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

Dynamic immunoediting by macrophages in homologous recombination deficiency-stratified pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease, notably resistant to existing therapies. Current research indicates that PDAC patients deficient in homologous recombination (HR) benefit from platinum-based treatments and poly-ADP-ribose polymerase inhibitors (PARPi). However, the effectiveness of PARPi in HR-deficient (HRD) PDAC is suboptimal, and significant challenges remain in fully understanding the distinct characteristics and implications of HRD-associated PDAC. We analyzed 16 PDAC patient-derived tissues, categorized by their homologous recombination deficiency (HRD) scores, and performed high-plex immunofluorescence analysis to define 20 cell phenotypes, thereby generating an in-situ PDAC tumor-immune landscape. Spatial phenotypic-transcriptomic profiling guided by regions-of-interest (ROIs) identified a crucial regulatory mechanism through localized tumor-adjacent macrophages, potentially in an HRD-dependent manner. Cellular neighborhood (CN) analysis further demonstrated the existence of macrophage-associated high-ordered cellular functional units in spatial contexts. Using our multi-omics spatial profiling strategy, we uncovered a dynamic macrophage-mediated regulatory axis linking HRD status with SIGLEC10 and CD52. These findings demonstrate the potential of targeting CD52 in combination with PARPi as a therapeutic intervention for PDAC.

Identification of potential immune-related mechanisms related to the development of multiple myeloma

BACKGROUND

Although significant advances have been made in the treatment of multiple myeloma (MM), leading to unprecedented response and survival rates among patients, the majority eventually relapse, and a cure remains elusive. This situation is closely related to an incomplete understanding of the immune microenvironment, especially monocytes/macrophages in patients with treatment-naïve MM. The aim of this study was to provide insight into the immune microenvironment, especially monocytes/macrophages, in patients with treatment-naïve MM.

METHODS

This study used the single-cell RNA sequencing (scRNA-seq) data of both patients with MM and heathy donors to identify immune cells, including natural killer (NK) cells, T cells, dendritic cells (DCs), and monocytes/macrophages. Transcriptomic data and flow cytometry analysis of monocytes/macrophages were used to further examine the effect of monocytes/macrophages in treatment-naïve MM patients.

RESULTS

A significant difference was observed between the bone marrow (BM) immune cells of the healthy controls and treatment-naïve MM patients through scRNA-seq. It is noteworthy that, through an scRNA-seq data analysis, this study found that interferon (IFN)-induced NK/T cells, terminally differentiated effector memory (TEMRA) cells, T-helper cells characterized by expression of IFN-stimulated genes (ISG + Th cells), IFN-responding exhausted T cells, mannose receptor C-type 1 (MRC1) + DCs, IFN-responding DCs, MHCII + DCs, and immunosuppressive monocytes/macrophages were enriched in patients with treatment-naïve MM. Significantly, transcriptomic data of monocytes/macrophages demonstrated that "don't eat me"-related genes and IFN-induced genes increase in treatment-naïve MM patients. Furthermore, scRNA-seq, transcriptomic data, and flow cytometry also showed an increased proportion of CD16 + monocytes/macrophages and expression level of CD16. Cell-cell communication analysis indicated that monocytes/macrophages, whose related important signaling pathways include migration inhibitory factor (MIF) and interleukin 16 (IL-16) signaling pathway, are key players in treatment-naïve MM patients.

CONCLUSIONS

Our findings provide a comprehensive and in-depth molecular characterization of BM immune cell census in MM patients, especially for monocytes/macrophages. Targeting macrophages may be a novel treatment strategy for patients with MM.

