Personalized and Precision Medicine Journal

Abstract Lung cancer is one of the leading causes of death globally, affecting both men and women with a high mortality rate. The majority of cases are diagnosed at an advanced stage, contributing to its poor prognosis. Early detection is crucial but challenging due to the asymptomatic nature of early-stage disease. Identifying reliable tumor markers is vital for improving diagnosis. Next-generation sequencing (NGS) has revolutionized oncology by offering detailed insights into the genetic makeup of lung cancer. NGS allows for comprehensive genomic profiling, even from small samples, identifying mutations, gene fusions, and copy number variations. This review explores the role of NGS panels in lung cancer's early detection, particularly within personalized medicine. NGS enables clinicians to detect actionable biomarkers, tailor treatments based on individual genomic profiles, and improve outcomes. Its ability to analyze multiple genes simultaneously makes it efficient in identifying therapeutic targets and resistance mechanisms. Additionally, NGS processes large datasets quickly, promoting its adoption in clinical practice. By identifying genetic mutations driving tumor development, NGS supports more precise treatment approaches, improving clinical management and reducing mortality. Its cost-effectiveness, particularly in reducing the need for multiple tests, strengthens its position in oncology. As personalized medicine advances, NGS is expected to play a key role in lung cancer's diagnosis, prognosis, and treatment, with ongoing technological improvements enhancing its clinical utility.

Abstract Exosomes are becoming recognized as crucial facilitators of interaction between cells. They deliver biological agents to target cells, play essential roles throughout multiple biological and pathological events, and have significant potential as innovative alternative therapies for illnesses. Exosomal communication between cells appears to have a role in the development of several illnesses, involving cancer, neurodegenerative conditions, and inflammatory disorders. Exosomes are diminutive (20–150 nm) entities characterized by a unique bilipid protein architecture. They transport and switch diverse cargos across cells and serve as noninvasive indicators for multiple disorders. Exosomes are regarded as the most effective indicators for cancer detection due to their distinctive properties. This document will examine the current uses of exosomes, their origins, and diverse isolation techniques. Furthermore, the function of exosomes and their use in biomedical studies and preclinical experiments are succinctly addressed.

Abstract Prostate cancer (PCa) is the most common solid tumor in men. While patients with local PCa have better prognostic survival, patients with metastatic PCa have relatively high mortality rates. Exosomes (and other extracellular vesicles) are now part of the cancer research landscape, involved both as players in pathophysiological mechanisms, as biomarkers of the cancer process, and as therapeutic tools. Exosomes contain miRNAs, mRNAs, and proteins with the potential to regulate signaling pathways in recipient cells. Accumulating evidence indicates that exosomes play important roles in cell communication and tumor progression and are suitable for monitoring PCa progression and metastasis.

Abstract Colorectal cancer (CRC) is the third most common type of cancer worldwide. It develops through a gradual accumulation of genetic and epigenetic changes, leading to the transformation of normal colonic mucosa into invasive cancer. Approximately 90% of colorectal cancer cases are sporadic without family history or genetic predisposition, while in less than 10% a causative genetic event has been identified. Since personalized medicine works on three subjects of determining disease indices in people, choosing the best therapeutic method and predicting disease relapse, it seems that regarding colorectal cancer, more researches are required in order to achieve favorable results. The recent advances in molecular biology and the genetic classification of CRC are essential to individualize these therapies and will be basic for improving the treatment in the next years. We are optimistic about the success of personalized medicine for this disease.

Abstract The increasing literature exploring the role of circulating miR-210 has clarified its potential as a promising biomarker for early detection, diagnosis and prognosis. Measuring circulating miR-210 levels could be a non-invasive method for early cancer detection. Even if, to date, most studies appear to be preliminary it seems that miR-210 will be a good target for drug development. In this study, we had detected the difference of serum miR-210 expression between health and breast cancer patients. total of 15 breast cancer patients were selected for the breast cancer (BC) group and 15 healthy people. The results showed The expression level of miR-210 in the serum of breast cancer patients was significantly higher compared with that in healthy individuals. Patients with breast cancer present increased levels of circulating miR-210; thus, circulating miR-210 may be a potential biomarker of tumor presence and therapeutic response in breast cancer

Abstract Diabetes mellitus (DM) is a major public health issue in worldwide. Type 2 diabetes does not have a clear pattern of inheritance, although many affected individuals have at least one close family member, such as a parent or sibling, with the disease. The KCNJ11 gene is a member of the potassium channel gene family. polymorphisms  in KCNJ11  result  in  neonatal  diabetes and congenital hyper-insulinaemia, wherein the E23K (rs5219) polymorphism is linked with diabetes susceptibility where the K allele plays an important role in insulin secretion. In this study, we evaluate the frequency of these polymorphisms in a Kurdish population of 85 with type 2 diabetes. E23K polymorphism of KCNJ11 gene was genotyped by PCR-RFLP method. heterozygous carriers for AG are more in non‑diabetic patients (P = 0.034).