Combination chemotherapies that introduce multi-agent treatments to target cancer cells are emerging as new paradigms to overcome chemotherapy resistance and side effects involved with conventional monotherapies. In environmental toxicology, characterizing effects of mixtures of toxins rather than simply analyzing the effect of single toxins are of significant interest. In order to determine such combination effects, it is necessary to systematically investigate interactions between different concentration-dependent components of a mixture. Conventional microtiter plate format based assays are efficient and cost-effective, however are not practical as the number of combinations increases drastically. Although robotic pipetting systems can overcome the labor-intensive and time-consuming limitations, they are too costly for general users. Microfluidic live cell screening platforms can allow precise control of cell culture microenvironments by applying accurate doses of biomolecular mixtures with specific mixing ratios generated through integrated on-chip microfluidic gradient generators. This thesis first presents a live cell array platform with integrated microfluidic network-based gradient generator which enables generation and dosing of 64 unique combinations of two cancer drugs at different concentrations to an 8 by 8 cell culture chamber array. We have developed the system into a fully automated microfluidic live cell screening platform with uniform cell seeding capability and pair-wise gradient profile generation. This platform was utilized to investigate the gene expression regulation of colorectal cancer cells in response to combination cancer drug treatment. The resulting cell responses indicate that the two cancer drugs show additive effect when sequential drug treatment scheme is applied, demonstrating the utility of the microfluidic live cell assay platform. However, large reagent consumption and difficulties of repeatedly generating the exact same concentrations and mixture profiles from batch to batch and device to device due to the fact that the generated gradient profiles or mixing ratios of chemicals have to rely on stable flow at optimized flow rate throughout the entire multi-day experiment limit the widespread use of this method. Moreover, producing three or more reagent mixtures require complicated microchannel structures and operating procedures when using traditional microfluidic network-based gradient generators. Therefore, an on-demand geometric metering-based mixture generator which facilitates robust, scalable, and accurate multi-reagent mixing in a high-throughput fashion has been developed and incorporated with a live cell array as a microfluidic screening platform for conducting combination drug or toxin assays. Integrated single cell trapping array allowed single cell resolution analysis of drugs and toxin effects. Reagent mixture generation and precise application of the mixtures to arrays of cell culture chambers repeatedly over time were successfully demonstrated, showing significantly improved repeatability and accuracy than those from conventional microfluidic network-based gradient generators. The influence of this improved repeatability and accuracy in generating concentration specified mixtures on obtaining more reliable and repeatable biological data sets were studied.

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The survival for high-grade glioma patients is poor and the treatment may cause severe side effects. A common obstacle in the treatment is chemoresistance. To improve the quality of life and prolong survival for these patients prognostic biomarkers and new approaches for chemotherapy are needed. To this end, a strategy to evade chemoresistance was evaluated by combining chemotherapeutic drugs with agents inhibiting resistance mechanisms identified by a bioinformatic analysis (paper I). The prognostic value of 13 different proteins was analyzed in this thesis (papers II-IV). Two of them, p38 mitogen-activated protein kinase (MAPK) and protein tyrosine phosphatase non-receptor type 6 (PTPN6, also known as SHP1) were analyzed for their potential as targets in combination chemotherapy (in paper III and IV, respectively).   We found that: PTPN6 expression and methylation status may be important for survival of anaplastic glioma patients, p38 MAPK phosphorylation may be a potential negative prognostic biomarker for high-grade glioma patients and FGF2 expression may be a potential negative prognostic biomarker for proneural glioma patients. PTPN6 may be a useful target for combination chemotherapy with cisplatin, melphalan or bortezomib in high-grade gliomas. The following drug combinations; camptothecin combined with an EGFR or RAC1 inhibitor, imatinib combined with a Notch or RAC1 inhibitor, temozolomide combined with an EGFR or FAK inhibitor and vandetanib combined with a p38 MAPK inhibitor may be useful combination chemotherapy for high-grade gliomas.

