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PubMed2024

Understanding the biological processes of kidney carcinogenesis: an integrative multi-omics approach.

Biological mechanisms related to cancer development can leave distinct molecular fingerprints in tumours. By leveraging multi-omics and epidemiological information, we can unveil relationships between carcinogenesis processes that would otherwise remain hidden. Our integrative analysis of DNA methylome, transcriptome, and somatic mutation profiles of kidney tumours linked ageing, epithelial-mesenchymal transition (EMT), and xenobiotic metabolism to kidney carcinogenesis. Ageing process was represented by associations with cellular mitotic clocks such as epiTOC2, SBS1, telomere length, and PBRM1 and SETD2 mutations, which ticked faster as tumours progressed. We identified a relationship between BAP1 driver mutations and the epigenetic upregulation of EMT genes (IL20RB and WT1), correlating with increased tumour immune infiltration, advanced stage, and poorer patient survival. We also observed an interaction between epigenetic silencing of the xenobiotic metabolism gene GSTP1 and tobacco use, suggesting a link to genotoxic effects and impaired xenobiotic metabolism. Our pan-cancer analysis showed these relationships in other tumour types. Our study enhances the understanding of kidney carcinogenesis and its relation to risk factors and progression, with implications for other tumour types.

Kidney Neoplasms↗
PubMed2025

Trajectory inference from single-cell genomics data with a process time model.

Single-cell transcriptomics experiments provide gene expression snapshots of heterogeneous cell populations across cell states. These snapshots have been used to infer trajectories and dynamic information even without intensive, time-series data by ordering cells according to gene expression similarity. However, while single-cell snapshots sometimes offer valuable insights into dynamic processes, current methods for ordering cells are limited by descriptive notions of "pseudotime" that lack intrinsic physical meaning. Instead of pseudotime, we propose inference of "process time" via a principled modeling approach to formulating trajectories and inferring latent variables corresponding to timing of cells subject to a biophysical process. Our implementation of this approach, called Chronocell, provides a biophysical formulation of trajectories built on cell state transitions. The Chronocell model is identifiable, making parameter inference meaningful. Furthermore, Chronocell can interpolate between trajectory inference, when cell states lie on a continuum, and clustering, when cells cluster into discrete states. By using a variety of datasets ranging from cluster-like to continuous, we show that Chronocell enables us to assess the suitability of datasets and reveals distinct cellular distributions along process time that are consistent with biological process times. We also compare our parameter estimates of degradation rates to those derived from metabolic labeling datasets, thereby showcasing the biophysical utility of Chronocell. Nevertheless, based on performance characterization on simulations, we find that process time inference can be challenging, highlighting the importance of dataset quality and careful model assessment.

Single-Cell Analysis↗
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↗
PubMed2004

Analysis of Bothrops jararacussu venomous gland transcriptome focusing on structural and functional aspects: I--gene expression profile of highly expressed phospholipases A2.

Snake venom glands are a rich source of bioactive molecules such as peptides, proteins and enzymes that show important pharmacological activity leading to in local and systemic effects as pain, edema, bleeding and muscle necrosis. Most studies on pharmacologically active peptides and proteins from snake venoms have been concerned with isolation and structure elucidation through methods of classical biochemistry. As an attempt to examine the transcripts expressed in the venom gland of Bothrops jararacussu and to unveil the toxicological and pharmacological potential of its products at the molecular level, we generated 549 expressed sequence tags (ESTs) from a directional cDNA library. Sequences obtained from single-pass sequencing of randomly selected cDNA clones could be identified by similarities searches on existing databases, resulting in 197 sequences with significant similarity to phospholipase A(2) (PLA(2)), of which 83.2% were Lys49-PLA(2) homologs (BOJU-I), 0.1% were basic Asp49-PLA(2)s (BOJU-II) and 0.6% were acidic Asp49-PLA(2)s (BOJU-III). Adjoining this very abundant class of proteins we found 88 transcripts codifying for putative sequences of metalloproteases, which after clustering and assembling resulted in three full-length sequences: BOJUMET-I, BOJUMET-II and BOJUMET-III; as well as 25 transcripts related to C-type lectin like protein including a full-length cDNA of a putative galactose binding C-type lectin and a cluster of eight serine-proteases transcripts including a full-length cDNA of a putative serine protease. Among the full-length sequenced clones we identified a nerve growth factor (Bj-NGF) with 92% identity with a human NGF (NGHUBM) and an acidic phospholipase A(2) (BthA-I-PLA(2)) displaying 85-93% identity with other snake venom toxins. Genetic distance among PLA(2)s from Bothrops species were evaluated by phylogenetic analysis. Furthermore, analysis of full-length putative Lys49-PLA(2) through molecular modeling showed conserved structural domains, allowing the characterization of those proteins as group II PLA(2)s. The constructed cDNA library provides molecular clones harboring sequences that can be used to probe directly the genetic material from gland venom of other snake species. Expression of complete cDNAs or their modified derivatives will be useful for elucidation of the structure-function relationships of these toxins and peptides of biotechnological interest.

Amino Acid Sequence↗
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↗
PubMed2005

Functional genomics in antibacterial drug discovery.

Antibacterial drug discovery has experienced a paradigm shift from phenotypic screening for antibacterial activity to rational inhibition of preselected targets. Functional genomics techniques are implemented at various stages of the early drug discovery process and play a central role in target validation and mode of action determination. The spectrum of methods ranges from genetic manipulations (e.g. knockout studies, mutation analyses and the construction of conditional mutants) to transcriptome and proteome expression profiling. Functional genomics supports antibacterial drug discovery by improving knowledge on gene function, bacterial physiology and virulence and the effects of antibiotics on bacterial metabolism.

