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Supplementary Figure S1 presents the viability of SW48 and SW48PK cells after treatment with BEZ235 and TAK-228 at the 100-400nM concentrations.

PIK3CA mutations are common in clinical molecular profiling, yet an effective means to target these cancers has yet to be developed. MTORC1 inhibitors are often used off-label for patients with PIK3CA mutant cancers with only limited data to support this approach. Here we describe a cohort of patients treated with cancers possessing mutations activating the PI3K signaling cascade with minimal benefit to treatment with the MTORC1 inhibitor everolimus. Previously, we demonstrated that dual PI3K/mTOR inhibition could decrease proliferation, induce differentiation, and result in a treatment response in APC and PIK3CA mutant colorectal cancer. However, reactivation of AKT was identified, indicating that the majority of the benefit may be secondary to MTORC1/2 inhibition. TAK-228, an MTORC1/2 inhibitor, was compared with dual PI3K/mTOR inhibition using BEZ235 in murine colorectal cancer spheroids. A reduction in spheroid size was observed with TAK-228 and BEZ235 (−13% and −14%, respectively) compared with an increase of >200% in control (P < 0.001). These spheroids were resistant to MTORC1 inhibition. In transgenic mice possessing Pik3ca and Apc mutations, BEZ235 and TAK-228 resulted in a median reduction in colon tumor size of 19% and 20%, respectively, with control tumors having a median increase of 18% (P = 0.02 and 0.004, respectively). This response correlated with a decrease in the phosphorylation of 4EBP1 and RPS6. MTORC1/2 inhibition is sufficient to overcome resistance to everolimus and induce a treatment response in PIK3CA mutant colorectal cancers and deserves investigation in clinical trials and in future combination regimens.

Detailed characteristics of CRC PDOCS.

Dot plots corresponding to population distribution curves and graphs of individual replicates for bar graphs in Figure 4.

Individual replicates for data shown in Figure 5B.

(A) Individual replicates of data shown in Figure 6A. (B) Individual replicates of data from Figure 6D.

Individual replicates for data shown in Figure 5E.

Purpose:Cancer treatment is limited by inaccurate predictors of patient-specific therapeutic response. Therefore, some patients are exposed to unnecessary side effects and delays in starting effective therapy. A clinical tool that predicts treatment sensitivity for individual patients is needed.Experimental Design:Patient-derived cancer organoids were derived across multiple histologies. The histologic characteristics, mutation profile, clonal structure, and response to chemotherapy and radiation were assessed using bright-field and optical metabolic imaging on spheroid and single-cell levels, respectively.Results:We demonstrate that patient-derived cancer organoids represent the cancers from which they were derived, including key histologic and molecular features. These cultures were generated from numerous cancers, various biopsy sample types, and in different clinical settings. Next-generation sequencing reveals the presence of subclonal populations within the organoid cultures. These cultures allow for the detection of clonal heterogeneity with a greater sensitivity than bulk tumor sequencing. Optical metabolic imaging of these organoids provides cell-level quantification of treatment response and tumor heterogeneity allowing for resolution of therapeutic differences between patient samples. Using this technology, we prospectively predict treatment response for a patient with metastatic colorectal cancer.Conclusions:These studies add to the literature demonstrating feasibility to grow clinical patient-derived organotypic cultures for treatment effectiveness testing. Together, these culture methods and response assessment techniques hold great promise to predict treatment sensitivity for patients with cancer undergoing chemotherapy and/or radiation.

Supplementary Methods

Success rates for growing human cancers in spheroid culture

Tumor heterogeneity is predicted to confer inferior clinical outcomes, however modeling heterogeneity in a manner that still represents the tumor of origin remains a formidable challenge. Sequencing technologies are limited in their ability to identify rare subclonal populations and predict response to the multitude of available treatments for patients. Patient-derived organotypic cultures have significantly improved the modeling of cancer biology by faithfully representing the molecular features of primary malignant tissues. Patient-derived cancer organoid (PCO) cultures contain numerous individual organoids with the potential to recapitulate heterogeneity, though PCOs are most commonly studied in bulk ignoring any diversity in the molecular profile or treatment response. Here we demonstrate the advantage of evaluating individual PCOs in conjunction with cellular level optical metabolic imaging to characterize the largely ignored heterogeneity within these cultures to predict clinical therapeutic response, identify subclonal populations, and determine patient specific mechanisms of resistance.

