Panel Of Biomarkers Research Articles

Cutaneous targets for topical pain medications in patients with neuropathic pain: individual differential expression of biomarkers supports the need for personalized medicine.

Numerous potential cutaneous targets exist for treating chronic pain with topically applied active pharmaceutical ingredients. This preliminary human skin tissue investigation was undertaken to characterize several key biomarkers in keratinocytes and provide proof-of-principle data to support clinical development of topical compounded formulations for peripheral neuropathic pain syndromes, such as postherpetic neuralgia (PHN). The study intended to identify objective biomarkers in PHN skin on a patient-by-patient personalized medicine platform. The totality of biopsy biomarker data can provide a tissue basis for directing individualized compounded topical preparations to optimize treatment efficacy. Referencing 5 of the most common actives used in topical pain relief formulations (ketamine, gabapentin, clonidine, baclofen, and lidocaine), and 3 well-established cutaneous mediators (ie, neuropeptides, cannabinoids, and vanilloids), comprehensive immunolabeling was used to quantify receptor biomarkers in skin biopsy samples taken from ipsilateral (pain) and contralateral (nonpain) dermatomes of patients with PHN. Epidermal keratinocyte labeling patterns were significantly different among the cohort for each biomarker, consistent with potential mechanisms of action among keratinocytes. Importantly, the total biomarker panel indicates that the enriched PHN cohort contains distinct subgroups. The heterogeneity of the cohort differences may explain studies that have not shown statistical group benefit from topically administered compounded therapies. Rather, the essential need for individual tissue biomarker evaluations is evident, particularly as a means to direct a more accurately targeted topical personalized medicine approach and generate positive clinical results.

Comparison between next-generation sequencing and multiplex polymerase chain reaction assays for nonsmall-cell lung cancer molecular diagnosis.

Genetic mutation detection has become an important step in nonsmall-cell lung cancer (NSCLC) treatment because of the increasing number of drugs that target genomic rearrangements. A multiplex test that can detect multiple gene mutations prior to treatment is thus necessary. Currently, either next-generation sequencing (NGS)-based or polymerase chain reaction (PCR)-based tests are used. We evaluated the performance of the Oncomine Dx Target Test (ODxTT), an NGS-based multiplex biomarker panel test, and the AmoyDx Pan Lung Cancer PCR Panel (AmoyDx PLC panel), a real-time PCR-based multiplex biomarker panel test. Patients with histologically diagnosed NSCLC and a sufficient sample volume to simultaneously perform the AmoyDx PLC panel and ODxTT-M were included in the study. The success and detection rates of both tests were evaluated. Biopsies revealed 116 cases of malignancies, 100 of which were NSCLC. Of these, 59 met the inclusion criteria and were eligible for analysis. The success rates were 100% and 98% for AmoyDx PLC panel and ODxTT-M, respectively. Nine driver mutations were detected in 35.9% and 37.3% of AmoyDx PLC and ODxTT-M panels, respectively. EGFR mutations were detected in 14% and 12% of samples using the AmoyDx PLC panel and ODxTT-M, respectively. Of the 58 cases in which both NGS and AmoyDx PLC panels were successful, discordant results were observed in seven cases. These differences were mainly due to different sensitivities of the detection methods used and the gene variants targeted in each test. The AmoyDx PLC panel, a PCR-based multiplex diagnostic test, exhibits a high success rate. The frequency of the nine genes targeted for treatment detected by the AmoyDx PLC panel was comparable to the frequency of mutations detected by ODxTT-M. Clinicians should understand and use the AmoyDx PLC panel and ODxTT-M with respect to their respective performances and limitations.

Integrated analysis of transcriptional changes in major depressive disorder: Insights from blood and anterior cingulate cortex

BackgroundMajor depressive disorder (MDD) was involved in widely transcriptional changes in central and peripheral tissues. While, previous studies focused on single tissues, making it difficult to represent systemic molecular changes throughout the body. Thus, there is an urgent need to explore the central and peripheral biomarkers with intrinsic correlation. MethodsWe systematically retrieved gene expression profiles of blood and anterior cingulate cortex (ACC). 3 blood datatsets (84 MDD and 88 controls) and 6 ACC datasets (100 MDD and 100 controls) were obtained. Differential expression analysis, RobustRankAggreg (RRA) analysis, functional enrichment analysis, immune associated analysis and protein-protein interaction networks (PPI) were integrated. Furthermore, the key genes were validated in an independent ACC dataset (12 MDD and 15 controls) and a cohort with 120 MDD and 117 controls. ResultsDifferential expression analysis identified 2211 and 2021 differential expressed genes (DEGs) in blood and ACC, respectively. RRA identified 45 and 25 robust DEGs in blood and ACC based on DEGs, and all of them were closely associated with immune cells. Functional enrichment results showed both the robust DEGs in blood and ACC were enriched in humoral immune response. Furthermore, PPI identified 8 hub DEGs (CD79A, CD79B, CD19, MS4A1, PLP1, CLDN11, MOG, MAG) in blood and ACC. Independent ACC dataset showed the area under the curve (AUC) based on these hub DEGs was 0.77. Meanwhile, these hub DEGs were validated in the serum of MDD patients, and also showed a promising diagnostic power. ConclusionsThe biomarker panel based on hub DEGs yield a promising diagnostic efficacy, and all of these hub DEGs were strongly correlated with immunity. Humoral immune response may be the key link between the brain and blood in MDD, and our results may provide further understanding for MDD.

