PAX8 lineage-driven T cell engaging antibody for the treatment of high-grade serous ovarian cancer.

High-grade serous ovarian cancers (HGSOC) represent the most common subtype of ovarian malignancies. Due to the frequency of late-stage diagnosis and high rates of recurrence following standard of care treatments, novel therapies are needed to promote durable responses. We investigated the anti-tumor activity of CD3 T cell engaging bispecific antibodies (TCBs) directed against the PAX8 lineage-driven HGSOC tumor antigen LYPD1 and demonstrated that anti-LYPD1 TCBs induce T cell activation and promote in vivo tumor growth inhibition in LYPD1-expressing HGSOC. To selectively target LYPD1-expressing tumor cells with high expression while sparing cells with low expression, we coupled bivalent low-affinity anti-LYPD1 antigen-binding fragments (Fabs) with the anti-CD3 scFv. In contrast to the monovalent anti-LYPD1 high-affinity TCB (VHP354), the bivalent low-affinity anti-LYPD1 TCB (QZC131) demonstrated antigen density-dependent selectivity and showed tolerability in cynomolgus monkeys at the maximum dose tested of 3 mg/kg. Collectively, these data demonstrate that bivalent TCBs directed against LYPD1 have compelling efficacy and safety profiles to support its use as a treatment for high-grade serous ovarian cancers.

Deregulation of ribosomal protein expression and translation promotes breast cancer metastasis.

Circulating tumor cells (CTCs) are shed into the bloodstream from primary tumors, but only a small subset of these cells generates metastases. We conducted an in vivo genome-wide CRISPR activation screen in CTCs from breast cancer patients to identify genes that promote distant metastasis in mice. Genes coding for ribosomal proteins and regulators of translation were enriched in this screen. Overexpression of RPL15, which encodes a component of the large ribosomal subunit, increased metastatic growth in multiple organs and selectively enhanced translation of other ribosomal proteins and cell cycle regulators. RNA sequencing of freshly isolated CTCs from breast cancer patients revealed a subset with strong ribosome and protein synthesis signatures; these CTCs expressed proliferation and epithelial markers and correlated with poor clinical outcome. Therapies targeting this aggressive subset of CTCs may merit exploration as potential suppressors of metastatic progression.

Stromal Microenvironment Shapes the Intratumoral Architecture of Pancreatic Cancer.

Single-cell technologies have described heterogeneity across tissues, but the spatial distribution and forces that drive single-cell phenotypes have not been well defined. Combining single-cell RNA and protein analytics in studying the role of stromal cancer-associated fibroblasts (CAFs) in modulating heterogeneity in pancreatic cancer (pancreatic ductal adenocarcinoma [PDAC]) model systems, we have identified significant single-cell population shifts toward invasive epithelial-to-mesenchymal transition (EMT) and proliferative (PRO) phenotypes linked with mitogen-activated protein kinase (MAPK) and signal transducer and activator of transcription 3 (STAT3) signaling. Using high-content digital imaging of RNA in situ hybridization in 195 PDAC tumors, we quantified these EMT and PRO subpopulations in 319,626 individual cancer cells that can be classified within the context of distinct tumor gland "units." Tumor gland typing provided an additional layer of intratumoral heterogeneity that was associated with differences in stromal abundance and clinical outcomes. This demonstrates the impact of the stroma in shaping tumor architecture by altering inherent patterns of tumor glands in human PDAC.

Single-cell RNA sequencing identifies extracellular matrix gene expression by pancreatic circulating tumor cells.

Circulating tumor cells (CTCs) are shed from primary tumors into the bloodstream, mediating the hematogenous spread of cancer to distant organs. To define their composition, we compared genome-wide expression profiles of CTCs with matched primary tumors in a mouse model of pancreatic cancer, isolating individual CTCs using epitope-independent microfluidic capture, followed by single-cell RNA sequencing. CTCs clustered separately from primary tumors and tumor-derived cell lines, showing low-proliferative signatures, enrichment for the stem-cell-associated gene Aldh1a2, biphenotypic expression of epithelial and mesenchymal markers, and expression of Igfbp5, a gene transcript enriched at the epithelial-stromal interface. Mouse as well as human pancreatic CTCs exhibit a very high expression of stromal-derived extracellular matrix (ECM) proteins, including SPARC, whose knockdown in cancer cells suppresses cell migration and invasiveness. The aberrant expression by CTCs of stromal ECM genes points to their contribution of microenvironmental signals for the spread of cancer to distant organs.

Efficiently identifying genome-wide changes with next-generation sequencing data.

We propose a new and effective statistical framework for identifying genome-wide differential changes in epigenetic marks with ChIP-seq data or gene expression with mRNA-seq data, and we develop a new software tool EpiCenter that can efficiently perform data analysis. The key features of our framework are: (i) providing multiple normalization methods to achieve appropriate normalization under different scenarios, (ii) using a sequence of three statistical tests to eliminate background regions and to account for different sources of variation and (iii) allowing adjustment for multiple testing to control false discovery rate (FDR) or family-wise type I error. Our software EpiCenter can perform multiple analytic tasks including: (i) identifying genome-wide epigenetic changes or differentially expressed genes, (ii) finding transcription factor binding sites and (iii) converting multiple-sample sequencing data into a single read-count data matrix. By simulation, we show that our framework achieves a low FDR consistently over a broad range of read coverage and biological variation. Through two real examples, we demonstrate the effectiveness of our framework and the usages of our tool. In particular, we show that our novel and robust 'parsimony' normalization method is superior to the widely-used 'tagRatio' method. Our software EpiCenter is freely available to the public.

Trophoblast stem cell maintenance by fibroblast growth factor 4 requires MEKK4 activation of Jun N-terminal kinase.

Trophoblast differentiation during placentation involves an epithelial-mesenchymal transition (EMT) with loss of E-cadherin and gain of trophoblast invasiveness. Mice harboring a point mutation that renders inactive the mitogen-activated protein kinase kinase kinase MEKK4 exhibit dysregulated placental development with increased trophoblast invasion. Isolated MEKK4 kinase-inactive trophoblast stem (TS) cells cultured under undifferentiating, self-renewing conditions in the presence of fibroblast growth factor 4 (FGF4) display increased expression of Slug, Twist, and matrix metalloproteinase 2 (MMP2), loss of E-cadherin, and hyperinvasion of extracellular matrix, each a hallmark of EMT. MEKK4 kinase-inactive TS cells show a preferential differentiation to Tpbp alpha- and Gcm1-positive trophoblasts, which are indicative of spongiotrophoblast and syncytiotrophoblast differentiation, respectively. FGF4-stimulated Jun N-terminal kinase (JNK) and p38 activity is markedly reduced in MEKK4 kinase-inactive TS cells. Chemical inhibition of JNK in wild-type TS cells induced a similar EMT response as loss of MEKK4 kinase activity, including inhibition of E-cadherin expression and increased expression of Slug, MMP2, Tpbp alpha, and Gcm1. Chromatin immunoprecipitation analyses revealed changes in AP-1 composition with increased Fra-2 and decreased Fra-1 and JunB binding to the regulatory regions of Gcm1 and MMP2 genes in MEKK4 kinase-inactive TS cells. Our results define MEKK4 as a signaling hub for FGF4 activation of JNK that is required for maintenance of TS cells in an undifferentiated state.