Urinary bladder cancer (BCa) is the 10th most frequent cancer in the world, most commonly found among the elderly population, and becomes highly lethal once cells have spread from the primary tumor to surrounding tissues and distant organs. Cystectomy, alone or with other treatments, is used to treat most BCa patients, as it offers the best chance of cure. However, even with curative intent, 29% of patients experience relapse of the cancer, 50% of which occur within the first year of surgery. This study aims to use the liquid biopsy to noninvasively detect disease and discover prognostic markers for disease progression. Using the third generation high-definition single cell assay (HDSCA3.0), 50 bladder cancer patient samples and 50 normal donor (ND) samples were analyzed for circulating rare events in the peripheral blood (PB), including circulating tumor cells (CTCs) and large extracellular vesicles (LEVs). Here, we show that (i) CTCs and LEVs are detected in the PB of BCa patients prior to cystectomy, (ii) there is a high heterogeneity of CTCs, and (iii) liquid biopsy analytes correlate with clinical data elements. We observed a significant difference in the incidence of rare cells and LEVs between BCa and ND samples (median of 74.61 cells/mL and 30.91 LEVs/mL vs. 34.46 cells/mL and 3.34 LEVs/mL, respectively). Furthermore, using classification models for the liquid biopsy data, we achieved a sensitivity of 78% and specificity of 92% for the identification of BCa patient samples. Taken together, these data support the clinical utility of the liquid biopsy in detecting BCa, as well as the potential for predicting cancer recurrence and survival post-cystectomy to better inform treatment decisions in BCa care.

Urothelial carcinomas (UCs) are a broad and heterogeneous group of malignancies, with the prevalence of upper tract urothelial carcinoma (UTUC) being rare, accounting for only 5–10% of total malignancies. There is a need for additional toolsets to assist the current clinical paradigm of care for patients with UTUC. As a non-invasive tool for the discovery of cancer-related biomarkers, the liquid biopsy has the potential to represent the complex process of tumorigenesis and metastasis. Herein, we show the efficacy of the liquid biopsy as a source of biomarkers for detecting UTUC. Using the third-generation high-definition single-cell assay (HDSCA3.0) workflow, we investigate liquid biopsy samples collected from patients with UTUC and normal donors (NDs) to provide critical information regarding the molecular and morphological characteristics of circulating rare events. We document several important findings from the liquid biopsy analysis of patients diagnosed with UTUC prior to surgery: (1) Large extracellular vesicles (LEVs) and circulating tumor cells (CTCs) are detectable in the peripheral blood. (2) The rare-event profile is highly heterogeneous. (3) Clinical data elements correlate with liquid biopsy analytes. Overall, this study provides evidence for the efficacy of the liquid biopsy in understanding the biology of UTUC with the future intent of informing clinical decision making, ultimately improving patient outcomes.

Metastatic colorectal cancer (mCRC) is characterized by its extensive disease heterogeneity, suggesting that individualized analysis could be vital to improving patient outcomes. As a minimally invasive approach, the liquid biopsy has the potential to longitudinally monitor heterogeneous analytes. Current platforms primarily utilize enrichment-based approaches for epithelial-derived circulating tumor cells (CTC), but this subtype is infrequent in the peripheral blood (PB) of mCRC patients, leading to the liquid biopsy’s relative disuse in this cancer type. In this study, we evaluated 18 PB samples from 10 mCRC patients using the unbiased high-definition single-cell assay (HDSCA). We first employed a rare-event (Landscape) immunofluorescence (IF) protocol, which captured a heterogenous CTC and oncosome population, the likes of which was not observed across 50 normal donor (ND) samples. Subsequent analysis was conducted using a colorectal-targeted IF protocol to assess the frequency of CDX2-expressing CTCs and oncosomes. A multi-assay clustering analysis isolated morphologically distinct subtypes across the two IF stains, demonstrating the value of applying an unbiased single-cell approach to multiple assays in tandem. Rare-event enumerations at a single timepoint and the variation of these events over time correlated with progression-free survival. This study supports the clinical utility of an unbiased approach to interrogating the liquid biopsy in mCRC, representing the heterogeneity within the CTC classification and warranting the further molecular characterization of the rare-event analytes with clinical promise.

