Blood-based Test Research Articles

Deep Learning-Based Identification of Tissue of Origin for Carcinomas of Unknown Primary Using MicroRNA Expression: Algorithm Development and Validation.

Carcinoma of unknown primary (CUP) is a subset of metastatic cancers in which the primary tissue source of the cancer cells remains unidentified. CUP is the eighth most common malignancy worldwide, accounting for up to 5% of all malignancies. Representing an exceptionally aggressive metastatic cancer, the median survival is approximately 3 to 6 months. The tissue in which cancer arises plays a key role in our understanding of sensitivities to various forms of cell death. Thus, the lack of knowledge on the tissue of origin (TOO) makes it difficult to devise tailored and effective treatments for patients with CUP. Developing quick and clinically implementable methods to identify the TOO of the primary site is crucial in treating patients with CUP. Noncoding RNAs may hold potential for origin identification and provide a robust route to clinical implementation due to their resistance against chemical degradation. This study aims to investigate the potential of microRNAs, a subset of noncoding RNAs, as highly accurate biomarkers for detecting the TOO through data-driven, machine learning approaches for metastatic cancers. We used microRNA expression data from The Cancer Genome Atlas data set and assessed various machine learning approaches, from simple classifiers to deep learning approaches. As a test of our classifiers, we evaluated the accuracy on a separate set of 194 primary tumor samples from the Sequence Read Archive. We used permutation feature importance to determine the potential microRNA biomarkers and assessed them with principal component analysis and t-distributed stochastic neighbor embedding visualizations. Our results show that it is possible to design robust classifiers to detect the TOO for metastatic samples on The Cancer Genome Atlas data set, with an accuracy of up to 97% (351/362), which may be used in situations of CUP. Our findings show that deep learning techniques enhance prediction accuracy. We progressed from an initial accuracy prediction of 62.5% (226/362) with decision trees to 93.2% (337/362) with logistic regression, finally achieving 97% (351/362) accuracy using deep learning on metastatic samples. On the Sequence Read Archive validation set, a lower accuracy of 41.2% (77/188) was achieved by the decision tree, while deep learning achieved a higher accuracy of 80.4% (151/188). Notably, our feature importance analysis showed the top 3 most important features for predicting TOO to be microRNA-10b, microRNA-205, and microRNA-196b, which aligns with previous work. Our findings highlight the potential of using machine learning techniques to devise accurate tests for detecting TOO for CUP. Since microRNAs are carried throughout the body via extracellular vesicles secreted from cells, they may serve as key biomarkers for liquid biopsy due to their presence in blood plasma. Our work serves as a foundation toward developing blood-based cancer detection tests based on the presence of microRNA.

Screening for Colorectal Cancer: The Role of Clinical Laboratories.

Colorectal cancer (CRC) is a leading cause of cancer incidence and mortality. Screening can result in reductions in incidence and mortality, but there are many challenges to uptake and follow-up. Here, we will review the changing epidemiology of CRC, including increasing trends for early and later onset CRC; evidence to support current and emerging screening strategies, including noninvasive stool and blood-based tests; key challenges to ensuring uptake and high-quality screening; and the critical role that clinical laboratories can have in supporting health system and public health efforts to reduce the burden of CRC on the population. Clinical laboratories have the opportunity to play a seminal role in optimizing early detection and prevention of CRC.

Diagnostic Efficiency of the Blood-Based Cepheid 3-Gene Host Response Test and Urine-Based Lipoarabinomannan for Active Tuberculosis Case Detection at a General Hospital in China.

To assess the diagnostic performance of the blood-based Cepheid 3-gene Host Response test (MTB-HR), urine-based Lipoarabinomannan (LAM), and a combination of MTB-HR and LAM (MTB-HR & LAM) for detecting active tuberculosis (ATB). All participants were recruited from the First Affiliated Hospital, Zhejiang University School of Medicine, between June 8, 2023 and September 13, 2023. Subsequently, the participants were classified into the ATB group or non-active tuberculosis (non-ATB) group based on microbiological evidence. MTB-HR and LAM tests were performed using fingerstick blood and urine samples from each participant, respectively. The diagnostic performance of the tests was evaluated based on the sensitivity, specificity, Youden index, and Kappa value. Pairwise comparisons of the areas under the receiver operating characteristic curves (AUROCs) between different tests were conducted using nonparametric methods. A total of 297 participants were included. The MTB-HR test demonstrated diagnostic efficacy with a sensitivity of 77.37% (95% CI: 70.37-84.38) and a specificity of 85.63% (95% CI: 80.19-91.06). The LAM test demonstrated a high specificity of 97.50% (95% CI: 95.08-99.92), albeit with a lower sensitivity of 54.74% (95% CI: 46.41-63.082). The sensitivity and specificity of the MTB-HR & LAM were 83.21% (95% CI: 76.95-89.47) and 83.13% (95% CI: 77.32-88.93), respectively. Only MTB-HR & LAM exhibited higher values of area under the receiver operating characteristic curve than the LAM test (MTB-HR & LAM vs LAM: 0.83 vs 0.76, P=0.0031). In this study, although both non-sputum-based triage MTB-HR and LAM do not meet the WHO diagnostic target currently, they show possible values for triage and diagnosis in ATB. Compared to single MTB-HR or LAM test, the combined MTB-HR & LAM does not demonstrate advantages.

