Evaluation of ex vivo drug combination optimization platform in recurrent high grade astrocytic glioma: An interventional, non-randomized, open-label trial protocol.

INTRODUCTION: High grade astrocytic glioma (HGG) is a lethal solid malignancy with high recurrence rates and limited survival. While several cytotoxic agents have demonstrated efficacy against HGG, drug sensitivity testing platforms to aid in therapy selection are lacking. Patient-derived organoids (PDOs) have been shown to faithfully preserve the biological characteristics of several cancer types including HGG, and coupled with the experimental-analytical hybrid platform Quadratic Phenotypic Optimization Platform (QPOP) which evaluates therapeutic sensitivity at a patient-specific level, may aid as a tool for personalized medical decisions to improve treatment outcomes for HGG patients. METHODS: This is an interventional, non-randomized, open-label study, which aims to enroll 10 patients who will receive QPOP-guided chemotherapy at the time of first HGG recurrence following progression on standard first-line therapy. At the initial presentation of HGG, tumor will be harvested for primary PDO generation during the first biopsy/surgery. At the point of tumor recurrence, patients will be enrolled onto the main study to receive systemic therapy as second-line treatment. Subjects who undergo surgery at the time of recurrence will have a second harvest of tissue for PDO generation. Established PDOs will be subject to QPOP analyses to determine their therapeutic sensitivities to specific panels of drugs. A QPOP-guided treatment selection algorithm will then be used to select the most appropriate drug combination. The primary endpoint of the study is six-month progression-free survival. The secondary endpoints include twelve-month overall survival, RANO criteria and toxicities. In our radiological biomarker sub-study, we plan to evaluate novel radiopharmaceutical-based neuroimaging in determining blood-brain barrier permeability and to assess in vivo drug effects on tumor vasculature over time. TRIAL REGISTRATION: This trial was registered on 8th September 2022 with ClinicalTrials.gov Identifier: NCT05532397.

Mitigating environmental pollution in China: Unlocking the potential for high-quality innovation.

The nexus between environmental pollution (EP) and technological innovation is crucial for achieving sustainable development. However, existing literature has paid less attention to the new form of high-quality innovation (HI) in environmental management. This paper uses panel data from 31 Chinese provinces from 2008 to 2020, employing the two-stage least squares method to investigate the relationship between HI and EP. The empirical results reveal that HI can effectively reduce the EP, which holds after multiple robustness tests, and this effect is more obvious in southern China. Meanwhile, HI drives clean and efficient energy transition and decreases EP. Moreover, increased environmental regulation weakens the influence of HI on EP. The major contributions of this study are constructing an HI index including innovation, human capital, and government support and examining its influence on EP in China. The findings encourage government to implement policies of innovation-driven transformation, energy conservation and emissions reduction.

N-of-1 health optimization: Digital monitoring of biomarker dynamics to gamify adherence to metabolic switching.

The digital health field is experiencing substantial growth due to its potential for sustained and longitudinal deployment. In turn, this may drive improved monitoring and intervention as catalysts for behavioral change compared to traditional point-of-care practices. In particular, the increase in incidence of population health challenges such as diabetes, heart disease, fatty liver disease, and other disorders coupled with rising healthcare costs have emphasized the importance of exploring technical, economics, and implementation considerations, among others in the decentralization of health and healthcare innovations. Both healthy individuals and patients stand to benefit from continued technical advances and studies in these domains. To address these points, this study reports a N-of-1 study comprised of sustained regimens of intermittent fasting, fitness (strength and cardiovascular training), and high protein, low carbohydrate diet and parallel monitoring. These regimens were paired with serial blood ketone, blood glucose (wearable and finger stick) and blood pressure readings, as well as body weight measurements using a collection of devices. Collectively this suite of platforms and approaches were used to monitor metabolic switching from glucose to ketones as energy sources-a process associated with potential cardio- and neuroprotective functions. In addition to longitudinal biomarker dynamics, this work discusses user perspectives on the potential role of harnessing digital devices to these dynamics as potential gamification factors, as well as considerations for the role of biomarker monitoring in health regimen development, user stratification, and potentially informing downstream population-scale studies to address metabolic disease, healthy aging and longevity, among other indications.

