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4. Compressive stress triggers fibroblasts spreading over cancer cells to generate carcinoma in situ organization

Author

Fabien Bertillot, Laetitia Andrique, Carlos Ureña Martin, Olivier Zajac, Ludmilla de Plater, Michael M. Norton, Aurélien Richard, Kevin Alessandri, Basile G. Gurchenkov, Florian Fage, Atef Asnacios, Christophe Lamaze, Moumita Das, Jean- Léon Maître, Pierre Nassoy, and Danijela Matic Vignjevic

Subjects
Biology (General), QH301-705.5
Abstract

Abstract At the early stage of tumor progression, fibroblasts are located at the outer edges of the tumor, forming an encasing layer around it. In this work, we have developed a 3D in vitro model where fibroblasts’ layout resembles the structure seen in carcinoma in situ. We use a microfluidic encapsulation technology to co-culture fibroblasts and cancer cells within hollow, permeable, and elastic alginate shells. We find that in the absence of spatial constraint, fibroblasts and cancer cells do not mix but segregate into distinct aggregates composed of individual cell types. However, upon confinement, fibroblasts enwrap cancer cell spheroid. Using a combination of biophysical methods and live imaging, we find that buildup of compressive stress is required to induce fibroblasts spreading over the aggregates of tumor cells. We propose that compressive stress generated by the tumor growth might be a mechanism that prompts fibroblasts to form a capsule around the tumor.

Published
2024
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5. Multi-institutional prognostic modeling of survival outcomes in NSCLC patients treated with first-line immunotherapy using radiomics

Author

Sevinj Yolchuyeva, Leyla Ebrahimpour, Marion Tonneau, Fabien Lamaze, Michele Orain, François Coulombe, Julie Malo, Wiam Belkaid, Bertrand Routy, Philippe Joubert, and Venkata SK. Manem

Subjects
Medicine
Abstract

Abstract Background Immune checkpoint inhibitors (ICIs) have emerged as one of the most promising first-line therapeutics in the management of non-small cell lung cancer (NSCLC). However, only a subset of these patients responds to ICIs, highlighting the clinical need to develop better predictive and prognostic biomarkers. This study will leverage pre-treatment imaging profiles to develop survival risk models for NSCLC patients treated with first-line immunotherapy. Methods Advanced NSCLC patients (n = 149) were retrospectively identified from two institutions who were treated with first-line ICIs. Radiomics features extracted from pretreatment imaging scans were used to build the predictive models for progression-free survival (PFS) and overall survival (OS). A compendium of five feature selection methods and seven machine learning approaches were utilized to build the survival risk models. The concordance index (C-index) was used to evaluate model performance. Results From our results, we found several combinations of machine learning algorithms and feature selection methods to achieve similar performance. K-nearest neighbourhood (KNN) with ReliefF (RL) feature selection was the best-performing model to predict PFS (C-index = 0.61 and 0.604 in discovery and validation cohorts), while XGBoost with Mutual Information (MI) feature selection was the best-performing model for OS (C-index = 0.7 and 0.655 in discovery and validation cohorts). Conclusion The results of this study highlight the importance of implementing an appropriate feature selection method coupled with a machine learning strategy to develop robust survival models. With further validation of these models on external cohorts when available, this can have the potential to improve clinical decisions by systematically analyzing routine medical images.

Published
2024
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9. Caveolin-1 protects endothelial cells from extensive expansion of transcellular tunnel by stiffening the plasma membrane

Author

Camille Morel, Eline Lemerle, Feng-Ching Tsai, Thomas Obadia, Nishit Srivastava, Maud Marechal, Audrey Salles, Marvin Albert, Caroline Stefani, Yvonne Benito, François Vandenesch, Christophe Lamaze, Stéphane Vassilopoulos, Matthieu Piel, Patricia Bassereau, David Gonzalez-Rodriguez, Cecile Leduc, and Emmanuel Lemichez

Subjects
caveolin-1, plasma membrane mechanics, transendothelial cell macroaperture, bacterial toxin, Medicine, Science, Biology (General), QH301-705.5
Abstract

Large transcellular pores elicited by bacterial mono-ADP-ribosyltransferase (mART) exotoxins inhibiting the small RhoA GTPase compromise the endothelial barrier. Recent advances in biophysical modeling point toward membrane tension and bending rigidity as the minimal set of mechanical parameters determining the nucleation and maximal size of transendothelial cell macroaperture (TEM) tunnels induced by bacterial RhoA-targeting mART exotoxins. We report that cellular depletion of caveolin-1, the membrane-embedded building block of caveolae, and depletion of cavin-1, the master regulator of caveolae invaginations, increase the number of TEMs per cell. The enhanced occurrence of TEM nucleation events correlates with a reduction in cell height due to the increase in cell spreading and decrease in cell volume, which, together with the disruption of RhoA-driven F-actin meshwork, favor membrane apposition for TEM nucleation. Strikingly, caveolin-1 specifically controls the opening speed of TEMs, leading to their dramatic 5.4-fold larger widening. Consistent with the increase in TEM density and width in siCAV1 cells, we record a higher lethality in CAV1 KO mice subjected to a catalytically active mART exotoxin targeting RhoA during staphylococcal bloodstream infection. Combined theoretical modeling with independent biophysical measurements of plasma membrane bending rigidity points toward a specific contribution of caveolin-1 to membrane stiffening in addition to the role of cavin-1/caveolin-1-dependent caveolae in the control of membrane tension homeostasis.

Published
2024
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12. Radiomics approaches to predict PD-L1 and PFS in advanced non-small cell lung patients treated with immunotherapy: a multi-institutional study

Author

Sevinj Yolchuyeva, Elena Giacomazzi, Marion Tonneau, Fabien Lamaze, Michele Orain, François Coulombe, Julie Malo, Wiam Belkaid, Bertrand Routy, Philippe Joubert, and Venkata S. K. Manem

Subjects
Medicine, Science
Abstract

Abstract With the increasing use of immune checkpoint inhibitors (ICIs), there is an urgent need to identify biomarkers to stratify responders and non-responders using programmed death-ligand (PD-L1) expression, and to predict patient-specific outcomes such as progression free survival (PFS). The current study is aimed to determine the feasibility of building imaging-based predictive biomarkers for PD-L1 and PFS through systematically evaluating a combination of several machine learning algorithms with different feature selection methods. A retrospective, multicenter study of 385 advanced NSCLC patients amenable to ICIs was undertaken in two academic centers. Radiomic features extracted from pretreatment CT scans were used to build predictive models for PD-L1 and PFS (short-term vs. long-term survivors). We first employed the LASSO methodology followed by five feature selection methods and seven machine learning approaches to build the predictors. From our analyses, we found several combinations of feature selection methods and machine learning algorithms to achieve a similar performance. Logistic regression with ReliefF feature selection (AUC = 0.64, 0.59 in discovery and validation cohorts) and SVM with Anova F-test feature selection (AUC = 0.64, 0.63 in discovery and validation datasets) were the best-performing models to predict PD-L1 and PFS. This study elucidates the application of suitable feature selection approaches and machine learning algorithms to predict clinical endpoints using radiomics features. Through this study, we identified a subset of algorithms that should be considered in future investigations for building robust and clinically relevant predictive models.

Published
2023
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13. Imaging-Based Biomarkers Predict Programmed Death-Ligand 1 and Survival Outcomes in Advanced NSCLC Treated With Nivolumab and Pembrolizumab: A Multi-Institutional Study

Author

Sevinj Yolchuyeva, PhD, Elena Giacomazzi, MSc, Marion Tonneau, PhD, Fabien Lamaze, PhD, Michele Orain, MT, François Coulombe, MD, Julie Malo, CCRP, Wiam Belkaid, PhD, Bertrand Routy, MD, PhD, Philippe Joubert, MD, PhD, and Venkata S.K. Manem, MSc, PhD

Subjects
Radiomics, Machine learning, Immunotherapy, Biomarker discovery, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Background: Although the immune checkpoint inhibitors, nivolumab and pembrolizumab, were found to be promising in patients with advanced NSCLC, some of them either do not respond or have recurrence after an initial response. It is still unclear who will benefit from these therapies, and, hence, there is an unmet clinical need to build robust biomarkers. Methods: Patients with advanced NSCLC (N = 323) who were treated with pembrolizumab or nivolumab were retrospectively identified from two institutions. Radiomics features extracted from baseline pretreatment computed tomography scans along with the clinical variables were used to build the predictive models for overall survival (OS), progression-free survival (PFS), and programmed death-ligand 1 (PD-L1). To develop the imaging and integrative clinical-imaging predictive models, we used the XGBoost learning algorithm with ReliefF feature selection method and validated them in an independent cohort. The concordance index for OS, PFS, and area under the curve for PD-L1 was used to evaluate model performance. Results: We developed radiomics and the ensemble radiomics-clinical predictive models for OS, PFS, and PD-L1 expression. The concordance indices of the radiomics model were 0.60 and 0.61 for predicting OS and PFS and area under the curve was 0.61 for predicting PD-L1 in the validation cohort, respectively. The combined radiomics-clinical model resulted in higher performance with 0.65, 0.63, and 0.68 to predict OS, PFS, and PD-L1 in the validation cohort, respectively. Conclusions: We found that pretreatment computed tomography imaging along with clinical data can aid as predictive biomarkers for PD-L1 and survival end points. These imaging-driven approaches may prove useful to expand the therapeutic options for nonresponders and improve the selection of patients who would benefit from immune checkpoint inhibitors.

