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Turkish Journal of Medical Sciences 2023Long noncoding RNAs (lncRNAs) are noncoding RNA molecules with a heterogeneous structure consisting of 200 or more nucleotides. Because these noncoding RNAs are... (Review)
Review
Long noncoding RNAs (lncRNAs) are noncoding RNA molecules with a heterogeneous structure consisting of 200 or more nucleotides. Because these noncoding RNAs are transcribed by RNA polymerase II, they have properties similar to messenger RNA (mRNA). Contrary to popular belief, the term "ncRNA" originated before the discovery of microRNAs. LncRNA genes are more numerous than protein-coding genes. They are the focus of current molecular research because of their pivotal roles in cancer-related processes such as cell proliferation, differentiation, and migration. The incidence of pancreatic cancer (PC) is increasing around the world and research on the molecular aspects of PC are growing. In this review, it is aimed to provide critical information about lncRNAs in PC, including the biological and oncological behaviors of lncRNAs in PC and their potential application in therapeutic strategies and as diagnostic tumor markers.
Topics: Humans; RNA, Long Noncoding; Pancreatic Neoplasms; Biomarkers, Tumor; Gene Expression Regulation, Neoplastic
PubMed: 38813489
DOI: 10.55730/1300-0144.5724 -
Cancer Research and Treatment Oct 2023The genetic attribution for pancreatic ductal adenocarcinoma (PDAC) has been reported as 5%-10%. However, the incidence of germline pathogenic variants (PVs) in Korean...
PURPOSE
The genetic attribution for pancreatic ductal adenocarcinoma (PDAC) has been reported as 5%-10%. However, the incidence of germline pathogenic variants (PVs) in Korean PDAC patients has not been thoroughly investigated. Therefore, we studied to identify the risk factors and prevalence of PV for future treatment strategies in PDAC.
MATERIALS AND METHODS
Total of 300 (155 male) patients with a median age of 65 years (range, 33 to 90 years) were enrolled in National Cancer Center in Korea. Cancer predisposition genes, clinicopathologic characteristics, and family history of cancer were analyzed.
RESULTS
PVs were detected in 20 patients (6.7%, median age 65) in ATM (n=7, 31.8%), BRCA1 (n=3, 13.6%), BRCA2 (n=3), and RAD51D (n=3). Each one patient showed TP53, PALB2, PMS2, RAD50, MSH3, and SPINK1 PV. Among them, two likely PVs were in ATM and RAD51D, respectively. Family history of various types of cancer including pancreatic cancer (n=4) were found in 12 patients. Three patients with ATM PVs and a patient with three germline PVs (BRCA2, MSH3, and RAD51D) had first-degree relatives with pancreatic cancer. Familial pancreatic cancer history and PVs detection had a significant association (4/20, 20% vs. 16/264, 5.7%; p=0.035).
CONCLUSION
Our study demonstrated that germline PVs in ATM, BRCA1, BRCA2, and RAD51D are most frequent in Korean PDAC patients and it is comparable to those of different ethnic groups. Although this study did not show guidelines for germline predisposition gene testing in patients with PDAC in Korea, it would be emphasized the need for germline testing for all PDAC patients.
Topics: Humans; Male; Adult; Middle Aged; Aged; Aged, 80 and over; Prevalence; Pancreatic Neoplasms; Carcinoma, Pancreatic Ductal; Risk Factors; Trypsin Inhibitor, Kazal Pancreatic
PubMed: 37024097
DOI: 10.4143/crt.2023.291 -
International Journal of Surgery... Feb 2024Undetectable occult liver metastases block the long-term survival of pancreatic ductal adenocarcinoma (PDAC). This study aimed to develop a radiomics-based model to...
BACKGROUND
Undetectable occult liver metastases block the long-term survival of pancreatic ductal adenocarcinoma (PDAC). This study aimed to develop a radiomics-based model to predict occult liver metastases and assess its prognostic capacity for survival.
