Integrated transcriptome meta-analysis of pancreatic ductal adenocarcinoma and matched adjacent pancreatic tissues

Variation in bulk RNA-seq and estimated cell type proportion using deconvolution when comparing pancreatic cancer samples within the same individual

Introduction

There is great promise in using genomic data to inform individual cancer treatment plans. Assessing intratumor genetic heterogeneity, studies have shown it may be possible to target biopsies to tumor subclones driving disease progression or treatment resistance. Here, we explore if the interpretation of tumor gene expression analysis varies across two specimens from the same patient.

Methods

We performed bulk RNA-seq using FFPE samples from 16 patients who also had a previous separate bulk RNA-seq performed and deposited in TCGA. We used three different deconvolution methods to compare cell type proportions for these paired data. We normalized study-specific gene expression values per gene by calculating transcripts per million and adjusted for batch effect across study to compare median expression values. We also compared the reliability of gene expression measurements. We selected KRAS, TP53, SMAD4, and CDKN2A, as the most mutated genes in pancreatic cancer, and CTNNB1, JUN, SMAD3, SMAD7, and TCF7, as these tend to be enriched in pancreatic cancer compared with adjacent normal tissue.

Results

We found that average cell type proportion varied the most between studies (i.e., samples for each patient) for NK and macrophages (using adjusted p-value 0.05/21=0.002). For the differential expression analysis, we did not observe significant differences in average expression of any of the selected genes. We observed substantial (kappa=0.75) for only JUN with low to moderate concordance (i.e., Kappa value 0.25-0.5) when using a median cut point for the remaining 8 genes across the two studies.

Discussion

Together, the findings suggest that more than one tumor sample may be needed for effective treatment planning. Any potential difference in observed expression values across the paired samples could be related to the different cell type proportions across the samples. The sample size was small, and each study used different sequencing technologies, so any interpretation should be confirmed with additional studies.

EVA1-antibody drug conjugate is a new therapeutic strategy for eliminating glioblastoma-initiating cells

BACKGROUND

The discovery of glioblastoma (GBM)-initiating cells (GICs) has impacted GBM research. These cells are not only tumorigenic but also exhibit resistance to radiotherapy and chemotherapy. Therefore, it is crucial to characterize GICs thoroughly and identify new therapeutic targets. In a previous study, we successfully identified epithelial-V-like antigen 1 (EVA1) as a novel functional factor specific to GICs.

METHODS

Hybridoma cells were generated by immunizing BALB/c mice with EVA1-Fc fusion protein. The reactivity of the supernatant from these hybridoma cells was examined using EVA1-overexpressing cells and GICs. Candidate antibodies were further selected using Biacore surface plasmon resonance analysis and 2 cytotoxicity assays-antibody-dependent cell cytotoxicity (ADCC) and complement-dependent cytotoxicity (CDC). Among the antibodies, the cytotoxicity of the B2E5-antibody drug conjugate (B2E5-ADC) was evaluated by both adding it to cultured GICs and injecting it into GIC tumor-bearing brains.

RESULTS

B2E5 demonstrated a high affinity for human EVA1 and effectively killed both EVA1-expressing cell lines and GICs in culture through ADCC and CDC. B2E5-ADC also exhibited strong cytotoxicity to GICs in culture and prevented their tumorigenesis in the brain when administered intracranially to the tumor-bearing brain.

CONCLUSION

Our data indicate that B2E5-ADC is a new and promising therapeutic strategy for GBM.

The crucial prognostic signaling pathways of pancreatic ductal adenocarcinoma were identified by single-cell and bulk RNA sequencing data

Pancreatic ductal adenocarcinoma (PDAC) is a malignant tumor with poor prognosis and high mortality. Although a large number of studies have explored its potential prognostic markers using traditional RNA sequencing (RNA-Seq) data, they have not achieved good prediction effect. In order to explore the possible prognostic signaling pathways leading to the difference in prognosis, we identified differentially expressed genes from one scRNA-seq cohort and four GEO cohorts, respectively. Then Cox and Lasso regression analysis showed that 12 genes were independent prognostic factors for PDAC. AUC and calibration curve analysis showed that the prognostic model had good discrimination and calibration. Compared with the low-risk group, the high-risk group had a higher proportion of gene mutations than the low-risk group. Immune infiltration analysis revealed differences in macrophages and monocytes between the two groups. Prognosis related genes were mainly distributed in fibroblasts, macrophages and type 2 ducts. The results of cell communication analysis showed that there was a strong communication between cancer-associated fibroblasts (CAF) and type 2 ductal cells, and collagen formation was the main interaction pathway.

Tumor microenvironment-like conditions alter pancreatic cancer cell metabolism and behavior

The tumor microenvironment is complex and dynamic, characterized by poor vascularization, limited nutrient availability, hypoxia, and an acidic pH. This environment plays a critical role in driving cancer progression. However, standard cell culture conditions used to study cancer cell biology in vitro fail to replicate the in vivo environment of tumors. Recently, "physiological" cell culture media that closely resemble human plasma have been developed (e.g., Plasmax, HPLM), along with more frequent adoption of physiological oxygen conditions (1%-8% O2). Nonetheless, further refinement of tumor-specific culture conditions may be needed. In this study, we describe the development of a tumor microenvironment medium (TMEM) based on murine pancreatic ductal adenocarcinoma (PDAC) tumor interstitial fluid. Using RNA-sequencing, we show that murine PDAC cells (KPCY) cultured in tumor-like conditions (TMEM, pH 7.0, 1.5% O2) exhibit profound differences in gene expression compared with plasma-like conditions (mouse plasma medium, pH 7.4, 5% O2). Specifically, the expression of genes and pathways associated with cell migration, biosynthesis, angiogenesis, and epithelial-to-mesenchymal transition were altered, suggesting tumor-like conditions promote metastatic phenotypes and metabolic remodeling. Using functional assays to validate RNA-seq data, we confirmed increased motility at 1.5% O2/TMEM, despite reduced cell proliferation. Moreover, a hallmark shift to glycolytic metabolism was identified via measurement of glucose uptake/lactate production and mitochondrial respiration. Taken together, these findings demonstrate that growth in 1.5% O2/TMEM alters several biological responses in ways relevant to cancer biology, and more closely models hallmark cancerous phenotypes in culture. This highlights the importance of establishing tumor microenvironment-like conditions in standard cancer research. NEW & NOTEWORTHY Standard cell culture conditions do not replicate the complex tumor microenvironment experienced by cells in vivo. Although currently available plasma-like media are superior to traditional supraphysiological media, they fail to model tumor-like conditions. Using RNA-seq analysis and functional metabolic and migratory assays, we show that tumor microenvironment medium (TMEM), used with representative tumor hypoxia, better models cancerous phenotypes in culture. This emphasizes the critical importance of accurately modeling the tumor microenvironment in cancer research.

