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PubMed2026

Integrating single-cell transcriptomics to construct an oncogene-driven prognostic model and elucidate metabolic-immune crosstalk in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths, its progression and treatment heterogeneity are mainly influenced by driver gene and tumor micro-environment (TME) interactions. Nevertheless, the mechanisms of this process at the single-cell level remain unclear. This study integrated TCGA and multi-center single-cell transcriptome data to identify a 575 genes HCC-specific core set, developing a single-cell "oncogene scoring" system to quantify individual carcinogenic activity. This score is significantly elevated in malignant and proliferative T cells and is closely associated with metabolic reprogramming, aberrant cell‒cell communication, and immunosuppressive phenotypes. Based on these characteristics, we constructed a machine learning-based Random Survival Forest (RSF) prognostic model validated in multiple independent cohorts, which classifies patients into distinct risk subtypes. The high-risk group exhibits genomic instability, increased tumor stemness, and immune evasion, while the low-risk group was more sensitive to drugs such as sorafenib. This study highlights the potential pathways by which high oncogenic activity is associated with HCC progression, suggesting a profound link with single-cell metabolic‒immune crosstalk. The constructed RSF model offers a promising computational framework for risk stratification and provides hypothesis-generating insights that may inform future personalized treatment strategies for HCC patients.

Hepatocellular carcinoma↗
PubMedDate not supplied

A DNA-binding peptide from a phage display library.

A DNA-binding peptide was selected from a random peptide phage display library. For competitive elution using the DNA methyltransferase M.TaqI in the selection step, a biotin-labeled duplex oligodeoxyribonucleotide containing the 5'-TCGA-3' recognition sequence of M.TaqI was employed. Nine of ten phages selected were found to have the same deduced amino acid sequence SVSVGMKPSPRP. The selected phage binds to DNA, as demonstrated in an ELISA.

Amino Acid Sequence↗
PubMed2026

Hypernetwork-guided fusion with intra-class MixUp for breast cancer subtyping.

Accurate breast cancer subtyping guides treatment selection, yet histopathology captures morphology without molecular state, while genomic profiling captures molecular signatures without spatial context. Existing fusion methods rely on concatenation, or on attention applied only after each modality is encoded independently. This work identifies a scale-dependent asymmetry in the direction of cross-modal conditioning: the direction that performs best under limited samples is not the one that holds at scale, and the reversal is traced to the capacity of the modulation pathway rather than to the fusion principle. The comparison is carried out within a hypernetwork-guided framework in which an auxiliary network maps one modality to conditioning parameters that modulate the other's feature representation, shaping features at the parametric level rather than the decision stage; modulation is patient-specific rather than patch-specific. Both directions are instantiated-gene-to-image (HyperG2I) and image-to-gene (HyperI2G) - and trained under a label-aware MixUp strategy that interpolates within-class samples across both modalities, preserving the hard binary labels clinical decisions require. The framework is evaluated on two paired TCGA-BRCA cohorts-one limited-sample, one independently assembled at scale-under a single protocol spanning two whole-slide representations, multiple visual backbones, and both conditioning directions. On the limited-sample cohort, gene-to-image conditioning at its optimal augmentation setting exceeds early fusion and both unimodal baselines, giving the highest recall on the aggressive Basal/HER2 class of any configuration evaluated, and an ablation favours intra-class over inter-class mixing. At scale this ordering does not hold: image-to-gene conditioning sustains its performance whereas gene-to-image does not, recovering only partially under the full tissue bag and isolating the capacity of the modulation pathway as the binding constraint. Direction and capacity of cross-modal conditioning, rather than fusion depth alone, therefore govern how such frameworks scale.

Breast Neoplasms↗
PubMed2026

AGRN activates GPX4 via the Wnt/beta-catenin signaling pathway to suppress ferroptosis in cervical cancer cells.