MATERIALS AND METHODS
Patients who underwent surgical resection and were pathologically proven with PDAC were recruited retrospectively from five tertiary hospitals between January 2015 and December 2020. Radiomics features were extracted from tumors, and the radiomics-based model was developed in the training cohort using LASSO-logistic regression. The model's performance was assessed in the internal and external validation cohorts using the area under the receiver operating curve (AUC). Subsequently, the association of the model's risk stratification with progression-free survival (PFS) and overall survival (OS) was then statistically examined using Cox regression analysis and the log-rank test.
RESULTS
A total of 438 patients [mean (SD) age, 62.0 (10.0) years; 255 (58.2%) male] were divided into the training cohort ( n =235), internal validation cohort ( n =100), and external validation cohort ( n =103). The radiomics-based model yielded an AUC of 0.73 (95% CI: 0.66-0.80), 0.72 (95% CI: 0.62-0.80), and 0.71 (95% CI: 0.61-0.80) in the training, internal validation, and external validation cohorts, respectively, which were higher than the preoperative clinical model. The model's risk stratification was an independent predictor of PFS (all P <0.05) and OS (all P <0.05). Furthermore, patients in the high-risk group stratified by the model consistently had a significantly shorter PFS and OS at each TNM stage (all P <0.05).
CONCLUSION
The proposed radiomics-based model provided a promising tool to predict occult liver metastases and had a great significance in prognosis.
Topics: Humans; Male; Middle Aged; Female; Radiomics; Retrospective Studies; Pancreatic Neoplasms; Carcinoma, Pancreatic Ductal; Liver Neoplasms
PubMed: 38085810
DOI: 10.1097/JS9.0000000000000908 -
Asian Journal of Surgery Jan 2024Pancreaticoduodenectomy (PD) is one of the most difficult procedures in general surgery which involves the removal and reconstruction of many organs. PD is the standard... (Review)
Review
Pancreaticoduodenectomy (PD) is one of the most difficult procedures in general surgery which involves the removal and reconstruction of many organs. PD is the standard surgical method for malignant tumors of the head, uncinate process and even the neck of the pancreas. During PD surgery, it often involves the removal and reconstruction of blood vessels. This is a clinical review about vascular resection and reconstruction in PD surgery.
Topics: Humans; Pancreaticoduodenectomy; Pancreatic Neoplasms; Pancreas
PubMed: 37723030
DOI: 10.1016/j.asjsur.2023.09.039 -
International Journal of Molecular... Nov 2023Pancreatic ductal adenocarcinoma (PDAC), a highly malignant neoplasm, is classified as one of the most severe and devastating types of cancer. PDAC is a notable... (Review)
Review
Pancreatic ductal adenocarcinoma (PDAC), a highly malignant neoplasm, is classified as one of the most severe and devastating types of cancer. PDAC is a notable malignancy that exhibits a discouraging prognosis and a rising occurrence. The interplay between diabetes and pancreatic cancer exhibits a reciprocal causation. The identified metabolic disorder has been observed to possess noteworthy consequences on health outcomes, resulting in elevated rates of morbidity. The principal mechanisms involve the suppression of the immune system, the activation of pancreatic stellate cells (PSCs), and the onset of systemic metabolic disease caused by dysfunction of the islets. From this point forward, it is important to recognize that pancreatic-cancer-related diabetes (PCRD) has the ability to increase the likelihood of developing pancreatic cancer. This highlights the complex relationship that exists between these two physiological states. Therefore, we investigated into the complex domain of PSCs, elucidating their intricate signaling pathways and the profound influence of chemokines on their behavior and final outcome. In order to surmount the obstacle of drug resistance and eliminate PDAC, researchers have undertaken extensive efforts to explore and cultivate novel natural compounds of the next generation. Additional investigation is necessary in order to comprehensively comprehend the effect of PCRD-mediated apoptosis on the progression and onset of PDAC through the utilization of natural compounds. This study aims to examine the potential anticancer properties of natural compounds in individuals with diabetes who are undergoing chemotherapy, targeted therapy, or immunotherapy. It is anticipated that these compounds will exhibit increased potency and possess enhanced pharmacological benefits. According to our research findings, it is indicated that naturally derived chemical compounds hold potential in the development of PDAC therapies that are both safe and efficacious.
