US20190160034A1 - Use of ape1/ref-1 inhibitors in combination therapies for treatment of cancer - Google Patents

Use of ape1/ref-1 inhibitors in combination therapies for treatment of cancer Download PDF

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US20190160034A1
US20190160034A1 US16/092,812 US201816092812A US2019160034A1 US 20190160034 A1 US20190160034 A1 US 20190160034A1 US 201816092812 A US201816092812 A US 201816092812A US 2019160034 A1 US2019160034 A1 US 2019160034A1
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ref
ape1
inhibitor
apx3330
cells
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Mark R. Kelley
Melissa L. Fishel
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Indiana University Research and Technology Corp
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Definitions

  • the present disclosure relates generally to the use of an Apurinic/Apyrimidinic Endonuclease/reduction-oxidation (redox) Factor-1 (APE1/Ref-1) inhibitor in a combination therapy to treat various cancers.
  • APE1/Ref-1 Apurinic/Apyrimidinic Endonuclease/reduction-oxidation Factor-1
  • the disclosure relates to the use of APX3330 (formerly known as E3330), a highly selective inhibitor of APE1/Ref-I's redox activity (also referred to herein as “Ref-1”), in a combination therapy to treat cancers such as prostate cancer, colon cancer, ovarian cancer, bladder cancer, non-small cell lung carcinoma, malignant peripheral nerve sheath tumors, leukemia, as well as other angiogenesis-mediated diseases (e.g., retinal diseases, cardiovascular diseases).
  • APX3330 originally known as E3330
  • Ref-1 a highly selective inhibitor of APE1/Ref-I's redox
  • APE1/Ref-1 Apurinic/Apyrimidinic Endonuclease/reduction-oxidation (Redox) Factor-1 (APE1/Ref-1) was originally identified as an endonuclease that plays a key role in the Base Excision Repair (BER) pathway's repair of oxidative and alkylating damage. Later, APE1/Ref-1 was recognized as a redox signaling protein that modulates the activity of certain transcription factors. Since then, additional functions of APE1/Ref-1 have been uncovered. APE1/Ref-1's duality and pivotal positions in repair and redox activities make it a unique target for therapeutic modulation.
  • BER Base Excision Repair
  • APE1/Ref-1 endonuclease activity is vital to the DNA damage response in all cells, making APE1/Ref-1 a crucial factor in cellular function and survival.
  • the repair function has been conserved from E. coli to humans; however, the redox signaling function is observed only in mammals.
  • APE1/Ref-1 redox signaling affects numerous transcription factors including STAT3, HIF-1 ⁇ , NF- ⁇ B, AP-1, p53, and a few others.
  • APE1/Ref-1 redox signaling is a highly regulated process that reduces oxidized cysteine residues in specific transcription factors as part of their transactivation ( FIG. 1 ).
  • APE1/Ref-1 expression is increased in many tumor types, and that change is associated with increased growth, migration, and drug resistance in tumor cells as well as decreased patient survival.
  • APE1/Ref-1 is seen as a critical node in tumor signaling ( FIG. 2 ), and thus, is a prime target for anticancer therapy
  • teasing apart APE1/Ref-1's activities to create a specific inhibitor that targets only its endonuclease or redox function is challenging.
  • a number of compounds isolated from natural sources have been proposed as Ref-1 redox signaling inhibitors, but none have been shown to directly or specifically inhibit Ref-1 redox signaling.
  • An example of these natural compounds, resveratrol is typical of the other compounds; it's in vivo efficacy is sporadic at best due to widely varying bioavailability and low molecular specificity.
  • Ref-1 redox inhibitor Curcumin
  • curcumin Another presumed natural Ref-1 redox inhibitor, curcumin, has been established as a promiscuous compound, interacting with a variety of molecules to give false-positive results in numerous biological assays. Thus, these are not specific or viable APE1/Ref-1 redox inhibitors.
  • APX3330 (formerly called E3330) has been identified as a specific APE1/Ref-1 redox inhibitor.
  • APX3330 has been extensively characterized as a direct, highly selective inhibitor of Ref-1 redox activity that does not affect the protein's endonuclease activity ( FIG. 6 ).
  • Treatment with APX3330 has shown tumor growth and progression, with limited toxicity, in both in vitro and in vivo models.
  • the present disclosure relates generally to the use of selective APE1/Ref-1 inhibitors, APX3330, and compounds derived therefrom (e.g., APX2009 and APX2014), in a combination therapy to treat various cancers.
  • the combination therapies are found to treat cancers such as prostate cancer, colon cancer, ovarian cancer, non-small cell lung carcinoma, malignant peripheral nerve sheath tumors, leukemia, as well as other angiogenesis-mediated diseases (e.g., retinal diseases, cardiovascular diseases).
  • the present disclosure is directed to a combination therapy comprising an Apurinic/Apyrimidinic Endonuclease/reduction-oxidation (redox) Factor-1 (APE1/Ref-1) inhibitor, wherein the APE1/Ref-1 inhibitor inhibits the redox function of APE1/Ref-1 and a second therapeutic agent.
  • APE1/Ref-1 Apurinic/Apyrimidinic Endonuclease/reduction-oxidation (redox) Factor-1
  • APE1/Ref-1 inhibitor inhibits the redox function of APE1/Ref-1 and a second therapeutic agent.
  • the present disclosure is directed to use of a combination therapy for the treatment of cancer, the combination therapy comprising an Apurinic/Apyrimidinic Endonuclease/reduction-oxidation (redox) Factor-1 (APE1/Ref-1) inhibitor, wherein the APE1/Ref-1 inhibitor inhibits the redox function of APE1/Ref-1 and a second therapeutic agent.
  • APE1/Ref-1 Apurinic/Apyrimidinic Endonuclease/reduction-oxidation (redox) Factor-1
  • APE1/Ref-1 inhibitor inhibits the redox function of APE1/Ref-1 and a second therapeutic agent.
  • the present disclosure is directed to use of a combination therapy for the treatment of retinal disease in a subject in need thereof, the combination therapy comprising an Apurinic/Apyrimidinic Endonuclease/reduction-oxidation (redox) Factor-1 (APE1/Ref-1) inhibitor, wherein the APE1/Ref-1 inhibitor inhibits the endonuclease or redox function of APE1/Ref-1 and a second therapeutic agent.
  • APE1/Ref-1 Apurinic/Apyrimidinic Endonuclease/reduction-oxidation (redox) Factor-1
  • the present disclosure is directed to use of a combination therapy for the treatment of a disease selected from the group consisting of a cardiovascular disease, bacterial infection, gastric inflammatory disorder, and neurodegenerative disease.
  • FIG. 1 depicts the dual functions of APE1/Ref-1.
  • APE1/Ref-1 is a multifunctional protein involved in redox signaling and DNA repair.
  • the redox signaling function (Ref-1) is responsible for reduction of oxidized cysteine residues in certain transcription factors (TF's), leading to increased transcriptional activity and upregulation of genes involved in cell growth, inflammation, angiogenesis, and other cellular functions.
  • the DNA repair function (APE1) is responsible for the endonuclease activity in base excision repair, cutting the phosphodiester backbone of DNA at abasic sites created by glycosylases. These cuts allow the abasic sites to be replaced with appropriate nucleotide bases, completing the DNA base excision repair process.
  • FIG. 2 depicts Ref-1 signaling as a node in tumor cells and potential inhibitors in related pathways.
  • Ref-1 redox signaling promotes the transactivation of transcription factors such as STAT3, HIF-1 ⁇ , and NF- ⁇ B.
  • Inhibiting Ref-1 with APX3330 decreases the expression of downstream genes, leading to tumor cell growth arrest and/or death.
  • other methods for inhibiting the signaling pathways affected by Ref-1, as well as the enzymes that are upregulated by these pathways have been shown to enhance the cytotoxic and cytostatic effects of Ref-1 inhibition.
  • FIGS. 3A & 3B depict that dual-targeting of Ref-1 and Jak/STAT signaling inhibits PDAC tumor growth in a 3D co-culture model.
  • 3B depicts the confirmation of inhibition of STAT3 activation via immunoblotting for pSTAT3 Y705 residue after 4 hours of Ruxolitinib treatment (12.5 uM) in the 3D assay 8-10 days post plating.
  • Total STAT3 protein is provided as a loading control and reference for the levels of STAT3 in both cell types. Representative western blot is shown from an n of 3.
  • FIG. 4 depicts the effects of APE1/Ref-1 in human diseases due to its multi-functional nature
  • APE1/Ref-1 impacts a wide range of human diseases.
  • Altered expression of Ref-1 affects its regulation of multiple transcriptional factors, leading to various cancers, retinal, cardiovascular, gastric and neurodegenerative diseases.
  • modified APE1 DNA repair function affects progression of different cancers and neurodegenerative diseases.
  • FIG. 5 depicts that anticancer treatments inducing oxidative DNA damage alters sensory neuronal function.
  • agents include cisplatin, oxaliplatin, ionizing radiation as well as other drugs.
  • ROS reactive oxygen species
  • Pt platinum adduct
  • APE apurinic/apyrimidinic endonuclease.
  • FIGS. 6A-6E depict the differential role of APE1 Redox Inhibition in Sensory Neurons vs. Tumor Cells.
  • Ref-1 redox inhibition has multiple downstream effects on tumor growth, survival, migration and tumor inflammation.
  • sensory neuron cells such as DRG neurons
  • the addition of APX3330 does not have a negative effect on the cells and promotes survival and functional protection through enhancement of Ref-1 DNA repair activity against oxidative DNA damaging agents (e.g. cisplatin, oxaliplatin) that invoked the DNA BER pathway ( FIG. 6A ).
  • oxidative DNA damaging agents e.g. cisplatin, oxaliplatin
  • FIG. 6B depicts that the treatment paradigm for investigation of the effects of cisplatin and APX3330 on DNA damage within DRG.
  • Neuroblastoma cells were implanted subcutaneously into the right flanks of 6-wk old male NSG mice and allowed to proliferate until tumor volumes ⁇ 150 mm 3 . Mice were then randomized for treatment with cisplatin ⁇ APX3330 treatment.
  • Cisplatin and APX3330 were administered concurrently for 3 weeks (Day 0-Day 17) and endpoints of neuronal toxicity were assessed within the DRG of mice at several time points following the last dose of cisplatin.
  • FIG. 6C are representative blots demonstrating pH2A.X immunoreactivity at D24 and D31.
  • 6D & 6E depict quantification of pH2A.X immunoreactivity.
  • An asterisk indicates statistical significance between D18 and D24 as determined by a one-way ANOVA with Tukey's posttest with p ⁇ 0.05.
  • a cross indicates statistical significance between Veh/Veh group and the Veh/C is group, as determined by a two-way ANOVA with Bonferroni's posttest with p ⁇ 0.05.
  • FIG. 7 depicts that APX3330 has broad potential in a variety of cancers. Supportive pre-clinical data exists for APX3330 in combination with each drug listed in the diagram (second column of boxes from the right) and for each indication (boxes at far right). *In addition to anti-tumor activity, APX3330 provides neuroprotection when administered with agents causing oxidative damage to neurons.
  • FIGS. 8A-8C depict APE1 expression and batch effects in cells following siRNA knockdown.
  • FIG. 8A is a representative Western Blot and densitometry analysis of Pa03C cells following APE1 knockdown using 20 nM siRNA. Vinculin is used as a loading control. siAPE1 samples had 10% APE1 levels in comparison to the SCR control sample.
  • FIG. 8B depicts Principal Components Analysis of Uncorrected Gene Expression Data.
  • FIG. 8C depicts Principal Components Analysis of Corrected Gene Expression Data. Following corrections for batch effects using cell cycle-annotated genes, the SCR1 and SCR2 groups come together along the x-axis to form a single SCR group.
  • FIGS. 9A-9C depict the results of scRNA-seq and comparison of analyses.
  • FIG. 9A is a Violin Plot illustrating the differences in APE1 RNA expression counts per million (CPM) reads in the SCR, Detectable siAPE1 and Undetectable siAPE1 samples.
  • FIG. 9B depicts Mean Expression and Fold Change Plot using SCR and siAPE1 cells as the two groups in the analysis.
