Copper-Binding Small Molecule Induces Oxidative Stress and Cell-Cycle Arrest in Glioblastoma-Patient-Derived Cells

Article

Copper-Binding Small Molecule Induces Oxidative

Stress and Cell-Cycle Arrest in Glioblastoma-

Patient-Derived Cells

Graphical Abstract

Authors

Kenichi Shimada, Eduard Reznik,

Michael E. Stokes, ...,

H

N

Ana C. deCarvalho, Donald C. Lo,

Brent R. Stockwell

+

Cu(I/II)

S

Thiosemicarbazone

(NSC319726)

Correspondence

bstockwell@columbia.edu

Hypoxia-inhibitable ROS

In Brief

Shimada et al. report that the compound

NSC319726 arrests glioblastoma-patient-

derived cells at picomolar

R

N

NH

concentrations. The compound binds to

copper, generates ROS using ambient

oxygen, and depletes nucleotide pools.

This represents a new strategy for

potently blocking the growth of

glioblastoma.

N

XO

N

R

O

OH

Deoxyribosyl purines

Cell growth arrest

Patient-derived glioblastoma EC50: 12 pM – 25 nM

Highlights

d

Picomolar NSC319726 arrests growth of glioblastoma-

patient-derived cells

NSC319726 binds to copper to induce oxidative stress using

ambient oxygen

NSC319726-derived ROS target purine

deoxyribonucleosides to arrest cell cycle

Shimada et al., 2018, Cell Chemical Biology 25, 1–10

May 17, 2018 ª 2018 Elsevier Ltd.

https://doi.org/10.1016/j.chembiol.2018.02.010

Please cite this article in press as: Shimada et al., Copper-Binding Small Molecule Induces Oxidative Stress and Cell-Cycle Arrest in Glioblastoma-

Patient-Derived Cells, Cell Chemical Biology (2018), https://doi.org/10.1016/j.chembiol.2018.02.010

Cell Chemical Biology

Article

Copper-Binding Small Molecule Induces

Oxidative Stress and Cell-Cycle

Arrest in Glioblastoma-Patient-Derived Cells

Kenichi Shimada,^1,8Eduard Reznik,¹Michael E. Stokes,¹Lakshmi Krishnamoorthy,³Pieter H. Bos,¹Yuyu Song,⁷

Christine E. Quartararo,¹Nen C. Pagano,¹Darren R. Carpizo,⁴Ana C. deCarvalho,⁵Donald C. Lo,⁶

and Brent R. Stockwell^1,2,9,

*

¹Department of Biological Sciences, Columbia University, New York, NY 10027, USA

²Department of Chemistry, Columbia University, New York, NY 10027, USA

³Howard Hughes Medical Institute, Department of Chemistry, University of California, Berkeley, CA 94720, USA

⁴Rutgers Cancer Institute of New Jersey, New Brunswick, NJ 08903, USA

⁵Department of Neurosurgery, Henry Ford Hospital, Detroit, MI 48202, USA

⁶Center for Drug Discovery and Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA

⁷Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA 02115, USA

⁸Present address: Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA 02115, USA

⁹Lead Contact

*Correspondence: bstockwell@columbia.edu

https://doi.org/10.1016/j.chembiol.2018.02.010

SUMMARY

toxic to cells. As a result, cellular abundance of transition metals

is tightly regulated. Copper is the third most abundant transition

Transition metals are essential, but deregulation of metal in biological systems, after iron and zinc. Copper is a

redox-active metal like iron, and this property is exploited by en-

zymes, such as cytochrome c oxidase, superoxide dismutase,

and tyrosinase, which participate in many biological processes

their metabolism causes toxicity. Here, we report

that the compound NSC319726 binds copper to

induce oxidative stress and arrest glioblastoma-pa-

tient-derived cells at picomolar concentrations. Phar-

macogenomic analysis suggested that NSC319726

and 65 other structural analogs exhibit lethality

through metal binding. Although NSC319726 has

been reported to function as a zinc ionophore,

we report here that this compound binds to

copper to arrest cell growth. We generated and

¨

(Malmstrom and Leckner, 1998; Solomon et al., 1992). Copper

also controls lipolysis in adipocytes by regulating the activity of

cAMP-degrading enzyme phosphodiesterase PDE3B (Krishna-

moorthy et al., 2016). Also, dysregulation of copper metabolism

can cause pathologies. For example, genetic diseases such as

Wilson’s disease or treatment with some xenobiotic compounds

leads to copper accumulation, which causes toxicity, in some

cases by triggering oxidative stress (Gaetke and Chow, 2003;

validated pharmacogenomic predictions: copper Uriu-Adams and Keen, 2005).

In this study, we discovered that the thiosemicarbazone

toxicity was substantially inhibited by hypoxia,

through an hypoxia-inducible-factor-1a-dependent

pathway; copper-bound NSC319726 induced the

generation of reactive oxygen species and depletion

of deoxyribosyl purines, resulting in cell-cycle arrest.

These results suggest that metal-induced DNA dam-

age may be a consequence of exposure to some xe-

nobiotics, therapeutic agents, as well as other causes

of copper dysregulation, and reveal a potent mecha-

nism for targeting glioblastomas.

NSC319726 induces copper-dependent cell-cycle arrest at

picomolar concentrations in glioblastoma (GBM) cells. Using

pharmacogenomic and molecular and cell biology approaches,

we found that this compound functions in GBM cells as a copper

ionophore. Copper bound to NSC319726 causes the generation

of reactive oxygen species (ROS), and induces G1 cell-cycle

arrest.

RESULTS

NSC319726 Is a Potent Growth Inhibitor of Cancer Cells

GBM is one of the most common and lethal cancers (Dunn et al.,

2012). To identify mechanisms for treating this intractable

INTRODUCTION

Transition metals play essential and diverse roles in cell biology cancer, we performed small-molecule screening in 13 primary-

(Dudev and Lim, 2008; Waldron and Robinson, 2009; Williams, tumor-derived models from GBM patients using stem cell culture

2014). Redox-inactive metals, such as sodium and potassium, conditions in a high-throughput assay format (Quartararo et al.,

signal by changing their distributions quickly, while redox-active 2015). We discovered that NSC319726 is an extremely potent

metals, such as iron embedded within protein active sites, act as growth inhibitor, with half maximal effective concentrations

co-factors to aid in catalytic functions (Chang, 2015). Despite ranging from 12 pM to 25 nM across these models (Table 1).

their critical role, excess abundance of transition metals can be NSC319726 induces a cytostatic effect not only in GBM

Cell Chemical Biology 25, 1–10, May 17, 2018 ª 2018 Elsevier Ltd.

1

Please cite this article in press as: Shimada et al., Copper-Binding Small Molecule Induces Oxidative Stress and Cell-Cycle Arrest in Glioblastoma-

Patient-Derived Cells, Cell Chemical Biology (2018), https://doi.org/10.1016/j.chembiol.2018.02.010

Zn(II) modulation and sensitivity to NSC319726

A

Table 1. Sensitivity to NSC319726 and TP53 Mutation Status of

Patient-Derived GBM Cells

GBM Line

HF3037

HF2998

HF2885

HF2906

HF3026

HF2381

HF2876

HF3013

HF2476

HF2303

HF3177

HF2790

HF2941

EC₅₀(nM)

0.012

0.014

0.040

0.042

0.046

0.095

0.130

0.197

0.959

1.747

6.791

24.960

TP53 Mutation

WT

1.0

0.5

0.0

1.0

0.5

0.0

0.1% DMSO

25 μM Zn(II)

100 μM Zn(II)

0.1% DMSO

1 μM TPEN

4 μM TPEN

WT

R175H

WT

10^-1

10⁰

10¹

10²

10³

10^-1

10⁰

10¹

10²

10³

[NSC319726] (nM)

WT

B Non-apoptotic cell death inducers

V272M

WT

structurally similar to NSC319726

H

N

S

N

G245S

M133T

C242F

WT

N

H

NSC319726

CIL52

Cl

S

EC₅₀, half maximal effective concentration; WT, wild-type.

N

H

N

H

primary-tumor-derived samples, but also in HT-1080 ﬁbrosar-

coma cells, albeit at lower potency, indicating a potentially broad

spectrum of effectiveness. Since HT-1080 cells grow rapidly and

are more amenable to diverse assay formats compared with

GBM lines, we initially characterized the mechanism of action

of NSC319726 in this cell line. We synthesized the compound,

which showed equivalent potency to commercially available

batches, conﬁrming the identity of the compound (Figures

S1A–S1C).

CIL13

CIL64

C Co(II) is a NSC319726 suppressor

1.0

media

Co(II)

0.5

NSC319726 was originally discovered as a selective lethal

compound for cancer cell lines carrying allele-speciﬁc TP53

mutation, R175H (Yu et al., 2014; Lin et al., 2015). The gain-of-

function R175H mutation is one of the most frequent mutations

observed in TP53 gene, contributing to various properties of

transformed cancers, such as invasion, proliferation, and drug

resistance (Soussi and Wiman, 2007). p53^R175Hprotein has

decreased binding afﬁnity to Zn²⁺, which is required for DNA

binding, resulting in a change in protein conformation (Xu et al.,

2011). NSC319726 was reported to function as zinc metallocha-

perone (and thereby named ZMC1), increasing the intracellular

Zn²⁺pool to correct the p53^R175Hprotein conformation to that

of wild-type p53. It was found that cancers carrying p53^R175H

0.0

10^-1

10⁰

10¹

10²

10³

[NSC319726] (nM)

Figure 1. NSC319726 Is a Potent Growth Inhibitor of Cancer Cells

(A) The effect of zinc supplementation and chelation on sensitivity to

NSC319726.

(B) Structures of NSC319726 and similar previously reported non-apoptotic

cell-death inducers.

(C) The effect of 100 mM Co²⁺on NSC319726 toxicity. Error bars in (A and C)

indicate SEM of technical triplicates. See also Figures S1A–S1D.

