Development and Validation of a Comprehensive Prognostic and Depression Risk Index for Gastric Adenocarcinoma.

Depressive disorder contributes to the initiation and prognosis of patients with cancer, but the interaction between cancer and depressive disorder remains unclear. We generated a gastric adenocarcinoma patient-derived xenograft mice model, treated with chronic unpredictable mild stimulation. Based on the RNA-sequence from the mouse model, patient data from TCGA, and MDD-related (major depressive disorder) genes from the GEO database, 56 hub genes were identified by the intersection of differential expression genes from the three datasets. Molecular subtypes and a prognostic signature were generated based on the 56 genes. A depressive mouse model was constructed to test the key changes in the signatures. The signature was constructed based on the NDUFA4L2, ANKRD45, and AQP3 genes. Patients with high risk-score had a worse overall survival than the patients with low scores, consistent with the results from the two GEO cohorts. The comprehensive results showed that a higher risk-score was correlated with higher levels of tumor immune exclusion, higher infiltration of M0 macrophages, M2 macrophages, and neutrophils, higher angiogenetic activities, and more enriched epithelial-mesenchymal transition signaling pathways. A higher risk score was correlated to a higher MDD score, elevated MDD-related cytokines, and the dysfunction of neurogenesis-related genes, and parts of these changes showed similar trends in the animal model. With the Genomics of Drug Sensitivity in Cancer database, we found that the gastric adenocarcinoma patients with high risk-score may be sensitive to Pazopanib, XMD8.85, Midostaurin, HG.6.64.1, Elesclomol, Linifanib, AP.24534, Roscovitine, Cytarabine, and Axitinib. The gene signature consisting of the NDUFA4L2, ANKRD45, and AQP3 genes is a promising biomarker to distinguish the prognosis, the molecular and immune characteristics, the depressive risk, and the therapy candidates for gastric adenocarcinoma patients.

Genetic architectures of the human hippocampus and those involved in neuropsychiatric traits.

BACKGROUND: The hippocampus, with its complex subfields, is linked to numerous neuropsychiatric traits. While most research has focused on its global structure or a few specific subfields, a comprehensive analysis of hippocampal substructures and their genetic correlations across a wide range of neuropsychiatric traits remains underexplored. Given the hippocampus's high heritability, considering hippocampal and subfield volumes (HASV) as endophenotypes for neuropsychiatric conditions is essential. METHODS: We analyzed MRI-derived volumetric data of hippocampal and subfield structures from 41,525 UK Biobank participants. Genome-wide association studies (GWAS) on 24 HASV traits were conducted, followed by genetic correlation, overlap, and Mendelian randomization (MR) analyses with 10 common neuropsychiatric traits. Polygenic risk scores (PRS) based on HASV traits were also evaluated for predicting these traits. RESULTS: Our analysis identified 352 independent genetic variants surpassing a significance threshold of 2.1 × 10-9 within the 24 HASV traits, located across 93 chromosomal regions. Notably, the regions 12q14.3, 17q21.31, 12q24.22, 6q21, 9q33.1, 6q25.1, and 2q24.2 were found to influence multiple HASVs. Gene set analysis revealed enrichment of neural differentiation and signaling pathways, as well as protein binding and degradation. Of 240 HASV-neuropsychiatric trait pairs, 75 demonstrated significant genetic correlations (P < 0.05/240), revealing 433 pleiotropic loci. Particularly, genes like ACBD4, ARHGAP27, KANSL1, MAPT, ARL17A, and ARL17B were involved in over 50 HASV-neuropsychiatric pairs. Leveraging Mendelian randomization analysis, we further confirmed that atrophy in the left hippocampus, right hippocampus, right hippocampal body, and right CA1-3 region were associated with an increased risk of developing Parkinson's disease (PD). Furthermore, PRS for all four HASVs were significantly linked to a higher risk of Parkinson's disease (PD), with the highest hazard ratio (HR) of 1.30 (95% CI 1.18-1.43, P = 6.15 × 10⁻8) for right hippocampal volume. CONCLUSIONS: These findings highlight the extensive distribution of pleiotropic genetic determinants between HASVs and neuropsychiatric traits. Moreover, they suggest a significant potential for effectively managing and intervening in these diseases during their early stages.

A depression-related lncRNA signature predicts the clinical outcome and immune characteristics of gastric cancer.

