Tian Liu on Muck Rack

Tian Liu

Raleigh
As seen in: Nature, CUInsight.com
Genworth Mortgage Insurance Chief Economist. I tweet #economy, #mortgage, #housing, all things #first-time homebuyer, and my views.

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Articles

FATP2-mediated lipid metabolism enhances chimeric antigen receptor T-cell therapy resistance in B-cell acute lymphoblastic leukemia

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By Clarissa Garcia, Julian Grandvallet Contreras, Tian Liu, Amanda Novak, Colin Anderson, Abby Grier, Sabrina Smith, Joshua A Michlin, Railey Mikeska, Xin Zhou, Huimin Geng, Jeremy Rahkola, Hiten Patel, Jeffrey G. Jacot, Markus Müschen, Angelo D’Alessandro, John Dick, Ilaria Iacobucci, Charles G. Mullighan, Julie A. Reisz, M. Kohler, Matthew T. Witkowski, Kaylyn U. Lyons, Alexis J. Donnelly, Amy Argabright, Jesutomisin Olusoji, Tzu Phang
| Nature Verified
Abstract Relapsed/refractory B-cell acute lymphoblastic leukemia (B-ALL) remains a leading cause of cancer-related death in children and young adults. While CD19-directed chimeric antigen receptor T cell (CAR-T) therapy offers promise, high rates of long-term failure underscore the need to understand resistance mechanisms. Our studies found p53 inactivation promotes CAR-T resistance in human pre-B-ALL cell lines.
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Efficacy and safety of infigratinib in patients with refractory advanced gastric or gastroesophageal junction adenocarcinoma harboring FGFR2 gene amplification: a single-arm, multicenter phase 2 trial Original

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By Jiajia Yuan, Jifang Gong, Zhi Peng, Tian Liu, Huiting Xu, Jianwei Yang, Jia Wei, Haiping Jiang, Yanhong Deng, Yusheng Wang, Changsong Qi, Cheng Lyu, Qiao Sun, Lin Song, Xiaotian Zhang, Lin Shen
| Nature Verified
Abstract FGFR2 has garnered attention as a promising therapeutic target for gastric cancer (GC) because of its role in GC progression. Infigratinib, an FGFR1–3 selective tyrosine kinase inhibitor, has shown potential in preclinical GC models. Infigratinib was evaluated in a phase 2 trial for patients with FGFR2-amplified GC or gastroesophageal junction (GEJ) adenocarcinoma who had failed two or more lines of systemic treatment for locally advanced or metastatic disease.
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Development and validation of artificial intelligence-based model for bladder cancer immunophenotyping using whole slide images

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By Qingyuan Zheng, Haonan Mei, Xiaodong Weng, Rui Yang, Kai Wang, Xinmiao Ni, Jiejun Wu, Junjie Fan, Tian Liu, Jingping Yuan, Xiuheng Liu, Lei Wang, Zhiyuan Chen
| Nature Verified
Abstract The classification of immunophenotypes in muscle-invasive bladder cancer (MIBC) is critical for predicting immunotherapy response and clinical outcomes, yet current assessment methods lack standardization and scalability. We developed and validated an artificial intelligence–based MIBC Immunophenotype Diagnostic System using computational pathology to enable reproducible classification from routine hematoxylin and eosin–stained whole-slide images.
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