Biology subjects

Lai, S. Y.

Publications and source records attributed to Lai, S. Y..

5 recordsLinked to original sources

bioRxiv2025

Role of the ETV5/p38 signaling axis in aggressive thyroid cancer cells

Patients with poorly differentiated thyroid cancer (PDTC) and anaplastic thyroid cancer (ATC) face a much poorer prognosis than those with differentiated thyroid cancers. Around 25% of PDTCs and 35% of ATCs carry the BRAFV600E mutation, which constitutively activates the MAPK pathway, a key driver of cell growth. Although combining BRAF and MEK inhibitors can shrink tumors, resistance often develops. The exact cause of this resistance remains unclear. We previously found that in PDTC and ATC cells the BRAFV600Emutation is strongly linked to the expression of ETV5, a transcription factor downstream of the MAPK pathway. In the current study, we observed a significant association between ETV5 expression and the activation of p38, a central component of the MAPK14 pathway. Upon reduction of ETV5 levels, p38 expression and activation decreased, along with its upstream regulators MKK3/MKK6. This suggests that the MAPK and p38/MAPK14 pathways are interconnected and that p38 has oncogenic properties in these cancers. Using high-throughput screening, we established that combining p38 inhibitors with the BRAF inhibitor dabrafenib showed strong synergy in vitro, including in cells resistant to dabrafenib and trametinib that had acquired a secondary TP53 mutation. We then tested this combination in a genetically engineered mouse model (GEMM) of ATC. Overall, our findings suggest an oncogenic link between the MAPK and p38/MAPK14 pathways and that combining p38 pathway inhibitors with dabrafenib-targeted therapy could improve treatment outcomes for aggressive thyroid cancers. However, more specific and effective p38 inhibitors are required to fully harness this potential.

cancer biology↗

bioRxiv2025

Bypassing cisplatin resistance in Nrf2 hyperactivated head and neck cancer through effective PI3Kinase targeting

BackgroundFor patients with head and neck squamous cell carcinoma (HNSCC), failure of definitive radiation combined with cisplatin nearly universally results in death. Although hyperactivation of the Nrf2 pathway can drive radiation and cisplatin resistance along with suppressed anti-tumor immunity, treatment-refractory HNSCC tumors may retain sensitivity to targeted agents secondary to synergistic lethality with other oncogenic drivers (e.g., NOTCH1 mutations). PurposeWe evaluated the efficacy of PI3K inhibitors (PI3Ki) in bypassing Nrf2-mediated cisplatin resistance in HNSCC. MethodsWe measured transcriptomic, metabolomic and signaling changes driven by PI3Kis in cisplatin-resistant HNSCCs in vitro and tested efficacy in vivo in subcutaneous, orthotopic and metastatic xenograft models using immunodeficient and humanized murine models of HNSCC coupled with spatial transcriptomics. ResultsThe PI3K pathway is activated in Nrf2-driven cisplatin-resistant HNSCC and is suitable for blockade as demonstrated in an in vivo shRNA screen. The PI3Ki gedatolisib inhibits cisplatin-resistant HNSCC proliferation, induces G2M arrest and potentiates cisplatin effectiveness through activation of autophagy, senescence and disruption of fatty acid metabolism. Gedatolisib suppresses HNSCC tumor growth in orthotopic and metastatic settings and demonstrates profound anti-tumor activity in humanized murine models of HNSCC, coupled with a reduction in hypoxia-rich regions and reduced infiltration by regulatory T lymphocytes. ConclusionOur findings emphasize the critical role of the PI3K-AKT-mTOR pathway in cisplatin-resistant HNSCC and highlight the therapeutic potential of PI3K inhibitors. Gedatolisib induced metabolic regulation and substantial re-sensitization of resistant cells to cisplatin, positioning it as a promising candidate for combination therapies aimed at overcoming primary chemo-radiation failure in HNSCC. Statement of translational relevanceCisplatin resistance, whether intrinsic or acquired, translates to treatment failure and nearly universal death in head and neck squamous cell carcinoma (HNSCC). However, the development of effective systemic regimens for cisplatin-resistant HNSCC has not yet been successful. Here, we present, for the first time, a mechanistic, biomarker-informed strategy for effective targeting of the PI3Kinase pathway in cisplatin-resistant HNSCC with substantial anti-tumor activity in both orthotopic and metastatic models, which may be capable of bypassing or reversing cisplatin resistance in this disease.

cancer biology↗

bioRxiv2024

Tobacco smoke exposure is a driver of altered oxidative stress response and immunity in head and neck cancer

