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PubMed2026

Sodium Overload-Related Molecular Subtypes and a Four-Gene Prognostic Signature Predict Survival, Immune Landscape, and Therapeutic Response in Acute Myeloid Leukemia.

Sodium overload has recently emerged as a critical metabolic stressor involved in cancer progression; however, its molecular characteristics and clinical relevance in acute myeloid leukemia (AML) remain unexplored. RNA-seq data sets, clinical annotations, and mutational profiles of AML patients were annotations from The Cancer Genome Atlas and integrated with Genotype-Tissue Expression normal samples. Sodium overload-related genes (SORGs) were obtained from GeneCards. Differentially expressed SORGs (DESORGs) screened by applying the limma statistical model, followed by univariate Cox proportional hazards regression, consensus clustering, functional enrichment, immune infiltration analysis, and pathway evaluation. A prognostic signature was developed through least absolute shrinkage and selection operator regression followed by multivariate Cox modeling. The model's performance was further verified in two external GEO data sets (GSE71014 and GSE37642). Nomogram construction, subgroup analysis, tumor mutational burden (TMB) assessment, drug sensitivity prediction, transcription factor (TF) analysis, and competing endogenous RNA (ceRNA) network analyses were also performed. A total of 57 DESORGs were identified, and 2 sodium overload-related molecular subtypes exhibited distinct survival, immune infiltration, and inflammatory pathway activation. A robust four-gene signature (DOCK1, GABRE, HTR7, ACSM1) stratified patients into high- and low-risk categories with significantly different survival across training and validation cohorts. High-risk patients displayed increased immune infiltration, higher TMB, reduced sensitivity to multiple chemotherapeutic drugs, and inferior predicted response to PD-L1 blockade. TF and ceRNA networks revealed multilayered transcriptional and post-transcriptional regulation of the signature genes. This study identifies sodium overload-related molecular heterogeneity in AML and establishes a validated four-gene prognostic signature that integrates genomic, immunologic, and therapeutic features, offering potential utility for personalized risk assessment and treatment optimization.

Humans↗
PubMed2026

Integrated analysis reveals the impact of obesity on triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is a highly aggressive and heterogeneous breast cancer subtype with limited therapeutic options. While the prevalence of overweight/obese (OW/OB) women continues to rise, the impact of obesity on molecular features of TNBC remains incompletely understood. We investigated clinicopathological and molecular data (including genomic, transcriptomic, proteomic and metabolomic profiling) using our original multi-omics database of TNBC (N = 465) for associations with patient body mass index (BMI). Multi-omics profiling revealed that OW/OB patients exhibited worse survival as well as elevated inflammation of tumor microenvironment, higher expression of immune checkpoints, and dysregulated lipid metabolism. Our in vivo experiments demonstrated that tumors in obese mice displayed faster growth rates, a higher proportion of PD-1+CD8+ T cells and enhanced responsiveness to anti-PD-1 treatment. In addition, we analyzed data from four independent clinical trials and discovered that OW/OB patients demonstrated higher pathological complete response rates and longer progression-free survival following anti-PD-1-based immunotherapy. In conclusion, our study systematically revealed that obesity is associated with coordinated immune-metabolic remodeling in TNBC, characterized by checkpoint enrichment and lipid dysregulation, which may help explain the enhanced anti-PD-1 responsiveness and should be taken into account in the field of precision medicine.

Immunity↗
PubMed2025

Multi-omics reveals an ecdysone-activated Eip75B-FABP signaling axis coordinating nutrient metabolism for development in Hermetia illucens.