Pancreatic ductal adenocarcinoma (PDAC) has a five-year survival rate of less than 10% due to its late diagnosis, rapid metastasis, and chemotherapeutic resistance. For a small proportion (10–20%) of early-stage patients however, surgical resection of the pancreatic tumor offers the best chance for survival but the effect of surgery on disease dissemination is unknown. The primary objective of this study was to characterize cellular and acellular blood-based analytes in portal and peripheral blood before pancreatic manipulation, during tumor dissection and immediately after surgical resection to determine the effects of the surgery. This study used the non-enriching third generation High-Definition Single Cell Assay (HDSCA3.0) workflow to investigate heterogeneous circulating rare cell population in the blood. Blood from both sites taken before surgical manipulation of the pancreas had significantly greater incidence of total rare cellular and acellular analytes than normal donor samples. Post-surgery portal and peripheral blood had significantly greater incidence of specific cellular and acellular subtypes compared to the matched pre- and during-surgery samples. Our results reveal that in patients with PDAC liquid biopsy analytes are increased in both the portal and peripheral blood; portal blood contains a higher frequency of analytes than in the peripheral blood; total analytes in the portal and peripheral blood samples were significantly associated with the tumor volume and pathological T stage; and the surgical procedure increased the blood levels of circulating cellular and acellular analytes, but not Epi.CTCs or Mes.CTCs. This study demonstrates liquid biopsy’s utility in monitoring patients with PDAC with surgically resectable disease.

Post-acute COVID-19 syndrome (PACS) is linked to severe organ damage. The identification and stratification of at-risk SARS-CoV-2 infected individuals is vital to providing appropriate care. This exploratory study looks for a potential liquid biopsy signal for PACS using both manual and machine learning approaches. Using a high definition single cell assay (HDSCA) workflow for liquid biopsy, we analysed 100 Post-COVID patients and 19 pre-pandemic normal donor (ND) controls. Within our patient cohort, 73 had received at least 1 dose of vaccination prior to SARS-CoV-2 infection. We stratified the COVID patients into 25 asymptomatic, 22 symptomatic COVID-19 but not suspected for PACS and 53 PACS suspected. All COVID-19 patients investigated in this study were diagnosed between April 2020 and January 2022 with a median 243 days (range 16-669) from diagnosis to their blood draw. We did a histopathological examination of rare events in the peripheral blood and used a machine learning model to evaluate predictors of PACS. The manual classification found rare cellular and acellular events consistent with features of endothelial cells and platelet structures in the PACS-suspected cohort. The three categories encompassing the hypothesised events were observed at a significantly higher incidence in the PACS-suspected cohort compared to the ND (p-value < 0.05). The machine learning classifier performed well when separating the NDs from Post-COVID with an accuracy of 90.1%, but poorly when separating the patients suspected and not suspected of PACS with an accuracy of 58.7%. Both the manual and the machine learning model found differences in the Post-COVID cohort and the NDs, suggesting the existence of a liquid biopsy signal after active SARS-CoV-2 infection. More research is needed to stratify PACS and its subsyndromes. This work was funded in whole or in part by Fulgent Genetics, Kathy and Richard Leventhal and Vassiliadis Research Fund. This work was also supported by the National Cancer InstituteU54CA260591.

Chemotactic bacteria form emergent spatial patterns of variable cell density within cultures that are initially spatially uniform. These patterns are the result of chemical gradients that are created from the directed movement and metabolic activity of billions of cells. A recent study on pattern formation in wild bacterial isolates has revealed unique collective behaviors of the bacteriaEnterobacter cloacae. As in other bacterial species,Enterobacter cloacaeform macroscopic aggregates. Once formed, these bacterial clusters can migrate several millimeters, sometimes resulting in the merging of two or more clusters. To better understand these phenomena, we examine the formation and dynamics of thousands of bacterial clusters that form within a 22 cm square culture dish filled with soft agar over two days. At the macroscale, the aggregates display spatial order at short length scales, and the migration of cell clusters is superdiffusive, with a merging acceleration that is correlated with aggregate size. At the microscale, aggregates are composed of immotile cells surrounded by low density regions of motile cells. The collective movement of the aggregates is the result of an asymmetric flux of bacteria at the boundary. An agent-based model is developed to examine how these phenomena are the result of both chemotactic movement and a change in motility at high cell density. These results identify and characterize a new mechanism for collective bacterial motility driven by a transient, density-dependent change in motility.