First, we explored the hypothesis that NSC319726 might

rely on the ‘‘acquired functions’’ of the mutant protein for their cause zinc accumulation or interfere with p53 activity in

survival, thus NSC319726 kills these addicted cells. Since the GBM and HT-1080 cells. While Zn²⁺supplementation slightly

binding afﬁnity of p53^R175Hto Zn²⁺is diminished, the mutant pro- increased the compound’s efﬁcacy in these contexts, treatment

tein lacks Zn²⁺, which is required for DNA binding. NSC319726 with a speciﬁc Zn²⁺chelator, N,N,N’,N’-tetrakis(2-pyridinyl-

was shown to facilitate the binding of zinc to p53^R175Hby acting methyl)-1,2-ethanediamine (Verhaegh et al., 1998), did not sub-

as a zinc ionophore, which enables the mutant protein to recover stantially change its potency or efﬁcacy in HT-1080 cells or

its wild-type conformation (Yu et al., 2012, 2014).

GBM models, suggesting that the effect of NSC319726 is largely

NSC319726 acts as a zinc metallochaperone in cancers independent of binding to Zn²⁺in these cell models, while Zn²⁺

carrying p53^R175H. Knockdown of TP53 in these cells blocks supplementation slightly potentiated the effect of the compound

the compound’s efﬁcacy dramatically, strongly indicating the (Figure 1A). Moreover, we did not observe a connection between

role of correctly folded p53 involved in the mechanism of TP53 mutation status and the sensitivity to NSC319726 across

NSC319726 in these cells. However, other cancer cells carrying the 13 GBM models (Table 1). Although the latter analysis was

wild-type or different mutations of p53 exhibit sensitivity to performed with too few cells to conclusively ﬁnd associations

NSC319726, and the compound’s mechanism of action against between genotype and phenotype, we were motivated to seek

these cells is not clear. Therefore, we sought to deﬁne the mech- additional mechanisms underlying the cytostatic effect of the

anism of action of this compound in these contexts.

compound in these cell types.

2

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Please cite this article in press as: Shimada et al., Copper-Binding Small Molecule Induces Oxidative Stress and Cell-Cycle Arrest in Glioblastoma-

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Figure 2. NSC319726, 8-Hydroxyquinoline,

A

and Phenothiazine Share Similar Mecha-

nisms of Action against Cancer Cells

(A) Left: relative growth inhibition (GI₅₀) proﬁles

across the NCI-60 panel against 18 compound

clusters representing distinct mechanisms of ac-

tion of 2,565 cell-line-selective lethal compounds.

Right: relative GI₅₀proﬁles of 83 compounds in the

cluster represented by NSC319726.

(B) Four core scaffolds represented in the same

cluster as NSC319726.

(C) Median sensitivity of the 83 compounds

across the NCI-60 panel. The red dot indicates

NSC319726.

able large pharmacogenomic dataset to

identify biomarkers predicting drug sensi-

tivity, and reported that lethal compounds

whose potency vary across different cells

were informative for study of molecular

mechanisms (Shimada et al., 2016b).

B

C

The NCI-60 dataset contains basal

gene expression proﬁles of 60 cell lines,

as well as drug sensitivity for 6,529 com-

pounds (Shoemaker, 2006). Of these, we

focused on 2,565 cell line-selective com-

pounds, clustered them into 18 groups

based on the similarity of the drug sensi-

tivity across 60 cell lines, and found that

each cluster represents distinct mecha-

nisms (e.g., DNA-targeting agents, tyro-

sine kinase inhibitors, and ferroptosis

inducers) (Shimada et al., 2016b).

NSC319726 was included in the 2,565

cell-line-selective compounds tested in

the NCI-60 dataset, and these analyses

Examination of the structure of NSC319726 revealed that it revealed that NSC319726 clustered together with 82 other com-

is similar to three cytotoxic compounds that induce a non- pounds (Figure 2A). While these 83 compounds were clustered

apoptotic form of cell death (Shimada et al., 2016a) (Figure 1B). based on the similarity of the sensitivity proﬁle across cell lines,

These compounds were discovered in a screen speciﬁcally for the compounds in this cluster also share substantial structural

lethal molecules that induce regulated, non-apoptotic cell death similarities and are characterized by four core scaffolds (Fig-

(Shimada et al., 2016a). Their lethality in cancer cell lines was ure 2B). The ﬁrst two classes contain a semicarbazone and a het-

inhibited by binding to Co²⁺, although their mechanism of action eroatom (either nitrogen or sulfur), suggesting that these scaf-

was not fully elucidated. Due to the structural similarity, we folds bind to metal ions. Notably, NSC319726 and three

suspected that NSC319726 might share a similar mechanism structural analogs are also nitro- or thiosemicarbazones (Fig-

of action. Intriguingly, NSC319726’s cytostatic effect was ure 2B). As for the latter two classes, 8-hydroxyquinoline com-

strongly inhibited by supplementation with 100 mM Co²⁺, which pounds are known to form metal complexes (Prachayasittikul

is similar to the effect observed with these three reported com- et al., 2013), while phenothiazines are not reported to bind to

pounds (Figure 1C). Co²⁺is an essential transition metal, widely metals. Whether these compounds are capable of binding to

known for its function in a co-factor vitamin B₁₂. However, as metals or not, these 83 compounds were suspected to induce

holo-B₁₂supplementation did not suppress NSC319726’s similar lethality compared with the other 2,565 cell line-selective

lethality, depletion of Co²⁺from B₁₂is likely not the cause of lethal compounds, based on their growth inhibition proﬁles.

NSC319726’s cytotoxic effect (Figure S1D).

Among these, thio-/nitrosemicarbazones were more potent

than 8-hydroxyquinolines or phenothiazines, and, notably,

NSC319726 was one of the most potent compounds (Figure 2C).

Three Distinct Compound Scaffolds Share Similar

Lethal Mechanisms

WhileNSC319726exhibited picomolarpotencyinsomeGBM-pa- NSC319726 Induces Copper-Dependent Toxicity

tient-derived models, the difference in potency between the 13 The NCI-60 data analysis suggested that semicarbazones,

cell lines was >2,000-fold. We previously studied a publicly avail- including NSC319726, bind to metal ions to induce lethality in

Cell Chemical Biology 25, 1–10, May 17, 2018

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Figure 3. NSC319726 Induces Copper

A

B

Toxicity

(A) The effect of various metal supplementation on

the sensitivity to NSC319726 was seen in HT-1080

cells.

(B) The effect of Cu²⁺and/or Co²⁺supplementa-

tion on HT-1080 cells’ sensitivity to NSC319726.

Color code is the same as (A). In (A) and (B), testing

metals were treated at 2-fold dilution series with

100 mM as highest concentration, while Co²⁺and

NSC319726 were co-supplemented at ﬁxed con-

centrations, 100 mM and 31 nM, respectively.

(C) The effect of Cu²⁺modulation on the sensitivity

to NSC319726, 7Br8HQ, and MB.

(D) Intracellular metal quantiﬁcation upon

NSC319726/7Br8HQ/MB treatment.

C

D

(E) Intracellular metal quantiﬁcation upon

NSC319726 and/or Co²⁺supplementation.

(F) Time course measurement of copper and

zinc for 0, 3, 9, and 24 hr. Values in (D–F) were

normalized to inorganic phosphate quantity of the

same samples. Error bars in (B and C) are SEM of

technical triplicates, (D–F) are SEM of biological

triplicates. See also Figure S1E.

E

F

mentation was previously found to

be protective against NSC319726 in

TOV112D cells, similar to Co²⁺supple-

mentation in HT-1080 cells (Yu et al.,

2012). Due to this idiosyncratic effect of

iron in different cells, and the com-

pound-independent nature of Co²⁺inhibi-

tion of iron toxicity in HT-1080 cells, we

concluded that iron toxicity was not the

key mechanism of NSC319726 lethality

in GBM and HT-1080 cells.

To ensure that NSC319726’s interac-

tion with copper was relevant to its

cancer cells. We sought to identify the metal species responsible lethality, we treated cells with a dilution series of NSC319726

for this effect. Thiosemicarbazones have long been studied as a in medium supplemented with either Cu²⁺, in the absence or

potential anticancer agent, and their binding to transition metal presence of the Cu²⁺-speciﬁc chelator, triethylenetetramine

ions, particularly iron, zinc, and copper, is suggested to be the (TETA) (Figure 3C) (Lu, 2010). Consistent with the hypothesis

key for their lethal effect (Crim and Petering, 1967; Sartorelli that NSC319726 binds copper to induce its growth inhibitory

et al., 1977). To ﬁnd out if this is the case, we assessed if any effect, the copper chelator reversed the synergy between Cu²⁺

speciﬁc metal-binding is important for semicarbazones. A cell- and NSC319726. Two other compounds were tested in similar

permeable metal-binding compound acting as an ionophore conditions: 7-bromo-8-hydroxyquinoline (7Br8HQ) and methy-

decreases the concentration gradient across the plasma mem- lene blue (MB), representing the 8-hydroxyquinoline and pheno-

brane. It may deplete or overload the metal, depending on the thiazine scaffolds, respectively. 7Br8HQ was potentiated by

ratio between its intra- and extracellular concentrations. In either Cu²⁺and unchanged by TETA; MB was unchanged by either

scenario, supplementation of the corresponding metal ion (Figure 3C).

should alter the effect of NSC319726. We co-treated HT-1080

To evaluate the relationship between these three compounds

cells with NSC319726 and various metal ions in a concentration and the cellular accumulation of metals, we directly measured

series, and found that only Cu²⁺dramatically enhanced the the abundance of iron, copper, and zinc in HT-1080 cells using

growth inhibitory effect of the compound. This effect of Cu²⁺inductively coupled plasma mass spectrometry. Consistent

was diminished by the addition of Co²⁺(Figures 3A and 3B). with previous and earlier ﬁndings, Cu²⁺and Zn²⁺were signiﬁ-

While Fe²⁺and Fe³⁺supplementation also induced growth cantly increased upon treatment with either NSC319726 or

inhibition that was inhibited by Co²⁺co-treatment (Figure 3A), 7Br8HQ, whereas treatment with MB had no effect. Moreover,

and the iron-speciﬁc chelator deferoxamine suppressed NSC319726 speciﬁcally increased cellular copper abundance,

NSC319726’s effect (Figure S1E), the effect of iron supplementa- while 7Br8HQ increased the level of all three metal ions. Taken

tion was independent of NSC319726. Moreover, iron supple- together, these ﬁndings indicate that NSC319276 can function

4

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Please cite this article in press as: Shimada et al., Copper-Binding Small Molecule Induces Oxidative Stress and Cell-Cycle Arrest in Glioblastoma-

Patient-Derived Cells, Cell Chemical Biology (2018), https://doi.org/10.1016/j.chembiol.2018.02.010

due to the difference in metal binding speciﬁcity of the two

A

B

molecules. Metals that 7Br8HQ binds to but NSC319726 does

not, such as iron, may induce complete lethality achieved by

7Br8HQ. Thus, 7Br8HQ seems to induce two mechanisms of

lethality: a copper-dependent mechanism that is comparable

with NSC319726’s toxicity and a copper-independent mecha-

nism that is orthogonal to NSC319726’s toxicity.