Published
2023
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14. Implementation of an automated process for Limnospira indica harvesting and culture medium recycling for space applications

Author

Jordan Tallec, Marie Vandermies, Céline Coene, Brigitte Lamaze-Lefebvre, Dries Demey, Matthieu Frappart, and Estelle Couallier

Subjects
regenerative life support, solid-liquid separation, filtration technology, harvesting of microalgae, biomass for food, Astronomy, QB1-991, Geophysics. Cosmic physics, QC801-809
Abstract

Future long-term space exploration missions require the implementation of circular life support systems for the supply of water, oxygen and food from mission wastes. Therefore, separation systems dealing with multi-phasic streams need to be addressed. The BioHarvest (BHV) study focused on solid/liquid separation in space with the aim to demonstrate the continuous separation and harvesting of the cyanobacterium Limnospira indica from its culture broth under axenic conditions. The cyanobacterium biomass is intended to be used for further food processing while the broth free of organic matter and resupplied with nutrients should be directly recycled into the photobioreactor (PBR). In this study, an automated breadboard model based on a two-step process was built. First, a Biomass Harvesting Unit (BHU) separates the biomass produced in the PBR from the culture medium with dead-end filtration. Second, the Medium Filtration Unit (MFU) further treats the culture medium to retain the dissolved organic compounds using crossflow filtration. The performances of BHU and MHU met the requirements in batch mode and in short continuous mode: the BHU was able to retain all the biomass and the MFU could retain more than 90% of organic matter while being permeable to nutrients. The productivity of the MFU was also very good, with a high permeation flux allowing treating the targeted 80 L of culture per day. However, continuous operation of the BHV technology could not be achieved in the long term due to biomass accumulation as a sticky cake with a high specific resistance on the BHU filter, despite backwashing cycles and intense vibrations. Future work shall therefore focus on this critical step, to improve process performance by preventing fouling of the filter sheets.

Published
2023
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18. Caveolin-1 dolines form a distinct and rapid caveolae-independent mechanoadaptation system

Author

Lolo, Fidel-Nicolás, Walani, Nikhil, Seemann, Eric, Zalvidea, Dobryna, Pavón, Dácil María, Cojoc, Gheorghe, Zamai, Moreno, Viaris de Lesegno, Christine, Martínez de Benito, Fernando, Sánchez-Álvarez, Miguel, Uriarte, Juan José, Echarri, Asier, Jiménez-Carretero, Daniel, Escolano, Joan-Carles, Sánchez, Susana A., Caiolfa, Valeria R., Navajas, Daniel, Trepat, Xavier, Guck, Jochen, Lamaze, Christophe, Roca-Cusachs, Pere, Kessels, Michael M., Qualmann, Britta, Arroyo, Marino, and del Pozo, Miguel A.

Published
2023
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19. A caveolin-1 dependent glucose-6-phosphatase trafficking contributes to hepatic glucose production

Author

Amandine Gautier-Stein, Julien Chilloux, Maud Soty, Bernard Thorens, Christophe Place, Carine Zitoun, Adeline Duchampt, Lorine Da Costa, Fabienne Rajas, Christophe Lamaze, and Gilles Mithieux

Subjects
Liver, Glucose-6 phosphatase, Gluconeogenesis, Intracellular glucose transport, Caveolin 1, Internal medicine, RC31-1245
Abstract

Objective: Deregulation of hepatic glucose production is a key driver in the pathogenesis of diabetes, but its short-term regulation is incompletely deciphered. According to textbooks, glucose is produced in the endoplasmic reticulum by glucose-6-phosphatase (G6Pase) and then exported in the blood by the glucose transporter GLUT2. However, in the absence of GLUT2, glucose can be produced by a cholesterol-dependent vesicular pathway, which remains to be deciphered. Interestingly, a similar mechanism relying on vesicle trafficking controls short-term G6Pase activity. We thus investigated whether Caveolin-1 (Cav1), a master regulator of cholesterol trafficking, might be the mechanistic link between glucose production by G6Pase in the ER and glucose export through a vesicular pathway. Methods: Glucose production from fasted mice lacking Cav1, GLUT2 or both proteins was measured in vitro in primary culture of hepatocytes and in vivo by pyruvate tolerance tests. The cellular localization of Cav1 and the catalytic unit of glucose-6-phosphatase (G6PC1) were studied by western blotting from purified membranes, immunofluorescence on primary hepatocytes and fixed liver sections and by in vivo imaging of chimeric constructs overexpressed in cell lines. G6PC1 trafficking to the plasma membrane was inhibited by a broad inhibitor of vesicular pathways or by an anchoring system retaining G6PC1 specifically to the ER membrane. Results: Hepatocyte glucose production is reduced at the step catalyzed by G6Pase in the absence of Cav1. In the absence of both GLUT2 and Cav1, gluconeogenesis is nearly abolished, indicating that these pathways can be considered as the two major pathways of de novo glucose production. Mechanistically, Cav1 colocalizes but does not interact with G6PC1 and controls its localization in the Golgi complex and at the plasma membrane. The localization of G6PC1 at the plasma membrane is correlated to glucose production. Accordingly, retaining G6PC1 in the ER reduces glucose production by hepatic cells. Conclusions: Our data evidence a pathway of glucose production that relies on Cav1-dependent trafficking of G6PC1 to the plasma membrane. This reveals a new cellular regulation of G6Pase activity that contributes to hepatic glucose production and glucose homeostasis.

Published
2023
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21. A natural timeless polymorphism allowing circadian clock synchronization in 'white nights'

Author

Angelique Lamaze, Chenghao Chen, Solene Leleux, Min Xu, Rebekah George, and Ralf Stanewsky

Subjects
Science
Abstract

The genus Drosophila originate in subSaharan Africa and spread North up to the polar circle where they experience long days in the summer or even constant light. Here, the authors show that a form of the TIMELESS protein enables flies to synchronise their behavioural activity to long summer days

Published
2022
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22. Metabolomic Profiling of Pulmonary Neuroendocrine Neoplasms.

Author

Boullier, Clémence, Lamaze, Fabien C., Haince, Jean-François, Bux, Rashid Ahmed, Orain, Michèle, Zheng, Jiamin, Zhang, Lun, Wishart, David S., Bossé, Yohan, Manem, Venkata S. K., and Joubert, Philippe

Subjects
*MEDICAL logic, *LIQUID chromatography-mass spectrometry, *T-test (Statistics), *BODY mass index, *DATA analysis, *RESEARCH funding, *EARLY detection of cancer, *SAMPLE size (Statistics), *TUMOR markers, *CANCER patients, *DESCRIPTIVE statistics, *CHI-squared test, *MANN Whitney U Test, *CELL lines, *LUNG tumors, *NEUROENDOCRINE tumors, *CASE-control method, *STATISTICS, *METABOLOMICS, *COMPARATIVE studies, *DATA analysis software, *CONFIDENCE intervals, *REGRESSION analysis
Abstract

Simple Summary: Pulmonary neuroendocrine neoplasms (NENs) are a challenging type of lung cancer due to their varied clinical features and aggressive behavior. This study aimed to find specific metabolomic profiles in the blood of patients with different subtypes of lung NENs, which could help in early diagnosis. By analyzing 153 metabolites in the plasma of 120 NEN patients and comparing them with healthy individuals and patients with other lung cancers, we identified specific metabolic changes. These findings could lead to new biomarkers for early detection and better management of lung NENs, ultimately improving patient outcomes. Background/Objectives: Pulmonary neuroendocrine neoplasms (NENs) account for 20% of malignant lung tumors. Their management is challenging due to their diverse clinical features and aggressive nature. Currently, metabolomics offers a range of potential cancer biomarkers for diagnosis, monitoring tumor progression, and assessing therapeutic response. However, a specific metabolomic profile for early diagnosis of lung NENs has yet to be identified. This study aims to identify specific metabolomic profiles that can serve as biomarkers for early diagnosis of lung NENs. Methods: We measured 153 metabolites using liquid chromatography combined with mass spectrometry (LC-MS) in the plasma of 120 NEN patients and compared them with those of 71 healthy individuals. Additionally, we compared these profiles with those of 466 patients with non-small-cell lung cancers (NSCLCs) to ensure clinical relevance. Results: We identified 21 metabolites with consistently altered plasma concentrations in NENs. Compared to healthy controls, 18 metabolites were specific to carcinoid tumors, 5 to small-cell lung carcinomas (SCLCs), and 10 to large-cell neuroendocrine carcinomas (LCNECs). These findings revealed alterations in various metabolic pathways, such as fatty acid biosynthesis and beta-oxidation, the Warburg effect, and the citric acid cycle. Conclusions: Our study identified biomarker metabolites in the plasma of patients with each subtype of lung NENs and demonstrated significant alterations in several metabolic pathways. These metabolomic profiles could potentially serve as biomarkers for early diagnosis and better management of lung NENs. [ABSTRACT FROM AUTHOR]

Published
2024
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26. Light triggers a network switch between circadian morning and evening oscillators controlling behaviour during daily temperature cycles.

