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Therapeutic targets in Paracoccidioides brasiliensis: post-transcriptome perspectives.

The rise in antifungal resistance, observed as a result of the increasing numbers of immunocompromised patients, has made the discovery of new targets for drug therapy imperative. The description of the Paracoccidioides brasiliensis transcriptome has allowed us to find alternatives to refine current therapy against paracoccidioidomycosis. We used comparative analysis of expressed sequence tags to find promising drug targets that have been addressed in other pathogens. We divided the analysis into six different categories, based on the involvement of the targeted mechanisms in the cell: i) cell wall construction, ii) plasma membrane composition, iii) cellular machinery, iv) cellular metabolism, v) signaling pathways, and vi) other essential processes. Through this approach, it has been possible to infer strategies to develop alternative drugs against this pathogen.

Antifungal Agents↗

A proteomic analysis of mammalian preimplantation embryonic development.

Genetic studies on the mammalian preimplantation embryo are providing a wealth of information regarding gene expression. However, changes in the transcriptome do not always reflect cellular function or the complexity and diversity of the mammalian proteome with post-translational modifications or protein-protein interactions. To elucidate embryonic cellular function, a detailed understanding at the protein level is necessary. The aim of this study was to generate protein profiles of mammalian embryos throughout development, and to investigate the effects of oxygen concentration on the embryonic proteome. A protocol was developed to analyse small groups of embryos (n = 5) by time-of-flight mass spectrometry. F1 mice zygotes were cultured in G1/G2 sequential media with recombinant albumin (2.5 mg/ml) in 6% CO(2) and O(2) concentrations of either 5% or 20%. In vivo-developed embryos were flushed from the reproductive tract (day 4). Protein profiles were generated for all embryonic samples and statistical analysis revealed 32 potential proteins/biomarkers with significant changes (P < 0.05). Embryos generated under 5% O(2) more closely resembled in vivo-developed embryos. Under 20% O(2) conditions, embryos showed down-regulation of 10 proteins/biomarkers (masses between 4 to 20 kDa) (P < 0.05) confirming the pathological effects of oxygen during embryonic development. These data demonstrate for the first time the complexity of the mammalian preimplantation proteome. The unique protein profiles of in vivo-developed embryos and a panel of selected biomarkers represent optimal cellular function, against which comparisons can be made to facilitate improvements in mammalian assisted reproduction techniques procedures.

Animals↗

Live-cell transcriptomics with engineered virus-like particles.

Transcriptomic profiling is widely applied to characterize cellular gene expression, yet existing approaches lyse cells and preclude direct analysis of transcriptional dynamics in the same sample over time. We addressed this limitation by engineering mammalian cells to "self-report" their transcriptional states via mRNA export in virus-like particles (VLPs). Repeated sampling of culture media from VLP-producing cell populations faithfully captured evolving transcriptional states in complex biological settings, including acute inflammatory stimulation of primary cell spheroids and multi-day differentiation of pluripotent stem cells. We engineered VLP components for multiplexed readouts from distinct cell types in co-culture and for tuning self-reported RNA profiles. Finally, we demonstrated the unique utility of self-reporting for selective longitudinal tracking of endothelial cell dynamics within the enclosed architecture of a microphysiological co-culture system to identify perivascular stroma-dependent temporal gene programs underlying vasculogenesis. Altogether, this work establishes cellular self-reporting as a broadly enabling technology for live-cell transcriptome-wide gene expression profiling.

RNA↗

Comparison of medulloblastoma and normal neural transcriptomes identifies a restricted set of activated genes.

Over 1.4 million transcript tags expressed in 20 different human medulloblastomas were counted using serial analysis of gene expression. Digital gene expression profiles in the medulloblastoma were compared to multiple regions of the normal human brain, revealing 30 transcripts with high expression in multiple tumors and little or no expression in the normal cerebellum and other adult and pediatric brain regions. Using independent medulloblastoma samples and normal tissue, real-time PCR verified eight of nine selected genes as candidate tumor-associated antigens. Differential protein expression for CD24, prolactin and Topo2A was further confirmed by immunohistochemical analysis using medulloblastoma and normal brain sections and a tissue microarray. The genes highly expressed in the medulloblastoma include PRAME, a cancer-testis antigen and potential targets for immunotherapy.

Brain↗

DNA array analysis of Candida albicans gene expression in response to adherence to polystyrene.

