Liquid biopsies using circulating tumor DNA for surveillance of gastrointestinal cancers in Hispanics: first real-world data report

This study characterizes in vivo glymphatic system alterations in spinocerebellar ataxia (SCA) using a structure-environment-function multimodal MRI framework and explores subtype-specific signatures and longitudinal progression. Twenty genetically confirmed SCA patients (SCA1 = 1, SCA2 = 11, SCA3 = 6, SCA7 = 2) and 23 matched healthy controls underwent MRI across two scanners. The framework included structural (perivascular space volume fraction, pPVS; choroid plexus volume, CPV), environmental (free water, FW), functional (DTI-ALPS index), and microstructural (fractional anisotropy, FA) metrics. Data were harmonized across sites. Cross-sectional, subtype, and longitudinal analyses were performed. SCA patients demonstrated significantly enlarged subcortical pPVS, elevated FW, and reduced FA compared to controls (all surviving FDR correction, q = 0.05), while CPV/rCPV showed non-significant trends and the ALPS index showed no group difference. Subtype analyses revealed higher white matter and total pPVS in SCA3 versus SCA2 (surviving FDR correction), but FW differences did not survive correction. Longitudinally, the SCA2 subset exhibited significant FA decline over time (p < 0.001), with robust group effects on FW and WM pPVS. Within a structure-environment-function framework, SCA exhibits prominent glymphatic-related abnormalities in perivascular and interstitial compartments, with preserved ALPS index. Distinct imaging signatures of SCA2 and SCA3 suggest divergent pathophysiologies. FW and FA emerge as promising complementary biomarkers for monitoring disease burden and progression in future trials.

A multiple sclerosis review for the primary care physician.

Clonotypic peptide mass spectrometry to monitor m-protein reduction in patients with relapsed/refractory multiple myeloma from ikema Study

Smartphone overdependence among South Korean adolescents, affecting nearly 40%, poses a growing public health concern, with usage patterns varying by regional context. Leveraging conceptually informed AI/ML models, this study (1) develops a high-performing low-risk screening tool to monitor disease burden, (2) leverages AI/ML to explore psychologically meaningful constructs, and (3) provides place-based policy implication profiles to inform public health policy. This study uses data from 1873 adolescents in the 2023 Smartphone Overdependence Survey by the National Information Society Agency (NISA) in South Korea. Across the sample, the adolescents were about 14 years old (SD = 2.4) and equally distributed by sex (48.1% male). We then conceptually selected 131 features across two domains and 10 identified constructs. A nested modeling approach identified a low-risk screening tool using 59 features that achieved strong predictive accuracy (AUC = 81.5%), with Smartphone Use Case features contributing approximately 20% to performance. Construct-specific models confirmed the importance of Smartphone Use Cases, Perceived Digital Competence and Risk, and Consequences and Dependence (AUC range: 80.6–89.1%) and uncovered cognitive patterns warranting further study. Place-stratified analysis revealed substantial regional variation in model performance (AUC range: 71.4–91.1%) and distinct local feature importance. Overall, this study demonstrated the value of integrating conceptual frameworks with AI/ML to detect adolescent smartphone overdependence, offering novel approaches to monitoring disease burden, advancing construct-level insights, and providing targeted place-based public health policy recommendations within the South Korean context.

Background Hereditary transthyretin amyloidosis with polyneuropathy (ATTRv-PN) is often associated with neuropathic pain (NP), involving developing mechanisms across different nerve fibres. This study aimed to explore the relationship between NP intensity and clinical/neurophysiological measures in symptomatic ATTR V30M (p.V50M)-PN patients. Methods We included 106 symptomatic patients (46 males; mean age 47.5 ± 13.2 years). NP severity was classified using three pain-related items from the Norfolk QOL-DN, generating three groups: no pain, mild pain, and moderate-to-severe pain. Clinical and neurophysiological assessments included the Neuropathy Impairment Score (NIS), nerve conduction studies (sural SNAP, peroneal CMAP), electrochemical skin conductance (ESC), sympathetic skin response (SSR), and Quantitative Sensory Testing (QST). Statistical analyses included non-parametric tests and ordinal logistic regression. Results Patients with NP had significantly higher NIS scores and reduced sural/peroneal amplitudes and ESC values. However, only NIS was significantly associated with NP intensity (OR = 1.062, 95% CI: 1.008–1.119, p = .024). Subscore analysis showed the sensory component as the main driver (OR = 1.205, p = .015). QST variables differed by pain presence but not intensity. Conclusion NIS, especially its sensory subscore, is a robust predictor of NP severity in ATTRv-PN. These findings support its utility in monitoring disease burden and guiding management.