Caregivers' attitudes toward blood-based biomarker testing for Alzheimer's disease.

We aimed to evaluate informal caregivers' attitudes toward undergoing and future implementation of blood-based biomarkers (BBBM) testing for Alzheimer's disease (AD). We explored caregivers' perspectives, by combining an online survey (n=107) with a subsequent focus group (n=7). We used descriptive statistics and thematic content analysis to identify common themes in answers to open-ended survey questions and focus group data. Most caregivers (72.0%) favored BBBM for AD diagnosis. Provided with hypothetical scenarios, confidence in a normal result decreased significantly if experienced symptoms were more severe (mild: 78.5%vs. severe: 48.6%). Caregivers' attitudes toward BBBM for screening purposes significantly improved with prospect of treatment (53.3%vs. 92.5%). Concerns toward BBBM testing included treatment unavailability, increased/prolonged distress, and AD-related stigma. Potential benefits were actionability, explanation for symptoms, and opportunities for better care and future treatment. Emerging AD treatment and reduction of AD-related stigma could profoundly increase public interest in BBBM testing for AD. Most informal caregivers would want blood-based biomarker (BBBM) testing for Alzheimer's disease (AD) diagnosis.Perceived (dis)advantages were related to diagnosing AD early.With severe symptoms, there was less confidence in normal BBBM results.Treatment availability would significantly increase interest in BBBM testing for AD.Informal caregivers showed uncertainty regarding the meaning of the term "AD."

Alzheimer’s disease early diagnostic and staging biomarkers revealed by large-scale cerebrospinal fluid and serum proteomic profiling

Amyloid-β, tau pathology, and biomarkers of neurodegeneration make up the core diagnostic biomarkers of Alzheimer disease (AD). However, these proteins represent only a fraction of the complex biological processes underlying AD, and individuals with other brain diseases in which AD pathology is a comorbidity also test positive for these diagnostic biomarkers. More AD-specific early diagnostic and disease staging biomarkers are needed. In this study, we performed tandem mass tag proteomic analysis of paired cerebrospinal fluid (CSF) and serum samples in a discovery cohort comprising 98 participants. Candidate biomarkers were validated by parallel reaction monitoring-based targeted proteomic assays in an independent multicenter cohort comprising 288 participants. We quantified 3,238 CSF and 1,702 serum proteins in the discovery cohort, identifying 171 and 860 CSF proteins and 37 and 323 serum proteins as potential early diagnostic and staging biomarkers, respectively. In the validation cohort, 58 and 21 CSF proteins, as well as 12 and 18 serum proteins, were verified as early diagnostic and staging biomarkers, respectively. Separate 19-protein CSF and an 8-protein serum biomarker panels were built by machine learning to accurately classify mild cognitive impairment (MCI) due to AD from normal cognition with areas under the curve of 0.984 and 0.881, respectively. The 19-protein CSF biomarker panel also effectively discriminated patients with MCI due to AD from patients with other neurodegenerative diseases. Moreover, we identified 21 CSF and 18 serum stage-associated proteins reflecting AD stages. Our findings provide a foundation for developing blood-based tests for AD screening and staging in clinical practice.

Clinical Biofluid Assays for Prostate Cancer.

This mini review summarizes the currently available clinical biofluid assays for PCa. The second most prevalent cancer worldwide is PCa. PCa is a heterogeneous disease, with a large percentage of prostate tumors being indolent, and with a relatively slow metastatic potential. However, due to the high case numbers, the absolute number of PCa-related deaths is still high. In fact, it causes the second highest number of cancer deaths in American men. As a first step for the diagnosis of PCa, the PSA test has been widely used. However, it has low specificity, which results in a high number of false positives leading to overdiagnosis and overtreatment. Newer derivatives of the original PSA test, including the Food and Drug Administration (FDA)-approved 4K (four kallikreins) and the PHI (Prostate Health Index) blood tests, have higher specificities. Tissue-based PCa tests are problematic as biopsies are invasive and have limited accuracy due to prostate tumor heterogeneity. Liquid biopsies offer a minimally or non-invasive choice for the patients, while providing a more representative reflection of the spatial heterogeneity in the prostate. In addition to the abovementioned blood-based tests, urine is a promising source of PCa biomarkers, offering a supplementary avenue for early detection and improved tumor classification. Four urine-based PCa tests are either FDA- or CLIA-approved: PCA3 (PROGENSA), ExoDX Prostate Intelliscore, MiPS, and SelectMDx. We will discuss these urine-based, as well as the blood-based, clinical PCa tests in more detail. We also briefly discuss a few promising biofluid marker candidates (DNA methylation, micro-RNAs) which are not in clinical application. As no single assay is perfect, we envision that a combination of biomarkers, together with imaging, will become the preferred practice.

