Schmid-type metaphyseal chondrodysplasia (SMCD) is primarily caused by mutations in the COL10A1 gene. This study reports a novel frameshift mutation, c.1940dup (p.Asn647Lysfs*2), identified in a Chinese SMCD pedigree. The mutation did not alter messenger RNA levels but significantly reduced COL10A1 protein expression. The mutant protein lacks the C-terminal 33 amino acids, resulting in a truncated polypeptide of 648 residues with a lower molecular weight than the wild-type protein. Degradation kinetics analysis showed no evidence of accelerated turnover. Notably, even under complete inhibition of degradation pathways, mutant protein expression remained substantially lower than that of wild-type, suggesting a potential defect in translational efficiency. Furthermore, the mutation severely disrupted the assembly of the characteristic collagen X trimer and led to markedly reduced extracellular secretion, as measured by accumulated protein levels in conditioned medium. These findings demonstrate that the c.1940dup mutation contributes to SMCD pathogenesis through coordinated mechanisms involving protein truncation, reduced expression, probable translational deficiency, and defective trimer formation and secretion, thereby revealing new potential therapeutic targets.
Coptis is a medically important genus renowned for producing valuable isoquinoline alkaloids. Although its chloroplast genomes encode key components for photosynthesis and plastid gene expression, the evolutionary constraints acting on their coding sequences and synonymous codon usage remain poorly resolved. Here, we combined a transparent taxon-level sampling strategy with comparative analyses of chloroplast CDSs from eight Coptis taxa. We quantified nucleotide composition, relative synonymous codon usage, effective number of codons, neutrality and PR2 patterns, and correspondence analysis, and then integrated these results with a core-CDS distance analysis and gene-wise pairwise dN/dS estimates. The chloroplast genomes showed a conserved AT-rich composition, especially at the third codon position (GC3 approximately 30.3–30.8
Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality worldwide and is characterized by a hypoxic tumor microenvironment that promotes tumor progression, cellular adaptation, and therapeutic resistance. Increasing evidence indicates that long non-coding RNAs (lncRNAs) play critical roles in regulating tumor-associated signaling networks; however, the contribution of MIR100HG to hepatocellular carcinoma progression, particularly under hypoxic conditions, remains insufficiently understood. In this study, we investigated the expression pattern and functional significance of MIR100HG in hepatocellular carcinoma using epithelial-like Hep3B and mesenchymal-like SNU-398 cells, together with non-tumor hepatocytes (Clone-9). Gain- and loss-of-function approaches were employed to evaluate the impact of MIR100HG on tumor-associated cellular phenotypes under both normoxic and hypoxic conditions. Functional assays demonstrated that MIR100HG overexpression significantly enhanced cell proliferation, clonogenic potential, migration, and invasion, whereas MIR100HG silencing markedly suppressed these tumorigenic properties and increased apoptotic cell death. Mechanistic analyses revealed that MIR100HG promotes oncogenic signaling through the p38/MAPK and AKT pathways under normoxic conditions, whereas MIR100HG depletion reduced the phosphorylation of these key signaling proteins. Notably, additional pathway analyses under hypoxia-mimicking conditions revealed a distinct signaling response, in which the MIR100HG-associated activation of p38/MAPK and AKT observed under normoxia was not maintained. Moreover, the expression patterns of AKT-associated regulatory genes, including GAS6 and PTEN, were reversed under hypoxia-mimicking conditions. These findings suggest that the effects of MIR100HG on oncogenic signaling are highly dependent on the cellular oxygenation context and that hypoxia reshapes the downstream signaling consequences of MIR100HG expression in HCC cells. Collectively, our findings identify MIR100HG as a hypoxia-associated oncogenic regulator that enhances tumorigenic phenotypes and promotes survival signaling in hepatocellular carcinoma. These results highlight MIR100HG as a potential biomarker and therapeutic target in liver cancer and provide new insights into the molecular mechanisms underlying hypoxia-driven tumor progression.
