Number Of Subpopulations Research Articles

Abstract 2550: Tumor microenvironment (TME) is more suppressive in hepatocellular carcinoma (HCC) than in colorectal cancer liver metastasis (CRLM): CXCR4 antagonism as strategy to revert T regulatory cells (Tregs) suppressive activity

Abstract Background: Hepatocellular carcinoma (HCC) and colorectal cancer liver metastasis (CRLM) represent the two most occurring liver cancer. Aim of the project was to analyze the impact of TME on HCC versus CRLM. In particular, Tregs were evaluated in tumor (TT), peritumoral (PT) tissue and peripheral blood (PB) of liver tumor to identify immune mechanisms and therapeutic targets. Methods: Tregs were characterized on PB/PT/TT cell suspension from 40 HCC and 34 CRLM by flow cytometry (FOXP3, CD25, CD4, CD45RA, CTLA-4, CXCR4, PD-1, ICOS and ENTPD1). PB-, PT- and TT-Tregs were isolated by Dynabeads Regulatory T-cell kit and tested for the capability to inhibit CFSE-labeled autologous T effector (Teff) proliferation. Tregs were also treated with Pep R29, a new CXCR4 antagonists, before coculturing with Teffs. Quantitative real-time PCR was performed to assess the expression of cyto-chemokines in PT and TT samples (IL-15, Arginase, CCL5, CXCL12). Results: In HCC/CRLM-PB higher number of CXCR4 (p<0,001/p<0,05), CTLA-4 (p<0,001/p<0,05), PD-1 (p<0,001/p<0,05), ICOS (p<0,05/0,06% vs 0,03%) and ENTPD-1 (p<0,001/p<0,05) expressing Tregs was detected as compared to healthy donors (HD). In HCC/CRLM-TT higher number of FOXP3hiCD45RA-Activated Tregs subpopulation (p<0,01/p<0,05) and higher CXCR4-positive Tregs (p<0,05) were observed as compared to PT. Moreover, Tregs from HCC showed higher expression of ICOS (p<0,05) and ENTPD1 (p<0,05) as compared to CRLM. In terms of function, TT-Tregs exert a stronger immunosuppressive effect on Teffs proliferation than PT-Tregs (p<0,05) as shown by IL-35 cytokine secretion (150 vs 15 pg/mL/p<0,05). Interestingly, HCC-Tregs more powerfully inhibit Teffs proliferation at the tumor site and also in periphery. Expression of TME cyto-chemokines responsible of immunity promotion (IL-15) or inhibition (CXCL12, CCL5, Arginase) and tumor features, such as epithelial to mesenchymal transition (EMT) are under evaluation. Preliminary data showed higher CCL5, Tregs recruiting, in HCC as compared to CRLM suggesting a more suppressive TME in HCC. Based on high % of CXCR4-positive Tregs in HCC and CRLM (PB-HCC/CRLM: p<0,001 and TT-HCC/CRLM: p<0,01), ex vivo PB-Tregs were treated with Pep R29. CXCR4 targeting re-induced Teffs proliferation (PB-HCC -/+ Pep R29:12% vs 32%, p<0,001; PB-CRLM-/+ Pep R29:18,3% vs 49%, p<0,01) and decreased Tregs-derived IL-35 secretion (PB-HCC -/+ Pep R29: 106vs 16,5pg/mL, p<0,05; -/+ Pep R29:70 vs 0,6pg/mL, p<0,01). Conclusions: These data suggest a more suppressive TME in HCC compared to CRLM and highlighted CXCR4 antagonism as a potential strategy to overcome Tregs-mediated TME immunosuppressive function in HCC and CRLM patients. Citation Format: Daniela Castaldo, Sara Santagata, Giuseppina Rea, Maria Napolitano, Crescenzo D'Alterio, Rita Guarino, Vittorio Albino, Andrea Belli, Carmen Cutolo, Francesco Izzo, Stefania Scala. Tumor microenvironment (TME) is more suppressive in hepatocellular carcinoma (HCC) than in colorectal cancer liver metastasis (CRLM): CXCR4 antagonism as strategy to revert T regulatory cells (Tregs) suppressive activity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2550.

