In silico screening using bulk and single-cell RNA-seq data identifies RIMS2 as a prognostic marker in basal-like breast cancer: A retrospective study

Transcriptomic Analysis Reveals Differentially Expressed Circular RNAs Associated with Fecundity in the Sheep Hypothalamus with Different FecB Genotypes

Circular RNAs (circRNAs) are a specific type of noncoding RNA, and some have defined roles in cellular and biological processes. However, little is known about the role of circRNAs in follicular development in sheep with FecB (fecundity Booroola) mutations. Here, the expression profiles of circRNAs were investigated using RNA sequencing (RNA-seq) in the follicular phase (F) and the luteal phase (L) of FecB mutant homozygous (BB) and wild-type (WW) Small Tail Han sheep. A total of 38,979 circRNAs were identified, and 314, 343, 336, and 296 of them were differentially expressed (DE) between BB_F and BB_L, WW_F and WW_L, BB_F and WW_F, and BB_L and WW_L, respectively. The length, type, and chromosome distribution of the circRNAs and the expression characteristic between the circRNAs and their host genes in the sheep hypothalamus were ascertained. Enrichment analysis showed that the host genes of DE circRNAs in the follicular and luteal phases were annotated to MAPK, gap junctions, progesterone-mediated oocyte maturation, oocyte meiosis, and other hormone-related signaling pathways, and the different FecB genotypes were annotated to the gap junctions, circadian entrainment, MAPK, and other hormone-related signaling pathways. The competing endogenous RNA network prediction revealed that the 129 target miRNAs might be bound to 336 DE circRNAs. oar_circ_0000523 and oar_circ_0028984, which were specifically expressed during the follicular phase in the BB genotype sheep, probably acted as miRNA sponges involved in the regulation of LH synthesis and secretion. This study reveals the expression profiles and characterization of circRNAs at two phases of follicular development considering different FecB genotypes, thereby providing an improved understanding of the roles of circRNAs in the sheep hypothalamus and their involvement in follicular development and ovulation.

A machine learning one-class logistic regression model to predict stemness for single cell transcriptomics and spatial omics

Cell annotation is a crucial methodological component to interpreting single cell and spatial omics data. These approaches were developed for single cell analysis but are often biased, manually curated and yet unproven in spatial omics. Here we apply a stemness model for assessing oncogenic states to single cell and spatial omic cancer datasets. This one-class logistic regression machine learning algorithm is used to extract transcriptomic features from non-transformed stem cells to identify dedifferentiated cell states in tumors. We found this method identifies single cell states in metastatic tumor cell populations without the requirement of cell annotation. This machine learning model identified stem-like cell populations not identified in single cell or spatial transcriptomic analysis using existing methods. For the first time, we demonstrate the application of a ML tool across five emerging spatial transcriptomic and proteomic technologies to identify oncogenic stem-like cell types in the tumor microenvironment.

Insights into Gene Regulation under Temozolomide-Promoted Cellular Dormancy and Its Connection to Stemness in Human Glioblastoma

The aggressive features of glioblastoma (GBM) are associated with dormancy. Our previous transcriptome analysis revealed that several genes were regulated during temozolomide (TMZ)-promoted dormancy in GBM. Focusing on genes involved in cancer progression, Chemokine (C-C motif) Receptor-Like (CCRL)1, Schlafen (SLFN)13, Sloan-Kettering Institute (SKI), Cdk5 and Abl Enzyme Substrate (Cables)1, and Dachsous Cadherin-Related (DCHS)1 were selected for further validation. All showed clear expression and individual regulatory patterns under TMZ-promoted dormancy in human GBM cell lines, patient-derived primary cultures, glioma stem-like cells (GSCs), and human GBM ex vivo samples. All genes exhibited complex co-staining patterns with different stemness markers and with each other, as examined by immunofluorescence staining and underscored by correlation analyses. Neurosphere formation assays revealed higher numbers of spheres during TMZ treatment, and gene set enrichment analysis of transcriptome data revealed significant regulation of several GO terms, including stemness-associated ones, indicating an association between stemness and dormancy with the involvement of SKI. Consistently, inhibition of SKI during TMZ treatment resulted in higher cytotoxicity, proliferation inhibition, and lower neurosphere formation capacity compared to TMZ alone. Overall, our study suggests the involvement of CCRL1, SLFN13, SKI, Cables1, and DCHS1 in TMZ-promoted dormancy and demonstrates their link to stemness, with SKI being particularly important.

