Growth inhibition of subcutaneous tumor with glioma cells in nude mice by silencing TLR4.

This study investigated the regulatory impact of Toll-like receptor 4 (TLR4) gene on glioma cell proliferation and apoptosis, elucidating the molecular mechanisms underlying TLR4-induced growth inhibition in vivo. U-87MG-Sh and U-87MG-NC cells, with silenced TLR4 and negative control plasmid respectively, were established. Eighteen nude mice, divided into transfection, negative control, and blank control groups, were inoculated with corresponding cells. Over four weeks, the transfection group exhibited significantly reduced tumor growth rates, smaller mass and volume, and lower growth activity compared to controls. Histological analysis revealed sparse tumor cells, increased fibrous connective tissue, and slower angiogenesis in the transfection group. Flow cytometry demonstrated a lower proliferation index and increased G0/1 cell count in the transfection group. mRNA levels of TLR4, NF-κB, and CyclinD1 were significantly lower in the transfection group. TLR4 silencing correlated with U-87MG cell proliferation regulation, growth inhibition, NF-κB and CyclinD1 modulation, and induction of cell cycle arrest and apoptosis. These findings suggest TLR4 as a potential gene therapy target for glioma.

A missing jigsaw within the hygiene hypothesis: Low-dose bisphenol A exposure attenuates lipopolysaccharide-induced asthma protection.

The rising occurrence of allergic asthma in early life across industrialized countries suggests that environmental factors play a crucial role in determining asthma susceptibility and severity. While prior exposure to microbial lipopolysaccharides (LPSs) has been found to offer protection against allergic asthma, infants residing in urban environments are increasingly exposed to environmental pollutants. Utilizing limulus lysate test screens and virtual screening models, we identified pollutants that can modulate LPS bioactivity. This investigation revealed that bisphenol A (BPA), a chemical commonly used in numerous household items and previously implicated in obesity and cancer, effectively neutralizes LPS. In-depth mechanistic analyses showed that BPA specifically binds to the lipid A component of LPS, leading to inactivation. This interaction eliminates the immunostimulatory activity of LPS, making mice more susceptible to house dust mite (HDM)-induced allergic asthma. BPA reactivates lung epithelial cells, consequently amplifying type 2 responses to HDMs in dendritic cells. This chemical interplay provides new insights into the pathophysiology of asthma in relation to human exposure. Understanding the intricate relationships between environmental chemicals and microbial antigens, as well as their impacts on innate immunity, is critical for the development of intervention strategies to address immune disorders resulting from urbanization.

Signalling by senescent melanocytes hyperactivates hair growth.

Niche signals maintain stem cells in a prolonged quiescence or transiently activate them for proper regeneration1. Altering balanced niche signalling can lead to regenerative disorders. Melanocytic skin nevi in human often display excessive hair growth, suggesting hair stem cell hyperactivity. Here, using genetic mouse models of nevi2,3, we show that dermal clusters of senescent melanocytes drive epithelial hair stem cells to exit quiescence and change their transcriptome and composition, potently enhancing hair renewal. Nevus melanocytes activate a distinct secretome, enriched for signalling factors. Osteopontin, the leading nevus signalling factor, is both necessary and sufficient to induce hair growth. Injection of osteopontin or its genetic overexpression is sufficient to induce robust hair growth in mice, whereas germline and conditional deletions of either osteopontin or CD44, its cognate receptor on epithelial hair cells, rescue enhanced hair growth induced by dermal nevus melanocytes. Osteopontin is overexpressed in human hairy nevi, and it stimulates new growth of human hair follicles. Although broad accumulation of senescent cells, such as upon ageing or genotoxic stress, is detrimental for the regenerative capacity of tissue4, we show that signalling by senescent cell clusters can potently enhance the activity of adjacent intact stem cells and stimulate tissue renewal. This finding identifies senescent cells and their secretome as an attractive therapeutic target in regenerative disorders.

Dimethylation of histone H3 lysine 36 (H3K36me2) as a potential biomarker for glioma diagnosis, grading, and prognosis.

