Measuring carbonic anhydrase IX as a hypoxia biomarker: differences in concentrations in serum and plasma using a commercial enzyme-linked immunosorbent assay due to influences of metal ions

Background There is increasing interest in measuring the soluble forms of carbonic anhydrase IX (CA IX) in blood as a marker of hypoxia for prognostic purposes or for predictive use in therapeutic trials in various cancers. Following our initial observations of marked differences in the measured concentrations of CA IX in EDTA plasma versus serum, we sought to investigate these further in order to determine their effects on results in published studies and to ensure accurate measurement in future studies. Methods Serum and EDTA plasma samples from healthy controls and patients with renal cancer were used in the validation of two commercially available enzyme-linked immunosorbent assays (ELISAs) for CA IX with examination of recovery, parallelism and specificity and comparison of paired plasma and serum. Results Successful validation of one of the ELISAs was not achieved with particular problems with parallelism and marked differences in measured CA IX concentrations between EDTA plasma and serum. This appeared to be due to a metal ion-dependent epitope on CA IX recognized by the detection antibody in this assay. The other commercially available ELISA examined was successfully validated and showed no difference in CA IX between EDTA plasma and serum. Conclusions These results have important consequences for published studies using this assay where the conclusions drawn from the measurements made may be invalid. This study highlights the need for stringent validation of commercially available assays, including examination of various sample types, before use in research studies. </jats:sec

C-STrap Sample Preparation Method—In-Situ Cysteinyl Peptide Capture for Bottom-Up Proteomics Analysis in the STrap Format

Recently we introduced the concept of Suspension Trapping (STrap) for bottom-up proteomics sample processing that is based upon SDS-mediated protein extraction, swift detergent removal and rapid reactor-type protein digestion in a quartz depth filter trap. As the depth filter surface is made of silica, it is readily modifiable with various functional groups using the silane coupling chemistries. Thus, during the digest, peptides possessing specific features could be targeted for enrichment by the functionalized depth filter material while non-targeted peptides could be collected as an unbound distinct fraction after the digest. In the example presented here the quartz depth filter surface is functionalized with the pyridyldithiol group therefore enabling reversible in-situ capture of the cysteine-containing peptides generated during the STrap-based digest. The described C-STrap method retains all advantages of the original STrap methodology and provides robust foundation for the conception of the targeted in-situ peptide fractionation in the STrap format for bottom-up proteomics. The presented data support the method’s use in qualitative and semi-quantitative proteomics experiments

Systematic Analysis of Circulating Soluble Angiogenesis-Associated Proteins in ICON7 Identifies Tie2 as a Biomarker of Vascular Progression on Bevacizumab

background: There is a critical need for predictive/resistance biomarkers for VEGF inhibitors to optimise their use. methods: Blood samples were collected during and following treatment and, where appropriate, upon progression from ovarian cancer patients in ICON7, a randomised phase III trial of carboplatin and paclitaxel with or without bevacizumab. Plasma concentrations of 15 circulating angio-biomarkers were measured using a validated multiplex ELISA, analysed through a novel network analysis and their relevance to the PFS then determined. results: Samples (n=650) were analysed from 92 patients. Bevacizumab induced correlative relationships between Ang1 and Tie2 plasma concentrations, which reduced after initiation of treatment and remained decreased until progressive disease occurred. A 50% increase from the nadir in the concentration of circulating Tie2 (or the product of circulating Ang1 and Tie2) predicted tumour progression. Combining Tie2 with GCIG-defined Ca125 data yielded a significant improvement in the prediction of progressive disease in patients receiving bevacizumab in comparison with Ca125 alone (74.1% vs 47.3%, P<1 × 10−9). conclusions: Tie2 is a vascular progression marker for bevacizumab-treated ovarian cancer patients. Tie2 in combination with Ca125 provides superior information to clinicians on progressive disease in patients with VEGFi-treated ovarian cancers