INTRODUCTION: Efficient nutrient storage is essential for insect development and energy homeostasis; however, the mechanisms coordinating nutrient allocation during ontogeny are not well understood. Elucidating these systems may yield valuable insights to insect metabolic adaptation. OBJECTIVES: This study aimed to identify regulatory modules governing nutrient metabolism in insects, focusing on hormonal and metabolic interplay. METHODS: Multi-omics profiling (proteomics, phosphoproteomics, and transcriptomics) was conducted throughout the life cycle, from egg to adult, to identify metabolic regulators. RNAi was utilized for gene knockdown, followed by qRT-PCR and mitochondrial DNA quantification to evaluate knockdown efficiency and its metabolic implications. Assessments of nutrient metabolism were performed using assays for triglycerides, crude protein, and fatty acid synthase. EMSA and BODIPY staining examined transcriptional regulation and lipid droplet dynamics. RESULTS: Utilizing an integrative multi-omics approach, this study elucidates the temporal metabolic regulators in insects. A conserved regulatory module was identified in which the PPAR homolog, ecdysone-induced protein 75B (Eip75B), functions as a transcriptional activator of fatty acid binding protein (FABP), sustaining lipid metabolic homeostasis during the larval stage. PPARγ modulators (rosiglitazone and GW9662) alter lipid accumulation, along with the expression of Eip75B and FABP, which was measured by qRT-PCR. Furthermore, the deficiency of FABP may reprogram metabolic pathways by inhibiting lipid storage and promoting mitochondrial β-oxidation, as supported by increased mitochondrial DNA copy number, as well as enhancing protein synthesis. This metabolic change could be modulated by ecdysone signaling, as hormonal supplementation effectively rescued the lipid loss phenotype. Our results establish the ecdysone-Eip75B-FABP signaling axis as a central regulatory module that integrates hormonal and nutrient-sensing signals to control insect nutritional metabolism. CONCLUSION: The ecdysone-Eip75B-FABP axis integrates hormonal and nutrient signals to regulate metabolic plasticity, underscoring a universal strategy for developmental energy allocation. The data also offer potential implications for research on metabolic disorders and bioenergy applications.

Animals↗
PubMed2026

CD36 Influences Leukemia Progression in MLL-AF9-Driven AML by Modulating the Leukemia Immune Microenvironment.

CD36, a fatty-acid translocase, is increasingly implicated in acute myeloid leukemia biology and treatment resistance, yet its contribution to leukemogenesis is still unclear. Using the MLL-AF9 model, we transduced hematopoietic stem/progenitor cells (HSPCs) from Cd36-knockout (KO) or wild-type (WT) mice and assessed leukemic potential with in vitro assays, transplants, and transcriptomic, metabolomic, and immune profiling. Both Cd36KO- and Cd36WT-HSPCs underwent efficient MA9-driven transformation, with comparable colony formation and Hox/Meis1 pathway activation, indicating Cd36 is dispensable for leukemic initiation. However, Cd36 deletion markedly attenuated disease progression, reducing leukemic burden and extending survival in irradiated mice (median 22 vs. 15 days, P = 0.001). Effects were strikingly amplified in immunocompetent, non-irradiated recipients (median 63 vs. 22 days, P = 0.002), revealing immune-dependent suppression. Immune profiling showed enhanced CD4⁺ and CD8⁺ T cell infiltration, reduced CD4⁺CD25⁺ regulatory-like cells, and lower Tim-3 expression in Cd36KO-MA9 spleens, consistent with a less exhausted, more effective anti-leukemic T cell response. Despite enhanced T cell infiltration, TCR repertoires remained conserved, indicating functional reprogramming rather than clonal selection. Consistent with a suppressive leukemia immune microenvironment, RNA-seq gene set enrichment analysis identified upregulation of inflammatory (TNFα/NF-κB) and hypoxic pathways in Cd36WT-MA9 cells. Untargeted metabolomics revealed metabolic shifts in Cd36KO cells, involving a reduction in three key metabolites, UDP-GlcNAc, UDP-Galactose/UDP-Glucose, and O-Phospho-L-Serine, that likely support an immune evasion mechanism. These findings demonstrate that while Cd36 is not essential for MLL-AF9-mediated transformation, its cell-intrinsic expression in leukemic cells suppresses anti-leukemic immunity and accelerates progression. This positions CD36 as a promising target to enhance immune surveillance and limit AML aggressiveness.

Acute Myeloid Leukemia (AML)↗
PubMed2026

Intratumoral collagen correlates with histological grade and patient prognosis in breast cancer.