The EFNA4 gene is a potential prognostic biomarker in pancreatic cancer: a bioinformatics analysis

Background

Pancreatic cancer is a highly aggressive malignancy with poor prognosis, and there is an urgent need to understand its molecular mechanisms for early diagnosis and treatment. Despite surgical resection being the only effective treatment, most patients are diagnosed at an advanced stage, missing the optimal window for therapy. Identifying novel biomarkers is crucial for prognostic assessment, treatment planning, and early intervention. Ephrin A4 (EFNA4), a member of the receptor tyrosine kinase family, is involved in vascular and epithelial development via regulation of cell migration and rejection. However, the role of EFNA4 in pancreatic cancer has not been reported. Therefore, our study aimed to clarify the role of EFNA4 in pancreatic cancer through bioinformatics analysis and vitro experiments.

Methods

The expression of EFNA4 and its potential value as a diagnostic and prognostic biomarker in pancreatic cancer was analyzed using data from The Cancer Genome Atlas (TCGA) and the Gene Expression Profiling Interactive Analysis (GEPIA) database. According to the expression level of EFNA4, patients were divided into high expression group and low expression group, and the correlation between overall survival (OS) and disease-free survival (DFS) with different expression levels of EFNA4 and clinical parameters were analyzed. Subsequently, reverse-transcription quantitative polymerase chain reaction (RT-qPCR) was performed to detect EFNA4 expression. The proliferation, invasion, and cloning ability of the cells were detected via Cell Counting Kit 8 (CCK8), Transwell, and plate cloning assays, respectively.

Results

EFNA4 is highly expressed in pancreatic cancer, and upregulation of EFNA4 is associated with poor prognosis. In this study, EFNA4 expression was correlated with T stage and TNM (tumor-node-metastasis) stage of pancreatic cancer, and the median survival time and progression-free survival (PFS) were worse in those with high EFNA4 expression (394 days) than in those with low expression (525 days) [hazard ratio (HR): 1.47, 95% confidence interval (CI): 1.00-2.16, P=0.047]. In addition, EFNA4 was also found to be involved in the regulation of signal pathways such as cell adhesion, cyclic AMP, insulin secretion, pancreatic secretion, and protein digestion and absorption. In vitro experiments demonstrated that EFNA4 knockdown significantly inhibited the proliferation, cloning ability, and invasiveness of the PANC-1 and SW1990 pancreatic cancer cell lines.

Conclusions

The abnormal expression of EFNA4 in pancreatic cancer is associated with poor prognosis. Knockout of EFNA4 gene could significantly inhibit the proliferation and invasion of pancreatic cancer cells. Therefore, EFNA4 may be one of the molecular targets for poor prognosis of patients with pancreatic cancer.

Identification and prognostic analysis of ferroptosis‑related gene HSPA5 to predict the progression of lung squamous cell carcinoma

Ferroptosis, an iron-dependent form of regulated cell death driven by excessive lipid peroxidation, is implicated in the development and therapeutic responses of cancer. However, the role of ferroptosis-related gene profiles in lung squamous cell carcinoma (LSCC) remains largely unknown. The present study aimed to identify the prognostic roles of ferroptosis-related genes in LSCC. Sequencing data from the Cancer Genome Atlas were analyzed and ferroptosis-related gene expression between tumor and para-tumor tissue was identified. The prognostic role of these genes was also assessed using Kaplan-Meier analyses and univariate and multivariate Cox proportional hazards regression model analyses. Immunological correlation, tumor stemness, drug sensitivity and the transcriptional differences of heat shock protein (HSP)A5 in LSCC were also analyzed. Thereafter, the expression of HSPA5 in 100 patients with metastatic LSCC was evaluated using immunohistochemistry (IHC) and the clinical significance of these markers with different risk factors was assessed. Of the 22 ferroptosis-related genes, the expression of HSPA5, HSPB1, glutathione peroxidase 4, Fanconi anemia complementation group D2, CDGSH iron sulfur domain 1, farnesyl-diphosphate farnesyltransferase 1, nuclear factor erythroid 2 like 2, solute carrier (SLC)1A5, ribosomal protein L8, nuclear receptor coactivator 4, transferrin receptor and SLC7A11 was significantly increased in LSCC compared with adjacent tissues. However, only high expression of HSPA5 was able to predict progression-free survival (PFS) and disease-free survival in LSCC. Although HSPA5 was also significantly elevated in patients with lung adenocarcinoma, HSPA5 expression did not predict the prognosis of patients with lung adenocarcinoma. Of note, a higher expression of HSPA5 was related to higher responses to chemotherapy but not to immunotherapy. In addition, HSPA5 expression was positively correlated with 'ferroptosis', 'cellular responses to hypoxia', 'tumor proliferation signature', 'G2M checkpoint', 'MYC targets' and 'TGFB'. IHC analysis also demonstrated that a high expression of HSPA5 in patients with metastatic LSCC in the study cohort was associated with shorter PFS and overall survival. In conclusion, the present study demonstrated that the expression of the ferroptosis-related gene HSPA5 may be a negative prognostic marker for LSCC.

