215 research outputs found
Tumor-targeted and immune-targeted monoclonal antibodies: Going from passive to active immunotherapy
No full textMonoclonal antibodies (mAbs) have inaugurated the concepts of tumor-targeted therapy and personalized medicine. A new family of mAbs is currently emerging in the clinic, which target immune cells rather than cancer cells. These immune-targeted therapies have recently demonstrated long-term tumor responses in adults with refractory/relapsing metastatic solid tumors. Pediatric cancers are different from their adult counterparts in terms of histological features and immune infiltrates. However, the same immune checkpoint targets can be expressed within the microenvironment of pediatric tumors. The benefits of immune checkpoint blockade in pediatric cancers are currently under evaluation in early phase clinical trials
Immunotherapy for Pediatric Malignancies
No full textThis book provides a comprehensive overview of current immunotherapy strategies, and how these may be applicable to childhood cancers. The first part of the book reviews how the immune system recognizes cancer, and the various escape mechanisms allowing tumour growth. The importance of the tumor microenvironment and the challenges this may present to achieving effective immunotherapy are discussed. Monoclonal antibodies, cellular, cytokine and vaccine therapies are all comprehensively reviewed, with particular focus on their potential application to pediatric cancers. Practical aspects of delivering such therapies to children, likely toxicities and potential biomarkers are considered. Finally, consideration is given to how, in the longer term, such therapies may be combined with conventional therapies such as chemotherapy and radiotherapy
AUTHOR CORRECTION - ERS International Congress 2019:highlights from Best Abstract awardees
No full textLorna E. Latimer, Marieke Duiverman, Mahmoud I. Abdel-Aziz, Gulser Caliskan, Sara M. Mensink-Bout, Alberto Mendoza-Valderrey, Aurelien Justet, Junichi Omura, Karthi Srikanthan, Jana De Brandt. Breathe 2019; 15: e143–e149. This article from the December 2019 issue of Breathe was published with an error in the name of one of the authors. The corrected author list is shown above. The article has been corrected and republished online.</p
Abstract 2466: Sequential tumor and immune targeted immunotherapy: Anti-tumor activity of antibody drug conjugate Trastuzumab Emtansine (T-DM1) with CD137 stimulation in HER-2+ breast cancer therapy
No full textInternational audienceThe mainstay of HER2+ breast cancer treatment has been monoclonal antibody therapy with Trastuzumab, a humanized antibody that targets HER-2. However, the efficacy of Trastuzumab monotherapy is only 10-15%. Therefore, strategies are being developed to enhance its therapeutic efficacy. Our previous study demonstrated that stimulation of NK cells with an anti-CD137 agonistic mAb enhanced Trastuzumab-mediated Antibody Dependent Cellular Cytotoxicity (ADCC). Anti-CD137 agonistic mAb enhanced anti-breast cancer activity of Trastuzumab in vivo in a xenotransplanted human breast cancer model (Kohrt et al. J Clin. Invest, 2012, 22:3). We have developed a treatment regimen consisting of sequential administration of Trastuzumab followed by CD137 antibody as three weekly injections. This regimen demonstrated more potent antitumor activity than administration of anti-CD137 mAb followed by Trastuzumab. Our combination therapy was superior to Traztuzumab alone in a primary HER2-overexpressing-breast tumor xenotransplant model but was ineffective in low HER-2 expressing breast cancer model. Next, we evaluated the therapeutic efficacy of FDA approved antibody drug conjugate Trastuzumab Emtansine (T-DM1) in combination with CD137 antibody. We used HER2 over-expressing HER18 xenograft model and an SU-258 primary breast cancer model in our studies. Following tumor inoculation, mice received either T-DM1 on day 3 (for HER18 xenograft), or day 30 (for SU-258) and anti-CD137 antibody on day 4(or HER18) or day 31(for SU-258) with each treatment repeated weekly