TAMs in the tumor microenvironment.

Macrophage heterogeneity and its interactions with stromal cells in tumour microenvironment

Macrophages and tumour stroma cells account for the main cellular components in the tumour microenvironment (TME). Current advancements in single-cell analysis have revolutionized our understanding of macrophage diversity and macrophage-stroma interactions. Accordingly, this review describes new insight into tumour-associated macrophage (TAM) heterogeneity in terms of tumour type, phenotype, metabolism, and spatial distribution and presents the association between these factors and TAM functional states. Meanwhile, we focus on the immunomodulatory feature of TAMs and highlight the tumour-promoting effect of macrophage-tumour stroma interactions in the immunosuppressive TME. Finally, we summarize recent studies investigating macrophage-targeted therapy and discuss their therapeutic potential in improving immunotherapy by alleviating immunosuppression.

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.

Semi-reference based cell type deconvolution with application to human metastatic cancers

Bulk RNA-seq experiments, commonly used to discern gene expression changes across conditions, often neglect critical cell type-specific information due to their focus on average transcript abundance. Recognizing cell type contribution is crucial to understanding phenotype and disease variations. The advent of single-cell RNA sequencing has allowed detailed examination of cellular heterogeneity; however, the cost and analytic caveat prohibits such sequencing for a large number of samples. We introduce a novel deconvolution approach, SECRET, that employs cell type-specific gene expression profiles from single-cell RNA-seq to accurately estimate cell type proportions from bulk RNA-seq data. Notably, SECRET can adapt to scenarios where the cell type present in the bulk data is unrepresented in the reference, thereby offering increased flexibility in reference selection. SECRET has demonstrated superior accuracy compared to existing methods using synthetic data and has identified unknown tissue-specific cell types in real human metastatic cancers. Its versatility makes it broadly applicable across various human cancer studies.

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.

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

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

C1q+ tumor-associated macrophages contribute to immunosuppression through fatty acid metabolic reprogramming in malignant pleural effusion

BACKGROUND

Although immune checkpoint blockade (ICB) therapy has shown remarkable benefits in cancers, a subset of patients with cancer exhibits unresponsiveness or develop acquired resistance due to the existence of abundant immunosuppressive cells. Tumor-associated macrophages (TAMs), as the dominant immunosuppressive population, impede the antitumor immune response; however, the underlying mechanisms have not been fully elucidated yet.

METHODS

Single-cell RNA sequencing analysis was performed to portray macrophage landscape and revealed the underlying mechanism of component 1q (C1q)+ TAMs. Malignant pleural effusion (MPE) of human and mouse was used to explore the phenotypes and functions of C1q+ TAMs.

RESULTS

C1q+ TAMs highly expressed multiple inhibitory molecules and their high infiltration was significantly correlated with poor prognosis. C1q+ TAMs promote MPE immunosuppression through impairing the antitumor effects of CD8+ T cells. Mechanistically, C1q+ TAMs enhance fatty acid binding protein 5 (FABP5)-mediated fatty acid metabolism, which activate transcription factor peroxisome proliferator-activated receptor-gamma, increasing the gene expression of inhibitory molecules. A high-fat diet increases the expression of inhibitory molecules in C1q+ TAMs and the immunosuppression of MPE microenvironment, whereas a low-fat diet ameliorates these effects. Moreover, FABP5 inhibition represses the expression of inhibitory molecules in TAMs and tumor progression, while enhancing the efficacy of ICB therapy in MPE and lung cancer.

CONCLUSIONS

C1q+ TAMs impede antitumor effects of CD8+ T cells promoting MPE immunosuppression. Targeting C1q+ TAMs effectively alleviates the immunosuppression and enhances the efficacy of ICB therapy. C1q+ TAMs subset has great potential to be a therapeutic target for cancer immunotherapy.

Pan-cancer molecular subtypes of metastasis reveal distinct and evolving transcriptional programs

Molecular mechanisms underlying cancer metastasis span diverse tissues of origin. Here, we synthesize and collate the transcriptomes of patient-derived xenografts and patient tumor metastases, and these data collectively represent 38 studies and over 3,000 patients and 4,000 tumors. We identify four expression-based subtypes of metastasis transcending tumor lineage. The first subtype has extensive copy alterations, higher expression of MYC transcriptional targets and DNA repair genes, and bromodomain inhibitor response association. The second subtype has higher expression of genes involving metabolism and prostaglandin synthesis and regulation. The third subtype has evidence of neuronal differentiation, higher expression of DNA and histone methylation genes and EZH2 transcriptional targets, and BCL2 inhibitor response association. The fourth subtype has higher expression of immune checkpoint and Notch pathway genes. The metastasis subtypes reflect expression differences from paired primaries, with subtype switching being common. These subtypes facilitate understanding of the molecular underpinnings of metastases beyond tissue-oriented domains, with therapeutic implications.

