Electroacupuncture facilitates vascular normalization by inhibiting Glyoxalase1 in endothelial cells to attenuate glycolysis and angiogenesis in triple-negative breast cancer.

Recent therapeutic strategies for the treatment of triple-negative breast cancer (TNBC) have shifted the focus from vascular growth factors to endothelial cell metabolism. This study highlights the underexplored therapeutic potential of peri-tumoral electroacupuncture, a globally accepted non-pharmacological intervention for TNBC, and molecular mechanisms. Our study showed that peri-tumoral electroacupuncture effectively reduced the density of microvasculature and enhanced vascular functionality in 4T1 breast cancer xenografts, with optimal effects on day 3 post-acupuncture. The timely integration of peri-tumoral electroacupuncture amplified the anti-tumor efficacy of paclitaxel. Multi-omics analysis revealed Glyoxalase 1 (Glo1) and the associated methylglyoxal-glycolytic pathway as key mediators of electroacupuncture-induced vascular normalization. Peri-tumoral electroacupuncture notably reduced Glo1 expression in the endothelial cells of 4T1 xenografts. Using an in vivo matrigel plug angiogenesis assay, we demonstrated that either Glo1 knockdown or electroacupuncture inhibited angiogenesis. In contrast, Glo1 overexpression increased blood vessel formation. In vitro pharmacological inhibition and genetic knockdown of Glo1 in human umbilical vein endothelial cells inhibited proliferation and promoted apoptosis via downregulating the methylglyoxal-glycolytic pathway. The study using the Glo1-silenced zebrafish model further supported the role of Glo1 in vascular development. This study underscores the pivotal role of Glo1 in peri-tumoral electroacupuncture, spotlighting a promising avenue for enhancing vascular normalization and improving TNBC treatment outcomes.

TET2-STAT3-CXCL5 nexus promotes neutrophil lipid transfer to fuel lung adeno-to-squamous transition.

Phenotypic plasticity is a rising cancer hallmark, and lung adeno-to-squamous transition (AST) triggered by LKB1 inactivation is significantly associated with drug resistance. Mechanistic insights into AST are urgently needed to identify therapeutic vulnerability in LKB1-deficient lung cancer. Here, we find that ten-eleven translocation (TET)-mediated DNA demethylation is elevated during AST in KrasLSL-G12D/+; Lkb1L/L (KL) mice, and knockout of individual Tet genes reveals that Tet2 is required for squamous transition. TET2 promotes neutrophil infiltration through STAT3-mediated CXCL5 expression. Targeting the STAT3-CXCL5 nexus effectively inhibits squamous transition through reducing neutrophil infiltration. Interestingly, tumor-infiltrating neutrophils are laden with triglycerides and can transfer the lipid to tumor cells to promote cell proliferation and squamous transition. Pharmacological inhibition of macropinocytosis dramatically inhibits neutrophil-to-cancer cell lipid transfer and blocks squamous transition. These data uncover an epigenetic mechanism orchestrating phenotypic plasticity through regulating immune microenvironment and metabolic communication, and identify therapeutic strategies to inhibit AST.

The value of radiomics model based on ultrasound image features in the differentiation between minimal breast cancer and small benign breast masses.

BACKGROUND: Female breast cancer has surpassed lung cancer as the most common cancer, and is also the main cause of cancer death for women worldwide. Breast cancer <1 cm showed excellent survival rate. However, the diagnosis of minimal breast cancer (MBC) is challenging. OBJECTIVE: The purpose of our research is to develop and validate an radiomics model based on ultrasound images for early recognition of MBC. METHODS: 302 breast masses with a diameter of <10 mm were retrospectively studied, including 159 benign and 143 malignant breast masses. The radiomics features were extracted from the gray-scale ultrasound image of the largest face of each breast mass. The maximum relevance minimum reduncancy and recursive feature elimination methods were used to screen. Finally, 10 features with the most discriminating value were selected for modeling. The random forest was used to establish the prediction model, and the rad-score of each mass was calculated. In order to evaluate the effectiveness of the model, we calculated and compared the area under the curve (AUC) value, sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of the model and three groups with different experience in predicting small breast masses, and drew calibration curves and decision curves to test the stability and consistency of the model. RESULTS: When we selected 10 radiomics features to calculate the rad-score, the prediction efficiency was the best, the AUC values for the training set and testing set were 0.840 and 0.793, which was significantly better than the insufficient experience group (AUC = 0.673), slightly better than the moderate experience group (AUC = 0.768), and was inferior to the experienced group (AUC = 0.877). The calibration curve and decision curve also showed that the radiomics model had satisfied stability and clinical application value. CONCLUSION: The radiomics model based on ultrasound image features has a satisfied predictive ability for small breast masses, and is expected to become a potential tool for the diagnosis of MBC, and it is a zero cost (in terms of patient participation and imaging time).

