mTOR signaling pathways in human cancers

Journal Pre-proof Peruvoside targets apoptosis and autophagy through MAPK Wnt/ β-catenin and PI3K/AKT/mTOR signaling pathways in human cancers

Dhanasekhar Reddy, Ranjith Kumavath, Tuan Zea Tan, Dinakara Rao Ampasala, Alan Prem Kumar PII:

S0024-3205(19)31075-6

DOI:

https://doi.org/10.1016/j.lfs.2019.117147

Reference:

LFS 117147

To appear in:

Life Sciences

Received date:

29 August 2019

Revised date:

30 October 2019

Accepted date:

4 November 2019

Please cite this article as: D. Reddy, R. Kumavath, T.Z. Tan, et al., Peruvoside targets apoptosis and autophagy through MAPK Wnt/β-catenin and PI3K/AKT/mTOR signaling pathways in human cancers, Life Sciences(2019), https://doi.org/10.1016/ j.lfs.2019.117147

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© 2019 Published by Elsevier.

Journal Pre-proof Peruvoside Targets Apoptosis and Autophagy through MAPK Wnt/β-catenin and PI3K/AKT/mTOR Signaling Pathways in Human Cancers Dhanasekhar Reddy1, Ranjith Kumavath1*, Tuan Zea Tan2, Dinakara Rao Ampasala3, and Alan Prem Kumar2, 4,5* 1

Department of Genomic Science, School of Biological Sciences, Central University of Kerala, Tejaswini Hills, Periya (P.O) Kasaragod, Kerala-671316, India.

2 3

Cancer Science Institute of Singapore, National University of Singapore, Singapore Centre for Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry,

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605014, India. Departments of Pharmacology, Yong Loo Lin School of Medicine, National University

Medical Science Cluster, Yong Loo Lin School of Medicine, National University of

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5

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of Singapore, Singapore.

Singapore, Singapore.

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*Correspondence: [email protected]; [email protected] Tel.: +91-8547648620 *Co-Correspondence: [email protected]; Tel.: 65-6516 5456

Journal Pre-proof Abstract Aim: To investigate the cytotoxic effect of Peruvoside and mechanism of action in human cancers. Main methods: Cell viability was measured by MTT assay and the cell cycle arrest was identified by FACS. Real-time qPCR and western blotting studies were performed to identify important gene and protein expressions in the different pathways leading to apoptosis. Immunofluorescence was performed to understand protein localization and molecular docking studies were performed to identify protein-ligand interactions.

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Key findings: Peruvoside showed significant anti-proliferative activities against human

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breast, lung, and liver cancer cells in dose-dependent manner. The anti-cancer mechanism was further confirmed by DNA damage and cell cycle arrest at the G0/G1 phase.

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Dysregulation of Wnt/β-catenin signaling with Peruvoside treatment resulted in inhibition of cyclin D1 and c-Myc also observed in this study. Furthermore, we identified that

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Peruvoside can inhibit autophagy by PI3K/AKT/mTOR signaling and through

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downregulating MEK1. Moreover, Peruvoside has the ability to modulate the expressions of key proteins from the cell cycle, MAPK, NF-kB, and JAK-STAT signaling. In silico studies revealed that Peruvoside has the ability to interact with crucial proteins from

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different biochemical signaling pathways.

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Significance: Our results demonstrated that Peruvoside has the ability to inhibit cancer cell proliferation by modulating the expression of various key proteins involved in cell cycle arrest, apoptosis, and autophagic cell death. Clinical data generated from the present study might provide a novel impetus for targeting several human cancers. Conclusively, our findings suggest that the Peruvoside possesses a broad spectrum of anticancer activity in breast, lung, and liver cancers, which provides an impetus for further investigation of the anticancer potentiality of this biomolecule. Keywords: Cardiac glycosides; Peruvoside; Apoptosis; Autophagy; Wnt/β-catenin pathway; PI3K/AKT/mTOR signaling; Molecular docking.

Journal Pre-proof

Introduction Cancer remains undefeated in the history of mankind with mortality rates of 10 million in the year 2018 [1]. Characterization of cancer can be done as unlimited growth, metastasis, and invasion of the cells [2]. Reportedly, synthetic drugs are the only option for cancer therapy but synthetic drug kills cancer cells as well as normal cells. Therefore, there is an urgent need for the identification of novel drugs or to use the existing drugs for new therapeutic indications through drug repurposing [3]. Plants remain as one of the important sources for various drugs for many diseases including cancer [4-5]. Among them, cardiac

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glycosides (CGs) are one of the ancient drugs, initially used for heart failure [6] and their

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activities towards cancer cells is novel. The current study was aimed to identify the cytotoxicity of a novel cardiac glycoside (Peruvoside) and to understand the mechanism

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action in breast, lung, and liver cancer cell lines.

CGs are natural chemical compounds extracted from plants and some animal species

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[7]. The well-recognized mechanism of CGs is to inhibit sodium/potassium (Na+/K+)-

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ATPase and increases intracellular sodium ions [8]. Na+/K+-ATPase is a P-type pump that actively carries potassium ions inside and sodium ions outside of the cell with 2:3 stoichiometry to maintain intracellular ion homeostasis, apoptosis, and communications [9].

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CGs also maintain ion homeostasis by restoring intracellular sodium concentrations to their maximum levels by stimulating the Na+/Ca2+ exchange pump to extrude sodium ions out of

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the cell and transports calcium ions into the cell in the absence or inhibition of Na+/K+ATPase. This activity results in increasing the intracellular calcium ions, which in turn increase cellular phenomena like myocardial contractility and calcium-dependent signaling [10]. CGs share a common core structure with a steroid nucleus, sugar moiety at C3 position and lactone moiety at the C17 position. Sugar moiety at the C3 position on the steroid ring generally affects the pharmacological profile of the CGs [11]. Moreover, the presence of free aglycones shows quicker and less complex absorption and metabolism associated with their glycosylated complements [12]. The clinical convention of CGs has raised to investigate whether CGs would influence the incidence and/or clinical outcome of several malignancies including cancers [13]. From a therapeutic point of view, some CGs such as Digoxin, Digitoxin, Ouabain, and Lanatoside C are the most important CGs used for congestive heart failures and other heart diseases such as atrial fibrillation [14]. However, the paucity in animal data on CGs is due to unusual species-dependent sensitivity in inhibiting cancer cell proliferation. Regardless

Journal Pre-proof of these empowering premises, convincing proof from randomized imminent clinical investigations that would bolster this thought is as yet missing. Presumably, in spite of the narrow therapeutic window only very few clinical trials have been attempted to investigate the putative and retrospective activity of CGs on tumor growth, response to therapy and oncogenes [15]. The complication and heterogeneity in cancer cells exposed to several systematic gaps that needed to be discovered before the anti-tumor mechanism [16-17]. An earlier interpretation of self-governing automatic aspects created many misleading concepts. Undeniably, unrelated intracellular intermediates and pathways were described to control

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by the CGs and these are proposed as substitute pathways to clarify cell-specific anti-cancer effects. But unfortunately, none of these mechanisms seem to be potent enough to draw

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conclusions [18-19]. The CGs are known to be produced endogenously, which can suggest

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the hormone-like autocrine functions [20-21]. Recent studies have witnessed on the anticancer activity of CGs [22] and reported that CGs could inhibit the influenza viral

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replication by cell protein translational machinery [23]. To the best of our knowledge, the underlying cellular mechanisms of CGs on the apoptosis and autophagy in cancer cells

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appears to be not clear. The reports on the mechanism of action state that mitochondrial apoptotic pathways are universally activated along with cytochrome C release and loss of

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mitochondrial membrane potential (MMP) [24]. It has been reported that some cardiac glycosides had the ability to inhibit general protein synthesis to cause apoptosis. The drugs

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such as rapamycin, whose function is to inhibit the translation is being used to treat neoplasms [25] which gives the motivation to identify the role of Peruvoside in general protein synthesis inhibition. Along with apoptosis, CGs can inhibit autophagy and promote cell death through necrosis [26].

