An Inflection Point in Cancer Protein Biomarkers: What was and What's Next.

Biomarkers remain the highest value proposition in cancer medicine today-especially protein biomarkers. Despite decades of evolving regulatory frameworks to facilitate the review of emerging technologies, biomarkers have been mostly about promise with very little to show for improvements in human health. Cancer is an emergent property of a complex system, and deconvoluting the integrative and dynamic nature of the overall system through biomarkers is a daunting proposition. The last 2 decades have seen an explosion of multiomics profiling and a range of advanced technologies for precision medicine, including the emergence of liquid biopsy, exciting advances in single-cell analysis, artificial intelligence (machine and deep learning) for data analysis, and many other advanced technologies that promise to transform biomarker discovery. Combining multiple omics modalities to acquire a more comprehensive landscape of the disease state, we are increasingly developing biomarkers to support therapy selection and patient monitoring. Furthering precision medicine, especially in oncology, necessitates moving away from the lens of reductionist thinking toward viewing and understanding that complex diseases are, in fact, complex adaptive systems. As such, we believe it is necessary to redefine biomarkers as representations of biological system states at different hierarchical levels of biological order. This definition could include traditional molecular, histologic, radiographic, or physiological characteristics, as well as emerging classes of digital markers and complex algorithms. To succeed in the future, we must move past purely observational individual studies and instead start building a mechanistic framework to enable integrative analysis of new studies within the context of prior studies. Identifying information in complex systems and applying theoretical constructs, such as information theory, to study cancer as a disease of dysregulated communication could prove to be "game changing" for the clinical outcome of cancer patients.

Protein Profiles and Novel Molecular Biomarkers of Schizophrenia Based on 4D-DIA Proteomics.

Schizophrenia is a severe psychological disorder. The current diagnosis mainly relies on clinical symptoms and lacks laboratory evidence, which makes it very difficult to make an accurate diagnosis especially at an early stage. Plasma protein profiles of schizophrenia patients were obtained and compared with healthy controls using 4D-DIA proteomics technology. Furthermore, 79 DEPs were identified between schizophrenia and healthy controls. GO functional analysis indicated that DEPs were predominantly associated with responses to toxic substances and platelet aggregation, suggesting the presence of metabolic and immune dysregulation in patients with schizophrenia. KEGG pathway enrichment analysis revealed that DEPs were primarily enriched in the chemokine signaling pathway and cytokine receptor interactions. A diagnostic model was ultimately established, comprising three proteins, namely, PFN1, GAPDH and ACTBL2. This model demonstrated an AUC value of 0.972, indicating its effectiveness in accurately identifying schizophrenia. PFN1, GAPDH and ACTBL2 exhibit potential as biomarkers for the early detection of schizophrenia. The findings of our studies provide novel insights into the laboratory-based diagnosis of schizophrenia.

Common variation in a long non-coding RNA gene modulates variation of circulating TGF-ß2 levels in metastatic colorectal cancer patients (Alliance).

BACKGROUND: Herein, we report results from a genome-wide study conducted to identify protein quantitative trait loci (pQTL) for circulating angiogenic and inflammatory protein markers in patients with metastatic colorectal cancer (mCRC). The study was conducted using genotype, protein marker, and baseline clinical and demographic data from CALGB/SWOG 80405 (Alliance), a randomized phase III study designed to assess outcomes of adding VEGF or EGFR inhibitors to systemic chemotherapy in mCRC patients. Germline DNA derived from blood was genotyped on whole-genome array platforms. The abundance of protein markers was quantified using a multiplex enzyme-linked immunosorbent assay from plasma derived from peripheral venous blood collected at baseline. A robust rank-based method was used to assess the statistical significance of each variant and protein pair against a strict genome-wide level. A given pQTL was tested for validation in two external datasets of prostate (CALGB 90401) and pancreatic cancer (CALGB 80303) patients. Bioinformatics analyses were conducted to further establish biological bases for these findings. RESULTS: The final analysis was carried out based on data from 540,021 common typed genetic variants and 23 protein markers from 869 genetically estimated European patients with mCRC. Correcting for multiple testing, the analysis discovered a novel cis-pQTL in LINC02869, a long non-coding RNA gene, for circulating TGF-ß2 levels (rs11118119; AAF = 0.11; P-value < 1.4e-14). This finding was validated in a cohort of 538 prostate cancer patients from CALGB 90401 (AAF = 0.10, P-value < 3.3e-25). The analysis also validated a cis-pQTL we had previously reported for VEGF-A in advanced pancreatic cancer, and additionally identified trans-pQTLs for VEGF-R3, and cis-pQTLs for CD73. CONCLUSIONS: This study has provided evidence of a novel cis germline genetic variant that regulates circulating TGF-ß2 levels in plasma of patients with advanced mCRC and prostate cancer. Moreover, the validation of previously identified pQTLs for VEGF-A, CD73, and VEGF-R3, potentiates the validity of these associations.