OBJECTIVE: Cancer treatment is limited by inaccurate predictors of patient-specific therapeutic response. Therefore, some patients are exposed to unnecessary side effects and delays in starting effective therapy. A clinical tool that predicts treatment sensitivity for individual patients is needed. DESIGN: Patient-derived cancer organoids were derived across multiple histologies. The histological characteristics, mutation profile, clonal structure, and response to chemotherapy and radiation were assessed using bright-field and optical metabolic imaging on spheroid and single cell-levels, respectively. RESULTS: We demonstrate that patient-derived cancer organoids represent the cancers from which they were derived, including key histologic and molecular features. These cultures were generated from numerous cancers, various biopsy sample types, and in different clinical settings. Next-generation sequencing reveals the presence of subclonal populations within the organoid cultures. These cultures allow for the detection of clonal heterogeneity with a greater sensitivity than bulk tumor sequencing. Optical metabolic imaging of these organoids provides cell-level quantification of treatment response and tumor heterogeneity allowing for resolution of therapeutic differences between patient samples. Using this technology, we prospectively predict treatment response for a patient with metastatic colorectal cancer. CONCLUSION: These studies add to the literature demonstrating feasibility to grow clinical patient-derived organotypic cultures for treatment effectiveness testing. Together, these culture methods and response assessment techniques hold great promise to predict treatment sensitivity for patients with cancer undergoing chemotherapy and/or radiation. STATEMENT OF TRANSLATIONAL RELEVANCE: The lack of predictive biomarkers is a major limitation in clinical oncology. Patient-derived cancer organoids are a major advance as they are readily generated and represent the tumors from which they are derived. This study further demonstrates the ability of these cultures to represent the phenotypic and molecular heterogeneity within cancers. In addition, this study establishes therapeutic thresholds for further validation using changes in organoid growth rate and optical metabolic imaging. These techniques measure organoid-level and single cell-level therapeutic heterogeneity, respectively. Here these techniques are applied for determining differential response of colorectal cancers to chemotherapy and radiation. In addition, this is one of the first studies to prospectively examine the use these cultures to predict response for an individual patient with cancer.

Background: Colorectal cancer (CRC) remains the second leading cause of cancer-related mortality with limited precision strategies. The human epidermal growth factor receptor (HER2) is amplified in 5% of patients with metastatic CRC. Therapeutic studies have demonstrated activity of HER2 targeting regimens in the late-line treatment setting though little characterization has been done in the setting of not having prior anti-epidermal growth factor receptor antibody therapy or in the first-line treatment setting. Methods: Patient with metastatic colorectal cancer underwent next-generation sequencing (NGS) panel testing by Strata Oncology through the University of Wisconsin Precision Medicine Molecular Tumor Board. Patients were treated per multi-disciplinary recommendation across multiple lines of therapy and tracked by prospective registry (IRB#UW15068). HER2 copy numbers >/= 10 were used to determine amplification. A subset of patients with HER2-amplified CRC were treated with single agent trastuzumab. Results: HER2 amplifications were identified in 4 of 78 cases of metastatic CRC (5.1%). All biopsies were performed prior to exposure to anti-epidermal growth factor receptor inhibitors. Median estimated copy number (CN) was 55.5 [range 13-178]. There was no concurrent alterations in extended RAS, BRAF, PIK3CA, AKT or MTOR. All cases included concurrent mutations in TP53 at R175H (2), C135W, or C135F. Single agent trastuzumab was administered to two patients at standard dosing (trastuzumab 8mg/kg intravenous day 1 cycle 1 followed by 6 mg/kg intravenous day 1 cycle 2+ on a 21 day cycle). One patient was treated in the treatment refractory setting. They had resolution of bowel obstructive symptoms and a minor response on imaging. Additionally, a patient with a HER2 amplification (CN 178) was treated in the first-line setting with single agent trastuzumab. The patient had grade 1 fever with the first cycle and no other treatment related adverse events thereafter. The patient’s CEA decreased from 7,506 to 2,525 ng/mL with the first cycle of therapy and overall reduced to 6.5 ng/mL after 12 cycles of therapy. The patient has had a partial response per RECIST v1.1 response criteria with a reduction of cross-sectional diameter of their disease by 60%. The patient currently continues on this therapy without evidence of disease progression. Conclusions: HER2 amplified colorectal cancers are an important subtype of colorectal cancer. Here we describe the potential benefit of HER2 targeting with single agent trastuzumab and even demonstrate single agent activity in the first-line setting. Further studies should be done to further characterize the benefit of this low toxicity treatment option for patients with metastatic HER2 amplified colorectal cancer. Citation Format: Jeremy Kratz, Nataliya Uboha, Kayla Lemmon, Hannah Houtler, Mark Burkard, Dustin Deming. Durable response to first-line Trastuzumab in HER2 amplified colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1414.

