The Reactome pathway Knowledgebase

Transcriptional and methylation outcomes of didehydro-cortistatin A use in HIV-1-infected CD4+ T cells

Ongoing viral transcription from the reservoir of HIV-1 infected long-lived memory CD4+ T cells presents a barrier to cure and associates with poorer health outcomes for people living with HIV, including chronic immune activation and inflammation. We previously reported that didehydro-cortistatin A (dCA), an HIV-1 Tat inhibitor, blocks HIV-1 transcription. Here, we examine the impact of dCA on host immune CD4+ T-cell transcriptional and epigenetic states. We performed a comprehensive analysis of genome-wide transcriptomic and DNA methylation profiles upon long-term dCA treatment of primary human memory CD4+ T cells. dCA prompted specific transcriptional and DNA methylation changes in cell cycle, histone, interferon-response, and T-cell lineage transcription factor genes, through inhibition of both HIV-1 and Mediator kinases. These alterations establish a tolerogenic Treg/Th2 phenotype, reducing viral gene expression and mitigating inflammation in primary CD4+ T cells during HIV-1 infection. In addition, dCA suppresses the expression of lineage-defining transcription factors for Th17 and Th1 cells, critical HIV-1 targets, and reservoirs. dCA's benefits thus extend beyond viral transcription inhibition, modulating the immune cell landscape to limit HIV-1 acquisition and inflammatory environment linked to HIV infection.

Transcriptome profiles of macrophages upon infection by morphotypic smooth and rough variants of Mycobacterium abscessus

Mycobacterium abscessus (Mab) infection can be deadly in patients with chronic lung diseases like cystic fibrosis (CF). In vitro and in vivo, Mab may adopt a smooth (S) or rough (R) morphotype, the latter linked to more severe disease conditions. In vitro studies revealed differences in pathogenicity and immune response to S and R morphotypes. We propose that in vivo both morphotypes exist and may transiently switch depending on the environment, having important pathogenic and immunologic consequences. This can be modeled by morphotypic S and R variants of Mab selected based on in vitro growth conditions. Here, we report the first analysis of early transcriptional events in mouse bone marrow derived macrophages (BMDMs) upon infection with media-selected interchangeable Mab-S and Mab-R morphotypes. The early transcriptional events after infection with both morphotypes showed considerable overlap of the pro-inflammatory genes that were differentially regulated compared to the uninfected macrophages. We also observed signature genes significantly differentially regulated in macrophages during infection of media-selected morphotypic Mab-S and Mab-R variants. In conclusion, media-selected Mab-S and Mab-R behave in a similar fashion to stable S and R types with respect to pathogenesis and immune response, serving as a useful model for environmentally influenced morphotype selection.

Development of a cellular assay as a personalized model for testing chronic wound therapeutics

Exudates of non-healing wounds contain drivers of pathogenicity. We utilized >800 exudates from non-healing and healing wounds of diverse etiologies, collected by three different methods, to develop a wound-specific, cell-based functional biomarker assay. Human dermal fibroblast proliferation served as readout to a) to differentiate between healing and non-healing wounds, b) follow the healing process of individual patients, and c) assess the effects of therapeutics for chronic wounds ex vivo. We observed a strong correlation between wound chronicity and inhibitory effects of individual exudates on fibroblast proliferation, with good diagnostic sensitivity (76-90%, depending on the sample collection method). Transition of a clinically non-healing to a healing phenotype restored fibroblast proliferation and extracellular matrix formation while reducing inflammatory cytokine production. Transcriptional analysis of fibroblasts exposed to ex vivo non-healing wound exudates revealed an induction of inflammatory cytokine- and chemokine pathways and the unfolded protein response, indicating that these changes may contribute to the pathology of non-healing wounds. Testing the wound therapeutics platelet derived growth factor and silver sulfadiazine yielded responses in line with clinical experience and indicate the usefulness of the assay to search for and profile new therapeutics.

Comparative Proteomics Analysis Reveals Distinct Molecular Phenotype and Biomarkers in Patients with Erythrodermic Atopic Dermatitis and Erythrodermic Psoriasis

Erythrodermic atopic dermatitis (EAD) and erythrodermic psoriasis (EP) are rare yet debilitating inflammatory skin disorders that propose challenges in diagnosis and discovering effective therapeutic targets. Despite their clinical and histological similarities, the underlying molecular mechanisms and systemic biomarkers of these diseases are substantially unclear. In this study, we sought to investigate the differential serum proteome of EP and EAD patients and identify biomarkers for these two subtypes of erythroderma. We recruited 14 EAD patients, 14 EP patients and 14 healthy controls. Serum samples were collected and analyzed using the Olink high-throughput platform to assess the levels of 269 inflammation-/immune response-/cardiovascular-related biomarkers. Both EAD and EP patients exhibited enhanced immune activation and dysregulated cardiovascular profiles compared to healthy controls. EAD demonstrated a more pronounced inflammation tone, characterized by Th1/Th2/Th22/IL-1-dominant patterns, as well as increased TNF superfamily, Th17, and apoptosis markers. Conversely, EP displayed inflammation with Th1/Th17/TNF-skewing and mild Th2 upregulation, along with notable increases in epidermal-development markers. Disease severity in EAD was strongly correlated with apoptosis/Th2 markers, while correlated with Th17 markers in EP. Furthermore, a panel of eight markers (IL-17A/IL-17C/PI3/CCL20/SH2D1A/SIRT2/DFFA/IL-13) was identified that effectively discriminated between EP and EAD, with an Area Under the Curve greater than 0.8. Our study comprehensively characterizes the circulating molecular profiles in EAD and EP patients, providing insights into the similarities and complexities of their inflammation phenotypes. The identified serum biomarkers have the potential to differentiate between EP and EAD, which could aid in the diagnosis and guiding tailored therapeutics.

Aberrant spliceosome activity via elevated intron retention and upregulation and phosphorylation of SF3B1 in chronic lymphocytic leukemia

Splicing factor 3b subunit 1 (SF3B1) is the largest subunit and core component of the spliceosome. Inhibition of SF3B1 was associated with an increase in broad intron retention (IR) on most transcripts, suggesting that IR can be used as a marker of spliceosome inhibition in chronic lymphocytic leukemia (CLL) cells. Furthermore, we separately analyzed exonic and intronic mapped reads on annotated RNA-sequencing transcripts obtained from B cells (n = 98 CLL patients) and healthy volunteers (n = 9). We measured intron/exon ratio to use that as a surrogate for alternative RNA splicing (ARS) and found that 66% of CLL-B cell transcripts had significant IR elevation compared with normal B cells (NBCs) and that correlated with mRNA downregulation and low expression levels. Transcripts with the highest IR levels belonged to biological pathways associated with gene expression and RNA splicing. A >2-fold increase of active pSF3B1 was observed in CLL-B cells compared with NBCs. Additionally, when the CLL-B cells were treated with macrolides (pladienolide-B), a significant decrease in pSF3B1, but not total SF3B1 protein, was observed. These findings suggest that IR/ARS is increased in CLL, which is associated with SF3B1 phosphorylation and susceptibility to SF3B1 inhibitors. These data provide additional support to the relevance of ARS in carcinogenesis and evidence of pSF3B1 participation in this process.

Bioinformatics for Dentistry: A secondary database for the genetics of tooth development

Genes strictly regulate the development of teeth and their surrounding oral structures. Alteration of gene regulation leads to tooth disorders and developmental anomalies in tooth, oral, and facial regions. With the advancement of gene sequencing technology, genomic data is rapidly increasing. However, the large sets of genomic and proteomic data related to tooth development and dental disorders are currently dispersed in many primary databases and literature, making it difficult for users to navigate, extract, study, or analyze. We have curated the scattered genetic data on tooth development and created a knowledgebase called 'Bioinformatics for Dentistry' (https://dentalbioinformatics.com/). This database compiles genomic and proteomic data on human tooth development and developmental anomalies and organizes them according to their roles in different stages of tooth development. The database is built by systemically curating relevant data from the National Library of Medicine (NCBI) GenBank, OMIM: Online Mendelian Inheritance in Man, AlphaFold Protein Structure Database, Reactome pathway knowledgebase, Wiki Pathways, and PubMed. The accuracy of the included data was verified from supporting primary literature. Upon data curation and validation, a simple, easy-to-navigate browser interface was created on WordPress version 6.3.2, with PHP version 8.0. The website is hosted in a cloud hosting service to provide fast and reliable data transfer rate. Plugins are used to ensure the browser's compatibility across different devices. Bioinformatics for Dentistry contains four embedded filters for complex and specific searches and free-text search options for quick and simple searching through the datasets. Bioinformatics for Dentistry is made freely available worldwide, with the hope that this knowledgebase will improve our understanding of the complex genetic regulation of tooth development and will open doors to research initiatives and discoveries. This database will be expanded in the future by incorporating resources and built-in sequence analysis tools, and it will be maintained and updated annually.