Emerging Prognostic and Predictive Significance of Stress Keratin 17 in HPV-Associated and Non HPV-Associated Human Cancers: A Scoping Review

A growing body of literature suggests that the expression of cytokeratin 17 (K17) correlates with inferior clinical outcomes across various cancer types. In this scoping review, we aimed to review and map the available clinical evidence of the prognostic and predictive value of K17 in human cancers. PubMed, Web of Science, Embase (via Scopus), Cochrane Central Register of Controlled Trials, and Google Scholar were searched for studies of K17 expression in human cancers. Eligible studies were peer-reviewed, published in English, presented original data, and directly evaluated the association between K17 and clinical outcomes in human cancers. Of the 1705 studies identified in our search, 58 studies met criteria for inclusion. Studies assessed the prognostic significance (n = 54), predictive significance (n = 2), or both the prognostic and predictive significance (n = 2). Altogether, 11 studies (19.0%) investigated the clinical relevance of K17 in cancers with a known etiologic association to HPV; of those, 8 (13.8%) were focused on head and neck squamous cell carcinoma (HNSCC), and 3 (5.1%) were focused on cervical squamous cell carcinoma (SCC). To date, HNSCC, as well as triple-negative breast cancer (TNBC) and pancreatic cancer, were the most frequently studied cancer types. K17 had prognostic significance in 16/17 investigated cancer types and 43/56 studies. Our analysis suggests that K17 is a negative prognostic factor in the majority of studied cancer types, including HPV-associated types such as HNSCC and cervical cancer (13/17), and a positive prognostic factor in 2/17 studied cancer types (urothelial carcinoma of the upper urinary tract and breast cancer). In three out of four predictive studies, K17 was a negative predictive factor for chemotherapy and immune checkpoint blockade therapy response.

Identification and characterization of interferon-γ signaling-based personalized heterogeneity and therapeutic strategies in patients with pancreatic cancer

Background

Interferon-γ (IFN-γ) is a key cytokine with diverse biological functions, including antiviral defense, antitumor activity, immune regulation, and modulation of cellular processes. Nonetheless, its role in pancreatic cancer (PC) therapy remains debated. Therefore, it is worthwhile to explore the role of Interferon-γ related genes (IFN-γGs) in the progression of PC development.

Methodology

Transcriptomic data from 930 PC were sourced from TCGA, GEO, ICGC, and ArrayExpress, and 93 IFN-γGs were obtained from the MSigDB. We researched the characteristics of IFN-γGs in pan-cancer. Subsequently, the cohort of 930 PC was stratified into two distinct subgroups using the NMF algorithm. We then examined disparities in the activation of cancer-associated pathways within these subpopulations through GSVA analysis. We scrutinized immune infiltration in both subsets and probed classical molecular target drug sensitivity variations. Finally, we devised and validated a novel IFN-γ related prediction model using LASSO and Cox regression analyses. Furthermore, we conducted RT-qPCR and immunohistochemistry assays to validate the expression of seven target genes included in the prediction model.

