Informatics strategies for early detection and risk mitigation in pancreatic cancer patients

Neoplasia, Journal Year: 2025, Volume and Issue: 60, P. 101129 - 101129

Published: Jan. 21, 2025

Language: Английский

---

Overcoming Obstacles: The Role of Lipid Nanocarriers in Therapeutic Approaches for Pancreatic Cancer

BioNanoScience, Journal Year: 2025, Volume and Issue: 15(2)

Published: March 11, 2025

Language: Английский

---

Lipid metabolism in pancreatic cancer: emerging roles and potential targets

Cancer Communications, Journal Year: 2022, Volume and Issue: 42(12), P. 1234 - 1256

Published: Sept. 15, 2022

Abstract Pancreatic cancer is one of the most serious health issues in developed and developing countries, with a 5‐year overall survival rate currently <9%. Patients typically present advanced disease due to vague symptoms or lack screening for early detection. Surgical resection represents only chance cure, but treatment options are limited diseases, such as distant metastatic locally progressive tumors. Although adjuvant chemotherapy has improved long‐term outcomes patients, its response low. So, exploring other new treatments urgent. In recent years, increasing evidence shown that lipid metabolism can support tumorigenesis progression well resistance through enhanced synthesis, storage, catabolism. Therefore, better understanding networks may provide novel promising strategies diagnosis, prognosis estimation, targeted therapy pancreatic patients. this review, we first enumerate discuss current knowledge about advances made regulation cancer. addition, summarize preclinical studies clinical trials drugs targeting metabolic systems Finally, highlight challenges opportunities pathways precision therapies

Language: Английский

---

Volatolomics in healthcare and its advanced detection technology

Nano Research, Journal Year: 2022, Volume and Issue: 15(9), P. 8185 - 8213

Published: June 29, 2022

Language: Английский

---

Proposing new early detection indicators for pancreatic cancer: Combining machine learning and neural networks for serum miRNA-based diagnostic model

Frontiers in Oncology, Journal Year: 2023, Volume and Issue: 13

Published: Aug. 3, 2023

Background Pancreatic cancer (PC) is a lethal malignancy that ranks seventh in terms of global cancer-related mortality. Despite advancements treatment, the five-year survival rate remains low, emphasizing urgent need for reliable early detection methods. MicroRNAs (miRNAs), group non-coding RNAs involved critical gene regulatory mechanisms, have garnered significant attention as potential diagnostic and prognostic biomarkers pancreatic (PC). Their suitability stems from their accessibility stability blood, making them particularly appealing clinical applications. Methods In this study, we analyzed serum miRNA expression profiles three independent PC datasets obtained Gene Expression Omnibus (GEO) database. To identify miRNAs associated with incidence, employed machine learning algorithms: Support Vector Machine-Recursive Feature Elimination (SVM-RFE), Least Absolute Shrinkage Selection Operator (LASSO), Random Forest. We developed an artificial neural network model to assess accuracy identified PC-related (PCRSMs) create nomogram. These findings were further validated through qPCR experiments. Additionally, patient samples classified using consensus clustering method. Results Our analysis revealed PCRSMs, namely hsa-miR-4648, hsa-miR-125b-1-3p, hsa-miR-3201, algorithms. The demonstrated high distinguishing between normal samples, verification training groups exhibiting AUC values 0.935 0.926, respectively. also utilized method classify into two optimal subtypes. Furthermore, our investigation PCRSMs unveiled negative correlation hsa-miR-125b-1-3p age. Conclusion study introduces novel diagnosis cancer, carrying implications. provide valuable insights pathogenesis offer avenues drug screening, personalized immunotherapy against disease.

Language: Английский

---

Artificial Intelligence-Driven Diagnosis of Pancreatic Cancer

Cancers, Journal Year: 2022, Volume and Issue: 14(21), P. 5382 - 5382

Published: Oct. 31, 2022

Pancreatic cancer is among the most challenging forms of to treat, owing its late diagnosis and aggressive nature that reduces survival rate drastically. has been primarily based on imaging, but current state-of-the-art imaging provides a poor prognosis, thus limiting clinicians’ treatment options. The advancement enhanced through integration artificial intelligence modalities make better clinical decisions. In this review, we examine how AI models can improve pancreatic using different along with discussion emerging trends in an AI-driven diagnosis, cytopathology serological markers. Ethical concerns regarding use these tools have also discussed.

