Ultrasound deep learning radiomics and clinical machine learning models to predict low nuclear grade, ER, PR, and HER2 receptor status in pure ductal carcinoma in situ

Background

Low nuclear grade ductal carcinoma in situ (DCIS) patients can adopt proactive management strategies to avoid unnecessary surgical resection. Different personalized treatment modalities may be selected based on the expression status of molecular markers, which is also predictive of different outcomes and risks of recurrence. DCIS ultrasound findings are mostly non mass lesions, making it difficult to determine boundaries. Currently, studies have shown that models based on deep learning radiomics (DLR) have advantages in automatic recognition of tumor contours. Machine learning models based on clinical imaging features can explain the importance of imaging features.

Methods

The available ultrasound data of 349 patients with pure DCIS confirmed by surgical pathology [54 low nuclear grade, 175 positive estrogen receptor (ER+), 163 positive progesterone receptor (PR+), and 81 positive human epidermal growth factor receptor 2 (HER2+)] were collected. Radiologists extracted ultrasonographic features of DCIS lesions based on the 5th Edition of Breast Imaging Reporting and Data System (BI-RADS). Patient age and BI-RADS characteristics were used to construct clinical machine learning (CML) models. The RadImageNet pretrained network was used for extracting radiomics features and as an input for DLR modeling. For training and validation datasets, 80% and 20% of the data, respectively, were used. Logistic regression (LR), support vector machine (SVM), random forest (RF), and eXtreme Gradient Boosting (XGBoost) algorithms were performed and compared for the final classification modeling. Each task used the area under the receiver operating characteristic curve (AUC) to evaluate the effectiveness of DLR and CML models.

Results

In the training dataset, low nuclear grade, ER+, PR+, and HER2+ DCIS lesions accounted for 19.20%, 65.12%, 61.21%, and 30.19%, respectively; the validation set, they consisted of 19.30%, 62.50%, 57.14%, and 30.91%, respectively. In the DLR models we developed, the best AUC values for identifying features were 0.633 for identifying low nuclear grade, completed by the XGBoost Classifier of ResNet50; 0.618 for identifying ER, completed by the RF Classifier of InceptionV3; 0.755 for identifying PR, completed by the XGBoost Classifier of InceptionV3; and 0.713 for identifying HER2, completed by the LR Classifier of ResNet50. The CML models had better performance than DLR in predicting low nuclear grade, ER+, PR+, and HER2+ DCIS lesions. The best AUC values by classification were as follows: for low nuclear grade by RF classification, AUC: 0.719; for ER+ by XGBoost classification, AUC: 0.761; for PR+ by XGBoost classification, AUC: 0.780; and for HER2+ by RF classification, AUC: 0.723.

Conclusions

Based on small-scale datasets, our study showed that the DLR models developed using RadImageNet pretrained network and CML models may help predict low nuclear grade, ER+, PR+, and HER2+ DCIS lesions so that patients benefit from hierarchical and personalized treatment.

Precise prediction of phase-separation key residues by machine learning

Understanding intracellular phase separation is crucial for deciphering transcriptional control, cell fate transitions, and disease mechanisms. However, the key residues, which impact phase separation the most for protein phase separation function have remained elusive. We develop PSPHunter, which can precisely predict these key residues based on machine learning scheme. In vivo and in vitro validations demonstrate that truncating just 6 key residues in GATA3 disrupts phase separation, enhancing tumor cell migration and inhibiting growth. Glycine and its motifs are enriched in spacer and key residues, as revealed by our comprehensive analysis. PSPHunter identifies nearly 80% of disease-associated phase-separating proteins, with frequent mutated pathological residues like glycine and proline often residing in these key residues. PSPHunter thus emerges as a crucial tool to uncover key residues, facilitating insights into phase separation mechanisms governing transcriptional control, cell fate transitions, and disease development.

The impact of age-specific childhood body-mass index on adult cardiometabolic traits: a Mendelian randomization study

Objective

To evaluate the causal relationship between childhood body-mass index (BMI) at different ages and adult cardiometabolic traits.

Methods

We retrieved genetic instrument variables (IVs) for exposures (standardized BMI at newborn, infant, toddler and late childhood), cardiometabolic traits and potential confounders or mediators (adult BMI, SHBG, testosterone and age at menarche) from the corresponding genome-wide association analysis. We performed univariate and multivariable Mendelian randomization (MR) to dissect associations between age-specific childhood BMI and adult cardiometabolic outcomes. Odds ratio was used to present the direction of the causal association.