Histological grading, using the Nottingham Grading System (NGS), is a major prognostic indicator for breast cancer. NGS involves the scoring of cancer cell-related morphological features, yet it overlooks tumor microenvironment (TME) components such as collagen. Collagen proteins, integral to the extracellular matrix (ECM), influence tumor architecture and progression but their relationship with histological grade is not fully characterized. Here, we assessed intratumoral collagen deposition using Masson Trichrome staining of whole slides (n = 166), proteomic profiling (n = 2) and transcriptomic analyses of the METABRIC (n = 1827) and TCGA-BRCA (n = 753) cohorts. We showed that low-grade tumors display significantly higher intratumoral collagen deposition compared to high-grade tumors. Moreover, we demonstrated that collagen expression at the transcript and protein levels (Masson Trichrome) could discriminate Grade II carcinomas into distinct prognostic groups, in which patients with Grade II carcinomas with elevated levels of collagen expression were associated with lower pTNM stage and better survival outcomes. Our results support the inclusion of TME features, such as collagen deposition, to enhance prognostic accuracy in breast cancer.

Humans↗
PubMed2026

A pro-inflammatory metastasis-associated macrophage subset induces tumor-promoting mesothelial cell conversion in ovarian cancer via IL-1α secretion.

Tumor-associated macrophages (TAMs) are key regulators of the tumor microenvironment, yet the functional specialization of TAM subsets in metastatic progression remains incompletely defined. Here, we characterized distinct TAM populations contributing to tumor-promoting mesothelial cell conversion in high-grade ovarian carcinoma using single-cell RNA sequencing of patient-derived macrophages from ascites (ascTAMs) and omental metastases (omTAMs). TAMs from these anatomical sites were clearly distinguishable by polarization states, with omTAMs exhibiting a mixed M1⁺/M2⁺ phenotype, in contrast to the M1low/M2⁺ profile observed in ascTAMs. Transcriptomic analysis further revealed functional divergence of these subsets. Notably, omTAMs displayed gene signatures associated with mesothelial-to-mesenchymal transition (MMT), a critical process enabling tumor invasion across the peritoneal lining. Functionally, conditioned media from omTAMs, similar to that from classically activated M1 macrophages, induced MMT in primary mesothelial cells via TGFβ and ERK/p38 MAPK signaling pathways. This phenotypic transition enhanced transmesothelial tumor cell invasion. Proteomic analysis identified IL-1α as a key MMT-inducing factor secreted by pro-inflammatory macrophages. Mechanistically, IL-1α cooperates with TGFβ by activating an autocrine TGFβ/TGFBR1 feedback loop in mesothelial cells, thereby amplifying MMT. Consistent with these findings, IL1A expression was enriched in omTAM clusters across independent patient samples and was confirmed by immunohistochemical analysis of clinical samples. From a therapeutic perspective, our study identifies new avenues to counteract the mesothelial reprogramming driven by IL-1α⁺ TAMs, potentially impeding metastatic progression. Created in BioRender. Heidemann, S. (2026) https://BioRender.com/aeu6yd0 .

Female↗
PubMedDate not supplied

The use of phage display in the study of receptors and their ligands.

Phage display technology presents a rapid means by which proteins and peptides that bind specifically to predefined molecular targets can be isolated from extremely complex combinatorial libraries. There are several important ways by which phage display can provide impetus to receptor-based research. Firstly, phage display can be applied, alongside transcriptome and proteome expression profiling techniques, to the identification and characterisation of receptors whose expression is specific to either a cell lineage, a tissue or a disease state. Secondly, specific monoclonal antibodies that enable researchers to identify, localize and quantify receptors can be produced very rapidly (weeks). Thirdly, it should be possible to apply phage display to the matching of orphan ligands and receptors. Finally, phage display can be used to identify proteins and peptides that modulate receptor activity. As well as being useful in the study of receptor function, biologically active proteins and peptides could also be used therapeutically, or as leads for drug design. Hence phage display is ready to play a central role in the study of receptors in the post-genome era. This review outlines the ways in which phage display has been applied to the study of receptor-ligand systems, and discusses how new developments in the technology may be of even greater utility to the field in the next decade.

Animals↗
PubMed2025

Iterative, multimodal, and scalable single-cell profiling for discovery and characterization of signaling regulators.

