MedComm - Future medicine最新文献

Immunotherapy has revolutionized cancer treatment in recent years, yet non-responsiveness of immunotherapy remains a challenge for cancer treatment. Therefore, the prediction method for potential clinical benefits of patients from immunotherapy is urgently needed. This study aims to develop an effective clinical practice assistance tool to evaluate the potential clinical benefits and therapy responsiveness of patients undergoing immunotherapy. We developed an immunotherapy resistance score (IRS), which performed well compared with conventional immunotherapy response indicators across different immunotherapy cohorts. Tumor microenvironment (TME) analysis showed that both immune and nonimmune features collectively impact immunotherapy responsiveness. Thus, IRS was constructed based on the TME features using machine learning approaches. The clinical application potential of IRS has been demonstrated in our in-house Harbin Medical University (HMU) cohort and an external validation cohort. Furthermore, we analyzed the correlation between IRS and pathways related to cancer therapy targets to explore the application potential of IRS in comprehensive cancer therapy. In conclusion, IRS is a robust tool for predicting patient immunotherapy prognosis, which has great potential to promote precise clinical therapy.

Most individuals with COVID-19, caused by SARS-CoV-2 infection, experience asymptomatic or mild-to-moderate symptoms, while a minority of patients may deteriorate to severe illness or fatal outcomes [1]. Severe COVID-19 can lead to critical complications, including respiratory distress and increased mortality rates [2]. One such complication is the development of “white lung” on chest radiographs (e.g., X-ray), characterized by extensive inflammation and fluid accumulation affecting 70%–80% of the lung area [3]. The appearance of white lung signals a critical stage in COVID-19 patients, profoundly impairing lung function, often requiring mechanical ventilation and ICU admission, and substantially increasing mortality risk [1, 2]. Despite extensive research into the pathophysiology of COVID-19, the mechanisms underlying “white lung” remain poorly understood.

Here, we performed single-cell RNA sequencing analysis of bronchoalveolar lavage fluid (BALF) to characterize the pathophysiology of “white lung” in COVID-19 (Figure 1A). BALF samples were collected from 16 patients with moderate (MO, n = 3), severe (SE, n = 6), and “white lung” (WL, n = 7) syndrome, as well as from 3 healthy controls (HC) (Figure 1A). After quality control filtering (Supporting Information S1: Figure S1A–C), we obtained transcriptome data sets from 136,015 cells (mean = 7159 cells/sample). Using uniform manifold approximation and projection (UMAP), we identified 7 major cell types (Supporting Information S1: Figure S1D) and, through sub-clustering, 44 distinct cell states representing diverse respiratory cell types (Supporting Information S1: Figure S1E). UMAP visualization (Supporting Information S1: Figure S1F) revealed substantial inter-group heterogeneity. The distribution of seven major clusters was portrayed through R_O/E (Supporting Information S1: Figure S1G) [1]. We observed an obvious expansion of NK and neutrophils in COVID-19 patients with “white lung” (Supporting Information S1: Figure S1G–J, Figure 1B). However, NK cells comprised < 0.5% of the total cell population in these patients (Supporting Information S1: Figure S1I), implying that their expansion is unlikely to be the primary driver of this complication. In contrast, neutrophils constituted up to 85% of BALF cells in COVID-19 patients with “white lung,” whereas this proportion did not exceed 25% in any other group (Figure 1B, Supporting Information S1: Figure S1H). PCA analysis clearly distinguished neutrophils from “white lung” patients from those in controls and patients with moderate and severe COVID-19 (Supporting Information S1: Figure S2A,B). Among BALF immune cells, neutrophils exhibited a significant association with “white lung” patients (Supporting Information S1: Figure S2C). These results suggested that neutrophil infiltration may be a key driver of “white lung” development in COVID-19.<

