Pancreatic Cancer (PC) is a highly aggressive tumor that is mainly diagnosed at later stages. Various imaging technologies, such as CT, MRI, and EUS, possess limitations in early PC diagnosis. Therefore, this review article explores the various innovative biomarkers for PC detection, such as DNA methylation, Noncoding RNAs, and proteomic biomarkers, and the role of AI in PC detection at early stages.

Innovative biomarkers, such as DNA methylation genes, show higher specificity and sensitivity in PC diagnosis. Additionally, various non-coding RNAs, such as long non-coding RNAs (lncRNAs) and microRNAs, show high diagnostic accuracy and serve as diagnostic and prognostic biomarkers. Additionally, proteomic biomarkers retain higher diagnostic accuracy in different body fluids. Apart from this, the utilization of AI showed that AI surpassed the radiologist's diagnostic performance in PC detection.

The combination of AI and advanced biomarkers can revolutionize early PC detection. However, large-scale, prospective studies are needed to validate its clinical utility. Further. standardization of biomarker panels and AI algorithms is a vital step toward their reliable applications in early PC detection, ultimately improving patient outcomes. [Figure: see text].

Unusual symptoms, rapid progression, lack of reliable early diagnostic biomarkers, and lack of efficient treatment choices are the ongoing challenges of pancreatic cancer. Numerous research studies have demonstrated the correlation between exosomes and various aspects of pancreatic cancer. In light of these facts, exosomes possess the potential to play functional roles in the treatment, prognosis, and diagnosis of the pancreatic cancer. In the present study, we reviewed the most recent developments in approaches for exosome separation, modification, monitoring, and communication. Moreover, we discussed the clinical uses of exosomes as less invasive liquid biopsies and drug carriers and their contribution to the control of angiogenic activity of pancreatic cancer. Better investigation of exosome biology would help to effectively engineer therapeutic exosomes with certain nucleic acids, proteins, and even exogenous drugs as their cargo. Circulating exosomes have shown promise as reliable candidates for pancreatic cancer early diagnosis and monitoring in high-risk people without clinical cancer manifestation. Although we have tried to reflect the status of exosome applications in the treatment and detection of pancreatic cancer, it is evident that further studies and clinical trials are required before exosomes may be employed as a routine therapeutic and diagnostic tools for pancreatic cancer.

Pancreatic cancer (PC) remains a significant contributor to global cancer mortality, with limited effective diagnostic and prognostic tools. MicroRNAs (miRNAs) have emerged as promising biomarkers for PC diagnosis and prognosis. A comprehensive literature search was conducted in PubMed, Web of Science, and Scopus. Studies reporting sensitivity, specificity or area under the curve (AUC) for miRNAs in PC diagnosis, as well as hazard ratios (HRs) for survival evaluations, were included. Data extraction and quality assessment followed PRISMA guidelines. Meta-analyses were conducted using appropriate statistical methods. The protocol is registered in PROSPERO. Diagnostic analysis included 290 evaluations, revealing an overall AUC of 0.8226 for PC diagnosis. Subgroup analyses showed varying accuracies, with blood and tissue specimens yielding higher AUC values. Promising miRNAs with AUC values above 0.8 included miR-320, miR-1290, miR-93, miR-25, miR-451, miR-20, miR-21, miR-223 and miR-122. Prognostic analysis encompassed 46 studies, indicating significant associations between miRNA expression and overall survival (OS) and progression-free survival (PFS). The combined HR for studies reporting OS HRs higher than one was 1.7613 (95% CI: 1.5394-2.0152, p < 0.0001; I2 = 81.7%). Notable miRNAs with prognostic significance included miR-10, miR-21 and miR-221. Studies reporting OS HRs less than one had a pooled HR of 0.6805 (95% CI: 0.5862-0.7901, p < 0.0001; I2 = 65.4%). MiRNAs hold promise as diagnostic and prognostic biomarkers for PC. Blood and tissue specimens offer superior diagnostic accuracy, and several miRNAs show potential for predicting patient outcomes.

