Automated tumor localization and segmentation through hybrid neural network in head and neck cancer.

PURPOSE: Head and Neck (H&N) cancer accounts for 3% of cancer cases in the United States. Precise tumor segmentation in H&N is of utmost importance for treatment planning and administering personalized treatment dose. We aimed to develop an automatic tumor localization and segmentation method in enhancing the clinical efficiency and ultimately improving treatment outcomes. APPROACH: In this study, a hybrid neural network (HNN) was developed by integrating object localization and segmentation into a unified framework. It consists of 4 stages: preprocessing, HNN training, object localization and segmentation, and postprocessing. We utilized a dataset consisting of PET and CT images for 48 patients and designed a Hybrid Neural Network (HNN) which consists of YOLOv4 object detection model + U-Net model for image segmentation. YOLOv4 was used to identify regions of interests (ROI), while the U-Net was employed for the precise image segmentation. In our experiments we considered 2 object detection architectures to identify possible tumor regions, namely YOLOv4 and Faster-RCNN. The evaluation metrics for both were evaluated and compared. RESULTS: We evaluated the performance of 3 model combinations: YOLOv4 + U-Net, Faster-RCNN + U-Net, and U-Net alone. The models were evaluated based on Sensitivity, Specificity, F-Score, and Intersection over Union (IoU). YOLOv4 + U-Net achieved the best values with Sensitivity of 0.89, Specificity of 0.99, F-Score of 0.84, and IoU of 0.72. CONCLUSION: A new hybrid neural network (HNN) for fully automatic tumor localization and segmentation was developed and the experimental results. showcased the HNN's impressive performance, indicating its potential to be a valuable H&N tumor segmentation tool.

COVID-19-induced granulomatosis with polyangiitis: A case report of a 16-year-old East Asian and literature review.

OBJECTIVE: Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is divided into granulomatosis with polyangiitis (GPA), microscopic polyangiitis, and eosinophilic GPA. It is one of the most severe and potentially fatal autoimmune inflammatory conditions. The etiology and pathology of AAV are complex and poorly understood. Since the onset of the Coronavirus Disease 2019 (COVID-19) pandemic, numerous reports have documented GPA cases following COVID-19, suggesting a potential link between COVID-19 and the development of GPA. This case report discusses a 16-year-old East Asian boy who developed GPA with diffuse alveolar hemorrhage after contracting COVID-19. Additionally, a literature review was conducted to gain a deeper understanding of this disorder. METHODS: The study involved a retrospective analysis of the data of a case of GPA post-COVID-19 infection, aiming to summarize the clinical characteristics of GPA post-COVID-19 infection through a search of databases (PubMed, Wanfang Data, and CNKI), supplemented by standard searches in Google Scholar, Cochrane, Scopus, and LitCovid, and to conduct a comprehensive analysis of the literature. RESULTS: A total of 12 cases were identified and, when combined with the present case, yielded 13 cases of GPA post-COVID-19 infection, comprising 5 males and 8 females with an average age of (40.6 ± 19.5) years. The interval between COVID-19 infection and the diagnosis of GPA varied from 1 day to 3 months across all cases. Mortality was reported at 7.7% (1/13). The most common clinical manifestations included cough (69.2%) and dyspnea (46.1%). Computed tomography scans revealed ground-glass opacities and multifocal pulmonary nodules. In all cases, positive findings for c-ANCA and protease 3-antibody were observed. Renal involvement was observed in more than half of the patients.

Is postoperative adjuvant radiotherapy necessary for patients with esophageal cancer after neoadjuvant chemoradiotherapy? An analysis based on the SEER database.