Systems-wide analysis of A. fumigatus using kinetic modeling of metabolic pathways to identify putative drug targets

Aspergillosis is a major causative factor for morbidity in those with impaired immune systems, often caused by Aspergillus fumigatus. The diagnosis and treatment are difficult due to the diversity of individuals and risk factors and still pose a challenge for medical professionals. To understand the pathogenicity of any organism, it is critical to identify the significant metabolic pathways that are involved. Our work focused on developing kinetic models of critical pathways crucial for the survival of A. fumigatus using COPASI. While focusing on the folate biosynthesis, ergosterol biosynthesis and glycolytic pathway; sensitivity, time-course and steady-state analysis were performed to find the proteins/enzymes that are essential in the pathway and can be considered as potential drug targets. For further analysis of the interaction of drug targets identified, a protein-protein interaction (PPI) network was built, and hub nodes were identified using the Cytohubba package from Cytoscape. Based on the findings, dihydropteroate-synthase, dihydrofolate-reductase, 4-amino-4-deoxychorismate synthase, HMG-CoA-reductase, PG-isomerase and hexokinase could act as potential drug targets. Further, molecular docking and MM-GBSA analysis were performed with ligands chosen from DrugBank, and PubChem, and validated by experimental evidence and existing literature based on results from kinetic modeling and PPI network analysis. Based on docking scores and MM-GBSA results, molecular simulations were carried out for 1AJ2-dapsone, 1DIS-sulfamethazine, 1T02-lovastatin and 70YL-3-bromopyruvic acid complexes, which validated our findings. Our study provides a deeper insight into the mechanisms of A. fumigatus's metabolism to reveal dapsone, sulfamethazine, lovastatin and 3-bromopyruvic acid as potential drugs for the treatment of Aspergillosis.

The axes of biology: a novel axes-based network embedding paradigm to decipher the functional mechanisms of the cell

Summary

Common approaches for deciphering biological networks involve network embedding algorithms. These approaches strictly focus on clustering the genes' embedding vectors and interpreting such clusters to reveal the hidden information of the networks. However, the difficulty in interpreting the genes' clusters and the limitations of the functional annotations' resources hinder the identification of the currently unknown cell's functioning mechanisms. We propose a new approach that shifts this functional exploration from the embedding vectors of genes in space to the axes of the space itself. Our methodology better disentangles biological information from the embedding space than the classic gene-centric approach. Moreover, it uncovers new data-driven functional interactions that are unregistered in the functional ontologies, but biologically coherent. Furthermore, we exploit these interactions to define new higher-level annotations that we term Axes-Specific Functional Annotations and validate them through literature curation. Finally, we leverage our methodology to discover evolutionary connections between cellular functions and the evolution of species.

Availability and implementation

Data and source code can be accessed at https://gitlab.bsc.es/sdoria/axes-of-biology.git.

RFX6 haploinsufficiency predisposes to diabetes through impaired beta cell function

AIMS/HYPOTHESIS

Regulatory factor X 6 (RFX6) is crucial for pancreatic endocrine development and differentiation. The RFX6 variant p.His293LeufsTer7 is significantly enriched in the Finnish population, with almost 1:250 individuals as a carrier. Importantly, the FinnGen study indicates a high predisposition for heterozygous carriers to develop type 2 and gestational diabetes. However, the precise mechanism of this predisposition remains unknown.

METHODS

To understand the role of this variant in beta cell development and function, we used CRISPR technology to generate allelic series of pluripotent stem cells. We created two isogenic stem cell models: a human embryonic stem cell model; and a patient-derived stem cell model. Both were differentiated into pancreatic islet lineages (stem-cell-derived islets, SC-islets), followed by implantation in immunocompromised NOD-SCID-Gamma mice.

RESULTS

Stem cell models of the homozygous variant RFX6-/- predictably failed to generate insulin-secreting pancreatic beta cells, mirroring the phenotype observed in Mitchell-Riley syndrome. Notably, at the pancreatic endocrine stage, there was an upregulation of precursor markers NEUROG3 and SOX9, accompanied by increased apoptosis. Intriguingly, heterozygous RFX6+/- SC-islets exhibited RFX6 haploinsufficiency (54.2% reduction in protein expression), associated with reduced beta cell maturation markers, altered calcium signalling and impaired insulin secretion (62% and 54% reduction in basal and high glucose conditions, respectively). However, RFX6 haploinsufficiency did not have an impact on beta cell number or insulin content. The reduced insulin secretion persisted after in vivo implantation in mice, aligning with the increased risk of variant carriers to develop diabetes.

CONCLUSIONS/INTERPRETATION

Our allelic series isogenic SC-islet models represent a powerful tool to elucidate specific aetiologies of diabetes in humans, enabling the sensitive detection of aberrations in both beta cell development and function. We highlight the critical role of RFX6 in augmenting and maintaining the pancreatic progenitor pool, with an endocrine roadblock and increased cell death upon its loss. We demonstrate that RFX6 haploinsufficiency does not affect beta cell number or insulin content but does impair function, predisposing heterozygous carriers of loss-of-function variants to diabetes.

DATA AVAILABILITY

Ultra-deep bulk RNA-seq data for pancreatic differentiation stages 3, 5 and 7 of H1 RFX6 genotypes are deposited in the Gene Expression Omnibus database with accession code GSE234289. Original western blot images are deposited at Mendeley ( https://data.mendeley.com/datasets/g75drr3mgw/2 ).

Tracking in situ checkpoint inhibitor-bound target T cells in patients with checkpoint-induced colitis

The success of checkpoint inhibitors (CPIs) for cancer has been tempered by immune-related adverse effects including colitis. CPI-induced colitis is hallmarked by expansion of resident mucosal IFNγ cytotoxic CD8+ T cells, but how these arise is unclear. Here, we track CPI-bound T cells in intestinal tissue using multimodal single-cell and subcellular spatial transcriptomics (ST). Target occupancy was increased in inflamed tissue, with drug-bound T cells located in distinct microdomains distinguished by specific intercellular signaling and transcriptional gradients. CPI-bound cells were largely CD4+ T cells, including enrichment in CPI-bound peripheral helper, follicular helper, and regulatory T cells. IFNγ CD8+ T cells emerged from both tissue-resident memory (TRM) and peripheral populations, displayed more restricted target occupancy profiles, and co-localized with damaged epithelial microdomains lacking effective regulatory cues. Our multimodal analysis identifies causal pathways and constitutes a resource to inform novel preventive strategies.

Biomarkers of Alzheimer's Disease Associated with Programmed Cell Death Reveal Four Repurposed Drugs

Alzheimer's disease (AD) is a neurodegenerative disorder and the most common cause of dementia. Programmed cell death (PCD) is mainly characterized by unique morphological features and energy-dependent biochemical processes. The predominant pathway leading to cell death in AD has not been thoroughly analyzed, although there is evidence of neuron loss in AD and numerous pathways of PCD have been associated with this process. A better understanding of the systems biology underlying the relationship between AD and PCD could lead to the development of new therapeutic approaches. To this end, publicly available transcriptome data were examined using bioinformatic methods such as differential gene expression and weighted gene coexpression network analysis (WGCNA) to find PCD-related AD biomarkers. The diagnostic significance of these biomarkers was evaluated using a logistic regression-based predictive model. Using these biomarkers, a multifactorial regulatory network was developed. Last, a drug repositioning study was conducted to propose new drugs for the treatment of AD targeting PCD. The development of 3PM (predictive, preventive, and personalized) drugs for the treatment of AD would be enabled by additional research on the effects of these drugs on this disease.

Gastric cancer actionable genomic alterations across diverse populations worldwide and pharmacogenomics strategies based on precision oncology

Introduction: Gastric cancer is one of the most prevalent types of cancer worldwide. The World Health Organization (WHO), the International Agency for Research on Cancer (IARC), and the Global Cancer Statistics (GLOBOCAN) reported an age standardized global incidence rate of 9.2 per 100,000 individuals for gastric cancer in 2022, with a mortality rate of 6.1. Despite considerable progress in precision oncology through the efforts of international consortia, understanding the genomic features and their influence on the effectiveness of anti-cancer treatments across diverse ethnic groups remains essential. Methods: Our study aimed to address this need by conducting integrated in silico analyses to identify actionable genomic alterations in gastric cancer driver genes, assess their impact using deleteriousness scores, and determine allele frequencies across nine global populations: European Finnish, European non-Finnish, Latino, East Asian, South Asian, African, Middle Eastern, Ashkenazi Jewish, and Amish. Furthermore, our goal was to prioritize targeted therapeutic strategies based on pharmacogenomics clinical guidelines, in silico drug prescriptions, and clinical trial data. Results: Our comprehensive analysis examined 275,634 variants within 60 gastric cancer driver genes from 730,947 exome sequences and 76,215 whole-genome sequences from unrelated individuals, identifying 13,542 annotated and predicted oncogenic variants. We prioritized the most prevalent and deleterious oncogenic variants for subsequent pharmacogenomics testing. Additionally, we discovered actionable genomic alterations in the ARID1A, ATM, BCOR, ERBB2, ERBB3, CDKN2A, KIT, PIK3CA, PTEN, NTRK3, TP53, and CDKN2A genes that could enhance the efficacy of anti-cancer therapies, as suggested by in silico drug prescription analyses, reviews of current pharmacogenomics clinical guidelines, and evaluations of phase III and IV clinical trials targeting gastric cancer driver proteins. Discussion: These findings underline the urgency of consolidating efforts to devise effective prevention measures, invest in genomic profiling for underrepresented populations, and ensure the inclusion of ethnic minorities in future clinical trials and cancer research in developed countries.

Dysfunctional neutrophil type 1 interferon responses in preschool children with recurrent wheezing and IL-4-mediated aeroallergen sensitization

Background

The innate mechanisms associated with viral exacerbations in preschool children with recurrent wheezing are not understood.

Objective

We sought to assess differential gene expression in blood neutrophils from preschool children with recurrent wheezing, stratified by aeroallergen sensitization, at baseline and after exposure to polyinosinic:polycytidylic acid (poly(I:C)) and also to examine whether poly(I:C)-stimulated blood neutrophils influenced airway epithelial gene expression.