Topics: Humans; Diabetes Mellitus, Type 2; Biological Products; Pancreatic Neoplasms; Carcinoma, Pancreatic Ductal; Pancreatic Stellate Cells; Tumor Microenvironment
PubMed: 37958889
DOI: 10.3390/ijms242115906 -
Advanced Science (Weinheim,... Apr 2024One major obstacle in the drug treatment of pancreatic ductal adenocarcinoma (PDAC) is its highly fibrotic tumor microenvironment, which is replete with activated...
One major obstacle in the drug treatment of pancreatic ductal adenocarcinoma (PDAC) is its highly fibrotic tumor microenvironment, which is replete with activated pancreatic stellate cells (a-PSCs). These a-PSCs generate abundant extracellular matrix and secrete various cytokines to form biophysical and biochemical barriers, impeding drug access to tumor tissues. Therefore, it is imperative to develop a strategy for reversing PSC activation and thereby removing the barriers to facilitate PDAC drug treatment. Herein, by integrating chromatin immunoprecipitation (ChIP)-seq, Assays for Transposase-Accessible Chromatin (ATAC)-seq, and RNA-seq techniques, this work reveals that super-enhancers (SEs) promote the expression of various genes involved in PSC activation. Disruption of SE-associated transcription with JQ1 reverses the activated phenotype of a-PSCs and decreases stromal fibrosis in both orthotopic and patient-derived xenograft (PDX) models. More importantly, disruption of SEs by JQ1 treatments promotes vascularization, facilitates drug delivery, and alters the immune landscape in PDAC, thereby improving the efficacies of both chemotherapy (with gemcitabine) and immunotherapy (with IL-12). In summary, this study not only elucidates the contribution of SEs of a-PSCs in shaping the PDAC tumor microenvironment but also highlights that targeting SEs in a-PSCs may become a gate-opening strategy that benefits PDAC drug therapy by removing stromal barriers.
Topics: Pancreatic Stellate Cells; Pancreatic Neoplasms; Humans; Animals; Mice; Immunotherapy; Tumor Microenvironment; Carcinoma, Pancreatic Ductal; Disease Models, Animal; Gemcitabine; Deoxycytidine; Azepines; Cell Line, Tumor; Triazoles
PubMed: 38417121
DOI: 10.1002/advs.202308637 -
Scientific Reports Dec 2023Tumor formation is closely associated with disulfidptosis, a new form of cell death induced by disulfide stress-induced. The exact mechanism of action of disulfidptosis... (Randomized Controlled Trial)
Randomized Controlled Trial
Tumor formation is closely associated with disulfidptosis, a new form of cell death induced by disulfide stress-induced. The exact mechanism of action of disulfidptosis in pancreatic cancer (PCa) is not clear. This study analyzed the impact of disulfidptosis-related genes (DRGs) on the prognosis of PCa and identified clusters of DRGs, and based on this, a risk score (RS) signature was developed to assess the impact of RS on the prognosis, immune and chemotherapeutic response of PCa patients. Based on transcriptomic data and clinical information from PCa tissue and normal pancreatic tissue samples obtained from the TCGA and GTEx databases, differentially expressed and differentially surviving DRGs in PCa were identified from among 15 DRGs. Two DRGs clusters were identified by consensus clustering by merging the PCa samples in the GSE183795 dataset. Analysis of DRGs clusters about the PCa tumor microenvironment and differential analysis to obtain differential genes between the two DRG clusters. Patients were then randomized into the training and testing sets, and a prognostic prediction signature associated with disulfidptosis was constructed in the training set. Then all samples were divided into high-disulfidptosis-risk (HDR) and