Quantitative Chemotherapeutic Profiling of Gynecologic Cancer Cell Lines Using Approved Drugs and Bioactive Compounds

Heterogeneous response to chemotherapy is a major issue for the treatment of cancer. For most gynecologic cancers including ovarian, cervical, and placental, the list of available small molecule therapies is relatively small compared to options for other cancers. While overall cancer mortality rates have decreased in the United States as early diagnoses and cancer therapies have become more effective, ovarian cancer still has low survival rates due to the lack of effective treatment options, drug resistance, and late diagnosis. To understand chemotherapeutic diversity in gynecologic cancers, we have screened 7914 approved drugs and bioactive compounds in 11 gynecologic cancer cell lines to profile their chemotherapeutic sensitivity. We identified two HDAC inhibitors, mocetinostat and entinostat, as pan-gynecologic cancer suppressors with IC50 values within an order of magnitude of their human plasma concentrations. In addition, many active compounds identified, including the non-anticancer drugs and other compounds, diversely inhibited the growth of three gynecologic cancer cell groups and individual cancer cell lines. These newly identified compounds are valuable for further studies of new therapeutics development, synergistic drug combinations, and new target identification for gynecologic cancers. The results also provide a rationale for the personalized chemotherapeutic testing of anticancer drugs in treatment of gynecologic cancer.


Introduction
The five main gynecologic cancers, including ovarian, cervical, uterine, vaginal, and vulvar, correspond to 12% (94,990) of new female cancer diagnoses annually in the United States [1]. Of those, uterine endometrial, ovarian, and cervical are the most prevalent, with ovarian being the fifth leading cause of death from cancer for females in the United States [2]. In 2018, it is estimated that there will be 22,240 new ovarian cancer cases (2.5% of all female cancer cases) and 14,070 ovarian cancer deaths (5% of all female cancer deaths) [2]. The high case-to-fatality ratio exhibited in ovarian cancer can be attributed to late-stage diagnosis, lack of effective drug therapies, and tumor heterogeneity. Thus, it is important to discover new therapeutics for ovarian cancers that can improve survival in latestage ovarian cancer patients.
While ovarian cancer is usually diagnosed at later stages of disease, resulting in a low 5-year survival of 29% for distant-stage disease, cervical cancer is typically diagnosed at early stages and thus has more favorable outcomes [2]. However, in 2017, it was found that cervical cancer death rates have been underestimated due to the prior inclusion of women who have had hysterectomies [3]. Additionally, and importantly, this study identified a large disparity in race, where black women were dying at a 77% higher rate (10.1 in 100,000 vs. 5.4 in 100,000) while white women were dying at a 47% (4.7 in 100,000 vs. 3.2 in 100,000) higher rate than previously calculated without the hysterectomy exclusion criteria. Thus, cervical cancer remains a critical driver of mortality in women.
Placental cancers, or gestational trophoblastic disease (GTD) choriocarcinomas, are another type of gynecologic cancer. Gestational carcinomas arise from the fetal-derived layer of cells called the trophoblast that surrounds an embryo [4] and are rare, with an incidence ranging from approximately 1 in 15,000 to 50,000 [4,5]. A combination of surgery, radiation, and chemotherapy is the common treatment modality for gynecologic cancers [6].
There is currently a set of standard anticancer drugs used in the clinic to treat gynecologic cancers. For ovarian and cervical cancer, these include chemotherapy agents gemcitabine, cisplatin, and doxorubicin as well as targeted therapeutics such as topotecan, a topoisomerase inhibitor, and bevacizumab, a monoclonal antibody directed against vascular endothelial growth factor [7,8]. While cisplatin is the most active and effective drug for ovarian cancer, resistance quickly develops, and many patients die with platinumresistant cancer [9]. For placental cancer, methotrexate, a dihydrofolate reductase inhibitor, or Actinomycin D, a transcription inhibitor, is often used [10]. Combination therapy is common with a platinum-based compound given along with paclitaxel, a tubulin inhibitor [11,12]. In addition to the compounds above, vaccine, antibody, and cell-based immunotherapies are being considered as treatments for gynecologic and other solid tumor cancers [13]. Despite great progress in developing novel solutions to improve the therapeutic outcome for treatment of gynecologic cancers, more work needs to be done to understand the varied responses to different drugs in patients with different gynecologic cancers [14].
To understand the diversity in compound efficacy across gynecologic cancers within individual cancer groups and identify new active compounds, we have screened 7914 compounds consisting of approved drugs and bioactive compounds using a quantitative high-throughput screening (qHTS) method against 11 unique gynecologic cancer cell lines derived from ovarian, cervical, and placental cancers. The results were analyzed to profile the chemotherapeutic activities of compounds against these gynecologic cancer cell lines. Our data demonstrate the commonality and diversity in responses of gynecologic cancers to the anticancer agents. We have also identified a group of non-anticancer compounds with antigynecologic cancer activities that can be further studied for target identification and drug development.