Identifying Liver Metastasis-Related Genes Through a Coexpression Network to Construct a 5-Gene Model for Predicting Pancreatic Ductal Adenocarcinoma Patient Prognosis

OBJECTIVES

This study aimed to develop a liver metastasis-related gene prognostic index (LMPI) for pancreatic ductal adenocarcinoma prognosis and therapy.

METHODS

The Cancer Genome Atlas data set was used to identify liver metastasis-related hub genes via weighted gene coexpression network analysis. The core genes were identified to construct an LMPI by using the Cox regression method. An immune cell abundance identifier was applied to determine the immune cell abundance.

RESULTS

A total of 78 hub liver metastasis-related genes in the black module were significantly enriched in complement and coagulation cascades, fat digestion and absorption, and the PPAR signaling pathway. Then, an LMPI was constructed on the basis of the 5 prognostic genes (MOGAT3, ASGR1, TRPM8, SGSM1, and LOC101927851). Patients with higher LMPI scores had poor overall survival, more co-occurring or mutually exclusive pairs of driver gene mutations, and less benefit from immunotherapy than patients with lower LMPI scores. In addition, a high correlation was also found between LMPI scores and immune infiltration, such as CD4 naive, CD8 T, cytotoxic T, T helper 2, follicular helper T, and natural killer cells.

CONCLUSIONS

The core genes of the LMPI developed may be independent factors for predicting prognosis, immune characteristics, and immunotherapy efficacy in pancreatic ductal adenocarcinoma.

Topological identification and interpretation for single-cell gene regulation elucidation across multiple platforms using scMGCA

Single-cell RNA sequencing provides high-throughput gene expression information to explore cellular heterogeneity at the individual cell level. A major challenge in characterizing high-throughput gene expression data arises from challenges related to dimensionality, and the prevalence of dropout events. To address these concerns, we develop a deep graph learning method, scMGCA, for single-cell data analysis. scMGCA is based on a graph-embedding autoencoder that simultaneously learns cell-cell topology representation and cluster assignments. We show that scMGCA is accurate and effective for cell segregation and batch effect correction, outperforming other state-of-the-art models across multiple platforms. In addition, we perform genomic interpretation on the key compressed transcriptomic space of the graph-embedding autoencoder to demonstrate the underlying gene regulation mechanism. We demonstrate that in a pancreatic ductal adenocarcinoma dataset, scMGCA successfully provides annotations on the specific cell types and reveals differential gene expression levels across multiple tumor-associated and cell signalling pathways.

Complement and Fungal Dysbiosis as Prognostic Markers and Potential Targets in PDAC Treatment

Pancreatic ductal adenocarcinoma (PDAC) is still hampered by a dismal prognosis. A better understanding of the tumor microenvironment within the pancreas and of the factors affecting its composition is of utmost importance for developing new diagnostic and treatment tools. In this context, the complement system plays a prominent role. Not only has it been shown to shape a T cell-mediated immune response, but it also directly affects proliferation and apoptosis of the tumor cells, influencing angiogenesis, metastatic spread and therapeutic resistance. This makes complement proteins appealing not only as early biomarkers of PDAC development, but also as therapeutic targets. Fungal dysbiosis is currently the new kid on the block in tumorigenesis with cancer-associated mycobiomes extracted from several cancer types. For PDAC, colonization with the yeast Malassezia seems to promote cancer progression, already in precursor lesions. One responsible mechanism appears to be complement activation via the lectin pathway. In the present article, we review the role of the complement system in tumorigenesis, presenting observations that propose it as the missing link between fungal dysbiosis and PDAC development. We also present the results of a small pilot study supporting the crucial interplay between the complement system and Malassezia colonization in PDAC pathogenesis.

