The shape of cancer relapse: Topological data analysis predicts recurrence in paediatric acute lymphoblastic leukaemia

Acute Lymphoblastic Leukaemia (ALL) is the most frequent paediatric cancer. Modern therapies have improved survival rates, but approximately 15-20 % of patients relapse. At present, patients' risk of relapse are assessed by projecting high-dimensional flow cytometry data onto a subset of biomarkers and manually estimating the shape of this reduced data. Here, we apply methods from topological data analysis (TDA), which quantify shape in data via features such as connected components and loops, to pre-treatment ALL datasets with known outcomes. We combine these fully unsupervised analyses with machine learning to identify features in the pre-treatment data that are prognostic for risk of relapse. We find significant topological differences between relapsing and non-relapsing patients and confirm the predictive power of CD10, CD20, CD38, and CD45. Further, we are able to use the TDA descriptors to predict patients who relapsed. We propose three prognostic pipelines that readily extend to other haematological malignancies.

In Vitro Biocompatibility of CPP-ACP and Fluoride-containing Desensitizers on Human Gingival Cells

SUMMARY Objectives: To analyze the biocompatibility of different desensitizers containing casein phosphopeptide-amorphous calcium phosphate (CPP-ACP) and fluoride in their composition: MI Varnish (MV), Clinpro White Varnish (3M Oral Care), Profluorid Varnish (VOCO), Duraphat (Colgate) and Embrace Varnish (Pulpdent) on human gingival fibroblast cells (hGF). Methods and Materials: Human gingival fibroblast (hGF) cells were exposed to several desensitizer extracts at different concentrations (0.1%, 1%, and 4% eluates). Then, in vitro biocompatibility was studied by analyzing the IC50 value, cell proliferation (MTT assay and cell cycle), cell migration (wound healing assay), cell morphology and F-actin content (immunocytofluorescence), and induction of apoptosis/necrosis (flow cytometry). Data were analyzed by one-way analysis of variance (ANOVA) followed by Tukey test. Results: The lowest cell viability and IC50 were observed in all concentrations of Embrace Varnish-treated hGFs (p<0.001), whereas the highest were exhibited by those treated with Clinpro White Varnish. Similar effects were evidenced when induction of apoptosis/necrosis and cell migration assays were assessed. Finally, MI Varnish, Profluorid Varnish, Duraphat, and Embrace Varnish extracts showed lower numbers of attached cells, some of them with an unusual fibroblastic morphology when cultured with 4% concentration of the varnishes, while Clinpro White Varnish exhibited a similar number of cells with an evident actin cytoskeleton compared to the control group. Conclusions: The results obtained in this study indicate that hGFs show better in vitro biocompatibility after exposure to Clinpro White Varnish, even at the highest concentration employed, making it the most eligible for topical applications. In contrast, Embrace Varnish exhibited a high cytotoxicity towards hGFs that could potentially delay the healing process and regeneration of the oral mucosa, although more studies are needed to confirm this hypothesis.

Purification and Characterization of Plantaricin YKX and Assessment of Its Inhibitory Activity Against Alicyclobacillus spp.

Consumers prefer natural over synthetic chemical preservatives on a food label. Therefore, it is crucial to ensure the safety and efficacy of such natural preservatives. The emergence of heat-resistant spore-forming Alicyclobacillus spp. has been associated with spoilage problems in the fruit juice industry. Herein, a bacteriocin-producing stain YKX was isolated from the traditional pickles in Hanzhong City, China, and it was identified as Lactobacillus plantarum by morphological, biochemical, physiological, and genotypic features. A stable bacteriocin, plantaricin YKX, was isolated, purified, and tested for its efficacy against Alicyclobacillus acidoterrestris. Plantaricin YKX is a 14-amino acid peptide (Lys-Tyr-Gly-Asn-Gly-Leu-Ser-Arg-Ile-Phe-Ser-Ala-Leu-Lys). Its minimal inhibitory concentrations (MICs) against the tested bacterial and fungal strains were ranged from 16 to 64 μg/mL. It is thermostable and active at pH 3–8. The flow cytometry data and microscopic observations suggested that plantaricin YKX can augment cell membrane permeability, induce potassium ion leakage and pore formation, and disrupt cell membranes. It also affects spore germination and guaiacol production of A. acidoterrestris, probably due to upregulation of the luxS gene linked to quorum sensing.