"I was screaming hallelujah": Patient and provider perceptions of blood-based testing for colorectal cancer screening.

Blood-based tests for colorectal cancer (CRC) screening can offer many advantages over stool-based tests such as FIT. Yet, we know little about patients' and providers' perceptions of this type of test. We report findings from a qualitative study comparing patient and provider perceptions of blood-based testing for CRC screening. Patient participants were aged 45-75 years and members of a large, integrated health system. Participants were mailed, but did not complete, a FIT through an organized FIT-screening program and were scheduled for a health-care encounter at any of nine clinical sites. Participants were consented to complete a blood draw. We used purposive sampling to select and recruit patients (who did and did not complete the blood test) and providers/specialists who would be involved in offering the blood test to patients or explaining results. We administered telephone interviews using a semi-structured interview guide and recorded and transcribed all interviews, then coded and analyzed content. We interviewed 15 patients (11 completed and 4 did not complete the blood test) and 5 providers (3 primary care providers, one gastroenterologist (GI), and one GI medical assistant). Patients were enthusiastic about completing a blood test, citing the simplicity, ease, convenience, and high perceived accuracy of the test. Providers were also receptive to a blood-based option, if adequate test performance could be achieved and if they have information that informs patients about the pros and cons of blood-based screening versus other screening tests. Patients and providers were willing and enthusiastic about blood-based CRC screening tests. Future research focusing on performance and communication is needed.

Urine-based point-of-care testing for factor-Xa-inhibitors in acute ischemic stroke patients: a feasibility study.

Direct oral anticoagulants (DOACs) have become widely used in clinical practice for preventing thromboembolic events. Point-of-care testing methods, particularly those based on urine samples, offer a promising approach for rapid and accurate assessment of DOAC presence. This pilot study aims to evaluate the utility of a urine-based DOAC dipstick test as a point-of-care tool for identifying DOAB presence in acute ischemic stroke (AIS) or transient ischemic attack (TIA) patients. This prospective pilot study included patients with AIS/TIA eligible for DOAC-measurement. After exclusion of 3 patients, 23 patients with DOAC-intake (DOAC group; factor-Xa-inhibitors; n = 23) and 21 patients without DOAC-intake (control-group) remained for analyses. The urine-based DOAC dipstick test and parallel blood-based specific DOAC-level assessment were performed in all patients. Time-intervals of sampling urine/blood sampling and result of DOAC-test were recorded to analyze a potential time benefit based on dipstick evaluation. The urine-based DOAC dipstick test demonstrated high sensitivity (100%) and specificity (100%), correctly identifying all patients with anticoagulatory activity due to DOAC intake (i.e., anti-Xalevel ≥30 ng/mL). Moreover, the visual readout of the test provided semiquantitative information on drug-specific anti-Xa levels, showing a sensitivity of 83% and specificity of 93% to detect anti-Xa levels ≥120 ng/mL. The dipstick test exhibited a median time-benefit of 2:25 h compared to standard blood-based DOAC-level testing. The results of this pilot study underline the efficacy of urine-based point-of-care testing as a rapid and reliable method for assessing DOAC presence in patients with acute ischemic stroke. The value of this tool for clinical decision-making in stroke management needs to be established in future trials.Clinical Trial Registration: Clinicaltrails.org identifier [NCT06037200].

S82 New Blood-Based Test, 7-Alpha-Hydroxy-4-Cholesten-3-One (7AlphaC4), for Bile Acid Malabsorption in Patients With Inflammatory Bowel Disease or Unspecified Diarrhea

S82 New Blood-Based Test, 7-Alpha-Hydroxy-4-Cholesten-3-One (7AlphaC4), for Bile Acid Malabsorption in Patients With Inflammatory Bowel Disease or Unspecified Diarrhea

Developing Topics.

Blood-based biomarker testing (BBT) to detect amyloid-beta and tau is becoming part of dementia care, with likely future use in asymptomatic populations. Little is known about older adults' awareness of and experiences with BBT, or their perceptions of its potential benefits, risks, and limitations. We analyzed data from the March 2023 NPHA, a recurring nationally representative web and telephone survey of community-dwelling US adults aged 50-80. For this substudy, respondents aged 65-80 were provided a brief definition of BBT for AD and asked about: 1) their familiarity and experiences with BBT, 2) perceptions of its pros and cons, and 3) their likely responses if they tested positive. For comparative purposes, a parallel set of questions was posed about cognitive screening. Chi-square analyses assessed differences in responses to the two types of testing (BBT vs. cognitive screening), as well as demographic differences in responses to items regarding BBT (significance level p < .05). Of 1,296 respondents, 19% said they were at least somewhat familiar with BBT, with 0.6% reporting having undergone BBT. Overall, respondents were more likely to endorse test pros than cons (e.g., 76% said BBT could be useful to inform medical care or advance planning). Women were more likely than men to say they'd respond to a positive BBT result with significant distress (21% vs. 10%) and engagement in brain health behaviors (67% vs. 56%), with men more likely to endorse concerns regarding privacy of test results (38% vs. 27%). Overall, BBT beliefs were similar to those about cognitive screening, although respondents were less likely to agree that BBT should be offered annually to all older adults (51% vs. 60%) and more likely to believe a positive test result would mean they'd be likely to develop AD (74% vs. 65%). Most US older adults are not currently familiar with blood biomarker testing for AD but view it as potentially useful for informing medical care and health behaviors to reduce AD risk. Women may respond differently to BBT results than men, with future studies needed to examine the process and impact of disclosing test results.