Development of ensemble learning models for prognosis of hepatocellular carcinoma patients underwent postoperative adjuvant transarterial chemoembolization.

Background: Postoperative adjuvant transarterial chemoembolization (PA-TACE) has been increasing widely used to improve the prognosis of hepatocellular carcinoma (HCC) patients. However, clinical outcomes vary from patient to patient, which calls for individualized prognostic prediction and early management. Methods: A total of 274 HCC patients who underwent PA-TACE were enrolled in this study. The prediction performance of five machine learning models was compared and the prognostic variables of postoperative outcomes were identified. Results: Compared with other machine learning models, the risk prediction model based on ensemble learning strategies, including Boosting, Bagging, and Stacking algorithms, presented better prediction performance for overall mortality and HCC recurrence. Moreover, the results showed that the Stacking algorithm had relatively low time consumption, good discriminative ability, and the best prediction performance. In addition, according to time-dependent ROC analysis, the ensemble learning strategies were found to perform well in predicting both OS and RFS for the patients. Our study also found that BCLC Stage, hsCRP/ALB and frequency of PA-TACE were relatively important variables in both overall mortality and recurrence, while MVI contributed more to the recurrence of the patients. Conclusion: Among the five machine learning models, the ensemble learning strategies, especially the Stacking algorithm, could better predict the prognosis of HCC patients following PA-TACE. Machine learning models could also help clinicians identify the important prognostic factors that are clinically useful in individualized patient monitoring and management.

Multimodal ultrasonography of male primary breast lymphoma.

① Gray scale ultrasound showed multiple hypoechoic masses of varying sizes in the right breast. The larger one was 1.8 × 0.7 cm (arrow), oval in shape, with clear boundaries, and lymphatic hilar-like structures. ② Color Doppler ultrasonography showed blood flow signals within the hypoechoic mass, and the larger (arrow) mass showed blood flow signals similar to lymphatic hilum. ③ Elastography showed the mass was soft and blue (short arrow) or green (long arrow) in texture, and the surrounding tissue was hard and red in texture. ④ Contrast-enhanced ultrasound showed that after 19 s of contrast agent injection, the whole breast showed a 'snowflake' high enhancement, but no enhancement was observed in local areas (arrow). ⑤ The ultrasound-guided puncture image clearly showed the puncture needle (arrow) insert into the hypoechoic mass for biopsy. ⑥ The arrow in the pathological image (HE, 20 × 10 times) showed tumor cells.

Invasive acupuncture for gastroparesis after thoracic or abdominal surgery: a systematic review and meta-analysis.