Results

We demonstrated the CNV, SNV, methylation, expression levels, and prognostic characteristics of IFN-γGs in pan-cancers. Notably, Cluster 2 demonstrated superior prognostic outcomes and heightened immune cell infiltration compared to Clusters 1. We also assessed the IC50 values of classical molecular targeted drugs to establish links between IFN-γGs expression levels and drug responsiveness. Additionally, by applying our prediction model, we segregated PC patients into high-risk and low-risk groups, identifying potential benefits of cisplatin, docetaxel, pazopanib, midostaurin, epothilone.B, thapsigargin, bryostatin.1, and AICAR for high-risk PC patients, and metformin, roscovitine, salubrinal, and cyclopamine for those in the low-risk group. The expression levels of these model genes were further verified through HPA website data and qRT-PCR assays in PC cell lines and tissues.

Conclusion

This study unveils IFN-γGs related molecular subsets in pancreatic cancer for the first time, shedding light on the pivotal role of IFN-γGs in the progression of PC. Furthermore, we establish an IFN-γGs related prognostic model for predicting the survival of PC, offering a theoretical foundation for exploring the precise mechanisms of IFN-γGs in PC.

Transcriptome analysis of divergent residual feed intake phenotypes in the M. longissimus thoracis et lumborum of Wannan Yellow rabbits

Introduction: Feed efficiency is an important economic trait in rabbit meat production. The identification of molecular mechanisms and candidate genes for feed efficiency may improve the economic and environmental benefits of the rabbit meat industry. As an alternative to the conventional feed conversion ratio, residual feed intake (RFI) can be used as an accurate indicator of feed efficiency. Methods: RNA sequencing was used to identify the differentially expressed genes (DEGs) in the M. longissimus thoracis et lumborum of eight Wannan Yellow rabbits with excessively high or low RFIs (HRFI or LRFI, respectively). Thereafter, Gene Ontology (GO) analysis, enrichment using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, gene set enrichment analysis (GSEA), and protein-protein interaction (PPI) network analysis was conducted. Results: In total, 445 DEGs were identified in the M. longissimus thoracis et lumborum of rabbits with high and low RFIs. The significantly enriched GO terms identified in these two groups were primarily involved in energy and mitochondrial metabolism and oxidation-reduction processes. KEGG analysis identified 11 significantly enriched pathways, including oxidative phosphorylation, PI3K-Akt signaling, and extracellular matrix-receptor interaction pathways. According to GSEA, the expressions of genes and pathways related to mitochondrial function were upregulated in HRFI rabbits, whereas genes with upregulated expressions in LRFI rabbits were related to immune response and energy metabolism. Additionally, PPI network analysis revealed five potential candidate genetic markers. Conclusion: Comparative analysis of the M. longissimus thoracis et lumborum transcriptomes in HRFI and LRFI rabbits revealed FOS, MYC, PRKACB, ITGA2, and FN1 as potential candidate genes that affect feed efficiency in rabbits. In addition, key signaling pathways involved in oxidative phosphorylation and PI3K-Akt and ECM-receptor interaction signaling impact rabbit feed efficiency. These findings will aid in breeding programs to improve feed efficiency and optimize RFI selection of rabbits for meat production.

Matrix metalloproteinase 1 is a poor prognostic biomarker for patients with hepatocellular carcinoma

