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Figueiredo, A. Q.

Publications and source records attributed to Figueiredo, A. Q..

2 recordsLinked to original sources
bioRxiv2026

To Recover or Not to Recover: A Urinary Proteomic Perspective on Severe Acute Kidney Injury

Rationale & Objective Early prediction of renal non-recovery after acute kidney injury (AKI) could support risk-adapted follow-up and clinical decision-making. We evaluated whether a urinary fatty acid-binding protein 3 (FABP3)/apolipoprotein A-I (APOA1) ratio based on Total Protein Approach (TPA) quantification could discriminate renal recovery from non-recovery after severe AKI. Study Design Exploratory biomarker discovery study with outcome-blinded independent validation. Setting & Participants Critically ill adults with KDIGO stage 2 or 3 AKI. Urine was collected 48 hours after AKI diagnosis. The discovery cohort included 20 patients (10 recovered and 10 non-recovered), and the outcome-blinded validation cohort included 10 patients. New Predictor Urinary TPA-derived FABP3/APOA1 ratio (AKI^TPA index). Outcome Renal recovery at day 14, defined as survival with serum creatinine returning to within 0.3 mg/dL or 150% of baseline; patients not meeting these criteria were classified as having non-recovery. Analytical Approach Urinary proteins were analyzed by LC-MS/MS and quantified using TPA. Differential analysis identified FABP3 and APOA1 as oppositely associated with renal outcome. A predefined FABP3/APOA1 threshold of 1 classified patients as non-recovery-like (>1) or recovery-like (<1) and was subsequently applied to the outcome-blinded validation cohort. Results In the discovery cohort, the AKI^TPA index correctly classified 17 of 20 patients (accuracy, 85.0%; sensitivity, 80.0%; specificity, 90.0%; ROC AUC, 0.930). In the validation cohort, 9 patients were evaluable, of whom 7 were correctly classified (accuracy, 77.8%; sensitivity, 75.0%; specificity, 80.0%; ROC AUC, 0.950). Limitations The exploratory design and limited cohort size warrant further validation in larger, independent populations. Conclusions The urinary FABP3/APOA1 TPA ratio showed encouraging preliminary discrimination of renal recovery after severe AKI and warrants prospective clinical validation in larger, independent multicenter cohorts.

biochemistry↗
bioRxiv2026

Absolute quantitative proteomics guides patient-stratified drug repurposing in clear cell and papillary renal cell carcinoma.

BackgroundRenal cell carcinoma (RCC) is a highly heterogeneous disease in which distinct molecular subtypes exhibit characteristic genomic, metabolic, and microenvironmental features that influence therapeutic response. Substantial inter-patient variability exists within each subtype, resulting in markedly different clinical outcomes even among tumours of the same histological category. Proteomics provides a direct readout of tumour biology and pathway activity, complementing genomic information and enabling the identification of patient-specific actionable vulnerabilities. We applied a Total Protein Approach (TPA)-based prescriptomics framework that integrates absolute quantitative proteomics with curated drug-target knowledge to nominate patient-specific drug-repurposing options, positioned as coadjuvants to the prevailing standard of care. MethodsSeventeen human kidney tissue specimens, seven clear cell RCC (ccRCC), five papillary RCC (pRCC), and five normal adjacent tissues (NAT), were retrieved from the publicly available PRIDE repository (PXD023296) and reanalysed by TPA-based absolute quantification applied to previously acquired label-free LC-MS/MS data. Differential expression analysis between each tumour subtype and NAT identified subtype-specific upregulated proteins, wich were intersected with Therapeutic Target Database (TTD) to nominate FDA-approved drugs targeting dysregulated proteins as candidate repurposing strategies. ResultsccRCC and pRCC produced distinct proteome-wide upregulation profiles consistent with their known biological drivers. TPA index stratification nominated bempedoic acid (ACLY inhibitor) and tipiracil hydrochloride (TYMP inhibitor) as patient-stratified candidates for ccRCC, and auranofin (TXNRD1 inhibitor), bempedoic acid, and mipomersen (APOB-directed antisense oligonucleotide) for pRCC. ACLY was the only top-priority target shared across both subtypes, pointing to a candidate cross-subtype metabolic vulnerability. Secondary candidates emerged from protein-protein interaction network analysis in both subtypes.. ConclusionsThis study presents a quantitative proteomics framework for translating individual-patient proteomic dysregulation into coadjuvant drug-repurposing hypotheses across the principal RCC subtypes. By combining the TPA for absolute protein quantification with prescriptomics-guided drug-target mapping, we show that ccRCC and pRCC harbour distinct, individually stratifiable therapeutic vulnerabilities. These findings provide a proof-of-concept for proteomics-based treatment stratification in RCC and establish a scalable framework that, pending functional validation, could inform personalised therapeutic decision-making across RCC subtypes.

biochemistry↗