CircSEMA6A upregulates PRRG4 by targeting MiR-520h and recruiting ELAVL1 to affect cell invasion and migration in papillary thyroid carcinoma.

Objective: As the most prevalent type of thyroid malignancy, papillary thyroid carcinoma (PTC) accounts for over 80% of all thyroid cancers. Circular RNAs (circRNAs) have been found to regulate multiple cancers, including PTC. Materials and methods: Quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting were used to analyse RNA and protein levels. Fluorescence in situ hybridization (FISH) was used to detect the distribution of the target genes. Functional experiments and animal experiments were implemented to analyse the biological functions of target genes in vitro and in vivo. Luciferase reporter, RNA pulldown, RNA binding protein immunoprecipitation (RIP) and mRNA stability assays were used to probe the underlying mechanisms. Results: CircSEMA6Awas found to be upregulated in PTC tissues and cells, and its circular structure was verified. CircSEMA6A promotes PTC cell migration and invasion. Moreover, circSEMA6A functions as a competing endogenous RNA (ceRNA) to upregulate proline rich and Gla domain 4 (PRRG4) expression by sponging microRNA-520h (miR-520h). CircSEMA6A recruits ELAV1 to stabilize PRRG4 mRNA and drives PTC progression via PRRG4. Conclusion: CircSEMA6A upregulates PRRG4 by targeting miR-520h and recruiting ELAVL1 to affect the invasion and migration of PTC cells, offering insight into the molecular mechanisms of PTC.

[Analysis of Delphain lymph node detection rate, metastasis rate and risk factors for metastasis in papillary thyroid adenocarcinoma patients].

Objective:To investigate the detection rate and metastasis rate of delphain lymph node （DLN）in thyroid papillary adenocarcinoma（PTC） and to analyze the risk factors for DLN metastasis. Methods:The clinicopathological data of 200 PTC patients admitted to the from January 2018 to June 2020 were retrospectively analyzed, and the detection of DLN was clearly recorded in the pathological reports of all patients. The number of DLN detected, the number of metastasis, the detection rate and the metastasis rate were counted. The clinicopathological factors that might affect DLN metastasis were analyzed by univariate analysis and multivariate Logistic regression analysis, including gender, age, tumor size and tumor location. Results:DLN was detected in 121 of 200 PTC patients, with a detection rate of 60.50% （121/200）. DLN metastasis was found in 46 of the 121 patients with a metastasis rate of 38.02% （46/121）.Univariate analysis showed that tumor diameter, multiple foci, capsular invasion, extradandular invasion, lymphatic vascular invasion, lymph node metastasis in central region （excluding DLN）, and lateral cervical lymph node metastasis were the risk factors for DLN metastasis of PTC （P<0.05）. Gender, age, tumor location, bilateral tumors, Hashimoto's thyroiditis and BRAFV600E mutation were not significantly correlated with DLN metastasis of PTC（P>0.05）. The 7 variables with statistically significant differences in univariate analysis were incorporated into Logistic regression model for multivariate analysis, and the results showed that, Tumor diameter ≥1.0 cm, capsule invasion, lymphatic vascular invasion, lymph node metastasis in central region （excluding DLN）, and lateral cervical lymph node metastasis were independent risk factors for DLN metastasis of PTC （OR= 3.386-9.186, P<0.05）. The sensitivity and specificity of DLN metastasis in predicting central lymph node （excluding DLN） metastasis in PTC patients were 36.79% and 92.55%, respectively, while the sensitivity and specificity of DLN metastasis in predicting lateral cervical lymph node metastasis were 41.03% and 81.37%, respectively.The incidence of central lymph node metastasis （excluding DLN） in DLN-positive patients were was 4.94 times higher than that in DLN-negative patients, and the incidence of lateral neck lymph node metastasis in DLN-positive patients were 2.20 times higher than that in DLN-negative patients. Conclusion:The detection rate and metastasis rate of DLN in PTC patients were higher, DLN metastasis predicts more extensive lymph node metastasis, and DLN metastasis was related to multiple factors,among which tumor diameter ≥ 1.0 cm, capsule invasion, lymphatic vascular infiltration, lymph node metastasis in the central region （excluding DLN）, and lateral cervical lymph node metastasis were independent risk factors for DLN metastasis of PTC. Therefore, PTC patients with the above characteristics should actively explore DLN and formulate appropriate surgical strategies.

Construction of a Diagnostic Model for Small Cell Lung Cancer Combining Metabolomics and Integrated Machine Learning.