Results

In univariate MR, higher newborn BMI was causally associated with reduced risk for type 2 diabetes in women. Late childhood BMI was associated with increased risk for female diabetes and coronary artery disease (CAD), myocardial infarction (MI), and chronic kidney disease (CKD) in general population. Among these associations, only association between late childhood BMI with MI remained significant after adjusting for adult male BMI and sex hormones, (OR = 1.120, 95% CI 1.023-1.226, p = 0.014). Besides, in multivariable MR, we found evidence for causal association between newborn BMI with reduced risk for CAD (OR = 0.862, 95% CI 0.751-0.989, p = 0.034) and MI (OR = 0.864, 95% CI 0.752-0.991, p = 0.037) in men. No obvious impact of infant or toddler BMI was identified on the above-mentioned diseases. For continuous cardiometabolic traits, in all age epochs except infant, higher BMI was associated with increased level of fasting glucose in women.

Conclusion

BMI at birth and late childhood exerts different impact on adult cardiometabolic diseases, while BMI at infant and toddler ages is not causally associated with these outcomes. The effect of childhood BMI may be influenced by sex disparities.

DASES: a database of alternative splicing for esophageal squamous cell carcinoma

Esophageal carcinoma ranks as the sixth leading cause of cancer-related mortality globally, with esophageal squamous cell carcinoma (ESCC) being particularly prevalent among Asian populations. Alternative splicing (AS) plays a pivotal role in ESCC development and progression by generating diverse transcript isoforms. However, the current landscape lacks a specialized database focusing on alternative splicing events (ASEs) derived from a large number of ESCC cases. Additionally, most existing AS databases overlook the contribution of long non-coding RNAs (lncRNAs) in ESCC molecular mechanisms, predominantly focusing on mRNA-based ASE identification. To address these limitations, we deployed DASES (http://www.hxdsjzx.cn/DASES). Employing a combination of publicly available and in-house ESCC RNA-seq datasets, our extensive analysis of 346 samples, with 93% being paired tumor and adjacent non-tumor tissues, led to the identification of 257 novel lncRNAs in esophageal squamous cell carcinoma. Leveraging a paired comparison of tumor and adjacent normal tissues, DASES identified 59,094 ASEs that may be associated with ESCC. DASES fills a critical gap by providing comprehensive insights into ASEs in ESCC, encompassing lncRNAs and mRNA, thus facilitating a deeper understanding of ESCC molecular mechanisms and serving as a valuable resource for ESCC research communities.

The Causal Association of Irritable Bowel Syndrome with Multiple Disease Outcomes: A Phenome-Wide Mendelian Randomization Study

BACKGROUND

This study aimed to identify novel associations between irritable bowel syndrome (IBS) and a broad range of outcomes.

METHODS

In total, 346,352 white participants in the U.K. Biobank were randomly divided into two halves, in which a genome-wide association study (GWAS) of IBS and a polygenic risk score (PRS) analysis of IBS using GWAS summary statistics were conducted, respectively. A phenome-wide association study (PheWAS) based on the PRS of IBS was performed to identify disease outcomes associated with IBS. Then, the causalities of these associations were tested by both one-sample (individual-level data in U.K. Biobank) and two-sample (publicly available summary statistics) Mendelian randomization (MR). Sex-stratified PheWAS-MR analyses were performed in male and female, separately.

RESULTS

Our PheWAS identified five diseases associated with genetically predicted IBS. Conventional MR confirmed these causal associations between IBS and depression (OR: 1.07, 95%CI: 1.01-1.14, p = 0.02), diverticular diseases of the intestine (OR: 1.13, 95%CI: 1.08-1.19, p = 3.00 × 10^-6), gastro-esophageal reflux disease (OR: 1.09, 95%CI: 1.05-1.13, p = 3.72 × 10^-5), dyspepsia (OR: 1.21, 95%CI: 1.13-1.30, p = 9.28 × 10^-8), and diaphragmatic hernia (OR: 1.10, 95%CI: 1.05-1.15, p = 2.75 × 10^-5). The causality of these associations was observed in female only, but not men.