Background: There are limited clinical tools for predicting the effectiveness of cancer therapies. We aim to prospectively predict patient treatment response using patient-derived organotypic cancer spheroids (PDOCS) as an in vitro model which recapitulates the genetic characteristics and 3D organization of the patient’s tumor. Using optical metabolic imaging (OMI) to analyze single cells, we can determine heterogeneous subpopulations in response to drug treatment. Further clinical validation of these techniques and analysis methods are needed before clinical translation. Methods: Tissue biopsies and gross tissue resections were acquired through the University of Wisconsin Precision Medicine Molecular Tumor Board (IRB#UW15068) and UWCCC TSB Biobank. Next-generation sequencing (NGS) from the biopsies was performed to determine molecular profiling. In alignment with the patient’s treatment course, PDOCS were treated with physiologic doses of chemotherapy or targeted therapy. Treatment response was evaluated by measuring change in diameter in conjunction with optical metabolic imaging (OMI) using a multiphoton microscope to measure the fluorescence and redox ratio of NAD(P)H and FAD as an indication of cellular metabolism. Diameter changes between control and treatment groups were compared using Glass’s delta; resistance to therapy was indicated by a Glass’s delta score of below 1.5. The optical redox ratios determined by OMI were compared using Glass’s delta, and resistance was indicated below 0.5. Clinical response was measured using RECIST v1.1 standard response assessment criteria. Results: PDOCS were successfully isolated from colorectal (CRC), lung, gastrointestinal stromal tumor (GIST), ovarian, and breast cancers. These biopsies were all obtained in the treatment refractory setting. PDOCS were generated for seven patients and treated with the same pharmacologic treatment as the patient from which the PDOCS were generated. Multiple treatments were able to be tested both in vitro and clinically for a subset of patients. Treatments included: 5-fluouracil, oxaliplatin, gemcitabine, paclitaxel, olaparib, panitumumab, osimertinib, fulvestrant, and palbociclib. In this cohort, two treatments resulted in stable disease and seven treatments resulted in disease progression. Change in spheroid diameter correlated with clinical treatment outcomes with an effect size (Glass’s delta) threshold of 1.5. OMI predicted response for all patients imaged with an effect size threshold of 0.5 which correlated with the size change analyses. Treatment heterogeneity of OMI was observed in many of the samples. Conclusions: In this largely prospective cohort of patients across disease types, changes in PDOCS size and OMI indices predict treatment benefit for individual patients. Studies on a larger scale are needed to further validate these findings. Citation Format: Carley M. Sprackling, Jeremy D. Kratz, Peter F. Favreau, Mohammad R. Karim, Christopher P. Babiarz, Cheri A. Pasch, Amani A. Gillette, Linda Clipson, Kristina A. Matkowskyj, Jens C. Eichoff, Kayla K. Lemmon, Hannah K. Houtler, Mark E. Burkard, Devon Miller, Melissa C. Skala, Dustin A. Deming. Predicting treatment response using patient derived organotypic cancer spheroids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3143.