Functional profiling is an emerging trend in precision medicine. Manual laboratory methods proved to be effective in predicting the response to drug treatments both in patients stratified according to genetic profiling and in patients without any specific molecular aberration. In this work, we validated the predictive power of an innovative functional profiling platform, based on lab-on-a-chip technology, which allows testing the response of live tumor cells exposed to anticancer drugs in a fully-automated process, requiring only a Ficoll stratification as a manual step. 15 AML patients (Age: 40% <60 years, 46% in the 60-70 years range, 14% >70 years; Gender: 40% Female; ELN Classification: 20% Favorable, 26% Intermediate-I, 33% Intermediate-II, 14% Adverse; AML stage: 53% De novo, 7% Relapse, 40% Refractory; Treatment: 20% FLAI-3, 40% FLAI-5, 26% Decitabine; 7% Cytarabine, 7% 5-azacitidine) were treated at the Policlinico Sant'Orsola in Bologna. At the same time, bone marrow samples were challenged with the same drugs at scaled concentrations in the functional profiling platform developed by CellPly and an output score was extracted from time-lapse fluorescence image analysis of patient tumor cells exposed to the drug or drug combination for 24 hours. Clinical follow up resulted in the following classification: complete hematologic response (CR) was found in 6/15 patients (6/6 with a De Novo disease), while the remaining 9/15 patients (2/9 de novo; 1/9 Relapse; 6/9 Refractory) were classified as stable disease (SD). In-vitro functional profiling of 14 patients provided a correlation with the clinical outcome (p=0.01) irrespective of the stage of the disease. 100% of the patients identified as responders by functional profiling (n = 5), resulted in a CR outcome. 89% of the patients identified as non-responders (n = 9) resulted in an SD outcome. The same patient samples were also investigated for the molecular assessment of the most relevant genes commonly analyzed in AML patients. FLT3-ITD mutation was found in 2/14 patients, both in SD. Negative FLT3 was not correlated to clinical outcome. FLT3-TKD mutation was found in 3/14 patients, 2/3 resulted in CR, 1/3 in SD. TP53 mutation was found in 1/13 patients, classified as SD. Intronic variant rs1625895 was found in 6/13 patients equally distributed in CR and SD. NPM1 mutation was identified in 4/13 patients, 2/4 resulted in CR, 2/4 in SD indicating no direct correlation. IDH2 was found in 1/11 patients (with R172K mutation) with an SD. As a conclusion, functional profiling proved to be highly correlated with clinical outcome irrespective of patient stage and demonstrated a superior predictive power compared to molecular profiling. Citation Format: Laura Rocchi, Andrea Faenza, Viviana Guadagnuolo, Laura Rambelli, Giovanni Marconi, Maria Chiara Fontana, Martina Pazzaglia, Cristina Papayannidis, Giorgia Simonetti, Nicola Pecorari, Luca Giulianelli, Dario Biscarini, Marco Bettelli, Michele Federici, Rita Ruggiano, Giovanni Martinelli, Roberto Guerrieri, Massimo Bocchi. Lab-on-a-chip-based in-vitro functional profiling proves to be effective in predicting therapy outcome in AML patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3613.

