Development and validation of a cancer stem cell-related signature for prognostic prediction in pancreatic ductal adenocarcinoma

TBP activates DCBLD1 transcription to promote cell cycle progression in cervical cancer

Discoidin, CUB, and LCCL domain-containing (DCBLD) proteins have been associated with poor prognosis of human cancers. This study investigated the function of DCBLD1 in the development of cervical cancer (CC) and explored its associated mechanism. DCBLD1 was identified as a dysregulated gene in CC via bioinformatics analysis. Immunohistochemistry and RT-qPCR assays revealed increased DCBLD1 expression in CC specimens and cells. Artificial DCBLD1 knockdown blocked the proliferation, invasion, and migration of cells, while promoting cell apoptosis and inducing cell cycle arrest in the G1 phase. Following bioinformatic predictions and subsequent chromatin-immunoprecipitation and luciferase reporter assays, TATA-box binding protein (TBP) was found to be a transcription factor that binds to the DCBLD1 promoter region for transcriptional activation. Knockdown of TBP similarly blocked the malignant properties of CC cells and induced cell cycle arrest, but these changes were reversed by further DCBLD1 overexpression. Xenograft mouse tumors were generated for in vivo validation. Consistently, the tumorigenic activity of CC cells in nude mice was suppressed by TBP knockdown, but restored by DCBLD1 overexpression. In conclusion, this study provides novel evidence that TBP-mediated DCBLD1 activation is correlated with cell cycle and CC progression. TBP and DCBLD1 may serve as potential therapeutic targets for CC management.

A Self-Assembled 3D Model Demonstrates How Stiffness Educates Tumor Cell Phenotypes and Therapy Resistance in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a dense and stiff extracellular matrix (ECM) associated with tumor progression and therapy resistance. To further the understanding of how stiffening of the tumor microenvironment (TME) contributes to aggressiveness, a three-dimensional (3D) self-assembling hydrogel disease model is developed based on peptide amphiphiles (PAs, PA-E3Y) designed to tailor stiffness. The model displays nanofibrous architectures reminiscent of native TME and enables the study of the invasive behavior of PDAC cells. Enhanced tuneability of stiffness is demonstrated by interacting thermally annealed aqueous solutions of PA-E3Y (PA-E3Yh) with divalent cations to create hydrogels with mechanical properties and ultrastructure similar to native tumor ECM. It is shown that stiffening of PA-E3Yh hydrogels to levels found in PDAC induces ECM deposition, promotes epithelial-to-mesenchymal transition (EMT), enriches CD133+/CXCR4+ cancer stem cells (CSCs), and subsequently enhances drug resistance. The findings reveal how a stiff 3D environment renders PDAC cells more aggressive and therefore more faithfully recapitulates in vivo tumors.

Gasdermin D: A Potential New Auxiliary Pan-Biomarker for the Detection and Diagnosis of Diseases

Pyroptosis is a form of programmed cell death mediated by gasdermins, particularly gasdermin D (GSDMD), which is widely expressed in tissues throughout the body. GSDMD belongs to the gasdermin family, which is expressed in a variety of cell types including epithelial cells and immune cells. It is involved in the regulation of anti-inflammatory responses, leading to its differential expression in a wide range of diseases. In this review, we provide an overview of the current understanding of the major activation mechanisms and effector pathways of GSDMD. Subsequently, we examine the importance and role of GSDMD in different diseases, highlighting its potential as a pan-biomarker. We specifically focus on the biological characteristics of GSDMD in several diseases and its promising role in diagnosis, early detection, and differential diagnosis. Furthermore, we discuss the application of GSDMD in predicting prognosis and monitoring treatment efficacy in cancer. This review proposes a new strategy to guide therapeutic decision-making and suggests potential directions for further research into GSDMD.