Abnormal histone methylation plays a key role in glioma development but the clinical value of specific alterations is still unclear. Here, the potential significance of histone H3 lysine 36 dimethylation (H3K36me2) was investigated as a biomarker for glioma. Seventy-three glioma patients were included in the study and the level of H3K36me2 in the tumor tissues was determined by immunohistochemistry. The χ2 test was used to explore the influence of clinical and pathological characteristics on H3K36me2 levels. The Kaplan-Meier method was used to estimate progression-free survival (PFS) and overall survival (OS). COX regression was used to explore the relationship between H3K36me2 levels and glioma prognosis. The results indicated that the H3K36me2 level increases with glioma grade. The proportion of high H3K36me2 levels was lower in glioma patients under the age of 52 years. H3K36me2 levels were negatively correlated with IDH1 mutation and MGMT promoter methylation, and positively correlated with p53 expression. Thus, high H3K36me2 levels positively correlated with poor prognosis of gliomas. In conclusion, H3K36me2 may be considered as a potential biomarker for glioma diagnosis, grading, and prognosis, but the overall clinical value of H3K36me2 determination deserves further investigation. These results may have important implications for accurate diagnosis and future precision treatment of gliomas.

Significance of differential expression of OLFM4 in the development of endometrial adenocarcinoma.

The incidence of endometrial adenocarcinoma (EA) has increased worldwide in recent years due to the widespread use of estrogen therapy and the overall increase in life expectancy. However, we know of no sensitive molecular index that can be used to predict the onset of EA, evaluate the therapeutic effects of treatment agents, or provide prognostic benefit in post-treatment follow-up. To explore the correlation between human olfactomedin 4 (OLFM4) and the clinicopathologic parameters of EA, and to determine the precise involvement of OLFM4 as a related factor in the occurrence and development of EA. We enrolled 61 gynecologic patients for a retrospective study at the Tai'an Central Hospital of Shandong Province from January 1, 2016, to June 30, 2022. We determined the expression levels of estrogen receptor α (ERα), progesterone receptor (PR), and OLFM4 proteins in endometrial tissue with the immunohistochemical S-P staining method, and analyzed the correlations among ERα, PR, and OLFM4 protein expression levels and with the pathologic stage, histologic grade, myometrial invasiveness, and lymphatic metastasis of EA. The expression levels of OLFM4 in EA were higher than in normal endometrium (P = .036). The expression level of OLFM4 protein in stage II-III patients was higher than that in stage I patients (P = .034), and the expression levels of ERα and PR proteins in EA were lower than those in normal endometrial tissue (P = .014 and P = .0005). While we observed no correlation in endometrial tissues of disparate pathologic types between OLFM4 and the expression levels of ERα and PR proteins, we noted a positive correlation between the expression levels of ERα and PR protein. The expression level of OLFM4 protein increased with the malignant degree of endometrial lesions and OLFM4 protein expression was related to the FIGO stage of EA. And OLFM4 protein can be used as 1 of the potential diagnostic factors for endometrial lesions, which is worthy of further study.

CYLD variants identified in Alzheimer's disease and frontotemporal dementia patients.

OBJECTIVES: CYLD was a novel causative gene for frontotemporal dementia (FTD) and amyotrophic lateral sclerosis. Given the clinical and pathological overlap of FTD and Alzheimer's disease (AD), it is necessary to screen CYLD in AD patients and FTD patients in the Chinese population. METHODS: In our study, using a targeted sequencing panel, we sequenced the CYLD gene in a large cohort of 2485 participants in the Chinese population, including 1008 AD patients, 105 FTD patients, and 1372 controls. RESULTS: In the present study, the average onset age of AD and FTD patients was 66.84 ± 30.42 years old and 60 ± 10.00 years old, respectively. Our study reported three novel CYLD variants: p.Phe288Leu (patient No. 1, AD), p.Tyr485Phe (patients No. 6-9, all AD) and p.Thr951Ala (patient No. 10, AD), plus a previously reported variant: p.Arg397Ser (patient No. 2-5, AD and No. 11, FTD). These variants were absent in our in-house controls and predicted to be deleterious according to the MutationTaster. The variant carriers were composed of 10 AD patients and one FTD patient, and the average onset age was 61.2 ± 10.9 years. The frequency of CYLD variants in AD was similar to that in FTD, which was 0.99% (10/1008) and 0.95% (1/105), respectively. INTERPRETATION: Our finding extended the genotype and phenotype of the CYLD gene and demonstrated that CYLD rare damaging variants may be implicated in AD and FTD pathogenesis.

Single-cell analysis of human basal cell carcinoma reveals novel regulators of tumor growth and the tumor microenvironment.

