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PubMed2025

MPAC: a computational framework for inferring pathway activities from multi-omic data.

Fully capturing cellular state requires examining genomic, epigenomic, transcriptomic, proteomic, and other assays for a biological sample and comprehensive computational modeling to reason with the complex and sometimes conflicting measurements. Modeling these so-called multi-omic data is especially beneficial in disease analysis, where observations across omic data types may reveal unexpected patient groupings and inform clinical outcomes and treatments. We present Multi-omic Pathway Analysis of Cells (MPAC), a computational framework that interprets multi-omic data through prior knowledge from biological pathways. MPAC leverages network relationships encoded in pathways through a factor graph to infer consensus activity levels for proteins and associated pathway entities from multi-omic data, runs permutation testing to eliminate spurious activity predictions, and groups biological samples by pathway activities to allow identifying and prioritizing proteins with potential clinical relevance, e.g., associated with patient prognosis. Using DNA copy number alteration and RNA-seq data from head and neck squamous cell carcinoma patients from The Cancer Genome Atlas as an example, we demonstrate that MPAC predicts a patient subgroup related to immune responses not identified by analysis with either input omic data type alone. Key proteins identified via this subgroup have pathway activities related to clinical outcome as well as immune cell compositions. Our MPAC R package, available at https://bioconductor.org/packages/MPAC, enables similar multi-omic analyses on new datasets.

Journal Article↗

PubMed2025

MPAC: a computational framework for inferring pathway activities from multi-omic data.

MOTIVATION: Fully capturing cellular state requires examining genomic, epigenomic, transcriptomic, proteomic, and other assays for a biological sample and comprehensive computational modeling to reason with the complex and sometimes conflicting measurements. Modeling these so-called multi-omic data is especially beneficial in disease analysis, where observations across omic data types may reveal unexpected patient groupings and inform clinical outcomes and treatments. RESULTS: We present Multi-omic Pathway Analysis of Cells (MPAC), a computational framework that interprets multi-omic data through prior knowledge from biological pathways. MPAC leverages network relationships encoded in pathways through a factor graph to infer consensus activity levels for proteins and associated pathway entities from multi-omic data, runs permutation testing to eliminate spurious activity predictions, and groups biological samples by pathway activities to allow identifying and prioritizing proteins with potential clinical relevance, e.g. associated with patient prognosis. Using DNA copy number alteration and RNA-seq data from head and neck squamous cell carcinoma patients from The Cancer Genome Atlas as an example, we demonstrate that MPAC predicts a patient subgroup related to immune responses not identified by analysis with either input omic data type alone. Key proteins identified via this subgroup have pathway activities related to clinical outcome as well as immune cell composition. Our MPAC R package enables similar multi-omic analyses on new datasets. AVAILABILITY AND IMPLEMENTATION: The MPAC package is available at Bioconductor https://bioconductor.org/packages/MPAC.

Humans↗

PubMed2026

Integrated bulk and single-cell RNA sequencing reveals a prognostic neuro-mimicry signature in papillary thyroid carcinoma.

BACKGROUND: Cancer cells can acquire neuron-like characteristics ("neural mimicry") to promote progression. However, the role of specific ion channel genes in Papillary Thyroid Carcinoma (PTC) and their clinical significance remains unclear. METHODS: We included transcriptomic data from 521 PTC patients in the TCGA cohort. A neuron-specific gene set was used to screen for potential targets. We constructed a prognostic model using LASSO logistic regression. To verify the cellular origin of the signature, we performed single-cell RNA sequencing (scRNA-seq) analysis on the GSE184362 dataset. RESULTS: We established an 8-gene signature involving KCNN4, KCNN1, KCNT2, SNAP25, KCNK16, GABRG1, GABRG2, and GABRB2. The model demonstrated good predictive performance for lymph node metastasis, with an AUC of 0.721 (95% CI 0.677-0.765). Single-cell analysis of seven integrated tumor samples (N = 65,744 cells) confirmed that GABRB2 was specifically enriched in malignant thyrocytes (EPCAM+/KRT18+) at 200-fold higher detection rates than immune cells (20.0% vs. 0.1%, P ≈ 0), supporting tumor-intrinsic neural mimicry. High-risk patients showed immunosuppressive features with altered immune cell infiltration patterns. CONCLUSION: This study identifies a malignant cell-intrinsic signature for predicting PTC prognosis. Validated by single-cell data, our findings suggest that targeting ion channels may represent a potential therapeutic strategy for modulating neuro-immune interactions in thyroid cancer, pending experimental validation.