Investigating the function and targeting of MET protein as an oncogene kinase in pancreatic ductal adenocarcinoma: A microarray data integration

Introduction

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease with a poor prognosis. Kinase proteins are essential regulators of cellular processes and potential targets for drug development.

Methods

Integration of multiple microarray datasets was screened to find differentially expressed kinases (DE-Kinases) across adjacent normal and tumor tissue samples in PDAC. The most effective kinase for drug design and docking in this study was selected by investigating biological mechanisms and survival analyses. Forty phytochemicals were extracted from the yellow sweet clover, Melilotus officinalis (Linn.) Pall, and were then subjected to in silico screening and molecular docking studies against a specific potent kinase.

Results

MET, PAK3, and PDK4 were identified as the DE-Kinases. After examining the pathways and biological processes, up-regulated MET had the most significant survival analysis and became our primary kinase for drug design and docking in this study. Four of the extracted phytocompounds of Melilotus officinalis (Linn.) Pall that exhibited high binding affinities with MET and were selected for toxicity analysis. Finally, the stability and mobility of the two nontoxic compounds that passed the toxicity test (dicumarol PubChem CID: 54676038 and melilotigenin PubChem CID: 14059499) were studied by molecular dynamics simulation.

Conclusion

This study's results identified two phytochemicals in yellow sweet clover that could be used to develop an anticancer drug, but experimental evaluation is necessary to confirm their efficacy.

CircRNA PGAM1 Promotes the Migration and Invasion of Pancreatic Adenocarcinoma Cells by Activating the AKT/mTOR Signaling Pathway

Pancreatic adenocarcinoma (PAAD) is a lethal malignancy of the gastrointestinal tract. Circular RNA, an endogenous noncoding RNA, is considered a new regulatory molecule in tumorigenesis and development. Here, we aimed to investigate the role of circPGAM1 in PAAD. The PAAD cell line HPAC was transfected with OE-circPGAM1 to overexpress circPGAM1 and treated with AZD5363 to inhibit the AKT/mTOR pathway. Simultaneously, another PAAD cell line BxPC-3 was transfected with sh-circPGAM1 to silence circPGAM1. The GEPIA database was used to determine the expression of circPGAM1 in PAAD and its association with overall and disease-free survival. CircPGAM1 expression levels were determined in cell lines using reverse transcription-quantitative PCR. The cell counting kit-8, wound healing, and transwell assays were performed to determine cell migration and invasion. The protein expression levels of phosphorylated AKT and mTOR were determined using western blotting. CircPGAM1 was overexpressed in PAAD and related to poor prognosis. Silencing circPGAM1 inhibited migration and invasion of BxPC-3 cells, and overexpression of circPGAM1 showed the opposite effects. Overall, circPGAM1 promoted the migration and invasion of PAAD cells through the AKT/mTOR axis.

Correlation of laminin subunit alpha 3 expression in pancreatic ductal adenocarcinoma with tumor liver metastasis and survival

BACKGROUND

The high mortality rate of pancreatic ductal adenocarcinoma (PDAC) is primarily attributed to metastasis. Laminin subunit alpha 3 (LAMA3) is known to modulate tumor progression. However, the influence of LAMA3 on liver metastasis in PDAC remains unclear. This study aimed to elucidate whether LAMA3 expression is increased in PDAC with liver metastasis.

PATIENTS AND METHODS

We extracted information related to LAMA3 expression levels and associated clinicopathological parameters from The Cancer Genome Atlas (TCGA) and four Gene Expression Omnibus (GEO) datasets. Clinicopathological analysis was performed; the Kaplan-Meier Plotter was used to evaluate LAMA3's prognostic effect in PDAC. We retrospectively collected clinicopathological data and tissue specimens from 117 surgically treated patients with PDAC at the Affiliated Hospital of Qingdao University. We assessed LAMA3 expression and investigated its correlation with the clinicopathological traits, clinical outcomes, and hepatic metastasis.

RESULTS

Amplified expression of LAMA3 was observed in PDAC tissue compared with normal tissue in the TCGA and GEO databases. High LAMA3 expression was associated with poor overall survival (OS) and relapse-free survival (RFS) in patients with PDAC. LAMA3 expression was significantly enhanced in PDAC tissues than in adjacent tissues. Tumor tissues from patients with PDAC exhibiting liver metastasis showed higher LAMA3 expression than those without liver metastasis. High LAMA3 expression correlated with large tumor size and TNM stage. LAMA3 expression and liver metastasis were independent predictive factors for OS; the former was independently associated with liver metastasis.

CONCLUSIONS

LAMA3 expression is elevated in patients with PDAC with liver metastasis and is a predictor of prognosis.

Single-Cell RNA Sequencing Analysis Reveals Metabolic Changes in Epithelial Glycosphingolipids and Establishes a Prognostic Risk Model for Pancreatic Cancer

OBJECTIVE

Metabolic reprogramming serves as a distinctive feature of cancer, impacting proliferation and metastasis, with aberrant glycosphingolipid expression playing a crucial role in malignancy. Nevertheless, limited research has investigated the connection between glycosphingolipid metabolism and pancreatic cancer.

