Predicting histologic grades for pancreatic neuroendocrine tumors by radiologic image-based artificial intelligence: a systematic review and meta-analysis.

Background: Accurate detection of the histological grade of pancreatic neuroendocrine tumors (PNETs) is important for patients' prognoses and treatment. Here, we investigated the performance of radiological image-based artificial intelligence (AI) models in predicting histological grades using meta-analysis. Method: A systematic literature search was performed for studies published before September 2023. Study characteristics and diagnostic measures were extracted. Estimates were pooled using random-effects meta-analysis. Evaluation of risk of bias was performed by the QUADAS-2 tool. Results: A total of 26 studies were included, 20 of which met the meta-analysis criteria. We found that the AI-based models had high area under the curve (AUC) values and showed moderate predictive value. The pooled distinguishing abilities between different grades of PNETs were 0.89 [0.84-0.90]. By performing subgroup analysis, we found that the radiomics feature-only models had a predictive value of 0.90 [0.87-0.92] with I2 = 89.91%, while the pooled AUC value of the combined group was 0.81 [0.77-0.84] with I2 = 41.54%. The validation group had a pooled AUC of 0.84 [0.81-0.87] without heterogenicity, whereas the validation-free group had high heterogenicity (I2 = 91.65%, P=0.000). The machine learning group had a pooled AUC of 0.83 [0.80-0.86] with I2 = 82.28%. Conclusion: AI can be considered as a potential tool to detect histological PNETs grades. Sample diversity, lack of external validation, imaging modalities, inconsistent radiomics feature extraction across platforms, different modeling algorithms and software choices were sources of heterogeneity. Standardized imaging, transparent statistical methodologies for feature selection and model development are still needed in the future to achieve the transformation of radiomics results into clinical applications. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42022341852.

LINC00909 up-regulates pluripotency factors and promotes cancer stemness and metastasis in pancreatic ductal adenocarcinoma by targeting SMAD4.

BACKGROUND: Pancreatic cancer stem cells are crucial for tumorigenesis and cancer metastasis. Presently, long non-coding RNAs were found to be associated with Pancreatic Ductal Adenocarcinoma stemness characteristics but the underlying mechanism is largely known. Here, we aim to explore the function of LINC00909 in regulating pancreatic cancer stemness and cancer metastasis. METHODS: The expression level and clinical characteristics of LINC00909 were verified in 80-paired normal pancreas and Pancreatic Ductal Adenocarcinoma tissues from Guangdong Provincial People's Hospital cohort by in situ hybridization. RNA sequencing of PANC-1 cells with empty vector or vector encoding LINC00909 was experimented for subsequent bioinformatics analysis. The effect of LINC00909 in cancer stemness and metastasis was examined by in vitro and in vivo experiments. The interaction between LINC00909 with SMAD4 and the pluripotency factors were studied. RESULTS: LINC00909 was generally upregulated in pancreatic cancer tissues and was associated with inferior clinicopathologic features and outcome. Over-expression of LINC00909 enhanced the expression of pluripotency factors and cancer stem cells phenotype, while knock-down of LINC00909 decreased the expression of pluripotency factors and cancer stem cells phenotype. Moreover, LINC00909 inversely regulated SMAD4 expression, knock-down of SMAD4 rescued the effect of LINC00909-deletion inhibition on pluripotency factors and cancer stem cells phenotype. These indicated the effect of LINC00909 on pluripotency factors and CSC phenotype was dependent on SMAD4 and MAPK/JNK signaling pathway, another downstream pathway of SMAD4 was also activated by LINC00909. Specifically, LINC00909 was localized in the cytoplasm in pancreatic cancer cells and decreased the stability the SMAD4 mRNA. Finally, we found over-expression of LINC00909 not only accelerated tumor growth in subcutaneous mice models, but also facilitated tumorigenicity and spleen metastasis in orthotopic mice models. CONCLUSION: We demonstrate LINC00909 inhibits SMAD4 expression at the post-transcriptional level, which up-regulates the expression of pluripotency factors and activates the MAPK/JNK signaling pathway, leading to enrichment of cancer stem cells and cancer metastasis in pancreatic cancer.

Prognostic significance of glucose-lipid metabolic index in pancreatic cancer patients with diabetes mellitus.

