Close proximity between cytotoxic T lymphocytes and tumour cells is required for effective immunotherapy. However, what controls the spatial distribution of T cells in the tumour microenvironment is not well understood. Here we couple digital pathology and transcriptome analysis on a large ovarian tumour cohort and develop a machine learning approach to molecularly classify and characterize tumour-immune phenotypes. Our study identifies two important hallmarks characterizing T cell excluded tumours: 1) loss of antigen presentation on tumour cells and 2) upregulation of TGFβ and activated stroma. Furthermore, we identify TGFβ as an important mediator of T cell exclusion. TGFβ reduces MHC-I expression in ovarian cancer cells in vitro. TGFβ also activates fibroblasts and induces extracellular matrix production as a potential physical barrier to hinder T cell infiltration. Our findings indicate that targeting TGFβ might be a promising strategy to overcome T cell exclusion and improve clinical benefits of cancer immunotherapy.

Small cell lung cancer (SCLC) is a devastating disease because of its tendency to early invasion and refractory relapse after initial treatment response. These aggressive traits have been associated with phenotypic heterogeneity, which however remains incompletely understood. To fill this knowledge gap, we inferred a set of 33 transcription factors (TFs) associated with gene signatures of the known neuroendocrine/epithelial (NE) and non-neuroendocrine/mesenchymal-like (ML) SCLC phenotypes. The topology of this SCLC TF network was derived from prior knowledge and simulated using Boolean modeling. These simulations predicted that the network settles into attractors (TF expression patterns) correlated with NE or ML phenotypes, suggesting that TF network dynamics underlie emergence of heterogeneous SCLC phenotypes in an epigenetic landscape. However, several cell lines and patient samples did not correlate with either the NE or ML attractors. Flow cytometry indicated that single cells within these cell lines simultaneously express surface markers of both NE and ML differentiation, revealing existence of a “hybrid” phenotype. Upon exposure to standard-of-care cytotoxic drugs or epigenetic modifiers, NE and ML cell populations converged toward the hybrid state, suggesting a possible escape route from treatment. Our findings indicate that SCLC phenotypic heterogeneity can be specified dynamically by attractor states of a master regulatory TF network. Thus, SCLC heterogeneity may be best understood as states within an epigenetic landscape. Understanding phenotypic transitions within this landscape could provide insights to clinical applications.

BackgroundOncogenic mechanisms in small-cell lung cancer remain poorly understood leaving this tumor with the worst prognosis among all lung cancers. Unlike other cancer types, sequencing genomic approaches have been of limited success in small-cell lung cancer, i.e., no mutated oncogenes with potential driver characteristics have emerged, as it is the case for activating mutations of epidermal growth factor receptor in non-small-cell lung cancer. Differential gene expression analysis has also produced SCLC signatures with limited application, since they are generally not robust across datasets. Nonetheless, additional genomic approaches are warranted, due to the increasing availability of suitable small-cell lung cancer datasets. Gene co-expression network approaches are a recent and promising avenue, since they have been successful in identifying gene modules that drive phenotypic traits in several biological systems, including other cancer types.ResultsWe derived an SCLC-specific classifier from weighted gene co-expression network analysis (WGCNA) of a lung cancer dataset. The classifier, termed SCLC-specific hub network (SSHN), robustly separates SCLC from other lung cancer types across multiple datasets and multiple platforms, including RNA-seq and shotgun proteomics. The classifier was also conserved in SCLC cell lines. SSHN is enriched for co-expressed signaling network hubs strongly associated with the SCLC phenotype. Twenty of these hubs are actionable kinases with oncogenic potential, among which spleen tyrosine kinase (SYK) exhibits one of the highest overall statistical associations to SCLC. In patient tissue microarrays and cell lines, SCLC can be separated into SYK-positive and -negative. SYK siRNA decreases proliferation rate and increases cell death of SYK-positive SCLC cell lines, suggesting a role for SYK as an oncogenic driver in a subset of SCLC.ConclusionsSCLC treatment has thus far been limited to chemotherapy and radiation. Our WGCNA analysis identifies SYK both as a candidate biomarker to stratify SCLC patients and as a potential therapeutic target. In summary, WGCNA represents an alternative strategy to large scale sequencing for the identification of potential oncogenic drivers, based on a systems view of signaling networks. This strategy is especially useful in cancer types where no actionable mutations have emerged.

