A novel unsupervised dynamic feature domain adaptation strategy for cross-individual myoelectric gesture recognition.

Objective.Surface electromyography pattern recognition (sEMG-PR) is considered as a promising control method for human-machine interaction systems. However, the performance of a trained classifier would greatly degrade for novel users since sEMG signals are user-dependent and largely affected by a number of individual factors such as the quantity of subcutaneous fat and the skin impedance.Approach.To solve this issue, we proposed a novel unsupervised cross-individual motion recognition method that aligned sEMG features from different individuals by self-adaptive dimensional dynamic distribution adaptation (SD-DDA) in this study. In the method, both the distances of marginal and conditional distributions between source and target features were minimized through automatically selecting the optimal feature domain dimension by using a small amount of unlabeled target data.Main results.The effectiveness of the proposed method was tested on four different feature sets, and results showed that the average classification accuracy was improved by above 10% on our collected dataset with the best accuracy reached 90.4%. Compared to six kinds of classic transfer learning methods, the proposed method showed an outstanding performance with improvements of 3.2%-13.8%. Additionally, the proposed method achieved an approximate 9% improvement on a publicly available dataset.Significance.These results suggested that the proposed SD-DDA method is feasible for cross-individual motion intention recognition, which would provide help for the application of sEMG-PR based system.

A Novel Transformer-Based Approach for Simultaneous Recognition of Hand Movements and Force Levels in Amputees Using Flexible Ultrasound Transducers.

Accurate hand motion intention recognition is essential for the intuitive control of intelligent prosthetic hands and other human-machine interaction systems. Sonomyography, which can detect the changes in muscle morphology and structure precisely, is a promising signal source for fine hand movement recognition. However, sonomyography measured by traditional rigid ultrasound probes may suffer from poor acoustic coupling because the rigid probe surfaces cannot accommodate the curvilinear shape of the human body, particularly in the case of small and irregular residual limbs in amputees. In this study, we used a self-designed lightweight, flexible, and wearable ultrasound transducer to acquire muscle ultrasound images, and proposed a sonomyography transformer (SMGT) model for simultaneous recognition of hand movements and force levels. The performance of SMGT was systematically compared to two commonly used image processing methods, HOG and Gray Gradient, as well as a deep CNN model, in simultaneously recognizing ten classes of hand/finger movements and three force levels. Additionally, ten subjects including seven non-disabled subjects and three trans-radial amputees who are the end users of prosthetic hands were recruited to evaluate the effectiveness of SMGT. Results showed that our proposed method achieved average classification accuracies of 98.4% ± 0.6% and 96.2% ± 3.0% in non-disabled subjects and amputee subjects, respectively, which are much higher than those of other methods. This study provided a valuable approach for ultrasound-based hand motion recognition that may promote the applications of intelligent prosthetic hands.

Establishment of nucleic acid sensing pathways-based model in predicting response to immunotherapy and targeted drug in hepatitis virus-related hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) accounts for 80% of liver cancers, while 70%-80% of HCC developed from chronic liver disease with hepatitis B virus (HBV) and hepatitis C virus (HCV) infection as the major etiology. Immunotherapy is assuming a role as a pillar of HCC treatment, but the remarkable immune-mediated responses are restricted in a minority of patients. Nucleic acid sensing (NAS) pathways are the central pathway of the innate immune system and antiviral immune response to viral infection, but their role in hepatitis virus-related HCC remains undetermined. In our study, we performed a comprehensive bioinformatics analysis based on transcriptomic data of hepatitis virus related-HCC tissues collected from multiple public data sets. Two subgroups were validated based on NAS-related genes in virus-related HCC patients, which were defined as NAS-activated subgroups and NAS-suppressed subgroups based on the expression of NAS-related genes. On this basis, a NAS-related risk score (NASRS) predictive model was established for risk stratification and prognosis prediction in the hepatitis virus-related HCC (TCGA-LIHC and ICGC cohorts). The predictive values of the NASRS in prognosis and immunotherapy were also verified in multiple data sets. A nomogram was also established to facilitate the clinical use of NASRS and demonstrate its effectiveness through different approaches. Additionally, six potential drugs binding to the core target of the NAS signature were predicted via molecular docking strategy. We subsequently evaluated the cytotoxic capabilities of potential drug in vitro and in vivo. Based on these results, we conclude that the NASRS model could serve as a power prognostic biomarker and predict responses to immunotherapy, which is meaningful in clinical decision-making of hepatitis virus-related HCC patients.