Estimating Metastatic Risk of Pancreatic Ductal Adenocarcinoma at Single-Cell Resolution

Pancreatic ductal adenocarcinoma (PDAC) is characterized by intra-tumoral heterogeneity, and patients are always diagnosed after metastasis. Thus, finding out how to effectively estimate metastatic risk underlying PDAC is necessary. In this study, we proposed scMetR to evaluate the metastatic risk of tumor cells based on single-cell RNA sequencing (scRNA-seq) data. First, we identified diverse cell types, including tumor cells and other cell types. Next, we grouped tumor cells into three sub-populations according to scMetR score, including metastasis-featuring tumor cells (MFTC), transitional metastatic tumor cells (TransMTC), and conventional tumor cells (ConvTC). We identified metastatic signature genes (MSGs) through comparing MFTC and ConvTC. Functional enrichment analysis showed that up-regulated MSGs were enriched in multiple metastasis-associated pathways. We also found that patients with high expression of up-regulated MSGs had worse prognosis. Spatial mapping of MFTC showed that they are preferentially located in the cancer and duct epithelium region, which was enriched with the ductal cells' associated inflammation. Further, we inferred cell-cell interactions, and observed that interactions of the ADGRE5 signaling pathway, which is associated with metastasis, were increased in MFTC compared to other tumor sub-populations. Finally, we predicted 12 candidate drugs that had the potential to reverse expression of MSGs. Taken together, we have proposed scMetR to estimate metastatic risk in PDAC patients at single-cell resolution which might facilitate the dissection of tumor heterogeneity.

Exploitation and Verification of a Stroma- and Metastasis-Associated Risk Prognostic Signature in Pancreatic Adenocarcinoma

Pancreatic adenocarcinoma (PAAD), one of the most malignant tumors, not only has abundant mesenchymal components, but is also characterized by an extremely high metastatic risk. The purpose of this study was to construct a model of stroma- and metastasis-associated prognostic signature, aiming to benefit the existing clinical staging system and predict the prognosis of patients. First, stroma-associated genes were screened from the TCGA database with the ESTIMATE algorithm. Subsequently, transcriptomic data from clinical tissues in the RenJi cohort were screened for metastasis-associated genes. Integrating the two sets of genes, we constructed a risk prognostic signature by Cox and LASSO regression analysis. We then obtained a risk score by a quantitative formula and divided all samples into high- and low-risk groups based on the scores. The results demonstrated that patients with high-risk scores have a worse prognosis than those with low-risk scores, both in the TCGA database and in the RenJi cohort. In addition, tumor mutation burden, chemotherapeutic drug sensitivity and immune infiltration analysis also exhibited significant differences between the two groups. In exploring the potential mechanisms of how stromal components affect tumor metastasis, we simulated different matrix stiffness in vitro to explore its effect on EMT key genes in PAAD cells. We found that cancer cells stimulated by high matrix stiffness may trigger EMT and promote PAAD metastasis.

Complement C1QC as a potential prognostic marker and therapeutic target in colon carcinoma based on single-cell RNA sequencing and immunohistochemical analysis

Immune cell infiltration plays an essential role in the occurrence and development of colon cancer. However, the main tumor-associated immune cell infiltration and its gene regulation in colon cancer still need to be further clarified in order to provide a new perspective for diagnosing and treating this disease. For this study, single-cell RNA sequencing (scRNA-seq) expression profiles and TCGA colon cancer data sets were first acquired from the GEO database. Then, Seurat, Monocle, LIMMA, Clusterprofile, GSVA and GSEABase algorithms were used to systematically examine the data. Potential target drugs corresponding to target genes were analyzed in the Drugbank database and detected by molecular docking. Immunohistochemistry was used to assess the level of C1QC expression in the tissue microarray. Single cell analysis suggested that neutrophil activation might be the critical regulatory pathway in colon cancer and that macrophages were the main cell population involved. Subsequent functional enrichment analysis on differential genes in macrophages suggested that C1QC may be a critical regulatory factor in the occurrence and progression of colon cancer, and was closely related to the survival of patients. According to the drug target prediction, palivizumab is a targeted drug for C1QC, and molecular docking demonstrated that palivizumab binds to C1QC. Additionally, tissue-microarray based immunohistochemical analysis showed that C1QC was highly expressed in colon cancer tissue, and the prognosis of colon cancer patients with high C1QC expression was worse, closely related to age, lymphatic metastasis and the TNM stage (Tumor, Nodes and Metastases). Our findings suggest that C1QC may regulate the macrophages in colon cancer immune infiltration, which is expected to be a potential immunotherapy target for colon cancer, and beneficial for the diagnosis and prognosis of colon cancer patients.