Hepatocellular carcinoma (HCC) remains an incurable malignancy despite the treatment methods being continually updated. Matrix metalloproteinases (MMPs) promote the progression of HCC; however, no consensus exists on which MMP plays the predominant role in HCCs. In the present study, we analyzed differentially expressed genes in HCCs, especially MMPs, compared with adjacent tissues using the Cancer Genome Atlas database. The KEGG enrichment pathway using differentially expressed genes included extracellular matrix-receptor interaction, which was correlated with MMPs. We found that among the MMP family, only MMP1, MMP3, MMP8, MMP9, MMP11, MMP12, MMP14, MMP15, MMP20, MMP21, and MMP24 significantly increased in HCCs compared with adjacent tissues. Crucially, survival and univariate analyses indicated that only MMPs 1, 9, 12, and 14 predict poor overall survival; however, multivariate Cox analysis and a nomogram demonstrated that only MMP1 is a poor prognostic biomarker for HCCs. In addition, we observed significant enrichment of uncharacterized cells but decreased macrophages in HCC tissues. Consistent with decreased macrophages in HCCs, MMP1 was negatively associated with macrophages but positively correlated with uncharacterized cells, indicating that the main producer of MMP1 is uncharacterized cells. Furthermore, MMP1 expression was negatively correlated with immune responses of HCCs. Taken together, our findings indicated that MMP1 is a poor and predominant prognostic biomarker for patients with HCC and that anti-MMP1 may be a novel therapy that is worth studying in depth.

Irreversible electroporation combined with chemotherapy and PD-1/PD-L1 blockade enhanced antitumor immunity for locally advanced pancreatic cancer

Background

Irreversible electroporation (IRE) is a novel local tumor ablation approach with the potential to stimulate an antitumor immune response. However, it is not effective in preventing distant metastasis in isolation. This study aimed to compare the potential of augmenting the antitumor immune response in patients with locally advanced pancreatic cancer (LAPC) who underwent IRE combined with chemotherapy and PD-1/PD-L1 blockade with those who underwent IRE combined with chemotherapy.

Methods

A retrospective review was conducted on LAPC patients treated either with IRE in combination with chemotherapy and PD-1/PD-L1 blockade (group A) or with IRE with chemotherapy alone (group B) from July 2015 to June 2021. The primary outcomes were overall survival (OS) and progression-free survival (PFS), with immune responses and adverse events serving as secondary endpoints. Risk factors for OS and PFS were identified using univariate and multivariate analyses.

Results

A total of 103 patients were included in the final analysis, comprising 25 in group A and 78 in group B. The median duration of follow-up was 18.2 months (3.0-38.6 months). Group A patients demonstrated improved survival compared to group B (median OS: 23.6 vs. 19.4 months, p = 0.001; median PFS: 18.2 vs. 14.7 months, p = 0.022). The data suggest a robust immune response in group A, while adverse events related to the treatment were similar in both groups. The multivariate analysis identified the combination of IRE, chemotherapy, and PD-1/PD-L1 blockade as an independent prognostic factor for OS and PFS.

Conclusion

The addition of PD-1/PD-L1 blockade to the regimen of IRE combined with chemotherapy enhanced antitumor immunity and extended survival in LAPC patients.

Contributions of bone marrow monocytes/macrophages in myeloproliferative neoplasms with JAK2V617F mutation