The extract of an herbal medicine Chebulae fructus inhibits hepatocellular carcinoma by suppressing the Apelin/APJ system.

Introduction: Hepatocellular carcinoma (HCC) has been a highly common and pathological disease worldwide, while current therapeutic regimens have limitations. Chebulae Fructus, a common herbal medicine in Asia, has been documented to exert potential therapeutic effects on HCC in ancient medicine clinical practice. However, the molecular mechanism underlying its inhibitory effects on HCC requires further investigation. Methods: In this study, the anti-HCC effect of the aqueous extract of Chebulae Fructus (CFE) on human HCC and its underlying mechanism were evaluated. Assays including CCK8, EdU staining, crystal violet staining, cell clone formation, flow cytometry, wound healing, and transwell were used in vitro. The cell-derived xenograft (CDX) and patient-derived xenograft (PDX) models were used in vivo. Transcriptomics analysis, qRT-PCR, ELISA, IHC staining, and Western blotting were employed to determine the mechanism of action of CFE. Results: The results demonstrate that CFE effectively suppressed the proliferation and activity of HepG2 and PLC/PRF/5 HCC cells. CFE also induced apoptosis, and suppressed the migration and invasion abilities of these cells. Furthermore, CFE exhibited inhibitory effects on tumor growth in both H22 and PLC/PRF/5 mouse models, as well as in an HCC PDX model which is derived from patient tumor samples. Moreover, it was identified that CFE treatment specifically suppressed the Apelin/APJ system in HCC cells and tumor tissues. To investigate the role of the Apelin/APJ system in mediating the effects of CFE treatment, an APJ overexpressed cell model is established. Interestingly, it was found that the overexpression of APJ significantly diminished the inhibitory effects of CFE on HCC in vitro. Discussion: Collectively, this study provides compelling evidence that CFE exerts significant anti-HCC effects in cell and animal models. Moreover, our findings suggest that the Apelin/APJ system may play a vital role in the therapeutic effects of CFE against HCC.

A novel signature based on twelve programmed cell death patterns to predict the prognosis of lung adenocarcinoma.

Programmed cell death (PCD) plays a pivotal role in tumor initiation and progression. However, the prognostic value and clinical characteristics of PCD-related genes (PRGs) remain unclear. We collected and analyzed genes associated with twelve PCD patterns, including apoptosis, necroptosis, pyroptosis, ferroptosis, cuproptosis, entotic cell death, netotic cell death, parthanatos, lysosome-dependent cell death, autophagy-dependent cell death, alkaliptosis, and oxeiptosis to construct a gene signature. Our analysis identified 215 differentially expressed PRGs out of 1254 in lung adenocarcinoma (LUAD) and normal lung tissues. Subsequently, we performed univariate Cox regression analysis and identified 58 prognostic PRGs. Based on LASSO Cox regression analysis, we constructed a risk score using the expression levels of seven genes: DAPK2, DDIT4, E2F2, GAPDH, MET, PIM2, and FOXF1. Patients with lower risk scores showed earlier stages of cancer, longer survival times, and better immune infiltrations and functions. Notably, we found that knockdown of DDIT4 significantly increased apoptosis and impaired the proliferation of human LUAD cell lines. Our study proposes a PRG-based prognostic signature that sheds light on the potential role of PCD-related genes in LUAD and provides valuable insights into future therapeutic strategies.

Carboxymethyl chitosan composited poly(ethylene oxide) electrolyte with high ion conductivity and interfacial stability for lithium metal batteries.