Cervical cancer remains a leading cause of cancer-related deaths among women worldwide. Targeting ferroptosis, a regulated form of cell death driven by lipid peroxidation, has emerged as a promising therapeutic strategy. This study aimed to elucidate the mechanisms by which cervical cancer cells acquire resistance to ferroptosis. AGRN expression and its prognostic significance were analyzed in cervical cancer using TCGA and GTEx data. In vitro, AGRN levels were measured in HeLa, CaSki, and Ect1/E6E7 cells via qRT-PCR. mRNA and protein expression levels of AGRN, beta-catenin, and ferroptosis-related markers were evaluated by qRT-PCR and western blot (WB). Cell viability, RSL3 sensitivity (IC50), and lipid ROS were assessed via CCK-8 assay and flow cytometry. In a xenograft model, RSL3's effect on tumor growth was examined. Immunohistochemistry (IHC) and molecular analyses (qRT-PCR, WB, and flow cytometry) were performed on tumor tissues to evaluate AGRN, beta-catenin, Ki-67, ferroptosis-related genes, and lipid ROS. It is found through research that, AGRN was significantly upregulated in cervical cancer tissues and cell lines. Its overexpression activated Wnt/beta-catenin signaling, resulting in elevated GPX4 and SLC7A11 levels and reduced CHAC1 and PTGS2 expression levels. These alterations decreased lipid ROS accumulation and enhanced resistance to RSL3-induced ferroptosis, an effect further confirmed in xenograft models. In short, In short, AGRN promotes ferroptosis resistance in cervical cancer by activating the Wnt/beta-catenin signaling pathway and upregulating GPX4 expression. Targeting the AGRN-Wnt/beta-catenin-GPX4 axis may represent a novel therapeutic approach for cervical cancer.

Humans↗
PubMed2025

miss-SNF: a multimodal patient similarity network integration approach to handle completely missing data sources.

MOTIVATION: Precision medicine leverages patient-specific multimodal data to improve prevention, diagnosis, prognosis, and treatment of diseases. Advancing precision medicine requires the non-trivial integration of complex, heterogeneous, and potentially high-dimensional data sources, such as multi-omics and clinical data. In the literature, several approaches have been proposed to manage missing data, but are usually limited to the recovery of subsets of features for a subset of patients. A largely overlooked problem is the integration of multiple sources of data when one or more of them are completely missing for a subset of patients, a relatively common condition in clinical practice. RESULTS: We propose miss-Similarity Network Fusion (miss-SNF), a novel general-purpose data integration approach designed to manage completely missing data in the context of patient similarity networks. miss-SNF integrates incomplete unimodal patient similarity networks by leveraging a non-linear message-passing strategy borrowed from the SNF algorithm. miss-SNF is able to recover missing patient similarities and is "task agnostic", in the sense that can integrate partial data for both unsupervised and supervised prediction tasks. Experimental analyses on nine cancer datasets from The Cancer Genome Atlas (TCGA) demonstrate that miss-SNF achieves state-of-the-art results in recovering similarities and in identifying patients subgroups enriched in clinically relevant variables and having differential survival. Moreover, amputation experiments show that miss-SNF supervised prediction of cancer clinical outcomes and Alzheimer's disease diagnosis with completely missing data achieves results comparable to those obtained when all the data are available. AVAILABILITY AND IMPLEMENTATION: miss-SNF code, implemented in R, is available at https://github.com/AnacletoLAB/missSNF.

Humans↗
PubMed2025

CrossAttOmics: multiomics data integration with cross-attention.

MOTIVATION: Advances in high throughput technologies enabled large access to various types of omics. Each omics provides a partial view of the underlying biological process. Integrating multiple omics layers would help have a more accurate diagnosis. However, the complexity of omics data requires approaches that can capture complex relationships. One way to accomplish this is by exploiting the known regulatory links between the different omics, which could help in constructing a better multimodal representation. RESULTS: In this article, we propose CrossAttOmics, a new deep-learning architecture based on the cross-attention mechanism for multiomics integration. Each modality is projected in a lower dimensional space with its specific encoder. Interactions between modalities with known regulatory links are computed in the feature representation space with cross-attention. The results of different experiments carried out in this article show that our model can accurately predict the types of cancer by exploiting the interactions between multiple modalities. CrossAttOmics outperforms other methods when there are few paired training examples. Our approach can be combined with attribution methods like LRP to identify which interactions are the most important. AVAILABILITY AND IMPLEMENTATION: The code is available at https://github.com/Sanofi-Public/CrossAttOmics and https://doi.org/10.5281/zenodo.15065928. TCGA data can be downloaded from the Genomic Data Commons Data Portal. CCLE data can be downloaded from the depmap portal.

