Blood molecular markers associated with COVID-19 immunopathology and multi-organ damage.

COVID-19 is characterized by dysregulated immune responses, metabolic dysfunction and adverse effects on the function of multiple organs. To understand host responses to COVID-19 pathophysiology, we combined transcriptomics, proteomics, and metabolomics to identify molecular markers in peripheral blood and plasma samples of 66 COVID-19-infected patients experiencing a range of disease severities and 17 healthy controls. A large number of expressed genes, proteins, metabolites, and extracellular RNAs (exRNAs) exhibit strong associations with various clinical parameters. Multiple sets of tissue-specific proteins and exRNAs varied significantly in both mild and severe patients suggesting a potential impact on tissue function. Chronic activation of neutrophils, IFN-I signaling, and a high level of inflammatory cytokines were observed in patients with severe disease progression. In contrast, COVID-19-infected patients experiencing milder disease symptoms showed robust T-cell responses. Finally, we identified genes, proteins, and exRNAs as potential biomarkers that might assist in predicting the prognosis of SARS-CoV-2 infection. These data refine our understanding of the pathophysiology and clinical progress of COVID-19.

Structure activity relationship and target prediction for ABX464 analogues in Caenorhabditis elegans.

Global challenges with treatment failures and/or widespread resistance in parasitic worms against commercially available anthelmintics lend impetus to the development of new anthelmintics with novel mechanism(s) of action. The free-living nematode Caenorhabditis elegans is an important model organism used for drug discovery, including the screening and structure-activity investigation of new compounds, and target deconvolution. Previously, we conducted a whole-organism phenotypic screen of the 'Pandemic Response Box' (from Medicines for Malaria Venture, MMV) and identified a hit compound, called ABX464, with activity against C. elegans and a related, parasitic nematode, Haemonchus contortus. Here, we tested a series of 44 synthesized analogues to explore the pharmacophore of activity on C. elegans and revealed five compounds whose potency was similar or greater than that of ABX464, but which were not toxic to human hepatoma (HepG2) cells. Subsequently, we employed thermal proteome profiling (TPP), protein structure prediction and an in silico-docking algorithm to predict ABX464-target candidates. Taken together, the findings from this study contribute significantly to the early-stage drug discovery of a new nematocide based on ABX464. Future work is aimed at validating the ABX464-protein interactions identified here, and at assessing ABX464 and associated analogues against a panel of parasitic nematodes, towards developing a new anthelmintic with a mechanism of action that is distinct from any of the compounds currently-available commercially.

Genome-Wide Analysis of Haemonchus contortus Proteases and Protease Inhibitors Using Advanced Informatics Provides Insights into Parasite Biology and Host-Parasite Interactions.

Biodiversity within the animal kingdom is associated with extensive molecular diversity. The expansion of genomic, transcriptomic and proteomic data sets for invertebrate groups and species with unique biological traits necessitates reliable in silico tools for the accurate identification and annotation of molecules and molecular groups. However, conventional tools are inadequate for lesser-known organismal groups, such as eukaryotic pathogens (parasites), so that improved approaches are urgently needed. Here, we established a combined sequence- and structure-based workflow system to harness well-curated publicly available data sets and resources to identify, classify and annotate proteases and protease inhibitors of a highly pathogenic parasitic roundworm (nematode) of global relevance, called Haemonchus contortus (barber's pole worm). This workflow performed markedly better than conventional, sequence-based classification and annotation alone and allowed the first genome-wide characterisation of protease and protease inhibitor genes and gene products in this worm. In total, we identified 790 genes encoding 860 proteases and protease inhibitors representing 83 gene families. The proteins inferred included 280 metallo-, 145 cysteine, 142 serine, 121 aspartic and 81 "mixed" proteases as well as 91 protease inhibitors, all of which had marked physicochemical diversity and inferred involvements in >400 biological processes or pathways. A detailed investigation revealed a remarkable expansion of some protease or inhibitor gene families, which are likely linked to parasitism (e.g., host-parasite interactions, immunomodulation and blood-feeding) and exhibit stage- or sex-specific transcription profiles. This investigation provides a solid foundation for detailed explorations of the structures and functions of proteases and protease inhibitors of H. contortus and related nematodes, and it could assist in the discovery of new drug or vaccine targets against infections or diseases.

Gut microbiome alterations and gut barrier dysfunction are associated with host immune homeostasis in COVID-19 patients.

