Sublethal effect and detoxifying metabolism of metaflumizone and indoxacarb on the fall armyworm, Spodoptera frugiperda.

The fall armyworm (FAW), Spodoptera frugiperda (J.E. Smith) (Lepidoptera, Noctuidae), is a highly polyphagous invasive pest that damages various crops. Pesticide control is the most common and effective strategy to control FAW. In this study, we evaluated the toxicity of metaflumizone and indoxacarb against third-instar FAW larvae using the insecticide-incorporated artificial diet method under laboratory conditions. Both metaflumizone and indoxacarb exhibited substantial toxicity against FAW, with LC50 values of 2.43 and 14.66 mg/L at 72 h, respectively. The sublethal effects of metaflumizone and indoxacarb on parental and F1 generation FAW were investigated by exposing third-instar larvae to LC10 and LC30 concentrations of these insecticides. Sublethal exposure to these two insecticides significantly shortened adult longevity, extended pupal developmental times and led to reduced pupal weight, pupation rates, and adult fecundity in the treated parental generation and F1 generation at LC10 or LC30 concentrations, in comparison to the control group. The larval developmental times were shortened in the parental generation but prolonged in the F1 generation, after being treated with sublethal concentrations of metaflumizone. Furthermore, larvae exposed to LC10 or LC30 concentrations of indoxacarb exhibited elevated activity levels of cytochrome P450 monooxygenase and glutathione S-transferase, which coincides with the observed synergistic effect of piperonyl butoxide and diethyl maleate. In conclusion, the high toxicity and negative impact of metaflumizone and indoxacarb on FAW provided significant implications for the rational utilization of insecticides against this pest.

Personalized circulating tumor DNA monitoring improves recurrence surveillance and management after curative resection of colorectal liver metastases: a prospective cohort study.

BACKGROUND: Approximately 60% of patients with colorectal liver metastases (CRLM) experience relapse within 2 years after radical resection, previous studies have proven that repeat local treatment (LT) could prolong survival, however, it is difficult to seize the window for LT due to the lack of a high-sensitive surveillance method. In this study, the authors aim to examine the value of longitudinal circulating tumor DNA (ctDNA) in guiding adjuvant chemotherapy, optimizing clinical surveillance strategy, and thereby improving CRLM outcomes. MATERIALS AND METHODS: The authors conducted a prospective clinical trial using a personalized, tumor-informed ctDNA assay to monitor 60 CRLM patients undergoing resection with curative intent. Formalin-fixed paraffin-embedded tumor samples were collected after surgery. Blood samples were collected before surgery, 30 days after surgery (post-OP), and every third month until relapse or up to 2 years. RESULTS: A total of 394 plasma samples from 60 eligible patients were analyzed, with a median follow-up time of 31.3 months. Landmark analyses revealed that detectable ctDNA at post-OP (HR, 4.8), postadjuvant chemotherapy (HR, 6.0), and end-of-treatment (HR, 5.6) were associated with higher recurrence risk ( P <0.001). Post-OP ctDNA positivity served as the only independent prognostic marker in the multivariant analysis (HR, 5.1; P <0.001). Longitudinal ctDNA analysis identified relapsed patients at both sensitivity and specificity of 100%. Most (75%) patients were found with radiological relapse within 6 months after the first detectable ctDNA with a median lead time of 3.5 months. In relapsed patients, 73.2% had oligometastatic disease and 61% were liver-restricted, of which 72.0% received repeat LTs, and 60.0% achieved a secondary no evidence of disease status. CONCLUSIONS: Longitudinal ctDNA monitoring assists in early prediction of relapse, and thereby improves survival of CRLM patients by increased secondary resection rate and secondary no evidence of disease rate.

Establishment of patient-derived organoids for guiding personalized therapies in breast cancer patients.