Language: Английский

---

Four Ounces Can Move a Thousand Pounds: The Enormous Value of Nanomaterials in Tumor Immunotherapy

Advanced Healthcare Materials, Journal Year: 2023, Volume and Issue: 12(26)

Published: Aug. 4, 2023

Abstract The application of nanomaterials in healthcare has emerged as a promising strategy due to their unique structural diversity, surface properties, and compositional diversity. In particular, have found significant role improving drug delivery inhibiting the growth metastasis tumor cells. Moreover, recent studies highlighted potential modulating microenvironment (TME) enhancing activity immune cells improve therapy efficacy. Various types are currently utilized carriers, immunosuppressants, activators, immunoassay reagents, more for immunotherapy. Necessarily, used immunotherapy can be grouped into two categories: organic inorganic nanomaterials. Though both shown ability achieve purpose immunotherapy, composition properties result differences mechanisms modes action. Organic further divided polymers, cell membranes, nanoemulsion‐modified, hydrogel forms. At same time, broadly classified nonmetallic metallic current work aims explore action these different prospects promoting

Language: Английский

---

Circulating microRNAs as Potential Biomarkers in Pancreatic Cancer—Advances and Challenges

International Journal of Molecular Sciences, Journal Year: 2023, Volume and Issue: 24(17), P. 13340 - 13340

Published: Aug. 28, 2023

There is an urgent unmet need for robust and reliable biomarkers early diagnosis, prognosis, prediction of response to specific treatments many aggressive deadly cancers, such as pancreatic cancer, liquid biopsy-based miRNA profiling has the potential this. MiRNAs are a subset non-coding RNAs that regulate expression multitude genes post-transcriptionally thus diagnostic, prognostic, predictive have also emerged therapeutics. Because miRNAs involved in post-transcriptional regulation their target mRNAs via repressing gene expression, defects biogenesis pathway perturb oncogenic or tumor-suppressive pathogenesis various cancers. As such, numerous been identified be downregulated upregulated functioning either oncomes oncosuppressor miRs. Moreover, dysregulation pathways can change function cancer. Profiling dysregulated cancer shown correlate with disease indicate optimal treatment options predict therapy. Specific signatures track stages hold markers, well therapeutics mimics inhibitors (antagomirs). Furthermore, they along downstream used therapeutic targets. However, limited understanding validation roles miRNAs, lack tissue specificity, methodological, technical, analytical reproducibility, harmonization isolation quantification methods, use standard operating procedures, availability automated standardized assays improve reproducibility between independent studies limit bench-to-bedside translation clinical applications. Here I review recent findings on markers.

Language: Английский

---

Advances in Liquid Biopsy Technology and Implications for Pancreatic Cancer

International Journal of Molecular Sciences, Journal Year: 2023, Volume and Issue: 24(4), P. 4238 - 4238

Published: Feb. 20, 2023

Pancreatic cancer is a highly aggressive malignancy with climbing incidence. The majority of cases are detected late, incurable locally advanced or metastatic disease. Even in individuals who undergo resection, recurrence unfortunately very common. There no universally accepted screening modality for the general population and diagnosis, evaluation treatment response, detection relies primarily on use imaging. Identification minimally invasive techniques to help diagnose, prognosticate, predict response resistance therapy, detect desperately needed. Liquid biopsies represent an emerging group technologies which allow non-invasive serial sampling tumor material. Although not yet approved routine pancreatic cancer, increasing sensitivity specificity contemporary liquid biopsy platforms will likely change clinical practice near future. In this review, we discuss recent technological advances biopsy, focusing circulating DNA, exosomes, microRNAs, cells.

Language: Английский

---

Early Diagnosis and Prognosis Prediction of Pancreatic Cancer Using Engineered Hybrid Core‐Shells in Laser Desorption/Ionization Mass Spectrometry

Advanced Materials, Journal Year: 2024, Volume and Issue: 36(18)

Published: Jan. 19, 2024

Abstract Effective detection of bio‐molecules relies on the precise design and preparation materials, particularly in laser desorption/ionization mass spectrometry (LDI‐MS). Despite significant advancements substrate performance single‐structured substrates remains suboptimal for LDI‐MS analysis complex systems. Herein, designer Au@SiO 2 @ZrO core‐shell are developed LDI‐MS‐based early diagnosis prognosis pancreatic cancer (PC). Through controlling Au core size ZrO shell crystallization, signal amplification metabolites up to 3 orders is not only achieved, but also synergistic mechanism LDI process revealed. The optimized enables a direct record serum metabolic fingerprints (SMFs) by LDI‐MS. Subsequently, SMFs employed distinguish PC (stage I/II) from controls, with an accuracy 92%. Moreover, prognostic prediction scoring system established enhanced efficacy predicting survival compared CA19‐9 (p < 0.05). This work contributes material‐based prognosis.

Language: Английский

---