BACKGROUND: To date, no study has systematically explored the potential role of serum metabolites and lipids in the diagnosis of small cell lung cancer (SCLC). Therefore, we aimed to conduct a case-cohort study that included 191 cases of SCLC, 91 patients with lung adenocarcinoma, 82 patients with squamous cell carcinoma, and 97 healthy controls. METHODS: Metabolomics and lipidomics were applied to analyze different metabolites and lipids in the serum of these patients. The SCLC diagnosis model (d-model) was constructed using an integrated machine learning technology and a training cohort (n = 323) and was validated in a testing cohort (n=138). RESULTS: Eight metabolites, including 1-mristoyl-sn-glycero-3-phosphocholine, 16b-hydroxyestradiol, 3-phosphoserine, cholesteryl sulfate, D-lyxose, dioctyl phthalate, DL-lactate and Leu-Phe, were successfully selected to distinguish SCLC from controls. The d-model was constructed based on these 8 metabolites and showed improved diagnostic performance for SCLC, with the area under curve (AUC) of 0.933 in the training cohort and 0.922 in the testing cohort. Importantly, the d-model still had an excellent diagnostic performance after adjusting the stage and related clinical variables and, combined with the progastrin-releasing peptide (ProGRP), showed the best diagnostic performance with 0.975 of AUC for limited-stage patients. CONCLUSION: This study is the first to analyze the difference between metabolomics and lipidomics and to construct a d-model to detect SCLC using integrated machine learning. This study may be of great significance for the screening and early diagnosis of SCLC patients.

Efficacy of immune checkpoint inhibitors in non-small cell lung cancer with NTRK family mutations.

BACKGROUND: The efficacy of immune checkpoint inhibitors (ICIs) in non-small cell lung cancer (NSCLC) patients harboring neurotrophin receptor kinase (NTRK) family mutations remains obscure. METHODS: The Zehir cohort from cBioPortal was used to analyze the mutations (MT) frequency of NTRK family in patients with NSCLC, and their correlation with clinical characteristics and patient survival. The influence of NTRK MT on ICIs efficacy was evaluated in ICIs-treated patients from Samstein cohort and further validated by use of data from OAK/POPLAR cohort. RESULTS: In the Zehir cohort, a significant difference was observed in median overall survival (mOS) between patients with NTRK MT and wild-type (WT) (mOS: 18.97 vs. 21.27 months, HR = 1.34, 95%CI 1.00-1.78; log-rank P = 0.047). In Samstein cohort, the mOS of NTRK mutant patients receiving ICIs has improved compared to WT patients (mOS: 21.00 vs. 11.00 months, log-rank P = 0.103). Notably, in subgroup analysis, ICIs significantly prolonged mOS in patients with NTRK3 MT than in WT patients (mOS: not available vs. 11.00 months, HR = 0.36, 95%CI 0.16-0.81; log-rank P = 0.009). Identical mOS between NTRK MT and WT patients receiving ICIs treatment (mOS: 13.24 vs. 13.50 months, log-rank P = 0.775) was observed in OAK/POPLAR cohort. Moreover, a similar programmed death ligand 1 (PD-L1) expression, but higher tumor mutational burden (TMB), blood TMB (bTMB) and enriched anti-tumor immunity were observed in NTRK MT compared to WT (P < 0.05). CONCLUSION: Taking high TMB or bTMB into consideration, patients with NTRK mutant NSCLC could benefit from ICIs treatment.

Constitutions in Traditional Chinese Medicine and Factors Influencing Them in Jilin Province of China.

