Biomedical subjects

Xin Hu

Publications and source records attributed to Xin Hu.

6 recordsLinked to original sources

PubMed2026

Integrated analysis reveals the impact of obesity on triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is a highly aggressive and heterogeneous breast cancer subtype with limited therapeutic options. While the prevalence of overweight/obese (OW/OB) women continues to rise, the impact of obesity on molecular features of TNBC remains incompletely understood. We investigated clinicopathological and molecular data (including genomic, transcriptomic, proteomic and metabolomic profiling) using our original multi-omics database of TNBC (N = 465) for associations with patient body mass index (BMI). Multi-omics profiling revealed that OW/OB patients exhibited worse survival as well as elevated inflammation of tumor microenvironment, higher expression of immune checkpoints, and dysregulated lipid metabolism. Our in vivo experiments demonstrated that tumors in obese mice displayed faster growth rates, a higher proportion of PD-1+CD8+ T cells and enhanced responsiveness to anti-PD-1 treatment. In addition, we analyzed data from four independent clinical trials and discovered that OW/OB patients demonstrated higher pathological complete response rates and longer progression-free survival following anti-PD-1-based immunotherapy. In conclusion, our study systematically revealed that obesity is associated with coordinated immune-metabolic remodeling in TNBC, characterized by checkpoint enrichment and lipid dysregulation, which may help explain the enhanced anti-PD-1 responsiveness and should be taken into account in the field of precision medicine.

Immunity↗

PubMed2026

Establishment of an efficient Agrobacterium-mediated genetic transformation protocol for Saccharum officinarum using Black Cheribon as a model genotype.

Efficient Agrobacterium-mediated transformation (AMT) is vital for the biotechnological improvement of sugarcane (Saccharum spp.). Saccharum officinarum is the main ancestor of all modern cultivars, yet little research has been conducted on its AMT system. In this work, an efficient AMT protocol for S. officinarum was developed, with Black Cheribon as the model genotype owing to its superior tissue culture performance and regeneration capacity. The optimized agro-infection protocol comprised the following main parameters: concentration of acetosyringone (AS) in Agrobacterium culture, concentration of AS for infection, Agrobacterium concentration at OD600 = 0.4, infection time of 30 minutes, vacuum infiltration time of 10 minutes and co-cultivation time of 3 days. To further improve transformation efficiency, 0.5 mg/L thidiazuron and 200 mg/L citric acid were added to the regeneration medium, which enhanced the regeneration of shoots. A modified stage-dependent selection strategy (FlexII) was established by using glufosinate-ammonium at concentrations of 2.0, 1.0, and 0.75 mg/L in the callus proliferation, shoot regeneration, and rooting stages, respectively. This strategy was more successful than the minimum inhibitory concentration-based strategy in S. officinarum transformation. The optimized protocol further boosted the transformation efficiency of Black Cheribon from 1.12% to 7.17%. The resulting transgenic lines were confirmed by PCR amplification of T-DNA regions and immunochromatographic detection of Bar protein expression in primary transformants, respectively. These results provide a sound technical foundation for the functional genomics and biotechnological optimization of S. officinarum germplasm, and may serve as a reference for future transformation studies in other sugarcane germplasm.

Agrobacterium↗

PubMed2026

Plasma signals of lung tumor promotion for molecular cancer prevention.

Predicting lung cancer risk would enhance prevention trials. Although the Canakinumab Anti-inflammatory Thrombosis Outcome Study (CANTOS) trial demonstrated reduced lung cancer incidence with interleukin (IL)-1β inhibition, the high number needed to treat (NNT) to prevent lung cancer limits its use in unselected populations. Using machine learning, we identified a 14-protein plasma signature predicting lung cancer more than 5 years before diagnosis. The signature, validated across eight cohorts, was elevated in current smokers and individuals exposed to particulate matter (PM) and linked to lung myeloid and alveolar cells. In epidermal growth factor receptor (EGFR)-driven lung adenocarcinoma, diverse epithelial lineages converged on a keratin8+/claudin4+ alveolar transitional state (KAC), whose transcriptional programs correlated with signature emergence. Components of the signature were induced by PM, oncogenic EGFR, or IL-1β, whereas IL-1β inhibition restrained PM-driven KAC expansion and early tumorigenesis. In CANTOS, the signature identified individuals who seemed to benefit more from anti-IL-1β therapy, lowering the NNT threshold and nominating circulating signals of tumor promotion for prevention.

Humans↗

PubMed2026

Age-related genomic characterization and therapeutic targets in Chinese breast cancer: insights from prospective targeted sequencing and clinical data analysis.

