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Pancreatic cancer, notorious for its grim 10% five-year survival rate, poses significant clinical challenges, largely due to late-stage diagnosis and limited therapeutic options. This review delves into the generation of organoids, including those derived from resected tissues, biopsies, pluripotent stem cells, and adult stem cells, as well as the advancements in 3D printing. It explores the complexities of the tumor microenvironment, emphasizing culture media, the integration of non-neoplastic cells, and angiogenesis. Additionally, the review examines the multifaceted properties of graphene oxide (GO), such as its mechanical, thermal, electrical, chemical, and optical attributes, and their implications in cancer diagnostics and therapeutics. GO's unique properties facilitate its interaction with tumors, allowing targeted drug delivery and enhanced imaging for early detection and treatment. The integration of GO with 3D cultured organoid systems, particularly in pancreatic cancer research, is critically analyzed, highlighting current limitations and future potential. This innovative approach has the promise to transform personalized medicine, improve drug screening efficiency, and aid biomarker discovery in this aggressive disease. Through this review, we offer a balanced perspective on the advancements and future prospects in pancreatic cancer research, harnessing the potential of organoids and GO. [ABSTRACT FROM AUTHOR]

The advancement in molecular techniques has been attributed to the quality and significance of cancer research. Pancreatic cancer (PC) is one of the rare cancers with aggressive behavior and a high mortality rate. The asymptomatic nature of the disease until its advanced stage has resulted in late diagnosis as well as poor prognosis. The heterogeneous character of PC has complicated cancer development and progression studies. The analysis of bulk tissues of the disease was insufficient to understand the disease, hence, the introduction of the single-cell separating technique aided researchers to decipher more about the specific cell population of tumors. This review gives an overview of the Laser Capture Microdissection (LCM) technique, one of the single-cell separation methods used in PC research. [ABSTRACT FROM AUTHOR]

Silver has been in clinical use since ancient times and silver nanoparticles (AgNPs) have attracted attention in cancer therapy. We investigated the mechanisms by which AgNPs inhibit pancreatic ductal adenocarcinoma (PDAC). AgNPs were synthesized and 3 human PDAC and 2 nonmalignant primary cell lines were treated with AgNPs. MTT, MAPK, colony, spheroid and scratch assays, Western blotting, TEM, annexin V, 7-AAD, and H2DCFDA staining, FACS analysis, mRNA array and bioinformatics analyses, tumor xenograft transplantation, and immunohistochemistry of the treated cells were performed. We found that minimal AgNPs amounts selectively eradicated PDAC cells within a few hours. AgNPs inhibited cell migration and spheroid and colony formation, damaged mitochondria, and induced paraptosis-like cell death with the presence of cytoplasmic vacuoles, dilation of the ER and mitochondria, ROS formation, MAPK activity, and p62 and LC3b expression, whereas effects on the nucleus, DNA fragmentation, or caspases were not detectable. AgNPs strongly decreased tumor xenograft growth without side effects and reduced the expression of markers for proliferation and DNA repair, but upregulated paraptosis markers. The results highlight nanosilver as complementary agent to improve the therapeutic efficacy in pancreatic cancer.

Objective: The mechanism of Dangshen (Codonopsis pilosula) in treating pancreatic cancer (PC) was explored by network pharmacology technology and platform. Methods: The traditional Chinese medicine systems pharmacology database and analysis platform(TCMSP) was used to collect the effective compounds and potential targets of C.pilosula, and the genes associated with PC were obtained through the GeneCards database, the interaction genes between the effective compound targets of C.pilosula and PC targets were explored by the Venny method. The following mapping the interaction genes into a protein-protein interaction (PPI) network, and the key targets were screened. Finally, the interactive genes were imported into the DAVID database for gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal enrichment. Results: Twenty-one effective compounds and 98 downstream target genes of C.pilosula were screened through the TCMSP database. A total of 1,278 PC target genes were obtained through the GeneCards database, and the number of overlap genes between C.pilosula targets and PC related genes was 54, of which 10 were key node genes, namely CASP3, TP53, MDM2, AKT1, ESR1, BCL2L1, MCL1, HSP90AA1, CASP9, and CCND. These interactive genes involved a total of 30 typical GO terms and 20 KEGG signals. Conclusion: C. pilosula may play a role in treating PC through multicomponent, multi-target, and multi-signal pathways. [ABSTRACT FROM AUTHOR]