Breast cancer has become the most commonly diagnosed cancer. The intra- and interpatient heterogeneity induced a considerable variation in treatment efficacy. There is an urgent requirement for preclinical models to anticipate the effectiveness of individualized drug responses. Patient-derived organoids (PDOs) can accurately recapitulate the architecture and biological characteristics of the origin tumor, making them a promising model that can overtake many limitations of cell lines and PDXs. However, it is still unclear whether PDOs-based drug testing can benefit breast cancer patients, particularly those with tumor recurrence or treatment resistance. Fresh tumor samples were surgically resected for organoid culture. Primary tumor samples and PDOs were subsequently subjected to H&E staining, immunohistochemical (IHC) analysis, and whole-exome sequencing (WES) to make comparisons. Drug sensitivity tests were performed to evaluate the feasibility of this model for predicting patient drug response in clinical practice. We established 75 patient-derived breast cancer organoid models. The results of H&E staining, IHC, and WES revealed that PDOs inherited the histologic and genetic characteristics of their parental tumor tissues. The PDOs successfully predicted the patient's drug response, and most cases exhibited consistency between PDOs' drug susceptibility test results and the clinical response of the matched patient. We conclude that the breast cancer organoids platform can be a potential preclinical tool used for the selection of effective drugs and guided personalized therapies for patients with advanced breast cancer.

Genome-wide DNA methylation analysis identifies potent CpG signature for temzolomide response in non-G-CIMP glioblastomas with unmethylated MGMT promoter: MGMT-dependent roles of GPR81.

PURPOSES: To identify potent DNA methylation candidates that could predict response to temozolomide (TMZ) in glioblastomas (GBMs) that do not have glioma-CpGs island methylator phenotype (G-CIMP) but have an unmethylated promoter of O-6-methylguanine-DNA methyltransferase (unMGMT). METHODS: The discovery-validation approach was planned incorporating a series of G-CIMP-/unMGMT GBM cohorts with DNA methylation microarray data and clinical information, to construct multi-CpG prediction models. Different bioinformatic and experimental analyses were performed for biological exploration. RESULTS: By analyzing discovery sets with radiotherapy (RT) plus TMZ versus RT alone, we identified a panel of 64 TMZ efficacy-related CpGs, from which a 10-CpG risk signature was further constructed. Both the 64-CpG panel and the 10-CpG risk signature were validated showing significant correlations with overall survival of G-CIMP-/unMGMT GBMs when treated with RT/TMZ, rather than RT alone. The 10-CpG risk signature was further observed for aiding TMZ choice by distinguishing differential outcomes to RT/TMZ versus RT within each risk subgroup. Functional studies on GPR81, the gene harboring one of the 10 CpGs, indicated its distinct impacts on TMZ resistance in GBM cells, which may be dependent on the status of MGMT expression. CONCLUSIONS: The 64 TMZ efficacy-related CpGs and in particular the 10-CpG risk signature may serve as promising predictive biomarker candidates for guiding optimal usage of TMZ in G-CIMP-/unMGMT GBMs.

Knockdown of the glutamate-gated chloride channel gene decreases emamectin benzoate susceptibility in the fall armyworm, Spodoptera frugiperda.

Emamectin benzoate (EB), a derivative of avermectin, is the primary insecticide used to control the fall armyworm (FAW) in China. However, the specific molecular targets of EB against FAW remain unclear. In this study, we cloned the glutamate-gated chloride channel (GluCl) gene, which is known to be a primary molecular target for avermectin. We first investigated the transcript levels of SfGluCl in FAW and found that the expression level of SfGluCl in the head and nerve cord was significantly higher than that in other tissues. Furthermore, we found that the expression level of SfGluCl was significantly higher in eggs than that in other developmental stages, including larvae, pupae, and adults. Additionally, we identified three variable splice forms of SfGluCl in exons 3 and 9 and found that their splice frequencies remained unaffected by treatment with the LC50 of EB. RNAi mediated knockdown of SfGluCl showed a significant reduction of 42% and 65% after 48 and 72 h of dsRNA feeding, respectively. Importantly, knockdown of SfGluCl sifgnificantly reduced LC50 and LC90 EB treatment induced mortality of FAW larvae by 15% and 44%, respectively, compared to the control group feeding by dsEGFP. In contrast, there were no significant changes in the mortality of FAW larvae treated with the control insecticides chlorantraniliprole and spinetoram. Finally, molecular docking simulations revealed that EB bound to the large amino-terminal extracellular domain of SfGluCl by forming five hydrogen bonds, two alkyl hydrophobic interactions and one salt bridge. These findings strongly suggest that GluCl may serve as one of the molecular targets of EB in FAW, shedding light on the mode of action of this important insecticide.