Advances in lung adenocarcinoma: A novel perspective on prognoses and immune responses of CENPO as an oncogenic superenhancer

Lung adenocarcinoma (LUAD) is the most prevalent form of lung cancer globally, and its treatment remains a significant challenge. Therefore, it is crucial to comprehend the microenvironment to improve therapy and prognosis urgently. In this study, we utilized bioinformatic methods to analyze the transcription expression profile of patient samples with complete clinical information from the TCGA-LUAD datasets. To validate our findings, we also analyzed the Gene Expression Omnibus (GEO) datasets. The super-enhancer (SE) was visualized using the peaks of the H3K27ac and H3K4me1 ChIP-seq signal, which were identified by the Integrative Genomics Viewer (IGV). To further investigate the role of Centromere protein O (CENPO) in LUAD, we conducted various assays including Western blot, qRT-PCR, flow cytometry, wound healing and transwell assays to assess the cell functions of CENPO in vitro. The overexpression of CENPO is linked to a poor prognosis in patients with LUAD. Strong signal peaks of H3K27ac and H3K4me1 were also observed near the predicted SE regions of CENPO. CENPO was found to be positively associated with the expression levels of immune checkpoints and drug IC50 value (Roscovitine and TGX221), but negatively associated with the fraction levels of several immature cells and drug IC50 value (CCT018159, GSK1904529A, Lenaildomide, and PD-173074). Additionally, CENPO-associated prognostic signature (CPS) was identified as an independent risk factor. The high-risk group for LUAD is identified based on CPS enrichment, which involved not only endocytosis that transfers mitochondria to promote cell survival in response to chemotherapy but also cell cycle promotion that leads to drug resistance. The removal of CENPO significantly suppressed metastasis and induced arrest and apoptosis of LUAD cells. The involvement of CENPO in the immunosuppression of LUAD provides a prognostic signature for LUAD patients.

Low HER2 expression in normal breast epithelium enables dedifferentiation and malignant transformation via chromatin opening

Overexpression of the HER2 protein in breast cancer patients is a predictor of poor prognosis and resistance to therapies. We used an inducible breast cancer transformation system that allows investigation of early molecular changes. HER2 overexpression to similar levels as those observed in a subtype of HER2-positive breast cancer patients induced transformation of MCF10A cells and resulted in gross morphological changes, increased anchorage-independent growth of cells, and altered the transcriptional programme of genes associated with oncogenic transformation. Global phosphoproteomic analysis during HER2 induction predominantly detected an increase in protein phosphorylation. Intriguingly, this correlated with chromatin opening, as measured by ATAC-seq on acini isolated from 3D cell culture. HER2 overexpression resulted in opening of many distal regulatory regions and promoted reprogramming-associated heterogeneity. We found that a subset of cells acquired a dedifferentiated breast stem-like phenotype, making them likely candidates for malignant transformation. Our data show that this population of cells, which counterintuitively enriches for relatively low HER2 protein abundance and increased chromatin accessibility, possesses transformational drive, resulting in increased anchorage-independent growth in vitro compared to cells not displaying a stem-like phenotype.

Prognosis and Characterization of Immune Microenvironment in Head and Neck Squamous Cell Carcinoma through a Pyroptosis-Related Signature

Pyroptosis, as a novel identified programmed cell death, is closely correlated with tumor immunity and shows potential roles in cancer treatment. Discerning a pyroptosis-related gene signature and its correlations with tumor immune microenvironment is critical in head and neck squamous cell carcinoma (HNSCC). Transcriptome data and corresponding clinical data were downloaded from TCGA and GEO databases. Tumor mutation burden (TMB) data were obtained from TCGA database. Firstly, univariate and least absolute shrinkage and selection operator (LASSO) regression analyses were used to construct a six pyroptosis-related gene signature. Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, and principal component analysis (PCA) results verified that the risk model has good performance in predicting the survival. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that the pyroptosis-related gene signature was immune related. Finally, the immune landscape and immunotherapy sensitivity prediction capabilities of the risk model were further explored. There were close correlations between the overall survival (OS) and various immune cells and immune functions. Single-sample gene set enrichment analysis (ssGSEA) showed that high risk group had decreased expression of various immune cells and lower activities of immune functions. Meanwhile, tumor mutation burden (TMB) data combining risk score could well predict the OS of HNSCC patients. However, tumor immune dysfunction and exclusion (TIDE) analysis revealed that there was no significant difference in the sensitivity to immunotherapies between high and low risk groups. Finally, a nomogram based on risk score and clinicopathological parameters was constructed. And, the risk model demonstrated better sensitivity and specificity than TIDE scores and T-cell-inflamed signature (TIS). In conclusion, although the risk model could not well predict the immune escape and response to immunotherapies, the signature established by pyroptosis-related genes, with better sensitivity and specificity than TIDE scores and TIS signature, could be used for predicting prognosis and immune status of HNSCC patients.