Background: Depression and long non-coding RNA (lncRNA) have been reported to be associated with tumor progression and prognosis in gastric cancer (GC). This study aims to build a GC risk classification and prognosis model based on depression-related lncRNAs (DRLs). Methods: To develop a risk model, we performed univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses using RNA sequencing data of GC from The Cancer Genome Atlas (TCGA) and depression-related genes (DRGs) from previous studies. Kaplan-Meier analysis, receiver operating characteristic (ROC) curve analysis, nomogram construction, pathway enrichment analysis, assessment of immunological features, and drug sensitivity testing were conducted using a series of bioinformatics methods. Results: Seven DRLs were identified to build a prognostic model, whose robustness was verified in an internal cohort. Subsequent prognostic analyses found that high risk scores were associated with worse overall survival (OS). Univariate and multivariate analyses revealed that the risk score could be used as an independent prognostic factor. Furthermore, the ROC curve indicated that the risk score had higher diagnostic efficiency than traditional clinicopathological features. The calibration curve confirmed the accuracy and reliability of the nomogram. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that there were differences in digestive system and nervous system-related pathways between the high- and low-risk groups. Results of tumor mutational burden (TMB) and tumor immune dysfunction and exclusion (TIDE) analyses indicated that patients in the low-risk group had a better response rate to immunotherapy. Finally, the results of drug sensitivity analysis showed that risk score could influence sensitivity to EHT 1864 in GC. Conclusion: We have successfully developed and verified a 7-DRL risk model which can assess the prognosis and immunological features and guide individualized therapy of GC patients.

Anti-tumor therapy through high ROS performance induced by Ag nanoenzyme from boron cluster with halloysite clay nanotubes.

The conventional silver nanoparticles (Ag NPs) are characterized with high loading rate and stacking phenomenon, leading to shedding caused biotoxicity and low catalytic efficiency. This seriously hinders their application in biomedicine. Here, we modified the highly dispersible Ag NPs and Ag single-atoms (SAs) synthesis by combining the halloysite clay nanotubes (HNTs) and dodecahydro-dodecaborate (closo-[B12H12]2-) to increase the biocompatible properties and decrease the loading rate. This novel Ag single-atom nanoenzyme alongside Ag NPs nanoenzyme avoid the elevated-temperature calcination while maintaining the exceptionally high-level efficiency of Ag utilization via the reducibility and coordination stabilization of closo-[B12H12]2- and HNTs. With theoretical calculation and electron paramagnetic resonance, we confirmed that both Ag SAzymes and Ag NPs in HNT@B12H12@Ag nanoenzyme are capable decompose the H2O2 into hydroxyl radical (·OH). For the application, we investigated the catalytic activity in the tumor cells and antitumor effects of HNT@B12H12@Ag nanoenzyme both in vitro and in vivo, and confirmed that it effectively suppressed melanoma growth through ·OH generation, with limited biotoxicity. This study provides a novel Ag nanoenzyme synthesis approach to increase the possibility of its clinical application.

CA IX-targeted Ag2S quantum dots bioprobe for NIR-II imaging-guided hypoxia tumor chemo-photothermal therapy.

Hypoxia is the common characteristic of almost all solid tumors, which prevents therapeutic drugs from reaching the tumors. Therefore, the development of new targeted agents for the accurate diagnosis of hypoxia tumors is widely concerned. As carbonic anhydrase IX (CA IX) is abundantly distributed on the hypoxia tumor cells, it is considered as a potential tumor biomarker. 4-(2-Aminoethyl)benzenesulfonamide (ABS) as a CA IX inhibitor has inherent inhibitory activity and good targeting effect. In this study, Ag2S quantum dots (QDs) were used as the carrier to prepare a novel diagnostic and therapeutic bioprobe (Ag2S@polyethylene glycol (PEG)-ABS) through ligand exchange and amide condensation reaction. Ag2S@PEG-ABS can selectively target tumors by surface-modified ABS and achieve accurate tumor imaging by the near infrared-II (NIR-II) fluorescence characteristics of Ag2S QDs. PEG modification of Ag2S QDs greatly improves its water solubility and stability, and therefore achieves high photothermal stability and high photothermal conversion efficiency (PCE) of 45.17%. Under laser irradiation, Ag2S@PEG-ABS has powerful photothermal and inherent antitumor combinations on colon cancer cells (CT-26) in vitro. It also has been proved that Ag2S@PEG-ABS can realize the effective treatment of hypoxia tumors in vivo and show good biocompatibility. Therefore, it is a new efficient integrated platform for the diagnosis and treatment of hypoxia tumors.

