Dynamic landscape of immune cell-specific gene regulation in immune-mediated diseases.

Genetic studies have revealed many variant loci that are associated with immune-mediated diseases. To elucidate the disease pathogenesis, it is essential to understand the function of these variants, especially under disease-associated conditions. Here, we performed a large-scale immune cell gene-expression analysis, together with whole-genome sequence analysis. Our dataset consists of 28 distinct immune cell subsets from 337 patients diagnosed with 10 categories of immune-mediated diseases and 79 healthy volunteers. Our dataset captured distinctive gene-expression profiles across immune cell types and diseases. Expression quantitative trait loci (eQTL) analysis revealed dynamic variations of eQTL effects in the context of immunological conditions, as well as cell types. These cell-type-specific and context-dependent eQTLs showed significant enrichment in immune disease-associated genetic variants, and they implicated the disease-relevant cell types, genes, and environment. This atlas deepens our understanding of the immunogenetic functions of disease-associated variants under in vivo disease conditions.

LGR5-positive colon cancer stem cells interconvert with drug-resistant LGR5-negative cells and are capable of tumor reconstitution.

The cancer stem cell (CSC) concept has been proposed as an attractive theory to explain cancer development, and CSCs themselves have been considered as targets for the development of diagnostics and therapeutics. However, many unanswered questions concerning the existence of slow cycling/quiescent, drug-resistant CSCs remain. Here we report the establishment of colon cancer CSC lines, interconversion of the CSCs between a proliferating and a drug-resistant state, and reconstitution of tumor hierarchy from the CSCs. Stable cell lines having CSC properties were established from human colon cancer after serial passages in NOD/Shi-scid, IL-2Rγ(null) (NOG) mice and subsequent adherent cell culture of these tumors. By generating specific antibodies against LGR5, we demonstrated that these cells expressed LGR5 and underwent self-renewal using symmetrical divisions. Upon exposure to irinotecan, the LGR5(+) cells transitioned into an LGR5(-) drug-resistant state. The LGR5(-) cells converted to an LGR5(+) state in the absence of the drug. DNA microarray analysis and immunohistochemistry demonstrated that HLA-DMA was specifically expressed in drug-resistant LGR5(-) cells, and epiregulin was expressed in both LGR5(+) and drug-resistant LGR5(-) cells. Both cells sustained tumor initiating activity in NOG mice, giving rise to a tumor tissue hierarchy. In addition, anti-epiregulin antibody was found to be efficacious in a metastatic model. Both LGR5(+) and LGR5(-) cells were detected in the tumor tissues of colon cancer patients. The results provide new biological insights into drug resistance of CSCs and new therapeutic options for cancer treatment.

Phosphoproteomic analysis of distinct tumor cell lines in response to nocodazole treatment.

Here, we report for the first time a comparative phosphoproteomic analysis of distinct tumor cell lines in the presence or absence of the microtubule-interfering agent nocodazole. In total, 1525 phosphorylation sites assigned to 726 phosphoproteins were identified using LC-MS-based technology following phosphopeptide enrichment. Analysis of the amino acid composition surrounding the identified in vivo phosphorylation sites revealed that they could be classified into two motif groups: pSer-Pro and pSer-Asp/Glu. Phosphoproteomic change resulting from nocodazole treatment varied among cell lines in terms of the numbers of total phosphopeptides identified, motif groups, and functional annotation groups; however, the cell lines were equally sensitive to nocodazole. The identified phosphoproteome subset contained major signaling proteins and proteins known to be involved in mitosis, but did not always exhibit the same changes in the tumor cells from nocodazole treatment. In spite of the complex changes observed in the phosphorylation of many of the proteins, possible common features induced by nocodazole were found, including phosphorylation of nucleophosmin (NPM) S254 and coatomer protein complex, subunit alpha (COPA) S173, suggesting that the events are not cell-type specific but events generally occurring in mitosis or induced by a microtubule-interfering agent. Further, temporal analysis of phosphoproteome change revealed that phosphorylation of NPM S254 and COPA S173 was observed from the early (6 h) and late (24 h) time point after nocodazole treatment, respectively, suggesting that NPM S254 may be involved in the induction of M-phase arrest by nocodazole, whereas COPA S173 may be caused as a result of M-phase arrest.

