Thyroid dysfunction (TD) induced by PD-1/PD-L1 inhibitors in advanced lung cancer.

Background: Thyroid Dysfunction (TD) is a common immune-related adverse events (irAEs) in the treatment of advanced lung cancer with programmed cell death protein 1 (PD-1) and programmed death 1 ligand (PD-L1) inhibitors, with incidence accounting for 6-8% of all irAEs. The incidence of TD is receiving increasing attention from clinicians, given its potential impact on clinical efficacy. However, the molecular mechanisms, biomarkers, and clinical impact of TD resulting from PD-1/PD-L1 inhibitor treatment in advanced lung cancer are unclear. Objective: To present a comprehensive review of current advancements in research about the molecular mechanisms, influential factors, and clinical manifestations in the treatment of advanced lung cancer with PD-1 and PD-L1 inhibitors, as well as the correlation between TD and the efficacy of PD-1 and PD-L1 inhibitors. Methods: A systematic search was conducted using PubMed, Web of Science, Cochrane Library, Embase and Google Scholar databases, with the keywords including thyroid dysfunction, efficacy, mechanisms, immune checkpoint inhibitors, PD-1/PD-L1 inhibitors, and advanced lung cancer. Results: PD-1/PD-L1 inhibitors can induce T cell-mediated destructive thyroiditis, thyroid autoantibody-mediated autoimmunity, and a decrease in the number of immunosuppressive monocytes (circulating cluster of differentiation (CD)14+ human leukocyte antigen (HLA)-DRlow/negatives monocytes, CD14+ HLA-DR + lo/neg), leading to TD. Several factors, including peripheral blood inflammatory markers, body mass index (BMI), baseline thyroid-stimulating hormone (TSH) level, gender, smoking history, hypertension, and previous opioid use, may also contribute to the development of TD. However, there is currently a lack of reliable predictive biomarkers for TD, although anti-thyroid antibodies, TSH levels, and peripheral blood inflammatory markers are expected to be predictive.Interestingly, some studies suggested a positive correlation between TD and clinical efficacy, i.e., patients experiencing TD showed better outcomes in objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), and overall survival (OS), compared with those without TD. However, most of these studies were single-center and had small sample sizes, so more multi-center studies are needed to provide further data support. Conclusion: TD resulting from PD-1/PD-L1 inhibitor treatment in advanced lung cancer may be associated with good clinical outcomes. The clarification of the molecular mechanisms underlying TD and the identification of reliable predictive biomarkers will guide clinicians in managing TD in this patient population.

How do crude oil futures hedge crude oil spot risk after the COVID-19 outbreak? A wavelet denoising-GARCHSK-SJC Copula hedge ratio estimation method.

In the current paper, we investigate the problem of how do crude oil futures hedge crude oil spot risk after the COVID-19 outbreak. Specifically, given that noise, conditional higher moments and asymmetric tail dependence may exist in crude oil markets, a Wavelet denoising-GARCHSK-SJC Copula hedge ratio estimation method is proposed to construct hedging portfolios in crude oil markets during the epidemic period. Based on the in-sample and out-of-sample results, the hedging roles of Brent futures and Shanghai crude oil (SC) futures for light and medium crude spots after the COVID-19 outbreak are further researched. The empirical results demonstrate that noise, conditional higher moments and asymmetric tail dependence do exist in crude futures and spots, which have impact on the precision of modeling results. Secondly, the Wavelet denoising-GARCHSK-SJC Copula hedge ratio estimation method outperforms all control groups, obtaining the best in-sample and out-of-sample hedging effectiveness. Finally, it is reported in the in-sample and out-of-sample hedging results that Brent is the optimal futures to hedge light oil, while SC is the optimal futures to hedge medium oil. The paper provides substantial recommendations for policymakers and investors.

Fecal gene detection based on next generation sequencing for colorectal cancer diagnosis.