Recent research has focused on gut bacteria in colorectal cancer, but the influence of other microbiota, including oral and nonbacterial gut microbiota, on treatment efficacy remains insufficiently explored. This study aimed to investigate their relationship with the efficacy of neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC). Saliva and fecal samples were collected from patients with LARC before treatment. Shotgun metagenomic sequencing was used to profile bacterial, archaeal, eukaryotic, and viral taxonomic groups and to examine oral and gut microbial functions. An artificial intelligence-based prediction model was developed by integrating oral and gut microbiome data with clinical information. Statistical analyses compared diversity and response-associated microbial features between responders and non-responders to nCRT. Response-associated differences were observed in bacterial and nonbacterial taxonomic profiles and in oral and gut microbial functional profiles. In the internal test subset, the integrated analysis yielded an observed AUC of 0.917. Given the small cohort and the exploratory comparison of candidate classifiers, this estimate requires confirmation in larger, independent cohorts. Baseline oral and gut microbiome profiles were associated with response to nCRT. Integrating microbiome and clinical features showed potential for response prediction, but the model remains exploratory and requires validation in larger, independent cohorts before clinical application. Retrospectively registered on 01/08/2026, NCT07346729.
Vegetable legumes are nutritionally and ecologically important crops. However, their genetic improvement has not kept pace with the increasing challenges posed by climate change due to the polygenic nature of stress tolerance, narrow genetic diversity, and the persistent gap between molecular discoveries and field-level cultivar development. Although recent reviews have examined individual genomic tools or specific stress responses, a comprehensive synthesis integrating genomics-assisted breeding, multi-omics technologies, genome editing, and speed breeding within a unified crop improvement framework has been lacking. This review addresses that gap by critically evaluating how these complementary approaches can accelerate the development of stress-resilient vegetable legumes, including pea, common bean, cowpea, faba bean, cluster bean, yard-long bean, and hyacinth bean. This review synthesizes advances in QTL mapping, genome-wide association studies, transcriptomics, metabolomics, and CRISPR-based functional genomics that have identified key regulators and pathways underlying resistance to major biotic and abiotic stresses. Rather than considering these technologies independently, the review emphasizes their convergence into a systems-level breeding framework integrating genomic discovery, functional validation, predictive breeding, and accelerated generation advancement to improve breeding efficiency. Speed breeding, enabling up to seven to eight generations annually under optimized controlled-environment experimental conditions in cowpea, is discussed as a complementary strategy with genomic selection and genome editing. The review further identifies major translational bottlenecks, including transformation recalcitrance, limited genomic resources for underutilized vegetable legumes, inadequate multi-environment validation, and fragmented omics integration, and presents an integrated systems-breeding framework to bridge the gap between gene discovery and cultivar development.
Breast cancer (BC) is the second most prevalent malignancy after lung cancer, and the life expectancy is still very low due to therapeutic resistance and tumor relapse. It is crucial to identify novel biomarkers that can serve as potential therapeutic targets. In TNBC, aberrant activation of EGFR has also been implicated in the development of drug resistance. STK35L1 is a critical regulator of diverse cellular processes, including apoptosis and DNA damage. Notably, STK35L1 promotes drug resistance and regulates glycolysis and apoptosis through AKT signaling. The oncogenic role of STK35L1 is established in various cancers, including osteosarcoma, colorectal cancer, and acute myeloid leukemia. However, its association in BC has not yet been explored. In this study, we found that STK35L1 was significantly upregulated in multiple cancers, and its higher expression was associated with poor survival outcomes in BC patients. STK35L1 was differentially upregulated across all BC subtypes. An association between EGFR and STK35L1 expression was observed in normal breast tissues but not in BC. Interestingly, compared with normal breast tissue, EGFR mRNA expression is downregulated in BC tissues, with the greatest downregulation in the luminal B subtype and the least in TNBC. Furthermore, EGFR inhibition with gefitinib increased STAT3 phosphorylation at Tyr-705, and STK35L1 and EGFR gene expression were significantly upregulated. These data suggest that EGFR-STAT3 signaling may regulate STK35L1 and EGFR expression. In conclusion, we report an association of STK35L1 and EGFR in BC, highlighting STK35L1 as a potential prognostic biomarker and therapeutic target.