A p300/GATA6 axis determines differentiation and Wnt dependency in pancreatic cancer models

Wnt signaling regulates the balance between stemness and differentiation in multiple tissues and in cancer. RNF43-mutant pancreatic cancers are dependent on Wnt production, and pharmacologic blockade of the pathway, e.g., by PORCN inhibitors, leads to tumor differentiation. However, primary resistance to these inhibitors has been observed. To elucidate potential mechanisms, we performed in vivo CRISPR screens in PORCN inhibitor-sensitive RNF43-mutant pancreatic cancer xenografts. As expected, genes in the Wnt pathway whose loss conferred drug resistance were identified, including APC, AXIN1, and CTNNBIP1. Unexpectedly, the screen also identified the histone acetyltransferase EP300 (p300), but not its paralog, CREBBP (CBP). We found that EP300 is silenced due to genetic alterations in all the existing RNF43-mutant pancreatic cancer cell lines that are resistant to PORCN inhibitors. Mechanistically, loss of EP300 directly downregulated GATA6 expression, thereby silencing the GATA6-regulated differentiation program and leading to a phenotypic transition from the classical subtype to the dedifferentiated basal-like/squamous subtype of pancreatic cancer. EP300 mutation and loss of GATA6 function bypassed the antidifferentiation activity of Wnt signaling, rendering these cancer cells resistant to Wnt inhibition.

Construction of ovarian metastasis-related immune signature predicting prognosis of gastric cancer patients

BACKGROUND

Ovarian metastasis (OM) results in poor survival of gastric cancer (GC) patients. While immunotherapy has emerged as a promising approach for late-stage GC, validated immune-related prognostic signatures still remain in need. In this study, we constructed an ovarian metastasis- and immune-related prognostic signature (OMIRPS), characterized the molecular and immune features of OMIRPS-categorized subgroups and predicted their potential response to immunotherapy.

METHODS

Three individual cohorts were used to construct and evaluate OMIRPS: RNA-seq of matched primary GC and OM from Fudan University Shanghai Cancer Center (FUSCC) (discovery cohort, n = 4), The Cancer Genome Atlas (TCGA) (training cohort, n = 544) and GSE84437 (validation cohort, n = 433). Differentially expressed genes (DEGs) identified between primary GC and OM and immune-related genes (IRGs) from the ImmPort and InnateDB databases were used to identify immune-related prognostic hub genes, which were further used to construct OMIRPS by using LASSO regression analysis. Prognosis, molecular characteristics, immune features, and differential immunotherapy efficacy between different OMIRPS subgroups were analyzed.

RESULTS

Functional analyses of DEGs revealed the significance of immune-related signatures and pathways in the OM. Immune-related prognostic hub genes including TNFRSF18, CARD11, BCL11B, NRP1, BNIP3L, and ATF3 were utilized to construct OMIRPS, which was identified as an independent prognostic factor. Comprehensive analyses unveiled the distinctive molecular and immune characteristics of OMIRPS-high and -low subgroup in regard to enriched pathways, mutation rate, tumor mutation burden, microsatellite instability status, infiltrated immune cell, immune exclusion score, and the prediction of immunotherapy efficacy. Additionally, OMIRPS was associated with Immune Subtypes with borderline significance.

CONCLUSIONS

RNA-seq of paired primary and ovarian metastatic tumors unveiled the significance of immune-related pathways and tumor immune microenvironment in OM. OMIRPS served as a promising biomarker to predict the prognosis of GC patients and distinguish the molecular features, immune characteristics, and efficacy of immunotherapy between different subgroups.

Oncogenic KRAS-Induced Feedback Inflammatory Signaling in Pancreatic Cancer: An Overview and New Therapeutic Opportunities

Pancreatic ductal adenocarcinoma (PDAC) remains highly refractory to treatment. While the KRAS oncogene is present in almost all PDAC cases and accounts for many of the malignant feats of PDAC, targeting KRAS or its canonical, direct effector cascades remains unsuccessful in patients. The recalcitrant nature of PDAC is also heavily influenced by its highly fibro-inflammatory tumor microenvironment (TME), which comprises an acellular extracellular matrix and various types of non-neoplastic cells including fibroblasts, immune cells, and adipocytes, underscoring the critical need to delineate the bidirectional signaling interplay between PDAC cells and the TME in order to develop novel therapeutic strategies. The impact of tumor-cell KRAS signaling on various cell types in the TME has been well covered by several reviews. In this article, we critically reviewed evidence, including work from our group, on how the feedback inflammatory signals from the TME impact and synergize with oncogenic KRAS signaling in PDAC cells, ultimately augmenting their malignant behavior. We discussed past and ongoing clinical trials that target key inflammatory pathways in PDAC and highlight lessons to be learned from outcomes. Lastly, we provided our perspective on the future of developing therapeutic strategies for PDAC through understanding the breadth and complexity of KRAS and the inflammatory signaling network.

