Lower respiratory tract microbiome dysbiosis impairs clinical responses to immune checkpoint blockade in advanced non-small-cell lung cancer

BACKGROUND

Gut microbiome on predicting clinical responses to immune checkpoint inhibitors (ICIs) has been discussed in detail for decades, while microecological features of the lower respiratory tract within advanced non-small-cell lung cancer (NSCLC) are still relatively vague.

METHODS

During this study, 26 bronchoalveolar lavage fluids (BALF) from advanced NSCLC participants who received immune checkpoint inhibitor monotherapy were performed 16S rRNA sequencing and untargeted metabolome sequencing to identify differentially abundant microbes and metabolic characteristics. Additionally, inflammatory cytokines and chemokines were also launched in paired BALF and serum samples by immunoassays to uncover their underlying correlations. The omics data were separately analyzed and integrated by using multiple correlation coefficients. Multiplex immunohistochemical staining was then used to assess the immune cell infiltration after immune checkpoint blockade therapy.

RESULTS

Lower respiratory tract microbiome diversity favoured preferred responses to ICIs. Microbial markers demonstrated microbial diversity overweight a single strain in favoured response to ICI therapy, where Bacillus matters. Sphingomonas and Sediminibacterium were liable to remodulate lipid and essential amino acid degradations to embrace progression after immunotherapies. Microbiome-derived metabolites reshaped the immune microenvironment in the lower respiratory tract by releasing inflammatory cytokines and chemokines, which was partially achieved by metabolite-mediated tumoral inflammatory products and reduction of CD8+ effective T cells and M1 phenotypes macrophages in malignant lesions.

CONCLUSIONS

This study provided a microecological landscape of the lower respiratory tract with advanced NSCLC to ICI interventions and presented a multidimensional perspective with favoured outcomes that may improve the predictive capacity of the localized microbiome in clinical practices.

HIGHLIGHTS

Alterations of the lower respiratory tract microbiome indicate different clinical responses to ICB within advanced NSCLC. Reduced microbial diversity of lower respiratory tracts impairs anti-tumoral performances. Microbe-derived metabolites perform as a dominant regulator to remodify the microecological environment in lower respiratory tracts. Multi-omics sequencings of the lower respiratory tract possess the potential to predict the long-term clinical responses to ICB among advanced NSCLC.

Multi-Omics Analysis Reveals Disturbances of Purine Metabolism and Glutamate Metabolism in the Hippocampus of Lipopolysaccharide-Induced Mouse Model of Depression

BACKGROUND

Depression is a global health concern characterized by high incidence, disability, and disease burden. Neuroimmunity, through the secretion of inflammatory mediators and mediation of neuroinflammation, plays a significant role in depression's pathogenesis. However, the underlying molecular mechanisms remain poorly understood.

METHODS

In this pioneering study, we employed a comprehensive multi-omics approach, integrating 2-DE proteomics, liquid chromatography mass spectrometry-based metabolomics, and real-time polymerase chain reaction (PCR) array, to investigate the hippocampal molecular profiles of lipopolysaccharide (LPS)-induced immune inflammation-related depression. This innovative approach aimed to explore the potential pathogenesis of depression by systematically integrating data across multiple molecular layers.

RESULTS

Compared to the control group, we identified 81 differential proteins, 44 differential metabolites, and 4 differential mRNAs in LPS-treated mice. Integrated analysis of these multidimensional data revealed that purine metabolism and glutamate metabolism are the most significantly altered molecular pathways in LPS-induced depression. Additionally, we constructed the corresponding compound-reaction-enzyme-gene regulatory network.

CONCLUSION

This study suggests that purine metabolism and glutamate metabolism may be the underlying mechanisms by which neuroinflammation regulates depression-like behaviors. Our findings confirm the important role of immune inflammation in depression and provide a new clue for the diagnosis and treatment of this disorder. Notably, the multi-omics approach employed in this study represents a pioneering effort in the field, providing unprecedented insights into the molecular mechanisms underlying depression.