OBJECTIVES: This meta-analysis aimed to systematically evaluate the efficacy of acupuncture in treating postsurgical gastroparesis syndrome (PGS) after thoracic or abdominal surgery. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Twelve databases (PubMed, Embase, Cochrane Library Cochrane Central Register of Controlled Trials (CENTRAL), Medline (Ovid) (from 1946), Web of Science, EBSCO, Scopus, Open Grey, China National Knowledge Infrastructure (CNKI), Wanfang Database, Chinese Scientific Journals Database (VIP) and China Biology Medicine disc (CBM)) and three registration websites (WHO International Clinical Trials Registry Platform (ICTRP), ClinicalTrials.gov, and Chinese Clinical Trial Registry (ChiCTR)) were searched from the inception to September 2022, and citations of the included literature were screened. ELIGIBILITY CRITERIA: All randomised controlled trials addressing invasive acupuncture for PGS. DATA EXTRACTION AND SYNTHESIS: Key information on the included studies was extracted by two reviewers independently. Risk ratio (RR) with 95% CI was used for categorical data, and mean difference with 95% CI for continuous data. The quality of evidence was assessed using Grading of Recommendations Assessment, Development and Evaluation. Outcomes were conducted with trial sequential analysis (TSA). RESULTS: Fifteen studies with 759 patients met the inclusion criteria. Subgroup analyses revealed that compared with the drug group, the drug and acupuncture group had a greater positive effect on the total effective rate (TER) (nine trials, n=427; RR=1.20; 95% CI 1.08 to 1.32; P-heterogeneity=0.20, I2=28%, p=0.0004) and the recovery rate (RCR) (six trials, n = 294; RR = 1.61; 95% CI 1.30 to 1.98; P-heterogeneity=0.29, I2=19%, p<0.0001) of PGS after abdominal surgery. However, acupuncture showed no significant advantages in terms of the TER after thoracic surgery (one trial, p=0.13) or thoracic/abdominal surgery-related PGS (two trials, n = 115; RR=1.18; 95% CI 0.89 to 1.57; P-heterogeneity=0.08, I2=67%, p=0.24) and the RCR after thoracic/abdominal surgery (two trials, n=115; RR=1.40; 95% CI 0.97 to 2.01; P-heterogeneity=0.96, I2=0%, p=0.07). The quality of evidence for TER and RCR was moderate certainty. Only one study reported an acupuncture-related adverse event, in the form of mild local subcutaneous haemorrhage and pain that recovered spontaneously. TSA indicated that outcomes reached a necessary effect size except for clinical symptom score. CONCLUSION: Based on subgroup analysis, compared with the drug treatment, acupuncture combined drug has significant advantages in the treatment of PGS associated with abdominal surgery, but not with thoracic surgery. PROSPERO REGISTRATION NUMBER: CRD42022299189.

A nomogram based on ultrasound characteristics to predict large-number cervical lymph node metastasis in papillary thyroid carcinoma.

To establish a nomogram for predicting large-number cervical lymph node metastases (LNMs) of primary papillary thyroid carcinoma (PTC) based on ultrasound characteristics. This retrospective study included patients with PTC diagnosed by pathological examination and who underwent surgery between August 2015 and May 2021 at Hwa Mei Hospital, University of Chinese Academy of Sciences (Ningbo, China). Large-number LNM was defined as >5 lymph nodes with metastases. The patients were propensity score-matched (PSM) for age and sex. A multivariable analysis was used to determine the risk factors for massive LNM. After PSM, the 78 patients with large-number LNM were matched with 312 patients with small-number LNM. Compared with the patients with small-number LNM, those with large-number LNM had larger tumors (13.0 ± 7.7 vs. 6.8 ± 3.8 mm, p < 0.001), and higher frequencies of multifocal nodules (42.3% vs. 22.4%, p < 0.001), taller-than-wide shape (82.1% vs. 56.7%, p < 0.001), calcifications (76.9% vs. 47.4%, p < 0.001), microcalcifications (68.0% vs. 36.5%, p < 0.001), capsule invasion (32.1% vs. 17.6%, p = 0.005), and ultrasound diagnosis of LNM (44.9% vs. 9.3%, p < 0.001). The multivariable analysis showed that nodule size (OR = 1.19, 95%CI: 1.11-1.27, p < 0.001), multifocal disease (OR = 2.50, 95%CI: 1.30-4.80, p = 0.006), taller-than-wide shape (OR = 0.45, 95%CI: 0.22-0.93, p = 0.032), and ultrasound diagnosis of LNM (OR = 5.57, 95%CI: 2.73-11.37, p < 0.001) were independently associated with large-number LNM. A nomogram was built, and the area under the receiver operating characteristics curve was 0.86 (95%CI: 0.81-0.90). A nomogram was successfully built to predict large-number LNM in patients with PTC, based on nodule size, multifocality, taller-than-wide shape, and ultrasound diagnosis of LNM.