for a total of three weeks. Sequential antibody strategy with T-DM1 and CD137 significantly improved survival compared to T-DM1 alone or with Trastuzumab and CD137 antibody. Our results demonstrate that T-DM1 retains its potency and demonstrates synergistic activity with anti-CD137 mAb therapy against HER2-overexpressing breast cancer models. Our results support a novel, sequential antibody approach against HER-2+breast cancer, by targeting first the tumor with an antibody drug conjugate and then the host immune system. Clinical investigations are now planned to determine the clinical outcome of our immunotherapy strategy. Citation Format: Suparna Dutt, Narendiran Rajasekaran, Aurelien Marabelle, Roch Houot, Mohith Sadaram, Jonathan Hebb, Idit Sagiv-Barfi, Sid Ambulkar, Amanda Rajapaksa, Cariad Chester, Erin Waller, Holbrook Kohrt. Sequential tumor and immune targeted immunotherapy: Anti-tumor activity of antibody drug conjugate Trastuzumab Emtansine (T-DM1) with CD137 stimulation in HER-2+ breast cancer therapy. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2466. doi:10.1158/1538-7445.AM2015-246
Pembrolizumab in Patients With Microsatellite Instability–High Advanced Endometrial Cancer: Results From the KEYNOTE-158 Study
No full textPURPOSE Pembrolizumab demonstrated durable antitumor activity in patients with previously treated, advanced microsatellite instability–high or mismatch repair–deficient (MSI-H/dMMR) tumors, including endometrial cancer, in the nonrandomized, open-label, multicohort, phase II KEYNOTE-158 study (NCT02628067). We report efficacy and safety outcomes for patients with MSI-H/dMMR endometrial cancer enrolled in KEYNOTE-158. METHODS Eligible patients from cohorts D (endometrial cancer, regardless of MSI-H/dMMR status) and K (any MSI-H/dMMR solid tumor, except colorectal) with previously treated, advanced MSI-H/dMMR endometrial cancer received pembrolizumab 200 mg once every 3 weeks for 35 cycles. The primary end point was objective response rate per RECIST version 1.1 by independent central radiologic review. Secondary end points included duration of response, progression-free survival, overall survival, and safety. RESULTS As of October 5, 2020, 18 of 90 treated patients (20%) had completed 35 cycles of pembrolizumab and 52 (58%) had discontinued treatment. In the efficacy population (patients who received 26 weeks of follow-up; N 5 79), the median time from first dose to data cutoff was 42.6 (range, 6.4-56.1) months. The objective response rate was 48% (95% CI, 37 to 60), and median duration of response was not reached (2.9-49.71 months). Median progression-free survival was 13.1 (95% CI, 4.3 to 34.4) months, and median overall survival was not reached (95% CI, 27.2 months to not reached). Among all treated patients, 76% had $ 1 treatment-related adverse event (grades 3-4, 12%). There were no fatal treatment-related events. Immune-mediated adverse events or infusion reactions occurred in 28% of patients (grades 3-4, 7%; no fatal events). CONCLUSION Pembrolizumab demonstrated robust and durable antitumor activity and encouraging survival outcomes with manageable toxicity in patients with previously treated, advanced MSI-H/dMMR endometrial cancer. © 2022 by American Society of Clinical Oncology
Parametrized cosmological mass maps dataset
No full textParametrized cosmological mass maps dataset
This dataset consists of the non-tomographic training and testing set without noise and intrinsic alignments.
It was introduced in the following paper
Fluri, Janis, et al. "Cosmological constraints with deep learning from KiDS-450 weak lensing maps." Physical Review D 100.6 (2019): 063514.
Furthermore, this dataset is released with the following paper:
Perraudin, Nathanaël, et al. "Emulation of cosmological mass maps with conditional generative adversarial networks." arXiv preprint arXiv:2004.08139 (2020).
Code related to this dataset can be found in https://renkulab.io/projects/nathanael.perraudin/darkmattergan
Description
The simulation grid consists of different cosmologies assuming a flat LambdaCDM universe.
