Single-cell-resolution transcriptome map revealed novel genes involved in testicular germ cell progression and somatic cells specification in Chinese tongue sole with sex reversal.

Female-to-male sex reversals (pseudomales) are common in lower vertebrates and have been found in natural populations, which is a concern under rapid changes in environmental conditions. Pseudomales can exhibit altered spermatogenesis. However, the regulatory mechanisms underlying pseudomale spermatogenesis remain unclear. Here, we characterized spermatogenesis in Chinese tongue sole (Cynoglossus semilaevis), a species with genetic and environmental sex determination, based on a high-resolution single-cell RNA-seq atlas of cells derived from the testes of genotypic males and pseudomales. We identified five germ cell types and six somatic cell types and obtained a single-cell atlas of dynamic changes in gene expression during spermatogenesis in Chinese tongue sole, including alterations in pseudomales. We detected decreased levels of Ca2+ signaling pathway-related genes in spermatogonia, insufficient meiotic initiation in spermatocytes, and a malfunction of somatic niche cells in pseudomales. However, a cluster of CaSR genes and MAPK signaling factors were upregulated in undifferentiated spermatogonia of pseudomales. Additionally, we revealed that Z chromosome-specific genes, such as piwil2, dhx37, and ehmt1, were important for spermatogenesis. These results improve our understanding of reproduction after female-to-male sex-reversal and provide new insights into the adaptability of reproductive strategies in lower vertebrates.

Single-Cell Atlas of the Chinese Tongue Sole (Cynoglossus semilaevis) Ovary Reveals Transcriptional Programs of Oogenesis in Fish.

Oogenesis is a highly orchestrated process that depends on regulation by autocrine/paracrine hormones and growth factors. However, many details of the molecular mechanisms that regulate fish oogenesis remain elusive. Here, we performed a single-cell RNA sequencing (scRNA-seq) analysis of the molecular signatures of distinct ovarian cell categories in adult Chinese tongue sole (Cynoglossus semilaevis). We characterized the successive stepwise development of three germ cell subtypes. Notably, we identified the cellular composition of fish follicle walls, including four granulosa cell types and one theca cell type, and we proposed important transcription factors (TFs) showing high activity in the regulation of cell identity. Moreover, we found that the extensive niche-germline bidirectional communications regulate fish oogenesis, whereas ovulation in fish is accompanied by the coordination of simultaneous and tightly sequential processes across different granulosa cells. Additionally, a systems biology analysis of the homologous genes shared by Chinese tongue sole and macaques revealed remarkably conserved biological processes in germ cells and granulosa cells across vertebrates. Our results provide key insights into the cell-type-specific mechanisms underlying fish oogenesis at a single-cell resolution, which offers important clues for exploring fish breeding mechanisms and the evolution of vertebrate reproductive systems.

Case Report: Transformation From Cold to Hot Tumor in a Case of NSCLC Neoadjuvant Immunochemotherapy Pseudoprogression.

A 56-year-old male was diagnosed with right lung upper lobe squamous cancer with right hilar and mediastinum lymph node metastasis. After four cycles of neoadjuvant immunochemotherapy, reexamination by computed tomography showed progressive disease of the primary lesion. Then, the patient underwent a right lung upper lobectomy, and hilar and mediastinum lymph node dissection. Surgical pathology showed a partial response to immunochemotherapy. Single-cell RNA sequencing was used to characterize the infiltrating immune cell atlas after neoadjuvant immunochemotherapy; the most common infiltrating immune cell types were cytotoxic CD8+ T cells, monocyte-derived dendritic cells, and macrophages. Imaging mass cytometry revealed a transformation from cold to hot tumor after neoadjuvant immunochemotherapy. In this case study, we are the first to report a case of neoadjuvant immunochemotherapy pseudoprogression, proved by surgical pathology, single-cell RNA sequencing, and imaging mass cytometry. Both single-cell RNA sequencing and imaging mass cytometry revealed an activated immune microenvironment after neoadjuvant immunochemotherapy.

Large-Scale Analysis of Drug Side Effects via Complex Regulatory Modules Composed of microRNAs, Transcription Factors and Gene Sets.