In the current study, we examined the role of Peruvoside in breast, lung, and liver cancer cells, to compare antitumor activity and to identify the cell-specific mode of action. To the best of our knowledge, the mechanism underlying the cell death was revealed by checking various cellular signaling pathways like Wnt/β-catenin and PI3K/AKT/mTOR signaling and MAPK signaling at mRNA and protein level expressions. Since the CGs are known inhibitors of the general translation mechanism, we intended to check the expression of total proteins upon Peruvoside treatment to compare with mRNA expressions. Along with that, we have checked the role of Peruvoside in cell cycle arrest and the effect of this compound on DNA damage. In silico studies revealed that the exact binding modes with target proteins from different cellular signaling pathways are interacting with Peruvoside. It

Journal Pre-proof is been observed that the drug could be potent to one type of cancer which may show an opposing effect on other cancer activities. Hence, the current study is performed to understand the specific anti-tumor mechanism of Peruvoside in breast, lung, and liver cancer cells to explore the activity of this compound. Materials and methods Chemicals and reagents: Peruvoside was purchased from Toronto Research Chemicals, (North York, Canada). MTT, propidium iodide, DMSO was purchased from Sigma-Aldrich (New Delhi, India). Bradford reagent, DMEM, FBS, antibiotic and antimycotic solution were procured from

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Himedia (Mumbai, India). DAPI (Roche, India), Prolong Gold Antifade and Alexaflour488 were obtained from Invitrogen (California, United States). SYBR green and nuclease-free

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water obtained from Origin chemicals (Kerala, India). Peruvoside was dissolved in 10%

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DMSO and stored at -20 ℃. For all the experiments, the concentration of DMSO was not more than 0.0001%.

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Cell culture:

Breast cancer (MCF-7), Lung cancer (A549) and Hepatocellular carcinoma (HepG2),

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normal Liver cells (WRL68), Normal Lung (L132) cell lines were obtained from National Centre for Cell Science (NCCS) Pune, India. All the cell lines were cultured in DMEM

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medium with 10% FBS and 2mM L-glutamine, 100 U/ml penicillin, and 100 mg/ml streptomycin. All cells were cultured in a 5% CO2 environment with 37 ℃ temperature.

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PBMC isolation:

Peripheral blood mononuclear cells (PBMC) were isolated by using the density gradient method by using HiSep LSM by following previous reports [27] and the cells were suspended in the RPMI medium with 10% FBS, 1% L-Glutamine and 1% penicillinstreptomycin. About 1*105 cells/ml were seeded in 96 well plates and incubated for 16 hrs. Further cells were treated with Peruvoside (0.001-100µM). Control cells were maintained with DMSO. All experiments have done with triplicates and graphs were plotted in Origin pro 9.0.0. Cell viability assay: Anticancer activity of Peruvoside on MCF-7, A549 and HepG2 and normal cells such as L132 and WRL68 were determined by MTT assay by following manufacturer instructions, briefly around 4000 cells were seeded in each well of 96 plate (Eppendorf, Hamburg, Germany) and allowed it for incubation for 16 hrs with complete media containing 10% FBS with antibiotics. After the incubation period, the cells were treated

Journal Pre-proof with various concentrations of Peruvoside ranging from low to high concentrations for 24 hrs with serum-free medium. Cell viability was evaluated by adding 10 µl of MTT in each well and allowed the plate for incubation for 3-4 hrs in dark. DMSO was added to dissolve the formazan crystals and the reading was observed at 570 nm and 630 nm absorbance as reference wavelength by using a multimode plate reader (Perkin Elmer, Bengaluru, India). Cell viability was expressed as a percentage compared with controls. All data averaged from at least three experiments and were expressed as means ± standard error of the means (SEM). All the graphs were plotted in origin pro 9.0.0 software. DNA damage assay:

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The alkaline version of the comet assay is one of the most sensitive and extensively used technique to evaluate DNA damage in single cells. As the rate of DNA breaks

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increases, the fraction of DNA spreading towards the anode forms the comet tails after

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electrophoresis in alkali. Comet assay was performed by using a modified protocol [28]. Briefly, comet slides were pre-coated with 1% low melting agarose. Cells were seeded in 6

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well plates and treated with Peruvoside for 24 hrs with appropriate concentrations. After the incubation period, the cells were trypsinized and washed with PBS then cells were mixed

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with 0.6 ml of low melting agarose and layered on top of the pre-coated (1.2 ml of low melting agarose) slides. Then the slides were allowed for 30 mins incubation for proper

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solidification of low melting agarose. Further, the slides were incubated for 24 hrs at room temperature with pre-chilled neutral lysis buffer [2% sarkosyl, 0.5M Na2EDTA, 0.5 mg/ml

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proteinase K (pH 10)]. After the incubation period, the slides were washed with Electrophoresis buffer (1X TAE) for thrice with 20 mins interval. Then slides were electrophoresed with 1x TAE for 25 min at 0.6 V/cm. The slides were then washed with distilled water and stained with 2.5 µg/ml concentration of propidium iodide for 20 mins. Then excess staining was removed by washing with distilled water and the comets were observed under a fluorescent microscope with 20X magnification (Leica DMI3000, Mumbai, India). Flow cytometry for cell cycle analysis: Flow cytometry analysis was done to identify the cell cycle distribution. Briefly, 10 5106 cells/sample was seeded in a 60mm dish and allowed the cells to attach to the surface for 16 hrs. Cells were treated with Peruvoside for 24 hrs with various concentrations in various cell lines. After 24 hrs the cells were trypsinized and centrifuged for 3 mins at 1000 rpm and removed the media. The cell pellet was dissolved in 0.5 ml of cold calcium- and magnesium-free PBS (to avoid cell clumping) and vortexed for 2-3 seconds. Then the pellet

Journal Pre-proof was resuspended in 5 ml of cold PBS and centrifuged for 5 mins at 1000 rpm. PBS was removed and 0.5 ml of fresh PBS was added to the tube and 4.5 ml of chilled 100% ethanol was added to the conical tube by vortexing and incubated on ice for 30mins. Further, the ethanol was removed by centrifuging at 1000 rpm for 10 mins and re-centrifuged with PBS to remove ethanol contents, and then cells were stained with 1 ml PI/Triton X-100 staining solution with RNaseA. The cells were allowed for incubation in dark at 37o C for 60 mins. Further, the sample was vortexed and subjected to BD bioscience FACS instrument (San Jose, USA) for cell cycle distribution. RNA isolation and quantitative real-time qPCR:

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Total RNA was isolated from Peruvoside treated cells by using TRIzol by following manufacturer protocol. A total of 2µg was used for cDNA synthesis and Reverse

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transcription was performed by using Verso cDNA synthesis kit by following the

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manufacturer instructions. Real-time PCR was performed with Roche thermal light cycler (Roche) by following the manufacturer’s instructions. The relative expression levels of

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various genes in the current study were normalized with GAPDH as a reference gene by using the 2-ΔΔCt method. Every sample was analyzed with triplicates, the mean level

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expressions were calculated, and the graphs were plotted in Origin pro 9.0.0. The primers used in this study were shown in the S1 Table.

