Summary The roles of tumor-associated macrophages (TAMs) and circulating monocytes in human cancer are poorly understood. Here, we show that monocyte subpopulation distribution and transcriptomes are significantly altered by the presence of endometrial and breast cancer. Furthermore, TAMs from endometrial and breast cancers are transcriptionally distinct from monocytes and their respective tissue-resident macrophages. We identified a breast TAM signature that is highly enriched in aggressive breast cancer subtypes and associated with shorter disease-specific survival. We also identified an auto-regulatory loop between TAMs and cancer cells driven by tumor necrosis factor alpha involving SIGLEC1 and CCL8, which is self-reinforcing through the production of CSF1. Together these data provide direct evidence that monocyte and macrophage transcriptional landscapes are perturbed by cancer, reflecting patient outcomes.

6589 Background: IBM Watson for Oncology (WFO) was trained by Memorial Sloan Kettering and is a cognitive computing system that uses natural language processing to ingest patient data in structured and unstructured formats. The system provides physicians with treatment options that are derived from established guidelines, the medical literature, and training from patient cases. In this study, we assessed the degree of concordance between treatment recommendations proposed by WFO and oncologists at Bumrungrad International Hospital (BIH). BIH is a 580-bed multispecialty hospital in Bangkok, Thailand. Methods: Data from breast, colorectal, gastric, and lung cancer patients treated at BIH were entered into WFO in 2015 and 2016. Retrospective cases were entered after a treatment plan had been determined, and prospective cases were entered during patients’ treatment planning sessions. WFO recommendations were provided in 3 categories: “Recommended”, “For Consideration”, and “Not Recommended.” Concordance was analyzed by comparing the decisions made by the oncologists to those proposed by WFO. Concordance was achieved when the oncologist’s treatment suggestion was in the “Recommended” or “For Consideration” categories given by WFO. Results: A total of 211 cases were assessed, 92 were retrospective and 119 were prospective. The overall concordance rate was 83%; 89% for colorectal, 91% for lung, 76% for breast, and 78% for gastric cancer. Similar concordance rates were observed when retrospective and prospective cases were analyzed separately. Discordance was attributable in part to local oncologists’ preferences for non-U.S. guidelines for certain cancers, especially gastric cancer. Conclusions: There was a high degree of concordance between WFO treatment options and the decisions made by local oncologists. Similar results were recently reported in a breast cancer concordance study conducted using WFO in India (San Antonio Breast Cancer Symposium 2016, Somashekhar et al). WFO’s capabilities as a cognitive decision support tool can be further improved by incorporating regional guidelines. Future work will analyze reasons for discordance such as cost, insurance requirements, and patient and physician preference.

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e18204 Background: IBM Watson for Oncology (WFO) is a Memorial Sloan Kettering-trained cognitive computing system that provides oncologists with evidence-based treatment options for cancer. Treatments are presented in three categories: “Recommended”, “For Consideration” and “Not Recommended”. We examined the concordance of treatment options between WFO and the tumor board from Gachon University Gil Medical Centre (GMC), Incheon, South Korea. GMC is an urban center that cares for 50,000 cancer patients annually. Methods: We enrolled 340 patients with stage II, III and IV colon cancer and 185 with chemotherapy-naïve advanced gastric cancer, all treated between 2012 and 2016. Cases were processed using WFO, and the output was compared to blinded tumor board recommendations. Treatment options were considered concordant when the GMC recommendation was included in the “Recommended” or “For Consideration” categories. Results: Treatment recommendations were concordant in 248 (73%) of the 340 evaluated colon cancer cases. Of 250 patients treated in the adjuvant setting, 212 (85%) were concordant. Of 90 patients with metastatic disease, 36 (40%) were concordant. Treatment recommendations were concordant in 90 (49%) of 185 chemotherapy-naïve gastric cancer patients. Low concordance rates in gastric cancer were explained by two observations: (1) The trastzumab/FOLFOX regimen is not covered by the Korean National Health Insurance System, and (2) A regimen known as S-1 (tegafur, gimeracil, and oteracil) plus cisplatin is routinely used in Korea and is not used in the U.S. Conclusions: Treatment options suggested by WFO were concordant with the therapeutic decisions of GMC in the large majority of colon cancer patients treated in the adjuvant setting. Lower degrees of concordance were seen in patients with metastatic colon and gastric cancer, reflecting differences in practice patterns between the United States, where WFO was trained, and GMC, in Korea. Geography-specific customization is available in WFO and should enable physicians and patients to benefit from WFO worldwide. WFO's ability to learn from gastric cancer cases in a part of the world with increased incidence may reveal insights that are applicable elsewhere.