Single-cell transcriptomics reveals heterogeneous progression and EGFR activation in pancreatic adenosquamous carcinoma

Co-expression of immune checkpoints in glioblastoma revealed by single-nucleus RNA sequencing and spatial transcriptomics

Glioblastoma (GBM) is one of the most malignant tumors of the central nervous system. The pattern of immune checkpoint expression in GBM remains largely unknown. We performed snRNA-Seq and spatial transcriptomic (ST) analyses on untreated GBM samples. 8 major cell types were found in both tumor and adjacent normal tissues, with variations in infiltration grade. Neoplastic cells_6 was identified in malignant cells with high expression of invasion and proliferator-related genes, and analyzed its interactions with microglia, MDM cells and T cells. Significant alterations in ligand-receptor interactions were observed, particularly between Neoplastic cells_6 and microglia, and found prominent expression of VISTA/VSIG3, suggesting a potential mechanism for evading immune system attacks. High expression of TIM-3, VISTA, PSGL-1 and VSIG-3 with similar expression patterns in GBM, may have potential as therapeutic targets. The prognostic value of VISTA expression was cross-validated in 180 glioma patients, and it was observed that patients with high VISTA expression had a poorer prognosis. In addition, multimodal cross analysis integrated SnRNA-seq and ST, revealing complex intracellular communication and mapping the GBM tumor microenvironment. This study reveals novel molecular characteristics of GBM, co-expression of immune checkpoints, and potential therapeutic targets, contributing to improving the understanding and treatment of GBM.

Whole transcriptome scanning and validation of negatively related genes in UC-MSCs

Background

Human umbilical cord mesenchymal stem cells (UC-MSCs) are one of the most extensively researched stem cell types due to their potential for multi-lineage differentiation, secretion of regenerative factors, modulations of immunological activities, and the release of regenerative substances and influence immunological processes. Since UC-MSCs must be cultivated on a large scale for clinical use, selecting the appropriate storing passage, such as the usage-based passage of UC-MSCs, is critical for long-term autologous or allogeneic usage. Long-term cultivation of stem cells, on the other hand, causes them to lose their pluripotent differentiation capacity. As a result, distinguishing between high and low passages of UC-MSCs and identifying the particular variations associated with stem cells and their modes of action is essential for regenerative medicine. Therefore, we investigated the biological features and transcriptional changes of UC-MSCs over passages.

Methods

UC-MSCs were isolated from the tissues of the human umbilical cord, and UC-MSCs from five passages (P1, P3, P5, P10 and P15) with three repetitions were compared and identified based on morphology, cell markers, differentiation capacity, and aging-related characteristics. It was previously assumed that the phenotype of cells before the P10 passage was stable, defined as early passage, and that culture could be continued until the 15th passage, defined as late passage. Next, the five passages of UC-MSCs were sequenced using high-throughput complete transcriptome sequencing. Fuzzy C-Means Clustering (FCM) and Weighted Gene Co-expression Network Analysis (WGCNA) were used to find hub genes, and gene silencing was performed to investigate the impact of missing genes on the stemness of UC-MSC cells.

Results

UC-MSCs of different passages displayed similar surface markers, including CD73, CD105, CD90, CD34, CD45 and HLA-DR. However, the proliferation time of late-phase UC-MSCs was longer than that of early-phase UC-MSCs, and the expression of the senescence-associated (SA)-β-gal staining marker was higher. At the same time, pluripotency markers (NANOG, OCT4, SOX2 and KIF4A) were down-regulated, and the multi-differentiation potential was reduced. Meanwhile, KIFC1 and UBE2C were down-regulated in late-phase UC-MSCs, which were involved in the maintenance of stemness.

Conclusions

KIFC1 and UBE2C were highly expressed in early-UC-MSCs and showed a downward gradient trend with cell expansion in vitro. They regulated UC-MSC proliferation, colony sphere formation, multiple differentiation, stemness maintenance, and other biological manifestations. Therefore, they are anticipated to be new biomarkers for UC-MSCs quality identification in regenerative medicine applications.