Association study between Apolipoprotein L and schizophrenia by exhaustive and rule-based combination analysis for identification of multilocus interactions.

Several single marker association and haplotypic analyses have been performed to identify susceptible genes for various common diseases, but these approaches using candidate genes did not provide accurate and consistent evidence in each analysis. This inconsistency is partly due to the fact that the common diseases are caused by complex interactions among various genetic factors. Therefore, in this study, to evaluate exhaustive genotype or allele combinations, we applied the binomial and random permutation test (BRP) proposed by Tomita et al. [IPSJ Digital Courier, 2, 691-709 (2006)] for the association analysis between an Apolipoprotein L gene cluster and schizophrenia. Using the seven selected representative single nucleotide polymorphisms (SNPs) based on the results of linkage disequilibrium evaluation, we analyzed 845 schizophrenic patients and 707 healthy controls, and investigated the validation of risk and protective factors with two randomly divided data sets. A comparative study of a method for analyzing the interactions was performed by conventional methods. Even if all the tested methods were used for analysis, the risk factor with a high significance was not commonly selected from both independent data sets. However, the significant interactions for the protective factor against disease development were commonly obtained from both data sets by BRP analysis. In conclusion, although it is considered that the causality of schizophrenia is too complex to identify a susceptible interaction using a small sample size, it was suggested that the healthy controls tend to have the same combination of certain alleles or genotypes for protection from disease development when BRP as a new exhaustive combination analytical method was used.

An anti-glypican 3/CD3 bispecific T cell-redirecting antibody for treatment of solid tumors.

Cancer care is being revolutionized by immunotherapies such as immune checkpoint inhibitors, engineered T cell transfer, and cell vaccines. The bispecific T cell-redirecting antibody (TRAB) is one such promising immunotherapy, which can redirect T cells to tumor cells by engaging CD3 on a T cell and an antigen on a tumor cell. Because T cells can be redirected to tumor cells regardless of the specificity of T cell receptors, TRAB is considered efficacious for less immunogenic tumors lacking enough neoantigens. Its clinical efficacy has been exemplified by blinatumomab, a bispecific T cell engager targeting CD19 and CD3, which has shown marked clinical responses against hematological malignancies. However, the success of TRAB in solid tumors has been hampered by the lack of a target molecule with sufficient tumor selectivity to avoid "on-target off-tumor" toxicity. Glypican 3 (GPC3) is a highly tumor-specific antigen that is expressed during fetal development but is strictly suppressed in normal adult tissues. We developed ERY974, a whole humanized immunoglobulin G-structured TRAB harboring a common light chain, which bispecifically binds to GPC3 and CD3. Using a mouse model with reconstituted human immune cells, we revealed that ERY974 is highly effective in killing various types of tumors that have GPC3 expression comparable to that in clinical tumors. ERY974 also induced a robust antitumor efficacy even against tumors with nonimmunogenic features, which are difficult to treat by inhibiting immune checkpoints such as PD-1 (programmed cell death protein-1) and CTLA-4 (cytotoxic T lymphocyte-associated protein-4). Immune monitoring revealed that ERY974 converted the poorly inflamed tumor microenvironment to a highly inflamed microenvironment. Toxicology studies in cynomolgus monkeys showed transient cytokine elevation, but this was manageable and reversible. No organ toxicity was evident. These data provide a rationale for clinical testing of ERY974 for the treatment of patients with GPC3-positive solid tumors.

Minimal sizes of cases with a susceptible genotype and minimal odds ratios among susceptible individuals in case-control studies.

