The supporting information file contains figures with experimental data such as tandem mass spectrometry mass spectra, 2D ion images, representative mass spectra of cancer and normal tissues, and mass spectra of standard compounds. Tables are also included which present identification of molecular markers, and predictive accuracy results for the molecular models.

Figure S1 shows results od cell viability assays, PRKRA expressions and time course experiments. Figure S2 shows results of heatmap for gene expressions and IPA. Figure S3 shows results of cell viability assay, in vivo experiment. Figure S4 shows the results of experiments for PACT-Dicer or PACT- miR 515-3p interaction. Figure S5 shows the results of experiments for miR-515-3p-AXL interaction.

Supplementary Figure 1 Functional genomic analysis of HeyA8 and SKOV3ip ovarian cancer cells 4 h after exposure to norepinephrine and compared to control cells. Supplementary Figure 2 A, Western blot analysis of ADRB1, ADRB2, ADRB3, and DUSP1 expression in 10 epithelial ovarian cancer cell lines and one breast cancer cell line (MDA-231), using non-transformed ovarian epithelium cells (HIO-180) as control. B, DUSP1 mRNA levels of cells exposed to norepinephrine 10 μM for 4 h. Supplementary Figure 3 A, DUSP1 silencing. Two commercially available siRNAs that directly target the DUSP1 gene were transfected to norepinephrine-treated HeyA8 cells. B, DUSP1 overexpression. SKOV3ip1 cells were transiently transfected with a DUSP1-myc/DDK-tagged expression vector (Origene). Supplementary Figure 4 SKOV3ip1 cells were treated with paclitaxel alone (10nM) or in combination with norepinephrine (NE; 10μM) or vascular endothelial growth factor (VEGF; 10ng/ml or 50ng/ml). NE or VEGF was administered 30 minutes prior to paclitaxel exposure.

Fig. S1. Sustained adrenergic signaling increases nerve counts in tumors. Fig. S2. Characterization of tumoral innervation. Fig. S3. NE induces BDNF expression. Fig. S4. NE-induced BDNF expression is mediated by ADRB3/Epac/Jnk. Fig. S5. BDNF increases nerve counts. Fig. S6. Adrenergic-mediated mTrkB activation leads to increased in vivo tumor nodule counts. Table S1. Alteration in pathways associated with neuronal growth and function after NE treatment (HeyA8 and SKOV3ip1 cells). Table S2. Association of Clinicopathologic variables with BDNF protein expression. Table S3. Association of Clinicopathologic variables with Nerve Counts.

Abstract For mucinous ovarian cancer (MOC), standard platinum-based therapy is largely ineffective. We sought to identify possible mechanisms of oxaliplatin resistance of MOC and develop strategies to overcome this resistance. A kinome-based siRNA library screen was carried out using human MOC cells to identify novel targets to enhance the efficacy of chemotherapy. In vitro and in vivo validations of antitumor effects were performed using mouse MOC models. Specifically, the role of PRKRA/PACT in oxaliplatin resistance was interrogated. We focused on PRKRA, a known activator of PKR kinase, and its encoded protein PACT because it was one of the five most significantly downregulated genes in the siRNA screen. In orthotopic mouse models of MOC, we observed a significant antitumor effect of PRKRA siRNA plus oxaliplatin. In addition, expression of miR-515-3p was regulated by PACT–Dicer interaction, and miR-515-3p increased the sensitivity of MOC to oxaliplatin. Mechanistically, miR-515-3p regulated chemosensitivity, in part, by targeting AXL. The PRKRA/PACT axis represents an important therapeutic target in MOC to enhance sensitivity to oxaliplatin.

Table S1 shows antibody concentrations. Table S2 shows siRNA sequences. Table S3 shows qPCR primers sequences. Table S5 shows IC50 values of oxaliplatin.

PDF - 312K, Storage stability of PLGA-PRINT nanoparticles.

