Transcriptomic profiling of tumor-infiltrating CD4 + TIM-3 + T Cells reveals their suppressive, exhausted, and metastatic characteristics in colorectal cancer patients

T cell immunoglobulin mucin-3 (TIM-3) is an immune checkpoint identified as one of the key players in regulating T-cell responses. Studies have shown that TIM-3 is upregulated in the tumor microenvironment (TME). However, the precise role of TIM-3 in colorectal cancer (CRC) TME is yet to be elucidated. We performed phenotypic and molecular characterization of TIM-3+ T cells in the TME and circulation of CRC patients by analyzing tumor tissues (TT, TILs), normal tissues (NT, NILs), and peripheral blood mononuclear cells (PBMC). TIM-3 was upregulated on both CD4+ and CD3+CD4− (CD8+) TILs. CD4+TIM-3+ TILs expressed higher levels of T regulatory cell (Tregs)-signature genes, including FoxP3 and Helios, compared with their TIM-3− counterparts. Transcriptomic and ingenuity pathway analyses showed that TIM-3 potentially activates inflammatory and tumor metastatic pathways. Moreover, NF-κB-mediated transcription factors were upregulated in CD4+TIM-3+ TILs, which could favor proliferation/invasion and induce inflammatory and T-cell exhaustion pathways. In addition, we found that CD4+TIM-3+ TILs potentially support tumor invasion and metastasis, compared with conventional CD4+CD25+ Tregs in the CRC TME. However, functional studies are warranted to support these findings. In conclusion, this study discloses some of the functional pathways of TIM-3+ TILs, which could improve their targeting in more specific therapeutic approaches in CRC patients

Transcriptomic profiling disclosed the role of DNA methylation and histone modifications in tumor-infiltrating myeloid-derived suppressor cell subsets in colorectal cancer

Increased numbers of myeloid-derived suppressor cells (MDSCs) are positively correlated with poor prognosis and reduced survivals of cancer patients. They play central roles in tumor immune evasion and tumor metastasis. However, limited data are available on phenotypic/transcriptomic characteristics of the different MDSCs subsets in cancer. These cells include immature (I-MDSCs), monocytic (M-MDSCs), and polymorphonuclear/granulocytic (PMN-MDSCs). Phenotypic characterization of myeloid subsets from 27 colorectal cancer (CRC) patients was assessed by flow cytometric analyses. RNA-sequencing of sorted I-MDSCs, PMN-MDSCs, and antigen-presenting cells (APCs) was also performed. We found that the levels of I-MDSCs and PMN-MDSCs were increased in tumor tissues (TT), compared with normal tissues (NT) in colorectal cancer. Our functional annotation analyses showed that genes associated with histone deacetylase (HDAC) activation- and DNA methylation-mediated transcriptional silencing were upregulated, and histone acetyl transferase (HAT)-related genes were downregulated in tumor-infiltrating I-MDSCs. Moreover, pathways implicated in cell trafficking and immune suppression, including Wnt, interleukin-6 (IL-6), and mitogen-activated protein kinase (MAPK) signaling, were upregulated in I-MDSCs. Notably, PMN-MDSCs showed downregulation in genes related to DNA methylation and HDAC binding. Using an ex vivo model, we found that inhibition of HDAC activation or neutralization of IL-6 in CRC tumor tissues downregulates the expression of genes associated with immunosuppression and myeloid cell chemotaxis, confirming the importance of HDAC activation and IL-6 signaling pathway in MDSC function and chemotaxis. This study provides novel insights into the epigenetic regulations and other molecular pathways in different myeloid cell subsets within the CRC tumor microenvironment (TME), giving opportunities to potential targets for therapeutic benefits

Bayesian analysis of bulk viscous matter dominated universe

In our previous works, we have analyzed the evolution of bulk viscous matter dominated universe with a more general form for bulk viscous coefficient, $\zeta=\zeta_{0}+\zeta_{1}\frac{\dot{a}}{a}+\zeta_{2}\frac{\ddot{a}}{\dot{a}}$ and also carried out the dynamical system analysis. We found that the model reasonably describes the evolution of the universe if the viscous coefficient is a constant. In the present work we are contrasting this model with the standard $\Lambda$CDM model of the universe using the Bayesian method. We have shown that, even though the viscous model gives a reasonable back ground evolution of the universe, the Bayes factor of the model indicates that, it is not so superior over the $\Lambda$CDM model, but have a slight advantage over it.Comment: 15 pages, 9 figure

Differential gene expression of tumor-infiltrating CD33 + myeloid cells in advanced- versus early-stage colorectal cancer