OBJECTIVE: Disease risk elevation due to an environmental factor only for individuals with a susceptible genotype is a typical example of gene-environment interaction. In order to identify risk factors interacting with susceptible genotypes in case-control studies, presumptions on minimal size of cases with the susceptible genotype (S (min)) and odds ratio (OR) among the susceptible individuals (OR(susceptible)) are useful. MODEL: Proportion of exposed cases (P(1)) and OR for whole cases (OR(whole)) statistically detectable in a case-control study can be calculated in a conventional method. P(1) was assumed to be a weighted sum of the exposed among cases with the genotype (P(x)) and cases without the genotype (equal to proportion of the exposed among controls, P(0)), i.e., S P(x) + (1 - S) P0, where S is the size (proportion) of cases with the genotype. For each calculated P(1), S became the minimum (S(min)) in case of P(x) = 1. OR(susceptible) was calculated by {P(x) (1 - P(0))} / {(1 - P(x)) P(0)}. RESULTS: S(min) and OR(susceptible) were listed for the combinations of the above components. For example, a detectable P(1) was 0.638 for P(0)=0.5 in a case-control study with 200 cases (N(1)) and 200 controls (N(0)), when a error of a two-sided test was 0.05 with an 80% of power. In case of P(1)=0.638, OR(whole) was 1.77, producing S(min) = 0.277 for infinite OR(susceptible). It indicates that an environmental factor cannot be detected in case that a high-risk genotype frequency is less than 0.277. INTERPRETATION: If the size of cases with a susceptible genotype is expected to be less than S(min), case-control studies are unlikely to detect a significant OR of the environmental factor.

Integration of proteomic analyses to monitor the activity status of phosphorylation signaling.

We performed here MS-based phosphoproteomics using both metal oxide affinity chromatography (pSTY proteomics) and anti-phosphotyrosine antibody (pY proteomics). The former method identified mainly phospho-serine and -threonine of nuclear or cytoplasmic proteins, whereas the latter did phosphotyrosine including more plasma membrane proteins and kinases. The overlap between these two methods was limited (24 tyrosine phosphorylation sites out of 325) and, by combining the two, coverage of the signaling molecules was enhanced as exemplified by Erk signaling. We also performed whole cell proteomics using an off-gel fractionator, and found 68.9% of the proteins identified by phosphoproteomics. Thus, the expression levels of phosphoproteins were roughly estimated. In addition to many uncharacterized phosphorylation sites, the dataset includes 136 sites that were experimentally verified elsewhere to be phosphorylated by a total of 83 kinases and kinase groups out of the 256 registered in the Phospho.ELM database. With the integration of various proteomic analyses and information from database, the responsible kinases of the identified phosphorylation sites and possibly their activity status were predicted by phosphorylation status and expression levels of their substrates, and thus our method may be able to monitor the activity status of phosphorylation signaling.

Cancer DNA microarray analysis considering multi-subclass with graph-based clustering method.

It is well known that various genes related to cell cycle, cell-cell adhesion, and transcriptional regulation cause the onset of cancer. Moreover, environmental factors including age, sex, and lifestyle can also contribute to the onset of cancer. Therefore, it is difficult to ascertain which factors influence the onset. Thus, patients suffering from same disease can be divided into several distinct groups. In the present study, we applied graph-based clustering to several DNA microarray datasets before the classification analysis. Several clusters formed by the graph-based clustering were used for the construction of multi-class classification model with the k-nearest neighbor and for finding genes, which are specific to a certain cluster, by One vs. Others classification. Using this approach, the classification model was constructed for four microarray datasets, leukemia, breast cancer, prostate cancer, and colon cancer, and the accuracies of classification with k-nearest neighbor were all more than 80%. And in the breast cancer dataset, we succeeded in finding genes that are specific in a cluster consisting of 38 control group samples. These results indicate the importance of sample clustering before classification model construction.