Abstract C108: Employer-based implementation of Galleri multi-cancer early detection testing to address socioeconomic disparities in receipt of screening

Abstract Background: Multi-cancer early detection (MCED) tests are designed to complement USPSTF-recommended screening to detect many cancers for which no established screening methods exist. Implementing an MCED test as an employee benefit offers an approach to detect cancers for which there is no screening method and to address socioeconomic disparities in receipt of screening. Methods: Galleri, a blood-based MCED test, was implemented in companies with employees in industrial/manufacturing spaces. We approximated educational attainment (≤12 years vs &amp;gt;12 years) as a dichotomous measurement of socioeconomic status (SES). The industrial locations with employees of lower SES were selected based on data from individual companies and focused on diverse employees, low rates of preventive screenings, high healthcare costs, and low health literacy. Enrollment was accomplished through on-site events where consent and blood draws were available, as well as telehealth visits with subsequent blood draws. Results: From October 2021 to May 2023, 812 Galleri MCED tests were administered in a population of industrial employees. Of the participants, 317 (39%) were female and 495 (61%) were male, and the median age was 54 years. A total of 217 (27%) participants were aged 35-49, 531 (65%) were aged 50-64, and 62 (8%) were aged 65-79. Four tests returned a cancer signal detected result with a predicted cancer signal origin of colorectal (n=2), anus (n=1), and breast (n=1). Of the four participants with a cancer signal detected result, three were in the 50-64 age group and one was in the 65-79 age group. The breast cancer diagnosis was confirmed, and follow-up is ongoing in the participants with a cancer sign origin of colorectal and anus. A total of 676 (83%) tests were administered during 9 on-site events and 136 (17%) were obtained by telehealth visits. Factors that were important for taking the Galleri test were onsite events, trusted long-time employees onsite that spoke their language and helped translate the request form, explanation of the test in their native language, and the ability to administer the test without a computer or other digital requirements. Conclusion: MCED testing may be implemented more widely among individuals of lower SES when it is included as an employee benefit with in-person communication by trusted employee messengers and by limiting digital requirements. Supporting the unique needs of individuals before administering an MCED test and those with a cancer signal detected result are important steps for improving access and achieving diagnostic resolution. Citation Format: Ahmedin Jamal, Robert Winn, William Cance, Tim Johnson, Wayne Lilyestrom. Employer-based implementation of Galleri multi-cancer early detection testing to address socioeconomic disparities in receipt of screening [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr C108.

Primary Care Provider Receptivity to Multi-Cancer Early Detection Test Use in Cancer Screening.

Multi-cancer early detection tests (MCEDs) are blood-based tests that detect biomarkers released or induced by cancer cells. If MCED tests are shown to be safe and effective in cancer screening, they are likely to be ordered and managed in primary care. To understand primary care providers' support for and concerns about the implementation and management of MCED testing, the research team developed a cross-sectional survey that was sent to 939 primary care providers (physicians, residents/fellows, and advanced practice providers) in a large academic health system in the greater Philadelphia area. The survey included standard items used to assess provider background characteristics and to measure provider awareness of challenges related to MCED test use (7 items), perceived competence in MCED testing (5 items), and receptivity to MCED test use in the future (4 items). A total of 351 (37.4%) primary care providers completed the survey. Among respondents, the awareness of challenges in MCED testing (mean = 3.95, sd = 0.64), perceived competence (3.67, sd = 0.85), and receptivity to MCED use in practice (mean = 3.62, 0.75) were moderately high. Multiple regression was performed to identify factors associated with receptivity to MCED testing. We found that provider number of years in practice (DATA), awareness of challenges related to MCED testing (DATA), and perceived competence in MCED test use (DATA) were positively and significantly associated with receptivity to MCED test use in practice. An exploratory factor analysis extracted two components: receptivity to MCEDs and awareness of challenges. Surprisingly, these factors had a positive correlation (r = 0.124, p = 0.024). Providers' perceived competence in using MCED tests and providers' experience level were significantly associated with receptivity to MCED testing. While there was strong agreement with potential challenges to implementing MCEDs, PCPs were generally receptive to using MCEDs in cancer screening. Keeping PCPs updated on the evolving knowledge of MCEDs is likely critical to building receptivity to MCED testing.