GABRB2↗

PubMed2005

A chemosensory system that regulates biofilm formation through modulation of cyclic diguanylate levels.

Pseudomonas aeruginosa causes chronic biofilm infections, and its ability to attach to surfaces and other cells is important for biofilm formation and maintenance. Mutations in a gene called wspF, part of a putative chemosensory signal-transduction operon, have been shown to result in cell aggregation and altered colony morphology. The WspF phenotypes depend on the presence of WspR, which is a member of a family of signal transduction proteins known as response regulators. It is likely that the effect of the wspF mutation is to cause constitutive activation of WspR by phosphorylation. WspR contains a GGDEF domain known to catalyze formation of a cytoplasmic signaling molecule cyclic diguanylate (c-diGMP). We determined that purified WspR catalyzed the formation of c-diGMP in vitro and phosphorylation stimulated this activity. We observed increased cellular levels of c-diGMP and increased biofilm formation in a wspF mutant. Expression of a protein predicted to catalyze degradation of c-diGMP reversed the phenotypes of a wspF mutant and inhibited biofilm initiation by wild-type cells, indicating that the presence of c-diGMP is necessary for biofilm formation. A transcriptome analysis showed that expression levels of at least 560 genes were affected by a wspF deletion. The psl and pel operons, which are involved in exopolysaccharide production and biofilm formation, were expressed at high levels in a wspF mutant. Together, the data suggest that the wsp signal transduction pathway regulates biofilm formation through modulation of cyclic diguanylate levels.

Bacterial Proteins↗

PubMed2004

Neuroendocrine transcriptome in genetic hypertension: multiple changes in diverse adrenal physiological systems.

The genetic basis of hypertension in the genetically/hereditary hypertensive (BPH/2) mouse strain is incompletely understood, although a recent genome scan uncovered evidence for several susceptibility loci. To probe the neuroendocrine transcriptome in this disease model, 12 488 probe set microarray experiments were performed on mRNA transcripts from adrenal glands of juvenile (prehypertensive) and adult BPH/2 (hypertensive), as well as the genetically/hereditary low-blood pressure (BPL/1), strains at both time points. To determine the impact of strain (BPH/2 versus BPL/1), age (juvenile versus adult), and the interaction of strain and age on gene expression levels, we performed standard 2-factor ANOVA and computed a concordance coefficient to assess the reproducibility of gene expression measurements among replicates. Of genes with significant (P<0.05) differential expression, 2647 showed strain differences, 982 showed age differences, and 757 exhibited strain-by-age interaction. Fold-changes in gene expression assayed by microarray were confirmed in a subset by real-time polymerase chain reaction (R=0.739, P=0.0094). We used a systems biology approach to evaluate alterations in contributing biochemical pathways and we statistically quantified these global pathway disturbances using the Kolmogorov-Smirnov goodness-of-fit test. We found widespread, indeed global, alterations in patterns of gene expression in diverse systems of BPH/2: in sympathochromaffin transcripts suggesting increased sympathetic stimulation; in vasoconstrictor/vasodilator systems; global reductions in carbohydrate intermediary metabolism; and increases in oxidative stress, with changes in oxygen radical forming and disposition enzymes. These analyses highlight widespread derangements in diverse physiological pathways, providing multiple avenues for further investigation into the pathogenesis of genetic hypertension.

Adrenal Glands↗

PubMed2003

Transcriptome analysis of sulfur depletion in Arabidopsis thaliana: interlacing of biosynthetic pathways provides response specificity.