BACKGROUND: The incidence of pancreatic cancer (PC) is higher in diabetic patients due to disturbances in glucose and lipid metabolism caused by insulin resistance (IR). However, the effect of diabetes as well as IR on the prognosis of PC patients remains inconclusive. Our study aims to assess the impact of IR on the prognosis of PC patients with diabetes. METHODS: We conducted a retrospective analysis of 172 PC patients with diabetes in our institute from 2015 to 2021. Prognostic assessment was performed using univariate/multifactorial analysis and survival analysis. The predictive efficacy of metabolic indices was compared using receiver operator characteristic (ROC) curve analysis. RESULTS: One hundred twenty-one of 172 patients died during follow-up, with a median follow-up of 477 days and a median overall survival (OS) of 270 days. Survival analysis showed a significant difference in OS by IR related parameters, which were triglyceride-glucose index (TyG), triglyceride-glucose index-body mass index (TyG-BMI), and triglyceride/high-density lipoprotein cholesterol ratio (TG/HDL-c). The ROC curve indicated that TyG, TyG-BMI, and TG/HDL-c had prognostic efficacy for PC with diabetes. We next optimized TyG-BMI and obtained a new parameter, namely glucose-lipid metabolism index (GLMI), and the patients were classified into GLMI low group and high group based on the calculated cutoff value. The GLMI high group had higher TyG, TyG-BMI, TyG/HDL-c, BMI, TG, total cholesterol (TC), TC/HDL-c, fasting plasma glucose, CA199, and more advanced tumor stage compared to low group. Univariate and multivariate analyses showed that GLMI was an independent prognostic factor. Furthermore, the patients of GLMI high group had worse OS compared to low group and the ROC curves showed GLMI had better predictive ability than TyG and TyG-BMI. CONCLUSIONS: IR is associated with the outcome of PC patients with diabetes and higher level of IR indicates worse prognosis. GLMI has a good predictive value for PC with diabetes.

Identification and validation of stemness-based and ferroptosis-related molecular clusters in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with an extremely poor prognosis. Cancer stem cells (CSCs) are considered to be responsible for the poor survival, recurrence and therapy resistance of PDAC. Ferroptosis plays a crucial role in the sustain and survival of CSCs. Here, we employed a rigorous evaluation of multiple datasets to identify a novel stemness-based and ferroptosis-related genes (SFRGs) signature to access the potential prognostic application. This work we retrieved RNA-sequencing and clinical annotation data from the TCGA, ICGC, GTEx and GEO database, and acquired 26 stem cell gene sets and 259 ferroptosis genes from StemChecker database and FerrDb database, respectively. Based on consensus clustering and ssGSEA analysis, we identified two expression patterns of CSCs traits (C1 and C2). Then, WGCNA analysis was implemented to screen out hub module genes correlated with stemness. Furthermore, differential expression analysis, Pearson correlation analysis, and the Least absolute shrinkage and selection operator (LASSO) and Cox regression were performed to identify the SFRGs and to construct model. In addition, the differences in prognosis, tumor microenvironment (TME) components and therapy responses were evaluated between two risk groups. Finally, we verified the most influential marker ARNTL2 experimentally by western blot, qRT-PCR, sphere formation assay, mitoscreen assay, intracellular iron concentration determination and MDA determination assays. In conclusion, we developed a stemness-based and ferroptosis-related prognostic model, which could help predict overall survival for PDAC patients. Targeting ferroptosis may be a promising therapeutic strategy to inhibit PDAC progression by suppressing CSCs.

Genome-wide CRISPR/Cas9 screening for drug resistance in tumors.

Genome-wide clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR associated nuclease 9 (Cas9) screening is a simple screening method for locating loci under specific conditions, and it has been utilized in tumor drug resistance research for finding potential drug resistance-associated genes. This screening strategy has significant implications for further treatment of malignancies with acquired drug resistance. In recent years, studies involving genome-wide CRISPR/Cas9 screening have gradually increased. Here we review the recent application of genome-wide CRISPR/Cas9 screening for drug resistance, involving mitogen-activated protein kinase (MAPK) pathway inhibitors, poly (ADP-ribose) polymerase inhibitors (PARPi), alkylating agents, mitotic inhibitors, antimetabolites, immune checkpoint inhibitors (ICIs), and cyclin-dependent kinase inhibitors (CDKI). We summarize drug resistance pathways such as the KEAP1/Nrf2 pathway MAPK pathway, and NF-κB pathway. Also, we analyze the limitations and conditions for the application of genome-wide CRISPR/Cas9 screening techniques.