RADAR Trial: MRD Response Adapted Trial for Newly Diagnosed Transplant Eligible Myeloma Patients

Background: Achieving and sustaining minimal disease negativity improves clinical outcomes in newly diagnosed transplant eligible myeloma (NDMM). Outcomes in NDMM are influenced by levels of minimal residual disease (MRD) post therapy and genetic risk by FISH or molecular profiling prior to therapy. Trials exploring response adapted post transplant strategies using MRD as a prognostic tool are going. We provide an update of the current UK-MRA RADAR study. Study Design/Methods: The UK-MRA RADAR study is a national multicentre risk adapted response guided multiarm multistage (MAMS) phase II/III trial which will recruit 1400 patients with NDMM eligible for ASCT. Eligible patients receive induction with 4 cycles of RCyBorD (lenalidomide, cyclophosphamide, bortezomib, dexamethasone), followed by high-dose melphalan and stem cell rescue. Patients with high-risk disease receive Isatuximab in addition to RCyBorD during induction. Genetic risk classification is performed using standard of care FISH testing at local sites. Participants enter the standard or high risk pathway based on presence of atleast two markers: t(4;14), t(14;16), t(14;20), del(17p), del(1p) and gain (1q21). MRD analysis in RADAR uses a multiparametric flow cytometry panel with CD319 and Cd229 used to augment post-isatuximab sample analysis at a central laboratory, with negativity defined at threshold of 10 -5(Figure 1). For standard risk patients, the study addresses two pivotal MRD-related questions: 1) For those with sustained MRD negativity after 12 months of isatuximab maintenance, can treatment be stopped safely to allow patients a treatment-free interval thereby reducing treatment burden? 2) For patients with persistent detectable disease after ASCT, does intensification of consolidation and maintenance therapy augment conversion to MRD negativity compared to lenalidomide maintenance? High risk participants receive intensified consolidation and maintenance regimens post_ASCT aligned to OPTIMUM/MUKnine ( NCT03188172). A further amendment is planned to explore the activity of a BCMA bispecific antibody in high risk patients pre and post transplant. It is hypothesised this will improve both depth (MRD negativity) and ability to sustain response (PFS). Feasibility and benefits of multimodal MRD incorporating imaging and blood-based testing will be tested in the new high risk pathway. In RADAR, we will also gather information on how patients respond to receiving information about their genetic risk assignment and treatment response (MRD). This is a unique opportunity to understand the patients perspective on personalised medicine, which has implications for implementation in clinical care, and future trial design. Trial Progress. RADAR opened to recruitment in May 2021 and is currently recruiting across 87 hospital sites with a further 16 sites in set up. 504 patients have been recruited; 87 are classified as high risk on FISH analysis ( 375 standard risk, 15 unable to determine, 19TBC, 8 withdrawn before FISH analysis). 220 have reached D+100 MRD assessment. Trackable phenotypes were available in 98.2% of patients. Discussion: The RADAR study simultaneously tests escalation and de-escalation strategies, according to disease response, and using MRD to guide post transplant therapy in NDMM patients. Use of central flow cytometry laboratory for MRD has proven feasible in patients to date. Recruitment is on target and outcomes will provide RCT-level evidence for the adaptive use of MRD in treatment allocation and intensification post transplant. The platform design enables adaptation with ability to test new strategies for high risk patients and for standard risk patients who are MRD positive post-transplant. Funding This trial is funded by Cancer Research UK (C9203/A24078), Sanofi Genzyme and Celgene : A BMS company. Sanofi Genzyme and Celgene: A BMS company provide study drug and unrestricted educational grants to support study coordination. This work is also supported by Core Clinical trials unit infrastructure from Cancer Research UK ( C7852/A25447). The funder of the study had no role in study design, data collection, data analysis, data interpretation or writing of the abstract

A Highly Sensitive and Specific Non-Invasive Test through Genome-Wide 5-Hydroxymethylation Mapping for Early Detection of Lung Cancer.

Low-dose computed tomography screening can increase the detection for non-small-cell lung cancer (NSCLC). To improve the diagnostic accuracy of early-stage NSCLC detection, ultrasensitive methods are used to detect cell-free DNA (cfDNA) 5-hydroxymethylcytosine (5hmC) in plasma. Genome-wide 5hmC is profiled in 1990 cfDNA samples collected from patients with non-small cell lung cancer (NSCLC, n=727), healthy controls (HEA, n=1,092), as well as patients with small cell lung cancer (SCLC, n=41), followed by sample randomization, differential analysis, feature selection, and modeling using a machine learning approach. Differentially modified features reflecting tissue origin. A weighted diagnostic model comprised of 105 features is developed to compute a detection score for each individual, which showed an area under the curve (AUC) range of 86.4%-93.1% in the internal and external validation sets for distinguishing lung cancer from HEA controls, significantly outperforming serum biomarkers (p<0.001). The 5hmC-based model detected high-risk pulmonary nodules (AUC: 82%)and lung cancer of different subtypes with high accuracy as well. A highly sensitive and specific blood-based test is developed for detecting lung cancer. The 5hmC biomarkers in cfDNA offer a promising blood-based test for lung cancer.

