Before anti-EGFR therapy is given to patients with colorectal cancer, it is required to determine KRAS mutation status in tumor. When tumor tissue is not available, cell-free DNA (liquid biopsy) is ...commonly used as an alternative. Due to the low abundance of tumor-derived DNA in cell-free DNA samples, methods with high sensitivity were preferred, including digital polymerase chain reaction, amplification refractory mutation system and next-generation sequencing. The aim of this systemic review and meta-analysis was to investigate the accuracy of those methods in detecting KRAS mutation in cell-free DNA sample from patients with colorectal cancer.
Literature search was performed in Pubmed, Embase, and Cochrane Library. After removing duplicates from the 170 publications found by literature search, eligible studies were identified using pre-defined criteria. Quality of the publications and relevant data were assessed and extracted thereafter. Meta-DiSc and STATA softwares were used to pool the accuracy parameters from the extracted data.
A total of 33 eligible studies were identified for this systemic review and meta-analysis. After pooling, the overall sensitivity, specificity, and diagnostic odds ratio were 0.77 (95%CI: 0.74-0.79), 0.87 (95%CI: 0.85-0.89), and 23.96 (95%CI: 13.72-41.84), respectively. The overall positive and negative likelihood ratios were 5.55 (95%CI: 3.76-8.19) and 0.29 (95%CI: 0.21-0.38), respectively. Area under curve of the summarized ROC curve was 0.8992.
Digital polymerase chain reaction, amplification refractory mutation system, and next-generation sequencing had overall high accuracy in detecting KRAS mutation in cell-free DNA sample. Large prospective randomized clinical trials are needed to further convince the accuracy and usefulness of KRAS mutation detection using cfDNA/liquid biopsy samples in clinical practice.
PROSPERO CRD42020176682; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=176682.
Non-small cell lung cancer (NSCLC) is the most common cancer type in China. Targeted therapies have been used to treat NSCLC for two decades, which is only suitable for a subgroup of patients with ...specific genetic variations. The aim of this study was to investigate the prevalence of genetic variations leading to sensitivity or resistance to targeted therapies in NSCLC, and their relationship with clinicopathological characteristics of the patients.
Tumor samples were collected from 404 patients who were diagnosed to have NSCLC and underwent surgery, transthoracic biopsy, bronchoscopy biopsy, or pleural aspiration in Sichuan Provincial People's Hospital from January 2019 to March 2020. Commercial amplification-refractory mutation system kits were used to detect targeted therapy-related genetic variations in those tumor samples. The prevalence of genetic variations and their relationship with patient clinicopathological characteristics were analyzed using statistical software, followed by subgroup analysis.
In all, 50.7% of the NSCLC patients had sensitive genetic variations to anti-EGFR therapies, and 4.9% of those patients had co-existing resistant genetic variations. Fusions in ALK, ROS1, or RET were found in 7.7% of the patients, including 2 patients with co-existing EGFR exon 19 deletion or L858R. EGFR exon 19 deletion and L858R were more common in female patients and adenocarcinoma. Further subgroup analysis confirmed the observation in female patients in adenocarcinoma subgroup, and in adenocarcinoma in male patients. In addition, smokers were more likely to have squamous cell carcinoma and KRAS mutation and less likely to have EGFR L858R, which were also confirmed after standardization of gender except KRAS mutations.
Nearly half of the NSCLC patients were eligible for anti-EGFR treatments. In NSCLC, female gender and adenocarcinoma may indicate higher chance of EGFR exon 19 deletion or L858R, and smoking history may indicate squamous cell carcinoma and EGFR L858R.
The aim of this study was to investigate the diagnostic accuracy of KRAS mutation detection using plasma sample of patients with non-small cell lung cancer (NSCLC).
Databases of Pubmed, Embase, ...Cochrane Library, and Web of Science were searched for studies detecting KRAS mutation in paired tissue and plasma samples of patients with NSCLC. Data were extracted from each eligible study and analyzed using MetaDiSc and STATA.
After database searching and screening of the studies with pre-defined criteria, 43 eligible studies were identified and relevant data were extracted. After pooling the accuracy data from 3341 patients, the pooled sensitivity, specificity and diagnostic odds ratio were 71%, 94%, and 59.28, respectively. Area under curve of summary receiver operating characteristic curve was 0.8883. Subgroup analysis revealed that next-generation sequencing outperformed PCR-based techniques in detecting
mutation using plasma sample of patients with NSCLC, with sensitivity, specificity, and diagnostic odds ratio of 73%, 94%, and 82.60, respectively.
Compared to paired tumor tissue sample, plasma sample showed overall good performance in detecting KRAS mutation in patients with NSCLC, which could serve as good surrogate when tissue samples are not available.
Synthetic lethality describes situations in which defects in two different genes or pathways together result in cell death. This concept has been applied to drug development for cancer treatment, as ...represented by Poly (ADP-ribose) polymerase (PARPs) inhibitors. In the current study, we performed a computational screening to discover new PARP inhibitors. Among the 11,247 compounds analyzed, one natural product, ZINC67913374, stood out by its superior performance in the simulation analyses. Compared with the FDA approved PARP1 inhibitor, olaparib, our results demonstrated that the ZINC67913374 compound achieved a better grid score (-86.8) and amber score (-51.42). Molecular dynamics simulations suggested that the PARP1-ZINC67913374 complex was more stable than olaparib. The binding free energy for ZINC67913374 was -177.28 kJ/mol while that of olaparib was -159.16 kJ/mol. These results indicated ZINC67913374 bound to PARP1 with a higher affinity, which suggest ZINC67913374 has promising potential for cancer drug development.