Cell of Origin of Pancreatic cancer: Novel Findings and Current Understanding

ABSTRACT

Pancreatic ductal adenocarcinoma (PDAC) stands as one of the most lethal diseases globally, boasting a grim 5-year survival prognosis. The origin cell and the molecular signaling pathways that drive PDAC progression are not entirely understood. This review comprehensively outlines the categorization of PDAC and its precursor lesions, expounds on the creation and utility of genetically engineered mouse models used in PDAC research, compiles a roster of commonly used markers for pancreatic progenitors, duct cells, and acinar cells, and briefly addresses the mechanisms involved in the progression of PDAC. We acknowledge the value of precise markers and suitable tracing tools to discern the cell of origin, as it can facilitate the creation of more effective models for PDAC exploration. These conclusions shed light on our existing understanding of foundational genetically engineered mouse models and focus on the origin and development of PDAC.

Single-cell RNA sequencing highlights epithelial and microenvironmental heterogeneity in malignant progression of pancreatic ductal adenocarcinoma

Intraductal papillary mucinous neoplasms (IPMNs) of the pancreas are bona fide precursor lesions of pancreatic ductal adenocarcinoma (PDAC). Single-cell transcriptomics provides a unique perspective for dissecting the epithelial and microenvironmental heterogeneity that accompanies progression from benign IPMNs to invasive PDAC. Single-cell RNA sequencing was performed through droplet-based sequencing on 35 693 cells from three high-grade IPMNs and two IPMN-derived PDACs (all surgically resected). Analysis of single-cell transcriptomes revealed heterogeneous alterations within the epithelium and the tumor microenvironment during the progression of noninvasive dysplasia to invasive cancer. For epithelial cells, we identified acinar-ductal cells and isthmus-pit cells enriched in IPMN lesions and profiled three types of PDAC-unique ductal cells. Notably, a proinflammatory immune component was distinctly observed in IPMNs, comprising CD4+ T cells, CD8+ T cells, and B cells, whereas M2 macrophages were significantly accumulated in PDAC. Through the analysis of cellular communication, the osteopontin gene (SPP1)-CD44 pathway between macrophages and epithelial cells were particularly strengthened in the PDAC group. Further prognostic analysis revealed that SPP1 is a biomarker of IPMN carcinogenesis for surveillance. This study demonstrates the ability to perform high-resolution profiling of single cellular transcriptomes during the progression of high-grade IPMNs to cancer. Notably, single-cell analysis provides an unparalleled insight into both epithelial and microenvironmental heterogeneity associated with early cancer pathogenesis and provides practical markers for surveillance and targets for cancer interception.

Single-cell sequencing reveals increased LAMB3-positive basal keratinocytes and ZNF90-positive fibroblasts in autologous cultured epithelium

Autologous cultured epithelium grafting (ACEG) presents a promising treatment for refractory vitiligo, yet concerns regarding infections and immunological reactions hinder its surgical use due to serum and feeder dependencies. Addressing this, we culture autologous epithelium under serum- and feeder-free (SFF) conditions, comparing its safety and efficacy with serum- and feeder-dependent (SFD) conditions in stable vitiligo patients, and we discover no significant differences in repigmentation between the SFF and SFD grafts. Single-cell RNA transcriptomics on SFF- and SFD-cultured epithelium alongside healthy skin reveal increased populations of LAMB3+ basal keratinocytes and ZNF90+ fibroblasts in the SFF sheets. Functional analyses showcase active cellular metabolism in LAMB3+ basal keratinocytes, vital in extracellular matrix homeostasis, while ZNF90+ fibroblasts demonstrate increased differentiation, essential in collagen formation for cell adhesion. Importantly, these cell populations in SFF sheets exhibit enhanced interactions with melanocytes compared to SFD sheets. Further, knockdown experiments of LAMB3 in keratinocytes and ZNF90 in fibroblasts lead to a downregulation in melanocyte ligand-receptor-related genes. Overall, SFF sheets demonstrate comparable efficacy to SFD sheets, offering superior safety. LAMB3+ basal keratinocytes and ZNF90+ fibroblasts act as potential drivers behind repigmentation in ACEG under SFF conditions. This study provides translational insights into ACEG repigmentation and potential therapeutic targets for vitiligo.