Increased demand for FAD synthesis in differentiated and stem pancreatic cancer cells is accomplished by modulating FLAD1 gene expression: the inhibitory effect of Chicago Sky Blue

FLAD1, along with its FAD synthase (FADS, EC 2.7.7.2) product, is crucial for flavin homeostasis and, due to its role in the mitochondrial respiratory chain and nuclear epigenetics, is closely related to cellular metabolism. Therefore, it is not surprising that it could be correlated with cancer. To our knowledge, no previous study has investigated FLAD1 prognostic significance in pancreatic ductal adenocarcinoma (PDAC). Thus, in the present work, the FAD synthesis process was evaluated in two PDAC cell lines: (a) PANC-1- and PANC-1-derived cancer stem cells (CSCs), presenting the R273H mutation in the oncosuppressor p53, and (b) MiaPaca2 and MiaPaca2-derived CSCs, presenting the R248W mutation in p53. As a control, HPDE cells expressing wt-p53 were used. FADS expression/activity increase was found with malignancy and even more with stemness. An increased FAD synthesis rate in cancer cell lines is presumably demanded by the increase in the FAD-dependent lysine demethylase 1 protein amount as well as by the increased expression levels of the flavoprotein subunit of complex II of the mitochondrial respiratory chain, namely succinate dehydrogenase. With the aim of proposing FADS as a novel target for cancer therapy, the inhibitory effect of Chicago Sky Blue on FADS enzymatic activity was tested on the recombinant 6His-hFADS2 (IC50  = 1.2 μm) and PANC-1-derived CSCs' lysate (IC50  = 2-10 μm). This molecule was found effective in inhibiting the growth of PANC-1 and even more of its derived CSC line, thus assessing its role as a potential chemotherapeutic drug.

Pan-cancer analyses identify DCBLD2 as an oncogenic, immunological, and prognostic biomarker

Discoidin, CUB, and LCCL domain-containing protein 2 (DCBLD2) is a two-domain transmembrane protein-coding gene located on chromosome 3, the protein expressed by which acts as the membrane receptor of semaphorin and vascular endothelial growth factor during the development of axons and blood vessels. Although several research evidences at the cellular and clinical levels have associated DCBLD2 with tumorigenesis, nothing is known regarding this gene from a pan-cancer standpoint. In this study, we systematically analyzed the influence of DCBLD2 on prognosis, cancer staging, immune characteristics, and drug sensitivity in a variety of cancers based on a unified and standardized pan-cancer dataset. In addition, we performed GO enrichment analyses and KEGG analyses of DCBLD2-related genes and DCBLD2-binding proteins. Our results showed that DCBLD2 is a potential oncogenic, immunological as well as a prognostic biomarker in terms of pan-cancer, and is expected to contribute to the improvement of tumor prognosis and the development of targeted therapy.

Development of a Prognostic Model Based on Pyroptosis-Related Genes in Pancreatic Adenocarcinoma

Background

The importance of pyroptosis in tumorigenesis and cancer progression is becoming increasingly apparent. However, the efficacy of using pyroptosis-related genes (PRGs) in predicting the prognosis of pancreatic adenocarcinoma (PAAD) patients is unknown.

Methods

This investigation used two databases to obtain expression data for PAAD patients. Differentially expressed PRGs (DEPRGs) were identified between PAAD and control samples. Several bioinformatic approaches were used to analyze the biological functions of DEPRGs and to identify prognostic DERPGs. A miRNA-prognostic DEPRG-transcription factor (TF) regulatory network was created via the miRNet online tool. A risk score model was created after each patient's risk score was calculated. The microenvironments of the low- and high-risk groups were assessed using xCell, the expression of immune checkpoints was determined, and gene set variation analysis (GSVA) was performed. Finally, the efficacy of certain potential drugs was predicted using the pRRophetic algorithm, and the results in the high- and low-risk groups were compared.