BACKGROUND: COVID-19 is an infectious disease characterized by multiple respiratory and extrapulmonary manifestations, including gastrointestinal symptoms. Although recent studies have linked gut microbiota to infectious diseases such as influenza, little is known about the role of the gut microbiota in COVID-19 pathophysiology. METHODS: To better understand the host-gut microbiota interactions in COVID-19, we characterized the gut microbial community and gut barrier function using metagenomic and metaproteomic approaches in 63 COVID-19 patients and 8 non-infected controls. Both immunohematological parameters and transcriptional profiles were measured to reflect the immune response in COVID-19 patients. RESULTS: Altered gut microbial composition was observed in COVID-19 patients, which was characterized by decreased commensal species and increased opportunistic pathogenic species. Severe illness was associated with higher abundance of four microbial species (i.e., Burkholderia contaminans, Bacteroides nordii, Bifidobacterium longum, and Blautia sp. CAG 257), six microbial pathways (e.g., glycolysis and fermentation), and 10 virulence genes. These severity-related microbial features were further associated with host immune response. For example, the abundance of Bu. contaminans was associated with higher levels of inflammation biomarkers and lower levels of immune cells. Furthermore, human-origin proteins identified from both blood and fecal samples suggested gut barrier dysfunction in COVID-19 patients. The circulating levels of lipopolysaccharide-binding protein increased in patients with severe illness and were associated with circulating inflammation biomarkers and immune cells. Besides, proteins of disease-related bacteria (e.g., B. longum) were detectable in blood samples from patients. CONCLUSIONS: Our results suggest that the dysbiosis of the gut microbiome and the dysfunction of the gut barrier might play a role in the pathophysiology of COVID-19 by affecting host immune homeostasis.

PROST: AlphaFold2-aware Sequence-Based Predictor to Estimate Protein Stability Changes upon Missense Mutations.

An essential step in engineering proteins and understanding disease-causing missense mutations is to accurately model protein stability changes when such mutations occur. Here, we developed a new sequence-based predictor for the protein stability (PROST) change (Gibb's free energy change, ΔΔG) upon a single-point missense mutation. PROST extracts multiple descriptors from the most promising sequence-based predictors, such as BoostDDG, SAAFEC-SEQ, and DDGun. RPOST also extracts descriptors from iFeature and AlphaFold2. The extracted descriptors include sequence-based features, physicochemical properties, evolutionary information, evolutionary-based physicochemical properties, and predicted structural features. The PROST predictor is a weighted average ensemble model based on extreme gradient boosting (XGBoost) decision trees and an extra-trees regressor; PROST is trained on both direct and hypothetical reverse mutations using the S5294 (S2647 direct mutations + S2647 inverse mutations). The parameters for the PROST model are optimized using grid searching with 5-fold cross-validation, and feature importance analysis unveils the most relevant features. The performance of PROST is evaluated in a blinded manner, employing nine distinct data sets and existing state-of-the-art sequence-based and structure-based predictors. This method consistently performs well on frataxin, S217, S349, Ssym, S669, Myoglobin, and CAGI5 data sets in blind tests and similarly to the state-of-the-art predictors for p53 and S276 data sets. When the performance of PROST is compared with the latest predictors such as BoostDDG, SAAFEC-SEQ, ACDC-NN-seq, and DDGun, PROST dominates these predictors. A case study of mutation scanning of the frataxin protein for nine wild-type residues demonstrates the utility of PROST. Taken together, these findings indicate that PROST is a well-suited predictor when no protein structural information is available. The source code of PROST, data sets, examples, and pretrained models along with how to use PROST are available at https://github.com/ShahidIqb/PROST and https://prost.erc.monash.edu/seq.

Functional consequences of a rare missense BARD1 c.403G>A germline mutation identified in a triple-negative breast cancer patient.

We identified a rare missense germline mutation in BARD1 (c.403G>A or p.Asp135Asn) as pathogenic using integrated genomics and transcriptomics profiling of germline and tumor samples from an early-onset triple-negative breast cancer patient who later was administrated with a PARP inhibitor for 2 months. We demonstrated in cell and mouse models that, compared to the wild-type, (1) c.403G>A mutant cell lines were more sensitive to irradiation, a DNA damage agent, and a PARP inhibitor; (2) c.403G>A mutation inhibited interaction between BARD1 and RAD51 (but not BRCA1); and (3) c.403G>A mutant mice were hypersensitive to ionizing radiation. Our study shed lights on the clinical interpretation of rare germline mutations of BARD1.

