Prostate cancer extracellular vesicle digital scoring assay - a rapid noninvasive approach for quantification of disease-relevant mRNAs.

Optimizing outcomes in prostate cancer (PCa) requires precision in characterization of disease status. This effort was directed at developing a PCa extracellular vesicle (EV) Digital Scoring Assay (DSA) for detecting metastasis and monitoring progression of PCa. PCa EV DSA is comprised of an EV purification device (i.e., EV Click Chip) and reverse-transcription droplet digital PCR that quantifies 11 PCa-relevant mRNA in purified PCa-derived EVs. A Met score was computed for each plasma sample based on the expression of the 11-gene panel using the weighted Z score method. Under optimized conditions, the EV Click Chips outperformed the ultracentrifugation or precipitation method of purifying PCa-derived EVs from artificial plasma samples. Using PCa EV DSA, the Met score distinguished metastatic (n = 20) from localized PCa (n = 20) with an area under the receiver operating characteristic curve of 0.88 (95% CI:0.78-0.98). Furthermore, longitudinal analysis of three PCa patients showed the dynamics of the Met scores reflected clinical behavior even when disease was undetectable by imaging. Overall, a sensitive PCa EV DSA was developed to identify metastatic PCa and reveal dynamic disease states noninvasively. This assay may complement current imaging tools and blood-based tests for timely detection of metastatic progression that can improve care for PCa patients.

HCC EV ECG score: An extracellular vesicle-based protein assay for detection of early-stage hepatocellular carcinoma.

BACKGROUND AND AIMS: The sensitivity of current surveillance methods for detecting early-stage hepatocellular carcinoma (HCC) is suboptimal. Extracellular vesicles (EVs) are promising circulating biomarkers for early cancer detection. In this study, we aim to develop an HCC EV-based surface protein assay for early detection of HCC. APPROACH AND RESULTS: Tissue microarray was used to evaluate four potential HCC-associated protein markers. An HCC EV surface protein assay, composed of covalent chemistry-mediated HCC EV purification and real-time immuno-polymerase chain reaction readouts, was developed and optimized for quantifying subpopulations of EVs. An HCC EV ECG score, calculated from the readouts of three HCC EV subpopulations ( E pCAM + CD63 + , C D147 + CD63 + , and G PC3 + CD63 + HCC EVs), was established for detecting early-stage HCC. A phase 2 biomarker study was conducted to evaluate the performance of ECG score in a training cohort ( n  = 106) and an independent validation cohort ( n  = 72).Overall, 99.7% of tissue microarray stained positive for at least one of the four HCC-associated protein markers (EpCAM, CD147, GPC3, and ASGPR1) that were subsequently validated in HCC EVs. In the training cohort, HCC EV ECG score demonstrated an area under the receiver operating curve (AUROC) of 0.95 (95% confidence interval [CI], 0.90-0.99) for distinguishing early-stage HCC from cirrhosis with a sensitivity of 91% and a specificity of 90%. The AUROCs of the HCC EV ECG score remained excellent in the validation cohort (0.93; 95% CI, 0.87-0.99) and in the subgroups by etiology (viral: 0.95; 95% CI, 0.90-1.00; nonviral: 0.94; 95% CI, 0.88-0.99). CONCLUSION: HCC EV ECG score demonstrated great potential for detecting early-stage HCC. It could augment current surveillance methods and improve patients' outcomes.

Discovery and characterization of circulating tumor cell clusters in neuroendocrine tumor patients using nanosubstrate-embedded microchips.

Circulating tumor cell (CTC) clusters are present in cancer patients with severe metastasis, resulting in poor clinical outcomes. However, CTC clusters have not been studied as extensively as single CTCs, and the clinical utility of CTC clusters remains largely unknown. In this study, we aim sought to explore the feasibility of NanoVelcro Chips to simultaneously detect both single CTCs and CTC clusters with negligible perturbation to their intrinsic properties in neuroendocrine tumors (NETs). We discovered frequent CTC clusters in patients with advanced NETs and examined their potential roles, together with single NET CTCs, as novel biomarkers of patient response following peptide receptor radionuclide therapy (PRRT). We observed dynamic changes in both total NET CTCs and NET CTC cluster counts in NET patients undergoing PRRT which correlated with clinical outcome. These preliminary findings suggest that CTC clusters, along with single CTCs, offer a potential non-invasive option to monitor the treatment response in NET patients undergoing PRRT.