  • FIG. 9C depicts Mean Expression and Fold Change Plot using SCR, detectable siAPE1 and undetectable siAPE1 cells in the analysis. Note that while the analysis uses three separate groups, this plot uses SCR and siAPE1 for calculation of the Mean Expression and Fold Change due to the limitations of the graph.
  • FIGS. 10A-10G depict the identification of differentially expressed genes in relation of APE1 levels.
  • FIG. 10A is a venn diagram showing the three analyses performed on the scRNA-Seq data and the overlapping genes between them. Six genes were significantly changed in all three analyses, ( FIG. 10B ) TMEM45A, ( FIG. 10C ) TMEM126A, ( FIG. 10D ) TMEM154, ( FIG. 10E ) COMMD7, ( FIG. 10F ) ISYNA1 and ( FIG. 10G ) TNFAIP2. These genes show increased changes in expression as APE1 levels are reduced further from SCR to detectable (but reduced) siAPE1 to undetectable siAPE1.
  • FIGS. 11A-11C depict overlapping overrepresented canonical pathways.
  • FIG. 11A depicts the 20 most significantly overrepresented pathways following IPA analysis on the SCR/detectable siAPE1/undetectable siAPE1 results.
  • the x-axis shows the number of genes that were differentially expressed and in the overrepresented pathways.
  • the percentages next to the pathway labels on the y-axis show the percentage of genes in the pathway which are differentially expressed between SCR and siAPE1 cells.
  • FIG. 11B depicts changes in the EIF2 pathway.
  • the EIF2 pathway was the pathway most affected by APE1 knockdown with 70 DEGs.
  • FIG. 11C is a heatmap showing changes in expression of DEGs per cell involved in the EIF2 pathway. Box showing colors corresponding to normalized changed in expression shown.
  • FIGS. 12A-12D depict the validation of scRNA-Seq by qRT-PCR in Pa03C cells.
  • FIG. 12A depicts genes chosen for qRT-PCR validation following SCR/siAPE1 validation.
  • FIG. 12B depicts genes statistically significant in all 3 analyses chosen for qRT-PCR validation.
  • FIG. 12C shows the expression of selected genes assessed via qRT-PCR in Pa03C cells. The cells were collected after siRNA knockdown and assessed for a reduction in APE1 protein levels of 80% or greater. Each graph is the result of 3 independent experiments, showing average fold change in siAPE samples compared to SCR+/ ⁇ SD. *p ⁇ 0.05 (ANCOVA model).
  • FIGS. 13A & 13B depict the effects of Ref-1 in combination with Docetaxel or Trametinib to PDAC cells and CAFs.
  • a higher dose of Docetaxel was used in co-culture due to the decreased potency in the presence of CAFs.
  • FIGS. 14A-14C depict 3D spheroid and in vivo combination studies with APX3330 and Gemcitabine (Gem).
  • Low passage patient derived PDAC cells (Pa03C, FIG. 14A ) in co-culture with cancer-associated fibroblasts (CAF19) treated with increasing amounts of Gem in combination with APX3330 (50 ⁇ M).
  • FIG. 14B is a graphical representation: *All Gem+APX330 treatments significantly different from Gem alone in tumor (p ⁇ 0.01).
  • FIG. 14C depicts tumor volume 30 days following treatment.
  • APX3330 25 mg/kg reduces tumor volume in both PaCa-2 and Panc253 patient derived cells in animal models as previously published.
  • FIGS. 15A-15C depict the effect of APX3330 and CPI-613 on the HCT-116 cell line.
  • FIGS. 16A-16D depict the different PDAC cell lines exhibiting varied changes to expression of select genes following siRNA knockdown. Expression of selected genes assessed via qRT-PCR in ( FIG. 16A ) Pa02C cells, ( FIG. 16B ) Panc10.05 cells and ( FIG. 16C ) Panc198 cells. The cells were collected after siRNA knockdown and assessed for a reduction in APE1 protein levels of 80% or greater. Each graph is the result of 3 independent experiments, showing average fold change in siAPE samples compared to SCR+/ ⁇ SD. *p ⁇ 0.05 (ANCOVA model).
  • FIG. 16D is a venn diagram showing the overlapping results of qRT-PCR between the 4 different PDAC cell lines.
  • COMMD7, ITGA1, RAB3D and TNFAIP2 were significantly changed in all 4 cell lines.
  • PPIF and SIPA1 were differentially expressed in Pa03C, Pa02C and Panc10.05 cells.
  • TAPBP was differentially expressed in Pa03C and Panc10.05.
  • PRDX5, ISYNA1, BCRP and NOTCH3 were common between Pa03C and Pa02C (with BCRP and NOTCH3 changing in opposite directions between the cell lines), while CIRBP was only differentially expressed in Pa03Cs.
  • FIG. 18 shows that APX3330 and Napabucasin (BBI-608-STAT3 inhibitor) have synergistic tumor killing in patient-derived 3D spheroid model (Tumor+CAFs) of pancreatic cancer. Concentrations shown are in microMolar; Napa 0.125 uM, APX3330 25 or 35 uM, and APX2009 3.5 uM.
  • FIGS. 19A & 19B show that APX3330 in combination with STAT3i napabucasin in 3D spheroid model (tumor and CAF) had synergistic killing of pancreatic tumor cells.
  • FIGS. 20A & 20B show that APX3330 and APX2009 in combination with STAT3i napabucasin in 3D spheroid model (tumor and CAF) demonstrated synergistic tumor cell killing. Concentrations shown are in microMolar; Napa 0.125 uM, APX3330 25 uM, and APX2009 3.5 uM. **p ⁇ 0.01, ***p ⁇ 0.001.
  • FIGS. 21A & 21B depict dual targeting of Ref-1 and STAT3 results in enhanced killing in genetic PDAC model in vitro ( FIG. 21A ) and in vivo ( FIG. 21B ).
  • FIGS. 22A-22C show that dual-targeting of CA9 and APE1 kills PDAC tumors in a 3D co-culture pancreatic cancer tumor model.
  • FIGS. 23A-23E depict combination therapy with APE1/Ref-1 inhibitors in a PDAC 3D co-culture model.
  • FIG. 23A depicts the combination therapy of APX3330+Obatoclax (Bcl2 antagonist).
  • FIG. 23B depicts the combination therapy of APX3330+Entinostat (HDAC 1 & 3 inhibitor).
  • FIG. 23C depicts the combination therapy of APX3330+Axitinib (TKI inhibitor).
  • FIG. 23D depicts the combination therapy of APX3330+Obatoclax (Bcl2 antagonist).
  • FIG. 23E depicts the combination therapy of APX3330+Entinostat (HDAC 1 & 3 inhibitor).
  • FIGS. 24A-24C depict combination therapy with APE1/Ref-1 inhibitors and CPI-613, a mito targeted TCA cycle inhibitor ( FIG. 24A ) or STAT3 inhibitor, napabucasin ( FIGS. 24B & 24C ), in a PDAC 3D co-culture model.
  • FIG. 25 depicts the effects of ruxolitinib in combination with APX3330 in a 3D model of pancreatic cancer.
  • FIG. 26 depicts the effects of ruxolitinib on the phosphorylation of p-STAT3 (Y705) in the 3D co-culture model of pancreatic cancer. Particularly, the Western blot depicts p-STAT3 (Y705) after 4 hours of Ruxolitinib (12.5 mM).
  • FIG. 27 depicts the effect of the combination treatment of Rux+APX in a flank co-culture model on tumor growth delay.
  • FIGS. 28A & 28B depict that combination treatment did not kill the CAFs in the co-cultured tumors.
  • FIGS. 29A-29G depict the anti-tumor efficacy of APX3330 in combination with oxaliplatin.
  • FIGS. 30A & 30B depict STAT3 inhibitor Napabucasin and Apel redox inhibitor APX2014 drug combination effects in mouse colon cell line MC-38.
  • FIGS. 31A-31E depict PDH and alpha-KDH Metabolic inhibitor CPI-613 and Apel redox inhibitor APX3330 synergistic drug combination effects in human adenocarcinoma colon suspension cell line Colo-201.
  • FIG. 31A depicts single agent effects.
  • FIG. 31B depicts combination therapy effects.
  • FIG. 31C depicts combination EC50 ( ⁇ M).
  • FIG. 31D depicts Chou-Talalay Index of dose combinations.
  • FIG. 31E depicts synergy doses.
  • FIGS. 32A-32E depict PDH and alpha-KDH Metabolic inhibitor CPI-613 and Apel redox inhibitor APX3330 (also referred to herein as E3330) synergistic drug combination effects in human carcinoma colon cell line HCT-116.
  • FIG. 32A depicts single agent effects.
  • FIG. 32B depicts combination therapy effects.
  • FIG. 32C depicts combination EC50 ( ⁇ M).
  • FIG. 32D depicts Chou-Talalay Index of dose combinations.
  • FIG. 32E depicts synergy doses.
  • FIGS. 33A-33E depict PDH and alpha-KDH Metabolic inhibitor CPI-613 and Apel redox inhibitor APX3330 synergistic drug combination effects in human carcinoma colon cell line HCT-116.
  • FIG. 33A depicts single agent effects.
  • FIG. 33B depicts combination therapy effects.
  • FIG. 33C depicts combination EC50 ( ⁇ M).
  • FIG. 33D depicts Chou-Talalay Index of dose combinations.
  • FIG. 33E depicts synergy doses.
  • FIGS. 34A-34E depict PDH and alpha-KDH Metabolic inhibitor CPI-613 and Apel redox inhibitor APX2014 synergistic drug combination effects in human carcinoma colon cell line HCT-116.
  • FIG. 34A depicts single agent effects.
  • FIG. 34B depicts combination therapy effects.
  • FIG. 34C depicts combination EC50 ( ⁇ M).
  • FIG. 34D depicts Chou-Talalay Index of dose combinations.
  • FIG. 34E depicts synergy doses.
  • FIGS. 35A-35E depict GLS1 Metabolic inhibitor CB-839 and Apel redox inhibitor APX3330 synergistic drug combination effects in human carcinoma colon cell line HCT-116.
  • FIG. 35A depicts single agent effects.
  • FIG. 35B depicts combination therapy effects.
  • FIG. 35C depicts combination EC50 ( ⁇ M).
  • FIG. 35D depicts Chou-Talalay Index of dose combinations.
  • FIG. 35E depicts synergy doses.
  • FIGS. 36A & 36B depict the effects of a 3-day treatment of APX2014+/ ⁇ cisplatin on the cisplatin resistant bladder cell line, BLCAb001.
  • FIGS. 37A & 37B depict the effects of a 3-day treatment of APX2014+/ ⁇ cisplatin on the cisplatin resistant bladder cell line, BLCAb002.
  • FIGS. 38A & 38B depict the effects of APX2014+/ ⁇ napabucasin on the bladder cell line, T24.
  • FIGS. 39A & 39B depict the effects of APX2009+/ ⁇ napabucasin on the bladder cell line, T24.
  • FIGS. 40A & 40B depict the effects of APX2014+/ ⁇ napabucasin on the bladder cell line, SCaBER.
  • FIGS. 41A & 41B depict the effects of APX2009+/ ⁇ napabucasin on the bladder cell line, SCaBER.
  • FIGS. 42A-42H depict the importance of the APE1/Ref-1-HIF-1-CA9 signaling axis in PDAC cells.
  • FIG. 42A shows the patient-derived PDAC tumor cell lines 10.05, Pa02C, and Pa03C, as well as the pancreatic CAF cell line CAF19, exposed to 0.2% oxygen for 24 hours. CA9 protein levels were compared via western blot (p ⁇ 0.05 for all cell line differences between normoxia and hypoxia).
  • FIG. 42B shows that LC50 values for SLC-0111 in PDAC cell lines under hypoxic conditions (0.2% O 2 ) are inversely correlated with CA9 induction in each cell line (R2>0.99).
  • FIG. 42A shows the patient-derived PDAC tumor cell lines 10.05, Pa02C, and Pa03C, as well as the pancreatic CAF cell line CAF19, exposed to 0.2% oxygen for 24 hours. CA9 protein levels were compared via western blot (p ⁇ 0.05 for all cell line differences between normoxia and hypoxia).