METHODS

This study utilized a single-cell sequencing dataset to analyze the cell composition in pancreatic cancer tissues and quantified single-cell metabolism using a newly developed computational pipeline called scMetabolism. A gene signature developed from the differential expressed genes (DEGs), related to epithelial cell glycosphingolipid metabolism, was established to forecast patient survival, immune response, mutation status, and reaction to chemotherapy with pancreatic adenocarcinoma (PAAD).

RESULTS

The single-cell sequencing analysis revealed a significant increase in epithelial cell proportions in PAAD, with high glycosphingolipid metabolism occurring in the cancerous tissue. A six-gene signature prognostic model based on abnormal epithelial glycosphingolipid metabolism was created and confirmed using publicly available databases. Patients with PAAD were divided into high- and low-risk categories according to the median risk score, with those in the high-risk group demonstrating a more unfavorable survival outcome in all three cohorts, with higher rates of gene mutations (e.g., KRAS, CDKN2A), increased levels of immunosuppressive cells (macrophages, Th2 cells, regulatory T cells), and heightened sensitivity to Acetalax and Selumetinlb.

CONCLUSIONS

Abnormal metabolism of glycosphingolipids in epithelial cells may promote the development of PAAD. A model utilizing a gene signature associated with epithelial glycosphingolipids metabolism has been established, serving as a valuable indicator for the prognostic stratification of patients with PAAD.

Genomic analysis and filtration of novel prognostic biomarkers based on metabolic and immune subtypes in pancreatic cancer

PURPOSE

Patients with pancreatic cancer (PC) can be classified into various molecular subtypes and benefit from some precise therapy. Nevertheless, the interaction between metabolic and immune subtypes in the tumor microenvironment (TME) remains unknown. We hope to identify molecular subtypes related to metabolism and immunity in pancreatic cancer METHODS: Unsupervised consensus clustering and ssGSEA analysis were utilized to construct molecular subtypes related to metabolism and immunity. Diverse metabolic and immune subtypes were characterized by distinct prognoses and TME. Afterward, we filtrated the overlapped genes based on the differentially expressed genes (DEGs) between the metabolic and immune subtypes by lasso regression and Cox regression, and used them to build risk score signature which led to PC patients was categorized into high- and low-risk groups. Nomogram were built to predict the survival rates of each PC patient. RT-PCR, in vitro cell proliferation assay, PC organoid, immunohistochemistry staining were used to identify key oncogenes related to PC RESULTS: High-risk patients have a better response for various chemotherapeutic drugs in the Genomics of Drug Sensitivity in Cancer (GDSC) database. We built a nomogram with the risk group, age, and the number of positive lymph nodes to predict the survival rates of each PC patient with average 1-year, 2-year, and 3-year areas under the curve (AUCs) equal to 0.792, 0.752, and 0.751. FAM83A, KLF5, LIPH, MYEOV were up-regulated in the PC cell line and PC tissues. Knockdown of FAM83A, KLF5, LIPH, MYEOV could reduce the proliferation in the PC cell line and PC organoids CONCLUSION: The risk score signature based on the metabolism and immune molecular subtypes can accurately predict the prognosis and guide treatments of PC, meanwhile, the metabolism-immune biomarkers may provide novel target therapy for PC.

Constitutive photomorphogenic protein 1 ubiquitinates interleukin-1 receptor accessory protein in human liver cancer

BACKGROUND

Constitutive photomorphogenic protein 1 (COP1) plays a pivotal role in the development and progression of several human cancers and is reported to be upregulated in liver cancer. However, the role of COP1 in human liver cancer is unclear.

METHODS

We analyzed the COP1 expression in normal liver and liver cancer tissue samples using western blot and immunohistochemical analysis. We overexpressed and silenced COP1 in HepG2 and Huh7 cells and analyzed the effect on liver cancer cell proliferation. Additionally, COP1 was used as a bait to screen COP1-interacting proteins in a human cDNA library in a yeast two-hybrid screen and the results were confirmed with co-immunoprecipitation (co-IP) assays. Moreover, immunofluorescence staining was performed to assess co-localization. The protein levels of COP1 and mIL1RAcP were determined in clinical samples.

RESULTS

COP1 was upregulated in liver cancer samples compared to that in normal tissue samples. COP1 overexpression promoted proliferation of liver cancer cells, while COP1 knockdown exerted the opposite effect. Yeast two-hybrid screen identified interleukin-1 receptor accessory protein (IL1RAP) as a potential COP1-interacting protein. Co-IP assays further confirmed that COP1 interacts with both preIL1RAP and membrane-bound form of IL1RAP (mIL1RAP). Furthermore, COP1 upregulated mIL1RAP protein levels and promoted nuclear translocation and activation of the nuclear factor kappa B (NF-κB) (p50/p65) dimer. Additionally, we demonstrated that COP1 regulated mIL1RAP expression through K63-linked polyubiquitination, suggesting that COP1 plays a role in stabilizing mIL1RAP. Finally, the protein levels of COP1 and mIL1RAcP were found to be positively correlated in clinical samples.

CONCLUSION

COP1 regulates IL1RAP, which in turn results in activation of the NF-κB signaling. Our findings suggest that the COP1/IL1RAP/NF-κB axis promotes proliferation of liver cancer cells and is a potential target for the treatment of liver cancer.

