Serum and Urine Metabolic Fingerprints Characterize Renal Cell Carcinoma for Classification, Early Diagnosis, and Prognosis
Contact us if these videos are not relevant.
Contact us if these videos are not relevant.
View abstract on PubMed
Summary
This summary is machine-generated.This study introduces nanoparticle-enhanced laser desorption ionization mass spectrometry (NELDI MS) for analyzing renal cell carcinoma (RCC) metabolic fingerprints. This method shows high accuracy in distinguishing tumors, classifying subtypes, and predicting disease progression.
Area Of Science
- Biomedical Science
- Analytical Chemistry
- Oncology
Background
- Renal cell carcinoma (RCC) presents a growing health challenge with heterogeneous manifestations, limiting current clinical management.
- Metabolic analyses offer a promising noninvasive approach for RCC characterization and diagnosis.
Purpose Of The Study
- To develop and validate a nanoparticle-enhanced laser desorption ionization mass spectrometry (NELDI MS) method for metabolic fingerprinting of RCC.
- To assess the diagnostic and prognostic capabilities of NELDI MS in classifying RCC tumors and predicting disease outcomes.
Main Methods
- Analysis of metabolic fingerprints from 456 renal tumors and 200 healthy controls using NELDI MS.
- Development of classification models to distinguish tumors from controls, malignant from benign tumors, and RCC subtypes.
- Construction of a predictive model for RCC prognosis.
Main Results
- Classification models achieved high AUC values: 0.938 for tumor vs. control, 0.850 for malignant vs. benign, and 0.925-0.932 for RCC subtypes.
- Early-stage RCC subtypes showed averaged diagnostic sensitivity of 90.5% and specificity of 91.3%.
- Metabolic biomarkers were identified as significant indicators for subtype diagnosis (p < 0.05), and a prognostic model predicted disease (p = 0.003).
Conclusions
- NELDI MS provides a powerful, noninvasive tool for accurate RCC characterization, including subtype classification and early detection.
- Identified metabolic biomarkers hold potential for guiding RCC diagnosis and prognosis.
- This approach offers a promising future for metabolic analytical tools in clinical RCC management.
Contact us if these videos are not relevant.
Contact us if these videos are not relevant.
Related Concept Videos
Renal dysfunction significantly impairs the renal clearance of drugs, leading to potential complications in drug therapy. Renal failure, which can be caused by various factors, poses a significant challenge in the elimination of drugs from the body.
One condition associated with renal failure is uremia. Uremia is characterized by impaired glomerular filtration and fluid accumulation in the body. This condition hinders the renal clearance of drugs, resulting in drug accumulation and potential...
The glomerulus and Bowman's capsule are two essential components of the nephron, which is the functional unit of the kidney. These microscopic structures play a critical role in the process of blood filtration to produce urine.
Glomerulus: Structure and Function
The glomerulus is a tiny, intricate network of capillaries located at the beginning of the nephron. It's enveloped by the Bowman's capsule and receives its blood supply from an afferent arteriole, which divides into numerous...
The glomerular filtration rate (GFR) is a critical marker of kidney function, reflecting the efficiency of filtration by the glomeruli. Renal clearance of specific substances, such as inulin or creatinine, is commonly used to measure GFR.
Renal clearance refers to the volume of plasma cleared of a specific substance, such as creatinine, per unit of time. To measure clearance, urine samples are collected over a 24-hour period during each bladder voiding, followed by a single blood sample at the...