PreMedKB: an integrated precision medicine knowledgebase for interpreting relationships between diseases, genes, variants and drugs.

One important aspect of precision medicine aims to deliver the right medicine to the right patient at the right dose at the right time based on the unique 'omics' features of each individual patient, thus maximizing drug efficacy and minimizing adverse drug reactions. However, fragmentation and heterogeneity of available data makes it challenging to readily obtain first-hand information regarding some particular diseases, drugs, genes and variants of interest. Therefore, we developed the Precision Medicine Knowledgebase (PreMedKB) by seamlessly integrating the four fundamental components of precision medicine: diseases, genes, variants and drugs. PreMedKB allows for search of comprehensive information within each of the four components, the relationships between any two or more components, and importantly, the interpretation of the clinical meanings of a patient's genetic variants. PreMedKB is an efficient and user-friendly tool to assist researchers, clinicians or patients in interpreting a patient's genetic profile in terms of discovering potential pathogenic variants, recommending therapeutic regimens, designing panels for genetic testing kits, and matching patients for clinical trials. PreMedKB is freely accessible and available at http://www.fudan-pgx.org/premedkb/index.html#/home.

Similarities and differences between variants called with human reference genome HG19 or HG38.

BACKGROUND: Reference genome selection is a prerequisite for successful analysis of next generation sequencing (NGS) data. Current practice employs one of the two most recent human reference genome versions: HG19 or HG38. To date, the impact of genome version on SNV identification has not been rigorously assessed. METHODS: We conducted analysis comparing the SNVs identified based on HG19 vs HG38, leveraging whole genome sequencing (WGS) data from the genome-in-a-bottle (GIAB) project. First, SNVs were called using 26 different bioinformatics pipelines with either HG19 or HG38. Next, two tools were used to convert the called SNVs between HG19 and HG38. Lastly we calculated conversion rates, analyzed discordant rates between SNVs called with HG19 or HG38, and characterized the discordant SNVs. RESULTS: The conversion rates from HG38 to HG19 (average 95%) were lower than the conversion rates from HG19 to HG38 (average 99%). The conversion rates varied slightly among the various calling pipelines. Around 1.5% SNVs were discordantly converted between HG19 or HG38. The conversions from HG38 to HG19 had more SNVs which failed conversion and more discordant SNVs than the opposite conversion (HG19 to HG38). Most of the discordant SNVs had low read depth, were low confidence SNVs as defined by GIAB, and/or were predominated by G/C alleles (52% observed versus 42% expected). CONCLUSION: A significant number of SNVs could not be converted between HG19 and HG38. Based on careful review of our comparisons, we recommend HG38 (the newer version) for NGS SNV analysis. To summarize, our findings suggest caution when translating identified SNVs between different versions of the human reference genome.

Correction to: Similarities and differences between variants called with human reference genome HG19 or HG38.

After publication of this supplement article.

A genomic characterization of the influence of silver nanoparticles on bone differentiation in MC3T3-E1 cells.

Silver nanoparticles (AgNPs) have been widely used in a variety of biomedical applications. Previous studies demonstrated that AgNPs significantly enhanced bone cell mineralization and differentiation in MC3T3-1 cells, a model in vitro system, when compared to several other NPs. This increased bone deposition was evaluated by phenotypic measurements and assessment of the expression of miRNAs associated with regulation of bone morphogenic proteins. In the present study, we used RNA-seq technology, a more direct measurement of gene expression, to investigate further the mechanisms of bone differentiation induced by AgNP treatment. Key factors associated with the osteoclast pathway were significantly increased in response to AgNP exposure including Bmp4, Bmp6 and Fosl1. In addition, genes of metabolism and toxicity pathways were significantly regulated as well. Although this study suggests the potential for AgNPs to influence bone morphogenesis in injury or disease applications, further investigation into the efficacy and safety of AgNPs in bone regeneration is warranted.

Application of a New Dynamic Model to Predict the In Vitro Intrinsic Clearance of Tolbutamide Using Rat Microsomes Encapsulated in a Fab Hydrogel.