Humans↗
PubMed2025

GE-IA-NAM: gene-environment interaction analysis via imaging-assisted neural additive model.

MOTIVATION: Gene-environment (G-E) interaction analysis is crucial in cancer research, offering insights into how genetic and environmental factors jointly influence cancer outcomes. Most existing G-E interaction methods are regression-based, which may lack flexibility to capture complex data patterns. Recent advances have investigated deep neural network-based G-E models. However, these methods may be more vulnerable to information deficiency due to challenges such as limited sample size and high dimensionality. Apart from genetic and environmental data, pathological images have emerged as a widely accessible and informative resource for cancer modeling, presenting its potential to enhance G-E modeling. RESULTS: We propose the pathological imaging-assisted neural additive model for G-E analysis (GE-IA-NAM). The flexible and interpretable additive network architecture is adopted to account for individualized effects associated with genetic factors, environmental factors, and their interactions. To improve G-E modeling, an assisted-learning strategy is investigated, which adopts a joint analysis to integrate information from pathological images. Simulations and the analysis of lung and skin cancer datasets from The Cancer Genome Atlas demonstrate the competitive performance of the proposed method. AVAILABILITY AND IMPLEMENTATION: Python code implementing the proposed method is available at https://github.com/Mr-maoge/NAM-IA-GE. The data that support the findings in this article are openly available in TCGA (The Cancer Genome Atlas) at https://portal.gdc.cancer.gov/.

Gene-Environment Interaction↗
PubMed2026

Robust prioritization of genomic features with stability selection.

MOTIVATION: The heterogeneity of complex diseases including cancer leads to heavy-tailed distributions in the disease traits. In such settings, non-robust variable selection methods are inherently susceptible to data contamination and can yield unstable or misleading results. This vulnerability becomes more severe for recently proposed approaches that introduce pseudo-features as negative controls, as these methods further amplify the curse of dimensionality by expanding the genotype matrix in the presence of outliers and high-dimensional genomic features. RESULTS: We develop a robust variable selection framework with stability selection to prioritize genomic features in the presence of contamination. In contrast to existing approaches that rely on pseudo-features for error control, the proposed method achieves double robustness. First, it adopts least absolute deviation (LAD) LASSO to ensure robustness against outliers and heavy-tailed errors in disease traits. Second, it avoids augmenting the genotype matrix with pseudo-features, thereby mitigating the curse of dimensionality that is particularly problematic in high-dimensional genomic data. The proposed method has been extensively evaluated in simulation studies to demonstrate its effectiveness over multiple competing methods for variable selection. In addition, we have applied the proposed method and competing approaches to two real-data case studies: the The Cancer Genome Atlas (TCGA) Skin Cutaneous Melanoma (SKCM) dataset and an eQTL dataset. The results demonstrate that the proposed method achieves superior performance by identifying genomic features with higher reproducibility. AVAILABILITY AND IMPLEMENTATION: The source code for implementing the proposed methods is publicly available at https://github.com/cenwu/RSS with an archival DOI https://doi.org/10.6084/m9.figshare.32306883.

Genomics↗
PubMed2026

Micropeptides encoded by lncRNAs associated with cancer progression reveal novel immunogenic epitopes.