Animals↗
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↗
PubMed2003

Effects of oxygen and light intensity on transcriptome expression in Rhodobacter sphaeroides 2.4.1. Redox active gene expression profile.

The roles of oxygen and light on the regulation of photosynthesis gene expression in Rhodobacter sphaeroides 2.4.1 have been well studied over the past 50 years. More recently, the effects of oxygen and light on gene regulation have been shown to involve the interacting redox chains present in R. sphaeroides under diverse growth conditions, and many of the redox carriers comprising these chains have been well studied. However, the expression patterns of those genes encoding these redox carriers, under aerobic and anaerobic photosynthetic growth, have been less well studied. Here, we provide a transcriptional analysis of many of the genes comprising the photosynthesis lifestyle, including genes corresponding to many of the known regulatory elements controlling the response of this organism to oxygen and light. The observed patterns of gene expression are evaluated and discussed in light of our knowledge of the physiology of R. sphaeroides under aerobic and photosynthetic growth conditions. Finally, this analysis has enabled to us go beyond the traditional patterns of gene expression associated with the photosynthesis lifestyle and to consider, for the first time, the full complement of genes responding to oxygen, and variations in light intensity when growing photosynthetically. The data provided here should be considered as a first step in enabling one to model electron flow in R. sphaeroides 2.4.1.

Gene Expression Profiling↗
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↗
PubMed2004

Genomewide analysis of gene expression in Staphylococcus epidermidis biofilms: insights into the pathophysiology of S. epidermidis biofilms and the role of phenol-soluble modulins in formation of biofilms.

Many bacterial pathogens form cellular agglomerations known as biofilms, which considerably limit the success of both antibiotic treatment and the human immune defense. To gain insight into the pathophysiology of the leading nosocomial pathogen, Staphylococcus epidermidis, we analyzed the genome of biofilm-forming S. epidermidis, constructed a microarray representing its entire transcriptome, and performed expression profiling of an S. epidermidis biofilm. Gene-regulated processes in the biofilm led to a nonaggressive and protected form of bacterial growth with low metabolic activity, which is optimally suited to guarantee long-term survival during chronic infection. A class of peptides known as phenol-soluble modulins, which combine proinflammatory activity with a putative role in detachment of biofilms, evolved as potential key determinants controlling the switch between aggressive and quiescent modes of infection. Our data suggest that S. epidermidis adjusts its lifestyle to varying requirements during colonization and infection by means of an expansive change of gene expression. The observed physiological characteristics of the biofilm mode of growth--in particular, the contribution of surfactant-like peptides--might serve as a model for a variety of biofilm-forming pathogens.

Bacterial Toxins↗
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↗
PubMed2006

The gene controlling the quantitative trait locus EPITHIOSPECIFIER MODIFIER1 alters glucosinolate hydrolysis and insect resistance in Arabidopsis.

Glucosinolates are sulfur-rich plant secondary metabolites whose breakdown products have a wide range of biological activities in plant-herbivore and plant-pathogen interactions and anticarcinogenic properties. In Arabidopsis thaliana, hydrolysis by the enzyme, myrosinase, produces bioactive nitriles, epithionitriles, or isothiocyanates depending upon the plant's genotype and the glucosinolate's structure. A major determinant of this structural specificity is the epithiospecifier locus (ESP), whose protein causes the formation of epithionitriles and nitriles. A quantitative trait locus (QTL) on chromosome 3 epistatically affects nitrile formation in combination with ESP; this QTL has been termed EPITHIOSPECIFIER MODIFIER1 (ESM1). We identified a myrosinase-associated protein as the ESM1 QTL in Arabidopsis using map-based cloning with recombinant inbred lines, natural variation transcriptomic analysis, and metabolic profiling. In planta and in vitro analyses with natural ESM1 alleles, ESM1 knockouts, and overexpression lines show that ESM1 represses nitrile formation and favors isothiocyanate production. The glucosinolate hydrolysis profile change influenced by ESM1 is associated with the ability to deter herbivory by Trichoplusia ni. This gene could provide unique approaches toward improving human nutrition.

Animals↗
PubMed2006

Multifunctional drugs with different CNS targets for neuropsychiatric disorders.

The multiple disease etiologies that lead to neuropsychiatric disorders, such as Parkinson's and Alzheimer's disease, amyotrophic lateral sclerosis, Huntington disease, schizophrenia, depressive illness and stroke, offer significant challenges to drug discovery efforts aimed at preventing or even reversing the progression of these disorders. Transcriptomic tools and proteomic profiling have clearly indicated that such diseases are multifactorial in origin. Further, they are thought to be initiated by a cascade of molecular events that involve several neurotransmitter systems. In response to this complexity, a new paradigm has recently emerged that challenges the widely held assumption that 'silver bullet' agents are superior to 'dirty drugs' in therapeutic approaches aimed at the prevention or treatment of neuropsychiatric diseases. A similar pattern of drug development has occurred in strategies for the treatment of cancer, AIDS and cardiovascular diseases. In this review, we offer an overview of therapeutic strategies and novel investigative drugs discovered or developed in our own and other laboratories, that address multiple CNS etiological targets associated with an array of neuropsychiatric disorders.

Animals↗
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↗