Integrated analysis on the N6-methyladenosine-related long noncoding RNAs prognostic signature, immune checkpoints, and immune cell infiltration in clear cell renal cell carcinoma.

BACKGROUND: Patients with advanced clear cell renal cell carcinoma (ccRCC) have a poor prognosis and lack effective prognostic biomarkers. N6-methyladenosine-related lncRNAs (m6A-related long noncoding RNAs [lncRNAs]) have been confirmed to be associated with the development of multiple tumors, but its role in ccRCC is not clear. METHODS: Gene expression data and clinical information of ccRCC patients were extracted from The Cancer Genome Atlas Database. The prognostic m6A-related lncRNAs were obtained by Pearson's correlation analysis and univariate Cox regression analysis. Afterward, the cluster classification and its correlation with prognosis, clinical characteristics, and immunity were analyzed. LASSO regression was used to establish the prognostic risk model. The predictive performance of the prognostic model was evaluated and validated by survival analysis and receiver operating characteristic curve analysis, et al. The expression of immune checkpoints and immune cell infiltration in patients with different risks were systematically analyzed. RESULTS: A total of 27 prognostic m6A-related lncRNAs were identified. These m6A-related lncRNAs were differentially expressed between tumor and normal tissues. Among them, 24 high-risk m6A-related lncRNAs were overexpressed in Cluster 2 and correlated with poor prognosis, low stromal score, high expression of immune checkpoints, and immunosuppressive cells infiltration. Based upon, a prognostic risk model composed of seven m6A-related lncRNAs was constructed. After a series of analyses, it was proved that this model had good sensitivity and specificity, and could predict the prognosis of patients with different clinical stratification. The expression of PD-1, PD-L1, CTLA-4, LAG-3, TIM-3, and TIGIT were significantly increased in the high-risk patients, and there was a correlation between the risk score and immune cell infiltration. CONCLUSIONS: The seven m6A-related lncRNAs prognostic risk signature showed reliable prognostic predictive power for ccRCC and was associated with the expression of immune checkpoints and immune cell infiltration. This seven m6A-related lncRNAs signature will be helpful in managing ccRCC and guiding individualized immunotherapy.

Heat Shock Protein 90 Family Isoforms as Prognostic Biomarkers and Their Correlations with Immune Infiltration in Breast Cancer.

BACKGROUND: The heat shock protein 90 (HSP90s) family is composed of molecular chaperones composed of four isoforms in humans, which has been widely reported as unregulated in various kinds of cancers. Nevertheless, the role of each HSP90s isoform in prognosis and immune infiltration in distinct subtypes of breast cancer (BRAC) remains unclear. METHODS: Public online databases including the Oncomine, UALCAN, Kaplan-Meier Plotter, Tumor IMmune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA), GeneMANIA, and Database for Annotation, Visualization, and Integrated Discovery (DAVID) were integrated to perform bioinformatic analyses and to explore the possible associations among HSP90s gene expression, prognosis, and immune infiltration in BRAC. RESULTS: The mRNA expression of all HSP90s members was elevated in distinct clinical stages and subtypes of BRAC, compared with the normal breast tissue (P < 0.05). Overexpressed HSP90AA1 was associated with poor prognosis, particularly, both short overall survival (OS) and release-free survival (RFS) in Basal-like BRAC patients; overexpressed HSP90AB1 and HSP90B1 were both associated with poor RFS in Luminal A BRAC patients, while overexpressed TRAP1 was associated with favorable RFS in Luminal A BRAC patients. Moreover, HSP90s gene expression in BRAC showed correlations with the infiltration of CD8+ T cells, neutrophils, macrophages, and dendritic cells (DCs), as well as the activation of tumor-associated macrophages (TAMs), DCs, and CD4+ helper T (Th) cells. The underlying mechanisms of HSP90s modulating tumor-infiltrating immune cells (TIICs) might be related with their functions in antigen processing and presentation, major histocompatibility complex (MHC) binding, and assisting client proteins. CONCLUSION: This study demonstrated that HSP90s family genes were overexpressed and might be serve as prognostic biomarkers in subtypes of BRAC. It might be a novel breakthrough point of BRAC treatment to regulate immune infiltration in BRAC microenvironment for more effective anticancer immunity through pharmacological intervention of HSP90s.