CONCLUSIONS

Increased risks of IBS is found to cause a series of disease outcomes. Our findings support further investigation on the clinical relevance of increased IBS risks with mental and digestive disorders.

Pediatric allergic rhinitis with functional gastrointestinal disease: Associations with the intestinal microbiota and gastrointestinal peptides and therapeutic effects of interventions

Children are susceptible to allergic rhinitis (caused by external allergens) accompanied by functional gastrointestinal disease, which seriously affects physical and mental health. Antihistamines and nasal spray hormones are commonly used in clinical treatment, but these drugs often have unsatisfactory efficacy and result in high recurrence rates. Therefore, understanding the pathogenesis of allergic rhinitis with functional gastrointestinal disease and seeking safer treatment and prevention methods is essential. Herein, molecular ecology and immunoassays were used to analyze correlations between pediatric allergic rhinitis with functional gastrointestinal disease and both the intestinal microbiota and gastrointestinal peptide levels. Fifty healthy children (healthy group) and 80 children with allergic rhinitis with functional gastrointestinal disease (case group: evenly divided into a control group (conventional drug therapy) and an intervention group (conventional drug therapy + glutamine+probiotics)), were enrolled. Bifidobacterium and Lactobacillus counts and the gastrin and motilin levels were lower in the case group than in the healthy group, whereas Enterobacter, yeast, and Enterococcus counts and the somatostatin, serotonin, and vasoactive intestinal peptide levels were higher. Post treatment, intestinal microbiota indices, gastrointestinal peptide levels, and intestinal barrier function were better in the intervention group than in the control group (p < 0.05). The intervention group had a significantly higher total therapeutic response rate (95.00%) than the control group (77.50%). The intestinal microbiota was closely associated with gastrointestinal peptide levels. Treatment with glutamine and probiotics regulated these levels, re-established balance in the intestinal microbiota, and restored intestinal barrier function.

The impacts of gene polymorphisms on methotrexate in Chinese psoriatic patients

BACKGROUND

Methotrexate (MTX) is the first-line treatment for psoriasis in China. The metabolic processes of MTX include various proteins and genes. Previous studies have shown that gene polymorphisms had significant impacts on the efficacy of MTX. However, the influence of gene polymorphisms has not been reported in the Chinese psoriatic patients.

OBJECTIVE

The aim of this study was to verify the impacts of candidate genes polymorphisms on the effectiveness of MTX in a Chinese psoriatic population.

METHODS

In this study, we enrolled 259 psoriasis patients from two clinical centres. Each of them received MTX treatment at 7.5-15 mg/week for at least 8 weeks. Patients were stratified as responders and non-responders according to whether the Psoriasis Area and Severity Index score declined more than 75% (PASI75). According to previous reports, 16 single nucleotide polymorphisms (SNPs) were selected and genotyped for each patient using the Sequenom platform. Fisher's exact test, the chi-square test, Mann-Whitney tests and ANOVA analyses were used for statistical analysis.

RESULTS

Among 259 patients, there were 182 males and 77 females, 63 patients with psoriatic arthritis and 196 patients without arthritis phenotype, and the age of all patients ranged from 19 to 70 years (49.7 ± 13.6). The baseline PASI value of patients was 13.8 ± 8.5, and 33.2% of patients achieved a PASI75 response after MTX treatment. Patients carrying the ATP-binding cassette subfamily B member 1 gene (ABCB1) rs1045642 TT genotype were associated with more severe psoriasis skin lesion (P = 0.032). Furthermore, the ABCB1 rs1045642 TT genotype was found to be more frequent in non-responders (P = 0.017), especially in moderate-to-severe patients (P = 0.002) and patients without psoriatic arthritis (P = 0.026) after MTX treatment.

CONCLUSION

We have demonstrated for the first time that polymorphism of the ABCB1 rs1045642 TT genotype is predictive of a worse clinical response of skin lesions to MTX therapy in a Chinese psoriatic population.