How basal cell carcinoma (BCC) interacts with its tumor microenvironment to promote growth is unclear. We use singe-cell RNA sequencing to define the human BCC ecosystem and discriminate between normal and malignant epithelial cells. We identify spatial biomarkers of tumors and their surrounding stroma that reinforce the heterogeneity of each tissue type. Combining pseudotime, RNA velocity-PAGA, cellular entropy, and regulon analysis in stromal cells reveals a cancer-specific rewiring of fibroblasts, where STAT1, TGF-ß, and inflammatory signals induce a noncanonical WNT5A program that maintains the stromal inflammatory state. Cell-cell communication modeling suggests that tumors respond to the sudden burst of fibroblast-specific inflammatory signaling pathways by producing heat shock proteins, whose expression we validated in situ. Last, dose-dependent treatment with an HSP70 inhibitor suppresses in vitro vismodegib-resistant BCC cell growth, Hedgehog signaling, and in vivo tumor growth in a BCC mouse model, validating HSP70's essential role in tumor growth and reinforcing the critical nature of tumor microenvironment cross-talk in BCC progression.

Anesthetic management for cesarean section in parturient with an uncorrected single ventricle: A case report and literature review.

RATIONALE: Patients with a single ventricle, who have not undergone surgery, reportedly have a lower survival rate. Furthermore, multiple pregnancies are rare among these females. We reported a case of anesthesia management of cesarean section in an uncorrected single-ventricular multi-pregnancy woman and review the anesthesia management of the published similar cases. PATIENT CONCERNS: An uncorrected single ventricular pregnant woman with a cardiac function of New York Heart Association class II, who had experienced one spontaneous abortion and three vaginal deliveries, was scheduled for cesarean section at 37+6 weeks of gestation. DIAGNOSES: : Echocardiography revealed a complex congenital heart disease in the mother: a single ventricle (the left ventricle is dominant), atrioventricular valve ectopic, double-inlet left ventricle, abnormal location of the great arteries, probably pulmonary stenosis, atrial septal defect, and left-to-right shunt. The fetus was in breech presentation with umbilical cord around the neck. INTERVENTIONS: Cesarean section was successfully performed under the combined spinal epidural anesthesia with careful monitoring. OUTCOMES: : Both mother and newborn recovered good and were discharged from the hospital 5 days after surgery without any adverse reactions. LESSONS: Single ventricular pregnant woman with a cardiac function of New York Heart Association class I-II could tolerate pregnancy and delivery well. Both general and regional anesthesia are applicable to cesarean section in these patients. The principle of anesthesia management is to maintain the appropriate balance between systemic vascular resistance and pulmonary vascular resistance, as well as to maintain preload and cardiac output.

KAT6B May Be Applied as a Potential Therapeutic Target for Glioma.

Glioma is a prevalent malignancy among brain tumors with high modality and low prognosis. Ferroptosis has been identified to play a crucial role in the progression and treatment of cancers. KAT6B, as a histone acetyltransferase, is involved in multiple cancer development. However, the function of KAT6B in glioma is still elusive. Here, we aimed to evaluate the effect of KAT6B on ferroptosis in glioma cells and explored the potential mechanisms. We observed that the expression of KAT6B was enhanced in clinical glioma samples. The viability of glioma cells was repressed by erastin and the overexpression of KAT6B rescued the phenotype in the cells. Meanwhile, the apoptosis of glioma cells was induced by the treatment of erastin, while the overexpression of KAT6B blocked the effect in the cells. The levels of lipid ROS and iron were promoted by the treatment of erastin and the overexpression of KAT6B could reverse the effect in the cells. Mechanically, we identified that the expression of STAT3 was repressed by the KAT6B knockdown in glioma cells. The KAT6B was able to enrich on the promoter of STAT3 in glioma cells. Meanwhile, ChIP assay showed that the knockdown of KAT6B inhibited the enrichment of histone H3 lysine 23 acetylation (H3K23ac) and RNA polymerase II (RNA pol II) on STAT3 promoter in the cells. Depletion of STAT3 reversed KAT6B-regulated viability, apoptosis, and ferroptosis of glioma cells. Thus, we concluded that KAT6B contributes to glioma progression by repressing ferroptosis via epigenetically inducing STAT3.

Automatic inverse treatment planning of Gamma Knife radiosurgery via deep reinforcement learning.