Methods

Blood neutrophils were purified and cultured overnight with poly(I:C) and underwent next-generation sequencing with Reactome pathway analysis. Primary human small airway epithelial cells were treated with poly(I:C)-treated neutrophil culture supernatants and were analyzed for type 1 interferon gene expression with a targeted array. Symptoms and exacerbations were assessed in participants over 12 months.

Results

A total of 436 genes were differently expressed in neutrophils from children with versus without aeroallergen sensitization at baseline, with significant downregulation of type 1 interferons. These type 1 interferons were significantly upregulated in sensitized children after poly(I:C) stimulation. Confirmatory experiments demonstrated similar upregulation of type 1 interferons in IL-4-treated neutrophils stimulated with poly(I:C). Poly(I:C)-treated neutrophil supernatants from children with aeroallergen sensitization also induced a type 1 interferon response in epithelial cells. Children with aeroallergen sensitization also had higher symptom scores during exacerbations, and these symptom differences persisted for 3 days after prednisolone treatment.

Conclusions

Type 1 interferon responses are dysregulated in preschool children with aeroallergen sensitization, which is in turn associated with exacerbation severity. Given the importance of type 1 interferon signaling in viral resolution, additional studies of neutrophil type 1 interferon responses are needed in this population.

Cardiopulmonary Phenotypes and Protein Signatures in Children With Down Syndrome

Pulmonary disease, lower respiratory tract infection, and pneumonia are the largest causes of morbidity and mortality in individuals with Down syndrome (DS), but whether pulmonary diagnoses in children with DS are common and occur independently of cardiac disease and pulmonary hypertension (PH) is unknown. Cardiopulmonary phenotypes were examined in a cohort of 1248 children with DS. Aptamer-based proteomic analysis of blood was performed in a subset (n = 120) of these children. By the age of 10 years, half of the patients in this cohort (n = 634, 50.8%) had co-occurring pulmonary diagnoses. That proteins and related pathways were distinct between children with pulmonary diagnoses and those with cardiac disease and/or PH may indicate that pulmonary diagnoses appear to occur independently of cardiac disease and PH. Heparin sulfate-glycosaminoglycandegradation, nicotinate metabolism, and elastic fiber formation were ranked highest in the group with pulmonary diagnoses.

bootGSEA: a bootstrap and rank aggregation pipeline for multi-study and multi-omics enrichment analyses

Introduction: Gene set enrichment analysis (GSEA) subsequent to differential expression analysis is a standard step in transcriptomics and proteomics data analysis. Although many tools for this step are available, the results are often difficult to reproduce because set annotations can change in the databases, that is, new features can be added or existing features can be removed. Finally, such changes in set compositions can have an impact on biological interpretation. Methods: We present bootGSEA, a novel computational pipeline, to study the robustness of GSEA. By repeating GSEA based on bootstrap samples, the variability and robustness of results can be studied. In our pipeline, not all genes or proteins are involved in the different bootstrap replicates of the analyses. Finally, we aggregate the ranks from the bootstrap replicates to obtain a score per gene set that shows whether it gains or loses evidence compared to the ranking of the standard GSEA. Rank aggregation is also used to combine GSEA results from different omics levels or from multiple independent studies at the same omics level. Results: By applying our approach to six independent cancer transcriptomics datasets, we showed that bootstrap GSEA can aid in the selection of more robust enriched gene sets. Additionally, we applied our approach to paired transcriptomics and proteomics data obtained from a mouse model of spinal muscular atrophy (SMA), a neurodegenerative and neurodevelopmental disease associated with multi-system involvement. After obtaining a robust ranking at both omics levels, both ranking lists were combined to aggregate the findings from the transcriptomics and proteomics results. Furthermore, we constructed the new R-package "bootGSEA," which implements the proposed methods and provides graphical views of the findings. Bootstrap-based GSEA was able in the example datasets to identify gene or protein sets that were less robust when the set composition changed during bootstrap analysis. Discussion: The rank aggregation step was useful for combining bootstrap results and making them comparable to the original findings on the single-omics level or for combining findings from multiple different omics levels.

Evaluation of large language models for discovery of gene set function

Gene set analysis is a mainstay of functional genomics, but it relies on curated databases of gene functions that are incomplete. Here we evaluate five Large Language Models (LLMs) for their ability to discover the common biological functions represented by a gene set, substantiated by supporting rationale, citations and a confidence assessment. Benchmarking against canonical gene sets from the Gene Ontology, GPT-4 confidently recovered the curated name or a more general concept (73% of cases), while benchmarking against random gene sets correctly yielded zero confidence. Gemini-Pro and Mixtral-Instruct showed ability in naming but were falsely confident for random sets, whereas Llama2-70b had poor performance overall. In gene sets derived from 'omics data, GPT-4 identified novel functions not reported by classical functional enrichment (32% of cases), which independent review indicated were largely verifiable and not hallucinations. The ability to rapidly synthesize common gene functions positions LLMs as valuable 'omics assistants.

Computational drug repurposing for primary hyperparathyroidism

In hyperparathyroidism (hyperPTH), excessive amounts of PTH are secreted, interfering with calcium regulation in the body. Several drugs can control the disease's side effects, but none of them is an alternative treatment to surgery. Therefore, new drug candidates are necessary. In this study, three computationally repositioned drugs, DG 041, IMD 0354, and cucurbitacin I, are evaluated in an in vitro model of hyperPTH. First, we integrated publicly available transcriptomics datasets to propose drug candidates. Using 3D spheroids derived from a single primary hyperPTH patient, we assessed their in vitro efficacy. None of the proposed drugs affected the viability of healthy cell control (HEK293) or overactive parathyroid cells at the level of toxicity. This behavior was attributed to the non-cancerous nature of the parathyroid cells, establishing the hyperPTH disease model. Cucurbitacin I and IMD 0354 exhibited a slight inverse relationship between increased drug concentrations and cell viability, whereas DG 041 increased viability. Based on these results, further studies are needed on the mechanism of action of the repurposed drugs, including determining the effects of these drugs on cellular PTH synthesis and secretion and on the metabolic pathways that regulate PTH secretion.

Single nucleotide variants in nuclear pore complex disassembly pathway associated with poor survival in osteosarcoma

Introduction

The bone tumor, osteosarcoma, remains challenging to treat in children and young adults, especially when patients present with metastatic disease. Developing new therapies based on genomic data from sequencing projects has proven difficult given the lack of recurrent genetic lesions across tumors. MYC overexpression has been associated with poor outcomes in osteosarcoma. However, other genomic markers of disease severity are lacking.

Materials and Methods

We utilized whole genome sequencing of 106 tumors and matched normal controls in order to define genomic characteristics that correlate with overall survival. Single nucleotide variants were overlaid onto annotated molecular pathways in order to define aberrant pathway signatures specific to aggressive osteosarcoma. Additionally, we calculated differential gene expression in a subsample of 71 tumors. Differentially expressed genes were then queried for known MYC-responsive genes.

Results

Molecular pathways specific to nuclear pore complex disassembly (NPCD) show significant correlation with poor overall survival in osteosarcoma when mutations were present. Genes involved in immune response and immune regulation are enriched in the differential expression analysis of samples with and without NPCD pathway aberrations. Furthermore, neither MYC nor MYC-responsive genes show differential expression between NPCD-aberrant and non-aberrant groups. The NPCD pathway mutations are dominated by regulatory region variants rather than protein-altering mutations, suggesting that dysregulation of genetic regulatory networks may be the underlying mechanism for their relation to osteosarcoma phenotype.

Discussion

Overall survival is significantly worse in patients whose tumors show aberrations in the NPCD pathway. Moreover, this difference in survival is not driven by MYC-overexpression, suggesting a novel mechanism for some aggressive osteosarcomas. These findings add light to the evolving understanding of the drivers of osteosarcoma and may aid in the search for new treatments based on patient-specific genetic data.

A mitochondrial NADPH-cholesterol axis regulates extracellular vesicle biogenesis to support hematopoietic stem cell fate

Mitochondrial fatty acid oxidation (FAO) is essential for hematopoietic stem cell (HSC) self-renewal; however, the mechanism by which mitochondrial metabolism controls HSC fate remains unknown. Here, we show that within the hematopoietic lineage, HSCs have the largest mitochondrial NADPH pools, which are required for proper HSC cell fate and homeostasis. Bioinformatic analysis of the HSC transcriptome, biochemical assays, and genetic inactivation of FAO all indicate that FAO-generated NADPH fuels cholesterol synthesis in HSCs. Interference with FAO disturbs the segregation of mitochondrial NADPH toward corresponding daughter cells upon single HSC division. Importantly, we have found that the FAO-NADPH-cholesterol axis drives extracellular vesicle (EV) biogenesis and release in HSCs, while inhibition of EV signaling impairs HSC self-renewal. These data reveal the existence of a mitochondrial NADPH-cholesterol axis for EV biogenesis that is required for hematopoietic homeostasis and highlight the non-stochastic nature of HSC fate determination.