Assay Development
To determine the inhibitory effects of approved drugs and bioactive compounds on the common gynecologic cancer cell lines, 11 cell lines including 7 ovarian cancer lines (CAOV-3, SK-OV-3, SW 626, ES-2, PA-1, TOV-21G), 3 cervical cancer lines (HeLa, Ca Ski, and C-33 A), and 2 placental cancer lines (JAR, JEG-3) were used in the drug repurposing screen with HEK 293T cells as a control line to determine selectivity index of anticancer compounds (SI) [15][16][17] (Table 1; Supplementary Figure 1). The optimal assay conditions for the ATP content cell viability assay were determined in the ovarian PA-1 ( Figure  1A

High-Throughput Compound Screening and Hit Confirmation
Following optimization, we next screened a collection of 7914 compounds including the FDA-approved drugs and bioactive compounds in 11 cancer cell lines shown in Table 1 (Supplementary  Figure 1; Pubchem AID 1345084). From the primary screen, 256 hits were identified with the criteria of IC 50 less than 10 μM, efficacy greater than 50%, and three-fold greater selectivity over the HEK 293T cells. From the primary screen, the signal-to-basal ratio was 9.30, coefficient of variation was 13.2% and Z' factor was 0.69 in the PA-1 cell line. For the CAOV-3 cell line, the signal-to-basal ratio was 9.86, coefficient of variation was 11.3%, and Z' factor was 0.71. Among the primary hits tested in a follow-up screen (Pubchem AID 1345085), 205 compounds were confirmed using criteria of IC 50 less than 30 μM, efficacy greater than 70%, and five-fold greater selectivity over HEK cells. A group of hits that were toxic to both cancer cells and HEK 293T cells was designated as the pan-toxic compounds (Supplementary Figure 4 and Table 2). The pan-cytotoxic compounds included panobinostat [19], givinostat [20], irestatin 9389 [21], NVP-BGT226 [22], vorinostat [23], TG-46 [24], NVP-TAE684 [25], and ponantinib [26]. The concentration-response curves for panobinostat (IC 50

Chemotherapeutic Diversity Among 11 Gynecologic Cancer Cell Lines
To further evaluate the 205 confirmed compounds in the 11 gynecologic cancer cell lines, we focused on the tissue types of these cancer cell lines to analyze the selectivity and diversity of compound activity. This analysis revealed two compounds, mocetinostat [27][28][29] (IC 50 = 2.76 ± 1.98 μM; SI N100) and entinostat [30,31] (IC 50 = 7.11 ± 6.62 μM; SI N100), both class I HDAC inhibitors and in clinical trials, as pan-killers of all three cancer cell groups (Figures 2A, 3, and Table 3). The ovarian and placental cancer cell line selective inhibitors included actinomycin D [32] (IC 50 = 0.78 ± 0.222 μM; SI N100), a DNA intercalator and common drug for GTD, and fedratinib [33] (IC 50 = 13.1 ± 7.51 μM; SI N100), a JAK2 inhibitor (Supplementary Figure 6 and Table 3). The ovarian and cervical cancer cell line selective inhibitors included TG-89 [24] (IC 50 = 11.2 ± 7.28 μM; SI N100), a JAK2 inhibitor, and CCT137690 [34] (IC 50 = 20.0 ± 7.02 μM; SI N100), an Aurora kinase inhibitor (Supplementary Figure  7 and Table 3). For the individual cancer types, the top ovarian cancer cell selective inhibitor was fostamatinib [35] (IC 50 = 6.24 ± 4.06 μM; SI N100), a Syk kinase inhibitor (Supplementary Figure 8A-D and Table 3). The top placental cancer line inhibitor was berberine [36,37] (IC 50 = 4.41 ± 0.662 μM; SI N100), an anti-parasitic alkaloid targeting Complex I of the mitochondrial respiratory chain and AP-1 machinery (Supplementary Figure 8E-H and Table 3). The cervical cancer selective inhibitory compounds found in our study were also active for the ovarian cancer cells. Compound profiling for gynecologic cancer lines Gorshkov et al.  Given that we included different numbers of cell lines for each of three gynecologic cancer groups, we assessed the number of compounds whose SI was greater than five ( Figure 2B) in each group. Interestingly, while there were only 2 placental lines included in the study, 13 compounds reached an SI of 5 or greater in this group. Four compounds killed all three cervical cancer lines selectively, and only one compound, fedratinib, selectivity killed all six ovarian cancer lines. Fedratinib, one of the ovarian and cervical CCL selective inhibitors, has completed two Phase I clinical trials for solid tumors (ClinicalTrials.gov Identifier: NCT01836705; NCT01585623) but is not an FDA-approved drug. The heat maps for each cancer tissue group provided a high-level view of the SI for each compound that fulfilled the criteria ( Figure 2C-E). These maps reveal that PA-1, TOV-21-G, and HeLa cells, the faster growing lines (Table 1), were more sensitive for qHTS as the compounds exhibited higher inhibitory activities.