Results

A total of 13 DEPRGs were identified between PAAD and control samples. Functional enrichment analysis showed that the DEPRGs had a close relationship with inflammation. In univariate and multivariate Cox regression analyses, GSDMC, IRF1, and PLCG1 were identified as prognostic biomarkers in PAAD. The results of the miRNA-prognostic DEPRG-TF regulatory network showed that GSDMC, IRF1, and PLCG1 were regulated by both specific and common miRNAs and TFs. Based on the risk score and other independent prognostic indicators, a nomogram with a good ability to predict the survival of PAAD patients was developed. By evaluating the tumor microenvironment, we observed that the immune and metabolic microenvironments of the two groups were substantially different. In addition, individuals in the low-risk group were more susceptible to axitinib and camptothecin, whereas lapatinib might be preferred for patients in the high-risk group.

Conclusion

Our study revealed the prognostic value of PRGs in PAAD and created a reliable model for predicting the prognosis of PAAD patients. Our findings will benefit the prognostication and treatment of PAAD patients.

Pyroptosis-related genes regulate proliferation and invasion of pancreatic cancer and serve as the prognostic signature for modeling patient survival

OBJECTIVE

Pancreatic ductal adenocarcinoma (PDAC) has high mortality and poor prognosis. Pyroptosis can influence the prognosis of patients by regulating the proliferation, invasion, and metastasis of cancer cells. However, the role of pyroptosis-related genes (PRGs) in PDAC remains unclear.

METHODS

In this study, based on the Cancer Genome Atlas (TCGA) cohort of PDAC samples, univariate Cox analysis and LASSO regression analysis were used to screen the prognostic PRGs and establish the gene signature. To further evaluate the functional significance of CASP4 and NLRP1 in PDAC, we also conducted an in vitro study to explore the mechanism of CASP4 and NLRP1 regulating the occurrence and development of PDAC. Finally, we investigated the relationship between CASP4 and NLRP1 expression levels and drug sensitivity in pancreatic cancer cells.

RESULTS

A risk prediction model based on CASP4 and NLRP1 was established, which can distinguish high-risk patients from low-risk patients (P < 0.001). Both internal validation and external GEO data sets validation demonstrate good predictive capability of the model (AUC = 0.732, AUC = 0.802, AUC = 0.632, P < 0.05). In vitro, CCK8 and Transwell assay suggested that CASP4 may accelerate the progression of PDAC by promoting proliferation and migration of pancreatic cancer cells, while NLRP1 has been found to have tumor suppressive effect. It should be noted that knockdown of CASP4 reduced the level of coke death, the expression levels of acetyl-CoA carboxylase, FASN, SREBP-1 and SREBP-2 were decreased, and the number of lipid droplets was also significantly reduced. Moreover, the enrichment of signaling pathways showed that NLRP1 was significantly correlated with MAPK and RAS/ERK signaling pathways, and knocking down NLRP1 could indeed up-regulate p-ERK expression. Finally, high expression of CASP4 and low expression of NLRP1 increased the sensitivity of pancreatic cancer cells to ERK inhibitors.

CONCLUSIONS

In especial, CASP4 can promote tumor progression by promoting the synthesis and accumulation of fatty acids, while NLRP1 acts on RAS/ERK signaling pathway. Both of genes play an important role in the diagnosis and treatment of PDAC, which may also affect the inhibitors of MAPK/ERK efficiency.

HDAC class I inhibitor domatinostat sensitizes pancreatic cancer to chemotherapy by targeting cancer stem cell compartment via FOXM1 modulation

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) represents an unmet clinical need due to the very poor prognosis and the lack of effective therapy. Here we investigated the potential of domatinostat (4SC-202), a new class I histone deacetylase (HDAC) inhibitor, currently in clinical development, to sensitize PDAC to first line standard gemcitabine (G)/taxol (T) doublet chemotherapy treatment.

METHODS

Synergistic anti-tumor effect of the combined treatment was assessed in PANC1, ASPC1 and PANC28 PDAC cell lines in vitro as well as on tumor spheroids and microtissues, by evaluating combination index (CI), apoptosis, clonogenic capability. The data were confirmed in vivo xenograft models of PANC28 and PANC1 cells in athymic mice. Cancer stem cells (CSC) targeting was studied by mRNA and protein expression of CSC markers, by limiting dilution assay, and by flow cytometric and immunofluorescent evaluation of CSC mitochondrial and cellular oxidative stress. Mechanistic role of forkhead box M1 (FOXM1) and downstream targets was evaluated in FOXM1-overexpressing PDAC cells.