Disparities in pancreatic cancer incidence and outcomes exist in Native American populations. These disparities are multifactorial, difficult to quantify, and are influenced by historical, socioeconomic, and health care structural factors. The objective of this article was to assess these factors and offer a call to action to overcome them. The authors reviewed published data on pancreatic cancer in Native American populations with a focus on disparities in incidence, outcomes, and research efforts. The historical context of the interactions between Native Americans and the United States health care system was also analyzed to form actionable items to build trust and collaboration. The incidence of pancreatic cancer in Native Americans is higher than that in the general US population and has the worst survival of any major racial or ethnic group. These outcomes are influenced by a patient population with often poor access to high‐quality cancer care, historical trauma potentially leading to reduced care utilization, and a lack of research focused on etiologies and comorbid conditions that contribute to these disparities. A collaborative effort between nontribal and tribal leaders and cancer centers is key to addressing disparities in pancreatic cancer outcomes and research. More population‐level studies are needed to better understand the incidence, etiologies, and comorbid conditions of pancreatic cancer in Native Americans. Finally, a concerted, focused effort should be undertaken between nontribal and tribal entities to increase the access of Native Americans to high‐quality care for pancreatic cancer and other lethal malignancies. More population‐level studies are needed to better understand the incidence, etiologies, and comorbid conditions of pancreatic cancer in Native Americans. A concerted, focused effort should be undertaken between nontribal and tribal entities to increase the access of Native Americans to high‐quality care for pancreatic cancer and other lethal malignancies. [ABSTRACT FROM AUTHOR]

Machine learning and semantic analysis are computer-based methods to evaluate complex relationships and predict future perspectives. We used these technologies to define recent, current and future topics in pancreatic cancer research. Publications indexed under the Medical Subject Headings (MeSH) term 'Pancreatic Neoplasms' from January 1996 to October 2021 were downloaded from PubMed. Using the statistical computing language R and the interpreted, high-level, general-purpose programming language Python, we extracted publication dates, geographic information, and abstracts from each publication's metadata for bibliometric analyses. The generative statistical algorithm "latent Dirichlet allocation" (LDA) was applied to identify specific research topics and trends. The unsupervised "Louvain algorithm" was used to establish a network to identify relationships between single topics. A total of 60,296 publications were identified and analyzed. The publications were derived from 133 countries, mostly from the Northern Hemisphere. For the term "pancreatic cancer research", 12,058 MeSH terms appeared 1,395,060 times. Among them, we identified the four main topics "Clinical Manifestation and Diagnosis", "Review and Management", "Treatment Studies", and "Basic Research". The number of publications has increased rapidly during the past 25 years. Based on the number of publications, the algorithm predicted that "Immunotherapy", Prognostic research", "Protein expression", "Case reports", "Gemcitabine and mechanism", "Clinical study of gemcitabine", "Operation and postoperation", "Chemotherapy and resection", and "Review and management" as current research topics. To our knowledge, this is the first study on this subject of pancreatic cancer research, which has become possible due to the improvement of algorithms and hardware. [ABSTRACT FROM AUTHOR]

Recent progress in the field of organoid-based cell culture systems has enabled the use of patient-derived cells in conditions that resemble those in cancer tissue, which are better than two-dimensional (2D) cultured cell lines. In particular, organoids allow human cancer cells to be handled in conditions that resemble those in cancer tissue, resulting in more efficient establishment of cells compared with 2D cultured cell lines, thus enabling the use of multiple patient-derived cells with cells from different genetic background, in keeping with the heterogeneity of the cells. One of the most valuable points of using organoids is that human cells from either healthy or cancerous tissue can be used. Using genome editing technology such as clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein, organoid genomes can be modified to, for example, cancer-prone genomes. The normal, cancer, or genome-modified organoids can be used to evaluate whether chemicals have genotoxic or non-genotoxic carcinogenic activity by evaluating the cancer incidence, cancer progression, and cancer metastasis. In this review, the organoid technology and the accompanying technologies were summarized and the advantages of organoid-based toxicology and its application to pancreatic cancer study were discussed. [ABSTRACT FROM AUTHOR]

Pancreatic cancer (PC) is one of the most common malignant tumors in the digestive tract worldwide, with increased morbidity and mortality. In recent years, with the development of surgery, chemotherapy, radiotherapy, targeted therapy, and immunotherapy, and the change of the medical thinking model, remarkable progress has been made in researching comprehensive diagnosis and treatment of PC. However, the present situation of diagnostic and treatment of PC is still unsatisfactory. There is an urgent need for academia to fully integrate the basic research and clinical data from PC to form a research model conducive to clinical translation and promote the proper treatment of PC. This paper summarized the translation progress of mass spectrometry (MS) in the pathogenesis, diagnosis, prognosis, and PC treatment to promote the basic research results of PC into clinical diagnosis and treatment. [ABSTRACT FROM AUTHOR]

The Cre/loxP system is a powerful tool for the generation of animal models with precise spatial and temporal gene expression. It has proven indispensable in the generation of cancer models with tissue specific expression of oncogenes or the inactivation of tumor suppressor genes. Consequently, Cre-transgenic mice have become an essential prerequisite in basic cancer research. While it is unlikely that pigs will ever replace mice in basic research they are already providing powerful complementary resources for translational studies. But, although conditionally targeted onco-pigs have been generated, no Cre-driver lines exist for any of the major human cancers. To model human pancreatic cancer in pigs, Cre-driver lines were generated by CRISPR/Cas9-mediated insertion of codon-improved Cre (iCre) into the porcine PTF1A gene, thus guaranteeing tissue and cell type specific function which was proven using dual fluorescent reporter pigs. The method used can easily be adapted for the generation of other porcine Cre-driver lines, providing a missing tool for modeling human cancers in large animals. [ABSTRACT FROM AUTHOR]