OBJECTIVES: To evaluate the outcomes of adjuvant radiotherapy in patients with esophageal cancer (EC) who underwent esophagectomy following neoadjuvant chemoradiotherapy (NCRT). METHODS: The data of EC patients who received adjuvant therapy after NCRT between 2004 to 2019 was retrieved from the SEER database. The patients were split into the adjuvant radiotherapy with or without chemotherapy (RT±CT) and the adjuvant chemotherapy (CT) groups. The process of propensity score matching (PSM) was employed. RESULTS: Following PSM, 157 patients in total were recruited in each treatment group. There were no significant variations in either overall survival (OS) or cancer-specific survival (CSS) between the RT±CT and CT groups (median OS: 28 months versus. 51 months, p=0.063; median CSS: 31 months versus. 52 months, p=0.16). Within the CT group, patients with ypI/II or cI/II tumor stage, positive lymph node ratio (LNR) ≤0.1, and tumor size ≥50 mm (p<0.05) had higher OS compared to the RT±CT groups. Among patients with cT3-4 tumors in N-stage downstaging group, the OS and CSS were significantly greater for those underwent RT±CT as opposed to the CT group (5-year OS:56.6% versus 19.4%, p=0.042; 5-year CSS:67.9% versus. 19.4%, p=0.023). Multivariate Cox regression analysis identified the tumor histology grade as an independent prognostic factor of OS and CSS. CONCLUSION: Radiotherapy-based adjuvant therapy does not significantly improve the prognosis of EC patients after NCRT, although it may provide a survival benefit for patients with cT3-4 tumors in N-stage downstaging.

Influence of static cartoons combined with dynamic virtual environments on preoperative anxiety of preschool-aged children undergoing surgery.

BACKGROUND: Preschoolers become anxious when they are about to undergo anesthesia and surgery, warranting the development of more appropriate and effective interventions. AIM: To explore the effect of static cartoons combined with dynamic virtual environments on preoperative anxiety and anesthesia induction compliance in preschool-aged children undergoing surgery. METHODS: One hundred and sixteen preschool-aged children were selected and assigned to the drug (n = 37), intervention (n = 40), and control (n = 39) groups. All the children received routine preoperative checkups and nursing before being transferred to the preoperative preparation room on the day of the operation. The drug group received 0.5 mg/kg midazolam and the intervention group treatment consisting of static cartoons combined with dynamic virtual environments. The control group received no intervention. The modified Yale Preoperative Anxiety Scale was used to evaluate the children's anxiety level on the day before surgery (T0), before leaving the preoperative preparation room (T1), when entering the operating room (T2), and at anesthesia induction (T3). Compliance during anesthesia induction (T3) was evaluated using the Induction Compliance Checklist (ICC). Changes in mean arterial pressure (MAP), heart rate (HR), and respiratory rate (RR) were also recorded at each time point. RESULTS: The anxiety scores of the three groups increased variously at T1 and T2. At T3, both the drug and intervention groups had similar anxiety scores, both of which were lower than those in the control group. At T1 and T2, MAP, HR, and RR of the three groups increased. The drug and control groups had significantly higher MAP and RR than the intervention group at T2. At T3, the MAP, HR, and RR of the drug group decreased and were significantly lower than those in the control group but were comparable to those in the intervention group. Both the drug and intervention groups had similar ICC scores and duration of anesthesia induction (T3), both of which were higher than those of the control group. CONCLUSION: Combining static cartoons with dynamic virtual environments as effective as medication, specifically midazolam, in reducing preoperative anxiety and fear in preschool-aged children. This approach also improve their compliance during anesthesia induction and helped maintain their stable vital signs.

Infectious wrist arthritis complicating acute carpal tunnel syndrome in a child: A CARE-compliant case report.

INTRODUCTION: The objective of this case report is to provide clinical evidence that acute infectious wrist arthritis in children can lead to the rare condition of acute carpal tunnel syndrome (ACTS). This article discusses in detail the characteristics of infectious wrist arthritis complicating ACTS in children in terms of etiology, pathogenic bacteria, treatment modalities, and sequelae to improve the understanding of this disease. PATIENT CONCERNS: A 10-year-old male child presented with a 15-day history of swelling and pain in the left forearm, wrist, and hand. DIAGNOSES: Left-sided infected wrist arthritis complicating ACTS. INTERVENTIONS: The child received emergency surgery and anti-infective treatment combined with regular rehabilitation. OUTCOMES: During the treatment period, the child's wrist pain and swelling gradually improved, and wrist movement was restored compared with the preoperative period. At 6-month follow-up, the activities of the metacarpophalangeal joints of the left hand were close to normal, and the flexion of the left wrist joint was slightly limited. CONCLUSION: In infectious wrist arthritis in children, ACTS is a serious complication that requires aggressive surgical carpal tunnel release to avoid median nerve injury in addition to anti-infective therapy.