Low ionic conductivity and poor interface stability of poly(ethylene oxide) (PEO) restrict the practical application as polymeric electrolyte films to prepare solid-state lithium (Li) metal batteries. In this work, biomass-based carboxymethyl chitosan (CMCS) is designed and developed as organic fillers into PEO matrix to form composite electrolytes (PEO@CMCS). Carboxymethyl groups of CMCS fillers can promote the decomposition of Lithium bis(trifluoromethane sulfonimide) (LiTFSI) to generate more lithium fluoride (LiF) at CMCS/PEO interface, which not only forms ionic conductive network to promote the rapid transfer of Li+ but also effectively enhances the interface stability between polymeric electrolyte and Li metal. The enrichment of carboxyl, hydroxyl, and amidogen functional groups within CMCS fillers can form hydrogen bonds with ethylene oxide (EO) chains to improve the tensile properties of PEO-based electrolyte. In addition, the high hardness of CMCS additives can also strengthen mechanical properties of PEO-based electrolyte to resist penetration of Li dendrites. LiLi symmetric batteries can achieve stable cycle for 2500 h and lithium iron phosphate full batteries can maintain 135.5 mAh g-1 after 400 cycles. This work provides a strategy for the enhancement of ion conductivity and interface stability of PEO-based electrolyte, as well as realizes the resource utilization of biomass-based CMCS.

Establishing subdivisions of M1 stage nasopharyngeal carcinoma based on decision tree classification: A multicenter retrospective study.

OBJECTIVES: To meet the demand for personalized treatment, effective stratification of patients with metastatic nasopharyngeal carcinoma (mNPC) is essential. Hence, our study aimed to establish an M1 subdivision for prognostic prediction and treatment planning in patients with mNPC. MATERIALS AND METHODS: This study included 1239 patients with mNPC from three medical centers divided into the synchronous mNPC cohort (smNPC, n = 556) to establish an M1 stage subdivision and the metachronous mNPC cohort (mmNPC, n = 683) to validate this subdivision. The primary endpoint was overall survival. Univariate and multivariate Cox analyses identified covariates for the decision-tree model, proposing an M1 subdivision. Model performance was evaluated using time-dependent receiver operating characteristic curves, Harrell's concordance index, calibration plots, and decision curve analyses. RESULTS: The proposed M1 subdivisions were M1a (≤5 metastatic lesions), M1b (>5 metastatic lesions + absent liver metastases), and M1c (>5 metastatic lesions + existing liver metastases) with median OS of 34, 22, and 13 months, respectively (p < 0.001). This M1 subdivision demonstrated superior discrimination (C-index = 0.698; 3-year AUC = 0.707) and clinical utility over those of existing staging systems. Calibration curves exhibited satisfactory agreement between predictions and actual observations. Internal and mmNPC cohort validation confirmed the robustness. Survival benefits from local metastatic treatment were observed in M1a, while immunotherapy improved survival in patients with M1b and M1c disease. CONCLUSION: This novel M1 staging strategy provides a refined approach for prognostic prediction and treatment planning in patients with mNPC, emphasizing the potential benefits of local and immunotherapeutic interventions based on individualized risk stratification.

CCT6A facilitates lung adenocarcinoma progression and glycolysis via STAT1/HK2 axis.

BACKGROUND: Chaperonin Containing TCP1 Subunit 6 A (CCT6A) is a prominent protein involved in the folding and stabilization of newly synthesized proteins. However, its roles and underlying mechanisms in lung adenocarcinoma (LUAD), one of the most aggressive cancers, remain elusive. METHODS: Our study utilized in vitro cell phenotype experiments to assess CCT6A's impact on the proliferation and invasion capabilities of LUAD cell lines. To delve into CCT6A's intrinsic mechanisms affecting glycolysis and proliferation in lung adenocarcinoma, we employed transcriptomic sequencing and liquid chromatography-mass spectrometry analysis. Co-immunoprecipitation (Co-IP) and chromatin immunoprecipitation (CHIP) assays were also conducted to substantiate the mechanism. RESULTS: CCT6A was found to be significantly overexpressed in LUAD and associated with a poorer prognosis. The silencing of CCT6A inhibited the proliferation and migration of LUAD cells and elevated apoptosis rates. Mechanistically, CCT6A interacted with STAT1 protein, forming a complex that enhances the stability of STAT1 by protecting it from ubiquitin-mediated degradation. This, in turn, facilitated the transcription of hexokinase 2 (HK2), a critical enzyme in aerobic glycolysis, thereby stimulating LUAD's aerobic glycolysis and progression. CONCLUSION: Our findings reveal that the CCT6A/STAT1/HK2 axis orchestrated a reprogramming of glucose metabolism and thus promoted LUAD progression. These insights position CCT6A as a promising candidate for therapeutic intervention in LUAD treatment.