RESULTS

We showed that domatinostat sensitized in vitro and in vivo models of PDAC to chemotherapeutics commonly used in PDAC patients management and particularly to GT doublet, by targeting CSC compartment through the induction of mitochondrial and cellular oxidative stress. Mechanistically, we showed that domatinostat hampers the expression and function of FOXM1, a transcription factor playing a crucial role in stemness, oxidative stress modulation and DNA repair. Domatinostat reduced FOXM1 protein levels by downregulating mRNA expression and inducing proteasome-mediated protein degradation thus preventing nuclear translocation correlated with a reduction of FOXM1 target genes. Furthermore, by overexpressing FOXM1 in PDAC cells we significantly reduced domatinostat-inducing oxidative mitochondrial and cellular stress and abolished GT sensitization, both in adherent and spheroid cells, confirming FOXM1 crucial role in the mechanisms described. Finally, we found a correlation of FOXM1 expression with poor progression free survival in PDAC chemotherapy-treated patients.

CONCLUSIONS

Overall, we suggest a novel therapeutic strategy based on domatinostat to improve efficacy and to overcome resistance of commonly used chemotherapeutics in PDAC that warrant further clinical evaluation.

Establishment of a 4-miRNA Prognostic Model for Risk Stratification of Patients With Pancreatic Adenocarcinoma

Pancreatic adenocarcinomas (PAADs) often remain undiagnosed until later stages, limiting treatment options and leading to poor survival. The lack of robust biomarkers complicates PAAD prognosis, and patient risk stratification remains a major challenge. To address this issue, we established a panel constructed by four miRNAs (miR-4444-2, miR-934, miR-1301 and miR-3655) based on The Cancer Genome Atlas (TCGA) and Human Cancer Metastasis Database (HCMDB) to predicted the prognosis of PAAD patients. Then, a risk prediction model of these four miRNAs was constructed by using Cox regression analysis with the least absolute shrinkage and selection operator (LASSO) regression analysis. This model stratified TCGA PAAD cohort into the low-risk and high-risk groups based on the panel-based risk score, which was significantly associated with 1-, 2-, 3-year OS (AUC=0.836, AUC=0.844, AUC=0.952, respectively). The nomogram was then established with a robust performance signature for predicting prognosis compared to clinical characteristics of pancreatic cancer (PC) patients, including age, gender and clinical stage. Moreover, two GSE data were validated the expressions of 4 miRNAs with prognosis/survival outcome in PC. In the external clinical sample validation, the high-risk group with the upregulated expressions of miR-934/miR-4444-2 and downregulated expressions of miR-1301/miR-3655 were indicated a poor prognosis. Furthermore, the cell counting kit-8 (CCK-8) assay, clone formation, transwell and wound healing assay also confirmed the promoting effect of miR-934/miR-4444-2 and the inhibiting effect of miR-1301/miR-3655 in PC cell proliferation and migration. Taken together, we identified a new 4-miRNA risk stratification model could be used in predicting prognosis in PAAD.

Breast Cancer Classification Based on Tumor Budding and Stem Cell-Related Signatures Facilitate Prognosis Evaluation

Background

Tumor budding (TB) is emerging as a prognostic factor in multiple cancers. Likewise, the stemness of cancer cells also plays a vital role in cancer progression. However, nearly no research has focused on the interaction of TB and tumor stemness in cancer.

Methods

Tissue microarrays including 229 cases of invasive breast cancer (BC) were established and subjected to pan-cytokeratin immunohistochemical staining to evaluate molecular expression. Univariate and multivariate analyses were applied to identify prognostic factors of BC, and the Chi-square test was used for comparison of categorical variables.