PURPOSE: Several inverse planning algorithms have been developed for Gamma Knife (GK) radiosurgery to determine a large number of plan parameters by solving an optimization problem, which typically consists of multiple objectives. The priorities among these objectives need to be repetitively adjusted to achieve a clinically good plan for each patient. This study aimed to achieve automatic and intelligent priority tuning by developing a deep reinforcement learning (DRL)-based method to model the tuning behaviors of human planners. METHODS: We built a priority-tuning policy network using deep convolutional neural networks. Its input was a vector composed of multiple plan metrics that were used in our institution for GK plan evaluation. The network can determine which tuning action to take based on the observed quality of the intermediate plan. We trained the network using an end-to-end DRL framework to approximate the optimal action-value function. A scoring function was designed to measure the plan quality to calculate the received reward of a tuning action. RESULTS: Vestibular schwannoma was chosen as the test bed in this study. The number of training, validation and testing cases were 5, 5, and 16, respectively. For these three datasets, the average scores of the initial plans obtained with the same initial priority set were 3.63 ± 1.34, 3.83 ± 0.86 and 4.20 ± 0.78, respectively, while they were improved to 5.28 ± 0.23, 4.97 ± 0.44 and 5.22 ± 0.26 through manual priority tuning by human expert planners. Our network achieved competitive results with 5.42 ± 0.11, 5.10 ± 0. 42, 5.28 ± 0.20, respectively. CONCLUSIONS: Our network can generate GK plans of comparable or slightly higher quality than the plans generated by human planners via manual priority tuning for vestibular schwannoma cases. The network can potentially be incorporated into the clinical workflow as planning assistance to improve GK planning efficiency and help to reduce plan quality variation caused by interplanner variability. We also hope that our method can reduce the workload of GK planners and allow them to spend more time on more challenging cases.

MRI classification using semantic random forest with auto-context model.

BACKGROUND: It is challenging to differentiate air and bone on MR images of conventional sequences due to their low contrast. We propose to combine semantic feature extraction under auto-context manner into random forest to improve reasonability of the MRI segmentation for MRI-based radiotherapy treatment planning or PET attention correction. METHODS: We applied a semantic classification random forest (SCRF) method which consists of a training stage and a segmentation stage. In the training stage, patch-based MRI features were extracted from registered MRI-CT training images, and the most informative elements were selected via feature selection to train an initial random forest. The rest sequence of random forests was trained by a combination of MRI feature and semantic feature under an auto-context manner. During segmentation, the MRI patches were first fed into these random forests to derive patch-based segmentation. By using patch fusion, the final end-to-end segmentation was obtained. RESULTS: The Dice similarity coefficient (DSC) for air, bone and soft tissue classes obtained via proposed method were 0.976±0.007, 0.819±0.050 and 0.932±0.031, compared to 0.916±0.099, 0.673±0.151 and 0.830±0.083 with random forest (RF), and 0.942±0.086, 0.791±0.046 and 0.917±0.033 with U-Net. SCRF also outperformed the competing methods in sensitivity and specificity for all three structure types. CONCLUSIONS: The proposed method accurately segmented bone, air and soft tissue. It is promising in facilitating advanced MR application in diagnosis and therapy.

Generation and Effect Testing of a SARS-CoV-2 RBD-Targeted Polyclonal Therapeutic Antibody Based on a 2-D Airway Organoid Screening System.

Coronavirus disease 2019 (COVID-19) is an acute respiratory infectious disease caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The US FDA has approved several therapeutics and vaccines worldwide through the emergency use authorization in response to the rapid spread of COVID-19. Nevertheless, the efficacies of these treatments are being challenged by viral escape mutations. There is an urgent need to develop effective treatments protecting against SARS-CoV-2 infection and to establish a stable effect-screening model to test potential drugs. Polyclonal antibodies (pAbs) have an intrinsic advantage in such developments because they can target rapidly mutating viral strains as a result of the complexity of their binding epitopes. In this study, we generated anti-receptor-binding domain (anti-RBD) pAbs from rabbit serum and tested their safety and efficacy in response to SARS-CoV-2 infection both in vivo and ex vivo. Primary human bronchial epithelial two-dimensional (2-D) organoids were cultured and differentiated to a mature morphology and subsequently employed for SARS-CoV-2 infection and drug screening. The pAbs protected the airway organoids from viral infection and tissue damage. Potential side effects were tested in mouse models for both inhalation and vein injection. The pAbs displayed effective viral neutralization effects without significant side effects. Thus, the use of animal immune serum-derived pAbs might be a potential therapy for protection against SARS-CoV-2 infection, with the strategy developed to produce these pAbs providing new insight into the treatment of respiratory tract infections, especially for infections with viruses undergoing rapid mutation.