Causal associations of Sjögren's syndrome with cancers: a two-sample Mendelian randomization study.

BACKGROUND: Several observational studies have explored the associations between Sjögren's syndrome (SS) and certain cancers. Nevertheless, the causal relationships remain unclear. Mendelian randomization (MR) method was used to investigate the causality between SS and different types of cancers. METHODS: We conducted the two-sample Mendelian randomization with the public genome-wide association studies (GWASs) summary statistics in European population to evaluate the causality between SS and nine types of cancers. The sample size varies from 1080 to 372,373. The inverse variance weighted (IVW) method was used to estimate the causal effects. A Bonferroni-corrected threshold of P < 0.0031 was considered significant, and P value between 0.0031 and 0.05 was considered to be suggestive of an association. Sensitivity analysis was performed to validate the causality. Moreover, additional analysis was used to assess the associations between SS and well-accepted risk factors of cancers. RESULTS: After correcting the heterogeneity and horizontal pleiotropy, the results indicated that patients with SS were significantly associated with an increased risk of lymphomas (odds ratio [OR] = 1.0010, 95% confidence interval [CI]: 1.0005-1.0015, P = 0.0002) and reduced risks of prostate cancer (OR = 0.9972, 95% CI: 0.9960-0.9985, P = 2.45 × 10-5) and endometrial cancer (OR = 0.9414, 95% CI: 0.9158-0.9676, P = 1.65 × 10-5). Suggestive associations were found in liver and bile duct cancer (OR = 0.9999, 95% CI: 0.9997-1.0000, P = 0.0291) and cancer of urinary tract (OR = 0.9996, 95% CI: 0.9992-1.0000, P = 0.0281). No causal effect of SS on other cancer types was detected. Additional MR analysis indicated that causal effects between SS and cancers were not mediated by the well-accepted risk factors of cancers. No evidence of the causal relationship was observed for cancers on SS. CONCLUSIONS: SS had significant causal relationships with lymphomas, prostate cancer, and endometrial cancer, and suggestive evidence of association was found in liver and bile duct cancer and cancer of urinary tract, indicating that SS may play a vital role in the incidence of these malignancies.

Chromosome-Scale Genome Assembly of the Solitary Parasitoid Wasp Microplitis manilae Ashmead, 1904 (Braconidae: Microgastrinae).

Parasitoid wasps are invaluable natural enemies extensively used to control coleopteran, dipteran, and lepidopteran pests in agriculture and forestry owing to their killing and reproductive actions on hosts. The important larval endoparasitoid wasp Microplitis manilae, which belongs to the Microgastrinae subfamily, parasitizes the larval stages of Spodoptera spp., such as Spodoptera litura and Spodoptera frugiperda. The absence of a genomic resource for M. manilae has impeded studies on chemosensory- and detoxification-related genes. This study presents a chromosome-level genome assembly of M. manilae with a genome size of 293.18 Mb, which includes 222 contigs (N50 size, 7.58 Mb) and 134 scaffolds (N50 size, 27.33 Mb). A major proportion of the genome (284.76 Mb; 97.13%) was anchored to 11 pseudochromosomes with a single-copy BUSCO score of 98.4%. Furthermore, 14,316 protein-coding genes, 165.14 Mb (57.99%) repetitive elements, and 871 noncoding RNAs were annotated and identified. Additionally, a manual annotation of 399 genes associated with chemosensation and 168 genes involved in detoxification was conducted. This study provides a valuable and high-quality genomic resource to facilitate further functional genomics research on parasitoid wasps.

