SheuLab - Research Topics

A. 探討特異性角蛋白融合如何改變細胞機械性特質並促進癌細胞惡化

Novel keratin fusions alter mechanical properties of cancer cells and promote cancer

aggressiveness

Keratins (A.K.A. cytokeratins) are cytoskeleton proteins which can be assembled into intermediate filament (IF) network to provide cells physiological strength against mechanical stress. Due to tissue-type/cell-type specificity, changes in keratin expression profiles have been shown to correlate with epithelial-mesenchymal transition and cancer stem cell (CSC) formation. In recent years, we discovered the existence of keratin fusions (KFs) in oral squamous cell carcinoma (OSCC) and other human SCCs, such as esophageal (ESCC) and cervical (CSCC) cancers. Once expressed in cells, those KFs can hijack wild type keratin and disturb the keratin network, resulting in reduced perinuclear array and nuclear deformation/instability. Because keratins significantly contribute to cell stiffness and impact invasive behavior, disturbance in keratin network by KFs may provide another mechanism to modulate cell stiffness and promote aggressive cancer phenotypes. To address our hypothesis, we are going to investigate how mechanical properties altered by keratin fusion (KFs) may contribute to cancer development and progression.

Graphical summary of our research aims in this project. The research aims were proposed based on our preliminary findings, and the main hypothesis in this project is whether disturbance in keratin network by KFs can provide another mechanism to modulate cell stiffness and thus promote cancer aggressiveness.

B. 能預測免疫檢查點抑制劑療效的癌症基因突變

Somatic mutations as predictive biomarkers for feasibility ofimmunotherapy with immune

checkpoint inhibitors

Immunotherapy by using immune checkpoint inhibitors is an emerging treatment which has been utilized as an attractive alternative way, as compared to traditional anti-cancer drugs, to cure cancers. Tumor-infiltrated lymphocyte scores and neo-antigen (Neo-Ag) burden are key parameters to evaluate the feasibility of such treatments for patients. Although PD-L1 levels in tumor cells were reported highly correlated with those parameters, PD-L1 testing alone is insufficient for patient selection in most malignancies. More reliable/useful predictive biomarkers for patient screening/classification may maximizes the efficacy of checkpoint inhibitors at clinics. In this study, a big data-based regression platform, HD-MAC established in our previous study, will be utilized to find the pivotal gene mutations that can predict overall survival (OS) and disease-free survival (DFS) in muscle-invasive bladder cancer (MIBC), the most aggressive cancer type of bladder cancer. Of note, several recently-defined Neo-Ags caused by somatic mutations were detected in genes which were not considered as cancer drivers and have been totally ignored in cancer genomics study. Here, through an approach from different angles, we will revisit those potently useful mutations and verify their clinical potentials as new prognostic markers for immune checkpoint therapy:

Proposed working flow to define novel Neo-Ags that facilitate the therapeutic efficacy of immune check point inhibitors.

To screen out potentially useful Neo-Ags, we will perform (A) high-dimensional analyses of molecular alterations in cancer (HD-MAC) to find out somatic mutations that determine (B) better clinical outcomes. This platform can be applied to search molecular alterations, e.g. CNVs, mutations, or RNA/protein overexpression, at high-dimensional levels that can associate with any clinical parameters defined. (C) MHC-1/II-binding affinity of peptides containing the mutations will be estimated by NetMHCpan to define Neo-Ags. The ones exposed on the molecular surface will be best candidates to explore. (D) Selected Neo-Ags will be further verified for their roles in immune surveillance by gene set enrichment analysis (GSEA), followed by (E) cytokine/lymphocyte profiling and immune suppressor detection.

C. 中醫理論在月經不調病徵的辨證方劑於西醫臨床與功能機制上的驗證

Clinical validation and functional characterization of TCM syndrome differentiation/treatments

on irregular menstruation

Women’s irregular menstruation that frequently associates with period pain and abnormal menstrual bleeding is a common clinical issue in traditional Chinese medicine (TCM). According to TCM syndrome differentiation, dysregulation in qi and blood circulation is the main cause for this disorder, which easily leads to stasis of menstrual blood in pelvic cavity, resulting in longterm inflammation and hyperalgesia. Although no specific disease term was mentioned in TCM, patients with above clinical symptoms are usually diagnosed as endometriosis by western medicine, a disease which lacks effective treatment so far. Due to unique food culture in Taiwan, most patients who are diagnosed as endometriosis also seek the assistance form TCM, making combined treatments of Chinese and Western medicine quite common here. Interestingly, clinical observations reveal that endometriosis patients co-treated with TCM show a lower medical necessity to receive surgery as compared to those without. In addition, adjuvant treatments with TCM can also delay disease progression in patients after the surgery; thus, the time to relapse in those patients can be significantly extended from 1.6 years to 2.2 years in average. These important clues indicate that TCM treatment should be able to activate certain mechanisms in the body beneficial for patients, which are still largely unknown and need to be further clarified. How to define a better treatment for endometriosis patients based on TCM theory and syndrome differentiation will be the challenge for scientists to explore.

Proposed working flow to investigate how TCM affects inflammation & hyperalgesia in abdomen of patients with endometriosis. To screen out potentially useful Neo-Ags, we will perform (A) high-dimensional analyses of molecular alterations in cancer (HD-MAC) to find out somatic mutations that determine (B) better clinical outcomes. This platform can be applied to search molecular alterations, e.g. CNVs, mutations, or RNA/protein overexpression, at high-dimensional levels that can associate with any clinical parameters defined. (C) MHC-1/II-binding affinity of peptides containing the mutations will be estimated by NetMHCpan to define Neo-Ags. The ones exposed on the molecular surface will be best candidates to explore. (D) Selected Neo-Ags will be further verified for their roles in immune surveillance by gene set enrichment analysis (GSEA), followed by (E) cytokine/lymphocyte profiling and immune suppressor detection.

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