NMDA glutamate receptor antagonist MK-801 induces proteome changes in adult human brain slices which are partially counteracted by haloperidol and clozapine

Deciphering the molecular pathways associated with N-methyl-D-aspartate receptor (NMDAr) hypofunction and its interaction with antipsychotics is necessary to advance our understanding of the basis of schizophrenia, as well as our capacity to treat this disease. In this regard, the development of human brain-derived models that are amenable to studying the neurobiology of schizophrenia may contribute to filling the gaps left by the widely employed animal models. Here, we assessed the proteomic changes induced by the NMDA glutamate receptor antagonist MK-801 on human brain slice cultures obtained from adult donors submitted to respective neurosurgery. Initially, we demonstrated that MK-801 diminishes NMDA glutamate receptor signaling in human brain slices in culture. Next, using mass-spectrometry-based proteomics and systems biology in silico analyses, we found that MK-801 led to alterations in proteins related to several pathways previously associated with schizophrenia pathophysiology, including ephrin, opioid, melatonin, sirtuin signaling, interleukin 8, endocannabinoid, and synaptic vesicle cycle. We also evaluated the impact of both typical and atypical antipsychotics on MK-801-induced proteome changes. Interestingly, the atypical antipsychotic clozapine showed a more significant capacity to counteract the protein alterations induced by NMDAr hypofunction than haloperidol. Finally, using our dataset, we identified potential modulators of the MK-801-induced proteome changes, which may be considered promising targets to treat NMDAr hypofunction in schizophrenia. This dataset is publicly available and may be helpful in further studies aimed at evaluating the effects of MK-801 and antipsychotics in the human brain.

Proteome changes in larval zebrafish (Danio rerio) and fathead minnow (Pimephales promelas) exposed to (±) anatoxin-a

Anatoxin-a and its analogues are potent neurotoxins produced by several genera of cyanobacteria. Due in part to its high toxicity and potential presence in drinking water, these toxins pose threats to public health, companion animals and the environment. It primarily exerts toxicity as a cholinergic agonist, with high affinity at neuromuscular junctions, but molecular mechanisms by which it elicits toxicological responses are not fully understood. To advance understanding of this cyanobacteria, proteomic characterization (DIA shotgun proteomics) of two common fish models (zebrafish and fathead minnow) was performed following  (±) anatoxin-a exposure. Specifically, proteome changes were identified and quantified in larval fish exposed for 96 h (0.01-3 mg/L (±) anatoxin-a and caffeine (a methodological positive control) with environmentally relevant treatment levels examined based on environmental exposure distributions of surface water data. Proteomic concentration - response relationships revealed 48 and 29 proteins with concentration - response relationships curves for zebrafish and fathead minnow, respectively. In contrast, the highest number of differentially expressed proteins (DEPs) varied between zebrafish (n = 145) and fathead minnow (n = 300), with only fatheads displaying DEPs at all treatment levels. For both species, genes associated with reproduction were significantly downregulated, with pathways analysis that broadly clustered genes into groups associated with DNA repair mechanisms. Importantly, significant differences in proteome response between the species was also observed, consistent with prior observations of differences in response using both behavioral assays and gene expression, adding further support to model specific differences in organismal sensitivity and/or response. When DEPs were read across from humans to zebrafish, disease ontology enrichment identified diseases associated with cognition and muscle weakness consistent with the prior literature. Our observations highlight limited knowledge of how (±) anatoxin-a, a commonly used synthetic racemate surrogate, elicits responses at a molecular level and advances its toxicological understanding.

Illuminating the functions of the understudied Fructosamine-3-kinase (FN3K) using a multi-omics approach reveals new links to lipid, carbon, and co-factor metabolic pathways

Fructosamine-3-kinases (FN3Ks) are a conserved family of repair enzymes that phosphorylate reactive sugars attached to lysine residues in peptides and proteins. Although FN3Ks are present across the tree of life and share detectable sequence similarity to eukaryotic protein kinases, the biological processes regulated by these kinases are largely unknown. To address this knowledge gap, we leveraged the FN3K CRISPR Knock-Out (KO) cell line alongside an integrative multi-omics study combining transcriptomics, metabolomics, and interactomics to place these enzymes in a pathway context. The integrative analyses revealed the enrichment of pathways related to oxidative stress response, lipid biosynthesis (cholesterol and fatty acids), carbon and co-factor metabolism. Moreover, enrichment of nicotinamide adenine dinucleotide (NAD) binding proteins and localization of human FN3K (HsFN3K) to mitochondria suggests potential links between FN3Ks and NAD-mediated energy metabolism and redox balance. We report specific binding of HsFN3K to NAD compounds in a metal and concentration-dependent manner and provide insight into their binding mode using modeling and experimental site-directed mutagenesis. By identifying a potential link between FN3Ks, redox regulation, and NAD-dependent metabolic processes, our studies provide a framework for targeting these understudied kinases in diabetic complications and metabolic disorders where redox balance is altered.

Association of plasma proteomics with incident coronary heart disease in individuals with and without type 2 diabetes: results from the population-based KORA study

BACKGROUND

Coronary heart disease (CHD) is a major global health concern, especially among individuals with type 2 diabetes (T2D). Given the crucial role of proteins in various biological processes, this study aimed to elucidate the aetiological role and predictive performance of protein biomarkers on incident CHD in individuals with and without T2D.

METHODS

The discovery cohort included 1492 participants from the Cooperative Health Research in the Region of Augsburg (KORA) S4 study with 147 incident CHD cases (45 vs. 102 cases in the group with T2D and without T2D, respectively) during 15.6 years of follow-up. The validation cohort included 888 participants from the KORA-Age1 study with 70 incident CHD cases (19 vs. 51 cases in the group with T2D and without T2D, respectively) during 6.9 years of follow-up. We measured 233 plasma proteins related to cardiovascular disease and inflammation using proximity extension assay technology. Associations of proteins with incident CHD were assessed using Cox regression and Mendelian randomization (MR) analysis. Predictive models were developed using priority-Lasso and were evaluated on top of Framingham risk score variables using the C-index, category-free net reclassification index (cfNRI), and relative integrated discrimination improvement (IDI).

RESULTS

We identified two proteins associated with incident CHD in individuals with and 29 in those without baseline T2D, respectively. Six of these proteins are novel candidates for incident CHD. MR suggested a potential causal role for hepatocyte growth factor in CHD development. The developed four-protein-enriched model for individuals with baseline T2D (ΔC-index: 0.017; cfNRI: 0.253; IDI: 0.051) and the 12-protein-enriched model for individuals without baseline T2D (ΔC-index: 0.054; cfNRI: 0.462; IDI: 0.024) consistently improved CHD prediction in the discovery cohort, while in the validation cohort, significant improvements were only observed for selected performance measures (with T2D: cfNRI: 0.633; without T2D: ΔC-index: 0.038; cfNRI: 0.465).

CONCLUSIONS

This study identified novel protein biomarkers associated with incident CHD in individuals with and without T2D and reaffirmed previously reported protein candidates. These findings enhance our understanding of CHD pathophysiology and provide potential targets for prevention and treatment.

CardiOmics signatures reveal therapeutically actionable targets and drugs for cardiovascular diseases

Cardiovascular diseases are the leading cause of death worldwide, with heart failure being a complex condition that affects millions of individuals. Single-nucleus RNA sequencing has recently emerged as a powerful tool for unraveling the molecular mechanisms behind cardiovascular diseases. This cutting-edge technology enables the identification of molecular signatures, intracellular networks, and spatial relationships among cardiac cells, including cardiomyocytes, mast cells, lymphocytes, macrophages, lymphatic endothelial cells, endocardial cells, endothelial cells, epicardial cells, adipocytes, fibroblasts, neuronal cells, pericytes, and vascular smooth muscle cells. Despite these advancements, the discovery of essential therapeutic targets and drugs for precision cardiology remains a challenge. To bridge this gap, we conducted comprehensive in silico analyses of single-nucleus RNA sequencing data, functional enrichment, protein interactome network, and identification of the shortest pathways to physiological phenotypes. This integrated multi-omics analysis generated CardiOmics signatures, which allowed us to pinpoint three therapeutically actionable targets (ADRA1A1, PPARG, and ROCK2) and 15 effective drugs, including adrenergic receptor agonists, adrenergic receptor antagonists, norepinephrine precursors, PPAR receptor agonists, and Rho-associated kinase inhibitors, involved in late-stage cardiovascular disease clinical trials.

Peripheral immune responses to filoviruses in a reservoir versus spillover hosts reveal transcriptional correlates of disease

Several filoviruses, including Marburg virus (MARV), cause severe disease in humans and nonhuman primates (NHPs). However, the Egyptian rousette bat (ERB, Rousettus aegyptiacus), the only known MARV reservoir, shows no overt illness upon natural or experimental infection, which, like other bat hosts of zoonoses, is due to well-adapted, likely species-specific immune features. Despite advances in understanding reservoir immune responses to filoviruses, ERB peripheral blood responses to MARV and how they compare to those of diseased filovirus-infected spillover hosts remain ill-defined. We thus conducted a longitudinal analysis of ERB blood gene responses during acute MARV infection. These data were then contrasted with a compilation of published primate blood response studies to elucidate gene correlates of filovirus protection versus disease. Our work expands on previous findings in MARV-infected ERBs by supporting both host resistance and disease tolerance mechanisms, offers insight into the peripheral immunocellular repertoire during infection, and provides the most direct known cross-examination between reservoir and spillover hosts of the most prevalently-regulated response genes, pathways and activities associated with differences in filovirus pathogenesis and pathogenicity.