Antitumor Therapy through Photothermal Performance Synergized with Catalytic Activity Based on the Boron Cluster Supramolecular Frameworks.

Chemodynamic therapy (CDT) has received widespread attention as a tumor optical treatment strategy in the field of malignant tumor therapy. Nonmetallic multifunctional nanomaterials as CDT agents, due to their low toxicity, long-lasting effects, and safety characteristics, have promising applications in the integrated diagnosis and treatment of cancer. Here, we modified the supramolecular framework of boron clusters, coupled with a variety of dyes to develop a series of metal-free agent compounds, and demonstrated that these nonmetallic compounds have excellent CDT activities through experiments. Subsequently, the best performing Methylene Blue/[closo-B12H12]2- (MB@B12H12) was used as an example. Through theoretical calculations, electron paramagnetic resonance spectroscopy, and 808 nm light irradiation, we confirmed that MB@B12H12 exhibited photothermal performance and CDT activity further. More importantly, we applied MB@B12H12 to melanoma cells and subcutaneous tumor, demonstrating its effective suppression of melanoma growth in vitro and in vivo through the synergistic effects of photothermal performance and CDT activity. This study emphasizes the generalizability of the coupling of dyes to [closo-B12H12]2- with important clinical translational potential for CDT reagents. Among them, MB@B12H12 may have a brighter future, paving the way for the rapid development of metal-free CDT reagents.

Developing an optimal stratification model for colorectal cancer screening and reducing racial disparities in multi-center population-based studies.

BACKGROUND: Early detection of colorectal neoplasms can reduce the colorectal cancer (CRC) burden by timely intervention for high-risk individuals. However, effective risk prediction models are lacking for personalized CRC early screening in East Asian (EAS) population. We aimed to develop, validate, and optimize a comprehensive risk prediction model across all stages of the dynamic adenoma-carcinoma sequence in EAS population. METHODS: To develop precision risk-stratification and intervention strategies, we developed three trans-ancestry PRSs targeting colorectal neoplasms: (1) using 148 previously identified CRC risk loci (PRS148); (2) SNPs selection from large-scale meta-analysis data by clumping and thresholding (PRS183); (3) PRS-CSx, a Bayesian approach for genome-wide risk prediction (PRSGenomewide). Then, the performance of each PRS was assessed and validated in two independent cross-sectional screening sets, including 4600 patients with advanced colorectal neoplasm, 4495 patients with non-advanced adenoma, and 21,199 normal individuals from the ZJCRC (Zhejiang colorectal cancer set; EAS) and PLCO (the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial; European, EUR) studies. The optimal PRS was further incorporated with lifestyle factors to stratify individual risk and ultimately tested in the PLCO and UK Biobank prospective cohorts, totaling 350,013 participants. RESULTS: Three trans-ancestry PRSs achieved moderately improved predictive performance in EAS compared to EUR populations. Remarkably, the PRSs effectively facilitated a thorough risk assessment across all stages of the dynamic adenoma-carcinoma sequence. Among these models, PRS183 demonstrated the optimal discriminatory ability in both EAS and EUR validation datasets, particularly for individuals at risk of colorectal neoplasms. Using two large-scale and independent prospective cohorts, we further confirmed a significant dose-response effect of PRS183 on incident colorectal neoplasms. Incorporating PRS183 with lifestyle factors into a comprehensive strategy improves risk stratification and discriminatory accuracy compared to using PRS or lifestyle factors separately. This comprehensive risk-stratified model shows potential in addressing missed diagnoses in screening tests (best NPV = 0.93), while moderately reducing unnecessary screening (best PPV = 0.32). CONCLUSIONS: Our comprehensive risk-stratified model in population-based CRC screening trials represents a promising advancement in personalized risk assessment, facilitating tailored CRC screening in the EAS population. This approach enhances the transferability of PRSs across ancestries and thereby helps address health disparity.

CoHIT: a one-pot ultrasensitive ERA-CRISPR system for detecting multiple same-site indels.