BACKGROUND: Colorectal cancer (CRC) is one of the most common malignancies worldwide. Given its insidious onset, the condition often already progresses to advanced stage when symptoms occur. Thus, early diagnosis is of great significance for timely clinical intervention, efficacy enhancement, and prognostic improvement. Featuring high throughput, fastness, and rich information, next generation sequencing (NGS) can greatly shorten the detection time, which is a widely used detection technique at present. AIM: To screen specific genes or gene combinations in fecal DNA that are suitable for diagnosis and prognostic prediction of CRC, and to establish a technological platform for CRC screening, diagnosis, and efficacy monitoring through fecal DNA detection. METHODS: NGS was used to sequence the stool DNA of patients with CRC, which were then compared with the genetic testing results of the stool samples of normal controls and patients with benign intestinal disease, as well as the tumor tissues of CRC patients. Specific genes or gene combinations in fecal DNA suitable for diagnosis and prognostic prediction of CRC were screened, and their significances in diagnosing CRC and predicting patients' prognosis were comprehensively evaluated. RESULTS: High mutation frequencies of TP53, APC, and KRAS were detected in the stools and tumor tissues of CRC patients prior to surgery. Contrastively, no pathogenic mutations of the above three genes were noted in the postoperative stools, the normal controls, or the benign intestinal disease group. This indicates that tumor-specific DNA was detectable in the preoperative stools of CRC patients. The preoperative fecal expression of tumor-associated genes can reflect the gene mutations in tumor tissues to some extent. Compared to the postoperative stools and the stools in the two control groups, the pathogenic mutation frequencies of TP53 and KRAS were significantly higher for the preoperative stools (χ 2 = 7.328, P < 0.05; χ 2 = 4.219, P < 0.05), suggesting that fecal TP53 and KRAS genes can be used for CRC screening, diagnosis, and prognostic prediction. No significant difference in the pathogenic mutation frequency of the APC gene was found from the postoperative stools or the two control groups (χ 2 = 0.878, P > 0.05), so further analysis with larger sample size is required. Among CRC patients, the pathogenic mutation sites of TP53 occurred in 16 of 27 preoperative stools, with a true positive rate of 59.26%, while the pathogenic mutation sites of KRAS occurred in 10 stools, with a true positive rate of 37.04%. The sensitivity and negative predictive values of the combined genetic testing of TP53 and KRAS were 66.67% (18/27) and 68.97%, respectively, both of which were higher than those of TP53 or KRAS mutation detection alone, suggesting that the combined genetic testing can improve the CRC detection rate. The mutation sites TP53 exon 4 A84G and EGFR exon 20 I821T (mutation start and stop positions were both 7579436 for the former, while 55249164 for the latter) were found in the preoperative stools and tumor tissues. These "undetected" mutation sites may be new types of mutations occurring during the CRC carcinogenesis and progression, which needs to be confirmed through further research. Some mutations of "unknown clinical significance" were found in such genes as TP53, PTEN, KRAS, BRAF, AKT1, and PIK3CA, whose clinical values is worthy of further exploration. CONCLUSION: NGS-based fecal genetic testing can be used as a complementary technique for the CRC diagnosis. Fecal TP53 and KRAS can be used as specific genes for the screening, diagnosis, prognostic prediction, and recurrence monitoring of CRC. Moreover, the combined testing of TP53 and KRAS genes can improve the CRC detection rate.

EXTL3 could serve as a potential biomarker of prognosis and immunotherapy for prostate cancer and its potential mechanisms.