The bioengineered and multifunctional nanoparticles in pancreatic cancer therapy: Bioresponisive nanostructures, phototherapy and targeted drug delivery

The multidisciplinary approaches in treatment of cancer appear to be essential in term of bringing benefits of several disciplines and their coordination in tumor elimination. Because of the biological and malignant features of cancer cells, they have ability of developing resistance to conventional therapies such as chemo- and radio-therapy. Pancreatic cancer (PC) is a malignant disease of gastrointestinal tract in which chemotherapy and radiotherapy are main tools in its treatment, and recently, nanocarriers have been emerged as promising structures in its therapy. The bioresponsive nanocarriers are able to respond to pH and redox, among others, in targeted delivery of cargo for specific treatment of PC. The loading drugs on the nanoparticles that can be synthetic or natural compounds, can help in more reduction in progression of PC through enhancing their intracellular accumulation in cancer cells. The encapsulation of genes in the nanoparticles can protect against degradation and promotes intracellular accumulation in tumor suppression. A new kind of therapy for cancer is phototherapy in which nanoparticles can stimulate both photothermal therapy and photodynamic therapy through hyperthermia and ROS overgeneration to trigger cell death in PC. Therefore, synergistic therapy of phototherapy with chemotherapy is performed in accelerating tumor suppression. One of the important functions of nanotechnology is selective targeting of PC cells in reducing side effects on normal cells. The nanostructures are capable of being surface functionalized with aptamers, proteins and antibodies to specifically target PC cells in suppressing their progression. Therefore, a specific therapy for PC is provided and future implications for diagnosis of PC is suggested.

Comprehensive machine learning-generated classifier identifies pro-metastatic characteristics and predicts individual treatment in pancreatic cancer: A multicenter cohort study based on super-enhancer profiling

Rationale: Accumulating evidence illustrated that the reprogramming of the super-enhancers (SEs) landscape could promote the acquisition of metastatic features in pancreatic cancer (PC). Given the anatomy-based TNM staging is limited by the heterogeneous clinical outcomes in treatment, it is of great clinical significance to tailor individual stratification and to develop alternative therapeutic strategies for metastatic PC patients based on SEs. Methods: In our study, ChIP-Seq analysis for H3K27ac was performed in primary pancreatic tumors (PTs) and hepatic metastases (HMs). Bootstrapping and univariate Cox analysis were implemented to screen prognostic HM-acquired, SE-associated genes (HM-SE genes). Then, based on 1705 PC patients from 14 multicenter cohorts, 188 machine-learning (ML) algorithm integrations were utilized to develop a comprehensive super-enhancer-related metastatic (SEMet) classifier. Results: We established a novel SEMet classifier based on 38 prognostic HM-SE genes. Compared to other clinical traits and 33 published signatures, the SEMet classifier possessed robust and powerful performance in predicting prognosis. In addition, patients in the SEMetlow subgroup owned dismal survival rates, more frequent genomic alterations, and more activated cancer immunity cycle as well as better benefits in immunotherapy. Remarkably, there existed a tight correlation between the SEMetlow subgroup and metastatic phenotypes of PC. Among 18 SEMet genes, we demonstrated that E2F7 may promote PC metastasis through the upregulation of TGM2 and DKK1. Finally, after in silico screening of potential compounds targeted SEMet classifier, results revealed that flumethasone could enhance the sensitivity of metastatic PC to routine gemcitabine chemotherapy. Conclusion: Overall, our study provided new insights into personalized treatment approaches in the clinical management of metastatic PC patients.

Fully automated magnetic resonance imaging-based radiomics analysis for differentiating pancreatic adenosquamous carcinoma from pancreatic ductal adenocarcinoma

PURPOSE

To develop and validate an automated magnetic resonance imaging (MRI)-based model to preoperatively differentiate pancreatic adenosquamous carcinoma (PASC) from pancreatic ductal adenocarcinoma (PDAC).

METHODS

This retrospective study included patients with surgically resected, histopathologically confirmed PASC or PDAC who underwent MRI between January 2011 and December 2020. According to time of treatment, they were divided into training and validation sets. Automated deep-learning-based artificial intelligence was used for pancreatic tumor segmentation. Linear discriminant analysis was performed with conventional MRI and radiomic features to develop clinical, radiomics, and mixed models in the training set. The models' performances were determined from their discrimination and clinical utility. Kaplan-Meier and log-rank tests were used for survival analysis.