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Total protein extraction and western blot analysis: Cells were treated with Peruvoside for 24 hrs with appropriate concentrations for

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different cells. Treated cells were then centrifuged and lysed on ice for 30 mins in lysis buffer (150 mM NaCl, 100 mM Tris (pH 8.0), 1% Triton X-100, 1% deoxycholic acid, 0.1% SDS, 5 mM EDTA, 10 mM sodium formate, 1 mM sodium orthovanadate, 2 mM leupeptin, 2 mM aprotinin, 1 mM phenylmethylsulfonyl fluoride, 1 mM dithiothreitol and 2 mM pepstatin A) along with Protease inhibitor Cocktail (Roche, Lewes, Sussex, UK). Then the cells were subjected to sonication for 5 mins to extract cytosolic proteins and centrifuged at 14,000 g for 15 min at 4o C, the supernatant was collected as to total cellular protein content. The concentrations of total proteins were estimated by the Bradford protein estimation assay by following manufacturer instructions. An equal 30 µg of total protein was used for different percentages of sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) for different sized proteins and transferred to PVDF membrane using turbo Trans blot transfer system (Bio-Rad, Mumbai, India). The membrane was then blocked with 5% BSA and incubated with primary antibody overnight at 40 C. After three washes with TBST (150 mM NaCl, 10 mM Tris, 0.1% Tween 20, pH

Journal Pre-proof 7.4) the membrane was incubated with HRP-conjugated secondary antibody for 1 hour and washed with TBST for 5-6 times with 5 mins interval. Immunoreactive proteins were detected with chemiluminescence ECL substrate (Bio-Rad) and quantified using the CDigit chemiluminescent western blot imaging system (Li-Cor, Biosciences, Nebraska, United States). Mean densitometry data from independent experiments were normalized to results in cells from control experiments. Antibodies for the identification of Caspase mediated apoptosis were obtained from Cell signaling technology (Cleaved Caspase Antibody Sampler Kit #9929) and antibodies such as Chk1, Chk2, BAX, c-Myc, Cyclin D1, CDK6, p38MAPK, MEK1, SAPK/JNK, p53, STAT3, Gsk3α, β-catenin, p62, AKT,

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PI3K, mTOR, Beclin, were procured from Elabsciences. Image J was used to analyze the bandwidth and all the graphs were plotted in origin pro 9.0.0. GAPDH was used as internal

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control and all the expressions were normalized to GAPDH.

Protein

subcellular

localization

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Immunofluorescence studies:

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Immunofluorescence.

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Approximately 0.3x106 cells were seeded on top of the coverslips in a six-well plate. After incubation, the cells were treated with lethal doses of Peruvoside for 24 hrs. The cells were

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then fixed with 4% paraformaldehyde and with 0.1% Triton X for 20 min respectively. After washing the coverslips with 1x TBS for 4-5 times, the coverslip was blocked with 5%

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BSA for 1 hr at room temperature. Then the coverslip containing cells was incubated with primary antibody overnight at 4 ℃. The coverslip was then washed with 1x TBS and

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incubated in a secondary antibody (Alexa flour 488) for 2 hrs. Then, the coverslips were washed and incubated with 0.1 µg/ml concentration of DAPI for 20 mins in dark and washed 5-6 times with 1xTBS. The coverslips were transferred to glass slides coated with ProLong Gold Antifade Mountant. Excess amount of Antifade was removed and the slides were sealed with wax and observed under a fluorescent microscope with 40X Magnification (Leica DMI3000, Mumbai, India).

Docking using Discovery studio: Using built-in- ligand preparation wizard of Discovery studio V3.1, hydrogen atoms, probable tautomer’s low energy ring confirmers, and isomers were produced. Aromaticity has been preserved for both of the compounds and applied pH (6.5–8.5) based ionization. Energy minimization has been performed by applying the CHARMm force field for dihedral angles and exact bond length. The 2D-chemical structures of Peruvoside were

Journal Pre-proof downloaded from PubChem (12314120) and it was exported to Discovery Studio V3.1 window for the generation of 3D-structure and it was optimized using CHARMm force field and it was minimized using RMS gradient energy with 0.001 kcal/mol by keeping all the other parameter at default [29]. Crystal structures of STAT3 (PDB:1BG1), Human poly ADP Ribose (PARP) (PDB: 1WOK), p38 alpha (PDB: 1OVE), NF-κB (PDB:1VKX), CDK6 (PDB: 1X02), BCL-XL(PDB: 2W3L), Caspase 3 (PDB: 1NMS), Bcl2 (PDB: 2O21), MEK1 (PDB: 3VVH), Chk1 (PDB: 2E9P) and Chk2 (PDB: 2WTJ) protein structures were retrieved from Protein Data Bank (PDB) and the retrieved structure was imported to LibDock Work environment. The structure of CDK4/Cyclin D1 was

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downloaded from the previously reported paper [30]. Later the protein was prepared by removing heteroatoms other than co-factors and unwanted water crystals from the structure.

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Along with this protonation, ionization, energy minimization, and hydrogen bonds have

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been added. The CHARMm force field was applied for optimizing the geometry. The prepared protein was used for defining the binding site from the ‘Edit binding site' option

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from the receptor-ligand interaction toolbar. By using the bound ligand, binding position the active site was created and found to be 9.16 Å radius [31]. Docking was carried out by

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all prepared ligands. Structure-based virtual screening was carried out by docking all prepared ligands with each of the protein structures at the defined active site using LibDock

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from the receptor-ligand interactions toolbar. According to the LibDock score, all the docked ligand poses were graded and grouped by names.

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Clinical patient data analysis for the identification of survival outcomes: For clinical survival outcomes we have used molecular and genomic data (mRNA and protein) from TCGA (The Cancer Genome Atlas) dataset. Gene expression (FPKM) data from TCGA cohorts were downloaded from Broad firehose, version 2016_01_28 [32]. The updated clinical outcome of TCGA cohorts were obtained from [33]. Statistical analysis: All data were presented as mean ± SEM from three independent experiments (n=3). Statistical significance of differences in drug-treated versus control cells was determined using the Student t-test. The Cox regression analyses were performed using Matlab R2016b version 9.1.0.441655 (MathWorks; Natick , MA). The minimal level of significance was p<0.05. All the graphs were plotted using GraphPad Software. Results In vitro cytotoxicity of Peruvoside against cancer cells

Journal Pre-proof The cytotoxic activity of Peruvoside was evaluated in MCF-7, HepG2, and A549 cells by following 3-(4, 5-dimethylthiazole-2-yl)-2, 5-diphenyltetrazoliumbromide (MTT) based colorimetric cell viability assay. The compound was assayed from low to high concentrations ranging from 1-2000 nm and DMSO was used as a negative control. The obtained IC50 values are, in A549 (21.16 ± 1.12 nM), HepG2 (29.3 ± 2.02 nM) and in MCF-7 cells (31.3 ± 5.21 nM) [Fig 1, (i)]. Toxicity was observed at a minimum of 2 log differences in non-malignant cells (L132 and WRL68) i.e., at 50 µM concentrations [Fig 1, (ii)]. In addition, we observed proliferation inhibition after treating with Peruvoside for 24 hrs, under the microscope. Microscopic images revealed the morphological destruction

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upon Peruvoside treatment for 24 and 48 hrs (S1 Fig.). These data demonstrated that Peruvoside is effective in suppressing the growth of cancer cells and non-toxic to normal

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cells. The structural comparison of Peruvoside with Convallotoxin, Digitoxin, and

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Strophanthidin was shown in S2 Fig. Effect of Peruvoside on PBMC:

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Cardiac glycosides (CGs) are toxic to most of the cells, which block their clinical use. In the current study, we attempted to evaluate the toxicity of Peruvoside in PBMC from low

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to high concentrations (0.001-100 µM). As we already identified that Peruvoside did not show any toxicity to non-malignant cells. No significant toxicity was observed up to 100

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µM. IC50 concentrations of cancer cells did not have any toxicity or morphological disturbances. The obtained results suggest that Peruvoside is toxic to cancer cells but not to

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normal cells and PBMC [Fig 1, (iii)].