Transcriptome Analysis Uncovered Gene Signatures of

Sensitivity and Resistance to NSC319726

In a prior NCI-60 analysis, we found that drug sensitivity proﬁles

are indicative of mechanisms of action, and that the transcrip-

tome can be used to successfully discover biomarkers of sensi-

tivity (Shimada et al., 2016b). Using the same approach, we

looked for pathways (entries in Gene Ontology, Kyoto Encyclo-

pedia of Genes and Genomes, Reactome, BioCarta, and

‘‘hallmarks’’ in the Molecular Signatures Database [MSigDB]

[Subramanian et al., 2005]) that serve as biomarkers for the

sensitivity of cells to compounds in the cluster containing

NSC319726 (Figure S2A). We discovered pathways that are

signiﬁcantly upregulated in cell lines sensitive or resistant to

this cluster (high signiﬁcance, corresponding to the x axis of

Figure S2B), which are also uniquely associated with this cluster

among the 18 clusters shown in Figure 2A (high speciﬁcity,

corresponding to y axis of Figure S2B).

C

E

D

We then measured gene expression changes after 24 hr of

10 mM NSC319726 treatment in the most sensitive (HF3037)

and resistant (HF2941) GBM-patient-derived cell models. We

asked if any of the pathways with high signiﬁcance and high

speciﬁcity in the NCI-60 dataset were up- or downregulated

in a meaningful way. We assumed that if genes in a pathway

overexpressed in NSC319726-resistant versus sensitive cells

in the NCI-60 panel were also upregulated in GBM cells upon

NSC319726 treatment, the pathway is likely to contribute to

cellular resistance to NSC319726. We found two pathways

satisfying these criteria, namely ‘‘tumor necrosis factor alpha

signaling via nuclear factor kB’’ and ‘‘hypoxia’’ (Figures 4A,

S2C, and S2D). These two pathways were also more upregu-

lated in resistant GBM cells (HF2941) than sensitive ones

(HF3037) in the basal state in both the NCI-60 and the GBM

cell panels, but they were also even more expressed upon

NSC319726 treatment in the two GBM cells; thus, we sus-

Figure 4. HIF-1a-Dependent Response to Hypoxia Induces Resis-

tance to NSC319726

(A) Summary of the pathway enrichment analysis.

(B) Effect of hypoxia on NSC319726-induced lethality. Error bars are SEM from

sigmoidal curve ﬁtting of a representative experiment.

(C) Effect of siHIF-1a on HIF-1a protein level (left) and cellular sensitivity to

NSC319726.

(D) Chemical induction of HIF-1a and cellular sensitivity to NSC319726.

(E) Schematic relationship between NSC319726 and hypoxia. Error bars in

(C and D) indicate SEM of technical triplicates. See also Figures S2 and S3.

as a speciﬁc copper and zinc ionophore, that 7Br8HQ is a non- pected that these pathways were functionally relevant to

speciﬁc transition metal ionophore, and that MB is not a metal the mechanism that cells use to acquire resistance to

chelator (Figure 3D). The increase in copper and zinc abundance NSC319726. We then evaluated how hypoxia might contribute

was suppressed by the addition of Co²⁺, suggesting that to resistance further.

NSC319726 binds to Co²⁺when the latter is present in excess

(Figure 3E). Copper levels signiﬁcantly increased as quickly as Hypoxia Suppresses NSC319726 through an HIF-

3 hr after NSC319726 treatment, and steadily increased up to 1a-Dependent Pathway

24 hr post treatment (Figure 3F).

We ﬁrst tested whether hypoxia made cells resistant to

The metal quantiﬁcation and cell viability assays after pertur- NSC319726 in four GBM models. Cells grown in hypoxia

bation of metal content suggest a couple of important features: (1.5% O₂) were more resistant to NSC319726 than cells grown

NSC319726 speciﬁcally binds to both copper and zinc, of which in normoxia (ambient, 21% O₂) by 100-fold in all four cell models

copper is speciﬁcally responsible for NSC319726’s cytotoxicity; tested (Figures 4B and S3A). As the transcriptional response to

7Br8HQ binds to several transition metals; the effect of MB is hypoxia is regulated in part by hypoxia-inducible factor 1a

independent of copper. Second, NSC319726 inhibited cell (HIF-1a), encoded by HIF1A gene, and copper can stabilize

growth and killed cells completely when Cu²⁺was further added HIF-1a by inhibiting its prolyl hydroxylation and subsequent

to the cell culture, while 7Br8HQ induced complete lethality degradation (Martin et al., 2005), we suspected that HIF-1a sta-

without copper supplementation. This discrepancy is possibly bilization might provide a cellular defense mechanism to

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NSC319726 Induces ROS Leading to Cell-Cycle Arrest

A

B

To further explore what causes cytostasis upstream of HIF-1a

upon NSC319726 treatment, we re-analyzed gene expression

changes in two GBM cell models treated with 10 mM

NSC319726. By comparing their expression proﬁles with those

from 1,698 experiments from chemical and genetic perturba-

tions collected in the MSigDB, we found that NSC319726

treatment of HF3037 and HF2941 GBM cell models induced

gene expression proﬁles similar to T24 bladder cancer

cells treated with hypericin-mediated photodynamic therapy

(Figure S4) (Buytaert et al., 2008). Photodynamic therapy is

chemotherapy consisting of the administration of photosensi-

tizing chemicals such as hypericin. The photosensitizing

compounds, preferentially taken up by cancers, absorb near

infrared light and transfer their energy to oxygen molecules,

generating singlet oxygen, which kills cells (Karioti and

Bilia, 2010).

D

C

Based on the similar transcriptome proﬁles, we hypothe-

sized that NSC319726 generates ROS, comparable with

photodynamic therapy. Semicarbazones were previously re-

ported to bind to and activate copper, facilitating redox cycling

between Cu⁺and Cu²⁺, leading to more efﬁcient ROS genera-

tion (Jansson et al., 2010); we suspected that NSC319726-

bound copper was more susceptible to redox changes.

Figure 5. NSC319726 Induces ROS Generation

(A) ROS measurement using CM-H₂DCFDA upon NSC319726 and/or Cu²⁺Notably, NSC319726-bound copper propagated ROS from

treatment.

hydrogen peroxide in a cell-free solution more efﬁciently than

(B) The effect of N-acetylcysteine (NAC) supplementation on the lethality of

the free unbound form (Figures 5A and S5A), supporting this

NSC319726.

hypothesis.

(C) Abundance of 2⁰-deoxyguanosine upon NSC319726 and/or Co²⁺supple-

To determine which ROS are involved in this cytotoxicity,

mentation.

cells were treated with both NSC319726 and one of several

antioxidants quenching different ROS; we found that N-acetyl-

cysteine rescued cells at 50 mM. While N-acetylcysteine is

not a very speciﬁc scavenger, other antioxidants (100 mM tro-

lox for lipophilic ROS, and 100 mM 4-hydroxy-TEMPO for

superoxide) showed little effect on NSC319726 lethality, indi-

(D) Cell-cycle analysis using Nuclear ID Red staining upon treatment of

NSC319726/7Br8HQ/MB. Error bars in (B) indicate SEM of technical tripli-

cates. See also Figures S4–S7.

NSC319726. A potent inhibitor of the NSC319726 lethality, Co²⁺

,

also stabilizes HIF-1a by inhibiting the interaction between cating that lipophilic hydroxyl radicals and superoxide were

HIF-1a and von Hippel-Lindau, an E3 ligase, ubiquitylating and likely not involved (Figures S5B and S5C). Moreover, a pan-

promoting HIF-1a degradation in response to oxygen, which caspase inhibitor, zVAD, or a necroptosis inhibitor, Necrosta-

may also contribute to the resistance (Yuan et al., 2003). We tin-1, did not suppress the cytotoxic effect of NSC319726,

conﬁrmed that HIF-1a protein was signiﬁcantly stabilized upon indicating that known regulated cell death phenotypes, such

both NSC319726 and Co²⁺treatment, supporting the hypothesis as apoptosis or necroptosis, were not involved (Figure S5D).

that HIF-1a may mediate cellular responses to NSC319726 Intriguingly, other scaffolds, 7Br8HQ and MB, also induce

(Figure S3B).