RESULTS

Overall, 389 and 123 patients with PDAC (age, 61.37 ± 9.47 years; 251 men) and PASC (age, 61.99 ± 9.82 years; 78 men) were included, respectively; they were split into the training (n = 358) and validation (n = 154) sets. The mixed model showed good performance in the training and validation sets (area under the curve: 0.94 and 0.96, respectively). The sensitivity, specificity, and accuracy were 76.74%, 93.38%, and 89.39% for the training set, respectively, and 67.57%, 97.44%, and 90.26% for the validation set, respectively. The mixed model outperformed the clinical (p = 0.001) and radiomics (p = 0.04) models in the validation set. Log-rank test revealed significantly longer survival in the predicted PDAC group than in the predicted PASC group (p = 0.003), according to the mixed model.

CONCLUSION

Our mixed model, which combined MRI and radiomic features, can be used to differentiate PASC from PDAC.

The PD-L1 Expression and Tumor-Infiltrating Immune Cells Predict an Unfavorable Prognosis in Pancreatic Ductal Adenocarcinoma and Adenosquamous Carcinoma

The tumor microenvironment (TME) plays a vital role in the development, progression, and metastasis of pancreatic cancer (PC). The composition of the TME and its potential prognostic value remains to be fully understood, especially in adenosquamous carcinoma of pancreas (ASCP) patients. Immunohistochemistry was used to explore the clinical significance of CD3, CD4, CD8, FoxP3, and PD-L1 expression within the TME and to identify correlations with the prognosis of PC in a series of 29 patients with ASCP and 54 patients with pancreatic ductal adenocarcinoma (PDAC). Data from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) were accessed to obtain the scRNA-seq data and transcriptome profiles. Seurat was used to process the scRNA-seq data, and CellChat was used to analyze cell-cell communication. CIBERSORT was used to approximate the constitution of tumor-infiltrating immune cell (TICs) profiles. Higher levels of PD-L1 were linked with a shorter overall survival in ASCP (p = 0.0007) and PDAC (p = 0.0594). A higher expression of CD3+ and CD8+ T-cell infiltration was significantly correlated with a better prognosis in PC. By influencing the composition of tumor-infiltrating immune cells (TICs), high levels of PD-L1 expression are linked with a shorter overall survival in ASCP and PDAC.

Research advances and treatment perspectives of pancreatic adenosquamous carcinoma

BACKGROUND

As a malignant tumor, pancreatic cancer has an extremely low overall 5-year survival rate. Pancreatic adenosquamous carcinoma (PASC), a rare pancreatic malignancy, owns clinical presentation similar to pancreatic ductal adenocarcinoma (PDAC), which is the most prevalent pancreatic cancer subtype. PASC is generally defined as a pancreatic tumor consisting mainly of adenocarcinoma tissue and squamous carcinoma tissue. Compared with PDAC, PASC has a higher metastatic potential and worse prognosis, and lacks of effective treatment options to date. However, the pathogenesis and treatment of PASC are not yet clear and are accompanied with difficulties.

CONCLUSION

The present paper systematically summarizes the possible pathogenesis, diagnosis methods, and further suggests potential new treatment directions through reviewing research results of PASC, including the clinical manifestations, pathological manifestation, the original hypothesis of squamous carcinoma and the potential regulatory mechanism. In short, the present paper provides a systematic review of the research progress and new ideas for the development mechanism and treatment of PASC.

Spatial transcriptomics reveals the heterogeneity and FGG+CRP+ inflammatory cancer-associated fibroblasts replace islets in pancreatic ductal adenocarcinoma

Background

Understanding the spatial heterogeneity of the tumor microenvironment (TME) in pancreatic cancer (PC) remains challenging.

Methods

In this study, we performed spatial transcriptomics (ST) to investigate the gene expression features across one normal pancreatic tissue, PC tissue, adjacent tumor tissue, and tumor stroma. We divided 18,075 spatial spots into 22 clusters with t-distributed stochastic neighbor embedding based on gene expression profiles. The biological functions and signaling pathways involved in each cluster were analyzed with gene set enrichment analysis.