  • FIGS. 42D-42F show 10.05 cells transfected with the indicated siRNAs and cultured in 3D spheroids. Cells were collected for western blot analysis on D8 to confirm knock-down ( FIG.
  • FIGS. 42G-42H depict 10.05 cells treated with APX3330 and exposed to 0.2% O 2 for 12 hours prior to protein-DNA cross-linking and collection.
  • IPs of HIF1a and a control for non-specific binding were performed using nuclear extracts.
  • qPCR for the HBS-containing region of the CA9 promoter was performed. ( FIG. 42G , **p ⁇ 0.01).
  • FIGS. 43A-43I depict blockade of CA9 via APE1/Ref-1 or CA9 inhibition.
  • FIGS. 43A & 43B show 10.05 cells treated with APX3330, APX2009, APX2014, and the negative analog RN7-58 and exposed to 0.2% O 2 for 24 hours prior to collection and analysis of CA9 mRNA ( FIG. 43A ) and protein ( FIG. 43B ) levels (p ⁇ 0.01 for differences in CA9 mRNA and protein levels at the highest concentration tested of each APE1/Ref-1 inhibitor vs. DMSO).
  • FIG. 43C show 10.05 cells cultured in 3D spheroids for 12 days prior to collection and Western Blot analysis.
  • FIGS. 43D & 43E show 10.05 cells transfected with the indicated siRNAs or treated with the indicated concentrations of APX2009 or APX2014 and exposed to 0.2% O 2 for 48 hours. Changes in intracellular pH were quantified using a pH-sensitive fluorescent dye (pHrodo Red channel, FIG. 43D ), and pH-mediated fluorescence changes were imaged by a blinded third party ( FIG. 43E ).
  • FIGS. 43D & 43E show 10.05 cells transfected with the indicated siRNAs or treated with the indicated concentrations of APX2009 or APX2014 and exposed to 0.2% O 2 for 48 hours. Changes in intracellular pH were quantified using a pH-sensitive fluorescent dye (pHrodo Red channel, FIG. 43D ), and pH-mediated fluorescence changes were imaged by a blinded third party ( FIG. 43E ).
  • FIGS. 43D pH-sensitive fluorescent dye
  • FIGS. 43F-43I show 3D co-cultures with 10.05 ( FIGS. 43F & 43H ) or Pa03C ( FIGS. 43G & 43I ) tumor cells (+CAFs) were treated with increasing concentrations of APX3330, APX2009, and APX2014 (F-G) or SLC-0111 and FC12-531A ( FIGS. 43H & 43I ) for 12 days, and fluorescence intensity was measured.
  • FIGS. 44A-44F depict characterization of 3D cultures and effects of dual-targeting APE1/Ref-1 and CA9.
  • FIGS. 44A-44F depict spheroids consisting of 10.05 or Pa03C cells cultured with CAFs for 12 days and collected for IHC. Slides with sections from these cultures were stained with the indicated antibodies/stains. Antibody stains ( FIGS. 44B and 44D-44F ) were counter-stained with hematoxylin. Images are 1,600 ⁇ magnification.
  • FIGS. 45A-45R depict APE1/Ref-1 redox signaling inhibition sensitizes 3D PDAC tumor spheroids to CA9 inhibition with second-generation inhibitors.
  • 10.05 and Pa03C cells were plated into 3D cultures with CAF19 cells, and cell growth in these spheroids was measured via fluorescence intensity on days 4, 8, 12, and 16 after plating. The growth of tumor cells vs. CAF cells in the spheroid co-cultures was assessed separately using different fluorescent labels in the two cell types.
  • 3D cultures were treated with FC12-531A+APX3330 ( FIGS. 45A-45F ), APX2009 ( FIGS. 45G-45L ), or APX2014 ( FIGS.
  • FC12-531A ⁇ 0.001 vs. FC12-531A.
  • FIG. 46 is a pathway schematic.
  • APE1/Ref-1 redox signaling contributes to the transactivation of HIF-1 and certain other transcription factors.
  • HIF1 ⁇ is stabilized under hypoxic conditions, leading to the formation of HIF-1 and subsequent expression of CA9.
  • CA9 coordinates with the bicarbonate transporter and intracellular CAs to stabilize intracellular pH.
  • APE1/Ref-1 redox signaling inhibition (with APX3330, APX2009, or APX2014) attenuates HIF-1-mediated CA9 expression, sensitizing tumor cells to CA9 inhibition (with SLC-0111 or FC12-531A).
  • Ref-1 alludes to its expansive roles in disease, particularly cancers.
  • Ref-1 is upregulated in many cancers (Table 1, FIG. 4 ). This increase is frequently associated with tumorigenesis, cancer aggressiveness, increased angiogenesis, radiotherapeutic and chemotherapeutic resistance, and overall poor prognosis. This makes Ref-1 and the transcription factors it regulates prime targets for anticancer therapies.
  • Ref-1 overexpression is prostate cancer. Overexpression is seen immunohistologically as a higher percentage of cells staining positive for Ref-1 in the cytoplasm and an increased intensity of Ref-1 nuclear staining.
  • STAT3 is constitutively active in prostate cancer.
  • STAT3 inhibition suppresses prostate cancer cell growth.
  • STAT3 activation negatively affects overall survival rates and shortens relapse-free survival (RFS).
  • FFS relapse-free survival
  • a downstream target of STAT3 is survivin; its increased expression is also associated with prostate cancer aggressiveness.
  • mRNA expression levels of survivin in prostate biopsy tissues show significantly higher survivin expression in cancerous tissue, which correlates with higher-grade cancer and aggressive phenotypes.
  • siRNA knockdown of survivin in prostate cancer cell lines reduces cell proliferation and increases chemosensitivity to the apoptosis-inducing agent cisplatin. The effects of decreased survivin expression extend in vivo. Mice injected subcutaneously with siRNA survivin knockdown cells exhibit significantly smaller tumors compared with controls.
  • Ref-1 redox-specific inhibitors APX3330 and APX2009 decreased survivin mRNA and protein levels in prostate cancer cells by affecting NF- ⁇ B activity. These inhibitors also reduced cell proliferation. In vivo, APX2009 reduced survivin protein levels and cell proliferation.
  • both STAT3 and survivin present as prime targets for anti-prostate cancer therapies.
  • they have been only moderately successful as single-agent therapies. Therefore, the potential combination of inhibiting both Ref-1 redox function and STAT3/survivin provides an avenue of targeting both the overarching regulator and downstream effector of an anti-apoptotic pathway integral to prostate cancer.
  • the present disclosure is directed to the combination of an APE1/Ref-1 inhibitor (5-(2,3-dimethoxy-6-methyl 1,4-benzoquinoyl)]-2-nonyl-2-propenoic acid (APX3330), [(2E)-2-[(3-methoxy-1,4-dioxo-1,4-dihydronaphthalen-2-yl)methylidene]-N,N-diethylpentanamide] (APX2009), (2E)-2-[(3-methoxy-1,4-dioxo-1,4-dihydronapthalen-2-yl)methylidene]-N-methoxypentanamide] (APX2014)) and a STAT3 inhibitor (e.g., napabucasin) for treating prostate cancer.
  • a combination of an APE1/Ref-1 inhibitor and a survivin inhibitor e.g., YM155 for treating prostate cancer is disclosed.
  • Colon cancer the second leading cause of cancer related death in the U.S., exhibits increased levels of cytoplasmic Ref-1.
  • increased Ref-1 expression corresponds to poor patient outcome.
  • siRNA Ref-1 knockdown significantly increases the sensitivity of colon cancer cells to ionizing irradiation (IR).
  • IR ionizing irradiation
  • APX3330 (hereafter referred to as “APX”) significantly reduces CCSC growth in vitro and enhances the cytotoxicity of 5-fluorouracil (5-FU), an anti-metabolite chemotherapeutic.
  • 5-fluorouracil 5-fluorouracil
  • intratumoral administration of APX3330 increases tumor response to 5-fluorouracil (5-FU) delivered intraperitoneally. This indicates that APX3330 could potentiate other colon cancer treatments by inhibiting Ref-1's crucial redox activity.
  • the present disclosure is directed to the combination of an APE1/Ref-1 inhibitor (APX3330, APX2009 and APX2014) and a chemotherapeutic (e.g., 5-FU) for treating colon cancer.
  • a combination of an APE1/Ref-1 inhibitor and an inhibitor of PDH and/or KDGH (e.g., CPI-613) for treating colon cancer is disclosed.
  • Ref-1 expression in ovarian cancer has been studied widely. Ref-1 expression is increased in malignant patient tissue samples, but studies vary as to the location of this increase.
  • Ref-1 knockdown in A2780 (nuclear APE1) and CP70 (cytoplasmic APE1) cells sensitizes both to cisplatin.
  • Ref-1 siRNA significantly reduces cell proliferation, colony formation, migration and invasion.
  • Ref-1 siRNA treatment of SKOV-3 ⁇ ovarian cells significantly reduces their growth; the same occurs with APX3330 redox inhibition.
  • Ref-1 siRNA cells implanted subcutaneously in mice show markedly reduced growth compared to control tumors: a 3.2-fold increase in tumor-doubling time (from 5 to more than 15 days). The tumors also exhibit reduced glucose metabolism.
  • Ref-1 has long been considered a prognostic marker in non-small-cell lung carcinoma (NSCLC), as Ref-1 protein levels are upregulated in patient tumor samples. Nuclear Ref-1 expression in tissue samples presents better survival chances for patients. Cytoplasmic Ref-1 and mRNA expression correlate strongly with poor patient survival and shorter RFS. Both immunohistochemistry and immunoblotting show increased cytoplasmic and reduced nuclear Ref-1 expression in patients with a recurrence of stage I NSCLC. Post-treatment serum Ref-1 levels are inversely associated with overall survival.
  • NSCLC non-small-cell lung carcinoma
  • Ref-1 affects platinum-based drugs commonly used in NSCLC.
  • An increase in Ref-1 expression in NSCLC confers resistance to cisplatin treatment, while Ref-1 siRNA knockdown in A549 cancer cells significantly enhances cisplatin cytotoxicity.
  • Patients with tumors not expressing Ref-1 respond better to platinum-paclitaxel therapy and cisplatin-docetaxel-gemcitabine treatment, with longer time to progression and overall survival.
  • Ref-1 knockdown with shRNA enhances the anti-tumor activity of oxymatrine, an alkaloid compound that inhibits proliferation of A549 cells.
  • Ref-1 plays a vital role in NSCLC progression, and targeting it might lead to better patient outcomes when combined with various chemotherapeutic treatments.
  • the present disclosure is directed to a combination of an APE1/Ref-1 inhibitor (e.g., APX3330, APX 2009 and APX2014) and a chemotherapeutic agent (e.g., paclitaxel, cisplatin, docetaxel, gemcitabine) for treating NSCLC.
  • a combination of an APE1/Ref-1 inhibitor and a photodynamic therapy for treating NSCLC is disclosed.
  • MPNST Malignant Peripheral Nerve Sheath Tumor
  • Phosphorylated STAT3 expression may indicate aggressive disease at disease onset.
  • a tissue microarray showed STAT3 expression in primary MPNST was associated with worse disease-specific overall survival and event-free survival.
  • both a JAK/STAT3 inhibitor and STAT3 knockdown by shRNA prevented tumor formation.
  • STAT3's downstream target survivin is amplified in MPNSTs.
  • Survivin is highly expressed in MPNST tissue samples.
  • Survivin knockdown via siRNA decreases cell growth, inhibits cell cycle progression and increases apoptosis.
  • survivin inhibitor YM155 represses MPNST xenograft growth and metastasis in vivo.
  • STAT3-HIF-1a pathway The role of the STAT3-HIF-1a pathway in MPNST supports the notion of STAT3 and/or HIF-1 ⁇ inhibition as a potential way to treat MPNST. Downstream markers like survivin also present as potential targets. Ref-1 regulates STAT3 as well as HIF-1 ⁇ ; therefore, targeting Ref-1 would inhibit multiple targets, providing hope for a viable treatment for MPNST. Additionally, the possibility of dual targeting Ref-1 and either STAT3 or HIF-1 ⁇ alludes to the potential of completely eliminating a pathway that is integral to MPNST progression.