Personalised Care in CKD: Moving Beyond Traditional Biomarkers

Background: Traditional biomarkers, such as estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio (uACR), have long been central to chronic kidney disease (CKD) diagnosis and management, leading to a standardized CKD classification system. However, these biomarkers are non-specific and fail to capture the heterogeneity within CKD and the nuances of an individual’s disease mechanism, limiting personalized treatment approaches. There is an increasing need for novel biomarkers that reflect the diverse pathophysiological processes underlying CKD progression, enabling more precise risk prediction and treatment strategies. Summary: This review examines the limitations of current CKD biomarkers and classification systems, highlighting the need for a precision medicine approach. While traditional markers like eGFR and uACR are foundational, they inadequately capture CKD’s complexity. Emerging biomarkers offer insights into specific disease processes, such as inflammation, oxidative stress, fibrosis, and tubular injury, which are crucial for personalized care. The article discusses the potential benefits of integrating these novel biomarkers into clinical practice, including more accurate risk prediction, tailored treatments, and personalized clinical trial designs, as well as the barriers to their implementation. Furthermore, advancements in multi-omics and high-throughput techniques offer opportunities to identify novel causative proteins with druggable targets, pushing CKD care towards greater precision. Key Messages: Current CKD classification systems, based on non-specific biomarkers, fail to capture CKD’s heterogeneity. Incorporating biomarkers reflecting diverse pathophysiological mechanisms can enhance risk prediction, customized treatments, and personalized clinical trials. High-throughput multi-omic techniques present a promising path towards precision medicine in nephrology.<br/

Aristolochic acid exposure in Romania and implications for renal cell carcinoma

Background: Aristolochic acid (AA) is a nephrotoxicant associated with AA nephropathy (AAN) and upper urothelial tract cancer (UUTC). Whole-genome sequences of 14 Romanian cases of renal cell carcinoma (RCC) recently exhibited mutational signatures consistent with AA exposure, although RCC had not been previously linked with AAN and AA exposure was previously reported only in localised rural areas. Methods: We performed mass spectrometric measurements of the aristolactam (AL) DNA adduct 7-(deoxyadenosin-N6-yl) aristolactam I (dA-AL-I) in nontumour renal tissues of the 14 Romanian RCC cases and 15 cases from 3 other countries. Results: We detected dA-AL-I in the 14 Romanian cases at levels ranging from 0.7 to 27 adducts per 108 DNA bases, in line with levels reported in Asian and Balkan populations exposed through herbal remedies or food contamination. The 15 cases from other countries were negative. Interpretation: Although the source of exposure is uncertain and likely different in AAN regions than elsewhere, our results demonstrate that AA exposure in Romania exists outside localised AAN regions and provide further evidence implicating AA in RCC

Integrated multi-level quality control for proteomic profiling studies using mass spectrometry

BACKGROUND: Proteomic profiling using mass spectrometry (MS) is one of the most promising methods for the analysis of complex biological samples such as urine, serum and tissue for biomarker discovery. Such experiments are often conducted using MALDI-TOF (matrix-assisted laser desorption/ionisation time-of-flight) and SELDI-TOF (surface-enhanced laser desorption/ionisation time-of-flight) MS. Using such profiling methods it is possible to identify changes in protein expression that differentiate disease states and individual proteins or patterns that may be useful as potential biomarkers. However, the incorporation of quality control (QC) processes that allow the identification of low quality spectra reliably and hence allow the removal of such data before further analysis is often overlooked. In this paper we describe rigorous methods for the assessment of quality of spectral data. These procedures are presented in a user-friendly, web-based program. The data obtained post-QC is then examined using variance components analysis to quantify the amount of variance due to some of the factors in the experimental design. RESULTS: Using data from a SELDI profiling study of serum from patients with different levels of renal function, we show how the algorithms described in this paper may be used to detect systematic variability within and between sample replicates, pooled samples and SELDI chips and spots. Manual inspection of those spectral data that were identified as being of poor quality confirmed the efficacy of the algorithms. Variance components analysis demonstrated the relatively small amount of technical variance attributable to day of profile generation and experimental array. CONCLUSION: Using the techniques described in this paper it is possible to reliably detect poor quality data within proteomic profiling experiments undertaken by MS. The removal of these spectra at the initial stages of the analysis substantially improves the confidence of putative biomarker identification and allows inter-experimental comparisons to be carried out with greater confidence