Abstract 13312: Statin Signature: Using Proteomics to Detect Pharmacological Fingerprints

Introduction: Lowering low-density lipoprotein cholesterol with statin therapy is a primary strategy for reducing cardiovascular morbidity and mortality. Yet, adherence to and persistence with statin medication is generally low, complicating the ability to evaluate whether treatment is effective. Hypothesis: Statin treatment may yield significant differences in abundances of proteins detectable in blood samples. Using machine learning and high-throughput proteomics, a blood-based biomarker test can be developed to assess statin medication compliance and demonstrate drug fingerprinting useful for clinical trials. Methods: Using modified-aptamer proteomics technology, SomaScan® assay v4.0, we assessed ∼5,000 proteins in 8,395 EDTA plasma samples from individuals aged 29-64 at visit 1 of the Fenland study, totaling ∼42 million protein measurements. A total of 305 individuals (3.6%) reported active statin medication use at this study visit. Predicted statin use was modeled with protein measurements using machine learning methods in 70% of Fenland as a training dataset. A hold-out dataset was used to assess model performance. A predictive model using elastic net logistic regression was optimized based on AUC and robustness to assay noise and sample handling conditions to detect a signature of statin usage. Results: A total of 839 proteins differed significantly between the ‘active statin’ and ‘no statin’ use groups in univariate analysis (FDR &lt;0.01). Eight of the top 50 significant proteins have known mechanistic associations with statin pharmacology, including HMGCS1, PCSK9, and APOB. A six-protein model was developed with an AUC of 0.91 (sensitivity=0.82, specificity=0.88) and 0.90 (sensitivity=0.80, specificity=0.87) on the training and hold-out datasets, respectively, to predict whether a statin signature is present or not. Conclusions: We successfully developed a blood-based protein-only model that detects mechanistically-relevant protein changes to predict active statin use in adults. The protein model could compliment self-reported medication status in clinical trials and in healthcare.

Methylation Biology of a Blood-Based MDS Risk Stratification Test

Background: Myelodysplastic syndromes (MDS) are a heterogeneous group of myeloid malignancies associated with a myriad of deleterious outcomes and a 5-year relative survival of 37%. MDS risk stratification is key for optimal treatment decisions. We previously demonstrated that methylation-based markers may help stratify MDS risk and achieved comparable performance relative to IPSS-R (the Revised International Prognostic Scoring System) by assessing the risk prediction ability of a classifier trained with features from either Bone Marrow (BM) whole-genome bisulfite sequencing (WGBS) or serum targeted methylation (TM) sequencing. Here, we elucidate the biological underpinnings of the methylation-based classifier and explore the survival stratification performance of our previously reported classifier. Methods: Utilizing datasets from BM WGBS and matched Serum TM sequencing of 127 patients with MDS (N=104) and secondary AML (N=23), we delineated the features used by the classifier by identifying differentially methylated regions (DMRs) that distinguished patients with overall survival of &amp;gt;3 years from those with &amp;lt;3 years. Our approach also included a functional enrichment and driver gene analysis associated with these DMRs, as well as cluster analysis across patients. We performed further evaluations of the survival outcomes of our BM WGBS and matched Serum TM prognostic classifier using concordance indices and log-rank tests. Results: Our analysis revealed 7,742 DMRs in BM WGBS and 14,093 DMRs in the Serum TM that significantly separated the long and short-term survival groups. Unsupervised hierarchical clustering of differential methylation patterns in both BM WGBS and Serum TM highlighted three distinctive subgroups of samples: short-term survivors, long-term survivors, and a group with intermediate survival outcomes. Notably, the short-term survivor group exhibited extensive hypermethylation across a majority of DMRs, which were linked to key biological pathways including calcium signaling, cAMP, MAPK, Rap1, and PI3K-Akt. Enrichment analysis of the BM WGBS DMRs between individuals with &amp;lt;3 and &amp;gt;3 years of survival underscored the differential hypermethylation of promoters, CpG islands, and CpG shores in association with worse survival outcomes. Our analysis of BM WGBS DMR driver genes via Hypergeometric Optimization of Motif EnRichment (HOMER) revealed potential contributors to differential survival outcomes, including known genes associated with MDS/AML, such as EWS/FLI-1, ERG, Pu.1, and RUNX1. Both pathway and driver gene analysis recapitulated previously known drivers of MDS to AML progression. The methylation classifier achieved comparable risk stratification performance for both BM WGBS comparing with IPSS-R (C-index: 0.69 [95% CI: 0.61-0.77] for methylation vs 0.71 [95% CI: 0.64-0.77] for IPSS-R) and Serum TM (C-index: 0.68 [95% CI: 0.60-0.75] for methylation vs. 0.70 [95% CI: 0.63-0.78] for IPSS-R). At a specificity threshold of 0.8, both BM WGBS and Serum TM prognostic classifiers were able to stratify between predicted short and predicted long survivors (BM WGBS HR: 2.83, p&amp;lt;0.0001; Serum TM HR: 3.01, p=0.0008). Conclusions: Our findings generated biological insights into the methylation-based risk stratification of MDS, shedding light on the specific genomic features and biological pathways that underlie these methylation patterns. We also demonstrated that methylation-based MDS risk stratification performs comparably with IPSS-R. These insights not only expand our understanding of the complexity of MDS, but also reinforce the potential of methylation-based sequencing as a viable, possibly less-invasive, alternative for MDS risk stratification compared to traditional IPSS-R methods.