The classic BCR-ABL1-negative myeloproliferative neoplasm (MPN) is a highly heterogeneous hematologic tumor that includes three subtypes, namely polycythemia vera (PV), essential thrombocytosis (ET), and primary myelofibrosis (PMF). Despite having the same JAK2^V617F mutation, the clinical manifestations of these three subtypes of MPN differ significantly, which suggests that the bone marrow (BM) immune microenvironment may also play an important role. In recent years, several studies have shown that peripheral blood monocytes play an important role in promoting MPN. However, to date, the role of BM monocytes/macrophages in MPN and their transcriptomic alterations remain incompletely understood. The purpose of this study was to clarify the role of BM monocytes/macrophages in MPN patients with the JAK2^V617F mutation. MPN patients with the JAK2^V617F mutation were enrolled in this study. We investigated the roles of monocytes/macrophages in the BM of MPN patients, using flow cytometry, monocyte/macrophage enrichment sorting, cytospins and Giemsa-Wright staining, and RNA-seq. Pearson correlation coefficient analysis was also used to detect the correlation between BM monocytes/macrophages and the MPN phenotype. In the present study, the proportion of CD163⁺ monocytes/macrophages increased significantly in all three subtypes of MPN. Interestingly, the percentages of CD163⁺ monocytes/macrophages are positively correlated with HGB in PV patients and PLT in ET patients. In contrast, the percentages of CD163⁺ monocytes/macrophages are negatively correlated with HGB and PLT in PMF patients. It was also found that CD14⁺CD16⁺ monocytes/macrophages increased and correlated with MPN clinical phenotypes. RNA-seq analyses demonstrated that the transcriptional expressions of monocytes/macrophages in MPN patients are relatively distinct. Gene expression profiles of BM monocytes/macrophages suggest a specialized function in support of megakaryopoiesis in ET patients. In contrast, BM monocytes/macrophages yielded a heterogeneous status in the support or inhibition of erythropoiesis. Significantly, BM monocytes/macrophages shaped an inflammatory microenvironment, which, in turn, promotes myelofibrosis. Thus, we characterized the roles of increased monocytes/macrophages in the occurrence and progression of MPNs. Our findings of the comprehensive transcriptomic characterization of BM monocytes/macrophages provide important resources to serve as a basis for future studies and future targets for the treatment of MPN patients.

S100A10 Promotes Pancreatic Ductal Adenocarcinoma Cells Proliferation, Migration and Adhesion through JNK/LAMB3-LAMC2 Axis

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive tumors, characterized by diagnosis at an advanced stage and a poor prognosis. As a member of the S100 protein family, S100A10 regulates multiple biological functions related to cancer progression and metastasis. However, the role of S100A10 in PDAC is still not completely elucidated. In this study, we reported that S100A10 was significantly up-regulated in PDAC tissue and associated with a poor prognosis by integrated bioinformatic analysis and human PDAC tissue samples. In vitro, down-regulation of S100A10 reduced the proliferation, migration, and adhesion of PDAC cell lines, whereas up-regulation of S100A10 showed the opposite effect. Furthermore, LAMB3 was proved to be activated by S100A10 using RNA-sequencing and western blotting. The effect of LAMB3 on the proliferation, migration, and adhesion of PDAC cells was similar to that of S100A10. Up-regulation or down-regulation of LAMB3 could reverse the corresponding effect of S100A10. Moreover, we validated S100A10 activates LAMB3 through the JNK pathway, and LAMB3 was further proved to interact with LAMC2. Mice-bearing orthotopic pancreatic tumors showed that S100A10 knocked-down PANC-1 cells had a smaller tumor size than the control group. In conclusion, S100A10 promotes PDAC cells proliferation, migration, and adhesion through JNK/LAMB3-LAMC2 axis.

Developing and validating a survival prediction model based on blood exosomal ceRNA network in patients with PAAD

BACKGROUND

Among the most lethal cancers, pancreatic adenocarcinoma (PAAD) is an essential component of digestive system malignancies that still lacks effective diagnosis and treatment methods. As exosomes and competing endogenous RNA (ceRNA) regulatory networks in tumors go deeper, we expect to construct a ceRNA regulatory network derived from blood exosomes of PAAD patients by bioinformatics methods and develop a survival prediction model based on it.

METHODS

Blood exosome sequencing data of PAAD patients and normal controls were downloaded from the exoRbase database, and the expression profiles of exosomal mRNA, lncRNA, and circRNA were differentially analyzed by R. The related mRNA, circRNA, lncRNA, and their corresponding miRNA prediction data were imported into Cytoscape software to visualize the ceRNA network. Then, we conducted GO and KEGG enrichment analysis of mRNA in the ceRNA network. Genes that express differently in pancreatic cancer tissues compared with normal tissues and associate with survival (P < 0.05) were determined as Hub genes by GEPIA. We identified optimal prognosis-related differentially expressed mRNAs (DEmRNAs) and generated a risk score model by performing univariate and multivariate Cox regression analyses.