Higher plants assimilate inorganic sulfate into cysteine, which is subsequently converted to methionine, and into a variety of other sulfur-containing organic compounds. To resist sulfur deficiency, plants must demonstrate physiological flexibility: the expression of an extensive set of genes and gene regulators that act in the affected pathways or signalling cascades must be delicately tuned in response to environmental challenges. To elucidate this network of interactions, we have applied an array hybridisation/transcript profiling method to Arabidopsis plants subjected to 6, 10 and 13 days of constitutive and induced sulfur starvation. The temporal expression behaviour of approximately 7200 non-redundant genes was analysed simultaneously. The experiment was designed in a way to identify statistically significant changes of gene expression based on sufficient numbers of repeated hybridisations performed with five uniform pools of plant material. The expression profiles were processed to select differentially expressed genes. Among the 1507 sulfur-responsive clones implicated in this way, 632 genes responded specifically to sulfur deficiency by significant over-expression. The sulfur-responsive genes were grouped according to functional categories or biosynthetic pathways. As expected, genes of the sulfur assimilation pathway were altered in expression. Furthermore, genes involved in flavonoid, auxin, and jasmonate biosynthesis pathways were upregulated in conditions of sulfur deficiency. Based on the correlative analysis of gene expression patterns, we suggest that a complex co-ordination of systematic responses to sulfur depletion is provided via integration of flavonoid, auxin and jasmonate pathway elements. Plait concept for transduction of specificity via the main non-specific signalling stream is proposed.

Adaptation, Physiological↗

PubMed2005

cDNA microarray analysis of HBV transgenic mouse liver identifies genes in lipid biosynthetic and growth control pathways affected by HBV.

Hepatitis B virus (HBV) transgenic mice that replicate HBV in the liver generally do not exhibit gross liver pathology, while maintaining a high level (10(7) or greater) of viral titer in the blood. We have used this model to determine the minimum effects of HBV replication in the liver on cellular gene transcription, using cDNA microarrays. cDNA microarray data from sets of HBV versus control cDNA microarrays revealed a very small impact of HBV on the cellular transcriptome. After deletion of genes that were variable in control cDNA microarrays and applying significance analysis of microarrays (SAM), an application to detect statistically significantly regulated genes, we identified 18 upregulated genes and 14 downregulated genes. Most of the regulated genes show a change in expression with respect to control of less than 40% in either direction, demonstrating small effects of HBV. The largest functional category for upregulated genes was lipid biosynthesis, in which ATP citrate lyase, fatty acid synthase, sterol regulatory element binding factor 2, and retinol binding protein 1 were all upregulated. The most strongly downregulated genes were in the cytochrome p450 group, particularly p450, 4a14. Several growth regulatory genes including cyclin D1, IGF binding protein 3, and PCNA were moderately upregulated. These data are the first to specifically identify enzymes involved in fatty acid and NADPH-electron transport pathways that are altered by the presence of HBV. The data also demonstrates that HBV is well adapted to non-cytopathic replication in hepatocytes. Cellular genes expected to be affected by viral secretion from membranes are clearly upregulated, and upregulation of growth regulatory genes may facilitate replacement of dying hepatocytes during persistent infection.

Animals↗

PubMed2006

Novel candidate targets of Wnt/beta-catenin signaling in hepatoma cells.

The activity of beta-catenin/TCF, the key component of Wnt signaling pathway, is frequently deregulated in HCC, resulting in the activation of genes whose dysregulation has significant consequences on tumor development. Therefore, identifying the target genes of Wnt signaling is important for understanding beta-catenin-mediated carcinogenesis. We analyzed the transcriptome profile of human hepatoma cell lines using cDNA microarrays representing 15,127 unique, liver-enriched gene loci to identify the target genes of beta-catenin-mediated transcription (p<0.005). This analysis yielded 130 potential Wnt-associated classifier genes, and we found 33 of them contain consensus TCF-binding sites in presumptive transcriptional regulatory sequences. These genes were, then, tested for their Wnt-dependence of expression in experimental models of Wnt activation. Genes such as RPL29, NEDD4L, FUT8, LYZ, STMN2, STARD7 and KIAA0998 were proven to be up-regulated upon Wnt/beta-catenin activation. Gene ontology analysis of the 33 candidate genes indicated the presence of functional categories relevant to Wnt pathway such as cell growth, proliferation, adhesion and signal transduction. In conclusion, we identified a number of candidate Wnt/beta-catenin target genes that can be useful for studying the role of altered Wnt signaling in liver cancer development, and showed that some of them might be direct targets of Wnt signaling in hepatoma cells.

Carcinoma, Hepatocellular↗

PubMed2006

Expression profiling by whole-genome interspecies microarray hybridization reveals differential gene expression in procyclic promastigotes, lesion-derived amastigotes, and axenic amastigotes in Leishmania mexicana.

