何信瑩教授研究團隊發表研究成果於Human Genetics and Genomics Advances

連結網址：https://pubmed.ncbi.nlm.nih.gov/37124139/

Abstract

The ability to detect cancer at an early stage in patients who would benefit from effective therapy is a key factor in increasing survivability. This work proposes an evolutionary supervised learning method called CancerSig to identify cancer stage-specific microRNA (miRNA) signatures for early cancer predictions. CancerSig established a compact panel of miRNA signatures as potential markers from 4,667 patients with 15 different types of cancers for the cancer stage prediction, and achieved a mean performance: 10-fold cross-validation accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve of 84.27% ± 6.31%, 0.81 ± 0.12, 0.80 ± 0.10, and 0.80 ± 0.06, respectively. The pan-cancer analysis of miRNA signatures suggested that three miRNAs, hsa-let-7i-3p, hsa-miR-362-3p, and hsa-miR-3651, contributed significantly toward stage prediction across 8 cancers, and each of the 67 miRNAs of the panel was a biomarker of stage prediction in more than one cancer. CancerSig may serve as the basis for cancer screening and therapeutic selection.

李宗夷教授研究團隊發表研究成果於Microbiology Spectrum

連結網址：https://pubmed.ncbi.nlm.nih.gov/37042778/

Abstract

In clinical microbiology, matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) is frequently employed for rapid microbial identification. However, rapid identification of antimicrobial resistance (AMR) in Escherichia coli based on a large amount of MALDI-TOF MS data has not yet been reported. This may be because building a prediction model to cover all E. coli isolates would be challenging given the high diversity of the E. coli population. This study aimed to develop a MALDI-TOF MS-based, data-driven, two-stage framework for characterizing different AMRs in E. coli. Specifically, amoxicillin (AMC), ceftazidime (CAZ), ciprofloxacin (CIP), ceftriaxone (CRO), and cefuroxime (CXM) were used. In the first stage, we split the data into two groups based on informative peaks according to the importance of the random forest. In the second stage, prediction models were constructed using four different machine learning algorithms-logistic regression, support vector machine, random forest, and extreme gradient boosting (XGBoost). The findings demonstrate that XGBoost outperformed the other four machine learning models. The values of the area under the receiver operating characteristic curve were 0.62, 0.72, 0.87, 0.72, and 0.72 for AMC, CAZ, CIP, CRO, and CXM, respectively. This implies that a data-driven, two-stage framework could improve accuracy by approximately 2.8%. As a result, we developed AMR prediction models for E. coli using a data-driven two-stage framework, which is promising for assisting physicians in making decisions. Further, the analysis of informative peaks in future studies could potentially reveal new insights. IMPORTANCE Based on a large amount of matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) clinical data, comprising 37,918 Escherichia coli isolates, a data-driven two-stage framework was established to evaluate the antimicrobial resistance of E. coli. Five antibiotics, including amoxicillin (AMC), ceftazidime (CAZ), ciprofloxacin (CIP), ceftriaxone (CRO), and cefuroxime (CXM), were considered for the two-stage model training, and the values of the area under the receiver operating characteristic curve (AUC) were 0.62 for AMC, 0.72 for CAZ, 0.87 for CIP, 0.72 for CRO, and 0.72 for CXM. Further investigations revealed that the informative peak m/z 9714 appeared with some important peaks at m/z 6809, m/z 7650, m/z 10534, and m/z 11783 for CIP and at m/z 6809, m/z 10475, and m/z 8447 for CAZ, CRO, and CXM. This framework has the potential to improve the accuracy by approximately 2.8%, indicating a promising potential for further research.

楊慕華教授與林峻宇助理教授團隊共同發表研究成果於Advanced Science

連結網址：https://pubmed.ncbi.nlm.nih.gov/37026630/

Abstract

As a type of immunogenic cell death, ferroptosis participates in the creation of immunoactive tumor microenvironments. However, knowledge of spatial location of tumor cells with ferroptosis signature in tumor environments and the role of ferroptotic stress in inducing the expression of immune-related molecules in cancer cells is limited. Here the spatial association of the transcriptomic signatures is demonstrated for ferroptosis and inflammation/immune activation located in the invasive front of head and neck squamous cell carcinoma (HNSCC). The association between ferroptosis signature and inflammation/immune activation is more prominent in HPV-negative HNSCC compared to HPV-positive ones. Ferroptotic stress induces PD-L1 expression through reactive oxygen species (ROS)-elicited NF-κB signaling pathway and calcium influx. Priming murine HNSCC with the ferroptosis inducer sensitizes tumors to anti-PD-L1 antibody treatment. A positive correlation between the ferroptosis signature and the active immune cell profile is shown in the HNSCC samples. This study reveals a subgroup of ferroptotic HNSCC with immune-active signatures and indicates the potential of priming HNSCC with ferroptosis inducers to increase the antitumor efficacy of immune checkpoint inhibitors.

