Dynamics of mRNA from circulating tumor cells (CTCs), mRNA from extracellular vesicles (EVs), and cell-free DNA (cfDNA) were assessed to examine the relevance of a longitudinal multi-parametric liquid biopsy strategy. Eighteen milliliters of blood was drawn from 27 hormone receptor-positive and human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer (MBC) patients at disease progression and at two subsequent radiologic staging time points. CTC mRNA and EV mRNA were analyzed using multi-marker qPCR, and cfDNA was analyzed using targeted next-generation sequencing (NGS). The presence of ERBB2 or ERBB3 overexpression signals in CTCs significantly correlated with disease progression (87% specificity, 36% sensitivity, p-value = 0.023), and the presence of either ERBB3 signals in CTCs or EVs or cfDNA variants in ERBB3 also showed a significant association with progressive MBC. Fluctuations during treatment were detected in the EV fraction with the appearance of hitherto undetected ERCC1 signals correlating with progressive disease (97% specificity, 18% sensitivity, p-value = 0.030). Allele frequency development of ESR1 and PIK3CA variants detected at subsequent staging time points could be used as a predictor for therapy success and, importantly, might help guide therapy decisions. The three analytes, each with their own unique features for disease monitoring, were shown to be complementary, underlining the usefulness of the longitudinal multi-parametric liquid biopsy approach.

Background Single liquid biopsy analytes (LBAs) have been utilized for therapy selection in metastatic breast cancer (MBC). We performed integrative statistical analyses to examine the clinical relevance of using multiple LBAs: matched circulating tumor cell (CTC) mRNA, CTC genomic DNA (gDNA), extracellular vesicle (EV) mRNA, and cell-free DNA (cfDNA). Methods Blood was drawn from 26 hormone receptor-positive, HER2-negative MBC patients. CTC mRNA and EV mRNA were analyzed using a multi-marker qPCR. Plasma from CTC-depleted blood was utilized for cfDNA isolation. gDNA from CTCs was isolated from mRNA-depleted CTC lysates. CTC gDNA and cfDNA were analyzed by targeted sequencing. Hierarchical clustering was performed within each analyte, and its results were combined into a score termed Evaluation of multiple Liquid biopsy analytes In Metastatic breast cancer patients All from one blood sample (ELIMA.score), which calculates the contribution of each analyte to the overall survival prediction. Singular value decomposition (SVD), mutual information calculation, k-means clustering, and graph-theoretic analysis were conducted to elucidate the dependence between individual analytes. Results A combination of two/three/four LBAs increased the prevalence of patients with actionable signals. Aggregating the results of hierarchical clustering of individual LBAs into the ELIMA.score resulted in a highly significant correlation with overall survival, thereby bolstering evidence for the additive value of using multiple LBAs. Computation of mutual information indicated that none of the LBAs is independent of the others, but the ability of a single LBA to describe the others is rather limited—only CTC gDNA could partially describe the other three LBAs. SVD revealed that the strongest singular vectors originate from all four LBAs, but a majority originated from CTC gDNA. After k-means clustering of patients based on parameters of all four LBAs, the graph-theoretic analysis revealed CTC ERBB2 variants only in patients belonging to one particular cluster. Conclusions The additional benefits of using all four LBAs were objectively demonstrated in this pilot study, which also indicated a relative dominance of CTC gDNA over the other LBAs. Consequently, a multi-parametric liquid biopsy approach deconvolutes the genomic and transcriptomic complexity and should be considered in clinical practice.

To estimate the costs and benefits of screening for latent tuberculosis infection (LTBI) in a migrant population in Malaysia. An economic model was developed from a Malaysian healthcare perspective to compare QuantiFERON-TB Gold Plus (QuantiFERON) with the tuberculin skin test (TST). A decision tree was used to capture outcomes relating to LTBI screening followed by a Markov model that simulated the lifetime costs and benefits of the patient cohort. The Markov model did not capture the impact of secondary infections. The model included an R shiny interactive interface to allow adaptation to other scenarios and settings. QuantiFERON is both more effective and less costly than TST (dominant). Compared with QuantiFERON, the lifetime risk of developing active TB increases by approximately 40% for TST due to missed LTBI cases during screening (i.e. a higher number of false negative cases for TST). For a migrant population in Malaysia, QuantiFERON is cost-effective when compared with TST. Further research should consider targeted LTBI screening for migrants in Malaysia based on common risk factors.