Genetic testing is crucial for precision cancer medicine. However, detecting multiple same-site insertions or deletions (indels) is challenging. Here, we introduce CoHIT (Cas12a-based One-for-all High-speed Isothermal Test), a one-pot CRISPR-based assay for indel detection. Leveraging an engineered AsCas12a protein variant with high mismatch tolerance and broad PAM scope, CoHIT can use a single crRNA to detect multiple NPM1 gene c.863_864 4-bp insertions in acute myeloid leukemia (AML). After optimizing multiple parameters, CoHIT achieves a detection limit of 0.01% and rapid results within 30 minutes, without wild-type cross-reactivity. It successfully identifies NPM1 mutations in 30 out of 108 AML patients and demonstrates potential in monitoring minimal residual disease (MRD) through continuous sample analysis from three patients. The CoHIT method is also competent for detecting indels of KIT, BRAF, and EGFR genes. Integration with lateral flow test strips and microfluidic chips highlights CoHIT's adaptability and multiplexing capability, promising significant advancements in clinical cancer diagnostics.

Genome-wide enhancer RNA profiling adds molecular links between genetic variation and human cancers.

BACKGROUND: Dysregulation of enhancer transcription occurs in multiple cancers. Enhancer RNAs (eRNAs) are transcribed products from enhancers that play critical roles in transcriptional control. Characterizing the genetic basis of eRNA expression may elucidate the molecular mechanisms underlying cancers. METHODS: Initially, a comprehensive analysis of eRNA quantitative trait loci (eRNAQTLs) was performed in The Cancer Genome Atlas (TCGA), and functional features were characterized using multi-omics data. To establish the first eRNAQTL profiles for colorectal cancer (CRC) in China, epigenomic data were used to define active enhancers, which were subsequently integrated with transcription and genotyping data from 154 paired CRC samples. Finally, large-scale case-control studies (34,585 cases and 69,544 controls) were conducted along with multipronged experiments to investigate the potential mechanisms by which candidate eRNAQTLs affect CRC risk. RESULTS: A total of 300,112 eRNAQTLs were identified across 30 different cancer types, which exert their influence on eRNA transcription by modulating chromatin status, binding affinity to transcription factors and RNA-binding proteins. These eRNAQTLs were found to be significantly enriched in cancer risk loci, explaining a substantial proportion of cancer heritability. Additionally, tumor-specific eRNAQTLs exhibited high responsiveness to the development of cancer. Moreover, the target genes of these eRNAs were associated with dysregulated signaling pathways and immune cell infiltration in cancer, highlighting their potential as therapeutic targets. Furthermore, multiple ethnic population studies have confirmed that an eRNAQTL rs3094296-T variant decreases the risk of CRC in populations from China (OR = 0.91, 95%CI 0.88-0.95, P = 2.92 × 10-7) and Europe (OR = 0.92, 95%CI 0.88-0.95, P = 4.61 × 10-6). Mechanistically, rs3094296 had an allele-specific effect on the transcription of the eRNA ENSR00000155786, which functioned as a transcriptional activator promoting the expression of its target gene SENP7. These two genes synergistically suppressed tumor cell proliferation. Our curated list of variants, genes, and drugs has been made available in CancereRNAQTL ( http://canernaqtl.whu.edu.cn/#/ ) to serve as an informative resource for advancing this field. CONCLUSION: Our findings underscore the significance of eRNAQTLs in transcriptional regulation and disease heritability, pinpointing the potential of eRNA-based therapeutic strategies in cancers.

Identification of a lactate metabolism-related lncRNAs signature for predicting the prognosis in patients with kidney renal clear cell carcinoma.