Feeding a Saccharomyces cerevisiae Fermentation Product (Olimond BB) Does Not Alter the Fecal Microbiota of Thoroughbred Racehorses.

Feed supplements such as Saccharomyces cerevisiae fermentation products (SCFP) alter immune responses in horses. The purpose of this study was to analyze whether a prebiotic activity of the SCFP alters the gut microbiome in horses. Racehorses were fed either SCFP (Olimond BB, OLI, n = 6) or placebo pellets (PLA, n = 5) for 43 days. Fecal microbiota analysis was performed using 16S rRNA gene sequencing. The numbers and function of circulating immune cell subpopulations were analyzed by flow cytometry. SCFP supplementation resulted in non-consistent differences in fecal microbiota between the PLA and OLI during the feeding period. Rather, the individual animal had the highest impact on fecal microbiota composition. OLI and PLA horses displayed the same changes in numbers of blood leukocyte subpopulations over time. One day after a booster vaccination against equine influenza during the feeding period, the alpha diversity of fecal microbiota of PLA horses was significantly higher compared to OLI horses. This suggests that SCFP feeding altered the vaccination-induced spectrum of released mediators, potentially affecting gut microbiota. The overall non-consistent findings argue against a strong prebiotic effect of Olimond BB on the microbiota in racehorses. Fecal microbiota differences between the groups were also noticed outside the feeding period and, hence, are most likely not caused by the SCFP additive.

Local cellular immunity in colorectal cancer depending on tumor site.

e15613 Background: Colorectal cancer (CRC) is the third most commonly diagnosed cancer. More than 60% of all cases of CRC are colon cancer (CC). The role of individual units of the immune system in the development of this tumor is ambiguous. The purpose of this study was to characterize local populations and subpopulations of immunocompetent cells in colorectal cancer with different tumor locations. Methods: The study included 50 CC (adenocarcinoma) patients aged 35-86 years, women n = 26 (52%). Stage I tumors were registered in 4 patients (8%), stage II 25 (50%), stage III 21 (42%). 20 patients (40%) had right-sided CC (group 1), 9 (18%) left-sided CC (group 2), and 21 (42%) sigmoid CC (group 3). All patients received surgical treatment. Cell suspensions were obtained from tumor (TT) and peritumoral tissues (PT) (1-3 cm from the tumor), and then processed with an antibody panel in accordance with the manufacturer instructions (Becton Dickinson, USA) to identify the main populations and subpopulations of leukocytes and lymphocytes. The relative number of major populations and subpopulations of lymphocytes was determined on the BD FACSCanto flow cytometer. Results: A decrease in lymphocytic infiltration was noted left-sided tumors and sigmoid tumors compared to right-sided CC, by 46% and 51%, respectively. The percentage of CD3+ cells was almost the same regardless of the colon tumor location, and the number of main populations of T lymphocytes differed: in group 3, the content of CD4+ cells was 21% higher, and CD8+ cells were 22% lower compared with group 1, while group 2 had no differences. Group 2 differed in the tumor infiltration with both NK and NKT lymphocytes, which were higher by 25% and 22%, respectively, than in group 1. An increase in NK cells was noted in the sigmoid colon (group 3), and the relative number of NKT lymphocytes decreased. A common feature of TT in groups 2 and 3 was an increase in the content of B lymphocytes by 98% and 133%, respectively. PT of group 2 showed a decrease by 72%, 33%, 66%, and 46% in the relative number of lymphocytes, CD4+, NKT and B lymphocytes compared with group 1, together with an increased content of NK and CD8+ lymphocytes. PT in patients of group 3 had a decrease in the number of total and NK lymphocytes by 46% and 26%, respectively, and a significant increase by 85% in the content of CD8+ cells, with no changes in CD3+, CD4+ cells, B and NKT lymphocytes. Conclusions: The local immune status of CRC patients demonstrated a number of differences: right-sided tumors were characterized by a higher T-lymphocytic infiltration with the same tendency in the perifocal tissues, while left-sided and sigmoid tumors showed higher B-lymphocytic infiltration, which can help in the disease prognosis and choice of treatment strategy.

Single-cell transcriptome reveals insights into the development and function of the zebrafish ovary.