PathBank 2.0-the pathway database for model organism metabolomics

PathBank (https://pathbank.org) and its predecessor database, the Small Molecule Pathway Database (SMPDB), have been providing comprehensive metabolite pathway information for the metabolomics community since 2010. Over the past 14 years, these pathway databases have grown and evolved significantly to meet the needs of the metabolomics community and respond to continuing changes in computing technology. This year's update, PathBank 2.0, brings a number of important improvements and upgrades that should make the database more useful and more appealing to a larger cross-section of users. In particular, these improvements include: (i) a significant increase in the number of primary or canonical pathways (from 1720 to 6951); (ii) a massive increase in the total number of pathways (from 110 234 to 605 359); (iii) significant improvements to the quality of pathway diagrams and pathway descriptions; (iv) a strong emphasis on drug metabolism and drug mechanism pathways; (v) making most pathway images more slide-compatible and manuscript-compatible; (vi) adding tools to support better pathway filtering and selecting through a more complete pathway taxonomy; (vii) adding pathway analysis tools for visualizing and calculating pathway enrichment. Many other minor improvements and updates to the content, the interface and general performance of the PathBank website have also been made. Overall, we believe these upgrades and updates should greatly enhance PathBank's ease of use and its potential applications for interpreting metabolomics data.

AutophagyNet: high-resolution data source for the analysis of autophagy and its regulation

Macroautophagy/autophagy is a highly-conserved catabolic procss eliminating dysfunctional cellular components and invading pathogens. Autophagy malfunction contributes to disorders such as cancer, neurodegenerative and inflammatory diseases. Understanding autophagy regulation in health and disease has been the focus of the last decades. We previously provided an integrated database for autophagy research, the Autophagy Regulatory Network (ARN). For the last eight years, this resource has been used by thousands of users. Here, we present a new and upgraded resource, AutophagyNet. It builds on the previous database but contains major improvements to address user feedback and novel needs due to the advancement in omics data availability. AutophagyNet contains updated interaction curation and integration of over 280,000 experimentally verified interactions between core autophagy proteins and their protein, transcriptional and post-transcriptional regulators as well as their potential upstream pathway connections. AutophagyNet provides annotations for each core protein about their role: 1) in different types of autophagy (mitophagy, xenophagy, etc.); 2) in distinct stages of autophagy (initiation, expansion, termination, etc.); 3) with subcellular and tissue-specific localization. These annotations can be used to filter the dataset, providing customizable download options tailored to the user's needs. The resource is available in various file formats (e.g. CSV, BioPAX and PSI-MI), and data can be analyzed and visualized directly in Cytoscape. The multi-layered regulation of autophagy can be analyzed by combining AutophagyNet with tissue- or cell type-specific (multi-)omics datasets (e.g. transcriptomic or proteomic data). The resource is publicly accessible at http://autophagynet.org.Abbreviations: ARN: Autophagy Regulatory Network; ATG: autophagy related; BCR: B cell receptor pathway; BECN1: beclin 1; GABARAP: GABA type A receptor-associated protein; IIP: innate immune pathway; LIR: LC3-interacting region; lncRNA: long non-coding RNA; MAP1LC3B: microtubule associated protein 1 light chain 3 beta; miRNA: microRNA; NHR: nuclear hormone receptor; PTM: post-translational modification; RTK: receptor tyrosine kinase; TCR: T cell receptor; TLR: toll like receptor.

Gene module reconstruction elucidates cellular differentiation processes and the regulatory logic of specialized secretion

During differentiation, cells become structurally and functionally specialized, but comprehensive views of the underlying remodeling processes are elusive. Here, we leverage scRNA-seq developmental trajectories to reconstruct differentiation using two secretory tissues as a model system - the zebrafish notochord and hatching gland. First, we present an approach to integrate expression and functional similarities for gene module identification, revealing dozens of gene modules representing known and newly associated differentiation processes and their temporal ordering. Second, we focused on the unfolded protein response (UPR) transducer module to study how general versus cell-type specific secretory functions are regulated. By profiling loss- and gain-of-function embryos, we found that the UPR transcription factors creb3l1, creb3l2, and xbp1 are master regulators of a general secretion program. creb3l1/creb3l2 additionally activate an extracellular matrix secretion program, while xbp1 partners with bhlha15 to activate a gland-specific secretion program. Our study offers a multi-source integrated approach for functional gene module identification and illustrates how transcription factors confer general and specialized cellular functions.

Unagi: Deep Generative Model for Deciphering Cellular Dynamics and In-Silico Drug Discovery in Complex Diseases

Human diseases are characterized by intricate cellular dynamics. Single-cell sequencing provides critical insights, yet a persistent gap remains in computational tools for detailed disease progression analysis and targeted in-silico drug interventions. Here, we introduce UNAGI, a deep generative neural network tailored to analyze time-series single-cell transcriptomic data. This tool captures the complex cellular dynamics underlying disease progression, enhancing drug perturbation modeling and discovery. When applied to a dataset from patients with Idiopathic Pulmonary Fibrosis (IPF), UNAGI learns disease-informed cell embeddings that sharpen our understanding of disease progression, leading to the identification of potential therapeutic drug candidates. Validation via proteomics reveals the accuracy of UNAGI's cellular dynamics analyses, and the use of the Fibrotic Cocktail treated human Precision-cut Lung Slices confirms UNAGI's predictions that Nifedipine, an antihypertensive drug, may have antifibrotic effects on human tissues. UNAGI's versatility extends to other diseases, including a COVID dataset, demonstrating adaptability and confirming its broader applicability in decoding complex cellular dynamics beyond IPF, amplifying its utility in the quest for therapeutic solutions across diverse pathological landscapes.

MicroRNA-152-3p and MicroRNA-196a-5p Are Downregulated When Müller Cells Are Promoted by Components of the Internal Limiting Membrane: Implications for Macular Hole Healing

Müller cells play a critical role in the closure of macular holes, and their proliferation and migration are facilitated by the internal limiting membrane (ILM). Despite the importance of this process, the underlying molecular mechanism remains underexplored. This study investigated the effects of ILM components on the microRNA (miRNA) profile of Müller cells. Rat Müller cells (rMC-1) were cultured with a culture insert and varying concentrations of ILM component coatings, namely, collagen IV, laminin, and fibronectin, and cell migration was assessed by measuring cell-free areas in successive photographs following insert removal. MiRNAs were then extracted from these cells and analyzed. Mimics and inhibitors of miRNA candidates were transfected into Müller cells, and a cell migration assay and additional cell viability assays were performed. The results revealed that the ILM components promoted Müller cell migration (p < 0.01). Among the miRNA candidates, miR-194-3p was upregulated, whereas miR-125b-1-3p, miR-132-3p, miR-146b-5p, miR-152-3p, miR-196a-5p, miR-542-5p, miR-871-3p, miR-1839-5p, and miR-3573-3p were significantly downregulated (p < 0.05; fold change > 1.5). Moreover, miR-152-3p and miR-196a-5p reduced cell migration (p < 0.05) and proliferation (p < 0.001), and their suppressive effects were reversed by their respective inhibitors. In conclusion, miRNAs were regulated in ILM component-activated Müller cells, with miR-152-3p and miR-196a-5p regulating Müller cell migration and proliferation. These results serve as a basis for understanding the molecular healing process of macular holes and identifying potential new target genes in future research.

Neuromuscular and gene signaling responses to passive whole-body heat stress in young adults

This study aimed to investigate whether acute passive heat stress 1) decreases muscle Maximal Voluntary Contraction (MVC); 2) increases peripheral muscle fatigue; 3) increases spinal cord excitability, and 4) increases key skeletal muscle gene signaling pathways in skeletal muscle. Examining the biological and physiological markers underlying passive heat stress will assist us in understanding the potential therapeutic benefits. MVCs, muscle fatigue, spinal cord excitability, and gene signaling were examined after control or whole body heat stress in an environmental chamber (heat; 82 °C, 10% humidity for 30 min). Heart Rate (HR), an indicator of stress response, was correlated to muscle fatigue in the heat group (R = 0.59; p < 0.05) but was not correlated to MVC, twitch potentiation, and H reflex suppression. Sixty-one genes were differentially expressed after heat (41 genes >1.5-fold induced; 20 < 0.667 fold repressed). A strong correlation emerged between the session type (control or heat) and principal components (PC1) (R = 0.82; p < 0.005). Cell Signal Transduction, Metabolism, Gene Expression and Transcription, Immune System, DNA Repair, and Metabolism of Proteins were pathway domains with the largest number of genes regulated after acute whole body heat stress. Acute whole-body heat stress may offer a physiological stimulus for people with a limited capacity to exercise.

Network medicine approaches for identification of novel prognostic systems biomarkers and drug candidates for papillary thyroid carcinoma

Papillary thyroid carcinoma (PTC) is one of the most common endocrine carcinomas worldwide and the aetiology of this cancer is still not well understood. Therefore, it remains important to understand the disease mechanism and find prognostic biomarkers and/or drug candidates for PTC. Compared with approaches based on single-gene assessment, network medicine analysis offers great promise to address this need. Accordingly, in the present study, we performed differential co-expressed network analysis using five transcriptome datasets in patients with PTC and healthy controls. Following meta-analysis of the transcriptome datasets, we uncovered common differentially expressed genes (DEGs) for PTC and, using these genes as proxies, found a highly clustered differentially expressed co-expressed module: a 'PTC-module'. Using independent data, we demonstrated the high prognostic capacity of the PTC-module and designated this module as a prognostic systems biomarker. In addition, using the nodes of the PTC-module, we performed drug repurposing and text mining analyzes to identify novel drug candidates for the disease. We performed molecular docking simulations, and identified: 4-demethoxydaunorubicin hydrochloride, AS605240, BRD-A60245366, ER 27319 maleate, sinensetin, and TWS119 as novel drug candidates whose efficacy was also confirmed by in silico analyzes. Consequently, we have highlighted here the need for differential co-expression analysis to gain a systems-level understanding of a complex disease, and we provide candidate prognostic systems biomarker and novel drugs for PTC.