low-disulfidptosis-risk (LDR) subgroups based on the RS calculated from the signature. The predictive efficacy of the signature was assessed by survival analysis, nomograms, correlation analysis of clinicopathological characteristics, and the receiver operating characteristic (ROC) curves. To assess differences between different risk subgroups in immune cell infiltration, expression of immune checkpoint molecules, somatic gene mutations, and effectiveness of immunotherapy and chemotherapy. The GSE57495 dataset was used as external validation, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to detect the expression levels of DRGs. A total of 12 DRGs with differential expression and prognosis in PCa were identified, based on which a risk-prognosis signature containing five differentially expressed genes (DEGs) was developed. The signature was a good predictor and an independent risk factor. The nomogram and calibration curve shows the signature's excellent clinical applicability. Functional enrichment analysis showed that RS was associated with tumor and immune-related pathways. RS was strongly associated with the tumor microenvironment, and analysis of response to immunotherapy and chemotherapy suggests that the signature can be used to assess the sensitivity of treatments. External validation further demonstrated the model's efficacy in predicting the prognosis of PCa patients, with RT-qPCR and immunohistochemical maps visualizing the expression of each gene in PCa cell lines and the tissue. Our study is the first to apply the subtyping model of disulfidptosis to PCa and construct a signature based on the disulfidptosis subtype, which can provide an accurate assessment of prognosis, immunotherapy, and chemotherapy response in PCa patients, providing new targets and directions for the prognosis and treatment of PCa.
Topics: Humans; Prognosis; Pancreatic Neoplasms; Immunotherapy; Nomograms; Computational Biology; Tumor Microenvironment
PubMed: 38097783
DOI: 10.1038/s41598-023-49752-4 -
Cancer Treatment Reviews Apr 2024Pancreatic cancer is one of the tumors with the worst prognosis, and unlike other cancers, few advances have been made in recent years. The only curative option is... (Review)
Review
Pancreatic cancer is one of the tumors with the worst prognosis, and unlike other cancers, few advances have been made in recent years. The only curative option is surgery, but only 15-20% of patients are candidates, with a high risk of relapse. In advanced pancreatic cancer there are few first-line treatment options and no validated biomarkers for better treatment selection. The development of targeted therapies in pancreatic cancer is increasingly feasible due to tumor-agnostic treatments, such as PARP inhibitors in patients with BRCA1, BRCA2 or PALB2 alterations or immunotherapies in patients with high microsatellite instability/tumor mutational burden. In addition, other therapeutic molecules have been developed for patients with KRAS G12C mutation or fusions in NTRK or NRG1. Consequently, there has been a growing interest in biomarkers that may help guide targeted therapy in pancreatic cancer. Therefore, this review aims to offer an updated perspective on biomarkers with therapeutic potential in pancreatic cancer.
Topics: Humans; Biomarkers, Tumor; Mutation; Precision Medicine; Neoplasm Recurrence, Local; Pancreatic Neoplasms; Microsatellite Instability
PubMed: 38490088
DOI: 10.1016/j.ctrv.2024.102719 -
Proceedings of the National Academy of... Apr 2024Dysregulation of polyamine metabolism has been implicated in cancer initiation and progression; however, the mechanism of polyamine dysregulation in cancer is not fully...