Drought stress severely constrains the growth, yield, and accumulation of bioactive compounds in Dendrobium officinale (D. officinale), a valuable medicinal orchid, and this challenge is exacerbated under simulated wild cultivation where plants are inevitably exposed to recurring water deficits. Basic helix-loop-helix (bHLH) transcription factors are well-established regulators of plant abiotic stress responses. However, the molecular mechanisms by which bHLH transcription factors respond to drought stress in this species remain largely unknown. In this study, a bHLH transcription factor gene, DobHLH25, was cloned from D. officinale. Phylogenetic analysis revealed that DobHLH25 shares the highest sequence identity with its ortholog in Dendrobium nobile. Additionally, subcellular localization analysis indicated that DobHLH25 is targeted to the nucleus and possesses a functional transcriptional activation domain. Expression pattern analysis showed that DobHLH25 is most abundantly expressed in old leaves, and its expression in roots, stems, and leaves is induced by polyethylene glycol treatments. Heterologous expression of DobHLH25 in Arabidopsis thaliana resulted in higher seed germination rates and longer root lengths under mannitol-induced osmotic stress compared to wild-type plants. Under drought stress, DobHLH25 heterologous expression lines exhibited higher survival rates, reduced leaf water loss, lower malondialdehyde accumulation, and increased proline content. Moreover, the activities of antioxidant enzymes such as superoxide dismutase and peroxidase were significantly enhanced, and the expression levels of multiple drought-responsive genes were markedly upregulated. Collectively, these findings suggest a correlation between DobHLH25 expression and plant drought tolerance, as evidenced by reduced oxidative damage, increased osmolyte accumulation, enhanced antioxidant enzyme activities, and upregulation of drought-responsive genes. Together, these results suggest that DobHLH25 plays a positive role in drought tolerance, and provides a basis for future dissection of its regulatory network in D. officinale.
Alkaline stress severely constrains the physiological metabolism and growth and development of rice through high pH and ionic toxicity. Domains of unknown function (DUF) play significant roles in plant stress responses. However, the function of the DUF1719 family (PF08224) in rice has not been reported and further research is needed. This study systematically identified the OsDUF1719 gene family in rice and investigated the function of OsDUF1719.8 under alkaline stress. The results demonstrate that the rice DUF1719 family comprises 13 protein members, all containing the PF08224 domain. It is predicted that this domain may play a role in ATPase activation. Evolutionary analysis divided DUF1719 proteins from eight grass species into six subgroups, with highly conserved gene structures, motifs, and tertiary architectures within each subgroup. Promoter analysis indicated enrichment of stress- and hormone-responsive elements, implying broad involvement in stress regulation. Expression analysis revealed that several genes, including OsDUF1719.5 and OsDUF1719.8, were upregulated under multiple abiotic stresses. Notably, OsDUF1719.8 was strongly induced during early alkaline stress. Consequently, we further analyzed the function of OsDUF1719.8 in the rice alkaline stress response. The results demonstrate that overexpression of OsDUF1719.8 enhanced rice alkaline tolerance, whereas knockout mutants exhibited stress sensitivity. OsDUF1719.8 enhances rice tolerance to alkaline stress by coordinately regulating reactive oxygen species metabolism, promoting the accumulation of osmotic adjustment compounds, and modulating ion homeostasis. This study provides the first systematic identification of the DUF1719 family and elucidates the function of OsDUF1719.8 in positively regulating rice alkaline tolerance, offering a novel gene for alkali-tolerant molecular breeding of rice.
