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Integrative dual-track transcriptomics reveals stage-specific coordination, regulatory divergence, and HSP90AA1-associated remodeling in human folliculogenesis.

Human folliculogenesis depends on coordinated yet non-identical developmental remodeling in the oocyte and its surrounding granulosa cells. When these two compartments remain synchronized and when they diverge into lineage-specific regulatory states, however, remains incompletely resolved. Here we performed an integrative dual-track re-analysis of the human RNA-seq dataset GSE107746, modeling oocytes and granulosa cells as distinct but developmentally linked compartments across follicular progression. Analysis of 148 sequencing libraries showed that compartment identity was the dominant source of transcriptomic variation, supporting compartment-aware downstream interpretation. Within this framework, oocytes followed a relatively continuous developmental trajectory, with substantial transcriptional remodeling already evident across adjacent stages, whereas granulosa cells showed weaker early-stage contrasts but markedly stronger late-stage reorganization, particularly around the antral and preovulatory transitions. Functional enrichment indicated that oocyte maturation was associated with RNA-processing and broader genome-regulatory remodeling, whereas granulosa maturation was dominated by progressive mitochondrial and bioenergetic activation. Co-expression analysis showed that both compartments contained strong late-stage programmes together with inverse early-state modules, indicating a shared systems-level architecture of maturation, although the hub-gene composition and biological content of these programmes were largely compartment-specific. Machine-learning validation reinforced this asymmetry: oocyte stage classification was best recovered from a compact eigengene-based representation, whereas granulosa stage discrimination was better resolved by a broader differential-expression-derived feature set. At the gene level, HSP90AA1 emerged as a stage-associated marker with compartment-specific behavior, showing progressive attenuation across oocyte development, assignment to the selected oocyte blue module, and sharper transitional dynamics in granulosa cells. Together, these findings support a model in which human folliculogenesis proceeds through coordinated but non-equivalent transcriptomic remodeling, with shared developmental logic at the systems level but distinct molecular execution in germline and somatic compartments.

Co-expression networks↗

Systems toxicology and the Chemical Effects in Biological Systems (CEBS) knowledge base.

The National Center for Toxicogenomics is developing the first public toxicogenomics knowledge base that combines molecular expression data sets from transcriptomics, proteomics, metabonomics, and conventional toxicology with metabolic, toxicologcal pathway, and gene regulatory network information relevant to environmental toxicology and human disease. It is called the Chemical Effects in Biological Systems (CEBS) knowledge base and is designed to meet the information needs of "systems toxicology," involving the study of perturbation by chemicals and stressors, monitoring changes in molecular expression and conventional toxicological parameters, and iteratively integrating biological response data to describe the functioning organism. Based upon functional genomics approaches used successfully in analyzing yeast gene expression data sets, relational and descriptive compendia will be assembled for toxicologically important genes, groups of genes, single nucleotide polymorphisms (SNPs), and mutant and knockout phenotypes. CEBS data sets will be fully documented in the experimental protocol and therefore searchable by compound, structure, toxicity end point, pathology and point, gene, gene group, SNP, pathway, and network as a function of dose, time, and the phenotype of the target tissue. A knowledge base is being developed by assimilating toxicological, biological, and chemical information from multiple public domain databases and by progressively refining that information about gene, protein, and metabolite expression for classes of chemicals and their biological effects in various species. By analogy to the GenBank database for genome sequences, researchers will globally query (or BLAST) CEBS using a transcriptome of a tissue of interest (or a list of outliers) to have the knowledge base return information on genes, groups of genes, metabolic and toxicological pathways, and contextually associated phenotypic information for compounds that display similar response profiles. With high-quality data content, CEBS will ultimately become a resource to support hypothesis-driven and discovery research that contributes effectively to drug safety and the improvement of risk assessments for chemicals in the environment. The CEBS development effort will span a decade or more.

Computational Biology↗

Genomic exploration of the hemiascomycetous yeasts: 4. The genome of Saccharomyces cerevisiae revisited.