Dysregulation of polyamine metabolism has been implicated in cancer initiation and progression; however, the mechanism of polyamine dysregulation in cancer is not fully understood. In this study, we investigated the role of MUC1, a mucin protein overexpressed in pancreatic cancer, in regulating polyamine metabolism. Utilizing pancreatic cancer patient data, we noted a positive correlation between MUC1 expression and the expression of key polyamine metabolism pathway genes. Functional studies revealed that knockdown of spermidine/spermine N1-acetyltransferase 1 (), a key enzyme involved in polyamine catabolism, attenuated the oncogenic functions of MUC1, including cell survival and proliferation. We further identified a regulatory axis whereby MUC1 stabilized hypoxia-inducible factor (HIF-1α), leading to increased SAT1 expression, which in turn induced carbon flux into the tricarboxylic acid cycle. MUC1-mediated stabilization of HIF-1α enhanced the promoter occupancy of the latter on promoter and corresponding transcriptional activation of , which could be abrogated by pharmacological inhibition of HIF-1α or CRISPR/Cas9-mediated knockout of . knockdown caused a significant reduction in the levels of SAT1-generated metabolites, N1-acetylspermidine and N8-acetylspermidine. Given the known role of MUC1 in therapy resistance, we also investigated whether inhibiting SAT1 would enhance the efficacy of FOLFIRINOX chemotherapy. By utilizing organoid and orthotopic pancreatic cancer mouse models, we observed that targeting SAT1 with pentamidine improved the efficacy of FOLFIRINOX, suggesting that the combination may represent a promising therapeutic strategy against pancreatic cancer. This study provides insights into the interplay between MUC1 and polyamine metabolism, offering potential avenues for the development of treatments against pancreatic cancer.
Topics: Mice; Animals; Humans; Antineoplastic Combined Chemotherapy Protocols; Pancreatic Neoplasms; Polyamines; Signal Transduction; Acetyltransferases; Mucin-1
PubMed: 38547055
DOI: 10.1073/pnas.2315509121 -
International Journal of Surgery... Dec 2023Diagnosing pancreatic lesions, including chronic pancreatitis, autoimmune pancreatitis, and pancreatic cancer, poses a challenge and, as a result, is time-consuming. To... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Diagnosing pancreatic lesions, including chronic pancreatitis, autoimmune pancreatitis, and pancreatic cancer, poses a challenge and, as a result, is time-consuming. To tackle this issue, artificial intelligence (AI) has been increasingly utilized over the years. AI can analyze large data sets with heightened accuracy, reduce interobserver variability, and can standardize the interpretation of radiologic and histopathologic lesions. Therefore, this study aims to review the use of AI in the detection and differentiation of pancreatic space-occupying lesions and to compare AI-assisted endoscopic ultrasound (EUS) with conventional EUS in terms of their detection capabilities.
METHODS
Literature searches were conducted through PubMed/Medline, SCOPUS, and Embase to identify studies eligible for inclusion. Original articles, including observational studies, randomized control trials, systematic reviews, meta-analyses, and case series specifically focused on AI-assisted EUS in adults, were included. Data were extracted and pooled, and a meta-analysis was conducted using Meta-xl. For results exhibiting significant heterogeneity, a random-effects model was employed; otherwise, a fixed-effects model was utilized.
RESULTS
A total of 21 studies were included in the review with four studies pooled for a meta-analysis. A pooled accuracy of 93.6% (CI 90.4-96.8%) was found using the random-effects model on four studies that showed significant heterogeneity ( P <0.05) in the Cochrane's Q test. Further, a pooled sensitivity of 93.9% (CI 92.4-95.3%) was found using a fixed-effects model on seven studies that showed no significant heterogeneity in the Cochrane's Q test. When it came to pooled specificity, a fixed-effects model was utilized in six studies that showed no significant heterogeneity in the Cochrane's Q test and determined as 93.1% (CI 90.7-95.4%). The pooled positive predictive value which was done using the random-effects model on six studies that showed significant heterogeneity was 91.6% (CI 87.3-95.8%). The pooled negative predictive value which was done using the random-effects model on six studies that showed significant heterogeneity was 93.6% (CI 90.4-96.8%).
CONCLUSION
AI-assisted EUS shows a high degree of accuracy in the detection and differentiation of pancreatic space-occupying lesions over conventional EUS. Its application may promote prompt and accurate diagnosis of pancreatic pathologies.
Topics: Adult; Humans; Artificial Intelligence; Sensitivity and Specificity; Pancreas; Endosonography; Pancreatic Neoplasms
PubMed: 37800594
DOI: 10.1097/JS9.0000000000000717