Usage of a simplified blumgart pancreaticojejunostomy in laparoscopic pancreaticoduodenectomy: a single center experience.

BACKGROUND: Blumgart pancreaticojejunostomy (PJ) was shown to be an effective method for pancreaticojejunostomy in open pancreaticoduodenectomy. But the original Blumgart method is involved in complicated and interrupted sutures, which may not be suitable for the laparoscopic approach. In this study, we introduced a simplified Blumgart method for laparoscopic pancreaticojejunostomy. METHODS: We retrospectively reviewed 90 cases of pancreaticoduodenectomy in our institute from 2019 to 2022. Among them, 32 patients received LPD with simplified Blumgart PJ, while 29 received LPD with traditional duct-to-mucosal anastomosis (the Cattel-Warren technique) and 29 received OPD with traditional duct-to-mucosal anastomosis. And the time length for PJ and the surgical outcome were compared in these three groups. RESULTS: The simplified Blumgart pancreaticojejunostomy was accomplished in all 32 cases with no conversion to open surgery due to improper sutures. And the time length for laparoscopic simplified Blumgart pancreaticojejunostomy was 26 ± 8.4 min, which was shorter than laparoscopic traditional ductal to mucosa pancreaticojejunostomy (39 ± 13.7 min). Importantly, the overall incidence for POPF and grade B&C POPF rate in the laparoscopic simplified Blumgart method group were 25% and 9.38% respectively, which were lower than the other two groups. Moreover, we performed univariate analysis and multivariate analysis and found soft pancreas, pancreatic ductal diameter < = 3 mm and intraoperative blood loss were independent risk factors for POPF after PD. CONCLUSION: Our data suggest that the simplified Blumgart method is a feasible and reliable method for laparoscopic PJ which deserves further validation.

A hierarchical prognostic model for Co-diabetes pancreatic adenocarcinoma.

Background: Co-diabetes pancreatic adenocarcinoma has a poorer prognosis than pancreatic adenocarcinoma without diabetes. This study aimed to develop a reliable prognostic model for patients with co-diabetes pancreatic adenocarcinoma. Method: Overall, 169 patients with co-diabetes pancreatic adenocarcinoma were included in our study. First, the independent risk factors affecting the prognosis of patients with co-diabetes pancreatic adenocarcinoma were determined by univariate and multivariate Cox regression analyses. Based on these identified risk factors, we developed a nomogram and evaluated its predictive ability using the concordance index, receiver operating characteristic curve, calibration plot, decision curve, and net reclassification index. Results: In this study, prealbumin, transferrin, carcinoembryonic antigen, distant metastasis, tumor differentiation neutrophil count, lymphocyte count and fasting blood glucose were confirmed as significant prognostic factors. Based on these predictors, a new nomogram was developed. Compared with the American Joint Committee on Cancer 8 staging system and other models, the nomogram achieved a higher concordance index in the training (0.795) and validation (0.729) queues. The area under the nomogram's curve for predicting patient survival at 0.5, 1, and 1.5 years in the training queue was >0.8. Patients were risk-stratified using the nomogram, and Kaplan-Meier survival curves of subgroups were plotted. The Kaplan-Meier curve also showed better separation than the American Joint Committee on Cancer 8 staging system, indicating that our model has a better risk hierarchical ability. Conclusions: Compared to the American Joint Committee on Cancer 8 staging system and other predictive models, our model showed better predictive ability for patients with co-diabetes pancreatic adenocarcinoma. Our model will help in patients' risk stratification and improves their prognosis.

Identification by genetic algorithm optimized back propagation artificial neural network and validation of a four-gene signature for diagnosis and prognosis of pancreatic cancer.

