Longitudinal tracking of circulating rare events in the liquid biopsy of stage III-IV non-small cell lung cancer patients.

In the United States, lung cancer is the second most common type of cancer with non-small cell lung cancer (NSCLC) encompassing around 85% of total lung cancer cases. Late-stage patients with metastatic disease have worsening prognosis, highlighting the importance of longitudinal disease monitoring. Liquid biopsy (LBx) represents a way for physicians to non-invasively track tumor analytes, such as circulating tumor cells (CTCs), and understand tumor progression in real-time through analyzing longitudinal blood samples. CTCs have been shown to be effective predictive biomarkers in measuring treatment efficacy and survival outcomes. We used the third-generation High-Definition Single Cell Assay (HDSCA3.0) workflow to analyze circulating rare events longitudinally during treatment in a cohort of 10 late-stage NSCLC patients, identifying rare events including circulating cancer cells (i.e., CTCs), and oncosomes. Here, we show (1) that there is a cancer specific LBx profile, (2) there is considerable heterogeneity of rare cells and oncosomes, and (3) that LBx data elements correlated with patient survival outcomes. Additional studies are warranted to understand the biological significance of the rare events detected, and the clinical potential of the LBx to monitor and predict response to treatment in NSCLC patient care.

Blood-based liquid biopsy: A promising noninvasive test in diagnosis, surveillance, and prognosis of patients with upper tract urothelial carcinoma.

OBJECTIVES: To assess the efficacy of blood-based liquid biopsy in the diagnosis, surveillance, and prognosis of upper tract urothelial carcinoma (UTUC). METHODS AND MATERIALS: In this prospective study, peripheral blood samples were collected from patients with primary UTUC before surgery with curative intent and follow-up visits at University of Southern California between May 2021 and September 2022. The samples were analyzed using the third-generation comprehensive high-definition single-cell assay (HDSCA3.0) to detect rare events, including circulating tumor cells (CTCs) and oncosomes, based on the immunofluorescence signals of DAPI (D), cytokeratin (CK), CD45/CD31 (CD), and vimentin (V). The findings of pre-surgery liquid biopsies were compared with those of blood samples from normal donors (NDs) and matched follow-up liquid biopsies. The association between liquid biopsy findings and clinical data, including recurrence-free survival (RFS), was also assessed. RESULTS: Twenty-eight patients with UTUC were included, of whom 21 had follow-up samples. Significant differences in specific rare analytes were detected in the preoperative samples compared to the NDs. In the post- vs. presurgery matched analysis, a significant decrease was detected in total-, CK-, and CK|V oncosomes, as well as in D-, D|V-, and D|V|CD cells. With a median follow-up of 11 months, 8 patients had disease recurrence. Survival analysis demonstrated that patients with >1.95 preoperative CK|V oncosomes (p = 0.020) and those with >4.18 D|CK|V cells (p = 0.050) had worse RFS compared to other patients. CONCLUSIONS: This study demonstrated promising initial evidence for the biomarker role of CTCs and oncosomes in the diagnosis and surveillance of patients with UTUC.

Cancer-related cells and oncosomes in the liquid biopsy of pancreatic cancer patients undergoing surgery.

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.

Investigation of liquid biopsy analytes in peripheral blood of individuals after SARS-CoV-2 infection.

BACKGROUND: 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. METHODS: 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. FINDINGS: 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%. INTERPRETATION: 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. FUNDING: 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.

Defining A Liquid Biopsy Profile of Circulating Tumor Cells and Oncosomes in Metastatic Colorectal Cancer for Clinical Utility.

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.

Liquid Biopsy Landscape in Patients with Primary Upper Tract Urothelial Carcinoma.

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.

Parameterized Computational Framework for the Description and Design of Genetic Circuits of Morphogenesis Based on Contact-Dependent Signaling and Changes in Cell-Cell Adhesion.