Disruption of the Circulating Proteome in Neonates Receiving Extracorporeal Membrane Oxygenation Following Congenital Heart Disease Surgery: A Nested Case-Control Study.

This nested case-control study identified broad dysregulation of the circulating proteome in neonates receiving postoperative extracorporeal membrane oxygenation support after congenital heart disease surgery, including differential responses in those not surviving to hospital discharge. Tissue hypoxia and mitochondrial-associated proteins may represent novel candidate biomarkers for poor extracorporeal membrane oxygenation outcomes.

Microneedle patch-based enzyme-linked immunosorbent assay to quantify protein biomarkers of tuberculosis.

There is a clinical need for differential diagnosis of the latent versus active stages of tuberculosis (TB) disease by a simple-to-administer test. Alpha-crystallin (Acr) and early secretory antigenic target-6 (ESAT-6) are protein biomarkers associated with the latent and active stages of TB, respectively, and could be used for differential diagnosis. We therefore developed a microneedle patch (MNP) designed for application to the skin to quantify Acr and ESAT-6 in dermal interstitial fluid by enzyme-linked immunosorbent assay (ELISA). We fabricated mechanically strong microneedles made of polystyrene and coated them with capture antibodies against Acr and ESAT-6. We then optimized assay sensitivity to achieve a limit of detection of 750 pg/ml and 3,020 pg/ml for Acr and ESAT-6, respectively. This study demonstrates the feasibility of an MNP-based ELISA for differential diagnosis of latent TB disease.

Association between adverse pregnancy outcome and placental biomarkers in the first trimester: A prospective cohort study.

OBJECTIVE: To determine the inter-relationships between five first-trimester biomarkers (pregnancy associated plasma protein A [PAPP-A], alpha-fetoprotein [AFP], beta human chorionic gonadotrophin [beta-hCG], placenta growth factor [PlGF] and soluble fms-like tyrosine kinase receptor-1 [sFlt-1]) and a range of adverse pregnancy outcomes (APOs). DESIGN: Prospective cohort study of nulliparous singleton pregnancy. SETTING: Cambridge, UK. POPULATION OR SAMPLE: 4056 pregnancy outcome prediction study participants. METHODS: The biomarker concentrations were measured in maternal serum at ~12 weeks of gestation. Univariable analysis of APOs was performed using logistic regression. Multivariable analysis used best subsets logistic regression with cross-validation. MAIN OUTCOME MEASURES: Pre-eclampsia (PE), small for gestational age (SGA), including severe SGA (birthweight <3rd), fetal growth restriction (FGR), preterm birth (PTB, both induced and spontaneous [iPTB and sPTB, respectively]), pre-viable loss and stillbirth, plus combinations of outcomes. RESULTS: Lower values of PAPP-A, PlGF and sFlt-1 and higher values of AFP were associated with FGR (OR for 1 SD higher value 0.59 [95% CI 0.48-0.74], OR 0.56 [95% CI 0.44-0.70], OR 0.68 [95% CI 0.54-0.87] and OR 1.53 [95% CI 1.25-1.88]), severe SGA (OR 0.59 [95% CI 0.49-0.72], OR 0.71 [95% CI 0.57-0.87], OR 0.74 [95% CI 0.60-0.91] and OR 1.41 [95% CI 1.17-1.71]), sPTB (OR 0.61 [95% CI 0.50-0.73], OR 0.79 [95% CI 0.66-0.96], OR 0.57 [95% CI 0.47-0.70] and OR 1.41 [95% CI 1.18-1.67]) and iPTB (OR 0.72 [95% CI 0.57-0.91], OR 0.62 [95% CI 0.49-0.78], OR 0.71 [95% CI 0.56-0.90] and OR 1.44 [95% CI 1.16-1.78]), respectively. When combinations of biomarkers were assessed, PAPP-A and AFP were independently associated with severe SGA; PAPP-A alone with PE + PTB; PlGF alone with severe PE; PlGF, beta-hCG, AFP and PAPP-A with the combination of PE and SGA; AFP and sFlt-1 with sPTB; and AFP and PlGF with iPTB. CONCLUSIONS: Combinations of first-trimester placental biomarkers are associated with APOs. However, the patterns vary for different types of APO, indicating heterogeneity in the underlying pathophysiological pathways.