BACKGROUND: Exostosin like glycosyltransferase 3 (EXTL3) had been reported to be associated with immune deficiency and play prognostic roles in various cancers. However, little is known about the associations between EXTL3 and prostate cancer (PCa). Hence, this article was designed to clarify their associations. METHODS: All original data were downloaded from The Cancer Genome Atlas (TCGA) database. Gene set enrichment analysis (GSEA) and CellMiner database was utilized, respectively, to identify EXTL3-related signaling pathways and drugs. We explored the relationships between EXTL3 expression and immunity to further evaluate the involvement of EXTL3 in response to immunotherapies. LncRNA/RBP/EXTL3 mRNA networks were also identified for its potential mechanism. RESULTS: Compared with normal prostate samples, EXTL3 was poorly expressed in PCa samples not only in mRNA expression levels, but also in protein expression levels, with worse overall survival (P < 0.05) and this gene could be an independent prognostic biomarker for PCa (both P < 0.05). EXTL3 was revealed to be markedly linked with seven signaling pathways in PCa by GSEA, including calcium, chemokine, ERBB, JAK STAT, MAPK, WNT, oxidative phosphorylation pathways. EXTL3 expression was also revealed to be significantly associated with MSI, immune cells, immune checkpoint molecules, tumor microenvironment and immune cells infiltration. We further predicted immune responses of EXTL3 gene to immunotherapies by TIDE database and the IMvigor210 cohort. A total of six LncRNA/RBP/EXTL3 mRNA networks were eventually identified for its potential mechanisms. CONCLUSIONS: EXTL3 could serve as a potential biomarker of prognosis and immunotherapy for PCa and six LncRNA/RBP/EXTL3 mRNA networks were also identified for its potential mechanisms.

Role of Gut Microbiota in Pulmonary Arterial Hypertension.

Gut microbiota and its metabolites play an important role in maintaining host homeostasis. Pulmonary arterial hypertension (PAH) is a malignant clinical syndrome with a frightening mortality. Pulmonary vascular remodeling is an important feature of PAH, and its pathogenesis is not well established. With the progress of studies on intestinal microbes in different disease, cumulative evidence indicates that gut microbiota plays a major role in PAH pathophysiology. In this review, we will systematically summarize translational and preclinical data on the correlation between gut dysbiosis and PAH and investigate the role of gut dysbiosis in the causation of PAH. Then, we point out the potential significance of gut dysbiosis in the diagnosis and treatment of PAH as well as several problems that remain to be resolved in the field of gut dysbiosis and PAH. All of this knowledge of gut microbiome might pave the way for the extension of novel pathophysiological mechanisms, diagnosis, and targeted therapies for PAH.

Preoperative prediction of lymph node metastasis using deep learning-based features.

Lymph node involvement increases the risk of breast cancer recurrence. An accurate non-invasive assessment of nodal involvement is valuable in cancer staging, surgical risk, and cost savings. Radiomics has been proposed to pre-operatively predict sentinel lymph node (SLN) status; however, radiomic models are known to be sensitive to acquisition parameters. The purpose of this study was to develop a prediction model for preoperative prediction of SLN metastasis using deep learning-based (DLB) features and compare its predictive performance to state-of-the-art radiomics. Specifically, this study aimed to compare the generalizability of radiomics vs DLB features in an independent test set with dissimilar resolution. Dynamic contrast-enhancement images from 198 patients (67 positive SLNs) were used in this study. Of these subjects, 163 had an in-plane resolution of 0.7 × 0.7 mm2, which were randomly divided into a training set (approximately 67%) and a validation set (approximately 33%). The remaining 35 subjects with a different in-plane resolution (0.78 × 0.78 mm2) were treated as independent testing set for generalizability. Two methods were employed: (1) conventional radiomics (CR), and (2) DLB features which replaced hand-curated features with pre-trained VGG-16 features. The threshold determined using the training set was applied to the independent validation and testing dataset. Same feature reduction, feature selection, model creation procedures were used for both approaches. In the validation set (same resolution as training), the DLB model outperformed the CR model (accuracy 83% vs 80%). Furthermore, in the independent testing set of the dissimilar resolution, the DLB model performed markedly better than the CR model (accuracy 77% vs 71%). The predictive performance of the DLB model outperformed the CR model for this task. More interestingly, these improvements were seen particularly in the independent testing set of dissimilar resolution. This could indicate that DLB features can ultimately result in a more generalizable model.