Functional immunophenotyping of blood neutrophils identifies novel endotypes of viral response in preschool children with recurrent wheezing

BACKGROUND

Preschool children with recurrent wheezing are heterogeneous, with differing responses to respiratory viral infections. Although neutrophils are crucial for host defense, their function has not been studied in this population.

OBJECTIVE

We performed functional immunophenotyping on isolated blood neutrophils from 52 preschool children with recurrent wheezing (aeroallergen sensitization, n = 16; no sensitization, n = 36).

METHODS

Blood neutrophils were purified and cultured overnight with polyinosinic:polycytidylic acid [poly(I:C)] as a viral analog stimulus. Neutrophils underwent next-generation sequencing with Reactome pathway analysis and were analyzed for cytokine secretion, apoptosis, myeloperoxidase, and extracellular DNA release. CD14+ monocytes were also exposed to neutrophil culture supernatant and analyzed for markers of M1 and M2 activation.

RESULTS

A total of 495 genes, related largely to the innate immune system and neutrophil degranulation, were differently expressed in children with versus without aeroallergen sensitization. Functional experiments identified more neutrophil degranulation and extracellular trap formation (ie, more myeloperoxidase and extracellular DNA) and less neutrophil proinflammatory cytokine secretion in children with aeroallergen sensitization. Neutrophils also shifted CD14+ monocytes to a more anti-inflammatory (ie, M2) phenotype in sensitized children and a more proinflammatory (ie, M1) phenotype in nonsensitized children. Although both groups experienced viral exacerbations, annualized exacerbation rates prompting unscheduled health care were also higher in children without aeroallergen sensitization after enrollment.

CONCLUSIONS

Systemic neutrophil responses to viral infection differ by allergic phenotype and may be less effective in preschool children without allergic inflammation. Further studies of neutrophil function are needed in this population, which often has less favorable therapeutic responses to inhaled corticosteroids and other therapies directed at type 2-high inflammation.

Fischer JDS. Proteomics reveals differentially regulated pathways when comparing grade 2 and 4 astrocytomas

Astrocytic tumors are known for their high progression capacity and high mortality rates; in this regard, proteins correlated to prognosis can aid medical conduct. Although several genetic changes related to progression from grade 2 to grade 4 astrocytoma are already known, mRNA copies do not necessarily correlate with protein abundance and therefore could shadow further comprehension about this tumor's biology. This motivates us to seek for complementary strategies to study tumor progression at the protein level. Here we compare the proteomic profile of biopsies from patients with grade 2 (diffuse, n = 6) versus grade 4 astrocytomas (glioblastomas, n = 10) using shotgun proteomics. Data analysis performed with PatternLab for proteomics identified 5,206 and 6,004 proteins in the 2- and 4-grade groups, respectively. Our results revealed seventy-four differentially abundant proteins (p < 0.01); we then shortlist those related to greater malignancy. We also describe molecular pathways distinctly activated in the two groups, such as differences in the organization of the extracellular matrix, decisive both in tumor invasiveness and in signaling for cell division, which, together with marked contrasts in energy metabolism, are determining factors in the speed of growth and dissemination of these neoplasms. The degradation pathways of GABA, enriched in the grade 2 group, is consistent with a favorable prognosis. Other functions such as platelet degranulation, apoptosis, and activation of the MAPK pathway were correlated to grade 4 tumors and, consequently, unfavorable prognoses. Our results provide an important survey of molecular pathways involved in glioma pathogenesis for these histopathological groups.

Unraveling Connective Tissue Growth Factor as a Therapeutic Target and Assessing Kahweol as a Potential Drug Candidate in Triple-Negative Breast Cancer Treatment

Triple-negative breast cancer (TNBC) is characterized by aggressive behavior and limited treatment options, necessitating the identification of novel therapeutic targets. In this study, we investigated the clinical significance of connective tissue growth factor (CTGF) as a prognostic marker and explored the potential therapeutic effects of kahweol, a coffee diterpene molecule, in TNBC treatment. Initially, through a survival analysis on breast cancer patients from The Cancer Genome Atlas (TCGA) database, we found that CTGF exhibited significant prognostic effects exclusively in TNBC patients. To gain mechanistic insights, we performed the functional annotation and gene set enrichment analyses, revealing the involvement of CTGF in migratory pathways relevant to TNBC treatment. Subsequently, in vitro experiments using MDA-MB 231 cells, a representative TNBC cell line, demonstrated that recombinant CTGF (rCTGF) administration enhanced cell motility, whereas CTGF knockdown using CTGF siRNA resulted in reduced motility. Notably, rCTGF restored kahweol-reduced cell motility, providing compelling evidence for the role of CTGF in mediating kahweol's effects. At the molecular level, kahweol downregulated the protein expression of CTGF as well as critical signaling molecules, such as p-ERK, p-P38, p-PI3K/AKT, and p-FAK, associated with cell motility. In summary, our findings propose CTGF as a potential prognostic marker for guiding TNBC treatment and suggest kahweol as a promising antitumor compound capable of regulating CTGF expression to suppress cell motility in TNBC. These insights hold promise for the development of targeted therapies and improved clinical outcomes for TNBC patients.

Immune inhibitory receptor-mediated immune response, metabolic adaptation, and clinical characterization in patients with COVID-19

Immune inhibitory receptors (IRs) play a critical role in the regulation of immune responses to various respiratory viral infections. However, in coronavirus disease 2019 (COVID-19), the roles of these IRs in immune modulation, metabolic reprogramming, and clinical characterization remain to be determined. Through consensus clustering analysis of IR transcription in the peripheral blood of patients with COVID-19, we identified two distinct IR patterns in patients with COVID-19, which were named IR_cluster1 and IR_cluster2. Compared to IR_cluster1 patients, IR_cluster2 patients with lower expressions of immune inhibitory receptors presented with a suppressed immune response, lower nutrient metabolism, and worse clinical manifestations or prognosis. Considering the critical influence of the integrated regulation of multiple IRs on disease severity, we established a scoring system named IRscore, which was based on principal component analysis, to evaluate the combined effect of multiple IRs on the disease status of individual patients with COVID-19. Similar to IR_cluster2 patients, patients with high IRscores had longer hospital-free days at day 45, required ICU admission and mechanical ventilatory support, and presented higher Charlson comorbidity index and SOFA scores. A high IRscore was also linked to acute infection phase and absence of drug intervention. Our investigation comprehensively elucidates the potential role of IR patterns in regulating the immune response, modulating metabolic processes, and shaping clinical manifestations of COVID-19. All of this evidence suggests the essential role of prognostic stratification and biomarker screening based on IR patterns in the clinical management and drug development of future emerging infectious diseases such as COVID-19.

The tumor microenvironment state associates with response to HPV therapeutic vaccination in patients with respiratory papillomatosis

Recurrent respiratory papillomatosis (RRP) is a rare, debilitating neoplastic disorder caused by chronic infection with human papillomavirus (HPV) type 6 or 11 and characterized by growth of papillomas in the upper aerodigestive tract. There is no approved medical therapy, and patients require repeated debulking procedures to maintain voice and airway function. PRGN-2012 is a gorilla adenovirus immune-therapeutic capable of enhancing HPV 6/11-specific T cell immunity. This first-in-human, phase 1 study (NCT04724980) of adjuvant PRGN-2012 treatment in adult patients with severe, aggressive RRP demonstrates the overall safety and clinically meaningful benefit observed with PRGN-2012, with a 50% complete response rate in patients treated at the highest dose. Responders demonstrate greater expansion of peripheral HPV-specific T cells compared with nonresponders. Additional correlative studies identify an association between reduced baseline papilloma HPV gene expression, greater interferon responses and expression of CXCL9 and CXCL10, and greater papilloma T cell infiltration in responders. Conversely, nonresponders were characterized by greater HPV and CXCL8 gene expression, increased neutrophilic cell infiltration, and reduced T cell papilloma infiltration. These results suggest that papilloma HPV gene expression may regulate interferon signaling and chemokine expression profiles within the tumor microenvironment that cooperate to govern clinical response to therapeutic HPV vaccination in patients with respiratory papillomatosis.

Niclosamide as a chemical probe for analyzing SARS-CoV-2 modulation of host cell lipid metabolism

Introduction

SARS-CoV-2 subverts host cell processes to facilitate rapid replication and dissemination, and this leads to pathological inflammation.

Methods

We used niclosamide (NIC), a poorly soluble anti-helminth drug identified initially for repurposed treatment of COVID-19, which activates the cells' autophagic and lipophagic processes as a chemical probe to determine if it can modulate the host cell's total lipid profile that would otherwise be either amplified or reduced during SARS-CoV-2 infection.

Results

Through parallel lipidomic and transcriptomic analyses we observed massive reorganization of lipid profiles of SARS-CoV-2 infected Vero E6 cells, especially with triglycerides, which were elevated early during virus replication, but decreased thereafter, as well as plasmalogens, which were elevated at later timepoints during virus replication, but were also elevated under normal cell growth. These findings suggested a complex interplay of lipid profile reorganization involving plasmalogen metabolism. We also observed that NIC treatment of both low and high viral loads does not affect virus entry. Instead, NIC treatment reduced the abundance of plasmalogens, diacylglycerides, and ceramides, which we found elevated during virus infection in the absence of NIC, resulting in a significant reduction in the production of infectious virions. Unexpectedly, at higher viral loads, NIC treatment also resulted in elevated triglyceride levels, and induced significant changes in phospholipid metabolism.