Zebrafish are an established research organism that has made many contributions to our understanding of vertebrate tissue and organ development, yet there are still significant gaps in our understanding of the genes that regulate gonad development, sex, and reproduction. Unlike the development of many organs, such as the brain and heart that form during the first few days of development, zebrafish gonads do not begin to form until the larval stage (≥5 days post-fertilization). Thus, forward genetic screens have identified very few genes required for gonad development. In addition, bulk RNA-sequencing studies that identify genes expressed in the gonads do not have the resolution necessary to define minor cell populations that may play significant roles in the development and function of these organs. To overcome these limitations, we have used single-cell RNA sequencing to determine the transcriptomes of cells isolated from juvenile zebrafish ovaries. This resulted in the profiles of 10,658 germ cells and 14,431 somatic cells. Our germ cell data represents all developmental stages from germline stem cells to early meiotic oocytes. Our somatic cell data represents all known somatic cell types, including follicle cells, theca cells, and ovarian stromal cells. Further analysis revealed an unexpected number of cell subpopulations within these broadly defined cell types. To further define their functional significance, we determined the location of these cell subpopulations within the ovary. Finally, we used gene knockout experiments to determine the roles of foxl2l and wnt9b for oocyte development and sex determination and/or differentiation, respectively. Our results reveal novel insights into zebrafish ovarian development and function, and the transcriptome profiles will provide a valuable resource for future studies.

329 Longitudinal immune profiling reveals unique myeloid and T cell phenotypes associated with spontaneous immunoediting in a novel prostate tumor model

OBJECTIVES/GOALS: Few preclinical models exist to study how tumors transition from prolonged stable disease ('equilibrium') to progressive disease ('escape'). We characterized a new murine tumor model the exhibits such behavior, and sought to identify and validate the role of unique tumor-infiltrating immune cell subsets in this process. METHODS/STUDY POPULATION: We evaluated growth of NPK-C1 (originally LM7304; received from Dr. Cory Abate-Shen at Columbia University), a cell line developed from spontaneous prostate cancer lung metastases in NPK mice (Nkx3.1CreERT2/+Ptenflox/floxKrasLSL-G12D/+R26R-LSL-YFP/+), in immune competent (C57BL/6) and immune deficient mice (J/Nu). We determined the role of CD4 and CD8 T cells in regulating the 'equilibrium to escape’ growth dynamics of NPK-C1 via in vivo cell depletions at key inflection points of tumor growth. To deeply profile the immune contexture of NPK-C1 at these inflection points, we developed a 28-color immunophenotyping panel for use on a Cytek Aurora spectral flow cytometer. We performed dimensionality reduction and clustering analyses on these data using tSNE and FlowSOM algorithms within FlowJo (v10.6). RESULTS/ANTICIPATED RESULTS: We found that activated CD4 effector T cells are enriched in regressing NPK-C1 tumors, highlighting a role for CD4 T cells in antitumor immunity. CD8 T cells are also important for NPK-C1 control; specifically central memory-like cytotoxic CD8 T cells. Depletion of either CD4 or CD8 T cells during the equilibrium phase of NPK-C1 growth confirmed the role of these cells in antagonizing NPK-C1 escape. Tregs as a whole were counterintuitively enriched in regressing tumors, however high dimensional analysis reveals their significant phenotypic diversity, with a number of Treg subpopulations enriched in progressing tumors. In the myeloid compartment, we found that iNOS+ DC-like cells are enriched in regressing tumors, while CD103+ DCs are associated with late stage tumor progression. DISCUSSION/SIGNIFICANCE: In total, these analyses of the NPK-C1 model provide novel insights into the roles of lymphoid and myeloid populations throughout key phases of tumor/immune co-evolution, and highlight a role for multi-dimensional flow cytometry-based analyses to more deeply understand immune cell dynamics in the tumor microenvironment.

The importance of using ordinal scores for patient classification based on health-related quality of life trajectories.