Currently used in vitro models for estimating liver metabolism do not take into account the physiologic structure and blood circulation process of liver tissue. The Bio-PK metabolic system was established as an alternative approach to determine the in vitro intrinsic clearance of the model drug tolbutamide. The system contained a peristaltic pump, recirculating pipeline, reaction chamber, and rat liver microsomes (RLMs) encapsulated in pluronic F127-acrylamide-bisacrylamide (FAB) hydrogel. The metabolism of tolbutamide at initial concentrations of 100, 150, and 200 µM was measured in both the FAB hydrogel and the circular medium. The data from the FAB hydrogel and the circular medium were fitted to a mathematical model to obtain the predicted intrinsic clearance of tolbutamide after different periods of preincubation. The in vitro clearance value for tolbutamide was incorporated into Simcyp software and used to predict both the in vivo clearance value and the dynamic process of elimination. The predicted in vivo clearance of tolbutamide was 0.107, 0.087, and 0.095 L/h/kg for i.v. injection and 0.113, 0.095, and 0.107 L/h/kg for oral administration. Compared with the reported in vivo clearance of 0.09 L/h/kg (i.v.) and 0.10 L/h/kg (oral), all the predicted values differed by less than twofold. Thus, the Bio-PK metabolic system is a reliable and general in vitro model, characterized by three-dimensional structured RLM and circulation and perfusion processes for predicting the in vivo intrinsic clearance of low-extraction compounds, making the system more analogous with the rat in terms of both morphology and physiology.

Amiloride sensitizes human pancreatic cancer cells to erlotinib in vitro through inhibition of the PI3K/AKT signaling pathway.

AIM: Blockade of EGFR by EGFR tyrosine kinase inhibitors such as erlotinib is insufficient for effective treatment of human pancreatic cancer due to independent activation of the Akt pathway, while amiloride, a potassium-sparing diuretic, has been found as a potential Akt inhibitor. The aim of this study was to investigate the anticancer effects of combined amiloride with erlotinib against human pancreatic cancer cells in vitro. METHODS: Cell proliferation, colony formation, cell cycle and apoptosis were analyzed in 4 human pancreatic cancer cell lines Bxpc-3, PANC-1, Aspc-1 and CFPAC-1 treated with erlotinib or amiloride alone, or in their combination. The synergistic analysis for the effects of combinations of amiloride and erlotinib was performed using Chou-Talalay's combination index isobolographic method. RESULTS: Amiloride (10, 30, and 100 µmol/L) concentration-dependently potentiated erlotinib-induced inhibition of cell proliferation and colony formation in the 4 pancreatic cancer cell lines. Isobolographic analysis confirmed that combinations of amiloride and erlotinib produced synergistic cytotoxic effects. Amiloride significantly potentiated erlotinib-induced G0/G1 cell-cycle arrest and apoptosis in Bxpc-3 and PANC-1 cells. Amiloride inhibited EGF-stimulated phorsphorylation of AKT, and significantly enhanced erlotinib-induced downregulation of phorsphorylation of EGFR, AKT, PI3K P85 and GSK 3ß in Bxpc-3 and PANC-1 cells. CONCLUSION: Amiloride sensitizes human pancreatic cancer cells to erlotinib in vitro through inhibition of the PI3K/AKT signaling pathway. Treatment of pancreatic cancer patients with combination of erlotinib and amiloride merits further investigation.

Physicochemical characteristics and gastrointestinal absorption behaviors of S-propargyl-cysteine, a potential new drug candidate for cardiovascular protection and antitumor treatment.

1. As a potential new drug candidate for cardiovascular protection and antitumor treatment, the physicochemical properties, gastrointestinal (GI) absorption behaviors and mechanisms of S-propargyl-cysteine (SPRC) were investigated in this study. 2. SPRC exhibited favorable solubility in aqueous media. The log P and log D values were low (≤1.93 ± 0.08). The pKa in the acidic and basic regions was 2.08 ± 0.02 and 8.72 ± 0.03, respectively. The isoelectric point was 5.40 ± 0.02. SPRC was stable in the rat GI fluids, and showed no obvious adsorption and metabolism in the rat GI tract. 3. SPRC displayed poor gastric absorption and favorable intestinal absorption in the rat in situ GI perfusion model. Absorption rate constants (ka), hourly absorption percentage (P) and apparent permeability coefficient (Papp) of SPRC in the small intestine were ≥0.77 ± 0.06 h(-1), 59.25 ± 4.02% and (7.99 ± 0.88) × 10(-5 )cm/s, respectively. Absorption of SPRC exhibited a certain dependence on physiological pH and absorption region. Absorption of SPRC was not inhibited by l-methionine and 2-aminobicyclo-(2,2,1)-heptane-2-carboxylic acid. 4. SPRC showed favorable oral absorption. It can be categorized as a BCS class I drug. The membrane pore transport appeared to be one of the predominant absorption modes for SPRC.