Proteomic analysis of diabetic retinopathy identifies potential plasma-protein biomarkers for diagnosis and prognosis.

OBJECTIVES: To identify molecular pathways and prognostic- and diagnostic plasma-protein biomarkers for diabetic retinopathy at various stages. METHODS: This exploratory, cross-sectional proteomics study involved plasma from 68 adults, including 15 healthy controls and 53 diabetes patients for various stages of diabetic retinopathy: non-diabetic retinopathy, non-proliferative diabetic retinopathy, proliferative diabetic retinopathy and diabetic macular edema. Plasma was incubated with peptide library beads and eluted proteins were tryptic digested, analyzed by liquid chromatography-tandem mass-spectrometry followed by bioinformatics. RESULTS: In the 68 samples, 248 of the 731 identified plasma-proteins were present in all samples. Analysis of variance showed differential expression of 58 proteins across the five disease subgroups. Protein-Protein Interaction network (STRING) showed enrichment of various pathways during the diabetic stages. In addition, stage-specific driver proteins were detected for early and advanced diabetic retinopathy. Hierarchical clustering showed distinct protein profiles according to disease severity and disease type. CONCLUSIONS: Molecular pathways in the cholesterol metabolism, complement system, and coagulation cascade were enriched in patients at various stages of diabetic retinopathy. The peroxisome proliferator-activated receptor signaling pathway and systemic lupus erythematosus pathways were enriched in early diabetic retinopathy. Stage-specific proteins for early - and advanced diabetic retinopathy as determined herein could be 'key' players in driving disease development and potential 'target' proteins for future therapies. For type 1 and 2 diabetes mellitus, the proteomic profiles were especially distinct during the early disease stage. Validation studies should aim to clarify the role of the detected molecular pathways, potential biomarkers, and potential 'target' proteins for future therapies in diabetic retinopathy.

Identification of novel protein biomarkers and therapeutic targets for ankylosing spondylitis using human circulating plasma proteomics and genome analysis.

The proteome serves as the primary basis for identifying targets for treatment. This study conducted proteomic range two-sample Mendelian randomization (MR) analysis to pinpoint potential protein markers and treatment targets for ankylosing spondylitis (AS). A total of 4907 data points on circulating protein expression were collected from a large-scale protein quantitative trait locus investigation involving 35,559 individuals. Using data from a Finnish study on AS as the outcome, the dataset comprised 166,144 individuals of European ancestry (1462 cases and 164,682 controls), and causal relationships were determined through bidirectional Mendelian randomization of two samples. Proteins were further validated and identified through single-cell expression analysis, certain cells showing enriched expression levels were detected, and possible treatment targets were optimized. Increased HERC5 expression predicted by genes was related to increased AS risk, whereas the expression of the remaining five circulating proteins, AIF1, CREB3L4, MLN, MRPL55, and SPAG11B, was negatively correlated with AS risk. For each increase in gene-predicted protein levels, the ORs of AS were 2.11 (95% CI 1.44-3.09) for HERC5, 0.14 (95% CI 0.05-0.41) for AIF1, 0.48 (95% CI 0.34-0.68) for CREB3L4, 0.54 (95% CI 0.42-0.68) for MLN, 0.23 (95% CI 0.13-0.38) for MRPL55, and 0.26 (95% CI 0.17-0.39) for SPAG11B. The hypothesis of a reverse causal relationship between these six circulating proteins and AS is not supported. Three of the six protein-coding genes were expressed in both the AS and healthy control groups, while CREB3L4, MLN, and SPAG11B were not detected. Increased levels of HERC5 predicted by genes are related to increased AS risk, whereas the levels of the remaining five circulating proteins, AIF1, CREB3L4, MLN, MRPL55, and SPAG11B, negatively correlate with AS risk. HERC5, AIF1, and MRPL55 are potential therapeutic targets for AS. This study advanced the field by employing a novel combination of proteomic range two-sample MR analysis and single-cell expression analysis to identify potential protein markers and therapeutic targets for AS. This approach enabled a comprehensive understanding of the causal relationships between circulating proteins and AS, which has not been extensively explored in previous studies.

Novel subtypes of severe COVID-19 respiratory failure based on biological heterogeneity: a secondary analysis of a randomized controlled trial.