Influence of Tumor Immune Infiltration on Immune Checkpoint Inhibitor Therapeutic Efficacy: A Computational Retrospective Study.

The tumor immune microenvironment (TIME) is likely an important determinant of sensitivity to immune checkpoint inhibitor (ICI) treatment. However, a comprehensive analysis covering the complexity and diversity of the TIME and its influence on ICI therapeutic efficacy is still lacking. Data from 782 samples from 10 ICI clinical trials were collected. To infer the infiltration of 22 subsets of immune cells, CIBERSORTx was applied to the bulk tumor transcriptomes. The associations between each cell fraction and the response to ICI treatment, progression-free survival (PFS) and overall survival (OS) were evaluated, modeling cellular proportions as quartiles. Activity of the interferon-γ pathway, the cytolytic activity score and the MHC score were associated with good prognosis in melanoma. Of the immune cells investigated, M1 macrophages, activated memory CD4+ T cells, T follicular helper (Tfh) cells and CD8+ T cells correlated with response and prolonged PFS and OS, while resting memory CD4+ T cells was associated with unfavorable prognosis in melanoma and urothelial cancer. Consensus clustering revealed four immune subgroups with distinct responses to ICI therapy and survival patterns. The cluster with high proportions of infiltrated CD8+ T cells, activated memory CD4+ T cells, and Tfh cells and low levels of resting memory CD4+ T cells exhibited a higher tumor mutation burden and neoantigen load in melanoma and conferred a higher probability of response and improved survival. Local systemic immune cellular differences were associated with outcomes after ICI therapy. Further investigations of the tumor-infiltrating cellular immune response will lay the foundation for achieving durable efficacy.

Research progress of omics technology in the field of tumor resistance: From single-omics to multi-omics combination application. / ç»„å­¦æŠ€æœ¯åœ¨è‚¿ç˜¤è€è¯é¢†åŸŸçš„ç ”ç©¶è¿›å±•ï¼šä»Žå•ç»„å­¦åˆ°å¤šç»„å­¦è”åˆåº”ç”¨.

Drug resistance is the main obstacle in the treatment of many cancers. It is of great clinical significance to study the mechanism of drug resistance and find new targets. Multi-omics mainly includes genomics, epigenomics, transcriptomics, proteomics, metabolomics, and radiomics. In recent years, the research of tumor resistance has made rapid development, which has significantly accelerated the discovery of new targets.

Rs3802278 in 3'-UTR of SULF1 associated with platinum resistance and survival in Chinese epithelial ovarian cancer patients.

Ovarian cancer is the leading cause of death from gynecologic cancers, but platinum resistance remains a major obstacle in the chemotherapy of ovarian cancer. This study aims to examine the role of polymorphisms in sulfatase 1 (SULF1) in platinum resistance and survival in advanced epithelial ovarian cancer (EOC) patients. We genotyped 12 SNPs of SULF1 in 195 EOC patients treated with platinum using MassARRAY method and evaluated the association between the SNPs and platinum response. SULF1 rs3802278 was marginal significantly associated with platinum resistance in recessive model with p value of 0.055. The patients with SULF1 rs3802278 AA were more resistant to platinum-based chemotherapy comparing to those with AG/GG genotype (OR: 2.317, 95%CI: 0.982 ∼ 5.465). In survival analysis, rs3802278 was significantly associated with both of PFS and OS after adjusted by FIGO stage and age. Patients with AA genotypes showed a shorter PFS and OS than with AG/GG genotypes (median PFS: 15 months vs. 21 months, p = 0.010, HR = 1.876, 95%CI: 1.165-3.022; median OS: 42 months vs. 73 months, p = 0.031, HR = 1.928, 95%CI: 1.061-3.504). SULF1 rs3802278 may serve as a potential candidate biomarker for the prediction of platinum resistance and prognosis in Chinese EOC patients.

A positive feedback loop between mTORC1 and cathelicidin promotes skin inflammation in rosacea.