Fully automated radiomic screening pipeline for osteoporosis and abnormal bone density with a deep learning-based segmentation using a short lumbar mDixon sequence.

BACKGROUND: Although lumbar bone marrow fat fraction (BMFF) has been demonstrated to be predictive of osteoporosis, its utility is limited by the requirement of manual segmentation. Additionally, quantitative features beyond simple BMFF average remain to be explored. In this study, we developed a fully automated radiomic pipeline using deep learning-based segmentation to detect osteoporosis and abnormal bone density (ABD) using a <20 s modified Dixon (mDixon) sequence. METHODS: In total, 222 subjects underwent quantitative computed tomography (QCT) and lower back magnetic resonance imaging (MRI). Bone mineral density (BMD) were extracted from L1-L3 using QCT as the reference standard; 206 subjects (48.8±14.9 years old, 140 females) were included in the final analysis, and were divided temporally into the training/validation set (142/64 subjects). A deep-learning network was developed to perform automated segmentation. Radiomic models were built using the same training set to predict ABD and osteoporosis using the mDixon maps. The performance was evaluated using the temporal validation set comprised of 64 subjects, along with the automated segmentation. Additional 25 subjects (56.1±8.8 years, 14 females) from another site and a different scanner vendor was included as independent validation to evaluate the performance of the pipeline. RESULTS: The automated segmentation achieved an outstanding mean dice coefficient of 0.912±0.062 compared to manual in the temporal validation. Task-based evaluation was performed in the temporal validation set, for predicting ABD and osteoporosis, the area under the curve, sensitivity, specificity, and accuracy were 0.925/0.899, 0.923/0.667, 0.789/0.873, 0.844/0.844, respectively. These values were comparable to that of manual segmentation. External validation (cross-vendor) was also performed; the area under the curve, sensitivity, specificity, and accuracy were 0.688/0.913, 0.786/0.857, 0.545/0.944, 0.680/0.920 for ABD and osteoporosis prediction, respectively. CONCLUSIONS: Our work is the first attempt using radiomics to predict osteoporosis with BMFF map, and the deep-learning based segmentation will further facilitate the clinical utility of the pipeline as a screening tool for early detection of ABD.

Effects of different surgical treatments on children with ankyloglossia: protocol for a systematic review and meta-analysis.

INTRODUCTION: Ankyloglossia is a situation where the tongue tip cannot go beyond the mandibular incisor because the frenulum linguae is short. It could affect children's health by interfering with their ability to talk, breast feeding and dental development. The most effective measure to control ankyloglossia is the surgical method. However, which surgical procedure is the best one is still controversial. Thus, this protocol aims to assess the effectiveness of different surgical interventions in children with ankyloglossia. METHODS AND ANALYSIS: PubMed, EMBASE, Cochrane Library, Web of Science and OVID will be searched for relevant information from inception to 31 May 2022. Observational studies in English that investigate the association between surgical methods and ankyloglossia will be included in this protocol. This protocol follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols. The Critical Appraisal Checklist for Analytical Cross-Sectional Studies and the Newcastle-Ottawa Quality Assessment Scale for longitudinal studies will be used to assess the included studies. The improvement of breast feeding and nipple pain will be the primary outcome. STATA V.15.1 will do the statistical analysis in the meta-analysis. Subgroup and meta-regression will be carried out based on the characteristics of included studies. ETHICS AND DISSEMINATION: This systematic review and meta-analysis will summarise relevant information on the effects of different surgical treatments on patients with ankyloglossia. The results will be disseminated through peer-reviewed publications. The data included in this study will be extracted from the published original studies. Thus, ethical approval and informed consent will not be required. PROSPERO REGISTRATION NUMBER: CRD42022323350.

Optimizing the Peritumoral Region Size in Radiomics Analysis for Sentinel Lymph Node Status Prediction in Breast Cancer.