BACKGROUND: Despite evidence associating inflammatory biomarkers with worse outcomes in hospitalized adults with COVID-19, trials of immunomodulatory therapies have met with mixed results, likely due in part to biological heterogeneity of participants. Latent class analysis (LCA) of clinical and protein biomarker data has identified two subtypes of non-COVID acute respiratory distress syndrome (ARDS) with different clinical outcomes and treatment responses. We studied biological heterogeneity and clinical outcomes in a multi-institutional platform randomized controlled trial of adults with severe COVID-19 hypoxemic respiratory failure (I-SPY COVID). METHODS: Clinical and plasma protein biomarker data were analyzed from 400 trial participants enrolled from September 2020 until October 2021 with severe COVID-19 requiring ≥ 6 L/min supplemental oxygen. Seventeen hypothesis-directed protein biomarkers were measured at enrollment using multiplex Luminex panels or single analyte enzyme linked immunoassay methods (ELISA). Biomarkers and clinical variables were used to test for latent subtypes and longitudinal biomarker changes by subtype were explored. A validated parsimonious model using interleukin-8, bicarbonate, and protein C was used for comparison with non-COVID hyper- and hypo-inflammatory ARDS subtypes. RESULTS: Average participant age was 60 ± 14 years; 67% were male, and 28-day mortality was 25%. At trial enrollment, 85% of participants required high flow oxygen or non-invasive ventilation, and 97% were receiving dexamethasone. Several biomarkers of inflammation (IL-6, IL-8, IL-10, sTNFR-1, TREM-1), epithelial injury (sRAGE), and endothelial injury (Ang-1, thrombomodulin) were associated with 28- and 60-day mortality. Two latent subtypes were identified. Subtype 2 (27% of participants) was characterized by persistent derangements in biomarkers of inflammation, endothelial and epithelial injury, and disordered coagulation and had twice the mortality rate compared with Subtype 1. Only one person was classified as hyper-inflammatory using the previously validated non-COVID ARDS model. CONCLUSIONS: We discovered evidence of two novel biological subtypes of severe COVID-19 with significantly different clinical outcomes. These subtypes differed from previously established hyper- and hypo-inflammatory non-COVID subtypes of ARDS. Biological heterogeneity may explain inconsistent findings from trials of hospitalized patients with COVID-19 and guide treatment approaches.

Biomarkers associated with cardiovascular disease in women with spontaneous preterm birth: A case-control study.

INTRODUCTION: Women with spontaneous preterm birth have an increased risk of cardiovascular disease later in life. Studies suggest potential pathophysiological mechanisms in common, but whether these could be identified by measurement of soluble circulating protein biomarkers in women with spontaneous preterm birth is unknown. The aim of this study was to determine if protein biomarkers associated with cardiovascular disease distinguish women with spontaneous preterm birth from healthy controls, both at pregnancy and at follow up. MATERIAL AND METHODS: Study participants were identified in the population-based Uppsala biobank of pregnant women in Sweden, where plasma samples were collected in mid-pregnancy. In a first screening phase, we identified participants who subsequently experienced spontaneous preterm birth (<37 weeks) in the index pregnancy (N = 13) and controls (N = 6). In these samples, differences in protein expression were examined by comparative mass spectrometry. In a second validation phase, we invited 100 cases with previous spontaneous preterm birth in the index pregnancy and 100 controls (matched for age, body mass index, and year of delivery) from the same source population, to a follow-up visit 4-15 years after pregnancy. At follow up, we collected plasma samples and data on cardiovascular risk factors. We measured concentrations of selected biomarkers identified in the screening phase, as well as lipid profiles in samples both from pregnancy (biobank) and follow up. CLINICALTRIALS: gov registration NCT05693285. RESULTS: In the screening phase, fibrinogen, cadherin-5, complement C5, factor XII, plasma kallikrein, apolipoprotein M, and vitamin D-binding protein differed significantly at pregnancy. In the validation phase, 65 women agreed to participate (35 cases and 30 controls), with a median follow-up time of 11.8 years since pregnancy. The concentration of fibrinogen (p = 0.02) and triglycerides (p = 0.03) were slightly higher in cases compared with matched controls at follow up. CONCLUSIONS: Compared with women without preterm birth, those with spontaneous preterm birth had slightly higher concentrations of fibrinogen, both at mid-pregnancy and a decade after pregnancy. Additionally, we found slightly higher concentration of triglycerides at follow up in women with previous spontaneous preterm birth. The relevance of this finding is uncertain but might indicate potential pathophysiological mechanisms in common between spontaneous preterm birth and cardiovascular disease.

Evaluation of maternal serum protein biomarkers in the prenatal evaluation of placenta accreta spectrum: A systematic scoping review.