Author

Clara Lorber, Solene Leleux, Ralf Stanewsky, and Angelique Lamaze

Subjects
Genetics, QH426-470
Abstract

Proper timing of rhythmic locomotor behavior is the consequence of integrating environmental conditions and internal time dictated by the circadian clock. Rhythmic environmental input like daily light and temperature changes (called Zeitgeber) reset the molecular clock and entrain it to the environmental time zone the organism lives in. Furthermore, depending on the absolute temperature or light intensity, flies exhibit their main locomotor activity at different times of day, i.e., environmental input not only entrains the circadian clock but also determines the phase of a certain behavior. To understand how the brain clock can distinguish between (or integrate) an entraining Zeitgeber and environmental effects on activity phase, we attempted to entrain the clock with a Zeitgeber different from the environmental input used for phasing the behavior. 150 clock neurons in the Drosophila melanogaster brain control different aspects of the daily activity rhythms and are organized in various clusters. During regular 12 h light: 12 h dark cycles at constant mild temperature (LD 25°C, LD being the Zeitgeber), so called morning oscillator (MO) neurons control the increase of locomotor activity just before lights-on, while evening oscillator (EO) neurons regulate the activity increase at the end of the day, a few hours before lights-off. Here, using 12 h: 12 h 25°C:16°C temperature cycles as Zeitgeber, we attempted to look at the impact of light on phasing locomotor behavior. While in constant light and 25°C:16°C temperature cycles (LLTC), flies show an unimodal locomotor activity peak in the evening, during the same temperature cycle, but in the absence of light (DDTC), the phase of the activity peak is shifted to the morning. Here, we show that the EO is necessary for synchronized behavior in LLTC but not for entraining the molecular clock of the other clock neuronal groups, while the MO controls synchronized morning activity in DDTC. Interestingly, our data suggest that the influence of the EO on the synchronization increases depending on the length of the photoperiod (constant light vs 12 h of light). Hence, our results show that effects of different environmental cues on clock entrainment and activity phase can be separated, allowing to decipher their integration by the circadian clock.

Published
2022
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27. Neuronal activity-dependent ATP enhances the pro-growth effect of repair Schwann cell extracellular vesicles by increasing their miRNA-21 loading

Author

Cristian Saquel, Romina J. Catalan, Rodrigo Lopez-Leal, Ramon A. Ramirez, David Necuñir, Ursula Wyneken, Christophe Lamaze, and Felipe A. Court

Subjects
Schwann cell, extracellular vesicles, ATP, purinergic receptors, axonal growth, axonal regeneration, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Functional recovery after peripheral nerve injuries is critically dependent on axonal regeneration. Several autonomous and non-cell autonomous processes regulate axonal regeneration, including the activation of a growth-associated transcriptional program in neurons and the reprogramming of differentiated Schwann cells (dSCs) into repair SCs (rSCs), triggering the secretion of neurotrophic factors and the activation of an inflammatory response. Repair Schwann cells also release pro-regenerative extracellular vesicles (EVs), but is still unknown whether EV secretion is regulated non-cell autonomously by the regenerating neuron. Interestingly, it has been described that nerve activity enhances axonal regeneration by increasing the secretion of neurotrophic factors by rSC, but whether this activity modulates pro-regenerative EV secretion by rSC has not yet been explored. Here, we demonstrate that neuronal activity enhances the release of rSC-derived EVs and their transfer to neurons. This effect is mediated by activation of P2Y receptors in SCs after activity-dependent ATP release from sensory neurons. Importantly, activation of P2Y in rSCs also increases the amount of miRNA-21 present in rSC-EVs. Taken together, our results demonstrate that neuron to glia communication by ATP-P2Y signaling regulates the content of SC-derived EVs and their transfer to axons, modulating axonal elongation in a non-cell autonomous manner.

Published
2022
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30. Glycolipid-dependent and lectin-driven transcytosis in mouse enterocytes

Author

Alena Ivashenka, Christian Wunder, Valerie Chambon, Roger Sandhoff, Richard Jennemann, Estelle Dransart, Katrina Podsypanina, Bérangère Lombard, Damarys Loew, Christophe Lamaze, Francoise Poirier, Hermann-Josef Gröne, Ludger Johannes, and Massiullah Shafaq-Zadah

Subjects
Biology (General), QH301-705.5
Abstract

Ivashenka et al. report that galectin-3 (Gal3) binding to lactotransferrin drives its transcytosis in enterocytes. Such trafficking is Gal3- and glycosphingolipid-dependent, and Gal3 is found in clathrin-independent carriers. These findings suggest that polarized trafficking across the intestinal barrier relies on this glycolipid and lectin (GL-Lect)-mediated endocytosis.

Published
2021
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31. Identification of a New Cholesterol‐Binding Site within the IFN‐γ Receptor that is Required for Signal Transduction

Author

Ornella Morana, Jon Ander Nieto‐Garai, Patrik Björkholm, Jorge Bernardino de la Serna, Oihana Terrones, Aroa Arboleya, Dalila Ciceri, Iratxe Rojo‐Bartolomé, Cédric M. Blouin, Christophe Lamaze, Maier Lorizate, and Francesc‐Xabier Contreras

Subjects
cholesterol, interferon gamma receptors, lipid nanodomains, protein–lipid interactions, signal transduction, Science
Abstract

Abstract The cytokine interferon‐gamma (IFN‐γ) is a master regulator of innate and adaptive immunity involved in a broad array of human diseases that range from atherosclerosis to cancer. IFN‐γ exerts it signaling action by binding to a specific cell surface receptor, the IFN‐γ receptor (IFN‐γR), whose activation critically depends on its partition into lipid nanodomains. However, little is known about the impact of specific lipids on IFN‐γR signal transduction activity. Here, a new conserved cholesterol (chol) binding motif localized within its single transmembrane domain is identified. Through direct binding, chol drives the partition of IFN‐γR2 chains into plasma membrane lipid nanodomains, orchestrating IFN‐γR oligomerization and transmembrane signaling. Bioinformatics studies show that the signature sequence stands for a conserved chol‐binding motif presented in many mammalian membrane proteins. The discovery of chol as the molecular switch governing IFN‐γR transmembrane signaling represents a significant advance for understanding the mechanism of lipid selectivity by membrane proteins, but also for figuring out the role of lipids in modulating cell surface receptor function. Finally, this study suggests that inhibition of the chol‐IFNγR2 interaction may represent a potential therapeutic strategy for various IFN‐γ‐dependent diseases.

Published
2022
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32. The French Cochlear Implant Registry (EPIIC): Perception and language results in infants with cochlear implantation under the age of 24 months

Author

Loundon, N., Simon, F., Aubry, K., Bordure, P., Bozorg-Grayeli, A., Deguine, O., Eyermann, C., Franco-Vidal, V., Godey, B., Guevara, N., Karkas, A., Klopp, N., Labrousse, M., Lebreton, J.-P., Lerosey, Y., Lescanne, E., Marianowski, R., Merklen, F., Mezouaghi, K., Mom, T., Moreau, S., Mosnier, I., Noël-Petroff, N., Parietti-Winkler, C., Piller, P., Poncet, C., Radafy, E., Roman, S., Roux-Vaillard, S., Schmerber, S., Tavernier, L., Truy, E., Vincent, C., and De Lamaze, A.

Published
2020
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34. Author Response: Caveolin-1 protects endothelial cells from extensive expansion of transcellular tunnel by stiffening the plasma membrane

Author

Morel, Camille, primary, Lemerle, Eline, additional, Tsai, Feng-Ching, additional, Obadia, Thomas, additional, Srivastava, Nishit, additional, Marechal, Maud, additional, Salles, Audrey, additional, Albert, Marvin, additional, Stefani, Caroline, additional, Benito, Yvonne, additional, Vandenesch, François, additional, Lamaze, Christophe, additional, Vassilopoulos, Stéphane, additional, Piel, Matthieu, additional, Bassereau, Patricia, additional, Gonzalez-Rodriguez, David, additional, Leduc, Cécile, additional, and Lemichez, Emmanuel, additional

Published
2024
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35. CXCL13 Positive Cells Localization Predict Response to Anti-PD-1/PD-L1 in Pulmonary Non-Small Cell Carcinoma

Author

Vahidian, Fatemeh, primary, Lamaze, Fabien C., additional, Bouffard, Cédrik, additional, Coulombe, François, additional, Gagné, Andréanne, additional, Blais, Florence, additional, Tonneau, Marion, additional, Orain, Michèle, additional, Routy, Bertrand, additional, Manem, Venkata S. K., additional, and Joubert, Philippe, additional

Published
2024
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36. The Cross-Scale Association between Pathomics and Radiomics Features in Immunotherapy-Treated NSCLC Patients: A Preliminary Study

Author

Dia, Abdou Khadir, primary, Ebrahimpour, Leyla, additional, Yolchuyeva, Sevinj, additional, Tonneau, Marion, additional, Lamaze, Fabien C., additional, Orain, Michèle, additional, Coulombe, Francois, additional, Malo, Julie, additional, Belkaid, Wiam, additional, Routy, Bertrand, additional, Joubert, Philippe, additional, Després, Philippe, additional, and Manem, Venkata S. K., additional

Published
2024
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42. Coupling of melanocyte signaling and mechanics by caveolae is required for human skin pigmentation

Author

Lia Domingues, Ilse Hurbain, Floriane Gilles-Marsens, Julia Sirés-Campos, Nathalie André, Melissa Dewulf, Maryse Romao, Christine Viaris de Lesegno, Anne-Sophie Macé, Cédric Blouin, Christelle Guéré, Katell Vié, Graça Raposo, Christophe Lamaze, and Cédric Delevoye

Subjects
Science
Abstract

Caveolae are plasma membrane invaginations playing crucial functions, like signal transduction and mechanoprotection. Here, the authors show that caveolae contribute to skin pigmentation by integrating the biochemical and mechanical response of epidermal melanocytes to extracellular cues.