Circulating Tumor Cell-Based Messenger RNA Scoring System for Prognostication of Hepatocellular Carcinoma: Translating Tissue-Based Messenger RNA Profiling Into a Noninvasive Setting.

Numerous studies in hepatocellular carcinoma (HCC) have proposed tissue-based gene signatures for individualized prognostic assessments. Here, we develop a novel circulating tumor cell (CTC)-based transcriptomic profiling assay to translate tissue-based messenger RNA (mRNA) signatures into a liquid biopsy setting for noninvasive HCC prognostication. The HCC-CTC mRNA scoring system combines the NanoVelcro CTC Assay for enriching HCC CTCs and the NanoString nCounter platform for quantifying the HCC-CTC Risk Score (RS) panel in enriched HCC CTCs. The prognostic role of the HCC-CTC RS was assessed in The Cancer Genome Atlas (TCGA) HCC cohort (n = 362) and validated in an independent clinical CTC cohort (n = 40). The HCC-CTC RS panel was developed through our integrated data analysis framework of 8 HCC tissue-based gene signatures and identified the top 10 prognostic genes (discoidin domain receptor tyrosine kinase 1 [DDR1], enoyl-CoA hydratase and 3-hydroxyacyl CoA dehydrogenase [EHHADH], androgen receptor [AR], lumican [LUM], hydroxysteroid 17-beta dehydrogenase 6[HSD17B6], prostate transmembrane protein, androgen induced 1 [PMEPA1], tsukushi, small leucine rich proteoglycan [TSKU], N-terminal EF-hand calcium binding protein 2 [NECAB2], ladinin 1 [LAD1], solute carrier family 27 member 5 [SLC27A5]) highly expressed in HCC with low expressions in white blood cells. The panel accurately discriminated overall survival in TCGA HCC cohort (hazard ratio [HR], 2.0; 95% confidence interval [CI], 1.4-2.9). The combined use of the scoring system and HCC-CTC RS panel successfully distinguished artificial blood samples spiked with an aggressive HCC cell type, SNU-387, from those spiked with PLC/PRF/5 cells (P = 0.02). In the CTC validation cohort (n = 40), HCC-CTC RS remained an independent predictor of survival (HR, 5.7; 95% CI, 1.5-21.3; P = 0.009) after controlling for Model for End-Stage Liver Disease score, Barcelona Clinic Liver Cancer stage, and CTC enumeration count. Our study demonstrates a novel interdisciplinary approach to translate tissue-based gene signatures into a liquid biopsy setting. This noninvasive approach will allow real-time disease profiling and dynamic prognostication of HCC.

Circulating trophoblast cell clusters for early detection of placenta accreta spectrum disorders.

Placenta accreta spectrum (PAS) is a high-risk obstetrical condition associated with significant morbidity and mortality. Current clinical screening modalities for PAS are not always conclusive. Here, we report a nanostructure-embedded microchip that efficiently enriches both single and clustered circulating trophoblasts (cTBs) from maternal blood for detecting PAS. We discover a uniquely high prevalence of cTB-clusters in PAS and subsequently optimize the device to preserve the intactness of these clusters. Our feasibility study on the enumeration of cTBs and cTB-clusters from 168 pregnant women demonstrates excellent diagnostic performance for distinguishing PAS from non-PAS. A logistic regression model is constructed using a training cohort and then cross-validated and tested using an independent cohort. The combined cTB assay achieves an Area Under ROC Curve of 0.942 (throughout gestation) and 0.924 (early gestation) for distinguishing PAS from non-PAS. Our assay holds the potential to improve current diagnostic modalities for the early detection of PAS.

Covalent Chemistry-Mediated Multimarker Purification of Circulating Tumor Cells Enables Noninvasive Detection of Molecular Signatures of Hepatocellular Carcinoma.