Serum N-glycomic profiling identifies candidate biomarker panels for assessing coronary artery stenosis severity

Stenosis severity may escalate over the course of coronary artery disease (CAD), increasing the risk of death for the patient. Conventionally, the assessment of stenosis degree relies on invasive coronary angiography (ICA), an invasive examination unsuitable for patients in poor physical condition or those with contrast allergies and one that imposes a psychological burden on patients. Although abnormal serum N-glycan profiles have exhibited robust associations with various cardiovascular diseases, including CAD, their potential in diagnosing CAD stenosis remains to be determined. In this study, we performed a comprehensive analysis of serum N-glycome from 132 patients who underwent ICA and 27 healthy controls using MALDI-TOF-mass spectrometry. The patients who underwent ICA examination were categorized into four groups based on stenosis severity: no/mild/moderate/severe stenosis. Twenty-seven N-glycans were directly quantified, and 47 derived glycan traits were obtained. Notably, among these 74 glycan features, 18 exhibited variations across the study groups. Using a combination of least absolute shrinkage and selection operator and logistic regression analyses, we developed five diagnostic models for recognizing stenosis degree. Our results suggested that alterations in serum N-glycosylation modifications might be valuable for identifying stenosis degree and monitoring disease progression in individuals with CAD. It is expected to offer a noninvasive alternative for those who could not undergo ICA because of various reasons. However, the diagnostic potential of serum N-glycan panels as biomarkers requires multicenter, large cohort validation in the future.

Biomarker and proteome analysis of milk from dairy cows with clinical mastitis: Determining the effect of different bacterial pathogens on the response to infection

Antimicrobial usage (AMU) could be reduced by differentiating the causative bacteria in cases of clinical mastitis (CM) as either Gram-positive or Gram-negative bacteria or identifying whether the case is culture-negative (no growth, NG) mastitis. Immunoassays for biomarker analysis and a Tandem Mass Tag (TMT) proteomic investigation were employed to identify differences between samples of milk from cows with CM caused by different bacteria. A total of 94 milk samples were collected from cows diagnosed with CM across seven farms in Scotland, categorized by severity as mild (score 1), moderate (score 2), or severe (score 3). Bovine haptoglobin (Hp), milk amyloid A (MAA), C-reactive protein (CRP), lactoferrin (LF), α-lactalbumin (LA) and cathelicidin (CATHL) were significantly higher in milk from cows with CM, regardless of culture results, than in milk from healthy cows (all P-values <0.001). Milk cathelicidin (CATHL) was evaluated using a novel ELISA technique that utilises an antibody to a peptide sequence of SSEANLYRLLELD (aa49–61) common to CATHL 1–7 isoforms. A classification tree was fitted on the six biomarkers to predict Gram-positive bacteria within mastitis severity scores 1 or 2, revealing that compared to the rest of the samples, Gram-positive samples were associated with CRP < 9.5 μg/ml and LF ≥ 325 μg/ml and MAA < 16 μg/ml. Sensitivity of the tree model was 64%, the specificity was 91%, and the overall misclassification rate was 18%. The area under the ROC curve for this tree model was 0.836 (95% bootstrap confidence interval: 0.742; 0.917). TMT proteomic analysis revealed little difference between the groups in protein abundance when the three groups (Gram-positive, Gram-negative and no growth) were compared, however when each group was compared against the entirety of the remaining samples, 28 differentially abundant protein were identified including β-lactoglobulin and ribonuclease. Whilst further research is required to draw together and refine a suitable biomarker panel and diagnostic algorithm for differentiating Gram- positive/negative and NG CM, these results have highlighted a potential panel and diagnostic decision tree. Host-derived milk biomarkers offer significant potential to refine and reduce AMU and circumvent the many challenges associated with microbiological culture, both within the lab and on the farm, while providing the added benefit of reducing turnaround time from 14 to 16 h of microbiological culture to just 15 min with a lateral flow device (LFD).

Prenatal air pollution exposure is associated with inflammatory, cardiovascular, and metabolic biomarkers in mothers and newborns

BackgroundPrenatal air pollution exposure has been associated with individual inflammatory, cardiovascular, and metabolic biomarkers in mothers and neonates. However, studies of air pollution and a comprehensive panel of biomarkers across maternal and cord blood samples remain limited. Few studies used data-driven methods to identify biomarker groupings that converge biomarkers from multiple biological pathways. This study aims to investigate the impacts of prenatal air pollution on groups of biomarkers in maternal and cord blood samples. MethodsIn the Maternal And Developmental Risks from Environmental and Social Stressors (MADRES) cohort, 87 biomarkers were quantified from 45 trimester 1 maternal blood and 55 cord blood samples. Pregnancy and trimester 1-averaged concentrations of particulate matter ≤2.5 μm and ≤10 μm in diameter (PM2.5 and PM10), nitrogen dioxide (NO2), and ozone (O3) were estimated, using inverse distance squared weighted spatial interpolation from regulatory air monitoring stations. Traffic-related NOx was assessed using California Line Source Dispersion Model: freeway/highway roads, non-freeway major roads, non-freeway minor roads, and their sum as total NOx. Elastic Net (EN) regression within the rexposome R package was used to group biomarkers and assess their associations with air pollution. ResultsIn maternal samples, trimester 1-averaged PM10 was associated with elevated inflammation biomarkers and lowered cardiovascular biomarkers. NO2 exhibited positive associations with cardiovascular and inflammation markers. O3 was inversely associated with inflammation, metabolic, and cardiovascular biomarkers. In cord blood, pregnancy-averaged PM2.5 was associated with higher cardiovascular biomarkers and lower metabolic biomarkers. PM10 was associated with lower inflammation and higher cardiovascular biomarkers. Total and major road NOx was associated with lower cardiovascular biomarkers. ConclusionPrenatal air pollution exposure was associated with changes in biomarkers related to inflammation, cardiovascular, metabolic, cancer, and neurological function in both mothers and neonates. This study shed light on mechanisms by which air pollution can influence biological function during pregnancy.