Muscle atrophy, characterized by the loss of muscle mass and function, is a hallmark of sarcopenia and cachexia, frequently associated with aging, malignant tumors, chronic heart failure, and malnutrition. Moreover, it poses significant challenges to human health, leading to increased frailty, reduced quality of life, and heightened mortality risks. Despite extensive research on sarcopenia and cachexia, consensus in their assessment remains elusive, with inconsistent conclusions regarding their molecular mechanisms. Muscle atrophy models are crucial tools for advancing research in this field. Currently, animal models of muscle atrophy used for clinical and basic scientific studies are induced through various methods, including aging, genetic editing, nutritional modification, exercise, chronic wasting diseases, and drug administration. Muscle atrophy models also include in vitro and small organism models. Despite their value, each of these models has certain limitations. This review focuses on the limitations and diverse applications of muscle atrophy models to understand sarcopenia and cachexia, and encourage their rational use in future research, therefore deepening the understanding of underlying pathophysiological mechanisms, and ultimately advancing the exploration of therapeutic strategies for sarcopenia and cachexia.

Cancer immunotherapies, developed on the basis of research into tumor escape mechanisms, manipulate the immune system to reactivate an antitumor immune response to recognize and attack cancer cells. Immunotherapy has demonstrated promising and exciting outcomes in the treatment of many cancers, yet not all patients experience favorable responses. The gut microbiota plays a critical role in modulating the host immune system, influencing responses to cancer immunotherapy. Research has increasingly demonstrated that specific microbial communities can increase the efficacy of immune checkpoint inhibitors, although the mechanisms involved remain under investigation. However, a clear gap exists in the understanding of how bacterial therapies can be further optimized for cancer treatment. This review provides an in-depth analysis of current bacterial therapies used in clinical trials as adjuncts to cancer immunotherapy, summarizing common research approaches and technologies utilized to investigate gut microbiota interactions with the immune system. Additionally, advanced strategies for modifying bacteria, including genetic engineering, surface modifications, and the development of bacterial derivatives, are discussed. By synthesizing these findings, this review highlights the potential of microbiota-based therapies to improve immunotherapy outcomes and offers future directions for improving clinical applications.

Acute kidney injury (AKI) is a significant global healthcare burden but lacks specific and effective treatment. Renal tubular cells damage is central to ischemia-reperfusion injury (IRI) induced AKI. It is critical to clarify the initiation mechanisms of renal IRI and develop early intervention targets of AKI. This study used label-free quantification proteomic analysis to identify new targets in AKI-related renal tubular injury and investigate the potential mechanisms. We discovered significant changes in cysteinyl-tRNA synthetase (CARS) in renal tubular cell during IRI. Considering the involvement of CARS in ATP metabolism and the close correlation between ATP and pyroptosis, we further explored pyroptosis phenotype with and without CARS intervention as well as the expression of CARS during pyroptosis activation and inhibition. Our findings suggest that CARS expression decreased over time and is linked to pyroptosis. Modifying CARS affects ATP metabolism and alters the expression of pyroptosis-related proteins during H/R and IRI treatments. Regulating pyroptosis may influence CARS expression during IRI treatment. Overall, CARS is associated with renal tubular damage from ischemia-reperfusion injury, possibly involving pyroptosis, though the regulatory mechanism remains unclear.

Vancomycin (VAN)-intermediate Staphylococcus aureus (VISA) is a critical cause of VAN treatment failure worldwide. Multiple genetic changes are reportedly associated with VISA formation, whereas VISA strains often present common phenotypes, such as reduced autolysis and thickened cell wall. However, how mutated genes lead to VISA common phenotypes remains unclear. Here, we show a metabolism regulatory cascade (CcpA-GlmS), whereby mutated two-component systems (TCSs) link to the common phenotypes of VISA. We found that ccpA deletion decreased VAN resistance in VISA strains with diverse genetic backgrounds. Metabolic alteration in VISA was associated with ccpA upregulation, which was directly controlled by TCSs WalKR and GraSR. RNA-sequencing revealed the crucial roles of CcpA in changing the carbon flow and nitrogen flux of VISA to promote VAN resistance. A gate enzyme (GlmS) that drives carbon flow to the cell wall precursor biosynthesis was upregulated in VISA. CcpA directly controlled glmS expression. Blocking CcpA sensitized VISA strains to VAN treatment in vitro and in vivo. Overall, this work uncovers a link between the formation of VISA phenotypes and commonly mutated genes. Inhibition of CcpA-GlmS cascade is a promising strategy to restore the therapeutic efficiency of VAN against VISA infections.