Changes in health-related quality of life (HRQoL) over time are not necessarily homogeneous within a population of interest. Our study aim was twofold: to determine homogeneous patient subpopulations distinguished by HRQoL trajectories, and to identify the particular patient profile associated with each subpopulation. To classify patients according to HRQoL dimension scores, we compared mixtures of linear mixed models (LMMs) classically applied to scores defined by the EORTC procedure, and mixtures of random effect cumulative models (CMs) applied to scores treated as ordinal variables. A simulation study showed that the mixture of LMMs overestimated the number of subpopulations and was less able to correctly classify patients than the mixture of CMs. Considering HRQoL scores as ordinal rather than continuous variables is relevant when classifying patients. The mixture of CMs for ordinal scores is able to identify homogeneous subpopulations and their associated trajectories. The application focused on changes over time in HRQoL data (collected using the EORTC QLQ-C30 questionnaire) from 132 breast cancer patients from the Moral study. Once the classification is obtained only from HRQoL scores, class membership was then explained through a logistic regression model, given a large panel of variables collected at baseline. Analysis of data revealed that deterioration over time of role functioning and insomnia was closely related to patient anxiety: anxiety at baseline is a prognostic factor for a poor level and/or a deterioration over time of HRQoL. For functional dimensions, large tumor size and high education level were associated with worse HRQoL scores.

Identification of potential MTAs and candidate genes for juice quality- and yield-related traits in Saccharum clones: a genome-wide association and comparative genomic study

Sugarcane is an economically important commercial crop which provides raw material for the production of sugar, jaggery, bioethanol, biomass and other by-products. Sugarcane breeding till today heavily relies on conventional breeding approaches which is time consuming, laborious and costly. Integration of marker-assisted selection (MAS) in sugarcane genetic improvement programs for difficult to select traits like sucrose content, resistance to pests and diseases and tolerance to abiotic stresses will accelerate varietal development. In the present study, association mapping approach was used to identify QTLs and genes associated with sucrose and other important yield-contributing traits. A mapping panel of 110 diverse sugarcane genotypes and 148 microsatellite primers were used for structured association mapping study. An optimal subpopulation number (ΔK) of 5 was identified by structure analysis. GWAS analysis using TASSEL identified a total of 110 MTAs which were localized into 27 QTLs by GLM and MLM (Q + K, PC + K) approaches. Among the 24 QTLs sequenced, 12 were able to identify potential candidate genes, viz., starch branching enzyme, starch synthase 4, sugar transporters and G3P-DH related to carbohydrate metabolism and hormone pathway-related genes ethylene insensitive 3-like 1, reversion to ethylene sensitive1-like, and auxin response factor associated to juice quality- and yield-related traits. Six markers, NKS 5_185, SCB 270_144, SCB 370_256, NKS 46_176 and UGSM 648_245, associated with juice quality traits and marker SMC31CUQ_304 associated with NMC were validated and identified as significantly associated to the traits by one-way ANOVA analysis. In conclusion, 24 potential QTLs identified in the present study could be used in sugarcane breeding programs after further validation in larger population. The candidate genes from carbohydrate and hormone response pathway presented in this study could be manipulated with genome editing approaches to further improve sugarcane crop.

Regulating Endogenous Neural Stem Cell Activation to Promote Spinal Cord Injury Repair.

Spinal cord injury (SCI) affects millions of individuals worldwide. Currently, there is no cure, and treatment options to promote neural recovery are limited. An innovative approach to improve outcomes following SCI involves the recruitment of endogenous populations of neural stem cells (NSCs). NSCs can be isolated from the neuroaxis of the central nervous system (CNS), with brain and spinal cord populations sharing common characteristics (as well as regionally distinct phenotypes). Within the spinal cord, a number of NSC sub-populations have been identified which display unique protein expression profiles and proliferation kinetics. Collectively, the potential for NSCs to impact regenerative medicine strategies hinges on their cardinal properties, including self-renewal and multipotency (the ability to generate de novo neurons, astrocytes, and oligodendrocytes). Accordingly, endogenous NSCs could be harnessed to replace lost cells and promote structural repair following SCI. While studies exploring the efficacy of this approach continue to suggest its potential, many questions remain including those related to heterogeneity within the NSC pool, the interaction of NSCs with their environment, and the identification of factors that can enhance their response. We discuss the current state of knowledge regarding populations of endogenous spinal cord NSCs, their niche, and the factors that regulate their behavior. In an attempt to move towards the goal of enhancing neural repair, we highlight approaches that promote NSC activation following injury including the modulation of the microenvironment and parenchymal cells, pharmaceuticals, and applied electrical stimulation.