Myocardial infarction (MI) remains a major global cause of morbidity and mortality, with a particularly high burden among individuals with type 2 diabetes mellitus (T2DM). Host genetic factors play a significant role in modulating individual susceptibility to MI by influencing lipid metabolism and immune-mediated inflammatory pathways. The proprotein convertase subtilisin/kexin type 9 (PCSK9) gene is a key regulator of cholesterol homeostasis, while C–C motif chemokine ligand 22 (CCL22) is involved in immune cell recruitment and vascular inflammation. In this study, we investigated the association of PCSK9 rs505151 and rs11591147 and CCL22 rs4359426 polymorphisms with MI risk in a South Indian population. This case–control study included 400 participants categorized into controls (n = 100), MI (n = 100), T2DM (n = 100), and MI with T2DM (n = 100). Significant differences in clinical and biochemical parameters, including lipid indices and cardiometabolic risk markers, were observed between groups (p < 0.05). Genetic analysis revealed a significant association between the PCSK9 rs505151 variant and MI susceptibility across allelic and genotypic distributions, with significant effects under dominant and recessive inheritance models. Multivariable logistic regression confirmed that the rs505151 risk genotype was independently associated with MI after adjustment for age, sex, body mass index, and smoking status. In contrast, PCSK9 rs11591147 was rare and showed no significant association. The CCL22 rs4359426 polymorphism showed limited evidence of association with MI, with a significant effect observed only under the dominant inheritance model. Furthermore, combined analysis using a genetic risk score suggested that cumulative genetic burden involving PCSK9 and CCL22 variants was associated with an increased risk of MI. Overall, our findings suggest that genetic variation in lipid-regulatory and immune-related pathways may contribute to MI susceptibility in South Indians. Further studies are warranted to validate these associations and clarify their biological and clinical relevance.
Female reproductive disorders (FRDs), including polycystic ovary syndrome, endometriosis, uterine leiomyomata, and infertility, have been epidemiologically associated with impaired pulmonary function. However, it remains unclear whether this cross-organ link reflects shared genetic etiology and, if so, which cellular mechanisms mediate it. We performed a systematic genome-wide cross-trait analysis of three FRDs and lung function traits (FEV₁, FVC, FEV₁/FVC) using GWAS summary statistics from individuals of European ancestry, integrating genetic correlation, bidirectional causal inference, pleiotropy mapping, and single-cell enrichment analyses. We identified significant negative genetic correlations between FRDs and lung volume traits, most prominently for FVC (rg range: − 0.077 to − 0.178). Bidirectional causal analyses indicated that FRDs have a detrimental effect on lung volume, with higher FRD genetic liability associated with reduced lung volume. Cross-trait meta-analysis identified 17 pleiotropic variants across 11 loci, with the 19q13.2 (LTBP4) and 12q13.13 (HOXC6/HOXC9) loci showing strong evidence of shared causal variants. Critically, single-cell analyses revealed that shared genetic risk converged on mesenchymal lineages across organs, specifically alveolar adventitial fibroblasts in the lung and stromal/smooth muscle cells in the endometrium. Transcriptome-wide analyses further nominated the estrogen-responsive gene RERG as a convergent gene linking these conditions with lung function. Our study revealed a shared genetic architecture between female reproductive disorders and lung function traits, providing a basis for further mechanistic investigations and potential clinical evaluation. Furthermore, our findings suggest that shared fibroproliferative and hormone-responsive pathways may offer insights into the biological mechanisms underlying these conditions.