Efficacy of metastatic lesion radiotherapy in patients with metastatic nasopharyngeal carcinoma: A multicenter retrospective study.

OBJECTIVE: We investigated the efficacy of metastatic lesion radiotherapy (MLRT) in patients with metastatic nasopharyngeal carcinoma (mNPC). MATERIALS AND METHODS: Patients with mNPC from three institutions were included in this study. Propensity score matching (PSM) was employed to ensure comparability between patient groups. Overall survival (OS) rates were assessed using the Kaplan-Meier method and compared using the log-rank test. Prognostic factors were identified using univariate and multivariate Cox hazard analyses. Subgroup analyses were conducted to assess the effects of MLRT on specific patient populations. RESULTS: We analyzed data from 1157 patients with mNPC. Patients who received MLRT had significantly better OS than those who did not, both in the original (28 vs. 21 months) and PSM cohorts (26 vs. 23 months). MLRT was identified as an independent favorable predictor of OS in multivariate analyses, with hazard ratios of 0.67. The subgroup analysis results indicated that radiotherapy effectively treated liver, lung, and bone metastatic lesions, particularly in patients with a limited tumor burden. Higher total radiation doses of MLRT (biologically effective dose (BED) ≥ 56 Gy) were associated with improved OS, while neither radiation technique nor dose fractionation independently influenced prognosis. CONCLUSIONS: MLRT offers survival advantages to patients diagnosed with mNPC. Patients with limited metastatic burden derive the most benefit from MLRT, and the recommended regimen for MLRT is a minimum BED of 56 Gy for optimal outcomes.

VEGF-induced Nrdp1 deficiency in vascular endothelial cells promotes cancer metastasis by degrading vascular basement membrane.

Vascular endothelial cells (VECs) are key players in the formation of neovessels and tumor metastasis, the ultimate cause of the majority of cancer-related human death. However, the crosstalk between VECs and metastasis remain greatly elusive. Based on our finding that tumor-associated VECs present significant decrease of Nrdp1 protein which is closely correlated with higher metastatic probability, herein we show that the conditional medium from hypoxia-incubated cancer cells induces extensive Nrdp1 downregulation in human and mouse VECs by vascular endothelial growth factor (VEGF), which activates CHIP, followed by Nrdp1 degradation in ubiquitin-proteasome-dependent way. More importantly, lung metastases of cancer cells significantly increase in conditional VECs Nrdp1 knockout mice. Mechanically, Nrdp1 promotes degradation of Fam20C, a secretory kinase involved in phosphorylating numerous secreted proteins. Reciprocally, deficiency of Nrdp1 in VECs (ecNrdp1) results in increased secretion of Fam20C, which induces degradation of extracellular matrix and disrupts integrity of vascular basement membrane, thus driving tumor metastatic dissemination. In addition, specific overexpression of ecNrdp1 by Nrdp1-carrying adeno-associated virus or chemical Nrdp1 activator ABPN efficiently mitigates tumor metastasis in mice. Collectively, we explore a new mechanism for VEGF to enhance metastasis and role of Nrdp1 in maintaining the integrity of vascular endothelium, suggesting that ecNrdp1-mediated signaling pathways might become potential target for anti-metastatic therapies.

Transcriptome profiling of aerial and subterranean peanut pod development.

Peanut (Arachis hypogaea) showcases geocarpic behavior, transitioning from aerial flowering to subterranean seed development. We recently obtained an atavistic variant of this species, capable of producing aerial and subterranean pods on a single plant. Notably, although these pod types share similar vigor levels, they exhibit distinct differences in their physical aspects, such as pod size, color, and shell thickness. We constructed 63 RNA-sequencing datasets, comprising three biological replicates for each of 21 distinct tissues spanning six developmental stages for both pod types, providing a rich tapestry of the pod development process. This comprehensive analysis yielded an impressive 409.36 Gb of clean bases, facilitating the detection of 42,401 expressed genes. By comparing the transcriptomic data of the aerial and subterranean pods, we identified many differentially expressed genes (DEGs), highlighting their distinct developmental pathways. By providing a detailed workflow from the initial sampling to the final DEGs, this study serves as an important resource, paving the way for future research into peanut pod development and aiding transcriptome-based expression profiling and candidate gene identification.