Context: The identification of a patient's constitution in Traditional Chinese Medicine (TCM) allows physicians to understand his or her risk for different diseases, forecast the mechanism of disease development, and direct treatment strategies, such as herbs and/or acupuncture. However, very few large-scale clinical trials have occurred on the relationships of the TCM constitution to lifestyles and diseases. Objective: The study intended investigate the complex and systematic relationship between the TCM constitution and lifestyles to provide solutions for adjusting unbalanced constitutions and maintaining a balanced constitution and health state among people of various lifestyles in Jilin, China. Design: The research team conducted a randomized cross-sectional survey. Setting: The study took place in Jilin Province in China. Participants: Participants were 1755 residents of Jilin Province in China, 794 men and 961 women, between September 2006 and February 2013. Outcome Measures: The research team: (1) collected participants' data using a basic informational and lifestyle questionnaire and the Constitution in Chinese Medicine Questionnaire (CCMQ); (2) used descriptive analysis to illustrate demographic characteristics and the distribution of TCM constitutions; (3) conducted multivariate logistic regressions to explore potential factors influencing the Deficiency, Excess, Gentleness, and Special-diathesis constitutions. Results: Approximately one-half of participants in Jilin, China had an unbalanced constitution and one-third had Deficiency constitutions. Lifestyles and disease histories were significant influencing factors for the unbalanced constitutions. Of the 1755 participants, 757 had the Gentleness constitution (43.1%); the remaining participants had unbalanced constitutions, including 501 with a Deficiency constitution (28.6%), 423 with an Excess constitution (24.1%), and 74 with a Special-Diathesis constitution (4.2%). Regarding the influencing factors, the Deficiency constitutions were significantly related to lifestyle factors-especially gender, age, exercise, and diet: (21) the Qi-deficiency constitution was significantly related to excessive exercise and chronic bronchia; (2) the Yang-deficiency constitution was significantly related to female gender and prefer to hot food; and (3) the Yin-deficiency constitution was significantly related to age, from 46 to ≥66, and the barbecue diet. The Excess constitutions were related to medical histories: (1) the Phlegm-dampness and Blood-stasis constitutions were both significantly related to cardio-cerebrovascular disease and hyperlipidemia; (2) the Dampness-heat constitution was significantly related to liver disease and osteoporosis; (3) the Qi-depression constitution was significantly related to liver disease and chronic bronchia. The Gentleness constitution was significantly related to a greasy diet, and the Special-diathesis constitution was significantly related to allergies. Conclusions: The identification of TCM constitutions would be beneficial to early identification of potential risk factors and could contribute to the creation of more comprehensive guidelines for health organizations. Controlling the factors influencing the TCM constitutions and using health management plans based on the TCM constitution could help people with unbalanced constitutions to adjust their lifestyles and improve their health.

A three-snoRNA signature: SNORD15A, SNORD35B and SNORD60 as novel biomarker for renal cell carcinoma.

BACKGROUND: Accumulating evidence has confirmed the role of snoRNAs in a variety of cancer, but rare in renal cell carcinoma (RCC). This study aims to clarify the role of snoRNAs in RCC tumorigenesis and their potential as novel tumor biomarkers. MATERIALS AND METHODS: The snoRNA expression matrix was obtained from the public TCGA and SNORic databases. SNORD15A, SNORD35B and SNORD60 were selected and validated by qPCR, then analyzed combined with related clinical factors using T-test and ROC curve. RESULTS: All three snoRNAs: SNORD15A, SNORD35B and SNORD60 were significantly upregulated in cancer tissues compared to adjacent tissues from TCGA or FFPE detection. These three snoRNAs were also increased in urinary sediment (US) of RCC as well as the early-stage RCC patients compared with the healthy controls. In addition, RNase stability experiments confirmed their stable existence in US. Meanwhile, the ROC curve shows that SNORD15A, SNORD35B and SNORD60 could effectively distinguish RCC (AUC = 0.7421) and early-stage RCC (AUC = 0.7465) from healthy individuals. CONCLUSION: SNORD15A, SNORD35B and SNORD60 were upregulated in tissues and US of RCC, serving as novel potential biomarkers for RCC diagnosis.

A Case of Maternal Uniparental Disomy of Chromosome 6 with Intrauterine Growth Restriction.

Background: Uniparental disomy (UPD) is a well-known epigenomic anomaly characterized by the inheritance of both copies of a homologous pair of chromosomes (or part thereof) from the same parent. This genetic condition can have significant implications for prenatal diagnosis and management. Case Presentation: We present a case of a 29-year-old gravida 1 para 0 female who underwent amniocentesis at pregnancy Week 19 due to a high possibility of trisomy chromosome 6, as indicated by noninvasive prenatal testing (NIPT). However, fluorescence in situ hybridization (FISH) and whole-exome sequencing (WES) revealed no abnormalities. Subsequently, chromosomal microarray analysis (CMA) detected uniparental disomy of chromosome 6. Additionally, an ultrasound examination at 28 weeks of gestation revealed intrauterine growth restriction (IUGR). Given these findings, the parents made the decision to terminate the pregnancy. Conclusions: The combination of genetic counseling, FISH, karyotype analysis, WES, CMA, NIPT, and prenatal ultrasound can provide valuable insights for the prenatal diagnosis of UPD. These diagnostic approaches play a crucial role in identifying and managing cases of UPD, primarily when associated with intrauterine growth restrictions.

Intratumor heterogeneity is associated with less CD8+ T cell infiltration and worse survival in patients with small cell lung cancer.