MOTIVATION: Long non-coding RNAs (lncRNAs) regulate gene expression, chromatin organization, and cellular signaling. Recent studies indicate that ∼20% of the ∼36 000 human lncRNA genes harbor small open reading frames (sORFs) capable of producing micropeptides (MPs), whose functions remain largely unknown. Whether these peptides contribute to the cancer immunopeptidome is largely unexplored. RESULTS: We systematically analyzed lncRNAs with strong experimental and computational evidence of MP-encoding potential (∼13% of the initial MP collection). Using The Cancer Genome Atlas (TCGA), we identified 2606 high-confidence lncRNA-derived MPs encoded by 647 genes across 16 cancer types. We then focused on 501 MPs from 124 lncRNA genes whose expression changes significantly across tumor stages and metastatic transitions, representing cancer transitional lncRNAs (Tr-lncRNAs). Dipeptide composition and conservation analyses showed that these MPs differ from a size-matched human coding proteome, supporting their potential as neoantigens. All possible 9-mer peptides were evaluated for predicted binding to prevalent European HLA class I alleles. Approximately 60% of Tr-lncRNA genes and 184 (37%) of derived peptides exhibited strong predicted HLA binding. Peptides from XIST, PCAT7, PVT1, HAND2-AS1 showed broad HLA coverage. Notably, TTN-AS1, encoded an MP (79 aa) generated 33 predicted distinct epitopes spanning all 27 HLA alleles. Our analysis identifies lncRNA-derived MPs as a previously underexplored source of potential cancer neoantigens, highlighting their promise as biomarkers and targets for immunotherapy. AVAILABILITY: Data, code and supplementary materials are available in https://doi.org/10.5281/zenodo.20167452 and GitHub: https://github.com/stavzok1/lncrna_peptide_analysis.

Humans↗
PubMed1987

Cloning, sequencing and expression of the Taq I restriction-modification system.

The Taq I modification and restriction genes (recognition sequence TCGA) have been cloned in E. coli and their DNA sequences have been determined. Both proteins were characterized and the N-terminal sequence of the endonuclease was determined. The genes have the same transcriptional orientation with the methylase gene 5' to the endonuclease gene. The methylase gene is 1089 bp in length (363 amino acids, 40,576 daltons); the endonuclease gene is 702 bp in length (234 amino acids, 27,523 daltons); they are separated by 132 bp. Both methylase and endonuclease activity can be detected in cell extracts. The clones fully modify the vector and chromosomal DNA but they fail to restrict infecting phage. Clones carrying only the restriction gene are viable even in the absence of modification. The restriction gene contains 7 Taq I sites; the modification gene contains none. This asymmetric distribution of sites could be important in the regulation of the expression of the endonuclease gene.

Amino Acid Sequence↗
PubMed1987

Molecular cloning and characterization of the gene encoding the DNA methyltransferase, M.CviBIII, from Chlorella virus NC-1A.

The gene encoding the DNA methyltransferase, M.CviBIII, from Chlorella virus NC-1A was cloned and expressed in E. coli plasmid pUC8. Plasmid (pNC-1A.14.8) encoded M.CviBIII methylates adenine in TCGA sequences both in vivo in E. coli and in vitro. Transposon Tn5 mutagenesis localized the M.CviBIII functional domain to a 1.5 kbp region of pNC-1A.14.8 and also indicated that a virus promoter directs transcription of the gene in E. coli. The 2.1 kbp insert containing the M.CviBIII gene was sequenced and a single open reading frame of 1131 bp was identified within the domain determined by Tn5 mutagenesis. When the M.CviBIII gene was fused in-frame with the 19 amino-terminal codons of lacZ a 45 kD polypeptide was identified in maxicells as predicted by the DNA sequence. The M.CviBIII gene was not essential for virus replication since a virus M.CviBIII deletion mutant also replicated in Chlorella.

Amino Acid Sequence↗
PubMed1991

Sequence preferences of DNA interstrand crosslinking agents: quantitation of interstrand crosslink locations in DNA duplex fragments containing multiple crosslinkable sites.

A general approach to the quantitative study of the sequence specificity of DNA interstrand crosslinking agents in synthetic duplex DNA fragments is described. In the first step, a DNA fragment previously treated with an interstrand crosslinking agent is subjected to denaturing PAGE. Not only does this distinguish crosslinked from native or monoadducted DNA, it is shown herein that isomeric crosslinked DNAs differing in position of the crosslink can in some cases be separated. In the second stage, the now fractionated crosslinked DNAs isolated from denaturing PAGE are subjected to fragmentation using iron(II)/EDTA. For those fractions which are structurally homogeneous, analysis of the resulting fragment distribution has previously been shown to reveal the crosslink position at nucleotide resolution. It is shown herein that in fractions which are structurally heterogeneous due to differences in position of crosslink, this analysis quantifies the relative extent of crosslinking at distinct sites. Using this method it is shown that reductively activated mitomycin C crosslinks the duplex sequences 5'-GCGC and 5'-TCGA with 3 +/- 1:1 relative efficiency.