ROS generation detectable by CM-H₂DCFDA, and sup-

To explore more directly the role of HIF-1a in response to pressed by 50 mM N-acetylcysteine (Figures 5B and S5C–

NSC319726, HIF-1a expression was inhibited by small inter- S5E). These shared features suggest that the three com-

fering RNA knockdown in HT-1080 cells. Inhibition of HIF-1a pounds evoke ROS-induced cytostasis through a similar

expression restored sensitivity to NSC319726 under hypoxic mechanism, and explain why these molecules co-segregated

conditions, explaining the resistance previously observed (Fig- in the clustering analysis.

ure 4C). However, HIF-1a-mediated resistance was achieved

To further understand the implication of NSC319726-medi-

only in hypoxic conditions, because HIF-1a knockdown margin- ated ROS production on cellular metabolism, and to glean

ally sensitizes cells to NSC319726 in normoxic conditions, and insight into how these changes could result in cell-cycle arrest,

treatment with dimethyloxalylglycine, a compound that stabi- we performed untargeted metabolomic proﬁling of cells treated

lizes HIF-1a in normoxic conditions, did not alter NSC319726 with DMSO, NSC319726, DMSO/Co²⁺, and NSC319726/Co²⁺

sensitivity under normoxia (Figures 4D and S3B). These results for 6 hr. Across these four conditions, only NSC319726 treat-

indicate that the extent of the stimuli that NSC319726 triggers, ment induced lethality. Among the 505 metabolites identiﬁed

leading to cytostasis, varies between hypoxia and normoxia; and quantiﬁed, we looked for metabolites whose abundance

although HIF-1a tries to protect cells from NSC319726, the lethal was changed signiﬁcantly over the other conditions, and the

stimuli under normoxia are greater than stabilized HIF-1a can analysis revealed that purine deoxyribonucleosides/deoxyribo-

handle (Figure 4E).

nucleotides, namely, 2⁰-deoxyadenosine and its phosphate

6

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Please cite this article in press as: Shimada et al., Copper-Binding Small Molecule Induces Oxidative Stress and Cell-Cycle Arrest in Glioblastoma-

Patient-Derived Cells, Cell Chemical Biology (2018), https://doi.org/10.1016/j.chembiol.2018.02.010

DISCUSSION

Although thiosemicarbazones have been long recognized as

metal binding molecules and potential anticancer agents, their

mechanism of action is complicated because abundant transi-

tion metals in cells, i.e., iron, zinc, and copper, seem all relevant

in their mechanisms. However, the fact that various thiosemicar-

bazones showed similar drug sensitivity proﬁles in a NCI-60 cell

line panel indicates that their mechanism of action is similar over-

all. In this study, we focused on characterizing the mechanism of

action of one of the most potent, NSC319726. NSC319726 func-

tions as a copper ionophore that generates ROS to deplete

deoxyribosyl-purines and induce growth inhibition in multiple

cancer cell models (Figure 6).

To identify molecular pathways involved in NSC319726’s

lethality, we adopted a pharmacogenomic approach. While

Figure 6. Model of NSC319726-Induced Toxicity

Current model of NSC319726’s mechanism of action. NSC319726 binds to

large pharmacogenomic efforts such as the NCI-60 project

copper to induce ROS (indicated by a red arrow), possibly singlet oxygen, and

are often considered noisy and inconsistent, we previously

showed that proper ﬁltering of the data provides useful signals

(Shimada et al., 2016b). In this study, we illustrated how

such data can characterize the mechanism of action of a

arrests cell cycle. While two other scaffolds, 8-hydroxyquinoline and pheno-

thiazine, do not generate ROS through copper binding, they also generate

NAC-inhibitable ROS to induce cell-cycle arrest.

conjugates, 2⁰-deoxyguanosine, and 2⁰-deoxyinosine, were lethal compound. Combining the NCI-60 data with RNA

completely depleted upon NSC319726 treatment (Figures 5C sequencing experiments to detect gene expression changes

and S6), while pyrimidine deoxyribonucleosides and purine upon NSC319726 treatment, we identiﬁed biomarkers of sensi-

ribonucleosides/ribonucleotides were unaffected. There are tivity, which are upregulated. This approach can serve to iden-

two possibilities explaining this observation: ﬁrst, purine bases tify gene sets that are not only biomarkers, but functionally rele-

were selectively oxidized by NSC319726-copper complex, vant to mechanisms of action. Our discovery of HIF-1a making

consistent with prior works showing 8-oxodeoxyguanosine cells resistant to thiosemicarbazone-induced cytotoxicity has

´

not been reported before; however, structurally related bis(thio-

formation upon NSC319726 treatment (Angele-Martınez et al.,

2014; Yu et al., 2014). However, this cannot explain why deox- semicarbazone) complexed with Cu²⁺was reported to be accu-

yribosyl-purines were only depleted while ribosyl-purines were mulated in hypoxic regions in vivo and thus is exploited as a

intact. The second possibility is that ribonucleotide reductase hypoxia imaging agent (Price et al., 2011). Notably, its hypox-

(RNR) activity is inhibited by NSC319726. RNR is an enzyme ia-selective biodistribution is highly correlated with the Cu²⁺

/

catalyzing the formation of deoxyribonucleotides from ribonu- Cu⁺redox potential (Dearling et al., 2002). Susceptibility to

cleotides. Triapine, a thiosemicarbazone, was reported to switch between Cu⁺and Cu²⁺is also the key for toxicity of

inhibit RNR activity (Finch et al., 2000). Whatever the mecha- thiosemicarbazone-copper complex, suggesting that these

nisms of deoxyribosyl-purine depletion may be, we found G1 two phenomena are related. Since a potential anticancer activ-

cell-cycle arrest in HT-1080 cells 24 hr after NSC319726 treat- ity of bis(thiosemicarbazone) has also been suggested (Palani-

ment. As expected from NCI-60 analysis, 7Br8HQ and MB muthu et al., 2013), hypoxic cells should be tolerant to both

treatments also induced G1-arrest in HT-1080 cells after 24 hr scaffolds assuming that the toxic mechanism of thiosemicarba-

(Figure 5D), possibly induced by the same ROS as generated zone and bis(thiosemicarbazone) is similar. On the other hand,

by NSC319726 treatment.

normoxic cells are more susceptible to thiosemicarbazone-

induced cytotoxicity, while they may excrete bis(thiosemicarba-

zone) from cells more efﬁciently and achieve hypoxia-selective

accumulation of the compound.

NSC319726 Does Not Exhibit Neurotoxicity in

Differentiated SH-SY5Y Cells

One major concern toward clinical application for GBM treat-

To fully connect how the NSC319726-copper complex

ment is neurotoxicity. Thus, we utilized a SH-SY5Y human neu- induces cytostatic effect, the identiﬁcation of the precise ROS

roblastoma cell model to assess the neurotoxicity of NSC319726 species generated upon NSC319726-copper treatment target-

(Figure S7). Undifferentiated SH-SY5Y cells were more sensitive ing purine deoxyribonucleosides is required. We also want to

to all four lethal compounds with distinct mechanisms compared note that, although NSC319726-bound Cu²⁺is susceptible to

with the differentiated cells. Among them, a non-speciﬁc kinase propagate free radicals from hydrogen peroxide more efﬁciently

inhibitor staurosporine was only 4-fold selective between undif- than unbound Cu²⁺(Figure S5A), hydroxyl radicals may not be

ferentiated and differentiated cells, but DNA damaging agents, the same ROS generated in vivo. In regard to the exact ROS,

i.e., NSC319726 and type II topoisomerase inhibitor doxorubicin, it is tempting to propose that singlet oxygen is generated

were much more selective, and differentiated cells did not show in response to any of the three compounds (NSC319726,

substantial toxicity up to the highest tested concentrations. 7Br8HQ, and MB). However, unlike photodynamic therapy, the

Selective lethality in GBM and neuroblastoma over differentiated source of energy to generate singlet oxygen for this mechanism

and non-growing neurons is

NSC319726 for an anti-GBM agent.

a

desired characteristic of is unknown. There has been evidence reported that small-mole-

cule-bound copper behaves differently to target DNA, possibly

Cell Chemical Biology 25, 1–10, May 17, 2018

7

Please cite this article in press as: Shimada et al., Copper-Binding Small Molecule Induces Oxidative Stress and Cell-Cycle Arrest in Glioblastoma-

Patient-Derived Cells, Cell Chemical Biology (2018), https://doi.org/10.1016/j.chembiol.2018.02.010

through generation of singlet oxygen (Devasagayam et al., 1991; and 65 other structural analogs exhibit lethality through

Frelon et al., 2003; Jose et al., 2011; Li and Trush, 1993; metal binding, consistent with their chemical structures

Macomber et al., 2007). We also have evidence supporting the and reported activities. Supplementing with multiple metal

hypothesis that NSC319726-copper complex induces singlet ions, we found that NSC319726 binds copper to arrest cell

oxygen: (1) transcriptome analysis against the MSigDB revealed growth in GBM cells. Furthermore, pharmacogenomic

that the genes up- and downregulated upon NSC319726 treat- analysis of both the NCI-60 data and transcriptomic

ment were most signiﬁcantly correlated with that in hypericin- changes of GBM cells upon NSC319726 treatment sug-

mediated photodynamic therapy, which induces singlet oxygen gested that the copper toxicity induced by NSC319726

(Figure 4C); (2) among multiple ROS scavengers, speciﬁc antiox- was substantially inhibited by hypoxia, through an HIF-

idants targeting hydroxyl radicals, lipid peroxides, and superox- 1a-dependent pathway; we conﬁrmed this hypoxia-depen-

ide were not effective, but only N-acetylcysteine suppressed dent lethality in GBM patient samples using a hypoxia

NSC319726 cytotoxicity, but only at higher concentrations; (3) chamber. Treatment with copper-bound NSC319726 re-

lethal stimuli generated upon NSC319726 treatment are oxygen sulted in the generation of reactive oxygen species and a

pressure dependent, suggesting that oxygen molecules may depletion of deoxyribosyl-purines, including 2⁰-deoxygua-

directly contribute to ROS production; and (4) 2⁰-deoxyguano- nosine, resulting in G1 cell-cycle arrest. These data

sine is a known target of singlet oxygen (Jose et al., 2011; Li suggest that DNA damage is the primary consequence of

and Trush, 1993; Ravanat and Cadet, 1995). While these multiple copper-mediated oxidative stress, subsequently inducing

lines of evidence point toward singlet oxygen, in the absence of a cell-cycle arrest. Thus, copper dysregulation and metal-

plausible mechanism for the generation of singlet oxygen, this induced DNA damage may be a consequence of exposure

remains speculative.