A new biomarker panel for differential diagnosis of cholangiocarcinoma: Results from an exploratory analysis.

Diagnosis of cholangiocarcinoma (CCA) can be challenging due to unclear imaging criteria and difficulty obtaining adequate tissue biopsy. Although serum cancer antigen 19-9 and carcinoembryonic antigen have been proposed as potential diagnostic aids, their use remains limited by insufficient sensitivity and specificity. This exploratory analysis aimed to identify individual- and combinations of serum biomarkers to distinguish CCA from hepatocellular carcinoma (HCC) and chronic liver disease (CLD) controls using samples from a published study. This prospective, multicenter, case-control study included patients aged ≥18 years at high-risk of HCC. Serum and ethylene diamine tetraacetic acid-plasma samples were collected prior to any treatment and confirmed diagnosis of HCC or CCA. Fourteen biomarkers (measured by electrochemiluminescence immunoassays or enzyme-linked immunosorbent assays) were subjected to univariate analysis and 13 included in a multivariate analysis (per selected combinations and exhaustive search). Overall, 55 CCA, 306 HCC, and 733 CLD control samples were analyzed. For distinguishing CCA from HCC, alpha-fetoprotein and matrix metalloproteinase-2 (MMP-2) showed the best individual performance (area under the curve (AUC) 86.6% and 84.4%, respectively); tissue inhibitor of metalloproteinase-1 (TIMP-1) was most able to distinguish CCA from CLD (AUC 94.5%) and from HCC + CLD (AUC 88.6%). The combination of MMP-2 and TIMP-1 was the best-performing two-marker panel, with AUC >90% for all comparisons. MMP-2 and TIMP-1 are promising biomarkers that could support differential diagnosis of CCA. Incorporating these assays into the diagnostic algorithm could provide additional diagnostic information in a non-invasive, rapid manner, and could supplement existing diagnostic methods.

Use of Nonhuman Sera as a Highly Cost-Effective Internal Standard for Quantitation of Multiple Human Proteins Using Species-Specific Tryptic Peptides: Applicability in Clinical LC-MS Analyses.

Quantitation of proteins using liquid chromatography-tandem mass spectrometry (LC-MS/MS) is complex, with a multiplicity of options ranging from label-free techniques to chemically and metabolically labeling proteins. Increasingly, for clinically relevant analyses, stable isotope-labeled (SIL) internal standards (ISs) represent the "gold standard" for quantitation due to their similar physiochemical properties to the analyte, wide availability, and ability to multiplex to several peptides. However, the purchase of SIL-ISs is a resource-intensive step in terms of cost and time, particularly for screening putative biomarker panels of hundreds of proteins. We demonstrate an alternative strategy utilizing nonhuman sera as the IS for quantitation of multiple human proteins. We demonstrate the effectiveness of this strategy using two high abundance clinically relevant analytes, vitamin D binding protein [Gc globulin] (DBP) and albumin (ALB). We extend this to three putative risk markers for cardiovascular disease: plasma protease C1 inhibitor (SERPING1), annexin A1 (ANXA1), and protein kinase, DNA-activated catalytic subunit (PRKDC). The results show highly specific, reproducible, and linear measurement of the proteins of interest with comparable precision and accuracy to the gold standard SIL-IS technique. This approach may not be applicable to every protein, but for many proteins it can offer a cost-effective solution to LC-MS/MS protein quantitation.

Straightforward Creation of Multishell Hollow Hybrids for an Integrated Metabolic Monitoring System in Disease Management.

Multidimensional metabolic analysis has become a new trend in establishing efficient disease monitoring systems, as the constraints associated with relying solely on a single dimension in refined monitoring are increasingly pronounced. Here, coordination polymers are employed as derivative precursors to create multishell hollow hybrids, developing an integrated metabolic monitoring system. Briefly, metabolic fingerprints are extracted from hundreds of serum samples and urine samples, encompassing not only membranous nephropathy but also related diseases, using high-throughput mass spectrometry. With optimized algorithm and initial feature selection, the established combined panel demonstrates enhanced accuracy in both subtype differentiation (over 98.1%) and prognostic monitoring (over 95.6%), even during double blind test. This surpasses the serum biomarker panel (≈90.7% for subtyping, ≈89.7% for prognosis) and urine biomarker panel (≈94.4% for subtyping, ≈76.5% for prognosis). Moreover, after attempting to further refine the marker panel, the blind test maintains equal sensitivity, specificity, and accuracy, showcasing a comprehensive improvement over the single-fluid approach. This underscores the remarkable effectiveness and superiority of the integrated strategy in discriminating between MN and other groups. This work has the potential to significantly advance diagnostic medicine, leading to the establishment of more effective strategies for patient management.