We have observed the comets in all three cancer cell lines with high frequency by following the Peruvoside treatment for 24 hrs in MCF-7, A549, and HepG2. Comets were found in the Peruvoside treated cells compared to untreated controls (S3 Fig.). We have observed clear comet tails and the movement of the comet in both control and treatments was measured by using CASP lab software and shown in Table 1 along with Head and Tail DNA percentages. Peruvoside induces cell cycle arrest and apoptosis in cancer cells Peruvoside induced cell death in breast, lung and liver carcinoma was observed by MTT and comet assays. Besides the effect of Peruvoside on Breast, Lung and Liver carcinoma proliferation and apoptosis, we further evaluated the cell cycle distribution after Peruvoside treatment. All the cells were exposed to serum starvation for 72 hrs and treated with Peruvoside with lethal concentrations of IC50 for (MCF-7- 100 nM), (A549 – 100 nM) and (HepG2- 100 nM), respectively. All the further experiments were carried out with the

Journal Pre-proof same concentrations as mentioned above. The results revealed that Peruvoside arrests cell cycle at G0/G1 in three cancer cells studied. As shown in Fig 2A. In MCF-7, control gated cells were 62.74% at G0/G1 phase whereas the treatment was restricted to 41.47% followed in HepG2, control gated cells were 61.33% at G0/G1 phase whereas the treatment was restricted to 43.99% and in A549, control gated cells were 63.38% cells at G0/G1 phase whereas the treatment was restricted to 41.35%. This indicates that Peruvoside was arrested cell cycle at the G0/G1 phase in breast, lung, and liver cancer cells. Along with the cell cycle, we have observed the percentage of dead cells in treatments compared to control cells. For example, in MCF-7 the percentage of dead cells in control was 2.27% but in the

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case of treatment of it increased almost triple and reached 6.16%. In the case of HepG2 cells dead cell percentage in control was 3.77% but in the case of treatment, the percentage

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increased almost double and reached 6.92%. A549 control cells contain only 2.23% of dead

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cells but in Peruvoside treatment, 5.60% of dead cells were observed Fig 2B. To authenticate this effect, we intended to check the role of important genes and proteins that

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can mediate cell cycle progressions, such as checkpoint and cyclin-dependent kinases. We have identified a significant downregulation in the expression of checkpoint (Chk1 and

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Chk2) and cyclin-dependent kinases (Cyclin D1 and CDK6).

apoptosis

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Peruvoside modulates the transcription of genes involved in cancer cell growth and

To validate the cell proliferative and apoptotic activity, we investigate the

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transcriptional effect of Peruvoside in MCF-7, A549, and HepG2 cells, by analyzing the selected representative target genes. We have checked the expression of proto-oncogenes such as c-Jun, c-Myc and c-Fos in Peruvoside treated cells and found to be constant dysregulation. In MCF-7, A549 and HepG2 cells, we observed a common significant decrease, in the transcription of Chk1, Chk2, CDK6 and Cyclin D1 cell cycle genes in Peruvoside treated MCF-7, A549, and HepG2 cells compared to untreated control cells. These results are reliable with cell cycle analysis (Figs 3A, 3B & 3C), showing that Peruvoside arrested cell cycle progression at the G0/G1 phase in MCF-7, A549, and HepG2 cells. The analysis of the expression of tumor suppressor genes (TSG’s) was found to be cellular specific. Although JAK was significantly induced by Peruvoside treatment in MCF7, A549, and HepG2 cells while PTEN was highly expressed in MCF-7 cells and downregulated in A549 and HepG2. On the other hand, p53 was consistently upregulated in all the Peruvoside treated cells. Genes such as p38MAPK, MEK1, MAPK24, p44, and SAPK/JNK were also assayed for identifying the expressions upon Peruvoside treatment.

Journal Pre-proof Peruvoside showed cell-specific expressions of p38MAPK and p44 was identified. Briefly, in A549 and HepG2 cells, these are downregulated whereas in MCF-7 it showed upregulation. Downregulation of MEK1, MAPK24, and SAPK/JNK was observed in all Peruvoside treated cancer cells. We then investigated the efficiency of Peruvoside in targeting AKT and mTOR pathways in MCF-7, A549, and HepG2 cells. Peruvoside treatment for 24 hrs inhibits the expression of p62, PI3K, mTOR, Beclin, LC3, and STAT3 in all the studied cancer cells. Differential upregulation of AKT and Sestrin were observed in HepG2 cells but dysregulated in MCF-7 and A549 cells. We further validated the role of Peruvoside in the Wnt signaling pathway. Peruvoside inhibited the expressions of Gsk3α

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and β-catenin as well as the related downstream target genes such as Cyclin D1 and c-Myc. Expressions of NF-kB and MSK1 from NF-κB signaling was assessed and found major

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upregulation in mRNA levels expressions on 24 hrs of Peruvoside treatment to MCF-7,

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A549, and HepG2 cells. Anti and pro-apoptotic genes such as Bcl-2 and BAX expressions were also examined with Peruvoside treatment and observed dysregulation of Bcl-2 and

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overexpression of BAX in all studied cells (Figs 3A, 3B & 3C). Peruvoside alters the key molecular pathways to promote apoptosis

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Several intracellular signaling pathways are modulated by the treatment of CGs as anticancer agents. By the western blot analysis, we determined the lethal dosage of

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Peruvoside at 24 hrs was able to create changes in protein expression and activation of signal transduction cascades known to possess roles in apoptosis and autophagy inhibition.

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Total cell lysates of MCF-7, A549, and HepG2 cells following 24 hrs Peruvoside treatment were isolated. First, we studied the effect of Peruvoside in caspase-mediated apoptosis. For this, we have checked the expressions of initiator caspase-9 and executioner caspases-3, 7. We observed the activation of initiator caspase leading to apoptosis by executing the activation of caspase 3 and 7 in A549 and HepG2 cells and we identified the activation of PARP cleavage. Proto-oncogene encoding protein c-Myc was also observed (S4 Fig.). We analyzed the effect of Peruvoside on the expression of cell cycle regulating proteins such as checkpoint kinases (Chk1 and Chk2) and cyclin-dependent kinases (CDK6 and Cyclin D1) as responsible proteins for cell cycle arrest at G0/G1 phase. To find out the impact of Peruvoside in cell cycle regulation of MCF-7, A549, and HepG2 cells, we performed western blot experiments for Chk1, Chk2, CDK6, and Cyclin D1. Our results revealed that at lethal dose concentrations Peruvoside downregulated the expressions of checkpoint kinases and cell cycle-dependent kinases, suggesting that the cell cycle arrest at

Journal Pre-proof G0/G1 phase may be due to the dysregulations of Chk1, Chk2, CDK6, and Cyclin D1 compared to untreated control consistent with G0/G1 phase cell cycle arrest (Fig 4). MAPK pathway plays a crucial role in apoptosis and cell survival. Therefore, we then sought to examine the effect of Peruvoside on Mitogen-Activated Protein Kinase (MAPK) pathway. To check the influence of Peruvoside in the MAPK pathway, we selected three crucial proteins p38MAPK, MEK1, and SAPK/JNK for the present study. Our results showed cell-specific expression of p38MAPK as upregulation in MCF-7 and dysregulation in A549 and HepG2 showing consistency with gene expressions. Constant dysregulation of

consistent with apoptosis-induction (Fig 5, S4 Fig.).

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MEK1 and SAPK/JNK was observed in all the three cells compared to untreated control

JAK/STAT signaling has a diversified role in activating/inhibiting many cellular

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signaling pathways such as PI3K/AKT/mTOR signaling, MAPK signaling, and NF-κB

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signaling. To investigate the effect of Peruvoside in JAK/STAT signaling, we selected one kinase protein (JAK) and one transcription factor (STAT3). The oncogenic transcription

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factor STAT3 is frequently activated in all tumors, our results revealed that Peruvoside downregulates STAT3 and JAK at 24 hrs treatment. Along with that, we have checked the

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expression of one key tumor suppressor protein (p53). The lethal dose of Peruvoside resulting in differential expression of p53. Our results revealed that p53 in MCF-7 cells

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downregulated whereas it is tremendously overexpressed in A549 and HepG2 along with that we have checked the expression of a pro-apoptotic protein (BAX) and found the