Background: Lactate metabolism-related (LMR) long noncoding RNAs (lncRNAs) play significant roles in various cancers, but their impact on kidney renal clear cell carcinoma (KIRC) remains unclear. This study aimed to explore the value of LMR lncRNA and develop a risk model for KIRC. Methods: Data on KIRC patients were downloaded from The Cancer Genome Atlas (TCGA) database. LMR lncRNAs were identified by co-expression, univariate and multivariate analyses, and least absolute shrinkage selection operator (LASSO) regression analysis. Subsequently, a prognostic signature was constructed and its accuracy was verified. To predict the prognosis of KIRC effectively, we established a nomogram based on this information. Enrichment analysis, tumor mutational burden (TMB) analysis, immune status and the therapeutic sensitivities of KIRC patients were also investigated. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to detect the expression of lncRNAs. Results: We constructed and verified a predictive signature based on six LMR lncRNA (LINC00944, AC090772.3, Z83745.1, AP001267.3, AC092296.1, and AL162377.1) to assess the patient prognoses of KIRC. Survival analyses showed a more unfavorable outcome in high-risk patients (P<0.001). Enrichment analysis demonstrated that immune-related pathways were enriched in the high-risk group. Besides, patients classified by risk scores had distinguishable immune status, TMB, response to immunotherapy, and sensitivity to chemotherapy and targeted drugs. Conclusions: The LMR lncRNAs signature has significant implications for prognostic assessment and clinical treatment guidance in KIRC.

Prioritization of risk genes in colorectal cancer by integrative analysis of multi-omics data and gene networks.

Genome-wide association studies (GWASs) have identified over 140 colorectal cancer (CRC)-associated loci; however, target genes at the majority of loci and underlying molecular mechanisms are poorly understood. Here, we utilized a Bayesian approach, integrative risk gene selector (iRIGS), to prioritize risk genes at CRC GWAS loci by integrating multi-omics data. As a result, a total of 105 high-confidence risk genes (HRGs) were identified, which exhibited strong gene dependencies for CRC and enrichment in the biological processes implicated in CRC. Among the 105 HRGs, CEBPB, located at the 20q13.13 locus, acted as a transcription factor playing critical roles in cancer. Our subsequent assays indicated the tumor promoter function of CEBPB that facilitated CRC cell proliferation by regulating multiple oncogenic pathways such as MAPK, PI3K-Akt, and Ras signaling. Next, by integrating a fine-mapping analysis and three independent case-control studies in Chinese populations consisting of 8,039 cases and 12,775 controls, we elucidated that rs1810503, a putative functional variant regulating CEBPB, was associated with CRC risk (OR=0.90, 95%CI=0.86-0.93, P=1.07×10-7). The association between rs1810503 and CRC risk was further validated in three additional multi-ancestry populations consisting of 24,254 cases and 58,741 controls. Mechanistically, the rs1810503 A to T allele change weakened the enhancer activity in an allele-specific manner to decrease CEBPB expression via long-range promoter-enhancer interactions, mediated by the transcription factor, REST, and thus decreased CRC risk. In summary, our study provides a genetic resource and a generalizable strategy for CRC etiology investigation, and highlights the biological implications of CEBPB in CRC tumorigenesis, shedding new light on the etiology of CRC.

A genetic variant in the immune-related gene ERAP1 affects colorectal cancer prognosis.

BACKGROUND: Findings on the association of genetic factors and colorectal cancer (CRC) survival are limited and inconsistent, and revealing the mechanism underlying their prognostic roles is of great importance. This study aimed to explore the relationship between functional genetic variations and the prognosis of CRC and further reveal the possible mechanism. METHODS: We first systematically performed expression quantitative trait locus (eQTL) analysis using The Cancer Genome Atlas (TCGA) dataset. Then, the Kaplan-Meier analysis was used to filter out the survival-related eQTL target genes of CRC patients in two public datasets (TCGA and GSE39582 dataset from the Gene Expression Omnibus database). The seven most potentially functional eQTL single nucleotide polymorphisms (SNPs) associated with six survival-related eQTL target genes were genotyped in 907 Chinese CRC patients with clinical prognosis data. The regulatory mechanism of the survival-related SNP was further confirmed by functional experiments. RESULTS: The rs71630754 regulating the expression of endoplasmic reticulum aminopeptidase 1 ( ERAP1 ) was significantly associated with the prognosis of CRC (additive model, hazard ratio [HR]: 1.43, 95% confidence interval [CI]: 1.08-1.88, P = 0.012). The results of dual-luciferase reporter assay and electrophoretic mobility shift assay showed that the A allele of the rs71630754 could increase the binding of transcription factor 3 (TCF3) and subsequently reduce the expression of ERAP1 . The results of bioinformatic analysis showed that lower expression of ERAP1 could affect the tumor immune microenvironment and was significantly associated with severe survival outcomes. CONCLUSION: The rs71630754 could influence the prognosis of CRC patients by regulating the expression of the immune-related gene ERAP1 . TRIAL REGISTRATION: No. NCT00454519 ( https://clinicaltrials.gov/ ).

