Mullinax2016 - Mathematical model of tumor-immune cell interactions to optimize the meta-phenotype of TIL subpopulations
This model is described in the publication:
John Mullinax, Cliona O’Farrelly, Jacob G. Scott, Andreas Buttenschön, Asmaa E. Elkenawi, Fadoua El Moustaid, Alexander G. Fletcher, Clemens Grassberger, Eunjung Kim, Andriy Marusyk, Harry L.O. McClelland, Daria Miroshnychenko, Daniel Nichol.
"Harnessing the lymphocyte meta-phenotype to optimize adoptive cell therapy".
bioRxiv 085910; doi: 10.1101/085910
Figure 4 could not be reproduced. Attempted changing parameter values for Fig. 4(D) simulation, but plots were still not exact match for all species.
Project description:Analysis of peripheral blood mononuclear cells (PBMCs) separated from whole blood of healthy male subjects; - prior to onset of exercise; - immediately following the end of exercise and; - immediately following 1 hour of recovery from exercise. To reduce individual variation and other confounding events, such as spontaneous up- and downregulation of genes, the 15 subjects in this study were pooled into 5 groups of 3 subjects each. The pools were not randomized; rather, we attempted to match the mean lymphocyte response to exercise across the five groups.
Project description:Adoptive T cell transfer (ACT) with ex vivo-expanded tumor-reactive T cells proved to be successful for the treatment of metastatic melanoma patients. Mixed lymphocyte tumor cell cultures (MLTC) can be used to generate tumor-specific T cells for ACT; however, in a number of cases tumor-reactive T cell, expansion is far from optimal. We hypothesized that this is due to tumor intrinsic and extrinsic factors and aimed to identify and manipulate these factors so to optimize our clinical, GMP-compliant MLTC protocol. We found that the tumor cell produced IDO and/or galectin-3, and the accumulation of CD4+CD25hiFoxP3+ T cells suppressed the expansion of tumor-specific T cells in the MLTC. Strategies to eliminate CD4+CD25hiFoxP3+ T cells during culture required the depletion of the whole CD4+ T cell population and were found to be undesirable. Blocking of IDO and galectin-3 was feasible and resulted in improved efficiency of the MLTC. Implementation of these findings in clinical protocols for ex vivo expansion of tumor-reactive T cells holds promise for an increased therapeutic potential of adoptive cell transfer treatments with tumor-specific T cells.
Project description:Comparative Dynamic Transcriptome Analysis (cDTA) enables global analysis of newly synthesized RNA as described in Sun et al. Genome Res. 2012 (DOI:10.1101/gr.130161.111) and reveals defects in transcription with much higher sensitivity than conventional steady-state methods. cDTA was carried out as described in Sun et al. Genome Res. 2012 (DOI:10.1101/gr.130161.111), using the S. cerevisiae heterozygous Med17/med17delta strain (Euroscarf) transfected with plasmids pRS315-SRB4 or pRS315-srb4-ts as described in Larivi?re et al. Nature. 2012 (DOI:10.1038/nature11670), and Y40343-wildtype (Euroscarf) or Med18-FRB-KanMX6 (Euroscarf) strains. Heatshock of SRB4 and srb4-ts strains was applied for 18 or 60 minutes at 37C prior to RNA labeling as described in Sun et al. Genome Res. 2012 (DOI:10.1101/gr.130161.111). To deplete the Med18 subunit from the nucleus, anchor-away experiments were performed by rapamycin treatment (1 ug/ml in 200 mL YPD) for 18 or 60 minutes at 30C prior to RNA labeling as described in Sun et al. Mol. Cell. 2013 (DOI:10.1016/j.molcel.2013.09.010). Data analysis was as described in Sun et al. Genome Res. 2012 (DOI:10.1101/gr.130161.111).
Project description:Predicting the results of soccer competitions and the contributions of match attributes, in particular, has gained popularity in recent years. Big data processing obtained from different sensors, cameras and analysis systems needs modern tools that can provide a deep understanding of the relationship between this huge amount of data produced by sensors and cameras, both linear and non-linear data. Using data mining tools does not appear sufficient to provide a deep understanding of the relationship between the match attributes and results and how to predict or optimize the results based upon performance variables. This study aimed to suggest a different approach to predict wins, losses and attributes' sensitivities which enables the prediction of match results based on the most sensitive attributes that affect it as a second step. A radial basis function neural network model has successfully weighted the effectiveness of all match attributes and classified the team results into the target groups as a win or loss. The neural network model's output demonstrated a correct percentage of win and loss of 83.3% and 72.7% respectively, with a low Root Mean Square training error of 2.9% and testing error of 0.37%. Out of 75 match attributes, 19 were identified as powerful predictors of success. The most powerful respectively were: the Total Team Medium Pass Attempted (MBA) 100%; the Distance Covered Team Average in zone 3 (15-20 km/h; Zone3_TA) 99%; the Team Average ball delivery into the attacking third of the field (TA_DAT) 80.9%; the Total Team Covered Distance without Ball Possession (Not in_Poss_TT) 76.8%; and the Average Distance Covered by Team (Game TA) 75.1%. Therefore, the novel radial based function neural network model can be employed by sports scientists to adapt training, tactics and opposition analysis to improve performance.