Each of these 57 configurations was run with different values of Omega_m and sigma_8, resulting in the following parameter grid.| Omega_m, sigma_8
0.101, 1.304
0.102, 1.125
0.103, 0.947
0.120, 1.178
0.123, 1.006
0.127, 0.836
0.137, 1.230
0.142, 1.063
0.148, 0.900
0.154, 1.281
0.156, 0.741
0.161, 1.119
0.169, 0.961
0.171, 1.331
0.178, 0.807
0.179, 1.173
0.188, 1.019
0.189, 0.659
0.196, 1.225
0.199, 0.870
0.207, 1.075
0.212, 0.727
0.219, 0.930
0.225, 1.129
0.227, 0.591
0.233, 0.791
0.238, 0.988
0.250, 0.658
0.254, 0.852
0.257, 1.043
0.269, 0.534
0.271, 0.723
0.273, 0.910
0.291, 0.601
0.291, 0.783
0.292, 0.966
0.311, 0.842
0.312, 0.664
0.314, 0.487
0.330, 0.898
0.332, 0.724
0.335, 0.552
0.352, 0.782
0.356, 0.614
0.370, 0.838
0.376, 0.673
0.382, 0.510
0.395, 0.730
0.402, 0.570
0.413, 0.784
0.421, 0.628
0.431, 0.475
0.440, 0.683
0.450, 0.533
0.458, 0.737
0.469, 0.589
0.487, 0.643
Each zip file in the dataset corresponds to 1 of these combinations and contains 12 files containing 1000 images.
The source galaxy redshift distribution corresponding to these maps is the full, non-tomographic redshift distribution n(z) from Fluri et. al.
The projected matter distribution was pixelised into images of size 128px x 128px, which correspond to 5deg x 5deg of the sky.
Eventually, the resulting dataset consists of 57 sets of 12'000 sky convergence maps for a total of samples.
Citations
If you use this dataset, please cite:
@article{perraudin2020emulation,
title={Emulation of cosmological mass maps with conditional generative adversarial networks},
author={Perraudin, Nathana{\"e}l and Marcon, Sandro and Lucchi, Aurelien and Kacprzak, Tomasz},
journal={arXiv preprint arXiv:2004.08139},
year={2020}
}
and
@article{fluri2019cosmological,
title={Cosmological constraints with deep learning from KiDS-450 weak lensing maps},
author={Fluri, Janis and Kacprzak, Tomasz and Lucchi, Aurelien and Refregier, Alexandre and Amara, Adam and Hofmann, Thomas and Schneider, Aurel},
journal={Physical Review D},
volume={100},
number={6},
pages={063514},
year={2019},
publisher={APS}
Abstract IA25: Local immunomodulation at a single site of tumor generates a therapeutic immune response that cures metastatic disease at distant sites, including the brain.
No full textCosmological N-body simulations: a challenge for scalable generative models: Tensorflow checkpoints
No full text<p><strong>Tensorflow checkpoints: Cosmological N-body simulations: a challenge for scalable generative models</strong></p>
<p>This corresponds to the Tensorflow checkpoints for the experiments in the paper <strong>Cosmological N-body simulations: a challenge for scalable generative models</strong> by Nathanaël Perraudin, Ankit Srivastava, Aurelien Lucchi, Tomasz Kacprzak, Thomas Hofmann, Alexandre Refregier, Adam Amara.</p>
<pre><code>@inproceedings{perraudin2019cosmological,
title = {Cosmological N-body simulations: a challenge for scalable generative models},
author = {Nathana\"el, Perraudin and Ankit, Srivastava and Kacprzak, Tomasz and Lucchi, Aurelien and Hofmann, Thomas and R{\'e}fr{\'e}gier, Alexandre},
year = {2019},
archivePrefix = {arXiv},
eprint = {1908.05519},
url = {https://arxiv.org/abs/1908.05519},
}
</code></pre>
<p>Please check the assotiated github page <a href="https://github.com/nperraud/3DcosmoGAN">https://github.com/nperraud/3DcosmoGAN</a> for additional information.</p>
<p>This corresponds to the Tensorflow checkpoints for the experiments in the paper<br>
**Cosmological N-body simulations: a challenge for scalable generative models** by<br>
Nathanaël Perraudin, Ankit Srivastava, Aurelien Lucchi, Tomasz Kacprzak, Thomas Hofmann, Alexandre Refregier, Adam Amara.</p>
<p>Please check the assotiated github page <a href="https://github.com/nperraud/3DcosmoGAN">https://github.com/nperraud/3DcosmoGAN</a> for additional information.</p>
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