We examined the Leishmania mexicana transcriptome to identify differentially regulated mRNAs using high-density whole-genome oligonucleotide microarrays designed from the genome data of a closely related species, Leishmania major. Statistical analysis on array hybridization data representing 8156 predicted coding regions revealed 288 genes (3.5% of all genes) whose steady-state mRNA levels meet criteria for differential regulation between promastigotes and lesion-derived amastigotes. Interestingly, sample comparison of promastigotes to axenic amastigotes resulted in only 17 genes (0.2%) that meet the same statistical criteria for differential regulation. The reduced number of regulated genes is a consequence of an increase in the magnitude of the transcript levels in cells under axenic conditions. The expression data for a subset of genes was validated by quantitative PCR. Our studies show that interspecies hybridization on microarrays can be used to analyze closely related protozoan parasites, that axenic culture conditions may alter amastigote transcript abundance, and that there is only a relatively modest change in abundance of a few mRNAs between morphologically distinct promastigote and amastigote cultured cells. Leishmania may represent an alternative paradigm for eukaryotic differentiation with minimal contributions from changes in mRNA abundance.

Animals↗

PubMed2003

The role of HIF-1 alpha in transcriptional regulation of the proximal tubular epithelial cell response to hypoxia.

Epithelial cells of the kidney represent a primary target for hypoxic injury in ischemic acute renal failure (ARF); however, the underlying transcriptional mechanism(s) remain undefined. In this study, human proximal tubular epithelial cells (HK-2) exposed to hypoxia in vitro demonstrated a non-lethal but dysfunctional phenotype, closely reflective of the epithelial pathobiology of ARF. HK-2 cells exposed to hypoxia demonstrated increased paracellular permeability, decreased proliferation, loss of tight junctional integrity, and significant actin disassembly in the absence of cell death. Microarray analysis of transcriptomic changes underlying this response identified a distinct cohort of 48 genes with a closely shared hypoxia-dependent expression profile. Within this hypoxia-sensitive cluster were genes identified previously as hypoxia-inducible factor-1 (HIF-1)-dependent (e.g. vascular endothelial growth factor and adrenomedullin) as well as genes not previously known to be hypoxia-responsive (e.g. stanniocalcin 2). In hypoxia, HIF-1 bound to evolutionarily conserved hypoxia-response elements (HRE) in the promoters of these genes as well as to the HRE consensus motif. A further subset of these genes, not associated with transcriptional regulation by HIF-1, was also present, suggesting alternative HIF-1-independent pathways. Overexpression of HIF-1 alpha in normoxia induced the expression of a significant number of the hypoxia-dependent genes; however, it did not induce the pathophysiologic epithelial response. In summary, hypoxia-elicited alterations in renal proximal tubular epithelial cells in vitro closely resemble the epithelial pathophysiology of ARF. Our data indicate that although this event may rely heavily on HIF-1-dependent gene transcription, it is likely that separate hypoxia-dependent transcriptional regulators also play a role.

Acute Kidney Injury↗

PubMed2006

Searching for IRES.

The cell has many ways to regulate the production of proteins. One mechanism is through the changes to the machinery of translation initiation. These alterations favor the translation of one subset of mRNAs over another. It was first shown that internal ribosome entry sites (IRESes) within viral RNA genomes allowed the production of viral proteins more efficiently than most of the host proteins. The RNA secondary structure of viral IRESes has sometimes been conserved between viral species even though the primary sequences differ. These structures are important for IRES function, but no similar structure conservation has yet to be shown in cellular IRES. With the advances in mathematical modeling and computational approaches to complex biological problems, is there a way to predict an IRES in a data set of unknown sequences? This review examines what is known about cellular IRES structures, as well as the data sets and tools available to examine this question. We find that the lengths, number of upstream AUGs, and %GC content of 5'-UTRs of the human transcriptome have a similar distribution to those of published IRES-containing UTRs. Although the UTRs containing IRESes are on the average longer, almost half of all 5'-UTRs are long enough to contain an IRES. Examination of the available RNA structure prediction software and RNA motif searching programs indicates that while these programs are useful tools to fine tune the empirically determined RNA secondary structure, the accuracy of de novo secondary structure prediction of large RNA molecules and subsequent identification of new IRES elements by computational approaches, is still not possible.

5' Untranslated Regions↗

PubMed2025

Genetic and transcriptional insights into immune checkpoint blockade response and survival: lessons from melanoma and beyond.