Transcriptomic profiling of tumor tissues introduces a large database, which has led to improvements in the ability of cancer diagnosis, treatment, and prevention. However, performing tumor transcriptomic profiling in the clinical setting is very challenging since the procurement of tumor tissues is inherently limited by invasive sampling procedures. Here, we demonstrated the feasibility of purifying hepatocellular carcinoma (HCC) circulating tumor cells (CTCs) from clinical patient samples with improved molecular integrity using Click Chips in conjunction with a multimarker antibody cocktail. The purified CTCs were then subjected to mRNA profiling by NanoString nCounter platform, targeting 64 HCC-specific genes, which were generated from an integrated data analysis framework with 8 tissue-based prognostic gene signatures from 7 publicly available HCC transcriptomic studies. After bioinformatics analysis and comparison, the HCC CTC-derived gene signatures showed high concordance with HCC tissue-derived gene signatures from TCGA database, suggesting that HCC CTCs purified by Click Chips could enable the translation of HCC tissue molecular profiling into a noninvasive setting.

The Role of Extracellular Vesicles in Disease Progression and Detection of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and one of the leading causes of cancer-related death worldwide. Despite the improvements in surveillance and treatment, the prognosis of HCC remains poor. Extracellular vesicles (EVs) are a heterogeneous group of phospholipid bilayer-enclosed particles circulating in the bloodstream and mediating intercellular communication. Emerging studies have shown that EVs play a crucial role in regulating the proliferation, immune escape, and metastasis of HCC. In addition, because EVs are present in the circulation at relatively early stages of disease, they are getting attention as an attractive biomarker for HCC detection. Over the past decade, dedicated efforts have been made to isolate EVs more efficiently and make them useful tools in different clinical settings. In this review article, we provide an overview of the EVs isolation methods and highlight the role of EVs as mediators in the pathogenesis and progression of HCC. Lastly, we summarize the potential applications of EVs in early-stage HCC detection.

Comparison of Clinical Features and Outcomes Between Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma in the United States.

BACKGROUND AND AIMS: Intrahepatic cholangiocarcinoma (iCCA) and hepatocellular carcinoma (HCC) are the most common primary liver cancers (PLCs). Differences in their clinical features and outcomes are open for investigation in a large-scale study. We aim to investigate the differences in clinical features and outcomes between iCCA and HCC. APPROACH AND RESULTS: The Surveillance, Epidemiology, and End Results Program 18 Database (2000-2017) was used to extract demographic and clinical features of HCC and iCCA patients. Logistic regression analysis was performed to identify factors associated with iCCA diagnosis versus HCC. Cox regression analysis was used to assess factors affecting overall survival (OS). There were 13,611 iCCA and 96,151 HCC patients. Half of iCCA (50.7%) and three quarters of HCC (76.3%) patients were male. Diagnosis in recent year, age (<50 or ≥65), female sex, non-Hispanic White race, higher income, rural area, and higher tumor burden were independently associated with iCCA diagnosis versus HCC. Patients with iCCA had worse OS than those with HCC (9 vs. 13 months; P < 0.001). However, OS was comparable between iCCA and HCC in multivariable analysis (adjusted hazard ratio [aHR] = 1.02; 95% CI = 0.99-1.05). In subgroup analyses, iCCA was associated with better OS than HCC in patients with tumor ≥5 cm (aHR = 0.83; 95% CI = 0.80-0.86), lymph node involvement (aHR = 0.76; 95% CI = 0.72-0.81), distant metastasis (aHR = 0.76; 95% CI = 0.73-0.79), poorly/undifferentiated tumors (aHR = 0.88; 95% CI = 0.83-0.94), and those receiving noncurative treatment (aHR = 0.96; 95% CI = 0.93-0.98). CONCLUSIONS: We identified the demographic, socioeconomic, and clinical features associated with iCCA diagnosis over HCC among patients with PLC. Although iCCA patients presented at an advanced stage, OS was similar between iCCA and HCC in multivariable analysis. iCCA was associated with longer OS for subgroups with poor prognostic features.