There has been a fast progress in clinical use of antibody-based immunotherapy, given the superior efficacy commonly achieved in clinic and the limited toxicity. However, personalization of treatment remains of major importance, both to achieve better clinical performance for monotherapy and to identify the best combinations on a patient-by-patient basis. Predicting patient's response is complex due to the need to characterize both tumor response and immunologic mechanisms possibly activated by the therapy, including antibody dependent cellular cytotoxicity (ADCC). We present the Inter-Cell Networking Profiling (ICNP), a novel analytical method enabling a comprehensive and precise characterization of the modulatory effect of immunotherapies on immune-tumor cell interactions. ICNP works on the Open Microwell (OMW) microfluidic system which recreates 20,000 unique cell clusters from ex-vivo patient samples and exposes them to anticancer drugs. We validated the ICNP using multiple myeloma (MM) patient samples to characterize the efficacy of Daratumumab, an anti-CD38 antibody (Ab). Bone marrow samples in EDTA were collected from 11 MM patients. 8 samples were processed by Ficoll-Paque, preserving the original composition of effector (E) and target (T) cells, i.e. NK and plasma cells respectively. 3 samples were processed to obtain co-cultures of WBC depleted of plasma cells (which include NK cells) and U-266 MM cell line. NK and plasma cells were stained with anti-CD16/CD56 and anti-CD138 fluorescently-labeled Abs, respectively. Propidium Iodide (PI) was used as death marker. A statistical model was created to project the optimal experimental setup (E:T ratio, cell concentration) to maximize the co-localization of E/T cells in the 20,000 microwells of the OMW platform. After seeding, cells were incubated with Daratumumab 10µg/mL or no drug and analyzed through fluorescence time lapse microscopy for up to 12 hours. ICNP analysis first separates microwells with both E/T cells in close proximity from those not featuring both cell types (Fig 1A). Then, anti-CD38 efficacy is evaluated in microwells with E/T co-localization, thus implementing a miniaturized ADCC assay (Fig 1B). At the same time, spontaneous NK activity is measured in microwells with E/T co-localization and no drug, while direct effect of the drug on target cells can be measured in microwells with T but not E cells. We first validated our statistical model of co-localization in microwells against the actual number of wells with E/T co-localization (correlation R2: 0.79-0.97, n=5). Then, we characterized the immune composition of 8 MM patients samples with the OMW, finding that E/T cell fractions were in the ranges 5-21% (E) and 1-28% (T). Interestingly, according to our statistical model, co-localization occurs in at least 1% of microwells for all the 8 samples, making ICNP applicable with good statistical significance in the OMW system on ex-vivo clinical samples without any pre-enrichment. Finally, ICNP was evaluated on 4 cases (3 obtained by mixing patient's WBC with U-266 MM cell line and 1 complete MM patient sample). We measured the effect of anti-CD38 Ab using i) the standard approach, considering all microwells regardless of the co-presence of E and T; ii) ICNP approach, considering only microwells featuring E/T co-localization. Results show that drug effect is much evident with ICNP in all the 4 cases with an average increase in target cell death of 40%, indicating a higher sensitivity of this approach than the averaged analysis (Fig 1C, right). Importantly, in one case, the standard analysis did not identify significant differences between anti-CD38 treated and control cells, that could instead be observed with ICNP (p<0.0001, 89% cell death) (Fig 1C, left). These results demonstrate that ICNP can determine the efficacy of the therapy taking into account the fitness of single NK cells that is commonly lost in averaged measurements. ICNP proved to enable a comprehensive profiling of the immune system by evaluating in one test the immune composition and the fitness of immune cells, both native and drug-treated. These results open the opportunity to develop functional precision medicine approaches for predicting patient's response to drugs with immune-mediated mechanisms of action. AB and RR equally contributed Figure 1 Disclosures Bettelli: CellPly.S.r.l.: Employment. Ruggiano:Cellply S.r.l.: Employment. Bocchi:CellPly S.r.l.: Employment. Rocchi:CellPly.S.r.l.: Employment. Faenza:CellPly S.r.l.: Employment. Zamagni:Janssen: Honoraria, Other: Advisory board, Speakers Bureau; Amgen: Honoraria, Other: Advisory board, Speakers Bureau; BMS: Honoraria, Other: Advisory Board, Speakers Bureau; Takeda: Honoraria, Speakers Bureau; Sanofi: Honoraria, Other: Advisory Board, Speakers Bureau; Celgene Corporation: Honoraria, Other: Advisory board, Speakers Bureau. Bettelli:CellPly S.r.l.: Employment. Rambelli:CellPly S.r.l.: Employment. Guadagnuolo:CellPly S.r.l.: Employment. Pecorari:CellPly S.r.l.: Employment. Giulianelli:CellPly S.r.l.: Employment. Pisani:CellPly S.r.l.: Employment. Biscarini:CellPly S.r.l.: Employment. Cavo:amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; bms: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations, Speakers Bureau; sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; novartis: Honoraria; takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations, Speakers Bureau; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Guerrieri:CellPly S.r.l.: Equity Ownership. Bocchi:CellPly S.r.l.: Equity Ownership, Membership on an entity's Board of Directors or advisory committees.