INTRODUCTION: Placenta accreta spectrum (PAS) is an increasingly commonly reported condition due to the continuous increase in the rate of cesarean deliveries (CD) worldwide; however, the prenatal screening for pregnant patients at risk of PAS at birth remains limited, in particular when imaging expertise is not available. MATERIAL AND METHODS: Two major electronic databases (MEDLINE and Embase) were searched electronically for articles published in English between October 1992 and January 2023 using combinations of the relevant medical subject heading terms and keywords. Two independent reviewers selected observational studies that provided data on one or more measurement of maternal blood-specific biomarker(s) during pregnancies with PAS at birth. PRISMA Extension for Scoping Review (PRISMA-ScR) was used to extract data and report results. RESULTS: Of the 441 reviewed articles, 29 met the inclusion criteria reporting on 34 different biomarkers. 14 studies were retrospective and 15 prospective overall including 18 251 participants. Six studies had a cohort design and the remaining a case-control design. Wide clinical heterogeneity was found in the included studies. In eight studies, the samples were obtained in the first trimester; in five, the samples were collected on hospital admission for delivery; and in the rest, the samples were collected during the second and/or third trimester. CONCLUSIONS: Measurements of serum biomarkers, some of which have been or are still used in screening for other pregnancy complications, could contribute to the prenatal evaluation of patients at risk of PAS at delivery; however, important evidence gaps were identified for suitable cutoffs for most biomarkers, variability of gestational age at sampling and the potential overlap of the marker values with other placental-related complications of pregnancy.

Cerebrospinal Fluid Protein Biomarker Discovery in CLN3.

Syndromic CLN3-Batten is a fatal, pediatric, neurodegenerative disease caused by variants in CLN3, which encodes the endolysosomal transmembrane CLN3 protein. No approved treatment for CLN3 is currently available. The protracted and asynchronous disease presentation complicates the evaluation of potential therapies using clinical disease progression parameters. Biomarkers as surrogates to measure the progression and effect of potential therapeutics are needed. We performed proteomic discovery studies using cerebrospinal fluid (CSF) samples from 28 CLN3-affected and 32 age-similar non-CLN3 individuals. Proximal extension assay (PEA) of 1467 proteins and untargeted data-dependent mass spectrometry [MS; MassIVE FTP server (ftp://MSV000090147@massive.ucsd.edu)] were used to generate orthogonal lists of protein marker candidates. At an adjusted p-value of <0.1 and threshold CLN3/non-CLN3 fold-change ratio of 1.5, PEA identified 54 and MS identified 233 candidate biomarkers. Some of these (NEFL, CHIT1) have been previously linked with other neurologic conditions. Others (CLPS, FAM217B, QRICH2, KRT16, ZNF333) appear to be novel. Both methods identified 25 candidate biomarkers, including CHIT1, NELL1, and ISLR2 which had absolute fold-change ratios >2. NELL1 and ISLR2 regulate axonal development in neurons and are intriguing new candidates for further investigation in CLN3. In addition to identifying candidate proteins for CLN3 research, this study provides a comparison of two large-scale proteomic discovery methods in CSF.

Liquid biopsy-based protein biomarkers for risk prediction, early diagnosis, and prognostication of cholangiocarcinoma.

