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PubMed2026

Multi-Omics Biomarker Signatures for Precision Diagnosis and Prognosis in Primary Liver Cancer: A Literature Review.

Primary liver cancer (PLC) is a biologically heterogeneous group of malignancies dominated by hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (iCCA), and a smaller subset of combined hepatocellular-cholangiocarcinoma (cHCC-CCA), and its clinical burden remains high because current diagnostic and prognostic tools do not adequately capture molecular diversity. Conventional imaging, serum markers, and histopathological assessment remain insufficient for precise early diagnosis, subtype-resolved classification, and outcome stratification, while tissue and liquid biopsy approaches have expanded the range of analytes available for clinical assessment. Recent studies have identified candidate biomarker signatures across genomic, epigenomic, transcriptomic, proteomic, metabolomic, and circulating layers, suggesting that integrated multi-omics profiling may better represent tumor lineage, clonal evolution, immune context, and therapeutic vulnerability than isolated molecular readouts. However, these layers are not equally mature for clinical use: genomic testing is closest to routine therapeutic application in iCCA, plasma methylation assays are advancing for HCC surveillance augmentation, and many proteomic or metabolomic panels remain validation-stage tools. Their clinical value remains constrained by sampling bias, biospecimen-dependent signal loss, assay standardization, cost, and the need for prospective validation across clinically diverse populations. This narrative review critically synthesizes current evidence on multi-omics biomarker signatures for precision diagnosis and prognosis in primary liver cancer and argues that clinically useful signatures should be question-specific, stage-aware, and specimen-aware rather than universal multi-analyte panels.

Humans↗

PubMed2026

A Risk Score for Polycystic Ovary Syndrome Based on Meta-Analysis and Machine Learning of Gut Microbiota Signatures.

Polycystic Ovary Syndrome (PCOS) is a prevalent endocrine and metabolic disorder among reproductive-age women, in which emerging evidence suggests a substantial role played by the gut microbiota. To comprehensively evaluate gut microbiota alterations in PCOS and identify microbial biomarkers through integrated analysis, a systematic search of PubMed, Web of Science, and Embase was conducted for studies employing 16S rRNA gene sequencing of fecal samples from PCOS cohorts. Ten eligible PCOS cohorts, comprising 858 individuals, were included in the study, from which a risk score was derived using a 20-gene gut microbial signature associated with PCOS. Meta-analysis at the genus level identified that Subdoligranulum, NK4A214_group, and Collinsella significantly decreased, and Bacteroides increased in PCOS across multiple cohorts. Machine learning analysis identified a 20-genus microbial signature using the least absolute shrinkage and selection operator (LASSO) method, which was used to construct a risk score with an AUC of 0.835 in diagnosis prediction. Network analysis further identified Negativibacillus and Lachnospiraceae_UCG_010 as potential driver microbes in PCOS. The analysis in this study highlights key alterations in the gut microbiota across PCOS cohorts. The identified gut microbial signature and derived LASSO-based risk model offer novel insights and a potential tool for PCOS diagnosis.

Polycystic Ovary Syndrome↗

PubMed2025

Whole-genome sequencing identifies genetic diversity and adaptive signatures of hypoxia and ultraviolet radiation in Chinese chickens.

INTRODUCTION: Domestic chickens primarily descended from the wild red junglefowl, play a crucial role in global egg and meat production. China hosts diverse indigenous chicken populations that have adapted to various environmental conditions, including high-altitude with hypoxic and ultraviolet radiation stress. METHOD: We analyzed whole-genome sequences of 118 birds from five Indigenous Chinese chicken populations and 295 chicken genomes from publicly available databases to identify genomic diversity, admixture, and selection signatures of chickens adapted to high-altitude environments. Selection signatures were identified using nucleotide diversity (π), Tajima's D, XPEHH, and XP-CLR, selection scan methods. RESULTS: We observed a reduction in genetic diversity and historical declines in effective population size in high-altitude chicken, suggesting ongoing selection pressures shaping these populations. Selection scans identified nine genomic regions under strong positive selection, enriched for genes associated with hypoxia and ultraviolet radiation. Notably, five genes (TPK1, BAZ2B, MARCHF7, LLGL2, and RCAN3) were repeatedly detected across multiple selection signature analyses. RNA-seq analysis further confirmed the differential expression of these genes in the lung and heart tissues of chickens adapted to high and low altitudes, reinforcing their role in physiological adaptation to hypoxic environments. Altitude adaptation is driven by the selection of genes involved in oxygen metabolism, cellular stress response, and energy regulation. CONCLUSION: Our study provides compelling genetic evidence for differentiation between high and low and high-altitude Chinese chicken populations. These findings also ensure our understanding of local adaptation in poultry and establish a genomic framework for breeding strategies to improve environmental resilience to altitude-related stressors.