Method to retrieve aerosol extinction profiles and aerosol scattering phase functions with a modified CCD laser atmospheric detection system

Vertical distributions of ambient aerosols and their corresponding optical properties are crucial to the assessment of aerosol radiative effects. Traditionally, ambient aerosol phase function is assumed as a constant of input parameter in the retrieval of the vertical distribution of aerosol optical characteristics from remote sensing measurements (e.g. lidar or camera-laser based instruments). In this work, sensitivity studies revealed that using constant aerosol phase function assumptions in the algorithm would cause large uncertainties. Therefore, an improved retrieval method was established to simultaneously measure ambient aerosol scattering phase functions and aerosol scattering function profiles with a modified charge-coupled device-laser aerosol detection system (CLADS), which are then combined to yield vertical profiles of aerosol extinction coefficients. This method was applied and evaluated in a comprehensive field campaign in the North China Plain during January 2016. The algorithm showed robust performance and was able to capture temporal variations in ambient aerosol scattering phase functions and aerosol scattering function profiles. Aerosol extinction coefficients derived with simultaneously measured aerosol phase functions agreed well with in-situ measurements, indicating that uncertainties in the retrieval of aerosol extinction vertical profiles have been significantly reduced by using the proposed method with the modified CLADS. The advantage of this modified CLADS is that it can accomplish these aerosol measurements independent of other supplementary instruments. Benefiting from its low cost and high spatial resolution (∼1 m on average) in the boundary layer, this measurement system can play an important role in the research of aerosol vertical distributions and its impacts on environmental and climatic studies.

Amplicon-based next-generation sequencing of plasma cell-free DNA for detection of driver and resistance mutations in advanced non-small cell lung cancer

Background

Genomic analysis of plasma cell-free DNA is transforming lung cancer care; however, available assays are limited by cost, turnaround time, and imperfect accuracy. Here, we study amplicon-based plasma next-generation sequencing (NGS), rather than hybrid-capture-based plasma NGS, hypothesizing this would allow sensitive detection and monitoring of driver and resistance mutations in advanced non-small cell lung cancer (NSCLC).

Patients and methods

Plasma samples from patients with NSCLC and a known targetable genotype (EGFR, ALK/ROS1, and other rare genotypes) were collected while on therapy and analyzed blinded to tumor genotype. Plasma NGS was carried out using enhanced tagged amplicon sequencing of hotspots and coding regions from 36 genes, as well as intronic coverage for detection of ALK/ROS1 fusions. Diagnostic accuracy was compared with plasma droplet digital PCR (ddPCR) and tumor genotype.

Results

A total of 168 specimens from 46 patients were studied. Matched plasma NGS and ddPCR across 120 variants from 80 samples revealed high concordance of allelic fraction (R2 = 0.95). Pretreatment, sensitivity of plasma NGS for the detection of EGFR driver mutations was 100% (30/30), compared with 87% for ddPCR (26/30). A full spectrum of rare driver oncogenic mutations could be detected including sensitive detection of ALK/ROS1 fusions (8/9 detected, 89%). Studying 25 patients positive for EGFR T790M that developed resistance to osimertinib, 15 resistance mechanisms could be detected including tertiary EGFR mutations (C797S, Q791P) and mutations or amplifications of non-EGFR genes, some of which could be detected pretreatment or months before progression.

Conclusions

This blinded analysis demonstrates the ability of amplicon-based plasma NGS to detect a full range of targetable genotypes in NSCLC, including fusion genes, with high accuracy. The ability of plasma NGS to detect a range of preexisting and acquired resistance mechanisms highlights its potential value as an alternative to single mutation digital PCR-based plasma assays for personalizing treatment of TKI resistance in lung cancer.

LncRNA ZNF667-AS1 inhibits inflammatory response and promotes recovery of spinal cord injury via suppressing JAK-STAT pathway

OBJECTIVE

The aim of this study was to explore the role of lncRNA ZNF667-AS1 in the recovery of spinal cord injury (SCI), and to investigate its underlying mechanism.

MATERIALS AND METHODS

Mice were randomly assigned to the SCI group, the sham group and the lncRNA ZNF667-AS1 group, with 10 mice in each group. With Infinite Horizon device at a dose of 80 Kdyn, mice in the SCI group and the lncRNA ZNF667-AS1 group experienced SCI by an acute hit on the C5 spinous process. Before animal procedures, mice in the lncRNA ZNF667-AS1 group were additionally injected with overexpression lentivirus of lncRNA ZNF667-AS1. On the contrary, mice in the sham group only received laminectomy. After successful construction of the SCI model in mice, grip strength was accessed. LncRNA ZNF667-AS1 expression in spinal cord tissues before and after SCI was detected by quantitative Real Time-Polymerase Chain Reaction (qRT-PCR), respectively. Meanwhile, the protein expression levels of relative genes in Janus Kinase-signal transducer and activator of transcription (JAK-STAT) pathway were detected by Western blot.