Published
2020
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44. An Abl-FBP17 mechanosensing system couples local plasma membrane curvature and stress fiber remodeling during mechanoadaptation

Author

Asier Echarri, Dácil M. Pavón, Sara Sánchez, María García-García, Enrique Calvo, Carla Huerta-López, Diana Velázquez-Carreras, Christine Viaris de Lesegno, Nicholas Ariotti, Ana Lázaro-Carrillo, Raffaele Strippoli, David De Sancho, Jorge Alegre-Cebollada, Christophe Lamaze, Robert G. Parton, and Miguel A. Del Pozo

Subjects
Science
Abstract

Mechanical forces are sensed by cells and can alter plasma membrane properties, but biochemical changes underlying this are not clear. Here the authors show tension is sensed by c-Abl and FBP17, which couples changes in mechanical tension to remodelling of the plasma membrane and actin cytoskeleton.

Published
2019
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46. Functional dissection of the retrograde Shiga toxin trafficking inhibitor Retro-2

Author

Forrester, Alison, Rathjen, Stefan J., Daniela Garcia-Castillo, Maria, Bachert, Collin, Couhert, Audrey, Tepshi, Livia, Pichard, Sylvain, Martinez, Jennifer, Munier, Mathilde, Sierocki, Raphael, Renard, Henri-François, Augusto Valades-Cruz, César, Dingli, Florent, Loew, Damarys, Lamaze, Christophe, Cintrat, Jean-Christophe, Linstedt, Adam D., Gillet, Daniel, Barbier, Julien, and Johannes, Ludger

Published
2020
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47. Author Correction: The landscape of viral associations in human cancers (Nature Genetics, (2020), 52, 3, (320-330), 10.1038/s41588-019-0558-9)