Measurable Residual Disease Status By Clonotypic Mass Spectrometry with Easym Assay Predicts Outcomes Following Autologous Hematopoietic Cell Transplant in Multiple Myeloma

Bone marrow (BM)-based measurable residual disease (MRD) has been established as one of the most important dynamic prognostic markers in multiple myeloma (MM). However, the necessity of bone marrow biopsies limits the feasibility of frequent MRD monitoring. Consequently, there is an urgent unmet need for peripheral blood-based MRD testing for serial monitoring of disease response to allow tailored therapy for patients achieving deep remissions. Quantification of myeloma (M)-protein using mass spectrometry (MS) is a promising approach for peripheral blood-based MRD monitoring due to its exceptional analytical sensitivity. Prior studies have examined the use of MALDI-TOF-based methods, which relies on the mass distribution of intact immunoglobulins light chains and is approximately 1-log more sensitive than traditional testing. However, recent advances in MS technology have allowed determination and tracking of a “clonotypic” MS signature in the peripheral blood which is highly sensitive and patient-specific (Liyasova et al, CCR 2021). Prior reports have demonstrated the feasibility of this approach, but data supporting the association of blood-based clonotypic MS MRD with clinical outcomes is currently lacking. Consequently, we performed a large retrospective analysis of patients enrolled in our institutional MM tissue bank to determine the association of clinical outcomes with clonotypic MS-based MRD testing (EasyM, Rapid Novor, Kitchener, ON). We identified patients in our institutional tissue bank who met the following criteria: 1) diagnosis of MM, 2) underwent autologous hematopoietic cell transplant (AHCT), 3) M-protein ≥0.2 g/dL by serum protein electrophoresis (SPEP) or &amp;gt;20 mg/dL (light chain) at diagnosis, 4) had no detectable M-protein by SPEP at day +100 and 5) had adequate samples for analysis collected at day +100 after AHCT. Patients were included regardless of M-protein isotype. Baseline and follow up samples were analyzed by Rapid Novor without access to the clinical outcomes. Percent residual EasyM at day +100, in respect to baseline EasyM, was used as the independent variable to predict Progression-free survival (PFS). 95 patients were included in the analysis. Median age was 63, 88% were White and 61% were male. 64% were IgG, 20% IgA and 16% were with light chain (LC) MM. 26%, 62% and 12% were R-ISS stage I, II and III, respectively. High-risk cytogenetics were present in 32%. 97% had received proteasome inhibitors, 89% received immunodulatory agents and 13% anti-CD38 antibodies prior to AHCT. The median year of transplant was 2018 (range: 2008 - 2022). 93% patients received AHCT as part of frontline therapy. 66% were in CR or better following AHCT. 95% received maintenance after AHCT. 9 patients had non-quantifiable EasyM at follow up and were excluded from derivation of the MRD definition. Of the remaining 86, patients with IgA/LC and IgG disease had significant different percent residual EasyM following AHCT (median: 0.19% vs. 1.00%, p &amp;lt; 0.001). A cutoff of 1.036% residual EasyM was derived for IgG and 0.048% residual EasyM for IgA/LC patients was determined to fit the PFS data best, and based on these cutoffs, 41 patients (47%) were MRD negative by EasyM. The incidence of MRD negativity between IgG and IgA/LC was similar (55% vs. 32%). MRD positivity by EasyM was a strong predictor of PFS following AHCT (Figure 1) (HR: 2.249, p = 0.017). The median PFS in MRD positive patients was 3.4 years versus not reached in MRD negative patients (log rank: p = 0.014) (Figure 1). Our study is the first, to our knowledge, to demonstrate the clinical utility of peripheral blood-based clonotypic mass spectrometry to predict outcomes for patients with MM. Notably, our results suggest that different cutoffs should be employed for IgG and IgA/LC myeloma if drawn at day +100 after transplant. This is possibly due to the differing half-lives of these molecules. Significant additional questions remain, including the utility of ongoing monitoring at multiple time points and the optimal time post-AHCT to assess for MRD, especially in patients with IgG myeloma. Additionally, these findings require prospective validation in an independent cohort of patients to demonstrate wider applicability.