Unsupervised Cluster Analysis and Gene Marker Extraction of scRNA-seq Data Based On Non-Negative Matrix Factorization.

The development of single-cell RNA sequencing (scRNA-seq) technology has made it possible to measure gene expression levels at the resolution of a single cell, which further reveals the complex growth processes of cells such as mutation and differentiation. Recognizing cell heterogeneity is one of the most critical tasks in scRNA-seq research. To solve it, we propose a non-negative matrix factorization framework based on multi-subspace cell similarity learning for unsupervised scRNA-seq data analysis (MscNMF). MscNMF includes three parts: data decomposition, similarity learning, and similarity fusion. The three work together to complete the data similarity learning task. MscNMF can learn the gene features and cell features of different subspaces, and the correlation and heterogeneity between cells will be more prominent in multi-subspaces. The redundant information and noise in each low-dimensional feature space are eliminated, and its gene weight information can be further analyzed to calculate the optimal number of subpopulations. The final cell similarity learning will be more satisfactory due to the fusion of cell similarity information in different subspaces. The advantage of MscNMF is that it can calculate the number of cell types and the rank of Non-negative matrix factorization (NMF) reasonably. Experiments on eight real scRNA-seq datasets show that MscNMF can effectively perform clustering tasks and extract useful genetic markers. To verify its clustering performance, the framework is compared with other latest clustering algorithms and satisfactory results are obtained. The code of MscNMF is free available for academic (https://github.com/wangchuanyuan1/project-MscNMF).

The relationship between myeloid-derived supressor cells and clinico-laboratory parameters in patients with liver cyrrosis

In the present study, we used multicolor flow cytometry assay to measure the numbers of various myeloid suppressor cell subpopulations (Lin-HLA-DR-CD33+, Lin-HLA-DR-CD33+CD66b+, and CD14+HLA-DRlow/-) in peripheral blood of 51 participants, including 33 patients with viral- and 1 8 patients with «nonviral» (alcoholic or biliary/autoimmune) liver cirrhosis. Patients in both groups had increased proportions of Lin-HLA-DR-CD33+, Lin-HLA-DR-CD33+CD66b+, and CD 14+HLA-DRlow/-cells which levels did not depend on the type and replication of the virus in viral liver cirrhosis. In viral liver cirrhosis, the relative numbers of Lin-HLA-DR-CD33+cells directly correlated with the albumin levels (Rs=0.45; p=0.029). In «nonviral» group an inverse relationship was found between these indicators (Rs = -0.56; p=0.02), in addition the proportion of Lin-HLA-DR-CD33+and CD14+HLA-DRlow/-cells directly correlated with disease severity scores (Child-Pugh and MELD) direct correlation of the proportion of Lin-HLA-DR-CD33+and CD14+HLA-DRlow/-cells with the disease severity scores (Child-Pugh and MELD). Comparison of the initial content of myeloid suppressors with the response to complex therapy (that included autologous bone marrow-derived cell transplantation), showed that in viral liver cirrhosis, the proportion of Lin-HLA-DR-CD33+cells was characterized by a prognostic significance and, at values

A Novel Multi-Population Artificial Bee Colony Algorithm for Energy-Efficient Hybrid Flow Shop Scheduling Problem

Considering green scheduling and sustainable manufacturing, the energy-efficient hybrid flow shop scheduling problem (EHFSP) with a variable speed constraint is investigated, and a novel multi-population artificial bee colony algorithm (MPABC) is developed to minimize makespan, total tardiness and total energy consumption (TEC), simultaneously. It is necessary for manufacturers to fully understand the notion of symmetry in balancing economic and environmental indicators. To improve the search efficiency, the population was randomly categorized into a number of subpopulations, then several groups were constructed based on the quality of subpopulations. A different search strategy was executed in each group to maintain the population diversity. The historical optimization data were also used to enhance the quality of solutions. Finally, extensive experiments were conducted. The results demonstrate that MPABC can achieve an outstanding performance on three metrics DIR, c and nd for the considered EHFSP.