Candidiasis is often initiated by the colonization of inert surfaces. In order to elucidate the mechanisms involved in this adherence process, DNA macroarrays were used to analyze the transcriptome of Candida albicans, the main causative agent of this mycoses, in a simple adherence model using germ tubes produced in polystyrene Petri dishes. Non-adherent germ tubes produced on glass surface were used as a control. Analysis of gene expression displayed 77 genes identified as statistically overexpressed in adherent germ tubes. Among these genes, some encoded enzymes participating in metabolism of lipids (such as LIP6), of proteins (such as SAP1) or of carbohydrates (like PGI1, PMI40 and PSA1. Some of these genes have already been reported as playing a role in pathogenesis of C. albicans. However, functions were unknown for a large part (45.5%) of the overexpressed genes which will be analyzed further in order to define their relationship with adherence.

Candida albicans↗

Serial analysis of gene expression (SAGE) in bovine trypanotolerance: preliminary results.

In Africa, trypanosomosis is a tsetse-transmitted disease which represents the most important constraint to livestock production. Several indigenous West African taurine Bos taurus) breeds, such as the Longhorn (N'Dama) cattle are well known to control trypanosome infections. This genetic ability named "trypanotolerance" results from various biological mechanisms under multigenic control. The methodologies used so far have not succeeded in identifying the complete pool of genes involved in trypanotolerance. New post genomic biotechnologies such as transcriptome analyses are efficient in characterising the pool of genes involved in the expression of specific biological functions. We used the serial analysis of gene expression (SAGE) technique to construct, from Peripheral Blood Mononuclear Cells of an N'Dama cow, 2 total mRNA transcript libraries, at day 0 of a Trypanosoma congolense experimental infection and at day 10 post-infection, corresponding to the peak of parasitaemia. Bioinformatic comparisons in the bovine genomic databases allowed the identification of 187 up- and down- regulated genes, EST and unknown functional genes. Identification of the genes involved in trypanotolerance will allow to set up specific microarray sets for further metabolic and pharmacological studies and to design field marker-assisted selection by introgression programmes.

Africa South of the Sahara↗

PGR expression as a pharmacogenomic companion biomarker to GENE70-derived genomic risk in ER-positive/HER2-negative breast cancer.

BACKGROUND: The biology of the estrogen receptor-positive (ER+) and human epidermal growth factor receptor 2-negative (HER2-) breast cancers is heterogeneous even when they are categorized by their risk via genomics. Transcriptomic PGR expression reflects endocrine pathway activity and may provide complementary biological information within established GENE70-derived genomic-risk categories. Whether this molecular marker improves the biological interpretation of genomic-risk stratification beyond conventional clinicopathological assessment remains uncertain. OBJECTIVES: The aim of this study was to determine whether transcriptomic PGR expression provides complementary biological and prognostic information within reconstructed GENE70-derived genomic-risk categories and refines the characterization of endocrine-related tumour biology in ER-positive/HER2-negative breast cancer. METHODS: This study analysed publicly available transcriptomic and clinical data from three cohorts: METABRIC (discovery cohort), GSE96058/SCAN-B cohort (validation cohort) and TCGA-BRCA cohort (molecular validation cohort). The GENE70-derived genomic-risk score was reconstructed for each cohort using matched genes. Cox regression, Kaplan-Meier analysis and subgroup comparisons were used to assess relationships between PGR expression, clinicopathologic variables, molecular features and survival outcomes. RESULTS: Across the three independent cohorts, low transcriptomic PGR expression was consistently associated with higher GENE70-derived genomic risk, increased MKI67 expression, reduced ESR1 expression and enrichment of the Luminal B subtype. Survival findings differed between cohorts. In the discovery METABRIC cohort, transcriptomic PGR expression showed heterogeneous associations with survival, particularly within GENE70-derived high-risk subgroups, whereas the external GSE96058/SCAN-B validation cohort demonstrated consistent associations between low PGR expression and poorer overall survival in both the overall ER-positive/HER2-negative population and GENE70-derived high-risk subgroups. CONCLUSION: These findings suggest that transcriptomic PGR provides complementary biological and prognostic information within GENE70-derived genomic-risk categories. However, because treatment response was not evaluated in the present study, the findings should not be interpreted as evidence of predictive or pharmacogenomic utility and prospective studies incorporating treatment-response analyses are required before such applications can be established.

Humans↗

Antioxidant defense in Plasmodium falciparum--data mining of the transcriptome.

