VPAC2 Receptor Signaling Promotes Growth and Immunosuppression in Pancreatic Cancer.

Pancreatic cancer (PDAC) harbors a complex tumor microenvironment (TME), and crosstalk between cells in the TME can contribute to drug resistance and relapse. Vasoactive intestinal peptide (VIP) is overexpressed in PDAC, and VIP receptors expressed on T cells are a targetable pathway that sensitizes PDAC to immunotherapy. In this study, we showed that pancreatic cancer cells engage in autocrine VIP signaling through VIP receptor 2 (VPAC2). High co-expression of VIP with VPAC2 correlated with reduced relapse-free survival in PDAC patients. VPAC2 activation in PDAC cells upregulated piwi-like RNA-mediated gene silencing 2 (Piwil2), which stimulated cancer cell clonogenic growth. In addition, VPAC2 signaling increased expression of TGF-ß1 to inhibit T cell function. Loss of VPAC2 on PDAC cells led to reduced tumor growth and increased sensitivity to anti-PD1 immunotherapy in mouse models of PDAC. Overall, these findings expand our understanding of the role of VIP/VPAC2 signaling in PDAC and provide the rationale for developing potent VPAC2-specific antagonists for treating PDAC patients.

CT-based peritumoral radiomics nomogram on prediction of response and survival to induction chemotherapy in locoregionally advanced nasopharyngeal carcinoma.

PURPOSE: The study aims to harness the value of radiomics models combining intratumoral and peritumoral features obtained from pretreatment CT to predict treatment response as well as the survival of LA-NPC(locoregionally advanced nasopharyngeal carcinoma) patients receiving multiple types of induction chemotherapies, including immunotherapy and targeted therapy. METHODS: 276 LA-NPC patients (221 in the training and 55 in the testing cohort) were retrospectively enrolled. Various statistical analyses and feature selection techniques were applied to identify the most relevant radiomics features. Multiple machine learning models were trained and compared to build signatures for the intratumoral and each peritumoral region, along with a clinical signature. The performance of each model was evaluated using different metrics. Subsequently, a nomogram model was constructed by combining the best-performing radiomics and clinical models. RESULTS: In the testing cohort, the nomogram model exhibited an AUC of 0.816, outperforming the other models. The nomogram model's calibration curve showed good agreement between predicted and observed outcomes in both the training and testing sets. When predicting survival, the model's concordance index (C-index) was 0.888 in the training cohort and 0.899 in the testing cohort, indicating its robust predictive ability. CONCLUSION: In conclusion, the combined nomogram model, incorporating radiomics and clinical features, outperformed other models in predicting treatment response and survival outcomes for LA-NPC patients receiving induction chemotherapies. These findings highlight the potential clinical utility of the model, suggesting its value in individualized treatment planning and decision-making.

Cost-Effectiveness Analysis of Sintilimab Combined with Chemotherapy Versus Chemotherapy Alone as the First-Line Treatment for Advanced Esophageal Cancer.

Background: Esophageal cancer has a poor prognosis and currently ranks sixth in global cancer mortality rates. The ORIENT-15 trial showed sintilimab plus chemotherapy significantly improved survival when compared to chemotherapy alone. This study aimed to evaluate the cost-effectiveness of sintilimab, a programmed death-ligand 1 (PD-L1) inhibitor, plus chemotherapy in treating patients with esophageal cancer compared with chemotherapy alone. Methods: A Markov model with a 10-year horizon was developed based on the perspective of the Chinese healthcare payers. We conducted a cost-effectiveness analysis for sintilimab combined with chemotherapy based on a questionnaire. Patients were grouped into the sintilimab group based on a positive score of 10 or more (combined positive score (CPS) ≥ 10 groups), and those with any other PD-L1 expression were randomized into patient groups. We estimated the cost and the effectiveness of sintilimab on the quality-adjusted life-years (QALYs), and the incremental cost-effectiveness ratio (ICER) was computed. One-way and probabilistic sensitivity analyses were conducted to explore the impact of uncertainties on the cost-effectiveness results. Results: In the base-case analysis, compared with chemotherapy alone, the ICER of sintilimab plus chemotherapy for all patients was $21024.05 per QALY, and in the CPS≥10 group, it was $20974.23 per QALY. This was lower than $37653 per QALY. One-way sensitivity analysis demonstrated that ICERs were most sensitive to the price of sintilimab. Conclusion: The study demonstrated that sintilimab plus chemotherapy for advanced esophageal cancer as its first-line treatment would be more cost-effective than chemotherapy alone in Chinese patients.

A new ferritin SjFer0 affecting the growth and development of Schistosoma japonicum.

