Single Nuclear RNA Sequencing Highlights Intra-Tumoral Heterogeneity and Tumor Microenvironment Complexity in Testicular Embryonic Rhabdomyosarcoma

Targeted immunotherapy and nanomedicine for rhabdomyosarcoma: The way of the future

Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma of childhood. Histology separates two main subtypes: embryonal RMS (eRMS; 60%-70%) and alveolar RMS (aRMS; 20%-30%). The aggressive aRMS carry one of two characteristic chromosomal translocations that result in the expression of a PAX3::FOXO1 or PAX7::FOXO1 fusion transcription factor; therefore, aRMS are now classified as fusion-positive (FP) RMS. Embryonal RMS have a better prognosis and are clinically indistinguishable from fusion-negative (FN) RMS. Next to histology and molecular characteristics, RMS risk groupings are now available defining low risk tumors with excellent outcomes and advanced stage disease with poor prognosis, with an overall survival of about only 20% despite intensified multimodal treatment. Therefore, development of novel effective targeted strategies to increase survival and to decrease long-term side effects is urgently needed. Recently, immunotherapies and nanomedicine have been emerging for potent and effective tumor treatments with minimal side effects, raising hopes for effective and safe cures for RMS patients. This review aims to describe the most relevant preclinical and clinical studies in immunotherapy and targeted nanomedicine performed so far in RMS and to provide an insight in future developments.

Single-cell RNA sequencing technology in human spermatogenesis: Progresses and perspectives

Spermatogenesis, a key part of the spermiation process, is regulated by a combination of key cells, such as primordial germ cells, spermatogonial stem cells, and somatic cells, such as Sertoli cells. Abnormal spermatogenesis can lead to azoospermia, testicular tumors, and other diseases related to male infertility. The application of single-cell RNA sequencing (scRNA-seq) technology in male reproduction is gradually increasing with its unique insight into deep mining and analysis. The data cover different periods of neonatal, prepubertal, pubertal, and adult stages. Different types of male infertility diseases including obstructive and non-obstructive azoospermia (NOA), Klinefelter Syndrome (KS), Sertoli Cell Only Syndrome (SCOS), and testicular tumors are also covered. We briefly review the principles and application of scRNA-seq and summarize the research results and application directions in spermatogenesis in different periods and pathological states. Moreover, we discuss the challenges of applying this technology in male reproduction and the prospects of combining it with other technologies.

Construction and validation model of necroptosis-related gene signature associates with immunity for osteosarcoma patients

Osteosarcoma is the most common malignant tumor in children and adolescents and its diagnosis and treatment still need to be improved. Necroptosis has been associated with many malignancies, but its significance in diagnosing and treating osteosarcoma remains unclear. The objective is to establish a predictive model of necroptosis-related genes (NRGs) in osteosarcoma for evaluating the tumor microenvironment and new targets for immunotherapy. In this study, we download the osteosarcoma data from the TARGET and GEO websites and the average muscle tissue data from GTEx. NRGs were screened by Cox regression analysis. We constructed a prediction model through nonnegative matrix factorization (NMF) clustering and the least absolute shrinkage and selection operator (LASSO) algorithm and verified it with a validation cohort. Kaplan–Meier survival time, ROC curve, tumor invasion microenvironment and CIBERSORT were assessed. In addition, we establish nomograms for clinical indicators and verify them by calibration evaluation. The underlying mechanism was explored through the functional enrichment analysis. Eight NRGs were screened for predictive model modeling. NRGs prediction model through NMF clustering and LASSO algorithm was established. The survival, ROC and tumor microenvironment scores showed significant statistical differences among subgroups (P < 0.05). The validation model further verifies it. By nomogram and calibration, we found that metastasis and risk score were independent risk factors for the poor prognosis of osteosarcoma. GO and KEGG analyses demonstrate that the genes of osteosarcoma cluster in inflammatory, apoptotic and necroptosis signaling pathways. The significant role of the correlation between necroptosis and immunity in promoting osteosarcoma may provide a novel insight into detecting molecular mechanisms and targeted therapy.