Identifying plasma metabolic characteristics of major depressive disorder, bipolar disorder, and schizophrenia in adolescents

Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) are classified as major mental disorders and together account for the second-highest global disease burden, and half of these patients experience symptom onset in adolescence. Several studies have reported both similar and unique features regarding the risk factors and clinical symptoms of these three disorders. However, it is still unclear whether these disorders have similar or unique metabolic characteristics in adolescents. We conducted a metabolomics analysis of plasma samples from adolescent healthy controls (HCs) and patients with MDD, BD, and SCZ. We identified differentially expressed metabolites between patients and HCs. Based on the differentially expressed metabolites, correlation analysis, metabolic pathway analysis, and potential diagnostic biomarker identification were conducted for disorders and HCs. Our results showed significant changes in plasma metabolism between patients with these mental disorders and HCs; the most distinct changes were observed in SCZ patients. Moreover, the metabolic differences in BD patients shared features with those in both MDD and SCZ, although the BD metabolic profile was closer to that of MDD than to SCZ. Additionally, we identified the metabolites responsible for the similar and unique metabolic characteristics in multiple metabolic pathways. The similar significant differences among the three disorders were found in fatty acid, steroid-hormone, purine, nicotinate, glutamate, tryptophan, arginine, and proline metabolism. Interestingly, we found unique characteristics of significantly altered glycolysis, glycerophospholipid, and sphingolipid metabolism in SCZ; lysine, cysteine, and methionine metabolism in MDD and BD; and phenylalanine, tyrosine, and aspartate metabolism in SCZ and BD. Finally, we identified five panels of potential diagnostic biomarkers for MDD-HC, BD-HC, SCZ-HC, MDD-SCZ, and BD-SCZ comparisons. Our findings suggest that metabolic characteristics in plasma vary across psychiatric disorders and that critical metabolites provide new clues regarding molecular mechanisms in these three psychiatric disorders.

Using the Traditional Ex Vivo Whole Blood Model to Discriminate Bacteria by Their Inducible Host Responses.

Whole blood models are rapid and versatile for determining immune responses to inflammatory and infectious stimuli, but they have not been used for bacterial discrimination. Staphylococcus aureus, S. epidermidis and Escherichia coli are the most common causes of invasive disease, and rapid testing strategies utilising host responses remain elusive. Currently, immune responses can only discriminate between bacterial 'domains' (fungi, bacteria and viruses), and very few studies can use immune responses to discriminate bacteria at the species and strain level. Here, whole blood was used to investigate the relationship between host responses and bacterial strains. Results confirmed unique temporal profiles for the 10 parameters studied: IL-6, MIP-1α, MIP-3α, IL-10, resistin, phagocytosis, S100A8, S100A8/A9, C5a and TF3. Pairwise analysis confirmed that IL-6, resistin, phagocytosis, C5a and S100A8/A9 could be used in a discrimination scheme to identify to the strain level. Linear discriminant analysis (LDA) confirmed that (i) IL-6, MIP-3α and TF3 could predict genera with 95% accuracy; (ii) IL-6, phagocytosis, resistin and TF3 could predict species at 90% accuracy and (iii) phagocytosis, S100A8 and IL-10 predicted strain at 40% accuracy. These data are important because they confirm the proof of concept that host biomarker panels could be used to identify bacterial pathogens.

Abstract 3789: Discovery of liquid biopsy-based novel protein biomarkers for early detection of breast cancer metastasis

Abstract Introduction and Objectives: Despite recent advances in screening and therapeutic technology, breast cancer is still the first leading cause of cancer death among females. When detected early (i.e., SEER Stage Localized), the 5-yr survival rate is 99%. The 5-yr survival rate is still 86% when cancer cells have spread beyond the breast, but this spread is limited to nearby lymph nodes (SEER Stage Regional). However, when the disease is noted to be SEER Stage Distant or metastasis, the 5-yr survival rate is significantly reduced to 31%. The evidence suggests that breast cancer is manageable if distant metastasis could be prevented. Thus, the prevailing idea is that early detection of breast cancer metastasis in surveillance will likely be the best modality to address advanced breast cancer’s dismal outcomes. Thus, liquid biopsy may be suitable for “early detection” of pre- and/or micro-metastasis because of its ease of obtaining biological material. In this pilot study, we explored the potential biomarkers for the early detection of breast cancer metastasis using publicly available datasets. Methods: We obtained 2 publicly available datasets from GEO (GSE102484 and GSE234114) containing primary tumor samples taken from subjects with and without metastatic disease. Both datasets were generated by mRNA microarray (Affymetrix Human Genome U133 Plus 2.0 Array). With these datasets, we performed the differentially expressed gene (DEG) analysis using GEO2R based on GEOquery and limma (Linear Models for Microarray Analysis) with a threshold criterion of Log 2 fold change &amp;gt;0 and p-value &amp;lt;0.05 as the cut-off point. The significantly upregulated genes were further screened using VerSeDa (Vertebrate Secretome Database) to select secreted proteins. Results: In the GSE102484 (N = 683, 582 non-metastasis and 101 metastasis), DEG identified 1798 upregulated and 1472 downregulated genes. Venn diagram analysis between the upregulated genes and VerSeDa identified 337 upregulated genes coding secreted proteins. In the GSE234114 (N = 120, 60 non-metastasis and 60 metastasis), DEG identified 2873 upregulated and 931 downregulated genes. Venn diagram analysis between the upregulated genes and VerSeDa identified 563 upregulated genes coding secreted proteins. By integrating the genes from GSE102484 and GSE234114, 82 commonly upregulated genes that code secreted proteins were identified. Conclusions: In this study, we identified 82 candidate mRNA biomarkers that are upregulated in breast tumor with metastasis. The panel of biomarkers will be validated in blood-based liquid biopsy samples in the next study. Citation Format: Cynthia Jinno, Sunao Tanaka, Takeo Fujii, Hideki Furuya. Discovery of liquid biopsy-based novel protein biomarkers for early detection of breast cancer metastasis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3789.