A novel nucleic acid sensing-related genes signature for predicting immunotherapy efficacy and prognosis of lung adenocarcinoma.

BACKGROUND: As a novel pillar for lung adenocarcinoma (LUAD) treatment, immunotherapy has limited efficiency in LUAD patients. The nucleic acid sensing (NAS) pathways are critical in the anti-tumor immune response, but their role in LUAD remains controversial. OBJECTIVE: The study aims to develop a classification system to identify immune subtypes of LUAD based on nucleic acid sensing-related genes so that it can help screen patients who may respond to immunotherapy. METHODS: We performed a comprehensive bioinformatics analysis of the NAS molecule expression profiles across multiple public datasets. Using qRT-PCR to verify the NAS genes in multiple lung cancer cell lines. Molecular docking was performed to screen drug candidates. RESULTS: The NAS-activated subgroup and NAS-suppressed subgroup were validated based on the different patterns of gene expression and pathways enrichment. The NAS-activated subgroup displayed a stronger immune infiltration and better prognosis of patients. Moreover, we constructed a seven nucleic acid sensing-related risk score (NASRS) model for the convenience of clinical application. The predictive values of NASRS in prognosis and immunotherapy were subsequently fully validated in the lung adenocarcinoma dataset and the uroepithelial carcinoma dataset. Additionally, five potential drugs binding to the core target of the NAS signature were predicted through molecular docking. CONCLUSION: We found a significant correlation between nucleic acid sensing function and the immune treatment efficiency in LUAD. The NASRS can be used as a robust biomarker for the predicting of prognosis and immunotherapy efficiency and may help in clinical decisions for LUAD patients.

Intratumoral Microbiota Composition Regulates Chemoimmunotherapy Response in Esophageal Squamous Cell Carcinoma.

Neoadjuvant chemoimmunotherapy (NACI) has shown promise in the treatment of resectable esophageal squamous cell carcinoma (ESCC). The microbiomes of patients can impact therapy response, and previous studies have demonstrated that intestinal microbiota influences cancer immunotherapy by activating gut immunity. Here, we investigated the effects of intratumoral microbiota on the response of patients with ESCC to NACI. Intratumoral microbiota signatures of ß-diversity were disparate and predicted the treatment efficiency of NACI. The enrichment of Streptococcus positively correlated with GrzB+ and CD8+ T-cell infiltration in tumor tissues. The abundance of Streptococcus could predict prolonged disease-free survival in ESCC. Single-cell RNA sequencing demonstrated that responders displayed a higher proportion of CD8+ effector memory T cells but a lower proportion of CD4+ regulatory T cells. Mice that underwent fecal microbial transplantation or intestinal colonization with Streptococcus from responders showed enrichment of Streptococcus in tumor tissues, elevated tumor-infiltrating CD8+ T cells, and a favorable response to anti-PD-1 treatment. Collectively, this study suggests that intratumoral Streptococcus signatures could predict NACI response and sheds light on the potential clinical utility of intratumoral microbiota for cancer immunotherapy. SIGNIFICANCE: Analysis of intratumoral microbiota in patients with esophageal cancer identifies a microbiota signature that is associated with chemoimmunotherapy response and reveals that Streptococcus induces a favorable response by stimulating CD8+ T-cell infiltration. See related commentary by Sfanos, p. 2985.

YAP nuclear translocation facilitates radiation resistance in nasopharyngeal carcinoma cells.