A missense mutation in Lama3 causes androgen alopecia

Hair loss disorders such as androgenetic alopecia have caused serious disturbances to normal human life. Animal models play an important role in exploring pathogenesis of disease and evaluating new therapies. NIH hairless mice are a spontaneous hairless mouse discovered and bred in our laboratory. In this study, we resequenced the genomes of NIH normal mice and NIH hairless mice and obtained 3,575,560 high-quality, plausible SNP loci and 995,475 InDels. The Euclidean distance algorithm was used to assess the association of SNP loci with the hairless phenotype, at a threshold of 0.62. Two regions of chromosome 18 having the highest association with the phenotype contained 345 genes with a total length of 13.98 Mb. The same algorithm was used to assess the association of InDels with the hairless phenotype at a threshold of 0.54 and revealed a region of 25.45 Mb in length, containing 518 genes. The mutation candidate gene Lama3 (NM_010680.2: c.652C>T; NP_034810.1: p. Arg217Cys) was selected based on the results of functional gene analysis and mutation prediction screening. Lama3 (R217C) mutant mice were further constructed using CRISPR/Cas9 technology, and the relationship between Lama3 point mutations and the hairless phenotype were clarified by phenotypic observation. The results showed that male Lama3 point mutation mice started to lose hair on the 80th day after birth, and the hair loss area gradually expanded over time. H&E staining of skin sections showed that the point mutation mice had increased sebaceous glands in the dermis and missing hair follicle structure (i.e., typical symptoms of androgenetic alopecia). This study is a good extension of the current body of knowledge about the function of Lama3, and the constructed Lama3 (R217C) mutant mice may be a good animal model for studying androgenetic alopecia.

Collagen XVII regulates tumor growth in pancreatic cancer through interaction with the tumor microenvironment

Expression of the gene for collagen XVII (COL17A1) in tumor tissue is positively or negatively associated with patient survival depending on cancer type. High COL17A1 expression is thus a favorable prognostic marker for breast cancer but unfavorable for pancreatic cancer. This study explored the effects of COL17A1 expression on pancreatic tumor growth and their underlying mechanisms. Analysis of published single-cell RNA-sequencing data for human pancreatic cancer tissue revealed that COL17A1 was expressed predominantly in cancer cells rather than surrounding stromal cells. Forced expression of COL17A1 did not substantially affect the proliferation rate of the mouse pancreatic cancer cell lines KPC and AK4.4 in vitro. However, in mouse homograft tumor models in which KPC or AK4.4 cells were injected into syngeneic C57BL/6 or FVB mice, respectively, COL17A1 expression promoted or suppressed tumor growth, respectively, suggesting that the effect of COL17A1 on tumor growth was influenced by the tumor microenvironment. RNA-sequencing analysis of tumor tissue revealed effects of COL17A1 on gene expression profiles (including the expression of genes related to cell proliferation, the immune response, Wnt signaling, and Hippo signaling) that differed between C57BL/6-KPC and FVB-AK4.4 tumors. Our data thus suggest that COL17A1 promotes or suppresses cancer progression in a manner dependent on the interaction of tumor cells with the tumor microenvironment.

CMTM6 as a potential therapy target is associated with immunological tumor microenvironment and can promote migration and invasion in pancreatic adenocarcinoma

CMTM6 has been connected to the development of several malignancies. However, it is still unknown what function CMTM6 serves in pancreatic adenocarcinoma (PAAD). We obtained RNA sequencing information of PAAD from public datasets and predicted statistical significance of CMTM6 survival in accordance with Kaplan-Meier curves. Gene set enrichment assessment (GSEA) was employed to analyze changes in pathways. Then, we systematically investigated the association involving CMTM6 and the immunological traits within the tumor microenvironment (TME) of PAAD, including immune pathways, immunomodulators, immune infiltrating cells, inflammatory activities, and immunotherapy response prediction. To demonstrate the biologically malignant properties of CMTM6 expression, the Cell Counting Kit-8, transwell experiments, colony formation, and wound healing were utilized. Upregulated CMTM6 expression was revealed within PAAD tissues, which was associated with more frequent somatic mutations and worse survival outcomes. Specifically, CMTM6 expression represented stronger immune infiltration, inflammatory activity, and better immunotherapeutic response in TME. Functional studies revealed that CMTM6 promoted the ability to proliferate, migrate, and invade. Additionally, CMTM6 and PD-L1 had a positive relationship, and CMTM6 can co-immunocoprecipitate with PD-L1 protein in pancreatic cell lines. CMTM6 overexpression shapes the inflammatory TME with a strong immune response. These findings support that CMTM6 is an immunotherapeutic target with promising effect to treat PAAD.

Overexpression of integrin alpha 2 (ITGA2) correlates with poor survival in patients with pancreatic ductal adenocarcinoma

AIMS

Due to the known malignant potential and the poor overall prognosis of pancreatic ductal adenocarcinoma (PDAC), the identification of new biomarkers is of utmost importance. It has been reported that integrin alpha 2 (ITGA2), plakophilin 3 (PKP3) and adenylate kinase 4 (AK4) are associated with poor survival and more aggressive malignant behaviour in multiple cancers; however, their role in PDAC is still unknown. Therefore, the aim of this study was to investigate the correlation of ITGA2, PKP3 and AK4 expression with PDAC tumour characteristics and patient survival.

METHODS

Of 105 patients undergoing oncological pancreatic resection between 2012 and 2018, tissue microarrays were prepared from formalin-fixed, paraffin-embedded PDAC tissues and immunohistochemically stained with PKP3, AK4 and ITGA2. Clinical and pathological patient data were retrieved from the electronic patient charts and correlated with biomarker staining scores.

RESULTS

ITGA2 expression was high in 43% of patients with PDAC, whereas AK4 and PKP3 expressions were high in 28% and 57%, respectively. Overall survival was negatively associated with high ITGA2 expression in comparison with low expression (13 months (95% CI 10 to 18 months) vs 25 months (95% CI 20 to 30 months), p<0.001). Expression of AK4 and PKP3 did not correlate with overall survival. Multivariate Cox regression identified ITGA2 as an independent predictor of shorter overall survival in PDAC of different lymph node status and high tumour grade (G3/G4).

CONCLUSIONS

ITGA2 is an independent prognostic parameter for survival in patients with resected PDAC. PKP3 and AK4 do not appear to have prognostic value for survival in PDAC.

Revealing platelet-related subtypes and prognostic signature in pancreatic adenocarcinoma

BACKGROUND

Pancreatic adenocarcinoma (PDAC) is a malignant tumor with high heterogeneity and poor prognosis. In this study, we sought to identify the value of platelet-related genes in prognosis and heterogeneity of PDAC through multiple transcriptomic methods.