Characterization of metabolites of leonurine (SCM-198) in rats after oral administration by liquid chromatography/tandem mass spectrometry and NMR spectrometry.

Leonurine, a major bioactive component from Herba Leonuri, shows therapeutic potential for cardiovascular disease and stroke prevention in some preclinical experiments. The aim of this study is to characterize metabolites of leonurine in rats using high performance liquid chromatography coupled with tandem mass spectrometry (HPLC/MS/MS). The chromatographic separation was performed on an Agilent ZORBAX SB-C18 column using a gradient elution with acetonitrile/ammonium acetate buffer (10 mM, pH 4.0) solvent system. An information dependent acquisition (IDA) method was developed for screening and identifying metabolites of leonurine under positive ion mode. Compared with control, the interesting compound in the extracted ion chromatogram (XIC) of the in vivo samples was chosen and further identified by analyzing their retention times, changes in observed mass (Δm/z), and spectral patterns of product ion utilizing advanced software tool. For the first time, a total of three metabolites were identified, including two phase II metabolites generated by glucuronidation (M1) and sulfation (M2) and one phase I metabolite formed by O-demethylation (M3). Finally, the lead metabolite M1 was isolated from urine and its structure was characterized as leonurine-10-O- ß-D-glucuronide by NMR spectroscopy (¹H, ¹³C, HMBC, and HSQC).

Plasma-Free Blood as a Potential Alternative to Whole Blood for Transcriptomic Analysis.

RNA sequencing (RNAseq) technology has become increasingly important in precision medicine and clinical diagnostics, and emerged as a powerful tool for identifying protein-coding genes, performing differential gene analysis, and inferring immune cell composition. Human peripheral blood samples are widely used for RNAseq, providing valuable insights into individual biomolecular information. Blood samples can be classified as whole blood (WB), plasma, serum, and remaining sediment samples, including plasma-free blood (PFB) and serum-free blood (SFB) samples that are generally considered less useful byproducts during the processes of plasma and serum separation, respectively. However, the feasibility of using PFB and SFB samples for transcriptome analysis remains unclear. In this study, we aimed to assess the suitability of employing PFB or SFB samples as an alternative RNA source in transcriptomic analysis. We performed a comparative analysis of WB, PFB, and SFB samples for different applications. Our results revealed that PFB samples exhibit greater similarity to WB samples than SFB samples in terms of protein-coding gene expression patterns, detection of differentially expressed genes, and immunological characterizations, suggesting that PFB can serve as a viable alternative to WB for transcriptomic analysis. Our study contributes to the optimization of blood sample utilization and the advancement of precision medicine research. Supplementary Information: The online version contains supplementary material available at 10.1007/s43657-023-00121-1.

Quartet metabolite reference materials for inter-laboratory proficiency test and data integration of metabolomics profiling.

BACKGROUND: Various laboratory-developed metabolomic methods lead to big challenges in inter-laboratory comparability and effective integration of diverse datasets. RESULTS: As part of the Quartet Project, we establish a publicly available suite of four metabolite reference materials derived from B lymphoblastoid cell lines from a family of parents and monozygotic twin daughters. We generate comprehensive LC-MS-based metabolomic data from the Quartet reference materials using targeted and untargeted strategies in different laboratories. The Quartet multi-sample-based signal-to-noise ratio enables objective assessment of the reliability of intra-batch and cross-batch metabolomics profiling in detecting intrinsic biological differences among the four groups of samples. Significant variations in the reliability of the metabolomics profiling are identified across laboratories. Importantly, ratio-based metabolomics profiling, by scaling the absolute values of a study sample relative to those of a common reference sample, enables cross-laboratory quantitative data integration. Thus, we construct the ratio-based high-confidence reference datasets between two reference samples, providing "ground truth" for inter-laboratory accuracy assessment, which enables objective evaluation of quantitative metabolomics profiling using various instruments and protocols. CONCLUSIONS: Our study provides the community with rich resources and best practices for inter-laboratory proficiency tests and data integration, ensuring reliability of large-scale and longitudinal metabolomic studies.

High Intensity Focused Ultrasound-Driven Nanomotor for Effective Ferroptosis-Immunotherapy of TNBC.