CRISPR-Cas9 gene-editing technology has advanced pharmacological research by enabling targeted genetic modification for disease modeling, therapeutic development, and precision medicine. This review discusses the applications of CRISPR-Cas9 in drug discovery, personalized therapy, cancer drug resistance research, genetic disorders, and antimicrobial resistance. By editing disease-associated genes, CRISPR-Cas9 supports the development of patient-specific therapeutic strategies and more accurate preclinical models. In cancer, CRISPR-Cas9 is used to investigate the target genes involved in treatment resistance, while in genetic disorders, it offers potential mutation-correcting approaches, with the most robust clinical evidence currently seen in selected hemoglobinopathies. CRISPR-based strategies also hold promise for restoring antibiotic susceptibility by targeting genes that confer antibiotic resistance. Despite these advances, clinical translation remains limited by off-target effects, delivery challenges, immune responses, long-term safety concerns, and ethical and regulatory issues. Continued improvements in editing precision, delivery systems, and governance frameworks are essential for responsible clinical integration. Overall, CRISPR-Cas9 represents a vital platform for future pharmacological innovation, but its broad clinical use may require further validation of safety, efficacy, durability, and accessibility.
Abiotic stress has a significant impact on soybean growth, development, and yield. Proteins containing the Regulator of Chromosome Condensation 1 (RCC1) domain, known as RCPs, play important roles in plant stress responses. However, systematic analysis of the RCP gene family in soybean remains limited. In this study, a total of 52 GmRCP genes were identified in the soybean genome and classified into nine phylogenetic clades. Members within the same clade exhibited similar domain architectures. Collinearity analysis suggested that segmental duplication served as the major driver for the expansion of this gene family, and most duplicated gene pairs underwent purifying selection. Analysis of gene structure and conserved motifs revealed high conservation within clades but divergence among them, indicating potential functional diversification of GmRCPs. Furthermore, promoter analysis identified abundant cis-acting elements associated with hormone signaling and stress responses. Expression profiling demonstrated that most GmRCP genes were expressed across various soybean tissues, and several members were responsive to salt, drought, and low-phosphorus stresses. Notably, GmRCP31, GmRCP43, and GmRCP46 were induced under multiple stresses, suggesting their potential roles in stress adaptation. These findings provide important insights into the functional diversity and evolutionary history of GmRCP genes and establish a foundation for further investigation of their roles in soybean development and stress resistance.
Cold stress limits alfalfa (Medicago sativa) growth and persistence, but public transcriptomic datasets differ widely in genotype, tissue, treatment duration, and experimental design. We integrated RNA-seq data from ten independent BioProjects using a common processing workflow while retaining project-specific structures. A recurrent contrast-level DEG-derived pool of 4,354 genes was ranked by random forest using expression profiles from 240 samples. The original model showed strong internal discrimination (OOB ROC–AUC = 0.937), whereas fully nested leave-one-BioProject-out validation yielded an accuracy of 0.729, balanced accuracy of 0.676, and ROC–AUC of 0.727. PlantTFDB annotation identified MsG0680033896.01, MsG0680033848.01, and MsG0480021906.01 as the three highest-ranked transcription factors. The first two candidates showed greater stability in project-held-out and alternative machine-learning analyses. In project-aware multilevel meta-analysis, neither the primary 50-contrast analysis nor the 54-contrast sensitivity analysis identified genome-wide significant transcripts after Benjamini–Hochberg correction. However, MsG0680033896.01 and MsG0680033848.01 showed predominantly positive effects, positive pooled estimates, and confidence intervals excluding zero in both analyses, whereas MsG0480021906.01 showed weaker directional consistency. Co-expression, promoter prediction, chromosomal localization, and AlphaFold3 modeling provided additional computational context, including localization of the two leading candidates within a Chr6 CBF/DREB1-like-enriched region. These results prioritize MsG0680033896.01 and MsG0680033848.01 as high-confidence computational candidates and retain MsG0480021906.01 as an additional project-sensitive candidate for future functional testing.