Cell signaling plays a critical role in regulating cellular state, yet uncovering regulators of signaling pathways and understanding their molecular consequences remains challenging. Here, we present an iterative experimental and computational framework to identify and characterize regulators of signaling proteins, using the mTOR marker phosphorylated RPS6 (pRPS6) as a case study. We present a customized workflow that uses the 10x Flex assay to jointly profile intracellular protein levels, transcriptomes, and CRISPR perturbations in single cells. We use this to generate a "glossary" dataset of paired protein-RNA measurements across targeted perturbations, which we leverage to train a predictive model of pRPS6 levels based solely on transcriptomic data. Applying this model to a genome-wide Perturb-seq dataset enables in silico screening for pRPS6 and nominates novel regulators of mTOR signaling. Experimental validation confirms these predictions and reveals mechanistic diversity among hits, including changes in signaling output driven by anabolic activity, cellular proliferation and multiple stress pathways. Our work demonstrates how integrated experimental and computational approaches provide a scalable framework for multimodal phenotyping and discovery.

Journal Article↗
PubMed2025

The chloroplast 16S rRNA dimethyltransferase BrPFC1 is required for Brassica rapa development under chilling stress.

Chloroplast ribosomal RNA (Ch-rRNA) methylation is critical for plant development and response to low temperatures. Several Ch-rRNA methyltransferases and their catalytic modes, as well as biological relevance, have been reported in model plant species. However, Ch-rRNA methyltransferases and their functional significance remain poorly characterized in crops, including leafy vegetables such as Chinese cabbage. In this study, we screened an EMS-mutagenized Chinese cabbage population and identified a yellow inner leaf (yif) mutant. This mutant develops yellowing inner leaves with reduced chlorophyll accumulation and ultrastructure-impaired chloroplasts under low-temperature conditions. Genetic analysis revealed a premature termination mutation in BrPFC1, encoding the chloroplast-localized 16S rRNA dimethyltransferase. The BrPFC1 mutation (yif) disrupts the dimethylation of 16S rRNA. The cold-sensitive phenotype of the yif mutant can be explained by temperature-dependent defects in the maturation and assembly of chloroplast ribosomes at 4°C. Through integrated analysis of chloroplast and nuclear transcriptomes coupled with translational profiling at 25°C and 4°C, we established that low temperature preferentially upregulates transcripts encoding nuclear-derived ribosomal proteins, while defective 16S rRNA specifically compromises the translational efficiency of chloroplast-encoded photosynthetic complex and ribosomal protein at 4°C. These findings establish rRNA modification by BrPFC1 as a critical regulatory layer for optimizing chloroplast translational efficiency at 4°C, providing mechanistic insights into post-translational adaptation strategies in Chinese cabbage.

Chloroplasts↗
PubMed2026

Beyond Canonical Neoantigens: Emerging Technologies for Identification of Noncanonical Antigens and Implications for Personalized Cancer Vaccines.

Over the past decade, advances in sequencing technologies and computational pipelines enabled the development of personalized cancer vaccines (PCVs). Current PCV strategies primarily target cancer neoantigens generated by non-synonymous DNA mutations, which can result in altered amino acid sequences capable of eliciting tumor-specific immune responses. More recently, a distinct class of tumor-specific antigens (TSA), termed noncanonical or cryptic antigens, has emerged as an additional source of immunogenic targets. Unlike canonical neoantigens, noncanonical antigens typically cannot be identified by tumor/normal whole-exome sequencing, as they do not arise from classical DNA mutations. Instead, they are often associated with less well recognized and/or aberrant processes in the pathways from DNA to human leukocyte antigen (HLA)-presented peptides. Examples include transposable elements, circular RNA, translation of alternative open reading frames and/or long non-coding RNA, among others. Emerging evidence suggests that noncanonical antigens represent a substantial portion of the tumor-specific immunopeptidome and, similar to canonical neoantigens, are absent during thymic selection and can evade central tolerance and elicit T cell responses. Technological advances have increasingly facilitated the identification of noncanonical antigens. Long-read RNA sequencing reveals noncanonical transcripts by improving transcriptome assembly, while ribosome profiling provides genome-wide maps of actively translated regions, facilitating the discovery of peptides from aberrant translation events. Specialized molecular approaches enable enrichment and sequencing of circular RNAs, and immunopeptidomics using mass spectrometry allows for direct characterization of HLA-presented peptides. Together, these technological advances have led to an increasing interest in prioritizing and targeting noncanonical antigens in the next generation of PCVs. This review provides an overview of the diverse origins of TSAs beyond classical neoantigens and discusses emerging approaches that may enable the integration of these antigens in future clinical trials.

circular RNA↗
PubMed2026

CCT2 defines a highly cisplatin-resistant and poor-prognosis subtype of lung adenocarcinoma.