BACKGROUND & AIMS: Cholangiocarcinoma (CCA), heterogeneous biliary tumours with dismal prognosis, lacks accurate early diagnostic methods especially important for individuals at high-risk (i.e. those with primary sclerosing cholangitis [PSC]). Here, we searched for protein biomarkers in serum extracellular vesicles (EVs). METHODS: EVs from patients with isolated PSC (n = 45), concomitant PSC-CCA (n = 44), PSC who developed CCA during follow-up (PSC to CCA; n = 25), CCAs from non-PSC aetiology (n = 56), and hepatocellular carcinoma (n = 34) and healthy individuals (n = 56) were characterised by mass spectrometry. Diagnostic biomarkers for PSC-CCA, non-PSC CCA, or CCAs regardless of aetiology (Pan-CCAs) were defined and validated by ELISA. Their expression was evaluated in CCA tumours at a single-cell level. Prognostic EV biomarkers for CCA were investigated. RESULTS: High-throughput proteomics of EVs identified diagnostic biomarkers for PSC-CCA, non-PSC CCA, or Pan-CCA, and for the differential diagnosis of intrahepatic CCA and hepatocellular carcinoma, which were cross-validated by ELISA using total serum. Machine learning-based algorithms disclosed CRP/FIBRINOGEN/FRIL for the diagnosis of PSC-CCA (local disease [LD]) vs. isolated PSC (AUC = 0.947; odds ratio [OR] =36.9) and, combined with carbohydrate antigen 19-9, overpowers carbohydrate antigen 19-9 alone. CRP/PIGR/VWF allowed the diagnosis of LD non-PSC CCAs vs. healthy individuals (AUC = 0.992; OR = 387.5). It is noteworthy that CRP/FRIL accurately diagnosed LD Pan-CCA (AUC = 0.941; OR = 89.4). Levels of CRP/FIBRINOGEN/FRIL/PIGR showed predictive capacity for CCA development in PSC before clinical evidence of malignancy. Multi-organ transcriptomic analysis revealed that serum EV biomarkers were mostly expressed in hepatobiliary tissues, and single-cell RNA sequencing and immunofluorescence analysis of CCA tumours showed their presence mainly in malignant cholangiocytes. Multivariable analysis unveiled EV prognostic biomarkers, with COMP/GNAI2/CFAI and ACTN1/MYCT1/PF4V associated negatively and positively with patients' survival, respectively. CONCLUSIONS: Serum EVs contain protein biomarkers for the prediction, early diagnosis, and prognostication of CCA that are detectable using total serum, representing a tumour cell-derived liquid biopsy tool for personalised medicine. IMPACT AND IMPLICATIONS: The accuracy of current imaging tests and circulating tumour biomarkers for cholangiocarcinoma (CCA) diagnosis is far from satisfactory. Most CCAs are considered sporadic, although up to 20% of patients with primary sclerosing cholangitis (PSC) develop CCA during their lifetime, constituting a major cause of PSC-related death. This international study has proposed protein-based and aetiology-related logistic models with predictive, diagnostic, or prognostic capacities by combining two to four circulating protein biomarkers, moving a step forward into personalised medicine. These novel liquid biopsy tools may allow the (i) easy and non-invasive diagnosis of sporadic CCAs, (ii) identification of patients with PSC with higher risk for CCA development, (iii) establishment of cost-effective surveillance programmes for the early detection of CCA in high-risk populations (e.g. PSC), and (iv) prognostic stratification of patients with CCA, which, altogether, may increase the number of cases eligible for potentially curative options or to receive more successful treatments, decreasing CCA-related mortality.

Comprehensive proteomics and platform validation of urinary biomarkers for bladder cancer diagnosis and staging.

BACKGROUND: Bladder cancer (BC) is among the most common cancers diagnosed in men in the USA. The current gold standards for the diagnosis of BC are invasive or lack the sensitivity to correctly identify the disease. METHODS: An aptamer-based screen analyzed the expression of 1317 proteins in BC compared to urology clinic controls. The top hits were subjected to systems biology analyses. Next, 30 urine proteins were ELISA-validated in an independent cohort of 68 subjects. Three of these proteins were next validated in an independent BC cohort of differing ethnicity. RESULTS: Systems biology analysis implicated molecular functions related to the extracellular matrix, collagen, integrin, heparin, and transmembrane tyrosine kinase signaling in BC susceptibility, with HNF4A and NFKB1 emerging as key molecular regulators. STEM analysis of the dysregulated pathways implicated a functional role for the immune system, complement, and interleukins in BC disease progression. Of 21 urine proteins that discriminated BC from urology clinic controls (UC), urine D-dimer displayed the highest accuracy (0.96) and sensitivity of 97%. Furthermore, 8 urine proteins significantly discriminated MIBC from NMIBC (AUC = 0.75-0.99), with IL-8 and IgA being the best performers. Urine IgA and fibronectin exhibited the highest specificity of 80% at fixed sensitivity for identifying advanced BC. CONCLUSIONS: Given the high sensitivity (97%) of urine D-dimer for BC, it may have a role in the initial diagnosis or detection of cancer recurrence. On the other hand, urine IL-8 and IgA may have the potential in identifying disease progression during patient follow-up. The use of these biomarkers for initial triage could have a significant impact as the current cystoscopy-based diagnostic and surveillance approach is costly and invasive when compared to a simple urine test.

Maternal serum levels of soluble fms-like tyrosine kinase-1 and placental growth factor at 20 and 28 weeks of gestational age and the risk of spontaneous preterm birth.