Challenges of early renal cancer detection: symptom patterns and incidental diagnosis rate in a multicentre prospective UK cohort of patients presenting with suspected renal cancer.

OBJECTIVES: To describe the frequency and nature of symptoms in patients presenting with suspected renal cell carcinoma (RCC) and examine their reliability in achieving early diagnosis. DESIGN: Multicentre prospective observational cohort study. SETTING AND PARTICIPANTS: Eleven UK centres recruiting patients presenting with suspected newly diagnosed RCC. Symptoms reported by patients were recorded and reviewed. Comprehensive clinico-pathological and outcome data were also collected. OUTCOMES: Type and frequency of reported symptoms, incidental diagnosis rate, metastasis-free survival and cancer-specific survival. RESULTS: Of 706 patients recruited between 2011 and 2014, 608 patients with a confirmed RCC formed the primary study population. The majority (60%) of patients were diagnosed incidentally. 87% of patients with stage Ia and 36% with stage III or IV disease presented incidentally. Visible haematuria was reported in 23% of patients and was commonly associated with advanced disease (49% had stage III or IV disease). Symptomatic presentation was associated with poorer outcomes, likely reflecting the presence of higher stage disease. Symptom patterns among the 54 patients subsequently found to have a benign renal mass were similar to those with a confirmed RCC. CONCLUSIONS: Raising public awareness of RCC-related symptoms as a strategy to improve early detection rates is limited by the fact that related symptoms are relatively uncommon and often associated with advanced disease. Greater attention must be paid to the feasibility of screening strategies and the identification of circulating diagnostic biomarkers

Challenges of early renal cancer detection: symptom patterns and incidental diagnosis rate in a multicentre prospective UK cohort of patients presenting with suspected renal cancer

Objectives: To describe the frequency and nature of symptoms in patients presenting with suspected renal cell carcinoma (RCC) and examine their reliability in achieving early diagnosis. Design: Multicentre prospective observational cohort study. Setting and participants: Eleven UK centres recruiting patients presenting with suspected newly diagnosed RCC. Symptoms reported by patients were recorded and reviewed. Comprehensive clinico-pathological and outcome data were also collected. Outcomes: Type and frequency of reported symptoms, incidental diagnosis rate, metastasis-free survival and cancer-specific survival. Results: Of 706 patients recruited between 2011 and 2014, 608 patients with a confirmed RCC formed the primary study population. The majority (60%) of patients were diagnosed incidentally. 87% of patients with stage Ia and 36% with stage III or IV disease presented incidentally. Visible haematuria was reported in 23% of patients and was commonly associated with advanced disease (49% had stage III or IV disease). Symptomatic presentation was associated with poorer outcomes, likely reflecting the presence of higher stage disease. Symptom patterns among the 54 patients subsequently found to have a benign renal mass were similar to those with a confirmed RCC. Conclusions: Raising public awareness of RCC-related symptoms as a strategy to improve early detection rates is limited by the fact that related symptoms are relatively uncommon and often associated with advanced disease. Greater attention must be paid to the feasibility of screening strategies and the identification of circulating diagnostic biomarkers

Comparing Cystatin C Estimated GFR With Creatinine Estimated GFR in Acute Kidney Injury Recovery