Pushing the Frontiers of Cancer Research: Highlights from the Frontiers in Cancer Science Conference 2023.

The 15th annual Frontiers in Cancer Science (FCS) conference gathered scientific experts who shared the latest research converging upon several themes of cancer biology. These themes included the dysregulation of metabolism, cell death, and other signaling processes in cancer cells; using patient "omics" datasets and single-cell and spatial approaches to investigate heterogeneity, understand therapy resistance, and identify targets; innovative strategies for inhibiting tumors, including rational drug combinations and improved drug delivery mechanisms; and advances in models that can facilitate screening for cancer vulnerabilities and drug testing. We hope the insights from this meeting will stimulate further progress in the field.

Effects of Total Intravenous Anesthesia on Circadian Rhythms in Patients Undergoing Cardiac Transcatheter Closure.

Objective To evaluate the effects of total intravenous anesthesia on the circadian rhythms in the patients undergoing cardiac transcatheter closure. Methods Thirty patients undergoing cardiac transcatheter closure under elective intravenous anesthesia were included in this study.Paired t-tests were performed to compare the mRNA levels of the genes encoding circadian locomotor output cycles kaput(CLOCK),brain and muscle ARNT-1 like protein-1(BMAL1),cryptochrome 1(CRY1),and period circadian clock 2(PER2),the Munich Chronotype Questionnaire(MCTQ)score,and the Pittsburgh Sleep Quality Index(PSQI)score before and after anesthesia.Multiple stepwise regression analysis was performed to screen the factors influencing sleep chronotype and PSQI total score one week after surgery. Results The postoperative mRNA level of CLOCK was higher [1.38±1.23 vs.1.90±1.47;MD(95%CI):0.52(0.20-0.84),t=3.327,P=0.002] and the postoperative mRNA levels of CRY1 [1.56±1.50 vs.1.13±0.98;MD(95%CI):-0.43(-0.81--0.05),t=-2.319,P=0.028] and PER2 [0.82±0.63 vs.0.50±0.31;MD(95%CI):-0.33(-0.53--0.12),t=-3.202,P=0.003] were lower than the preoperative levels.One week after surgery,the patients presented advanced sleep chronotype [3∶03±0∶59 vs.2∶42±0∶37;MD(95%CI):-21(-40--1),t=-2.172,P=0.038],shortened sleep latency [(67±64)min vs.(37±21)min;MD(95%CI):-30.33(-55.28--5.39),t=-2.487,P=0.019],lengthened sleep duration [(436±83)min vs.(499±83)min;MD(95%CI):62.80(26.93-98.67),t=3.581,P=0.001],increased sleep efficiency [(87.59±10.35)% vs.(92.98±4.27)%;MD(95%CI):5.39(1.21-9.58),t=2.636,P=0.013],decreased sleep quality score [1.13±0.78 vs.0.80±0.71;MD(95%CI):-0.33(-0.62--0.05),t=-2.408,P=0.023],and declined PSQI total score [6.60±3.17 vs.4.03±2.58;MD(95%CI):-2.57(-3.87--1.27),t=-4.039,P<0.001].Body mass index(BMI)(B=-227.460,SE=95.475,t=-2.382,P=0.025),anesthesia duration(B=-47.079,SE=18.506,t=-2.544,P=0.017),and mRNA level of PER2(B=2815.804,SE=1080.183,t=2.607,P=0.015)collectively influenced the sleep chronotype,and the amount of anesthesia medicine(B=0.067,SE=0.028,t=2.385,P=0.024)independently influenced the PSQI one week after surgery. Conclusions Total intravenous anesthesia can improve sleep habits by advancing sleep chronotype.BMI,anesthesia duration,and mRNA level of PER2 collectively influence sleep chronotype one week after surgery.The amount of anesthesia medicine independently influences the PSQI total score one week after surgery.