Identifying Changes in Peripheral Lymphocyte Subpopulations in Adult Onset Type 1 Diabetes.

T- and B-lymphocytes play an important role in the pathogenesis of type 1 diabetes (T1D), a chronic disease caused by the autoimmune destruction of the insulin-producing cells in the pancreatic islets. Flow cytometry allows their characterization in peripheral blood, letting to investigate changes in cellular subpopulations that can provide insights in T1D pathophysiology. With this purpose, CD4+ and CD8+ T cells (including naïve, central memory, effector memory and terminally differentiated effector (TEMRA), Th17 and Tregs) and B cells subsets (naïve, unswitched memory, switched memory and transitional B cells) were analysed in peripheral blood of adult T1D patients at disease onset and after ≥2 years using multiparametric flow cytometry. Here we report changes in the percentage of early and late effector memory CD4+ and CD8+ T cells as well as of naïve subsets, regulatory T cells and transitional B cells in peripheral blood of adult patients at onset of T1D when compared with HD. After 2 years follow-up these changes were maintained. Also, we found a decrease in percentage of Th17 and numbers of T cells with baseline. In order to identify potential biomarkers of disease, ROC curves were performed being late EM CD4 T cell subset the most promising candidate. In conclusion, the observed changes in the percentage and/or absolute number of lymphocyte subpopulations of adult T1D patients support the hypothesis that effector cells migrate to the pancreas and this autoimmune process perseveres along the disease. Moreover, multiparametric flow allows to identify those subsets with potential to be considered biomarkers of disease.

Reduction of peripheral regulatory T cells in active rheumatoid arthritis patients with coronary artery disease

ObjectiveTo identify lymphocyte and CD4 + T cell subset characteristics, particularly regulatory T cells (Tregs), in active rheumatoid arthritis (RA) patients with coronary artery disease (CAD).MethodsA total of 54 RA patients with CAD (RA-CAD group), 43 RA patients without CAD (pure RA group), and 43 healthy controls (HC group) were enrolled. The absolute number and frequency of lymphocyte subpopulations and CD4 + T cell subsets were analyzed by flow cytometry. Serum levels of cytokines were analyzed using a cytometric bead array. Clinical and laboratory data were collected retrospectively and their correlation with CD4 + T subsets were analyzed.ResultsThere was a significant decrease in the absolute number of Treg cells (CD4 + CD25 + Foxp3 + T cells) in the RA-CAD group compared to the pure RA group (p < 0.001). Similarly, both the absolute number (p = 0.001) and frequency (p = 0.011) of Tregs in the RA-CAD group were decreased compared to the HCs, causing a Th17/Treg imbalance (p = 0.044). No difference was found in the absolute number and frequency of Treg cells between the pure RA and HC groups. However, the absolute Th17 cell count was increased in the pure RA group (p = 0.032). The serum level of cytokine IL-17 was lower in the RA-CAD group than in the pure RA group (p = 0.023). In the RA-CAD group, the Treg number was negatively correlated with the RA disease activity score and ESR value, and LDL and ApoB100 levels were negatively correlated with the number of Th17 cells.ConclusionsActive RA patients with CAD sustain more severe immune tolerance damage and Th17/Treg disorder. Monitoring of lymphocyte and CD4 + T cell subsets, particularly Treg cells, is crucial to understanding immune status in this group. Focusing on RA activity and CAD risk control, immune-regulatory therapy based on the Treg level may be more beneficial for RA patients with CAD.

Dynamics of local adaptation in a stable environmental gradient

Microbial populations in nature generally inhabit extended environments with substantial spatial variation in ecological factors: light intensity in the ocean, temperature in geothermal hot springs, or a variety of chemical concentrations including salt and pH. In such continuously varying environments, it remains unclear why a finite number of subpopulations form and how this number is set. Here we show that a model of asexual evolution in a gradient maps onto a no-gradient neutral model, and by mapping this model to a gas of kinks and antikinks, we derive the full distribution of the number of coexisting lineages, and their correlation functions. Testing these predictions in controlled laboratory experiments would provide valuable insights into many real-world microbial communities.Received 28 March 2021Revised 13 September 2021Accepted 12 October 2021DOI:https://doi.org/10.1103/PhysRevResearch.3.L042026Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.Published by the American Physical SocietyPhysics Subject Headings (PhySH)Research AreasBiological complexityEcological population dynamicsEvolutionary dynamicsBiological Physics