Since its completion more than 4 years ago, the sequence of Saccharomyces cerevisiae has been extensively used and studied. The original sequence has received a few corrections, and the identification of genes has been completed, thanks in particular to transcriptome analyses and to specialized studies on introns, tRNA genes, transposons or multigene families. In order to undertake the extensive comparative sequence analysis of this program, we have entirely revisited the S. cerevisiae sequence using the same criteria for all 16 chromosomes and taking into account publicly available annotations for genes and elements that cannot be predicted. Comparison with the other yeast species of this program indicates the existence of 50 novel genes in segments previously considered as 'intergenic' and suggests extensions for 26 of the previously annotated genes.

Ascomycota↗

Dysregulated Sheddase Signalling as a Molecular Driver of Plaque Instability Revealed by Integrative Transcriptomics.

Atherosclerosis is a major cause of mortality due to chronic and progressive low-grade inflammation and fibroproliferative remodelling of the intima of arteries. Comprehensive understanding of the interplay between plaque biology and the mechanisms underlying plaque vulnerability and rupture is essential. Here, we aimed to investigate the transcriptomic profiles of stable and unstable atherosclerotic plaques using RNA sequencing data from human carotid atherosclerotic plaque samples based on next-generation knowledge discovery (NGKD) methods. High-throughput RNA-seq data from plaques dissected in stable and unstable regions of four patients were obtained from the Gene Expression Omnibus (GEO) database. GEO RNA-seq Experiments Interactive Navigator (GREIN) software was used to obtain raw gene-level counts and filtered metadata for this dataset. The data were further filtered and normalized using Express analyst to derive differentially expressed genes (DEGs) in unstable plaques compared to stable plaques. The DEGs were further analysed using WebGestalt, STRING DB, preranked gene set enrichment analysis (GSEA), and Ingenuity Pathway Analysis (IPA) software. We identified 4792 DEGs in unstable plaques based on a p-value cutoff of <&#x2009;0.05. NGKD analysis revealed that the sheddase pathway, collagen degradation, activation of matrix metalloproteinases (MMPs), and extracellular matrix (ECM) degradation ranked among the top five upregulated pathways, whereas the inhibition of MMPs and smooth muscle contraction pathways were identified as the most prominent downregulated pathways in unstable plaques. We found that the sheddase pathway was one of the most significantly upregulated canonical pathways in unstable plaques and this finding opens new avenues for potential therapeutic interventions in patients with atherosclerosis.

Humans↗

Pan-genomics and multi-omics for deciphering genetic variation and accelerating genetic improvement in ruminant livestock.

Livestock reference genomes have transformed the discovery of variants associated with production, reproduction, health, and environmental adaptation. Nevertheless, a single linear reference represents only one mosaic haplotype and incompletely captures sequence diversity within a species, particularly structural variants, copy-number changes, repeat-rich regions, and breed-specific sequences. Pangenomes address this limitation by integrating multiple high-quality assemblies or population-scale variants into a unified sequence or graph representation. Concurrently, multi-omics approaches connect genomic variation with transcriptomic, epigenomic, manuscriptproteomic, metabolomic, and microbiome responses, thereby improving biological interpretation of genotype-phenotype relationships. This review synthesizes recent progress in livestock pangenomics and multi-omics, with emphasis on cattle, goats, sheep, water buffalo, and chickens. It describes advances in long-read and haplotype-resolved sequencing, graph construction, structural-variant discovery and genotyping, functional annotation, and integrative analysis. Recent pangenome studies have uncovered substantial non-reference sequence, reduced reference bias, identified breed- and population-specific structural variants, and resolved candidate variants underlying pigmentation, body size, tail morphology, cashmere production, altitude adaptation, and other economically relevant traits. However, translation into routine breeding remains constrained by uneven population representation, inconsistent structural-variant definitions, limited functional annotation, computational demands, and insufficient validation across environments. Future progress will depend on diverse near-complete assemblies, graph-aware imputation and genomic prediction, long-read transcriptomics, single-cell and spatial omics, rigorous causal validation, and open, interoperable resources. Together, these developments can support more accurate, resilient, and biologically informed livestock improvement. Importantly, current dairy-cattle evidence indicates that pangenome-derived structural variants can substantially improve variant discovery and functional interpretation while yielding only marginal average gains in routine genomic prediction, favoring targeted augmentation rather than wholesale replacement of established SNP-based evaluations.