OBJECTIVES: Investigate the role of the Hippo-YAP signaling pathway in radioresistant Nasopharyngeal Carcinoma (NPC). METHODS: Establishment of radioresistant CNE-1 cells (CNE-1-RR) by gradually increasing ionizing radiation (IR) doses, and identifying the apoptosis of CNE-1-RR by flow cytometry. We employed immunoblot and immunofluorescence staining to detect the expression of YAP in both CNE-1-RR and control group cells. Moreover, we validated the role of YAP in CNE-1-RR by inhibiting its nuclear translocation. RESULTS: In contrast to the control group, radioresistant NPC cells demonstrated significant YAP dephosphorylation and nuclear translocation. CNE-1-RR cells exhibited enhanced activation of γ-H2AX (Ser139) upon exposure to IR and greater recruitment of double-strand breaks (DSBs) repair-related proteins. Additionally, inhibiting YAP nuclear translocation in radioresistant CNE-1-RR cells significantly increased their sensitivity to radiotherapy. CONCLUSIONS: The present investigation has unveiled the intricate mechanisms and physiological roles of YAP in CNE-1-RR cells exhibiting resistance to IR. Based on our findings, it can be inferred that a combinational therapeutic strategy involving radiotherapy and inhibitors that impede the nuclear translocation of YAP holds promising potential for treating radioresistant NPC.

Resistance to immune checkpoint inhibitors in KRAS-mutant non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) patients with Kirsten rat sarcoma viral oncogene homolog (KRAS) mutation are associated with significant clinical heterogeneity and a poor prognosis to standard NSCLC therapies such as surgical resection, radiotherapy, chemotherapies, and targeted medicines. However, the application of immune checkpoints inhibitors (ICIs) has dramatically altered the therapeutic pattern of NSCLC management. Clinical studies have indicated that some KRAS-mutant NSCLC patients could benefit from ICIs; however, the responses in some patients are still poor. This review intends to elucidate the mechanisms of resistance to immunotherapy in KRAS-driven NSCLC and highlight the TME functions altered by immunoinhibitors, immunostimulators, and cancer metabolism. These metabolic pathways could potentially be promising approaches to overcome immunotherapy resistance.

The SOX9-MMS22L Axis Promotes Oxaliplatin Resistance in Colorectal Cancer.

BACKGROUND: Colorectal cancer (CRC) is estimated to be one of the most common cancers and the leading cause of cancer-related death worldwide. SOX9 is commonly overexpressed in CRC and participates in drug resistance. In addition, DNA damage repair confers resistance to anticancer drugs. However, the correlation between DNA damage repair and high SOX9 expression is still unclear. In this study, we aimed to investigate the function and the specific underlying mechanism of the SOX9-dependent DNA damage repair pathway in CRC. METHODS: The expression levels of SOX9 and MMS22L in CRC were examined by immunohistochemistry (IHC) and TCGA analysis. RNA sequencing was conducted in RKO SOX9-deficient cells and RKO shControl cells. Mechanistic studies were performed in CRC cells by modulating SOX9 and MMS22L expression, and we evaluated drug sensitivity and DNA damage repair signaling events. In addition, we investigated the effect of oxaliplatin in tumors with SOX9 overexpression and low expression of MMS22L in vivo. RESULTS: Our study showed that SOX9 has a higher expression level in CRC tissues than in normal tissues and predicts poor prognosis in CRC patients. Overexpression and knockdown of SOX9 were associated with the efficacy of oxaliplatin. In addition, SOX9 activity was enriched in the DNA damage repair pathway via regulation of MMS22L expression and participation in DNA double-strand break repair. SOX9 was upregulated and formed a complex with MMS22L, which promoted the nuclear translocation of MMS22L upon oxaliplatin treatment. Moreover, the xenograft assay results showed that oxaliplatin abrogated tumor growth from cells with MMS22L downregulation in mice. CONCLUSIONS: In CRC, activation of the SOX9-MMS22L-dependent DNA damage pathway is a core pathway regulating oxaliplatin sensitivity. Targeting this pathway in oxaliplatin-resistant CRC cells is a promising therapeutic option.