RATIONALE AND OBJECTIVES: Peritumoral features have been suggested to be useful in improving the prediction performance of radiomic models. The aim of this study is to systematically investigate the prediction performance improvement for sentinel lymph node (SLN) status in breast cancer from peritumoral features in radiomic analysis by exploring the effect of peritumoral region sizes. MATERIALS AND METHODS: This retrospective study was performed using dynamic contrast-enhanced MRI scans of 162 breast cancer patients. The effect of peritumoral features was evaluated in a radiomics pipeline for predicting SLN metastasis in breast cancer. Peritumoral regions were generated by dilating the tumor regions-of-interest (ROIs) manually annotated by two expert radiologists, with thicknesses of 2 mm, 4 mm, 6 mm, and 8 mm. The prediction models were established in the training set (∼67% of cases) using the radiomics pipeline with and without peritumoral features derived from different peritumoral thicknesses. The prediction performance was tested in an independent validation set (the remaining ∼33%). RESULTS: For this specific application, the accuracy in the validation set when using the two radiologists' ROIs could be both improved from 0.704 to 0.796 by incorporating peritumoral features. The choice of the peritumoral size could affect the level of improvement. CONCLUSION: This study systematically investigates the effect of peritumoral region sizes in radiomic analysis for prediction performance improvement. The choice of the peritumoral size is dependent on the ROI drawing and would affect the final prediction performance of radiomic models, suggesting that peritumoral features should be optimized in future radiomics studies.

Implementation of the plasma MYCN/NAGK ratio to detect MYCN amplification in patients with neuroblastoma.

Detection of amplification of the MYCN gene is essential for determining optimal treatment and estimating prognosis of patients with neuroblastoma (NB). DNA FISH with neuroblastoma tissues or patient-derived bone marrow cells is the standard clinical practice for the detection of MYCN amplification. As tumor cells may often be unavailable, we developed a method to detect MYCN amplification in the plasma of patients with neuroblastoma. Taking single-copy NAGK DNA as reference, we used real-time quantitative PCR (qPCR) to determine the MYCN/NAGK ratio in the plasma of 115 patients diagnosed with NB. An increased MYCN/NAGK ratio in the plasma was consistent with MYCN amplification as assessed by DNA FISH. The AUC for a MYCN/NAGK ratio equal to 6.965 was 0.943, with 86% sensitivity and 100% specificity. Beyond the threshold of 6.965, the MYCN/NAGK ratio correlated with a heavier tumor burden. Event-free and overall survival of two years were significantly shortened in stage 4 patients with a MYCN/NAGK ratio higher than 6.965. Plasma MYCN/NAGK ratios increased in patients with progressive disease and relapse. Thus, we conclude that the determination of the plasma MYCN/NAGK ratio by qPCR is a noninvasive and reproducible method to measure MYCN amplification in patients with NB.

Avicularin inhibits cell proliferation and induces cell apoptosis in cutaneous squamous cell carcinoma.

Avicularin (AL), quercetin-3-α-L-arabinofuranoside, has various pharmacological properties such as anticancer and anti-infective effects. However, the potential molecular mechanism via which AL exerts its anticancer activity is not fully understood. Cutaneous squamous cell carcinoma (CSCC) is the second most common skin cancer, where metastasis has resulted in in effective clinical treatments. The aim of the present in vitro study was to investigate the anticancer effects and underlying mechanism of AL on human CSCC. The present results suggested that AL dose-dependently inhibited SCC13 cell viability and induced apoptosis. In addition, the present results suggested that AL induced apoptosis via repression of the mitogen-activated protein kinase kinase (MEK)/NF-κB signal pathway, thereby affecting the expression of apoptosis-related genes. Bax expression level was increased, while Bcl-2 expression level was decreased in SCC13 cells following AL treatment. In addition, the MEK/NF-κB signaling pathway-related genes p-MEK and phosphorylated-p65 were also decreased. The present results suggested that AL treatment increased the expression level of E-cadherin, but decreased the expression levels of N-cadherin, matrix metalloproteinase (MMP)-9 and vimentin in SCC13 cells. Collectively, the present results suggested that AL may have an anti-CSCC effect by inhibiting cell viability, inducing apoptosis and inhibiting epithelial-mesenchymal transition (EMT) of CSCC cells. The mechanism of these anti-CSCC effects was suggested to be via the regulation of apoptosis-related genes and EMT-related genes, and the inhibition of the MEK/NF-κB signaling pathway.