Animals↗

An array of insights: application of DNA chip technology in the study of cell biology.

The advent of DNA microarray technology has ushered in an era of systems biology whereby researchers can study the transcriptional behavior of thousands of genes in parallel. Advances in manufacturing techniques and informatics, and the availability of several genome sequences have furthered these capabilities to the point where whole-transcriptome studies can be accomplished in yeast, flies and plants, and soon will be possible in mammals. Concomitant with the expanding ability of the technology has been the development of novel techniques and their application towards the study of cellular biology.

Animals↗

Biotechnological manufacture of lysine.

L-Lysine has been manufactured using Corynebacterium glutamicum for more than 40 years. Nowadays production exceeds 600,000 tons per year. Based on conventionally bred strains, further improvement of lysine productivity has been achieved by genetic engineering. Pyruvate carboxylase, aspartate kinase, dihydrodipicolinate synthase, homoserine dehydrogenase and the specific lysine exporter were shown to be key enzymes for lysine production and were characterized in detail. Their combined engineering led to a striking increase in lysine formation. Pathway modeling with data emerging from 13C-isotope experiments revealed a coordinated flux through pentose phosphate cycle and tricarboxylic acid cycle and intensive futile cycling between C3 compounds of glycolysis and C4 compounds of tricarboxylic acid cycle. Process economics have been optimized by developing repeated fed-batch techniques and technical continuous fermentations. In addition, on-line metabolic pathway analysis or flow cytometry may help to improve the fermentation performance. Finally, the availability of the Corynebacterium glutamicum genome sequence has a major impact on the improvement of the biotechnological manufacture of lysine. In this context, all genes of the carbon flow from sugar uptake to lysine secretion have been identified and are accessible to manipulation. The whole sequence information gives access to post genome technologies such as transcriptome analysis, investigation of the proteome and the active metabolic network. These multi-parallel working technologies will accelerate the generation of knowledge. For the first time there is a chance of understanding the overall picture of the physiological state of lysine overproduction in a technical environment.

Bioreactors↗

Using Callus as an Ex Vivo System for Chromatin Analysis.

Next-generation sequencing has revolutionized epigenetics research, enabling a comprehensive analysis of DNA methylation and histone modification profiles to explore complex biological systems at unprecedented depth. Deciphering the intricate epigenetic mechanisms that regulate gene activity presents significant challenges, including the issue of analyzing heterogeneous cell populations in bulk. Bulk analysis introduces bias and can obscure crucial information by averaging readouts from distinct cells. Various approaches have been developed to address this issue, such as cell-type-specific enrichment or single-cell sequencing techniques. However, the need for transgenic lines with fluorescent markers, along with technical challenges such as efficient protoplast isolation and low yield, limits their widespread adoption and use in multi-omic studies. This review discusses the pros and cons of these approaches, providing a valuable basis for selecting the most suitable strategy to minimize heterogeneity. We will also highlight the use of cotyledon-derived callus as an ex vivo system as a simple, accessible, and robust platform for enabling high-throughput multi-omic analyses.

Chromatin↗

The pseudouridine epitranscriptomic landscape of advanced prostate cancer therapeutic resistance identifies TIMM17A as a key player.

BACKGROUND: Resistance to androgen receptor signaling inhibitors (ARSIs) remains a major barrier of advanced prostate cancer (PCa) treatment. While RNA epitranscriptomic modifications are increasingly recognized as key regulators of tumor biology, the role of pseudouridine (&#x3a8;) in therapeutic resistance is largely unexplored. METHODS: A darolutamide-resistant PCa cell model was established and subjected to integrated multi-omics profiling using bulk RNA sequencing and photo-crosslinking-assisted &#x3a8; sequencing (PA-&#x3a8;-seq). Differential expression and pseudouridylation analyses were combined to identify &#x3a8;-associated genes. Public datasets validated expression and prognosis. Functional assays including RNA knockdown, cell proliferation, colony formation, and xenograft models were conducted. Single-cell RNA sequencing investigated tumor microenvironment (TME) interactions. RESULTS: We identified extensive transcriptomic and pseudouridylation alterations associated with ARSI resistance, with a significant positive correlation between &#x3a8; modification and mRNA expression. Integrated analysis highlighted a subset of "hyper-up" genes enriched in resistance-related pathways. Thus, TIMM17A was identified as a novel candidate. TIMM17A expression was significantly elevated in PCa and correlated with disease progression and poor prognosis. Experimental validations demonstrated that TIMM17A promoted tumor growth and resistance, while its knockdown restored sensitivity to darolutamide both in vitro and in vivo. Mechanistically, TIMM17A expression may be regulated by PUS1&#x2011;mediated pseudouridylation. Single-cell analysis further revealed that TIMM17A is enriched in malignant epithelial cells and associated with enhanced cell-cell communication within the TME. CONCLUSIONS: This study delineates the pseudouridine epitranscriptomic landscape in advanced PCa and identifies TIMM17A as a key mediator of therapeutic resistance. Targeting the &#x3a8;-TIMM17A axis may offer a novel strategy to overcome ARSI resistance.