The Mortality and Overall Survival Trends of Primary Liver Cancer in the United States.

BACKGROUND: Recent trends of hepatocellular carcinoma (HCC) mortality and outcome remain unknown in the United States. We investigated the recent trends of primary liver cancer (excluding intrahepatic cholangiocarcinoma) mortality and HCC stage, treatment, and overall survival (OS) in the United States. METHODS: The National Center for Health Statistics Database was analyzed to investigate the trend of primary liver cancer mortality. We analyzed the Surveillance, Epidemiology, and End Results 18 Database to assess the temporal trend of tumor size, stage, treatment, and OS of HCC. We investigated the association between HCC diagnosis year and OS using Cox regression analysis. All statistical tests were 2-sided. RESULTS: During 2000-2018, liver cancer mortality rates increased until 2013, plateaued during 2013-2016 (annual percent change = 0.1%/y, 95% confidence interval [CI] = -2.1%/y to 2.4%/y, P = .92), and started to decline during 2016-2018 (annual percent change = -1.5%/y, 95% CI = -3.2%/y to 0.2%/y, P = .08). However, mortality continues to increase in American Indian and Alaska Native, individuals aged 65 years or older, and in 33 states. There was a 0.61% (95% CI = 0.53% to 0.69%, P < .001) increase in localized stage HCC and a 0.86-mm (95% CI = -1.10 to -0.62 mm, P < .001) decrease in median tumor size per year. The 1-year OS rate increased from 36.3% (95% CI = 34.3% to 38.3%) to 58.1% (95% CI = 56.9% to 59.4%) during 2000-2015, and the 5-year OS rate almost doubled from 11.7% (95% CI = 10.4% to 13.1%) to 21.3% (95% CI = 20.2% to 22.4%) during 2000-2011. Diagnosis year (per year) (adjusted hazard ratio = 0.96, 95% CI = 0.96 to 0.97) was independently associated with OS in multivariable analysis. CONCLUSIONS: Primary liver cancer mortality rates have started to decline in the United States with demographic and state-level variation. With an increasing detection of localized HCC, the OS of HCC has improved over the past decades.

State-Level HCC Incidence and Association With Obesity and Physical Activity in the United States.

BACKGROUND AND AIMS: Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality, with a disproportionate impact on racial/ethnic minority groups. However, state-level variation in racial/ethnic disparities and temporal trends of HCC incidence remain unknown. Therefore, we aimed to characterize (1) state-level racial/ethnic disparity in HCC incidence, (2) state-level temporal changes in HCC incidence, and (3) the ecological correlation between HCC incidence and obesity/physical activity levels in the USA. APPROACH AND RESULTS: Trends in HCC incidence between 2001 and 2017 were calculated using data from the Centers for Disease Control and Prevention's National Program of Cancer Registries and the National Cancer Institute's Surveillance, Epidemiology and End Results, and annual percent change in rates were calculated. State-level percent of obesity and level of physical activity were obtained from the Centers for Disease Control and Prevention, and the correlation among obesity, physical activity, and state-specific average annual percent change was tested by Pearson correlation coefficient. There were striking state-level racial/ethnic disparities in HCC incidence; incidence rate ratios ranged between 6.3 and 0.9 in Blacks, 6.1 and 1.7 in Asians/Pacific Islanders, 3.8 and 0.9 in Hispanics, and 6.0 and 0.9 in American Indians/Alaska Natives (compared with Whites as reference). Despite overall decreasing HCC incidence rates after 2015, HCC incidence continued increasing in 26 states over recent years. HCC incidence trends had a moderate correlation with state-level obesity (r = 0.45, P < 0.001) and a moderate inverse correlation with state-level physical activity (r = -0.40, P = 0.004). CONCLUSIONS: There is wide state-level variation in racial/ethnic disparity of HCC incidence. There are also disparate incidence trends across states, with HCC incidence continuing to increase in over half of the states. Regional obesity and lack of physical activity have moderate correlations with HCC incidence trends, suggesting that interventions targeting these factors may help curb rising HCC incidence.

