Discovery of a novel potentially transforming somatic mutation in CSF2RB gene in breast cancer

Exploration of the shared diagnostic genes and mechanisms between periodontitis and primary Sjögren's syndrome by integrated comprehensive bioinformatics analysis and machine learning

BACKGROUND

Accumulating evidence has showed a bidirectional link between periodontitis (PD) and primary Sjögren's syndrome (pSS), but the mechanisms of their occurrence remain unclear. Hence, this study aimed to investigate the shared diagnostic genes and potential mechanisms between PD and pSS using bioinformatics methods.

METHODS

Gene expression data for PD and pSS were acquired from the Gene Expression Omnibus (GEO) database. Differential expression genes (DEGs) analysis and weighted gene co-expression network analysis (WGCNA) were utilized to search common genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were conducted to explore biological functions. Three machine learning algorithms (least absolute shrinkage and selection operator (LASSO), support vector machine recursive feature elimination (SVM-RFE), and random forest (RF)) were used to further identify shared diagnostic genes, and these genes were assessed via receiver operating characteristic (ROC) curves in discovery and validation datasets. CIBERSORT was employed for immune cell infiltration analysis. Transcription factors (TFs)-genes and miRNAs-genes regulatory networks were conducted by NetworkAnalyst. Finally, relevant drug targets were predicted by DSigDB.

RESULTS

Based on DEGs, 173 overlapping genes were obtained and primarily enriched in immune- and inflammation-related pathways. WGCNA revealed 34 common disease-related genes, which were enriched in similar biological pathways. Intersecting the DEGs with WGCNA results yielded 22 candidate genes. Moreover, three machine learning algorithms identified three shared genes (CSF2RB, CXCR4, and LYN) between PD and pSS, and these genes demonstrated good diagnostic performance (AUC>0.85) in both discovery and validation datasets. The immune cell infiltration analysis showed significant dysregulation in several immune cell populations. Regulatory network analysis highlighted that WRNIP1 and has-mir-155-5p might be pivotal co-regulators of the three shared gene expressions. Finally, the top 10 potential gene-targeted drugs were screened.

CONCLUSION

CSF2RB, CXCR4, and LYN may serve as potential biomarkers for the concurrent diagnosis of PD and pSS. Additionally, we identified common molecular mechanisms, TFs, miRNAs, and candidate drugs between PD and pSS, which may provide novel insights and targets for future research on the pathogenesis, diagnosis, and therapy of both diseases.

Transactivation DNA-binding protein-related genes were associated with salivary gland injury in primary Sjögren syndrome

The purpose was to identify transactivation DNA-binding protein-related genes in salivary gland injury in primary Sjögren syndrome (pSS) in southwest China. We downloaded the datasets of GSE7451, GSE23117, and GSE40611. In order to screen the candidate genes, 2 kinds of machine learning algorithms were used. We collected blood from 28 patients and 20 controls to verify the expression of candidate genes using quantitative real-time polymerase chain reaction. The receiver operating characteristic curve was used to evaluate the diagnostic efficiency. Correlations between candidate genes and immune cells were examined. A total of 31 differentially expressed genes were obtained. Through different algorithms, 6 genes including IFIT1, CSF2RB, TRIM22, PPM1H, VAMP7, and C21orf2 were getted. Validation results suggested that the expression of CSF2RB, VAMP7, IFIT1, C21orf2, and TRIM22 was significantly increased in pSS. The area under the curve of CSF2RB was 0.937 and that of TRIM22 was 0.915. Immune infiltration analysis showed that the percentage of activated mast cells was lower than the controls (P = .025). Correlation analysis suggested that CSF2RB was associated with immune cell infiltration. The expression of CSF2RB was significantly upregulated, which could be related to the increase of γδ T cells. We revealed that CSF2RB could be the candidate gene of pSS. CSF2RB was involved by regulating various immune cells. The expression of CSF2RB was significantly upregulated, which was related to the increase of γδ T cells.

Population-enriched innate immune variants may identify candidate gene targets at the intersection of cancer and cardio-metabolic disease

Both cancer and cardio-metabolic disease disparities exist among specific populations in the US. For example, African Americans experience the highest rates of breast and prostate cancer mortality and the highest incidence of obesity. Native and Hispanic Americans experience the highest rates of liver cancer mortality. At the same time, Pacific Islanders have the highest death rate attributed to type 2 diabetes (T2D), and Asian Americans experience the highest incidence of non-alcoholic fatty liver disease (NAFLD) and cancers induced by infectious agents. Notably, the pathologic progression of both cancer and cardio-metabolic diseases involves innate immunity and mechanisms of inflammation. Innate immunity in individuals is established through genetic inheritance and external stimuli to respond to environmental threats and stresses such as pathogen exposure. Further, individual genomes contain characteristic genetic markers associated with one or more geographic ancestries (ethnic groups), including protective innate immune genetic programming optimized for survival in their corresponding ancestral environment(s). This perspective explores evidence related to our working hypothesis that genetic variations in innate immune genes, particularly those that are commonly found but unevenly distributed between populations, are associated with disparities between populations in both cancer and cardio-metabolic diseases. Identifying conventional and unconventional innate immune genes that fit this profile may provide critical insights into the underlying mechanisms that connect these two families of complex diseases and offer novel targets for precision-based treatment of cancer and/or cardio-metabolic disease.