  • the present disclosure is directed to a combination of an APE1/Ref-1 inhibitor (e.g., APX3330, APX 2009 and APX2014) and a STAT3 inhibitor (e.g., napabucasin) for treating MPNST.
  • a combination of an APE1/Ref-1 inhibitor and a HIF-1 ⁇ for treating MPNST is disclosed.
  • present disclosure is directed to a combination of an APE1/Ref-1 inhibitor and a survivin inhibitor (e.g., YM155) for treating MPNST.
  • Ref-1 Ref-1 in leukemias.
  • APL acute promyelocytic leukemia
  • ATRA all-trans retinoic acid
  • RAR retinoic acid receptor
  • RAR alpha binds to its DNA binding site (RARE) in a redox-dependent fashion.
  • RARE DNA binding site
  • APX3330 the addition of APX3330 to ATRA increases apoptosis and cellular differentiation of APL cells by three-fold.
  • Ref-1 is highly expressed in T-cell acute lymphoblastic leukemia (T-ALL).
  • Blockade of Ref-1 by the redox-specific inhibitor APX3330 potently inhibits viability of leukemia T-cells, including primary cells, relapsed and chemotherapy-resistant cells, and cells from a mouse model of T-ALL.
  • Ref-1 redox inhibition promotes leukemia cell apoptosis, which is associated with downregulation of pro-survival genes.
  • Tet2-deficient stem cells demonstrate resistance to inflammatory challenge as revealed by a higher repopulating and engraftment potential in both primary and secondary recipients compared to wildtype controls, which, when stressed, show a remarkable decline in overall engraftment. This process invokes the NF- ⁇ B pathway, which Ref-1 regulates.
  • APX3330 blocks NF- ⁇ B function, which decreases inflammation and reverses the progression from pre-AML to frank AML in mice bearing AML-associated epigenetic mutations often observed in healthy individuals with clonal hematopoiesis.
  • the present disclosure is directed to a combination of an APE1/Ref-1 inhibitor (e.g., APX3330, APX 2009 and APX2014) and a NF- ⁇ B inhibitor (e.g., napabucasin) for treating T-ALL.
  • an APE1/Ref-1 inhibitor e.g., APX3330, APX 2009 and APX2014
  • a NF- ⁇ B inhibitor e.g., napabucasin
  • the patient to be treated is carrying TET2 mutations that show signs of clonal hematopoiesis.
  • the combination of an APE1/Ref-1 inhibitor e.g., APX3330, APX 2009 and APX2014
  • a NF- ⁇ B inhibitor can be used for treating patients with TET2 mutations who also have acute myeloid leukemia, myeloproliferative disease or myelodysplastic syndrome.
  • Ref-1 Increased levels of Ref-1 are not limited to cancers ( FIG. 4 ). Elevated Ref-1 has been implicated in age-related cataracts. Ref-1 levels are higher in the lens epithelium cells of patients versus controls, and Ref-1 levels decrease as the opaque degree worsens.
  • Ref-1 is highly expressed in developing murine retinas, as well as retinal pigment epithelium (RPE) cells, retinal pericytes, choroid endothelial cells (CECs) and retinal vascular endothelial cells (RVECs).
  • RPE retinal pigment epithelium
  • CECs choroid endothelial cells
  • RVECs retinal vascular endothelial cells
  • APX3330 shows that Ref-1 redox activity is required for RVEC proliferation, migration and angiogenesis in vitro.
  • APX3330 treatment reduced proliferation, migration and angiogenesis in CECs in primate cells in vitro and had an additive effect when combined with bevacizumab.
  • RPEs stressed using oxidized low-density lipoproteins (oxLDLs) were rescued from proliferation decline and senescence by APX.
  • APX3330 reduced the transcriptional activity of NF- ⁇ B, a key factor associated with inflammation in angiogenesis. It also blocked activation of HIF-1 ⁇ and reduced the expression of its downstream target VEGF.
  • VEGF expression via NF- ⁇ B and HIF-1 ⁇ is primarily responsible for choroidal neovascularization (CNV), a characteristic of neovascular Age-related Macular Degeneration (AMD), also known as wet AMD.
  • CNV choroidal neovascularization
  • AMD Age-related Macular Degeneration
  • VLDLR very low density lipoprotein receptor
  • Angiogenesis is also a prime component of other retinal diseases, including Retinopathy of Prematurity (ROP) and Diabetic Retinopathy (DR).
  • ROP Retinopathy of Prematurity
  • DR Diabetic Retinopathy
  • Ref-1's redox ability to modulate angiogenesis makes it worth investigating in those diseases.
  • HIF-1 ⁇ and VEGF are increased in ROP and DR.
  • Retinal neovascularization a marker of ROP and DR, is markedly reduced in mice with ischemic retinopathy when treated with siRNA targeting HIF-1 ⁇ or VEGF.
  • Ref-1 has also been shown to play a role in several other diseases. Ref-1's involvement in cardiovascular disease and regulation of blood pressure is illustrated by aortic coarctation-induced hypersensitive rat models showing increased Ref-1 expression levels. Furthermore, heterozygous Ref-1+/ ⁇ mice exhibit hypertension and diminished endothelium-dependent vasorelaxation. Ref-1 is part of the SET complex of proteins that are involved in HIV pathogenesis by inhibiting suicidal autointegration. Consequently, knocking down Ref-1 inhibits HIV infection.
  • Ref-1 is also implicated in gastric cellular response to Helicobacter pylori ( H. pylori ) infection. Ref-1 expression levels were elevated following H. pylori infection in human gastric epithelial cells. H. pylori induced ROS and downstream activated genes were higher in Ref-1 deficient cells compared to control, with Ref-1 overexpression reversing these effects. Additionally, Ref-1 siRNA knockdown inhibited H. pylori and TNF- ⁇ -induced AP-1 and NF- ⁇ B DNA binding, as well as IL-8 mRNA expression and protein secretion in gastric epithelial cells. Collectively, that implicates Ref-1 in gastric inflammatory disorders as well as sepsis.
  • NDs neurodegenerative disease
  • AD Alzheimer's disease
  • PD Parkinson's disease
  • ALS amyotrophic lateral sclerosis
  • cerebral ischemia is all affected by APE1/Ref-1 dysfunction.
  • Ref-1 protein levels are elevated in nuclear extracts from the midfrontal cortex and cerebral cortex of AD patients compared to controls, with Ref-1 redox activity being seen as a compensatory mechanism for increased oxidative stress.
  • reduced APE1 endonuclease activity is seen in peripheral blood mononuclear cells of AD patients, suggesting impaired Base Excision Repair (BER).
  • BER Base Excision Repair
  • Ref-1 levels are elevated in the central nervous system of patients with ALS, a disease exhibiting elevated oxidative stress and DNA damage.
  • loss of Ref-1 function via gene variants suggests it is a risk factor, contributing to increased oxidative stress that leads to loss of dorsal root ganglion (DRG) neurons.
  • Ref-1 is upregulated in cells treated with rotenone and MPP + (1-methyl-4-phenylpyridinium), both of which are used to simulate a PD model. Ref-1 upregulation protects against neuronal death in these cells.
  • Ref-1 conditional knockout mice exhibit larger infract volume and diminished recovery of spatial and cognitive function following cerebral ischemia.
  • APX3330 and APX2009 can be combined with inhibitors of STAT3, HIF1 ⁇ , CA9, VEGF, NF ⁇ B, JAK2, Bcl-2, PTEN, WNT/ ⁇ -catenin, Endostatin, 5-fluorouracil (5-FU), and a photodynamic therapy (PDT), and the like, and combinations thereof. More particularly, exemplary combinations include APX3330 and/or APX2009 with one or more of a second therapeutic agent selected from those in Tables 2 & 3.
  • Suitable dosages of the Ref-1 inhibitor (e.g., APX3330) and second therapeutic agent for use in the combination therapies of the present disclosure will depend upon a number of factors including, for example, age and weight of an individual, at least one precise cancer/disease requiring treatment, severity of a disease, specific Ref-1 inhibitor and/or second therapeutic agent to be combined, nature of a composition, route of administration and combinations thereof.
  • a suitable dosage can be readily determined by one skilled in the art such as, for example, a physician, a veterinarian, a scientist, and other medical and research professionals. For example, one skilled in the art can begin with a low dosage that can be increased until reaching the desired treatment outcome or result. Alternatively, one skilled in the art can begin with a high dosage that can be decreased until reaching a minimum dosage needed to achieve the desired treatment outcome or result.
  • the combination therapies can include pharmaceutically acceptable carriers, for example, excipients, vehicles, diluents, and combinations thereof.
  • pharmaceutically acceptable carriers for example, excipients, vehicles, diluents, and combinations thereof.
  • the combination therapies may be formulated as tablets, capsules, granules, powders, or syrups; or for parenteral administration, they may be formulated as injections (intramuscular, subcutaneous, intramedullary, intrathecal, intraventricular, intravenous, intravitreal), drop infusion preparations, or suppositories.
  • compositions can be prepared by conventional means, and, if desired, the active compounds (i.e., APX3330 and second therapeutic agent) may be mixed with any conventional additive, such as an excipient, a binder, a disintegrating agent, a lubricant, a corrigent, a solubilizing agent, a suspension aid, an emulsifying agent, a coating agent, or combinations thereof.
  • any conventional additive such as an excipient, a binder, a disintegrating agent, a lubricant, a corrigent, a solubilizing agent, a suspension aid, an emulsifying agent, a coating agent, or combinations thereof.
  • an “individual in need” refers to an individual at risk for or having cancer, and in particular, prostate cancer, breast cancer, ovarian cancer, cervical cancer, osteosarcoma, colon cancer, bladder cancer, pancreatic cancer, gliomas, and the like as listed in Table 1.
  • an “individual in need” refers to an individual at risk for or having a retinal disease (e.g., choroidal neovascularization (CNV), age-related macular degeneration (AMD), retinopathy of prematurity (ROP), diabetic retinopathy (DR)).
  • CNV choroidal neovascularization
  • AMD age-related macular degeneration
  • ROP retinopathy of prematurity
  • DR diabetic retinopathy
  • an “individual in need” refers to an individual at risk for or having cardiovascular disease, bacterial infection, gastric inflammatory disorders, neurodegenerative diseases (e.g., Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), cerebral ischemia). Additionally, an “individual in need” is also used herein to refer to an individual at risk for or diagnosed by a medical professional as having any one of these diseases and/or disorders. As such, in some embodiments, the methods disclosed herein are directed to a subset of the general population such that, in these embodiments, not all of the general population may benefit from the methods.
  • the individual in need is a human.
  • the individual in need can also be, for example, a research animal such as, for example, a non-human primate, a mouse, a rat, a rabbit, a cow, a pig, and other types of research animals known to those skilled in the art.
  • AT-101 exerts its anti-tumor effects in many ways: it is a BH3-mimetic and also has been shown to inhibit Ref-1's DNA repair and redox activities. Blockade of the anti-apoptotic proteins Bcl-2 and Bcl-XL through Ref-1's redox inhibition of STAT3 activity contributes to the enhanced cell killing and tumor growth seen in this combination. Furthermore, in NSCLC cell line A549, siRNA inhibition of APE1 expression significantly sensitizes A549 cells to cisplatin and increased cell apoptosis. Both of these studies point to Ref-1 function as critical in the cells' response to cisplatin, especially in apoptosis signaling through STAT3.
  • a second option for uncovering new treatment options is to mine publicly available data sets such as TCGA (The Cancer Genome Atlas) and CCLE (Cancer Cell Line Encyclopedia) to elucidate [in silico] effective combination treatments to utilize in cancer treatment settings.
  • the goal is to accelerate the selection of likely increased lethal targets, particularly for aggressive cancers that have few treatment options.
  • the downregulation of DNA repair proteins following Ref-1 knockdown is another confirmation that the addition of a Ref-1 inhibitor to a DNA-damaging agent is deleterious to cancer cells.