Single-Cell Proteomics Identifies Leukemia Landscape Associated with Clinical Outcomes in R/R AML Treated with MDM2i (Milademetan) and FLT3i (Quizartinib): Putative Role of CD68 and Diversity Index

Single-Cell Proteomics Identifies Leukemia Landscape Associated with Clinical Outcomes in R/R AML Treated with MDM2i (Milademetan) and FLT3i (Quizartinib): Putative Role of CD68 and Diversity Index

Bayesian Mixture Model of Extended Redundancy Analysis.

Extended redundancy analysis (ERA), a generalized version of redundancy analysis (RA), has been proposed as a useful method for examining interrelationships among multiple sets of variables in multivariate linear regression models. As a limitation of the extant RA or ERA analyses, however, parameters are estimated by aggregating data across all observations even in a case where the study population could consist of several heterogeneous subpopulations. In this paper, we propose a Bayesian mixture extension of ERA to obtain both probabilistic classification of observations into a number of subpopulations and estimation of ERA models within each subpopulation. It specifically estimates the posterior probabilities of observations belonging to different subpopulations, subpopulation-specific residual covariance structures, component weights and regression coefficients in a unified manner. We conduct a simulation study to demonstrate the performance of the proposed method in terms of recovering parameters correctly. We also apply the approach to real data to demonstrate its empirical usefulness.

Development and Validation of the Satisfaction Survey for Inflatable Penile Implant (SSIPI)

No validated English language patient-reported outcome (PRO) currently exists that assesses satisfaction with inflatable penile prosthesis (IPP). Satisfaction data have been largely based primarily on surgeon assessment of patients or using questionnaires that have not been designed for this purpose. To develop an English-language validated PRO that assesses patient satisfaction after IPP surgery. Initially, a literature review and discussions with experts defined domains important to IPP satisfaction (pain, appearance, function, overall satisfaction). The initial 35-item Satisfaction Survey for Inflatable Penile Implant (SSIPI) was developed. Cognitive interviews were then performed with IPP patients (n = 12) to gain feedback on the SSIPI domains and items. These data were used to modify SSIPI with the addition of 2 questions for a final item number of 37. Patients from 4 centers, who were between 6 months and 5 years after IPP, were administered the questionnaire through RedCap. Reliability statistics and content analysis were used to winnow questions to yield the final 16-item version of the SSIPI. Internal consistency was assessed via Cronbach's alpha and item-total correlation. Test-retest reliability was assessed via intraclass correlation coefficients using baseline and 2-week data. For convergent validity, the Erectile Dysfunction Inventory of Treatment Satisfaction and the Self-Esteem and Relationship (SEAR) questionnaire were used. For discriminant validity, the International Prostate Symptom Score (IPSS) was used. Confirmatory factor analysis was used to assess the factor structure of the SSIPI. Internal consistency, test-retest reliability, convergent and discriminant validity, and confirmatory factor analysis were assessed. 118 men were surveyed. Mean age was 66.8 ± 9.5 years. The 16-item SSIPI showed high internal consistency with an overall Cronbach's Alpha of 0.97 (domains 0.85-0.89). Item-total correlations for individual items to subscales ranged from 0.60 to 0.91. The overall test-retest reliability was 0.94 (domains 0.87-0.93). Erectile Dysfunction Inventory of Treatment Satisfaction and Self-Esteem and Relationship had correlations of 0.84 overall (domains 0.57-0.79) and 0.47 overall (domains 0.34-0.44), respectively. International Prostate Symptom Score (discriminant validity) had correlations of -0.29 overall (domains -0.17 to -0.31). SSIPI is the first English-language validated IPP satisfaction PRO. This will enable clinicians to collect satisfaction data in a standardized way. As strengths we have used a rigorous psychometric process and have no industry sponsorship. Limitations include small numbers of specific subpopulations. The SSIPI has demonstrated robust psychometric properties.