Author

Zapatka M., Zapatka, M, Borozan, I, Brewer, D, Iskar, M, Grundhoff, A, Alawi, M, Desai, N, Sultmann, H, Moch, H, Cooper, C, Eils, R, Ferretti, V, Kleinheinz, K, Lichter, P, Nakagawa, H, Ojesina, A, Pedamallu, C, Schlesner, M, Su, X, Aaltonen, L, Abascal, F, Abeshouse, A, Aburatani, H, Adams, D, Agrawal, N, Ahn, K, Ahn, S, Aikata, H, Akbani, R, Akdemir, K, Al-Ahmadie, H, Al-Sedairy, S, Al-Shahrour, F, Albert, M, Aldape, K, Alexandrov, L, Ally, A, Alsop, K, Alvarez, E, Amary, F, Amin, S, Aminou, B, Ammerpohl, O, Anderson, M, Ang, Y, Antonello, D, Anur, P, Aparicio, S, Appelbaum, E, Arai, Y, Aretz, A, Arihiro, K, Ariizumi, S, Armenia, J, Arnould, L, Asa, S, Assenov, Y, Atwal, G, Aukema, S, Auman, J, Aure, M, Awadalla, P, Aymerich, M, Bader, G, Baez-Ortega, A, Bailey, M, Bailey, P, Balasundaram, M, Balu, S, Bandopadhayay, P, Banks, R, Barbi, S, Barbour, A, Barenboim, J, Barnholtz-Sloan, J, Barr, H, Barrera, E, Bartlett, J, Bartolome, J, Bassi, C, Bathe, O, Baumhoer, D, Bavi, P, Baylin, S, Bazant, W, Beardsmore, D, Beck, T, Behjati, S, Behren, A, Niu, B, Bell, C, Beltran, S, Benz, C, Berchuck, A, Bergmann, A, Bergstrom, E, Berman, B, Berney, D, Bernhart, S, Beroukhim, R, Berrios, M, Bersani, S, Bertl, J, Betancourt, M, Bhandari, V, Bhosle, S, Biankin, A, Bieg, M, Bigner, D, Binder, H, Birney, E, Birrer, M, Biswas, N, Bjerkehagen, B, Bodenheimer, T, Boice, L, Bonizzato, G, De Bono, J, Boot, A, Bootwalla, M, Borg, A, Borkhardt, A, Boroevich, K, Borst, C, Bosenberg, M, Bosio, M, Boultwood, J, Bourque, G, Boutros, P, Bova, G, Bowen, D, Bowlby, R, Bowtell, D, Boyault, S, Boyce, R, Boyd, J, Brazma, A, Brennan, P, Brinkman, A, Bristow, R, Broaddus, R, Brock, J, Brock, M, Broeks, A, Brooks, A, Brooks, D, Brors, B, Brunak, S, Bruxner, T, Bruzos, A, Buchanan, A, Buchhalter, I, Buchholz, C, Bullman, S, Burke, H, Burkhardt, B, Burns, K, Busanovich, J, Bustamante, C, Butler, A, Butte, A, Byrne, N, Borresen-Dale, A, Caesar-Johnson, S, Cafferkey, A, Cahill, D, Calabrese, C, Caldas, C, Calvo, F, Camacho, N, Campbell, P, Campo, E, Cantu, C, Cao, S, Carey, T, Carlevaro-Fita, J, Carlsen, R, Cataldo, I, Cazzola, M, Cebon, J, Cerfolio, R, Chadwick, D, Chakravarty, D, Chalmers, D, Chan, C, Chan, K, Chan-Seng-Yue, M, Chandan, V, Chang, D, Chanock, S, Chantrill, L, Chateigner, A, Chatterjee, N, Chayama, K, Chen, H, Chen, J, Chen, K, Chen, Y, Chen, Z, Cherniack, A, Chien, J, Chiew, Y, Chin, S, Cho, J, Cho, S, Choi, J, Choi, W, Chomienne, C, Chong, Z, Choo, S, Chou, A, Christ, A, Christie, E, Chuah, E, Cibulskis, C, Cibulskis, K, Cingarlini, S, Clapham, P, Claviez, A, Cleary, S, Cloonan, N, Cmero, M, Collins, C, Connor, A, Cooke, S, Cope, L, Corbo, V, Cordes, M, Cordner, S, Cortes-Ciriano, I, Covington, K, Cowin, P, Craft, B, Craft, D, Creighton, C, Cun, Y, Curley, E, Cutcutache, I, Czajka, K, Czerniak, B, Dagg, R, Danilova, L, Davi, M, Davidson, N, Davies, H, Davis, I, Davis-Dusenbery, B, Dawson, K, De La Vega, F, De Paoli-Iseppi, R, Defreitas, T, Tos, A, Delaneau, O, Demchok, J, Demeulemeester, J, Demidov, G, Demircioglu, D, Dennis, N, Denroche, R, Dentro, S, Deshpande, V, Deshwar, A, Desmedt, C, Deu-Pons, J, Dhalla, N, Dhani, N, Dhingra, P, Dhir, R, Dibiase, A, Diamanti, K, Ding, L, Ding, S, Dinh, H, Dirix, L, Doddapaneni, H, Donmez, N, Dow, M, Drapkin, R, Drechsel, O, Drews, R, Serge, S, Dudderidge, T, Dueso-Barroso, A, Dunford, A, Dunn, M, Dursi, L, Duthie, F, Dutton-Regester, K, Eagles, J, Easton, D, Edmonds, S, Edwards, P, Edwards, S, Eeles, R, Ehinger, A, Eils, J, El-Naggar, A, Eldridge, M, Ellrott, K, Erkek, S, Escaramis, G, Espiritu, S, Estivill, X, Etemadmoghadam, D, Eyfjord, J, Faltas, B, Fan, D, Fan, Y, Faquin, W, Farcas, C, Fassan, M, Fatima, A, Favero, F, Fayzullaev, N, Felau, I, Fereday, S, Ferguson, M, Feuerbach, L, Field, M, Fink, J, Finocchiaro, G, Fisher, C, Fittall, M, Fitzgerald, A, Fitzgerald, R, Flanagan, A, Fleshner, N, Flicek, P, Foekens, J, Fong, K, Fonseca, N, Foster, C, Fox, N, Fraser, M, Frazer, S, Frenkel-Morgenstern, M, Friedman, W, Frigola, J, Fronick, C, Fujimoto, A, Fujita, M, Fukayama, M, Fulton, L, Fulton, R, Furuta, M, Futreal, P, Fullgrabe, A, Gabriel, S, Gallinger, S, Gambacorti-Passerini, C, Gao, J, Gao, S, Garraway, L, Garred, O, Garrison, E, Garsed, D, Gehlenborg, N, Gelpi, J, George, J, Gerhard, D, Gerhauser, C, Gershenwald, J, Gerstein, M, Gerstung, M, Getz, G, Ghori, M, Ghossein, R, Giama, N, Gibbs, R, Gibson, B, Gill, A, Gill, P, Giri, D, Glodzik, D, Gnanapragasam, V, Goebler, M, Goldman, M, Gomez, C, Gonzalez, S, Gonzalez-Perez, A, Gordenin, D, Gossage, J, Gotoh, K, Govindan, R, Grabau, D, Graham, J, Grant, R, Green, A, Green, E, Greger, L, Grehan, N, Grimaldi, S, Grimmond, S, Grossman, R, Gundem, G, Guo, Q, Gupta, M, Gupta, S, Gut, I, Gut, M, Goke, J, Ha, G, Haake, A, Haan, D, Haas, S, Haase, K, Haber, J, Habermann, N, Hach, F, Haider, S, Hama, N, Hamdy, F, Hamilton, A, Hamilton, M, Han, L, Hanna, G, Hansmann, M, Haradhvala, N, Harismendy, O, Harliwong, I, Harmanci, A, Harrington, E, Hasegawa, T, Haussler, D, Hawkins, S, Hayami, S, Hayashi, S, Hayes, D, Hayes, S, Hayward, N, Hazell, S, He, Y, Heath, A, Heath, S, Hedley, D, Hegde, A, Heiman, D, Heinold, M, Heins, Z, Heisler, L, Hellstrom-Lindberg, E, Helmy, M, Heo, S, Hepperla, A, Heredia-Genestar, J, Herrmann, C, Hersey, P, Hess, J, Hilmarsdottir, H, Hinton, J, Hirano, S, Hiraoka, N, Hoadley, K, Hobolth, A, Hodzic, E, Hoell, J, Hoffmann, S, Hofmann, O, Holbrook, A, Holik, A, Hollingsworth, M, Holmes, O, Holt, R, Hong, C, Hong, E, Hong, J, Hooijer, G, Hornshoj, H, Hosoda, F, Hou, Y, Hovestadt, V, Howat, W, Hoyle, A, Hruban, R, Hu, J, Hu, T, Hua, X, Huang, K, Huang, M, Huang, V, Huang, Y, Huber, W, Hudson, T, Hummel, M, Hung, J, Huntsman, D, Hupp, T, Huse, J, Huska, M, Hutter, B, Hutter, C, Hubschmann, D, Iacobuzio-Donahue, C, Imbusch, C, Imielinski, M, Imoto, S, Isaacs, W, Isaev, K, Ishikawa, S, Islam, S, Ittmann, M, Ivkovic, S, Izarzugaza, J, Jacquemier, J, Jakrot, V, Jamieson, N, Jang, G, Jang, S, Jayaseelan, J, Jayasinghe, R, Jefferys, S, Jegalian, K, Jennings, J, Jeon, S, Jerman, L, Ji, Y, Jiao, W, Johansson, P, Johns, A, Johns, J, Johnson, R, Johnson, T, Jolly, C, Joly, Y, Jonasson, J, Jones, C, Jones, D, Jones, N, Jones, S, Jonkers, J, Y. S., J, Juhl, H, Jung, J, Juul, M, Juul, R, Juul, S, Jager, N, Kabbe, R, Kahles, A, Kahraman, A, Kaiser, V, Kakavand, H, Kalimuthu, S, von Kalle, C, Kang, K, Karaszi, K, Karlan, B, Karlic, R, Karsch, D, Kasaian, K, Kassahn, K, Katai, H, Kato, M, Katoh, H, Kawakami, Y, Kay, J, Kazakoff, S, Kazanov, M, Keays, M, Kebebew, E, Kefford, R, Kellis, M, Kench, J, Kennedy, C, Kerssemakers, J, Khoo, D, Khoo, V, Khuntikeo, N, Khurana, E, Kilpinen, H, Kim, H, Kim, J, Kim, Y, King, T, Klapper, W, Klimczak, L, Knappskog, S, Kneba, M, Knoppers, B, Koh, Y, Komorowski, J, Komura, D, Komura, M, Kong, G, Kool, M, Korbel, J, Korchina, V, Korshunov, A, Koscher, M, Koster, R, Kote-Jarai, Z, Koures, A, Kovacevic, M, Kremeyer, B, Kretzmer, H, Kreuz, M, Krishnamurthy, S, Kube, D, Kumar, K, Kumar, P, Kumar, S, Kumar, Y, Kundra, R, Kubler, K, Kuppers, R, Lagergren, J, Lai, P, Laird, P, Lakhani, S, Lalansingh, C, Lalonde, E, Lamaze, F, Lambert, A, Lander, E, Landgraf, P, Landoni, L, Langerod, A, Lanzos, A, Larsimont, D, Larsson, E, Lathrop, M, Lau, L, Lawerenz, C, Lawlor, R, Lawrence, M, Lazar, A, Lazic, A, Le, X, Lee, D, Lee, E, Lee, H, Lee, J, Lee, M, Lee-Six, H, Lehmann, K, Lehrach, H, Lenze, D, Leonard, C, Leongamornlert, D, Leshchiner, I, Letourneau, L, Letunic, I, Levine, D, Lewis, L, Ley, T, Li, C, C. H., L, H. I., L, Li, J, Li, L, Li, S, Li, X, Li, Y, Liang, H, Liang, S, Lin, P, Lin, Z, Linehan, W, Lingjaerde, O, Liu, D, Liu, E, Liu, F, Liu, J, Liu, X, Livingstone, J, Livitz, D, Livni, N, Lochovsky, L, Loeffler, M, Long, G, Lopez-Guillermo, A, Lou, S, Louis, D, Lovat, L, Lu, Y, Y. -J., L, Luchini, C, Lungu, I, Luo, X, Luxton, H, Lynch, A, Lype, L, Lopez, C, Lopez-Otin, C, E. Z., M, Ma, Y, Macgrogan, G, Macrae, S, Macintyre, G, Madsen, T, Maejima, K, Mafficini, A, Maglinte, D, Maitra, A, Majumder, P, Malcovati, L, Malikic, S, Malleo, G, Mann, G, Mantovani-Loffler, L, Marchal, K, Marchegiani, G, Mardis, E, Margolin, A, Marin, M, Markowetz, F, Markowski, J, Marks, J, Marques-Bonet, T, Marra, M, Marsden, L, Martens, J, Martin, S, Martin-Subero, J, Martincorena, I, Martinez-Fundichely, A, Maruvka, Y, Mashl, R, Massie, C, Matthew, T, Matthews, L, Mayer, E, Mayes, S, Mayo, M, Mbabaali, F, Mccune, K, Mcdermott, U, Mcgillivray, P, Mclellan, M, Mcpherson, J, Mcpherson, T, Meier, S, Meng, A, Meng, S, Menzies, A, Merrett, N, Merson, S, Meyerson, M, Meyerson, W, Mieczkowski, P, Mihaiescu, G, Mijalkovic, S, Mikkelsen, T, Milella, M, Mileshkin, L, Miller, C, Miller, D, Miller, J, Mills, G, Milovanovic, A, Minner, S, Miotto, M, Arnau, G, Mirabello, L, Mitchell, C, Mitchell, T, Miyano, S, Miyoshi, N, Mizuno, S, Molnar-Gabor, F, Moore, M, Moore, R, Morganella, S, Morris, Q, Morrison, C, Mose, L, Moser, C, Muinos, F, Mularoni, L, Mungall, A, Mungall, K, Musgrove, E, Mustonen, V, Mutch, D, Muyas, F, Muzny, D, Munoz, A, Myers, J, Myklebost, O, Moller, P, Nagae, G, Nagrial, A, Nahal-Bose, H, Nakagama, H, Nakamura, H, Nakamura, T, Nakano, K, Nandi, T, Nangalia, J, Nastic, M, Navarro, A, Navarro, F, Neal, D, Nettekoven, G, Newell, F, Newhouse, S, Newton, Y, A. W. T., N, Ng, A, Nicholson, J, Nicol, D, Nie, Y, Nielsen, G, Nielsen, M, Nik-Zainal, S, Noble, M, Nones, K, Northcott, P, Notta, F, O'Connor, B, O'Donnell, P, O'Donovan, M, O'Meara, S, O'Neill, B, O'Neill, J, Ocana, D, Ochoa, A, Oesper, L, Ogden, C, Ohdan, H, Ohi, K, Ohno-Machado, L, Oien, K, Ojima, H, Okusaka, T, Omberg, L, Ong, C, Ossowski, S, Ott, G, Ouellette, B, P'Ng, C, Paczkowska, M, Paiella, S, Pairojkul, C, Pajic, M, Pan-Hammarstrom, Q, Papaemmanuil, E, Papatheodorou, I, Paramasivam, N, Park, J, Park, K, Park, P, Parker, J, Parsons, S, Pass, H, Pasternack, D, Pastore, A, Patch, A, Pauporte, I, Pea, A, Pearson, J, Pedersen, J, Pederzoli, P, Peifer, M, Pennell, N, Perou, C, Perry, M, Petersen, G, Peto, M, Petrelli, N, Petryszak, R, Pfister, S, Phillips, M, Pich, O, Pickett, H, Pihl, T, Pillay, N, Pinder, S, Pinese, M, Pinho, A, Pitkanen, E, Pivot, X, Pineiro-Yanez, E, Planko, L, Plass, C, Polak, P, Pons, T, Popescu, I, Potapova, O, Prasad, A, Preston, S, Prinz, M, Pritchard, A, Prokopec, S, Provenzano, E, Puente, X, Puig, S, Puiggros, M, Pulido-Tamayo, S, Pupo, G, Purdie, C, Quinn, M, Rabionet, R, Rader, J, Radlwimmer, B, Radovic, P, Raeder, B, Raine, K, Ramakrishna, M, Ramakrishnan, K, Ramalingam, S, Raphael, B, Rathmell, W, Rausch, T, Reifenberger, G, Reimand, J, Reis-Filho, J, Reuter, V, Reyes-Salazar, I, Reyna, M, Reynolds, S, Rheinbay, E, Riazalhosseini, Y, Richardson, A, Richter, J, Ringel, M, Ringner, M, Rino, Y, Rippe, K, Roach, J, Roberts, L, Roberts, N, Roberts, S, Robertson, A, Rodriguez, J, Rodriguez-Martin, B, Rodriguez-Gonzalez, F, Roehrl, M, Rohde, M, Rokutan, H, Romieu, G, Rooman, I, Roques, T, Rosebrock, D, Rosenberg, M, Rosenstiel, P, Rosenwald, A, Rowe, E, Royo, R, Rozen, S, Rubanova, Y, Rubin, M, Rubio-Perez, C, Rudneva, V, Rusev, B, Ruzzenente, A, Ratsch, G, Sabarinathan, R, Sabelnykova, V, Sadeghi, S, Sahinalp, S, Saini, N, Saito-Adachi, M, Saksena, G, Salcedo, A, Salgado, R, Salichos, L, Sallari, R, Saller, C, Salvia, R, Sam, M, Samra, J, Sanchez-Vega, F, Sander, C, Sanders, G, Sarin, R, Sarrafi, I, Sasaki-Oku, A, Sauer, T, Sauter, G, Saw, R, Scardoni, M, Scarlett, C, Scarpa, A, Scelo, G, Schadendorf, D, Schein, J, Schilhabel, M, Schlomm, T, Schmidt, H, Schramm, S, Schreiber, S, Schultz, N, Schumacher, S, Schwarz, R, Scolyer, R, Scott, D, Scully, R, Seethala, R, Segre, A, Selander, I, Semple, C, Senbabaoglu, Y, Sengupta, S, Sereni, E, Serra, S, Sgroi, D, Shackleton, M, Shah, N, Shahabi, S, Shang, C, Shang, P, Shapira, O, Shelton, T, Shen, C, Shen, H, Shepherd, R, Shi, R, Shi, Y, Shiah, Y, Shibata, T, Shih, J, Shimizu, E, Shimizu, K, Shin, S, Shiraishi, Y, Shmaya, T, Shmulevich, I, Shorser, S, Short, C, Shrestha, R, Shringarpure, S, Shriver, C, Shuai, S, Sidiropoulos, N, Siebert, R, Sieuwerts, A, Sieverling, L, Signoretti, S, Sikora, K, Simbolo, M, Simon, R, Simons, J, Simpson, J, Simpson, P, Singer, S, Sinnott-Armstrong, N, Sipahimalani, P, Skelly, T, Smid, M, Smith, J, Smith-McCune, K, Socci, N, Sofia, H, Soloway, 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F., Baumhoer D., Bavi P., Baylin S. B., Bazant W., Beardsmore D., Beck T. A., Behjati S., Behren A., Niu B., Bell C., Beltran S., Benz C., Berchuck A., Bergmann A. K., Bergstrom E. N., Berman B. P., Berney D. M., Bernhart S. H., Beroukhim R., Berrios M., Bersani S., Bertl J., Betancourt M., Bhandari V., Bhosle S. G., Biankin A. V., Bieg M., Bigner D., Binder H., Birney E., Birrer M., Biswas N. K., Bjerkehagen B., Bodenheimer T., Boice L., Bonizzato G., De Bono J. S., Boot A., Bootwalla M. S., Borg A., Borkhardt A., Boroevich K. A., Borst C., Bosenberg M., Bosio M., Boultwood J., Bourque G., Boutros P. C., Bova G. S., Bowen D. T., Bowlby R., Bowtell D. D. L., Boyault S., Boyce R., Boyd J., Brazma A., Brennan P., Brinkman A. B., Bristow R. G., Broaddus R. R., Brock J. E., Brock M., Broeks A., Brooks A. N., Brooks D., Brors B., Brunak S., Bruxner T. J. C., Bruzos A. L., Buchanan A., Buchhalter I., Buchholz C., Bullman S., Burke H., Burkhardt B., Burns K. H., Busanovich J., Bustamante C. 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Abstract