Combining chemotherapeutics to treat malignant tumors has been shown to be effectivein preventing drug resistance, tumor recurrence, and reducing tumor size. We modeledcombination drug therapy in PC-3 human prostate cancer cells using mixture design responsesurface methodology (MDRSM), a statistical technique designed to optimize compositions thatwe applied in a novel manner to design combinations of chemotherapeutics. Conventionalchemotherapeutics (mitoxantrone, cabazitaxel, and docetaxel) and natural bioactive compounds(resveratrol, piperlongumine, and flavopiridol) were used in twelve different combinationscontaining three drugs at varying concentrations. Cell viability and cell cycle data werecollected and used to plot response surfaces in MDRSM that identified the most effectiveconcentrations of each drug in combination. MDRSM allows for extrapolation of data fromthree or more compounds in variable ratio combinations, unlike the Chou-Talalay method.MDRSM combinations were compared with combination index data from the Chou-Talalaymethod and were found to coincide. We propose MDRSM as an effective tool in devisingcombination treatments that can improve treatment effectiveness, and increase treatmentpersonalization because MDRSM measures effectiveness rather than synergism, potentiation orantagonism.

Objective: Epithelioid sarcoma (ES) presents unique clinical features in comparison to other sarcoma subtypes. Data regarding the benefits of chemotherapy are very limited. Combination regimens using gemcitabine and docetaxel (Gem/Doce) have proven to be effective, especially in uterine and nonuterine leiomyosarcoma. Yet, there is no available data on the efficacy of Gem/Doce in ES. Methods: A retrospective analysis of the three participating institutions was performed. Twenty-eight patients with an ES diagnosis presented at one of the participating institutions between 1989 and 2012. Of this group, 17 patients received chemotherapy. Results: Patients’ median overall survival (OS) after the beginning of palliative chemotherapy was 21 months, and the 1-year OS was 87%. Twelve patients received Gem/Doce with a clinical benefit rate of 83%. The median progression-free survival (PFS) was 8 months for all patients receiving Gem/Doce. The best response was complete remission in 1 patient and partial remission in 6 patients. All 6 patients receiving Gem/Doce as a first-line treatment showed measurable responses with a median PFS of 9 months. Conclusions: In this retrospective study, Gem/Doce was an effective chemotherapeutic regimen for ES. Prospective studies are needed to better assess the effects of this combination drug therapy.

<p>Despite advancements in therapies, such as surgery, irradiation (IR) and chemotherapy, outcome for patients suffering from glioblastoma (GBM) remains fatal; the median survival time is only about 15 months. Even with novel therapeutic targets, networks and signaling pathways being discovered, monotherapy with such agents targeting such pathways has been disappointing in clinical trials. Poor prognosis for GBM can be attributed to several factors, including failure of drugs to cross the blood-brain-barrier (BBB), tumor heterogeneity, invasiveness, and angiogenesis. Development of tumor resistance, particularly to temozolomide (TMZ) and IR, creates a substantial clinical challenge.</p><p> </p><p>The primary focus of the work described herein was to develop a modeling and simulation approach that could be applied to rationally develop novel combination therapies and dose regimens that mitigate resistance development. Specifically, TMZ was combined with small molecule inhibitors that are either currently in clinical trials or are approved drugs for other cancer types, and which target the disease at various resistance signaling pathways that are induced in response to TMZ monotherapy. To accomplish this objective, an integrated PKPD modeling approach was used. A PK model for each drug was first defined. PK models were subsequently linked to a PD model description of tumor growth dynamics in the presence of a single drug or combinations of drugs. A key outcome of these combined PKPD models was tumor static concentration (TSC) curves of TMZ in combination with small molecule inhibitors that identify combination drug exposures predicted to arrest tumor growth. This approach was applied to TMZ in combination with abemaciclib (a dual CDK4/6 small molecule inhibitor) based on data from a published study evaluating abemaciclib (ACB) efficacy in combination with TMZ in a U87 GBM xenograft model. TSC was also constructed for TMZ in combination with RG7388 (MDM2 inhibitor) based on the data from an in-vivo study that evaluated effects on tumor growth suppression of these small molecule inhibitors in combination with TMZ in GBM 10 patient derived xenografts.</p><p>In GBM 43 mouse xenografts, emergence of resistance to TMZ treatment was identified. Thus, a resistance integrated PKPD model was developed to predict tumor growth kinetics after treatment with TMZ in GBM 43 tumors. Population PK models in immune deficient NOD.Cg-<em>Prkdc^scid Il2rg^tm1Wjl</em>/SzJ (NSG) mice for TMZ and small molecule inhibitors (GDC0068/RG7112) were developed based on a combination of data obtained from an in-vivo study and published sources. Subsequently, PK models were linked to tumor volume data obtained from GBM 43 subcutaneous xenografts. Model parameters quantifying tumor volume dynamics were precisely estimated (coefficient of variation < 40%) compared to a base tumor growth inhibition model in GBM 43 that did not incorporate resistance development. Graphical diagnostics of the resistance incorporated PKPD tumor growth inhibition model demonstrated a superior fit compared to the base model, and accurately captured the emergence of resistance to the TMZ monotherapy treatment observed in the GBM 43 patient derived xenograft model.</p>