Background: Although some improvements in the management of pancreatic cancer (PC) have been made, no major breakthroughs in terms of biomarker discovery or effective treatment have emerged. Here, we applied artificial intelligence (AI)-based methods to develop a model to diagnose PC and predict survival outcome. Methods: Multiple bioinformatics methods, including Limma Package, were performed to identify differentially expressed genes (DEGs) in PC. A Back Propagation (BP) model was constructed, followed by Genetic Algorithm (GA) filtering and verification of its prognosis capacity in the TCGA cohort. Furthermore, we validated the protein expression of the selected DEGs in 92 clinical PC tissues using immunohistochemistry. Finally, intro studies were performed to assess the function of SLC6A14 and SPOCK1 on pancreatic ductal adenocarcinoma (PDAC) cells proliferation and apoptosis. Results: Four candidate genes (LCN2, SLC6A14, SPOCK1, and VCAN) were selected to establish a four-gene signature for PC. The gene signature was validated in the TCGA PC cohort, and found to show satisfactory discrimination and prognostic power. Areas under the curve (AUC) values of overall survival were both greater than 0.60 in the TCGA training cohort, test cohort, and the entire cohort. Kaplan-Meier analyses showed that high-risk group had a significantly shorter overall survival and disease-free survival than the low-risk group. Further, the elevated expression of SLC6A14 and SPOCK1 in PC tissues was validated in the TCGA + GETx datasets and 92 clinical PC tissues, and was significantly associated with poor survival in PC. In PDAC cell line, SLC6A14 or SPOCK1 knockdown inhibited cells proliferation, migration and promoted cells apoptosis. Conclusions: Using Limma Package and GA-ANN, we developed and validated a diagnostic and prognostic gene signature that yielded excellent predictive capacity for PC patients' survival. In vitro studies were further conducted to verify the functions of SLC6A14 and SPOCK1 in PC progression.

Genome-Wide CRISPR/Cas9 Library Screening Identified that DUSP4 Deficiency Induces Lenvatinib Resistance in Hepatocellular Carcinoma.

Background: Lenvatinib is in a first-line therapy for advanced hepatocellular carcinoma (HCC). However, drug resistance is one of the principal obstacles for treatment failure. The molecular mechanism of Lenvatinib resistance has not been well investigated. Materials and methods: A genome-wide CRISPR/Cas9 knockout screening system was established and bioinformatic analysis was used to identify critical genes associated with Lenvatinib resistance. Cell proliferation assays, colony formation assays and cell migration assays were performed to investigate the effect of drug resistance associated genes, particularly DUSP4, on cancer cell malignant behavior during Lenvatinib treatment. In vivo experiments were conducted by using a xenograft mouse model. Results: We identified six genes that were associated with Lenvatinib resistance in HCC, including DUSP4, CCBL1, DHDH, CNTN2, NOS3 and TNF. DUSP4 was found to be significantly decreased at the mRNA and protein levels in Lenvatinib resistant HCC cells. DUSP4 knockout enhanced HCC cell survival, cell proliferation and migration during Lenvatinib treatment in vitro and in vivo, accompanied by regulation of p-ERK and p-MEK levels. This finding implied that DUSP4 deficiency induced Lenvatinib resistance. Interestingly, DUSP4 deficiency induced Lenvatinib resistance was abrogated by the MEK inhibitor Selumetinib, implying that MEK phosphorylation and DUSP4-inhibition dependent ERK activation were required for drug resistance. Finally, we found that DUSP4 deficiency was associated with HCC prognosis and response to Lenvatinib based on clinical data. Conclusions: DUSP4 deficiency mediates Lenvatinib resistance by activating MAPK/ERK signaling and combination therapy using Lenvatinib and MEK inhibitors may be a promising therapeutic strategy for overcoming Lenvatinib resistance.

Identification of LSM Family Members as Novel Unfavorable Biomarkers in Hepatocellular Carcinoma.

Background: Smith-like (LSM) family members play critical roles in multiple oncologic processes in several types of malignancies. The study on LSM family members of HCC might provide new insights into the tumorigenesis and therapeutic strategies of HCC. Methods: The clinical significance and oncologic biological functions of LSM family members were assessed through multiple bioinformatics methods and in vitro studies. The potential correlation between LSM family members and tumor immunity was also investigated using single sample gene set enrichment analysis (ssGSEA) and the ESTIMATE algorithm. Results: LSM family member overexpression in HCC was significantly correlated with poor clinical outcomes such as higher TNM stage, advanced histologic grade, and worse prognosis. A risk score system based on LSM5, LSM10, LSM12, and LSM14B showed a reliable predictive ability for OS of HCC patients. Functional enrichment analysis demonstrated that LSM family members overexpressed were all involved in cell cycle related biological processes. Besides, LSM12, LSM14A, and LSM14B were found to be significantly associated with PI3K-Akt-mTOR and T cell receptor signaling pathways. Tumors with LSM12, LSM14A, and LSM14B overexpression exhibited lower infiltration of activated CD8+ T cells with declined cytolytic activity and immune score, but increased infiltration of Th2 cells and Th2/Th1. LSM12, LSM14A, and LSM14B overexpression is also associated with higher tumor-related immune checkpoints (e.g., PD-L1, B7-H3, and PVR) expression and increased therapeutic insensitivity to immune checkpoint blockade (ICB). Moreover, the knockdown of LSM12, LSM14A, and LSM14B significantly inhibited the proliferation and invasion of HCC cells. Conclusion: This study systematically investigated the expression pattern and biological values of LSM family members in HCC and identified LSM family members as novel therapeutic targets in HCC.