Background: To gain comprehensive insights into the aspects of genomic and transcriptomic complexity which could be beneficial for therapy management in metastatic breast cancer (MBC), we established the isolation and analysis of mRNA and gDNA from circulating tumor cells (CTCs), mRNA from extracellular vesicles (EVs), and cell-free DNA (cfDNA) from a minimized blood volume. Here, we aimed to assemble the results of all four analytes and elucidated the relevance of the diverse parameters within a multimodal data set. Methods: EDTA blood (2x 9 ml) was drawn from 26 MBC patients with hormone receptor-positive and HER2 negative primary tumors at the time of disease progression. CTCs and their mRNA were isolated using the AdnaTest EMT2/StemCell Select/Detect. Plasma of CTC-depleted blood was used for cfDNA isolation, while mRNA from EVs was isolated by exoRNeasy using the remaining blood. The mRNA purified from CTCs and EVs was analyzed by a multimarker qPCR panel. gDNA from CTCs was isolated from the mRNA-depleted CTC lysates using the AllPrep DNA/RNA Nano Kit prototype. CTC gDNA and cfDNA were analyzed with a customized QIAseq Targeted DNA Panel for Illumina with unique molecular indices. Consumables: QIAGEN, Germany. The statistical tools for evaluating the results included: Hierarchical clustering according to Ward’s method with Euclidean distance, singular value decomposition, mutual information calculation, and k-means clustering. Results: Isolation of mRNA and gDNA from CTCs, mRNA from EVs, and cfDNA was successfully established in a condensed workflow. 88% of the patients showed at least one variant in CTC gDNA or one overexpression signal in the CTC mRNA fraction. The mean number of variants/signals was also higher in CTC gDNA/mRNA when compared to cfDNA/EV mRNA. The analysis of individual analytes identified a similar number of patients (50%-73%) with actionable markers, but a multi-parametric evaluation of all four analytes identified actionable markers in 96% of the patients. After hierarchical clustering of the results of each individual analyte into four clusters, combining the two patient clusters with the worst overall survival resulted in prognostic value for CTC gDNA, cfDNA, and EV mRNA. Combination of the information above analyte borders showed additive value and resulted in a prognostic factor defined here as the ‘ELIMA score’. A calculation of the mutual information showed that CTC gDNA has the highest potential to describe the other three analytes. However, an Eigenvector analysis based on singular value decomposition revealed that the 10 most influential vectors contain parameters from all four analytes. This indicates that each of the analytes add valuable information not conveyed by the other analytes. K-means clustering was used to generate clusters based solely on CTC gDNA and based on all four analytes. A comparison of the clusters based on these two criteria showed that clustering based on all four analytes resulted in a division of patients according to their tumor histology type and ERBB2 variants in CTCs; thereby, underscoring the importance of taking all four analytes into consideration. Conclusion: We established a workflow for parallel isolation of multiple liquid biopsy analytes from a minimized blood volume. Though the mutual information calculation showed that CTC gDNA has a relatively greater ability to describe the other three analytes, further statistical analysis showed that each analyte carried information of additive value. Thus, a comprehensive picture of the genomic and transcriptomic complexity obtained by a multi-parametric liquid biopsy might enable easier identification of the most suitable therapy regimen for each individual patient in the future. Citation Format: Sabine Kasimir-Bauer, Vinay Suryaprakash, Markus Storbeck, Peter Hahn, Siegfried Hauch, Markus Sprenger-Haussels, Oliver Hoffmann, Rainer Kimmig, Corinna Keup. A clustering and mutual information based analysis of the ELIMA study results: The additive value of multi-parametric liquid biopsies, including CTCs, EVs and cfDNA, in metastatic breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS6-60.