Intrauterine adhesion (IUA) is a common endometrial disease caused by injury, leading to reproductive health issues. Current treatments have limited effectiveness, side effects, and high recurrence rates, especially, in severe cases. However, the underlying molecular and cellular mechanisms are largely unknown. Here we performed a comprehensive analysis by profiling integrated single-cell transcriptomes of over 72,000 individual endometrial cells, encompassing samples from both patients with IUA and those with normal endometrium. We identified changes in cell type-specific molecular signatures, including the inflammatory activation in immune cells, extensive damage in epithelial subpopulations, and the deposition of collagen secreted by fibroblasts subpopulations. Our results demonstrated activation of the TREM2⁺ macrophages, which displayed properties of inflammatory regulation. Annexin A1⁺ NK subpopulations exhibited the highest susceptibility among NK subtypes, displaying decreased cellular density and the most pronounced differential gene expression. Furthermore, we identified the matrix metallopeptidase 7 (MMP7⁺) and C-C motif chemokine ligand 5 (CCL5⁺) unciliated epithelial subtype originated from pituitary tumor-transforming gene 1 (PTTG1⁺) unciliated epithelium as the most vulnerable subpopulations to epithelial injury. Collectively, our study offers integrated resources of the cellular microenvironment of IUA, serving as a comprehensive cellular map of the disease in affected individuals. The insights gained from this study are expected to provide valuable resources for future diagnostic and therapeutic approaches.

Long coronavirus disease (COVID) is characterized by persistent symptoms following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and has emerged as a significant health concern. As SARS-CoV-2 evolved from the wild-type strain to the Alpha, Beta, Delta, and Omicron variants, there may be a variant-specific influence on long COVID akin to the acute disease. This review aims to summarize our current knowledge of variant-specific influences in long COVID incidence, symptom profile as well as mechanisms of pathogenesis. We highlight that long COVID incidence may be lower with the Omicron variants. The symptom profile of long COVID may also show some dependence on the different variants, with a reduction in cardiopulmonary symptoms with more recent SARS-CoV-2 variants. This heterogeneity of long COVID may also be related to the variant-specific differences in affecting the immune system, viral persistence, and autoimmunity. However, emerging data also suggest that vaccinations may play a big role in shaping the presentation of long COVID. We also highlight ongoing work on long COVID incidence and symptom profiles in populations infected only by the Omicron variants. This will be beneficial toward more useful disease definitions and the development of effective diagnostic and therapeutic strategies.

Next-generation sequencing (NGS) has emerged as a transformative technology in oncology, revolutionizing cancer diagnostics and personalized treatment strategies. By providing comprehensive insights into the genetic landscape of tumors, NGS enables the identification of critical somatic and germline mutations, copy number variations (CNVs), and gene fusions. Over the past decade, advancements in NGS platforms have led to greater accuracy, speed, and cost-effectiveness, making it an integral part of cancer research and clinical diagnostics. Despite its widespread adoption, significant challenges remain, including the need for improved methods to detect minimal residual disease (MRD) and accurately profile tumor heterogeneity. This review explores the evolution of NGS technologies and their pivotal role in cancer biology, from early diagnostics to therapeutic guidance. It delves into the application of NGS in identifying CNVs and gene fusions, monitoring MRD, and the increasing relevance of targeted NGS and spatial genomics. Furthermore, the integration of spatial transcriptomics is highlighted as a frontier in understanding the tumor microenvironment. By addressing these critical aspects, this review provides a comprehensive overview of how NGS is shaping the future of cancer research and treatment, offering a complete overview of potential NGS applications in scientific and clinical oncology.