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significant upregulation compared to untreated control (Fig 5, S4 Fig.). PI3K/AKT/mTOR signaling pathway plays a crucial role in cell survival, apoptosis, cell cycle regulation, and autophagy. To explore the role of PI3K/AKT/mTOR signaling in Peruvoside induced MCF-7, A549 and HepG2 cells, the expression of PI3K, AKT, LC3, Beclin, p62 and mTOR was examined by western blot assay. Treatment with Peruvoside inhibited the expression of PI3K, LC3, Beclin, p62 and mTOR in MCF-7, A549 and HepG2 cells (Fig 5). However, cell-specific dysregulation of AKT was observed in MCF-7 cells and upregulation in both A549 and HepG2 cells, correlating to the gene expressions. The activity of Wnt signaling changes according to a specific cellular environment and it can either initiate or inhibit the processes of apoptosis. Our results suggested that Peruvoside can initiate apoptosis by suppressing Wnt/ β-catenin signaling, through dysregulation of GSK3α and β-catenin. Therefore, we initiated an approach to investigate the effect of Wnt/ β-catenin signaling with Peruvoside treatment in MCF-7, A549, and HepG2 cells. In the current study, we checked the expression of two important proteins

Journal Pre-proof GSK3α and β-catenin. Our results revealed that Peruvoside inhibits the expression of GSK3α and β-catenin, which can further obstruct the cell cycle regulation with Cyclin D1, and inhibition of c-Myc, which results in apoptosis (Fig 5, S4 Fig.). Immunofluorescence To study the protein presence and localization in the nucleus during apoptosis, we performed immunofluorescence. The MCF-7, A549 and HepG2 cells were incubated with lethal doses of Peruvoside for 24 hrs and labeled with fluorescence-conjugated antibody and the nucleus was stained with DAPI. As shown in (Fig 6) in MCF-7 cells we have

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shown the localizations of Cyclin D1 and the remaining proteins including Chk1, Chk2, CDK6, GSK3α, β-catenin, MEK1, SAPK/JNK, P62, AKT, mTOR, LC3, p62, STAT3, p53, were shown (S5A-5G Fig.). In A549 cells we checked the

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JAK, c-Myc, and BAX

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localizations of several crucial proteins from MAPK, Wnt, JAK-STAT, and PI3K/AKT/mTOR signaling pathways (S6A-6G Fig.). Here we have shown the localization

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of PI3K in control and Peruvoside treated cells (Fig 6). In HepG2 cells, we have checked the localization of various proteins including, cyclin-dependent, checkpoint kinases, pro-

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apoptotic proteins, and proto-oncogenes, proteins from MAPK, JAK-STAT, Wnt, and PI3K/AKT/mTOR signaling (S7A-7 G Fig.) three cancer cell and here we have shown the

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localization attenuations of p38MAPK. We found significant variations in the protein localizations such as protein migrations compared to untreated control. Some proteins

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moved from the nucleus to extracellular matrix and/or membrane and the other proteins moved from extracellular to the nucleus upon Peruvoside treatment. Molecular Docking of Peruvoside with various target proteins from various pathways Subsequently, we have done the docking studies to understand the apoptosis interactions of Peruvoside with various cell cycle regulating proteins like CDK6, Chk1, Chk2, and Cyclin D1. We have found satisfactory results with all the tested proteins. We observed that ASP32, ARG78, and LYS160 are interacting with Peruvoside and forming hydrogen bonding with CDK6 with the LibDock score of 91.3536 and we have identified that these residues may play a pivotal role in the inhibition of CDK6 at molecular levels with Peruvoside treatment. In the case of Chk1 downregulation has been observed at the molecular level and it is forming a hydrogen bond with Peruvoside at the ILE52 position with the LibDock score of 106.248. Chk2 is interacting with Peruvoside at GLY227, CYS231, LYS249, MET304, and ASP368 positions to form five hydrogen bonds with a score of 105.75 and showed significant downregulation in mRNA and protein levels. We have modeled the structure of Cyclin D1, which showed complete dysregulation in all three

Journal Pre-proof cancer cells and found that ASP158 is interacting with Peruvoside to form hydrogen bonds with 109.867 scores. Further, we have checked the interactions with anti-apoptotic proteins Bcl-2 and Bcl-XL. We have observed that ARG143, PHE150, and SER64, SER75, SER76, HIS79, GLU119, ARG123 is interacting with the ligand and forming hydrogen bonding with LibDock score of 89.565 and 106.151 respectively. At molecular experimentations, Anti-apoptotic gene/protein (Bcl-2) was found to be downregulated in all Peruvoside treated cancer cells. Then we checked the binding interaction of transcription factor STAT3 and mTOR, which was earlier found as downregulated in Peruvoside induced cancer cells to cause apoptosis and autophagic cell death by JAK-STAT and PI3K/AKT/mTOR

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signaling. Residues SER372, ASP374, ASN420, HIS437 and TYR2144, ARG2224 are interacting with Peruvoside to form hydrogen bonding with 109.855 and 130.991 LibDock

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scores respectively. We further extended our study to identify the binding mechanisms of

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Peruvoside with MEK1 and p38MAPK and found that ASP208 and TYR35 are interacting with 137.534 and 90.3457 LibDock score. MEK1 and p38MAPK were known to play a

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crucial role in cancer cell survival and cell death. At molecular experimentations through Real-time PCR and western blotting MEK1 has shown consistent downregulation and

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p38MAPK showed cell-specific expressions. At last, we have checked the interactions of Peruvoside with apoptosis-regulating proteins Caspase-3 and PARP, which is known to

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play a vital role by its activation in mediating Caspase dependent apoptosis. We have found fitting molecular docking with both the target proteins. Residues GLY60, MET61, ARG64,

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SER120, TYR204, SER205, ARG207 and ASP766, LEU769, ASP770, GLY894, ILE895, TYR896, SER904 are interacting with ligand and forming hydrogen bonds with 101.086 and 150.457 LibDock scores respectively. The protein-ligand complex (Fig 6 A-L), residues are interacting within 4 Å distance (Table 2) and 2D interactions were shown in fig 8 A-L. Clinical significance:

For clinical survival endpoint analyses, Overall survival (OS) and recurrence-free survival (RFS) Cox regression analyses on mRNA expression and protein abundance of MAPK1, MAP2K1, Gsk3α, CTNNB1, AKT1, mTOR, MAP1LC3A, SQSTM1, PIK3CA, BECN1,

AKT1/AKT2/AKT3|Akt,

AKT1/AKT2/AKT3|Akt_pS473,

AKT1/AKT2/AKT3|Akt_pT308, BECN1|Beclin, MAPK1|ERK2, GSK3A/GSK3B|GSK3alpha-beta,

GSK3A/GSK3B|GSK3-alpha-beta_pS21_S9,

GSK3A/GSK3B|GSK3_pS9,

MAPK1/MAPK3|MAPK_pT202_Y204, MAP2K1|MEK1, MAP2K1|MEK1_pS217_S221, PIK3CA/|PI3K-p110-alpha, CTNNB1|beta-Catenin, and SQSTM1|p62-LCK-ligand were analyzed. The obtained significant positive correlation (yellow) and significant negative

Journal Pre-proof correlation (gray) were shown in Table 3. We validated the TCGA data by using Cox regression model to determine the hazard ratio of the patients with high stage (III, IV) in comparison with low-stage (I, II). All these outcomes were generated based on baseline survival models. Discussion Nature is one of the richest sources for different biomolecules with various medical benefits [34-38]. Recent studies have suggested that CGs are showing promising anticancer activity against several cancers and non-toxic to normal cells [39]. In preclinical models, CGs and its derivatives have shown enriched vulnerability towards apoptosis in

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tumors/tumor cells. But in terms of the achieved response rates are inadequate for the human trails. Several mechanisms have been reported for the mechanisms of CGs in

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causing cell death from the past decade. For example, Oleandrin suppresses the activation

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of NF-κB to cause apoptosis [40-41], Digitoxin induces the mitochondrial pathway to cause apoptosis [42-43], other CGs initiates apoptosis by up-regulating the death receptors 4 and

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5, and some CGs inhibits general protein synthesis [44]. Ouabain induces apoptosis by downregulating Mcl-1 and sensitizes lung cancer cells to TRAIL-induced apoptosis [45].