Project description:The prognostic role of tumor-infiltrating CD57-positive lymphocytes (CD57+ lymphocytes) in human solid tumors remains controversial. Herein, we conducted a meta-analysis including 26 published studies with 7656 patients identified from PubMed and EBSCO to assess the prognostic impact of tumor-infiltrating CD57+ lymphocytes in human solid tumors. We found that CD57+ lymphocyte infiltration significantly improved overall survival (OS) including 1 - year, 3 - year and 5 - year survival, and disease - free survival (DFS) in all types of solid tumors. In stratified analyses, CD57+ lymphocyte infiltration was significantly associated with better OS in hepatocellular, esophageal, head and neck carcinoma, non-small cell lung cancer, 5 - year survival in colorectal cancer, and 3 - year and 5 - year survival in gastric cancer, but not with 1 - year survival in gastric cancer, or 1 - year or 3 - year survival in colorectal cancer. In addition, high density of intratumoral CD57+ lymphocytes was significantly inversely correlated with lymph node metastasis and TNM stage of solid tumor. In conclusion, CD57+ lymphocyte infiltration leads to a favorable clinical outcome in solid tumors, implicating that it is a useful biomarker for prognosis and adoptive immunotherapy based on these cells may be a promising choice for treatment.
Project description:Novel strategies for the therapy of recurrent ovarian cancer are warranted. We report a study of a combinatorial approach encompassing dendritic cell (DC)-based autologous whole tumor vaccination and anti-angiogenesis therapy, followed by the adoptive transfer of autologous vaccine-primed CD3/CD28-co-stimulated lymphocytes. Recurrent ovarian cancer patients for whom tumor lysate was available from prior cytoreductive surgery underwent conditioning with intravenous bevacizumab and oral metronomic cyclophosphamide, sequentially followed by (1) bevacizumab plus vaccination with DCs pulsed with autologous tumor cell lysate supernatants, (2) lymphodepletion and (3) transfer of 5 × 109 autologous vaccine-primed T-cells in combination with the vaccine. Feasibility, safety as well as immunological and clinical efficacy were evaluated. Six subjects received this vaccination. Therapy was feasible, well tolerated, and elicited antitumor immune responses in four subjects, who also experienced clinical benefits. Of these, three patients with residual measurable disease received outpatient lymphodepletion and adoptive T-cell transfer, which was well tolerated and resulted in a durable reduction of circulating regulatory T cells and increased CD8+ lymphocyte counts. The vaccine-induced restoration of antitumor immunity was achieved in two subjects, who also demonstrated clinical benefits, including one complete response. Our findings indicate that combinatorial cellular immunotherapy for the treatment of recurrent ovarian cancer is well tolerated and warrants further investigation. Several modifications of this approach can be envisioned to optimize immunological and clinical outcomes.
Project description:Glioma is the most common malignant brain tumor and has high lethality. This tumor generated a robust inflammatory response that results in the deterioration of the disease. However, the prognostic role of systemic cellular inflammatory indicators in gliomas remains controversial. This meta-analysis aimed to assess the prognostic significance of preoperative neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), lymphocyte/monocyte ratio (LMR), red cell distribution width (RDW), and prognostic nutritional index (PNI) in patients with gliomas. Databases of PubMed, EMBASE, Web of Science, and The Cochrane Library were systematically searched for all studies published up to January 2019. Study screening and data extraction followed established Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The Newcastle-Ottawa Scale was used to assess the quality of studies. Eighteen studies containing 3,261 patients were included. The analyses showed an increased NLR or RDW was found to be an independent predictor of worse survival in patients with gliomas (hazard ratio (HR): 1.38; 95% confidence interval (CI): 1.09-1.74; P = 0.008; and HR: 1.40; 95% CI: 1.13-1.74; P = 0.002, respectively). Furthermore, a higher PNI indicates a better overall survival (OS; HR: 0.57; 95% CI: 0.42-0.77; P = 0.0002). For the evaluation of PLR and LMR, none of these variables correlated with OS (P = 0.91 and P = 0.21, respectively). Our meta-analysis indicates the NLR, RDW, and PNI rather than PLR and LMR are the independent index for predicting the OS of gliomas. Pre-operative NLR, RDW, and PNI can help to evaluate disease progression, optimize treatment, and follow-up in patients with gliomas.
Project description:The San Andreas fault is considered to be the primary plate boundary fault in southern California and the most likely fault to produce a major earthquake. I use dynamic rupture modeling to show that the San Jacinto fault is capable of rupturing along with the San Andreas in a single earthquake, and interpret these results along with existing paleoseismic data and historic damage reports to suggest that this has likely occurred in the historic past. In particular, I find that paleoseismic data and historic observations for the ~M7.5 earthquake of 8 December 1812 are best explained by a rupture that begins on the San Jacinto fault and propagates onto the San Andreas fault. This precedent carries the implications that similar joint ruptures are possible in the future and that the San Jacinto fault plays a more significant role in seismic hazard in southern California than previously considered. My work also shows how physics-based modeling can be used for interpreting paleoseismic data sets and understanding prehistoric fault behavior.