Assessing the Influence of B-US, CDFI, SE, and Patient Age on Predicting Molecular Subtypes in Breast Lesions Using Deep Learning Algorithms.

OBJECTIVES: Our study aims to investigate the impact of B-mode ultrasound (B-US) imaging, color Doppler flow imaging (CDFI), strain elastography (SE), and patient age on the prediction of molecular subtypes in breast lesions. METHODS: Totally 2272 multimodal ultrasound imaging was collected from 198 patients. The ResNet-18 network was employed to predict four molecular subtypes from B-US imaging, CDFI, and SE of patients with different ages. All the images were split into training and testing datasets by the ratio of 80%:20%. The predictive performance on testing dataset was evaluated through 5 metrics including mean accuracy, precision, recall, F1-scores, and confusion matrix. RESULTS: Based on B-US imaging, the test mean accuracy is 74.50%, the precision is 74.84%, the recall is 72.48%, and the F1-scores is 0.73. By combining B-US imaging with CDFI, the results were increased to 85.41%, 85.03%, 85.05%, and 0.84, respectively. With the integration of B-US imaging and SE, the results were changed to 75.64%, 74.69%, 73.86%, and 0.74, respectively. Using images from patients under 40 years old, the results were 90.48%, 90.88%, 88.47%, and 0.89. When images from patients who are above 40 years old, they were changed to 81.96%, 83.12%, 80.5%, and 0.81, respectively. CONCLUSION: Multimodal ultrasound imaging can be used to accurately predict the molecular subtypes of breast lesions. In addition to B-US imaging, CDFI rather than SE contribute further to improve predictive performance. The predictive performance is notably better for patients under 40 years old compared with those who are 40 years old and above.

Oxygen-Independent Radiodynamic Therapy: Radiation-Boosted Chemodynamics for Reprogramming the Tumor Immune Environment and Enhancing Antitumor Immune Response.

Radiodynamic therapy (RDT) has emerged as a promising modality for cancer treatment, offering notable advantages such as deep tissue penetration and radiocatalytic generation of oxygen free radicals. However, the oxygen-dependent nature of RDT imposes limitations on its efficacy in hypoxic conditions, particularly in modulating and eliminating radioresistant immune suppression cells. A novel approach involving the creation of a "super" tetrahedron polyoxometalate (POM) cluster, Fe12-POM, has been developed for radiation boosted chemodynamic catalysis to enable oxygen-independent RDT in hypoxic conditions. This nanoscale cluster comprises four P2W15 units functioning as energy antennas, while the Fe3 core serves as an electron receptor and catalytic center. Under X-ray radiation, a metal-to-metal charge transfer phenomenon occurs between P2W15 and the Fe3 core, resulting in the valence transition of Fe3+ to Fe2+ and a remarkable 139-fold increase in hydroxyl radical generation compared to Fe12-POM alone. The rapid generation of hydroxyl radicals, in combination with PD-1 therapy, induces a reprogramming of the immune environment within tumors. This reprogramming is characterized by upregulation of CD80/86, downregulation of CD163 and FAP, as well as the release of interferon-γ and tumor necrosis factor-α. Consequently, the occurrence of abscopal effects is facilitated, leading to significant regression of both local and distant tumors in mice. The development of oxygen-independent RDT represents a promising approach to address cancer recurrence and improve treatment outcomes.

AMS-U-Net: automatic mass segmentation in digital breast tomosynthesis via U-Net.

