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Michael C. Jin

Harbin Medical University

ORCID: 0000-0001-7709-1551

Publishes on Cancer Genomics and Diagnostics, Lymphoma Diagnosis and Treatment, Glioma Diagnosis and Treatment. 153 papers and 4.9k citations.

153Publications
4.9kTotal Citations

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Top publicationsby citations

The Use of Immersive Virtual Reality in the Learning Sciences: Digital Transformations of Teachers, Students, and Social Context
Jeremy N. Bailenson, Nick Yee, Jim Blascovich et al.|Journal of the Learning Sciences|2008
Cited by 589

This article illustrates the utility of using virtual environments to transform social interaction via behavior and context, with the goal of improving learning in digital environments. We first describe the technology and theories behind virtual environments and then report data from 4 empirical studies. In Experiment 1, we demonstrated that teachers with augmented social perception (i.e., receiving visual warnings alerting them to students not receiving enough teacher eye gaze) were able to

Circulating Tumor DNA Measurements As Early Outcome Predictors in Diffuse Large B-Cell Lymphoma
David M. Kurtz, Florian Scherer, Michael C. Jin et al.|Journal of Clinical Oncology|2018
Cited by 493Open Access

PURPOSE: Outcomes for patients with diffuse large B-cell lymphoma remain heterogeneous, with existing methods failing to consistently predict treatment failure. We examined the additional prognostic value of circulating tumor DNA (ctDNA) before and during therapy for predicting patient outcomes. PATIENTS AND METHODS: We studied the dynamics of ctDNA from 217 patients treated at six centers, using a training and validation framework. We densely characterized early ctDNA dynamics during therapy using cancer personalized profiling by deep sequencing to define response-associated thresholds within a discovery set. These thresholds were assessed in two independent validation sets. Finally, we assessed the prognostic value of ctDNA in the context of established risk factors, including the International Prognostic Index and interim positron emission tomography/computed tomography scans. RESULTS: Before therapy, ctDNA was detectable in 98% of patients; pretreatment levels were prognostic in both front-line and salvage settings. In the discovery set, ctDNA levels changed rapidly, with a 2-log decrease after one cycle (early molecular response [EMR]) and a 2.5-log decrease after two cycles (major molecular response [MMR]) stratifying outcomes. In the first validation set, patients receiving front-line therapy achieving EMR or MMR had superior outcomes at 24 months (EMR: EFS, 83% v 50%; P = .0015; MMR: EFS, 82% v 46%; P < .001). EMR also predicted superior 24-month outcomes in patients receiving salvage therapy in the first validation set (EFS, 100% v 13%; P = .011). The prognostic value of EMR and MMR was further confirmed in the second validation set. In multivariable analyses including International Prognostic Index and interim positron emission tomography/computed tomography scans across both cohorts, molecular response was independently prognostic of outcomes, including event-free and overall survival. CONCLUSION: Pretreatment ctDNA levels and molecular responses are independently prognostic of outcomes in aggressive lymphomas. These risk factors could potentially guide future personalized risk-directed approaches.