Results

The results revealed that KRT13+FABP5+ malignant cell subpopulation had keratinization characteristics in the tumor tissue. Fibroblasts from adjacent tumor tissue exhibited a tumor-inhibiting role such as "B-cell activation" and "positive regulation of leukocyte activation." The FGG+CRP+ inflammatory cancer-associated fibroblasts replaced the islets in tumor stroma. During PC progression, the damage to pancreatic structure and function was heavier in the pancreatic exocrine (AMYA2+PRSS1+) than in the endocrine (INS+GCG+).

Conclusion

Our results revealed the spatial heterogeneity of dynamic changes and highlighted the significance of impaired exocrine function in PC.

EREG is a risk factor for the prognosis of patients with cervical cancer

Background

Cervical cancer continues to threaten women's health worldwide. Identifying critical oncogenic molecules is important to drug development and prognosis prediction for patients with cervical cancer. Recent studies have demonstrated that epiregulin (EREG) is upregulated in various cancer types, which contributes to cancer progression by triggering the EGFR signaling pathway. However, the role of EREG is still unclear.

Methods

In this study, we first conducted a comprehensive biological analysis to investigate the expression of EREG in cervical cancer. Then, we investigated the correlations between EREG expression level and clinicopathological features. In addition, we validated the effects of EREG expression on the proliferation and apoptosis of cervical cancer cells.

Results

Based on the public database, we found that the expression of EREG was higher in advanced cervical cancer samples. Survival analysis showed that EREG was a risk factor for the prognosis of cervical cancer. In vitro experiments demonstrated that EREG knockdown undermined proliferation and promoted apoptosis in cancer cells.

Conclusion

EREG plays a vital role in the progression of cervical cancer, which contributes to hyperactive cell proliferation and decreased cell apoptosis. It might be a valuable target for prognosis prediction and drug development for cervical cancer in the future.

The study on the morphological changes of oropharynx in patients with complete unilateral cleft lip and palate after palatopharyngeal closure

Cleft lip and palate can be treated as one of the most common craniofacial congenital malformations in humans. Such disease influences tens of millions of patients all over the world. Cleft lip and palate deformity affects many important physiological functions, including breathing, swallowing, speech, chewing, and aesthetics. This work focuses on investigating the morphology and airway volume of oropharynx patients with unilateral complete cleft lip and palate after palatopharyngeal closure. In addition, this work evaluated the similarities and differences between patients with cleft lip and palate and those without such an issue. The employed data, selected from the Department of Stomatology of Xuzhou First People's Hospital, are based on the conical beam CT images. The study sample was divided into two groups: the selected experimental group, who confronted the cleft lip, cleft palate, and velopharyngeal closure surgery, and the selected control group, who are healthy children at the corresponding age. The parameters, including the airway volume, the airway volume of velopharyngeal and oropharyngeal segments, the minimum cross-sectional area of the pharynx, the horizontal plane airway area of the hard palate and soft one, the horizontal airway area of the hyoid bone, and the vertical distance between the hard palate and soft palate, can be measured by Dolphin. These parameters were analyzed with a statistical approach. The analysis of the above-mentioned parameters reveals that the airway volume, the minimum cross-sectional area of the pharynx, the horizontal cross-sectional area of the hyoid, and the distance between the hard palate and soft palate tip in patients with complete unilateral cleft lip and palate show significant differences between the experimental group and the control group. Meanwhile, other parameters, including the horizontal cross-sectional area of the airway in the horizontal plane of the hard palate and the horizontal plane of the soft palate, did not show noticeable differences in the two groups. The patients, who confronted the unilateral complete cleft lip and palate, can improve with the velopharyngeal closure surgery. Furthermore, the length and vertical distance of the soft palate and the volume of each segment of the airway exhibit differences between the experimental group and the control group.