BACKGROUND: Integration of immune checkpoint inhibitors (ICIs) with non-immune therapies relies on identifying combinatorial biomarkers, which are essential for patient stratification and personalized treatment. METHODS: We analyzed genomic and transcriptomic data from pretreatment tumor samples of 342 melanoma patients treated with ICIs to identify mutations and expression signatures associated with ICI response and survival. External validation and mechanistic exploratory analyses were conducted in two additional datasets to assess generalizability. RESULTS: Responders were more likely to have received anti-PD-1 therapy rather than anti-CTLA-4 and exhibited a higher tumor mutation burden (both P < 0.001). Mutations in the dynein axonemal heavy chain (DNAH) family genes, specifically DNAH2 (P = 0.03), DNAH6 (P < 0.001), and DNAH9 (P < 0.01), were enriched in responders. The combined mutational status of DNAH 2/6/9 effectively stratified patients by progression-free survival (hazard ratio [HR]: 0.69; 95% confidence interval [CI] 0.51-0.92; P = 0.013) and overall survival (HR: 0.58; 95% CI 0.43-0.78; P < 0.001), with consistent association observed in the validation cohort (HR: 0.28; 95% CI 0.12-0.61; P < 0.001). DNAH-altered melanomas exhibited upregulation of chemokine signaling, cytokine-cytokine receptor interaction, and cell cycle-related pathways, along with elevated expression of immune-related signatures in interferon signaling, cytolytic activity, T cell function, and immune checkpoints. Using LASSO logistic regression, we identified a 26-gene composite signature predictive of clinical response, achieving an area under the curve (AUC) of 0.880 (95% CI 0.825-0.936) in the training dataset and 0.725 (95% CI 0.595-0.856) in the testing dataset. High-risk patients, stratified by the expression levels of a 13-gene signature, demonstrated significantly shorter overall survival in both datasets (HR: 3.35; P < 0.001; HR: 2.93; P = 0.002). CONCLUSIONS: This analysis identified potential molecular determinants of response and survival to ICI treatment. Insights from melanoma biomarker research hold significant promise for translation into other malignancies, guiding individualized anti-tumor immunotherapy.

Humans↗

PubMed2005

Expression of CTL associated transcripts precedes the development of tubulitis in T-cell mediated kidney graft rejection.

The usual phenotype of clinical kidney allograft rejection is infiltration by lymphocytes and macrophages and evolution of histologic Banff lesions, particularly tubulitis, which indicate parenchymal injury. Using Affymetrix microarrays, we evaluated the relationship between the evolution of pathologic lesions and the transcriptome. We studied CBA/J into C57Bl/6 mouse kidney allografts in which one host kidney is left in place to permit observation of lesion development. Histology was dominated by early infiltration by mononuclear cells from day 3 and slower evolution of tubulitis after day 7. We defined a set of cytotoxic T lymphocyte-associated transcripts (CATs) on the basis of expression in purified cytotoxic T lymphocytes (CTL) and in a mixed lymphocyte culture, and absence in normal kidney. CATs were detectable by day 3 and highly expressed by day 5 in rejecting kidneys, with a median signal 14% of that in CTL, compared to 4% in isografts and normal kidneys, and persisted through day 42. Lack of mature B cells had little effect on CAT expression, confirming that CATs reflect T-cell-mediated rejection. Expression of CATs was established before diagnostic lesions and remained remarkably consistent through day 42 despite massive alterations in the pathology, and probably reflects T cells recruited to the graft.

Animals↗

PubMed2005

Discovery of a new biomarker for gastroenterological cancers.

Various genomic technologies have been applied to address crucial problems in cancer biology, because cancer develops through the accumulation of various genetic alterations. Of these, gene expression profiling analysis using microarray technology has been widely applied not only to classify cancers at molecular levels, but also to identify novel molecular targets for therapeutics and/or diagnostics. To gain molecular understanding of gastric carcinogenesis, progression, and diversity, we analyzed primary advanced gastric cancer and noncancerous gastric tissues by high-density oligonucleotide microarray. Genes differentially expressed between cancer and noncancerous tissues were identified. In cancer tissues, genes related to cell cycle, growth factor, cell motility, cell adhesion, and matrix remodeling were highly expressed, whereas those related to gastrointestinal-specific function and immune response were rather downregulated. These results provide not only a new molecular basis for understanding biological properties of gastric cancer but also useful resources for future development of therapeutic and diagnostic biomarkers for gastric cancer. Several microarray studies have been published since and have been compared for validation in meta-analysis. As integration of transcriptome information with other biological data is crucial to interpret gene expression data, we have applied oligonucleotide microarray technology to assess allelic gene dosage at 10000 polymorphic loci, namely with an average interval of 200kb. Using a newly developed algorithm, genome imbalance map, loss of heterozygosity (LOH) status can be determined simultaneously. Besides several loci with genomic amplification, we also identified a homozygously deleted chromosomal region in 7q, where frequent chromosomal instability was observed. Finally, we are currently developing novel biomarkers for gastroenterological cancers. Glypican 3 is detected at high levels in serum of hepatocellular carcinoma patients and could be a potential target for antibody therapy.