Identification of MBOAT2 as an Unfavorable Biomarker Correlated with KRAS Activation and Reduced CD8+ T-Cell Infiltration in Pancreatic Cancer.

Objectives: Limited research on the role of membrane-bound O-acyltransferase domain-containing 2 (MBOAT2) in cancer biology exists. In particular, the underlying role of MBOAT2 and its potential mechanisms in pancreatic cancer have not yet been explored. Further study of MBOAT2 could provide new ideas about the carcinogenesis and treatment of pancreatic cancer (PC). Methods: In the current study, the potential biological and clinical significances of MBOAT2 were explored by bioinformatics analysis. Real-time quantitative polymerase chain reaction and western blot analysis were performed to determine the level of MBOAT2 in pancreatic ductal adenocarcinoma (PDAC) cell lines. MTT, colony formation, and Transwell assays and flow cytometry of cell cycle were performed to analyze PDAC cell proliferation, migration, and cycle progression. The potential relationship between MBOAT2 level and tumor immunity was analyzed using the ESTIMATE algorithm, CIBERSORT algorithm, and single-sample gene set enrichment analysis. Results: The level of MBOAT2 was remarkably upregulated in most tumors, especially pancreatic tumors, and was positively correlated with a greater rate of tumor recurrence, higher histologic grade, and worse overall survival. MBOAT2 overexpression was also closely correlated with the mutation status and expression level of driver genes, especially KRAS. Meanwhile, functional enrichment analysis demonstrated that MBOAT2 might be involved in cell-cell communication; cell cycling; the Ras signaling pathway; and immune-related biological functions such as the leukocyte activation involved in T-cell-receptor signaling pathway, the inflammatory response, and antigen processing and presentation. Furthermore, in vitro experiments demonstrated that MBOAT2 overexpression accelerated PC cell proliferation and migration. MBOAT2 overexpression also enhanced CDK2 and CCNA2 expression, leading to cell cycle progression from the G1 phase to the G2 phase. Lastly, MBOAT2 overexpression reduced the infiltration level of CD8+ T-cells, plasmacytoid dendritic cells, and activated dendritic cells but triggered a high type-2 T helper/type-1 T helper cell ration (Th2/Th1 ration) in PC. Conclusion: Our findings suggest that MBOAT2 is a potential protooncogene in PDAC that predicts a poor prognosis and is related to KRAS activation and inferior infiltration of CD8+ T-cells in PC.

ZMAT1 acts as a tumor suppressor in pancreatic ductal adenocarcinoma by inducing SIRT3/p53 signaling pathway.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancer due to its highly aggressive phenotype and lack of effective biomarkers or treatment strategies. ZMAT1 belongs to the C2H2 type zinc finger family, but its biological function is rarely investigated, as well as its role in cancer development. METHODS: Multiple bioinformatics analyses were used to evaluate ZMAT1 expression and potential role in PDAC. Intro and vivo studies were performed to assess the effects of ZMAT1 on PDAC cells growth. Furthermore, CHIP-seq and luciferase reporter assay was conducted to identify its specific regulatory mechanism in PDAC. RESULTS: The current study identified the down-regulation of ZMAT1 and its associations with unfavorable clinicopathological characteristics and poor survival of PDAC. Further, we found overexpression of ZMAT1 inhibited pancreatic cancer cell proliferation by inducing p21, leading to impaired S/G2 cell cycle progression. Besides, over-expression of ZMAT1 led to decreased pancreatic cancer cell apoptosis. Mechanistically, ZMAT1 up-regulated p53 expression and inhibition of p53 abrogated the effect of ZMAT1 over-expression on pancreatic cancer cell, indicating the role of ZMAT1 in PDAC was dependent on p53. By performing CHIP-seq assay, we found ZMAT1 did not bind to P53 but bound to the promoter region of SIRT3, an upstream regulator for p53. Luciferase reporter assay showed transfection of ZMAT1 induced SIRT3 transcription, suggesting ZMAT1 was a transcriptional activator for SIRT3. CONCLUSION: Our findings indicated the role of ZMAT1-SIRT3-p53 signaling pathway during tumor growth, highlighting that ZMAT1 is a tumor suppressor and novel biomarker of PDAC.

