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Expression of programmed-death ligand 1 (PD-L1) in non-small cell lung cancer (NSCLC) is typically evaluated through invasive biopsies; however, recent advances in the identification of circulating tumor cells (CTCs) may be a less invasive method to assay tumor cells for these purposes. These liquid biopsies rely on accurate identification of CTCs from the diverse populations in the blood, where some tumor cells share characteristics with normal blood cells. While many blood cells can be excluded by their high expression of CD45, neutrophils and other immature myeloid subsets have low to absent expression of CD45 and also express PD-L1. Furthermore, cytokeratin is typically used to identify CTCs, but neutrophils may stain non-specifically for intracellular antibodies, including cytokeratin, thus preventing accurate evaluation of PD-L1 expression on tumor cells. This holds even greater significance when evaluating PD-L1 in epithelial cell adhesion molecule (EpCAM) positive and EpCAM negative CTCs (as in epithelial-mesenchymal transition (EMT)). To evaluate the impact of CTC misidentification on PD-L1 evaluation, we utilized CD11b to identify myeloid cells. CTCs were isolated from patients with metastatic NSCLC using EpCAM, MUC1 or Vimentin capture antibodies and exclusion-based sample preparation (ESP) technology. Large populations of CD11b+CD45lo cells were identified in buffy coats and stained non-specifically for intracellular antibodies including cytokeratin. The amount of CD11b+ cells misidentified as CTCs varied among patients; accounting for 33-100% of traditionally identified CTCs. Cells captured with vimentin had a higher frequency of CD11b+ cells at 41%, compared to 20% and 18% with MUC1 or EpCAM, respectively. Cells misidentified as CTCs ultimately skewed PD-L1 expression to varying degrees across patient samples. Interfering myeloid populations can be differentiated from true CTCs with additional staining criteria, thus improving the specificity of CTC identification and the accuracy of biomarker evaluation.

Although therapeutic options for patients with advanced renal cell carcinoma (RCC) have increased in the past decade, no biomarkers are yet available for patient stratification or evaluation of therapy resistance. Given the dynamic and heterogeneous nature of clear cell RCC (ccRCC), tumor biopsies provide limited clinical utility, but liquid biopsies could overcome these limitations. Prior liquid biopsy approaches have lacked clinically relevant detection rates for patients with ccRCC. This study employed ccRCC‐specific markers, CAIX and CAXII, to identify circulating tumor cells (CTC) from patients with metastatic ccRCC. Distinct subtypes of ccRCC CTCs were evaluated for PD‐L1 and HLA‐I expression and correlated with patient response to therapy. CTC enumeration and expression of PD‐L1 and HLA‐I correlated with disease progression and treatment response, respectively. Longitudinal evaluation of a subset of patients demonstrated potential for CTC enumeration to serve as a pharmacodynamic biomarker. Further evaluation of phenotypic heterogeneity among CTCs is needed to better understand the clinical utility of this new biomarker. Circulating tumor cells (CTCs) were evaluated for their expression of programmed death ligand‐1 (PD‐L1) and human leukocyte antigen class I (HLA‐I), so that biomarkers of therapeutic resistance of clear cell renal cell carcinoma can be developed. CTCs were captured with antibody‐conjugated magnetic beads against EpCAM and CAIX then probed for CAXII and CK expression using microfluidic technology.

Introduction PD-L1 expression in non-small cell lung cancer (NSCLC) predicts response to immune checkpoint blockade, however is an imperfect biomarker given tumor heterogeneity, and the antigen presentation pathway requiring other components including HLA I expression. HLA I downregulation may contribute to resistance, warranting its evaluation in attempts to guide patient selection. In addition, earlier detection of acquired resistance could prompt earlier change in treatment and prolong patient survival. Analysis of circulating tumor cells (CTCs) captures heterogeneity across multiple sites of metastases, enables detection of changes in tumor burden that precede radiographic response, and can be obtained in serial fashion. Methods To quantify the expression of both PD-L1 and HLA I on CTCs, we developed exclusion-based sample preparation technology, achieving high-yield with gentle magnetic movement of antibody-labeled cells through virtual barriers of surface tension. To achieve clinical-grade quantification of rare cells, we employ high quality fluorescence microscopy image acquisition and automated image analysis together termed quantitative microscopy. Results In preparation for clinical laboratory implementation, we demonstrate high precision and accuracy of these methodologies using a diverse set of control materials. Preliminary testing of CTCs isolated from patients with NSCLC demonstrate heterogeneity in PD-L1 and HLA I expression and promising clinical value in predicting PFS in response to PD-L1 targeted therapies. Conclusions By confirming high performance, we ensure compatibility for clinical laboratory implementation and future application to better predict and detect resistance to PD-L1 targeted therapy in patients with NSCLC.