Carcinoma, Hepatocellular↗

PubMed2026

AI-Driven Precision Medicine in Alzheimer's Disease: Drug Repurposing, Digital Therapeutics and Clinical Decision Support.

Alzheimer's Disease (AD) is a neurodegenerative disease that causes significant clinical, social, and economic burden worldwide. Despite improvements in understanding its multifaceted pathogenesis, current treatments are mostly symptomatic and ineffective across varied patient populations. To overcome these constraints, AI-driven precision medicine allows tailored risk assessment, treatment selection, and disease monitoring. This review covers AI's role in AD precision medicine, focusing on drug repurposing, digital therapies and clinical decision support systems. Machine and deep learning models are used to predict medication response, integrate heterogeneous data sources such as genomics, transcriptomics, neuroimaging and electronic health records, and uncover pharmacogenomic treatment success factors. The paper covers AIenabled precision pharmacology, including tailored dosing algorithms, adaptive therapeutic monitoring, and adverse drug reaction prediction. Bioinformatics-based target identification, network pharmacology, graphbased AI models, virtual screening, and real-world and clinical data validation are emphasized in AI-driven medication repurposing. AI-powered digital treatments like personalized cognitive training platforms, wearable- derived digital biomarkers, virtual and mixed reality interventions, adherence monitoring, and digital twins for therapy optimization have been discussed. AI-based clinical decision support systems are also thoroughly assessed for clinical value, accuracy, and explainability in disease subtyping, trajectory prediction, and risk stratification in preclinical and prodromal AD. Despite these promises, data heterogeneity, algorithmic bias, legal barriers, and privacy concerns exist. Federated learning enables safe multi-center collaboration and hybrid AI-human approaches, and it represents the future. AI's ability to alter AD care opens the door to precision medicine paradigms that use repurposed medications, digital tools and intelligent decision-making to improve patient outcomes.

Alzheimer’s disease↗

PubMed2026

Allelochemical signaling and phytohormone crosstalk in plants: molecular mechanisms and implications for sustainable weed management.

Phytotoxic effects from allelopathy occur due to signaling pathways that induce alterations in hormonal balance within the plants, thereby hindering weed growth. Signaling crosstalk between various hormones and signaling pathways (Ca2⁺, MAPK, ROS) is involved in the molecular response mechanisms found through omics. Utilizing such mechanisms would help develop new environmentally friendly methods for sustainable weed management. Allelopathy serves as an essential component of plant-plant interaction via controlling the secretion of secondary metabolites (allelochemicals), which affect the growth, development, and physiological activity of nearby plants. The latest findings indicate that allelochemicals disturb phytohormone balance and signaling pathways resulting in oxidative stress, metabolism dysfunctions, cellular processes disturbances, and eventually inhibiting the growth of target weed species. Molecular biology progress and omics techniques brought information about the sophisticated regulation processes involved in allelopathic interactions. This review summarizes the information about the molecular mechanism of weed suppression mediated by allelopathy with the emphasis on allelochemical perception, phytohormone signaling, ROS responses, and evidence obtained by the application of transcriptomics, proteomics, metabolomics, and other omics-based studies. In addition, it introduces novel approaches, such as rhizosphere engineering, nanotechnologies, and genome editing, which may improve the effectiveness and reliability of allelopathic weed suppression. Overall, these achievements provide prospects for creating a new generation of weed control technologies that are sustainable, environmentally friendly, and climate-adaptive.

Plant Growth Regulators↗

PubMed2026

Genomic and Transcriptomic Correlates of Deep PSA Response in Patients with Metastatic Androgen Pathway Modulation-Sensitive Prostate Cancer.