Abstract 6223: Personalized MRI-informed forecasting of prostate cancer progression during active surveillance

Abstract Low and intermediate-risk prostate cancer (PCa) patients are eligible for active surveillance (AS), whereby treatment is delayed until progression to higher-risk disease is detected via longitudinal multiparametric magnetic resonance imaging (mpMRI) scans, biopsies, and prostate specific antigen (PSA) tests. However, AS relies on a population-based observational paradigm in which standard testing frequencies may not match the patient’s tumor dynamics, resulting in a delayed diagnosis of progressive disease. To address these issues, we propose to advance AS towards a patient-specific predictive paradigm by leveraging computational tumor forecasts obtained with a biomechanistic model informed by mpMRI and clinical data collected during standard AS. Here, we present a retrospective study with n = 16 PCa cases. All patients had three mpMRI scans obtained over 2.6 to 5.6 years during AS. Our biomechanistic model describes PCa growth in terms of the dynamics of tumor cell density as a combination of tumor cell mobility and net proliferation. The model is defined on the patient’s prostate geometry, which is segmented on T2-weighted MRI data. Tumor cell density estimates are derived from apparent diffusion coefficient (ADC) maps obtained from diffusion-weighted MRI data. To facilitate modeling, the longitudinal imaging datasets are non-rigidly co-registered for each patient. We initialize the model with the tumor cell density map obtained from the ADC map of the first scan. The model is parameterized by minimizing the model-data mismatch in tumor cell density at the second scan date, and then we perform a tumor forecast up to the third scan date. Finally, we build a logistic classifier from a panel of model-based biomarkers calculated from the personalized model forecasts (e.g., tumor volume, total proliferation activity) at the times of histopathological assessment (i.e., biopsy, surgery) to classify tumors as low risk (Gleason score 3+3, n = 16) or intermediate-high risk (Gleason score ≥ 3+4, n = 15). We obtained a concordance correlation coefficient (CCC) for tumor volume of 0.89 at both model calibration and forecasting horizon. The spatial fit of tumor cell density yielded a median Dice score and CCC of 0.80 and 0.59 at the second mpMRI date, and of 0.76 and 0.60 at the third mpMRI date, respectively. The logistic classifier of PCa risk yielded an area under the ROC curve of 0.90 and operates at optimal sensitivity, specificity, and accuracy of 86.7%, 93.8%, and 90.3%, respectively. The time trajectories of PCa risk obtained from the temporal predictions of the model-based biomarkers enabled identification of PCa progression by more than 1 year. Thus, while further development and validation over larger cohorts are required, these results suggest that our forecasting technology is a promising tool to predict PCa progression in AS and, hence, optimally guide monitoring and treatment decisions during AS. Citation Format: Guillermo Lorenzo Gomez, Chengyue Wu, Joshua P. Yung, John F. Ward, Hector Gomez, Alessandro Reali, Thomas E. Yankeelov, Aradhana M. Venkatesan, Thomas J. Hughes. Personalized MRI-informed forecasting of prostate cancer progression during active surveillance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6223.

Abstract 5567: Breast cancer cell alteration of immune cell transcriptome through indirect communication

Abstract Crosstalk between tumor and non-tumor cells plays an important role in cancer progression and metastasis often leading to a modification of non-malignant cells into pro-oncogenic phenotypes. Understanding this process is important for diagnostic and therapeutic advances. We previously reported clinical validation results for a new way to detect early-stage breast cancer using a panel of RNA biomarkers from whole blood and a machine learning software-powered testing system. Recently, we showed that immune cells undergo transcriptomic and functional changes upon direct contact with breast cancer cells. Here, we report results from investigation of indirect communication between breast cancer and immune cells leading to cancer-driven immune cell transformation and activation of multiple oncogenic pathways. To characterize these modifications, we performed RNAseq and pathway analysis on a human monocytic cell line, THP1, exposed to media from triple negative breast cancer (TNBC) cells (MDA-MB-231) in culture. Our results demonstrate that 24 hours of THP1 cell exposure to soluble factors secreted by tumor cells leads to significant gene modulation, with over 1,100 differentially expressed genes (|Fold Change|&amp;gt;2; p&amp;lt;0.05). KEGG and Reactome enrichment analysis revealed overlap of multiple pathways between THP1 cells exposed to direct and indirect cancer cell contact conditions, such as cytokine-cytokine receptor interaction, JAK-STAT signaling pathways and others. TNF, NMP1, STING1 and TGM2 were identified as key upstream regulators potentially driving this transformation in both direct and indirect contact conditions. The S100 pathway, which we previously found to be activated by fluid shear stress in MDA-MB-231 cells was also activated in THP1 cells upon both direct and indirect contact. The observed gene expression changes in THP1 cells exposed to media from MDA-MB-231 suggests that indirect intercellular communication alone can transmit an oncogenic signal. These results support a role for secreted factors from breast cancer cells in transforming immune cells and modulating the gene expression markers detected by our blood test, expanding the potential for leveraging this type of tumor education response in advancing cancer detection and treatment. Citation Format: Jacob Kennard, Karen Norek, Kenneth Fuh, Robert D. Shepherd, Kristina D. Rinker, Olesya A. Kharenko. Breast cancer cell alteration of immune cell transcriptome through indirect communication [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5567.