Longitudinal MRI-Driven Multi-Modality Approach for Predicting Pathological Complete Response and B Cell Infiltration in Breast Cancer

Accurately predicting pathological complete response (pCR) to neoadjuvant treatment (NAT) in breast cancer remains challenging due to tumor heterogeneity. This study enrolled 2279 patients across 12 centers and develops a novel multi-modality model integrating longitudinal magnetic resonance imaging (MRI) spatial habitat radiomics, transcriptomics, and single-cell RNA sequencing for predicting pCR. By analyzing tumor subregions on multi-timepoint MRI, the model captures dynamic intra-tumoral heterogeneity during NAT. It shows superior performance over traditional radiomics, with areas under the curve of 0.863, 0.813, and 0.888 in the external validation, immunotherapy, and multi-omics cohorts, respectively. Subgroup analysis shows its robustness across varying molecular subtypes and clinical stages. Transcriptomic and single-cell RNA sequencing analysis reveals that high model scores correlate with increased immune activity, notably elevated B cell infiltration, indicating the biological basis of the imaging model. The integration of imaging and molecular data demonstrates promise in spatial habitat radiomics to monitor dynamic changes in tumor heterogeneity during NAT. In clinical practice, this study provides a noninvasive tool to accurately predict pCR, with the potential to guide treatment planning and improve breast-conserving surgery rates. Despite promising results, the model requires prospective validation to confirm its utility across diverse patient populations and clinical settings.

Multi-Omics Analysis of the Molecular Mechanisms by Which Extract of Artemisia selengensis Turcz. Ameliorates DBP-Induced Liver Injury

Artemisia selengensis Turcz. is a perennial herb belonging to the genus Artemisia in the family Asteraceae. Known for its nutrient richness, distinct flavor, and medicinal properties, Artemisia selengensis Turcz. has garnered attention. However, its efficacy, particularly in alleviating hepatic injury, remains underexplored. This study aims to assess the therapeutic potential of the 50% ethanol extract of Artemisia selengensis Turcz. (ASTE) in a mouse model of dibutyl phthalate (DBP)-induced liver injury. Through multi-omics analysis, including transcriptomics, metabolomics, and intestinal flora examination, we explored the pathways and key targets of ASTE in treating liver injury. Network pharmacology further identified the crucial components of ASTE for liver injury treatment. Our findings indicate that ASTE affects intestinal flora such as Adlercreutzia through flavonoids, particularly naringin and epicatechin. Additionally, key genes in the PPAR pathway, such as fatty acid-binding protein 3 (Fabp3), fatty acid-binding protein 5 (Fabp5), 3-hydroxyacyl-CoA dehydrogenase (Ehhadh), and phospholipid transfer protein (Pltp), influence glycerophospholipid metabolism, contributing to liver injury amelioration. This study sheds light on the molecular mechanisms underlying ASTE's hepatoprotective effects, laying the groundwork for its potential application as a functional food.

From Images to Genes: Radiogenomics Based on Artificial Intelligence to Achieve Non-Invasive Precision Medicine in Cancer Patients

With the increasing demand for precision medicine in cancer patients, radiogenomics emerges as a promising frontier. Radiogenomics is originally defined as a methodology for associating gene expression information from high-throughput technologies with imaging phenotypes. However, with advancements in medical imaging, high-throughput omics technologies, and artificial intelligence, both the concept and application of radiogenomics have significantly broadened. In this review, the history of radiogenomics is enumerated, related omics technologies, the five basic workflows and their applications across tumors, the role of AI in radiogenomics, the opportunities and challenges from tumor heterogeneity, and the applications of radiogenomics in tumor immune microenvironment. The application of radiogenomics in positron emission tomography and the role of radiogenomics in multi-omics studies is also discussed. Finally, the challenges faced by clinical transformation, along with future trends in this field is discussed.