Discussion

We posit that future screens of approved or new partner drugs should prioritize compounds that effectively counter SARS-CoV-2 subversion of lipid metabolism, thereby reducing virus replication, egress, and the subsequent regulation of key lipid mediators of pathological inflammation.

Dissection of paracrine/autocrine interplay in lung tumor microenvironment mimicking cancer cell-monocyte co-culture models reveals proteins that promote inflammation and metastasis

BACKGROUND

Tumor cell-monocyte interactions play crucial roles in shaping up the pro-tumorigenic phenotype and functional output of tumor-associated macrophages. Within the tumor microenvironment, such heterotypic cell-cell interactions are known to occur via secretory proteins. Secretory proteins establish a diabolic liaison between tumor cells and monocytes, leading to their recruitment, subsequent polarization and consequent tumor progression.

METHODS

We co-cultured model lung adenocarcinoma cell line A549 with model monocytes, THP-1 to delineate the interactions between them. The levels of prototypical pro-inflammatory cytokines like TNF-𝛼, IL-6 and anti-inflammatory cytokines like IL-10 were measured by ELISA. Migration, invasion and attachment independence of lung cancer cells was assessed by wound healing, transwell invasion and colony formation assays respectively. The status of EMT was evaluated by immunofluorescence. Identification of secretory proteins differentially expressed in monocultures and co-culture was carried out using SILAC LC-MS/MS. Various insilico tools like Cytoscape, Reacfoam, CHAT and Kaplan-Meier plotter were utilized for association studies, pathway analysis, functional classification, cancer hallmark relevance and predicting the prognostic potential of the candidate secretory proteins respectively.

RESULTS

Co-culture of A549 and THP-1 cells in 1:10 ratio showed early release of prototypical pro-inflammatory cytokines TNF-𝛼 and IL-6, however anti-inflammatory cytokine, IL-10 was observed to be released at the highest time point. The conditioned medium obtained from this co-culture ratio promoted the migration, invasion and colony formation as well as the EMT of A549 cells. Co-culturing of A549 with THP-1 cells modulated the secretion of proteins involved in cell proliferation, migration, invasion, EMT, inflammation, angiogenesis and inhibition of apoptosis. Among these proteins Versican, Tetranectin, IGFBP2, TUBB4B, C2 and IFI30 were found to correlate with the inflammatory and pro-metastatic milieu observed in our experimental setup. Furthermore, dysregulated expression of these proteins was found to be associated with poor prognosis and negative disease outcomes in lung adenocarcinoma compared to other cancer types. Pharmacological interventions targeting these proteins may serve as useful therapeutic approaches in lung adenocarcinoma.

CONCLUSION

In this study, we have demonstrated that the lung cancer cell-monocyte cross-talk modulates the secretion of IFI30, RNH1, CLEC3B, VCAN, IGFBP2, C2 and TUBB4B favoring tumor growth and metastasis.

BMP4, SGSH, and SLC11A2 are Predicted to Be Biomarkers of Aging Associated with Programmed Cell Death

Most neurodegenerative diseases are exacerbated by aging, with symptoms often worsening over time. Programmed cell death (PCD) is a controlled cell suicide mechanism that is essential for the stability, growth, and homeostasis of organisms. Understanding the effects of aging at the level of systems biology could lead to new therapeutic approaches for a broad spectrum of neurodegenerative diseases. In the absence of comprehensive functional studies on the relationship between PCD and aging of the prefrontal cortex, this study provides prefrontal brain biomarkers of aging associated with PCD that could open the way for improved therapeutic techniques for age-related neurodegenerative diseases. To this end, publicly available transcriptome data were subjected to bioinformatic analyses such as differential gene expression, functional enrichment, and the weighted gene coexpression network analysis (WGCNA). The diagnostic utility of the biomarkers was tested using a logistic regression-based prediction model. Three genes, namely BMP4, SGSH, and SLC11A2, were found to be aging biomarkers associated with PCD. Finally, a multifactorial regulatory network with interacting proteins, transcription factors (TFs), competing endogenous RNAs (ceRNAs), and microRNAs (miRNAs) was constructed around these biomarkers. The elements of this multifactorial regulatory network were mainly enriched in BMP signaling. Further exploration of these three biomarkers and their regulatory elements would enable the development of 3PM (predictive, preventive, and personalized) medicine for the treatment of age-related neurodegenerative diseases.

Three candidate anticancer drugs were repositioned by integrative analysis of the transcriptomes of species with different regenerative abilities after injury

Regeneration is a homeostatic process that involves the restoration of cells and body parts. Most of the molecular mechanisms and signalling pathways involved in wound healing, such as proliferation, have also been associated with cancer cell growth, suggesting that cancer is an over/unhealed wound. In this study, we examined differentially expressed genes in spinal cord samples from regenerative organisms (axolotl and zebrafish) and nonregenerative organisms (mouse and rat) compared to intact control spinal cord samples using publicly available transcriptomics data and bioinformatics analyses. Based on these gene signatures, we investigated 3 small compounds, namely cucurbitacin I, BMS-754807, and PHA-793887 as potential candidates for the treatment of cancer. The predicted target genes of the repositioned compounds were mainly enriched with the greatest number of genes in cancer pathways. The molecular docking results on the binding affinity between the repositioned compounds and their target genes are also reported. The repositioned 3 small compounds showed anticancer effect both in 2D and 3D cell cultures using the prostate cancer cell line as a model. We propose cucurbitacin I, BMS-754807, and PHA-793887 as potential anticancer drug candidates. Future studies on the mechanisms associated with the revealed gene signatures and anticancer effects of these three small compunds would allow scientists to develop therapeutic approaches to combat cancer. This research contributes to the evaluation of mechanisms and gene signatures that either limit or cause cancer, and to the development of new cancer therapies by establishing a link between regeneration and carcinogenesis.

Integrated analysis of proteomics, epigenomics and metabolomics data revealed divergent pathway activation patterns in the recent versus chronic post-traumatic stress disorder

Metabolomics, proteomics and DNA methylome assays, when done in tandem from the same blood sample and analyzed together, offer an opportunity to evaluate the molecular basis of post-traumatic stress disorder (PTSD) course and pathogenesis. We performed separate metabolomics, proteomics, and DNA methylome assays on blood samples from two well-characterized cohorts of 159 active duty male participants with relatively recent onset PTSD (<1.5 years) and 300 male veterans with chronic PTSD (>7 years). Analyses of the multi-omics datasets from these two independent cohorts were used to identify convergent and distinct molecular profiles that might constitute potential signatures of severity and progression of PTSD and its comorbid conditions. Molecular signatures indicative of homeostatic processes such as signaling and metabolic pathways involved in cellular remodeling, neurogenesis, molecular safeguards against oxidative stress, metabolism of polyunsaturated fatty acids, regulation of normal immune response, post-transcriptional regulation, cellular maintenance and markers of longevity were significantly activated in the active duty participants with recent PTSD. In contrast, we observed significantly altered multimodal molecular signatures associated with chronic inflammation, neurodegeneration, cardiovascular and metabolic disorders, and cellular attritions in the veterans with chronic PTSD. Activation status of signaling and metabolic pathways at the early and late timepoints of PTSD demonstrated the differential molecular changes related to homeostatic processes at its recent and multi-system syndromes at its chronic phase. Molecular alterations in the recent PTSD seem to indicate some sort of recalibration or compensatory response, possibly directed in mitigating the pathological trajectory of the disorder.

Immunomodulatory contribution of mast cells to the regenerative biomaterial microenvironment

Bioactive immunomodulatory biomaterials have shown promise for influencing the immune response to promote tissue repair and regeneration. Macrophages and T cells have been associated with this response; however, other immune cell types have been traditionally overlooked. In this study, we investigated the role of mast cells in the regulation of the immune response to decellularized biomaterial scaffolds using a subcutaneous implant model. In mast cell-deficient mice, there was dysregulation of the expected M1 to M2 macrophage transition typically induced by the biomaterial scaffold. Polarization progression deviated in a sex-specific manner with an early transition to an M2 profile in female mice, while the male response was unable to properly transition past a pro-inflammatory M1 state. Both were reversed with adoptive mast cell transfer. Further investigation of the later-stage immune response in male mice determined a greater sustained pro-inflammatory gene expression profile, including the IL-1 cytokine family, IL-6, alarmins, and chemokines. These results highlight mast cells as another important cell type that influences the immune response to pro-regenerative biomaterials.

Evaluation of large language models for discovery of gene set function

Gene set analysis is a mainstay of functional genomics, but it relies on manually curated databases of gene functions that are incomplete and unaware of biological context. Here we evaluate the ability of OpenAI's GPT-4, a Large Language Model (LLM), to develop hypotheses about common gene functions from its embedded biomedical knowledge. We created a GPT-4 pipeline to label gene sets with names that summarize their consensus functions, substantiated by analysis text and citations. Benchmarking against named gene sets in the Gene Ontology, GPT-4 generated very similar names in 50% of cases, while in most remaining cases it recovered the name of a more general concept. In gene sets discovered in 'omics data, GPT-4 names were more informative than gene set enrichment, with supporting statements and citations that largely verified in human review. The ability to rapidly synthesize common gene functions positions LLMs as valuable functional genomics assistants.

Rare FGFR fusion genes in cervical cancer and transcriptome-based subgrouping of patients with a poor prognosis

BACKGROUND

Although cervical cancer is often characterized as preventable, its incidence continues to increase in low- and middle-income countries, underscoring the need to develop novel therapeutics for this disease.This study assessed the distribution of fusion genes across cancer types and used an RNA-based classification to divide cervical cancer patients with a poor prognosis into subgroups.