METHODS

Based on datasets from Gene Expression Omnibus and The Cancer Genome Atlas (TCGA), platelet-related genes were screened out, and the TCGA cohort (n = 171) was identified into two subtypes by unsupervised clustering. The platelet-related risk score model (PLRScore) was constructed by univariate Cox and LASSO regression, and the predictive ability was evaluated by Kaplan-Meier test and time-dependent receiver operating characteristic (ROC) curves. The results were validated in two other external validation sets, ICGC-CA (n = 140) and GSE62452 (n = 66). Furthermore, predictive nomogram containing clinical characteristics and PLRScore was established. In addition, we determined the possible correlation between PLRScore and immune infiltration and response of immunotherapy. Finally, we analyzed the heterogeneity of our signature in various types of cells using single-cell analysis.

RESULTS

Platelet-related subtypes that have significant difference of overall survival and immune states (p < 0.05) were identified. PLRScore model based on four-gene signature (CEP55, LAMA3, CA12, SCN8A) was constructed to predict patient prognosis. The AUCs of training cohort were 0.697, 0.687 and 0.675 for 1-, 3-and 5-year, respectively. Further evaluation of the validation cohorts yielded similar results. In addition, PLRScore was associated with immune cell infiltration and immune checkpoint expression, and had promising ability to predict response to immunotherapy of PDAC.

CONCLUSIONS

In this study, the platelet-related subtypes were identified and the four-gene signature was constructed and validated. It may provide new insights into the therapeutic decision-making and molecular targets of PDAC.

New progress with calcium-binding protein S100A16 in digestive system disease

INTRODUCTION

This review summarizes and analyzes the abnormal expression and mechanism of S100A16 in digestive system diseases, which is expected to provide new ideas and methods for adjuvant treatment and prognosis evaluation of digestive system diseases.

AREAS COVERED

Based on original publications found in database systems (PubMed, Cochrane), we introduce the mechanism and research progress of S100A16 in digestive system tumors, inflammatory bowel disease and fatty liver.

EXPERT OPINION

S100A16 is closely related to the proliferation, migration, and invasion of digestive system tumor cells. Further, it plays an important role in inflammatory bowel disease and fatty liver.

Development of a basement membrane gene signature and identification of the potential candidate therapeutic targets for pancreatic cancer

Background

Pancreatic cancer is a deadly cancer with a poor prognosis. In light of mounting evidence that basement membrane genes (BMGs) play a role in the development of cancer, we sought to examine the prognostic importance and role of BMGs in pancreatic ductal adenocarcinoma (PDAC) patients.

Methods

BMGs were obtained from previous top research studies. The clinical and messenger ribonucleic acid expression data were retrieved from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) data sets, respectively. Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were used for the PDAC risk modeling and gene identification. The Kaplan-Meier method was used to compare outcomes between the low- and high-risk groups. Finally, we analyzed small-molecule drugs that could be used to target BMGs for treatment using the Enrichr data set and validated the function of the tubulointerstitial nephritis antigen (TINAG) in pancreatic cancer.

Results

We successfully constructed and validated a 7 BMG-based model to predict PDAC patient outcomes. Additionally, we discovered that 7 BMG-based model was an independent predictive factor for PDAC. According to our functional analysis, the majority of the signaling pathways enriched in BMGs were those connected to malignancy. Immune cell infiltration and immunological checkpoints were also linked to the BMG-based model. Further, we identified 5 small-molecule drugs that may be useful in treating PDAC patients. We also found that TINAG promoted cell proliferation in pancreatic cancer.

Conclusions

Our study extended understandings of how BMGs work in PDAC. We identified a credible predictive biomarker for PDAC patients' survival.

Construction and comprehensive analysis of a novel prognostic signature associated with pyroptosis molecular subtypes in patients with pancreatic adenocarcinoma

Background

Treatment of cancer with pyroptosis is an emerging strategy. Molecular subtypes based on pyroptosis-related genes(PRGs) seem to be considered more conducive to individualized therapy. It is meaningful to construct a pyroptosis molecular subtypes-related prognostic signature (PMSRPS) to predict the overall survival (OS) of patients with pancreatic adenocarcinoma(PAAD) and guide treatment.

Methods

Based on the transcriptome data of 23 PRGs, consensus clustering was applied to divide the TCGA and GSE102238 combined cohort into three PRGclusters. Prognosis-related differentially expressed genes(DEGs) among PRGclusters were subjected to LASSO Cox regression analysis to determine a PMSRPS. External cohort and in vitro experiments were conducted to verify this PMSRPS. The CIBERSORT algorithm, the ESTIMATE algorithm and the Immunophenoscore (IPS) were used to analyze the infiltrating abundance of immune cells, the tumor microenvironment (TME), and the response to immunotherapy, respectively. Wilcoxon analysis was used to compare tumor mutational burden (TMB) and RNA stemness scores (RNAss) between groups. RT-qPCR and in vitro functional experiments were used for evaluating the expression and function of SFTA2.

Results

Based on three PRGclusters, 828 DEGs were obtained and a PMSRPS was subsequently constructed. In internal and external validation, patients in the high-risk group had significantly lower OS than those in the low-risk group and PMSRPS was confirmed to be an independent prognostic risk factor for patients with PAAD with good predictive performance. Immune cell infiltration abundance and TME scores indicate patients in the high-risk group have typical immunosuppressive microenvironment characteristics. Analysis of IPS suggests patients in the high-risk group responded better to novel immune checkpoint inhibitors (ICIs) than PD1/CTLA4. The high-risk group had higher TMB and RNAss. In addition, 10 potential small-molecule compounds were screened out. Finally, we found that the mRNA expression of SFTA2 gene with the highest risk coefficient in PMSRPS was significantly higher in PAAD than in paracancerous tissues, and knockdown of it significantly delayed the progression of PAAD.

Conclusions

PMSRPS can well predict the prognosis, TME and immunotherapy response of patients with PAAD, identify potential drugs, and provide treatment guidance based on individual needs.