Single Cancer Cell Line Selective Compounds
In addition to finding compounds with general antineoplastic activity, the selective inhibitory activities of compounds to individual cell lines were evaluated. We identified five compounds with selective inhibitory activities for PA-1, two compounds for TOV-21-G, and four compounds for HeLa ( Figure 4 and Table 4). As mentioned above, these cell lines were the most susceptible to anticancer compounds because of their fast cell growth rates. We did not find selective compounds that only exhibited inhibitory activities to any of the eight remaining cancer cell lines individually. Since we performed a detailed analysis of the compounds' concentration-response curves,  Table 4 for the full list of the best compounds from the confirmation screen.

Top Clinically Relevant Compounds
The results from our qHTS gynecologic cancer profiling revealed a diverse set of compounds with potencies ranging from the nanomolar to micromolar and different selectivity among three types of cancer tissues. We wanted to highlight these nanomolar compounds which may be useful to researchers and clinicians alike as these are the ones with anticancer activity to likely be far below their blood plasma concentrations, Cmax, in patients. We analyzed our data to uncover the number of compounds with less than 1 μM potency and greater than 70% efficacy regardless of selectivity. The data correspond with the similar trend for cytotoxic susceptibility in PA-1 (43 compounds), TOV-21-G (19 compounds), and HeLa (33 compounds) cells (Supplementary Figure 9A). We arranged the data to reflect how many cell lines have a number of compounds with a potency less than 1 μM. These data show that only one compound, the multitargeted HDAC inhibitor panobinostat (IC 50 = 0.355 ± 0.268 μM; SI = 0.92 ± 0.57), exhibited sub-μM potency in every cancer cell line among 11 cancer cell lines tested (Supplementary Figure 9B).
To provide useful information with clinical relevance, we have analyzed the IC 90 s, the concentration needed to inhibit 90% of growth, of these potent compounds and correlated it to the relevant human plasma concentration of the drug. The most potent and effective drug we identified without taking selectivity into account was panobinostat. In one clinical trial, panobinostat's median Cmax human plasma concentration after oral administration was measured to be 0.061 μM (range 0.038-0.119 μM) [42]. In an independent study, intravenous administration of panobinostat at doses from 1.20 to 20.0 mg/m 2 resulted in a Cmax of 0.107 to 2.24 μM [43]. The IC 50 of panobinostat for the ovarian, cervical, and placental lines in our study is 0.343, 0.224, and 0.516 μM, respectively. The IC 90 average for all cell lines is 0.719 μM, within the range of the intravenous, but not oral, Cmax values.
Bortezomib, a 20S proteasome inhibitor, exhibited an average IC 50 of 0.150 μM with good efficacy in 8 of the 11 cancer cell lines excluding SKOV-3, HeLa, and JAR. Its average IC 90 was 0.218 μM, well within the intravenous dose Cmax of 580 nM [44]. Elesclomol, a ROS inducer, was active in six cell lines with an IC 50 of 0.173 μM and an IC 90 of 0.283 μM. The Cmax of elesclomol in a clinical trial ranged from 1.32 to 12.84 μM with doses of 44 to 438 mg/m 2 [45]. Thus, elesclomol is a good clinically relevant candidate for gynecologic cancers. Actinomycin D, mentioned previously as an FDA-approved drug for multiple cancers, exhibited nanomolar potency against six cell lines as well while maintaining high selectivity for cancer cell lines. The average IC 90 for Actinomycin D in our study against ES-2, CAOV3, PA-1, TOV-21-G, SK-OV-3, and Ca Ski was 512 nM, while the Cmax in a pediatric population can range from 4 to 97.2 nM after 15 minutes of exposure to the drug [46]. Another trial measured a Cmax ranging from 2.5 to 79 nM, indicating that the IC 90 identified in our study is several-fold above what can be achieved in human blood plasma [47]. The extended comparison of IC 90 to Cmax values for the most promising clinical candidates from Supplementary Figure 9 is presented in Table 5.