Linkage of diabetic retinopathy with blood antioxidants and gut microbiota in type two diabetes mellitus Saudi patients

Background: The retina is a light-sensitive nerve layer located at the back of the eye that creates images of objects. These cells kept alive by getting oxygen and nutrients from tiny blood vessels in the eye. Retinopathy is a disease of the retina that is more prevalent in type 2 diabetes mellitus patients. Diabetic retinopathy is a leading cause of blindness because hyperglycemia weakens retinal capillaries, resulting in leakage of blood into the surrounding space. This bleeding can result in formation of scar tissue, which can cause traction retinal detachment and maculopathy. The development of a panel of blood biomarkers to monitor diabetic retinopathies is essential for both diagnosis and prognosis. Proteomics as a powerful tool for the analysis of complex mixtures of proteins and the identification of biomarkers can be of great importance. Purpose: To detect early nerve fiber layer changes around macula and optic disc in diabetic patients, and to correlate diabetic retinopathy with blood antioxidants and gut microbiota in T2DM in Saudi patients. Materials and Methods: In this cross-sectional case-control study, a total of 77 eyes of 39 subjects aged 40-60 years who did not have any history of eye injuries or eye diseases affecting fundus viewing, were recruited from King Saud University Campus and the department of ophthalmology in King Abdul Aziz university hospital in Riyadh. All subjects underwent full ophthalmic examination including Peripapillary retinal nerve fiber layer thickness and macular profile, Proteomic approach of collected overnight fasting plasma and Microbial stool examination. Results: The nerve fiber layer thickness around the optic disc was measured for all groups, and there was no statistically significant difference in all quadrants between groups. The total retinal thickness at the macular area was different among all groups and tends to increase in group 3 due to diabetic retinopathy. The macular thickness in the 4 quadrants revealed no statistical difference except in the inferior quadrant. Glutathione S transferase and lipid peroxides showed no significant difference between the three studied groups; vitamin C and Glutathione were surprisingly higher in controlled diabetic patients relative to controls. Moreover, over growth of bacteroids participated to the evolution of retinopathy in diabetic patients. Conclusion: As hyperglycemia and oxidative stress are implicated in the pathogenesis of diabetic retinopathy, the present study certified that the progressive damage can be delayed in controlled type 2 diabetic patients using different treatment modalities that subside oxidative stress.

Abstract 6193: Exploring interplay between tumor intrinsic features and immune cell phenotypes in multi-tumor tissue microarrays by a single step 15-plex fluorescence immunohistochemistry and imaging on the Orion platform

Abstract Purpose: Deeper understanding of the intricacies between tumor microenvironments and immune cell infiltrates is critical for creation of next generation therapies. However, current immunohistochemistry protocols in clinical practice are restricted to one to six markers (cell types) and rely on multiple rounds of antigen retrieval and sequential staining over two days. This current workflow has high risk for tissue and signal loss. Hence, we explored utility of a single step staining workflow using 15 distinct antibodies conjugated novel flours (Argo Dye System) of formalin fixed paraffin embedded (FFPE) tumor microarrays and imaged on the Orion microscope (Rarecyte). Fidelity of the staining was assessed by comparing data from the Orion platform to internally developed clinical grade assays. The implementation of higher plex imaging will enable greater insight into immune surveillance, mechanisms of resistance and patient stratification while minimizing patient tissue required for analysis. Study Design: We utilized a custom panel developed by RareCyte (Hoescht, CD3e, CD4, CD8a, CD20, CD68, CD163, FOXP3, Ki67, Pan-CK, PD1, PDL1, CD45, Granzyme B, LAG3) to evaluate expression of immune markers on a pan-tumor and melanoma TMA including Hodgkin’s lymphoma, ovarian cancer, esophageal carcinoma, hepatic cell carcinoma, head and neck cancer. Serial sections were stained with 6-plex clinical grade assays, and correlation scores were determined between the 15-plex Orion and 6-plex assays utilizing TSA-based amplification. Results: In this study, the performance of Orion platform was assessed by quantitative and qualitative measures. Linear regression between the 6-plex clinical grade assays and 15-plex Orion workflow were calculated for a panel of biomarkers including CD3, CD4, CD8, CD68, CD163, CK, FOXP3, GZMB, Ki67, and PD1. Our results demonstrated that the Orion performed similarly to clinical grade assays both in terms of proportion of cells and fluorescence intensity (R2 ~ 0.7-0.98, Slope ~ 0.7-1.1). Conclusion: Our results suggest that the Orion platform offers a reliable and efficient solution for comprehensive biomarker analysis. Our results demonstrate that this platform can successfully capture the expression of 15 biomarkers on a single FFPE slide which offers workflow advantages over traditional TSA-based fIHC multiplexing that is limited to detection of 6 biomarkers on a single slide. The ability to analyze a wider range of biomarkers through a single platform has the potential to enhance the efficiency of biomarker analysis, leading to improved diagnostic and therapeutic outcomes in clinical practice. Citation Format: Richard Van Krieken, Jehovana O. Bender, Sophia Kekchidou, Michelle Burgin, Kristen Ruma, Naveen Dakappagari, Jennifer Bordeaux. Exploring interplay between tumor intrinsic features and immune cell phenotypes in multi-tumor tissue microarrays by a single step 15-plex fluorescence immunohistochemistry and imaging on the Orion platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6193.