Novel models by machine learning to predict prognosis of breast cancer brain metastases.

BACKGROUND: Breast cancer brain metastases (BCBM) are the most fatal, with limited survival in all breast cancer distant metastases. These patients are deemed to be incurable. Thus, survival time is their foremost concern. However, there is a lack of accurate prediction models in the clinic. What's more, primary surgery for BCBM patients is still controversial. METHODS: The data used for analysis in this study was obtained from the SEER database (2010-2019). We made a COX regression analysis to identify prognostic factors of BCBM patients. Through cross-validation, we constructed XGBoost models to predict survival in patients with BCBM. Meanwhile, a BCBM cohort from our hospital was used to validate our models. We also investigated the prognosis of patients treated with surgery or not, using propensity score matching and K-M survival analysis. Our results were further validated by subgroup COX analysis in patients with different molecular subtypes. RESULTS: The XGBoost models we created had high precision and correctness, and they were the most accurate models to predict the survival of BCBM patients (6-month AUC = 0.824, 1-year AUC = 0.813, 2-year AUC = 0.800 and 3-year survival AUC = 0.803). Moreover, the models still exhibited good performance in an externally independent dataset (6-month: AUC = 0.820; 1-year: AUC = 0.732; 2-year: AUC = 0.795; 3-year: AUC = 0.936). Then we used Shiny-Web tool to make our models be easily used from website. Interestingly, we found that the BCBM patients with an annual income of over USD$70,000 had better BCSS (HR = 0.523, 95%CI 0.273-0.999, P < 0.05) than those with less than USD$40,000. The results showed that in all distant metastasis sites, only lung metastasis was an independent poor prognostic factor for patients with BCBM (OS: HR = 1.606, 95%CI 1.157-2.230, P < 0.01; BCSS: HR = 1.698, 95%CI 1.219-2.365, P < 0.01), while bone, liver, distant lymph nodes and other metastases were not. We also found that surgical treatment significantly improved both OS and BCSS in BCBM patients with the HER2 + molecular subtypes and was beneficial to OS of the HR-/HER2- subtype. In contrast, surgery could not help BCBM patients with HR + /HER2- subtype improve their prognosis (OS: HR = 0.887, 95%CI 0.608-1.293, P = 0.510; BCSS: HR = 0.909, 95%CI 0.604-1.368, P = 0.630). CONCLUSION: We analyzed the clinical features of BCBM patients and constructed 4 machine-learning prognostic models to predict their survival. Our validation results indicate that these models should be highly reproducible in patients with BCBM. We also identified potential prognostic factors for BCBM patients and suggested that primary surgery might improve the survival of BCBM patients with HER2 + and triple-negative subtypes.

Comprehensive analysis of NT5DC family prognostic and immune significance in breast cancer.

Among the most common malignancies, breast cancer has a high incidence and mortality rate. NT5DC family is a highly well-conserved 5'-nucleotidase. Previous studies showed that the progression of tumors was associated with some NT5DC family members. However, there are no studies about the comprehensive analysis such as expression, prognosis, and immune properties of NT5DC family in breast cancer. Based on the data from The Cancer Genome Atlas database, we used UALCAN, Tumor Immune Estimation Resource, Breast cancer gene-expression miner (Bc-GenExMiner), Kaplan-Meier Plotter, TISIDB, cBioPortal, GeneMANIA, Search Tool for the Retrieval of Interacting Genes, Metascape, Tumor Immune Single-cell Hub, The Database for Annotation, Visualization and Integrated Discovery, and Gene Set Cancer Analysis databases to explore expression, prognostic and diagnostic value, genetic alterations, biological function, immune value and drug sensitivity of NT5DC family in breast cancer patients. There was a downregulation of NT5C2, NT5DC1, and NT5DC3 in breast cancer compared to normal tissues, and NT5DC2 instead. All NT5DC family members were associated with the clinicopathological parameters of breast cancer patients. Survival and ROC analysis revealed that NT5DC family genes were related to the prognosis and diagnosis of breast cancer. NT5DC family were mainly involved in nucleotide metabolism. Moreover, NT5DC family were significantly associated with tumor immune microenvironment, diverse immune cells, and immune checkpoints in breast cancer. This research showed that NT5DC family might be novel prognostic biomarkers and immunotherapeutic targets of breast cancer.