YTHDF1 amplification is correlated with worse outcome and lower immune cell infiltrations in breast cancer.

OBJECTIVE: N6-methyladenosine (m6A) is a common RNA modification on eukaryotic mRNA and some of the m6A regulatory proteins play a crucial role in breast cancer. However, the copy number variations for m6A regulatory proteins and their role in clinicopathological characteristics and survival in breast cancer remain unclear. METHODS: In this study, we screened the m6A related genes alterations in breast cancer by analyzing the Molecular Taxonomy of Breast Cancer International Consortium and The Cancer Genome Atlas database, and further analyzed the clinical prognostic value of YTHDF1 amplification. RESULTS: The YTH domain family (YTHDF3 and YTHDF1) amplification exhibited higher alteration rates among 10 m6A regulatory genes. YTHDF1 and YTHDF3 amplification resulted in higher mRNA expression (P< 0.0001). Protein expression of YTHDF1 and YTHDF3 were higher in breast cancer (P< 0.0001). YTHDF1 amplification presented a high correlation with worse clinicopathological characteristics and overall survival in patients with breast cancer. Cox regression analysis showed that YTHDF1 amplification was an independent risk factor for 10-year overall survival in breast cancer (Hazard ratio: 1.663; 95% confidence interval: 1.298-2.131; P< 0.001). Gene set enrichment analysis revealed that the downstream target of YTHDF1 may be related to MYC signaling regulation and T cell differentiation. Moreover, YTHDF1 amplification and high expression resulted in lower immune cell infiltration. YTHDF1 knockdown retrained proliferation, migration and invasion in breast cancer cells in vitro. CONCLUSIONS: We found significant worse clinical characteristics and lower immune infiltrates in patients with YTHDF1 amplification. The findings indicate that YTHDF1 amplification may be a potential target for the treatment of breast cancer.

An injectable thermosensitive hydrogel loaded with a theranostic nanoprobe for synergistic chemo-photothermal therapy for multidrug-resistant hepatocellular carcinoma.

Multi-drug resistance (MDR) is a complicated cellular defense mechanism for tumor cells to resist chemotherapy drugs, which is also the main cause of chemotherapy failure. In this study, a local injectable hydrogel delivery system was used to construct an on-demand sustained-release platform with the advantages of chemotherapy, photothermal therapy (PTT), and magnetic resonance imaging (MRI). It could achieve synergistic chemo-photothermal therapy and real-time evaluation of the therapeutic effects (via MRI) for MDR hepatocellular carcinoma (HCC). Furthermore, after a single administration, the prepared hydrogel with a theranostic nanoprobe could release the therapeutic agents on demand for up to 14 d. Firstly, doxorubicin (DOX) and gold-manganese oxide (Au-MnO) nanoparticles (NPs) were incorporated into liposome-based self-assembled micelles, then loaded into the thermosensitive hydrogel (F127) to form DOX@Au-MnO-L NPs/F127 hydrogel (DAML/H). The prepared NP complex showed a spherical morphology with a narrow size distribution. The prepared hydrogel drug delivery system had injectable properties and stable photothermal conversion. Both the DOX@Au-MnO-L NPs and DAML/H showed controlled drug release under near infrared (NIR) laser irradiation. The in vitro MRI studies indicated that the prepared DAML/H had a high relaxation rate (14.38 mM-1 s-1) and good MRI scanning sensitivity conditions. The in vitro and in vivo results suggested the synergistic chemo-photothermal therapy of DAML/H with NIR irradiation (808 nm, 1 W cm-2, 10 min) improved the antitumor efficacy for MDR HCC. The in vivo retention experiment of Au in tumors indicated that the prepared hydrogel drug delivery system (DAML/H) had a good ability to retain Au in the tumor for a long time (at least 14 d). The western blotting results revealed that DAML/H with laser treatment could effectively downregulate P-glycoprotein (P-gp), p53 and antiapoptotic protein (Bcl-2), whereas the expression level of proapoptotic protein (Bax) and caspase-3 were increased. Therefore, DAML/H could serve as a promising synergistic chemo-photothermal therapy for MDR HCC, and a single administration might achieve long-term (14 d), on-demand, sustained-release treatment of tumors.