Identifying novel interactions of the colon-cancer related APC protein with Wnt-pathway nuclear transcription factors

BACKGROUND

Colon cancer is often driven by mutations of the adenomatous polyposis coli (APC) gene, an essential tumor suppressor gene of the Wnt β-catenin signaling pathway. APC and its cytoplasmic interactions have been well studied. However, various groups have also observed its presence in the nucleus. Identifying novel interactions of APC in the Wnt pathway will provide an opportunity to understand APC's nuclear role better and ultimately identify potential cancer treatment targets.

METHODS

We used the all-vs-all sequencing (AVA-Seq) method to interrogate the interactome of protein fragments spanning most of the 60 Wnt β-catenin pathway proteins. Using protein fragments identified the interacting regions between the proteins with more resolution than a full-length protein approach. Pull-down assays were used to validate a subset of these interactions.

RESULTS

74 known and 703 novel Wnt β-catenin pathway protein-protein interactions were recovered in this study. There were 8 known and 31 novel APC protein-protein interactions. Novel interactions of APC and nuclear transcription factors TCF7, JUN, FOSL1, and SOX17 were particularly interesting and confirmed in validation assays.

CONCLUSION

Based on our findings of novel interactions between APC and transcription factors and previous evidence of APC localizing to the nucleus, we suggest APC may compete and repress CTNNB1. This would occur through APC binding to the transcription factors (JUN, FOSL1, TCF7) to regulate the Wnt signaling pathway including through enhanced marking of CTNNB1 for degradation in the nucleus by APC binding with SOX17. Additional novel Wnt β-catenin pathway protein-protein interactions from this study could lead researchers to novel drug designs for cancer.

SMAD2/3 mediate oncogenic effects of TGF-β in the absence of SMAD4

TGF-β signaling is involved in pancreatic ductal adenocarcinoma (PDAC) tumorigenesis, representing one of the four major pathways genetically altered in 100% of PDAC cases. TGF-β exerts complex and pleiotropic effects in cancers, notably via the activation of SMAD pathways, predominantly SMAD2/3/4. Though SMAD2 and 3 are rarely mutated in cancers, SMAD4 is lost in about 50% of PDAC, and the role of SMAD2/3 in a SMAD4-null context remains understudied. We herein provide evidence of a SMAD2/3 oncogenic effect in response to TGF-β1 in SMAD4-null human PDAC cancer cells. We report that inactivation of SMAD2/3 in SMAD4-negative PDAC cells compromises TGF-β-driven collective migration mediated by FAK and Rho/Rac signaling. Moreover, RNA-sequencing analyses highlight a TGF-β gene signature related to aggressiveness mediated by SMAD2/3 in the absence of SMAD4. Using a PDAC patient cohort, we reveal that SMAD4-negative tumors with high levels of phospho-SMAD2 are more aggressive and have a poorer prognosis. Thus, loss of SMAD4 tumor suppressive activity in PDAC leads to an oncogenic gain-of-function of SMAD2/3, and to the onset of associated deleterious effects.

In pancreatic ductal adenocarcinoma cells and patient tissue, SMAD2/3 is shown to mediate oncogenic effects of TGF-β in the absence of SMAD4.

Transcriptomic and immunologic implications of the epithelial-mesenchymal transition model reveal a novel role of SFTA2 in prognosis of non-small-cell lung carcinoma

Non-small-cell lung cancer (NSCLC) is the second most common cancer worldwide, and most deaths are associated with epithelial-mesenchymal transition (EMT). Therefore, this study aimed to explore the role of EMT-related transcriptomic profiles in NSCLC and the effect of EMT-based signatures on clinical diagnosis, prognosis, and treatment responses for patients with NSCLC. After integrating the transcriptomics and clinicopathological data, we first constructed EMT clusters (C1 and C2) using machine learning algorithms, found the significant relationship between EMT clusters and survival outcomes, and then explored the impact of EMT clusters on the tumor heterogeneity, drug efficiency, and immune microenvironment of NSCLC. Prominently, differential-enriched tumor-infiltrated lymphocytes were found between EMT clusters, especially the macrophages and monocyte. Next, we identified the most significantly down-regulated gene SFTA2 in the EMT clusters C2 with poor prognosis. Using RT-qPCR and RNA-seq data from the public database, we found prominently elevated SFTA2 expression in NSCLC tissues compared with normal lung tissues, and the tumor suppressor role of SFTA2 in 82 Chinese patients with NSCLC. After Cox regression and survival analysis, we demonstrated that higher SFTA2 expression in tumor samples significantly predicts favorable prognosis of NSCLC based on multiple independent cohorts. In addition, the prognostic value of SFTA2 expression differs for patients with lung adenocarcinoma and squamous cell carcinoma. In conclusion, this study demonstrated that the EMT process is involved in the malignant progression and the constructed EMT clusters exerted significant predictive drug resistance and prognostic value for NSCLC patients. In addition, we first identified the high tumoral expression of SFTA2 correlated with better prognosis and could serve as a predictive biomarker for outcomes and treatment response of NSCLC patients.

Evaluation of tumoral glypican 3 mRNA level as a diagnostic and prognostic biomarker for hepatitis-b virus-associated hepatocellular carcinoma by an integrative transcriptomic meta-analysis and bioinformatics

Aim: The aim of this study is to evaluate the potential of GPC3 mRNA level as a diagnostic and prognostic biomarker for HBV-associated HCC. Materials and Methods: GPC3 mRNA expression in HBV-associated HCC tumor tissues compared to matched adjacent tissues was evaluated by integrative transcriptomic meta-analysis. The results were validated in a different patient cohort and the possible associations between GPC3 mRNA level and the clinical variables were evaluated. Results: Transcriptomic data of HBV-associated HCC tissues (n=61) and matched adjacent tissues (n=61) from four datasets (GSE19665;GSE84402;GSE121248;GSE55092) were included in the meta-analysis. GPC3 mRNA level was found to be higher in tumors than adjacent tissues (fold change=12.88; p= 0;FDR=0). The result was validated in GSE14520, (HBV-associated HCC(n)=203; matched adjacent tissue(n)=203), (log-fold-change= 4.82; adj.p=1.43E-79). It was found that GPC3 mRNA level could distinguish HCC from adjacent tissues with high specificity and sensitivity (AUC=0.9108;95%CI=0.08792-0.9424;p