Discussion
Heterogeneous responses in gynecologic cancers to chemotherapeutic drugs make it challenging to predict the drug's clinical effectiveness.   Table 4 for the full list of the most effective compounds for a single cell line. This heterogeneity arises from differences in patient genetic background, patient age, tumor microenvironment, treatment regimen, and intrinsic resistance to drug therapy. In general, overall cancer incidence and death rates for women have been falling since the 1930s [2,48]. Ovarian cancer death rates peaked in 1970 at 10.6 deaths per 100,000 women and in 2015 stood at 7.1 deaths per 100,000 women [48]. Uterine cancer, including cervix and corpus, however, killed 37.6 women per 100,000 in 1932 and now stands at 7.1 deaths per 100,000 women [48]. The last few years have seen a slight rise in death rates for uterine cancers from 6.5 in 2009 to 7.1 in 2015 [48]. Ovarian cancer's 5-year survival rates remain among the lowest survival rates of all female cancer types, rising slowly from 1975 (36% survival) to 2013 (47% survival) [49]. Furthermore, the development of selective chemotherapeutics that are selectively toxic to cancer cells is an ongoing mission in the cancer therapeutic research field. Understanding the differences and similarities in the chemotherapeutic responses of different gynecologic cancer cell types through chemotherapeutic profiling can aid in the development of safer, more effective therapies for these types of cancers. In this work, we have utilized a qHTS approach to profile the chemotherapeutic responses and selectivity of 11 gynecologic cancer cell lines to known chemotherapeutic molecules as well as other approved drugs and biologically active compounds.
We assessed the cytotoxicity of 7914 compounds consisting of approved drugs, drug candidates tested in clinical trials, and bioactive compounds in six ovarian, three cervical, and two placental cancer cell lines. Two Class I HDACIs, mocetinostat and entinostat, were identified and confirmed as pan-gynecologic cancer inhibitors with high degrees of efficacy and selectivity (SI N100) in all three cancer groups. Interestingly, we did not find other HDACIs to be as selective except for these two. Indeed, panobinostat, givinostat, and vorinostat, three other HDAC inhibitors, were found to be equally toxic to HEK 293T cells in our screens in addition to suppressing the 11 gynecologic cancer cell lines. HDACIs prevent the removal of acetyl groups on histone lysines and, in effect, open chromatin structure to modulate gene expression [50]. Generally, epigenetic pathways are modified by HDACIs to cause changes in the expression of genes which can induce cell-cycle arrest or apoptosis [51]. In addition to regulating histone acetylation, HDACIs can inhibit the function of nonhistone effectors such as transcription factors to modulate gene expression.
In order to advance the compounds identified from a drug repurposing screen to potential clinical trials, the blood plasma concentration of the drug should be a few-fold higher than its IC 50 value or similar to or below its IC 90 value in the cells of the newly identified indication. We researched the human Cmax values of our most broadly potent compounds and compared them to the experimental IC 90 values in this study. In most cases, our experimental IC 90 is at or below the human plasma concentration, indicating that the effective drug concentration against the new indication is achievable in patients. Mocetinostat has a Cmax of approximately 21.4 μM at 10 mg/kg and 75.7 μM at 40 mg/kg in humans [52], while entinostat in humans reached a Cmax of 0.46 μM with 15 mg [53]. For mocetinostat, whose IC 50 in our work was found to be 2.76 ± 1.98 μM, this indicates that the Cmax is well above its anticancer activity. For entinostat, however, although the patient Cmax is significantly lower than the average IC 50 achieved in our study (7.11 ± 6.62 μM) for gynecologic cancers, its in vivo activity could possibly be achieved in higher doses or with compound structure-activity optimization. It is possible that the low toxicity of mocetinostat and entinostat is due to their specific HDAC isotype selectivity for certain HDACs. Both are class I HDAC inhibitors but exhibit varying IC 50 s for specific HDACs. For example, mocetinostat was found to inhibit only HDAC 1/ 2/3/11 at low micromolar potency or below [54]. On the other hand, entinostat exhibited submicromolar potency against HDAC 1/2/3 only [55]. Their similar isotype selectivity profiles correlate with their similar in vitro effects against gynecologic cancers in our study. This HDAC isotype selectivity may be related to the drugs' activity against the gynecologic cancer cell lines as HDAC 1/2/3 have been implicated in ovarian tumor malignancy and growth [56], while HDAC2 is overexpressed in cervical cancer carcinogenesis [57].
We also identified single cell line selective compounds with submicromolar potency and high selectivity for PA-1 (ovarian), TOV-21-G (ovarian), and HeLa (cervical), which could be due to their faster growth rates compared to other cancer cell lines and the cell cycle-interrupting nature of many compounds. Empirically, cells which cycle faster are more susceptible to interruptions of cell growth at different cycle stages [58]. However, certain drugs may act by disrupting specific cycle stage progression, i.e., G 0 to G 1 [59]. It is known that certain drugs are specific to certain phases. For example, 5-fluorouracil interrupts S phase by reducing thymidylate content for DNA synthesis [60], docetaxel interrupts M phase by preventing microtubule polymerization [61,62], and seliciclib interrupts G1 phase by inhibiting CDKs 2/7/9 [63]. In this screen, PHA-793887 [64], a CDK2/1/4/9 inhibitor, was found to be potently toxic to PA-1 specifically, while milciclib [65], another CDK2 selective inhibitor, was specifically toxic to TOV-21-G with nanomolar potency. Both of these two CDK inhibitors suppress the cell growth phase.