Base Sequence↗
PubMed1994

M.phi 3TII: a new monospecific DNA (cytosine-C5) methyltransferase with pronounced amino acid sequence similarity to a family of adenine-N6-DNA-methyltransferases.

The temperate B.subtilis phages phi 3T and rho 11s code, in addition to the multispecific DNA (cytosine-C5) methyltransferases (C5-MTases) M.phi 3TI and M.rho 11sI, which were previously characterized, for the identical monospecific C5-MTases M.phi 3TII and M.rho 11sII. These enzymes modify the C to TCGA sites, a novel target specificity among C5-MTases. The primary sequence of M.phi 3TII (326 amino acids) shows all conserved motifs typical of the building plan of C5-MTases. The degree of relatedness between M.phi 3TII and all other mono- or multispecific C5-MTases ranges from 30-40% amino acid identity. Particularly M.phi 3TII does not show pronounced similarity to M.phi 3TI indicating that both MTase genes were not generated from one another but were acquired independently by the phage. The amino terminal part of the M.phi 3TII (preceding the variable region 'V'), which predominantly constitutes the catalytic domain of the enzyme, exhibits pronounced sequence similarity to the amino termini of a family of A-N6-MTases, which--like M.Taql--recognize the general sequence TNNA. This suggests that recently described similarities in the general three dimensional organization of C5- and A-N6-MTases imply divergent evolution of these enzymes originating from a common molecular ancestor.

Amino Acid Sequence↗
PubMed1994

M.phi 3TII: a new monospecific DNA (cytosine-C5) methyltransferase with pronounced amino acid sequence similarity to a family of adenine-N6-DNA-methyltransferases.

The temperate B.subtilis phages phi 3T and rho 11s code, in addition to the multispecific DNA (cytosine-C5) methyltransferases (C5-MTases) M. phi 3TI and M. rho 11sI, which were previously characterized, for the identical monospecific C5-MTases M. phi 3TII and M. rho 11sII. These enzymes modify the C of TCGA sites, a novel target specificity among C5-MTases. The primary sequence of M. phi 3TII (326 amino acids) shows all conserved motifs typical of the building plan of C5-MTases. The degree of relatedness between M. phi 3TII and all other mono- or multispecific C5-MTases ranges from 30-40% amino acid identity. Particularly M. phi 3TII does not show pronounced similarity to M. phi 3TI indicating that both MTase genes were not generated from one another but were acquired independently by the phage. The amino terminal part of the M. phi 3TII (preceding the variable region 'V'), which predominantly constitutes the catalytic domain of the enzyme, exhibits pronounced sequence similarity to the amino termini of a family of A-N6-MTases, which--like M.TaqI--recognize the general sequence TNNA. This suggests that recently described similarities in the general three dimensional organization of C5- and A-N6-MTases imply divergent evolution of these enzymes originating from a common molecular ancestor.

Amino Acid Sequence↗
PubMed1997

Sensitivity of NMR internucleotide distances to B-DNA conformation: underlying mechanics.

Nuclear magnetic resonance (NMR) spectroscopy, combining correlated spectroscopy (COSY) coupling constant measurements with nuclear Overhauser effect spectroscopy (NOESY) interatomic distances, should make it possible to determine an averaged solution structure for DNA oligomers. However, even if such data could be obtained with high accuracy, it is not clear which structural parameters of DNA would be determined. Here, the relationships between measurable internucleotide distances and helical parameters are systematically studied through molecular modelling. Investigations are carried out using four representative sequences, (ACGT)n, (TCGA)n, (AGCT)n and (TGCA)n, composed of repeated tetranucleotides belonging to oligomers previously studied by NMR. Correlations between interatomic distances become evident and strong connections between distances and inter-base helical parameters are observed. Results imply that twist, roll, shift and slide values can be accurately determined from NMR data. Sequence independent mechanical coupling which link backbone and sugar conformations to helical twist are also described.

Base Sequence↗
PubMed1998

Chemical display of thymine residues flipped out by DNA methyltransferases.