Pre-clinical Models of Metastasis in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is a hostile solid malignancy coupled with an extremely high mortality rate. Metastatic disease is already found in most patients at the time of diagnosis, resulting in a 5-year survival rate below 5%. Improved comprehension of the mechanisms leading to metastasis is pivotal for the development of new targeted therapies. A key field to be improved are modeling strategies applied in assessing cancer progression, since traditional platforms fail in recapitulating the complexity of PDAC. Consequently, there is a compelling demand for new preclinical models that mirror tumor progression incorporating the pressure of the immune system, tumor microenvironment, as well as molecular aspects of PDAC. We suggest the incorporation of 3D organoids derived from genetically engineered mouse models or patients as promising new tools capable to transform PDAC pre-clinical modeling and access new frontiers in personalized medicine.

Serum C1q Levels Have Prognostic Value for Sepsis and are Related to the Severity of Sepsis and Organ Damage

Objective

To explore the clinical application value of serum complement component C1q levels in sepsis.

Methods

The clinical data and laboratory examination data of 320 research subjects (including 132 cases as sepsis group, 93 cases as nonsepsis group and 95 cases as control group) who were diagnosed and treated in Renmin Hospital of Wuhan University from July 2020 to March 2021 were collected. We compared the levels of each index among the three groups and further analyzed the C1q levels of different severity subgroups and different outcome subgroups of sepsis. Afterwards, we explored the correlation between C1q levels and SOFA score, organ damage indexes and coagulation indexes. Finally, the receiver operating characteristic curve (ROC) was used to analyze the prognostic value of C1q in patients with sepsis.

Results

C1q levels were significantly reduced in the serum of patients with sepsis; the level of C1q in the death group was lower than that in the survival group (127.1 mg/L vs 153.2 mg/L, P < 0.05), and the mortality in the C1q decreased group was higher when compared with C1q normal group; in addition, serum C1q levels were correlated with SOFA score, organ damage indexes and coagulation indexes; C1q had a high area under the curve (AUC) for the prognosis of sepsis, and the combination of other indexes can further improve the prognostic value.

Conclusion

Serum C1q levels have potential clinical value for the condition and prognosis of sepsis.

Pan-Cancer Analysis of Immune Complement Signature C3/C5/C3AR1/C5AR1 in Association with Tumor Immune Evasion and Therapy Resistance

Despite the advances in our understanding of the genetic and immunological basis of cancer, cancer remains a major public health burden with an ever-increasing incidence rate globally. Nevertheless, increasing evidence suggests that the components of the complement system could regulate the tumor microenvironment (TME) to promote cancer progression, recurrence, and metastasis. In the present study, we used an integrative multi-omics analysis of clinical data to explore the relationships between the expression levels of and genetic and epigenetic alterations in C3, C5, C3AR1, and C5AR1 and tumor immune evasion, therapy response, and patient prognosis in various cancer types. We found that the complements C3, C5, C3AR1, and C5AR1 have deregulated expression in human malignancies and are associated with activation of immune-related oncogenic processes and poor prognosis of cancer patients. Furthermore, we found that the increased expression levels of C3, C5, C3AR1, and C5AR1 were primarily predicted by copy number variation and gene methylation and were associated with dysfunctional T-cell phenotypes. Single nucleotide variation in the gene signature co-occurred with multiple oncogenic mutations and is associated with the progression of onco-immune-related diseases. Further correlation analysis revealed that C3, C5, C3AR1, and C5AR1 were associated with tumor immune evasion via dysfunctional T-cell phenotypes with a lesser contribution of T-cell exclusion. Lastly, we also demonstrated that the expression levels of C3, C5, C3AR1, and C5AR1 were associated with context-dependent chemotherapy, lymphocyte-mediated tumor killing, and immunotherapy outcomes in different cancer types. In conclusion, the complement components C3, C5, C3AR1, and C5AR1 serve as attractive targets for strategizing cancer immunotherapy and response follow-up.

Squamousness gain defines pancreatic ductal adenocarcinoma hepatic metastases phenotype, and gemcitabine response

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is a dismal disease with a survival rate of less than 7%, mainly due to the hepatic metastatic spread. Despite the importance of understanding PDAC metastases, central questions remain concerning their biology and chemosensitivity. Moreover, the transcriptomic divergence between primary tumor (PT) and hepatic metastases (HM) has been poorly studied and without a clear dissection of the confounding tumoral-surrounding tissue.