PURPOSE: Small cell lung cancer (SCLC) is a heterogeneous malignancy with genetic and phenotypic disparity. However, the association between intratumor heterogeneity (ITH) and immunological features as well as the impact of ITH on prognosis has never been explored in SCLC. Hence, we investigated the relationship between ITH and their immunological features and explored the effect of ITH on overall survival (OS) in patients with SCLC. METHODS: Programmed cell death-ligand 1 (PD-L1), CD8+ cell infiltration was calculated through immunohistochemical staining and tumor mutational burden (TMB), tumor neoantigen burden (TNB), and ITH levels via whole-exome sequencing (WES). RESULTS: Significant correlation was not found in ITH versus TMB, ITH versus TNB (P = 0.1821, P = 0.0612). No significant variation in ITH was found between negative PD-L1 SCLC patients and positive PD-L1 ones (P = 0.0610 for TPS, P = 0.6347 for CPS). Interestingly, we demonstrated the negative correlation between CD8+ T cell infiltration and ITH (P = 0.0220). More importantly, significant OS benefit was detected in ITH-low SCLC patients in comparison with ITH-high ones (P = 0.0049). ITH was an independent prognostic factor on OS with clinicopathological variables adjusted (HR, 2.044; 95% CI 1.190-3.512; P = 0.010). We also demonstrated significantly different driver genes and CNV between ITH-low and ITH-high SCLC. CONCLUSION: Our work pointed the negative association of ITH with CD8+ T cell infiltration and suggested ITH as a potential predictor of OS in SCLC, putting forward a direction for more precise and individualized therapeutic strategies for SCLC.

Anti-ß2-glycoprotein I antibody maybe a novel biomarker of spontaneous preterm birth.

BACKGROUND: Spontaneous preterm birth is challenging to prevent. Only few predictors of spontaneous preterm birth risk have been reported, and further studies on spontaneous preterm birth should be conducted to reduce the number of cases. PURPOSE: The aim of the present study was to explore if anti-ß2-glycoprotein I antibody can be used to predict the risk of spontaneous preterm birth, and its clinical value in assessing the risk of spontaneous preterm birth. METHODS: A total of 302 pregnant women who had delivered between January 2019 and December 2021 were enrolled into the study. The subjects were assigned to the case group (28-33+6 weeks, n = 41; 34-36+6 weeks, n = 96) and control group (37-42 weeks, n = 165) according to the gestational period. The age, body mass index, and gestational days of the two groups were recorded. Blood samples were collected and the levels of anti-ß2-glycoprotein I antibody, white blood cell, red blood cell, hemoglobin, aspartate aminotransferase, alanine aminotransferase, alkaline phosphatase, urea, creatinine, glucose, triglyceride, and total cholesterol were evaluated. Pregnant women diagnosed with sPTB that met the standards after evaluation by the clinician were included in the study. RESULTS: The level of anti-ß2-glycoprotein I antibody was higher in case group than in the control group [(23.93 ± 8.11)Ru/mL vs (11.50 ± 5.33)Ru/mL]. The results showed that anti-ß2-glycoprotein I antibody was an independent risk factor for spontaneous preterm birth. The area under ROC curve of anti-ß2-glycoprotein I antibody to predict spontaneous preterm birth was 0.8875 (95%CI 0.8443-0.9307). The highest predicted value of anti-ß2-glycoprotein I antibody was 16.49Ru/ml. CONCLUSION: Anti-ß2-glycoprotein I antibody has a high clinical significance and can be used by clinicians to evaluate the probability of spontaneous preterm birth.

Molecular subtyping of small-cell lung cancer based on mutational signatures with different genomic features and therapeutic strategies.

Small-cell lung cancer (SCLC) is an exceptionally lethal malignancy characterized by extremely high alteration rates and tumor heterogeneity, which limits therapeutic options. In contrast to non-small-cell lung cancer that develops rapidly with precision oncology, SCLC still remains outside the realm of precision medicine. No recurrent and actionable mutations have been detected. Additionally, a paucity of substantive tumor specimens has made it even more difficult to classify SCLC subtypes based on genetic background. We therefore carried out whole-exome sequencing (WES) on the largest available Chinese SCLC cohort. For the first time, we partitioned SCLC patients into three clusters with different genomic alteration profiles and clinical features based on their mutational signatures. We showed that these clusters presented differences in intratumor heterogeneity and genome instability. Moreover, a wide existence of mutually exclusive gene alterations, typically within similar biological functions, was detected and suggested a high SCLC intertumoral heterogeneity. Particularly, Cluster 1 presented the greatest potential to benefit from immunotherapy, and Cluster 3 constituted recalcitrant SCLC, warranting biomarker-directed drug development and targeted therapies in clinical trials. Our study would provide an in-depth insight into the genome characteristics of the Chinese SCLC cohort, defining distinct molecular subtypes as well as subtype-specific therapies and biomarkers. We propose tailoring differentiated therapies for distinct molecular subgroups, centering on a personalized precision chemotherapy strategy combined with immunization or targeted therapy for patients with SCLC.