BackgroundNeuroendocrine prostate cancer (NEPC) is an aggressive subtype, the presence of which changes the prognosis and management of metastatic prostate cancer.MethodsWe performed analytical validation of a Circulating Tumor Cell (CTC) multiplex RNA qPCR assay to identify the limit of quantification (LOQ) in cell lines, synthetic cDNA, and patient samples. We next profiled 116 longitudinal samples from a prospectively collected institutional cohort of 17 patients with metastatic prostate cancer (7 NEPC, 10 adenocarcinoma) as well as 265 samples from 139 patients enrolled in 3 adenocarcinoma phase II trials of androgen receptor signaling inhibitors (ARSIs). We assessed a NEPC liquid biomarker via the presence of neuroendocrine markers and the absence of androgen receptor (AR) target genes.ResultsUsing the analytical validation LOQ, liquid biomarker NEPC detection in the longitudinal cohort had a per-sample sensitivity of 51.35% and a specificity of 91.14%. However, when we incorporated the serial information from multiple liquid biopsies per patient, a unique aspect of this study, the per-patient predictions were 100% accurate, with a receiver-operating-curve (ROC) AUC of 1. In the adenocarcinoma ARSI trials, the presence of neuroendocrine markers, even while AR target gene expression was retained, was a strong negative prognostic factor.ConclusionOur analytically validated CTC biomarker can detect NEPC with high diagnostic accuracy when leveraging serial samples that are only feasible using liquid biopsies. Patients with expression of NE genes while retaining AR-target gene expression may indicate the transition to neuroendocrine differentiation, with clinical characteristics consistent with this phenotype.FundingNIH (DP2 OD030734, 1UH2CA260389, R01CA247479, and P30 CA014520), Department of Defense (PC190039 and PC200334), and Prostate Cancer Foundation (Movember Foundation - PCF Challenge Award).

BACKGROUND. Neuroendocrine prostate cancer (NEPC) is an aggressive subtype, the presence of which changes the prognosis and management of metastatic prostate cancer. METHODS. We performed analytical validation of a Circulating Tumor Cell (CTC) multiplex RNA qPCR assay to identify the limit of quantification (LOQ) in cell lines, synthetic cDNA, and patient samples. We next profiled 116 longitudinal samples from a prospectively collected institutional cohort of 17 patients with metastatic prostate cancer (7 NEPC, 10 adenocarcinoma) as well as 265 samples from 139 patients enrolled in 3 adenocarcinoma phase II trials of androgen receptor signaling inhibitors (ARSIs). We assessed a NEPC liquid biomarker via the presence of neuroendocrine markers and the absence of androgen receptor (AR) target genes. RESULTS. Using the analytical validation LOQ, liquid biomarker NEPC detection in the longitudinal cohort had a per-sample sensitivity of 51.35% and a specificity of 91.14%. However, when we incorporated the serial information from multiple liquid biopsies per patient, a unique aspect of this study, the per-patient predictions were 100% accurate, with a receiver-operating-curve (ROC) AUC of 1. In the adenocarcinoma ARSI trials, the presence of neuroendocrine markers, even while AR target gene expression was retained, was a strong negative prognostic factor. CONCLUSION. Our analytically validated CTC biomarker can detect NEPC with high diagnostic accuracy when leveraging serial samples that are only feasible using liquid biopsies. Patients with expression of NE genes while retaining AR-target gene expression may indicate the transition to neuroendocrine differentiation, with clinical characteristics consistent with this phenotype. FUNDING. NIH (DP2 OD030734, 1UH2CA260389, R01CA247479, and P30 CA014520), Department of Defense (PC190039 and PC200334), and Prostate Cancer Foundation (Movember Foundation - PCF Challenge Award).

Fragmentomics based analysis of cell-free DNA (cfDNA) has recently emerged as a method to infer epigenetic and transcriptional data. Many of these reports analyze whole genome sequencing (WGS) which is not readily available clinically. Targeted exon panels are used for clinical cfDNA variant calling. In this report, we conduct an investigation of multiple published fragmentomics methods for WGS, but on cancer exon panels. We find that strategies utilizing normalized depth metrics, as well as all exons present on the panel, generally allow for better prediction of cancer phenotypes across a range of tumor fractions, though other metrics work particularly well in specific applications. Additionally, genes from commercial clinical targeted sequencing panels could be similarly employed for cancer phenotyping with a minimal decrease in performance despite their smaller genomic coverage. These results suggest that fragmentomics-based analysis of cfDNA can utilize targeted sequencing panels and does not necessarily require additional WGS. cfDNA fragmentomics is a potential clinically applicable method for identifying cancer. Here, the authors assess fragmentomics analysis methods and their application to commercial targeted sequencing panels.