Identification of aberrant luminal progenitors and mTORC1 as a potential breast cancer prevention target in BRCA2 mutation carriers.

Inheritance of a BRCA2 pathogenic variant conveys a substantial life-time risk of breast cancer. Identification of the cell(s)-of-origin of BRCA2-mutant breast cancer and targetable perturbations that contribute to transformation remains an unmet need for these individuals who frequently undergo prophylactic mastectomy. Using preneoplastic specimens from age-matched, premenopausal females, here we show broad dysregulation across the luminal compartment in BRCA2mut/+ tissue, including expansion of aberrant ERBB3lo luminal progenitor and mature cells, and the presence of atypical oestrogen receptor (ER)-positive lesions. Transcriptional profiling and functional assays revealed perturbed proteostasis and translation in ERBB3lo progenitors in BRCA2mut/+ breast tissue, independent of ageing. Similar molecular perturbations marked tumours bearing BRCA2-truncating mutations. ERBB3lo progenitors could generate both ER+ and ER- cells, potentially serving as cells-of-origin for ER-positive or triple-negative cancers. Short-term treatment with an mTORC1 inhibitor substantially curtailed tumorigenesis in a preclinical model of BRCA2-deficient breast cancer, thus uncovering a potential prevention strategy for BRCA2 mutation carriers.

sccomp: Robust differential composition and variability analysis for single-cell data.

Cellular omics such as single-cell genomics, proteomics, and microbiomics allow the characterization of tissue and microbial community composition, which can be compared between conditions to identify biological drivers. This strategy has been critical to revealing markers of disease progression, such as cancer and pathogen infection. A dedicated statistical method for differential variability analysis is lacking for cellular omics data, and existing methods for differential composition analysis do not model some compositional data properties, suggesting there is room to improve model performance. Here, we introduce sccomp, a method for differential composition and variability analyses that jointly models data count distribution, compositionality, group-specific variability, and proportion mean-variability association, being aware of outliers. sccomp provides a comprehensive analysis framework that offers realistic data simulation and cross-study knowledge transfer. Here, we demonstrate that mean-variability association is ubiquitous across technologies, highlighting the inadequacy of the very popular Dirichlet-multinomial distribution. We show that sccomp accurately fits experimental data, significantly improving performance over state-of-the-art algorithms. Using sccomp, we identified differential constraints and composition in the microenvironment of primary breast cancer.

Early immune pressure initiated by tissue-resident memory T cells sculpts tumor evolution in non-small cell lung cancer.

Tissue-resident memory T (TRM) cells provide immune defense against local infection and can inhibit cancer progression. However, it is unclear to what extent chronic inflammation impacts TRM activation and whether TRM cells existing in tissues before tumor onset influence cancer evolution in humans. We performed deep profiling of healthy lungs and lung cancers in never-smokers (NSs) and ever-smokers (ESs), finding evidence of enhanced immunosurveillance by cells with a TRM-like phenotype in ES lungs. In preclinical models, tumor-specific or bystander TRM-like cells present prior to tumor onset boosted immune cell recruitment, causing tumor immune evasion through loss of MHC class I protein expression and resistance to immune checkpoint inhibitors. In humans, only tumors arising in ES patients underwent clonal immune evasion, unrelated to tobacco-associated mutagenic signatures or oncogenic drivers. These data demonstrate that enhanced TRM-like activity prior to tumor development shapes the evolution of tumor immunogenicity and can impact immunotherapy outcomes.

Venetoclax treatment in patients with cancer has limited impact on circulating T and NK cells.

Venetoclax is an effective treatment for certain blood cancers, such as chronic lymphocytic leukemia (CLL) and acute myeloid leukemia (AML). However, most patients relapse while on venetoclax and further treatment options are limited. Combining venetoclax with immunotherapies is an attractive approach; however, a detailed understanding of how venetoclax treatment impacts normal immune cells in patients is lacking. In this study, we performed deep profiling of peripheral blood (PB) cells from patients with CLL and AML before and after short-term treatment with venetoclax using mass cytometry (cytometry by time of flight) and found no impact on the concentrations of key T-cell subsets or their expression of checkpoint molecules. We also analyzed PB from patients with breast cancer receiving venetoclax long-term using a single-cell multiomics approach (cellular indexing of transcriptomes and epitopes by sequencing) and functional assays. We found significant depletion of B-cell populations with low expression of MCL-1 relative to other immune cells, attended by extensive transcriptomic changes. By contrast, there was less impact on circulating T cells and natural killer (NK) cells, with no changes in their subset composition, transcriptome, or function following venetoclax treatment. Our data indicate that venetoclax has minimal impact on circulating T or NK cells, supporting the rationale of combining this BH3 mimetic drug with cancer immunotherapies for more durable antitumor responses.

Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets.

Mass cytometry (CyTOF) is a technology that has revolutionised single-cell biology. By detecting over 40 proteins on millions of single cells, CyTOF allows the characterisation of cell subpopulations in unprecedented detail. However, most CyTOF studies require the integration of data from multiple CyTOF batches usually acquired on different days and possibly at different sites. To date, the integration of CyTOF datasets remains a challenge due to technical differences arising in multiple batches. To overcome this limitation, we developed an approach called CytofRUV for analysing multiple CyTOF batches, which includes an R-Shiny application with diagnostic plots. CytofRUV can correct for batch effects and integrate data from large numbers of patients and conditions across batches, to confidently compare cellular changes and correlate these with clinically relevant outcomes.

Smchd1 regulates long-range chromatin interactions on the inactive X chromosome and at Hox clusters.

The regulation of higher-order chromatin structure is complex and dynamic, and a full understanding of the suite of mechanisms governing this architecture is lacking. Here, we reveal the noncanonical SMC protein Smchd1 to be a novel regulator of long-range chromatin interactions in mice, and we add Smchd1 to the canon of epigenetic proteins required for Hox-gene regulation. The effect of losing Smchd1-dependent chromatin interactions has varying outcomes that depend on chromatin context. At autosomal targets transcriptionally sensitive to Smchd1 deletion, we found increased short-range interactions and ectopic enhancer activation. In contrast, the inactive X chromosome was transcriptionally refractive to Smchd1 ablation, despite chromosome-wide increases in short-range interactions. In the inactive X, we observed spreading of trimethylated histone H3 K27 (H3K27me3) domains into regions not normally decorated by this mark. Together, these data suggest that Smchd1 is able to insulate chromatin, thereby limiting access to other chromatin-modifying proteins.

Defined chromosome structure in the genome-reduced bacterium Mycoplasma pneumoniae.

DNA-binding proteins are central regulators of chromosome organization; however, in genome-reduced bacteria their diversity is largely diminished. Whether the chromosomes of such bacteria adopt defined three-dimensional structures remains unexplored. Here we combine Hi-C and super-resolution microscopy to determine the structure of the Mycoplasma pneumoniae chromosome at a 10 kb resolution. We find a defined structure, with a global symmetry between two arms that connect opposite poles, one bearing the chromosomal Ori and the other the midpoint. Analysis of local structures at a 3 kb resolution indicates that the chromosome is organized into domains ranging from 15 to 33 kb. We provide evidence that genes within the same domain tend to be co-regulated, suggesting that chromosome organization influences transcriptional regulation, and that supercoiling regulates local organization. This study extends the current understanding of bacterial genome organization and demonstrates that a defined chromosomal structure is a universal feature of living systems.

Assessing the limits of restraint-based 3D modeling of genomes and genomic domains.

Restraint-based modeling of genomes has been recently explored with the advent of Chromosome Conformation Capture (3C-based) experiments. We previously developed a reconstruction method to resolve the 3D architecture of both prokaryotic and eukaryotic genomes using 3C-based data. These models were congruent with fluorescent imaging validation. However, the limits of such methods have not systematically been assessed. Here we propose the first evaluation of a mean-field restraint-based reconstruction of genomes by considering diverse chromosome architectures and different levels of data noise and structural variability. The results show that: first, current scoring functions for 3D reconstruction correlate with the accuracy of the models; second, reconstructed models are robust to noise but sensitive to structural variability; third, the local structure organization of genomes, such as Topologically Associating Domains, results in more accurate models; fourth, to a certain extent, the models capture the intrinsic structural variability in the input matrices and fifth, the accuracy of the models can be a priori predicted by analyzing the properties of the interaction matrices. In summary, our work provides a systematic analysis of the limitations of a mean-field restrain-based method, which could be taken into consideration in further development of methods as well as their applications.