Identifying cell-to-cell variability in internalisation using flow cytometry

Biological heterogeneity is a primary contributor to the variation observed in experiments that probe dynamical processes, such as internalisation. Given that internalisation is the primary means by which cells absorb drugs, viruses and other material, quantifying cell-to-cell variability in internalisation is of high biological interest. Yet, it is common for studies of internalisation to neglect cell-to-cell variability. We develop a simple mathematical model of internalisation that captures the dynamical behaviour, cell-to-cell variation, and extrinsic noise introduced by flow cytometry. We calibrate our model through a novel distribution-matching approximate Bayesian computation algorithm to flow cytometry data collected from an experiment that probes the internalisation of antibody by transferrin receptors in C1R cells. Our model reproduces experimental observations, identifies cell-to-cell variability in the internalisation and recycling rates, and, importantly, provides information relating to inferential uncertainty. Given that our approach is agnostic to sample size and signal-to-noise ratio, our modelling framework is broadly applicable to identify biological variability in single-cell data from experiments that probe a range of dynamical processes.

How to Prepare Spectral Flow Cytometry Datasets for High Dimensional Data Analysis: A Practical Workflow

Spectral flow cytometry is an upcoming technique that allows for extensive multicolor panels, enabling simultaneous investigation of a large number of cellular parameters in a single experiment. To fully explore the resulting high-dimensional single cell datasets, high-dimensional analysis is needed, as opposed to the common practice of manual gating in conventional flow cytometry. However, preparing spectral flow cytometry data for high-dimensional analysis can be challenging, because of several technical aspects. In this article, we will give insight into the pitfalls of handling spectral flow cytometry datasets. Moreover, we will describe a workflow to properly prepare spectral flow cytometry data for high dimensional analysis and tools for integrating new data at later time points. Using healthy control data as example, we will go through the concepts of quality control, data cleaning, transformation, correcting for batch effects, subsampling, clustering and data integration. This methods article provides an R-based pipeline based on previously published packages, that are readily available to use. Application of our workflow will aid spectral flow cytometry users to obtain valid and reproducible results.

Internalized Nanoceria Modify the Radiation-Sensitivity Profile of MDA MB231 Breast Carcinoma Cells

Owing to its unique redox properties, cerium oxide (nanoceria) nanoparticles have been shown to confer either radiosensitization or radioprotection to human cells. We investigated nanoceria’s ability to modify cellular health and reactive oxygen species (ROS) at various absorbed doses (Gray) of ionizing radiation in MDA-MB231 breast carcinoma cells. We used transmission electron microscopy to visualize the uptake and compartmental localization of nanoceria within cells at various treatment concentrations. The effects on apoptosis and other cellular health parameters were assessed using confocal fluorescence imaging and flow cytometry without and with various absorbed doses of ionizing radiation, along with intracellular ROS levels. Our results showed that nanoceria were taken up into cells mainly by macropinocytosis and segregated into concentration-dependent large aggregates in macropinosomes. Confocal imaging and flow cytometry data showed an overall decrease in apoptotic cell populations in proportion to increasing nanoparticle concentrations. This increase in cellular health was observed with a corresponding reduction in ROS at all tested absorbed doses. Moreover, this effect appeared pronounced at lower doses compared to unirradiated or untreated populations. In conclusion, internalized nanoceria confers radioprotection with a corresponding decrease in ROS in MDA-MB231 cells, and this property confers significant perils and opportunities when utilized in the context of radiotherapy.

Prognostic Relevance of Tumor-Infiltrating T-Lymphocytes on Total Metabolic Tumor Volume-Based Risk Stratification of Patients with Diffuse Large B-Cell Lymphoma