Animals↗

PubMed2025

A novel glycogene-related signature for prognostic prediction and immune microenvironment assessment in kidney renal clear cell carcinoma.

BACKGROUND: Kidney Renal Clear Cell Carcinoma (KIRC) is a prevalent urinary malignancies worldwide. Glycosylation is a key post-translational modification that is essential in cancer progression. However, its relationship with prognosis, tumour microenvironment (TME), and treatment response in KIRC remains unclear. METHOD: Expression profiles and clinical data were retrieved from The Cancer Genome Atlas and Gene Expression Omnibus databases. Consensus clustering, Cox regression, and LASSO regression analyses were conducted to develop an optimal glycogene-related signature. The prognostic relevance of this molecular signature was rigorously analyzed, along with its connections to tumour microenvironment (TME), tumour mutation burden, immune checkpoint activity, cancer-immunity cycle regulation, immunomodulatory gene expression patterns, and therapeutic response profiles. Validation was performed using real-world clinical specimens, quantitative PCR (qPCR), and immunohistochemistry (IHC), supported by cohort analyses from the Human Protein Atlas (HPA) database. RESULTS: A glycogene-associated prognostic scoring system was established to categorize patients into risk-stratified subgroups. Patients in the high-risk cohort exhibited significantly poorer survival outcomes (p < 0.001). By incorporating clinicopathological variables into this framework, we established a predictive nomogram demonstrating strong calibration and a concordance index (C-index) of 0.78. The high-risk subgroup displayed elevated immune infiltration scores (p < 0.001), upregulated expression of immune checkpoint-related genes (p < 0.05), and an increased frequency of somatic mutations (p = 0.043). The risk score positively correlated with cancer-immunity cycle activation and immunotherapy-related signals. The high-risk groups also showed associations with T cell exhaustion, immune-activating genes, chemokines, and receptors. Drug sensitivity analysis revealed that low-risk patients were more sensitive to sorafenib, pazopanib, and erlotinib, whereas high-risk individuals responded better to temsirolimus (p < 0.01). qPCR and IHC analyses consistently revealed distinct expression patterns of MX2 and other key genes across the risk groups, further corroborated by the HPA findings. CONCLUSION: This glycogene-based signature provides a robust tool for predicting prognosis, TME characteristics, and therapeutic responses in KIRC, offering potential clinical utility in patient management.

Humans↗

PubMed2026

Mutational signatures in blood-brain barrier: mechanisms, computational insights, and clinical applications in precision oncology.

The blood - brain barrier (BBB) plays a central role in maintaining central nervous system (CNS) homeostasis, and its disruption is a defining feature of malignant brain tumors such as glioblastoma. Emerging evidence indicates that BBB dysfunction not only alters the tumor microenvironment but also shapes the mutational processes that drive genomic instability in CNS malignancies. This review synthesizes current understanding of the biological mechanisms linking BBB breakdown with distinct mutational signatures, including those arising from oxidative stress, hypoxia-induced replication stress, lipid peroxidation, inflammation, and metabolic reprogramming. Advances in next-generation sequencing, coupled with computational tools such as non-negative matrix factorization, Bayesian modeling, and deep learning, have enabled precise extraction of these signatures and their integration with multi-omics data. Clinically, BBB-associated mutational signatures offer significant promise for therapeutic stratification, prediction of treatment response, and noninvasive monitoring through cerebrospinal fluid - derived circulating tumor DNA. Despite these advances, challenges persist due to limited tissue accessibility, low-yield CSF samples, incomplete mechanistic models, and the lack of CNS-specific analytical frameworks. A deeper understanding of BBB-driven mutational processes, supported by improved computational approaches and integrative datasets, holds potential to advance precision oncology in neuro-oncology.

Humans↗

PubMed2026

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 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↗

PubMed2000

Signature-based analysis of MET proto-oncogene mutations using DHPLC.

