Multiple studies have identified transcriptome subtypes of high-grade serous ovarian carcinoma (HGSOC), but their interpretation and translation are complicated by tumor evolution and polyclonality accompanied by extensive accumulation of somatic aberrations, varying cell type admixtures, and different tissues of origin. In this study, we examined the chronology of HGSOC subtype evolution in the context of these factors using a novel integrative analysis of absolute copy-number analysis and gene expression in The Cancer Genome Atlas complemented by single-cell analysis of six independent tumors. Tumor purity, ploidy, and subclonality were reliably inferred from different genomic platforms, and these characteristics displayed marked differences between subtypes. Genomic lesions associated with HGSOC subtypes tended to be subclonal, implying subtype divergence at later stages of tumor evolution. Subclonality of recurrent HGSOC alterations was evident for proliferative tumors, characterized by extreme genomic instability, absence of immune infiltration, and greater patient age. In contrast, differentiated tumors were characterized by largely intact genome integrity, high immune infiltration, and younger patient age. Single-cell sequencing of 42,000 tumor cells revealed widespread heterogeneity in tumor cell type composition that drove bulk subtypes but demonstrated a lack of intrinsic subtypes among tumor epithelial cells. Our findings prompt the dismissal of discrete transcriptome subtypes for HGSOC and replacement by a more realistic model of continuous tumor development that includes mixtures of subclones, accumulation of somatic aberrations, infiltration of immune and stromal cells in proportions correlated with tumor stage and tissue of origin, and evolution between properties previously associated with discrete subtypes.Significance: This study infers whether transcriptome-based groupings of tumors differentiate early in carcinogenesis and are, therefore, appropriate targets for therapy and demonstrates that this is not the case for HGSOC.

Invariant NKT cells differentiate into three predominant effector lineages in the steady state. To understand these lineages, we sorted undifferentiated invariant NK T progenitor cells and each effector population and analyzed their transcriptional profiles by RNAseq. Bioinformatic comparisons were made to effector subsets among other lymphocytes, specifically Th cells, innate lymphoid cells (ILC), and γδ T cells. Myc-associated signature genes were enriched in NKT progenitors, like in other hematopoietic progenitors. Only NKT1 cells, but not NKT2 and NKT17 cells, had transcriptome similarity to NK cells and were also similar to other IFN-γ–producing lineages such as Th1, ILC1, and intraepithelial γδ T cells. NKT2 and NKT17 cells were similar to their analogous subsets of γδ T cells and ILCs, but surprisingly, not to Th2 and Th17 cells. We identified a set of genes common to each effector lineage regardless of Ag receptor specificity, suggesting the use of conserved regulatory cores for effector function.

CD8 effector T cells with a CD127hi KLRG1− phenotype are considered precursors to the long-lived memory pool, whereas KLRG1+CD127low cells are viewed as short-lived effectors. Nevertheless, we and others have shown that a KLRG1+CD127low population persists into the memory phase and that these T cells (termed long-lived effector cells [LLEC]) display robust protective function during acute rechallenge with bacteria or viruses. Whether these T cells represent a true memory population or are instead a remnant effector cell population that failed to undergo initial contraction has remained unclear. In this study, we show that LLEC from mice express a distinct phenotypic and transcriptional signature that shares characteristics of both early effectors and long-lived memory cells. We also find that in contrast to KLRG1+ effector cells, LLEC undergo homeostatic proliferation and are not critically dependent on IL-15 for their maintenance. Furthermore, we find that LLEC are predominantly derived from KLRG1+ effector cells when isolated at day 12 of the response. Our work challenges the concept that the KLRG1+CD127low population is dominated by short-lived cells and shows that KLRG1 downregulation is not a prerequisite to become a long-lived protective memory T cell.

Purpose: Prostate cancer is the second leading cause of male cancer deaths. Castration-resistant prostate cancer (CRPC) is a lethal stage of the disease that emerges when endocrine therapies are no longer effective at suppressing activity of the androgen receptor (AR) transcription factor. The purpose of this study was to identify genomic mechanisms that contribute to the development and progression of CRPC. Experimental Design: We used whole-genome and targeted DNA-sequencing approaches to identify mechanisms underlying CRPC in an aggregate cohort of 272 prostate cancer patients. We analyzed structural rearrangements at the genome-wide level and carried out a detailed structural rearrangement analysis of the AR locus. We used genome engineering to perform experimental modeling of AR gene rearrangements and long-read RNA sequencing to analyze effects on expression of AR and truncated AR variants (AR-V). Results: AR was among the most frequently rearranged genes in CRPC tumors. AR gene rearrangements promoted expression of diverse AR-V species. AR gene rearrangements occurring in the context of AR amplification correlated with AR overexpression. Cell lines with experimentally derived AR gene rearrangements displayed high expression of tumor-specific AR-Vs and were resistant to endocrine therapies, including the AR antagonist enzalutamide. Conclusions: AR gene rearrangements are an important mechanism of resistance to endocrine therapies in CRPC.

Introduction: Targeted therapies for aggressive breast cancers like triple negative breast cancer (TNBC) are needed. The use of small interfering RNAs (siRNAs) to disable expression of survival genes provides a tool for killing these cancer cells. Cyclin dependent kinase 11 (CDK11) is a survival protein kinase that regulates RNA transcription, splicing and mitosis. Casein kinase 2 (CK2) is a survival protein kinase that suppresses cancer cell death. Eliminating the expression of these genes has potential therapeutic utility for breast cancer. Methods: Expression levels of CDK11 and CK2 mRNAs and associated proteins were examined in breast cancer cell lines and tissue arrays. RNA expression levels of CDC2L1, CDC2L2, CCNL1, CCNL2, CSNK2A1, CSNK2A2, and CSNK2B genes in breast cancer subtypes were analyzed. Effects following transfection of siRNAs against CDK11 and CK2 in cultured cells were examined by viability and clonal survival assays and by RNA and protein measures. Uptake of tenfibgen (TBG) nanocapsules by TNBC cells was analyzed by fluorescence-activated cell sorting. TBG nanocapsules delivered siRNAs targeting CDK11 or CK2 in mice carrying TNBC xenograft tumors. Transcript cleavage and response parameters were evaluated. Results: We found strong CDK11 and CK2 mRNA and protein expression in most human breast cancer cells. Immunohistochemical analysis of TNBC patient tissues showed 100% of tumors stained positive for CDK11 with high nuclear intensity compared to normal tissue. The Cancer Genome Atlas analysis comparing basal to other breast cancer subtypes and to normal breast revealed statistically significant differences. Down-regulation of CDK11 and/or CK2 in breast cancer cells caused significant loss of cell viability and clonal survival, reduced relevant mRNA and protein expression, and induced cell death changes. TBG nanocapsules were taken up by TNBC cells both in culture and in xenograft tumors. Treatment with TBG- siRNA to CDK11 or TBG- siRNA to CK2αα’ nanocapsules induced appropriate cleavage of CDK11 and CK2α transcripts in TNBC tumors, and caused MDA-MB-231 tumor reduction, loss of proliferation, and decreased expression of targeted genes. Conclusions: CDK11 and CK2 expression are individually essential for breast cancer cell survival, including TNBC. These genes serve as promising new targets for therapeutic development in breast cancer.