to some therapeutic agents or xenobiotics. Moreover, this

However, and whatever ROS may be generated upon study highlights the power of a data-driven pharmacoge-

NSC319726 treatment, its picomolar potency to sensitive nomic approach to characterize mechanism of action of

GBM cells is a valuable property. Toward clinical application, small molecules.

it may be noteworthy that NSC319726’s effectiveness may

depend on the sex of the patients. Although our analysis based

STAR+METHODS

on 13 patient-derived GBM models was not powered for this

analysis (p value of 0.073 using Wilcoxon’s rank-sum test),

Detailed methods are provided in the online version of this paper

NSC319726 was more effective against GBM cells from female

and include the following:

patients than GBM cells from male patients (Experimental

Model and Subject Details describes the genders of the pa-

tients). While there are still certain obstacles to translating this

ﬁnding into a therapeutic agent, e.g., it was unclear whether

NSC319726 penetrates the blood-brain barrier, and what the

oxygen tension is in various GBM tissues, a sophisticated

drug delivery system to selectively administer drugs to GBM

cells along with oxygen might overcome such issues. Irrespec-

tively, these ﬁndings suggest that copper dysregulation can

induce oxidative stress and DNA damage, leading to cell-cycle

arrest. This may have applications in a variety of pathological

and therapeutic contexts.

d KEY RESOURCES TABLE

d CONTACT FOR REAGENT AND RESOURCE SHARING

d EXPERIMENTAL MODEL AND SUBJECT DETAILS

B Cell Lines and Tissue Culture

d METHOD DETAILS

B Synthesis of NSC319726

B Cell Viability Assay

B Sequencing of TP53 Gene of 13 GBM Primary Cells

B Screening for Lethal Compounds in 13 GBM Pri-

mary Cells

B Screening for a Responsible Metal in NSC319726-

Induced Cell Death

SIGNIFICANCE

B Inductively Coupled Plasma-Mass Spectrometry (ICP-

MS) for Metal Quantiﬁcation

Transition metals are essential for many cellular functions;

deregulation of their metabolism causes toxicity that may

be exploited for therapeutic gain. In this study, we report

that the compound NSC319726 binds copper to induce

oxidative stress and arrest glioblastoma (GBM)-patient-

derived cells at picomolar to nanomolar concentrations.

This effect was discovered through screening compounds

in 13 patient-derived GBM cell models. While NSC319726

has been reported to function as a zinc ionophore at micro-

molar concentrations in some cancer cell lines, we found

that it was not responsible for NSC319726’s cytotoxicity

to GBM cells. Therefore, we decided to adopt a data-driven

pharmacogenomic approach to identify likely mechanism

of action of NSC319726; through analysis of drug sensi-

tivity data and basal transcriptome of the NCI-60 human

cancer cell line panel, we hypothesized that NSC319726

B RNA-Seq Experiment

B HIF-1a Knockdown

B Hypoxia Induction

B Western Blotting

B ROS Detection in Cell Culture

B ROS Detection in Cell Free System

B Cell Cycle Assay

B Metabolomic Proﬁling

B Neurotoxicity Assays

d QUANTIFICATION AND STATISTICAL ANALYSIS

B Pharmacogenomic Analysis of the NCI-60 Data

B Processing of Raw Sequences from RNA-Seq

B Analysis of RNA-Seq Data

B Pathway Enrichment Analysis

B Predicting Functionally Relevant Pathways

d DATA AND SOFTWARE AVAILABILITY

8

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Please cite this article in press as: Shimada et al., Copper-Binding Small Molecule Induces Oxidative Stress and Cell-Cycle Arrest in Glioblastoma-

Patient-Derived Cells, Cell Chemical Biology (2018), https://doi.org/10.1016/j.chembiol.2018.02.010

SUPPLEMENTAL INFORMATION

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thiosemicarbazone): a potent inhibitor of ribonucleotide reductase activity

with broad spectrum antitumor activity. Biochem. Pharmacol. 59 , 983–991.

Supplemental Information includes seven ﬁgures and can be found with this

article online at https://doi.org/10.1016/j.chembiol.2018.02.010.

Frelon, S., Douki, T., Favier, A., and Cadet, J. (2003). Hydroxyl radical is not the

main reactive species involved in the degradation of DNA bases by copper in

the presence of hydrogen peroxide. Chem. Res. Toxicol. 16 , 191–197.

ACKNOWLEDGMENTS

We thank Anna Kaplan of Columbia University, Tom Mikkelsen of Henry Ford

Hospital, and Christopher Chang of University of California, and Ray Pagliarini

at Novartis Institutes for BioMedical Research, for helpful discussions. This

study was supported by funding from the Accelerate Brain Cancer Cure

(ABC2) foundation and NIH grants R35CA209896 and P01CA087497 (to

B.R.S.). L.K. was supported by NIH grant R01GM079465 and Howard Hughes

Medical Institutes.

Gaetke, L.M., and Chow, C.K. (2003). Copper toxicity, oxidative stress, and

antioxidant nutrients. Toxicology 189 , 147–163.

Hahne, F., LeMeur, N., Brinkman, R.R., Ellis, B., Haaland, P., Sarkar, D.,

Spidlen, J., Strain, E., and Gentleman, R. (2009). ﬂowCore: a bioconductor

package for high throughput ﬂow cytometry. BMC Bioinformatics 10 , 106.

Jansson, P.J., Sharpe, P.C., Bernhardt, P.V., and Richardson, D.R. (2010).

Novel thiosemicarbazones of the ApT and DpT series and their copper com-

plexes: identiﬁcation of pronounced redox activity and characterization of their

antitumor activity. J. Med. Chem. 53 , 5759–5769.

AUTHOR CONTRIBUTIONS

Conceptualization, K.S. and B.R.S.; Methodology, K.S., E.R., M.E.S., L.K.,

P.H.B., Y.S., and C.E.Q.; Software, K.S.; Formal Analysis, K.S.; Investigation,

K.S., E.R., M.E.S., L.K., P.H.B., Y.S., C.E.Q., and N.C.P.; Resources, A.C.d.C.,

P.H.B., and B.R.S.; Data Curation, K.S., E.R., M.E.S., L.K., C.E.Q., and N.C.P.;

Writing – Original Draft, K.S. and B.R.S.; Writing – Review & Editing, K.S.,

M.E.S., L.K., P.H.B., C.E.Q., D.R.C., D.C.L., and B.R.S.; Visualization, K.S.;

Supervision, B.R.S.; Project Administration, K.S.; Funding Acquisition, B.R.S.

Jose, G.P., Santra, S., Mandal, S.K., and Sengupta, T.K. (2011). Singlet oxy-

gen mediated DNA degradation by copper nanoparticles: potential towards

cytotoxic effect on cancer cells. J. Nanobiotechnology 9 , 9.

Karioti, A., and Bilia, A.R. (2010). Hypericins as potential leads for new thera-

peutics. Int. J. Mol. Sci. 11 , 562–594.

Klayman, D.L., Bartosevich, J.F., Grifﬁn, T.S., Mason, C.J., and Scovill, J.P.

(1979a). 2-Acetylpyridine thiosemicarbazones. 1. A new class of potential anti-

malarial agents. J. Med. Chem. 22 , 855–862.

DECLARATION OF INTERESTS

Klayman, D.L., Scovill, J.P., Bartosevich, J.F., and Mason, C.J. (1979b).

2-Acetylpyridine thiosemicarbazones. 2. N4,N4-Disubstituted derivatives as

potential antimalarial agents. J. Med. Chem. 22 , 1367–1373.

The authors declare no conﬂict of interest.

Received: June 29, 2017

Revised: January 2, 2018

Accepted: February 18, 2018

Published: March 22, 2018

Krishnamoorthy, L., Cotruvo, J.A., Jr., Chan, J., Kaluarachchi, H., Muchenditsi,

A., Pendyala, V.S., Jia, S., Aron, A.T., Ackerman, C.M., Wal, M.N., et al. (2016).

Copper regulates cyclic-AMP-dependent lipolysis. Nat. Chem. Biol. 12 ,

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cer: the p53 mutation paradigm. Cancer Cell 12 , 303–312.

Yuan, Y., Hilliard, G., Ferguson, T., and Millhorn, D.E. (2003). Cobalt inhibits the

interaction between hypoxia-inducible factor-a and von Hippel-Lindau protein

by direct binding to hypoxia-inducible factor-a . J. Biol. Chem. 278 ,

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(2005). Gene set enrichment analysis: a knowledge-based approach for inter-

10 Cell Chemical Biology 25, 1–10, May 17, 2018

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STAR+METHODS

KEY RESOURCES TABLE

REAGENT or RESOURCE

Antibodies

SOURCE

IDENTIFIER

Mouse monoclonal anti-alpha tubulin (DM1A)

Rabbit monoclonal anti-HIF1 alpha

Biological Samples

Santa Cruz Biotechnology

Abcam

Cat# sc-32293, RRID:AB_628412

Cat# ab51608, RRID:AB_880418

Patient-derived glioblastoma cells

Henry Ford Hospital

N/A

(Quartararo et al., 2015)

Chemicals, Peptides, and Recombinant Proteins

NSC319726

Selleck Chemicals

Sigma-Aldrich

Tocris Bioscience

Cat# S7149

Cat# 722049

Cat# M9140

Cat# 90460

Cat# B1125

Cat# V6629

Cat# D3695

Cat# 238813

Cat# 176141

Cat# A0737

Cat# C7352

Cat# 516813

Cat# 4309

7-bromo-8-hydroxyquinoline

methylene blue

Triethylenetetramine

Bathocuproinedisulfonic acid disodium salt (BCS)