Untargeted metabolomics and lipidomics identified four subtypes of small cell lung cancer.

INTRODUCTION: Small cell lung cancer (SCLC) is a heterogeneous malignancy with dismal prognosis. However, few studies have conducted on the metabolic heterogeneity in SCLC. OBJECTIVE: We therefore identify SCLC classifications using untargeted metabolomics and lipidomics. We also compared their survival and the immunotherapy responses. METHODS: Liquid Chromatography-Mass Spectrometry/Mass Spectrometry (LC-MS/MS) analysis was performed in 191 SCLC serum samples. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was conducted to identify metabolic pathways. The Kaplan-Meier and log-rank test were used to analyze the survival curves. The univariate and multivariate Cox proportional hazards regression models were used to evaluate prognostic factors for OS in patients with SCLC. RESULTS: Distinct subtypes of SCLC were identified by consensus clustering algorithm using partioning around medoids (pam) based on untargeted metabolomics and lipidomics. Four distinct subtypes of SCLC were identified, with distinct metabolic pathways. Subgroup 2 had the longest survival whereas Subgroup 1 had the shortest. Subtype 2 benefited most from immunotherapy in OS, as in contrast to Subtype 3 with shortest survival. CONCLUSION: Our study revealed the metabolic heterogeneity in SCLC and identified four subtypes with distinct metabolic features. It indicates promising therapeutic and prognostic value that may guide treatment for SCLC. The subtype-specific clinical trials may be designed and would be instructive for drug development.

ANK2 as a novel predictive biomarker for immune checkpoint inhibitors and its correlation with antitumor immunity in lung adenocarcinoma.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have been shown to significantly improve the survival of patients with advanced lung adenocarcinoma (LUAD). However, only limited proportion of patients could benefit from ICIs. Novel biomarkers with strong predictability are needed for clinicians to maximize the efficacy of ICIs. Our study aimed to identify potential biomarkers predicting ICIs efficacy in LUAD. METHODS: The Cancer Genome Atlas (TCGA) PanCancer Atlas studies in cBioportal were used to evaluate the mutation frequency of ANK2 across multiple cancers. Clinical and mutational data for LUAD from ICIs-treated cohorts (Hellmann et al. and Rizvi et al.) were collected to explore the correlation between ANK2 mutation and clinical outcomes. In addition, the relationship between ANK2 expression and clinical outcomes was analyzed using LUAD data from TCGA and Gene Expression Omnibus. Furthermore, the impact of ANK2 mutation and expression on the tumor immune microenvironment of LUAD was analyzed using TCGA and TISIDB databases. RESULTS: Patients with ANK2 mutation benefited more from ICIs. In ICIs-treated cohort, prolonged progression-free survival (PFS) (median PFS: NR (not reached) vs. 5.42 months, HR (hazard ratio) 0.31, 95% CI 0.18-0.54; P = 0.0037), improved complete response rate (17.65% vs. 1.85%, P = 0.0402), and improved objective response rate (64.71% vs. 24.07%, P = 0.0033) were observed in LUAD patients with ANK2 mutation compared to their wild-type counterparts. Regarding ANK2 expression, it was observed that ANK2 expression was decreased in LUAD (P < 0.05) and a higher level of ANK2 expression was associated with longer overall survival (HR 0.69, 95% CI 0.52-0.92; P = 0.012) in TCGA LUAD cohort. Moreover, ANK2 mutation or higher ANK2 expression correlated with enhanced antitumor immunity and "hot" tumor microenvironment in LUAD, which could be potential mechanisms that ANK2 mutation facilitated ICIs therapy and patients with higher ANK2 expression survived longer. CONCLUSION: Our findings suggest that ANK2 mutation or increased ANK2 expression may serve as a favorable biomarker for the efficacy of ICIs in patients with LUAD.

The causal relationship between white blood cell counts and hepatocellular carcinoma: a Mendelian randomization study.