Identification of LIPH as an unfavorable biomarkers correlated with immune suppression or evasion in pancreatic cancer based on RNA-seq.

BACKGROUND: It is widely considered that pancreatic cancer (PC) is an immunosuppressive cancer. Immune-based therapies remain promising therapeutic strategies for PC. Overexpression of lipase H (LIPH) was reported to be related to immunity in cattle and has also been demonstrated to promote tumor progression in several tumors, but its role in pancreatic carcinogenesis remains unclear. Study on LIPH in PC might provide a new insight into the immunosuppression in PC. METHODS: The potential biological and clinical significance of LIPH was evaluated by bioinformatics analysis. We further investigated potential associations between the expression of LIPH and tumor immune infiltration using the CIBERSORT algorithm, the ESTIMAT algorithm, and single sample gene set enrichment analysis (ssGSEA). RESULTS: LIPH was significantly overexpressed in tumor tissues compared with normal tissues. LIPH overexpression correlated with tumor recurrence, advanced histologic grade, and poorer overall survival (OS). Four of the most common somatic mutation, including KRAS, TP53, CDKN2A, and SMAD4, in PC were all correlated with high LIPH expression. And high LIPH expression was significantly correlated with KRAS activation and SMAD4 inactivation. Besides, LIPH expression was involved in various biological pathways such as negative regulation of cell-cell adhesion, actin cytoskeleton, EMT, angiogenesis, and signaling by MST1. And LIPH overexpression caused high infiltration of TAMs, Treg cells, and Th2/Th1, but reduced the infiltration of CD8+ T cells and Th1 cells. CONCLUSIONS: Our findings demonstrated that LIPH correlated with immune suppression or evasion and may function as a novel unfavorable prognostic biomarker in PC.

Prognostic Stratification Based on HIF-1 Signaling for Evaluating Hypoxic Status and Immune Infiltration in Pancreatic Ductal Adenocarcinomas.

Pancreatic ductal adenocarcinoma (PDAC) has a hypoxic and desmoplastic tumor microenvironment (TME), leading to treatment failure. We aimed to develop a prognostic classifier to evaluate hypoxia status and hypoxia-related molecular characteristics of PDAC. In this study, we classified PDAC into three clusters based on 16 known hypoxia-inducible factor 1 (HIF-1)-related genes. Nine differentially expressed genes were identified to construct an HIF-1 score system, whose predictive efficacy was evaluated. Furthermore, we investigated oncogenic pathways and immune-cell infiltration status of PDAC with different scores. The C-index of the HIF-1score system for OS prediction in the meta-PDAC cohort and the other two validation cohorts were 0.67, 0.63, and 0.65, respectively, indicating that it had a good predictive value for patient survival. Furthermore, the area under the curve (AUC) of the receiver operating characteristic (ROC) curve of the HIF-1α score system for predicting 1-, 3-, and 4-year OS indicated the HIF-1α score system had an optimal discrimination of prognostic prediction for PDAC. Importantly, our model showed superior predictive ability compared to previous hypoxia signatures. We also classified PDAC into HIF-1 scores of low, medium, and high groups. Then, we found high enrichment of glycolysis, mTORC1 signaling, and MYC signaling in the HIF-1 score high group, whereas the cGMP metabolic process was activated in the low score group. Of note, analysis of public datasets and our own dataset showed a high HIF-1 score was associated with high immunosuppressive TME, evidenced by fewer infiltrated CD8+ T cells, B cells, and type 1 T-helper cells and reduced cytolytic activity of CD8+ T cells. In summary, we established a specific HIF-1 score system to discriminate PDAC with various hypoxia statuses and immune microenvironments. For highly hypoxic and immunosuppressive tumors, a combination treatment strategy should be considered in the future.

Development of a KRAS-Associated Metabolic Risk Model for Prognostic Prediction in Pancreatic Cancer.