The intraerythrocytic malaria parasite is under constant oxidative stress originating both from endogenous and exogenous processes. The parasite is endowed with a complete network of enzymes and proteins that protect it from those threats, but also uses redox activities to regulate enzyme activities. In the present analysis, the transcription of the genes coding for the antioxidant defense elements are viewed in the time-frame of the intraerythrocytic cycle. Time-dependent transcription data were taken from the transcriptome of the human malaria parasite Plasmodium falciparum. Whereas for several processes the transcription of the many participating genes is coordinated, in the present case there are some outstanding deviations where gene products that utilize glutathione or thioredoxin are transcribed before the genes coding for elements that control the levels of those substrates are transcribed. Such insights may hint to novel, non-classical pathways that necessitate further investigations.

Animals↗

Serial analysis of gene expression during elongation of the peri-implantation porcine trophectoderm (conceptus).

Conceptus loss during the preimplantation and early postimplantation period hinders the efficiency of swine reproduction. Significant conceptus loss occurs during trophectoderm elongation between gestational day 11 (D11) and day 12 (D12). Elongation of the porcine conceptus is a key stage of development during which maternal recognition of pregnancy, initial placental development, and preparation for implantation occurs. The objective of this study was to establish comparative transcriptome profiles of D11 ovoid and D12 filamentous conceptuses and thereby identify temporally regulated genes essential for developmental progression during conceptus elongation. Serial analysis of gene expression (SAGE) libraries were constructed from in vivo derived ovoid and filamentous swine conceptuses to yield a total of 42,389 tags (ovoid) and 42,391 tags (filamentous) representing 14,464 and 13,098 putative unique transcripts, respectively. Statistical analysis of tag frequencies revealed the differential expression of 431 tags between libraries (P < 0.05). Nucleotide sequence alignment searches on public databases provided SAGE tag annotation and gene ontology assignments. Comparisons between the SAGE profiles of ovoid and filamentous conceptuses revealed increased expression of key genes in the steroidogenesis [cytochrome P-450(scc) (CYP11A1), aromatase (CYP19A), and steroidogenic acute regulatory protein (STAR)] and oxidative stress response pathways [microsomal glutathione S-transferase 1 (MGST1) and copper-zinc superoxide dismutase (SOD1)]. Differential expression of these genes in the steroidogenic and oxidative stress response pathways was confirmed by real-time PCR. These results validate the utility of SAGE in the pig and establish an initial model linking gene expression profiles at the pathway level with phenotypic progression from ovoid to filamentous stages of conceptus development.

Animals↗

The iron-regulated transcriptome and proteome of Neisseria meningitidis serogroup C.

Restricting bacterial growth by iron-chelating proteins that reduce iron availability in mucosal secretions and body fluids belongs to basic mechanisms of innate immunity. Most pathogens and commensals thus developed gene regulons responding to iron concentration and encoding iron acquisition systems and genes involved in host colonization and virulence. Here, we analyzed the steady-state composition of the iron-regulated proteome and transcriptome of an invasive serogroup C clinical isolate of Neisseria meningitidis. The proteome of meningococci grown under iron-depleted and iron-replete conditions was analyzed by 2-DE and proteins exhibiting significantly altered expression were identified by MALDI-TOF MS analysis. In parallel, total RNA was isolated from the same cultures and iron-regulated genes were identified using whole-genome DNA microarrays. The proteome and the transcriptome were found to overlap by only 19 iron-regulated genes/proteins, with 111 genes/proteins being significantly up-regulated in iron-replete cultures and 130 genes/proteins being up-regulated during iron starvation, respectively. Comparisons with published transcriptomic data for N. meningitidis serogroup B, moreover, indicate that expression of up to 20% of all meningococcal genes can be subject to regulation in function of iron availability.

Deferoxamine↗

Proteomics combined with single-cell sequencing reveals key genes and computational lead compound related to ligamentum flavum hypertrophy, lactate metabolism and lactate modification.