Cisplatin-based chemotherapy is a standard treatment for lung adenocarcinoma (LUAD), yet acquired cisplatin resistance remains a marked cause of treatment failure. The molecular mechanisms driving cisplatin resistance in LUAD have not been fully elucidated. The present study integrated bulk transcriptomic data, genomic mutation profiles and single-cell RNA sequencing data to systematically investigate cisplatin resistance in LUAD. Resistance-associated genes were identified through differential expression, survival analysis and database integration. Unsupervised clustering was used to define cisplatin resistance-associated subtypes. Functional characteristics were explored using pathway enrichment, immune infiltration, tumor mutation burden and weighted gene co-expression network analysis. A machine learning framework incorporating 101 algorithms was applied to identify key genes and construct a prognostic model. Single-cell analyses and in vitro experiments were performed to validate the biological role of the core gene. Molecular docking and molecular dynamics simulations were conducted to identify potential therapeutic compounds. A total of two molecular subtypes with distinct cisplatin resistance levels and prognostic outcomes were identified. The high-resistance subtype exhibited enhanced cell cycle activity, DNA repair signaling and immune heterogeneity. Machine learning analysis revealed a five-gene signature, with chaperonin-containing TCP1 subunit 2 (CCT2) emerging as a key regulator of cisplatin resistance. Single-cell analyses showed that CCT2 was predominantly enriched in resistant epithelial cell subpopulations. Functional experiments demonstrated that CCT2 knockdown significantly inhibited cell proliferation and enhanced cisplatin sensitivity in LUAD cell lines. A number of candidate compounds targeting CCT2 exhibited stable binding in silico. The present findings identified CCT2 as a key mediator of cisplatin resistance in LUAD and provided potential therapeutic strategies to overcome chemotherapy resistance.

chaperonin-containing TCP-1 subunit 2↗
PubMed2026

The ASH HematOmics Program supports integrative analysis of genomic and clinical data in hematologic diseases.

The increasing availability of genomic and transcriptomic sequencing has uncovered diverse genomic alterations and distinct gene expression profiles driving hematologic diseases, yet a data integration and sharing platform dedicated to hematology remains lacking. We developed the American Society of Hematology (ASH) HematOmics Program (ASHOP; ashop.hematology.org), a resource for exploring somatic alterations and gene fusions, transcriptomic results, and clinical data from 5960 patients spanning B-cell precursor and T-cell acute lymphoblastic leukemia, acute myeloid leukemia, myelodysplastic syndromes, and chronic lymphocytic leukemia. Users can explore genomic alteration landscapes and comutation patterns via lollipop and matrix plots and analyze significantly altered genes in user-defined subcohorts. Transcriptomes can be explored through interactive uniform manifold approximation and projections, clustering, differential expression, and pathway enrichment. Genomic, transcriptomic features, and clinical outcomes can be correlated in a user-driven manner or combined to precisely define study cohorts. We illustrate the following 4 use cases of ASHOP: (1) stratification of DUX4-rearranged B-cell leukemias into Early/Multipotent and Committed subgroups with distinct outcomes, (2) characterization of HOXA/HOXB expression patterns in acute myeloid leukemias, (3) correlating mutational burden with mismatch repair deficiency and mutational signatures, and (4) investigation of TP53 alteration landscape. ASHOP is an open-access resource to inform genomic and transcriptomic data interpretation for hematologic malignancies and will expand to support additional diseases and data modalities from the ASH community.

Humans↗
PubMed2026

Integrative pooled transcriptomic analysis reveals shared and distinct molecular signatures in adult T-cell leukemia/lymphoma and peripheral T-cell lymphoma.