Plant-LncPipe: a computational pipeline providing significant improvement in plant lncRNA identification.

Long non-coding RNAs (lncRNAs) play essential roles in various biological processes, such as chromatin remodeling, post-transcriptional regulation, and epigenetic modifications. Despite their critical functions in regulating plant growth, root development, and seed dormancy, the identification of plant lncRNAs remains a challenge due to the scarcity of specific and extensively tested identification methods. Most mainstream machine learning-based methods used for plant lncRNA identification were initially developed using human or other animal datasets, and their accuracy and effectiveness in predicting plant lncRNAs have not been fully evaluated or exploited. To overcome this limitation, we retrained several models, including CPAT, PLEK, and LncFinder, using plant datasets and compared their performance with mainstream lncRNA prediction tools such as CPC2, CNCI, RNAplonc, and LncADeep. Retraining these models significantly improved their performance, and two of the retrained models, LncFinder-plant and CPAT-plant, alongside their ensemble, emerged as the most suitable tools for plant lncRNA identification. This underscores the importance of model retraining in tackling the challenges associated with plant lncRNA identification. Finally, we developed a pipeline (Plant-LncPipe) that incorporates an ensemble of the two best-performing models and covers the entire data analysis process, including reads mapping, transcript assembly, lncRNA identification, classification, and origin, for the efficient identification of lncRNAs in plants. The pipeline, Plant-LncPipe, is available at: https://github.com/xuechantian/Plant-LncRNA-pipline.

N6-methyladenosine mRNA methylation positively regulated the response of poplar to salt stress.

As the most abundant form of methylation modification in messenger RNA (mRNA), the distribution of N6-methyladenosine (m6A) has been preliminarily revealed in herbaceous plants under salt stress, but its function and mechanism in woody plants were still unknown. Here, we showed that global m6A levels increased during poplar response to salt stress. Methylated RNA immunoprecipitation sequencing (MeRIP-seq) revealed that m6A significantly enriched in the coding sequence region and 3'-untranslated regions in poplar, by recognising the conserved motifs, AGACU, GGACA and UGUAG. A large number of differential m6A transcripts have been identified, and some have been proved involving in salt response and plant growth and development. Further combined analysis of MeRIP-seq and RNA-seq revealed that the m6A hypermethylated and enrich in the CDS region preferred to positively regulate expression abundance. Writer inhibitor, 3-deazaneplanocin A treatment increased the sensitivity of poplar to salt stress by reducing mRNA stability to regulate the expression of salt-responsive transcripts PagMYB48, PagGT2, PagNAC2, PagGPX8 and PagARF2. Furthermore, we verified that the methyltransferase PagFIP37 plays a positively role in the response of poplar to salt stress, overexpressed lines have stronger salt tolerance, while RNAi lines were more sensitive to salt, which relied on regulating mRNA stability in an m6A manner of salt-responsive transcripts PagMYB48, PagGT2, PagNAC2, PagGPX8 and PagARF2. Collectively, these results revealed the regulatory role of m6A methylation in poplar response to salt stress, and revealed the importance and mechanism of m6A methylation in the response of woody plants to salt stress for the first time.

High-quality genome assembly enables prediction of allele-specific gene expression in hybrid poplar.