MATERIAL AND METHODS

RNA sequencing of 116 patients with cervical cancer was conducted. Fusion genes were extracted using StarFusion program. To identify a high-risk group for recurrence, 65 patients who received postoperative adjuvant therapy were subjected to non-negative matrix factorization to identify differentially expressed genes between recurrent and nonrecurrent groups.

RESULTS

We identified three cases with FGFR3-TACC3 and one with GOPC-ROS1 fusion genes as potential targets. A search of publicly available data from cBioPortal (21,789 cases) and the Center for Cancer Genomics and Advanced Therapeutics (32,608 cases) showed that the FGFR3 fusion is present in 1.5% and 0.6% of patients with cervical cancer, respectively. The frequency of the FGFR3 fusion gene was higher in cervical cancer than in other cancers, regardless of ethnicity. Non-negative matrix factorization identified that the patients were classified into four Basis groups. Pathway enrichment analysis identified more extracellular matrix kinetics dysregulation in Basis 3 and more immune system dysregulation in Basis 4 than in the good prognosis group. CIBERSORT analysis showed that the fraction of M1 macrophages was lower in the poor prognosis group than in the good prognosis group.

CONCLUSIONS

The distribution of FGFR fusion genes in patients with cervical cancer was determined by RNA-based analysis and used to classify patients into clinically relevant subgroups.

Network pharmacology and topological analysis on tibolone metabolites and their molecular mechanisms in traumatic brain injury

Traumatic brain injury (TBI) is a pathology of great social impact, affecting millions of people worldwide. Despite the scientific advances to improve the management of TBI in recent years, we still do not have a specific treatment that controls the inflammatory process after mechanical trauma. The discovery and implementation of new treatments is a long and expensive process, making the repurpose of approved drugs for other pathologies a clinical interest. Tibolone is a drug in use for the treatment of symptoms associated with menopause and has been shown to have a broad spectrum of actions by regulating estrogen, androgen and progesterone receptors, whose activation exerts potent anti-inflammatory and antioxidant effects. In the present study, we aimed to investigate the therapeutic potential of the tibolone metabolites 3α-Hydroxytibolone, 3β-Hydroxytibolone, and Δ4-Tibolone as a possible therapy in TBI using network pharmacology and network topology analysis. Our results demonstrate that the estrogenic component mediated by the α and β metabolites can regulate synaptic transmission and cell metabolism, while the Δ metabolite may be involved in modulating the post-TBI inflammatory process. We identified several molecular targets, including KDR, ESR2, AR, NR3C1, PPARD, and PPARA, which are known to play critical roles in the pathogenesis of TBI. Tibolone metabolites were predicted to regulate the expression of key genes involved in oxidative stress, inflammation, and apoptosis. Overall, the repurposing of tibolone as a neuroprotective treatment for TBI holds promise for future clinical trials. However, further studies are needed to confirm its efficacy and safety in TBI patients.

Heterogeneity in the gene regulatory landscape of leiomyosarcoma

Characterizing inter-tumor heterogeneity is crucial for selecting suitable cancer therapy, as the presence of diverse molecular subgroups of patients can be associated with disease outcome or response to treatment. While cancer subtypes are often characterized by differences in gene expression, the mechanisms driving these differences are generally unknown. We set out to model the regulatory mechanisms driving sarcoma heterogeneity based on patient-specific, genome-wide gene regulatory networks. We developed a new computational framework, PORCUPINE, which combines knowledge on biological pathways with permutation-based network analysis to identify pathways that exhibit significant regulatory heterogeneity across a patient population. We applied PORCUPINE to patient-specific leiomyosarcoma networks modeled on data from The Cancer Genome Atlas and validated our results in an independent dataset from the German Cancer Research Center. PORCUPINE identified 37 heterogeneously regulated pathways, including pathways representing potential targets for treatment of subgroups of leiomyosarcoma patients, such as FGFR and CTLA4 inhibitory signaling. We validated the detected regulatory heterogeneity through analysis of networks and chromatin states in leiomyosarcoma cell lines. We showed that the heterogeneity identified with PORCUPINE is not associated with methylation profiles or clinical features, thereby suggesting an independent mechanism of patient heterogeneity driven by the complex landscape of gene regulatory interactions.

Integrated multi-omics analysis reveals the molecular interplay between circadian clocks and cancer pathogenesis

Circadian rhythms (CRs) are fundamental biological processes that significantly impact human well-being. Disruption of these rhythms can trigger insufficient neurocognitive development, insomnia, mental disorders, cardiovascular diseases, metabolic dysfunctions, and cancer. The field of chronobiology has increased our understanding of how rhythm disturbances contribute to cancer pathogenesis, and how circadian timing influences the efficacy of cancer treatments. As the circadian clock steadily gains recognition as an emerging factor in tumorigenesis, a thorough and comprehensive multi-omics analysis of CR genes/proteins has never been performed. To shed light on this, we performed, for the first time, an integrated data analysis encompassing genomic/transcriptomic alterations across 32 cancer types (n = 10,918 tumors) taken from the PanCancer Atlas, unfavorable prognostic protein analysis, protein-protein interactomics, and shortest distance score pathways to cancer hallmark phenotypes. This data mining strategy allowed us to unravel 31 essential CR-related proteins involved in the signaling crossroad between circadian rhythms and cancer. In the context of drugging the clock, we identified pharmacogenomic clinical annotations and drugs currently in late phase clinical trials that could be considered as potential cancer therapeutic strategies. These findings highlight the diverse roles of CR-related genes/proteins in the realm of cancer research and therapy.

A co-formulation of interferons alpha2b and gamma distinctively targets cell cycle in the glioblastoma-derived cell line U-87MG

BACKGROUND

HeberFERON is a co-formulation of α2b and γ interferons, based on their synergism, which has shown its clinical superiority over individual interferons in basal cell carcinomas. In glioblastoma (GBM), HeberFERON has displayed promising preclinical and clinical results. This led us to design a microarray experiment aimed at identifying the molecular mechanisms involved in the distinctive effect of HeberFERON compared to the individual interferons in U-87MG model.

METHODS

Transcriptional expression profiling including a control (untreated) and three groups receiving α2b-interferon, γ-interferon and HeberFERON was performed using an Illumina HT-12 microarray platform. Unsupervised methods for gene and sample grouping, identification of differentially expressed genes, functional enrichment and network analysis computational biology methods were applied to identify distinctive transcription patterns of HeberFERON. Validation of most representative genes was performed by qPCR. For the cell cycle analysis of cells treated with HeberFERON for 24 h, 48 and 72 h we used flow cytometry.

RESULTS

The three treatments show different behavior based on the gene expression profiles. The enrichment analysis identified several mitotic cell cycle related events, in particular from prometaphase to anaphase, which are exclusively targeted by HeberFERON. The FOXM1 transcription factor network that is involved in several cell cycle phases and is highly expressed in GBMs, is significantly down regulated. Flow cytometry experiments corroborated the action of HeberFERON on the cell cycle in a dose and time dependent manner with a clear cellular arrest as of 24 h post-treatment. Despite the fact that p53 was not down-regulated, several genes involved in its regulatory activity were functionally enriched. Network analysis also revealed a strong relationship of p53 with genes targeted by HeberFERON. We propose a mechanistic model to explain this distinctive action, based on the simultaneous activation of PKR and ATF3, p53 phosphorylation changes, as well as its reduced MDM2 mediated ubiquitination and export from the nucleus to the cytoplasm. PLK1, AURKB, BIRC5 and CCNB1 genes, all regulated by FOXM1, also play central roles in this model. These and other interactions could explain a G2/M arrest and the effect of HeberFERON on the proliferation of U-87MG.

CONCLUSIONS

We proposed molecular mechanisms underlying the distinctive behavior of HeberFERON compared to the treatments with the individual interferons in U-87MG model, where cell cycle related events were highly relevant.

Proteomic Profile Distinguishes New Subpopulations of Breast Cancer Patients with Different Survival Outcomes

As a highly heterogeneous disease, breast cancer (BRCA) demonstrates a diverse molecular portrait. The well-established molecular classification (PAM50) relies on gene expression profiling. It insufficiently explains the observed clinical and histopathological diversity of BRCAs. This study aims to demographically and clinically characterize the six BRCA subpopulations (basal, HER2-enriched, and four luminal ones) revealed by their proteomic portraits. GMM-based high variate protein selection combined with PCA/UMAP was used for dimensionality reduction, while the k-means algorithm allowed patient clustering. The statistical analysis (log-rank and Gehan-Wilcoxon tests, hazard ratio HR as the effect size ES) showed significant differences across identified subpopulations in Disease-Specific Survival (p = 0.0160) and Progression-Free Interval (p = 0.0264). Luminal subpopulations vary in prognosis (Disease-Free Interval, p = 0.0277). The A2 subpopulation is of the poorest, comparable to the HER2-enriched subpopulation, prognoses (HR = 1.748, referenced to Luminal B, small ES), while A3 is of the best (HR = 0.250, large ES). Similar to PAM50 subtypes, no substantial dependency on demographic and clinical factors was detected across Luminal subpopulations, as measured by χ2 test and Cramér's V for ES, and ANOVA with appropriate post hocs combined with η2 or Cohen's d-type ES, respectively. Progesterone receptors can serve as the potential A2 biomarker within Luminal patients. Further investigation of molecular differences is required to examine the potential prognostic or clinical applications.