BACKGROUND: Spontaneous preterm birth is the endpoint of multiple different pathophysiological pathways. Fetal growth restriction, assessed by serial ultrasonic fetal biometry, has been shown to predict both preterm and early-term spontaneous labor. The soluble fms-like tyrosine kinase-1 to placental growth factor ratio is predictive of early-term spontaneous labor, but its association with spontaneous preterm birth is unclear. OBJECTIVE: This study aimed to determine whether maternal serum levels of soluble fms-like tyrosine kinase-1, placental growth factor, and the soluble fms-like tyrosine kinase-1: placental growth factor ratio at 20 and 28 weeks' gestation, and the rate of change in these biomarkers between 20 and 28 weeks were predictive of risk of spontaneous preterm birth. STUDY DESIGN: The biomarkers were measured in maternal serum at 20- and 28-weeks' gestation in women recruited to a prospective cohort of unselected nulliparous women as part of the Pregnancy Outcome Prediction study in Cambridge, United Kingdom. The risk of spontaneous preterm birth was assessed using Cox regression and competing-risks regression. Associations from Cox regression were quantified by the adjusted hazard ratio for a 1 standard deviation higher level of a given biomarker or a 1 standard deviation increase in the marker between 20 and 28 weeks' gestation. A previously identified risk factor, slow femur length growth, was used as an additional predictor of spontaneous preterm birth for the purpose of risk stratification. RESULTS: Of the 3763 participants in the analysis, 95 (2.5%) had spontaneous preterm birth and 54 (1.4%) had medically indicated preterm birth. At 20 weeks' gestation, higher levels of soluble fms-like tyrosine kinase-1 and the soluble fms-like tyrosine kinase-1:placental growth factor ratio were associated with reduced risk of spontaneous preterm birth (adjusted hazard ratio [95% confidence interval], 0.75 [0.61-0.92]; P=.006 and 0.71 [0.59-0.87]; P=.0009, respectively). At 28 weeks' gestation, there was no association between either soluble fms-like tyrosine kinase-1 or placental growth factor and the risk of spontaneous preterm birth, but there was a U-shaped relation with the soluble fms-like tyrosine kinase-1:placental growth factor ratio. However, when the biomarkers were quantified as the rate of increase between 20 and 28 weeks' gestation, there were strong positive associations between spontaneous preterm birth and rate of increase in soluble fms-like tyrosine kinase-1 (1.36 [1.13-1.63]; P=.001) and the soluble fms-like tyrosine kinase-1:placental growth factor ratio (1.50 [1.30-1.73]; P<.0001), and a strong negative association with the rate of increase in placental growth factor (0.71 [0.61-0.82]; P<.0001). Women who were in the highest decile of increase in the soluble fms-like tyrosine kinase-1:placental growth factor ratio and the lowest decile of femur length growth between 20 and 28 weeks' gestation had approximately 9-fold risk of spontaneous preterm birth (9.27 [4.21-20.37]; P<.0001). Competing-risks regression yielded similar results. CONCLUSION: Changing levels of soluble fms-like tyrosine kinase-1 and placental growth factor are indicative of placental dysfunction and are strongly associated with the risk of spontaneous preterm birth, especially when combined with slower fetal femur length growth.

Molecular targets and therapeutic strategies for triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is known for its heterogeneous complexity and is often difficult to treat. TNBC lacks the expression of major hormonal receptors like estrogen receptor, progesterone receptor, and human epidermal growth factor receptor-2 and is further subdivided into androgen receptor (AR) positive and AR negative. In contrast, AR negative is also known as quadruple-negative breast cancer (QNBC). Compared to AR-positive TNBC, QNBC has a great scarcity of prognostic biomarkers and therapeutic targets. QNBC shows excessive cellular growth and proliferation of tumor cells due to increased expression of growth factors like EGF and various surface proteins. This study briefly reviews the limited data available as protein biomarkers that can be used as molecular targets in treating TNBC as well as QNBC. Targeted therapy and immune checkpoint inhibitors have recently changed cancer treatment. Many studies in medicinal chemistry continue to focus on the synthesis of novel compounds to discover new antiproliferative medicines capable of treating TNBC despite the abundance of treatments currently on the market. Drug repurposing is one of the therapeutic methods for TNBC that has been examined. Moreover, some additional micronutrients, nutraceuticals, and functional foods may be able to lower cancer risk or slow the spread of malignant diseases that have already been diagnosed with cancer. Finally, nanomedicines, or applications of nanotechnology in medicine, introduce nanoparticles with variable chemistry and architecture for the treatment of cancer. This review emphasizes the most recent research on nutraceuticals, medication repositioning, and novel therapeutic strategies for the treatment of TNBC.

Immunosensors for Autoimmune-Disease-Related Biomarkers: A Literature Review.