Purpose: The objective of this study was to develop a fully automatic mass segmentation method called AMS-U-Net for digital breast tomosynthesis (DBT), a popular breast cancer screening imaging modality. The aim was to address the challenges posed by the increasing number of slices in DBT, which leads to higher mass contouring workload and decreased treatment efficiency. Approach: The study used 50 slices from different DBT volumes for evaluation. The AMS-U-Net approach consisted of four stages: image pre-processing, AMS-U-Net training, image segmentation, and post-processing. The model performance was evaluated by calculating the true positive ratio (TPR), false positive ratio (FPR), F-score, intersection over union (IoU), and 95% Hausdorff distance (pixels) as they are appropriate for datasets with class imbalance. Results: The model achieved 0.911, 0.003, 0.911, 0.900, 5.82 for TPR, FPR, F-score, IoU, and 95% Hausdorff distance, respectively. Conclusions: The AMS-U-Net model demonstrated impressive visual and quantitative results, achieving high accuracy in mass segmentation without the need for human interaction. This capability has the potential to significantly increase clinical efficiency and workflow in DBT for breast cancer screening.

Manganese(III) Phthalocyanine Complex Nanoparticle-Loaded Glucose Oxidase to Enhance Tumor Inhibition through Energy Metabolism and Macrophage Polarization.

Elevated levels of reactive oxygen species (ROS) have demonstrated efficacy in eliminating tumor cells by modifying the tumor microenvironment and inducing the polarization of tumor-associated macrophages (TAMs). Nevertheless, the transient nature and limited diffusion distance inherent in ROS present significant challenges in cancer treatment. In response to these limitations, we have developed a nanoparticle (MnClPc-HSA@GOx) that not only inhibits tumor energy metabolism but also facilitates the transition of TAMs from the M2 type (anti-inflammatory type) to the M1 type (proinflammatory type). MnClPc-HSA@GOx comprises a manganese phthalocyanine complex (MnClPc) enveloped in human serum albumin (HSA), with glucose oxidase (GOx) loaded onto MnClPc@HSA nanoparticles. GOx was employed to catalyze the decomposition of glucose to produce H2O2 and gluconic acid. Additionally, in the presence of MnClPc, it catalyzes the conversion of H2O2 into •O2- and 1O2. Results indicate that the nanoparticle effectively impedes the glucose supply to tumor cells and suppresses their energy metabolism. Simultaneously, the ROS-mediated polarization of TAMs induces a shift from M2 to M1 macrophages, resulting in a potent inhibitory effect on tumors. This dual-action strategy holds promising clinical inhibition applications in the treatment of cancer.

Nitisinone attenuates cartilage degeneration and subchondral osteoclastogenesis in osteoarthritis and concomitantly inhibits the cGAS/STING/NF-κB pathway.

Osteoarthritis (OA) is a chronic degenerative joint disease characterized by cartilage degeneration and subchondral bone remodelling. Currently, conservative treatment strategies cannot effectively alleviate the progression of OA. In this study, we used computer network analysis to show that Nitisinone (NTBC) is closely related to extracellular matrix degradation in OA and mainly interferes with the TNF-α signaling pathway. NTBC is an orphan drug used to treat hereditary type I tyrosinemia by altering phenylalanine/tyrosine metabolic flow. In this study, we found that NTBC effectively reduced chondrocyte inflammation and extracellular matrix degradation induced by TNF-α. Mechanistically, NTBC inhibited the cGAS/STING signaling pathway and reduced activation of the STING-dependent NF-κB pathway to alleviate inflammation. In addition, NTBC inhibited osteoclastogenesis and delayed the occurrence of subchondral bone remodelling. In mice with ACLT-induced osteoarthritis, intra-articular injection of NTBC significantly reduced cartilage degradation and subchondral bone remodelling. NTBC showed impressive therapeutic efficacy as a potential pharmaceutical intervention for the treatment of OA.

Carnitine functions as an enhancer of NRF2 to inhibit osteoclastogenesis via regulating macrophage polarization in osteoporosis.