Synthetic development is a nascent field of research that uses the tools of synthetic biology to design genetic programs directing cellular patterning and morphogenesis in higher eukaryotic cells, such as mammalian cells. One specific example of such synthetic genetic programs was based on cell-cell contact-dependent signaling using synthetic Notch pathways and was shown to drive the formation of multilayered spheroids by modulating cell-cell adhesion via differential expression of cadherin family proteins in a mouse fibroblast cell line (L929). The design method for these genetic programs relied on trial and error, which limited the number of possible circuits and parameter ranges that could be explored. Here, we build a parameterized computational framework that, given a cell-cell communication network driving changes in cell adhesion and initial conditions as inputs, predicts developmental trajectories. We first built a general computational framework where contact-dependent cell-cell signaling networks and changes in cell-cell adhesion could be designed in a modular fashion. We then used a set of available in vitro results (that we call the "training set" in analogy to similar pipelines in the machine learning field) to parameterize the computational model with values for adhesion and signaling. We then show that this parameterized model can qualitatively predict experimental results from a "testing set" of available in vitro data that varied the genetic network in terms of adhesion combinations, initial number of cells, and even changes to the network architecture. Finally, this parameterized model is used to recommend novel network implementation for the formation of a four-layered structure that has not been reported previously. The framework that we develop here could function as a testing ground to identify the reachable space of morphologies that can be obtained by controlling contact-dependent cell-cell communications and adhesion with these molecular tools and in this cellular system. Additionally, we discuss how the model could be expanded to include other forms of communication or effectors for the computational design of the next generation of synthetic developmental trajectories.

Avalanches during epithelial tissue growth; Uniform Growth and a drosophila eye disc model.

Epithelial tissues constitute an exotic type of active matter with non-linear properties reminiscent of amorphous materials. In the context of a proliferating epithelium, modeled by the quasistatic vertex model, we identify novel discrete tissue scale rearrangements, i.e. cellular rearrangement avalanches, which are a form of collective cell movement. During the avalanches, the vast majority of cells retain their neighbors, and the resulting cellular trajectories are radial in the periphery, a vortex in the core. After the onset of these avalanches, the epithelial area grows discontinuously. The avalanches are found to be stochastic, and their strength is correlated with the density of cells in the tissue. Overall, avalanches redistribute accumulated local spatial pressure along the tissue. Furthermore, the distribution of avalanche magnitudes is found to obey a power law, with an exponent consistent with sheer induced avalanches in amorphous materials. To understand the role of avalanches in organ development, we simulate epithelial growth of the Drosophila eye disc during the third instar using a computational model, which includes both chemical and mechanistic signaling. During the third instar, the morphogenetic furrow (MF), a ~10 cell wide wave of apical area constriction propagates through the epithelium. These simulations are used to understand the details of the growth process, the effect of the MF on the growth dynamics on the tissue scale, and to make predictions for experimental observations. The avalanches are found to depend on the strength of the apical constriction of cells in the MF, with a stronger apical constriction leading to less frequent and more pronounced avalanches. The results herein highlight the dependence of simulated tissue growth dynamics on relaxation timescales, and serve as a guide for in vitro experiments.

Characterization of Cellular and Acellular Analytes from Pre-Cystectomy Liquid Biopsies in Patients Newly Diagnosed with Primary Bladder Cancer.

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.

Formation, collective motion, and merging of macroscopic bacterial aggregates.

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 bacteria Enterobacter cloacae. As in other bacterial species, Enterobacter cloacae form 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.

Threshold response to stochasticity in morphogenesis.

During development of biological organisms, multiple complex structures are formed. In many instances, these structures need to exhibit a high degree of order to be functional, although many of their constituents are intrinsically stochastic. Hence, it has been suggested that biological robustness ultimately must rely on complex gene regulatory networks and clean-up mechanisms. Here we explore developmental processes that have evolved inherent robustness against stochasticity. In the context of the Drosophila eye disc, multiple optical units, ommatidia, develop into crystal-like patterns. During the larva-to-pupa stage of metamorphosis, the centers of the ommatidia are specified initially through the diffusion of morphogens, followed by the specification of R8 cells. Establishing the R8 cell is crucial in setting up the geometric, and functional, relationships of cells within an ommatidium and among neighboring ommatidia. Here we study an PDE mathematical model of these spatio-temporal processes in the presence of parametric stochasticity, defining and applying measures that quantify order within the resulting spatial patterns. We observe a universal sigmoidal response to increasing transcriptional noise. Ordered patterns persist up to a threshold noise level in the model parameters. In accordance with prior qualitative observations, as the noise is further increased past a threshold point of no return, these ordered patterns rapidly become disordered. Such robustness in development allows for the accumulation of genetic variation without any observable changes in phenotype. We argue that the observed sigmoidal dependence introduces robustness allowing for sizable amounts of genetic variation and transcriptional noise to be tolerated in natural populations without resulting in phenotype variation.