Mechanisms of Core Chinese Herbs against Colorectal Cancer: A Study Based on Data Mining and Network Pharmacology.

Colorectal cancer (CRC) is now the second most deadly cancer globally. Chinese herbal medicine (CHM) plays an indispensable role in CRC treatment in China. However, the core herbs (the CHs) in the treatment of CRC and their underlying therapeutic mechanisms remain unclear. This study aims to uncovering the CHs and their mechanisms of action of CRC treatment, applying data mining and network pharmacology approach. First, CHM prescriptions treating CRC were collected from clinical studies from the Chinese National Knowledge Infrastructure (CNKI) and MEDLINE databases, and the CHs were identified through data mining. Then, the bioactive compounds and the corresponding putative targets of the CHs were obtained from three traditional Chinese medicine (TCM) databases. CRC related targets were acquired from three disease databases; the overlapping targets between the CHs and CRC were identified as the therapeutic targets. Subsequently, functional enrichment analysis was performed to elucidate the mechanisms of the CHs on CRC. Moreover, networks were constructed to screen the major bioactive compounds and therapeutic targets. Finally, prognostic values of the major target genes were evaluated by survival analysis, and molecular docking simulation was performed to assess the binding affinity of key targets and major bioactive compounds. It came out that 10 the CHs from 113 prescriptions and 190 bioactive compounds with 118 therapeutic targets were identified. The therapeutic targets were mainly enriched in the biological progress of transcription, apoptosis, and response to cytokine. Various cancer-associated signaling pathways, including microRNAs, TNF, apoptosis, PI3K-Akt, and p53, were involved. Furthermore, 15 major bioactive compounds and five key target genes (VEGFA, CASP3, MYC, CYP1Y1, and NFKB1) with prognostic significance were identified. Additionally, most major bioactive compounds might bind firmly to the key target proteins. This study provided an overview of the anti-CRC mechanisms of the CHs, which might refer to the regulation of apoptosis, transcription, and inflammation.

Development and validation of a novel immune-related prognostic model in lung squamous cell carcinoma.

Background: The immune system plays an important role in the development of lung squamous cell carcinoma (LUSC). Therefore, immune-related genes (IRGs) expression may be an important predictor of LUSC prognosis. However, a prognostic model based on IRGs that can systematically assess the prognosis of LUSC patients is still lacking. This study aimed to construct a LUSC immune-related prognostic model by using IRGs. Methods: Gene expression data about LUSC were obtained from The Cancer Genome Atlas (TCGA). Differential expression analysis and univariate Cox regression analysis were performed to identify prognostic differentially expressed IRGs. A prognostic model was constructed using the Lasso and multivariate Cox regression analyses. Then we validated the performance of the prognostic model in training and test cohorts. Furthermore, associations with clinical variables and immune infiltration were also analyzed. Results: 593 differentially expressed IRGs were identified, and 8 of them were related to prognosis. Then a transcription factor regulatory network was established. A prognostic model consisted of 4 immune-related genes was constructed by using Lasso and multivariate Cox regression analyses. The prognostic value of this model was successfully validated in training and test cohorts. Further analysis showed that the prognostic model could be used independently to predict the prognosis of LUSC patients. The relationships between the risk score and immune cell infiltration indicated that the model could reflect the status of the tumor immune microenvironment. Conclusions: We constructed a risk model using four PDIRGs that can accurately predict the prognosis of LUSC patients. The risk score generated by this model can be used as an independent prognostic indicator. Moreover, the model can predict the infiltration of immune cells in patients, which is conducive to the prediction of patient sensitivity to immunotherapy.

Differential Diagnosis of Benign and Malignant Thyroid Nodules Using Deep Learning Radiomics of Thyroid Ultrasound Images.