Osteoporosis, which manifests as reduced bone mass and deteriorated bone quality, is common in the elderly population. It is characterized by persistent elevation of macrophage-associated inflammation and active osteoclast bone resorption. Currently, the roles of intracellular metabolism in regulating these processes remain unclear. In this study, we initially performed bioinformatics analysis and observed a significant increase in the proportion of M1 macrophages in bone marrow with aging. Further metabolomics analysis demonstrated a notable reduction in the expression of carnitine metabolites in aged macrophages, while carnitine was not detected in osteoclasts. During the differentiation process, osteoclasts took up carnitine synthesized by macrophages to regulate their own activity. Mechanistically, carnitine enhanced the function of Nrf2 by inhibiting the Keap1-Nrf2 interaction, reducing the proteasome-dependent ubiquitination and degradation of Nrf2. In silico molecular ligand docking analysis of the interaction between carnitine and Keap1 showed that carnitine binds to Keap1 to stabilize Nrf2 and enhance its function. In this study, we found that the decrease in carnitine levels in aging macrophages causes overactivation of osteoclasts, ultimately leading to osteoporosis. A decrease in serum carnitine levels in patients with osteoporosis was found to have good diagnostic and predictive value. Moreover, supplementation with carnitine was shown to be effective in the treatment of osteoporosis.

Oral VV116 versus placebo in patients with mild-to-moderate COVID-19 in China: a multicentre, double-blind, phase 3, randomised controlled study.

BACKGROUND: Spread of SARS-CoV-2 led to a global pandemic, and there remains unmet medical needs in the treatment of Omicron infections. VV116, an oral antiviral agent that has potent activity against SARS-CoV-2, was compared with a placebo in this phase 3 study to investigate its efficacy and safety in patients with mild-to-moderate COVID-19. METHODS: This multicentre, double-blind, phase 3, randomised controlled study enrolled adults in hospitals for infectious diseases and tertiary general hospitals in China. Eligible patients were randomly assigned in a 1:1 ratio using permuted block randomisation to receive oral VV116 (0·6 g every 12 h on day 1 and 0·3 g every 12 h on days 2-5) or oral placebo (on the same schedule as VV116) for 5 days. Randomisation stratification factors included SARS-CoV-2 vaccination status and the presence of high-risk factors for progression to severe COVID-19. Inclusion criteria were a positive SARS-CoV-2 test, an initial onset of COVID-19 symptoms 3 days or less before the first study dose, and a score of 2 or more for any target COVID-19-related symptoms in the 24 h before the first dose. Patients who had severe or critical COVID-19 or who had taken any antiviral drugs were excluded from the study. The primary endpoint was the time to clinical symptom resolution for 2 consecutive days. Efficacy analyses were performed on a modified intention-to-treat population, comprising all patients who received at least one dose of VV116 or placebo, tested positive for SARS-CoV-2 nucleic acid, and did not test positive for influenza virus before the first dose. Safety analyses were done on all participants who received at least one dose of VV116 or placebo. This study was registered with ClinicalTrials.gov, NCT05582629, and has been completed. FINDINGS: A total of 1369 patients were randomly assigned to treatment groups and 1347 received either VV116 (n=674) or placebo (n=673). At the interim analysis, VV116 was superior to placebo in reducing the time to sustained clinical symptom resolution among 1229 patients (hazard ratio [HR] 1·21, 95% CI 1·04-1·40; p=0·0023). At the final analysis, a substantial reduction in time to sustained clinical symptom resolution was observed for VV116 compared with placebo among 1296 patients (HR 1·17, 95% CI 1·04-1·33; p=0·0009), consistent with the interim analysis. The incidence of adverse events was similar between groups (242 [35·9%] of 674 patients vs 283 [42·1%] of 673 patients). INTERPRETATION: Among patients with mild-to-moderate COVID-19, VV116 significantly reduced the time to sustained clinical symptom resolution compared with placebo, with no observed safety concerns. FUNDING: Shanghai Vinnerna Biosciences, Shanghai Science and Technology Commission, and the National Key Research and Development Program of China. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Immunotherapy Combined with Chemotherapy in Relapse Metaplastic Breast Cancer.