Vitamin B₁₂

dimethyloxalylglycine

Trolox

4-hydroxy-TEMPO

N-acetylcysteine

L-Cystein

Hydrogen peroxide

N, N, N’, N’- tetrakis(2- pyridinylmethyl)- 1,

2- ethanediamine

NaCl

Sigma-Aldrich

Cat #S7653

Cat #P5405

Cat #M8266

Cat #442909

Cat #244589

Cat #380024

Cat #701122

Cat #8661

KCl

MgCl₂

CaCl₂,6H₂O

MnCl₂

FeCl₂,4H₂O

FeCl₃

CoCl₂,6H₂O

NiCl₂

Cat #339350

Cat #C3279

Cat #208086

Cat #G7532

CuCl₂,2H₂O

ZnCl₂

GdCl₃,6H₂O

Critical Commercial Assays

CM-H₂DCFDA

FxCycle PI/RNase staining solution

CellTiter-Glo

Thermo Fisher Scientiﬁc

Promega

Cat# C6827

Cat# F10797

Cat# G7572

Cat# A13261

FC-122-1001

PrestoBlue Cell Viability Reagent

TruSeq RNA prep kit

Deposited Data

Thermo Fisher Scientiﬁc

Illumina

Normalized RNA-seq data of patient derived

glioblastoma cells

This paper; Mendeley Data

https://doi.org/10.17632/2d8wzkcn3v.1

Metabolomic proﬁling data of HT-1080 cells

This paper; Mendeley Data

https://doi.org/10.17632/2d8wzkcn3v.1

Chemical structures of 83 compounds whose

drug sensitivity proﬁles across NCI-60 cell lines

are similar to NSC319726

(Continued on next page)

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Continued

REAGENT or RESOURCE

Experimental Models: Cell Lines

Human: HT-1080 cells

SOURCE

IDENTIFIER

ATCC

CCL-121

Human: SH-SY5Y cells

Oligonucleotides

CRL-2266

SMARTpool: ON-TARGETplus HIF1A siRNA

Negative Control siRNA

Software and Algorithms

Tophat (v2.0.4)

GE Dharmacon

QIAGEN

Cat# L-004018-00-0005

Cat# 1027310

Trapnell et al., 2009

Trapnell et al., 2010

https://ccb.jhu.edu/software/tophat/

index.shtml

Cufﬂinks (v2.0.2)

R (v3.2.1)

http://cole-trapnell-lab.github.io/cufﬂinks/

https://cran.r-project.org/

The Comprehensive

R Archive Network

ﬂowCore package (R/Bioconductor) (v1.40.3)

mclust package (R) (v5.2)

Hahne et al., 2009

http://bioconductor.org/packages/release/

bioc/html/ﬂowCore.html

Scrucca et al., 2016

https://cran.r-project.org/web/packages/

mclust/index.html

CONTACT FOR REAGENT AND RESOURCE SHARING

Further information about reagents and resources used in this study, please contact Brent Stockwell (bstockwell@columbia.edu).

EXPERIMENTAL MODEL AND SUBJECT DETAILS

Cell Lines and Tissue Culture

Collection of 13 patient-derived GBM samples were executed by Henry Ford Hospital as approved by the Institutional Review Board.

The use of patient-derived GBM cell culture was executed as approved by the Institutional Review Boards of Columbia University and

Henry Ford Hospital. Of 13 cells, 7 are from female patients (HF3037, HF2998, HF2885, HF2906, HF3026, HF2476, HF2790) and

6 from male (HF2381, HF2876, HF3013, HF2303, HF3177, HF2941).

Brieﬂy, GBM cells were defrosted and grown in T-25, T-75, or T-175 tissue-culture-treated ﬂasks as non-adhesive neurospheres in

a serum-free, DMEM/F12 base media (Invitrogen #11330-057) supplemented with N-2 (Invitrogen #17502048), Bovine Serum Albu-

min (Sigma-Aldrich #A4919), and recombinant human EGF and FGF (PeproTech #AF-100-15 and # 100-18B, respectively). GBMs

that failed to grow in suspension as neurospheres were supplemented with laminin (Sigma-Aldrich #L2020), added directly to the

ﬂask, at a concentration of 1 mL/cm². Cells were cultured at 37^ꢀC, 100% humidity, and 5% CO₂. Neurospheres were dissociated

via Dulbecco’s PBS and mechanical pipetting, while Accutase was used to detach GBMs grown on laminin. Upon dissociation, cells

were counted using a Beckman Coulter Vi-Cell Cell Viability Analyzer and re-plated in the afore-described conditions.

HT-1080 cells were acquired from ATCC. Cells were submitted for authentication to ATCC (sample #STRA3235) and veriﬁed as an

exact match for ATCC CCL-121 (HT-1080) on March 13^th2017. The cells grew at 37^ꢀC under 100% humidity, 5% CO₂. For mainte-

nance, HT-1080 cells were cultured in 1% non-essential amino acid and 10% fetal bovine serum containing Dulbecco modiﬁed

Eagle’s MEM (Gibco, #11995). One million cells were seeded per 50 mL in a T-175 ﬂask, and cells were trypsinized and reseeded

at 1:10 dilution to a new ﬂask every two days.

SH-SY5Y cell line was obtained from ATCC and passaged a few times before use. For maintenance, cells were cultured in

DMEM/F12 (ThermoFisher 10565042) supplemented with GlutaMAX, 10% heat-inactivated FBS, and Penicillin Streptomycin

(Pen Strep, ThermoFisher 15070063). When reaching 90% conﬂuency, cells were trypsinized and replated at 1:3 dilution. For

differentiation, cells were plated at 40% conﬂuency with maintenance media for 12 h, replaced with D1 media (DMEM/F12 +

GlutaMAX + 5% FBS + 10 mM retinoic acid + Pen Strep) for 5 days (fresh media change every 2 days), followed by D2 media

(DMEM/F12 + GlutaMAX + 50mg/ml BDNF + Pen Strep) for 3 days before drug treatment. Retinoic acid and BDNF were purchased

from Sigma-Aldrich (B3795-10UG and R2625-100mg, respectively).

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METHOD DETAILS

Synthesis of NSC319726

Scheme 1: Synthesis of NSC319726

Methyl Hydrazinecarbodithioate (1)

To a cooled solution of potassium hydroxide (6.60 g, 0.1 mol, 1.0 eq) in water (8 mL) and isopropanol (6.7 mL) was added 80%

hydrazine hydrate (6.26 g, 6.06 mL, 0.1 mol, 1.0 eq). Ice-cooled carbon disulﬁde (7.61 g, 6.04 mL, 0.1 mol, 1.0 eq) was added drop-

wise to the stirred solution over 90 min, while keeping the temperature of the reaction mixture below 10^ꢀC. The bright yellow mixture

was stirred for an additional 1 h, after which ice-cooled methyl iodide (14.2 g, 6.23 mL, 0.1 mol, 1.0 eq) was added dropwise over a 2 h

period and the mixture was allowed to stir overnight while slowly warming to room temperature. The white precipitate was collected

by ﬁltration and washed with ice-cold water. The crude product was recrystallized from dichloromethane to give methyl hydrazine-

carbodithioate (1): 2.8 g, 23% yield. The spectroscopic data matched those reported in the literature (Klayman et al., 1979a).

Methyl 2-(1-(pyridin-2-yl)ethylidene)Hydrazine-1-Carbodithioate (2)

Methyl hydrazinecarbodithioate (1, 2.8 g, 22.95 mmol) was dissolved in isopropanol (7 mL) and 2-acetylpyridine was added (2.79 g,

2.59 mL, 23.07 mmol, 1.005 eq). The reaction mixture turned yellow followed by precipitation of a yellow solid. The reaction mixture

was stirred for an additional 2 h and cooled overnight. The precipitate was collected by ﬁltration, washed with isopropanol and

air-dried to yield methyl 2-(1-(pyridin-2-yl)ethylidene)hydrazine-1-carbodithioate (2): 4.72 g, 91% yield as a 63:37 mixture of E/Z-iso-

mers. The spectroscopic data matched those reported in the literature (Klayman et al., 1979a).

(E)-N’-(1-(pyridin-2-yl)ethylidene)azetidine-1-carbothiohydrazide (NSC319726) (Klayman et al., 1979b):

Methyl 2-(1-(pyridin-2-yl)ethylidene)hydrazine-1-carbodithioate (2, 2.25 g, 10 mmol, 1.0 eq) was suspended in methanol (25 mL)

and azetidine (0.57 g, 674 mL, 10 mmol, 1.0 eq) was added and the mixture was stirred at 50^ꢀC for 6 h. The solid dissolved and after

20 min a white solid precipitated. After cooling to room temperature the solid was collected by ﬁltration to give the product as a ﬁne

white powder, NSC319726: 1.81 g, 77% yield.

¹H NMR (400 MHz, DMSO-d6): d 10.19 (s, 1H), 8.59 (dt, J = 4.9, 1.2 Hz, 1H), 7.93 (d, J = 8.0 Hz, 1H), 7.82 (td, J = 7.7, 1.8 Hz, 1H), 7.38

(ddd, J = 7.4, 4.8, 1.2 Hz, 1H), 4.58 (bs, 2H), 4.13 (bs, 2H), 2.35 (s, 3H), 2.25 (p, J = 7.8 Hz, 2H) ppm.

¹³C NMR (100 MHz, DMSO-d6): d 175.8, 155.0, 148.6, 148.5, 136.7, 123.8, 119.8, 56.6, 53.1, 16.0, 11.6 ppm.

HRMS (ESI+, m/z): calcd for C₁₁H₁₅N₄S [M+H]⁺: 235.1017, found: 235.1020.

Cell Viability Assay

When cellular viability assays were performed in 384-well plates (Corning #3712), we often treated cells with two components.

