No abstract

Adaptive immune responses are tailored to different types of pathogens through differentiation of naïve CD4 T cells into functionally distinct subsets of effector T cells (TH1, TH2, and TH17) defined by expression of key transcription factors (TFs)1. Regulatory T (Treg) cells comprise a distinct anti-inflammatory lineage specified by the X-linked TF Foxp32, 3. Paradoxically, some activated Treg cells express the aforementioned effector CD4 T cell TFs, which have been suggested to endow Treg cells with enhanced suppressive capacity4, 5, 6. Whether expression of these factors in Treg cells—akin to effector T cells—is indicative of heterogeneity of functionally discrete and stable differentiation states, or conversely may be readily reversible, is unknown. Here, we demonstrate that in Treg cells expression of the TH1-associated TF T-bet, induced at steady state and following infection, gradually becomes highly stable even under non-permissive conditions. Loss-of-function or elimination of T-bet-expressing Treg cells—but not of T-bet in Treg cells—resulted in severe TH1 autoimmunity. Conversely, following depletion of T-bet-negative Treg cells, remaining T-bet+ cells specifically inhibited TH1 and CD8 T cell activation in agreement with their co-localization with T-bet+ effector T cells. These results suggest an essential immunosuppressive function for T-bet+ Treg cells and indicate that Treg cell functional heterogeneity is a critical feature of immune tolerance.

A substantial proportion of tumors consist of genotypically distinct subpopulations of cancer cells. This intra-tumor genetic heterogeneity poses a significant challenge for the implementation of precision medicine. Single-cell genomics constitutes a powerful approach to resolve complex mixtures of cancer cells by tracing cell lineages and discovering cryptic genetic variations that would otherwise be obscured in tumor bulk analyses. Given the chemical alterations that result from formalin fixation, single-cell genomic approaches have largely remained limited to fresh/frozen specimens. Here we describe the development and validation of a robust and accurate methodology to perform whole-genome copy-number profiling of single nuclei obtained from formalin-fixed paraffin-embedded clinical tumor samples. We applied the single-cell sequencing approach described here to study the progression from in situ to invasive breast cancer, which revealed that ductal carcinomas in situ display intra-tumor genetic heterogeneity at diagnosis and that these lesions may progress to invasive breast cancer through a variety of evolutionary processes.

Metaplastic breast carcinoma is a rare and aggressive histologic type of breast cancer, preferentially displaying a triple-negative phenotype. We sought to define the transcriptomic heterogeneity of metaplastic breast cancers on the basis of current gene expression microarray-based classifiers, and to determine whether these tumors display gene copy number profiles consistent with those of BRCA1-associated breast cancers. Twenty-eight consecutive triple-negative metaplastic breast carcinomas were reviewed, and the metaplastic component present in each frozen specimen was defined (ie, spindle cell, squamous, chondroid metaplasia). RNA and DNA extracted from frozen sections with tumor cell content >60% were subjected to gene expression (Illumina HumanHT-12 v4) and copy number profiling (Affymetrix SNP 6.0), respectively. Using the best practice PAM50/claudin-low microarray-based classifier, all metaplastic breast carcinomas with spindle cell metaplasia were of claudin-low subtype, whereas those with squamous or chondroid metaplasia were preferentially of basal-like subtype. Triple-negative breast cancer subtyping using a dedicated website (http://cbc.mc.vanderbilt.edu/tnbc/) revealed that all metaplastic breast carcinomas with chondroid metaplasia were of mesenchymal-like subtype, spindle cell carcinomas preferentially of unstable or mesenchymal stem-like subtype, and those with squamous metaplasia were of multiple subtypes. None of the cases was classified as immunomodulatory or luminal androgen receptor subtype. Integrative clustering, combining gene expression and gene copy number data, revealed that metaplastic breast carcinomas with spindle cell and chondroid metaplasia were preferentially classified as of integrative clusters 4 and 9, respectively, whereas those with squamous metaplasia were classified into six different clusters. Eight of the 26 metaplastic breast cancers subjected to SNP6 analysis were classified as BRCA1-like. The diversity of histologic features of metaplastic breast carcinomas is reflected at the transcriptomic level, and an association between molecular subtypes and histology was observed. BRCA1-like genomic profiles were found only in a subset (31%) of metaplastic breast cancers, and were not associated with a specific molecular or histologic subtype.