The cuproptosis-related signature predicts prognosis and indicates immune microenvironment in breast cancer.

Breast cancer (BC) is the most diagnosed cancer in women. Cuproptosis is new regulated cell death, distinct from known death mechanisms and dependent on copper and mitochondrial respiration. However, the comprehensive relationship between cuproptosis and BC is still blank until now. In the present study, we acquired 13 cuproptosis-related regulators (CRRs) from the previous research and downloaded the RNA sequencing data of TCGA-BRCA from the UCSC XENA database. The 13 CRRs were all differently expressed between BC and normal samples. Using consensus clustering based on the five prognostic CRRs, BC patients were classified into two cuproptosis-clusters (C1 and C2). C2 had a significant survival advantage and higher immune infiltration levels than C1. According to the Cox and LASSO regression analyses, a novel cuproptosis-related prognostic signature was developed to predict the prognosis of BC effectively. The high- and low-risk groups were divided based on the risk scores. Kaplan-Meier survival analysis indicated that the high-risk group had shorter overall survival (OS) than the low-risk group in the training, test and entire cohorts. GSEA indicated that the immune-related pathways were significantly enriched in the low-risk group. According to the CIBERSORT and ESTIMATE analyses, patients in the high-risk group had higher infiltrating levels of antitumor lymphocyte cell subpopulations and higher immune score than the low-risk group. The typical immune checkpoints were all elevated in the high-risk group. Furthermore, the high-risk group showed a better immunotherapy response than the low-risk group based on the Tumor Immune Dysfunction and Exclusion (TIDE) and Immunophenoscore (IPS). In conclusion, we identified two cuproptosis-clusters with different prognoses using consensus clustering in BC. We also developed a cuproptosis-related prognostic signature and nomogram, which could indicate the outcome, the tumor immune microenvironment, as well as the response to immunotherapy.

A novel hypoxia- and lactate metabolism-related signature to predict prognosis and immunotherapy responses for breast cancer by integrating machine learning and bioinformatic analyses.

Background: Breast cancer is the most common cancer worldwide. Hypoxia and lactate metabolism are hallmarks of cancer. This study aimed to construct a novel hypoxia- and lactate metabolism-related gene signature to predict the survival, immune microenvironment, and treatment response of breast cancer patients. Methods: RNA-seq and clinical data of breast cancer from The Cancer Genome Atlas database and Gene Expression Omnibus were downloaded. Hypoxia- and lactate metabolism-related genes were collected from publicly available data sources. The differentially expressed genes were identified using the "edgeR" R package. Univariate Cox regression, random survival forest (RSF), and stepwise multivariate Cox regression analyses were performed to construct the hypoxia-lactate metabolism-related prognostic model (HLMRPM). Further analyses, including functional enrichment, ESTIMATE, CIBERSORTx, Immune Cell Abundance Identifier (ImmuCellAI), TIDE, immunophenoscore (IPS), pRRophetic, and CellMiner, were performed to analyze immune status and treatment responses. Results: We identified 181 differentially expressed hypoxia-lactate metabolism-related genes (HLMRGs), 24 of which were valuable prognostic genes. Using RSF and stepwise multivariate Cox regression analysis, five HLMRGs were included to establish the HLMRPM. According to the medium-risk score, patients were divided into high- and low-risk groups. Patients in the high-risk group had a worse prognosis than those in the low-risk group (P < 0.05). A nomogram was further built to predict overall survival (OS). Functional enrichment analyses showed that the low-risk group was enriched with immune-related pathways, such as antigen processing and presentation and cytokine-cytokine receptor interaction, whereas the high-risk group was enriched in mTOR and Wnt signaling pathways. CIBERSORTx and ImmuCellAI showed that the low-risk group had abundant anti-tumor immune cells, whereas in the high-risk group, immunosuppressive cells were dominant. Independent immunotherapy datasets (IMvigor210 and GSE78220), TIDE, IPS and pRRophetic analyses revealed that the low-risk group responded better to common immunotherapy and chemotherapy drugs. Conclusions: We constructed a novel prognostic signature combining lactate metabolism and hypoxia to predict OS, immune status, and treatment response of patients with breast cancer, providing a viewpoint for individualized treatment.