Recent developments in application of single-cell RNA sequencing in the tumour immune microenvironment and cancer therapy

The advent of single-cell RNA sequencing (scRNA-seq) has provided insight into the tumour immune microenvironment (TIME). This review focuses on the application of scRNA-seq in investigation of the TIME. Over time, scRNA-seq methods have evolved, and components of the TIME have been deciphered with high resolution. In this review, we first introduced the principle of scRNA-seq and compared different sequencing approaches. Novel cell types in the TIME, a continuous transitional state, and mutual intercommunication among TIME components present potential targets for prognosis prediction and treatment in cancer. Thus, we concluded novel cell clusters of cancer-associated fibroblasts (CAFs), T cells, tumour-associated macrophages (TAMs) and dendritic cells (DCs) discovered after the application of scRNA-seq in TIME. We also proposed the development of TAMs and exhausted T cells, as well as the possible targets to interrupt the process. In addition, the therapeutic interventions based on cellular interactions in TIME were also summarized. For decades, quantification of the TIME components has been adopted in clinical practice to predict patient survival and response to therapy and is expected to play an important role in the precise treatment of cancer. Summarizing the current findings, we believe that advances in technology and wide application of single-cell analysis can lead to the discovery of novel perspectives on cancer therapy, which can subsequently be implemented in the clinic. Finally, we propose some future directions in the field of TIME studies that can be aided by scRNA-seq technology.

Single-cell sequencing reveals heterogeneity between pancreatic adenosquamous carcinoma and pancreatic ductal adenocarcinoma with prognostic value

Pancreatic adenosquamous carcinoma (ASPC) is a rare subtype of pancreatic cancer with lethal malignancy, and few studies have focused on the heterogeneity of ASPC. Here, we performed a single-cell sequencing procedure on pancreatic tumor tissue from an ASPC patient and a patient with high-grade intraductal papillary mucinous neoplasm (IPMN). Through the combined analysis of single-cell sequencing data from five pancreatic ductal adenocarcinoma (PDAC) patients, one IPMN patient, and one ASPC patient in a public database, we identified 11 main types of cells, including macrophages, B cells, cancer stem cells, ductal cells, fibroblasts, endo/stellate cells, neutrophils, acinar cells, T cells, natural killer (NK) cells, dendritic cells, and mast cells. Then, the different characteristics and differentiation paths of the immune microenvironment among IPMN, ASPC, and PDAC in macrophages, T cells, and cancer-associated fibroblasts (CAFs) were identified through multiple bioinformatics analyses. Two novel special cancer-associated fibroblasts were identified as nCAFs and imCAFs. Then, cancer cells in duct cells were identified using the infercnv software. Two ASPC-specific subgroups of cancer cells with squamous cell features were identified. Finally, the identified specific CAFs and cancer cells were mapped to TCGA-PAAD cohort through the cibersoftx software. All of these identified subgroups were calculated to have a significant prognostic value in pancreatic cancer patients. These findings will promote the clinical application of single-cell sequencing data of pancreatic cancer and deepen our understanding of ASPC.

The Emerging Role of RNA N6-Methyladenosine Modification in Pancreatic Cancer

Pancreatic cancer (PC) is one of the most common malignant cancers, ranking the seventh highest causes of cancer-related deaths globally. Recently, RNA N6-methyladenosine (m6A) is emerging as one of the most abundant RNA modifications in eukaryote cells, involved in multiple RNA processes including RNA translocation, alternative splicing, maturation, stability, and degradation. As reported, m6A was dynamically and reversibly regulated by its “writers”, “erasers”, and “readers”, Increasing evidence has revealed the vital role of m6A modification in the development of multiple types of cancers including PC. Currently, aberrant m6A modification level has been found in both PC tissues and cell lines. Moreover, abnormal expressions of m6A regulators and m6A-modified genes have been reported to contribute to the malignant development of PC. Here in this review, we will focus on the function and molecular mechanism of m6A-modulated RNAs including coding RNAs as well as non-coding RNAs. Then the m6A regulators will be summarized to reveal their potential applications in the clinical diagnosis, prognosis, and therapeutics of PC.

Survival Analysis and Prediction Model of ASCP Based on SEER Database

Background

This study aims to compare the incidence and clinical and survival characteristics of adenosquamous carcinoma of the pancreas (ASCP) and adenomatous carcinoma of the pancreas (ACP), analyze the survival factors of ASCP and construct a prognostic model.

Method

Patients diagnosed with pancreatic cancer from 2000 to 2018 are selected from the SEER database. ASCP and ACP are compared in terms of epidemiology, clinical characteristics and prognosis. Cases are matched in a 1:2 ratio, and survival analysis is performed. The Cox proportional hazard model is used to determine covariates related to overall survival (OS), and an ASCP prognosis nomogram is constructed and verified by consistency index (C-index), calibration chart and decision curve analysis (DCA). The accuracy of the model is compared with that of AJCC.Stage and SEER.Stage to obtain the area under the receiver operating characteristic (ROC) curve.