Small-cell lung cancer (SCLC) is the most aggressive subtype of lung cancer in its clinical behavior, with a 5-year overall survival as low as 5%. Despite years of research in the field, molecular determinants of SCLC behavior are still poorly understood, and this deficiency has translated into an absence of specific diagnostics and targeted therapeutics. We hypothesized that tumor DNA copy number alterations would allow the identification of molecular pathways involved in SCLC progression. Array comparative genomic hybridization was performed on DNA extracted from 46 formalin-fixed paraffin-embedded SCLC tissue specimens. Genomic profiling of tumor and sex-matched control DNA allowed the identification of 70 regions of copy number gain and 55 regions of copy number loss. Using molecular pathway analysis, we found a strong enrichment in these regions of copy number alterations for 11 genes associated with the focal adhesion pathway. We verified these findings at the genomic, gene expression and protein level. Focal Adhesion Kinase (FAK), one of the central genes represented in this pathway, was commonly expressed in SCLC tumors and constitutively phosphorylated in SCLC cell lines. Those were poorly adherent to most substrates but not to laminin-322. Inhibition of FAK phosphorylation at Tyr397 by a small-molecule inhibitor, PF-573,228, induced a dose-dependent decrease of adhesion and an increase of spreading in SCLC cell lines on laminin-322. Cells that tended to spread also showed a decrease in focal adhesions, as demonstrated by a decreased vinculin expression. These results support the concept that pathway analysis of genes in regions of copy number alterations may uncover molecular mechanisms of disease progression and demonstrate a new role of FAK and associated adhesion pathways in SCLC. Further investigations of FAK at the functional level may lead to a better understanding of SCLC progression and may have therapeutic implications.

We describe a simple iterative approach to augment TCR affinity, which we studied using a myelin oligodendrocyte glycoproteinspecific TCR. We hypothesized that single amino acid modifications in TCR CDR3 could enhance TCR sensitivity through focal interactions with antigenic peptide while minimizing the risk of cross-reactivity observed previously in TCR more broadly mutagenized using in vitro evolution techniques. We show that this iterative method can indeed generate TCR with Ag sensitivity 100-fold greater than the parental receptor and can endow TCR with coreceptor independence. However, we also find that single amino acid mutations in the CDR3 can alter TCR fine specificity, affecting recognition requirements for Ag residues over most of the length of the MHC binding groove. Furthermore, minimal changes in surface-exposed CDR3 amino acids, even the addition of a single hydroxyl group or conversion of a methyl or sulfhydryl moiety to a hydroxyl, can confer modified Ag-specific TCR with new self-reactivity. In vivo modeling of modified TCR through retroviral TCR gene transfer into Rag ؊/؊ mice confirmed the biological significance of these altered reactivities, although it also demonstrated the feasibility of producing Ag-specific, positively selecting, coreceptor-independent receptors with markedly increased Ag sensitivity. These results affirm the possibility of readily generating affinity-enhanced TCR for therapeutic purposes but demonstrate that minimal changes in TCR CDR3 L imits on the TCR repertoire imposed by developmental selection and peripheral tolerance restrict the availability of T cells that can effectively target tumors or some pathogens. To overcome this, there has been growing interest in therapeutically skewing the T cell compartment through the enforced expression on T cells of cloned Ag-specific TCR, thereby promoting desirable immune responses (1, 2). One recent clinical trial, for example, showed that tumors in a subset of metastatic melanoma patients remitted after the infusion of CTL redirected with retrovirally transduced tumor Ag-specific TCR (3). Redirection of regulatory T lymphocytes with introduced autoantigen-specific TCR has similarly been proposed for use in the treatment of autoimmune conditions (4) and has been a subject of our interest. However, TCR gene therapy is currently limited by the availability within the natural TCR repertoire of Ag-specific receptors with desirable therapeutic properties. Both tumor-specific and autoantigen-specific TCR are often of low affinity. T cells transduced with these frequently express low levels of receptor that must compete with endogenous TCR for expression (5). Target ligand may be weakly expressed or expressed in the context of insufficient costimulation. Simple approaches to engineer TCR response characteristics, particularly affinity, are therefore desirable and may aid in the creation of receptors with optimized therapeutic potential.Essentially two approaches have been used to manipulate TCR affinity, and studies of these have ...