Correction to: Nature Genetics, published online 05 February 2020. In the published version of this paper, the members of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium were listed in the Supplementary Information; however, these members should have been included in the main paper. The original Article has been corrected to include the members and affiliations of the PCAWG Consortium in the main paper; the corrections have been made to the HTML version of the Article but not the PDF version. Additional corrections to affiliations have been made to the PDF and HTML versions of the original Article for consistency of information between the PCAWG list and the main paper. An additional affiliation has been added for Adam Grundhoff (German Center for Infection Research (DZIF), Partner Site Hamburg-Borstel-Lübeck-Riems, Hamburg, Germany); and Malik Alawi was included in the PCAWG Pathogens group.

Published
2023

48. Author Correction: The repertoire of mutational signatures in human cancer (Nature, (2020), 578, 7793, (94-101), 10.1038/s41586-020-1943-3)

Author

Alexandrov L. 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B., Gallinger S., Gambacorti-Passerini C., Gao J., Gao S., Garraway L., Garred O., Garrison E., Garsed D. W., Gehlenborg N., Gelpi J. L. L., George J., Gerhard D. S., Gerhauser C., Gershenwald J. E., Gerstein M., Gerstung M., Ghori M., Ghossein R., Giama N. H., Gibbs R. A., Gibson B., Gill A. J., Gill P., Giri D. D., Glodzik D., Gnanapragasam V. J., Goebler M. E., Goldman M. J., Gomez C., Gonzalez S., Gonzalez-Perez A., Gossage J., Gotoh K., Govindan R., Grabau D., Graham J. S., Grant R. C., Green A. R., Green E., Greger L., Grehan N., Grimaldi S., Grimmond S. M., Grossman R. L., Grundhoff A., Gundem G., Guo Q., Gupta M., Gupta S., Gut I. G., Gut M., Goke J., Ha G., Haake A., Haan D., Haas S., Haase K., Haber J. E., Habermann N., Hach F., Haider S., Hama N., Hamdy F. C., Hamilton A., Hamilton M. P., Han L., Hanna G. B., Hansmann M., Harismendy O., Harliwong I., Harmanci A. O., Harrington E., Hasegawa T., Haussler D., Hawkins S., Hayami S., Hayashi S., Hayes D. N., Hayes S. J., Hayward N. K., Hazell S., He Y., Heath A. P., Heath S. C., Hedley D., Hegde A. M., Heiman D. I., Heinold M. C., Heins Z., Heisler L. E., Hellstrom-Lindberg E., Helmy M., Heo S. G., Hepperla A. J., Heredia-Genestar J. M., Herrmann C., Hersey P., Hess J. M., Hilmarsdottir H., Hinton J., Hirano S., Hiraoka N., Hoadley K. A., Hobolth A., Hodzic E., Hoell J. I., Hoffmann S., Hofmann O., Holbrook A., Holik A. Z., Hollingsworth M. A., Holmes O., Holt R. A., Hong C., Hong E. P., Hong J. H., Hooijer G. K., Hornshoj H., Hosoda F., Hou Y., Hovestadt V., Howat W., Hoyle A. P., Hruban R. H., Hu J., Hu T., Hua X., Huang K. -L., Huang M., Huang V., Huang Y., Huber W., Hudson T. J., Hummel M., Hung J. A., Huntsman D., Hupp T. R., Huse J., Huska M. R., Hutter B., Hutter C. M., Hubschmann D., Iacobuzio-Donahue C. A., Imbusch C. D., Imielinski M., Imoto S., Isaacs W. B., Isaev K., Ishikawa S., Iskar M., Ittmann M., Ivkovic S., Izarzugaza J. M. G., Jacquemier J., Jakrot V., Jamieson N. B., Jang G. 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M., Koh Y., Komorowski J., Komura D., Komura M., Kong G., Kool M., Korbel J. O., Korchina V., Korshunov A., Koscher M., Koster R., Kote-Jarai Z., Koures A., Kovacevic M., Kremeyer B., Kretzmer H., Kreuz M., Krishnamurthy S., Kube D., Kumar K., Kumar P., Kumar S., Kumar Y., Kundra R., Kubler K., Kuppers R., Lagergren J., Lai P. H., Laird P. W., Lakhani S. R., Lalansingh C. M., Lalonde E., Lamaze F. C., Lambert A., Lander E., Landgraf P., Landoni L., Langerod A., Lanzos A., Larsimont D., Larsson E., Lathrop M., Lau L. M. S., Lawerenz C., Lawlor R. T., Lawrence M. S., Lazar A. J., Lazic A. M., Le X., Lee D., Lee E. A., Lee H. J., Lee J. J. -K., Lee J. -Y., Lee J., Lee M. T. M., Lee-Six H., Lehmann K. -V., Lehrach H., Lenze D., Leonard C. R., Leongamornlert D. A., Leshchiner I., Letourneau L., Letunic I., Levine D. A., Lewis L., Ley T., Li C., Li C. H., Li H. I., Li J., Li L., Li S., Li X., Li Y., Liang H., Liang S. -B., Lichter P., Lin P., Lin Z., Linehan W. M., Lingjaerde O. 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Abstract

In the published version of this paper, the members of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium were listed in the Supplementary Information; however, these members should have been included in the main paper. The original Article has been corrected to include the members and affiliations of the PCAWG Consortium in the main paper; the corrections have been made to the HTML version of the Article but not the PDF version. Additional minor corrections to affiliations have been made to the PDF and HTML versions of the original Article for consistency of information between the PCAWG list and the main paper.