Results

High-grade TB was significantly associated with T stage, lymph node metastasis, tumor node metastasis (TNM) stage, epithelial-mesenchymal transition, and poor disease-free survival (DFS) of BC patients. We also found that the prognostic value of TB varied widely among different subtypes and subgroups. Cox regression analysis then showed that TB grade was an independent prognostic factor. Moreover, cancer stem cell (CSC) markers CD44 and ALDH1A1 were significantly higher in high-grade TB tumors. Consequently, patients were classified into high CSC score subgroup and low CSC score subgroups. Further research found that CSC scores correlated with clinicopathological features and DFS of BC patients. Based on TB grade and CSC scores, we classified BC patients into TB_low-CSCs_low (type I), TB_low-CSCs_high (type II), TB_high-CSCs_low (type III), and TB_high-CSCs_high (type IV) subgroups. Survival analysis showed that patients in the type I subgroup had the best DFS, whereas those in the type IV subgroup had the worst DFS. Finally, a TB-CSC-based nomogram for use in BC was established. The nomogram was well calibrated to predict the probability of 5-year DFS, and the C-index was 0.837. Finally, the area under the curve value for the nomogram (0.892) was higher than that of the TNM staging system (0.713).

Conclusion

The combination of TB grade with CSC score improves the prognostic evaluation of BC patients. A novel nomogram containing TB grade and CSC score provides doctors with a candidate tool to guide the individualized treatment of cancer patients.

Prognostic Value and Correlation With Tumor Immune Infiltration of a Novel Metabolism-Related Gene Signature in Pancreatic Cancer

Background

Energy metabolism has been considered as one of the novel features of neoplasms. This study aimed to establish the prognostic signature for pancreatic cancer (PC) based on metabolism-related genes (MRGs).

Methods

We obtained MRGs from the Molecular Signatures Database (MSigDB) and gene sequence data in the Cancer Genome Atlas (TCGA) databases. Then, differentially expressed MRGs (DE-MRGs) were identified utilizing the R software. We built the prognostic model via multivariate Cox regression. Moreover, external validation of the prognostic signature was also performed. Nomogram was created to predict the overall survival (OS). Next, this study analyzed the prognostic value, clinical relationship, and metabolism-related signaling pathways of the prognostic signature. The role in tumor infiltration was further evaluated. Eventually, the expression level of the three MRGs along with the function of NT5E was validated.

Results

Twenty-two MRGs were chosen, eight of which were identified to be most significantly correlated with the prognosis of PC. Meanwhile, a 3-MRG prognostic signature was established, and we verified this prognostic model in two separate external cohorts. What is more, the nomogram was used to predict 1-/2-/3-year OS of PC patients. In addition, the immune cell infiltration and expression of immune checkpoint were significantly influenced by the risk score. Finally, three MRGs were highly expressed in PC cell lines, and NT5E was associated with the proliferation and migration ability of PC.

Conclusion

To sum up, the study established and validated a 3-MRG prognostic signature for PC, and the signature could be utilized to predict the prognosis and assist the individualized clinical management of patients with PC.

Epithelial to Mesenchymal Transition: A Challenging Playground for Translational Research. Current Models and Focus on TWIST1 Relevance and Gastrointestinal Cancers

Resembling the development of cancer by multistep carcinogenesis, the evolution towards metastasis involves several passages, from local invasion and intravasation, encompassing surviving anoikis into the circulation, landing at distant sites and therein establishing colonization, possibly followed by the outgrowth of macroscopic lesions. Within this cascade, epithelial to mesenchymal transition (EMT) works as a pleiotropic program enabling cancer cells to overcome local, systemic, and distant barriers against diffusion by replacing traits and functions of the epithelial signature with mesenchymal-like ones. Along the transition, a full-blown mesenchymal phenotype may not be accomplished. Rather, the plasticity of the program and its dependency on heterotopic signals implies a pendulum with oscillations towards its reversal, that is mesenchymal to epithelial transition. Cells in intermixed E⇔M states can also display stemness, enabling their replication together with the epithelial reversion next to successful distant colonization. If we aim to include the EMT among the hallmarks of cancer that could modify clinical practice, the gap between the results pursued in basic research by animal models and those achieved in translational research by surrogate biomarkers needs to be filled. We review the knowledge on EMT, derived from models and mechanistic studies as well as from translational studies, with an emphasis on gastrointestinal cancers (GI).

