Frontiers in Molecular Biosciences最新文献

Background: Colorectal carcinoma (CRC) has emerged as one of the most widespread cancers and was the third leading cause of cancer-related mortality in 2020. The role of the podosomal protein Tks4 in tumor formation and progression is well established, including its involvement in gastric carcinoma and hepatocellular carcinoma; however, exploration of Tks4 and its associated EMT-regulating interactome in the context of colon cancer remains largely unexplored.

Methods: We conducted a comprehensive bioinformatic analysis to investigate the mRNA and protein expression levels of Tks4 and its associated partner molecules (CD2AP, GRB2, WASL, SRC, CTTN, and CAPZA1) across different tumor types. We quantified the expression levels of Tks4 and its partner molecules using qPCR, utilizing a TissueScan colon cancer array. We then validated the usefulness of Tks4 and its associated molecules as biomarkers via careful statistical analyses, including Pearson's correlation analysis, principal component analysis (PCA), multiple logistic regression, confusion matrix analysis, and ROC analysis.

Results: Our findings indicate that the co-expression patterns of the seven examined biomarker candidates better differentiate between tumor and normal samples compared with the expression levels of the individual genes. Moreover, variable importance analysis of these seven genes revealed four core genes that yield consistent results similar to the seven genes. Thus, these four core genes from the Tks4 interactome hold promise as potential combined biomarkers for colon adenocarcinoma diagnosis and prognosis.

Conclusion: Our proposed biomarker set from the Tks4 interactome shows promising sensitivity and specificity, aiding in colon cancer prevention and diagnosis.

Immune-related drug delivery systems (DDSs) in humanized mouse models are at the forefront of cancer research and serve as bridges between preclinical studies and clinical applications. These systems offer unique platforms for exploring new therapies and understanding their interactions with human cells and the immune system. Here, we focus on a DDS and a peripheral blood mononuclear cell (PBMC)-engrafted humanized mouse model that we recently developed, and consider some of the key components, challenges, and applications to advance these systems towards better cancer treatment on the basis of a better understanding of the immune response. Our DDS is unique and has a dual function, an anticancer effect and a capacity to fine-tune the immune reaction. The PBL-NOG-hIL-4-Tg mouse system is superior to other available humanized mouse systems for the development of such multifunctional DDSs because it supports the rapid reconstruction of an individual donor's immunity and avoids the onset of graft-versus-host disease.

Melanin is an amino acid derivative produced by melanocyte through a series of enzymatic reactions using tyrosinase as substrate. Human skin and hair color is also closely related to melanin, so understanding the mechanisms and proteins that produce melanin is very important. There are many proteins involved in the process of melanin expression, For example, proteins involved in melanin formation such as p53, HNF-1α (Hepatocyte nuclear factor 1α), SOX10 (Sry-related HMg-Box gene 10) and pax3 (paired box gene 3), MC1R(Melanocortin 1 Receptor), MITF (Microphthalmia-associated transcription factor), TYR (tyrosinase), TYRP1 (tyrosinase-related protein-1), TYRP2 (tyrosinase-related protein-2), and can be regulated by changing their content to control the production rate of melanin. Others, such as OA1 (ocular albinism type 1), Par-2 (protease-activated receptor 2) and Mlph (Melanophilin), have been found to control the transfer rate of melanosomes from melanocytes to keratinocytes, and regulate the amount of human epidermal melanin to control the depth of human skin color. In addition to the above proteins, there are other protein families also involved in the process of melanin expression, such as BLOC, Rab and Rho. This article reviews the origin of melanocytes, the related proteins affecting melanin and the basic causes of related gene mutations. In addition, we also summarized the active ingredients of 5 popular whitening cosmetics and their mechanisms of action.

Inositol 1,4,5-Trisphosphate Receptor-Interacting Protein-Like 1 (ITPRIPL1), a single-pass type I membrane protein located in the membrane, functions as an inhibitory ligand of CD3ε. Recent studies have shown that its expression suppresses T cells activation and promote tumor immune evasion. Despite increasing evidence suggesting that ITPRIPL1 plays a significant role in tumor growth, no systematic pan-cancer analysis of ITPRIPL1 has been conducted to date. This study utilized datasets curated from The Cancer Genome Atlas, Genotype Tissue-Expression, and Human Protein Atlas to investigate the relationship between ITPRIPL1 expression and clinical outcomes, immune infiltration, and drug sensitivity across 33 cancer types. We employed multiple methods to assess its prognostic value in pan-cancer, such as univariate Cox regression, survival analysis, and ROC curve analysis and explored the relationship between ITPRIPL1 and tumor mutation burden (TMB), tumor microsatellite instability (MSI), CNV, DNA methylation, immune-related genes, immune cell infiltration, and drug sensitivity to reveal its immunological role. The mRNA expression levels of the ITPRIPL1 gene vary significantly across multiple types of cancer and significantly reduced in breast cancer. Conversely, high ITPRIPL1 expression was associated with a better prognosis in BRCA. Furthermore, the expression of ITPRIPL1 highly correlates with the presence of tumor-infiltrating immune cells and immune checkpoint genes across various types of cancers. Additionally, ITPRIPL1 expression was associated with TMB in 6 cancer types and with MSI in 13 cancer types. High expression of ITPRIPL1 serves as a protective factor in certain cancer types, correlating with longer overall survival in BRCA. Our study further confirms that ITPRIPL1 participates in regulating immune infiltration and affecting the prognosis of patients in pan-cancer. These findings underscore the promising potential of ITPRIPL1 as a therapeutic target for human cancer.