Ligamentum flavum hypertrophy (LFH) is a hallmark pathological feature of lumbar spinal stenosis; however, its underlying molecular mechanisms remain incompletely understood. Lactate metabolism and related lactylation modifications have emerged as critical links between cellular metabolism and epigenetic regulation, with established roles in various fibrotic and inflammatory diseases. Nevertheless, the specific contribution of lactylation to LFH pathogenesis remains unexplored. In this study, we integrated proteomic profiling of ligamentum flavum tissues with single-cell transcriptomic data to identify differentially expressed proteins associated with LFH. Cross-referencing these genes with genes involved in lactate metabolism and lactylation yielded 16 candidate genes. Through functional enrichment analysis, protein-protein interaction network construction, and GraphBAN model prediction, we identified five hub genes (NDUFS2, HMOX1, SPR, FABP5, and PFKP) and two potential lead compounds (ZINC000014879975 and ZINC000242437513). Molecular docking analysis confirmed favorable binding affinities between these compounds, suggesting that they may serve as potential lead compounds worthy of further experimental investigation. Single-cell analysis further revealed that macrophages occupy a central position in the LFH microenvironment, resulting in pronounced metabolic reprogramming and remodeling of intercellular communication networks, particularly via the MIF-CD74/CD44 axis, under pathological conditions.

Proteomics↗

Genome-wide association studies of plant traits and functional analysis of leaf development-related genes in citrus.

Labor-saving and high-light-efficiency tree architecture is a key breeding objective for woody fruit trees like citrus. However, population genetics information on these traits remains limited. In this study, tree architecture, thorn, and leaf traits were evaluated in 353&#x2009;F2 progeny derived from a cross between Clementine mandarin and precocious trifoliate orange-an early-flowering variety. A random subset of 300 offspring was sequenced for a genome-wide association study (GWAS), which detected 10&#x2009;216 significantly associated SNPs and defined several major quantitative trait loci (QTLs) for the target traits. Subsequent bulked segregant analysis (BSA) and GWAS on individuals with extreme compound leaf phenotypes mapped the causal gene(s) to a 0.8&#x2009;Mb region (22.15-22.95&#x2009;Mb) on chromosome 4. Genetic analysis across multiple hybrid combinations confirmed that the compound leaf trait in trifoliate orange is dominantly inherited and follows Mendelian segregation. Transcriptome profiling of parental leaves at different developmental stages identified a KNOX gene, CiKNAT6, as a candidate. Further validation using CAPS markers and Hi-Tom sequencing demonstrated tight linkage between an InDel polymorphism in CiKNAT6 and leaf shape across diverse citrus species and the F2 population, with co-segregation observed for the compound leaf trait. Due to alternative splicing producing seven splice variants, the CiKNAT6 DNA sequence was selected for genetic transformation experiments. Functional analysis revealed that the Clementine mandarin allele of CiKNAT6 is non-functional owing to an InDel, whereas ectopic expression of the trifoliate orange allele in tobacco and lemon induced leaf curling and reduced leaf size. CRISPR-Cas9 knockout of CiKNAT6 in trifoliate orange resulted in increased leaf area. These findings provide valuable genetic resources and insights for future studies on tree architecture and leaf morphology.

Plant Leaves↗

Transcript-guided targeted cell enrichment for scalable single-nucleus RNA sequencing.

Large-scale single-cell atlases have revealed many aging- and disease-associated cell types, yet these populations are often underrepresented in heterogeneous tissues, limiting detailed molecular analyses. To address this, we developed EnrichSci-a scalable, microfluidics-free platform that combines hybridization chain reaction RNA fluorescence in situ hybridization (FISH) with combinatorial indexing to profile single-nucleus transcriptomes of target cell types with full gene-body coverage. Applied to oligodendrocytes in the aging mouse brain, EnrichSci uncovered aging-associated molecular dynamics across distinct oligodendrocyte subtypes, revealing both shared and subtype-specific gene expression changes. Additionally, we identified aging-associated exon-level signatures missed by conventional gene-level analyses, highlighting post-transcriptional regulation as a critical dimension of cell-state dynamics in aging. By coupling transcript-guided enrichment with a scalable sequencing workflow, EnrichSci provides a versatile approach to decode dynamic regulatory landscapes in diverse cell types from complex tissues.

Animals↗

Integrative analysis of single-cell sequencing identifies CD8+ TIM3+ CD101+ T cell-associated genes as prognostic biomarkers in breast cancer.