RESULTS

Grip strength of forelimb in the SCI group recovered significantly slower than that of the sham group. With the prolongation of SCI, the expression of lncRNA ZNF667-AS1 was gradually decreased. However, the expression levels of JAK2, STAT3 and iNOS were upregulated in a time-dependent manner. In addition, mice in the lncRNA ZNF667-AS1 group presented remarkable grip strength recovery of forelimb after SCI.

CONCLUSIONS

LncRNA ZNF667-AS expression is gradually downregulated after SCI. Meanwhile, it inhibits the inflammatory response and promotes SCI recovery via suppressing the JAK-STAT pathway.

Smart identification of psoriasis by images using convolutional neural networks: a case study in China

BACKGROUND

Psoriasis is a chronic inflammatory skin disease, which holds a high incidence in China. However, professional dermatologists who can diagnose psoriasis early and correctly are insufficient in China, especially in the rural areas. A smart approach to identify psoriasis by pictures would be highly adaptable countrywide and could play a useful role in early diagnosis and regular treatment of psoriasis.

OBJECTIVES

Design and evaluation of a smart psoriasis identification system based on clinical images (without relying on a dermatoscope) that works effectively similar to a dermatologist.

METHODS

A set of deep learning models using convolutional neural networks (CNNs) was explored and compared in the system for automatic identification of psoriasis. The work was carried out on a standardized dermatological dataset with 8021 clinical images of 9 common disorders including psoriasis along with full electronic medical records of patients built over the last 9 years in China. A two-stage deep neural network was designed and developed to identify psoriasis. In the first stage, a multilabel classifier was trained to learn the visual patterns for each individual skin disease. In the second stage, the output of the first stage was utilized to distinguish psoriasis from other skin diseases.

RESULTS

The area under the curve (AUC) of the two-stage model reached 0.981 ± 0.015, which outperforms a single-stage model. And, the classifier showed superior performance (missed diagnosis rate: 0.03, misdiagnosis rate: 0.04) than 25 Chinese dermatologists (missed diagnosis rate: 0.19, misdiagnosis rate: 0.10) in the diagnosis of psoriasis on 100 clinical images.

CONCLUSIONS

Using clinical images to identify psoriasis is feasible and effective based on CNNs, which also builds a solid technical base for smart care of skin diseases especially psoriasis using mobile/tablet applications for teledermatology in China.

A microRNA expression signature as a predictor of survival for colon adenocarcinoma

Colon cancer is a major cause of cancer mortality worldwide and most colon cancers are adenocarcinoma. MicroRNA (miRNA) expression signature has been shown to be able to predict progression and prognosis of various cancers. The aim of our study was to explore a novel signature of microRNA expression for predicting survival of colon adenocarcinoma patients. By analyzing the miRNA expression profiles and clinical information of 329 colon adenocarcinoma patients derived from The Cancer Genome Atlas database. 129 miRNAs were identified to be expressed differentially between the cancer and adjacent tissues. Among them, 27 miRNAs were found to be associated with the corresponding clinical characteristics of the patients. Furthermore, 7 miRNAs (let-7a-2, mir-32, mir-181a-1, mir-197, mir-328, mir-505 and mir-652) were found to be significantly correlated with the patient survival. The risk established by the 7-miRNA signature we built was proved be an independent prognostic factor (Hazard ratio [HR] = 2.048; 95% CI = 1.144-3.664; p, 0.016). In summary, our study identified miRNAs correlated with progression and prognosis of colon adenocarcinoma and built a 7-microRNA expression signature for prediction of the survival of the patients with colon adenocarcinoma.