METHODS

Here, to unravel key biological features not biased by the surrounding tissue, we implemented a blind source separation based on independent component analysis, ProDenICA, on a treatment-naïve cohort of PDAC paired samples and a cohort of 305 resectable patients. In addition, a time-lapse experiment was performed to assess the gemcitabine chemosensitivity profile between the PT and HM.

RESULTS

We identified HM's specific transcriptomic characteristics related to the upregulation of cell cycle checkpoint, mitochondria activity, and extracellular matrix reorganization, which could be associated with metastatic niche adaptation mechanisms. Furthermore, squamous lineage emerged as a key feature linked with a downregulation in the epithelial-to-mesenchymal program that can stratifies PDAC HM independent of the classical/basal-like spectrum. Remarkably, we also demonstrated that gemcitabine response is influenced by the squamous profile, being the HM more refractory to the treatment than the PT.

CONCLUSIONS

These results pointed out divergent HM aspects compared to PT and allowed their stratification through the squamous lineage. Moreover, we unravel a clinical actionable squamous signature that predicts the gemcitabine response.

Involvement of Neutrophils in Metastatic Evolution of Pancreatic Neuroendocrine Tumors

Well-differentiated pancreatic neuroendocrine tumors (pNET) have an unpredictable natural history. The identification of both blood and tumor immune features associated with patients' outcomes remains limited. Herein, we evaluated the best prognostic value of the neutrophils-to-lymphocyte ratio (NLR) in a cohort of 144 pNETs. The NLR ≥ 4 was associated with worse overall survival in both univariate analysis (HR = 3.53, CI95% = 1.50-8.31, p = 0.004) and multivariate analysis (HR = 2.57, CI95% = 1.061-6.216, p = 0.036). The presence of synchronous liver metastasis was identified as a prognostic factor in multivariate analysis (HR = 3.35, CI95% = 1.411-7.973, p = 0.006). Interestingly, the absolute tumor-associated neutrophils count was higher in liver metastasis as compared to their paired primary tumor (p = 0.048). Deconvolution of immune cells from the transcriptome of 83 primary tumors and 30 liver metastases reveals enrichment for neutrophils in metastasis relative to primary tumors (p = 0.005), and this was associated with upregulation of the complement pathway (NES = 1.84, p < 0.0001). Combining neutrophils signature and complement pathway genes, unsupervised clustering identified two pNETs subgroups, namely Neu-Comp1 and Neu-Comp2. Characterized by neutrophils infiltration and activation of the complement pathway, Neu-Comp1 was highly enriched for metastatic liver samples as compared to Neu-Comp2 (p < 0.0001). These data suggest the possible link between liver metastasis, complement pathway activation, and neutrophils infiltration in well-differentiated pNET and open avenues for targeting complement pathways in these tumors.

ERO1L Promotes Hepatic Metastasis through Activating Epithelial-Mesenchymal Transition (EMT) in Pancreatic Cancer

Background

Endoplasmic reticulum oxidoreductase 1 alpha (ERO1L) serves as an effector for tumor growth in human malignancies. However, the mechanism of ERO1L on promoting metastasis of pancreatic ductal adenocarcinoma (PDAC) remains to be further explored.

Methods

Bioinformatics analysis of public databases and large-scale metastatic PDAC sequencing was performed to determine the expression profile and prognostic value of ERO1L in PDAC. The effect of ERO1L on metastasis of PDAC was analyzed in vitro and in vivo, via cell biological, molecular, and biochemical approaches.

Results

ERO1L in PDAC hepatic metastatic tissues were highly expressed and related to disease-free survival (DFS). Genetic silencing and pharmacological inhibition of ERO1L with EN460 suppressed cell migration and invasion of PDAC. Furthermore, EN460 also suppressed hepatic metastasis of PDAC in vivo. Using shRNAs and EN460 to inhibit the ERO1L expression in Capan-2 and MiaPaca-2 led to the remarkable change of EMT-related protein Vimentin and E-cadherin, which indicated that EMT acted as a key pathway for ERO1L to promote invasion, dissemination, colonization, and growth of hepatic metastasis in PDAC.

Conclusion

Our findings uncover ERO1L contributes to hepatic metastasis in PDAC via epithelial-mesenchymal transition (EMT) process and indicate a promising therapeutic strategy for PDAC hepatic metastasis.