Background/Objectives: In patients with metastatic castration-resistant prostate cancer (mCRPC) and osseous metastases only, 223Radium therapy represents a valuable therapeutic option. Bone scintigraphy (BS) is typically performed to assess metastasis load, with the BS-derived automated bone scan index (aBSI) used for response assessment. This study aimed to evaluate the prognostic value of aBSI in patients receiving three or six cycles of 223Ra therapy. Methods: We included patients that were diagnosed with extensive osseous tumor load on BS, had no visceral or nodal metastases, had undergone 223Ra therapy. The aBSI prior to and following three or six cycles of therapy, total tumor volume (TTV), SUVmax, and overall survival were analyzed. Results: This study included 49 mCRPC patients (mean age: 70 ± 9 years) with 42 (85.7%) receiving six and 7 (14.3%) receiving three cycles. After three cycles, the mean aBSI (p = 0.369), TTV (p = 0.902), and SUVmax (p = 0.149) remained unchanged. After six cycles, the mean aBSI (p = 0.247) and TTV (p = 0.784) were unchanged, while SUVmax decreased significantly (p = 0.001). The aBSI did not significantly correlate with the mean aBSI (six cycles: χ2 = 1.823, p = 0.177; three cycles: χ2 = 0.308, p = 0.579). Conclusions: Although quantitative changes in TTV and aBSI did not significantly correlate with each other, their respective absolute values consistently indicated stable disease burden under therapy. This highlights its potential as a useful tool for monitoring disease burden while indicating that aBSI alone is insufficient for predicting overall survival.

1073 Background: The combination of CDK4/6 inhibitor (CDK4/6i) and endocrine therapy (ET) is the standard first-line treatment for patients with hormone receptor-positive/HER2-negative (HR+/HER2-) metastatic breast cancer (MBC). However, it exhibits highly variable efficacy, with some cancers progressing within 3–6 months while many others achieve durable and potentially indefinite complete responses (CRs). While pharmacologic strategies to escalate or deescalate this therapy exist, diagnostic tools to identify the patients who would benefit from each approach are needed. Ultrasenstive ctDNA offers the potential to assess disease burden dynamically and with more precision. In this study, we evaluate the validity of an ultrasensitive assay capable of detecting ctDNA levels in the parts per million range for monitoring patients with HR+/HER2- MBC. Methods: Patients from the MSK-LINC prospective ctDNA monitoring study, who received CDK4/6i+ET for HR+/HER2- MBC were included in the study. MRD monitoring was performed using personalized tumor-informed panels designed from whole genome sequencing (WGS) of matched tumor and normal specimens to identify up to 2,000 somatic alterations for each patient using the Precise MRD assay (Myriad Genetics). Results were reported as an overall ctDNA detection status and a quantitative tumor fraction. Results: 29 patients with HR+/HER2- MBC (8 de novo , 21 recurrent) were included in this ongoing study. The median progression-free survival (PFS) was 48.8 months (range 2.6 – 78.5) with 17/29 of patients experiencing disease progression. ctDNA panels were successfully designed for all cases, and 140/146 (95.9%) plasma samples passed QC. All pre-treatment samples had detectable ctDNA with a median tumor fraction of 1.4% (range 0.00093%, 14.0%). An early decrease in ctDNA levels, &gt; 50% reduction from baseline or levels &lt; 0.01% in the second sample collected within 3 months, was significantly associated with longer PFS (p &lt; 0.001). We focused on 7 patients who achieved radiographic CR all with PFS &gt; 3y. Notably, 3 patients had continued to have ultra low levels of ctDNA (median: 0.0086%, range 0.00032%, 0.11%), indicating stable viable micrometastatic disease below the threshold of imaging, effectively controlled by treatment. In contrast, 4 patients also achieved molecular CR (mCR) defined as sustained undetectable ctDNA suggesting that metastatic disease was either eradicated or rendered dormant without significant cell turnover. Conclusions: Ultrasensitive ctDNA monitoring is a promising tool for monitoring disease burden and treatment response. Our results highlight the ability of ctDNA to distinguish between stable molecular disease vs. mCR, highlighting the potential of ctDNA as a biomarker for tailoring treatment strategies in patients who achieve outstanding clinical responses.