BACKGROUND: Breast cancer is a prevalent and deadly malignancy that significantly impacts women's quality of life and imposes financial burdens. Despite therapeutic advancements, tumour heterogeneity and frequent relapses remain major challenges. Accordingly, this study aimed to characterize immune features associated with CD8+ TIM3+ CD101+ T cells and develop a prognostic signature for breast cancer. METHODS: This study integrated single-cell and bulk transcriptomic datasets to characterize CD8+ TIM3+ CD101+ T cell (CCT)-related immune features and construct a prognostic signature in breast cancer. Single-cell RNA-seq data were sourced from the Gene Expression Omnibus (GEO) repository, and bulk transcriptomic data were from The Cancer Genome Atlas (TCGA) and GEO databases. Analytical methods included pseudo-time trajectory reconstruction (Monocle2), intercellular signalling analysis (CellChat), functional enrichment (ClusterProfiler), and immune profiling (ssGSEA). Prognostic modeling was conducted using least absolute shrinkage and selection operator (LASSO) Cox regression, with validation via Kaplan-Meier and time-dependent receiver operating characteristic (ROC) analyses. RESULTS: Single-cell analysis identified 17 clusters spanning seven cell types, including T cells, myeloid cells, and epithelial cells. T-cell sub-clustering revealed four subtypes. Pseudotime analysis suggested a potential state-transition relationship between CD8+ CD101- TIM3+ and CD8+ CD101+ TIM3+ T-cell states. A total of 121 differentially expressed genes were enriched in vital biological processes. An 11-gene prognostic model showed strong predictive power across cohorts. Single-cell T-cell reclustering identified a CD8+ CD101+ TIM3+ T-cell subpopulation, which was primarily characterized by the expression of markers such as CD101 and HAVCR2/TIM3. CONCLUSIONS: This study maps cellular heterogeneity and molecular networks in breast cancer, offering insights for targeted therapy and improved prognosis.

Breast invasive carcinoma↗

[DNA arrays: technological aspects and applications].

The Human Genome Project has allowed considerable progress in the construction of physical and genetic maps and the identification of genes involved in human sicknesses. The accelerated accumulation of biological information and knowledge is due in large part to the sequencing projects of other organisms, which in fact paved the way for the Human Genome Project. In parallel, recently developed techniques which take advantage of genomic sequences allow large scale molecular analyses resulting in the functional annotation of many of the proteins represented by these genes. This is the goal of functional genomics. These progresses are at the origin of the present revolution in biomedical research. DNA microarrays are playing a dominant role compared to the other developing technologies since they are relatively easy to make and use and are applicable to numerous scientific inquiries. They allow the simultaneous analysis of several thousands of genes in biological samples from sick or healthy tissues, at the genome or transcriptome level. The data obtained is expected to result in major advances in the health sciences. In addition to an improved understanding of the complex molecular interaction networks of healthy cells and tissues, a more precise genetic characterization of the molecular mechanisms involved in pathology should result in the identification of new therapeutic targets and the development of new medicines. The genetic profiles thus obtained should also permit the definition of new pathologic subclasses not recognizable by traditional clinical factors, as well as new markers for susceptibility to certain illnesses, and new prognostic markers or methods of predicting responses to treatment. In this article, we present the different approaches and potential applications of DNA microarray technology, in particular as applied to cancer research.

Chromosome Mapping↗

Nuclear export inhibition activates TP53 pathways and is a potent therapeutic strategy in atypical teratoid rhabdoid tumors.

BACKGROUND: Atypical teratoid/rhabdoid tumor (ATRT) is an aggressive central nervous system tumor mostly affecting young children. Improved and less toxic therapies for children with ATRT are imperative due to the toxicities associated with current treatments. Furthermore, existing therapies do not address the underlying genetic drivers of ATRT. In this study, we sought to determine whether exportin-1 (XPO1) is a genetic dependency and therapeutic target in ATRT. METHODS: We utilized an integrative approach harnessing patient-derived ATRT cell lines, functional genomics, pharmacologic assays, transcriptomics, and in vivo intracranial xenograft models to systematically test the hypothesis that XPO1 is a novel dependency in ATRT. RESULTS: Analysis of RNA-sequencing datasets revealed high XPO1 expression in ATRT cells compared to other pediatric brain tumor cell lines. Both CRISPR/Cas9 genetic knockdown and pharmacologic inhibition of XPO1 using 6 selective inhibitors of nuclear export (SINEs) in patient-derived atypical teratoid/rhabdoid tumor (ATRT) cells led to significant reduction in cell viability and proliferation. Furthermore, we observed increased apoptosis, G0 phase cell cycle arrest, and upregulation of TP53 signaling pathways in cells treated with the SINE selinexor. Consistently, our transcriptomic data revealed the upregulation of apoptosis and TP53 signaling pathways and concomitant depletion of cell cycle gene sets. In vivo, selinexor in combination with radiation and cyclophosphamide led to significant reduction in tumor volume and increased animal survival in intracranial ATRT xenograft models. CONCLUSIONS: Our data reveals XPO1 as a novel genetic dependency and potent therapeutic target in ATRT.

atypical teratoid rhabdoid tumor↗

A preliminary transcriptome map of non-small cell lung cancer.