BACKGROUND: Most of hepatocellular carcinoma (HCC) arises on the background of chronic inflammation. The presence of infiltrating inflammatory cells is associated with tumour initiation, progression and clinical response to treatment. The influence of white blood cell (WBC) subtype counts on HCC progression remains unclear. METHODS: In this study, we performed a Mendelian randomization (MR) study with the validation of two datasets. The summary data for WBC counts were extracted from a recent large GWAS of individuals of European ancestry. The GWAS data related to HCC were obtained from the UK Biobank (UKB). Univariable and multivariable MR analyses were used to identify risk factors genetically associated with HCC risks. RESULTS: In the discovery dataset, multivariable MR analysis revealed that sum basophil neutrophil counts had an independent causal effect on the occurrence of HCC, with the sum basophil neutrophil counts as follows: (OR = 0.437, P = 0.003, CI 0.252-0.757). Similarly, in the validation dataset, total basophil neutrophil counts were also been identified as an independent risk factor for HCC. The sum basophil neutrophil counts were as follows: (OR = 0.574, P = 0.021, CI 0.358-0.920). CONCLUSION: In the European population, genetically predicted lower total basophil neutrophil counts might be an independent risk factor for HCC.

Liver metastases and the efficacy of immune checkpoint inhibitors in advanced lung cancer: A systematic review and meta-analysis.

Background: Liver metastasis is the most common type of lung cancer metastasis, and is a significant prognostic factor in lung cancer. However, the effect of liver metastases on the efficacy of immune checkpoint inhibitors (ICIs) remains inconsistent and controversial. The aim of this study was to explore the relationship between liver metastases and ICI efficacy in patients with advanced lung cancer based on data from randomized controlled trials (RCTs) and observational studies. Methods: PubMed, EMBASE, Cochrane Library databases, conference proceedings, as well as grey literature websites were searched for eligible studies without language restrict ion. Study quality was assessed using Cochrane tools and the Newcastle-Ottawa Quality Assessment Scale (NOS). Outcomes of interest were overall survival (OS) and progression-free survival (PFS). The difference in efficacy between patients with and without liver metastases was calculated by pooling ratios of hazard ratios (HR), as calculated using the deft approach. Results: A total of 16 RCTs and 14 observational trials were included. Analyses of RCTs revealed a survival benefit for ICI treatment (i.e., ICI monotherapy, ICI + Chemotherapy, dual ICI therapy and dual ICI + Chemotherapy) versus standard therapies among non-small cell lung cancer (NSCLC) patients with liver metastases (PFS HR, 0.77; 95%CI, 0.61-0.97; OS HR, 0.78; 95%CI, 0.68-0.90). NSCLC patients with liver metastases achieved less PFS benefit and comparable OS benefit from ICI treatment compared with those without liver metastases (ratios of PFS-HRs, 1.19; 95%CI, 1.02-1.39; P=0.029; Ratios of OS-HRs, 1.10; 95%CI, 0.94-1.29; P=0.24). For patients with small cell lung cancer (SCLC), ICI treatment achieved a marginal effect on patients with liver metastases as compared with standard therapies (OS HR, 0.94; 95%CI, 0.73-1.23). SCLC patients with liver metastases benefited less from ICI treatment than patients without liver metastases (ratio of OS-HRs, 1.22; 95%CI, 1.01-1.46; P=0.036). In real-world data analysis, liver metastasis could be used as an independent prognostic risk factor, increasing the risk of death by 21% in lung cancer patients receiving ICI treatment compared with those without liver metastases (OS HR, 1.21; 95%CI, 1.17-1.27; P<0.0001). Subgroup analysis confirmed that this association was not modified by race (Asian vs. Western) or number of treatment lines. Conclusions: The presence of liver metastases does not significantly influence the OS benefit of ICIs in patients with NSCLC. However, a small amount of data shows that liver metastasis restrains the magnitude of OS benefit in patients with SCLC. Liver metastasis has potential as an independent prognostic risk factor for lung cancer patients receiving ICI treatment in clinical practice. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/, identifier (CRD42022306449).

Fibroblast growth factor receptor family mutations as a predictive biomarker for immune checkpoint inhibitors and its correlation with tumor immune microenvironment in melanoma.