Abstract Background: Liquid biopsies in advanced solid tumors can provide a unique noninvasive approach to monitor disease burden over time. Detection and capturing circulating tumor cells (CTCs) in melanoma patients have faced many challenges and limitations. In our study, we use our novel, high-sensitivity, CTC capturing technology to assess numerical heterogeneity of serially collected CTCs in advanced stage melanoma patients undergoing systemic treatment and correlate CTC dynamics with tumor response and risk of disease progression. Methods: We utilize a unique microfluidic exclusion-based sample preparation (ESP) technology at the University of Wisconsin (Madison) to isolate CTCs from patients with stage III/IV melanoma. Capture specificity of antibodies against melanoma associated proteins, NG2 (MCSP) and CD146 (MCAM) were used. We prospectively collected plasma samples from patients and evaluated the quantitative and qualitative change in numerical CTCs at baseline to 1-3 months after the start of systemic therapy. Based on CTC dynamics, a logistic regression model was used to evaluate the odds of an objective response (partial response and complete response per RECIST v1.1) and a cox proportional hazard model was used to investigate its effect on progression free survival (PFS). Results: 35 patients were evaluated and longitudinally followed. Patients were treated with immune checkpoint inhibitors (29), BRAF/MEK targeted therapy (4), or tebentafusp-tbn (2). Median follow up was 13.1 months. A range of 0 and 531 CTCs were detected at baseline (i.e. before start of treatment). Patients with an objective response had a mean slope of -22.2 CTCs/month and patients with stable disease or progressive disease had a mean slope of +10.4 CTCs/month (Wilcox p=0.0008). A qualitative decrease in CTC count was associated with an objective response (OR 6.50, 95% CI 1.80-41.57, p=0.0004) and a longer PFS (HR 0.38, 95% CI 0.15-0.91, p=0.031) compared to an increase in CTC count from baseline to 1-3 months after starting systemic therapy. Discussion: Our study demonstrates the prognostic value of CTC enumeration in advanced stage melanoma patients. Using our novel ESP technology, we are able to successfully capture CTCs and correlate CTC dynamics with clinical outcomes, including objective response and PFS. A larger sample cohort is planned to validate its utility in predicting treatment outcomes in clinical practice. Citation Format: Vincent T. Ma, Yeonhee Park, Matthew C. Mannino, Jennifer L. Schehr, Alexander Birbrair, Joshua M. Lang, George S. Zhao. Correlating circulating tumor cell dynamics with clinical outcomes in patients with advanced stage melanoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1984.