Rosacea is a chronic inflammatory skin disorder whose pathogenesis is unclear. Here, several lines of evidence were provided to demonstrate that mTORC1 signaling is hyperactivated in the skin, especially in the epidermis, of both rosacea patients and a mouse model of rosacea-like skin inflammation. Both mTORC1 deletion in epithelium and inhibition by its specific inhibitors can block the development of rosacea-like skin inflammation in LL37-induced rosacea-like mouse model. Conversely, hyperactivation of mTORC1 signaling aggravated rosacea-like features. Mechanistically, mTORC1 regulates cathelicidin through a positive feedback loop, in which cathelicidin LL37 activates mTORC1 signaling by binding to Toll-like receptor 2 (TLR2) and thus in turn increases the expression of cathelicidin itself in keratinocytes. Moreover, excess cathelicidin LL37 induces both NF-κB activation and disease-characteristic cytokine and chemokine production possibly via mTORC1 signaling. Topical application of rapamycin improved clinical symptoms in rosacea patients, suggesting mTORC1 inhibition can serve as a novel therapeutic avenue for rosacea.

Inhibition of proliferation and migration and induction of apoptosis in glioma cells by silencing TLR4 expression levels via RNA interference.

The objective of the present study was to investigate the expression levels of toll-like receptor 4 (TLR4) in glioma cells and the mechanisms underlying its regulatory effects on proliferation, migration and apoptosis of glioma cells. A total of three TLR4 silencing short hairpin (sh)RNA plasmids were established, and Lipofectamine® was used to the transfect the human glioma cell line U-87MG. Transfection efficiency was measured via flow cytometry. The interference plasmid exhibiting the largest silencing effect on TLR4 was screened for subsequent experiments using puromycin. Reverse transcription-quantitative PCR and western blot analysis were used to detect the TLR4 gene and protein expression levels, respectively, in stably transfected cells. Flow cytometry measured cell cycle and apoptosis and a wound healing assay was employed to assess the migration ability of transfected cells. The proliferation of transfected cells was detected using Cell Counting Kit-8 assay. TLR4-sh2 exhibited the highest transfection efficiency. Following transfection of U-87MG cells with TLR4-sh2 and negative control (NC) plasmids for 48 h and screening by puromycin, stable transfected cells were named U-87MG-Sh and U-87MG-NC cells respectively. The TLR4 gene and protein expression levels in the U-87MG-Sh cells were significantly lower than in U-87MG and U-87MG-NC cells. The apoptosis rate and the percentage of G0/1 cells were significantly higher, whereas the cell proliferation rate was notably lower, in U-87MG-Sh cells than in the U-87MG-NC and U-87MG cells. The proliferation rate and the cell migration ability of U-87MG-Sh cells were significantly lower than those of U-87MG-NC and U-87MG cells. TLR4 is associated with the proliferation of glioma cells. Inhibition of TLR4 expression levels significantly inhibited proliferation of glioma cells and induced apoptosis. The present study provided insights into the mechanisms associated with the development, progression and invasion ability of glioma cells.

Incorporating SULF1 polymorphisms in a pretreatment CT-based radiomic model for predicting platinum resistance in ovarian cancer treatment.

OBJECTIVE: Early detection of platinum resistance for ovarian cancer treatment remains challenging. This study aims to develop a machine learning model incorporating genomic data such as Single-Nucleotide Polymorphisms (SNPs) of Human Sulfatase 1 (SULF1) with a CT radiomic model based on pre-treatment CT images, to predict platinum resistance for ovarian cancer (OC) treatment. METHODS: A cohort of 102 patients with pathologically confirmed OC was retrospectively enrolled into this study from January 2006 to February 2018. All patients had platinum-based chemotherapy after maximal cyto-reductive surgery. This cohort was separated into two groups according to treatment response, i.e., the group with platinum-resistant disease (PR group) and the group with platinum-sensitive disease (PS group). We genotyped 12 SNPs of SULF1 for all OC patients using Mass Array Method. Radiomic features, SNP data and clinicopathological data of the 102 patients were used to build the differentiation models. The study participants were divided into two cohorts: the training cohort (n = 71) and the validation cohort (n = 31). Feature selection and predictive modeling were performed using least absolute shrinkage and selection operator (LASSO), Random Forest Classifier and Support Vector Machine methods. Model performance for predicting platinum resistance was assessed with respect to its calibration, discrimination, and clinical application. RESULTS: For prediction of platinum resistance, the approach combining the radiomics, clinicopathological data and SNP data demonstrated higher classification efficiency, with an AUC value of 0.993 (95 % CI: 0.83 to 0.98) in the training cohort and 0.967 (95 % CI: 0.83 to 0.98) in validation cohort, than the performance with only the SNPs of SULF1 model (AUC: training, 0.843 [95 %CI: 0.738-0.948]; validation, 0.815 [0.601-1.000]), or with only the radiomic model (AUC: training, 0.874 [95 %CI: 0.789-0.960]; validation, 0.832 [95 %CI: 0.687-0.976]). This integrated approach also showed good calibration and favorable clinical utility. CONCLUSIONS: A predictive model combining pretreatment CT radiomics with genomic data such as SNPs of SULF1 could potentially help to predict platinum resistance in ovarian cancer treatment.