  • Chemotherapy-induced peripheral neuropathy is one of the most prevalent dose-limiting toxicities of anticancer therapy. Up to 90% of cancer patients experience chemotherapy-induced peripheral neuropathy (CIPN) at some point during or after anticancer treatment. Indeed, anticancer drugs used for the six most common malignancies pose a substantial risk for CIPN. These drugs include, but are not limited to platinum agents, taxanes, vinca alkaloids, proteasome inhibitors, immunomodulators and even new, targeted therapeutic agents. There are currently no approved treatments to prevent or treat CIPN, thus the neurotoxicity can be dose-limiting for some patients.
  • Platinum drugs are an important component of numerous standard-of-care treatment (SOC) regimens for pediatric and adult cancers; for example, oxaliplatin is a part of the FOLFIRINOX and FOLFOX protocols.
  • CIPN can persist after treatment is completed. Up to 40% of cancer patients continue to struggle with CIPN five years after treatment ends—and 10% remain symptomatic after more than 20 years. Thus, CIPN directly affects cancer survivorship, quality of life, and may limit future treatment options if cancer recurs.
  • APX3330 is a targeted inhibitor of APE1/Ref-1's redox function, it appears that, in the setting of sensory neurons, it can also enhance the protein's DNA repair (AP endonuclease) activity ( FIG. 6 ). Although this seems counterintuitive, APX3330 causes the protein to unfold over time. This unfolding primarily alters the amino end of APE1/Ref-1, affecting its interactions with downstream transcription factor targets by perturbing the equilibrium of the protein's folded/unfolded states and facilitating repair activity. This disengagement of APE1 from its Ref-1 redox activity could enhance APE1 repair endonuclease activity.
  • APX3330 When isolated sensory neurons are exposed to APX3330, a concentration-dependent increase in Ref-1 endonuclease activity occurs, which is not observed in tumor cells. As discussed herein, it was found that APX3330 protected sensory neurons from DNA damage and reactive oxygen species (ROS) production induced by agents such as ionizing IR, cisplatin and oxaliplatin.
  • ROS reactive oxygen species
  • a critical property of any putative therapeutic for neurotoxicity is that it will not compromise the anticancer function of the treatment(s) administered.
  • the enhancement of DNA repair activity by APX3330 was not observed in mitotic cells. It was shown that APX3330 negatively affects the growth and/or survival of tumor cell lines, patient-derived cell lines, and tumors in animal models. Therefore, it is possible that APX3330 could protect postmitotic cells without altering the effects of anticancer drugs on tumor cells ( FIG. 6 ). Additionally, APX3330 does not affect cisplatin or oxaliplatin's tumor-killing efficacy in vivo, yet it protects DRG neurons from oxidative DNA damage.
  • APX3330 could be offered as a neuroprotective mechanism in humans, facilitating BER repair of oxidative DNA damage and protecting sensory neurons.
  • DNA repair function not the redox function of APE1/Ref-1—is necessary for sensory neuronal survival/function. That is opposite from tumor cells.
  • APE1 knockout in mice results in embryonic lethality, post-implantation, between days E5-E9. As such, it has not historically been possible to generate stable APE1 knockout cell lines.
  • RNA Sequencing scRNA-seq
  • Pa03C, Pa02C, Panc10.05 and Panc198 were obtained from Dr. Anirban Maitra at The Johns Hopkins University. All cells were maintained at 37° C. in 5% CO 2 and grown in DMEM (Invitrogen; Carlsbad, Calif.) with 10% Serum (Hyclone; Logan, Utah). Cell line identity was confirmed by DNA fingerprint analysis (IDEXX BioResearch, Columbia, Mo.) for species and baseline short-tandem repeat analysis testing. All cell lines were 100% human and a nine-marker short tandem repeat analysis is on file. They were also confirmed to be mycoplasma free.
  • siRNAs used were Scrambled (SCR) (5′ CCAUGAGGUCAGCAUGGUCUG 3′, 5′ GACCAUGCUGACCUCAUGGAA 3′) (SEQ ID NO:1) and siAPE1 (5′ GUCUGGUACGACUGGAGUACC 3′ (SEQ ID NO:2), 5′ UACUCCAGUCGUACCAGACCU 3′) (SEQ ID NO:3). All siRNA transfections were performed by plating 1 ⁇ 10 5 cells per well of a 6-well plate and allowing the cells to attach overnight.
  • Lipofectamine RNAiMAX reagent (Invitrogen, Carlsbad, Calif.) was used to transfect in the APE1 and SCR siRNA at concentrations between 10 and 50 nM following the manufacturer's indicated protocol. Opti-MEM, siRNA, and Lipofectamine was left on the cells for 16 hours and then regular DMEM media with 10% Serum was added. Cells were assayed for RNA and protein expression 3 days following transfection.
  • APE1 Novus Biologicals, Littleton, Colo.
  • Vinculin Sigma, St. Louis, Mo.
  • SCR/siAPE1 cells were collected and loaded into 96-well microfluidic C1 Fluidigm array (Fluidigm, South San Francisco, Calif., USA). All chambers were visually assessed and any chamber containing dead or multiple cells was excluded.
  • the SMARTer system (Clontech, Mountain View, Calif.) was used to generate cDNA from captured single cells. The dscDNA quantity and quality was assessed using an Agilent Bioanalyzer (Agilent Technologies, Santa Clara, Calif., USA) with the High Sensitivity DNA Chip. A total of 48 SCR and 48 siAPE1 cells were chosen for sequencing.
  • the Purdue Genomics Facility prepared libraries using a Nextera kit (Illumina, San Diego, Calif.). Unstranded 2 ⁇ 100 bp reads were sequenced using the HiSeq2500 on rapid run mode in 1 lane. RNA-seq data are available at the Gene Expression Omnibus (GEO) through accession number pending.
  • GEO Gene Expression Omnibus
  • Ingenuity Pathway Analysis was utilized in performing network analyses (IPA, QIAGEN Redwood City, www.qiagen.com/ingenuity). An upstream regulator analysis, canonical pathway analysis, mechanistic networks analysis, causal network analysis, and downstream effects analysis were performed using IPA (results were deemed significant for p-values ⁇ 0.05). Algorithms and details of each type of network analysis are presented in Kramer, A., et al., Causal analysis approaches in Ingenuity Pathway Analysis. Bioinformatics, 2014. 30(4): pp. 523-30.
  • qRT-PCR was used to measure the mRNA expression levels of the various genes identified from the scRNA-seq analysis. Following transfection, total RNA was extracted from cells using the Qiagen RNeasy Mini kit (Qiagen, Valencia, Calif.) according to the manufacturer's instructions. First-strand cDNA was obtained from RNA using random hexamers and MultiScribe reverse transcriptase (Applied Biosystems, Foster City, Calif.). Quantitative PCR was performed using SYBR Green Real Time PCR master mix (Applied Biosystems, Foster City, Calif.) in a CFX96 Real Time detection system (Bio-Rad, Hercules, Calif.).
  • the relative quantitative mRNA level was determined using the comparative Ct method using ribosomal protein L6 (RPL6) (Pa03C) or Actin (Pancl0.05, Panc 198, Pa02C) as the reference gene.
  • RPL6 ribosomal protein L6
  • Actin Pancl0.05, Panc 198, Pa02C
  • the primers used for qRT-PCR are detailed in Table 4. Experiments were performed in at least triplicate for each sample. Statistical analysis performed using the 2 ⁇ C T method and analysis of covariance (ANCOVA) models.
  • siRNA knockdown of APE1 did not result in complete loss of the APE1 protein, as detected by Western blotting, with 10-20% APE1 protein expression observed in the siAPE1 samples compared to the scrambled controls (SCR) as shown by representative Western blot shown in FIG. 8A .
  • 20 nM siRNA was used, as levels greater than this results in off-target effects and cell killing not related to APE1 functions. Therefore, in order to clearly identify changes in gene expression specifically related to the amount of APE1 protein within each individual cell, single-cell RNA-seq was performed on cells following APE1 siRNA knockdown.
  • the siAPE1 and SCR cells were split across three batches, with one batch containing siAPE1 and two batches containing SCR cells (SCR1 and SCR2). Differences between cell batches were corrected by applying the scLVM R package.
  • the Biomart R package was used to obtain a list of cell cycle-annotated genes. Specifically, the Gene Ontology (GO) term GO:0007049 was used to identify 189 genes with the annotation name of “cell cycle”. Of these 189 genes, only 102 coincided with the genes remaining in the analysis due to removal of genes exhibiting low expression across all cells (gene detection rate quality control filtering).
  • a latent variable model was fit to account for cell cycle confounding, while also incorporating treatment and control covariates into the model. Using the fitted latent variable model, it was then possible to regress out the cell cycle confounding and compute a corrected dataset.
  • the plot in FIG. 8B demonstrates the two principal components before correcting for cell cycle and shows that the most influential source of variation (i.e., the x-axis representing 6.84% of the total variation) in the data corresponds to the axis along which SCR1 and SCR2 cells were separated.
  • the second most influential source of variation i.e. the y-axis representing 4.57% of the total variation
  • siAPE1 and SCR cells were separated corresponds to the axis along which siAPE1 and SCR cells were separated.
  • the SCR1 and SCR2 cells showed greater similarity, which resulted in the largest source of variation (i.e., the horizontal axis representing 4.88% of the total variation) now corresponding to the axis along which the siAPE1 and SCR cells were separated.
  • the variation attributed to cell cycle annotated genes was effectively removed without removing the variation attributed to the differences between siAPE1 treatment and scrambled control.
  • the largest source of variation between the cells was attributed to APE1 knockdown.
  • the number of genes detected per cell averaged 7095.7 using the original (i.e. prior to correcting for cell-cycle confounding) gene expression counts. For each gene, the average number of cells with non-zero gene counts was 42.1 using the original gene expression counts.
  • a violin plot showing the distribution of the cells in each of these groups can be found in FIG. 9A .
  • edgeR models the counts with an overdispersed (larger variance) Poisson distribution (also known as the negative-binomial distribution), which may not be appropriate for single cell RNA-seq data due the fact that there are many more zero counts in this data (a phenomenon referred to as zero-inflation) compared to bulk RNA-seq.
  • ⁇ ij is the expected value of the beta-Poisson count distribution of the i th cell for the j th gene
  • ⁇ 0 is the intercept
  • ⁇ 1 is the gene expression in log(Counts per Million).
  • the expression I[siAPE1] i is an indicator variable that takes the value of one when a cell belongs to the siAPE1 knockdown group.
  • the differential expression of the j th gene can then be tested using the null (denoted as H 0 ) and alternative (denoted as H 1 ) hypotheses as follows:
  • One of the advantages of performing scRNA-seq is that it allows looking at APE1 expression in each individual cell. It was therefore possible to use this information to categorize cells within the siAPE1 group as having either undetectable APE1 (defined as a cell with zero expression of APE1) or detectable APE1 (defined as a cell with greater than zero expression of APE1). As previously mentioned, within the siAPE1 group there were 25 cells with undetectable APE1 (hereafter called undetectable siAPE1) and 20 cells exhibiting detectable but reduced APE1 expression (hereafter called detectable siAPE1).
  • the delineation of the siAPE1 cells allowed consideration of the SCR control, detectable siAPE1 and undetectable siAPE1 cells as three different categories. Such a model is appropriate if detectable siAPE1 cells were considered to be distinct from both undetectable siAPE1 as well as SCR control cells.
  • the model in this case is given by
  • H 1 At least one of ⁇ 1j ⁇ 0 or ⁇ 2j ⁇ 0
  • This model has two parameters that can be tested for joint significance, whereas the initial SCR/siAPE1 model only had one parameter to test. While it is possible to estimate the joint significance with a single test of both parameters, the parameter specific significance was computed in order to gain insight into the individual differences between undetectable siAPE1 and detectable siAPE1 groups with respect to the SCR control. In practice, each of these parameters was tested separately and their joint significance was reported as the resulting p-values using Fisher's method. For two p-values p 1j ,p 2j corresponding to test of ⁇ 1j , ⁇ 2j for the j th gene, the combined test statistic is described as
  • This analysis allows for detection of differences that may be present between SCR and detectable siAPE1 cells, between SCR and undetectable siAPE1 cells, or between SCR and both categories of siAPE1 cells.