Investigating the Role of Scd1 in OSAHS-Induced Vascular Changes

This study investigates the role of Stearoyl-CoA Desaturase-1 (Scd1) in vascular remodeling associated with Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) using multi-omics analysis. Transcriptomic and metabolomic datasets of OSAHS mouse models were analyzed to identify differentially expressed genes and metabolites, followed by functional enrichment analysis. Key genes were screened using weighted gene correlation network analysis (WGCNA) and machine learning, and a PPI network was constructed. An OSAHS mouse model was developed via intermittent hypoxia exposure. Human aortic smooth muscle cells (HASMCs) were subjected to hypoxia/reoxygenation cycles to simulate OSAHS in vitro. Blood pressure, plasma lipid profiles, histological changes in the thoracic aorta, and Scd1 protein expression were assessed. CCK-8 and Transwell assays evaluated HASMC proliferation and migration. Scd1 was identified as a critical factor in OSAHS-related vascular remodeling, with its expression significantly upregulated in vascular tissues of OSAHS mice. Metabolomic analysis revealed changes in fatty acid metabolism. Scd1 knockdown reduced blood pressure, lipid levels, aortic wall thickness, collagen deposition, elastic fiber accumulation, and mucin deposition in vivo. In vitro, hypoxia/reoxygenation cycles elevated Scd1 expression, while Scd1 knockdown inhibited HASMC proliferation and migration. Multi-omics analyses highlight Scd1 as a key regulator in OSAHS-associated vascular remodeling, driving pathological changes through its upregulation. These findings suggest Scd1 as a potential therapeutic target for managing OSAHS-related vascular pathologies.

Ecotype-specific phenolic acid accumulation and root softness in Salvia miltiorrhiza are driven by environmental and genetic factors

Salvia miltiorrhiza Bunge, a renowned medicinal herb in traditional Chinese medicine, displays distinctive root texture and high phenolic acid content, traits influenced by genetic and environmental factors. However, the underlying regulatory networks remain unclear. Here, we performed multi-omics analyses on ecotypes from four major Chinese regions, focusing on environmental impacts on root structure, phenolic acid accumulation and lignin composition. Lower temperatures and increased UV-B radiation were associated with elevated rosmarinic acid (RA) and salvianolic acid B (SAB) levels, particularly in the Sichuan ecotype. Structural models indicated that the radial arrangement of xylem conduits contributes to greater root hardness. Genomic assembly and comparative analysis of the Sichuan ecotype revealed a unique phenolic acid metabolism gene cluster, including SmWRKY40, a WRKY transcription factor essential for RA and SAB biosynthesis. Overexpression of SmWRKY40 enhanced phenolic acid levels and lignin content, whereas its knockout reduced root hardness. Integrating high-throughput (DNA affinity purification sequencing) and point-to-point (Yeast One-Hybrid, Dual-Luciferase and Electrophoretic Mobility Shift Assay) protein-DNA interaction detection platform further identified SmWRKY40 binding sites across ecotypes, revealing specific regulatory networks. Our findings provide insights into the molecular basis of root texture and bioactive compound accumulation, advancing breeding strategies for quality improvement in S. miltiorrhiza.

Deciphering the Immunomodulatory Function of GSN+ Inflammatory Cancer-Associated Fibroblasts in Renal Cell Carcinoma Immunotherapy: Insights From Pan-Cancer Single-Cell Landscape and Spatial Transcriptomics Analysis

The heterogeneity of cancer-associated fibroblasts (CAFs) could affect the response to immune checkpoint inhibitor (ICI) therapy. However, limited studies have investigated the role of inflammatory CAFs (iCAFs) in ICI therapy using pan-cancer single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics sequencing (ST-seq) analysis. We performed pan-cancer scRNA-seq and ST-seq analyses to identify the subtype of GSN+ iCAFs, exploring its spatial distribution characteristics in the context of ICI therapy. The pan-cancer scRNA-seq and bulk RNA-seq data are incorporated to develop the Caf.Sig model, which predicts ICI response based on CAF gene signatures and machine learning approaches. Comprehensive scRNA-seq analysis, along with in vivo and in vitro experiments, investigates the mechanisms by which GSN+ iCAFs influence ICI efficacy. The Caf.Sig model demonstrates well performances in predicting ICI therapy response in pan-cancer patients. A higher proportion of GSN+ iCAFs is observed in ICI non-responders compared to responders in the pan-cancer landscape and clear cell renal cell carcinoma (ccRCC). Using real-world immunotherapy data, the Caf.Sig model accurately predicts ICI response in pan-cancer, potentially linked to interactions between GSN+ iCAFs and CD8+ Tex cells. ST-seq analysis confirms that interactions and cellular distances between GSN+ iCAFs and CD8+ exhausted T (Tex) cells impact ICI efficacy. In a co-culture system of primary CAFs, primary tumour cells and CD8+ T cells, downregulation of GSN on CAFs drives CD8+ T cells towards a dysfunctional state in ccRCC. In a subcutaneously tumour-grafted mouse model, combining GSN overexpression with ICI treatment achieves optimal efficacy in ccRCC. Our study provides the Caf.Sig model as an outperforming approach for patient selection of ICI therapy, and advances our understanding of CAF biology and suggests potential therapeutic strategies for upregulating GSN in CAFs in cancer immunotherapy.