A lactate-related LncRNA model for predicting prognosis, immune landscape and therapeutic response in breast cancer.

Breast cancer (BC) has the highest incidence rate of all cancers globally, with high heterogeneity. Increasing evidence shows that lactate and long non-coding RNA (lncRNA) play a critical role in tumor occurrence, maintenance, therapeutic response, and immune microenvironment. We aimed to construct a lactate-related lncRNAs prognostic signature (LRLPS) for BC patients to predict prognosis, tumor microenvironment, and treatment responses. The BC data download from the Cancer Genome Atlas (TCGA) database was the entire cohort, and it was randomly assigned to the training and test cohorts at a 1:1 ratio. Difference analysis and Pearson correlation analysis identified 196 differentially expressed lactate-related lncRNAs (LRLs). The univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis were used to construct the LRLPS, which consisted of 7 LRLs. Patients could be assigned into high-risk and low-risk groups based on the medium-risk sore in the training cohort. Then, we performed the Kaplan-Meier survival analysis, time-dependent receiver operating characteristic (ROC) curves, and univariate and multivariate analyses. The results indicated that the prognosis prediction ability of the LRLPS was excellent, robust, and independent. Furthermore, a nomogram was constructed based on the LRLPS risk score and clinical factors to predict the 3-, 5-, and 10-year survival probability. The GO/KEGG and GSEA indicated that immune-related pathways differed between the two-risk group. CIBERSORT, ESTIMATE, Tumor Immune Dysfunction and Exclusion (TIDE), and Immunophenoscore (IPS) showed that low-risk patients had higher levels of immune infiltration and better immunotherapeutic response. The pRRophetic and CellMiner databases indicated that many common chemotherapeutic drugs were more effective for low-risk patients. In conclusion, we developed a novel LRLPS for BC that could predict the prognosis, immune landscape, and treatment response.

Genome of the parasitoid wasp Cotesia chilonis sheds light on amino acid resource exploitation.

BACKGROUND: A fundamental feature of parasitism is the nutritional exploitation of host organisms by their parasites. Parasitoid wasps lay eggs on arthropod hosts, exploiting them for nutrition to support larval development by using diverse effectors aimed at regulating host metabolism. However, the genetic components and molecular mechanisms at the basis of such exploitation, especially the utilization of host amino acid resources, remain largely unknown. To address this question, here, we present a chromosome-level genome assembly of the parasitoid wasp Cotesia chilonis and reconstruct its amino acid biosynthetic pathway. RESULTS: Analyses of the amino acid synthetic pathway indicate that C. chilonis lost the ability to synthesize ten amino acids, which was confirmed by feeding experiments with amino acid-depleted media. Of the ten pathways, nine are known to have been lost in the common ancestor of animals. We find that the ability to synthesize arginine was also lost in C. chilonis because of the absence of two key genes in the arginine synthesis pathway. Further analyses of the genomes of 72 arthropods species show that the loss of arginine synthesis is common in arthropods. Metabolomic analyses by UPLC-MS/MS reveal that the temporal concentrations of arginine, serine, tyrosine, and alanine are significantly higher in host (Chilo suppressalis) hemolymph at 3 days after parasitism, whereas the temporal levels of 5-hydroxylysine, glutamic acid, methionine, and lysine are significantly lower. We sequence the transcriptomes of a parasitized host and non-parasitized control. Differential gene expression analyses using these transcriptomes indicate that parasitoid wasps inhibit amino acid utilization and activate protein degradation in the host, likely resulting in the increase of amino acid content in host hemolymph. CONCLUSIONS: We sequenced the genome of a parasitoid wasp, C. chilonis, and revealed the features of trait loss in amino acid biosynthesis. Our work provides new insights into amino acid exploitation by parasitoid wasps, and this knowledge can specifically be used to design parasitoid artificial diets that potentially benefit mass rearing of parasitoids for pest control.