Identification of immune subtypes of cervical squamous cell carcinoma predicting prognosis and immunotherapy responses.

BACKGROUND: The main limitation of current immune checkpoint inhibitors (ICIs) in the treatment of cervical cancer comes from the fact that it benefits only a minority of patients. The study aims to develop a classification system to identify immune subtypes of cervical squamous cell carcinoma (SCC), thereby helping to screen candidates who may respond to ICIs. METHODS: A real-world cervical SCC cohort of 36 samples were analyzed. We used a nonnegative matrix factorization (NMF) algorithm to separate different expression patterns of immune-related genes (IRGs). The immune characteristics, potential immune biomarkers, and somatic mutations were compared. Two independent data sets containing 555 samples were used for validation. RESULTS: Two subtypes with different immunophenotypes were identified. Patients in sub1 showed favorable progression-free survival (PFS) and overall survival (OS) in the training and validation cohorts. The sub1 was remarkably related to increased immune cell abundance, more enriched immune activation pathways, and higher somatic mutation burden. Also, the sub1 group was more sensitive to ICIs, while patients in the sub2 group were more likely to fail to respond to ICIs but exhibited GPCR pathway activity. Finally, an 83-gene classifier was constructed for cervical SCC classification. CONCLUSION: This study establishes a new classification to further understand the immunological diversity of cervical SCC, to assist in the selection of candidates for immunotherapy.

Targeting Mouse Double Minute 2: Current Concepts in DNA Damage Repair and Therapeutic Approaches in Cancer.

Defects in DNA damage repair may cause genome instability and cancer development. The tumor suppressor gene p53 regulates cell cycle arrest to allow time for DNA repair. The oncoprotein mouse double minute 2 (MDM2) promotes cell survival, proliferation, invasion, and therapeutic resistance in many types of cancer. The major role of MDM2 is to inhibit p53 activity and promote its degradation. In this review, we describe the influence of MDM2 on genomic instability, the role of MDM2 on releasing p53 and binding DNA repair proteins to inhibit repair, and the regulation network of MDM2 including its transcriptional modifications, protein stability, and localization following DNA damage in genome integrity maintenance and in MDM2-p53 axis control. We also discuss p53-dependent and p53 independent oncogenic function of MDM2 and the outcomes of clinical trials that have been used with clinical inhibitors targeting p53-MDM2 to treat certain cancers.

A prognostic nomogram integrating novel biomarkers identified by machine learning for cervical squamous cell carcinoma.

BACKGROUND: Cervical cancer (CC) represents the fourth most frequently diagnosed malignancy affecting women all over the world. However, effective prognostic biomarkers are still limited for accurately identifying high-risk patients. Here, we provided a combination machine learning algorithm-based signature to predict the prognosis of cervical squamous cell carcinoma (CSCC). METHODS AND MATERIALS: After utilizing RNA sequencing (RNA-seq) data from 36 formalin-fixed and paraffin-embedded (FFPE) samples, the most significant modules were highlighted by the weighted gene co-expression network analysis (WGCNA). A candidate genes-based prognostic classifier was constructed by the least absolute shrinkage and selection operator (LASSO) and then validated in an independent validation set. Finally, based on the multivariate analysis, a nomogram including the FIGO stage, therapy outcome, and risk score level was built to predict progression-free survival (PFS) probability. RESULTS: A mRNA-based signature was developed to classify patients into high- and low-risk groups with significantly different PFS and overall survival (OS) rate (training set: p < 0.001 for PFS, p = 0.016 for OS; validation set: p = 0.002 for PFS, p = 0.028 for OS). The prognostic classifier was an independent and powerful prognostic biomarker for PFS in both cohorts (training set: hazard ratio [HR] = 0.13, 95% CI 0.05-0.33, p < 0.001; validation set: HR = 0.02, 95% CI 0.01-0.04, p < 0.001). A nomogram that integrated the independent prognostic factors was constructed for clinical application. The calibration curve showed that the nomogram was able to predict 1-, 3-, and 5-year PFS accurately, and it performed well in the external validation cohorts (concordance index: 0.828 and 0.864, respectively). CONCLUSION: The mRNA-based biomarker is a powerful and independent prognostic factor. Furthermore, the nomogram comprising our prognostic classifier is a promising predictor in identifying the progression risk of CSCC patients.