The control cell line in this study, HEK 293T, is a normal human cell line originating from human embryonic kidney cells that is typically used as control cell line. The selectivity values determined in this study were relevant to the cytotoxicity of the compounds in HEK 293T cells. Given a different control line, the resulting selectivity may be different. The in vivo toxicity of compounds may also be different from the in vitro SI data. The selectivity reported here is for reference, and it should be noted that it cannot replace the data obtained from in vivo drug safety experiments and in clinical trials. We acknowledge the unequal numbers of lines for each cancer group (ovarian, cervical, and placental). Having fewer lines in one group will potentially increase the number of compounds that are pankillers for that particular group. This is evident in the larger number of compounds that killed both placental lines as compared to the number of compounds that killed all six ovarian lines. The results of this study warrant further investigation into the different responses cancers have to similar classes of compounds. Here, different HDAC inhibitors exhibit differential selectivity. This could possibly be due to differences in HDAC class specificity, with some inhibitors targeting class I HDACs preferentially to class II HDACs, for example [66]. Of the 19 compounds found to be pankillers for all or some of the cancer groups, only three are FDAapproved drugs including Actinomycin D, nebupent [67], and cyclosporin A [68]. Of these, only Actinomycin D is an FDAapproved antineoplastic, while nebupent is an antifungal targeting Topoisomerase II and cyclosporin A is an immunosuppressant targeting calcineurin. Actinomycin D has been used as an alternative chemotherapeutic regimen for ovarian cancer [69] and GTD (placental cancer) [12]. As nebupent disrupts mitotic activities, it has been researched as an antineoplastic agent in vivo against adenocarcinomic human alveolar basal epithelial (A549 cells) and colorectal carcinoma (HCT116 cells) xenografts in combination with chlorpromazine [70] but is not used as an anticancer therapy in the clinic nor has it been used in the study of gynecologic cancer. Lastly, cyclosporin A showed no efficacy for platinum-resistant ovarian cancer in one Phase II trial [71]. In another trial studying drugresistant gynecologic cancer, however, patients had an overall response rate of 29% after cyclosporin A treatment, and it was well tolerated [72]. Future work will seek to understand chemotherapeutic selectivity in more advanced models such as tumor spheroids, organoids, and in vivo xenograft models that could provide more physiologically relevant data on tumor killing.
Drug resistance to chemotherapy is a common cause for relapse and recurrence of many different types of cancers [73,74]. Platinum resistance is a common form of drug resistance in ovarian cancer with several suspected underlying causes including CDK expression, Akt signaling, and EGFR expression [75][76][77]. Our group recently published a set of compounds that were able to overcome cisplatin resistance in several platinum-resistant ovarian cancer cell lines when given alone and in combination with cisplatin [78]. The newly identified compounds in this study against gynecologic cancers can be used to further study the drugs' synergistic effects with the SOC anticancer drugs. Therefore, some of our hits may be of interest in studying how to overcome drug resistance in ovarian, cervical, and placental cancers using the synergistic drug combination with the SOC anticancer drugs.
In conclusion, the compounds identified and confirmed in this drug repurposing screen and profiling can be used to further investigate their utility in the treatment of gynecological cancer, especially for multidrug-resistant cancer patients. We demonstrate here the variability and heterogeneous responses of gynecologic cancer cells to anticancer drugs that may be related to patient genetic background, age, intrinsic drug resistance, and cancer aggressiveness. Two HDAC inhibitors identified in this study, mocetinostat and entinostat, may have high clinical relevance and can be moved to clinical trials as bona fide gynecologic cancer therapeutics. Indeed, entinostat in combination with avelumab is already in Phase I/II clinical trials for epithelial ovarian cancer, peritoneal cancer, and fallopian tube cancer (ClinicalTrials.gov: NCT02915523). Likewise, despite its toxicity to HEK 293T cells, panobinostat may be further studied in in vivo experiments due to its extremely high potency in gynecologic cancers. In conclusion, the chemotherapeutic profiling in individual cancer cells is an effective method to reveal the best anticancer therapeutics that might be particularly useful for those cancers with multidrug resistance, poor prognosis, and survival rates.