BACKGROUND: KRAS was reported to affect some metabolic genes and promote metabolic reprogramming in solid tumors. However, there was no comprehensive analysis to explore KRAS-associated metabolic signature or risk model for pancreatic cancer (PC). METHODS: In the current study, multiple bioinformatics analyses were used to identify differentially expressed metabolic genes based on KRAS mutation status in PC. Then, we developed and validated a prognostic risk model based on the selected KRAS-associated metabolic genes. Besides, we explored the association between the risk model and the metabolic characteristics as well as gemcitabine-associated chemoresistance in PC. RESULTS: 6 KRAS-associated metabolic genes (i.e., CYP2S1, GPX3, FTCD, ENPP2, UGT1A10, and XDH) were selected and enrolled to establish a prognostic risk model. The prognostic model had a high C-index of 0.733 for overall survival (OS) in TCGA pancreatic cancer database. The area under the curve (AUC) values of 1- and 3-year survival were both greater than 0.70. Then, the risk model was validated in two GEO datasets and also presented a satisfactory discrimination and calibration performance. Further, we found that the expression of some KRAS-driven glycolysis-associated genes (PKM, GLUT1, HK2, and LDHA) and gemcitabine-associated chemoresistance genes (i.e., CDA and RMM2) was significantly upregulated in high-risk PC patients evaluated by the risk model. CONCLUSIONS: We constructed a risk model based on 6 KRAS-associated metabolic genes, which predicted patients' survival with high accuracy and reflected tumor metabolic characteristics and gemcitabine-associated chemoresistance in PC.

CMTM3 Overexpression Predicts Poor Survival and Promotes Proliferation and Migration in Pancreatic Cancer.

Background: Recent evidence has shown that CKLF-like MARVEL transmembrane domain containing 3 (CMTM3) promoted carcinogenesis and tumor progression in a variety of cancer types. The goal of our study is to investigate the association between CMTM3 and pancreatic cancer (PC). Materials and Methods: In current study, data from public databases was used to analyze CMTM3 expression in PC. Quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC) were used to investigate CMTM3 expression and determine its clinical significance in PC. Then CMTM3 promoting PC aggressiveness was demonstrated in vitro experiments by cell proliferation and migration assay. Functional and pathway enrichment analyses were performed to evaluate the potential role of CMTM3 in PC. Results: Results of qRT-PCR and IHC revealed that CMTM3 was significantly overexpressed in PC tissues. High CMTM3 expression was an independent risk factor for poor prognosis of PC patients. Overexpression of CMTM3 was associated with poor overall survival (P-value =0.031) and disease-free survival (P-value =0.0047) in the TCGA cohort. Functional and pathway enrichment analyses showed that CMTM3 were enriched in "Regulation of cell proliferation and regulation of cell differentiation, cell morphogenesis, regulation of cell differentiation, Hedgehog signaling pathway, Wnt signaling pathway, ECM-receptor interaction and pathways in cancer". In PC cell lines, CCK8, clone formation and transwell assays showed that CMTM3 knockdown inhibited cells proliferation and migration. Conclusion: CMTM3 was overexpressed and promotes tumor aggressiveness in PC. Our findings provided a novel therapeutic target for PC.

SLC39A10 Upregulation Predicts Poor Prognosis, Promotes Proliferation and Migration, and Correlates with Immune Infiltration in Hepatocellular Carcinoma.

BACKGROUND: Recent evidence has shown that Solute Carrier Family 39 Member 10 (SLC39A10) promoted tumor progression in several cancer types. The study intended to explore the expression and function of SLC39A10 in hepatocellular carcinoma (HCC). METHODS: Multiple bioinformatics analyses were used to evaluate SLC39A10 expression and potential role in HCC. Quantitative real-time polymerase chain reaction and immunohistochemistry were used to confirm SLC39A10 expression. Intro studies were performed to assess the effects of SLC39A10 on HCC cells proliferation and migration. Furthermore, flow cytometry was conducted to identify its specific function in apoptosis of HCC. RESULTS: SLC39A10 was significantly over-expressed in HCC samples from both bioinformatic databases and our cohort. Survival analyses suggested patients with high expression of SLC39A10 had poor overall survival and disease-free survival (P-value <0.01). Further, the expression of SLC39A10 was positively correlated with tumor-infiltrating lymphocytes and some immune checkpoints like CTLA4, TIM3 and TGFB1. In HCC cell lines, SLC39A10 knockdown inhibited cells proliferation and migration, but promoted apoptosis. CONCLUSION: An increased SLC39A10 expression was found and served as an unfavorable indicator of survival in HCC. Further studies suggested SLC39A10 promotes tumor aggressiveness and may provide a novel target for HCC therapy.