A compound tested in a 2-fold dilution series (denoted as L as they are often lethal compounds), and a modulator tested at a single

concentration (denoted as M here). M may interfere with cellular signaling responding to the stimuli L and consequently it may affect

the phenotype. M was already treated to the cellular suspension before seeding cells (e.g., when M is a compound, it was added to

the cell suspension just before seeding the cells to plates; when siRNAs, cells were ﬁrst transfected as described in the following

section, and in two days transfected cells expressing the siRNAs were reseeded in 384 well plates). 1,000 (HT-1080) or

2,000 (GBMs) cells treated with M were seeded per 36 ml in each well of 384 well plates (Corning, #3712). Compounds examined

in assays were ﬁrst dissolved in appropriate solutions (dimethylsulfoxide, ethanol, or culture media, depending on the compounds’

solubility), and then diluted to make 10x concentrations of the tested concentrations in the culture media. 4 ml of the 10x solutions

were added to each well, which results in treating cells with 1x concentration of the compounds. After cells were incubated with

the compounds for 48 h, 10 ml per well of 50% Presto Blue (Thermo Fisher Scientiﬁc) in culture media was added to each plate,

the plates were further incubated for eight hours, and the ﬂuorescence (ex/em: 530/590) was measured using a Victor plate reader

(Perkin Elmer). The raw ﬂuorescence acquired from the plate reader was normalized using the following equation: V_LjM= (I_M,L– I₀)/

(I_M– I₀), where I_M,L, I_M, and I₀correspond to ﬂuorescence intensity from wells containing cells treated with M and L, wells containing

cells treated with M only, and wells containing media, M, and L (but no cells), respectively. The resulting value (V_LjM) is the normalized

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viability. Note that V_LjM= 0 and 1 indicate that L completely kills the cells or that L does not induce any growth inhibitory effect,

respectively. When only a lethal compound was treated to cells in dilution series, we still use this equation but in this case M is

the vehicle control. The assays were done in biological triplicates; a representative single experiment was chosen to show dose-con-

centration curves for viability. In a plot, points are the mean of normalized viability tested in technical triplicates.

Sequencing of TP53 Gene of 13 GBM Primary Cells

TP53 primers were designed using the Consensus CDS (CCDS) available on the NCBI website (CCDS11118.1), with forward primer

TGAAGCTCCCAGAATGCCAG and reverse primer TCTCGGAACATCTCGAAGCG. The total sequence covered 846 bp, including

both primers. The forward primer extended from nucleotide 183 to 202, with the reverse primer extending from nucleotide 1009

to 1028.

Upon neurosphere dissociation or laminin detachment, RNA was collected from untreated GBM cells with a Qiagen QIAshredder

(#79656) and RNeasy Mini Kit (#74106) as per the protocol provided with the kit, analyzed for quality via Nanodrop Lite spectropho-

tometer, and cDNA was generated from each sample through PCR reaction with the aforementioned TP53 primers.

cDNA samples were sent to GENEWIZ for sequencing, and GBM TP53 sequences were returned aligned with the actual, expected

TP53 sequence. Upon visual inspection, mismatched pairs of nucleotides were identiﬁed, highlighted, and matched to the translated

amino acid they code for.

Screening for Lethal Compounds in 13 GBM Primary Cells

Lethal compounds were tested within GBM patient models as per the high-throughput screening protocol established in Quartararo

et al. (Quartararo et al., 2015). In brief, immediately upon detachment of adhesive cells or dissociation of neurospheres, GBMs were

seeded in 384-well, white, opaque, tissue-culture-treated plates (PerkinElmer, #6007688) at a density of 1,000 cells per well, with

26 mL of growth media in each well. 24 h later, inhibitors were added in a 17-point, two-fold dilution series. The ﬁnal concentration

range was 0.8 nM to 50 mM. 72 h post inhibitor addition, a one-to-one mixture of DMEM/F12 and CellTiter-Glo (CTG) was added, and

luminescence was quantiﬁed with a PerkinElmer Victor X5 plate reader. A Biomek FX liquid handling system was used to seed cells,

add inhibitors, and add the DMEM/F12:CTG luminescence mix, with cell-seeded plates maintained in a 37^ꢀC,100% humidity, 5%

CO₂environment during incubation and post inhibitor addition.

Percent viability was calculated using growth media only wells as 0% viable, and 0.5% DMSO treated cells as 100% viable.

GraphPad Prism 6.0e was used to calculate the EC₅₀values for each compound with four-parameter Hill equation, or ‘‘log(inhibitor)

vs. response- Variable slope (four parameters)’’.

Screening for a Responsible Metal in NSC319726-Induced Cell Death

1,000 HT-1080 cells/32 mL per well were seeded in a 384-well plate. The cells were grown overnight under 5% CO₂at 37^ꢀC. On the

next day, 4mL/well of 10x metal chloride and 4 mL/well 310 nM NSC319726 with or without 1 mM Co(II) were concomitantly added.

When the solutions were added, cells were treated with 31 nM NSC319726, with or without 100 mM Co(II) and with 2-fold 12-point

dilution series of metal chloride with the highest concentration of 100mM. The cells were incubated for 48 h followed by addition of

Presto Blue, incubation for 5 h and subsequent ﬂuorescence measurement. Note that metal salts were tested in a dilution series and

NSC319726 was tested at a ﬁxed concentration. Therefore, as described in ‘Cell Viability Assay’ section above, the normalized

viability of one corresponds to the viability of cells treated with DMSO, NSC319726, DMSO/Co(II), or NSC319726/Co(II), equivalent

to the condition of interest, but only without metals.

Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) for Metal Quantiﬁcation

Cells were plated in 6-well plates and cultured for one day. The vehicle or compounds were added to the cells the following day and

incubated for speciﬁed times. NSC319726, 7Br8HQ and MB were added for 24 h. Cobalt chloride was added either alone or in com-

bination with NSC319726 for 24 h. The plates were then washed 2 times with PBS containing 1 mM EDTA and 2 times with PBS alone.

After the addition of 215 mL concentrated nitric acid (BDH Aristar Ultra), the plates were sealed with paraﬁlm and incubated overnight.

The samples (150 mL) were then diluted in 2 mL 2% nitric acid (ultrapure nitric acid diluted in MilliQ water) and analyzed on a Thermo

Fisher iCAP Qc ICP mass spectrometer in Kinetic Energy Discrimination (KED) mode against a calibration curve of known copper,

zinc, iron, cobalt and phosphorus concentrations, with gallium (20 mg/L, Inorganic Ventures) as an internal standard. Each experiment

was carried out thrice and each condition was repeated in at least triplicate.

RNA-Seq Experiment

Sample collection. Poly-A pull-down was performed to enrich mRNAs from total RNA samples (200 ng - 1 mg per sample, RIN>8

required) and mRNAs were proceeded to library preparation by using Illumina TruSeq RNA prep kit. Libraries were then sequenced

using Illumina HiSeq2000 at Columbia Genome Center.

Samples were multiplexed in each lane, which yields targeted number of single-end/paired-end 100bp reads for each sample, as a

fraction of 180 million reads for the whole lane. The data analysis of the acquired sequencing was performed as described later in

Quantiﬁcation and Statistical Analysis.

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HIF-1a Knockdown

Gene knockdown was performed using siRNA reverse transfection. Non-targeting control or HIF-1a-targeting siRNAs (GE Dharma-

con) were dissolved in RNase-free water to make 10 mM stocks. 6 mL of siRNA solution and 15 mL of Lipofectamine RNAiMAX (Thermo

Fisher Scientiﬁc) were added to 500 mL OptiMEM media (Thermo Fisher) in each eppendorf tube, and placed on a well in 6-well plate.

Three wells per each siRNA were prepared. After the plates were incubated for 15 minutes at 37^ꢀC, 120,000 HT-1080 cells per 1.5 mL

in each well (i.e., 80,000 cells per mL) were seeded. Cells were incubated to allow knockdown proceeded for 48 h. Cells were trypsi-

nized and reseeded for further western blotting and viability assays.

Hypoxia Induction

In order to perform assays at 1.5% O2, a H35 HypOxystation (HypOxygen) was used. Upon seeding cells, plates designated for

hypoxia testing were manually transferred into the station, and inhibitors were added 24 h later by hand with the plates still inside

the Hypoxia chamber. For cell viability assay, 48 h (HT-1080) or 72 h (GBM) post inhibitor addition, plates were removed and

DMEM/F12:CTG was added as described above.

Western Blotting

300,000 HT-1080 cells were seeded per well in a 6-well plate. The cells were treated with 100 mM Co(II) chloride, 100 mM DMOG, or

media. The plates were grown under either hypoxia (1.5% O₂) or normoxia (21% O₂) and under 5% CO₂at 37^ꢀC for 24 h. As soon as

the plates were taken out of the incubator or hypoxia chamber, they were harvested at normoxia and ambient temperature. Proced-

ure for cell lysis, SDS–PAGE, and western blotting, was described previously (Dixon et al., 2012). Antibodies used were: anti-human

a-tubulin (Santa Cruz Biotechnology, sc-32293, 1:10,000 dilution), and anti-human HIF-1a (Abcam, ab51608).

ROS Detection in Cell Culture

HT-1080 cells were trypsinized and diluted to a ﬁnal density of 100,000 per mL. The cells were then incubated with 1 mM of

CM-H₂DCFDA for 30 min, spun down at 660 x g for 3 mins, and the supernatant was replaced with fresh media containing lethal

compounds and/or Cu(II). Then, the cells were incubated for 30 mins, spun down, and the supernatant was replaced with fresh

media. Fluorescence of samples was measured at the FL1-H channel using the Accuri C6 ﬂow cytometer (BD Bioscences). Flow

cytometry data were analyzed and visualized using ﬂowCore package (Hahne et al., 2009) and R.