  • the joint analysis guards against a single outlier preventing a gene from being reported as differentially expressed as one parameter may be reported as insignificant, but not the other.
  • this experimental design aids in the interpretation of results and helps to identify genes potentially affected by outliers.
  • This SCR/detectable siAPE1/undetectable siAPE1 analysis identified 2,837 genes using a false discovery rate of 5%.
  • TCGA Cancer Genome Atlas
  • SCR/siAPE1 and SCR/detectable siAPE1/undetectable siAPE1 analyses were utilized. Performing this TCGA analysis allowed for measurement of the clinical relevance of the DEGs identified in this Example, and also provided a performance metric for the two analyses.
  • the RTCGA toolbox was used to analyze the data from the TCGA.
  • a gene is defined as clinically relevant if its expression level at the time of sequencing is statistically significantly related to the number of days until death in patients with pancreatic cancer.
  • the statistical significance of a gene is determined using the Cox proportional hazards regression model, a commonly used model in clinical trials and biostatistics. Specifically, the outcome of days until death (accounting for censoring due to a patient still being alive at the time of sequencing) was regressed on the normalized gene expression data of patient tumor samples via bulk RNA-Seq using the R package survival. Only expression levels in the analysis were used, modeling one gene at a time across all tumor types and stages.
  • the TCGA analysis resulted in 1,627 genes statistically significantly related to time until death using a false discovery rate of 5%.
  • 1,486 DEGs considered from the SCR/siAPE1 analysis 246 genes (16.6%) were found to be clinically relevant.
  • the SCR/detectable siAPE1/undetectable siAPE1 analysis identified 345 clinically relevant genes (16.3%) out of the available 2,115 DEGs.
  • the SCR/detectable siAPE1/undetectable siAPE1 analysis identified more DEGs that are clinically relevant without a change in the overall percentage of clinically relevant genes. This further illustrates that the 856 genes unique to the analysis were not statistical anomalies, but authentic results identified due to a more stringent statistical model. Because of this result, all following analyses were carried out using the SCR/detectable siAPE1/undetectable siAPE1 results.
  • IPA Ingenuity pathway analysis
  • a number of the significant pathways affected by APE1 knockdown confirm previous observations and therefore provided validation for the results.
  • the HIF1 ⁇ signaling pathway shown to be regulated by APE1
  • the mitochondrial dysfunction pathway has 37 DEGs, while there are 42 DEGs in the Huntington's disease signaling pathway.
  • Mitochondrial dysfunction is believed to play a role in Huntington's disease pathology, and prior studies have demonstrated that APE1 is important for the maintenance of mitochondrial function.
  • APE1 is also known to participate in mitochondrial DNA repair functions. While APE1 is known to influence these pathways, this Example expands the understanding of APE1 within the cell by implicating the genes in the pathways that are affected by APE1 knockdown.
  • the scRNA-seq results of the SCR/siAPE1 analysis were validated by performing qRT-PCR in Pa03C cells following siRNA knockdown.
  • the genes that showed statistically significant increased or decreased expression in scRNA-seq exhibit changes in the same direction following qRT-PCR ( FIG. 12C ), with a decrease seen in the mRNA levels of CIRBP, COMMD7, ISYNA1, ITGA1, NOTCH3, PRDX5, RAB3D, SIPA1, TAPBP and TNFAIP2.
  • the expression of BCRP and PPIF was significantly increased following knockdown.
  • the fold changes from scRNA-seq were plotted against qRT-PCR fold changes in FIG. 12D . With an R 2 value of 0.82 and p ⁇ 0.0001 (Linear Regression analysis), it was confirmed that the fold changes were consistent and validated the single-cell scRNA-seq studies.
  • the “connectivity map” project compared the query gene expression signatures against a database of gene expression profiles derived from treating human cells with various agents to identify similarities and predict drug mechanisms. Incorporating drug sensitivity data of cell lines with similar gene expression profiles were used to predict effective combination treatments.
  • Cancer Cell Line Encyclopedia (CCLE, https://portals.broadinstitute.org/ccle/home) contains baseline gene expression data of 1,036 cancer cell lines and pharmacologic profiles (IC 50 , AUC) for anticancer drugs across 504 cell lines.
  • CCLE gene expression profile set as the reference was used, as well as data from Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Therapeutics Response Portal (CTRP, http://portals.broadinstitute.org/ctrp/).
  • Standard 3D co-culture assays as described in Example 2 were used to evaluate the cytotoxicity of the combination on tumor cells as well as cancer-associated fibroblasts.
  • FIG. 14C the beneficial effects of combining APX3330 with gemcitabine in vivo were demonstrated.
  • APX3330 25 mg/kg was combined with a standard dose of gemcitabine (35 mg/kg) to demonstrate the “additive” effects of APX3330 in reducing pancreatic tumor volumes.
  • the data in FIG. 14C is tumor volume at sacrifice. Combination therapy was well-tolerated. There was a significantly decreased tumor volume in the combination treatments of APX3330 with gemcitabine compared to the single agents alone. All treatments, single or combination were significantly different from the vehicle control.
  • Standard 3D co-culture assays as described in Example 2 were used to evaluate the cytotoxicity of the combination on tumor cells as well as cancer-associated fibroblasts.
  • APE1 siRNA knockdowns were then analyzed in other PDAC low passage patient-derived cells.
  • Pa02C cells BCRP, COMMD7, ISYNA1, ITGA1, PRDX5, RAB3D, SIPA1 and TNFAIP2 all demonstrated a decrease in expression, while NOTCH3 and PPIF were significantly increased following knockdown ( FIG. 16A ).
  • changes in expression of BCRP and NOTCH3 were significant, they were in opposing directions to the changes seen in Pa03C cells.
  • Panc10.05 cells derived from a primary PDAC tumor, exhibited similar results to Pa03C cells, with eight of the 12 genes showing similar changes in expression ( FIG. 16B ).
  • COMMD7, ITGA1, RAB3D, SIPA1, TAPBP and TNFAIP2 show decrease, while BCRP and PPIF increased expression.
  • CIRBP, ISYNA1, NOTCH3 and PRDX5 show no change in expression in the Panc10.05 cells.
  • Panc198 cells also originating from a primary tumor, produced the most varied results ( FIG. 16C ). No change in expression was seen for BCRP, CIRBP, ISYNA1, NOTCH3, PRDX5, PPIF, SIPA1 and TAPBP.
  • COMMD7, ITGA1, RAB3D and TNFAIP2 all showed significantly decreased expression.
  • COMMD7, ITGA1, RAB3D and TNFAIP2 were significantly changed in all four patient-derived cell lines tested ( FIG. 16D ).
  • BCRP Breast cancer resistance protein
  • ABCG2 is an ATP-binding cassette (ABC) transporter that is one of the proteins responsible for multidrug resistance of cancer cells.
  • ABSC ATP-binding cassette
  • high BCRP expression corresponds to carcinogenesis, tumor progression, early recurrence and poor survival.
  • chemotherapeutic drugs are substrates for BCRP, which results in their efflux from and reduced accumulation within the cells.
  • An affected drug of particular interest is 5-fluorouracil (5-FU), which is currently part of the treatment regimen for PDAC patients. Therefore, the discovery that APE1 knockdown affects BCRP expression is crucial when looking at future drug combinations to improve survival in PDAC.
  • APE1-targeted agents with 5-FU in tumors genetically similar to Pa02C should respond favorably to this combination due to reduced BCRP expression.
  • a study in colon cancer stem cells indeed demonstrated dramatically increased cell killing when 5-FU and an inhibitor of APE1, APX3330, were used in vivo.
  • NOTCH3 a highly conserved member of the eponymous Notch signaling pathway, has been implicated in cell survival, proliferation, differentiation, development and homeostasis. Increased Notch3 protein levels have been identified as a prognostic marker for PDAC patients, and leads to increased tumor invasion, metastasis and shortened patient survival. Because of this, Notch3 has become a target for novel cancer therapies. ⁇ -secretase inhibitors and DLL4-inhibiting antibodies both target proteins upstream of Notch3, leading to the inhibition of the Notch signaling pathway.
  • Notch3 as being affected by APE1 opens up the possibility of combining APE1-targeted therapies with these inhibitors to enhance (in Pa03C) or counteract (in Pa02C) the effects of APE1 inhibition on NOTCH3 expression and function in PDAC.
  • COMMD7, ITGA1, RAB3D and TNFAIP2 showed decreased expression in all four patient cell lines ( FIG. 16D ).
  • COMMD7, ITGA1, RAB3D and TNFAIP2 have all been shown to be upregulated in various cancers including PDAC. While it cannot be assumed these changes will be universal in all PDAC samples, this consistency suggests that some of these genes could make promising targets or biomarkers for APE1-based therapy or combination therapies that potentially will be useful across multiple PDAC tumor subtypes and in other tumor types.
  • these genes represent a fraction of the genes identified in this initial Example affected by APE1 knockdown.
  • 3D tumor spheroid cultures were grown in DMEM growth media supplemented with 5% FBS (Hyclone, Logan, Utah) and containing 3% Reduced Growth Factor Matrigel (RGF, BD Biosciences) in ultra low-attachment 96-well plates (Corning Life Sciences) as described in Sempere et al., Cancer biology & therapy 2011, 12(3), 198-207; Arpin et al., Mol Cancer Ther 2016, 15(5), 794-805; and Logsdon et al., Mol Cancer Ther 2016, 15(11), 2722-2732.
  • FBS Hyclone, Logan, Utah
  • REF Reduced Growth Factor Matrigel
  • tumor cells were stably transduced with TdTomato (red channel), and CAFs were stably transduced with EGFP (green channel).
  • TdTomato red channel
  • EGFP green channel
  • 3D spheroid cultures were analyzed on Days 4, 8 and 12 after plating using Thermo ArrayScan high-content imaging system as described in Logsdon, Mol Cancer Ther 2016, 15(11), 2722-2732 and Lindblom et al., Toxicologic pathology 2012, 40(1), 18-32.
  • 3D culture images were obtained by the ArrayScan system at 2.5 ⁇ magnification with filters for TdTomato and EGFP. Quantification of tumor and CAF intensity and area was accomplished using 2D projections of these 3D images.
  • Spheroids were treated on Days 4 and 8 following ArrayScan analysis/imaging.
  • spheroid cultures were grown with Panc10.05 tumor cells alone or in the presence of CAFs (cancer-assoicated fibroblasts).
  • Pa03C cells were plated into 3D cultures alone or with CAF19 cells.
  • Spheriods were treated with increasing concentrations of napabucasin, vehicle (DMSO), APX3330 at 25 ⁇ M or 35 ⁇ M or combination of napabucasin and APX3330 on days 4 and 8 following ArrayScan analysis/imaging. Tumor cell growth in these spheroids was measured via fluorescence intensity (as well as area, data not shown) on days 4, 8, and 12 after plating.
  • 3D cultures were treated with APX3330 (top row), APX2009 (middle row), or APX2014 (bottom row) following measurements on days 4 and 8.
  • APX3330 and its second generation compounds reduced cell growth, cell proliferation.
  • APX2009 and APX2014 appeared as effective as APX3330 even when administered at a lower dosage.
  • Example 6 the combination of APX330 and the STAT3 inhibitor, napabucasin (BB1-608-STAT3 inhibitor), was analyzed for its tumor killing ability in a patient-derived 3D spheroid model of pancreatic cancer as described in Example 6.
  • the combination of APX3330 and napabucasin had a synergistic tumor killing effect.
  • Example 6 combination therapy with APE1/Ref-1 inhibitors in a PDAC 3D co-culture model prepared as in Example 6 was analyzed.
  • Pa03C and Panc10.05 tumor cells were grown in 3D cultures in the presence of CAFs. Spheroids were treated with either single agents, vehicle (DMSO) or combination of targeted agents on days 4 and 8 (black arrows), and the intensity of tumor (red) and CAF (green) were quantified as described in Example 7 every 3-4 days in culture.
  • the combination of APX3330 and napabucasin had a synergistic tumor killing effect on pancreatic tumor cells.