RESULTS

205 DEmRNAs, 118 differentially expressed lncRNAs (DElncRNAs), and 98 differentially expressed circRNAs (DEcircRNAs) were screened out. We constructed the ceRNA network, and a total of 26 mRNA nodes, 7 lncRNA nodes, 6 circRNA nodes, and 16 miRNA nodes were identified. KEGG enrichment analysis showed that the DEmRNAs in the regulatory network were mainly enriched in Human papillomavirus infection, PI3K-Akt signaling pathway, Osteoclast differentiation, and ECM-receptor interaction. Next, six hub genes (S100A14, KRT8, KRT19, MAL2, MYO5B, PSCA) were determined through GEPIA. They all showed significantly increased expression in cancer tissues compared with control groups, and their high expression pointed to adverse survival. Two optimal prognostic-related DEmRNAs, MYO5B (HR = 1.41, P < 0.05) and PSCA (HR = 1.10, P < 0.05) were included to construct the survival prediction model.

CONCLUSION

In this study, we successfully constructed a ceRNA regulatory network in blood exosomes from PAAD patients and developed a two-gene survival prediction model that provided new targets which shall aid in diagnosing and treating PAAD.

Targeting macrophages: a novel treatment strategy in solid tumors

In the tumor microenvironment (TME), tumor-associated macrophages (TAMs) are the most abundant immune cells, which act as a key regulator in tumorigenesis and progression. Increasing evidence have demonstrated that the TME alters the nature of macrophages to maintain dynamic tissue homeostasis, allowing TAMs to acquire the ability to stimulate angiogenesis, promote tumor metastasis and recurrence, and suppress anti-tumor immune responses. Furthermore, tumors with high TAM infiltration have poor prognoses and are resistant to treatment. In the field of solid tumor, the exploration of tumor-promoting mechanisms of TAMs has attracted much attention and targeting TAMs has emerged as a promising immunotherapeutic strategy. Currently, the most common therapeutic options for targeting TAMs are as follows: the deletion of TAMs, the inhibition of TAMs recruitment, the release of phagocytosis by TAMs, and the reprogramming of macrophages to remodel their anti-tumor capacity. Promisingly, the study of chimeric antigen receptor macrophages (CAR-Ms) may provide even greater benefit for patients with solid tumors. In this review, we discuss how TAMs promote the progression of solid tumors as well as summarize emerging immunotherapeutic strategies that targeting macrophages.

Blockade of the protease ADAM17 ameliorates experimental pancreatitis

Acute and chronic pancreatitis, the latter associated with fibrosis, are multifactorial inflammatory disorders and leading causes of gastrointestinal disease-related hospitalization. Despite the global health burden of pancreatitis, currently, there are no effective therapeutic agents. In this regard, the protease A Disintegrin And Metalloproteinase 17 (ADAM17) mediates inflammatory responses through shedding of bioactive inflammatory cytokines and mediators, including tumor necrosis factor α (TNFα) and the soluble interleukin (IL)-6 receptor (sIL-6R), the latter of which drives proinflammatory IL-6 trans-signaling. However, the role of ADAM17 in pancreatitis is unclear. To address this, Adam17^ex/ex mice-which are homozygous for the hypomorphic Adam17^ex allele resulting in marked reduction in ADAM17 expression-and their wild-type (WT) littermates were exposed to the cerulein-induced acute pancreatitis model, and acute (1-wk) and chronic (20-wk) pancreatitis models induced by the cigarette smoke carcinogen nicotine-derived nitrosamine ketone (NNK). Our data reveal that ADAM17 expression was up-regulated in pancreatic tissues of animal models of pancreatitis. Moreover, the genetic (Adam17^ex/ex mice) and therapeutic (ADAM17 prodomain inhibitor [A17pro]) targeting of ADAM17 ameliorated experimental pancreatitis, which was associated with a reduction in the IL-6 trans-signaling/STAT3 axis. This led to reduced inflammatory cell infiltration, including T cells and neutrophils, as well as necrosis and fibrosis in the pancreas. Furthermore, up-regulation of the ADAM17/IL-6 trans-signaling/STAT3 axis was a feature of pancreatitis patients. Collectively, our findings indicate that the ADAM17 protease plays a pivotal role in the pathogenesis of pancreatitis, which could pave the way for devising novel therapeutic options to be deployed against this disease.