Introduction: This study investigated the prognostic relevance between tumor-infiltrating T-lymphocytes (TIL) in lymphoma tissue and total metabolic tumor volume (TMTV) measured by positron emission tomography/computed tomography (PET/CT) in patients with diffuse large B-cell lymphoma (DLBCL). We further examined the effect of combining these on the predictive efficacy in DLBCL patients receiving R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) or R-CHOP-like chemotherapy. Methods: Newly diagnosed DLBCL patients at the Kameda Medical Center between 2007 and 2019 were retrospectively analyzed. The patients were selected based on data, including baseline PET/CT, flow-cytometry data of biopsied specimens, and the use of R-CHOP or R-CHOP-like regimens. TMTV was defined as the volume of lymphoma-associated lesions with a standardized uptake value of ≥ 2.5 as the absolute threshold. To calculate TMTV, a semi-automatic computer-aided analysis of PET/CT images for TMTV was conducted using the open-source software Metavol (Hokkaido University, Sapporo, Japan). To assess the degree of TIL, mononuclear cells from biopsied specimens stained with monoclonal antibodies, including CD19, CD3, CD4, CD8, and CD45, were measured using a Navios flow cytometer (Beckman Coulter, USA). Results: Among 536 DLBCL patients, 288 were excluded because of insufficient flow cytometry data, while another 140 were excluded due to lacking baseline TMTV measurements. Lastly, 18 patients, who did not receive R-CHOP or R-CHOP-like regimens, were excluded. Ninety patients were enrolled in this study. The median age of the patients was 68 years (range: 36-86). 44% of the patients had a poor risk of revised-international prognostic index (R-IPI) score. After a median follow-up period of 53 months, the five-year progression-free survival (PFS) and five-year overall survival (OS) rates were 69% and 74%, respectively. First, the prognostic value of TMTV was evaluated at baseline. The median TMTV was 302 cm 3 (range: 3-3923 cm 3). The optimal cut-off value, calculated by the receiver operating curve, was 564 cm 3 (area under the curve, 0.701). Using this cut-off value, high TMTV was associated with a significantly worse PFS (hazard ratio [HR] =2.669; 95% confidence interval [CI] 1.209-5.892; p=0.01) and OS (HR=3.845; CI 1.699-8.704; p=0.001, Figure 1). Next, the prognostic value of TIL was assessed. The median percentages of CD3 +, CD4 +, and CD8 + cells within the tumor were 43% (range: 1-91), 23% (range: 0.5-81), and 15% (range: 0.4-41), respectively. Using the median cut-off value for each percentage of T-cell subsets, low percentages of CD3 + and CD4 + cells were associated with worse PFS and OS, but the difference was not statistically significant for PFS (PFS: HR=1.71; CI 0.767-3.81; p=0.18 and HR=1.799; CI 0.808-4.007; p=0.15, respectively; OS: HR=3.045; CI 1.279-7.246; p=0.01, Figure 2, and HR=3.275; CI 1.375-7.803; p=0.007, respectively), while a low percentage of CD8 + cells was not associated with either PFS or OS. (HR=1.33; CI 0.603-2.93; p=0.47, and HR=1.672; CI 0.755-3.699; p=0.2, respectively). The positivity of CD4 + cells was strongly correlated with that of CD3 (Pearson's correlation analysis, r=0.881, p<0.0001). On multivariate analysis, including TMTV, CD3 + TIL, and R-IPI poor risk as variables, TMTV and CD3 + TIL predicted worse OS (HR=2.943; CI 1.133-7.64; p=0.02, and HR=2.753; CI 1.153-6.575; p=0.02, respectively). Finally, a prognostic model, combining TMTV and CD3 + TIL, was constructed. The model demonstrated that patients with low TMTV and high CD3 + TIL had favorable outcomes (5-year OS: 100%), and patients with high TMTV or low CD3 + TIL had an intermediate prognosis (5-year OS: 70%). However, patients with high TMTV and low CD3 + TIL had a poor prognosis with a five-year OS of 41% (Figure 3). Conclusions: This study indicated that baseline high TMTV and low percentages of TIL in DLBCL patients were associated with a worse prognosis. The combination of TMTV and TIL improved the TMTV-based prognostic stratification of DLBCL patients. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Cyton2: A Model of Immune Cell Population Dynamics That Includes Familial Instructional Inheritance

Lymphocytes are the central actors in adaptive immune responses. When challenged with antigen, a small number of B and T cells have a cognate receptor capable of recognising and responding to the insult. These cells proliferate, building an exponentially growing, differentiating clone army to fight off the threat, before ceasing to divide and dying over a period of weeks, leaving in their wake memory cells that are primed to rapidly respond to any repeated infection. Due to the non-linearity of lymphocyte population dynamics, mathematical models are needed to interrogate data from experimental studies. Due to lack of evidence to the contrary and appealing to arguments based on Occam’s Razor, in these models newly born progeny are typically assumed to behave independently of their predecessors. Recent experimental studies, however, challenge that assumption, making clear that there is substantial inheritance of timed fate changes from each cell by its offspring, calling for a revision to the existing mathematical modelling paradigms used for information extraction. By assessing long-term live-cell imaging of stimulated murine B and T cells in vitro, we distilled the key phenomena of these within-family inheritances and used them to develop a new mathematical model, Cyton2, that encapsulates them. We establish the model’s consistency with these newly observed fine-grained features. Two natural concerns for any model that includes familial correlations would be that it is overparameterised or computationally inefficient in data fitting, but neither is the case for Cyton2. We demonstrate Cyton2’s utility by challenging it with high-throughput flow cytometry data, which confirms the robustness of its parameter estimation as well as its ability to extract biological meaning from complex mixed stimulation experiments. Cyton2, therefore, offers an alternate mathematical model, one that is, more aligned to experimental observation, for drawing inferences on lymphocyte population dynamics.