Felicia Ng

We compared the transcriptomes of marrow-derived mesenchymal stem cells (MSCs) with differentiated adipocytes, osteocytes, and chondrocytes derived from these MSCs. Using global gene-expression profiling arrays to detect RNA transcripts, we have identified markers that are specific for MSCs and their differentiated progeny. Further, we have also identified pathways that MSCs use to differentiate into adipogenic, chondrogenic, and osteogenic lineages. We identified activin-mediated transforming growth factor (TGF)-beta signaling, platelet-derived growth factor (PDGF) signaling and fibroblast growth factor (FGF) signaling as the key pathways involved in MSC differentiation. The differentiation of MSCs into these lineages is affected when these pathways are perturbed by inhibitors of cell surface receptor function. Since growth and differentiation are tightly linked processes, we also examined the importance of these 3 pathways in MSC growth. These 3 pathways were necessary and sufficient for MSC growth. Inhibiting any of these pathways slowed MSC growth, whereas a combination of TGF-beta, PDGF, and beta-FGF was sufficient to grow MSCs in a serum-free medium up to 5 passages. Thus, this study illustrates it is possible to predict signaling pathways active in cellular differentiation and growth using microarray data and experimentally verify these predictions.

CODEX (http://codex.stemcells.cam.ac.uk/) is a user-friendly database for the direct access and interrogation of publicly available next-generation sequencing (NGS) data, specifically aimed at experimental biologists. In an era of multi-centre genomic dataset generation, CODEX provides a single database where these samples are collected, uniformly processed and vetted. The main drive of CODEX is to provide the wider scientific community with instant access to high-quality NGS data, which, irrespective of the publishing laboratory, is directly comparable. CODEX allows users to immediately visualize or download processed datasets, or compare user-generated data against the database's cumulative knowledge-base. CODEX contains four types of NGS experiments: transcription factor chromatin immunoprecipitation coupled to high-throughput sequencing (ChIP-Seq), histone modification ChIP-Seq, DNase-Seq and RNA-Seq. These are largely encompassed within two specialized repositories, HAEMCODE and ESCODE, which are focused on haematopoiesis and embryonic stem cell samples, respectively. To date, CODEX contains over 1000 samples, including 221 unique TFs and 93 unique cell types. CODEX therefore provides one of the most complete resources of publicly available NGS data for the direct interrogation of transcriptional programmes that regulate cellular identity and fate in the context of mammalian development, homeostasis and disease.

Treatment with anti-PD-1 and anti-PD-L1 therapies has shown durable clinical benefit in non-small cell lung cancer (NSCLC). However, patients with NSCLC with epidermal growth factor receptor (EGFR) mutations do not respond as well to treatment as patients without an EGFR mutation. We show that EGFR-mutated NSCLC expressed higher levels of CD73 compared with EGFR WT tumors and that CD73 expression was regulated by EGFR signaling. EGFR-mutated cell lines were significantly more resistant to T cell killing compared with WT cell lines through suppression of T cell proliferation and function. In a xenograft mouse model of EGFR-mutated NSCLC, neither anti-PD-L1 nor anti-CD73 antibody alone inhibited tumor growth compared with the isotype control. In contrast, the combination of both antibodies significantly inhibited tumor growth, increased the number of tumor-infiltrating CD8+ T cells, and enhanced IFN-γ and TNF-α production of these T cells. Consistently, there were increases in gene expression that corresponded to inflammation and T cell function in tumors treated with the combination of anti-PD-L1 and anti-CD73. Together, these results further support the combination of anti-CD73 and anti-PD-L1 therapies in treating EGFR-mutated NSCLC, while suggesting that increased T cell activity may play a role in response to therapy.