Metaplastic breast cancer (MBC) is a rare disease, and there was rarely reported the treatment after recurrence and metastasis. Here, we report the treatment of an adult patient who suffered from MBC with lung, lymph nodes and left pleura metastasis after radical surgery. The next-generation sequencing result demonstrated that it had tumor mutational burden (TMB) of 12.0 Muts/Mb and microsatellite stability. The patient received sintilimab, an immune checkpoint inhibitor, plus chemotherapy and achieved partial response (PR). This is a report of a good outcome of metastatic MBC achieving 24 months of progression-free survival (PFS) and 39 months of overall survival (OS) with a combination therapy of immune checkpoint inhibitor and chemotherapy. Immuno-chemotherapy may have antitumor activity for relapse MBC. TMB may serve as a potential predictor associated with PD-1 inhibitors in MBC and help clinicians make an optimum treatment strategy.

Prognostic value of neutrophil to lymphocyte ratio and platelet counts during chemotherapy in patients with advanced gastric cancer.

OBJECTIVES: To investigate the predictive significance of dynamic changes in the neutrophil to lymphocyte ratio (NLR) and platelet counts (PLTs) in patients with advanced gastric cancer (GC) during chemotherapy. METHODS: A total of 259 advanced GC patients receiving chemotherapy were enrolled and grouped by high or low NLR with a cut value of 2.5 and PLT with cut value of 300×109/L. The Kaplan-Meier survival model and the Log-rank test were carried out to determine the comparison on the overall survival differences. Cox regression analysis was employed to carry out both univariate and multivariate regression studies, aiming to explore potential prognostic factors acting independently. RESULTS: Higher pre-chemotherapy NLR exhibited an association with metastasis and advanced grade of Borrmann type, and higher NLR of pre- or post-chemotherapy GC patients was related with Borrmann type grade. Moreover, higher PLT counts are associated with advanced grades of Borrmann type. Interestingly, patients with lower post-chemotherapy NLR or decreasing NLR hold better overall response rate and disease control rate than those with higher NLR or increasing NLR. Furthermore, patients with high post-chemotherapy NLR alone or higher post-chemotherapy NLR plus higher post-chemotherapy PLT. CONCLUSION: Our study suggested that high post-chemotherapy NLR and post-chemotherapy PLT might be adverse prognostic markers in advanced GC patients undergoing chemotherapy.

A pairwise radiomics algorithm-lesion pair relation estimation model for distinguishing multiple primary lung cancer from intrapulmonary metastasis.

Background: Distinguishing multiple primary lung cancer (MPLC) from intrapulmonary metastasis (IPM) is critical for their disparate treatment strategy and prognosis. This study aimed to establish a non-invasive model to make the differentiation pre-operatively. Methods: We retrospectively studied 168 patients with multiple lung cancers (307 pairs of lesions) including 118 cases for modeling and internal validation, and 50 cases for independent external validation. Radiomic features on computed tomography (CT) were extracted to calculate the absolute deviation of paired lesions. Features were then selected by correlation coefficients and random forest classifier 5-fold cross-validation, based on which the lesion pair relation estimation (PRE) model was developed. A major voting strategy was used to decide diagnosis for cases with multiple pairs of lesions. Cases from another institute were included as the external validation set for the PRE model to compete with two experienced clinicians. Results: Seven radiomic features were selected for the PRE model construction. With major voting strategy, the mean area under receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity of the training versus internal validation versus external validation cohort to distinguish MPLC were 0.983 versus 0.844 versus 0.793, 0.942 versus 0.846 versus 0.760, 0.905 versus 0.728 versus 0.727, and 0.962 versus 0.910 versus 0.769, respectively. AUCs of the two clinicians were 0.619 and 0.580. Conclusions: The CT radiomic feature-based lesion PRE model is potentially an accurate diagnostic tool for the differentiation of MPLC and IPM, which could help with clinical decision making.

