T cell acute lymphoblastic leukemia (T-ALL) is an immature hematopoietic malignancy driven mainly by oncogenic activation of NOTCH1 signaling1. In this study we report the presence of loss-of-function mutations and deletions of the EZH2 and SUZ12 genes, which encode crucial components of the Polycomb repressive complex 2 (PRC2)2,3, in 25% of T-ALLs. To further study the role of PRC2 in T-ALL, we used NOTCH1-dependent mouse models of the disease, as well as human T-ALL samples, and combined locus-specific and global analysis of NOTCH1-driven epigenetic changes. These studies demonstrated that activation of NOTCH1 specifically induces loss of the repressive mark Lys27 trimethylation of histone 3 (H3K27me3)4 by antagonizing the activity of PRC2. These studies suggest a tumor suppressor role for PRC2 in human leukemia and suggest a hitherto unrecognized dynamic interplay between oncogenic NOTCH1 and PRC2 function for the regulation of gene expression and cell transformation.

Background: Theobroma cacao L. cultivar Matina 1-6 belongs to the most cultivated cacao type. The availability of its genome sequence and methods for identifying genes responsible for important cacao traits will aid cacao researchers and breeders. Results: We describe the sequencing and assembly of the genome of Theobroma cacao L. cultivar Matina 1-6. The genome of the Matina 1-6 cultivar is 445 Mbp, which is significantly larger than a sequenced Criollo cultivar, and more typical of other cultivars. The chromosome-scale assembly, version 1.1, contains 711 scaffolds covering 346.0 Mbp, with a contig N50 of 84.4 kbp, a scaffold N50 of 34.4 Mbp, and an evidence-based gene set of 29,408 loci. Version 1.1 has 10x the scaffold N50 and 4x the contig N50 as Criollo, and includes 111 Mb more anchored sequence. The version 1.1 assembly has 4.4% gap sequence, while Criollo has 10.9%. Through a combination of haplotype, association mapping and gene expression analyses, we leverage this robust reference genome to identify a promising candidate gene responsible for pod color variation. We demonstrate that green/red pod color in cacao is likely regulated by the R2R3 MYB transcription factor TcMYB113, homologs of which determine pigmentation in Rosaceae, Solanaceae, and Brassicaceae. One SNP within the target site for a highly conserved trans-acting siRNA in dicots, found within TcMYB113, seems to affect transcript levels of this gene and therefore pod color variation. Conclusions: We report a high-quality sequence and annotation of Theobroma cacao L. and demonstrate its utility in identifying candidate genes regulating traits.

Sacituzumab govitecan (SG), the first antibody–drug conjugate (ADC) approved for triple-negative breast cancer, incorporates the anti-TROP2 antibody hRS7 conjugated to a topoisomerase-1 (TOP1) inhibitor payload. We sought to identify mechanisms of SG resistance through RNA and whole-exome sequencing of pretreatment and postprogression specimens. One patient exhibiting de novo progression lacked TROP2 expression, in contrast to robust TROP2 expression and focal genomic amplification of TACSTD2/TROP2 observed in a patient with a deep, prolonged response to SG. Analysis of acquired genomic resistance in this case revealed one phylogenetic branch harboring a canonical TOP1E418K resistance mutation and subsequent frameshift TOP1 mutation, whereas a distinct branch exhibited a novel TACSTD2/TROP2T256R missense mutation. Reconstitution experiments demonstrated that TROP2T256R confers SG resistance via defective plasma membrane localization and reduced cell-surface binding by hRS7. These findings highlight parallel genomic alterations in both antibody and payload targets associated with resistance to SG. Significance: These findings underscore TROP2 as a response determinant and reveal acquired SG resistance mechanisms involving the direct antibody and drug payload targets in distinct metastatic subclones of an individual patient. This study highlights the specificity of SG and illustrates how such mechanisms will inform therapeutic strategies to overcome ADC resistance. This article is highlighted in the In This Issue feature, p. 2355

The inference of the number of clusters in a dataset, a fundamental problem in Statistics, Data Analysis and Classification, is usually addressed via internal validation measures. The stated problem is quite difficult, in particular for microarrays, since the inferred prediction must be sensible enough to capture the inherent biological structure in a dataset, e.g., functionally related genes. Despite the rich literature present in that area, the identification of an internal validation measure that is both fast and precise has proved to be elusive. In order to partially fill this gap, we propose a speed-up of Consensus (Consensus Clustering), a methodology whose purpose is the provision of a prediction of the number of clusters in a dataset, together with a dissimilarity matrix (the consensus matrix) that can be used by clustering algorithms. As detailed in the remainder of the paper, Consensus is a natural candidate for a speed-up.