Abstract 3774: Evaluation of FibraChek™ for non-invasive detection of hepatic fibrosis and hepatocellular carcinoma

Abstract Introduction and Objectives: The incidence of hepatocellular carcinoma (HCC) has almost tripled since the early 1980s in the United States where it is the fastest rising cause of cancer-related deaths. Advanced liver fibrosis and cirrhosis are ones of major risk factors for HCC. The recent evidence demonstrates that successfully treating the cause of early to moderate hepatic fibrosis may reverse most. For this reason, detecting hepatic fibrosis in an early stage is crucial. Liver biopsy is currently the gold standard for the assessment of hepatic fibrosis in clinical practice. Thus, there is an urgent clinical need for the development of non-invasive blood-based tests because of its ease of obtaining biological material. Previously, we developed FibraChek™, non-invasive blood-based tests. In this study, we tested the performance of FibraChek™ on detecting hepatic fibrosis and HCC in the US. Methods: The performance of FibraChek™ was evaluated in a single-institutional cohort of 14 prospectively collected subjects presenting for chronic liver disease (NAFLD/NASH) patients with hepatic fibrosis, 19 prospectively collected subjects diagnosed with HCC, and 12 prospectively collected controls from the US. The algorithm uses weighted value of the 5 biomarkers: AST, ALT, Platelet, Taurocholic Acid (TCA) &amp; Tyrosine plus age to derive a risk score. The ability of the test to identify patients harboring hepatic fibrosis or HCC was assessed. Hepatic fibrosis status was confirmed by tissue biopsy or definitive surgery. Diagnostic performance was assessed using AUC. Results: FibraChek™ provided an AUC of 0.923 with an overall sensitivity of 93.9%, specificity of 81.8%, NPV 91.2% and PPV 81.8%. Interestingly, risk scores in HCC cohort indicated higher than those in patients with hepatic fibrosis. Thus, FibraChek™ may be also able to use for HCC detection. Conclusions: Serum levels of a biomarker panel enabled the accurate discrimination of hepatic fibrosis and controls. The FibraChek™ test can achieve the easy, efficient, and accurate detection of hepatic fibrosis and HCC in a non-invasive patient setting. Citation Format: Sunao Tanaka, Guoxiang Xie, Hideki Furuya, Wei Jia, Charles J. Rosser. Evaluation of FibraChek™ for non-invasive detection of hepatic fibrosis and hepatocellular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3774.

Abstract 1028: Assessment of the diagnostic accuracy of Oncuria-Detect® for detection of upper tract urothelial carcinoma

Abstract Introduction and Objective: Due to insufficient accuracy, urine-based assays currently have a limited role in the management of patients with upper tract urothelial carcinoma (UTUC). The application of a robust urine-based multiplex assay, Oncuria-Detect®, to aid in the detection of UTUC has the potential to address this deficiency and to assist with accurate, non-invasive diagnosis. Methods: To evaluate the performance of Oncuria-Detect®, a multiplex immunoassay capable of querying a voided urine sample for 10 protein biomarkers associated with urothelial carcinoma (A1AT, APOE, ANG, CA9, IL8, MMP9, MMP10, PAI1, SDC1 and VEGFA). Its application to UTUC was evaluated in a multi-institutional cohort of 35 prospectively collected subjects presenting for evaluation of upper tract mass along with 46 prospective collected matched controls (i.e., non-tumor bearing). The ability of the test to identify patients harboring UTUC was assessed. UTCU status was confirmed by endoscopy and tissue biopsy or definitive surgery. Diagnostic performance was assessed using ROC curves. Results: Oncuria-Detect® provided an AUC of 0.886 (95% CI: 0.807-0.964) with an overall sensitivity of 91.4%, specificity of 73.9%, NPV 91.9% and PPV 72.7%. Sensitivity values of the diagnostic panel for low-grade UTUC, high-grade UTUC, non-invasive UTUC and invasive UTUC were 86.7%, 90.9%, 88.9% and 94.1%, respectively. Urinary cytology or selective ureteral washing/cytology was associated with an overall sensitivity of 54.2%, specificity of 100%, NPV 63.3% and PPV 100%. Sensitivity values of cytology for low-grade UTUC, high-grade UTUC, non-invasive UTUC and invasive UTUC were 100%, 100%, 100%, and 77.8%, respectively. Conclusions: Urinary levels of a biomarker panel enabled the accurate discrimination of UTUC and controls non-tumor bearing individuals. The multiplex Oncuria-Detect® test can achieve the efficient and accurate detection of UTUC in a non-invasive patient setting. Citation Format: Toru Sakatani, Sunao Tanaka, Kazutoshi Fujita, Jennifer Linehan, Kaoru Murakami, Riko Lee, Ian Pagano, Charles J. Rosser, Hideki Furuya. Assessment of the diagnostic accuracy of Oncuria-Detect® for detection of upper tract urothelial carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1028.