Anoikis-related gene signatures can aid prognosis of lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer, and while advancements in diagnosis, surgery, radiotherapy, and molecular therapy have improved clinical prognosis, the long-term survival rate and quality of life of patients remain unsatisfactory. Therefore, identifying new prognostic biomarkers and potential therapeutic targets is crucial. OBJECTIVES: This study aimed to analyze the role of anoikis-related gene characteristics in LUAD. MATERIAL AND METHODS: The anoikis-related genes were obtained from the GeneCards database. Genetic expression data and clinical characteristic information were collected from The Cancer Genome Atlas (TCGA)-LUAD, and the Gene Expression Omnibus (GEO) GSE31210, GSE37745, and GSE68465 datasets. Random survival forest and least absolute shrinkage and selection operator (LASSO) models were applied to construct the risk model. An analysis of immune cell infiltration and function was performed with the scores. RESULTS: Four prognosis-related genes (TLE1, GLI2, PLK1, and BAK1) were obtained and used to construct the anoikis score. We found that the patient survival rate was higher in the low-anoikis score (LAS) group. Moreover, both the stromal and immune scores were negatively correlated with the anoikis score. With the increase of the anoikis score, the levels of natural killer cells, regulatory T cells, CD4+ T cells, CD8+ T cells, B cells, and macrophages decreased. The anoikis score had a negative regulatory relationship with the immune response, natural killer cell activation and T cell activation. The TP53 mutation was significant in LUAD patients and was present in 56% of the high-anoikis score (HAS) group and in 40% of the LAS group. CONCLUSIONS: The anoikis score was associated with poor prognosis in LUAD patients. Anoikis-related genes were associated with tumor immune dysregulation and TP53 mutation in LUAD. This study opens a new perspective for LUAD therapy.

An integrated network based on 2D/3D feature correlations for benign-malignant tumor classification and uncertainty estimation in digital breast tomosynthesis.

Objective.Classification of benign and malignant tumors is important for the early diagnosis of breast cancer. Over the last decade, digital breast tomosynthesis (DBT) has gradually become an effective imaging modality for breast cancer diagnosis due to its ability to generate three-dimensional (3D) visualizations. However, computer-aided diagnosis (CAD) systems based on 3D images require high computational costs and time. Furthermore, there is considerable redundant information in 3D images. Most CAD systems are designed based on 2D images, which may lose the spatial depth information of tumors. In this study, we propose a 2D/3D integrated network for the diagnosis of benign and malignant breast tumors.Approach.We introduce a correlation strategy to describe feature correlations between slices in 3D volumes, corresponding to the tissue relationship and spatial depth features of tumors. The correlation strategy can be used to extract spatial features with little computational cost. In the prediction stage, 3D spatial correlation features and 2D features are both used for classification.Main results.Experimental results demonstrate that our proposed framework achieves higher accuracy and reliability than pure 2D or 3D models. Our framework has a high area under the curve of 0.88 and accuracy of 0.82. The parameter size of the feature extractor in our framework is only 35% of that of the 3D models. In reliability evaluations, our proposed model is more reliable than pure 2D or 3D models because of its effective and nonredundant features.Significance.This study successfully combines 3D spatial correlation features and 2D features for the diagnosis of benign and malignant breast tumors in DBT. In addition to high accuracy and low computational cost, our model is more reliable and can output uncertainty value. From this point of view, the proposed method has the potential to be applied in clinic.

Prognostic roles of hematological indicators for the efficacy and prognosis of immune checkpoint inhibitors in patients with advanced tumors: a retrospective cohort study.