Cell Culture
Cells were kept in cryovials frozen at −150°C and thawed quickly in a 37°C water bath. A total of 1.5 million cells were seeded into T-225 flasks and subcultured once using TrypLE before freezing down for future experiments. For all assays, cells were seeded at 1000 cells per well into white, solid-bottom 1536-well plates using a Thermo Fisher Multidrop Combi reagent dispenser.

ATP Content Assay for Cell Viability, Growth Rate, and Positive Control Determination
The ATPlite luminescence assay system assay kit was used to determine cell viability. The reagent was reconstituted and prepared as described by the manufacturer. To measure the cell death caused by the compounds, cells were cultured in 4 μl of media for 16 hours at 37°C with 5% CO 2 in assay plates, followed by the addition of DMSO or 16 SOC chemotherapeutic compounds dissolved in DMSO. SOC compounds were dosed at 11 concentrations (1:3 dilution) in quadruplicate from 57.5 μM to 0.977 nM using the automated Wako 1536 Pin Tool workstation and incubated at 37°C with 5% CO 2 for 24, 48, or 72 hours. Four microliters of ATPlite, the ATP monitoring reagent, was then added to each well of the assay plates using the Multidrop Combi reagent dispenser followed by incubation for 15 minutes at room temperature. The resulting luminescence was measured using the ViewLux plate reader. Data were normalized for each drug using the largest luminescence value as 100% full cell viability (0% cell killing) and to the smallest luminescence value 0% viability (100% cell killing).
for the primary compound screen using the NPC [80] and NPACT drug libraries at NCATS. The OBGYN cancer and HEK 293T control cells were seeded into 1536-well assay plates at 1000 cells per 4 μl/well and incubated at 37°C in 5% CO2 for 48 hours. The ATPlite assay to determine the IC 50 values for each compound was conducted as described above. Plates were processed on the fully integrated Kalypsys robotic system. Hits were selected from the primary screen for follow-up confirmation, dosed in triplicate at 11 concentrations (1:3 dilution) from 57.5 μM to 0.977 nM, and incubated for 48 hours, and the ATPlite assay was used to determine the IC 50 values.

Statistical Analysis
Data analysis was performed using Microsoft Excel, and figures were generated using Prism Graphpad 7.0. In-house qHTS data normalization, correction, curve fitting, and classification were performed using custom programs developed at NCATS [81][82][83]. All data presented as mean ± S.D. unless otherwise stated.