Cytotoxic effect of oxaloacetate on HepG2-human hepatic carcinoma cells via apoptosis and ROS accumulation

Oxaloacetate (OA) is one of the intermediates of the Krebs cycle. In addition to its role in energy production, OA may have other effects on the cell. We report here that OA could have a cell type dependent cytotoxic effect on the human hepatic carcinoma cell line HepG2 through induction of apoptosis and reactive oxygen species (ROS) accumulation. In our study, OA decreased the viability and colony formation of HepG2 cells and induced cell death. Caspase-3 activity was increased, the pro-apoptotic protein Bax was up-regulated, and the anti-apoptotic protein Bcl-2 was down-regulated in OA-treated HepG2 cells indicating that apoptosis through the intrinsic pathway was involved in the cell death. The ROS level in OA-treated HepG2 cells was increased. The anti-oxidant N-acetylcysteine (NAC) and glutathione (GSH) prevented the OA-induced decrease in cell but did not alter the enhanced apoptotic Bax/Bcl-2 mRNA ratio. These results suggest that the OA-induced apoptosis of HepG2 cell is not driven by oxidative damage and at least two distinct mechanisms, one mediated by ROS and one involving apoptosis, result in the cytotoxic effects of OA on HepG2 cells. These studies expand the biological functional repertoire of OA and provide a mechanism by which hepatocellular carcinoma may be targeted by OA.

Modelling and characterisation of a ultrasound-actuated needle for improved visibility in ultrasound-guided regional anaesthesia and tissue biopsy

Clear needle visualisation is recognised as an unmet need for ultrasound guided percutaneous needle procedures including regional anaesthesia and tissue biopsy. With inadequate needle visibility, these procedures may result in serious complications or a failed operation. This paper reports analysis of the modal behaviour of a previously proposed ultrasound-actuated needle configuration, which may overcome this problem by improving needle visibility in colour Doppler imaging. It uses a piezoelectric transducer to actuate longitudinal resonant modes in needles (outer diameter 0.8-1.2mm, length>65mm). The factors that affect the needle's vibration mode are identified, including the needle length, the transducer's resonance frequency and the gripping position. Their effects are investigated using finite element modelling, with the conclusions validated experimentally. The actuated needle was inserted into porcine tissue up to 30mm depth and its visibility was observed under colour Doppler imaging. The piezoelectric transducer is able to generate longitudinal vibration with peak-to-peak amplitude up to 4μm at the needle tip with an actuating voltage of 20Vpp. Actuated in longitudinal vibration modes (distal mode at 27.6kHz and transducer mode at 42.2kHz) with a drive amplitude of 12-14Vpp, a 120mm needle is delineated as a coloured line in colour Doppler images, with both needle tip and shaft visualised. The improved needle visibility is maintained while the needle is advanced into the tissue, thus allowing tracking of the needle position in real time. Moreover, the needle tip is highlighted by strong coloured artefacts around the actuated needle generated by its flexural vibration. A limitation of the technique is that the transducer mode requires needles of specific lengths so that the needle's resonance frequency matches the transducer. This may restrict the choice of needle lengths in clinical applications.

CD147 interacts with NDUFS6 in regulating mitochondrial complex I activity and the mitochondrial apoptotic pathway in human malignant melanoma cells

Malignant melanoma (MM) is one of the most lethal tumors and is characterized by high invasiveness, frequent metastasis, and resistance to chemotherapy. The risk of metastatic MM is accompanied by disordered energy metabolism involving the oxidative phosphorylation (OXPHOS) process, which is largely carried out in mitochondrial complexes. Complex I is the first and largest mitochondrial enzyme complex associated with this process. CD147 is a transmembrane glycoprotein mainly expressed on the cell surface, and also appears in the cytoplasm in some tumors. We found that CD147 is often translocated to the cytoplasm in metastatic MM specimens as compared to primary MM. We also demonstrated high expression of CD147 in isolated mitochondrial fractions of A375 cells. The yeast two-hybrid (Y2H) assay identified NDUFS6 (which encodes a subunit of mitochondrial respiratory chain complex I) as a candidate that interacts with CD147 and depletion of CD147 in A375 cells significantly decreased complex I enzyme activity. We also showed that CD147 increased the viability of A375 cells exposed to berberine-induced mitochondrial damage, and protected them from apoptosis through a mitochondrial-dependent pathway. This finding was confirmed by adding exogenous Bcl-2 to A375 cell cultures. In summary, our results identify the existence of CD147 in human melanoma cell mitochondria. They indicate that CD147 appears to regulate complex I activity and apoptosis in MM by interacting with mitochondrial NDUFS6. Our findings provide new insight into the function of CD147 and identify it as a promising therapeutic target in melanoma through disruption of the energy metabolism.