PURPOSE: We aimed to propose a highly automatic and objective model named deep learning Radiomics of thyroid (DLRT) for the differential diagnosis of benign and malignant thyroid nodules from ultrasound (US) images. METHODS: We retrospectively enrolled and finally include US images and fine-needle aspiration biopsies from 1734 patients with 1750 thyroid nodules. A basic convolutional neural network (CNN) model, a transfer learning (TL) model, and a newly designed model named deep learning Radiomics of thyroid (DLRT) were used for the investigation. Their diagnostic accuracy was further compared with human observers (one senior and one junior US radiologist). Moreover, the robustness of DLRT over different US instruments was also validated. Analysis of receiver operating characteristic (ROC) curves were performed to calculate optimal area under it (AUC) for benign and malignant nodules. One observer helped to delineate the nodules. RESULTS: AUCs of DLRT were 0.96 (95% confidence interval [CI]: 0.94-0.98), 0.95 (95% confidence interval [CI]: 0.93-0.97) and 0.97 (95% confidence interval [CI]: 0.95-0.99) in the training, internal and external validation cohort, respectively, which were significantly better than other deep learning models (P < 0.01) and human observers (P < 0.001). No significant difference was found when applying DLRT on thyroid US images acquired from different US instruments. CONCLUSIONS: DLRT shows the best overall performance comparing with other deep learning models and human observers. It holds great promise for improving the differential diagnosis of benign and malignant thyroid nodules.

Pathological diagnosis and treatment outcome of gastric metastases from small cell lung cancer: A case report.

Small cell lung cancer (SCLC) is a type of lung cancer characterized by a rapid disease progression and poor prognosis. Its diagnosis is often accompanied by distant metastasis. A literature review revealed that metastases to the stomach from breast, lung and esophageal cancer are frequently reported. While SCLC is a common pathological subtype of lung cancer, literature on SCLC with gastric metastases is sporadic. The present study reviewed the literature using databases, including PubMed, WanFang Data and China National Knowledge Infrastructure, to analyze the clinicopathological features and outcome of patients with gastric metastases from SCLC. A total of 11 case reports and 6 retrospective studies comprising of 19 cases were compared and analyzed. In addition to the aforementioned studies, a case study describing a patient who survived for 10 months following a diagnosis of SCLC with gastric metastases is presented. The aim of the present study was to increase the understanding regarding the diagnosis and treatment of SCLC gastric metastasis.

Treatment of severe rash caused by crizotinib with both traditional Chinese medicine and Western medicine: Two case reports and literature review.

RATIONALE: Lung adenocarcinoma is the most common pathologic pattern of lung cancer. During the past decades, a number of targeted agents have been explored to treat advanced lung adenocarcinoma. Recently, Crizotinib, the antagonist of anaplastic lymphoma kinase (ALK), has been widely used in ALK-rearranged lung cancer treatment. Crizotinib is generally well tolerated while its most frequent adverse events include visual disorders, gastrointestinal disturbances, cardiac and endocrine abnormalities. Rash caused by crizotinib is rarely seen, and there are few case reports of severe rash caused by crizotinib. PATIENT CONCERNS AND DIAGNOSES: Here we report cases of an 81-year-old man and a 66-year-old woman with ALK-rearranged advanced lung adenocarcinoma. When patients came to our department, they both had crizotinib-induced severe rash. INTERVENTIONS: Crizotinib was initiated as the 1st-line treatment without other therapies. We treated severe rash with traditional Chinese medicine (TCM) therapy called Zhiyang Pingfu liquid along with Western medicine. Zhiyang Pingfu liquid consists of Scutellaria baicalensis 20 g, Portulaca oleracea 30 g, Cortex Dictamni 30 g, Sophora flavescens 30 g, and other substances. Western medicine includes Minocycline hydrochloride tablets and Aprepitant capsules. OUTCOMES: Both patients achieved a partial response when treated with crizotinib, and suffered from severe rash. With Zhiyang Pingfu liquid and Western medicine, their rash gradually disappeared with no sign of cancer progression. Also the male patient did not relieve after taking only antibiotics (standard therapy) and anti-allergic medicine. LESSONS: Despite the dramatic benefit of crizotinib for patients with ALK rearrangement, crizotinib-induced severe rash needs to be dealt with caution. This is the 1st case in which TCM and Western medicine are used to successfully treat crizotinib-induced severe rash. The mechanism of crizotinib-induced rash deserves further attention in future research.