Lineage specific extracellular vesicle-associated protein biomarkers for the early detection of high grade serous ovarian cancer

High grade serous ovarian carcinoma (HGSOC) accounts for ~ 70% of ovarian cancer cases. Non-invasive, highly specific blood-based tests for pre-symptomatic screening in women are crucial to reducing the mortality associated with this disease. Since most HGSOCs typically arise from the fallopian tubes (FT), our biomarker search focused on proteins found on the surface of extracellular vesicles (EVs) released by both FT and HGSOC tissue explants and representative cell lines. Using mass spectrometry, 985 EV proteins (exo-proteins) were identified that comprised the FT/HGSOC EV core proteome. Transmembrane exo-proteins were prioritized because these could serve as antigens for capture and/or detection. With a nano-engineered microfluidic platform, six newly discovered exo-proteins (ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF) plus a known HGSOC associated protein, FOLR1 exhibited classification performance ranging from 85 to 98% in a case–control study using plasma samples representative of early (including stage IA/B) and late stage (stage III) HGSOCs. Furthermore, by a linear combination of IGSF8 and ITGA5 based on logistic regression analysis, we achieved a sensitivity of 80% with 99.8% specificity and a positive predictive value of 13.8%. Importantly, these exo-proteins also can accurately discriminate between ovarian and 12 types of cancers commonly diagnosed in women. Our studies demonstrate that these lineage-associated exo-biomarkers can detect ovarian cancer with high specificity and sensitivity early and potentially while localized to the FT when patient outcomes are more favorable.

Preferences for oral-fluid-based or blood-based HIV self-testing and provider-delivered testing: an observational study among different populations in Zimbabwe

BackgroundThere is limited data on client preferences for different HIV self-testing (HIVST) and provider-delivered testing options and associated factors. We explored client preferences for oral-fluid-based self-testing (OFBST), blood-based self-testing (BBST) and provider-delivered blood-based testing (PDBBT) among different populations.MethodsAt clinics providing HIV testing services to general populations (1 urban, 1 rural clinic), men seeking voluntary medical male circumcision (VMMC, 1 clinic), and female sex workers (FSW, 1 clinic), clients had the option to test using OFBST, BBST or PDBBT. A pre-test questionnaire collected information on demographics and testing history. Two weeks after collecting a self-test kit, participants responded to a questionnaire. We used logistic regression to determine predictors of choices. We also conducted 20 in-depth interviews to contextualise quantitative findings.ResultsMay to June 2019, we recruited 1244 participants of whom 249 (20%), 251 (20%), 244 (20%) and 500 (40%) were attending urban general, rural, VMMC and FSW clinics, respectively. Half (n = 619, 50%) chose OFBST, 440 (35%) and 185 (15%) chose BBST and PDBBT, respectively. In multivariable analysis comparing those choosing HIVST (OFBST and BBST combined) versus not, those who had never married aOR 0.57 (95% CI 0.34–0.93) and those previously married aOR0.56 (0.34–0.93) were less likely versus married participants to choose HIVST. HIVST preference increased with education, aOR 2.00 (1.28–3.13), 2.55 (1.28–5.07), 2.76 (1.48–5.14) for ordinary, advanced and tertiary education, respectively versus none/primary education. HIVST preference decreased with age aOR 0.97 (0.96–0.99). Urban participants were more likely than rural ones to choose HIVST, aOR 9.77 (5.47–17.41), 3.38 (2.03–5.62) and 2.23 (1.38–3.61) for FSW, urban general and VMMC clients, respectively. Comparing those choosing OFBST with those choosing BBST, less literate participants were less likely to choose oral fluid tests, aOR 0.29 (0.09–0.92).ConclusionsMost testing clients opted for OFBST, followed by BBST and lastly, PDBBT. Those who self-assessed as less healthy were more likely to opt for PDBBT which likely facilitated linkage. Results show importance of continued provision of all strategies in order to meet needs of different populations, and may be useful to inform both HIVST kit stock projections and tailoring of HIVST programs to meet the needs of different populations.

Serum methylation of GALNT9, UPF3A, WARS, and LDB2 as noninvasive biomarkers for the early detection of colorectal cancer and advanced adenomas

BackgroundEarly detection has proven to be the most effective strategy to reduce the incidence and mortality of colorectal cancer (CRC). Nevertheless, most current screening programs suffer from low participation rates. A blood test may improve both the adherence to screening and the selection to colonoscopy. In this study, we conducted a serum-based discovery and validation of cfDNA methylation biomarkers for CRC screening in a multicenter cohort of 433 serum samples including healthy controls, benign pathologies, advanced adenomas (AA), and CRC.ResultsFirst, we performed an epigenome-wide methylation analysis with the MethylationEPIC array using a sample pooling approach, followed by a robust prioritization of candidate biomarkers for the detection of advanced neoplasia (AN: AA and CRC). Then, candidate biomarkers were validated by pyrosequencing in independent individual cfDNA samples. We report GALNT9, UPF3A, WARS, and LDB2 as new noninvasive biomarkers for the early detection of AN. The combination of GALNT9/UPF3A by logistic regression discriminated AN with 78.8% sensitivity and 100% specificity, outperforming the commonly used fecal immunochemical test and the methylated SEPT9 blood test.ConclusionsOverall, this study highlights the utility of cfDNA methylation for CRC screening. Our results suggest that the combination methylated GALNT9/UPF3A has the potential to serve as a highly specific and sensitive blood-based test for screening and early detection of CRC.