Comprehensive characterization of posttranscriptional impairment-related 3'-UTR mutations in 2413 whole genomes of cancer patients

The 3' untranslated region (3'-UTR) is the vital element regulating gene expression, but most studies have focused on variations in RNA-binding proteins (RBPs), miRNAs, alternative polyadenylation (APA) and RNA modifications. To explore the posttranscriptional function of 3'-UTR somatic mutations in tumorigenesis, we collected whole-genome data from 2413 patients across 18 cancer types. Our updated algorithm, PIVar, revealed 25,216 3'-UTR posttranscriptional impairment-related SNVs (3'-UTR piSNVs) spanning 2930 genes; 24 related RBPs were significantly enriched. The somatic 3'-UTR piSNV ratio was markedly increased across all 18 cancer types, which was associated with worse survival for four cancer types. Several cancer-related genes appeared to facilitate tumorigenesis at the protein and posttranscriptional regulation levels, whereas some 3'-UTR piSNV-affected genes functioned mainly via posttranscriptional mechanisms. Moreover, we assessed immune cell and checkpoint characteristics between the high/low 3'-UTR piSNV ratio groups and predicted 80 compounds associated with the 3'-UTR piSNV-affected gene expression signature. In summary, our study revealed the prevalence and clinical relevance of 3'-UTR piSNVs in cancers, and also demonstrates that in addition to affecting miRNAs, 3'-UTR piSNVs perturb RBPs binding, APA and m6A RNA modification, which emphasized the importance of considering 3'-UTR piSNVs in cancer biology.

Transcriptomic analysis reveals high ITGB1 expression as a predictor for poor prognosis of pancreatic cancer

Transcriptomic analysis of cancer samples helps identify the mechanism and molecular markers of cancer. However, transcriptomic analyses of pancreatic cancer from the Japanese population are lacking. Hence, in this study, we performed RNA sequencing of fresh and frozen pancreatic cancer tissues from 12 Japanese patients to identify genes critical for the clinical pathology of pancreatic cancer among the Japanese population. Additionally, we performed immunostaining of 107 pancreatic cancer samples to verify the results of RNA sequencing. Bioinformatics analysis of RNA sequencing data identified ITGB1 (Integrin beta 1) as an important gene for pancreatic cancer metastasis, progression, and prognosis. ITGB1 expression was verified using immunostaining. The results of RNA sequencing and immunostaining showed a significant correlation (r = 0.552, p = 0.118) in ITGB1 expression. Moreover, the ITGB1 high-expression group was associated with a significantly worse prognosis (p = 0.035) and recurrence rate (p = 0.028). We believe that ITGB1 may be used as a drug target for pancreatic cancer in the future.

SPCS: a spatial and pattern combined smoothing method for spatial transcriptomic expression

High-dimensional, localized ribonucleic acid (RNA) sequencing is now possible owing to recent developments in spatial transcriptomics (ST). ST is based on highly multiplexed sequence analysis and uses barcodes to match the sequenced reads to their respective tissue locations. ST expression data suffer from high noise and dropout events; however, smoothing techniques have the promise to improve the data interpretability prior to performing downstream analyses. Single-cell RNA sequencing (scRNA-seq) data similarly suffer from these limitations, and smoothing methods developed for scRNA-seq can only utilize associations in transcriptome space (also known as one-factor smoothing methods). Since they do not account for spatial relationships, these one-factor smoothing methods cannot take full advantage of ST data. In this study, we present a novel two-factor smoothing technique, spatial and pattern combined smoothing (SPCS), that employs the k-nearest neighbor (kNN) technique to utilize information from transcriptome and spatial relationships. By performing SPCS on multiple ST slides from pancreatic ductal adenocarcinoma (PDAC), dorsolateral prefrontal cortex (DLPFC) and simulated high-grade serous ovarian cancer (HGSOC) datasets, smoothed ST slides have better separability, partition accuracy and biological interpretability than the ones smoothed by preexisting one-factor methods. Source code of SPCS is provided in Github (https://github.com/Usos/SPCS).

Integrative Analysis Constructs an Extracellular Matrix-Associated Gene Signature for the Prediction of Survival and Tumor Immunity in Lung Adenocarcinoma

Background: Lung adenocarcinoma (LUAD) accounts for the majority of lung cancers, and the survival of patients with advanced LUAD is poor. The extracellular matrix (ECM) is a fundamental component of the tumor microenvironment (TME) that determines the oncogenesis and antitumor immunity of solid tumors. However, the prognostic value of extracellular matrix-related genes (ERGs) in LUAD remains unexplored. Therefore, this study is aimed to explore the prognostic value of ERGs in LUAD and establish a classification system to predict the survival of patients with LUAD.

Methods: LUAD samples from The Cancer Genome Atlas (TCGA) and GSE37745 were used as discovery and validation cohorts, respectively. Prognostic ERGs were identified by univariate Cox analysis and used to construct a prognostic signature by Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis. The extracellular matrix-related score (ECMRS) of each patient was calculated according to the prognostic signature and used to classify patients into high- and low-risk groups. The prognostic performance of the signature was evaluated using Kaplan–Meier curves, Cox regression analyses, and ROC curves. The relationship between ECMRS and tumor immunity was determined using stepwise analyses. A nomogram based on the signature was established for the convenience of use in the clinical practice. The prognostic genes were validated in multiple databases and clinical specimens by qRT-PCR.

Results: A prognostic signature based on eight ERGs (FERMT1, CTSV, CPS1, ENTPD2, SERPINB5, ITGA8, ADAMTS8, and LYPD3) was constructed. Patients with higher ECMRS had poorer survival, lower immune scores, and higher tumor purity in both the discovery and validation cohorts. The predictive power of the signature was independent of the clinicopathological parameters, and the nomogram could also predict survival precisely.

