The extent and importance of functional heterogeneity and crosstalk between tumor cells is poorly understood. Here, we describe the generation of clonal populations from a patient-derived ovarian clear cell carcinoma model which forms malignant ascites and solid peritoneal tumors upon intraperitoneal transplantation in mice. The clonal populations are engineered with secreted Gaussia luciferase to monitor tumor growth dynamics and tagged with a unique DNA barcode to track their fate in multiclonal mixtures during tumor progression. Only one clone, CL31, grows robustly, generating exclusively malignant ascites. However, multiclonal mixtures form large solid peritoneal metastases, populated almost entirely by CL31, suggesting that transient cooperative interclonal interactions are sufficient to promote metastasis of CL31. CL31 uniquely harbors ERBB2 amplification, and its acquired metastatic activity in clonal mixtures is dependent on transient exposure to amphiregulin, which is exclusively secreted by non-tumorigenic clones. Amphiregulin enhances CL31 mesothelial clearance, a prerequisite for metastasis. These findings demonstrate that transient, ostensibly innocuous tumor subpopulations can promote metastases via “hit-and-run” commensal interactions.

Introduction: While an association between AI diseases and the development of lymphoma (LYM) is known, the impact of AI diseases on patient (pt) outcome across varying LYM subtypes, including the role of immunosuppressive medications (ISM), is not well understood. Methods: We conducted a large, multicenter, RWE retrospective analysis of adult pts with a diagnosis (dx) of lymphoma (LYM) between 1/2000 and 12/2020 and a pre-existing AI disease (see full list AI in Table 1). We examined baseline clinical features at LYM diagnosis, underlying AI disease characteristics, type/duration of ISM, LYM therapy received and survival outcomes. Multinomial regression models adjusted for age and sex identified associations between LYM subtypes, AI diseases, and ISM exposure, and were reported as relative risk ratio (RRR). Survival rates were estimated by Kaplan-Meier. Univariate associations of baseline factors with survival in cases with non-missing data were examined by Cox model and stratified by International Prognostic Index (IPI). Results: In total, 785 pts were identified across 14 North American institutions, of which 694 pts with complete data were included in the final analysis. Rheumatoid arthritis was the most common AI disease (30%) (Table 1). Diffuse large B-cell lymphoma (DLBCL) was the most common histologic subtype (n=303, 44%), and it was the most prevalent histology for nearly every AI disease. The median duration between AI disease and LYM diagnosis was 108 months (mo) (1-816 mo). Several associations were found between specific AI diseases and LYM subtypes, including: Hashimoto's thyroiditis with marginal zone lymphoma (MZL, RRR 2.78 (95% CI 1.14-6.78, P=0.024), Waldenstrom's macroglobulinemia (RRR 7.12 (95% CI 1.07-47.3, P=0.031), and follicular lymphoma (RRR, 2.71, 95% CI 1.01-7.24, P=0.047); Polymyalgia rheumatica with CLL/SLL (RRR 21.27 (95% CI 4.57-98.96), P=0.0001) and MZL (RRR 6.62 (95% CI 1.38-31.80), P=0.018); Psoriasis with peripheral T-cell lymphoma (PTCL, RRR 3.85 (95% CI 1.21-12.22), P=0.022); and Inflammatory bowel disease with CLL/SLL (HR 4.60 (95% CI 1.72-12.34), P=0.002). Overall, 402 (58%) pts had ISM exposure prior to LYM dx, with 279 (40%) pts on active ISM at time of LYM dx. The most commonly used ISM agent was methotrexate (26%); the median duration of ISM prior to LYM diagnosis was 60 mo (1-480). Compared with DLBCL pts, those diagnosed with PTCLs were more likely to have had exposure to TNF-α inhibitors (RR 1.89, 95% CI 1.23-2.89, P=0.004) or apremilast, a phosphodiesterase-4 inhibitor (RR 19.2, 95% CI 2.6-149.9, P=0.005). Rituximab +/- chemotherapy was used as frontline therapy in the majority of B-cell LYM pts, including 90% of DLBCL. Of LYM pts on ISM at initial dx, 41% had a reduction in immunosuppression (RIS), of whom 81% stopped ISM completely (Table 1). Only 10% of pts who underwent RIS were reported to have a flare of AI disease during initial therapy, compared with 7% of pts who had a flare despite no RIS (P=NS). Survival by histology is depicted in Figure A/B. For DLBCL pts (n=303), survival appeared overall comparable to historically reported outcomes in the general DLBCL population. Neither antecedent use of ISM nor duration of ISM were associated with pt outcomes (data not shown). However, a survival advantage was identified among DLBCL pts whose ISM was stopped completely during frontline therapy compared with pts who were not on ISM at diagnosis (Figure C/D). In addition, 10 DLBCL pts underwent 100% RIS +/- rituximab with therapeutic intent and did not receive cytotoxic chemotherapy as part of frontline therapy. Among these, 4 pts (mean age 62 years (26-84); ISM: n=2 MTX, and 1 each azathioprine and etanercept/MTX; EBV+ 2/4) achieved complete remission and remain disease-free at time of last follow-up at 5, 74, 105, and 221 months post-DLBCL dx. Conclusions: Altogether, we identified several novel histologic associations of AI diseases with LYM histologic subtypes. Furthermore, prior receipt of TNF-α inhibitor or a phosphoediesterase 4 inhibitor were associated with a diagnosis of PTCL. For DLBCL pts with antecedent AI disease, complete cessation of ISM during frontline LYM therapy appeared to be associated with improved survival. Finally, there were a small number of select DLBCL pts who garnered long-term disease-free survival using RIS +/- rituximab as frontline therapy, similar to the treatment paradigm in post-transplant lymphoproliferative disorders. Figure 1 Figure 1. Disclosures Olszewski: TG Therapeutics: Research Funding; PrecisionBio: Research Funding; Celldex Therapeutics: Research Funding; Acrotech Pharma: Research Funding; Genentech, Inc.: Research Funding; Genmab: Research Funding. Feldman: Alexion, AstraZeneca Rare Disease: Honoraria, Other: Study investigator. Karmali: Karyopharm: Consultancy; Epizyme: Consultancy; Morphosys: Consultancy, Speakers Bureau; Kite, a Gilead Company: Consultancy, Research Funding, Speakers Bureau; Genentech: Consultancy; AstraZeneca: Speakers Bureau; BeiGene: Consultancy, Speakers Bureau; BMS/Celgene/Juno: Consultancy, Research Funding; EUSA: Consultancy; Janssen/Pharmacyclics: Consultancy; Roche: Consultancy; Takeda: Research Funding. Lunning: TG Therapeutics: Consultancy; Janssen: Consultancy; Verastem: Consultancy; Spectrum: Consultancy; Myeloid Therapeutics: Consultancy; AstraZeneca: Consultancy; Morphosys: Consultancy; ADC Therapeutics: Consultancy; Beigene: Consultancy; Daiichi-Sankyo: Consultancy; Kyowa Kirin: Consultancy; Celgene, a Bristol Myers Squibb Co.: Consultancy; Legend: Consultancy; Acrotech: Consultancy; Novartis: Consultancy; Kite, a Gilead Company: Consultancy; Karyopharm: Consultancy; AbbVie: Consultancy. Palmisiano: Genentech: Research Funding; AbbVie: Consultancy, Research Funding; Takeda: Consultancy; Foundation One: Consultancy. Danilov: Bristol-Meyers-Squibb: Honoraria, Research Funding; Gilead Sciences: Research Funding; Pharmacyclics: Consultancy, Honoraria; Beigene: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; TG Therapeutics: Consultancy, Research Funding; Takeda Oncology: Research Funding; Genentech: Consultancy, Honoraria, Research Funding; Bayer Oncology: Consultancy, Honoraria, Research Funding; Astra Zeneca: Consultancy, Honoraria, Research Funding; SecuraBio: Research Funding; Rigel Pharm: Honoraria. Barta: Kyowa Kirin: Honoraria; Acrotech: Honoraria; Daiichi Sankyo: Honoraria; Seagen: Honoraria. Lansigan: Celgene/BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees. Savage: Astra-Zeneca: Consultancy, Honoraria; Takeda: Other: Institutional clinical trial funding; Roche: Research Funding; Merck: Consultancy, Honoraria, Other: Institutional clinical trial funding; BMS: Consultancy, Honoraria, Other: Institutional clinical trial funding; Seattle Genetics: Consultancy, Honoraria; Servier: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Beigene: Other: Institutional clinical trial funding; Genentech: Research Funding.

Purpose: In the genomic era, more women with low-risk breast cancer will forego chemotherapy and rely on adjuvant endocrine therapy (AET) to prevent metastatic recurrence. However, some of these patients will unfortunately relapse. We sought to understand this outcome. Preliminary work suggested that early discontinuation of AET, also known as non-persistence, may play an important role. A retrospective analysis exploring factors related to our breast cancer patients’ non-persistence with AET was performed. Methods: Women who underwent Oncotype DX® testing between 2011-2014 with minimum 5-year follow-up were included. ‘Low risk’ was defined as Oncotype score < 26. Outcomes of recurrence and persistence were determined by chart review. Patient, tumor and treatment factors were collected, and persistent vs non-persistent groups compared using multivariable ANOVA and Fisher Chi square exact test. Results: We identified 6 cases of distant recurrence among low-risk patients with a median follow-up of 7.7 years. Among them, 5 of 6 patients (83%) were non-persistent with AET. The non-persistence rate in our cohort regardless of recurrence was 57/228 (25%). Non-persistent patients reported more severe side effects compared with persistent patients (p=0.002) andwere more likely to be offered a switch in endocrine therapy, rather than symptom-relief (p=0.006). In contrast, persistent patients were 10.3 times more likely to have been offeredsymptom-alleviating medications compared with non-persistent patients (p<0.001). A subset analysis revealed that patients who persisted with therapy had a higher Oncotype-DX® score than patients who discontinued early (p=0.028). Conclusions: Metastatic recurrence in low-risk breast cancer patients may be primarily due to non-persistence with endocrine therapy. Further work is needed to optimize care for patients who struggle with side effects. To our knowledge, these are the first published data suggesting that Oncotype-DX® score may influence persistence with AET.