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Earlier studies have reported that Peruvoside possesses anticancer activity in different types of cancer cells [46-47] and in the present study, we evoked the potent, significant

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cytotoxicity of Peruvoside at nanomolar concentrations and identified its non-toxic nature towards non-malignant cells and PBMC’s. Herein we report our efforts to show the

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underlying mechanism of in vitro anticancer activity in MCF-7, A549, and HepG2 cells. MTT assay [Fig 1, (i)] and morphological (S1 Fig.) revealed cell death at the lowest inhibitory concentrations (IC50) in cancer cells. Cell cycle analysis revealed the cell cycle arrest at the G0/G1 phase (Figs 2A & B) and the expression attenuations in biochemical signaling pathways such as MAPK, JAK-STAT, NF-κB, Wnt/β-catenin, PI3K/AKT/mTOR signaling was also identified. Along with that, we have identified the dysregulation of proto-oncogenes (c-Myc, c-Fos, and c-Jun) and anti-apoptotic genes (Bcl-2), activation of tumor suppressor genes (Figs 3A, B & C) and pro-apoptotic gene (BAX). The summary of several gene/protein expressions was listed in the S2 Table. Caspase-dependent apoptosis was also observed by finding the activation of caspase-7,-9 and 3 and PARP cleavage. Molecular docking revealed the significant protein-ligand interactions of apoptotic proteins with Peruvoside for the identification of the best orientation of the ligand to form docking complex with overall energy.

Journal Pre-proof Tumor suppressor genes were known to play a crucial role in signal transduction, which contributes to the development of chemotherapy-resistance [48]. TSGs such as p53, PTEN, and oncogenes regulate each other and forms the interconnection between several signaling pathways [49]. In the current study, we have checked the expressions of two key TSGs such as p53 and PTEN in MCF-7, A549 and HepG2 cells (Figs 3A, B & C). It was known that these genes regulate negative signals like cell cycle and apoptosis in cancer cells [50]. The loss of function of these tumor suppressor genes was associated with carcinogenesis. The up-regulation of TSGs was identified in all cancer cells with Peruvoside treatment. In brief, our study demonstrates that overexpression of tumor

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suppressor genes will be one of the factors in causing apoptosis in cancer cells by a gain of function by tumor suppressor genes.

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Activation of caspases leads to the inactivation of multiple cellular signaling pathways

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that led to carcinogenesis. In our current study, we have checked the expressions of initiator caspase-9 and effector caspase-3 and PARP [51]. We have found that cleaved caspase-3

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and caspase-7 activation upon the activation of caspase-9. The cleaved caspase-3 activation was mediated by caspase-9 and found to be the key mechanism for apoptosis in Peruvoside

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induced cells at 24 hrs incubation. At transcription, we have also checked the expressions of anti-apoptotic genes such as Bcl-2 and pro-apoptotic genes (BAX). A significant down-

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regulation in Bcl-2 and BAX overexpression was observed. Taken together our results suggest that Peruvoside at 24 hrs treatment in cancer cells can also initiate BAX induced

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apoptosis as well as caspase-mediated apoptosis. Interestedly, few reports still claim the presence of caspase-3 [52] in MCF-7 cells. Even though caspase-3-inadequate MCF-7 cells are yet delicate to cell death by a few expansions including TNF, staurosporine and different DNA destructive causes [53]. It has been reported that despite the fact that caspase-7 may remunerate under certain conditions for the absence of caspase-3, it is very much valued that the executioner caspases 3, 6 and 7 perform unique, non-repetitive roles during the annihilation period of apoptosis [54-55]. Apoptosis/cell death is an extremely regulated mechanism to decide the fate of the cancer cells in response to different types of stress [56-58]. The DNA damage was involved in many cell signal repair processes like checkpoint activations that leads to cell cycle arrest. DNA damage leads to genomic flux, which could further results in the activation of pro-apoptotic pathways, survival of polyploid cells and will be having inactivated telomere maintenance [59]. Checkpoints induce changes in telomeric chromatin DNA damage and activation of transcription and ultimately induces cell death by apoptosis [60]. Chk1 and

Journal Pre-proof Chk2 are serine/threonine kinases that have great variation structurally but functionally the same. Chk1 is responsible for cell cycle arrest in reaction to DNA damage [61]. We detected DNA damage and cell cycle arrest at the G0/G1 phase upon treating with Peruvoside to cancer cells for 24 hrs (Figs 2A & B). To evaluate the result we have checked the expression of Chk1 and Chk2 at molecular levels. Chk1 and Chk2 will be activated upon the phosphorylation of ATM/ATR/ATX [62]. Chk2 known to be highly inactive in response to DNA damage and will be activated upon the response to ATM [63]. We have found a significant downregulation in both of the checkpoint kinases at transcriptional and translational conditions and DNA damage was observed by the comet assay. For further

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confirmation, we checked the expressions of cyclin-dependent kinases such as CDK6 and Cyclin D1 and found significant down-regulation in Peruvoside treated cancer cells (Fig 4).

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Both of these cyclin-dependent kinases play a vital role in specific phases of the cell cycle

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[64]. Our study concludes that Peruvoside at its inhibitory concentrations can cause

damaging DNA and cell cycle arrest.

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significant down-regulation of checkpoint kinases and cyclin-dependent kinases by

The mitogen-activated protein kinase signaling is one of the crucial pathways for

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mammalian cancer cell survival, proliferation and apoptosis include drug resistance therapy [65]. This pathway was tightly regulated under normal conditions by bidirectional

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communications from the AKT/mTOR pathway [66]. In the current study, we have checked the expressions of p38MAPK, p44, MAPK24, and MEK1 (Fig 4, S4 Fig.). Activation of

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p38MAPK controls many functions such as cell cycle re-modeling. Depending on the cell type’s p38MAPK can either induce or inhibit the cell cycle at different phases along with the regulation of checkpoints [67]. We have observed the significant down-regulation of MEK1 and MAPK24 in three cancer cells. The downregulation of MEK1 can lead to the modulation of ATP synthesis and thus the cell can be unable to perform glycolysis which leads to apoptosis/necrosis [68]. We have observed the overexpression of p44 in the breast cancer cell and the inhibition in lung and liver cancer cell lines after treating with Peruvoside. We further concluded that p44 tended to regulate differently in the case of tumor initiation compared to tumor progression [69-70]. Taken together in our study we have identified the underlying apoptosis mechanism through MAPK signaling. In brief, DNA damage leads to the deregulation of MEK1 and which intern leads for the activation of pro-apoptotic signaling protein (BAX) and helps in the activation of caspase-3 to initiate apoptosis. Hence, it is hereby concluded that Peruvoside at 24 hrs treatment can cause great expression alterations in cancer cells.

Journal Pre-proof JAK-STAT signaling pathway consists of a chain of interactions between a group of proteins in the cell that can lead to immunity, cell growth/division and apoptosis [71]. Aberrant expression/ dysregulation of JAK-STAT has been reported in many cancers along with our study [72]. In the current study, we have found the aberrant expressions of JAKSTAT signaling, in the case of MCF7 and HepG2 upregulation of JAK has been observed while downregulation was identified in A549 cells. A significant downregulation has been observed in the case of STAT3 in all studied cell lines upon the treatment with Peruvoside (S4 Fig.). Aberrant expression of JAK-STAT either includes up or down-regulation can be possible in case of cell death induced by Peruvoside in cancer cell lines for 24 hrs. The

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central position of JAK-STAT signaling contributes to the progression and development of cancers. In our present study, we have identified the deregulation of JAK and STAT3 at

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transcription and translational stages to conclude that inhibiting JAK-STAT signaling could

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be harnessed therapeutically to treat cancers. Inhibited STAT3 can result in the inhibition of transcription to cause cell death. Conclusively, Peruvoside can inhibit the JAK-STAT

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pathway that brings therapeutic benefits in treating a variety of cancers. Alterations in the PI3K/AKT/mTOR signaling pathway is one of the most common

