Improving information retrieval in functional analysis

Downregulation of Macrophage-Specific Act-1 Intensifies Periodontitis and Alveolar Bone Loss Possibly via TNF/NF-κB Signaling

Periodontitis is a chronic inflammatory oral disease that affects almost half of the adult population. NF-κB activator 1 (Act1) is mainly expressed in immune cells, including macrophages, and modulates immune cells' function to regulate inflammation in inflammatory diseases. Macrophages play a vital role in the pathophysiology of periodontitis. However, the effect of macrophage-specific Act1 on periodontitis has not been investigated yet. This study aims to unravel the role of macrophage-specific Act1 on the pathophysiology of periodontitis. The expression of Act1 in healthy and periodontitis periodontal tissue was confirmed by immunohistochemistry. Macrophage-specific Act1 expression downregulated (anti-Act1) mice were developed by inserting anti-Act1 antisense oligonucleotides after the CD68 promoter of C57BL/6 mice. Ligature-induced periodontitis (LIP) was induced in anti-Act1 mice and wildtype mice. Micro-CT, histology, and TRAP staining analyzed the periodontal tissue status, alveolar bone loss, and osteoclast numbers. Immunohistochemistry, RT-qPCR, and ELISA analyzed the inflammatory cells infiltration, expression of inflammatory cytokines, and M1/M2 macrophage polarization. mRNA sequencing of in vitro bacterial lipopolysaccharide (LPS)-treated peritoneal macrophages analyzed the differentially expressed genes in anti-Act1 mice during inflammation. Anti-Act1 mice showed aggravated periodontitis and alveolar bone loss compared to wildtype. Periodontitis-affected periodontal tissue (PAPT) of anti-Act1 mice showed a higher degree of macrophage infiltration, and M1 macrophage polarization compared to wildtype. Levels of pro-inflammatory cytokines (IL-1β, IL-6, and TNFα), and macrophage activity-related factors (CCL2, CCL3, and CCL4) were robustly high in PAPT of anti-Act1 mice compared to wildtype. mRNA sequencing and KEGG analysis showed activated TNF/NF-κB signaling in LPS-treated macrophages from anti-Act1 mice. In vitro studies on LPS-treated peritoneal macrophages from anti-act1 mice showed a higher degree of cell migration and expression of inflammatory cytokines, macrophage activity-related factors, M1 macrophage-related factors, and TNF/NF-κB signaling related P-p65 protein. In conclusion, downregulation of macrophage-specific Act1 aggravated periodontitis, alveolar bone loss, macrophage infiltration, inflammation, and M1 macrophage polarization. Furthermore, LPS-treated macrophages from anti-Act1 mice activated TNF/NF-κB signaling. These results indicate the distinct role of macrophage-specific Act1 on the pathophysiology of periodontitis possibly via TNF/NF-κB signaling.

Pan-Cancer Molecular Patterns and Biological Implications Associated with a Tumor-Specific Molecular Signature

Studying tissue-independent components of cancer and defining pan-cancer subtypes could be addressed using tissue-specific molecular signatures if classification errors are controlled. Since PAM50 is a well-known, United States Food and Drug Administration (FDA)-approved and commercially available breast cancer signature, we applied it with uncertainty assessment to classify tumor samples from over 33 cancer types, discarded unassigned samples, and studied the emerging tumor-agnostic molecular patterns. The percentage of unassigned samples ranged between 55.5% and 86.9% in non-breast tissues, and gene set analysis suggested that the remaining samples could be grouped into two classes (named C1 and C2) regardless of the tissue. The C2 class was more dedifferentiated, more proliferative, with higher centrosome amplification, and potentially more TP53 and RB1 mutations. We identified 28 gene sets and 95 genes mainly associated with cell-cycle progression, cell-cycle checkpoints, and DNA damage that were consistently exacerbated in the C2 class. In some cancer types, the C1/C2 classification was associated with survival and drug sensitivity, and modulated the prognostic meaning of the immune infiltrate. Our results suggest that PAM50 could be repurposed for a pan-cancer context when paired with uncertainty assessment, resulting in two classes with molecular, biological, and clinical implications.