Changes in seminal plasma microecological dynamics and the mechanistic impact of core metabolite hexadecanamide in asthenozoospermia patients

Asthenozoospermia (AZS) is a prevalent contributor to male infertility, characterized by a substantial decline in sperm motility. In recent years, large-scale studies have explored the interplay between the male reproductive system's microecology and its implications for reproductive health. Nevertheless, the direct association between seminal microecology and male infertility pathogenesis remains inconclusive. This study used 16S rDNA sequencing and multi-omics analysis to conduct a comprehensive investigation of the seminal microbial community and metabolites in AZS patients. Patients were categorized into four distinct groups: Normal, mild AZS (AZS-I), moderate AZS (AZS-II), and severe AZS (AZS-III). Microbiome differential abundance analysis revealed significant differences in microbial composition and metabolite profiles within the seminal plasma of these groups. Subsequently, patients were classified into a control group (Normal and AZS-I) and an AZS group (AZS-II and AZS-III). Correlation and cross-reference analyses identified distinct microbial genera and metabolites. Notably, the AZS group exhibited a reduced abundance of bacterial genera such as Pseudomonas, Serratia, and Methylobacterium-Methylorubrum in seminal plasma, positively correlating with core differential metabolite (hexadecanamide). Conversely, the AZS group displayed an increased abundance of bacterial genera such as Uruburuella, Vibrio, and Pseudoalteromonas, with a negative correlation with core differential metabolite (hexadecanamide). In vitro and in vivo experiments validated that hexadecanamide significantly enhanced sperm motility. Using predictive metabolite-targeting gene analysis and single-cell transcriptome sequencing, we profiled the gene expression of candidate target genes PAOX and CA2. Protein immunoblotting techniques validated the upregulation protein levels of PAOX and CA2 in sperm samples after hexadecanamide treatment, enhancing sperm motility. In conclusion, this study uncovered a significant correlation between six microbial genera in seminal plasma and the content of the metabolite hexadecanamide, which is related to AZS. Hexadecanamide notably enhances sperm motility, suggesting its potential integration into clinical strategies for managing AZS, providing a foundational framework for diagnostic and therapeutic advancements.

NAT10 functions as a pivotal regulator in gastric cancer metastasis and tumor immunity

Gastric cancer (GC) presents a significant global health burden, with metastasis being the leading cause of treatment failure and mortality. NAT10, a regulatory protein involved in mRNA acetylation, has been implicated in various cancers. However, its role in GC, especially concerning metastasis and immune interactions, remains unclear. Utilizing multi-omics data from gastric cancer samples, we conducted comprehensive analyses to investigate NAT10 expression, its correlation with clinical parameters and immune relevance. Bioinformatics analysis and digital image processing were employed for this purpose. Furthermore, in vitro and in vivo experiments were conducted to elucidate the functional role of NAT10 in gastric cancer progression, aiming to provide deeper biological insights. Our findings reveal a significant association between NAT10 expression and various aspects of transcriptional, protein, as well as tumor immunity in GC patients. Additionally, we demonstrated that NAT10 promotes gastric cancer cell proliferation and migration, both in cellular models and in animal studies, suggesting its involvement in early tumor microvascular metastasis. NAT10 emerges as a promising molecular target, offering potential avenues for further research into molecular mechanisms and therapeutic strategies for GC.