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genomic abnormalities in many cancers [72]. In the case of breast cancer, 60% of tumors change their genetic alterations that in turn leads to hyper-activation of the

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PI3K/AKT/mTOR pathway. It has been reported that PI3K controls multiple signals to prevent apoptosis and promotes cellular survival and proliferation in different types of cells

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[73]. PI3K signaling was initiated by the activation of receptor tyrosine kinases (RTK) or G-protein-coupled receptors (GPCR) situated on the cell surface along with some oncogenic proteins. AKT is a serine/threonine kinase that plays a vital role in multiple cellular processes including proliferation and apoptosis [74]. Expressions of multiple genes from mTOR signaling like p62, Sestrin, Beclin, LC3, PI3K, and AKT were investigated in the present study (Fig 5). We have found significant differences in expression from one cell line to another. Downregulation of Beclin and LC3 indicates that Peruvoside can also cause autophagy in cancer cells. Drugs that target PI3K/AKT/mTOR signaling have the potentiality to inhibit the cell proliferation pathways to initiate cell death in cancer cells. However, in HepG2 cells, we have identified a 2-fold expression of AKT upon treatment with Peruvoside. Previous reports [75-76], demonstrated that AKT could also be activated in response to mitochondrial apoptotic stimuli. Similar results were reported in Daunorubicin [78] induced U937 cells, which showed the activation of AKT in response to apoptosis and this activation was further inhibited in a PI3K‐ dependent manner. In the

Journal Pre-proof present study, we have identified that Peruvoside treated cancer cells are sensitive to autophagy and also showed decreased levels of PI3K and mTOR. These results indicated that Peruvoside inhibits cancer cell proliferation and autophagy by deregulating the PI3K/AKT/mTOR pathway to cause autophagic cell death. Convincingly, our study is the first to show that Peruvoside induced apoptosis and autophagy via inhibiting PI3K/AKT/mTOR signaling in breast, lung, and hepatocellular carcinoma cells. Wnt/β-catenin signaling is the most critical oncogenic pathway related to immune evasion. Mutations/deregulation in the Wnt pathway is leading to cancer and other diseases [79]. Wnt pathway is known to regulate cell proliferation, apoptosis and tissue homeostasis

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[80]. In the present study, we have checked the expressions of Gsk3α and β-catenin (Fig 5). Gsk3α is known to be the key regulator that mediates a crucial role in many cellular

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signaling pathways like Wnt, hedgehog, and GPCR [81]. In the current study, we have

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found the significant downregulation of Gsk3α and β-catenin on treating with Peruvoside in gene and protein expressions. It is well known that blocking of Wnt/β-catenin pathway at

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the cellular, the nuclear and cytoplasmic levels could lead to a decrease in cancer cell proliferation. Inhibition of β-catenin with Peruvoside led to the activation of pro-apoptotic

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protein BAX and caspase-3 activation. Dysregulated β-catenin also blocked the expression of proto-oncogene (c-Myc) and cyclin-dependent kinases (Cyclin D1) to inhibit the cell

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cycle regulation to initiate apoptosis.

Understanding the regulatory mechanisms controlling the oncogene expressions is

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important since these oncogenes can play a crucial role in cell death and survival [82-83]. Proto-oncogenes are known to be the transcription factors that play in the activation of proproliferative genes [84]. In the current study, we identified the role of Peruvoside in altering the expression of proto-oncogenes like c-Fos, c-Myc, and c-Jun. Activation of protooncogenes can happen in multiple ways, for example, c-Myc will be activated by the mitogenic signals and/or Wnt-signaling and through MAPK/ERK pathway. Whereas c-Jun will activate upon the response from the ERK pathway and activated ERK is known to enhance c-Jun transcription through GSK3 and CREB [85]. The activation of c-Fos can happen with multiple factors such as tumor promoters, cytokines, and phosphorylation of MAPK signaling [86]. As we know and reported that proto-oncogenes will be expressing aggressively in almost all types of cancer cells/tissues. Compounds that can down-regulate proto-oncogenes can initiate apoptosis [87]. We observed that the downregulation of protooncogenes against Peruvoside treatment. Overall, our identifications suggest that 24 hrs

Journal Pre-proof treatment of Peruvoside can down-regulates proto-oncogenes expression and can activate many downstream cellular signaling pathways [88]. Molecular docking is one of the finest methods to identify the drug targets for several diseases including cancers. Several other computational tools have been developed for the network and pathway analysis that enhances the identification of novel drug targets [89]. Molecular docking can predict how a ligand can interact with the target protein to enhance its conformation and function for rapid drug discovery to prevent cancer and other diseases [90]. Understanding the molecular interaction between a novel ligand and the target protein is one of the crucial steps in the target discovery. One such approach has been initiated in

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this study to identify interactions between Peruvoside and key target proteins from the cancer genome. Our findings suggest that Peruvoside can efficiently interact STAT3,

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Caspase-3, p38 alpha, PARP, CDK6, Chk1, Chk2, Cyclin D1, Bcl-2, BCL-XL, mTOR and

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MEK1 (Figs 7 and 8). Taken together our results suggest that Peruvoside can mediate different amino acids to form hydrophobic and hydrogen bonds with different ligand-

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protein interactions.

The clinical significance of genes used in this study were generated in the form of OS RFS

and

identified

AKT1/AKT2/AKT3|Akt_pS473,

several

genes

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and

such

as

MAP1LC3A,

GSK3A/GSK3B|GSK3-alpha-beta_pS21_S9

PIK3CA, and

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GSK3A/GSK3B|GSK3_pS9 in breast cancers, MAPK1, Gsk3α, PIK3CA, and p38_MAPK in lung cancers and MAPK1, Gsk3α, MAP1LC3A, and AKT on liver cancers are linked to

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cancer progression. The expression of MAP1LC3A is found to be dysregulated in many cancers, suggesting that this inhibited expression may be involved in the cancer progression [91]. PIK3CA has been found to be oncogenic and has been implicated in development and progression of cancers suggesting that may be involved in carcinogenesis [92]. Several survival factors uses AKT for inactivating the apoptosis machinery in cancers which then leads to cancer progression [93]. A multifunctional Ser/Thr kinase gene GSK3A helps in regulating the glycogen synthase and activates proto-oncogenes such c-Jun to promote cancers [94]. Activation of MAPK1 leads to the nuclear translocation and further phosphorylates the nucleus [95]. Activation of p38MAPK depends on the activity of other pathways and this activation could leads to the cancer cell survival [96]. The clinical significance of CGs has brought up in the past decade as CGs like Anvirzel, PBI-05204 from Nerium oleander and UNBS1450 (a semisynthetic CG derived from 2”oxovoruscharin) were very outstanding for its inhibitory properties against malignant growth, which made them to clear phase-II clinical trials[14, 97]. Anvirzel contains a vast

Journal Pre-proof number of CGs including Oleandrin, oleandrigenin, and neritaloside which are presently at phase I clinical trials to treat solid tumors and NSCLC alone and in blend with carboplatin and docetaxel [98]. The mechanism of the anti-cancer activity of Anvirzel is by inhibiting the fibroblast growth factor 2 (FGF-2) in solid tumors [99]. The maximum tolerated dose (MTD) of these compounds were identified as safe and is up to 1.2 mL/m2/day. However, a limiting toxic dose was not identified [100]. Along with that, a phase I clinical trial has been completed for PBI-05204 (a derivative of Anvirzel) for its activities against advanced cancers such as breast, bladder, colon, and pancreas [101]. MTD of this compound was identified as 0.6 to 10.2 mg/day and interestingly even at 10.2 mg/day, it doesn’t contain A

total

of

17

clinical

trials

are

in

progress

of

cardiotoxicity.

for

Digoxin

(https://clinicaltrials.gov/ct2/results?cond=cancer&term=digoxin) for several types of

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cancers including acute myeloid leukemia (AML), breast, prostate, lung, neck, and

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Kaposi’s sarcoma with the combination of cisplatin due to the common nature of digoxin in potentiating the antitumor immunity (https://clinicaltrials.gov/ct2/show/NCT02906800).