The DNA cytosine-C5 methyltransferase M. Hha I flips its target base out of the DNA helix during interaction with the substrate sequence GCGC. Binary and ternary complexes between M. Hha I and hemimethylated DNA duplexes were used to examine the suitability of four chemical methods to detect flipped-out bases in protein-DNA complexes. These methods probe the structural peculiarities of pyrimidine bases in DNA. We find that in cases when the target cytosine is replaced with thymine (GTGC), KMnO4proved an efficient probe for positive display of flipped-out thymines. The generality of this procedure was further verified by examining a DNA adenine-N6 methyltransferase, M. Taq I, in which case an enhanced reactivity of thymine replacing the target adenine (TCGT) in the recognition sequence TCGA was also observed. Our results support the proposed base-flipping mechanism for adenine methyltransferases, and offer a convenient laboratory tool for detection of flipped-out thymines in protein-DNA complexes.

DNA (Cytosine-5-)-Methyltransferases↗
PubMed1999

Nucleotide analogs and new buffers improve a generalized method to enrich for low abundance mutations.

A high sensitivity method for detecting low level mutations is under development. A PCR reaction is performed in which a restriction site is introduced in wild-type DNA by alteration of specific bases. Digestion of wild-type DNA by the cognate restriction endonuclease (RE) enriches for products with mutations within the recognition site. After reamplification, mutations are identified by a ligation detection reaction (LDR). This PCR/RE/LDR assay was initially used to detect PCR error in known wild-type samples. PCR error was measured in low |Deltap K a| buffers containing tricine, EPPS and citrate, as well as otherwise identical buffers containing Tris. PCR conditions were optimized to minimize PCR error using perfect match primers at the Msp I site in the p53 tumor suppressor gene at codon 248. However, since mutations do not always occur within pre-existing restriction sites, a generalized PCR/RE/LDR method requires the introduction of a new restriction site. In principle, PCR with mismatch primers can alter specific bases in a sequence and generate a new restriction site. However, extension from 3' mismatch primers may generate misextension products. We tested conversion of the Msp I (CCGG) site to a Taq I site (TCGA). Conversion was unsuccessful using a natural base T mismatch primer set. Conversion was successful when modified primers containing the 6 H,8 H -3, 4-dihydropyrimido[4,5- c ][1,2]oxazine-7-one (Q6) base at 3'-ends were used in three cycles of preconversion PCR prior to conversion PCR using the 3' natural base T primers. The ability of the pyrimidine analog Q6 to access both a T-like and C-like tautomer appears to greatly facilitate the conversion.

Base Sequence↗
PubMed1980

A DNA methylase from Thermus thermophilus HB8.

A DNA methylase was purified in a homogeneous state from a extremely thermophilic bacterium, Thermus thermophilus HB8, by chromatography on, successively, phosphocellulose, CM-cellulose, and heparin-Sepharose. The molecular weight of the enzyme was determined to be about 44,000 by gel filtration on a Sephadex G-100 column and 41,000 by SDS-poly-acrylamide gel electrophoresis, and these findings suggest a single polypeptide enzyme. The enzyme develops maximum activity around pH 7.4 and at 70 degrees C. Enzymatic activity is completely inhibited by 0.2 M NaCl or 2 mM HgCl2. The enzyme transfers methyl groups from S-adenosyl-L-methionine to a double stranded DNA. The sole product of the reaction was identified as N-6-methyl adenine after hydrolysis of the DNA with formic acid. The enzyme kinetics obey the Michaelis-Menten equation and Km values for S-adenosylmethionine and lambda phage DNA were determined to be 0.8 muM and 10 microgram/ml, respectively. The enzyme does not transfer methyl groups to TthHB8I endonuclease digested DNA as well as the host (T. thermophilus HB8) DNA. The number of methyl groups of the fully methylated phiX174 RF DNA was about twice as many as TthHB8I endonuclease sites on the DNA. The distribution of the methyl groups of phiX174 RF DNA among the HaeIII fragments was the same as that of TthHB8I endonuclease sites, suggesting that this DNA methylase is the other component of the modification-restriction system including TthHB8I endonuclease. The enzyme probably recognizes the sequence, 5'-TCGA-3', in a double stranded DNA and probably methylates adenine in the above sequence.

Bacteriophage phi X 174↗