Identifying the occurrence mechanism of drug-induced side effects (SEs) is critical for design of drug target and new drug development. The expression of genes in biological processes is regulated by transcription factors(TFs) and/or microRNAs. Most of previous studies were focused on a single level of gene or gene sets, while studies about regulatory relationships of TFs, miRNAs and biological processes are very rare. Discovering the complex regulating relations among TFs, gene sets and miRNAs will be helpful for researchers to get a more comprehensive understanding about the mechanism of side reaction. In this study, a framework was proposed to construct the relationship network of gene sets, miRNAs and TFs involved in side effects. Through the construction of this network, the potential complex regulatory relationship in the occurrence process of the side effects was reproduced. The SE-gene set network was employed to characterize the significant regulatory SE-gene set interaction and molecular basis of accompanied side effects. A total of 117 side effects complex modules including four types of regulating patterns were obtained from the SE-gene sets-miRNA/TF complex regulatory network. In addition, two cases were used to validate the complex regulatory modules which could more comprehensively interpret occurrence mechanism of side effects.

Drug repositioning by applying 'expression profiles' generated by integrating chemical structure similarity and gene semantic similarity.

Drug repositioning, also known as drug repurposing or reprofiling, is the process of finding new indications for established drugs. Because drug repositioning can reduce costs and enhance the efficiency of drug development, it is of paramount importance in medical research. Here, we present a systematic computational method to identify potential novel indications for a given drug. This method utilizes some prior knowledge such as 3D drug chemical structure information, drug-target interactions and gene semantic similarity information. Its prediction is based on another form of 'expression profile', which contains scores ranging from -1 to 1, reflecting the consensus response scores (CRSs) between each drug of 965 and 1560 proteins. The CRS integrates chemical structure similarity and gene semantic similarity information. We define the degree of similarity between two drugs as the absolute value of their correlation coefficients. Finally, we establish a drug similarity network (DSN) and obtain 33 modules of drugs with similar modes of action, determining their common indications. Using these modules, we predict new indications for 143 drugs and identify previously unknown indications for 42 drugs without ATC codes. This method overcomes the instability of gene expression profiling derived from experiments due to experimental conditions, and predicts indications for a new compound feasibly, requiring only the 3D structure of the compound. In addition, the high literature validation rate of 71.8% also suggests that our method has the potential to discover novel drug indications for existing drugs.

Network characteristic analysis of ADR-related proteins and identification of ADR-ADR associations.

Adverse drug reactions (ADRs) are caused by interactions between drugs or their metabolites and specific proteins. Knowledge of these proteins is important for facilitating mechanistic research of ADRs and new drug discovery. Here, we identified 41 network modules from an ADR-protein network; analysed the function of each module; revealed the potential accompanying actions of the ADRs and the new ADR-related proteins (ADRPs) to a unique ADR and studied the characteristics of composition, subcellular location and tissue distribution of these ADRPs by comparing them with drug-related proteins (DRPs). The results indicated that ADRs are mainly caused by risk drug-related proteins (RDRPs) and that drug off-target effects are a secondary cause. Biological processes that enzymes involve are the main reason for the occurrence of ADRs. However, drug-related transporters have a higher risk of inducing ADRs than drug-related enzymes do, and ADRPs locating in the cell membrane tend to induce multiple ADRs.

A sub-pathway-based approach for identifying drug response principal network.

MOTIVATION: The high redundancy of and high degree of cross-talk between biological pathways hint that a sub-pathway may respond more effectively or sensitively than the whole pathway. However, few current pathway enrichment analysis methods account for the sub-pathways or structures of the tested pathways. We present a sub-pathway-based enrichment approach for identifying a drug response principal network, which takes into consideration the quantitative structures of the pathways. RESULT: We validated this new approach on a microarray experiment that captures the transcriptional profile of dexamethasone (DEX)-treated human prostate cancer PC3 cells. Compared with GeneTrail and DAVID, our approach is more sensitive to the DEX response pathways. Specifically, not only pathways but also the principal components of sub-pathways and networks related to prostate cancer and DEX response could be identified and verified by literature retrieval.