Applications of Boron Cluster Supramolecular Frameworks as Metal-Free Chemodynamic Therapy Agents for Melanoma.

Chemodynamic therapy (CDT) is a highly targeted approach to treat cancer since it converts hydrogen peroxide into harmful hydroxyl radicals (OH·) through Fenton or Fenton-like reactions. However, the systemic toxicity of metal-based CDT agents has limited their clinical applications. Herein, a metal-free CDT agent: 2,4,6-tri(4-pyridyl)-1,3,5-triazine (TPT)/ [closo-B12 H12 ]2- (TPT@ B12 H12 ) is reported. Compared to the traditional metal-based CDT agents, TPT@B12 H12 is free of metal avoiding cumulative toxicity during long-term therapy. Density functional theory (DFT) calculation revealed that TPT@B12 H12 decreased the activation barrier more than 3.5 times being a more effective catalyst than the Fe2+ ion (the Fenton reaction), which decreases the barrier about twice. Mechanismly, the theory calculation indicated that both [B12 H12 ]-· and [TPT-H]2+ have the capacity to decompose hydrogen into 1 O2 , OH·, and O2 -· . With electron paramagnetic resonance and fluorescent probes, it is confirmed that TPT@B12 H12 increases the levels of 1 O2 , OH·, and O2 -· . More importantly, TPT@B12 H12 effectively suppress the melanoma growth both in vitro and in vivo through 1 O2 , OH·, and O2 -· generation. This study specifically highlights the great clinical translational potential of TPT@B12 H12 as a CDT reagent.

Healthy dietary patterns, genetic risk, and gastrointestinal cancer incident risk: a large-scale prospective cohort study.

BACKGROUND: Dietary patterns have been associated with several cancers, especially gastrointestinal cancer (GIC). However, whether a healthy dietary pattern could modify the risk of GIC among people with different genetic backgrounds is not clear. OBJECTIVE: The objective of the study was to investigate how dietary patterns and genetic susceptibility contribute to the risk of GIC independently and jointly. METHODS: This large-scale prospective cohort study included 105,463 participants in UK Biobank who were aged 40-72 y and cancer-free at baseline. Dietary intake (Oxford WebQ) was used to calculate dietary pattern scores including dietary approach to stop hypertension (DASH) score and healthful plant-based diet index (hPDI). Genetic risk was quantified by a polygenic risk score (PRS) comprising 129 known GIC-associated loci. Cox proportional hazards regression was performed to estimate the associations of dietary patterns and PRS with GIC incidence after adjusting for potential confounders. RESULTS: Over a median follow-up of 11.70 y, 1,661 participants were diagnosed with GIC. DASH and hPDI were associated with 20% and 36% reductions, respectively, in GIC risk. Low PRS was associated with a 30 % decrease in GIC risk (HR: 0.70; 95% CI: 0.62, 0.79). Participants with healthy dietary scores at high-genetic risk had a lower GIC risk with HR of 0.77 (95% CI: 0.60, 0.98) for DASH and 0.66 (95% CI: 0.52, 0.84) for hPDI than those with unhealthy dietary score. Participants with both high-dietary score and low-genetic risk showed the lowest risk of GIC, with HR of 0.58 (95% CI: 0.45, 0.75) for DASH and 0.45 (95% CI: 0.34, 0.58) for hPDI. CONCLUSIONS: Adherence to DASH and hPDI were associated with a lower risk of some gastrointestinal cancers, and these 2 dietary patterns may partly compensate for genetic predispositions to cancer. Our results advance the development of precision medicine strategies that consider both dietary patterns and genetics to improve gastrointestinal health.

Synthesis of iron-boride/carbon-nitride composites and their applications in chemodynamic therapy.

Chemodynamic therapy (CDT) is an emerging treatment strategy that inhibits tumor growth by catalyzing the generation of reactive oxygen species (ROS), such as hydroxyl radicals (•OH), using specific nanomaterials. Herein, we have developed a new class of iron-based nanomaterials, i.e., iron-based borides (FeB), using the superchaotropic effect of a boron cluster (closo-[B12H12]2-) and organic ligands, followed by high-temperature calcination. Experimental data and theoretical calculations revealed that FeB nanoparticles exhibit a Fenton-like effect, efficiently decomposing hydrogen peroxide into •OH and thus increasing the concentration of ROS. FeB nanomaterials demonstrate excellent catalytic performance, efficiently generate ROS, and exert significant antitumor effects in cell experiments and animal models. Therefore, FeB nanomaterials have considerable potential for application in tumor treatment and offer new insights for the development of novel and efficient cancer therapy strategies.