PDF file - 2766KB, Supplementary methods and reports describing all data analyses. Supplementary Table 1. Probesets (N=47) and associated genes (N=38) having consistent differences in expression between residual disease (RD) and No-RD patients in the TCGA and Tothill data sets at a 10 percent false discovery rate in each data set. Figure 1. Bivariate plot of two-sample RD-No RD t-values for TCGA and Tothill. The vast majority of the probesets selected show higher expression in RD cases. Lumican (LUM) is the strongest overall. Figure 2. Zoom on the upper quadrant of the bivariate plot of two-sample RD-No RD t-values for TCGA and Tothill, to show the names more clearly. Figure 3. Heatmap of the TCGA Samples using just the 8 probesets passing the 5 percent FDR filter for both TCGA and Tothill. Figure 4. Heatmap of the Tothill Samples using just the 8 probesets passing the 5 percent FDR filter for both TCGA and Tothill. Figure 5. Heatmap of the TCGA Samples using the 47 probesets passing the 10 percent FDR filter for both TCGA and Tothill. Figure 6. Heatmap of the Tothill Samples using the 47 probesets passing the 10 percent FDR filter for both TCGA and Tothill. Figure 7. Correlations in the TCGA data between the 47 probesets selected by 10 percent FDR cutoffs. Figure 8. Correlations in the Tothill data between the 47 probesets selected by 10 percent FDR cutoffs. Figure 9. Dot and density plots for lumican (LUM) in TCGA and Tothill. Figure 10. Dot and density plots for decorin (DCN) in TCGA and Tothill. Figure 11. Dot and density plots for GADD45B in TCGA and Tothill. Figure 12. Dot and density plots for FABP4 in TCGA and Tothill. Figure 13. Dot and density plots for ADH1B in TCGA and Tothill. Figure 14. Dot and density plots for ADIPOQ in TCGA and Tothill.

Supplementary figure 1 provides a schematic of DOPC:siRNA nanoliposomal preparation, and Supplementary figure 2 shows tumor volumetric measurements of the A549 orthotopic lung cancer therapeutic experiment described in the main figure 2.

CARS imaging of ex vivo ovarian cancer samples

Supplementary Figures S1-5, Tables S1-5. Figure S1 The Cytotoxic Effect of KPT-185 is Tumor Suppressor-independent. Figure S2 Combination Index of KPT-185 with Chemotherapeutic Agents. Figure S3 1D Gel Analysis of Cytoplasmic Protein. Figure S4 Effects of Selinexor (KPT-330) in an Ovarian Cancer Mouse Model. Figure S5 The Efficacy of Selinexor (KPT-330) on Tumor Regression and Metastasis Table S1 p53 status and IC50 concentration of KPT-185 after 72 hours of incubation in human cancer cell lines Table S2 Combination index (CI) of KPT-185 with cytotoxic agents Table S3 Proteins showing altered mitochondrial localization after treatment with KPT-185 Table S4 1D Proteomic analysis of cytoplasmic proteins immunoprecipitated with eIF5A Table S5 siRNA Sequences

PDF - 2261K, Characterization and efficacy of Chitosan nanoparticles.

CARS imaging of ex vivo ovarian cancer samples

Current antiangiogenesis therapy relies on inhibiting newly developed immature tumor blood vessels and starving tumor cells. This strategy has shown transient and modest efficacy. Here, we report a better approach to target cancer-associated endothelial cells (ECs), reverse permeability and leakiness of tumor blood vessels, and improve delivery of chemotherapeutic agents to the tumor. First, we identified deregulated microRNAs (miRs) from patient-derived cancer-associated ECs. Silencing these miRs led to decreased vascular permeability and increased maturation of blood vessels. Next, we screened a thioaptamer (TA) library to identify TAs selective for tumor-associated ECs. An annexin A2-targeted TA was identified and used for delivery of miR106b-5p and miR30c-5p inhibitors, resulting in vascular maturation and antitumor effects without inducing hypoxia. These findings could have implications for improving vascular-targeted therapy.

Noncoding RNAs (ncRNAs) have long been known to play important roles in gene regulation and have attracted attention for their use in medicine. In particular, the utility of ncRNAs for cancer-targeted therapies is being tested in a large number of preclinical and clinical studies. Here, we describe the role of specific ncRNAs, including microRNAs (miRNAs), long noncoding RNAs, small interfering RNAs (siRNAs), PIWI-interacting RNAs, small nucleolar RNAs (snoRNAs), and sno-derived RNAs. Although a majority of contemporary literature on the topic of ncRNAs in cancer is on miRNAs and siRNAs, the variety of other types are also likely to play major roles in cancer. Many recent studies on the other types of ncRNAs have shown promise in their potential application for treating cancer. The role that these ncRNAs play in various types of cancers and how they can be manipulated to benefit and optimize anticancer drug development will be discussed in this chapter.

The standard treatment for high-grade serous ovarian cancer is primary debulking surgery followed by chemotherapy. The extent of metastasis and invasive potential of lesions can influence the outcome of these primary surgeries. Here, we explored the underlying mechanisms that could increase metastatic potential in ovarian cancer. We discovered that FABP4 (fatty acid binding protein) can substantially increase the metastatic potential of cancer cells. We also found that miR-409-3p regulates FABP4 in ovarian cancer cells and that hypoxia decreases miR-409-3p levels. Treatment with DOPC nanoliposomes containing either miR-409-3p mimic or FABP4 siRNA inhibited tumor progression in mouse models. With RPPA and metabolite arrays, we found that FABP4 regulates pathways associated with metastasis and affects metabolic pathways in ovarian cancer cells. Collectively, these findings demonstrate that FABP4 is functionally responsible for aggressive patterns of disease that likely contribute to poor prognosis in ovarian cancer.