Abstract 7003: Microfluidic platform for DNA methylation profiling towards early detection of ovarian cancer

Abstract We present a microfluidic platform for molecule-by-molecule detection of heterogeneous epigenetic patterns of rare tumor-derived DNA by highly parallelized digital melt. The platform digitizes DNA molecules in a 4-module, 40,000 1-nL array microfluidic device and observes sequence-dependent fluorescence changes during temperature ramping. The platform is applied to quantify DNA methylation heterogeneity of a biomarker panel within Pap specimens in a small cohort of healthy and ovarian cancer patients, and demonstrates an accuracy of 0.9. DNA hypermethylation of tumor-suppressor genes is an epigenetic phenomena that occurs early in tumorigenesis. Variable methylation patterns are observed in ovarian cancer precursor tissue, and trace amounts of ovarian-tumor-derived DNA can be found in Pap specimens, albeit at low frequencies (&amp;lt;0.01%). This suggests that methylation profiles of DNA extracted from routinely-obtained Pap specimens could contain early cancer biomarkers. However, due to the scarcity of these molecules, current techniques, such as sequencing and digital PCR (dPCR), have technical limitations precluding their ability to profile methylation patterns reliably. Sequencing, although comprehensive, has limited sensitivity, undermining its utility for routine detection of fractions below 0.1%. dPCR achieves high sensitivity, but is limited to known sequences, thus cannot provide comprehensive analysis of molecular heterogeneity. To overcome these limitations, we developed a technique called digital high resolution melt (dHRM), a thermodynamics-based approach to detecting molecular variability by observing the sequence-specific release of a DNA-intercalating dye under a thermal ramp. dHRM can discriminate methylation patterns on CpG-by-CpG basis and detect methylated epialleles at frequencies as low as 0.00005%. Here, DNA from Pap specimens was loaded on a microfluidic chip that digitizes rare target molecules into individual reaction chambers. A thermal-optical platform was developed to perform parallelized dPCR and dHRM. Methylation patterns of a biomarker panel were analyzed to produce a probability score that the Pap specimen contained tumor-derived DNA. 12 healthy and 12 ovarian cancer Pap specimens were assessed for methylation heterogeneity of 9 genes. Optimal methylation density thresholds were determined, and data above each threshold was combined into a single score for each possible combination of biomarkers. In this small cohort, methylation heterogeneity analysis of just 2 loci produced an area under the receiver-operator characteristics curve (AUC) of 0.9. This highly sensitive methylation profiling technology demonstrates promising utility towards early cancer detection. Future work aims to expand the testing cohort for ovarian cancer detection and permit further studies on the impact of methylation heterogeneity on early cancer development. Citation Format: Chrissy O'Hersey, Yang Zhao, Thomas R. Pisanic, Tian-Li Wang, Ie-Ming Shih, Tza-Huei Jeff Wang. Microfluidic platform for DNA methylation profiling towards early detection of ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7003.

Abstract 2439: Potential target genes for early stage detection in Hispanic colorectal cancer

Abstract Background: Colorectal Cancer (CRC) has become the second leading cause of death related to cancer worldwide and the third most common malignancy. CRC tumors are classified into stages to describe the cancer; early (stages I and II) and advanced (stages III and IV). Despite the available screening methods and the scientific efforts in the development of a universal biomarker panel for CRC early detection, there still exists a gap in a reliable non-invasive screening method for the Hispanic community. We aimed to elucidate the most important pathways along with the differential gene expression in early and advanced CRC stages in a Hispanic population. Methods: We examined restrospectively 7 tissue samples from a Puerto Rican Hispanic population recruited throughout the Puerto Rico Familial Colorectal Cancer Registry (PURIFICAR) IRB #A2210207. We evaluated transcriptomic changes in advance tumors (n=4) vs. early tumors (n=3) with their respective normal mucosal tissue as negative control. Extracted RNA was sequenced using the Illumina NextSeq (2 × 75bp). The higher-quality reads were aligned, annotated, and quantified to the human genome (hg38) using STAR and RSEM softwares. Gene expression analysis was performed in R statistical software (packages tximport and DESeq2). We compared significantly expressed genes (adjusted p-value &amp;lt;0.05) between study groups (Tumor Advance [TA] vs. Mucosal Advance [MA] and Tumor Early [TE] vs. Mucosal Early [ME]) using Venny, and we performed enrichment analyses and protein-protein interaction networks using Metascape and STRING database, respectively. Results: There were 2284 differentially expressed genes (TA vs. MA) and 984 (TE vs. ME), in which 1736 were unique to advance stages, 436 were unique to early stages and 548 were shared in both tumor stages. Significantly impacted biological processes and pathways include: granulocyte chemotaxis, regulation of inflammatory response, positive regulation of apoptotic process, tissue morphogenesis, G alpha signaling events, interleukin-10 signaling, signaling by interleukins. Additionally, physical and functional interaction networks showed 11 major clusters (≥ 5 genes), which contained several gene hubs including LYN (proto-oncogene), IL-1β, IL-1α, TNF, CCL3, CCL4, CXCR1 and CXCR2 (cytokines/chemokines) among others genes previously reported as CRC biomarkers (DKK1, AQP8, AQP9, CTNNB1, and GNAQ). Discussion/Conclusions: Differential analysis of early CRC tumor samples shows a deregulation of genes related to the inflammatory response which plays an important role in CRC. Modulation of these genes suggests significant potential targets for early detection of CRC in a Hispanic population. Future studies will be focus on the evaluation of selected target genes as a non-invasive early CRC screening method. Citation Format: Elba V. Caraballo, Camille Zenón-Meléndez, Josué Pérez-Santiago, Marcia Cruz-Correa. Potential target genes for early stage detection in Hispanic colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2439.