Research tools which improve mutation detection, SNP discovery, and allele characterization will facilitate studies of cancer, inherited disease, and genomic evolution. Denaturing High-Performance Liquid Chromatography (DHPLC) is a recently developed methodology for detection of heteroduplexes formed in DNA samples containing mismatches between wild type and mutant strands. In an effort to develop a rapid, sensitive mutation detection method for studies of families with inherited kidney cancer, we evaluated DHPLC for detection and analysis of MET proto-oncogene mutations in papillary renal carcinomas (PRC). We found DHPLC to be 100% accurate in detecting 15 known disease-associated MET mutations. Significantly, each MET mutation and two novel SNPs generated a characteristic chromatographic profile or signature with reproducible distinguishing features. Standardization of DHPLC reagents and improved methods design were critical to the reliability and accuracy of mutation prediction. Improvements included addition of a 75% acetonitrile wash followed by a rejuvenating gradient, and detailed analysis of signature shape, retention time (RT), RT differences (DeltaRT), and temperature-dependent (melt) profiling. We used signatures to predict mutations in new PRC samples, mutation carriers in asymptomatic hereditary PRC family members, and in a blind study of previously characterized DNAs. Application to SNP discovery is discussed. Wiley-Liss, Inc.

Carcinoma, Renal Cell↗

PubMed2002

Circular dichroism signatures of features simultaneously present in structured guanine-rich oligonucleotides: a combined spectroscopic and electrophoretic approach.

In order to identify possible signatures of the most typical structures adopted by guanine-rich oligonucleotides, we submitted them to the crossed fire of circular dichroism (CD) and electrophoresis. These signatures show up in the circular dichroism spectra even when simultaneously present within the same molecule. Guanine-rich oligonucleotides, when structured, manifest themselves by CD contributions around 260 or 295 nm. For instance, positive bands at 264 nm and 295 nm, respectively, signal the parallel and antiparallel guanine quartets, while a positive band around 261 nm may indicate the presence of a (parallel?) Hoogsteen duplex. A positive band at 264 nm may also reflect the presence of rigidly and unusually oriented GpT and TpG steps within loops. The signatures are additive with those of other structural features of the same molecule, such as hairpins or Watson-Crick duplexes, whose bands are observed at 280 nm.

Base Sequence↗

PubMed2026

Identifying gene expression signatures for risk stratification of postoperative adjuvant chemotherapy in colorectal cancer.

Clinical risk stratification for postoperative recurrence in patients with pathological stage II (pStage II) colorectal cancer (CRC) is essential for guiding the use of postoperative adjuvant chemotherapy (ACT). In this study, we identified novel prognostic gene expression biomarkers in patients with pStage II CRC and developed a new risk stratification framework for ACT decision-making. First, genome-wide biomarker discovery was conducted to identify prognostic gene expression biomarkers associated with recurrence risk in pStage II CRC. This analysis identified 10 differentially expressed genes as potential biomarkers for recurrence. The efficacy of these biomarkers was then tested using 188 clinical surgical specimens obtained from patients with pStage II CRC. A predictive panel was developed using qRT-PCR and used to assess 93 clinical specimens with an area under the curve (AUC) of 0.82, and its performance was further validated in an independent cohort (n = 95). By incorporating key clinicopathological features, a Gene expression-based Prediction of Recurrence in pStage II CRC (GPRSC) signature was developed, which robustly predicted postoperative recurrence (AUC: 0.80). Finally, combining the GPRSC signature, microsatellite instability status, and conventional criteria, we developed a novel risk stratification system for postoperative ACT decision-making in pStage II CRC. Overall, we identified novel gene expression biomarkers and developed a prognostic signature that informs clinical decision-making regarding postoperative ACT in patients with pStage II CRC.

Humans↗

PubMed2004

Blood transcriptional signatures of multiple sclerosis: unique gene expression of disease activity.