  • Example 6 the combination of APX330 and the CA9 inhibitor,SLC-0111, was analyzed for its tumor killing ability in a 3D co-culture pancreatic cancer tumor model prepared as described in Example 6.
  • Pa03C and Pancl0.05 tumor cells were grown in 3D cultures in the presence of CAFs (cancer-associated fibroblasts). Spheroids were treated with either single agents, vehicle (DMSO) or combination of targeted agents on Days 4 and 8, and the area of tumor (red) and CAF (green) were quantified following 12 days in culture. Results are shown in FIGS. 23A-23E .
  • Pa03C and Panc10.05 tumor cells were grown in 3D cultures in the presence of CAFs. Spheroids were treated with either single agents, vehicle (DMSO) or combination of targeted agents on Days 4 and 8 (black arrows), and the area of tumor (red) and CAF (green) were quantified following 12 days in culture. Results are shown in FIGS. 24A-24C .
  • Immunohistochemistry with vimentin as a marker for the CAFs was used to ensure that the combination treatment was not killing all the CAFs in the co-culture model. Staining for vimentin was performed at sacrifice.
  • Tissues were fixed overnight at room temperature in 10% NBF after which they were transferred through graded concentrations of alcohol to xylene inside a Leica Automated Vacuum Tissue Processor. Tissues were embedded in paraffin before being cut into 5-mm thick sections, mounted onto positively charged slides, and baked at 60° C. The slides were then deparaffinized in xylene and rehydrated through graded alcohols to water. Antigen retrieval was performed by immersing the slides in a Target Retrieval Solution (Dako) for 20 minutes at 90° C. (in a water bath), cooling at room temperature for 10 minutes, washing in water, and then proceeding with immunostaining.
  • Dako Target Retrieval Solution
  • Treatment of the implanted tumors started on day 11 post implant.
  • the co-cultures implanted included 2.5 ⁇ 10 6 tumor cells +/ ⁇ 5 ⁇ 10 6 CAFs, providing a 1:2 ratio of tumor cell to CAF.
  • the tumors had an initial average tumor size of about 200 mm 3 .
  • the mice were then administered either 50 mg/kg APX3330 BID in 4% Cr:EtOH, 50 mg/kg Rux SID pm in 4% Cr:EtOH, or combinations of the agents.
  • Treatment schedule consisted of treating for 5 days and then giving 2 days off treatment until the tumors reached an average size of 2000 mm 3 .
  • mice With no treatment, the mice reached an average tumor size of 2700 mm 3 at day 26, with Rux or APX3330 treatment alone, the mice reached an average size of 1750 m 3 at day 28, and with the combination therapy, the mice reached an average size of 1200 mm 3 at day 31.
  • FIG. 29A Immune competent mice were injected with mouse C26 colon cancer cells in the caecum ( FIG. 29A ). Animals were treated with either oxaliplatin or oxaliplatin with APX3330 and tumor size determined compared to vehicle controls ( FIG. 29B ). There was a dramatic and significantly increased tumor cell killing the in oxaliplatin and APX3330 treated mice compared to the mice treated with oxaliplatin alone ( FIGS. 29B & 29D ). Additionally, APX3330 treatment alleviated oxaliplatin induced loss of myenteric neurons in the colon of the CRC mice ( FIG. 29C ).
  • MC-38 cells (Yunhua Liu) were seeded in a 96-well tissue culture plate at 2000 cells/well in DMEM+10% FBS and grown overnight at 37° C., 5% CO 2 . Media was exchanged with DMEM+5% FBS drug media containing Napabucasin (SELLECK CHEMICALS) serially diluted 1:2 in a 5-point spread of 750 nM to 47 nM and spiked with APX2014 at EC30 (3.0 uM), or APX2014 EC10 (2.0 uM), or alone for single agent. Cells were incubated for 72 hours at 37° C., 5% CO 2 .
  • Napabucasin SELLECK CHEMICALS
  • FIG. 30A Media was exchanged with DMEM+5% FBS+10% Alamar blue fluorescent cell viability indicator (InvitrogenTM) and incubated 4 hours at 37° C., 5% CO 2 and then read on a fluorescent reader (SynergyTM H4 BioTek). Results are shown in FIG. 30A .
  • FIG. 30B shows APX2014 single agent effect. Data shown is the average of 3 separate cytotoxicity assays; each assay normalized to media only control.
  • Colo-201 (Yunhua Liu) was seeded in a 96-well tissue culture plate at 2000 cells/well in RPMI+Sodium Pyruvate+10% FBS and grown overnight at 37° C., 5% CO 2 .
  • 2 ⁇ Drug Media RPMI+Sodium Pyruvate+5% FBS was added at dosages of APX3330 (Apexian) in a 5-point spread from 75 uM to 6.3 uM and spiked with CPI-613 (Apexbio Technology) at 75 uM, or 50 uM, or alone for single agent.
  • Cells were incubated 72 hours at 37° C., 5% CO 2 and then 10% Alamar blue fluorescent cell viability indicator (INVITROGENTM) was added directly to plate.
  • FIG. 31A shows APX3330 and CPI-613 single agent effects.
  • FIG. 31B shows APX3330 and CPI-613 synergistic combo effects.
  • FIG. 31C shows APX3330 and CPI-613 EC50 (CalcuSyn).
  • FIG. 31D depicts Chou-Talalay Index (CI) of dose combinations (CalcuSyn).
  • FIG. 31E depicts synergistic drug combinations (CalcuSyn) of APX3330 spiked with 50 uM CPI-613 or 75 uM CPI-613.
  • Drug combination synergy was observed at APX3330 dosages of 75 uM and 50 uM when spiked with 50 uM CPI-613. Synergy was observed at all but one APX3330 dosage (6.3 uM) when spiked with 75 uM CPI-613. Data shown is the average of 3 separate cytotoxicity assays; each assay normalized to media only control.
  • HTC-116 (Yunhua Liu) was seeded in a 96-well tissue culture plate at 2000 cells/well in DMEM+10% FBS and grown overnight at 37° C., 5% CO 2 .
  • Drug Media DMEM+5% FBS was added at dosages of APX3330 (Apexian) in a 5-point spread from 75 uM to 6.3 uM and spiked with CPI-613 (Apexbio Technology) at 75 uM, or 50 uM, or alone for single agent. Cells were incubated for 72 hours at 37° C., 5% CO 2 .
  • FIG. 32A shows APX3330 and CPI-613 single agent effects.
  • FIG. 32B shows APX3330 and CPI-613 synergistic combo effects.
  • FIG. 32C shows APX3330 and CPI-613 EC50 (CalcuSyn).
  • Figure d32D depicts Chou-Talalay Index (CI) of dose combinations (CalcuSyn).
  • 32E depicts synergistic drug combinations (CalcuSyn) of APX3330 spiked with 50 uM CPI-613 or 75 uM CPI-613.
  • Drug combination synergy was observed at APX3330 dosages of 75 uM and 50 uM when spiked with 50 uM CPI-613.
  • Synergy was observed at all but one APX3330 dosage (6.3 uM) when spiked with 75 uM CPI-613.
  • Data shown is the average of 3 separate cytotoxicity assays; each assay normalized to media only control.
  • HTC-116 (Yunhua Liu) was seeded in a 96-well tissue culture plate at 2000 cells/well in DMEM+10% FBS and grown overnight at 37° C., 5% CO 2 .
  • Drug Media DMEM+5% FBS was added at dosages of APX3330 (Apexian) from 100 uM to 0.4 uM in a 10-point spread and spiked with CPI-613 (Apexbio Technology) at 100 uM, or 75 uM, or alone for single agent. Cells were incubated for 72 hours at 37° C., 5% CO 2 .
  • FIG. 33A shows APX3330 and CPI-613 single agent effects.
  • FIG. 33B shows APX3330 and CPI-613 synergistic combo effects.
  • FIG. 33C shows APX3330 and CPI-613 EC50 (CalcuSyn).
  • FIG. 33D depicts Chou-Talalay Index (CI) of dose combinations (CalcuSyn).
  • 33E depicts synergistic drug combinations (CalcuSyn) of APX3330 spiked with 100 uM CPI-613 or 75 uM CPI-613. Drug combination synergy was observed at all APX3330 dosages when spiked with 100 uM CPI-613. Synergy was observed at APX3330 dosages 100 uM-12.5 uM when spiked with 75 uM CPI-613. Data shown is the average of 3 separate cytotoxicity assays; each assay normalized to media only control.
  • HTC-116 (Yunhua Liu) was seeded in a 96-well tissue culture plate at 2000 cells/well in DMEM+10% FBS and grown overnight at 37° C., 5% CO 2 .
  • Drug Media DMEM+5% FBS was added at dosages of APX2014 (Apexian) in a 5-point spread from 25 uM to 1.6 uM and spiked with CPI-613 (Apexbio Technology) at 75 uM, or 50 uM, or alone for single agent. Cells were incubated for 72 hours at 37° C., 5% CO 2 .
  • FIG. 34A shows APX2014 and CPI-613 single agent effects.
  • FIG. 34B shows APX2014 and CPI-613 synergistic combo effects.
  • FIG. 34C shows APX2014 and CPI-613 EC50 (CalcuSyn).
  • FIG. 34D depicts Chou-Talalay Index (CI) of dose combinations (CalcuSyn).
  • 34E depicts synergistic drug combinations (CalcuSyn) of APX2014 spiked with 50 uM CPI-613 or 75 uM CPI-613. Drug combination synergy could not be ascertained at APX2014 dosages when spiked with 50 uM CPI-613. Synergy was observed at only one APX2014 dosage (12.5 uM) when spiked with 75 uM CPI-613. Data shown is the average of 3 separate cytotoxicity assays; each assay normalized to media only control.
  • HTC-116 (Yunhua Liu) was seeded in a 96-well tissue culture plate at 2000 cells/well in DMEM+10% FBS and grown overnight at 37° C., 5% CO 2 .
  • Drug Media DMEM+5% FBS was added at dosages of APX3330 (Apexian) from 100 uM to 0.4 uM in a 10-point spread and spiked with CB-839 (Sigma-Aldrich) at 1000 nM, or 500 nM, or alone for single agent. Cells were incubated for 72 hours at 37° C., 5% CO 2 .
  • FIG. 35A depicts APX3330 and CB-839 single agent effects.
  • FIG. 35B depicts APX3330 and CB-839 synergistic combo effects.
  • FIG. 35C shows APX3330 and CB-839 EC50 (CalcuSyn).
  • FIG. 35D shows Chou-Talalay Index (CI) of dose combinations (CalcuSyn).
  • 35E depicts synergistic drug combinations (CalcuSyn) of APX3330 spiked with 1000 nM CB-839 or 500 nM CB-839 (5-pt only).
  • Drug combination synergy was observed at APX3330 dosages 100 uM-25 uM when spiked with 1000 nM.
  • Synergy was observed at APX3330 dosages 100 uM-50 uM when spiked with 500 nM CB-839.
  • Data shown is the average of 3 separate cytotoxicity assays; each assay normalized to media only control.
  • the BLCAb001 (cisplatin resistant) cell line was treated with increasing concentrations of APX2014 and cisplatin as single agents and in combination and assayed in a 96-hour viability assay.
  • the concentrations of APX2014 range from 6 mM-0.38 mM in combination with the indicated cisplatin doses ( FIG. 36A ).
  • Doses of 6 mM-3 mM were shown to be synergistic with combination indexes of >1.0.
  • the concentrations of Cisplatin as a single agent range from 2.5 mM-0.04 mM ( FIG. 36B ).
  • the BLCAb002 (cisplatin sensitive) cell line was treated with increasing concentrations of APX2014 and cisplatin as single agents and in combination and assayed in a 96-hour viability assay.
  • the concentrations of APX2014 range from 6 mM-0.38 mM in combination with the indicated cisplatin doses ( FIG. 37A ).
  • Doses of 6 mM-1.5 mM were shown to be synergistic with combination indexes of >1.0.
  • the concentrations of cisplatin as a single agent range from 2.5 mM-0.04 mM ( FIG. 37B ).