<p>Adrenocortical cancer (ACC) is a rare disease that is often difficult to diagnose, and therefore often presents at an advanced stage. Various cytotoxic treatments have been tried with little success. Evaluation of new diagnostic methods and improvement of medical therapies are therefore crucial.</p><p>The diagnostic potential of 11C-metomidate positron emission tomography (PET) was evaluated in eleven ACC patients. PET visualized all viable tumors with high tracer uptake, including two lesions that CT failed to detect. Necrotic or fibrotic tumors were PET negative. Medication with adrenal steroid inhibitors and chemotherapy may decrease the tracer uptake.</p><p>We performed a phase-II study with streptozocin and o,p’-DDD (SO) combination therapy in 40 ACC patients. The SO therapy was found to have impact on the disease-free interval (P = 0.02) as well as on survival (P = 0.01) in patients who received adjuvant therapy after curative resection. Complete or partial response was obtained in 36.4% of patients with measurable disease.</p><p>The efficacy and tolerability of combination therapy with vincristine, cisplatin, teniposide, and cyclophosphamide (OPEC) were evaluated in eleven patients with advanced ACC after failure of SO therapy. The median survival was 21 months from the start of treatment. A partial response was achieved in two patients. Adverse events were mainly restricted to grade 1-2 toxicities, and grade 3 toxicities were observed in only two cycles.</p><p>We tested 21 ACC tumors to analyze the expression of receptor tyrosine kinases and 15 ACC for mutation analysis of c-Kit exon 11, which can be targeted by antagonists such as imatinib. All ACCs expressed one or more kinases: c-Kit in 19 ACC and phospho-c-Kit in three while 14 ACCs expressed PDGFR-beta, suggesting the potential usefulness of tyrosine kinase inhibitors. No c-Kit mutations were detected in exon 11. Further evaluation of other mutations targeted by this drug may be needed.</p>

Adrenocortical cancer (ACC) is a rare disease that is often difficult to diagnose, and therefore often presents at an advanced stage. Various cytotoxic treatments have been tried with little success. Evaluation of new diagnostic methods and improvement of medical therapies are therefore crucial. The diagnostic potential of 11C-metomidate positron emission tomography (PET) was evaluated in eleven ACC patients. PET visualized all viable tumors with high tracer uptake, including two lesions that CT failed to detect. Necrotic or fibrotic tumors were PET negative. Medication with adrenal steroid inhibitors and chemotherapy may decrease the tracer uptake. We performed a phase-II study with streptozocin and o,p’-DDD (SO) combination therapy in 40 ACC patients. The SO therapy was found to have impact on the disease-free interval (P = 0.02) as well as on survival (P = 0.01) in patients who received adjuvant therapy after curative resection. Complete or partial response was obtained in 36.4% of patients with measurable disease. The efficacy and tolerability of combination therapy with vincristine, cisplatin, teniposide, and cyclophosphamide (OPEC) were evaluated in eleven patients with advanced ACC after failure of SO therapy. The median survival was 21 months from the start of treatment. A partial response was achieved in two patients. Adverse events were mainly restricted to grade 1-2 toxicities, and grade 3 toxicities were observed in only two cycles. We tested 21 ACC tumors to analyze the expression of receptor tyrosine kinases and 15 ACC for mutation analysis of c-Kit exon 11, which can be targeted by antagonists such as imatinib. All ACCs expressed one or more kinases: c-Kit in 19 ACC and phospho-c-Kit in three while 14 ACCs expressed PDGFR-beta, suggesting the potential usefulness of tyrosine kinase inhibitors. No c-Kit mutations were detected in exon 11. Further evaluation of other mutations targeted by this drug may be needed.