Characterization of Tigecycline-Heteroresistant Klebsiella pneumoniae Clinical Isolates From a Chinese Tertiary Care Teaching Hospital.

Tigecycline has been used as one of the therapeutic choices for the treatment of infections caused by multidrug-resistant Klebsiella pneumoniae. However, the emergence of tigecycline heteroresistance has led to great challenges in treating these infections. The purpose of this study was to investigate whether tigecycline-heteroresistant K. pneumoniae (TGCHR-Kp) exists in clinical isolates, and to further characterize the underlying molecular mechanisms involved in the development of tigecycline-resistant subpopulations. Of the 268 tigecycline-susceptible clinical K. pneumoniae isolates, 69 isolates were selected as tigecycline-heteroresistant candidates in the preliminary heteroresistant phenotypic selection by a modified disk diffusion method, and only 21 strains were confirmed as TGCHR-Kp by the population analysis profile (PAP). Pulsed-field gel electrophoresis (PFGE) analysis demonstrated that all the parental TGCHR-Kp isolates were clonally unrelated, and colonies confirmed as the heteroresistant subpopulation showed no significant differences from their respective parental TGCHR-Kp isolates. Efflux pump inhibitors reversed the tigecycline susceptibility in heteroresistant subpopulations. Mutations in the ramR and soxR genes lead to upregulation of the ramA and soxS transcriptional regulators, which in turn induced overexpression of the AcrAB-TolC efflux pump genes in TGCHR-Kps-resistant subpopulations. Moreover, mutations of rpsJ were also found in resistant subpopulations, which suggested that the rpsJ mutation may also lead to tigecycline resistance. Time-kill assays showed that the efficacy of tigecycline against TGCHR-Kps was weakened, whereas the number of resistant subpopulations was enriched by the presence of tigecycline. Our findings imply that the presence of TGCHR-Kps in clinical strains causes severe challenges for tigecycline therapy in clinical practice.

Semiparametric likelihood inference for heterogeneous survival data under double truncation based on a Poisson birth process

We study a selective sampling scheme in which survival data are observed during a data collection period if and only if a specific failure event is experienced. Individual units belong to one of a finite number of subpopulations, which may exhibit different survival behaviour, and thus cause heterogeneity. Based on a Poisson process model for individual emergence of population units, we derive a semiparametric likelihood model, in which the birth distribution is modeled nonparametrically and the lifetime distributions parametrically, and define maximum likelihood estimators. We propose a Newton–Raphson-type optimization method to address numerical challenges caused by the high-dimensional parameter space. The finite-sample properties and computational performance of the proposed algorithms are assessed in a simulation study. Personal insolvencies are studied as a special case of double truncation and we fit the semiparametric model to a medium-sized dataset to estimate the mean age at insolvency and the birth distribution of the underlying population.

PhyliCS: a Python library to explore scCNA data and quantify spatial tumor heterogeneity

BackgroundTumors are composed by a number of cancer cell subpopulations (subclones), characterized by a distinguishable set of mutations. This phenomenon, known as intra-tumor heterogeneity (ITH), may be studied using Copy Number Aberrations (CNAs). Nowadays ITH can be assessed at the highest possible resolution using single-cell DNA (scDNA) sequencing technology. Additionally, single-cell CNA (scCNA) profiles from multiple samples of the same tumor can in principle be exploited to study the spatial distribution of subclones within a tumor mass. However, since the technology required to generate large scDNA sequencing datasets is relatively recent, dedicated analytical approaches are still lacking.ResultsWe present PhyliCS, the first tool which exploits scCNA data from multiple samples from the same tumor to estimate whether the different clones of a tumor are well mixed or spatially separated. Starting from the CNA data produced with third party instruments, it computes a score, the Spatial Heterogeneity score, aimed at distinguishing spatially intermixed cell populations from spatially segregated ones. Additionally, it provides functionalities to facilitate scDNA analysis, such as feature selection and dimensionality reduction methods, visualization tools and a flexible clustering module.ConclusionsPhyliCS represents a valuable instrument to explore the extent of spatial heterogeneity in multi-regional tumour sampling, exploiting the potential of scCNA data.