Pancreatic cancer (PC) is a serious malignant tumor with a high mortality rate, mainly due to late diagnosis and a lack of effective therapeutic interventions. The possibility of recognizing this cancer with reliable biomarkers using minimally invasive methods is of great importance for improving early detection, prognostic assessment, and targeted treatment methods. In recent years, small non-coding RNAs, especially microRNAs, have emerged as promising candidates for biomarkers of pancreatic cancer. Despite the methodological and analytical limitations of microRNA determination and a lack of available automated and standardized tests, a prospective systematic assessment of this new parameter's use in the detection of pancreatic cancer is warranted. This review provides general information on the diagnostic and prognostic utility of microRNAs, which appear to be well-established in many studies. In summary, microRNAs are promising non-invasive biomarkers of pancreatic cancer, offering potential opportunities for early detection, prognosis, and treatment monitoring. As research in this field progresses, microRNAs should become valuable tools in the fight against pancreatic cancer.

Pancreatic cancer remains a formidable malignancy characterized by high mortality rates, primarily attributable to late-stage diagnosis and a dearth of effective therapeutic interventions. The identification of reliable biomarkers holds paramount importance in enhancing early detection, prognostic evaluation, and targeted treatment modalities. Small non-coding RNAs, particularly microRNAs, have emerged as promising candidates for pancreatic cancer biomarkers in recent years. In this review, we delve into the evolving role of cellular and circulating miRNAs, including exosomal miRNAs, in the diagnosis, prognosis, and therapeutic targeting of pancreatic cancer. Drawing upon the latest research advancements in omics data-driven biomarker discovery, we also perform a case study using public datasets and address commonly identified research discrepancies, challenges, and limitations. Lastly, we discuss analytical approaches that integrate multimodal analyses incorporating clinical and molecular features, presenting new insights into identifying robust miRNA-centric biomarkers.

Antimicrobials are frequently used in both humans and animals for the treatment of bacterially-generated illnesses. Antibiotic usage has increased for more than 40% from last 15 years globally per day in both human populations and farm animals leading to the large-scale discharge of antibiotic residues into wastewater. Most antibiotics end up in sewer systems, either directly from industry or healthcare systems, or indirectly from humans and animals after being partially metabolized or broken down following consumption. To prevent additional antibiotic compound pollution, which eventually impacts on the spread of antibiotic resistance, it is crucial to remove antibiotic residues from wastewater. Antibiotic accumulation and antibiotic resistance genes cannot be effectively and efficiently eliminated by conventional sewage treatment plants. Because of their high energy requirements and operating costs, many of the available technologies are not feasible. However, the biosorption method, which uses low-cost biomass as the biosorbent, is an alternative technique to potentially address these problems. An extensive literature survey focusing on developments in the field was conducted using English language electronic databases, such as PubMed, Google Scholar, Pubag, Google books, and ResearchGate, to understand the relative value of the available antibiotic removal methods. The predominant techniques for eliminating antibiotic residues from wastewater were categorized and defined by example. The approaches were contrasted, and the benefits and drawbacks were highlighted. Additionally, we included a few antibiotics whose removal from aquatic environments has been the subject of extensive research. Lastly, a few representative publications were identified that provide specific information on the removal rates attained by each technique. This review provides evidence that biosorption of antibiotic residues from biological waste using natural biosorbent materials is an affordable and effective technique for eliminating antibiotic residues from wastewater.

Among malignant neoplasms, pancreatic ductal adenocarcinoma (PDAC) has one of the highest fatality rates due to its late detection. Therefore, it is essential to discover a noninvasive, early, specific, and sensitive diagnostic method. MicroRNAs (miRNAs) are attractive biomarkers because they are accessible, highly specific, and sensitive. It is crucial to find miRNAs that could be used as possible biomarkers because PDAC is the eighth most common cause of cancer death in Mexico. With the help of microRNA microarrays, differentially expressed miRNAs (DEmiRNAs) were found in PDAC tissues. The presence of these DEmiRNAs in the plasma of Mexican patients with PDAC was determined using RT-qPCR. Receiver operating characteristic curve analysis was performed to determine the diagnostic capacity of these DEmiRNAs. Gene Expression Omnibus datasets (GEO) were employed to verify our results. The Prisma V8 statistical analysis program was used. Four DEmiRNAs in plasma from PDAC patients and microarray tissues were found. Serum samples from patients with PDAC were used to validate their overexpression in GEO databases. We discovered a new panel of the two miRNAs miR-222-3p and miR-221-3p that could be used to diagnose PDAC, and when miR-221-3p and miR-222-3p were overexpressed, survival rates decreased. Therefore, miR-222-3p and miR-221-3p might be employed as noninvasive indicators for the diagnosis and survival of PDAC in Mexican patients.

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