In January 2021, the Gulf Health Council (GHC), established the Gulf Centre for Disease Prevention and Control (Gulf CDC) in Riyadh, marking a pivotal step in harmonizing health strategies, enhancing knowledge generation, and promoting evidence-based approaches to both communicable (CD) and non-communicable diseases (NCD). The Gulf CDC's mission includes consolidating the region's health information systems, crucial for monitoring disease burden and shaping effective public health policies. An initial assessment of public health surveillance systems across the Gulf Cooperation Council (GCC) member states was conducted by the Gulf CDC. This revealed strong national surveillance coverage of CDs but identified areas for improvement, particularly in data quality and representativeness. These findings informed the development of the Gulf CDC's health information strategy and confirmed the need for a regional surveillance system. Prior to the introduction of this system, senior experts in this field from all GCC member states were surveyed and a consensus process launched to agree on the first steps. This led to the strategic selection of a small number of priority communicable and non-communicable diseases for the pilot phase of the system. The final agreed list of diseases and conditions for the pilot are the CDs: acute respiratory infection (ARI), endemic dengue, brucellosis, measles and pulmonary tuberculosis together with the NCDs: cancer (registry) and road traffic injuries. The initiative will showcase the potential benefits of regional collaboration to improve health outcomes and will ultimately also contribute to global health security efforts.

Disease surveillance data are used for monitoring and understanding disease burden, which provides valuable information in allocating health programme resources. Statistical methods play an important role in estimating disease burden since disease surveillance systems are prone to undercounting. This paper is motivated by the challenge of estimating mortality associated with respiratory infections (e.g. influenza and COVID-19) that are not ascertained from death certificates. We propose a Bayesian spatial-temporal model incorporating measures of infection activity to estimate excess deaths. Particularly, the inclusion of time-varying coefficients allows us to better characterize associations between infection activity and mortality counts time series. Software to implement this method is available in the R package NBRegAD. Applying our modelling framework to weekly state-wide COVID-19 data in the US from 8 March 2020 to 3 July 2022, we identified temporal and spatial differences in excess deaths between different age groups. We estimated the total number of COVID-19 deaths in the US to be 1,168,481 (95% CI: 1,148,953 1,187,187) compared to the 1,022,147 from using only death certificate information. The analysis also suggests that the most severe undercounting was in the 18-49 years age group with an estimated underascertainment rate of 0.21 (95% CI: 0.16, 0.25).

e15063 Background: Blood plasma cell-free DNA (cfDNA) testing of cancer patients allows for genomic profiling when tissue sampling is too invasive or of insufficient quality. This approach has demonstrated clinical utility to identify treatment targets, screen for resistance and monitor disease burden. MSK-ACCESS (Memorial Sloan Kettering – Analysis of Circulating cfDNA to Evaluate Somatic Status) is a validated, high sensitivity cfDNA assay employed at MSK to identify biologically actionable tumor alterations in clinical care. SOPHiA GENETICS is developing a decentralized solution of this assay that incorporates major features of MSK-ACCESS such as molecular barcoding, duplex-based variant calling, the inclusion of tumor-informed prior knowledge and identification of somatic alterations through the removal of both germline and clonal hematopoiesis (CH) variants. Here, we present the results of a performance study obtained during product development. Methods: A cohort of 24 plasma cfDNA and matched white blood cell (WBC) DNA samples were collected from patients with solid tumors and processed at MSK according to the validated standard operating procedures and bioinformatic analyses. In parallel, for the same set of materials libraries were constructed at SOPHiA GENETICS using the proprietary CUMIN molecular identifiers, captured with probes targeting the updated MSK-ACCESS v2 set of 146 genes and sequenced on an Illumina NovaSeq 6000. Variants were called using a duplex-aware approach by SOPHiA GENETICS and germline and CH variants were identified and filtered by paired cfDNA – WBC DNA analysis. Accuracy of the decentralized “MSK-ACCESS powered with SOPHiA DDM” solution was assessed through concordance to the orthogonal results obtained by MSK. Results: A total of 104 somatic SNV/Indels were detected with variant allele fractions (VAF) ranging from 0.1% to 97.0% with a median of 5 variants per sample. The positive percent agreement (PPA) for all variants above the limit of detection of the original MSK-ACCESS assay was 98.9% with 99.98% specificity. For the subset of prior-knowledge variants PPA was 95.6% down to 0.1% VAF. A total of additional 59 variants with ≤ 15% VAF were found both in cfDNA and WBC and assigned as CH-derived. Importantly, these occurred not only in CH-associated genes but also in common oncogenes such as BRCA1/2 and ERBB2, highlighting the utility of matched WBC analysis to correctly identify somatic variants. Conclusions: The results demonstrate that the decentralized “MSK-ACCESS powered with SOPHiA DDM” solution exhibits a high degree of agreement to the results achieved by MSK. Further studies will be conducted to expand the analytical performance evaluation.