To control COVID-19 pandemic, complete lockdown was initiated in 2020. We investigated the impact of lockdown on tertiary-level academic performance, by comparing educational outcomes amongst ...first-year students during second semester of their medical course prior to and during lockdown. Evidence: The demographics, including educational outcomes of the two groups were not significantly different during semester one (prior to the lockdown). The academic performance amongst women was better than men prior to lockdown. However, the scores were improved significantly for both sexes during lockdown in 2020, following the complete online teaching, compared to that in 2019, showing no significant difference between men and women in 2020, for English and Chinese History. There were significant different scores between men and women in lab-based Histology Practice in 2019 (in-person tuition) and 2020 (online digital tuition), although only a significant improvement in women was observed between 2019 and 2020. Implication: the forced change to online delivery of the second semester of the first-year medical program in 2020 due to the COVID-19 pandemic did not result in any decline in assessment outcomes in any of the subjects undertaken. We believe extensive online digital media should continue to be available to students in future.
To combat/control the COVID-19 pandemic, a complete lockdown was implemented in China for almost 6 months during 2020.
To determine the impact of a long-term lockdown on the academic performance of ...first-year nursing students via mandatory online learning, and to determine the benefits of online teaching.
The recruitment and academic performance of 1st-year nursing students were assessed between 2019 prior to COVID-19, n = 195, (146 women) and 2020 during COVID-19, n = 180 (142 women). The independent sample t test or Mann-Whitney test was applied for a comparison between these two groups.
There was no significant difference in student recruitment between 2019 and 2020. The overall performance of the first-year students improved in the Biochemistry, Immunopathology, Traditional Chinese Medicine Nursing and Combined Nursing courses via mandatory online teaching in 2020 compared with traditional teaching in 2019.
Suspension of in-class learning but continuing education virtually online has occurred without negatively impacting academic performance, thus academic goals are more than achievable in a complete lockdown situation. This study offers firm evidence to forge a path for developments in teaching methods to better incorporate virtual learning and technology in order to adapt to fast-changing environments. However, the psychological/psychiatric and physical impact of the COVID-19 lockdown and the lack of face-to-face interaction on these students remains to be explored.
Abstract
Due to the difficulty in sampling of metastatic tumors, patient selection is commonly based on results of primary tumor samples when metastatic samples are not available. However, due to ...tumor heterogeneity, metastatic tumors may be different from primary tumors in their phenotypes. The aim of this study was to investigate the expression of EGFR, HER2, and HER3 between primary and lymph node metastatic lesions of colorectal cancer. Paired primary tumors and lymph node metastases from 79 patients with colorectal cancer were retrospectively collected and analyzed for EGFR, HER2, and HER3 expression. High EGFR, HER2, and HER3 expression (2+ and 3+) was found in 64.2%, 66.0%, and 85.0% of primary tumors, and 56.8%, 46.0%, and 76.0% of lymph node metastases, respectively. Correlation rates between primary and metastatic lesions were 67.1%, 63.3%, and 74.7% for EGFR, HER2, and HER3, respectively. Stage IV tumors (with distant metastasis) had higher correlation rates of HER2 expression compared to stage III tumors (without distant metastasis) (
P
= 0.050). Moderate correlation rates in EGFR, HER2, and HER3 expression were observed between primary and metastatic lesions of colorectal cancer. Tumor stage or existence of distant metastasis could serve as potential predictive markers for the correlation of HER2 expression between primary tumors and lymph node metastases of colorectal cancer.
Introduction
Hemagglutinin (HA) is responsible for facilitating viral entry and infection by promoting the fusion between the host membrane and the virus. Given its significance in the process of ...influenza virus infestation, HA has garnered attention as a target for influenza drug and vaccine development. Thus, accurately identifying HA is crucial for the development of targeted vaccine drugs. However, the identification of HA using in-silico methods is still lacking. This study aims to design a computational model to identify HA.
Methods
In this study, a benchmark dataset comprising 106 HA and 106 non-HA sequences were obtained from UniProt. Various sequence-based features were used to formulate samples. By perform feature optimization and inputting them four kinds of machine learning methods, we constructed an integrated classifier model using the stacking algorithm.
Results and discussion
The model achieved an accuracy of 95.85% and with an area under the receiver operating characteristic (ROC) curve of 0.9863 in the 5-fold cross-validation. In the independent test, the model exhibited an accuracy of 93.18% and with an area under the ROC curve of 0.9793. The code can be found from
https://github.com/Zouxidan/HA_predict.git
. The proposed model has excellent prediction performance. The model will provide convenience for biochemical scholars for the study of HA.
Snake venom contains many toxic proteins that can destroy the circulatory system or nervous system of prey. Studies have found that these snake venom proteins have the potential to treat ...cardiovascular and nervous system diseases. Therefore, the study of snake venom protein is conducive to the development of related drugs. The research technologies based on traditional biochemistry can accurately identify these proteins, but the experimental cost is high and the time is long. Artificial intelligence technology provides a new means and strategy for large-scale screening of snake venom proteins from the perspective of computing. In this paper, we developed a sequence-based computational method to recognize snake toxin proteins. Specially, we utilized three different feature descriptors, namely
, natural vector and word 2 vector, to encode snake toxin protein sequences. The analysis of variance (ANOVA), gradient-boost decision tree algorithm (GBDT) combined with incremental feature selection (IFS) were used to optimize the features, and then the optimized features were input into the deep learning model for model training. The results show that our model can achieve a prediction performance with an accuracy of 82.00% in 10-fold cross-validation. The model is further verified on independent data, and the accuracy rate reaches to 81.14%, which demonstrated that our model has excellent prediction performance and robustness.
PDF