RIOK1: A Novel Oncogenic Driver in Hepatocellular Carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common and highly lethal cancers worldwide. RIO kinase 1 (RIOK1), a protein kinase/ATPase that plays a key role in regulating translation and ribosome assembly, is associated with a variety of malignant tumors. However, the role of RIOK1 in HCC remains largely unknown.

METHODS

Changes in RIOK1 expression in HCC and patient prognosis were evaluated using HCC tissues and public databases. The functional role of RIOK1 in HCC was analyzed by RTCA assay, clonogenic assay, and flow cytometry in vitro, and by mouse tumor xenograft model in vivo. Potential mechanism studies were performed using multi-omics analysis, public database screening, and qRT-PCR assay.

RESULTS

In this study, we found that RIOK1 was elevated in HCC tissues and correlated with poor prognosis. Functional assays demonstrated that RIOK1 knockdown suppressed HCC cell proliferation, survival, and tumor growth in vivo, while RIOK1 overexpression enhanced these oncogenic phenotypes. Meanwhile, RIOK1 knockdown affected cell cycle progression and the expression of cyclin A2 and cyclin B1. Furthermore, integrated transcriptomic and proteomic analysis revealed that RIOK1 may promote HCC cell proliferation by affecting the cell cycle and DNA repair pathways. Moreover, we identified five potential effectors regulated by RIOK1: PMS1, SPDL1, RAD18, BARD1, and SMARCA5, which were highly expressed in HCC tissues and negatively correlated with the overall survival of HCC patients.

CONCLUSION

Our findings suggest that RIOK1 is a novel oncogenic driver that may serve as a potential diagnostic and therapeutic target for HCC.

Enhancing erythromycin production in Saccharopolyspora erythraea through rational engineering and fermentation refinement: A Design-Build-Test-Learn approach

Industrial production of bioactive compounds from actinobacteria, such as erythromycin and its derivatives, faces challenges in achieving optimal yields. To this end, the Design-Build-Test-Learn (DBTL) framework, a systematic metabolic engineering approach, was employed to enhance erythromycin production in Saccharopolyspora erythraea (S. erythraea) E3 strain. A genetically modified strain, S. erythraea E3-CymRP21-dcas9-sucC (S. erythraea CS), was developed by suppressing the sucC gene using an inducible promoter and dcas9 protein. The strain exhibited improved erythromycin synthesis, attributed to enhanced precursor synthesis and increased NADPH availability. Transcriptomic and metabolomic analyses revealed altered central carbon metabolism, amino acid metabolism, energy metabolism, and co-factor/vitamin metabolism in CS. Augmented amino acid metabolism led to nitrogen depletion, potentially causing cellular autolysis during later fermentation stages. By refining the fermentation process through ammonium sulfate supplementation, erythromycin yield reached 1125.66 mg L-1, a 43.5% increase. The results demonstrate the power of the DBTL methodology in optimizing erythromycin production, shedding light on its potential for revolutionizing antibiotic manufacturing in response to the global challenge of antibiotic resistance.

An Emerging Approach of Age-Related Hearing Loss Research: Application of Integrated Multi-Omics Analysis

As one of the most common otologic diseases in the elderly, age-related hearing loss (ARHL) usually characterized by hearing loss and cognitive disorders, which have a significant impact on the elderly's physical and mental health and quality of life. However, as a typical disease of aging, it is unclear why aging causes widespread hearing impairment in the elderly. As molecular biological experiments have been conducted for research recently, ARHL is gradually established at various levels with the application and development of integrated multi-omics analysis in the studies of ARHL. Here, the recent progress in the application of multi-omics analysis in the molecular mechanisms of ARHL development and therapeutic regimens, including the combined analysis of different omics, such as transcriptome, proteome, and metabolome, to screen for risk sites, risk genes, and differences in lipid metabolism, etc., is outlined and the integrated histological data further promote the profound understanding of the disease process as well as physiological mechanisms of ARHL. The advantages and disadvantages of multi-omics analysis in disease research are also discussed and the authors speculate on the future prospects and applications of this part-to-whole approach, which may provide more comprehensive guidance for ARHL and aging disease prevention and treatment.