Purification of HCC-specific extracellular vesicles on nanosubstrates for early HCC detection by digital scoring.

We report a covalent chemistry-based hepatocellular carcinoma (HCC)-specific extracellular vesicle (EV) purification system for early detection of HCC by performing digital scoring on the purified EVs. Earlier detection of HCC creates more opportunities for curative therapeutic interventions. EVs are present in circulation at relatively early stages of disease, providing potential opportunities for HCC early detection. We develop an HCC EV purification system (i.e., EV Click Chips) by synergistically integrating covalent chemistry-mediated EV capture/release, multimarker antibody cocktails, nanostructured substrates, and microfluidic chaotic mixers. We then explore the translational potential of EV Click Chips using 158 plasma samples of HCC patients and control cohorts. The purified HCC EVs are subjected to reverse-transcription droplet digital PCR for quantification of 10 HCC-specific mRNA markers and computation of digital scoring. The HCC EV-derived molecular signatures exhibit great potential for noninvasive early detection of HCC from at-risk cirrhotic patients with an area under receiver operator characteristic curve of 0.93 (95% CI, 0.86 to 1.00; sensitivity = 94.4%, specificity = 88.5%).

A Circulating Tumor Cell-RNA Assay for Assessment of Androgen Receptor Signaling Inhibitor Sensitivity in Metastatic Castration-Resistant Prostate Cancer.

Rationale: Our objective was to develop a circulating tumor cell (CTC)-RNA assay for characterizing clinically relevant RNA signatures for the assessment of androgen receptor signaling inhibitor (ARSI) sensitivity in metastatic castration-resistant prostate cancer (mCRPC) patients. Methods: We developed the NanoVelcro CTC-RNA assay by combining the Thermoresponsive (TR)-NanoVelcro CTC purification system with the NanoString nCounter platform for cellular purification and RNA analysis. Based on the well-validated, tissue-based Prostate Cancer Classification System (PCS), we focus on the most aggressive and ARSI-resistant PCS subtype, i.e., PCS1, for CTC analysis. We applied a rigorous bioinformatic process to develop the CTC-PCS1 panel that consists of prostate cancer (PCa) CTC-specific RNA signature with minimal expression in background white blood cells (WBCs). We validated the NanoVelcro CTC-RNA assay and the CTC-PCS1 panel with well-characterized PCa cell lines to demonstrate the sensitivity and dynamic range of the assay, as well as the specificity of the PCS1 Z score (the likelihood estimate of the PCS1 subtype) for identifying PCS1 subtype and ARSI resistance. We then selected 31 blood samples from 23 PCa patients receiving ARSIs to test in our assay. The PCS1 Z scores of each sample were computed and compared with ARSI treatment sensitivity. Results: The validation studies using PCa cell line samples showed that the NanoVelcro CTC-RNA assay can detect the RNA transcripts in the CTC-PCS1 panel with high sensitivity and linearity in the dynamic range of 5-100 cells. We also showed that the genes in CTC-PCS1 panel are highly expressed in PCa cell lines and lowly expressed in background WBCs. Using the artificial CTC samples simulating the blood sample conditions, we further demonstrated that the CTC-PCS1 panel is highly specific in identifying PCS1-like samples, and the high PCS1 Z score is associated with ARSI resistance samples. In patient bloods, ARSI-resistant samples (ARSI-R, n=14) had significantly higher PCS1 Z scores as compared with ARSI-sensitive samples (ARSI-S, n=17) (Rank-sum test, P=0.003). In the analysis of 8 patients who were initially sensitive to ARSI (ARSI-S) and later developed resistance (ARSI-R), we found that the PCS1 Z score increased from the time of ARSI-S to the time of ARSI-R (Pairwise T-test, P=0.016). Conclusions: Using our new methodology, we developed a first-in-class CTC-RNA assay and demonstrated the feasibility of transforming clinically-relevant tissue-based RNA profiling such as PCS into CTC tests. This approach allows for detecting RNA expression relevant to clinical drug resistance in a non-invasive fashion, which can facilitate patient-specific treatment selection and early detection of drug resistance, a goal in precision oncology.