Precision medicine requires computational methods that can integrate genomic, transcriptomic, proteomic, metabolomic, epigenomic, single-cell and spatial measurements into decisions about individual patients, and artificial intelligence has become the enabling technology for doing so. This review argues that the binding constraint is no longer modelling capability but validation, calibration and governance. We compare seventeen multi-omics integration algorithms on the sample sizes they actually require and on whether independent groups have reproduced them; we set classical machine learning against deep learning by omics task and sample-size regime, and find that penalised regression and tree ensembles remain competitive wherever the number of samples is small relative to the number of features. We then examine seven documented failures of deployed clinical artificial intelligence, trace each to its root cause, and derive an eighteen-item appraisal checklist adapting existing reporting and risk-of-bias instruments to the failure modes of molecular data. Calibration, uncertainty quantification, batch effects and information leakage are treated as first-class problems rather than caveats. To show what leakage costs, we analysed 696 breast tumours with matched transcriptomic and copy-number profiles under randomly permuted labels, where the only honest result is chance. A pipeline that selects features before splitting the data reports an area under the receiver operating characteristic curve of 0.95 in cohorts of forty and 0.65 on the full cohort; the corresponding leak-free pipeline returns 0.50 at every size. What limits clinical adoption is the evidence a model can be held to, not the sophistication of the model.
Ischemic stroke is a major cause of disability and mortality worldwide, but its underlying pathogenic mechanisms remain elusive. Although cellular senescence has been implicated in a wide range of age-related diseases, its specific contribution through endothelial cells to ischemic stroke pathogenesis remains unclear. To address this gap, the present study adopted an integrative strategy, combining single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (RNA-seq), to systematically characterize the senescent endothelial landscape in ischemic stroke. We identified a distinct senescence-associated gene signature in endothelial cells and highlighted four key genes-- Arhgap31, Tm4sf1, Itm2a, and Vwa1--that were closely associated with ischemic stroke pathogenesis. These genes showed differential expression and apparent discriminatory potential in the discovery bulk RNA-seq dataset, and external validation using independent scRNA-seq and cerebral microvessel bulk RNA-seq datasets provided additional support for the signature, particularly for Arhgap31, Tm4sf1, and Vwa1. Pathway enrichment and transcription factor analyses suggested potential pathways and upstream regulators associated with these candidate genes. In vitro experiments confirmed the differential expression of Arhgap31, Tm4sf1, Itm2a, and Vwa1 in senescent endothelial cells. Reduced expression of Arhgap31 attenuated endothelial cell senescence while enhancing migration and vasculogenesis capabilities. Arhgap31 may emerge as a potential target for ameliorating endothelial cell senescence and promoting tissue repair. Moreover, Connectivity Map analysis predicted several candidate compounds with expression profiles opposing the disease-associated signature, providing hypotheses for future pharmacological validation. Our findings highlight the contribution of endothelial cell senescence to post-ischemic endothelial dysfunction and inflammatory remodeling, supporting further investigation of this process in ischemic stroke pathogenesis. This work provides crucial insights into the interplay between cellular senescence and cerebrovascular disease, opening new avenues for precision medicine interventions in ischemic stroke management.
Salmonella enterica serovar Typhi (S. Typhi) is the aetiologic agent of typhoid fever in humans. The burden of typhoid is highest in low- and middle-income countries such as Pakistan. Moreover, the increasing emergence of antibiotic-resistant and hypervirulent S. Typhi strains highlights the need for deeper genomic understanding as current treatment regimens become progressively less effective. Therefore, this study analyzed publicly available S. Typhi genomes from Pakistan to characterize genomic diversity, sequence types, plasmid content, and antimicrobial resistance and virulence profiles. Subsequently, pangenome analysis identified conserved core proteins, which were screened via reverse vaccinology to prioritize potential vaccine candidates. Analysis of 71 high-quality S. Typhi genomes identified ST-1 and ST-2 as the predominant sequence types, a finding aligned with global trends. While plasmids were detected in 32