Identification of macrophage correlated biomarkers to predict the prognosis in patients with intrahepatic cholangiocarcinoma

Background

It has been shown that tumor-associated immune cells, particularly macrophages, play a fundamental role in the development and treatment response of intrahepatic cholangiocarcinoma (ICC). However, little is known about macrophages at the single cellular level of ICC patients.

Methods

ScRNA-seq from Zhang et al. was used in the present study to identify the genes differentially expressed in ICCs. Furthermore, transcriptomic data from TCGA datasets, IHC and flowcytometry from our cohort were used to confirm the findings. Kaplan-Meier and TIDE scores were also used for prognostic analysis and ICB responses.

Results

A significant number of macrophages were found in ICCs as compared to adjacent tissues. We then extracted, processed, and classified the macrophages from the ICCs and adjacent tissues into 12 clusters. Significantly, the macrophages from the ICC exhibited an immunosuppressed state in terms of both signature gene expression and functional enrichment. Furthermore, our results indicate that, of the 10 selective tumor-promoting genes of macrophages, only MMP19 and SIRPα can predict ICB responses in ICCs. Although a higher expression of MMP19 and SIRPα predict a poor prognosis for ICCs without immunotherapy after surgery, patients with high SIRPα expression were more sensitive to immunotherapy, whereas those with high MMP19 expression were not sensitive to immunotherapy. To define the mechanisms, we found that SIRPα^hi ICCs exhibited an increased enrichment KEGG pathway of leukocyte transendothelial migration and neutrophil extracellular trap formation. The increased immune cell infiltration will increase sensitivity to immunotherapy.

Conclusion

Collectively, macrophages are critical to the immune status of ICCs, and MMP19 and SIRPα can predict prognosis and ICB responses for ICCs.

Identification of a Novel Risk Model: A Five-Gene Prognostic Signature for Pancreatic Cancer

Objective. Biomarkers for pancreatic cancer (PCa) prognosis provide evidence for improving the survival outcome of this disease. This study aimed to identify a prognostic risk model based on gene expression profiling of microarray bioinformatics analysis. Methods. Prognostic immune genes in the TCGA-PAAD cohort were identified using the univariate Cox regression and Kaplan–Meier survival analysis. Multivariate Cox regression (stepAIC) was used to identify prognostic genes from the top 20 hub genes in the protein-protein interaction (PPI) network. A prognostic risk model was established and its performance in predicting the overall survival in PCa was validated in GSE62452. Gene mutations and infiltration immune cells in PCa tumors were analyzed using online databases. Results. Univariate Cox regression and Kaplan–Meier survival analyses identified 128 prognostic genes. Multivariate Cox regression (stepAIC) identified five prognostic genes (PLCG1, MET, TNFSF10, CXCL9, and TLR3) out of the 20 hub genes in the PPI network. A prognostic risk model was established using the signature of five genes. This model had moderate to high accuracies (AUC > 0.700) in predicting 3-year and 5-year overall survival in TCGA and GSE62452 cohorts. The Kaplan–Meier survival analysis showed that high-risk scores were correlated with poor survival outcomes in PCa ( $p<0.05$ ). Also, mutations in the five genes were related to poor survival. The five genes were related to multiple immune cells. Conclusions. The prognostic risk model was significantly correlated with the survival in PCa patients. This model modulated PCa tumor progression and prognosis by regulating immune cell infiltration.