（此来宾帖子最初发表在the SU2C blog和is reproduced here with permission.)

年度SU2C科学峰会是一次了不起的会议，将最好的科学家和医生聚集在一起，以抗癌。结合临床肿瘤学，癌症生物学和定量科学的多学科“融合”梦想团队的形成是一种真正的协同作用，将癌症的研究提高到任何单一学科都无法实现的较高水平。作为一名肿瘤学家，这种团队心态正是我们在将医学，放射线和外科肿瘤学护理结合的多学科诊所中所做的。癌症研究的新模式确实是一项团队运动。

I have been fortunate to be a part of one of the originalSU2C Convergence Teams, which has allowed me to work closely with Ben Greenbaum at Mt. Sinai Medical School. A convergence team is exactly what it sounds like: Ben’s physics and computational biology background complements my expertise on RNA cancer biology and clinical oncology to tackle some complex cancer research questions. Through our work together, Ben created the first mathematical model that can predict the potential benefit of different treatments for patients diagnosed with melanoma or cancer of the lung or pancreas. The model, which captures aspects of the tumor’s evolution and the underlying interactions of the tumor with the immune system, is more accurate than previous genomic biomarkers in predicting how the tumor will respond. Even without our discovery, I have been so fortunate from this work to have made such a great friend.

At the recent Summit, it was so exciting to see the field move forward with the next step of Convergence research. SU2C awarded $11 million to seven multi-disciplinary research teams to investigate immune system response to cancers. The multi-institutional teams draw from the nation’s top academic research centers and will have access to Microsoft Research’s experts in machine learning and artificial intelligence.

Each team will be comprised of experts in life sciences, physical sciences, mathematics and engineering and will have the opportunity to work collaboratively with Microsoft’s machine learning experts to discover key aspects of the interaction between cancer and the immune system that can lead to the development of new treatments. For Convergence 2.0, Ben and I will collaborate on a study connecting immune health and tumor biology in gynecologic cancers.

Mismatch repair (MMR)-deficient cells are unable to repair base pairing mistakes within the DNA helix, so as they divide over and over, the new cells accumulate more of these mistakes or mutations. The response to immune checkpoint inhibitors has been varied in gynecologic cancers, possibly due to the number of mutations carried by each tumor cell (mutational burden). We hypothesize that the tumors with a high mutational burden fail to respond to checkpoint inhibition because of an immune dysfunction that is based on the mechanism for the MMR deficiency. The team plans to initiate two clinical trials that will test whether a) tumor-intrinsic factors affect the response to checkpoint inhibition; b) baseline immune function and quality affects response to checkpoint inhibition; and c) on-treatment blood markers may reflect the tumor-immune interaction. Understanding the mechanism that leads to this phenomenon has the potential to dramatically affect those patients who do not respond to current treatments.

In addition to the significant support from Microsoft, the Lustgarten Foundation for Pancreatic Cancer Research provided funding for one team, and the Society for Immunotherapy of Cancer (SITC) did as well – the latter to support post-doctoral fellows on five of the seven teams, providing an opportunity for early-career scientists to work with leading researchers.

I am excited for these new teams to utilize artificial intelligence and statistical physics to tackle some of the most provocative questions that need to be answered for the field. It has been amazing to watch the progress we have had in pancreatic cancer research, and the funding provided by SU2C, Lustgarten Foundation and others has propelled my young career forward. I am thrilled to be part of this growing SU2C family.