BACKGROUND: Immunocheckpoint inhibitor(ICI) is a major breakthrough in tumor treatment. It can activate the patient's own immune system and play an anti-tumor role, but not all patients can benefit from it. At present, there is still a lack of effective biomarkers to guide clinical application. The systemic immune inflammation(SII) index reflects the systemic inflammatory state and immune state of patients. Prognostic nutrition index(PNI) can be used to evaluate immune status of patients. Therefore, SII and PNI indexes may have some value in predicting the efficacy and prognosis of immunotherapy, but there is still a lack of relevant research. The purpose of our study was to explore the influence of SII and PNI index on the efficacy and prognosis of immunotherapy. METHODS: A total of 1935 patients treated with ICIs treatment in the Fourth Hospital of Hebei Medical University from November 2016 to October 2021 were retrospectively collected. 435 patients who met the inclusion criteria and did not meet the exclusion criteria. The imaging data, blood results of each patient were collected within 1 week before ICIs treatment. The neutrophil lymphocyte ratio(NLR), platelet lymphocyte ratio(PLR), monocyte lymphocyte ratio(MLR), PNI,systemic inflammatory response index(SIRI),neutrophil-eosinophil ratio(NER) was calculated. The patients were followed up by in-patient, out-patient reexamination and telephone contact, and the efficacy evaluation and survival status were recorded. The deadline of follow-up: January 2021. SPSS-24.0 software was employed for statistical analysis. RESULTS: Among the 435 patients receiving ICI treatment, 61,236 and 138 patients were evaluated respectively as partial response (PR), stable disease (SD) and progressive disease (PD). The overall response rate(ORR) and disease control rate (DCR) of this cohort were 14.0% and 68.3%, respectively. Median progression-free survival (mPFS) is 4.0 months, The overall survival (mOS) of this cohort is 6.8 months. Multivariate analysis showed that SIRI(Hazard Ratio, HR = 1.304, P = 0.014), PNI (HR = 0.771, P = 0.019), prealbumin (PAB) (HR = 0.596, P = 0.001), and PNI(HR = 0.657, P = 0.008) were independent risk factors for PFS and OS, respectively. CONCLUSIONS: Patients with high SIRI value and low PNI value before ICI treatment have shorter PFS. Patients with higher PNI value have better prognosis. Therefore, hematological indicators may become predictors of immunotherapy.

Cardiac tropoini T (TNNT2) plays a potential oncogenic role in colorectal carcinogenesis.

PURPOSE: Colorectal cancer (CRC) is the third most common cancer in the world. The purpose of this study was to investigate the role of TNNT2 in the proliferation, migration and invasion of CRC cells and its expression in CRC tissues to better understand the regulatory role of TNNT2 in CRC. METHODS: Western blotting (WB) and qPCR were used to detect the expression of TNNT2 in colorectal cancer tissues and paracancerous tissues. CCK-8, colony formation, Transwell and other experiments were used to clarify the role of TNNT2 in the proliferation, migration and invasion of colorectal cancer cells. Changes in TNNT2, EGFR and HER2 mRNA transcription levels were detected by SYBR Real-Time PCR assay, and the effects of TNNT2 overexpression or knockdown on the expression of EGFR, HER2 and EMT-related proteins in CRC cells were determined by WB. TNNT2 and EGFR intreaction was carried out in HCT116 cells by coimmunoprecipitation experiments. RESULTS: The protein and mRNA expression level of TNNT2 in CRC tissues were higher than those in paracancerous tissues. The CCK-8 results suggested that overexpression of TNNT2 significantly promoted the proliferation of HCT116 and RKO cells, and TNNT2 konckdown gets the opposite result; and the colony formation results were the same as tthose of CCK-8 assay. Transwell invasion and migration experiments showed that overexpression of TNNT2 promoted the migration and invasion of HCT116 and PKO cells, and TNNT2 konckdown suppressed the migration and invasion of the these cells. The SYBR Green I real-time PCR method revealed that them RNA levels of TNNT2, EGFR and HER2 in the TNNT2 overexpression group were higher than those in RKO cells. WB showed that overexpressing TNNT2 increased the expression of EGFR and HER2 in HCT16 and RKO cells,decreased the expression of EMT marker E-cadherin, and increased the expression of Vimentin and N-cadherin. Konckdown of TNNT2 decreased the expression of EGFR and HER2, increased the expression of E-cadherin, and decreased the expression of Vimentin and N-cadherin in HCT16 and RKO cells. The immunocoprecipitation experiment showed that there was an interaction between EGFR and TNNT2. CONCLUSION: TNNT2 can promote the proliferation, invasion and metastasis of colorectal cancer cells. There is an interaction between TNNT2 and EGFR protein. TNNT2 can upregulate EGFR and HER2-related proteins in colorectal cancer cells and promote the occurrence of EMT. Therefore, TNNT2 can promote the invasion and metastasis of CRC cells through the EGFR/HER2/EMT signal axis, suggesting that TNNT2 is a potential target of CRC treatment.