Primary debulking surgery followed by adjuvant chemotherapy is the standard treatment for ovarian cancer. Residual disease after primary surgery is associated with poor patient outcome. Previously, we discovered ADH1B to be a molecular biomarker of residual disease. In the current study, we investigated the functional role of ADH1B in promoting ovarian cancer cell invasiveness and contributing to residual disease. We discovered that ADH1B overexpression leads to a more infiltrative cancer cell phenotype, promotes metastasis, increases the adhesion of cancer cells to mesothelial cells, and increases extracellular matrix degradation. Live cell imaging revealed that ADH1B-overexpressing cancer cells efficiently cleared the mesothelial cell layer compared to control cells. Moreover, gene array analysis revealed that ADH1B affects several pathways related to the migration and invasion of cancer cells. We also discovered that hypoxia increases ADH1B expression in ovarian cancer cells. Collectively, these findings indicate that ADH1B plays an important role in the pathways that promote ovarian cancer cell infiltration and may increase the likelihood of residual disease following surgery.

TPS77 Background: Adoptive cellular therapy (ACT) has dramatically changed the landscape of immunotherapy; however, only a small proportion of solid tumor patients have benefited from these advances due to i) heterogeneity of tumor antigen expression, ii) tumor escape (e.g. only one target is addressed), or iii) off-target toxicities (e.g. expression of targets on normal tissues). The ACTolog concept, utilizing antigen specific T cells (IMA101) against targets identified by the Immatics’ proprietary XPRESIDENT technology, is intended to overcome these limitations by addressing multiple novel relevant tumor antigens per patient. ACTolog is a personalized, multi-targeted ACT approach in which autologous T-cell products are manufactured against the most relevant tumor target peptides for individual patients whose tumors are positive against a predefined target warehouse. Methods: This study is an open-label first-in-human phase I trial in patients with relapsed or refractory solid tumors expressing at least one target from a warehouse of 8 cancer targets. Key eligibility criteria include: HLA-A*02:01 phenotype, qPCR expression of warehouse target(s), prior established lines of therapy, RECIST v1.1 measurable lesions, and ECOG performance status 0 or 1. At baseline, patients will undergo leukapheresis to collect mononuclear cells for manufacturing of IMA101 cells. Patients will receive their last line of established therapy during the production phase of IMA101. IMA101 will be infused after a pre-conditioning regimen (lymphodepletion) followed by LD-IL2. The primary objective is to assess safety and tolerability of IMA101. Secondary endpoints include overall response rate (RECIST and irRC), PFS and OS. The translational objective is to assess the in vivo persistence and ex vivo functionality of transferred T cells in addition to evaluation of target expression in tumors. Enrollment to the study is currently ongoing. Clinical trial information: NCT02876510 .

Adrenergic signaling is known to promote tumor growth and metastasis, but the effects on tumor stroma are not well understood. An unbiased bioinformatics approach analyzing tumor samples from patients with known biobehavioral profiles identified a prominent stromal signature associated with cancer-associated fibroblasts (CAFs) in those with a high biobehavioral risk profile (high Center for Epidemiologic Studies Depression Scale [CES-D] score and low social support). In several models of epithelial ovarian cancer, daily restraint stress resulted in significantly increased CAF activation and was abrogated by a nonspecific β-blocker. Adrenergic signaling-induced CAFs had significantly higher levels of collagen and extracellular matrix components than control tumors. Using a systems-based approach, we found INHBA production by cancer cells to induce CAFs. Ablating inhibin β A decreased CAF phenotype both in vitro and in vivo. In preclinical models of breast and colon cancers, there were increased CAFs and collagens following daily restraint stress. In an independent data set of renal cell carcinoma patients, there was an association between high depression (CES-D) scores and elevated expression of ACTA2, collagens, and inhibin β A. Collectively, our findings implicate adrenergic influences on tumor stroma as important drivers of CAFs and establish inhibin β A as an important regulator of the CAF phenotype in ovarian cancer.

Angiogenesis inhibitors are important for cancer therapy, but clinically approved anti-angiogenic agents have shown only modest efficacy and can compromise wound healing. This necessitates the development of novel anti-angiogenesis therapies. Here, we show significantly increased EGFL6 expression in tumor versus wound or normal endothelial cells. Using a series of in vitro and in vivo studies with orthotopic and genetically engineered mouse models, we demonstrate the mechanisms by which EGFL6 stimulates tumor angiogenesis. In contrast to its antagonistic effects on tumor angiogenesis, EGFL6 blockage did not affect normal wound healing. These findings have significant implications for development of anti-angiogenesis therapies.