PurposeExposomes are critical drivers of carcinogenesis. However, how they modulate tumor behavior remains unclear. Extensive clinical data link cigarette smoke as a key exposome that promotes aggressive tumors, higher rates of metastasis, reduced response to chemoradiotherapy, and suppressed anti-tumor immunity. We sought to determine whether smoke itself can modulate aggressive tumor behavior in head and neck squamous cell carcinoma (HNSCC) through reprogramming the cellular reductive state. Experimental designUsing established human and murine HNSCC cell lines and syngeneic mouse models, we utilized conventional western blotting, steady state and flux metabolomics, RNA sequencing, quantitative proteomics and flow cytometry to analyze the impact of smoke exposure on HNSCC tumor biology. ResultsCigarette smoke persistently activated Nrf2 target genes essential for maintenance of the cellular reductive state and survival under conditions of increased oxidative stress in HNSCC regardless of HPV status. In contrast to e-cigarette vapor, conventional cigarette smoke mobilizes cellular metabolism toward oxidative stress adaptation, resulting in development of cross-resistance to cisplatin. In parallel, smoke exposure modulates both expression of PDL1 and the secretory phenotype of HNSCC cells through activation of NF-{kappa}B resulting in an altered tumor immune microenvironment (TIME) in syngeneic mouse models and altered PBMC differentiation that includes downregulated expression of antigen presentation and costimulatory genes in myeloid cells. ConclusionCigarette smoke exposome is a potent activator of the Nrf2 pathway and is a likely primary trigger for the tripartite phenotype of aggressive HNSCC consisting of: 1) reduced chemotherapy sensitivity, 2) enhanced metastatic potential and 3) suppressed anti-tumor immunity. Statement of significanceThe smoke exposome drives aggressive tumor behavior, treatment resistance and suppressed immunity through coordinated metabolic reprogramming. Successfully targeting this adaptation is critical to improving survival in smokers with head and neck cancer.

cancer biology↗

bioRxiv2022

Feasibility of Using Wearable EMG Armbands combined with Unsupervised Transfer Learning for Seamless Myoelectric Control

Myoelectric control uses electromyography (EMG) signals as human-originated input to enable intuitive interfaces with machines. As such, recent rehabilitation robotics employs myoelectric control to autonomously classify user intent or operation mode using machine learning. However, performance in such applications inherently suffers from the non-stationarity of EMG signals across measurement conditions. Current laboratory-based solutions rely on careful, time-consuming control of the recordings or periodic recalibration, impeding real-world deployment. We propose that robust yet seamless myoelectric control can be achieved using a low-end, easy-to-"don" and "doff" wearable EMG sensor combined with unsupervised transfer learning. Here, we test the feasibility of one such application using a consumer-grade sensor (Myo armband, 8 EMG channels @ 200 Hz) for gesture classification across measurement conditions using an existing dataset: 5 users x 10 days x 3 sensor locations. Specifically, we first train a deep neural network using Temporal-Spatial Descriptors (TSD) with labeled source data from any particular user, day, or location. We then apply the Self-Calibrating Asynchronous Domain Adversarial Neural Network (SCADANN), which automatically adjusts the trained TSD to improve classification performance for unlabeled target data from a different user, day, or sensor location. Compared to the original TSD, SCADANN improves accuracy by 12{+/-}5.2% (avg{+/-}sd), 9.6{+/-}5.0%, and 8.6{+/-}3.3% across all possible user-to-user, day-to-day, and location-to-location cases, respectively. In one best-case scenario, accuracy improves by 26% (from 67% to 93%), whereas sometimes the gain is modest (e.g., from 76% to 78%). We also show that the performance of transfer learning can be improved by using a "better" model trained with "good" (e.g., incremental) source data. We postulate that the proposed approach is feasible and promising and can be further tailored for seamless myoelectric control of powered prosthetics or exoskeletons.

bioengineering↗

bioRxiv2017

Imaging-Genomics Study Of Head-Neck Squamous Cell Carcinoma: Associations Between Radiomic Phenotypes And Genomic Mechanisms Via Integration Of TCGA And TCIA

PurposeRecent data suggest that imaging radiomics features for a tumor could predict important genomic biomarkers. Understanding the relationship between radiomic and genomic features is important for basic cancer research and future patient care. For Head and Neck Squamous Cell Carcinoma (HNSCC), we perform a comprehensive study to discover the imaging-genomics associations and explore the potential of predicting tumor genomic alternations using radiomic features.\n\nMethodsOur retrospective study integrates whole-genome multi-omics data from The Cancer Genome Atlas (TCGA) with matched computed tomography imaging data from The Cancer Imaging Archive (TCIA) for the same set of 126 HNSCC patients. Linear regression analysis and gene set enrichment analysis are used to identify statistically significant associations between radiomic imaging features and genomic features. Random forest classifier is used to predict two key HNSCC molecular biomarkers, the status of human papilloma virus (HPV) and disruptive TP53 mutation, based on radiomic features.\n\nResultsWide-spread and statistically significant associations are discovered between genomic features (including miRNA expressions, protein expressions, somatic mutations, and transcriptional activities, copy number variations, and promoter region DNA methylation changes of pathways) and radiomic features characterizing the size, shape, and texture of tumor. Prediction of HPV and TP53 mutation status using radiomic features achieves an area under the receiver operating characteristics curve (AUC) of 0.71 and 0.641, respectively.\n\nConclusionOur analysis suggests that radiomic features are associated with genomic characteristics in HNSCC and provides justification for continued development of radiomics as biomarkers for relevant genomic alterations in HNSCC.

cancer biology↗