Published
2023

49. Author Correction: The evolutionary history of 2,658 cancers (Nature, (2020), 578, 7793, (122-128), 10.1038/s41586-019-1907-7)

Author

Gerstung M., Gerstung, M, Jolly, C, Leshchiner, I, Dentro, S, Gonzalez, S, Rosebrock, D, Mitchell, T, Rubanova, Y, Anur, P, Yu, K, Tarabichi, M, Deshwar, A, Wintersinger, J, Kleinheinz, K, Vazquez-Garcia, I, Haase, K, Jerman, L, Sengupta, S, Macintyre, G, Malikic, S, Donmez, N, Livitz, D, Cmero, M, Demeulemeester, J, Schumacher, S, Fan, Y, Yao, X, Lee, J, Schlesner, M, Boutros, P, Bowtell, D, Zhu, H, Getz, G, Imielinski, M, Beroukhim, R, Sahinalp, S, Ji, Y, Peifer, M, Markowetz, F, Mustonen, V, Yuan, K, Wang, W, Morris, Q, Adams, D, Campbell, P, Cao, S, Christie, E, Cun, Y, Dawson, K, Drews, R, Eils, R, Fittall, M, Garsed, D, Ha, G, Lee-Six, H, Martincorena, I, Oesper, L, Peto, M, Raphael, B, Salcedo, A, Shi, R, Shin, S, Spiro, O, Stein, L, Vembu, S, Wheeler, D, Yang, T, Spellman, P, Wedge, D, Van Loo, P, Aaltonen, L, Abascal, F, Abeshouse, A, Aburatani, H, Agrawal, N, Ahn, K, Ahn, S, Aikata, H, Akbani, R, Akdemir, K, Al-Ahmadie, H, Al-Sedairy, S, Al-Shahrour, F, Alawi, M, Albert, M, Aldape, K, Alexandrov, L, Ally, A, Alsop, K, Alvarez, E, Amary, F, Amin, S, Aminou, B, Ammerpohl, O, Anderson, M, Ang, Y, Antonello, D, Aparicio, S, Appelbaum, E, Arai, Y, Aretz, A, Arihiro, K, Ariizumi, S, Armenia, J, Arnould, L, Asa, S, Assenov, Y, Atwal, G, Aukema, S, Auman, J, Aure, M, Awadalla, P, Aymerich, M, Bader, G, Baez-Ortega, A, Bailey, M, Bailey, P, Balasundaram, M, Balu, S, Bandopadhayay, P, Banks, R, Barbi, S, Barbour, A, Barenboim, J, Barnholtz-Sloan, J, Barr, H, Barrera, E, Bartlett, J, Bartolome, J, Bassi, C, Bathe, O, Baumhoer, D, Bavi, P, Baylin, S, Bazant, W, Beardsmore, D, Beck, T, Behjati, S, Behren, A, Niu, B, Bell, C, Beltran, S, Benz, C, Berchuck, A, Bergmann, A, Bergstrom, E, Berman, B, Berney, D, Bernhart, S, Berrios, M, Bersani, S, Bertl, J, Betancourt, M, Bhandari, V, Bhosle, S, Biankin, A, Bieg, M, Bigner, D, Binder, H, Birney, E, Birrer, M, Biswas, N, Bjerkehagen, B, Bodenheimer, T, Boice, L, Bonizzato, G, De Bono, J, Boot, A, Bootwalla, M, Borg, A, Borkhardt, A, Boroevich, K, Borozan, I, Borst, C, Bosenberg, M, Bosio, M, Boultwood, J, Bourque, G, Bova, G, Bowen, D, Bowlby, R, Boyault, S, Boyce, R, Boyd, J, Brazma, A, Brennan, P, Brewer, D, Brinkman, A, Bristow, R, Broaddus, R, Brock, J, Brock, M, Broeks, A, Brooks, A, Brooks, D, Brors, B, Brunak, S, Bruxner, T, Bruzos, A, Buchanan, A, Buchhalter, I, Buchholz, C, Bullman, S, Burke, H, Burkhardt, B, Burns, K, Busanovich, J, Bustamante, C, Butler, A, Butte, A, Byrne, N, Borresen-Dale, A, Caesar-Johnson, S, Cafferkey, A, Cahill, D, Calabrese, C, Caldas, C, Calvo, F, Camacho, N, Campo, E, Cantu, C, Carey, T, Carlevaro-Fita, J, Carlsen, R, Cataldo, I, Cazzola, M, Cebon, J, Cerfolio, R, Chadwick, D, Chakravarty, D, Chalmers, D, Chan, C, Chan, K, Chan-Seng-Yue, M, Chandan, V, Chang, D, Chanock, S, Chantrill, L, Chateigner, A, Chatterjee, N, Chayama, K, Chen, H, Chen, J, Chen, K, Chen, Y, Chen, Z, Cherniack, A, Chien, J, Chiew, Y, Chin, S, Cho, J, Cho, S, Choi, J, Choi, W, Chomienne, C, 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M., Hubschmann D., Iacobuzio-Donahue C. A., Imbusch C. D., Imoto S., Isaacs W. B., Isaev K., Ishikawa S., Iskar M., Islam S. M. A., Ittmann M., Ivkovic S., Izarzugaza J. M. G., Jacquemier J., Jakrot V., Jamieson N. B., Jang G. H., Jang S. J., Jayaseelan J. C., Jayasinghe R., Jefferys S. R., Jegalian K., Jennings J. L., Jeon S. -H., Jiao W., Johansson P. A., Johns A. L., Johns J., Johnson R., Johnson T. A., Joly Y., Jonasson J. G., Jones C. D., Jones D. R., Jones D. T. W., Jones N., Jones S. J. M., Jonkers J., Ju Y. S., Juhl H., Jung J., Juul M., Juul R. I., Juul S., Jager N., Kabbe R., Kahles A., Kahraman A., Kaiser V. B., Kakavand H., Kalimuthu S., von Kalle C., Kang K. J., Karaszi K., Karlan B., Karlic R., Karsch D., Kasaian K., Kassahn K. S., Katai H., Kato M., Katoh H., Kawakami Y., Kay J. D., Kazakoff S. H., Kazanov M. D., Keays M., Kebebew E., Kefford R. F., Kellis M., Kench J. G., Kennedy C. J., Kerssemakers J. N. A., Khoo D., Khoo V., Khuntikeo N., Khurana E., Kilpinen H., Kim H. K., Kim H. -L., Kim H. -Y., Kim H., Kim J., Kim J. K., Kim Y., King T. A., Klapper W., Klimczak L. J., Knappskog S., Kneba M., Knoppers B. M., Koh Y., Komorowski J., Komura D., Komura M., Kong G., Kool M., Korbel J. O., Korchina V., Korshunov A., Koscher M., Koster R., Kote-Jarai Z., Koures A., Kovacevic M., Kremeyer B., Kretzmer H., Kreuz M., Krishnamurthy S., Kube D., Kumar K., Kumar P., Kumar S., Kumar Y., Kundra R., Kubler K., Kuppers R., Lagergren J., Lai P. H., Laird P. W., Lakhani S. R., Lalansingh C. M., Lalonde E., Lamaze F. C., Lambert A., Lander E., Landgraf P., Landoni L., Langerod A., Lanzos A., Larsimont D., Larsson E., Lathrop M., Lau L. M. S., Lawerenz C., Lawlor R. T., Lawrence M. S., Lazar A. J., Lazic A. M., Le X., Lee D., Lee E. A., Lee H. J., Lee J. J. -K., Lee J. -Y., Lee M. T. M., Lehmann K. -V., Lehrach H., Lenze D., Leonard C. R., Leongamornlert D. A., Letourneau L., Letunic I., Levine D. A., Lewis L., Ley T., Li C., Li C. H., Li H. I., Li J., Li L., Li S., Li X., Li Y., Liang H., Liang S. -B., Lichter P., Lin P., Lin Z., Linehan W. M., Lingjaerde O. C., Liu D., Liu E. M., Liu F. -F. F., Liu F., Liu J., Liu X., Livingstone J., Livitz D., Livni N., Lochovsky L., Loeffler M., Long G. V., Lopez-Guillermo A., Lou S., Louis D. N., Lovat L. B., Lu Y., Lu Y. -J., Luchini C., Lungu I., Luo X., Luxton H. J., Lynch A. G., Lype L., Lopez C., Lopez-Otin C., Ma E. Z., Ma Y., MacGrogan G., MacRae S., Madsen T., Maejima K., Mafficini A., Maglinte D. T., Maitra A., Majumder P. P., Malcovati L., Malleo G., Mann G. J., Mantovani-Loffler L., Marchal K., Marchegiani G., Mardis E. R., Margolin A. A., Marin M. G., Markowski J., Marks J., Marques-Bonet T., Marra M. A., Marsden L., Martens J. W. M., Martin S., Martin-Subero J. I., Martinez-Fundichely A., Maruvka Y. E., Mashl R. J., Massie C. E., Matthew T. J., Matthews L., Mayer E., Mayes S., Mayo M., Mbabaali F., McCune K., McDermott U., McGillivray P. D., McLellan M. D., McPherson J. D., McPherson J. R., McPherson T. A., Meier S. R., Meng A., Meng S., Menzies A., Merrett N. D., Merson S., Meyerson M., Meyerson W., Mieczkowski P. A., Mihaiescu G. L., Mijalkovic S., Mikkelsen T., Milella M., Mileshkin L., Miller C. A., Miller D. K., Miller J. K., Mills G. B., Milovanovic A., Minner S., Miotto M., Arnau G. M., Mirabello L., Mitchell C., Miyano S., Miyoshi N., Mizuno S., Molnar-Gabor F., Moore M. J., Moore R. A., Morganella S., Morrison C., Mose L. E., Moser C. D., Muinos F., Mularoni L., Mungall A. J., Mungall K., Musgrove E. A., Mutch D., Muyas F., Muzny D. M., Munoz A., Myers J., Myklebost O., Moller P., Nagae G., Nagrial A. M., Nahal-Bose H. K., Nakagama H., Nakagawa H., Nakamura H., Nakamura T., Nakano K., Nandi T., Nangalia J., Nastic M., Navarro A., Navarro F. C. P., Neal D. E., Nettekoven G., Newell F., Newhouse S. J., Newton Y., Ng A. W. T., Ng A., Nicholson J., Nicol D., Nie Y., Nielsen G. P., Nielsen M. M., Nik-Zainal S., Noble M. S., Nones K., Northcott P. A., Notta F., O'Connor B. D., O'Donnell P., O'Donovan M., O'Meara S., O'Neill B. P., O'Neill J. R., Ocana D., Ochoa A., Ogden C., Ohdan H., Ohi K., Ohno-Machado L., Oien K. A., Ojesina A. I., Ojima H., Okusaka T., Omberg L., Ong C. K., Ossowski S., Ott G., Ouellette B. F. F., P'ng C., Paczkowska M., Paiella S., Pairojkul C., Pajic M., Pan-Hammarstrom Q., Papaemmanuil E., Papatheodorou I., Paramasivam N., Park J. W., Park J. -W., Park K., Park P. J., Parker J. S., Parsons S. L., Pass H., Pasternack D., Pastore A., Patch A. -M., Pauporte I., Pea A., Pearson J. V., Pedamallu C. S., Pedersen J. S., Pederzoli P., Pennell N. A., Perou C. M., Perry M. D., Petersen G. M., Petrelli N., Petryszak R., Pfister S. M., Phillips M., Pich O., Pickett H. A., Pihl T. D., Pillay N., Pinder S., Pinese M., Pinho A. V., Pitkanen E., Pivot X., Pineiro-Yanez E., Planko L., Plass C., Polak P., Pons T., Popescu I., Potapova O., Prasad A., Preston S. R., Prinz M., Pritchard A. L., Prokopec S. D., Provenzano E., Puente X. S., Puig S., Puiggros M., Pulido-Tamayo S., Pupo G. M., Purdie C. A., Quinn M. C., Rabionet R., Rader J. S., Radlwimmer B., Radovic P., Raeder B., Raine K. M., Ramakrishna M., Ramakrishnan K., Ramalingam S., Rathmell W. K., Rausch T., Reifenberger G., Reimand J., Reis-Filho J., Reuter V., Reyes-Salazar I., Reyna M. A., Reynolds S. M., Rheinbay E., Riazalhosseini Y., Richardson A. L., Richter J., Ringel M., Ringner M., Rino Y., Rippe K., Roach J., Roberts L. R., Roberts N. D., Roberts S. A., Robertson A. G., Robertson A. J., Rodriguez J. B., Rodriguez-Martin B., Rodriguez-Gonzalez F. G., Roehrl M. H. A., Rohde M., Rokutan H., Romieu G., Rooman I., Roques T., Rosenberg M., Rosenstiel P. C., Rosenwald A., Rowe E. W., Royo R., Rozen S. G., Rubin M. A., Rubio-Perez C., Rudneva V. 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Abstract