Results

the age-adjusted incidence of ACP increased significantly over time from 2000 to 2008 and from 2008 to 2018 (P < 0.05). APC was 2.01% (95% CI: 1.95–2.21) and 1.08% (95% CI: 0.93–1.25) respectively. The age-adjusted incidence of ASCP increased with time from 2000 to 2018 (P < 0.05) and APC was 3.64% (95% CI: 3.25–4.01).After propensity score matching (PSM), the OS and cancer-specific survival (CSS) of ACP are better than those of ASCP. The survival time of ASCP is significantly improved by the combined treatment of surgery + chemotherapy + radiotherapy, with a median OS of 31 months. Cox proportional hazard regression analysis shows that age, race, surgery, radiotherapy, chemotherapy and tumor size are independent factors affecting the prognosis. DCA and area under the curve (AUC) value shows that the model has good discrimination ability.

Conclusion

The OS prognosis of ASCP is worse than that of ACP, and the nomogram has high accuracy for the prognosis prediction of ASCP.

Discovering a Four-Gene Prognostic Model Based on Single-Cell Data and Gene Expression Data of Pancreatic Adenocarcinoma

Background

Pancreatic cancer has a 5-year overall survival lower than 8%. Pancreatic adenocarcinoma (PAAD) is the most common type. This study attempted to explore novel molecular subtypes and a prognostic model through analyzing tumor microenvironment (TME).

Materials and Methods

Single-cell RNA sequencing (scRNA-seq) data and expression profiles from public databases were downloaded. Three PAAD samples with single-cell data and 566 samples with gene expression data were included. Seurat was used to identify cell subsets. SVA merged and removed batch effects from multichip datasets. CIBERSORT was used to evaluate the components of different cells in transcriptome, ConsensusClusterPlus was used to identify molecular subtypes, and gene set enrichment analysis was used for functional enrichment analysis. LASSO Cox was performed to construct dimensionality reduction and prognosis model.

Results

Memory B cells (MBCs) were identified to be significantly with PAAD prognosis. Two immune subtypes (IS1 and IS2) with distinct overall survival were constructed. Forty-one DEGs were identified between IS1 and IS2. Four prognostic genes (ANLN, ARNTL2, SERPINB5, and DKK1) were screened to develop a prognostic model. The model was effective in classifying samples into high-risk and low-risk groups with distinct prognosis. Three subgroups of MBCs were identified, where MBC_0 and MBC_1 were differentially distributed between IS1 and IS2, high-risk and low-risk groups.

Conclusions

MBCs were closely involved in PAAD progression, especially MBC_0 and MBC_1 subgroups. The four-gene prognostic model was predictive of overall survival and could guide immunotherapy for patients with PAAD.

BUB1 Is Identified as a Potential Therapeutic Target for Pancreatic Cancer Treatment

Pancreatic cancer is one of the most challenging cancer types in clinical treatment worldwide. This study aimed to understand the tumorigenesis mechanism and explore potential therapeutic targets for patients with pancreatic cancer. Single-cell data and expression profiles of pancreatic cancer samples and normal tissues from multiple databases were included. Comprehensive bioinformatics analyses were applied to clarify tumor microenvironment and identify key genes involved in cancer development. Immense difference of cell types was shown between tumor and normal samples. Four cell types (B cell_1, B cell_2, cancer cell_3, and CD1C+_B dendritic cell_3) were screened to be significantly associated with prognosis. Three ligand-receptor pairs, including CD74-MIF, CD74-COPA, and CD74-APP, greatly contributed to tumorigenesis. High expression of BUB1 (BUB1 Mitotic Checkpoint Serine/Threonine Kinase) was closely correlated with worse prognosis. CD1C+_B dendritic cell_3 played a key role in tumorigenesis and cancer progression possibly through CD74-MIF. BUB1 can serve as a prognostic biomarker and a therapeutic target for patients with pancreatic cancer. The study provided a novel insight into studying the molecular mechanism of pancreatic cancer development and proposed a potential strategy for exploiting new drugs.