3049 Background: Identification of minimal residual disease (MRD) with circulating tumor DNA (ctDNA) in pts with early-stage breast cancer holds promise to identify risk of relapse. MSK-LINC is prospective ctDNA plasma analysis of breast cancer pts. This pilot study evaluated the utility of serial ctDNA assessment as a biomarker for monitoring MRD and recurrence prediction in clinical stage II-III breast cancer pts undergoing neoadjuvant chemotherapy (NAC). Methods: 30 pts who underwent NAC across all subtypes were identified from MSK-LINC. The ctDNA analysis was performed at baseline, on-NAC, post-NAC/pre-surgery, within 8 weeks post-surgery, and during follow-up. Personalized ctDNA RaDaR assays were designed using whole exome sequencing data of paired primary tumor and germline samples from each pt. ctDNA levels were quantified as an estimated variant allele fraction (eVAF). Results: ctDNA panels were successfully designed for 29/30 pts (16 Stage II, 13 Stage III), including 6 HR+/HER2-, 12 HER2+, and 11 TNBC, with a median follow up of 4.2 years. The bespoke ctDNA assays targeted a median of 48 variants (21-51), with a median of 43 variants (11-48) passing quality control. A total of 175 plasma samples were analyzed, including 24 baseline and 24 post-surgery. A 100% ctDNA detection rate was observed at baseline in the 24 pts for whom a baseline sample was available (median eVAF 0.33%, range 0.0083% - 8.91%). Pathologic complete response (pCR) was achieved in 11 pts who remained disease free; and of the 18 pts without a pCR, 5 recurred. All patients with a pCR were ctDNA negative post treatment. In 3/5 patients who recurred, MRD detection was achieved, including one patient with persistent ctDNA positivity throughout all timepoints. For the other two pts, ctDNA was first detected in follow-up plasma collected at 4.4 and 9.8 months prior to clinical recurrence. Conclusions: This study demonstrates the potential of ctDNA as a dynamic biomarker for monitoring disease burden in pts with high-risk early-stage breast cancer, highlighting its remarkable sensitivity at baseline and its capability for MRD detection preceding clinical recurrence. These findings suggest the need for further research to fully understand the relationship between ctDNA dynamics during and after NACT with prediction of breast cancer outcomes. ctDNA detection rates in plasma samples across collection timepoints. [Table: see text]