A comparative study on point cloud down-sampling strategies for deep learning-based crop organ segmentation.

The 3D crop data obtained during cultivation is of great significance to screening excellent varieties in modern breeding and improvement on crop yield. With the rapid development of deep learning, researchers have been making innovations in aspects of both data preparation and deep network design for segmenting plant organs from 3D data. Training of the deep learning network requires the input point cloud to have a fixed scale, which means all point clouds in the batch should have similar scale and contain the same number of points. A good down-sampling strategy can reduce the impact of noise and meanwhile preserve the most important 3D spatial structures. As far as we know, this work is the first comprehensive study of the relationship between multiple down-sampling strategies and the performances of popular networks for plant point clouds. Five down-sampling strategies (including FPS, RS, UVS, VFPS, and 3DEPS) are cross evaluated on five different segmentation networks (including PointNet + + , DGCNN, PlantNet, ASIS, and PSegNet). The overall experimental results show that currently there is no strict golden rule on fixing down-sampling strategy for a specific mainstream crop deep learning network, and the optimal down-sampling strategy may vary on different networks. However, some general experience for choosing an appropriate sampling method for a specific network can still be summarized from the qualitative and quantitative experiments. First, 3DEPS and UVS are easy to generate better results on semantic segmentation networks. Second, the voxel-based down-sampling strategies may be more suitable for complex dual-function networks. Third, at 4096-point resolution, 3DEPS usually has only a small margin compared with the best down-sampling strategy at most cases, which means 3DEPS may be the most stable strategy across all compared. This study not only helps to further improve the accuracy of point cloud deep learning networks for crop organ segmentation, but also gives clue to the alignment of down-sampling strategies and a specific network.

MGA-seq: robust identification of extrachromosomal DNA and genetic variants using multiple genetic abnormality sequencing.

Genomic abnormalities are strongly associated with cancer and infertility. In this study, we develop a simple and efficient method - multiple genetic abnormality sequencing (MGA-Seq) - to simultaneously detect structural variation, copy number variation, single-nucleotide polymorphism, homogeneously staining regions, and extrachromosomal DNA (ecDNA) from a single tube. MGA-Seq directly sequences proximity-ligated genomic fragments, yielding a dataset with concurrent genome three-dimensional and whole-genome sequencing information, enabling approximate localization of genomic structural variations and facilitating breakpoint identification. Additionally, by utilizing MGA-Seq, we map focal amplification and oncogene coamplification, thus facilitating the exploration of ecDNA's transcriptional regulatory function.

Total marrow lymphoid irradiation IMRT treatment using a novel CT-linac.

BACKGROUND: A novel CT-linac (kilovolt fan-beam CT-linac) has been introduced into total marrow and lymphoid irradiation (TMLI) treatment. Its integrated kilovolt fan-beam CT (kV FBCT) can be used not only for image guidance (IGRT) but also to re-calculate the dose. PURPOSE: This study reported our clinical routine on performing TMIL treatment on the CT-linac, as well as dose distribution comparison between planned and re-calculated based on IGRT FBCT image sets. METHODS: 11 sets of data from 5 male and 6 female patients who had underwent the TMLI treatment with uRT-linac 506c were selected for this study. The planning target volumes consist of all skeletal bones exclusion of the mandible and lymphatic sanctuary sites. A planned dose of 10 Gy was prescribed to all skeletal bones exclusion of the mandible in two fractions and 12 Gy in two fractions was prescribed to lymphatic sanctuary sites. Each TMLI plan contained two sub-plans, one dynamic IMRT for the upper body and the other VMAT for the lower extremity. Two attempts were made to obtain homogeneous dose in the overlapping region, i.e., applying two plans with different isocenters for the treatment of two fractions, and using a dose gradient matching scheme. The CT scans, including planning CT and IGRT FBCT, were stitched to a whole body CT scan for dose distribution evaluation. RESULTS: The average beam-on time of Planupper is 30.6 min, ranging from 24.9 to 37.5 min, and the average beam-on time of Planlower is 6.3 min, ranging from 5.7 to 8.2 min. For the planned dose distribution, the 94.79% of the PTVbone is covered by the prescription dose of 10 Gy (V10), and the 94.68% of the PTVlymph is covered by the prescription dose of 12 Gy (V12). For the re-calculated dose distribution, the 92.17% of the PTVbone is covered by the prescription dose of 10 Gy (V10), and the 90.07% of the PTVlymph is covered by the prescription dose of 12 Gy (V12). The results showed that there is a significant difference (p < 0.05) between planning V10, V12 and delivery V10, V12. There is no significant difference (p > 0.05) between planned dose and re-calculated dose on selected organs, except for right lens (p < 0.05, Dmax). The actual delivered maximum dose of right lens is apparently larger than the planned dose of it. CONCLUSION: TMLI treatment can be performed on the CT-linac with clinical acceptable quality and high efficiency. Evaluation of the recalculated dose on IGRT FBCT suggests the treatment was delivered with adequate target coverage.