Advanced prostate cancer↗

Integrative ATAC-seq and RNA-seq analysis reveals lactation performance between Sewa sheep and East Friesian sheep.

Lactation performance is a pivotal economic trait in sheep production, yet its underlying epigenetic regulatory mechanisms remain poorly understood. In the present study, we integrated ATAC-seq and RNA-seq to compare chromatin accessibility landscapes and transcriptomic in mammary gland tissues from Sewa sheep (SWS) and East Friesian sheep (EFS). Histological characterization revealed that SWS exhibited significantly smaller mammary acini area, smaller lipid droplet area, and reduced lipid droplet diameter compared to EFS. ATAC-seq analysis identified 15,902 differentially accessible regions (DARs) between the two breeds, with motif enrichment analysis uncovering key transcription factors potentially governing lactation traits. RNA-seq analysis revealed 1,163 differentially expressed genes (DEGs), which were involved in lactation regulation. Integrated analysis identified 441 overlapping genes, and enriched in glycolysis/gluconeogenesis (e.g., PGAM1, ENO1) and pyruvate metabolism (e.g., ACACA, ACSS1, ACYP1). Collectively, our study provides new insights into the epigenetic regulatory mechanisms underlying lactation performance differences in sheep.

Animals↗

Transcriptome analysis of channel catfish (Ictalurus punctatus): initial analysis of gene expression and microsatellite-containing cDNAs in the skin.

Previous molecular genetic studies on channel catfish (Ictalurus punctatus) have focused on limited number of genes and gene products. Recent advancement of molecular techniques made high throughput analysis of transcriptomes possible. As part of our transcriptome analysis of channel catfish, we have analyzed 1909 expressed sequence tags (ESTs) derived from a skin library. Of the 1909 ESTs analyzed, 1376 (72.1%) ESTs representing 496 unique genes had homologies with other organisms while 478 (25.0%) ESTs had no significant homologies and were designated as unknown. The remaining 55 (2.9%) EST clones were eliminated because of their low quality or short sequences. Of the 496 unique genes, 327 (65.9%) genes were singletons while 169 (34.1%) genes represented by two or more ESTs. A total of 1007 (52.8%) ESTs representing 235 unique genes matched previously reported channel catfish ESTs while 847 (44.4%) ESTs representing 261 unique genes were newly identified from this research. Functional categorization of the channel catfish genes indicated that the largest group was ribosomal proteins with 65 unique genes represented by 500 clones. The most abundantly expressed gene, the calcium binding protein ictacalcin, accounted for almost 5% of overall expression, indicating its important function in the skin. Sequence analysis of ESTs revealed the presence of 89 microsatellite-containing genes that may be valuable for future mapping studies.

Animals↗

ITPRIPL1: A tumor immune-associated biomarker with prognostic and therapeutic implications in gastrointestinal cancer.