Background: The emergence of immune checkpoint inhibitors (ICIs) has significantly improved the clinical outcomes of patients with metastatic melanoma. However, survival benefits are only observed in a subset of patients. The fibroblast growth factor receptor (FGFR) family genes are frequently mutated in melanoma, yet their impacts on the efficacy of ICIs remain unclear. Our study aimed to explore the association of FGFR mutations with ICIs efficacy in metastatic melanoma. Methods: The Cancer Genome Atlas (TCGA) data (PanCancer Atlas, skin cutaneous melanoma (SKCM), n = 448) in cBioPortal were collected as a TCGA cohort to investigate the association between FGFR mutations and prognosis of melanoma patients. To explore the impact of FGFR mutations on the efficacy of ICIs in melanoma, clinical and tumor whole-exome sequencing (WES) data of four ICI-treated studies from cBioPortal were consolidated as an ICIs-treated cohort. Moreover, the relationship between FGFR mutations and immunogenicity (tumor mutation burden (TMB), neo-antigen load (NAL), mismatch repair (MMR)-related genes and DNA damage repair (DDR)-related genes) of melanoma was evaluated utilizing data from the ICIs-treated cohort. The influence of FGFR mutations on the tumor immune microenvironment (TIME) of melanoma was also analyzed using the TCGA cohort. Results: In the TCGA cohort, survival in melanoma patients with or without FGFR mutations was nearly equivalent. In the ICIs-treated cohort, patients with FGFR mutations had better survival than those without (median overall survival: 60.00 vs. 31.00 months; hazard ratio: 0.58, 95% CI: 0.42-0.80; P = 0.0051). Besides, the objective response rate was higher for patients harboring FGFR mutations (55.56%) compared to wild-type patients (22.40%) (P = 0.0076). Mechanistically, it was revealed that FGFR mutations correlated with increased immunogenicity (e.g., TMB, NAL, MMR-related gene mutations and DDR-related gene mutations). Meanwhile, FGFR mutant melanoma tended to exhibit an enhanced antitumor TIME compared with its wild-type counterparts. Conclusions: Our study demonstrated that FGFR mutations is a promising biomarker in stratifying patients with advanced melanoma who might benefit from ICIs therapy.

Neutrophil-related genes predict prognosis and response to immune checkpoint inhibitors in bladder cancer.

Neutrophils play a key role in the occurrence and development of cancer. However, the relationship between neutrophils and cancer prognosis remains unclear due to their great plasticity and diversity. To explore the effects of neutrophils on the clinical outcome of bladder cancer, we acquired and analyzed gene expression data and clinical information of bladder cancer patients from IMvigor210 cohort and The Cancer Genome Atlas dataset (TCGA) database. We established a neutrophil-based prognostic model incorporating five neutrophil-related genes (EMR3, VNN1, FCGRT, HIST1H2BC, and MX1) and the predictive value of the model was validated in both an internal and an external validation cohort. Multivariate Cox regression analysis further proved that the model remained an independent prognostic factor for overall survival and a nomogram was constructed for clinical practice. Additionally, FCGRT was identified as the key neutrophil-related gene linked to an adverse prognosis of bladder cancer. Up-regulation of FCGRT indicated activated cancer metabolism, immunosuppressive tumor environment, and dysregulated functional status of immune cells. FCGRT overexpression was also correlated with decreased expression of PD-L1 and low levels of tumor mutation burden (TMB). FCGRT predicted a poor response to immunotherapy and had a close correlation with chemotherapy sensitivity. Taken together, a novel prognostic model was developed based on the expression level of neutrophil-related genes. FCGRT served as a promising candidate biomarker for anti-cancer drug response, which may contribute to individualized prognostic prediction and may contribute to clinical decision-making.

PTPRD/PTPRT mutation as a predictive biomarker of immune checkpoint inhibitors across multiple cancer types.