Plantamajoside represses the growth and metastasis of malignant melanoma.

Plantamajoside (PMS) has been shown to have anticancer effects and is the main compound of Plantago asiatica. The aim of the present study was to investigate the effects of PMS on malignant melanoma and its molecular mechanisms. The malignant melanoma cell line A2058 was treated with different concentrations of PMS (0, 20, 80 and 160 µg/ml) for 24, 48 or 72 h, followed by cell viability detection using the Cell Counting Kit-8 assay. The present results suggested that PMS inhibited cell viability in a dose-dependent manner. In addition, flow cytometry was used to analyze cell apoptosis, and Transwell assays were used to investigate cell migration and invasion. The present results suggested that PMS induced A2058 cell apoptosis, and inhibited cell invasion and migration in a dose-dependent manner. In order to study the molecular mechanism by which PMS inhibited malignant melanoma growth and metastasis, reverse transcription-quantitative PCR and western blotting were used to determine the expression levels of apoptotic-related genes and PI3K/AKT signaling pathway-related proteins. The present results indicated that PMS inhibited the protein and mRNA expression of Bcl-2, and promoted the expression of Bax and caspase-3 in a dose-dependent manner. The protein expression level of phosphorylated-AKT was dose-dependently reduced by PMS treatment. Collectively, the present results suggested that PMS inhibited the invasion, migration and viability of malignant melanoma cells. In addition, PMS induced apoptosis by regulating the expression levels of apoptotic-related genes and the activation of the PI3K/AKT signaling pathway, thereby exerting anti-malignant melanoma effects.

Plasma cell-free DNA quantification is highly correlated to tumor burden in children with neuroblastoma.

To evaluate plasma cell-free DNA (cfDNA) as a promising biomarker for neuroblastoma (NB) tumor burden. Seventy-nine eligible patients with newly diagnosed NB were recruited from Beijing Children's Hospital between April 2016 and April 2017. Additionally, from September 2011 to June 2017, 79 patients with stable NB were evaluated with a median follow-up time of 21 months. Approximately 2 mL of peripheral blood was drawn upon enrollment, and plasma cfDNA levels were measured via quantitative polymerase chain reaction (qPCR). Total cfDNA analysis was performed using the long interspersed nuclear element 1 (LINE-1) 79 bp fragment, and DNA integrity was calculated by the ratio of the LINE-1 300 bp fragment to the LINE-1 79 bp fragment. A total of 79 NB patients with a median age of 36 months comprised the group of newly diagnosed NB patients. The main primary tumor site was the retroperitoneal and adrenal region (81%). Three or more metastatic sites were found in 17.7% of patients. Stable NB patients older than 18 months comprised 98.7% of the stable NB patients. Neuron-specific enolase (NSE), lactate dehydrogenase (LDH), and cfDNA levels were dramatically increased in the newly diagnosed NB patients and significantly different from those in the stable NB patients. Moreover, the concentration of cfDNA was much higher in patients with larger tumors. By analyzing the area under the receiver operator characteristic (ROC) curve (AUC), the areas of total cfDNA, NSE, and LDH levels were 0.953, 0.929, and 0.906, respectively. The sensitivity and specificity data clarified that the level of circulating cfDNA in plasma can be considered as a reliable biomarker for describing tumor load in NB. The plasma cfDNA concentration was as good as the levels of LDH and NSE to discriminate the tumor burden in children with NB.