SLIT2 Overexpression in Periodontitis Intensifies Inflammation and Alveolar Bone Loss, Possibly via the Activation of MAPK Pathway

SLIT2, a member of neuronal guidance cues, has been reported to regulate inflammation and cancer progression. Periodontitis is an oral inflammatory disease that degenerates periodontal tissue, alveolar bone and tooth. This study aims to explore the expression pattern of SLIT2 in periodontitis and its role in disease progression and bone loss. Gingival tissue of 20 periodontitis patients and 20 healthy-controls was obtained. Ligature-induced periodontitis (LIP) mice-model was developed in Slit2-Tg and wild-type mice. The effect of SLIT2 on inflammation, immune cell infiltration, M1 macrophage polarization, and alveolar bone loss in periodontitis was analyzed extensively. In periodontitis-affected gingival-tissue, SLIT2 expression was 4.4-fold higher compared to healthy-volunteers. LIP enhanced SLIT2 expression in mice periodontitis-affected periodontal tissue (PAPT) and blood circulation of wild-type mice by 4. 6-, and 5.0-fold, respectively. In Slit2-Tg-mice PAPT, SLIT2 expression was 1.8-fold higher compared to wild-type mice. Micro-CT and histomorphometric analysis revealed a 1.3-fold higher cement-enamel-junction to the alveolar-bone-crest (CEJ-ABC) distance and alveolar bone loss in LIP Slit2-Tg-mice compare to LIP wild-type mice. Results from RNA-sequencing, RT-qPCR, and ELISA showed a higher expression of Cxcr2, Il-18, TNFα, IL-6, and IL-1β in Slit2-Tg-mice PAPT compared to wild-type-mice. Slit2-Tg-mice PAPT showed a higher number of osteoclasts, M1 macrophages, and the upregulation of Robo1 expression. Slit2-Tg-mice PAPT showed upregulation of M1 macrophage marker CD16/32 and osteoclastogenic markers Acp5, Ctsk, and Nfatc1, but osteogenic markers (Alp, Bglap) remained unchanged. Immunohistochemistry unveiled the higher vasculature and infiltration of leucocytes and macrophages in Slit2-Tg-mice PAPT. RNA-sequencing, GO-pathway enrichment analysis, and western blot analysis revealed the activation of the MAPK signaling pathway in Slit2-Tg mice PAPT. In conclusion, SLIT2 overexpression in periodontitis intensifies inflammation, immune cells infiltration, M1 macrophage polarization, osteoclastogenesis, and alveolar bone loss, possibly via activation of MAPK signaling, suggesting the role of SLIT2 on exacerbation of periodontitis and alveolar bone loss.

Massive integrative gene set analysis enables functional characterization of breast cancer subtypes

The availability of large-scale repositories and integrated cancer genome efforts have created unprecedented opportunities to study and describe cancer biology. In this sense, the aim of translational researchers is the integration of multiple omics data to achieve a better identification of homogeneous subgroups of patients in order to develop adequate diagnostic and treatment strategies from the personalized medicine perspective. So far, existing integrative methods have grouped together omics data information, leaving out individual omics data phenotypic interpretation. Here, we present the Massive and Integrative Gene Set Analysis (MIGSA) R package. This tool can analyze several high throughput experiments in a comprehensive way through a functional analysis strategy, relating a phenotype to its biological function counterpart defined by means of gene sets. By simultaneously querying different multiple omics data from the same or different groups of patients, common and specific functional patterns for each studied phenotype can be obtained. The usefulness of MIGSA was demonstrated by applying the package to functionally characterize the intrinsic breast cancer PAM50 subtypes. For each subtype, specific functional transcriptomic profiles and gene sets enriched by transcriptomic and proteomic data were identified. To achieve this, transcriptomic and proteomic data from 28 datasets were analyzed using MIGSA. As a result, enriched gene sets and important genes were consistently found as related to a specific subtype across experiments or data types and thus can be used as molecular signature biomarkers.

A Census of Disease Ontologies

For centuries, humans have sought to classify diseases based on phenotypic presentation and available treatments. Today, a wide landscape of strategies, resources, and tools exist to classify patients and diseases. Ontologies can provide a robust foundation of logic for precise stratification and classification along diverse axes such as etiology, development, treatment, and genetics. Disease and phenotype ontologies are used in four primary ways: ( a) search, retrieval, and annotation of knowledge; ( b) data integration and analysis; ( c) clinical decision support; and ( d) knowledge discovery. Computational inference can connect existing knowledge and generate new insights and hypotheses about drug targets, prognosis prediction, or diagnosis. In this review, we examine the rise of disease and phenotype ontologies and the diverse ways they are represented and applied in biomedicine.