Introduction: Current guidelines recommend creatinine-based estimated glomerular filtration rate (eGFRcr) to assess kidney recovery after acute kidney injury (AKI); however, this may be inaccurate because of loss of muscle mass. Cystatin C-based eGFR (eGFRcys) is an alternative that is not similarly affected. In addition, simple calculations (e.g., creatinine muscle index, CMI) incorporating the difference between eGFRcr and eGFRcys may indicate prognosis. We sought to determine whether eGFRcr differs from eGFRcys after AKI and whether CMI is associated with mortality.Methods: The AKI Risk in Derby (ARID) study is a prospective parallel-group cohort study. Hospitalized participants with and without exposure to AKI were matched 1:1 for age, baseline kidney function, and diabetes. eGFRcr and eGFRcys at 3 months after admission were compared in 849 participants. Associations between CMI and outcomes, including mortality, heart failure, and hospitalization were assessed at 5 years.Results: eGFRcys was lower than eGFRcr (53.4, [interquartile range, IQR: 34.3-85.5] vs. 68.4 [IQR: 52.5-84.7] ml/min per 1.73 m2, P < 0.001), with more pronounced differences in those with AKI. eGFRcys categorized more participants with chronic kidney disease (CKD) (in AKI group: eGFRcr < 60 ml/min per 1.73 m2 in 44.9%; eGFRcys < 60 ml/min per 1.73 m2 in 69.6%, P < 0.001). In the AKI group, higher CMI was independently associated with lower mortality at 5 years (adjusted hazard ratio: 0.931 [0.874-0.992] mg/d per 1.73 m2, P = 0.03).Conclusion: There are significant differences at 3 months after AKI in eGFR derived from creatinine versus cystatin C. The magnitude of difference between these estimates is associated with subsequent mortality. Further research is required to determine the optimal approach to patient assessment after AKI

Biomarkers of Kidney Failure and All-Cause Mortality in CKD

Background: Chronic kidney disease (CKD) carries a variable risk for multiple adverse outcomes, highlighting the need for a personalised approach. This study evaluated several novel biomarkers linked to key disease mechanisms to predict the risk of kidney failure (first event of eGFR &lt;15 ml/min/1.73m2 or kidney replacement therapy), all-cause mortality, and a composite of both.Methods: We included 2,884 adults with non-dialysis CKD from 16 nephrology centres across the UK. Twenty-one biomarkers associated with kidney damage, fibrosis, inflammation, and cardiovascular disease were analysed in urine, plasma, or serum. Cox proportional hazards models were used to assess biomarker associations and develop risk prediction models.Results: Participants had mean age 63 (15) years, 58% were male and 87% White. Median eGFR 35 (25, 47) ml/min/1.73m2, and median urinary albumin-to-creatinine ratio (UACR) 197 (32, 895) mg/g. During median 48 (33, 55) months follow-up, 680 kidney failure events and 414 all-cause mortality events occurred. For kidney failure, a model combining three biomarkers (sTNFR1, sCD40, UCOL1A1) showed good discrimination (c-index 0.86, 95% CI: 0.83-0.89) but was outperformed by a model using established risk factors (age, sex, ethnicity, eGFR, UACR; c-index 0.90, 95% CI: 0.88-0.92). For all-cause mortality, a model using three biomarkers (hs-cTnT, NT-proBNP, suPAR) demonstrated equivalent discrimination (c-index 0.80, 95% CI: 0.75-0.84) to an established risk factor model (c-index 0.80, 95% CI: 0.76-0.84).For the composite outcome, the biomarker model discrimination (C-index 0.78, 95% CI: 0.76, 0.81) was numerically higher than for established risk factors (C-index 0.77, 95% CI: 0.74, 0.80), and the addition of biomarkers to the established risk factors led to a small but statistically significant improvement in discrimination (C-index 0.80, 95% CI: 0.77, 0.82; p value &lt; 0.01).Conclusions: Risk prediction models incorporating novel biomarkers showed comparable discrimination to established risk factors for kidney failure and all-cause mortality