A Novel Ferroptosis-Related Gene Signature Predicts Recurrence in Patients With Pancreatic Ductal Adenocarcinoma

Background: Recurrence after surgery is largely responsible for the extremely poor outcomes for patients with pancreatic ductal adenocarcinoma (PDAC). Ferroptosis is implicated in chemotherapy sensitivity and tumor recurrence, we aimed to find out survival-associated ferroptosis-related genes and use them to build a practical risk model with the purpose to predict PDAC recurrence. Methods: Univariate Cox regression analysis was conducted to obtain prognostic ferroptosis-related genes in The Cancer Genome Atlas (TCGA, N = 140) cohort. Multivariate Cox regression analysis was employed to construct a reliable and credible gene signature. The prognostic performance was verified in a MTAB-6134 (N = 286) validation cohort and a PACA-CA (N = 181) validation cohort. The stability of the signature was tested in TCGA and MTAB-6134 cohorts by ROC analyses. Pathway enrichment analysis was adopted to preliminary illuminate the biological relevance of the gene signature. Results: Univariate and multivariate Cox regression analyses identified a 5-gene signature that contained CAV1, DDIT4, SLC40A1, SRXN1 and TFAP2C. The signature could efficaciously stratify PDAC patients with different recurrence-free survival (RFS), both in the training and validation cohorts. Results of subgroup receiver operating characteristic curve (ROC) analyses confirmed the stability and the independence of this signature. Our signature outperformed clinical indicators and previous reported models in predicting RFS. Moreover, the signature was found to be closely associated with several cancer-related and drug response pathways. Conclusion: This study developed a precise and concise prognostic model with the clinical implication in predicting PDAC recurrence. These findings may facilitate individual management of postoperative recurrence in patients with PDAC.

Development and Validation of a 7-Gene Prognostic Signature to Improve Survival Prediction in Pancreatic Ductal Adenocarcinoma

Background: Previous prognostic signatures of pancreatic ductal adenocarcinoma (PDAC) are mainly constructed to predict the overall survival (OS), and their predictive accuracy needs to be improved. Gene signatures that efficaciously predict both OS and disease-free survival (DFS) are of great clinical significance but are rarely reported. Methods: Univariate Cox regression analysis was adopted to screen common genes that were significantly associated with both OS and DFS in three independent cohorts. Multivariate Cox regression analysis was subsequently performed on the identified genes to determine an optimal gene signature in the MTAB-6134 training cohort. The Kaplan-Meier (K-M), calibration, and receiver operating characteristic (ROC) curves were employed to assess the predictive accuracy. Biological process and pathway enrichment analyses were conducted to elucidate the biological role of this signature. Results: Multivariate Cox regression analysis determined a 7-gene signature that contained ASPH, DDX10, NR0B2, BLOC1S3, FAM83A, SLAMF6, and PPM1H. The signature had the ability to stratify PDAC patients with different OS and DFS, both in the training and validation cohorts. ROC curves confirmed the moderate predictive accuracy of this signature. Mechanically, the signature was related to multiple cancer-related pathways. Conclusion: A novel OS and DFS prediction model was constructed in PDAC with multi-cohort and cross-platform compatibility. This signature might foster individualized therapy and appropriate management of PDAC patients.

An EMT-Related Gene Signature for Predicting Response to Adjuvant Chemotherapy in Pancreatic Ductal Adenocarcinoma

Background

For pancreatic ductal adenocarcinoma (PDAC) patients, chemotherapy failure is the major reason for postoperative recurrence and poor outcomes. Establishment of novel biomarkers and models for predicting chemotherapeutic efficacy may provide survival benefits by tailoring treatments.