In the realm of biomedical advancement, extracellular vesicles (EVs) are revolutionizing our capacity to diagnose, monitor, and predict disease progression. However, the comprehensive exploration and clinical application of EVs face significant limitations due to the current isolation techniques. The size exclusion chromatography, commercial precipitation reagents, and ultracentrifugation are frequently employed, necessitating skilled operators and entailing challenges related to consistency, reproducibility, quality, and yields. Notably, the formidable challenge of extracellular vesicle isolation persists when dealing with clinical samples of limited availability. This study addresses these challenges by aiming to devise a rapid, user-friendly, and high-recovery EVs isolation technique tailored for blood samples. The NTI-EXO precipitation method demonstrated a 5-fold increase in the recovery of serum EVs compared to current methodologies. Importantly, we illustrate that a mere two drops of blood (∼100 µL) suffice for the recovery of enriched EVs. The integrity and quality of these isolated EVs were rigorously assessed for the size, purity, and contaminants. This method was validated through the successful isolation of EVs from organ transplant recipients to detect disease-specific exosomal markers, including LKB1, SARS-CoV-2 spike protein, and PD-L1. In conclusion, NTI-EXO method can be used for small clinical samples, thereby advancing discoveries in the EV-centric domain and propelling the frontiers of biomedical research and clinical applications.

In terms of time, cost, and reproducibility of clinical laboratory tests, a mass spectrometric clinical blood metabogram (CBM) enables the investigation of the blood metabolome. Metabogram's components provide clinically relevant information by describing related groups of blood metabolites connected to humoral regulation, the metabolism of lipids, carbohydrates and amines, lipid intake into the organism, and liver function. For further development of the CBM approach, the ability of CBM to detect metabolic changes in the blood in the early stages of Parkinson's disease (PD) was studied in this work. In a case-control study (n = 56), CBM enabled the detection of the signature in blood metabolites related to 1-2.5 clinical stages of PD, according to the modified Hoehn and Yahr scale, which is formed by alterations in eicosanoids, phospholipids and, presumably, in the butadione metabolism. The CBM component-based diagnostic accuracy reached 77%, with a specificity of 71% and sensitivity of 82%. The research results extend the range of disorders for which CBM is applicable and offer new opportunities for revealing PD-specific metabolic alterations and diagnosing early-stage PD.

Background: Leprosy, a chronic infectious disease caused by Mycobacterium leprae, continues to pose a public health challenge in many parts of the world. Early and accurate diagnosis is crucial for effective treatment and prevention of disabilities associated with the disease. Molecular techniques such as PCR have demonstrated great potential as a diagnostic tool for directly detecting M. leprae DNA in different clinical samples, providing better sensitivity and specificity than conventional diagnostic techniques. The objective of this study was to measure the amount of M. leprae DNA in leprosy patients' urine samples using the Rlep gene target through qPCR.

Methods: Different clinical samples such as smear, blood, and urine samples were collected from leprosy patients and healthy individuals. Leprosy patients were classified by the Ridley-Jopling classification. The Ziehl-Neelsen staining method was used for the slit skin smear (SSS) samples, and the bacteriological index (BI) was calculated for leprosy patients. DNA extraction and qPCR were performed for all three types of clinical samples using the Rlep gene target.

Results: The Mycobacterial leprae DNA was successfully detected and quantified in all clinical samples across all types of leprosy among all the study groups using the Rlep gene (129 bp) target. The Rlep gene target was able to detect the presence of M. leprae DNA in 100% of urine, 96.1% of blood, and 92.2% of SSS samples of leprosy patients. Urine samples showed significant differences (p < 0.001) between the control and the different clinical forms and between borderline tuberculoid (BT) and pure neuritic leprosy (PNL) cases. There are significant differences in cycle threshold (Ct) values between control cases and clinical categories (p < 0.001), as well as specific differences within clinical categories (p < 0.001), reflecting the variability in bacterial load and detection sensitivity across different sample types and clinical manifestations of leprosy.

Conclusion: Overall, this study's findings suggest that the qPCR technique can be used to detect M. leprae DNA in urine samples of leprosy patients using the Rlep gene target. It can also be used for diagnosing the disease and monitoring the effectiveness of anti-leprosy drugs, including multi-drug therapy (MDT), across various leprosy disease groups.

Introduction: Individuals with diabetes mellitus (DM) are at an increased risk of Mycobacterium tuberculosis (Mtb) infection and progressing from latent tuberculosis (TB) infection to active tuberculosis disease. TB in the DM population is more likely to go undiagnosed due to smear-negative results.

Methods: Exhaled breath samples were collected and analyzed using high-pressure photon ionization time-of-flight mass spectrometry. An eXtreme Gradient Boosting (XGBoost) model was utilized for breathomics analysis and TB detection.

Results: XGBoost model achieved a sensitivity of 88.5%, specificity of 100%, accuracy of 90.2%, and an area under the curve (AUC) of 98.8%. The most significant feature across the entire set was m106, which demonstrated a sensitivity of 93%, specificity of 100%, and an AUC of 99.7%.

Discussion: The breathomics-based TB detection method utilizing m106 exhibited high sensitivity and specificity potentially beneficial for clinical TB screening and diagnosis in individuals with diabetes.