ROS Detection in Cell Free System

Phosphate Buffered Saline (PBS), L-Cysteine (Sigma-Aldrich, #C7352), and H₂O₂(Sigma-Aldrich, #516813, 50 wt. % in H₂O) were

used to generate a master mix (MM) at a pH of 7.4. A clear 96 well plate (Sigma-Aldrich, #CLS3596) had the following conditions

added per row, with a technical triplicate of wells for each condition: PBS only, H₂DCFDA only, MM only, MM with CuCl₂, MM

with NSC319726, and MM with both CuCl₂and NSC319726. The ﬁnal volume per well was 200 mL, with the following concentrations

of components per relevant well: H₂DCFDA at 5 mM, Cysteine at 100 mM, H₂O₂at 100 mM, NSC319276 at 10 mM, and CuCl₂at 10 mM.

The plate was incubated at 37^ꢀC for minutes and read using a Victor X5 plate reader (ex/em: 485/535). The experiment was done in

biological duplicates. Data was analyzed using Microsoft Excel.

Cell Cycle Assay

300,000 HT-1080 cells per well were plated in 6-well plates and treated with 1 mM NSC319726, 50 mM 7Br8HQ, or 50 mM MB for 12 h.

The cells were trypsinized and spun down at 700 rcf. The pellets were triturated and ﬁxed with ice-cold 70% ethanol for 30 mins. The

cells were then spun down at 1,500 x g. After a PBS wash, the cells were incubated in 500 mL FxCycle PI/RNase staining solution at

room temperature for 30 mins while protected from light. Cells were immediately analyzed on the Accuri C6 ﬂow cytometer (BD

Biosciences), and the ﬂuorescence intensity on the FL2-A or FL3-A channel was monitored. Flow cytometry data were analyzed

and visualized using ﬂowCore package and R.

Metabolomic Proﬁling

HT-1080 cells were seeded into 10 million cells per T-175 ﬂask in four ﬂasks. Immediately, two ﬂasks were treated with 0.1% DMSO

and two with 5 mM NSC319726 and incubated for six hours. The cells were trypsinized and collected into 15 mL conical tubes. 500 mL

from each tube was saved for cell counting using ViCell (Beckman Coulter), and the rest of the tubes were spun down at 1,500 rpm for

5 mins. Pellets were washed gently with 5mL PBS. 500 mL PBS was added to the pellets, triturated, and transferred to cryovials. The

tubes were spun down at 1,500 rpm for 5mins, and the supernatant was removed. The pellet was ﬂash frozen in a dry ice-isopropanol

bath and stored at -80^ꢀC. Sample collection was performed in biological quadruplicates. After the last sample collection, the samples

were shipped in dry ice to Metabolon for further sample preparation. At Metabolon, 505 metabolites from the samples were identiﬁed

and quantiﬁed using LC/MS and GC/MS as described previously (Skouta et al., 2014).

Neurotoxicity Assays

For 96-well plate assays, SH-SY5Y cells were plated at 5K/well. For undifferentiated condition, cells were treated with drugs 24 h

after seeding, and for differentiated condition, cells were treated 3 days after switching to D2 media. In both conditions, four drugs

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were treated at 9-point 2-fold dilution series and cells were incubated for 48 h before viability was measured using CellTiter-Glo

(Promega, G7572). Images were taken by IncuCyte (EssenBioscience) at 10X after drug treatment for 48 h.

QUANTIFICATION AND STATISTICAL ANALYSIS

Pharmacogenomic Analysis of the NCI-60 Data

The NCI-60 data analysis was done as described previously (Shimada et al., 2016b). Brieﬂy, 2,565 cell-line-selective lethal com-

pounds were clustered into 18 groups based on growth inhibition (GI₅₀) proﬁles in the NCI-60 panel using Gaussian ﬁnite mixture

model and hierarchical clustering. The former was performed using mclust R package (Scrucca et al., 2016). Each cluster represents

distinct mechanisms of action. The Spearman correlation between each compound cluster’s GI₅₀proﬁle and each gene’s expression

across the panel was computed. This correlation matrix (18 compound clusters x 11,642 genes) was used for pathway enrichment

analysis (see below).

Processing of Raw Sequences from RNA-Seq

Raw sequences from RNA-seq of GBM cells were acquired as described above. RTA (Illumina) was used for base calling and

bcl2fastq (version 1.8.4) for converting BCL to fastq format, coupled with adaptor trimming. The reads were mapped to a reference

genome (Human: NCBI/build37.2) using Tophat (version 2.0.4) with 4 mismatches and 10 maximum multiple hits (Trapnell et al.,

2009). The relative abundance (aka expression level) of genes and splice isoforms were estimated using cufﬂinks (version 2.0.2)

with default settings (Trapnell et al., 2010).

Analysis of RNA-Seq Data

Normalized data (FPKM values) of the eight samples (HF3037 and HF2941 cells treated with DMSO or NSC319726, each with

biological duplicate) were provided by Columbia University Genome Center. A pseudo-count one was added to all the FPKM values,

which were then log–transformed, i.e., x_g= log10(n_g+ 1). For each cell line, the expression change of each gene g is computed by

averaging the log-expressions between the duplicates and subtract the expressions induced by NSC319726 from the ones induced

by DMSO. These expression proﬁles were then examined for pathway enrichment analysis as described above to identify pathways

(i.e., gene sets) that were up- or down-regulated upon NSC319726 treatment.

Pathway Enrichment Analysis

Pathway enrichment analysis is the core of our transcriptome analysis to understand the mechanism of lethality of NSC319726. From

the normalized NCI-60 and GBM data, we looked for pathways overrepresenting positively or negatively correlated genes in the

NCI-60 data and up- or down-regulated genes upon NSC319726 treatment in the GBM transcriptome (Figures 4A and S2). We

utilized the Broad Institute’s Molecular Signature Database (MSigDB) as collection of pathways (Subramanian et al., 2005). In the ﬁrst

analysis (Figure S2), we limited our analysis to Gene Ontology, Canonical pathways, BIOCARTA, KEGG, REACTOME, and

‘Hallmarks’ in MSigDB. In the second analysis (Figure S4), we used 3,400 ‘chemical and genetic perturbation’ gene sets in MSigDB

that are collections of up- and down-regulated genes from previously published experiments; we looked for experimental conditions

that induce similar gene expression changes to our NSC319726 treatment in GBM cells.

To compute the signiﬁcance of overrepresentation of a pathway, we developed a method using one-sided Fisher’s exact test. First,

genes were sorted based on correlation coefﬁcients for the NCI-60 data, or log fold changes for the GBM RNA-seq data (NSC319726

treatment over vehicle treatment). Second, we selected top and bottom n% of sorted genes (n=5,10,15,., 95), which gives 38 ways

of gene selection. Third, we assessed the signiﬁcance of overrepresentation of a pathway for each of these 38 selections. Finally,

p-value that gives the lowest of the 38 selections was set as the signiﬁcance of the enrichment of this pathway. When the lowest

p-value was given by ‘‘top’’ or ‘‘bottom’’ genes, the pathway was considered up- or down-regulated, respectively. The p-values

were further converted to signed log p-values, namely log10(p-value) multiplied by 1 or -1 when the pathway was up- or down-regu-

lated, respectively; large positive or negative signed log p-values indicate signiﬁcant up- or down-regulation.

To further assess the mechanism of action of the compound cluster containing NSC319726 and other thiosemicarbazones (we call

it cluster g here), we looked for pathways that are not only signiﬁcantly but also exclusively associated with the cluster here. To ﬁnd

such exclusive association, we calculated pathways’ ‘‘speciﬁcity’’ for the cluster g (Shimada et al., 2016b). Speciﬁcity of a pathway in

a compound cluster across multiple clusters becomes positive only when the pathway is most signiﬁcantly associated with

the cluster g in the same direction (up- or down-regulated) across the 18 clusters. Speciﬁcity (Sp) is mathematically deﬁned as

Sp = min(Dslp_g),sign(slp_g), where Dslp_gis a vector containing difference of signed log p-values (slp) between cluster g and the other

17 clusters, min() returns a minimum value of the vector, and sign() is a sign function.

Predicting Functionally Relevant Pathways

As summarized in Figure S2A, we suspected that pathways i) enriched in genes positively correlated with drug-sensitivity proﬁles

(i.e., genes more expressed in resistant cells) from NCI-60 analysis and ii) whose transcriptional activity is upregulated upon

NSC319726 treatment are more likely to be involved in protecting cells from the compound, while pathways i) enriched in negatively

correlated genes as well as ii) whose transcriptional activity is downregulated upon the compound treatment are more likely to sensi-

tize cells to the lethal stimuli. In both NCI60 and GBM transcriptome analyses, we set speciﬁcity of 5 and signiﬁcance of 10 as

e6 Cell Chemical Biology 25, 1–10.e1–e7, May 17, 2018

Please cite this article in press as: Shimada et al., Copper-Binding Small Molecule Induces Oxidative Stress and Cell-Cycle Arrest in Glioblastoma-

Patient-Derived Cells, Cell Chemical Biology (2018), https://doi.org/10.1016/j.chembiol.2018.02.010

thresholds for calling them speciﬁc and signiﬁcant, respectively (Figures S2B and S2C), and we eventually found two pathways

(HALLMARK_TNFA_SIGNALING_VIA_NFKB and HALLMARK_HYPOXIA) that likely support the cells to survive from the

NSC319726’s lethality.

DATA AND SOFTWARE AVAILABILITY

Normalized RNA-seq data of patient-derived glioblastoma cells, normalized metabolomic proﬁling data of HT-1080 cells, and chem-

ical structures of 83 compounds whose drug sensitivity proﬁles across NCI-60 cell lines are similar to NSC319726, are available at

Mendeley Data (https://doi.org/10.17632/2d8wzkcn3v.1).

Cell Chemical Biology 25, 1–10.e1–e7, May 17, 2018 e7

Article Doi

Copper-Binding Small Molecule Induces Oxidative Stress and Cell-Cycle Arrest in Glioblastoma-Patient-Derived Cells

DOI: 10.1016/j.chembiol.2018.02.010

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Authors:

Article abstract of DOI:10.1016/j.chembiol.2018.02.010

Full text of DOI:10.1016/j.chembiol.2018.02.010

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