Inositol 1,4,5-trisphosphate receptor-interacting protein-like 1(ITPRIPL1) has recently been implicated in tumor-immune regulation, yet its tumor-type specificity and clinical relevance in gastrointestinal malignancies remain unclear. Here, we performed an integrative analysis of ITPRIPL1 across stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD), rectal adenocarcinoma (READ), and esophageal carcinoma (ESCA) using bulk transcriptomics, immune pathway analyses, survival modeling, single-cell RNA sequencing, immunofluorescence validation, and therapeutic correlation analyses. Although ITPRIPL1 was upregulated across gastrointestinal cancers, its prognostic significance was highly tumor-specific, with elevated expression consistently predicting unfavorable survival only in STAD. In gastric cancer, ITPRIPL1 expression was closely associated with immune-related pathways and genomic instability features, and its prognostic association varied across immune contexts, particularly according to CD8&#x207a;/CD4&#x207a; T-cell abundance, with an exploratory association also observed for zeta-chain-associated protein kinase 70 (ZAP70) expression. Single-cell and immunofluorescence analyses demonstrated preferential enrichment of ITPRIPL1 in T cells and tumor-adjacent immune structures. Notably, Exploratory analyses further showed that higher ITPRIPL1 expression was associated with favorable survival outcomes in selected external pretreatment immunotherapy cohorts and with lower IC50 values for several agents in cancer cell-line pharmacogenomic datasets. Collectively, these findings identify ITPRIPL1 as an immune-associated biomarker with primary clinical relevance in gastric cancer.

Humans↗

Selection at the wobble position of codons read by the same tRNA in Saccharomyces cerevisiae.

The transfer RNA gene complement of Saccharomyces cerevisiae was utilized for a whole-genome analysis of the deviation from a neutral usage of pyrimidine-ending cognate codons, that is, codons read by a single tRNA species having either inosine or guanosine as the first anticodon base. Mutational pressure at the wobble position was estimated from the base composition of the noncoding portion of the yeast genome. The selective pressure for translational efficiency was inferred from the degree of codon adaptation to tRNA gene redundancy and from mRNA abundance data derived from yeast transcriptome analysis. Amino acid conservation in orthologous comparisons with wholly sequenced microbial genomes was used to estimate translational accuracy requirements. A close correspondence was observed between the usage of wobble position pyrimidines and the frequency predicted by mutational bias. However, in the case of four cognate pairs (Gly: ggu/ggc; Asn: aau/aac; Phe: uuu/uuc; Tyr: uau/ uac) all read by guanosine-starting anticodons, we found evidence for a strong selective pressure driven by translational efficiency. Only for the glycine pair, wobble pyrimidine choice also appears to fulfill a translational accuracy requirement. Wobble pyrimidine selection is strictly related to the number of hydrogen bonds formed by alternative cognate codons: whenever a different number of hydrogen bonds can be formed at the wobble position, there is selection against six- or nine-hydrogen-bonded codon-anticodon pairs. Our results indicate that an intrinsic codon preference, critically dependent on the stability of codon-anticodon interaction and mainly reflecting selection for the optimization of translational efficiency, is built into the translational apparatus.

Codon↗

Dual RNA isolation from blood: an optimized protocol for host and bacterial RNA purification for dual RNA-sequencing analysis in whole blood sepsis samples.

Dual RNA-sequencing (dual RNA-seq) holds significant promise for deciphering bacterial virulence mechanisms during systemic infections. However, its application in sepsis research is hindered by technical challenges, including a low bacterial burden in blood and limited sample volumes and RNA yield from vulnerable populations, such as neonates. We developed an optimized protocol [dual RNA isolation from blood (DRIB)] for simultaneous stabilization, isolation and purification of high-quality host leukocyte and bacterial RNA from low-volume whole blood samples (0.5&#x2009;ml). This protocol is compatible with clinical sample collection workflows and high-throughput RNA sequencing. The feasibility of DRIB for dual RNA-seq was validated using a pilot cohort of clinical adult sepsis samples, enabling the investigation of host-bacterial gene expression during sepsis. The DRIB protocol yielded 2.10-6.91&#x2009;&#xb5;g of total RNA per clinical sample in our pilot cohort. Dual-species ribosomal RNA (rRNA) depletion and RNA-seq generated 16.6-24.8&#x2009;million filtered reads per sample, with 63&#xb1;7% of reads uniquely mapped to host or bacterial sequences. Host genes accounted for 51-68% (8.4-10.9&#x2009;million) reads, while 0.5-6.7% (79,496-789,808 reads) mapped to bacterial genomes. Bioinformatic analysis revealed that both shared and individual transcriptional patterns were identified in host and bacterial responses, including pathways related to immune metabolism and metal-ion binding. Our optimized DRIB protocol and RNA-seq pipeline effectively captured both host and bacterial RNA transcription in clinical sepsis samples. Expanding this approach to larger cohorts and varying disease timepoints will provide crucial new insights into host-bacterial gene co-expression dynamics in sepsis progression and outcomes.