CT-based multi-organ segmentation using a 3D self-attention U-net network for pancreatic radiotherapy.

PURPOSE: Segmentation of organs-at-risk (OARs) is a weak link in radiotherapeutic treatment planning process because the manual contouring action is labor-intensive and time-consuming. This work aimed to develop a deep learning-based method for rapid and accurate pancreatic multi-organ segmentation that can expedite the treatment planning process. METHODS: We retrospectively investigated one hundred patients with computed tomography (CT) simulation scanned and contours delineated. Eight OARs including large bowel, small bowel, duodenum, left kidney, right kidney, liver, spinal cord and stomach were the target organs to be segmented. The proposed three-dimensional (3D) deep attention U-Net is featured with a deep attention strategy to effectively differentiate multiple organs. Performance of the proposed method was evaluated using six metrics, including Dice similarity coefficient (DSC), sensitivity, specificity, Hausdorff distance 95% (HD95), mean surface distance (MSD) and residual mean square distance (RMSD). RESULTS: The contours generated by the proposed method closely resemble the ground-truth manual contours, as evidenced by encouraging quantitative results in terms of DSC, sensitivity, specificity, HD95, MSD and RMSD. For DSC, mean values of 0.91 ± 0.03, 0.89 ± 0.06, 0.86 ± 0.06, 0.95 ± 0.02, 0.95 ± 0.02, 0.96 ± 0.01, 0.87 ± 0.05 and 0.93 ± 0.03 were achieved for large bowel, small bowel, duodenum, left kidney, right kidney, liver, spinal cord and stomach, respectively. CONCLUSIONS: The proposed method could significantly expedite the treatment planning process by rapidly segmenting multiple OARs. The method could potentially be used in pancreatic adaptive radiotherapy to increase dose delivery accuracy and minimize gastrointestinal toxicity.

Head and neck multi-organ auto-segmentation on CT images aided by synthetic MRI.

PURPOSE: Because the manual contouring process is labor-intensive and time-consuming, segmentation of organs-at-risk (OARs) is a weak link in radiotherapy treatment planning process. Our goal was to develop a synthetic MR (sMR)-aided dual pyramid network (DPN) for rapid and accurate head and neck multi-organ segmentation in order to expedite the treatment planning process. METHODS: Forty-five patients' CT, MR, and manual contours pairs were included as our training dataset. Nineteen OARs were target organs to be segmented. The proposed sMR-aided DPN method featured a deep attention strategy to effectively segment multiple organs. The performance of sMR-aided DPN method was evaluated using five metrics, including Dice similarity coefficient (DSC), Hausdorff distance 95% (HD95), mean surface distance (MSD), residual mean square distance (RMSD), and volume difference. Our method was further validated using the 2015 head and neck challenge data. RESULTS: The contours generated by the proposed method closely resemble the ground truth manual contours, as evidenced by encouraging quantitative results in terms of DSC using the 2015 head and neck challenge data. Mean DSC values of 0.91 ± 0.02, 0.73 ± 0.11, 0.96 ± 0.01, 0.78 ± 0.09/0.78 ± 0.11, 0.88 ± 0.04/0.88 ± 0.06 and 0.86 ± 0.08/0.85 ± 0.1 were achieved for brain stem, chiasm, mandible, left/right optic nerve, left/right parotid, and left/right submandibular, respectively. CONCLUSIONS: We demonstrated the feasibility of sMR-aided DPN for head and neck multi-organ delineation on CT images. Our method has shown superiority over the other methods on the 2015 head and neck challenge data results. The proposed method could significantly expedite the treatment planning process by rapidly segmenting multiple OARs.