In the published version of this paper, the members of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium were listed in the Supplementary Information; however, these members should have been included in the main paper. The original Article has been corrected to include the members and affiliations of the PCAWG Consortium in the main paper; the corrections have been made to the HTML version of the Article but not the PDF version. Additional minor corrections to affiliations have been made to the PDF and HTML versions of the original Article for consistency of information between the PCAWG list and the main paper.

Published
2023

50. Publisher Correction: Comprehensive molecular characterization of mitochondrial genomes in human cancers (Nature Genetics, (2020), 52, 3, (342-352), 10.1038/s41588-019-0557-x)

Author

Yuan Y., Yuan, Y, Y. S., J, Kim, Y, Li, J, Wang, Y, Yoon, C, Yang, Y, Martincorena, I, Creighton, C, Weinstein, J, Xu, Y, Han, L, Kim, H, Nakagawa, H, Park, K, Campbell, P, Liang, H, Aaltonen, L, Abascal, F, Abeshouse, A, Aburatani, H, Adams, D, Agrawal, N, Ahn, K, Ahn, S, Aikata, H, Akbani, R, Akdemir, K, Al-Ahmadie, H, Al-Sedairy, S, Al-Shahrour, F, Alawi, M, Albert, M, Aldape, K, Alexandrov, L, Ally, A, Alsop, K, Alvarez, E, Amary, F, Amin, S, Aminou, B, Ammerpohl, O, Anderson, M, Ang, Y, Antonello, D, Anur, P, Aparicio, S, Appelbaum, E, Arai, Y, Aretz, A, Arihiro, K, Ariizumi, S, Armenia, J, Arnould, L, Asa, S, Assenov, Y, Atwal, G, Aukema, S, Auman, J, Aure, M, Awadalla, P, Aymerich, M, Bader, G, Baez-Ortega, A, Bailey, M, Bailey, P, Balasundaram, M, Balu, S, Bandopadhayay, P, Banks, R, Barbi, S, Barbour, A, Barenboim, J, Barnholtz-Sloan, J, Barr, H, Barrera, E, Bartlett, J, Bartolome, J, Bassi, C, Bathe, O, Baumhoer, D, Bavi, P, Baylin, S, Bazant, W, Beardsmore, D, Beck, T, Behjati, S, Behren, A, 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D, Dennis, N, Denroche, R, Dentro, S, Desai, N, Deshpande, V, Deshwar, A, Desmedt, C, Deu-Pons, J, Dhalla, N, Dhani, N, Dhingra, P, Dhir, R, Dibiase, A, Diamanti, K, Ding, L, Ding, S, Dinh, H, Dirix, L, Doddapaneni, H, Donmez, N, Dow, M, Drapkin, R, Drechsel, O, Drews, R, Serge, S, Dudderidge, T, Dueso-Barroso, A, Dunford, A, Dunn, M, Dursi, L, Duthie, F, Dutton-Regester, K, Eagles, J, Easton, D, Edmonds, S, Edwards, P, Edwards, S, Eeles, R, Ehinger, A, Eils, J, Eils, R, El-Naggar, A, Eldridge, M, Ellrott, K, Erkek, S, Escaramis, G, Espiritu, S, Estivill, X, Etemadmoghadam, D, Eyfjord, J, Faltas, B, Fan, D, Fan, Y, Faquin, W, Farcas, C, Fassan, M, Fatima, A, Favero, F, Fayzullaev, N, Felau, I, Fereday, S, Ferguson, M, Ferretti, V, Feuerbach, L, Field, M, Fink, J, Finocchiaro, G, Fisher, C, Fittall, M, Fitzgerald, A, Fitzgerald, R, Flanagan, A, Fleshner, N, Flicek, P, Foekens, J, Fong, K, Fonseca, N, Foster, C, Fox, N, Fraser, M, Frazer, S, Frenkel-Morgenstern, M, Friedman, W, Frigola, 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Abstract

Correction to: Nature Genetics, published online 5 February 2020. This paper was originally published without open access. As of the date of this correction, the paper is available online as an open-access paper under a Creative Commons Attribution 4.0 International License.

Published
2023

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