Methods

Univariate cox regression analysis was employed to identify EMT-related genes with prognostic potential for DFS. These genes were subsequently submitted to LASSO regression analysis and multivariate cox regression analysis to identify an optimal gene signature in TCGA training cohort. The predictive accuracy was assessed by Kaplan–Meier (K-M), receiver operating characteristic (ROC) and calibration curves and was validated in PACA-CA cohort and our local cohort. Pathway enrichment and function annotation analyses were conducted to illuminate the biological implication of this risk signature.

Results

LASSO and multivariate Cox regression analyses selected an 8-gene signature comprised DLX2, FGF9, IL6R, ITGB6, MYC, LGR5, S100A2, and TNFSF12. The signature had the capability to classify PDAC patients with different DFS, both in the training and validation cohorts. It provided improved DFS prediction compared with clinical indicators. This signature was associated with several cancer-related pathways. In addition, the signature could also predict the response to immune-checkpoint inhibitors (ICIs)-based immunotherapy.

Conclusion

We established a novel EMT-related gene signature that was capable of predicting therapeutic response to adjuvant chemotherapy and immunotherapy. This signature might facilitate individualized treatment and appropriate management of PDAC patients.

Transcriptomic Profiling Identifies DCBLD2 as a Diagnostic and Prognostic Biomarker in Pancreatic Ductal Adenocarcinoma

Background: Accumulating evidence shows that the elevated expression of DCBLD2 (discoidin, CUB and LCCL domain-containing protein 2) is associated with unfavorable prognosis of various cancers. However, the correlation of DCBLD2 expression value with the diagnosis and prognosis of pancreatic ductal adenocarcinoma (PDAC) has not yet been elucidated. Methods: Univariate Cox regression analysis was used to screen robust survival-related genes. Expression pattern of selected genes was investigated in PDAC tissues and normal tissues from multiple cohorts. Kaplan–Meier (K–M) survival curves, ROC curves and calibration curves were employed to assess prognostic performance. The relationship between DCBLD2 expression and immune cell infiltrates was conducted by CIBERSORT software. Biological processes and KEGG pathway enrichment analyses were adopted to clarify the potential function of DCBLD2 in PDAC. Results: Univariate analysis, K–M survival curves and calibration curves indicated that DCBLD2 was a robust prognostic factor for PDAC with cross-cohort compatibility. Upregulation of DCBLD2 was observed in dissected PDAC tissues as well as extracellular vesicles from both plasma and serum samples of PDAC patients. Both DCBLD2 expression in tissue and extracellular vesicles had significant diagnostic value. Besides, DCBLD2 expression was correlated with infiltrating level of CD8⁺ T cells and macrophage M2 cells. Functional enrichment revealed that DCBLD2 might be involved in cell motility, angiogenesis, and cancer-associated pathways. Conclusion: Our study systematically analyzed the potential diagnostic, prognostic and therapeutic value of DCBLD2 in PDAC. All the findings indicated that DCBLD2 might play a considerably oncogenic role in PDAC with diagnostic, prognostic and therapeutic potential. These preliminary results of bioinformatics analyses need to be further validated in more prospective studies.

A Novel DNA Replication-Related Signature Predicting Recurrence After R0 Resection of Pancreatic Ductal Adenocarcinoma: Prognostic Value and Clinical Implications

The aim of any surgical resection for pancreatic ductal adenocarcinoma (PDAC) is to achieve tumor-free margins (R0). R0 margins give rise to better outcomes than do positive margins (R1). Nevertheless, postoperative morbidity after R0 resection remains high and prognostic gene signature predicting recurrence risk of patients in this subgroup is blank. Our study aimed to develop a DNA replication-related gene signature to stratify the R0-treated PDAC patients with various recurrence risks. We conducted Cox regression analysis and the LASSO algorithm on 273 DNA replication-related genes and eventually constructed a 7-gene signature. The predictive capability and clinical feasibility of this risk model were assessed in both training and external validation sets. Pathway enrichment analysis showed that the signature was closely related to cell cycle, DNA replication, and DNA repair. These findings may shed light on the identification of novel biomarkers and therapeutic targets for PDAC.