On the Properties of the R2 Indicator

International audienceIn multiobjective optimization, set-based performance indicators are commonly used to assess the quality of a Pareto front approximation. Based on the scalarization obtained by these indicators, a performance comparison of multiobjective optimization algorithms becomes possible. The R2 and the Hypervolume (HV) indicator represent two recommended approaches which have shown a correlated behavior in recent empirical studies. Whereas the HV indicator has been comprehensively analyzed in the last years, almost no studies on the R2 indicator exist. In this paper, we thus perform a comprehensive investigation of the properties of the R2 indicator in a theoretical and empirical way. The influence of the number and distribution of the weight vectors on the optimal distribution of μ solutions is analyzed. Based on a comparative analysis, specific characteristics and differences of the R2 and HV indicator are presented

Biobjective Performance Assessment with the COCO Platform

This document details the rationales behind assessing the performance of numerical black-box optimizers on multi-objective problems within the COCO platform and in particular on the biobjective test suite bbob-biobj. The evaluation is based on a hypervolume of all non-dominated solutions in the archive of candidate solutions and measures the runtime until the hypervolume value succeeds prescribed target values

Salivary gland mucoepidermoid carcinoma is a clinically, morphologically and genetically heterogeneous entity: a clinicopathological study of 40 cases with emphasis on grading, histological variants and presence of the t(11;19) translocation

International audienceAims: To correlate World Health Organization (WHO) grade, patient's outcome and presence of t(11;19) to histological tumor variants in 40 well characterized mucoepidermoid carcinomas (MECs) out of a series of 290 salivary gland carcinomas. Methods and Results: MECs were classified as classical based on the presence of equal proportions of the three cell types or the dominance (≥50%) of mucous cells beside at least one other cell type, and as variant if composed of ≥80% single cell type. Classical MECs were more common (n=23). Variant MECs had predominant squamoid (n=9), eosinophilic (n=5), or clear cell (n=3) morphology. 27 tumors were WHO grade 1, 3 grade 2 and 10 grade 3. The t(11;19) was detected in 82%, 35% and 0% of classical MEC, variant MEC and non-MEC, respectively. Classical MECs were significantly associated with age ≤60 years (p<0.001), grade 1 (p<0.001), and t(11;19) (p=0.003). Short overall survival was significantly associated with age >60 years (p=0.001) and UICC stage >I (p=0.031), residual tumor (p<0.001), tumor grade >1 (p=0.001) and squamoid variant (p=0.002) in Kaplan-Meier analysis. Conclusions: The results underscore the great histological diversity of MEC, the reproducibility of the WHO grading and the value of histological subtypes as an additional prognostic factor

Benchmarking the Pure Random Search on the Bi-objective BBOB-2016 Testbed

International audienceThe Comparing Continuous Optimizers platform COCO has become a standard for benchmarking numerical (single-objective) optimization algorithms effortlessly. In 2016, COCO has been extended towards multi-objective optimization by providing a first bi-objective test suite. To provide a baseline, we benchmark a pure random search on this bi-objective bbob-biobj test suite of the COCO platform. For each combination of function, dimension n, and instance of the test suite, $10^6 · n$ candidate solutions are sampled uniformly within the sampling box $[−5, 5]^n$

Benchmarking MATLAB's gamultiobj (NSGA-II) on the Bi-objective BBOB-2016 Test Suite

International audienceIn this paper, we benchmark a variant of the well-known NSGA-II algorithm of Deb et al. on the biobjective bbob-biobj test suite of the Comparing Continuous Optimizers platform COCO. To this end, we employ the implementation of MATLAB's gamultiobj toolbox with its default settings and a population size of 100

CX3CL1 Overexpression Prevents the Formation of Lung Metastases in Trastuzumab-Treated MDA-MB-453-Based Humanized Tumor Mice (HTM)

CX3CL1 is a multifunctional chemokine that is involved in numerous biological processes, such as immune cell attraction and enhanced tumor immune cell interaction, but also in enhancing tumor cell proliferation and metastasis. The multifarious activity is partially determined by two CX3CL1 isoforms, a membrane-bound and a soluble version generated by proteolytic cleavage through proteases. Here, we investigated the impact of CX3CL1 overexpression in MDA-MB-453 and SK-BR-3 breast cancer cells. Moreover, we evaluated the therapeutic capacity of Matrix-Metalloproteinases-inhibitors TMI-1 and GI254023X in combination with the anti-HER2 antibody trastuzumab in vitro and in vivo. TMI-1 and GI254023X caused a reduced shedding of CX3CL1 and of HER2 in vitro but without effects on tumor cell proliferation or viability. In addition, trastuzumab treatment did not retard MDA-MB-453 cell expansion in vitro unless CX3CL1 was overexpressed upon transfection (MDA-MB-453CX3CL1). In humanized tumor mice, which show a coexistence of human tumor and human immune system, CX3CL1 overexpression resulted in a slightly enhanced tumor growth. However, trastuzumab treatment attenuated tumor growth of both MDA-MB-453CX3CL1 and empty vector transfected MDA-MB-453 transplanted mice but showed enhanced efficiency especially in preventing lung metastases in CX3CL1 overexpressing cancer cells. However, TMI-1 did not further enhance the trastuzumab treatment efficacy

Differential Expression of PD-L1 during Cell Cycle Progression of Head and Neck Squamous Cell Carcinoma

The expression of PD-L1 by tumor cells is mainly associated with its immunosuppressive effect. In fact, PD-1/PD-L1 immune checkpoint inhibitors demonstrated remarkable effects in advanced cancer patients including HNSCC. In this context, irradiation is currently being investigated as a synergistic treatment modality to immunotherapy. However, the majority of HNSCC patients still show little improvement or even hyperprogression. Interestingly, there is increasing evidence for additional cell-intrinsic functions of PD-L1 in tumor cells. In previous studies, we showed that PD-L1 has a strong influence on proliferation, migration, invasion, and survival after irradiation. We demonstrated that cellular expression and localization of PD-L1 differed depending on sensitivity to irradiation. Here, we show that PD-L1 is also differentially expressed during cell cycle progression of HNSCC. Furthermore, cellular localization of PD-L1 also changes depending on a particular cell cycle phase. Moreover, distinct observations occurred depending on the general differentiation status. Overall, the function of PD-L1 cannot be generalized. Rather, it depends on the differentiation status and microenvironment. PD-L1 expression and localization are variable, depending on different factors. These findings may provide insight into why differential response to PD-1/PD-L1 antibody therapy can occur. Detailed understanding of cell-intrinsic PD-L1 functions will further allow antibody-based immunotherapy to be optimized

The Impact of Initial Designs on the Performance of MATSuMoTo on the Noiseless BBOB-2015 Testbed: A Preliminary Study

International audienceMost surrogate-assisted algorithms for expensive optimization follow the same framework: After an initial design phase in which the true objective function is evaluated for a few search points, an iterative process builds a surrogate model of the expensive function and, based on the current model, a so-called infill criterion suggests one or more points to be evaluated on the true problem. The evaluations are used to successively update and refine the model. Implementing surrogate-assisted algorithms requires several design choices to be made. It is practically relevant to understand their impact on the algorithms' performance. Here, we start to look at the initial design phase and experimentally investigate the performance of the freely available MATLAB Sur-rogate Model Toolbox (MATSuMoTo) with regard to the initial design. The results are preliminary in the sense that not all possible choices are investigated, but we can make first well-founded statements about whether Latin Hyper-cube or uniform random sampling should be preferred and about the effect of the size of the initial design on the performance of MATSuMoTo on the 24 noiseless test functions of the BBOB-2015 test suite