BACKGROUND: Schistosomiasis, an acute and chronic parasitic disease, causes substantial morbidity and mortality in tropical and subtropical regions of the world. Iron is an essential constituent of numerous macromolecules involving in important cellular reactions in virtually all organisms. Trematodes of the genus Schistosoma live in iron-rich blood, feed on red blood cells and store abundant iron in vitelline cells. Ferritins are multi-meric proteins that store iron inside cells. Three ferritin isoforms in Schistosoma japonicum are known, namely SjFer0, SjFer1 and SjFer2; however, their impact on the growth and development of the parasites  is still unknown. In this study we report on and characterize the ferritins in S. japonicum. METHODS: A phylogenetic tree of the SjFer0, SjFer1 and SjFer2 genes was constructed to show the evolutionary relationship among species of genus Schistosoma. RNA interference in vivo was used to investigate the impact of SjFer0 on schistosome growth and development.  Immunofluorescence assay was applied  to localize the expression of the ferritins. RNA-sequencing was performed  to characterize the iron transport profile after RNA interference. RESULTS: SjFer0 was found to have low similarity with SjFer1 and SjFer2 and contain an additional signal peptide sequence. Phylogenetic analysis revealed that SjFer0 can only cluster with some ferritins of other trematodes and tapeworms, suggesting that this ferritin branch might be unique to these parasites. RNA interference in vivo showed that SjFer0 significantly affected the growth and development of schistosomula but did not affect egg production of adult female worms. SjFer1 and SjFer2 had no significant impact on growth and development. The immunofluorescence study showed that SjFer0 was widely expressed in the somatic cells and vitelline glands but not in the testicle or ovary. RNA-sequencing indicated  that, in female, the ion transport process and calcium ion binding function were downregulated after SjFer0 RNA interference. Among the differentially downregulated genes, Sj-cpi-2, annexin and insulin-like growth factor-binding protein may be accounted for the suppression of schistosome growth and development. CONCLUSIONS: The results indicate that SjFer0 affects the growth and development of schistosomula but does not affect egg production of adult female worms. SjFer0 can rescue the growth of the fet3fet4 double mutant Saccharomyces cerevisiae (strain DEY1453), suggesting being able to promote iron absorption. The RNA interference of SjFer0 inferred that  the suppression of worm growth and development may via  down-regulating Sj-cpi-2, annexin, and IGFBP.

Integrating Genomic Data with Transcriptomic Data for Improved Survival Prediction for Adult Diffuse Glioma.

Background: Glioma is the most common type of primary central nervous system tumors. However, the relationship between gene mutations and transcriptome is unclear in diffuse glioma, and there are no systemic analyses with regard to the genotype-phenotype association currently. Methods: We performed the multi-omics analysis in large glioblastoma multiforme (GBM, n=126) and low-grade glioma (LGG, n=481) cohorts obtained from The Cancer Genome Atlas (TCGA) database. We used multivariate linear models to evaluate associations between driver gene mutations and global gene expression. We developed generalized linear models to evaluate associations between genetic/expression factors with clinicopathologic features. Multivariate Cox proportional hazards models were used to predict the overall survival. Results: The potential relationship between genotype and genetics, clinical as well as pathologic features, on diffused glioma was observed. At least one driver mutation correlated with expression changes of about 10% of genes in GBMs while about 80% of genes in LGGs. The strongest association between mutations and expression changes was observed for DRG2 and LRCC41 gene in GBMs and LGGs, respectively. Additionally, the association between genomics features and clinicopathologic features suggested the different underlying molecular mechanisms in molecular subtypes or histology subtypes. For predicting survival, among genetics, transcriptome and clinical variables, transcriptome features made the largest contribution. By combining all the available data, the accuracy in predicting the prognosis of diffuse glioma in patients was also improved. Conclusion: Our study results revealed the influences of driver gene mutations on global gene expression in diffuse glioma patients. A more accurate model in predicting the prognosis of patients was achieved when combining with all the available data than just transcriptomic data.

The interplay of circulating tumor DNA and chromatin modification, therapeutic resistance, and metastasis.

Peripheral circulating free DNA (cfDNA) is DNA that is detected in plasma or serum fluid with a cell-free status. For cancer patients, cfDNA not only originates from apoptotic cells but also from necrotic tumor cells and disseminated tumor cells that have escaped into the blood during epithelial-mesenchymal transition. Additionally, cfDNA derived from tumors, also known as circulating tumor DNA (ctDNA), carries tumor-associated genetic and epigenetic changes in cancer patients, which makes ctDNA a potential biomarker for the early diagnosis of tumors, monitory and therapeutic evaluations, and prognostic assessments, among others, for various kinds of cancer. Moreover, analyses of cfDNA chromatin modifications can reflect the heterogeneity of tumors and have potential for predicting tumor drug resistance.