Studies have shown that the circulating tumor cell (CTC) is a necessary condition for the invasion and distant metastasis of renal cell carcimona (RCC). However, few CTCs-related gene mutations have been developed which could promote the metastasis and implantation of RCC. The objective of this study is to explore the potential driver gene mutations that promote RCC metastasis and implantation based on CTCs culture. Fifteen patients with primary mRCC and three healthy subjects were included, and peripheral blood was obtained. After the preparation of synthetic biological scaffolds, peripheral blood CTCs were cultured. Successful cultured CTCs were applied to construct CTCs-derived xenograft (CDX) models, followed by DNA extraction, whole exome sequencing (WES) and bioinformatics analysis. Synthetic biological scaffolds were constructed based on previously applied techniques, and peripheral blood CTCs culture was successfully performed. We then constructed CDX models and performed WES, and explored the potential driver gene mutations that may promote RCC metastasis and implantation. Bioinformatics analysis showed that KAZN and POU6F2 may be closely related to the prognosis of RCC. We successfully performed the culture of peripheral blood CTCs and, on this basis we initially explored the potential driver mutations for the metastasis and implantation of RCC.

Background/Objectives: Bone metastasis is a frequent and life-threatening event in advanced cancers, affecting up to 70–85% of prostate cancer patients. Understanding the cellular and molecular mechanisms underlying bone metastasis is essential for developing targeted therapies. This study aimed to systematically characterize the heterogeneity and microenvironmental adaptation of prostate cancer bone metastases using single-cell transcriptomics. Methods: We integrated the largest single-cell transcriptome dataset to date, encompassing 124 samples from primary prostate tumors, various bone metastatic sites, and non-malignant tissues (e.g., benign prostatic hyperplasia, normal bone marrow). After quality control, 602,497 high-quality single-cell transcriptomes were analyzed. We employed unsupervised clustering, gene expression profiling, mutation analysis, and metabolic pathway reconstruction to characterize cancer cell subtypes and tumor microenvironmental remodeling. Results: Cancer epithelial cells dominated the tumor microenvironment but exhibited pronounced heterogeneity, posing challenges for conventional clustering methods. By integrating genetic and metabolic features, we revealed key evolutionary trajectories of epithelial cancer cells during metastasis. Notably, we identified a novel epithelial subpopulation, NEndoCs, characterized by unique differentiation patterns and distinct spatial distribution across metastatic niches. We also observed significant metabolic reprogramming and recurrent mutations linked to prostate-to-bone microenvironmental transitions. Conclusions: This study comprehensively elucidates the mutation patterns, metabolic reprogramming, and microenvironment adaptation mechanisms of bone metastasis in prostate cancer, providing key molecular targets and clinical strategies for the precise treatment of bone metastatic prostate cancer.

Single-cell RNA sequencing (scRNA-seq) is one of the most efficient technologies for human tumor research. However, data analysis is still faced with some technical challenges, especially the difficulty in efficiently and accurately discriminate cancer/normal cells in the scRNA-seq expression matrix. In this study, we developed a cancer/normal cell discrimination pipeline called pan-cancer seeker (CaSee) devoted to scRNA-seq expression matrix, which is based on the traditional high-quality pan-cancer bulk sequencing data using transfer learning. It is compatible with mainstream sequencings technology platforms, 10x Genomics Chromium, Smart-seq2, and Microwell-seq. Here, CaSee pipeline exhibited excellent performance in the multicenter data evaluation of 11 retrospective cohorts and one independent dataset, with an average discrimination accuracy of 96.69%. In general, the development of a deep-learning based, pan-cancer cell discrimination model, CaSee, to distinguish cancer cells from normal cells will be compelling to researchers working in the genomics, cancer, and single-cell fields.

Tuberculosis (TB) has returned as the leading cause of death caused by a single infectious agent in 2023. Human macrophages and their secreted exosomes play important roles in combating invading Mycobacterium tuberculosis (Mtb). However, a comprehensive understanding of the mechanisms underlying immune regulation in Mtb-infected macrophages, as well as the packaging mechanisms and anti-TB effects of Mtb-treated exosomes, is still lacking. Here, we conducted comprehensive analyses of the macrophages infected with avirulent and virulent Mtb strains (H37Ra and H37Rv) and their exosomes through omics and phenotypic approaches. The results showed that H37Ra stimulated strong immune responses and apoptosis in macrophages to eliminate invading Mtb, while H37Rv induced severe necrosis and immune escape for survival. Interestingly, our results suggest that macrophages kill Mtb in an interferon-gamma (IFN-γ)-independent but compensatory way, highlighting the central role of IFN signaling pathway in anti-TB response. Moreover, we observed selective transport of host and Mtb RNAs from macrophages to exosomes. Notably, H37Ra-treated exosomes displayed a higher anti-TB effect than H37Rv-treated exosomes due to some enriched pro-inflammatory and immune escape-related Mtb proteins in these two exosomes, respectively. In conclusion, our findings shed new light on the immune mechanisms of macrophages in response to Mtb infection, offering a new TB treatment strategy and promising vaccine candidates.

Male breast cancer (MBC) is a relatively rare and inadequately researched disease, and its cellular and molecular traits remain obscure. In this study, we conducted single-cell sequencing (N=20) and spatial transcriptomics (N=14) on 34 fresh tissue samples from 27 MBC patients. We identified six major cancer cell subtypes that are associated with the development and progression of MBC. Specifically, cancer cells exhibiting neuroendocrine-like properties facilitate immune evasion, tumor angiogenesis, epithelial-to-mesenchymal transition, cell proliferation, tumor invasion, and metastasis. They do so by secreting neuro-related factors and engaging in regulating neuro-related signaling pathways, synergistically interacting with T cells, macrophages, and fibroblasts within the tumor microenvironment. Additionally, we found that mutations or copy number variations amplifications of the UTY gene on the Y chromosome and/or its high transcript expression are closely associated with adverse clinical outcomes in male cancer patients, including MBC patients. In conclusion, our study provides important data support for a deeper understanding of the molecular characteristics and tumor microenvironment of MBC, and offers important clues for developing improved therapeutic strategies to improve the prognosis of MBC patients.