Multiple sclerosis (MS) is a central nervous system disease with an unpredictable course and outcome. Peripheral blood mononuclear cells (PBMCs) are involved in the disease pathogenesis and induce active demyelination. Using oligonucleotide microarrays, we identified a statistically significant transcriptional signature of 1,109 genes in PBMCs from 26 MS patients, irrespective of disease activation state or immunomodulatory treatment. This signature contains genes that implicate underlying processes involved in MS pathogenesis including T-cell activation and expansion, inflammation, and apoptosis. Another transcriptional signature of 721 genes involved in cellular recruitment, epitope spreading, and escape from regulatory immune surveillance identified MS patients in acute relapse compared with remission. Our results offer new opportunity for understanding the mechanisms involved in MS and indicate that gene expression patterns in PBMCs contain information about a remote-target disease process that may be useful for diagnosis and future tailoring of therapeutic strategies for MS.

Adjuvants, Immunologic↗

PubMed2005

A signature-based method to distinguish time-of-flight secondary-ion mass spectra from biological samples.

Time-Of-Flight Mass Spectrometry (TOF-SIMS) was used to determine elemental and biomolecular ions from isolated protein samples. We identified a set of 23 mass-to-charge ratio (m/z) peaks that represent signatures for distinguishing biological samples. The 23 peaks were identified by Singular Value Decomposition (SVD) and Canonical Analysis (CA) to find the underlying structure in the complex mass-spectra data sets. From this modified data, SVD was used to identify sets of m/z peaks, and we used these patterns from the TOF-SIMS data to predict the biological source from which individual mass spectra were generated. The signatures were validated using an additional data set different from the initial training set used to identify the signatures. We present a simple method to identify multiple variables required for sample classification based on mass spectra that avoids overfit. This is important in a variety of studies using mass spectrometry, including the ability to identify proteins in complex mixtures and for the identification of new biomarkers.

Biological Products↗

PubMed2026

Coordinated inflammatory macrophage and vascular smooth muscle cell remodeling signatures in human atherosclerosis: An integrative single-cell and bulk transcriptomic analysis.

Atherosclerotic plaque progression is shaped by coordinated inflammatory and remodeling programs involving immune cells and vascular wall cells. Inflammatory macrophage activation and vascular smooth muscle cell (VSMC) phenotypic remodeling are central features of human atherosclerosis, but their transcriptomic relationships during plaque progression remain incompletely characterized. This study integrated single-cell and bulk transcriptomic datasets to examine highly inflammatory macrophage states, VSMC remodeling-related transcriptional programs, and candidate ligand-receptor expression patterns in human atherosclerotic plaques. Human atherosclerotic plaque single-cell RNA sequencing data from GSE260657 and bulk transcriptomic data from GSE28829 were analyzed. After quality control, 7628 cells were retained for single-cell analysis. Major cell types were annotated using canonical markers, followed by reclustering of macrophages and VSMC-related cells. Functional module scoring, differential expression analysis, Gene Ontology biological process enrichment, and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed to characterize macrophage transcriptional states. Slingshot was applied to infer VSMC pseudotime ordering. CellChat and NicheNet were used to prioritize candidate ligand-receptor expression patterns and ligand-associated VSMC target gene programs. External bulk transcriptomic analysis was performed to examine whether single-cell-derived inflammatory and remodeling signatures were represented at the tissue-transcriptome level during plaque progression. Macrophage reclustering identified a highly inflammatory macrophage state characterized by prominent inflammatory activation, cytokine-response, and stress-response features. Genes upregulated in this population were enriched in pathways related to tumor necrosis factor (TNF) response, nuclear factor kappa B signaling, leukocyte activation, cytokine signaling, lipid and atherosclerosis, toll-like receptor signaling, and inflammasome-associated inflammation. VSMC reclustering revealed contractile VSMCs, PTHLH+ synthetic VSMCs, KRT7+ VSMC-like cells, interferon-responsive VSMCs, pericyte-like mural cells, and osteogenic/modulated VSMCs. Pseudotime analysis showed a broad contractile-to-osteogenic/modulated transcriptional continuum accompanied by increased expression of remodeling-associated genes and selected inflammatory or remodeling-associated receptor genes. CellChat and NicheNet analyses prioritized candidate ligand-receptor and ligand-associated target gene expression patterns involving SPP1-CD44, TNF-TNFRSF1A, IL1B-IL1R1/IL1RAP, MIF-ACKR3, PDGFB-PDGFRB, and FN1-SDC1/ITGB1. In GSE28829, inflammatory macrophage-, osteogenic/modulated VSMC-, candidate ligand-receptor expression-, SPP1-CD44 candidate axis-, and NicheNet-prioritized target program-related signatures were more prominent in advanced plaques and were positively correlated with each other. This integrative transcriptomic analysis identified a highly inflammatory macrophage state and a VSMC remodeling continuum in human atherosclerotic plaques. Candidate ligand-receptor and ligand-associated target gene expression patterns linked inflammatory macrophage activation with osteogenic/modulated VSMC remodeling at the computational level. External bulk data further showed coordinated enrichment of inflammatory and remodeling signatures in advanced plaques. These findings provide a descriptive and hypothesis-generating transcriptomic framework for understanding inflammatory macrophage activation and VSMC remodeling in human atherosclerosis.