An endoparasitoid uses its egg surface proteins to regulate its host immune response.

With proteomic analysis, we identified 379 egg surface proteins from an endoparasitoid, Cotesia chilonis. Proteins containing conserved enzymatic domains constitute a large proportion of egg surface components. Some proteins, such as superoxidase dismutase, homolog of C. rubecula 32-kDa protein, and immunoevasive protein-2A, are classical parasitism factors that have known functions in host immunity regulation. Melanization assays revealed that a novel egg surface protein, C. chilonis egg surface serpin domain-containing protein had the same function as a C. chilonis venom serpin, as both suppressed host melanization in a dose-dependent manner. C. chilonis egg surface serpin domain-containing protein is mainly transcribed in C. chilonis oocytes with follicular cells, and it is located on both the anterior and posterior sides of the mature egg surface. Additionally, we used LC-MS/MS to identify 586 binding proteins sourced from C. suppressalis plasma located on the eggshell surface of C. chilonis, which included some immunity-related proteins. These results not only indicate that C. chilonis uses its egg surface proteins to reduce the immune response of its host but also imply that endoparasitoid egg surface proteins might be a new parasitism factor involved in host immune regulation.

Super-ARMS: A new method for plasma ESR1 mutation detection.

BACKGROUND: ESR1 mutation is an important mechanism of drug resistance and recurrence in hormone receptor-positive breast cancer patients during AI treatment. Patient could still benefit from treatment with fulvestrant after ESR1 mutated. OBJECTIVE: At present, there is still no suitable method to detect ESR1 mutation in plasma as clinical promotion method. We aim to improve from ARMS-PCR to get a method with higher sensitivity but no additional cost is incurred. METHODS: We designed new primers for ESR1. Then positive and negative standard sample was used for sensitivity and specificity tests. Lastly, we collected patient peripheral blood sample and analyzed the performance of Super-ARMS in plasma ctDNA samples. RESULTS: A total of 207 patients were enrolled in this study, including 142 prime breast cancer (PBC) patients and 65 metastasis breast cancer(MBC) patients. The mutation rate was as high as 27.9%(12/43) in MBC patients with AI treatment. But only 2.97%(3/101) in PBC patients with AI and 0% in both MBC or PBC patient without AI. There was no significant difference in Super-ARMS results compared with DDPCR method. CONCLUSION: Super-ARMS is a method that has sensitivity close to DDPCR and has the convenience and low price of ARMS-PCR for plasma ctDNA ESR1 mutation detection. It has obvious advantages compared with other method such NGS and DDPCR as clinical promotion method.

FOXD1 promotes dedifferentiation and targeted therapy resistance in melanoma by regulating the expression of connective tissue growth factor.