We constructed a genome-wide transcriptome map of non-small cell lung carcinomas based on gene-expression profiles generated by serial analysis of gene expression (SAGE) using primary tumors and bronchial epithelial cells of the lung. Using the human genome working draft and the public databases, 25,135 nonredundant UniGene clusters were mapped onto unambiguous chromosomal positions. Of the 23,056 SAGE tags that appeared more than once among the nine SAGE libraries, 11,156 tags representing 7,097 UniGene clusters were positioned onto chromosomes. A total of 43 and 55 clusters of differentially expressed genes were observed in squamous cell carcinoma and adenocarcinoma, respectively. The number of genes in each cluster ranged from 18 to 78 in squamous cell carcinomas and from 20 to 165 in adenocarcinomas. The size of these clusters varied from 1.8 Mb to 65.5 Mb in squamous cell carcinomas and from 1.6 Mb to 98.1 Mb in adenocarcinomas. Overall, the clusters with genes over-represented in tumors had an average of 3-4-fold increase in gene expression compared with the normal control. In contrast, clusters of genes with reduced expression had about 50-65% of the gene expression level compared with the normal. Examination of clusters identified in squamous cell lung cancer suggested that 9 of 15 clusters with overexpressed genes and 13 of 28 clusters with underexpressed genes were concordant with previously reported cytogenetic, comparative genomic hybridization or loss of heterozygosity studies. Therefore, at least a portion of the gene clusters identified via the transcriptome map most likely represented the transcriptional or genetic alterations occurred in the tumors. Integrating chromosomal mapping information with gene expression profiles may help reveal novel molecular changes associated with human lung cancer.

Carcinoma, Non-Small-Cell Lung↗

Lymphangiogenesis-related gene signature-based risk model for prognostic assessment of cervical cancer: immune-metabolic characterization and molecular subtype analysis.

BACKGROUND: Lymphangiogenesis promotes tumor dissemination and may shape the immune contexture of cervical cancer, yet lymphangiogenesis-related prognostic stratification and its immunometabolic implications remain insufficiently defined in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). METHODS: TCGA-CESC transcriptomes and clinical data were obtained from UCSC Xena and integrated with normal cervix tissues from the Genotype-Tissue Expression Project after batch correction. Prognostic LYMRGs were first identified from the differentially expressed set using univariable Cox proportional hazards analysis. Candidate genes were then reduced using an L1-regularized Cox model (Least Absolute Shrinkage and Selection Operator), and the remaining markers were entered into a multivariable Cox regression to obtain the final coefficients and compute an individualized risk score. The model's prognostic value was further assessed in an independent Gene Expression Omnibus dataset. In addition, expression patterns of the signature genes were leveraged for molecular subtyping of TCGA samples via non-negative matrix factorization (NMF). Immune infiltration and immunotherapy-associated characteristics were interrogated through a multi-algorithm strategy (single-sample gene set enrichment analysis, CIBERSORT, ESTIMATE, Tumor Immune Dysfunction and Exclusion (TIDE), and Immunophenoscore . Additional analyses included pathway enrichment (GSEA/GO/KEGG), drug sensitivity prediction (pRRophetic/CellMiner), and ceRNA network analysis. RESULTS: A six-gene LYMRG signature robustly stratified survival. High-risk patients had significantly worse overall survival in The Cancer Genome Atlas with AUCs of 0.819/0.801/0.801&#xa0;at 1/3/5 years, and in GSE52903 (P = 0.001) with AUCs of 0.733/0.719/0.725. NMF identified two subtypes with distinct prognosis (P = 0.01) and divergent immune landscapes. Risk groups and subtypes exhibited consistent differences in immune infiltration, checkpoint expression, TIDE/IPS patterns, and pathway enrichment. Predicted chemosensitivity differed by risk group, and the ceRNA network suggested candidate upstream lncRNA regulators of the signature. CONCLUSION: A lymphangiogenesis-related six-gene model enables clinically meaningful prognostic stratification of CESC and links lymphangiogenesis programs to distinct tumor immune phenotypes and therapeutic vulnerabilities.

cancer↗

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