謝仁俊教授研究團隊發表研究成果於Rhinology

連結網址：https://pubmed.ncbi.nlm.nih.gov/37000430/

Abstract

Background: Olfactory capacity increases during the period of ovulation, perhaps as an adjunct to mate selection; however, researchers have yet to elucidate the neural underpinning of menstrual cycle-dependent variations in olfactory performance.

Methodology: A cohort of healthy volunteers (n = 88, grand cohort) underwent testing for gonadal hormone levels and resting-state functional magnetic resonance imaging with a focus on intrinsic functional connectivity (FC) in the olfactory network based on a priori seeds (piriform cortex and orbitofrontal cortex) during the periovulatory (POV) and menstrual (MEN) phases. A subcohort (n = 20, olfaction cohort) returned to the lab to undergo testing of olfactory performance during the POV and MEN phases of a subsequent menstrual cycle.

Results: Olfactory performance and FC were both stronger in the periovulatory phase than in the menstrual phase. Enhanced FC was observed in the network targeting the cerebellum in both the grand and olfaction cohorts, while enhanced FC was observed in the middle temporal gyrus, lingual gyrus, dorsal medial prefrontal cortex, and postcentral gyrus in the grand cohort. Periovulatory progesterone levels in the grand cohort were positively correlated with FC in the network targeting the insula and paracentral lobule.

Conclusion: Our analysis revealed that superior olfactory function in the periovulatory period is associated with enhanced intrinsic connectivity in the olfactory network. These findings can be appreciated in the context of evolutionary biology.

趙瑞益教授研究團隊發表研究成果於Anti-Cancer Agents in Medicinal Chemistry

連結網址：https://www.eurekaselect.com/article/129735

Abstract

Background: Lung cancer has become one of the leading causes of cancer incidence and mortality worldwide. Non-small cell lung carcinoma (NSCLC) is the most common type among all lung cancer cases. NSCLC patients contained high levels of activating epidermal growth factor receptor (EGFR) mutations, such as exon 19 deletion, L858R and T790M. Osimertinib, a third-generation of EGFR tyrosine kinase inhibitor (EGFR-TKI), has therapeutic efficacy on the EGFR-T790M mutation of NSCLC patients; however, treatment of osimertinib still can induce drug resistance in lung cancer patients. Therefore, investigation of the drug resistance mechanisms of osimertinib will provide novel strategies for lung cancer therapy.

Methods: The H1975OR osimertinib-resistant cell line was established by prolonged exposure with osimertinib derived from the H1975 cells. The cell proliferation ability was evaluated by the cell viability and cell growth assays. The cell migration ability was determined by the Boyden chamber assays. The differential gene expression profile was analyzed by genome-wide RNA sequencing. The protein expression and location were analyzed by western blot and confocal microscopy.

Results: In this study, we established the osimertinib-resistant H1975 (T790M/L858R) cancer cells, named the H1975OR cell line. The cell growth ability was decreased in the H1975OR cells by comparison with the H1975 parental cells. Conversely, the cell migration ability was elevated in the H1975OR cells. We found the differential gene expression profile of cell proliferation and migration pathways between the H1975OR and H1975 parental cells. Interestingly, the protein levels of phospho-EGFR, PD-L1, E-cadherin and β-catenin were decreased, but the survivin and N-cadherin proteins were increased in the H1975OR drug-resistant cells.

Conclusion: Osimertinib induces the opposite effect of proliferation and migration in the drug resistance of EGFRT790M lung cancer cells. We suggest that differential gene and protein expressions in the cell proliferation and migration pathways may mediate the drug resistance of osimertinib in lung cancer cells. Understanding the molecular drugresistant mechanisms of proliferation and migration pathways of osimertinib may provide novel targets and strategies for the clinical treatment of EGFR-TKIs in lung cancer patients.