Metastatic melanoma is an aggressive skin cancer and associated with a poor prognosis. In clinical terms, targeted therapy is one of the most important treatments for patients with BRAFV600E -mutated advanced melanoma. However, the development of resistance to this treatment compromises its therapeutic success. We previously demonstrated that forkhead box D1 (FOXD1) regulates melanoma migration and invasion. Here, we found that FOXD1 was highly expressed in melanoma cells and was associated with a poor survival of patients with metastatic melanoma. Upregulation of FOXD1 expression enhanced melanoma cells' resistance to vemurafenib (BRAF inhibitor [BRAFi]) or vemurafenib and cobimetinib (MEK inhibitor) combination treatment whereas loss of FOXD1 increased the sensitivity to treatment. By comparing gene expression levels between FOXD1 knockdown (KD) and overexpressing (OE) cells, we identified the connective tissue growth factor (CTGF) as a downstream factor of FOXD1. Chromatin immunoprecipitation and luciferase assay demonstrated the direct binding of FOXD1 to the CTGF promoter. Similar to FOXD1, knockdown of CTGF increased the sensitivity of BRAFi-resistant cells to vemurafenib. FOXD1 KD cells treated with recombinant CTGF protein were less sensitive towards vemurafenib compared to untreated FOXD1 KD cells. Based on these findings, we conclude that FOXD1 might be a promising new diagnostic marker and a therapeutic target for the treatment of targeted therapy resistant melanoma.

Amino acid synthesis loss in parasitoid wasps and other hymenopterans.

Insects utilize diverse food resources which can affect the evolution of their genomic repertoire, including leading to gene losses in different nutrient pathways. Here, we investigate gene loss in amino acid synthesis pathways, with special attention to hymenopterans and parasitoid wasps. Using comparative genomics, we find that synthesis capability for tryptophan, phenylalanine, tyrosine, and histidine was lost in holometabolous insects prior to hymenopteran divergence, while valine, leucine, and isoleucine were lost in the common ancestor of Hymenoptera. Subsequently, multiple loss events of lysine synthesis occurred independently in the Parasitoida and Aculeata. Experiments in the parasitoid Cotesia chilonis confirm that it has lost the ability to synthesize eight amino acids. Our findings provide insights into amino acid synthesis evolution, and specifically can be used to inform the design of parasitoid artificial diets for pest control.

An Ovarian Protein Involved in Passive Avoidance of an Endoparasitoid To Evade Its Host Immune Response.

Through a combination of transcriptomic and proteomic analyses, we identified 817 secreted ovarian proteins from an endoparasitoid wasp, Cotesia chilonis, of which five proteins are probably involved in passive evasion. The results of an encapsulation assay revealed that one of these passive evasion-associated proteins (Crp32B), a homologue of a 32-kDa protein (Crp32) from C. rubecula, could protect resin beads from being encapsulated by host hemocytes in a dose-dependent manner. Crp32B is transcribed in ovarian cells, nurse cells, follicular cells, and oocytes, and the protein is located throughout the ovary and on the egg surface. Moreover, Crp32B has antigenic similarity to several host components. These results indicate that C. chilonis may use molecular mimicry as a mechanism to avoid host cellular immune response.

Expression of Neural Crest Markers GLDC and ERRFI1 is Correlated with Melanoma Prognosis.

Regulation of particular genes during the formation of neural crest (NC) cells is also described during progression of malignant melanoma. In this context, it is of paramount importance to develop neural crest models allowing the identification of candidate genes, which could be used as biomarkers for melanoma prognosis. Here, we used a human induced Pluripotent Stem Cells (iPSC)-based approach to present novel NC-associated genes, expression of which was upregulated in melanoma. A list of 8 candidate genes, based on highest upregulation, was tested for prognostic value in a tissue microarray analysis containing samples from advanced melanoma (good versus bad prognosis) as well as from high-risk primary melanomas (early metastasizing versus non or late-metastasizing). CD271, GLDC, and ERRFI1 showed significantly higher expression in metastatic patients who died early than the ones who survived at least 30 months. In addition, GLDC and TWIST showed a significantly higher immunohistochemistry (IHC) score in primary melanomas from patients who developed metastases within 12 months versus those who did not develop metastases in 30 months. In conclusion, our iPSC-based study reveals a significant association of NC marker GLDC protein expression with melanoma prognosis.