Abstract Pancreatic ductal adenocarcinoma (PDAC) remains a formidable challenge in the realm of oncology, characterized by its aggressive nature and resistance to treatment. Several therapeutic regimens have been shown to extend patient survival, but the majority of the patients become refractory to the treatments in a short period of time. Hence, it is critical to monitor a patient’s response to treatment in a timely manner so that different treatment regimens can be considered promptly. Currently, CA19-9 is the most common blood-based marker being used to monitor disease burden in patients with PDAC. However, 15-20% of patients with PDAC do not have elevated blood CA19-9 levels. In this study, we sought to determine the utility of two circulating extracellular vesicle (EV) based protein biomarkers, ALPPL2 (Alkaline phosphatase, placental-like 2) and THBS2 (Thrombospondin 2), for disease monitoring in patients with PDAC. We first established and optimized EV assays using the ExoViewTM platform for detecting and quantifying the number of ALPPL2+ or THBS2+ EVs in serum samples. We then determined the concentrations of ALPPL2+ or THBS2+ EVs in samples from healthy individuals and longitudinal samples from patients with Stage IV PDAC undergone treatment. The longitudinal samples were from 26 patients of which 16 were CA19-9 secretors (defined as &amp;gt;35 U/ml) and 10 were CA19-9 non-secretors (defined as &amp;lt;35 U/ml) that were treated with various regimens for 4-24 months with monthly blood sample collection and CT scans (a total of 305 samples). We found that the concentrations of ALPPL2+ and THBS2+ EVs are on average 1,737 and 1,113 times higher in PDAC patients than in the healthy controls, respectively. Correlation analysis using the mixed linear model showed that the concentrations of both ALPPL2+ and THBS2+ EVs significantly correlate with changes in tumor size (based on RECIST measurements) in the longitudinal samples of CA19-9 non-secretors or secretors. In CA19-9 non-secretors the correlation p values are 0.003 and 0.006 for ALPPL2+ and THBS2+ EVs, respectively, whereas in CA19-9 secretors, the p values are 0.014 and 0.016 for ALPPL2+ and THBS2+ EVs, respectively. Our data indicates that EV based ALPPL2 and THBS2 could potentially serve as biomarkers for disease monitoring in patients with PDAC. (This work was supported in part by the Dorrance Family Fund and the Flinn Foundation) Citation Format: Kuntal Halder, Gayle Jameson, Erkut Borazanci, Wei Lin, Dereck Cridebring, Daniel Von Hoff, Haiyong Han. Extracellular vesicle based ALPPL2 and THBS2 as biomarkers for disease monitoring in patients with pancreatic ductal adenocarcinoma [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 2497.

Surveillance of incidence and survival of central nervous system tumors is essential to monitor disease burden and epidemiological changes, and to allocate health care resources. Here, we describe glioma incidence and survival trends by histopathology group, age, and sex in the Norwegian population. We included patients with a histologically verified glioma reported to the Cancer Registry of Norway from 2002 to 2021 (N = 7,048). Population size and expected mortality were obtained from Statistics Norway. Cases were followed from diagnosis until death, emigration, or 31 December 2022, whichever came first. We calculated age-standardized incidence rates (ASIR) per 100,000 person-years and age-standardized relative survival (RS). Results: The ASIR for histologically verified gliomas was 7.4 (95% CI: 7.3-7.6) and was higher for males (8.8; 95% CI: 8.5-9.1) than females (6.1; 95% CI: 5.9-6.4). Overall incidence was stable over time. Glioblastoma was the most frequent tumor entity (ASIR = 4.2; 95% CI: 4.1-4.4). Overall, glioma patients had a 1-year RS of 63.6% (95% CI: 62.5-64.8%), and a 5-year RS of 32.8% (95% CI: 31.6-33.9%). Females had slightly better survival than males. For most entities, 1- and 5-year RS improved over time (5-year RS for all gliomas 29.0% (2006) and 33.1% (2021), p < 0.001). Across all tumor types, the RS declined with increasing age at diagnosis. The incidence of gliomas has been stable while patient survival has increased over the past 20 years in Norway. As gliomas represent a heterogeneous group of primary CNS tumors, regular reporting from cancer registries at the histopathology group level is important to monitor disease burden and allocate health care resources in a population.

DNA replication-repair deficiency (RRD) arises from pathogenic variants in the mismatch repair and/or polymerase-proofreading genes. Multiple germline cancer predisposition syndromes in children and young adults, including constitutional mismatch repair deficiency (CMMRD), Lynch, polymerase-proofreading deficiency, and rare digenic syndromes can lead to RRD cancers. The most frequent brain tumors in these children are high-grade gliomas. Embryonal tumors like medulloblastoma have also been described. Lower-grade tumors are reported from cancer surveillance initiatives. The latter has an extremely high rate of malignant transformation. Novel functional assays quantifying the genomic microsatellite indel load have been demonstrated to be highly sensitive and specific for the diagnosis of RRD cancers and children with germline CMMRD. Importantly, RRD brain tumors uniformly harbor high mutation and microsatellite burden. High T-cell infiltration makes these aggressive cancers amenable to immune checkpoint inhibition, irrespective of their germline genetic background. Synergistic combinations are reported to be successful in patients failing checkpoint inhibitor monotherapy. Future directions include the development of innovative approaches to improve immune surveillance for RRD brain cancers. Additionally, the use of novel tools including circulating tumor DNA and quantifying microsatellite indel load over time can be useful to monitor disease burden and treatment responses in patients.