atherosclerosis↗

PubMed2026

Age-Associated Four-Gene Prognostic Signature in Breast Cancer.

BACKGROUND: Young-onset breast cancer is associated with inferior disease-free survival (DFS), but the contribution of additional molecular heterogeneity remains unclear. AIMS: To identify an exploratory age-associated gene expression signature linked to recurrence-related outcomes and evaluate its prognostic association. METHODS AND RESULTS: We analyzed clinicopathological and RNA-sequencing data from 821 patients with Stages I-III invasive ductal or lobular carcinoma in The Cancer Genome Atlas, including 142 patients aged ≤ 45 years. Genes associated with both age and DFS were screened, followed by LASSO-Cox and stepwise multivariable Cox regression. A four-gene signature (Sig4: C4orf14 [NOA1], LINC01124, ZNF704, and AGFG2) was identified. Young patients had significantly worse DFS than older patients, whereas overall and disease-specific survival did not differ significantly. After adjustment for clinicopathological factors, young age remained associated with worse DFS. Following inclusion of the continuous Sig4 score, the age association was attenuated and no longer statistically significant, while Sig4 remained independently associated with worse DFS. Sig4-high tumors were enriched for proliferation, cell-cycle, DNA-repair, metabolic, and stress-response pathways. In METABRIC, the fixed TCGA-derived Sig4 score was associated with worse relapse-free survival in the overall cohort but not in patients aged ≤ 45 years. CONCLUSION: Sig4 is an exploratory age-associated four-gene signature with potential general prognostic relevance in breast cancer. Its utility for risk stratification specifically in young-onset breast cancer was not externally validated and requires confirmation in independent prospective cohorts enriched for young patients.

Humans↗

PubMed1991

Individual olfactory signatures as major determinants of early maternal discrimination in sheep.

Responses of recently parturient ewes to their familiar versus separated (i.e., unfamiliar) twin lambs were observed in an attempt to elucidate further the characteristics of the phenotypic traits (signatures) mediating maternal recognition and bonding. Ewes responded more positively to their familiar lamb than to its twin that had been isolated at birth. Nonetheless, those same mothers also discriminated between their separated twin and unfamiliar alien lambs. Alien lambs elicited similar rejection behavior regardless of whether they had been housed with their own mother or in isolation prior to testing. Lambs appear to have individually distinct (olfactory) signatures; however, the signatures of twin siblings may be sufficiently similar to enable the mother to detect a resemblance. No evidence suggests that acquired maternal labels play a role in either the acceptance of the ewe's own lamb(s) or rejection of aliens.

Animals↗

PubMed2005

Pattern robustness of diagnostic gene expression signatures in leukemia.

Microarray technology has been proposed as an addition to the methods in current use for diagnosing leukemia. Before a new technology can be used in a diagnostic setting, the method has to be shown to produce robust results. It is known that, given the technical aspects of specimen sampling and target preparation, global gene expression patterns can change dramatically. Various parameters such as RNA degradation, shipment time, sample purity, and patient age can principally influence measured gene expression. However, thus far, no information has been available on the robustness of a diagnostic gene expression signature. We demonstrate here that for a subset of acute leukemia, expression profiling is applicable in a diagnostic setting, considering various influencing parameters. With the use of a set of differentially expressed genes, that is, a diagnostic gene expression signature, four genetically defined acute myeloid leukemia subtypes with recurrent chromosomal aberrations can clearly be identified. In addition, we show that preparation by different operators and using different sample-handling procedures did not impair the robustness of diagnostic expression signatures. In conclusion, our results provide additional support for the applicability of microarrays in a diagnostic setting, and we have been encouraged to enroll patients in a prospective study in which microarrays will be tested as an additional routine diagnostic method in parallel with standard diagnostic procedures.