  • T24 bladder cancer cells were treated with increasing concentrations of napabucasin in the presence or absence of APX2014 (2.5 or 5.0 mM) for 72 hours. The cells were then fixed, stained with methylene blue and relative cell number was calculated via spectrophotometry. Results are shown in FIGS. 38A & 38B .
  • T24 bladder cancer cells were treated with increasing concentrations of napabucasin in the presence or absence of APX2009 (2.5 or 5.0 mM; 3.5 or 7 mM) for 72 hours. The cells were then fixed, stained with methylene blue and relative cell number was calculated via spectrophotometry. Results are shown in FIGS. 39A & 39B .
  • SCaBER bladder cancer cells were treated with increasing concentrations of napabucasin in the presence or absence of APX2014 (2.5 or 5.0 mM) for 72 Hrs. The cells were then fixed, stained with methylene blue and relative cell number was calculated via spectrophotometry. Results are shown in FIGS. 40A & 40B .
  • SCaBER bladder cancer cells were treated with increasing concentrations of napabucasin in the presence or absence of APX2009 (2.5 or 5.0 mM; 3.5 or 7 mM) for 72 hours. The cells were then fixed, stained with methylene blue and relative cell number was calculated via spectrophotometry. Results are shown in FIGS. 41A & 41B .
  • siRNA Transfections PDAC cells were transfected with siRNA as previously described in Logsdon et al. (2016 Mol Cancer Ther 15(11):2722-2732), Fishel et al. (2011 Mol Cancer Ther 10(9):1698-1708), and Arpin era al. (2016 Mol Cancer Ther 15(5):794-805).
  • siRNAs used were scrambled control and siAPE1/Ref-1 (SEQ ID NOS:1-3), as well as OriGene (Rockville, Md.) Trisilencer siCA9.
  • APE1/Ref-1 redox signaling was inhibited using APX3330, APX2009, and APX2014 (Apexian Pharmaceuticals; Indianapolis, Ind.), with RN7-58 (Apexian Pharmaceuticals) used as a negative control that, although structurally similar, does not inhibit APE1/Ref-1 redox signaling activity (Shah et al. 2017 NPJ Precision Oncology 1; Kelley et al., 2017 Neural Regen Res 12(1):72-74; Kelley et al., 2016 J Pharmacol Exp Ther 359(2):300-039; Fishel et al., 2011 Mol Cancer Ther 10(9):1698-1708).
  • ChIP Chromatin Immunoprecipitation
  • IP Immunoprecipitation
  • HBS HIF-1-Binding Site
  • Primer sequences used for ChIP qPCR were: CA9 HBS-Fwd (5′-CTCACTCCACCCCCATCCTA-3′)(SEQ ID NO:32) and CA9 HBS-Rev (5′-GGACCGAGGGAGACAACTAG-3′) (SEQ ID NO:33). 1% of the cross-linked DNA from each sample was evaluated (without IP) as a control to normalize the qPCR signal across samples (Input).
  • qRT-PCR mRNA levels were measured using qRT-PCR as previously described in Logsdon et al. (2016 Mol Cancer Ther 15(11):2722-2732), Fishel et al. (2011 Mol Cancer Ther 10(9):1698-1708), Fischer et al. (2015 J Biol Chem 290(5):3057-3068).
  • the comparative Ct method was used to quantitate mRNA levels using RPLPO and B2M as reference genes.
  • the primers for CA9, RPLPO, and B2M are commercially available (Applied Biosystems). Experiments were performed in triplicate for each sample.
  • Immunohistochemistry 3D spheroid cultures were collected on day 12 after plating, fixed with 4% paraformaldehyde (PFA) (Electron Microscopy Sciences; Hatfield, Pa.), and permeabilized with 70% ethanol. Fixed/permeabilized 3D cultures were solidified in HistoGel (LifeTech). HistoGel plugs were paraffin embedded and slides were prepared by the laboratory of Dr. Keith Condon (Indiana University School of Medicine; Indianapolis, Ind.). Samples were stained with the specified antibodies by the Indiana University School of Medicine Research Immunohistochemistry Facility (Indianapolis, Ind.).
  • CA9 is well-established as a hypoxia-regulated enzyme, the level of CA9 expression induced under hypoxic conditions is variable between patient lines. Therefore, the relative CA9 expression in a selection of low-passage patient-derived PDAC cell lines (10.05, Pa02C, and Pa03C) was determined following 24 hrs exposure to 0.2% oxygen, as compared to cells incubated in normoxic conditions. Hypoxia exposure significantly induced CA9 protein levels in all cell lines (2.5-21.5-fold), including cancer-associated fibroblast cells (CAF19) ( FIG. 42A ).
  • CA9 was most strongly induced in the 10.05 cells (21.5-fold over normoxia), and Pa03C cells had the lowest levels of hypoxia-induced CA9 protein (2.5-fold over normoxia). Notably, APE1/Ref-1 expression was not significantly affected by hypoxia exposure in these cells. The majority of mechanistic experiments were evaluated in 10.05 cells because of their robust CA9 induction and were repeated in the CA9-weak Pa03C cells to confirm and compare responses.
  • APE1/Ref-1 and CA9 expression was evaluated in 3D spheroid cultures to determine whether the growth and survival of PDAC cells in this relevant microenvironment was dependent upon CA9 and APE1/Ref-1 expression.
  • Spheroids were collected on day 8 to confirm the continued knockdown of CA9 and APE1.
  • Each siRNA significantly reduced the expression of its target gene/enzyme product, confirming the continued knockdown of these enzymes throughout the duration of the 3D cultures.
  • APE1/Ref-1 knockdown also decreased CA9 expression to a similar extent to that seen in siCA9 cultures ( FIG. 42D FIG. 1D ).
  • APE1/Ref-1 and/or CA9 significantly slowed 3D tumor spheroid growth by ⁇ 50-80% (p ⁇ 0.001) as measured by fluorescence intensity and area ( FIGS. 42E and 42F ). These results confirm the importance of APE1/Ref-1 and CA9 expression in PDAC tumor growth. Additionally, APE1/Ref-1 knockdown slowed 3D tumor spheroid growth significantly more than CA9 knockdown, which indicated that inhibition of CA9 alone may not be as efficient at attenuating PDAC tumor growth as dual-targeting these enzymes.
  • IPs Immunoprecipitations of HIF1 ⁇ demonstrated a 4.3-fold increase in HIF1 ⁇ binding to the HIF-1-Binding Site (HBS) in the CA9 promoter under hypoxic conditions, which was decreased by ⁇ 60% in cells treated with APX3330 ( FIGS. 42G and 42H ).
  • HBS HIF-1-Binding Site
  • hypoxia-induced CA9 mRNA and protein levels were evaluated in 10.05 cells following treatment with APX3330, APX2009, APX2014, and the inactive analog RN7-58.
  • Inhibition of APE1/Ref-1 with all three inhibitors resulted in concentration-dependent decreases in hypoxia-induced CA9 mRNA and protein levels, with 10-fold less required for APX2009 and APX2014 vs. APX3330 ( FIGS. 43A and 43B ), indicating that these analogs were more potent inhibitors of APE1/Ref-1 redox signaling than APX3330.
  • the inactive analog (RN7-58) did not affect hypoxia-induced CA9 expression even at 100 ⁇ M, further confirming the selective contribution of APE1/Ref-1 redox signaling activity to the effects seen with the other compounds.
  • APE1/Ref-1 redox inhibition was also measured in 3D tumor spheroids. 10.05 cells were grown in 3D cultures for 12 days and treated on days 4 and 8 with APX3330, APX2009 and APX2014, or the inactive analog (RN7-58). APE1/Ref-1 redox inhibition significantly decreased the expression of CA9 protein in 3D tumor cultures in a concentration-dependent manner ( FIG. 43C ). Importantly, the APX2009 and APX2014 APE1/Ref-1 inhibitors required 10-fold less of the concentration compared to APX3330 to attenuate CA9 expression in the spheroid cultures, further validating the potency of these compounds. The inactive analog (RN7-58) did not affect CA9 expression in PDAC spheroid cultures, once again corroborating the specificity of the effects of the APE1/Ref-1 redox signaling inhibitors on HIF1 ⁇ activity.
  • CA9 expression is important for tumor cell growth, and CA9 functions by stabilizing intracellular pH to counteract the acidification that occurs in response to metabolic changes under hypoxic conditions.
  • As a functional marker for CA9 activity the effects of CA9 on intracellular pH were evaluated. Hypoxia exposure (0.2% O 2 for 48 hrs) did not significantly affect intracellular pH in 10.05 cells ( FIGS. 43D and 43E ), indicating that these cells compensate for the effects of hypoxia on pH.
  • CA9 expression was reduced via siRNA, the result was a significant decrease in intracellular pH in hypoxia-exposed cells, as measured by increased fluorescence of the pH-sensitive pHrodo Red AM dye ( FIGS. 43D and 43E ).
  • APX3330 and SLC-0111 did not affect intracellular pH as single-agents at concentrations up to 50 ⁇ M APX3330 or 100 ⁇ M SLC-0111, instead requiring the combination of both compounds to acidify hypoxic PDAC cells. Therefore, the APX3330 analogs, APX2009 and APX2014, were used to determine whether APE1/Ref-1 redox inhibition alone can shift intracellular pH in hypoxic PDAC cells given a sufficiently potent inhibitor. Treatment with either 8 ⁇ M APX2009 or 5 ⁇ M APX2014 alone resulted in a significant increase in fluorescence (normalized to cell survival), indicating decreased intracellular pH with single-agent APE1/Ref-1 redox signaling inhibition ( FIGS.
  • a more potent analog of CA9 inhibitor, SLC-0111, FC12-531A exhibited LC 50 s ⁇ 15-fold lower than SLC-0111 in this 3D tumor spheroid model ( FIGS. 43H and 43I , Table 7), demonstrating improved potency in its tumor growth-inhibitory effects over SLC-0111.
  • APX2009 and APX2014 were more potent as single agents compared to the parent compound, APX3330.
  • the analogs, APX2009 and APX2014 could be used at much lower concentrations to achieve a better combinatory effect.
  • hypoxia markers CA9 and Glucose Transporter 1 showed positivity in distinct regions ( FIGS. 44E and 44F ), indicating differential zones of hypoxia within the spheroid cultures.
  • APE1/Ref-1 Redox Signaling Inhibition Sensitized 3D PDAC Tumor Spheroids to CA9 Inhibition with Second-Generation Inhibitors
  • Combination treatment with APX3330 and SLC-0111 significantly attenuated tumor cell growth with minimal effects on the CAFs in the spheroid co-cultures at Day 12 of co-culture in 3D co-cultures containing both PDAC tumor cells and CAFs.
  • the time in culture was extended to 16 days and assayed for growth after each treatment.
  • the combination therapy was more effective than monotherapy in both patient-derived cell lines.
  • SLC-0111 was also combined with APX2009 at 10 ⁇ M or APX2014 at 0.6 ⁇ M in 3D co-cultures, which showed similar results as with APX3330 at 50 ⁇ M.
  • FC12-531A SLC-0111 analog
  • FC12-531A SLC-0111 analog
  • 3 ⁇ M FC12-531A monotherapy significantly affected tumor cell growth in Pa03C co-cultures, but not in 10.05 co-cultures
  • FC12-531A significantly enhanced the effects of APX3330, APX2009, and APX2014 on 3D tumor cell growth in both 10.05 and Pa03C co-cultures ( FIGS. 45A-45R ).
  • results demonstrate an arm of the APE1/Ref-1 regulatory node connecting APE1/Ref-1 redox signaling through HIF-1-mediated transcription to CA9 expression and activity ( FIG. 46 ).
  • results presented herein expand the significance of this signaling axis using novel analogs of clinical compounds to dual-target APE1/Ref-1 redox signaling and CA9 activity in 3D PDAC tumor cultures, resulting in enhanced killing of tumor cells in spheroid co-cultures.
  • the results presented herein also show for the first time that hypoxia-induced interactions between HIF-1 and the promoter of one of its major transcriptional targets are decreased following APE1/Ref-1 redox signaling inhibition ( FIG. 42C ), providing a key bridge in the understanding of APE1/Ref-1 contributions to HIF-1-mediated transcription.

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