Reduced Subclone Diversity in Clonal Cytopenia of Undetermined Significance Compared to Myelodysplastic Syndrome

Abstract Background Serological surveillance is essential for monitoring disease burden and vaccine uptake at an individual and population level. During the pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), several serological assays were developed and obtained emergency use authorization to detect antibodies after infection. At that time, the need was to differentiate the infected from the naïve population, and these qualitative assays played a critical role in disease management. In the wake of vaccinations, there is a need for the development of quantitative assays. The world health organization (WHO) developed an international standard for quantitation. We performed this study to develop and validate an in-house secondary standard for our multiplex assay based on this WHO standard. Methods We developed a novel multiplex assay for quantifying human IgG antibodies to four different SARS-CoV-2 antigens in human serum or plasma. We have used Luminex® xMAP® technology for this assay and immobilized four recombinant proteins, namely, the receptor-binding domain of S1(RBD), nucleocapsid protein (NP), S1 protein (S1), and trimeric Spike protein (trimer) on internally coded magnetic microspheres. We procured lyophilized WHO quantification standard 20/136 from the National Institute for Biological Standards and Control (NIBSC), which has the arbitrary assignment of 1000 BAU/mL after reconstitution in 0.25 mL. We tested this standard in the range of 10 to 0.01 BAU/mL for the standard curve. We tested NIBSC 20/162 control reagent using this assay for the linearity of dilution. Thirty-seven samples from the NIBSC verification panel were also tested for this evaluation. We also quantified IgG antibodies in 25 samples from vaccinated individuals, ten samples from vaccine breakthrough individuals, 25 samples from PCR-positive individuals, and 75 samples collected before 2019. Results The secondary standard was calibrated using the 20/136 standard. The NIBSC 20/136 and the secondary standard displayed a wide dynamic range of quantitation. The difference in the expected and actual concentrations was less than 20%. Multiple dilutions of the serum or plasma samples were used to get readings within the standard curve range. Excellent linearity was noted at various sample dilutions to get the correct quantification. We observed that vaccinated individuals had a higher concentration of binding antibodies to S1, Trimer, and RBD and were negative for NP antibodies. Conversely, the acute samples from infected individuals collected less than ten days post-positive PCR showed higher antibodies to NP than different spike proteins. The vaccine break-through infection samples showed lower NP antibodies than unvaccinated but infected individuals. Conclusion Our development of a secondary standard calibrated against WHO international standard is vital for quantitatively measuring different SARS-CoV-2 antibodies. A secondary standard can help manufacturers and users to normalize results from various assays and lots over a prolonged period.

The gold standard for monitoring response status in patients with multiple myeloma (MM) is serum and urine protein electrophoresis which quantify M-spike proteins; however, the turnaround time for results is 3-7 days which delays treatment decisions. We hypothesized that machine learning (ML) could integrate readily available clinical and laboratory data to rapidly and accurately predict patient M-spike values. A retrospective chart review was performed using the deidentified, electronic medical records of 171 patients with MM. Random forest (RF) analysis identified the weighted value of each independent variable (N = 43) integrated into the ML algorithm. Pearson and Spearman coefficients indicated that the ML-predicted M-spike values correlated highly with laboratory-measured serum protein electrophoresis values. Feature selected RF modeling revealed that only two variables-the first lagged M-spike and serum total protein-accurately predicted the M-spike. Taken together, our results demonstrate the feasibility and prognostic potential of ML tools that integrate electronic data to longitudinally monitor disease burden. ML tools support the seamless, secure exchange of patient information to expedite and personalize clinical decision making and overcome geographic, financial, and social barriers that currently limit the access of underserved populations to cancer care specialists so that the benefits of medical progress are not limited to selected groups.

Clinical applications of circulating tumor DNA in indolent B-cell lymphomas