Adult↗

PubMed2006

Genomic alterations in lobular neoplasia: a microarray comparative genomic hybridization signature for early neoplastic proliferationin the breast.

The identification of genomic alterations occurring in neoplastic lesions provides insight into both lesion occurrence and disease progression. In this study, we used microarray comparative genomic hybridization (CGH) to investigate genetic changes in atypical lobular hyperplasia (ALH) and lobular carcinoma in situ (LCIS), as the presence of these lobular neoplastic lesions is an indicator of risk in the development of invasive breast cancer. DNA was extracted from microdissected archival breast tissue containing ALH or LCIS, lacking adjacent invasive carcinoma, and subjected to whole-genome tiling path microarray-CGH using the submegabase resolution tiling set (SMRT)-array platform. Twelve ALH and 13 LCIS lesions were examined. Copy number alterations were identified using statistical criteria and validated with Real-Time PCR and fluorescence in situ hybridization. From statistical analysis, a greater number of alterations were observed in ALH compared to LCIS. Alterations common to ALH include gain at 2p11.2 and loss at 7p11-p11.1 and 22q11.1. Alterations common to LCIS include gain at 20q13.13 and loss at 19q13.2-q13.31. In both ALH and LCIS, we observed loss of 16q21-q23.1, an altered region previously identified in lobular neoplasia and invasive carcinoma. The validation of select alterations reinforces the genomic signature. This study represents the first whole-genome investigation of lobular neoplastic breast lesions using clinical archival specimens. The identified genomic signature includes copy number alterations not previously identified for lobular neoplasia. This genomic signature, common to ALH and LCIS, suggests a role for the acquisition of novel genomic alterations in the aberrant cellular proliferation that defines lobular neoplasia.

Breast Neoplasms↗

PubMed2006

Oncogene-specific gene expression signatures at preneoplastic stage in mice define distinct mechanisms of hepatocarcinogenesis.

We applied a genome-wide microarray analysis to three transgenic mouse models of liver cancer in which targeted overexpression of c-Myc, E2f1, and a combination of the two was driven by the albumin promoter. Although gene expression profiles in HCC derived in all three transgenic lines were highly similar, oncogene-specific gene expression signatures were identified at an early dysplastic stage of hepatocarcinogenesis. Overexpression of E2f1 was associated with a strong alteration in lipid metabolism, and Srebp1 was identified as a candidate transcription factor responsible for lipogenic enzyme induction. The molecular signature of c-Myc overexpression included the induction of more than 60 genes involved in the translational machinery that correlated with an increase in liver mass. In contrast, the combined activity of c-Myc and E2f1 specifically enhanced the expression of genes involved in mitochondrial metabolism--particularly the components of the respiratory chain--and correlated with an increased ATP synthesis. Thus, the results suggest that E2f1, c-Myc, and their combination may promote liver tumor development by distinct mechanisms. In conclusion, determination of tissue-specific oncogene expression signatures might be useful to identify conserved expression modules in human cancers.

Adenosine Triphosphate↗

PubMed2006

Transcriptional census of 36 microdissected colorectal cancers yields a gene signature to distinguish UICC II and III.

UICC stage II and III colorectal cancers (CRC) differ fundamentally in prognosis and therapeutic concepts. To analyze differential gene expression between both stages and to establish a relationship between molecular background and clinical presentation, tumor material from 36 unselected consecutive patients presenting with sporadic CRC, 18 UICC stage II and 18 UICC stage III, were laser microdissected to separate epithelial tumor cells. Gene expression levels were measured using U133A Affymetrix gene arrays. Twelve CRC associated signal transduction pathways as well as all 22,000 probe sets were screened for differential gene expression. We identified a signature consisting of 45 probe sets that allowed discrimination between UICC stage II and stage III with a rate of correct classification of about 80%. The most distinctive elements in this signature were the gene GSTP-binding elongation factor (GSPT2) and the transcription factor HOXA9. Differential expression of these genes was confirmed by quantitative real-time polymerase chain reaction (p(HOXA9) = 0.04, p(GSTP2) = 0.02). Despite the reliability of the presented data, there was no substantial differential expression of genes in cancer-related pathways. However, the comparison with recently published data corroborates the 45 gene signature showing structural agreement in the direction of fold changes of gene expression levels for our set of genes chosen to discriminate between both stages.

Aged↗