Gottardo lab

The Translational Data Science (TDS) group focuses on developing novel computational tools, statistical methods and machine learning algorithms for the analysis of high-throughput and high-dimensional datasets generated by novel assay technologies with applications in human immunology, vaccine and cancer immunotherapy. Our group aims to develop and apply novel computational tools and methods that address important immunological problems through high-dimensional modeling and data integration. Our interests cover a wide range of applications such as assessing vaccine immunogenicity, characterizing immune responses to cancer and immunotherapies to name a few. We collaborate with multiple research groups locally, nationally, and internationally to address important immunological problems through high-dimensional modeling and data integration. ...

Research projects

Single-cell and spatial transcriptomics

We are actively working on the development of statistical methods and tools for novel single and spatial technologies. We have developed the first model that accounts for the bimodality of expression observed in single-cells. This model is implemented in a package called MAST, and it is one of the most cited methods for differential gene expression analysis of scRNA-seq data. We have also developed one of the first models for the analysis of spatial transcriptomics that enables near single-cell resolution analysis of 10X Visium data. This method is implemented in the BayesSpace package available. Both MAST and BayesSpace are available from the Bioconductor project.

Characterizing responses to immunotherapy

Our group has contributed to many studies using single-cell and spatial computational analyses to characterize the tumor microenvironment (including immune cells) to better understand mechanisms of response and relapse to immunotherapy. Using computational tools (including some that we have developed) we have identified novel biomarkers of responses to anti-PD1 therapy (Greene et al 2021) and escape mechanisms to adoptive T-cell therapies (Paulson et al 2018, Chapuis et al 2019, Lahman et al. 2022).

Team

Raphaël Gottardo

Director Biomedical Data Sciences Center Professor of Immunology, Immunotherapy, Single-Cell, Statistics and Machine Learning UNIL & CHUV, SIB

raphael.gottardo@chuv.ch GottardoLab

Selected Publications

Shared acute phase traits in effector and memory human CD8 T cells.

Fuertes Marraco SA, Alpern D, Lofek S, (...), Delorenzi M, Deplancke B, Speiser DE

Current research in immunology – 2021 Dec 29

The analysis of GSTA1 promoter genetic and functional diversity of human populations.

Mlakar V, Curtis PH, Armengol M, (...), Mlakar SJ, Nava T, Ansari M

Scientific reports – 2021 Mar 3

Antiangiogenic immunotherapy suppresses desmoplastic and chemoresistant intestinal tumors in mice.

Ragusa S, Prat-Luri B, González-Loyola A, (...), Delorenzi M, De Palma M, Petrova TV

The Journal of clinical investigation – 2020 Mar 2

Neutrophils suppress tumor-infiltrating T cells in colon cancer via matrix metalloproteinase-mediated activation of TGFβ.

Germann M, Zangger N, Sauvain MO, (...), Tejpar S, Coukos G, Radtke F

EMBO molecular medicine – 2019 Dec 2

Consensus molecular subgroups (CMS) of colorectal cancer (CRC) and first-line efficacy of FOLFIRI plus cetuximab or bevacizumab in the FIRE3 (AIO KRK-0306) trial.

Stintzing S, Wirapati P, Lenz HJ, (...), Aderka D, Tejpar S, Heinemann V

Annals of oncology : official journal of the European Society for Medical Oncology – 2019 Nov 1

The DNA methylome of DDR genes and benefit from RT or TMZ in IDH mutant low-grade glioma treated in EORTC 22033.

Bady P, Kurscheid S, Delorenzi M, (...), Stupp R, Baumert BG, Hegi ME

Acta neuropathologica – 2018 Jan 24

Sensitivity Analysis of the MGMT-STP27 Model and Impact of Genetic and Epigenetic Context to Predict the MGMT Methylation Status in Gliomas and Other Tumors.

Bady P, Delorenzi M, Hegi ME

The Journal of molecular diagnostics : JMD – 2016 Feb 27

The consensus molecular subtypes of colorectal cancer.

Guinney J, Dienstmann R, Wang X, (...), Kopetz S, Vermeulen L, Tejpar S

Nature medicine – 2015 Oct 12

Gene expression patterns unveil a new level of molecular heterogeneity in colorectal cancer.

Budinska E, Popovici V, Tejpar S, (...), Bosman F, Roth A, Delorenzi M

The Journal of pathology – 2013 Jul 8

A comparison of methods for differential expression analysis of RNA-seq data.

Soneson C, Delorenzi M

BMC bioinformatics – 2013 Mar 9

Prognostic role of KRAS and BRAF in stage II and III resected colon cancer: results of the translational study on the PETACC-3, EORTC 40993, SAKK 60-00 trial.

Roth AD, Tejpar S, Delorenzi M, (...), Cunningham D, Van Cutsem E, Bosman F

Journal of clinical oncology : official journal of the American Society of Clinical Oncology – 2009 Dec 14

Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures.

Wirapati P, Sotiriou C, Kunkel S, (...), Goldstein DR, Piccart M, Delorenzi M

Breast cancer research : BCR – 2008 Jul 28