Few data exist on health‐related quality of life (QoL) in patients with metastatic pancreatic cancer (mPC) receiving first‐line chemotherapy (Awad L ZE, Mesbah M Boston, MA. Applying survival data methodology to analyze quality of life data, in Mesbah M, Cole BF, Ting Lee M‐L (eds): Statistical Methods for Quality of Life Studies: Design, Measurements and Analysis. Kluwer Academic Publishers 2002). The QOLIXANE study is a prospective, noninterventional, multicenter substudy of the Platform for Outcome, Quality of Life and Translational Research on Pancreatic Cancer (PARAGON) registry, which evaluated QoL in patients with mPC receiving first‐line gemcitabine and nab‐paclitaxel chemotherapy in real‐life setting. QoL was prospectively measured via EORTC QLQ‐C30 questionnaires at baseline and every month thereafter. Therapy and efficacy parameters were prospectively collected. Main objectives were the rate of patients without deterioration of Global Health Status/QoL (GHS/QoL) at 3 and 6 months. Six hundred patients were enrolled in 95 German study sites. Median progression‐free survival was 5.9 months (95% confidence interval [CI], 5.2‐6.3). Median overall survival (OS) was 8.9 months (95% CI, 7.9‐10.2), while median time to deterioration of GHS/QoL was 4.7 months (95% CI, 4.0‐5.6). With a baseline GHS/QoL score of 46 (SD, 22.8), baseline QoL of the patients was severely impaired, in most cases due to loss in role functioning and fatigue. In the Kaplan‐Meier analysis, 61% and 41% of patients had maintained GHS/QoL after 3 and 6 months, respectively. However, in the QoL response analysis, 35% and 19% of patients had maintained (improved or stable) GHS/QoL after 3 and 6 months, respectively, while 14% and 9% had deteriorated GHS/QoL with the remaining patients being nonevaluable. In the Cox regression analysis, GHS/QoL scores strongly predicted survival with a hazard ratio of 0.86 (P <.0001). Patients with mPC have poor QoL at baseline that deteriorates within a median of 4.7 months. Treatment with gemcitabine and nab‐paclitaxel is associated with maintained QoL in relevant proportions of patients. However, overall, results remain poor, reflecting the aggressive nature of the disease. What's new?: In metastatic pancreatic cancer (mPC), chemotherapy with nab‐paclitaxel plus gemcitabine has shown significant survival benefits. However, less attention has been paid to quality of life (QoL) for these patients. In this prospective study, the authors found that, due to the aggressive nature of mPC, QoL declined rapidly for most patients. But surprisingly, as many as 41% of patients were able to maintain their baseline QoL at six months. Thus, while overall results remain poor, it does appear possible to stabilize QoL for a subset of patients receiving this first‐line combination chemotherapy. [ABSTRACT FROM AUTHOR]

BACKGROUND. Recent genomic and bioinformatic technological advances have made it possible to dissect the immune response to personalized neoantigens encoded by tumor-specific mutations. However, timely and efficient identification of neoantigens is still a major obstacle to personalized neoantigen-based cancer immunotherapy. METHODS. Two different pipelines of neoantigen identification were established in this study: (a) Clinical-grade targeted sequencing was performed in patients with refractory solid tumor, and mutant peptides with high variant allele frequency and predicted high HLA-binding affinity were synthesized de novo. (b) An inventory-shared neoantigen peptide library of common solid tumors was constructed, and patients' hotspot mutations were matched to the neoantigen peptide library. The candidate neoepitopes were identified by recalling memory T cell responses in vitro. Subsequently, neoantigen-loaded dendritic cell vaccines and neoantigen-reactive T cells were generated for personalized immunotherapy in 6 patients. RESULTS. Immunogenic neoepitopes were recognized by autologous T cells in 3 of 4 patients who used the de novo synthesis mode and in 6 of 13 patients who used the shared neoantigen peptide library. A metastatic thymoma patient achieved a complete and durable response beyond 29 months after treatment. Immune-related partial response was observed in another patient with metastatic pancreatic cancer. The remaining 4 patients achieved prolonged stabilization of disease with a median progression-free survival of 8.6 months. CONCLUSION. The current study provides feasible pipelines for neoantigen identification. Implementing these strategies to individually tailor neoantigens could facilitate neoantigen-based translational immunotherapy research. TRIAL REGISTRATION. ChiCTR.org ChiCTR-OIC-16010092, ChiCTR-OIC-17011275, ChiCTR-OIC-17011913; ClinicalTrials.gov NCT03171220. FUNDING. This work was funded by grants from the National Key Research and Development Program of China (2017YFC1308900), the National Major Projects for 'Major New Drugs Innovation and Development' (2018ZX09301048-003), the National Natural Science Foundation of China (81672367, 81572329, 81572601), and the Key Research and Development Program of Jiangsu Province (BE2017607)., Introduction T cell-based immunotherapy has been successfully used to treat many human solid cancers (1). Administering autologous tumorinfiltrating T lymphocytes (TILs) can lead to complete, durable tumor regressions in patients [...]