Uncovering hidden cancer self-dependencies through analysis of shRNA-level dependency scores

Large-scale short hairpin RNA (shRNA) screens on well-characterized human cancer cell lines have been widely used to identify novel cancer dependencies. However, the off-target effects of shRNA reagents pose a significant challenge in the analysis of these screens. To mitigate these off-target effects, various approaches have been proposed that aggregate different shRNA viability scores targeting a gene into a single gene-level viability score. Most computational methods for discovering cancer dependencies rely on these gene-level scores. In this paper, we propose a computational method, named NBDep, to find cancer self-dependencies by directly analyzing shRNA-level dependency scores instead of gene-level scores. The NBDep algorithm begins by removing known batch effects of the shRNAs and selecting a subset of concordant shRNAs for each gene. It then uses negative binomial random effects models to statistically assess the dependency between genetic alterations and the viabilities of cell lines by incorporating all shRNA dependency scores of each gene into the model. We applied NBDep to the shRNA dependency scores available at Project DRIVE, which covers 26 different types of cancer. The proposed method identified more well-known and putative cancer genes compared to alternative gene-level approaches in pan-cancer and cancer-specific analyses. Additionally, we demonstrated that NBDep controls type-I error and outperforms statistical tests based on gene-level scores in simulation studies.

New Born Calf Serum Can Induce Spheroid Formation in Breast Cancer KAIMRC1 Cell Line

Three-dimensional (3D) cell culture systems have become very popular in the field of drug screening and discovery. There is an immense demand for highly efficient and easy methods to produce 3D spheroids in any cell format. We have developed a novel and easy method to produce spheroids from the newly isolated KAIMRC1 cell line in vitro. It can be used as a 3D model to study proliferation, differentiation, cell death, and drug response of cancer cells. Our procedure requires growth media supplemented with 10% new born calf serum (NBCS) and regular cell culture plates to generate KAIMRC1 spheroids without the need for any specialized 3D cell culture system. This procedure generates multiple spheroids within a 12–24-h culture. KAIMRC1 spheroids are compact, homogeneous in size and morphology with a mean size of 55.8 µm (±3.5). High content imaging (HCI) of KAIMRC1 spheroids treated with a panel of 240 compounds resulted in the identification of several highly specific compounds towards spheroids. Immunophenotyping of KAIMRC1 spheroids revealed phosphorylation of FAK, cJUN, and E-cadherin, which suggests the involvement of JNK/JUN pathway in the KAIMRC1 spheroids formation. Gene expression analysis showed upregulation of cell junction genes, GJB3, DSC1, CLDN5, CLDN8, and PLAU. Furthermore, co-culture of KAIMRC1 cells with primary cancer-associated-fibroblasts (CAFs) showcased the potential of these cells in drug discovery application.

Discovery of a novel potentially transforming somatic mutation in CSF2RB gene in breast cancer

The colony stimulating factor 2 receptor subunit beta (CSF2RB) is the common signaling subunit of the cytokine receptors for IL-3, IL-5, and GM-CSF. Several studies have shown that spontaneous and random mutants of CSF2RB can lead to ligand independence in vitro. To date, no report(s) have been shown for the presence of potentially transforming and oncogenic CSF2RB mutation(s) clinically in cancer patients until the first reported case of a leukemia patient in 2016 harboring a germline-activating mutation (R461C). We combined exome sequencing, pathway analyses, and functional assays to identify novel somatic mutations in KAIMRC1 cells and breast tumor specimen. The patient's peripheral blood mononuclear cell (PBMC) exome served as a germline control in the identification of somatic mutations. Here, we report the discovery of a novel potentially transforming and oncogenic somatic mutation (S230I) in the CSF2RB gene of a breast cancer patient and the cell line, KAIMRC1 established from her breast tumor tissue. KAIMRC1 cells are immortalized and shown to survive and proliferate in ligand starvation condition. Immunoblot analysis showed that mutant CSF2RB signals through JAK2/STAT and PI3K/mTOR pathways in ligand starvation conditions. Screening a small molecule kinase inhibitor library revealed potent JAK2 inhibitors against KAIMRC1 cells. We, for the first time, identified a somatic, potentially transforming, and oncogenic CSF2RB mutation (S230I) in breast cancer patients that seem to be an actionable mutation leading to the development of new therapeutics for breast cancer.