BACKGROUND: Despite advances in metastatic androgen pathway modulation-sensitive prostate cancer (mAPMS) treatment, outcomes remain heterogeneous. Achieving a post-treatment undetectable prostate specific antigen (PSA) is a strong prognostic marker. We aimed to identify genomic and transcriptomic determinants of PSA response in a real-world clinical-genomic cohort. PATIENTS AND METHODS: Patients with mAPMS who underwent DNA (Tempus xT) and, in a subset, RNA (Tempus xR) sequencing were identified from the Tempus Lens database. Inclusion required stage IV disease within 90 days of sample collection and samples obtained within 12 months before or 3 months after treatment initiation. Patients with PSA at 6 months (n = 525) were classified as PSA-low (<0.1 ng/mL, n = 240) or PSA-high (≥0.1 ng/mL, n = 285). Overall survival (OS) was assessed by 6-month landmark analysis with delayed-entry adjustment. Logistic and Cox models were adjusted for clinical variables. Sensitivity analyses used a relative definition of > 95% PSA decline from baseline. RESULTS: Baseline PSA was lower in PSA-low versus PSA-high patients (24 vs 36 ng/mL, p = 0.01). SPOP (17% vs 11%) and ZFHX3 (2.5% vs 6%) alterations differed between groups, but neither persisted after adjustment. Using the relative definition, ZMYM3 and JAK1 alterations were independently associated with failure to achieve a deep PSA response. Expression of PSMA, TROP2, B7-H3, and STEAP1 did not differ between groups. PSA-low status was independently associated with improved OS, as was deep relative response. CONCLUSION: Deep PSA response at 6 months correlates with improved OS in mAPMS. Integrating molecular markers with PSA response may inform treatment intensification or de-escalation strategies.

Biomarkers↗

PubMed2001

Microarray analysis of hippocampal gene expression in global cerebral ischemia.

The brain's response to ischemia, which helps determine clinical outcome after stroke, is regulated partly by competing genetic programs that respectively promote cell survival and delayed cell death. Many genes involved in this response have been identified individually or systematically, providing insights into the molecular basis of ischemic injury and potential targets for therapy. The development of microarray systems for gene expression profiling permits screening of large numbers of genes for possible involvement in biological or pathological processes. Therefore, we used an oligodeoxynucleotide-based microarray consisting of 374 human genes, most implicated previously in apoptosis or related events, to detect alterations in gene expression in the hippocampus of rats subjected to 15 minutes of global cerebral ischemia followed by up to 72 hours of reperfusion. We found 1.7-fold or greater increases in the expression of 57 genes and 1.7-fold or greater decreases in the expression of 34 genes at 4, 24, or 72 hours after ischemia. The number of induced genes increased from 4 to 72 hours, whereas the number of repressed genes decreased. The induced genes included genes involved in protein synthesis, genes mutated in hereditary human diseases, proapoptotic genes, antiapoptotic genes, injury-response genes, receptors, ion channels, and enzymes. We detected transcriptional induction of several genes implicated previously in cerebral ischemia, including ALG2, APP, CASP3, CLU, ERCC3, GADD34, GADD153, IGFBP2, TIAR, VEGF, and VIM, as well as other genes not so implicated. We also found coinduction of several groups of related genes that might represent functional modules within the ischemic neuronal transcriptome, including VEGF and its receptor, NRP1; the IGF1 receptor and the IGF1-binding protein IGFBP2; Rb, the Rb-binding protein E2F1, and the E2F-related transcription factor, TFDP1; the CACNB3 and CACNB4 beta-subunits of the voltage-gated calcium channel; and caspase-3 and its substrates, ACINUS, FEM1, and GSN. To test the hypothesis that genes identified through this approach might have roles in the pathophysiology of cerebral ischemia, we measured expression of the products of two induced genes not heretofore implicated in cerebral ischemia-GRB2, an adapter protein involved in growth-factor signaling pathways, and SMN1, which participates in RNA processing and is deleted in most cases of spinal muscular atrophy. Western analysis showed enhanced expression of both proteins in hippocampus at 24 to 72 hours after ischemia, and SMN1 was localized by immunohistochemistry to hippocampal neurons. These results suggest that microarray analysis of gene expression may be useful for elucidating novel molecular mediators of cell death and survival in the ischemic brain.

Animals↗