Abstract: Colorectal cancer (CRC) has high mortality rates, especially in patients with advanced disease stages, who often do not respond to therapy. The cellular components of the tumor microenvironment are essentially responsible for dictating disease progression and response to therapy. Expansion of different myeloid cell subsets in CRC tumors has been reported previously. However, tumor-infiltrating myeloid cells have both pro- and anti-tumor roles in disease progression. In this study, we performed transcriptomic profiling of cells of myeloid lineage (CD33+) from bulk CRC tumors at varying disease stages. We identified differentially expressed genes and pathways between CRC patients with advanced stage and early stages. We found that pro-angiogenic and hypoxia-related genes were upregulated, while genes related to immune and inflammatory responses were downregulated in CD33+ myeloid cells from patients with advanced stages, implying that immune cell recruitment and activation could be compromised in advanced disease stages. Moreover, we identified a unique “poor prognosis CD33+ gene signature” by aligning top upregulated and downregulated genes in tumor-infiltrating myeloid cells from our analyses with data from The Cancer Genome Atlas. Our results showed that this gene signature is an independent prognostic indicator for disease-specific survival in CRC patients, potentially reflecting its clinical importance

Transcriptome of tumor-Infiltrating T cells in colorectal cancer patients uncovered a unique gene signature in CD4 + T cells associated with poor disease-specific survival

Colorectal cancer (CRC) is influenced by infiltration of immune cell populations in the tumor microenvironment. While elevated levels of cytotoxic T cells are associated with improved prognosis, limited studies have reported associations between CD4+ T cells and disease outcomes. We recently performed transcriptomic profiling and comparative analyses of sorted CD4+ and CD8+ tumor-infiltrating lymphocytes (TILs) from bulk tumors of CRC patients with varying disease stages. In this study, we compared the transcriptomes of CD4+ with CD8+ TILs. Functional annotation pathway analyses revealed the downregulation of inflammatory response-related genes, while T cell activation and angiogenesis-related genes were upregulated in CD4+ TILs. The top 200 deregulated genes in CD4+ TILs were aligned with the cancer genome atlas (TCGA) CRC dataset to identify a unique gene signature associated with poor prognosis. Moreover, 69 upregulated and 20 downregulated genes showed similar trends of up/downregulation in the TCGA dataset and were used to calculate “poor prognosis score” (ppScore), which was significantly associated with disease-specific survival. High ppScore patients showed lower expression of Treg-, Th1-, and Th17-related genes, and higher expression of Th2-related genes. Our data highlight the significance of T cells within the TME and identify a unique candidate prognostic gene signature for CD4+ TILs in CRC patients

Global Identification and Characterization of Transcriptionally Active Regions in the Rice Genome

Genome tiling microarray studies have consistently documented rich transcriptional activity beyond the annotated genes. However, systematic characterization and transcriptional profiling of the putative novel transcripts on the genome scale are still lacking. We report here the identification of 25,352 and 27,744 transcriptionally active regions (TARs) not encoded by annotated exons in the rice (Oryza. sativa) subspecies japonica and indica, respectively. The non-exonic TARs account for approximately two thirds of the total TARs detected by tiling arrays and represent transcripts likely conserved between japonica and indica. Transcription of 21,018 (83%) japonica non-exonic TARs was verified through expression profiling in 10 tissue types using a re-array in which annotated genes and TARs were each represented by five independent probes. Subsequent analyses indicate that about 80% of the japonica TARs that were not assigned to annotated exons can be assigned to various putatively functional or structural elements of the rice genome, including splice variants, uncharacterized portions of incompletely annotated genes, antisense transcripts, duplicated gene fragments, and potential non-coding RNAs. These results provide a systematic characterization of non-exonic transcripts in rice and thus expand the current view of the complexity and dynamics of the rice transcriptome

Mapping genetic variations to three- dimensional protein structures to enhance variant interpretation: a proposed framework

The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability or formation of interactions; these may explain the effect of mutations and in some cases even open a path for targeted drug development. To accelerate progress in the integration of these data types, we held a two-day Gene Variation to 3D (GVto3D) workshop to report on the latest advances and to discuss unmet needs. The overarching goal of the workshop was to address the question: what can be done together as a community to advance the integration of genetic variants and 3D protein structures that could not be done by a single investigator or laboratory? Here we describe the workshop outcomes, review the state of the field, and propose the development of a framework with which to promote progress in this arena. The framework will include a set of standard formats, common ontologies, a common application programming interface to enable interoperation of the resources, and a Tool Registry to make it easy to find and apply the tools to specific analysis problems. Interoperability will enable integration of diverse data sources and tools and collaborative development of variant effect prediction methods