TY  - JOUR
AB  - Understanding the recognition of disease-derived epitopes through T cell receptors (TCRs) has the potential to serve as a stepping stone for the development of efficient immunotherapies and vaccines. While a plethora of sequence-based prediction methods for TCR-epitope binding exists, their pre-trained models have not been comparatively evaluated. To alleviate this shortcoming, we integrated 21 TCR-epitope prediction models into the immune-prediction framework ePytope, offering interoperable interfaces with standard TCR repertoire data formats. We showcase the applicability of ePytope-TCR by evaluating the performance of these publicly available prediction models on two challenging datasets. While novel predictors successfully predicted binding to frequently observed epitopes, all methods failed for less frequently observed epitopes. Further, we detected a strong bias in the prediction scores between different epitope classes. We envision this benchmark to guide researchers in their choice of a predictor and to accelerate the method development by defining standardized evaluation settings.
AU  - Drost, F.
AU  - Chernysheva, A.
AU  - Albahah, M.
AU  - Kocher, K.*
AU  - Schober, K.*
AU  - Schubert, B.
C1  - 75113
C2  - 57819
CY  - 50 Hampshire St, Floor 5, Cambridge, Ma 02139 Usa
TI  - Benchmarking of T cell receptor-epitope predictors with ePytope-TCR.
JO  - Cell Genom.
VL  - 5
IS  - 8
PB  - Cell Press
PY  - 2025
SN  - 2666-979X
ER  - 

TY  - JOUR
AB  - There is a pressing need to generate molecular data from diverse tissues across global populations. These currently missing data are necessary to resolve genome-wide association study loci, identify effector genes, and move the translational genomics needle beyond European-ancestry individuals and the minority of diseases for which blood is the relevant tissue.
AU  - De Santana Villasboas Arruda, A.L.
AU  - Morris, A.P.
AU  - Zeggini, E.
C1  - 69861
C2  - 55289
CY  - Radarweg 29, 1043 Nx Amsterdam, Netherlands
TI  - Advancing equity in human genomics through tissue-specific multi-ancestry molecular data.
JO  - Cell Genom.
VL  - 4
IS  - 2
PB  - Elsevier
PY  - 2024
SN  - 2666-979X
ER  - 

TY  - JOUR
AB  - Cancer cells and pathogens can evade T cell receptors (TCRs) via mutations in immunogenic epitopes. TCR cross-reactivity (i.e., recognition of multiple epitopes with sequence similarities) can counteract such escape but may cause severe side effects in cell-based immunotherapies through targeting self-antigens. To predict the effect of epitope point mutations on T cell functionality, we here present the random forest-based model Predicting T Cell Epitope-Specific Activation against Mutant Versions (P-TEAM). P-TEAM was trained and tested on three datasets with TCR responses to single-amino-acid mutations of the model epitope SIINFEKL, the tumor neo-epitope VPSVWRSSL, and the human cytomegalovirus antigen NLVPMVATV, totaling 9,690 unique TCR-epitope interactions. P-TEAM was able to accurately classify T cell reactivities and quantitatively predict T cell functionalities for unobserved single-point mutations and unseen TCRs. Overall, P-TEAM provides an effective computational tool to study T cell responses against mutated epitopes.
AU  - Drost, F.
AU  - Dorigatti, E.
AU  - Straub, A.*
AU  - Hilgendorf, P.*
AU  - Wagner, K.I.*
AU  - Heyer, K.*
AU  - López Montes, M.*
AU  - Bischl, B.*
AU  - Busch, D.H.*
AU  - Schober, K.*
AU  - Schubert, B.
C1  - 71492
C2  - 56213
CY  - Radarweg 29, 1043 Nx Amsterdam, Netherlands
TI  - Predicting T cell receptor functionality against mutant epitopes.
JO  - Cell Genom.
VL  - 4
IS  - 9
PB  - Elsevier
PY  - 2024
SN  - 2666-979X
ER  - 

TY  - JOUR
AB  - Human milk has long been recognized for its critical role in infant and maternal health. In this issue of Cell Genomics, Johnson et al.1 apply a human genetics and genomics approach to shed light on the complex relationship between maternal genetics, milk variation, and the infant gut microbiome.
AU  - Nussbaum, C.*
AU  - Kim-Hellmuth, S.
C1  - 71989
C2  - 56347
CY  - Radarweg 29, 1043 Nx Amsterdam, Netherlands
TI  - Unlocking the genetic influence on milk variation and its potential implication for infant health.
JO  - Cell Genom.
VL  - 4
IS  - 10
PB  - Elsevier
PY  - 2024
SN  - 2666-979X
ER  - 

TY  - JOUR
AB  - Identifying factors that affect treatment response is a central objective of clinical research, yet the role of common genetic variation remains largely unknown. Here, we develop a framework to study the genetic architecture of response to commonly prescribed drugs in large biobanks. We quantify treatment response heritability for statins, metformin, warfarin, and methotrexate in the UK Biobank. We find that genetic variation modifies the primary effect of statins on LDL cholesterol (9% heritable) as well as their side effects on hemoglobin A1c and blood glucose (10% and 11% heritable, respectively). We identify dozens of genes that modify drug response, which we replicate in a retrospective pharmacogenomic study. Finally, we find that polygenic score (PGS) accuracy varies up to 2-fold depending on treatment status, showing that standard PGSs are likely to underperform in clinical contexts.
AU  - Sadowski, M.*
AU  - Thompson, M.*
AU  - Mefford, J.*
AU  - Haldar, T.*
AU  - Oni-Orisan, A.*
AU  - Border, R.*
AU  - Pazokitoroudi, A.*
AU  - Cai, N.
AU  - Ayroles, J.F.*
AU  - Sankararaman, S.*
AU  - Dahl, A.W.*
AU  - Zaitlen, N.*
C1  - 72676
C2  - 56702
CY  - Radarweg 29, 1043 Nx Amsterdam, Netherlands
TI  - Characterizing the genetic architecture of drug response using gene-context interaction methods.
JO  - Cell Genom.
VL  - 4
IS  - 12
PB  - Elsevier
PY  - 2024
SN  - 2666-979X
ER  -