Adult T-cell leukemia/lymphoma (ATLL) and peripheral T-cell lymphomas (PTCLs) are aggressive neoplasms of mature T cells with poor prognosis and limited therapies. ATLL originates from HTLV-1 infection, while PTCL comprises heterogeneous subtypes without a defined etiologic factor. Comparative molecular profiling of these malignancies remains limited. We conducted an integrative pooled transcriptomic analysis of publicly available Gene Expression Omnibus (GEO) microarray datasets to compare ATLL, PTCL, and normal T-cell samples. Differential expression, functional enrichment, and protein-protein interaction (PPI) network analyses were performed using STRING, Cytoscape, and Gephi. Key hub genes and functional modules were further analyzed through KEGG and Enrichr databases. Comparative analyses revealed upregulation of extracellular matrix (ECM) components (COL1A1, COL3A1, FN1, SPARC, THBS1) and immune-regulatory molecules (CD163, CXCL12-CXCR4, complement subunits). Shared pathways included ECM-receptor interaction, focal adhesion, and PI3K-Akt signaling. PTCL showed enrichment in coagulation and angiogenesis, while ATLL displayed distinct enrichment of cytoskeletal, chemokine, immune-regulatory, and signaling-associated pathways. PPI networks identified ECM and chemokine signaling as key hubs, with subtype-specific modules related to immune regulation, proliferation, and metabolism. This integrative approach uncovers common and distinct oncogenic programs in ATLL and PTCL, emphasizing ECM remodeling and immune modulation as shared hallmarks. Hub genes such as COL1A1, FN1, and CXCL12-CXCR4 may represent candidate molecular signatures that warrant validation in independent patient cohorts and functional studies before their clinical utility can be established.

Humans↗
PubMed2025

RNA sequencing offers new diagnostic opportunities in neurodevelopmental disorders: A systematic review.

PURPOSE: Transcriptomics by way of RNA sequencing (RNAseq) has emerged as a means to increase the diagnostic yield in genetic conditions. In this systematic review, we focus on the contribution of transcriptomics to improve the diagnostic yield in neurodevelopmental disorders. METHODS: We performed a systematic literature search in PubMed until January 2024, including articles describing diagnostic RNAseq on at least 1 individual with a primary neurodevelopmental phenotype. We extracted data on cohort size, phenotype, sample tissue, previously used diagnostic methods, added diagnostic yield of RNAseq, the use of control samples, and technical aspects of the RNA sequencing methodology. RESULTS: A total of 17 articles were eligible for inclusion in the systematic review. We found an average added diagnostic yield of 15.5% through RNA sequencing for individuals with neurodevelopmental disorders. There is heterogeneity in the tissue type, reported quality measures, and the computational pipeline. CONCLUSION: The significantly increased diagnostic yield demonstrates the value of this novel tool in the diagnostic setting of neurodevelopmental disorders. Our results offer an overview of common methodologies for RNAseq and allow us to formulate recommendations for genetic labs and clinicians when implementing RNAseq as a diagnostic tool. Lastly, we provide recommendations for future publications to increase transparency and reproducibility.

Humans↗
PubMed2026

CoxFormer enables spatial omics inference with multimodal generative modeling.

Gene co-expression maps transcriptome-wide gene-gene relationships, yet high-quality estimates cover less than half the genome. Meanwhile, spatial omics either profiles restricted in situ panels or lacks cellular resolution. Extending co-expression transcriptome-wide could overcome these limitations by inferring unassayed gene expression at subcellular resolution. Here we show that CoxFormer integrates literature-derived gene knowledge with co-expression networks from bulk tissues and large-scale single-cell atlases to learn 512-dimensional representations for 32,016 human genes. These embeddings capture functional gene relationships and serve as a generative prior for spatial inference across platforms and modalities. Without requiring a matched single-cell RNA-sequencing reference, CoxFormer supports four applications beyond measured genes: histology-based expression imputation, gene activity prediction from chromatin accessibility, subcellular super-resolution inference, and pathological region detection. Together, CoxFormer extends gene embedding from gene- and cell-level tasks to whole-transcriptome spatial inference, providing a unified framework for biological analysis beyond the limited gene coverage of current spatial omics technologies.