The heterogeneity of triple-negative breast cancers (TNBC) remains challenging for various treatments. Ferroptosis, a recently identified form of cell death resulting from the unrestrained peroxidation of phospholipids, represents a potential vulnerability in TNBC. In this study, a high intensity focused ultrasound (HIFU)-driven nanomotor is developed for effective therapy of TNBC through induction of ferroptosis. Through bioinformatics analysis of typical ferroptosis-associated genes in the FUSCCTNBC dataset, gambogic acid is identified as a promising ferroptosis drug and loaded it into the nanomotor. It is found that the rapid motion of nanomotors propelled by HIFU significantly enhanced tumor accumulation and penetration. More importantly, HIFU not only actuated nanomotors to trigger effective ferroptosis of TNBC cells, but also drove nanomotors to activate ferroptosis-mediated antitumor immunity in primary and metastatic TNBC models, resulting in effective tumor regression and prevention of metastases. Overall, HIFU-driven nanomotors show great potential for ferroptosis-immunotherapy of TNBC.

Analysis of blood methylation quantitative trait loci in East Asians reveals ancestry-specific impacts on complex traits.

Methylation quantitative trait loci (mQTLs) are essential for understanding the role of DNA methylation changes in genetic predisposition, yet they have not been fully characterized in East Asians (EAs). Here we identified mQTLs in whole blood from 3,523 Chinese individuals and replicated them in additional 1,858 Chinese individuals from two cohorts. Over 9% of mQTLs displayed specificity to EAs, facilitating the fine-mapping of EA-specific genetic associations, as shown for variants associated with height. Trans-mQTL hotspots revealed biological pathways contributing to EA-specific genetic associations, including an ERG-mediated 233 trans-mCpG network, implicated in hematopoietic cell differentiation, which likely reflects binding efficiency modulation of the ERG protein complex. More than 90% of mQTLs were shared between different blood cell lineages, with a smaller fraction of lineage-specific mQTLs displaying preferential hypomethylation in the respective lineages. Our study provides new insights into the mQTL landscape across genetic ancestries and their downstream effects on cellular processes and diseases/traits.

Structure-activity relationship and target investigation of 2-aryl quinolines with nematocidal activity.

Within the context of our anthelmintic discovery program, we recently identified and evaluated a quinoline derivative, called ABX464 or obefazimod, as a nematocidal candidate; synthesised a series of analogues which were assessed for activity against the free-living nematode Caenorhabditis elegans; and predicted compound-target relationships by thermal proteome profiling (TPP) and in silico docking. Here, we logically extended this work and critically evaluated the anthelmintic activity of ABX464 analogues on Haemonchus contortus (barber's pole worm) - a highly pathogenic nematode of ruminant livestock. First, we tested a series of 44 analogues on H. contortus (larvae and adults) to investigate the nematocidal pharmacophore of ABX464, and identified one compound with greater potency than the parent compound and showed moderate activity against a select number of other parasitic nematodes (including Ancylostoma, Heligmosomoides and Strongyloides species). Using TPP and in silico modelling studies, we predicted protein HCON_00074590 (a predicted aldo-keto reductase) as a target candidate for ABX464 in H. contortus. Future work aims to optimise this compound as a nematocidal candidate and investigate its pharmacokinetic properties. Overall, this study presents a first step toward the development of a new nematocide.

Integrated multiomic profiling of breast cancer in the Chinese population reveals patient stratification and therapeutic vulnerabilities.

Molecular profiling guides precision treatment of breast cancer; however, Asian patients are underrepresented in publicly available large-scale studies. We established a comprehensive multiomics cohort of 773 Chinese patients with breast cancer and systematically analyzed their genomic, transcriptomic, proteomic, metabolomic, radiomic and digital pathology characteristics. Here we show that compared to breast cancers in white individuals, Asian individuals had more targetable AKT1 mutations. Integrated analysis revealed a higher proportion of HER2-enriched subtype and correspondingly more frequent ERBB2 amplification and higher HER2 protein abundance in the Chinese HR+HER2+ cohort, stressing anti-HER2 therapy for these individuals. Furthermore, comprehensive metabolomic and proteomic analyses revealed ferroptosis as a potential therapeutic target for basal-like tumors. The integration of clinical, transcriptomic, metabolomic, radiomic and pathological features allowed for efficient stratification of patients into groups with varying recurrence risks. Our study provides a public resource and new insights into the biology and ancestry specificity of breast cancer in the Asian population, offering potential for further precision treatment approaches.