BACKGROUND: In China, breast cancer occurs at a much younger age and has a higher recurrence and mortality rate. However, with changes in lifestyle, there has been a trend towards an older age of breast cancer incidence in Chinese women. There is a paucity of large-scale next-generation sequencing cohorts for the analysis of genomic characterization in these populations and the identification of potential therapeutic targets. METHODS: To address this gap, we performed prospective targeted sequencing of tumor and blood samples from Chinese patients and collected detailed clinical information. We then categorized patients into two groups based on age (< 40 years, n = 637; ≥ 40 years, n = 3442) and proceeded to provide comprehensive descriptions of somatic and germline mutations in both groups. RESULTS: The somatic mutation analysis revealed that PIK3CA, FOXA1, and TBX3 mutations were more prevalent in elderly patients. By leveraging the aforementioned mutational characteristics, we employed our institution's FUTURE-SUPER clinical trial, an umbrella study targeting metastatic breast cancer, to confirm the potential benefits of PI3K-AKT-mTOR pathway inhibitors among elderly patients with breast cancer. Furthermore, TP53 and ERBB2 were more likely to be co-mutated in young women. Patients with TP53 and ERBB2 co-mutation tend to have a poorer prognosis, but through investigation of the SPARK cohort, patients carrying the TP53 and ERBB2 co-mutation are more likely to benefit from immune checkpoint inhibitor combination with tyrosine kinase inhibitor therapy. In our study, we observed a higher frequency of mutations in the DNA homology-dependent recombination pathway in young patients with breast cancer, which was associated with an elevated Ki67 index. Additionally, we confirmed a significant prevalence of germline breast cancer susceptibility gene 1 (gBRCA1) mutations in young patients, whereas germline checkpoint kinase 2 (gCHEK2) mutations are more common in elderly patients. CONCLUSIONS: Our study, which makes use of the largest Chinese breast cancer sequencing cohort, sought to characterize the age-related genomic profile of breast cancer patients and identify novel therapeutic opportunities for individuals with breast cancer.

Adult↗

PubMed2025

Foundation model based multimodal transformer framework for survival analysis in HER2 stratified breast cancer.

Objective. To improve survival prediction for HER2-positive breast cancer by integrating histopathological, molecular, and clinical data using a multimodal transformer framework.Approach. We propose a multimodal transformer framework for breast cancer survival prediction using HER2 stratified (SurvMBC), a foundation model-enhanced architecture that fuses three data modalities: whole-slide images, clinical narratives, and molecular features. Tumor microenvironment features are extracted using a pathology language and image pre-training (PLIP), clinical narratives are processed with BioBERT, and miRNA expression plus DNA methylation data are embedded using Gen2Vec. These representations are integrated through a cross-modal transformer with attention mechanisms for survival prediction.Main results. The model was evaluated on 1,095 HER2-positive breast cancer patients from The Cancer Genome Atlas. SurvMBC achieved a concordance index (C-index) of 0.857 (95% CI: 0.834, 0.880), a low integrated Brier score, and a strong inverse negative binomial log-likelihood. Risk stratification based on model outputs significantly separated high- and low-risk groups (log-rankp< 0.01) and showed strong associations with tumor stage, grade, and hormone receptor status (allp< 0.05).Significance. SurvMBC demonstrates the effectiveness of multimodal fusion in addressing tumor heterogeneity and improving prognostic accuracy. The attention-based integration enables context-aware learning of survival-relevant features across modalities, supporting individualized risk stratification and risk-adaptive treatment planning for HER2 stratified breast cancer patients.

Breast Neoplasms↗

PubMed2024

DKK1-SE recruits AP1 to activate the target gene DKK1 thereby promoting pancreatic cancer progression.

Super-enhancers are a class of DNA cis-regulatory elements that can regulate cell identity, cell fate, stem cell pluripotency, and even tumorigenesis. Increasing evidence shows that epigenetic modifications play an important role in the pathogenesis of various types of cancer. However, the current research is far from enough to reveal the complex mechanism behind it. This study found a super-enhancer enriched with abnormally active histone modifications in pancreatic ductal adenocarcinoma (PDAC), called DKK1-super-enhancer (DKK1-SE). The major active component of DKK1-SE is component enhancer e1. Mechanistically, AP1 induces chromatin remodeling in component enhancer e1 and activates the transcriptional activity of DKK1. Moreover, DKK1 was closely related to the malignant clinical features of PDAC. Deletion or knockdown of DKK1-SE significantly inhibited the proliferation, colony formation, motility, migration, and invasion of PDAC cells in vitro, and these phenomena were partly mitigated upon rescuing DKK1 expression. In vivo, DKK1-SE deficiency not only inhibited tumor proliferation but also reduced the complexity of the tumor microenvironment. This study identifies that DKK1-SE drives DKK1 expression by recruiting AP1 transcription factors, exerting oncogenic effects in PDAC, and enhancing the complexity of the tumor microenvironment.

Humans↗