Humans↗
PubMed2002

Integrating cancer genomics and proteomics in the post-genome era.

The dawn of the post-genome era is leading to extraordinary opportunities in biomedicine. Our group has embarked on a major effort to integrate genomics, transcriptomics and proteomics for the profiling of tumor tissues, an approach we refer to as operomics. Our major goals are the molecular classification of tumors and the identification of markers for the early detection of cancer. Molecular analyses of tumors rely on microdissected tissues, which are simultaneously investigated for genomic, transcriptomic and proteomic changes. Genomic alterations in tumor cells being investigated include deletions, amplifications and methylation changes across the entire genome as well as point mutations in specific genes. Expression analysis at the RNA level is being undertaken using oligonucleotide and cDNA based microarrays. An important aspect of our approach is the large-scale identification and quantitative analysis of tumor proteins in whole cell lysates as well as in protein compartments. Protein separation strategies include two-dimensional polyacrylamide gel electrophoresis and liquid chromatography. Specific protein subsets, of interest include membrane proteins, secreted proteins and antigenic proteins as sources of biomarkers for early detection of cancer. Our current approach is illustrated with findings stemming from our studies of human gliomas.

Brain Neoplasms↗
PubMed2003

Sex-dependent gene expression and evolution of the Drosophila transcriptome.

Comparison of the gene-expression profiles between adults of Drosophila melanogaster and Drosophila simulans has uncovered the evolution of genes that exhibit sex-dependent regulation. Approximately half the genes showed differences in expression between the species, and among these, approximately 83% involved a gain, loss, increase, decrease, or reversal of sex-biased expression. Most of the interspecific differences in messenger RNA abundance affect male-biased genes. Genes that differ in expression between the species showed functional clustering only if they were sex-biased. Our results suggest that sex-dependent selection may drive changes in expression of many of the most rapidly evolving genes in the Drosophila transcriptome.

Animals↗
PubMed2025

Interaction of host gene-gut microbiota in male grading of Macrobrachium rosenbergii.

UNLABELLED: The giant freshwater prawn (GFP; Macrobrachium rosenbergii), a crustacean of high nutritional and economic value, is crucial for aquaculture. During the same growth cycle, male GFPs develop into three distinct forms: small males, orange claw males, and blue claw males. These morphotypes display varying social behaviors, which severely constrain their industrial development. To address this, this study collected male GFP samples at critical developmental time points (100, 110, and 120 days post-hatching) for phenotypic trait measurement and analysis to obtain external morphological data. Through gut microbiota diversity analysis, we identified key gut bacteria (Lactococcus garvieae and Lactobacillus taiwanensis) influencing male morphotype differentiation. Transcriptomic analysis revealed host Kyoto Encyclopedia of Gene and Genome pathways and key genes (Wnt-6, CTSB, CTSL, PPAE, and TP53) associated with morphotype differentiation. The interactions among phenotypic traits, gut microbiota, and key genes were systematically studied through association analysis. Weighted gene co-expression network analysis was employed to construct co-expression modules, from which critical gene modules influencing phenotypic variation were identified. Through association network analysis, we established an "Achromobacter-CD-TRINITY_DN93139_c0_g2 (calpain clp-1)" interaction model. Our findings provide novel insights into the genetic enhancement of GFPs and offer guidelines for future research regarding gut symbiotic bacteria and breeding initiatives. IMPORTANCE: Male Macrobrachium rosenbergii (giant freshwater prawn [GFP]) in the same growth cycle will develop into small males, orange claw males, and blue claw males. This individual heterogeneity in growth significantly impacts the benefits of aquaculture. However, the factors influencing the differentiation of male GFP morphotype remain unclear. This study analyzed the phenotypic data of various GFP levels, the structure of the intestinal microbiota, and the differential genes within the gonadal transcriptome at critical time points of male GFP-level type differentiation. The aim was to explore the potential role of intestinal microbiota and differential genes in this phenomenon. This study offers new insights into the research on the phenomenon of male GFP-level type differentiation.

Animals↗