Genetic Variants That Impact Alternative Polyadenylation in Cancer Represent Candidate Causal Risk Loci.

Alternative polyadenylation (APA) is emerging as a major mechanism of posttranscriptional regulation. APA can impact the development and progression of cancer, suggesting that the genetic determinants of APA might play an important role in regulating cancer risk. Here, we depicted a pan-cancer atlas of human APA quantitative trait loci (apaQTL), containing approximately 0.7 million apaQTLs across 32 cancer types. Systematic multiomics analyses indicated that cancer apaQTLs could contribute to APA regulation by altering poly(A) motifs, RNA-binding proteins (RBP), and chromatin regulatory elements and were preferentially enriched in genome-wide association studies (GWAS)-identified cancer susceptibility loci. Moreover, apaQTL-related genes (aGene) were broadly related to cancer signaling pathways, high mutational burden, immune infiltration, and drug response, implicating their potential as therapeutic targets. Furthermore, apaQTLs were mapped in Chinese colorectal cancer tumor tissues and then screened for functional apaQTLs associated with colorectal cancer risk in 17,789 cases and 19,951 controls using GWAS-ChIP data, with independent validation in a large-scale population consisting of 6,024 cases and 10,022 controls. A multi-ancestry-associated apaQTL variant rs1020670 with a C>G change in DNM1L was identified, and the G allele contributed to an increased risk of colorectal cancer. Mechanistically, the risk variant promoted aberrant APA and facilitated higher usage of DNM1L proximal poly(A) sites mediated by the RBP CSTF2T, which led to higher expression of DNM1L with a short 3'UTR. This stabilized DNM1L to upregulate its expression, provoking colorectal cancer cell proliferation. Collectively, these findings generate a resource for understanding APA regulation and the genetic basis of human cancers, providing insights into cancer etiology. SIGNIFICANCE: Cancer risk is mediated by alternative polyadenylation quantitative trait loci, including the rs1020670-G variant that promotes alternative polyadenylation of DNM1L and increases colorectal cancer risk.

Genome-wide enhancer-gene regulatory maps link causal variants to target genes underlying human cancer risk.

Genome-wide association studies have identified numerous variants associated with human complex traits, most of which reside in the non-coding regions, but biological mechanisms remain unclear. However, assigning function to the non-coding elements is still challenging. Here we apply Activity-by-Contact (ABC) model to evaluate enhancer-gene regulation effect by integrating multi-omics data and identified 544,849 connections across 20 cancer types. ABC model outperforms previous approaches in linking regulatory variants to target genes. Furthermore, we identify over 30,000 enhancer-gene connections in colorectal cancer (CRC) tissues. By integrating large-scale population cohorts (23,813 cases and 29,973 controls) and multipronged functional assays, we demonstrate an ABC regulatory variant rs4810856 associated with CRC risk (Odds Ratio = 1.11, 95%CI = 1.05-1.16, P = 4.02 × 10-5) by acting as an allele-specific enhancer to distally facilitate PREX1, CSE1L and STAU1 expression, which synergistically activate p-AKT signaling. Our study provides comprehensive regulation maps and illuminates a single variant regulating multiple genes, providing insights into cancer etiology.