Conclusions: We constructed an ECM-related gene signature which can be used to predict survival and tumor immunity in patients with LUAD. This signature can serve as a novel prognostic indicator and therapeutic target in LUAD.

DNA Methylation Mediates EMT Gene Expression in Human Pancreatic Ductal Adenocarcinoma Cell Lines

Due to abundant stroma and extracellular matrix, accompanied by lack of vascularization, pancreatic ductal adenocarcinoma (PDAC) is characterized by severe hypoxia. Epigenetic regulation is likely one of the mechanisms driving hypoxia-induced epithelial-to-mesenchymal transition (EMT), responsible for PDAC aggressiveness and dismal prognosis. To verify the role of DNA methylation in this process, we assessed gene expression and DNA methylation changes in four PDAC cell lines. BxPC-3, MIA PaCa-2, PANC-1, and SU.86.86 cells were exposed to conditioned media containing cytokines and inflammatory molecules in normoxic and hypoxic (1% O2) conditions for 2 and 6 days. Cancer Inflammation and Immunity Crosstalk and Human Epithelial to Mesenchymal Transition RT² Profiler PCR Arrays were used to identify top deregulated inflammatory and EMT-related genes. Their mRNA expression and DNA methylation were quantified by qRT-PCR and pyrosequencing. BxPC-3 and SU.86.86 cell lines were the most sensitive to hypoxia and inflammation. Although the methylation of gene promoters correlated with gene expression negatively, it was not significantly influenced by experimental conditions. However, DNA methyltransferase inhibitor decitabine efficiently decreased DNA methylation up to 53% and reactivated all silenced genes. These results confirm the role of DNA methylation in EMT-related gene regulation and uncover possible new targets involved in PDAC progression.

Syntenin Regulated by miR-216b Promotes Cancer Progression in Pancreatic Cancer

Outcomes for patients with pancreatic cancer (PC) are poor; therefore, there is an urgent need to identify novel therapeutic targets involved in the progression of PC. We previously identified 161 differentially expressed proteins (DEPs) in PC. Syntenin (SDCBP) was identified as a survival-related protein through integrated, survival, and Cox analyses. High expression of SDCBP was associated with a poor prognosis in PC tissue and promoted the proliferation, migration, and invasion of PC cells, and induced epithelial–mesenchymal transition (EMT) via the PI3K/AKT pathway. Additionally, we elucidated the regulatory mechanism underlying these roles of SDCBP at the post-transcriptional level. microRNAs (miRNAs) of SDCBP were predicted using bioinformatics. Low levels of miR-216b expression were confirmed in PC tissues and were negatively correlated with SDCBP expression. miR-216b was found to directly regulate SDCBP expression through luciferase reporter assays. Furthermore, agomiR-216b restrained PC proliferation, migration, invasion, and EMT via the PI3K/AKT pathway, whereas antagomiR-216b facilitated this process. Notably, the knockout of SDCBP counteracted the effect of antagomiR-216b in PC, which suggested that miR-216b and SDCBP represent molecular targets underlying PC progression and EMT. Finally, the results were validated in in vivo studies. These findings indicated that low expression of miR-216b and the oncogene SDCBP contributes to PC migration, invasion, and EMT, and that they have potential as future therapeutic targets for patients with PC.

IMUP and GPRC5A: two newly identified risk score indicators in pancreatic ductal adenocarcinoma

Background

Pancreatic cancer has been a threateningly lethal malignant tumor worldwide. Despite the promising survival improvement in other cancer types attributing to the fast development of molecular precise medicine, the current treatment situation of pancreatic cancer is still woefully challenging since its limited response to neither traditional radiotherapy and chemotherapy nor emerging immunotherapy. The study is to explore potential responsible genes during the development of pancreatic cancer, thus identifying promising gene indicators and probable drug targets.

Methods

Different bioinformatic analysis were used to interpret the genetic events in pancreatic cancer development. Firstly, based on multiple cDNA microarray profiles from Gene Expression Omnibus (GEO) database, the genes with differently mRNA expression in cancer comparing to normal pancreatic tissues were identified, followed by being grouped based on the difference level. Then, GO and KEGG were performed to separately interpret the multiple groups of genes, and further Kaplan–Meier survival and Cox Regression analysis assisted us to scale down the candidate genes and select the potential key genes. Further, the basic physicochemical properties, the association with immune cells infiltration, mutation or other types variations besides expression gap in pancreatic cancer comparing to normal tissues of the selected key genes were analyzed. Moreover, the aberrant changed expression of key genes was validated by immunohistochemistry (IHC) experiment using local hospital tissue microarray samples and the clinical significance was explored based on TCGA clinical data.

Results

Firstly, a total of 22,491 genes were identified to express differently in cancer comparing to normal pancreatic tissues based on 5 cDNA expression profiles, and the difference of 487/22491 genes was over eightfold, and 55/487 genes were shared in multi profiles. Moreover, after genes interpretation which showed the > eightfold genes were mainly related to extracellular matrix structural constituent regulation, Kaplan–Meier survival and Cox-regression analysis were performed continually, and the result indicated that of the 55 extracellular locating genes, GPRC5A and IMUP were the only two independent prognostic indicators of pancreatic cancer. Further, detailed information of IMUP and GPRC5A were analyzed including their physicochemical properties, their expression and variation ratio and their association with immune cells infiltration in cancer, as well as the probable signaling pathways of genes regulation on pancreatic cancer development. Lastly, local IHC experiment performed on PAAD tissue array which was produced with 62 local hospital patients samples confirmed that GPRC5A and IMUP were abnormally up-regulated in pancreatic cancer, which directly associated with worse patients both overall (OS) and recurrence free survival (RFS).

Conclusions

Using multiple bioinformatic analysis as well as local hospital samples validation, we revealed that GPRC5A and IMUP expression were abnormally up-regulated in pancreatic cancer which associated statistical significantly with patients survival, and the genes’ biological features and clinical significance were also explored. However, more detailed experiments and clinical trials are obligatory to support their further potential drug-target role in clinical medical treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02324-w.