Adjuvant gamma knife surgery and image-guided, intensity-modulated radiation therapy for the treatment of sacral chordomas.

AIM: The aim of this study was to confirm whether patients with sacral chordoma benefit from adjuvant radiotherapy and to determine the optimal photon radiotherapy module for comprehensive treatment. BACKGROUND: Chordoma is a rare slow-growing neoplasm arisen from cellular remnants of the notochord. About 50% occur in the sacrococcygeal region. Surgical resection and adjuvant radiation therapy are recommended treatment due to the improving local control rate. MATERIALS AND METHODS: 118 patients treated by surgery and adjuvant radiotherapy from August 2003 to May 2015 were retrospectively analyzed. All patients received surgical resection after diagnosis. Among these patients, 44 were treated by exclusive surgery, and 48 were treated with adjuvant image-guided, intensity-modulated radiation therapy (IG-IMRT). In addition, 26 patients were treated with gamma knife surgery (GKS) after surgical resection. The median follow-up was 54 months for all patients. Kaplan-Meier analysis was used to calculate recurrence-free survival (RFS) overall survival (OS). RESULTS: Patients treated with adjuvant radiotherapy had better RFS (p = 0.014) than those treated exclusively by surgery. The patients in the IG-IMRT group exhibited better recurrence-free survival (p = 0.01) than the GKS group. Moreover, in the IG-IMRT group, patients treated by higher dose were associated with better RFS (p = 0.04). No significant difference in OS was found. No grade 3 late toxicity was found. CONCLUSIONS: We confirmed that adjuvant radiotherapy improved RFS but not OS in sacral chordoma patients after surgery. Furthermore, favorable RFS and low adverse event rates were observed following IG-IMRT. Our results suggest that high dose IG-IMRT is an appropriate module of adjuvant radiotherapy for sacral chordoma patients.

lncRNA TUG1-Mediated Mir-142-3p Downregulation Contributes to Metastasis and the Epithelial-to-Mesenchymal Transition of Hepatocellular Carcinoma by Targeting ZEB1.

BACKGROUND/AIMS: MicroRNA-142-3p (miR-142-3p) is dysregulated in many malignancies and may function as a tumor suppressor or oncogene in tumorigenesis and tumor development. However, few studies have investigated the clinical significance and biological function of miR-142-3p in hepatocellular carcinoma (HCC). METHODS: The expression levels of taurine upregulated gene 1 (TUG1), miR-142-3p, and zinc finger E-box-binding homeobox 1 (ZEB1) were evaluated in HCC tissues and cell lines by quantitative real-time PCR. MTT and colony formation assays were used to detect cell proliferation ability, transwell assays were used to assess cell migration and invasion, and luciferase reporter assays were used to examine the interaction between the long noncoding RNA TUG1 and miR-142-3p. Tumor formation was evaluated through in vivo experiments. RESULTS: miR-142-3p was significantly downregulated in HCC tissues, but TUG1 was upregulated in HCC tissues. Knockdown of TUG1 and upregulation of miR-142-3p inhibited cell proliferation, cell migration, cell invasion, and the epithelial-mesenchymal transition (EMT). miR-142-3p was found to be a prognostic factor of HCC, and the mechanism by which TUG1 upregulated ZEB1 was via direct binding to miR-142-3p. In vivo assays showed that TUG1 knockdown suppressed cell proliferation and the EMT in nude mice. CONCLUSION: The results of this study suggest that the TUG1/miR-142-3p/ ZEB1 axis contributes to the formation of malignant behaviors in HCC.