Humans↗

Ovarian development is driven by early spatiotemporal priming of the coelomic epithelium.

Ovarian organogenesis requires the coordinated specification of supporting and steroidogenic cell lineages from multipotent coelomic epithelium (CE) progenitors. A longstanding question is whether the CE contains transcriptionally distinct, spatially organized progenitor subpopulations with predetermined lineage biases, or whether specification into supporting and steroidogenic lineages occurs only after delamination and integration into the bipotential gonad. The developmental origins of granulosa cells and the emergence of ovarian steroidogenic/stromal progenitors (SPs) also remain poorly defined. Here, we show that CE cells covering the fetal mouse ovary are transcriptionally heterogeneous and spatially organized into subdomains already primed toward supporting or steroidogenic fates. CE priming is dynamic, with transient coexistence of supporting- and steroidogenic-biased CE progenitors before resolving into a predominantly supporting-biased CE. Local delamination of these primed cells seeds intragonadal niches where pre-granulosa cells and SPs mirror the spatio-temporal arrangements of CE-primed progenitors. We further demonstrate a dual origin for the supporting lineage, with granulosa cells deriving from both the CE and supporting-like cells (SLCs). In parallel, we show that SPs arise from steroidogenic-primed CE cells, expand to represent 52% of ovarian somatic cells at birth, persist into adulthood and contribute to both theca and steroidogenic stromal cells. Together, these findings reveal transcriptionally and spatially distinct CE subpopulations that shape somatic lineage emergence with important implications for ovarian pathophysiology.

Ovarian development↗

Probiotic Lacticaseibacillus casei 2S-1 Attenuates Escherichia coli-Induced Enteritis via Gut Microbiota Modulation and Host Gene Regulation.

Maintaining gut microbial homeostasis is crucial for host health, whereas infection with Escherichia coli (E. coli) is a major contributor to intestinal inflammation and microbial dysbiosis. Recent research has focused on probiotic strategies for managing enteric inflammatory disorders. Previous studies have shown that beneficial microorganisms show protection through modulating host immune responses, enhancing intestinal epithelial barrier integrity, and inhibiting pathogenic bacteria. To evaluate the prophylactic effectiveness of a recently isolated strain, Lacticaseibacillus casei 2S-1, in a murine model of E. coli-induced enteritis, this study focuses on interactions within the microbiota-intestinal-immune axis, together with host transcriptional responses and pathway enrichment associated with oxidative stress and mitochondrial function. In vitro analysis of probiotic features, including growth dynamics, acidogenic capacity, and tolerance to acidic and bile salt environments, as well as genetic safety profiling, followed the methodical isolation and taxonomic identification of L. casei 2S-1. A preventive intervention protocol was established, and a murine model of enteritis was induced by exposure to E. coli. Histopathological analyses were performed to observe in vivo safety and protective efficacy. Changes in gut microbial structure were characterized by 16S rRNA gene sequencing, while host responses were identified by intestinal immunohistochemistry and transcriptome profiling. L. casei 2S-1 showed probiotic properties. In vitro analyses showed that the strain exhibited tolerance to acidic and bile salt conditions, and its untreated culture supernatant showed antimicrobial activity against pathogenic bacteria. Its safety profile was supported by genomic analysis, which verified the lack of virulence-associated genes and antibiotic resistance factors. In vivo, L. casei 2S-1 pretreatment reduced mortality and intestinal inflammation, modulated gut microbial composition, and preserved intestinal barrier-associated protein expression in infected mice. This study provides experimental evidence supporting the prophylactic effects of L. casei 2S-1 and its associations with gut microbiota modulation and host transcriptional responses, providing a foundation for further investigation of probiotic-based preventive strategies against intestinal infections.

Animals↗

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↗