Poplar (Populus) is a well-established model system for tree genomics and molecular breeding, and hybrid poplar is widely used in forest plantations. However, distinguishing its diploid homologous chromosomes is difficult, complicating advanced functional studies on specific alleles. In this study, we applied a trio-binning design and PacBio high-fidelity long-read sequencing to obtain haplotype-phased telomere-to-telomere genome assemblies for the 2 parents of the well-studied F1 hybrid "84K" (Populus alba × Populus tremula var. glandulosa). Almost all chromosomes, including the telomeres and centromeres, were completely assembled for each haplotype subgenome apart from 2 small gaps on one chromosome. By incorporating information from these haplotype assemblies and extensive RNA-seq data, we analyzed gene expression patterns between the 2 subgenomes and alleles. Transcription bias at the subgenome level was not uncovered, but extensive-expression differences were detected between alleles. We developed machine-learning (ML) models to predict allele-specific expression (ASE) with high accuracy and identified underlying genome features most highly influencing ASE. One of our models with 15 predictor variables achieved 77% accuracy on the training set and 74% accuracy on the testing set. ML models identified gene body CHG methylation, sequence divergence, and transposon occupancy both upstream and downstream of alleles as important factors for ASE. Our haplotype-phased genome assemblies and ML strategy highlight an avenue for functional studies in Populus and provide additional tools for studying ASE and heterosis in hybrids.

Artificial intelligence-assisted system for the assessment of Forrest classification of peptic ulcer bleeding: a multicenter diagnostic study.

BACKGROUND: Inaccurate Forrest classification may significantly affect clinical outcomes, especially in high risk patients. Therefore, this study aimed to develop a real-time deep convolutional neural network (DCNN) system to assess the Forrest classification of peptic ulcer bleeding (PUB). METHODS: A training dataset (3868 endoscopic images) and an internal validation dataset (834 images) were retrospectively collected from the 900th Hospital, Fuzhou, China. In addition, 521 images collected from four other hospitals were used for external validation. Finally, 46 endoscopic videos were prospectively collected to assess the real-time diagnostic performance of the DCNN system, whose diagnostic performance was also prospectively compared with that of three senior and three junior endoscopists. RESULTS: The DCNN system had a satisfactory diagnostic performance in the assessment of Forrest classification, with an accuracy of 91.2% (95%CI 89.5%-92.6%) and a macro-average area under the receiver operating characteristic curve of 0.80 in the validation dataset. Moreover, the DCNN system could judge suspicious regions automatically using Forrest classification in real-time videos, with an accuracy of 92.0% (95%CI 80.8%-97.8%). The DCNN system showed more accurate and stable diagnostic performance than endoscopists in the prospective clinical comparison test. This system helped to slightly improve the diagnostic performance of senior endoscopists and considerably enhance that of junior endoscopists. CONCLUSION: The DCNN system for the assessment of the Forrest classification of PUB showed satisfactory diagnostic performance, which was slightly superior to that of senior endoscopists. It could therefore effectively assist junior endoscopists in making such diagnoses during gastroscopy.

A functional personalised oncology approach against metastatic colorectal cancer in matched patient derived organoids.

Globally, colorectal cancer (CRC) is the third most frequently occurring cancer. Progression on to an advanced metastatic malignancy (metCRC) is often indicative of poor prognosis, as the 5-year survival rates of patients decline rapidly. Despite the availability of many systemic therapies for the management of metCRC, the long-term efficacies of these regimens are often hindered by the emergence of treatment resistance due to intratumoral and intertumoral heterogeneity. Furthermore, not all systemic therapies have associated biomarkers that can accurately predict patient responses. Hence, a functional personalised oncology (FPO) approach can enable the identification of patient-specific combinatorial vulnerabilities and synergistic combinations as effective treatment strategies. To this end, we established a panel of CRC patient-derived organoids (PDOs) as clinically relevant biological systems, of which three pairs of matched metCRC PDOs were derived from the primary sites (ptCRC) and metastatic lesions (mCRC). Histological and genomic characterisation of these PDOs demonstrated the preservation of histopathological and genetic features found in the parental tumours. Subsequent application of the phenotypic-analytical drug combination interrogation platform, Quadratic Phenotypic Optimisation Platform, in these pairs of PDOs identified patient-specific drug sensitivity profiles to epigenetic-based combination therapies. Most notably, matched PDOs from one patient exhibited differential sensitivity patterns to the rationally designed drug combinations despite being genetically similar. These findings collectively highlight the limitations of current genomic-driven precision medicine in guiding treatment strategies for metCRC patients. Instead, it suggests that epigenomic profiling and application of FPO could complement the identification of novel combinatorial vulnerabilities to target synchronous ptCRC and mCRC.