Immunosensors are a special class of biosensors that employ specific antibodies for biorecognition of the target analyte. Immunosensors that target disease biomarkers may be exploited as tools for disease diagnosis and/or follow-up, offering several advantages over conventional analytical techniques, such as rapid and easy analysis of patients' samples at the point-of-care. Autoimmune diseases have been increasingly prevalent worldwide in recent years, while the COVID-19 pandemic has also been associated with autoimmunity. Consequently, demand for tools enabling the early and reliable diagnosis of autoimmune diseases is expected to increase in the near future. To this end, interest in immunosensors targeting autoimmune disease biomarkers, mainly, various autoantibodies and specific pro-inflammatory proteins (e.g., specific cytokines), has been rekindled. This review article presents most of the immunosensors proposed to date as potential tools for the diagnosis of various autoimmune diseases, such as type 1 diabetes, rheumatoid arthritis, and multiple sclerosis. The signal transduction and the immunoassay principles of each immunosensor have been suitably classified and are briefly presented along with certain sensor elements, e.g., special nano-sized materials used in the construction of the immunosensing surface. The main concluding remarks are presented and future perspectives of the field are also briefly discussed.

Genetic and Epigenetic Features of Uveal Melanoma-An Overview and Clinical Implications.

Uveal melanoma (UM) is rare, but it is the most common primary intraocular malignancy among adults. This review represents the molecular, genetic, and immunobiological mechanisms involved in UM carcinogenesis and progression, as well as data about the association of chromosomal changes, genetic mutations, selective proteins, and biochemical biomarkers with the clinical implications of UM. Genetic analysis has the potential to identify patients with a high risk of UM metastasis, enabling management that is more effective and allowing for the follow-up of patients. Advancements in molecular characterization of UM offer opportunities to develop targeted therapeutic strategies by focusing on relevant signaling pathways. Changes in miRNA expression could be useful in the diagnosis and prognosis of UM, due to unique miRNA profiles in melanoma cells or tissue and its association with metastasis. Although liver function tests do not provide enough data on the prognosis of UM, due to the high frequency of liver metastasis, liver function tests (LFTs) might be useful indicators; however, the absence of rising LFT values cannot lead to the exclusion of liver metastases. Molecular analysis of tumor tissue will allow us to identify patients with the added benefit of new therapeutic agents and provide a better insight into melanoma pathogenesis and its biological behavior.

Review Insights on Salivary Proteomics Biomarkers in Oral Cancer Detection and Diagnosis.

Early detection is crucial for the treatment and prognosis of oral cancer, a potentially lethal condition. Tumor markers are abnormal biological byproducts produced by malignant cells that may be found and analyzed in a variety of bodily fluids, including saliva. Early detection and appropriate treatment can increase cure rates to 80-90% and considerably improve quality of life by reducing the need for costly, incapacitating medicines. Salivary diagnostics has drawn the interest of many researchers and has been proven to be an effective tool for both medication monitoring and the diagnosis of several systemic diseases. Since researchers are now searching for biomarkers in saliva, an accessible bodily fluid, for noninvasive diagnosis of oral cancer, measuring tumor markers in saliva is an interesting alternative to blood testing for early identification, post-treatment monitoring, and monitoring high-risk lesions. New molecular markers for oral cancer detection, treatment, and prognosis have been found as a result of developments in the fields of molecular biology and salivary proteomics. The numerous salivary tumor biomarkers and how they relate to oral cancer and pre-cancer are covered in this article. We are optimistic that salivary protein biomarkers may one day be discovered for the clinical detection of oral cancer because of the rapid advancement of proteomic technology.

Human peripheral blood mononuclear cells: A review of recent proteomic applications.

Human peripheral blood mononuclear cells (PBMCs) represent a sentinel blood sample which reacts to different pathophysiological stimuli in the form of immunological responses/immunophenotypic changes. The study of molecular content of PBMCs can provide better understanding of immune processes giving the possibility of monitoring the health conditions of the host organism. Proteomic analysis of PBMCs can achieve mentioned goal as important immune-related biomarkers are easily accessible for analysis. PBMCs have been gaining attention in different research areas including preclinical or clinical investigations. In this review, recent applications of proteomic analysis of PBMCs are described and discussed. Approaches are divided based on different proteomic workflows such as in-gel, in-solution and on-filter modes. The effect of various diseases such as autoimmune, cancer, neurodegenerative, viral, metabolic, and various immune stimulations such as radiation, vaccine, corticosteroids over PBMCs proteome, are described with emphasis on promising protein biomarker candidates.