Understanding the genetic regulation underlying host–microbiota interactions is key to elucidating how microbial communities influence host metabolism, immunity, and physiology. In this context, the main objective of this study was to integrate genomic, transcriptomic, and microbial data to identify shared regulatory variants, highlight key microbial taxa, and prioritize biological pathways related to lipid metabolism, immune function, and host metabolic adaptation across multiple tissues in 72 immunocastrated male Large White pigs (Sus scrofa). Expression quantitative trait loci (eQTL)-informed association analyses were performed to link the gut microbiota with host genetics. The analyses included microbial amplicon sequence variants (ASVs, ≥ 10
Nuclear receptor coactivator 3 (NCOA3) is associated with various cancers, but its function and mechanism in glioblastoma multiforme (GBM) are still unclear. Bioinformatics analysis, in vitro cell experiments (NCOA3 silencing (si-NCOA3) or NCOA3 small-molecule inhibitor SI-2), in vivo animal models, and metabolic level detection were used to elucidate the activity of NCOA3 in GBM. The data revealed that GBM tissues had NCOA3 overexpression, which was linked with poor prognosis. It regulates pathways related to glycolysis, the cell cycle, and immunosuppression. Functionally, si-NCOA3/SI-2 suppressed GBM cell proliferation and migration. In vivo, sh-NCOA3/SI-2 demonstrated anti-glioma effects. Metabolically, treatment with si-NCOA3/SI-2 reduced glucose uptake, pyruvate and lactate production, ATP levels, and glycolysis-related enzyme expression in GBM cells. Combination therapy with SI-2 and TMZ enhanced GBM cell sensitivity to TMZ. Single-cell RNA sequencing revealed high NCOA3 expression in glioma stem cells (GSCs). si-NCOA3 inhibited GSCs proliferation and self-renewal while reducing the expression of Nestin and SOX2. NCOA3 is an oncogene in GBM. In mechanism, NCOA3 promotes GBM progression by enhancing the Warburg effect. In addition, NCOA3 is also highly expressed in GSCs and significantly promotes their proliferation and self-renewal ability. NCOA3 may represent a promising therapeutic target for GBM.
Clear cell renal cell carcinoma (ccRCC) exhibits substantial molecular and clinical heterogeneity, contributing to variable disease progression and therapeutic outcomes. We previously identified a de-clear cell differentiation (DCCD) tumor state characterized by loss of canonical clear-cell features and aggressive clinical behavior. This study aimed to translate DCCD-associated biology into a prognostic framework and investigate its underlying molecular basis. Using TCGA-KIRC as the training cohort, we developed a five-gene prognostic signature comprising COL7A1, IGFN1, AJAP1, SMIM24, and ADGRV1, which consistently stratified patient survival across multiple public and institutional cohorts. Comparison with SSIGN, Leibovich, and ClearCode34-like models demonstrated that the DCCD signature provided complementary prognostic information. High-risk tumors exhibited enhanced proliferative and invasive programs, increased IL6-JAK-STAT3 pathway activity, and an immune-excluded microenvironment. Associations with treatment response were also observed in retrospective therapeutic cohorts. Integrated analyses of bulk and single-cell transcriptomics, spatial transcriptomics, tissue microarrays, CPTAC proteomics, and molecular interaction networks identified SMIM24 as an epithelial-associated factor linked to favorable outcomes and preserved metabolic programs. Functional experiments showed that SMIM24 overexpression suppressed migration, invasion, three-dimensional spheroid invasion, and clonogenic growth in ccRCC cells, accompanied by reduced JAK1 and STAT3 phosphorylation and decreased PD-L1 expression. Pharmacological activation of STAT3 with Colivelin partially restored PD-L1 expression in SMIM24-overexpressing cells. Collectively, these findings support the reproducibility of the DCCD-associated prognostic framework and identify SMIM24 as a candidate suppressor of ccRCC aggressiveness and PD-L1 expression, potentially acting in part through reduced STAT3 activation.
The genus Serratia encompasses metabolically versatile and ecologically significant bacteria, yet the genomic and biosynthetic potential of Serratia rubidaea remains largely unexplored compared to the well-studied S. marcescens. In this study, we present a comprehensive genomic characterization of S. rubidaea MJ24, a pigment-producing strain isolated from the Western Ghats, India. The 4.98 Mb genome (GC content: 59.22