Background: Immune checkpoint inhibitors (ICIs) are dramatically changing the treatment landscape of a variety of cancers. Nevertheless, the variability in ICI responses highlight the importance in identifying predictive biomarkers. PTPRD and PTPRT (PTPRD/PTPRT) are the phosphatases of JAK-STAT signaling, a critical pathway in anti-cancer immunity regulation. However, the pan-cancer association between PTPRD/PTPRT mutation and the efficacy of ICIs remains unclear across pan-cancer patients. Methods: We analyzed the association between PTPRD/PTPRT mutations and patient outcomes using clinical data and genomic mutations from TCGA pan-cancer cohort. Furthermore, the ICI-treatment cohort was used to evaluate the relationship between PTPRD/PTPRT mutation and the efficacy of ICIs. Another ICIs-treatment cohort was used to validate the findings. The TCGA pan-cancer dataset was analyzed to explore the correlation between PTPRD/PTPRT mutations and immune signatures. Moreover, we combined four factors to construct a nomogram model that could be used to predict the survival of pan-cancer patients receiving ICI treatment. The calibration curves and area under the curve were applied to assess the performance of the model. Results: PTPRD/PTPRT mutations were shown to be associated with a worse prognosis in TCGA cohort (P < 0.05). In the Samstein cohort, prolonged overall survival (OS) was observed in PTPRD/PTPRT mutant cancers, compared with wild-type cancers (mOS: 40.00 vs 16.00 months, HR = 0.570, 95%CI: 0.479-0.679, P < 0.0001). In the validation cohort, significant OS advantage was observed in PTPRD/PTPRT mutant patients (mOS: 31.32 vs 15.53 months, HR = 0.658, 95%CI: 0.464-0.934, P = 0.0292). Furthermore, PTPRD/PTPRT mutations were associated with a higher tumor mutational burden, MSI score, and TCR score (P < 0.0001). Enhanced immune signatures were found in the PTPRD/PTPRT mutant cancers (P < 0.05). Finally, we successfully established a nomogram model that could be used to predict the survival of NSCLC patients who received ICI treatment. Based on the risk score of the model, patients in the low-risk group showed a better mOS than those in the high-risk group (mOS: 2.75 vs 1.08 years, HR = 0.567, 95%CI: 0.492-0.654; P < 0.001). Conclusions: PTPRD/PTPRT mutations may be a potential biomarker for predicting ICI treatment responsiveness in multiple cancer types.

Features of patients with advanced EGFR-mutated non-small cell lung cancer benefiting from immune checkpoint inhibitors.

Background: Although immune checkpoint inhibitors (ICIs) generally show poor therapeutic efficacy in patients with epidermal growth factor receptor (EGFR) mutations, certain research indicate that a small proportion of these patients do respond to ICIs. The present study sought to identify the features of patients with EGFR mutations who might benefit from ICIs from multiple studies and discussed the optimal treatment paradigm for advanced non-small cell lung cancer (NSCLC) patients with EGFR mutations. Methods: The profiles of 114 advanced NSCLC patients with EGFR mutations who received ICIs treatment were retrospectively reviewed. EGFR subtypes, programmed cell death ligand 1 (PD-L1) expression, and clinical characteristics regarding their impact on the efficacy of ICIs were investigated. Results: Patients with major EGFR mutations (L858R or 19Del) had a shorter progression-free survival (PFS) and a lower objective response rate (ORR) as compared to patients with rare (20ins or G719X) and other EGFR mutations. Although not statistically significant, median overall survival (OS) tended to be longer in patients with negative (<1%) PD-L1 expression than with positive (≥1%) PD-L1 expression (15.61 vs. 7.40 months, p = 0.138). Median PFS and OS were significantly shorter in heavily treated patients (prior lines of therapy ≥3 lines vs. <3 lines: mPFS, 1.80 vs. 2.50 months, p = 0.003; mOS, 6.70 vs. 14.00 months, p = 0.031). ORR was also lower in patients who had received ≥3 prior lines of therapy compared to in those <3 prior lines of therapy (0.00% vs. 21.67%, p = 0.002). Conclusion: Patients with major EGFR mutations showed poorer responses to ICIs than those with rare EGFR mutations. EGFR-mutated patients with lower PD-L1 expression showed a trend towards a longer OS after receiving ICIs. ICIs should be administered as early as possible to previously treated EGFR-mutated NSCLC patients. ICI-based combined therapies may be a direction for treatment of these patient subtypes in the future.

An Intelligent Health Monitoring Model Based on Fuzzy Deep Neural Network.

An intelligent health detection model is a new technology developed under an artificial intelligence environment, which is of great significance to the care of the elderly and other people who cannot take care of themselves. This paper comprehensively reviews the structural health monitoring method based on an intelligent algorithm, introduces the application model of neural networks in structural health monitoring in detail, and points out the shortcomings of using neural network technology alone. On the basis of previous work, the genetic algorithm and fuzzy theory were introduced as optimization tools, and a new neural network training algorithm was constructed by combining genetic algorithm, fuzzy theory, and neural network technology for structural health monitoring research. Aimed at the shortcoming of insufficient samples for training neural networks based on experimental data, this paper proposes to use the finite element method to construct a genetic fuzzy RBF neural network after corresponding processing of the first six-order bending modal frequencies of the structure, so as to realize the localization and detection of delamination damage of composite beams. Injury Assessment. The experimental results of this paper show that the finite element method proposed in this paper can effectively carry out damage localization and damage assessment; compared with the traditional algorithm, the localization accuracy of this algorithm is improved by 20%, and the damage assessment performance is improved by 10%.