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The core structure of all these compounds including Peruvoside is the same as steroid nucleus (non-sugar) linked with sugar moiety at C3 position and lactone ring at C17

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position and all these compounds contain a four-membered non-sugar nucleus attached to the lactone moiety. As the non-sugar moiety is solely responsible for pharmacological

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function [102], the current study finds attention in moving further for its activity in the patients. The first However, so far no clinical trials/in vivo studies were instigated for

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Peruvoside hence the current study might provide the impetus for future clinical investigations. The first anti-cancer activity of Peruvoside was reported by Feng et al in 2016 [103]. In this the authors have stated that Peruvoside induces primitive myeloid leukemia cell death by upregulating CDKN1A and also by activating Caspase 3, 8 and PARP. Similar results were shown by Kaushik et al 2017 in human ER+ and triple-negative breast cancers [46] and in human lung cancers [47]. In this concern, it is the desire of the authors that this paper may assist scientists to evaluate the therapeutic prospective of Peruvoside in preclinical studies. Conclusion The fundamental feature of a competent cancer drug depends on its capability to kill the cancer cell or inhibit the growth that does not affect the non-malignant cells. Here, in the current study, we showed Peruvoside at nanomolar concentrations exhibited potent cytotoxicity against breast, lung, and liver cancer cells and non-toxic to non-malignant cells (L132 & WRL68) and PBMCs. The anti-cancer activities of Peruvoside are probably due to

Journal Pre-proof dysregulation of MAPK and Wnt/β-catenin pathways, which resulted in the inhibition of downstream targets such as Cyclin D1 and c-Myc. Similarly, Peruvoside induced autophagic cell death and apoptosis were evaluated with PI3K/AKT/mTOR signaling by checking the expressions and localization of p62, LC3, mTOR, PI3K, Beclin-1, and AKT. A variety of stress due to Peruvoside is attenuating MAPK signaling which leads to the inhibition of autophagy through MEK1 and ERK1/2 inhibition also witnessed. Clinical significance of genes identified in this study could leads to the development of novel therapeutic target for treating human breast, lung and liver cancers. Our results suggest that Peruvoside induces apoptosis and autophagic cell death in breast, lung and hepatocellular

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carcinoma cells by in vitro and might serve as a potent anti-cancer drug.

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Acknowledgments: The authors would like to acknowledge to Science and Engineering Research Board (SERB) Govt. of India for financial assistance, DR thanks to DST-Inspire

University

of

Kerala.

DRA

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Fellowship (IF140890) Govt. of India and the research facilities supported by Central thanks

to

the

DBT

project

(6242-

re

P104/RGCB/PMD/DBT/ADRO/2015). APK was supported by grants from National

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Medical Research Council of Singapore, NCIS Yong Siew Yoon Research Grant through donations from the Yong Loo Lin Trust and by the National Research Foundation Singapore and the Singapore Ministry of Education under its Research Center for

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Singapore.

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Excellence initiative to Cancer Science Institute of Singapore, National University of

Authors contributions. Conceived and designed the experiments: RK and DR. Analyzed the data: RK and DR. Contributed reagents/materials/analysis tools: RK, TZT and DRA. Wrote the paper/Language corrections: DR, RK, and APK. Funding: This work was supported by to Science and Engineering Research Board (SERB) Govt. of India funds through EMR (2016/003715/BBM) scheme. Grants from the National Medical Research Council of Singapore; Research Centers of Excellence initiative to Cancer Science Institute of Singapore. Ethics approval and consent to participate. Not applicable Conflicts of Interest. The authors declare that they have no competing interests.

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List of figure legends: Fig 1: Peruvoside inhibits the viability of MCF-7, A549, and HepG2 cancer cells in a dosedependent manner. All the cells were incubated in serum-free media with designated doses of Peruvoside for 24 hrs. Cell viability was assessed by the MTT assay. Plots show mean values ± S.E. of quadruplicates determinations of three or more experiments at P<0.05.

Journal Pre-proof Peruvoside treatment in cancer cells results in increased levels of DNA damage Fig 2: (A) Peruvoside induces cell cycle arrest at the G0/G1 phase. All the cells were left for serum deprivation for 72 hrs for G0/G1 phase synchronization followed by drug treatments (100 nM) for 24 hrs in complete media. Cells were fixed with chilled ethanol and stained with propidium iodide and RNase A for 1 hr at 37 0C in dark and analyzed by flow cytometry. (B) Quantitative representation of cell cycle data. Data are the mean values ± S.E. of at least three independent experiments performed in triplicates at P<0.05. Fig 3: Gene expression analysis of various genes related to cell death and survival from

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various signaling pathways, GAPDH was used as the internal control. (A) MCF-7 cells treated with 100 nM concentration of Peruvoside for 24hrs and the expressions were

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normalized with GAPDH. (B) Gene expression analysis of A549 cells induced with 100

-p

nM concentration of Peruvoside for 24 hrs and the obtained results were normalized with GAPDH. (C) Real-time PCR gene expression analysis of HepG2 cells treated with 100 nM

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concentrations of Peruvoside and the expressions were normalized to GAPDH. All the significant (n=3 and P≤0.01).

lP

expressions were analyzed with the 2–∆∆Ct method and the obtained results are statistically

Fig 4: Peruvoside modulates the expression of key signaling proteins. The total cell lysate

na

was collected after 24 hrs treatment with Peruvoside and equal concentration was used for the experiment. Expression of cell cycle regulating proteins such as Chk1, Chk2, Cdk6 and

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Cyclin D1 in three cancer cell lines and statistical analysis of cell cycle regulating proteins. Representative blots from three independent experiments are shown. Fig 5: Effect of Peruvoside in different biochemical signaling pathways. All the cancer cells were treated with 100 nM concentration of Peruvoside for 24 hrs and total protein (30 µg) was used for the experiment. Expression of the representative blot and statistical analysis of some crucial proteins (p38MAPK, and MEK1) from MAPK signaling, proteins such as AKT, mTOR, LC3, PI3K, p62 and Beclin 1 from PI3K/AKT/mTOR signaling, Gsk3α and β-catenin from Wnt/β-catenin pathways GAPDH was used as loading control and data are expressed as means ± SEM of three independent determinations. Fig 6: Immunofluorescence imaging of subcellular localization of target proteins. Cyclin D1 from MCF-7 cells, PI3K from A549 cells, and p38MAPK from HepG2 cells, control, and Peruvoside treated cells. Peruvoside induced A549 cells with Target proteins from PI3K/AKT/mTOR signaling i.e., LC3, PI3K Scale bar 10 μM.

Journal Pre-proof Fig 7: Protein –ligand docking complex of (A) STAT3, (B) Caspase-3, (C) p38, (D) MEK1, (E) PARP, (F) CDK6, (G) Chk1, (H) mTOR and (I) Bcl-2, (J) Bcl-XL, (K) Chk2 and (L) Cyclin D1 with Peruvoside. Fig 8: 2D interactions showing the residues involved in Peruvoside and target protein interaction. (A) STAT3, (B) Caspase-3, (C) p38, (D) MEK1, (E) PARP, (F) CDK6, (G)

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Chk1, (H) mTOR and (I)Bcl-2, (J) Bcl-XL, (K) Chk2 and (L) Cyclin D1.

Journal Pre-proof Length of head 103.05±8.125

Length of tail

Tail DNA (%) 11.78±1.874

Tail movement

OTM

25.63±2.54

Head DNA (%) 88.21±6.154

5.973±0.951

5.984±1.517

231.125±3.124

13±1.248

205.477±14.257

23.59±2.478

76.40±6.314

381.2523±21.549

249.0746±29.314

134.778±7.218

109.778±6.132

25±1.265

88.98±6.871

11.01±2.547

4.69±1.247

5.84±2.713

284.36±15.346

19±3.574

265.36±19.246

24.68±3.457

75.31±6.475

440.6126±19.314

248.5507±21.034

104.9286±8.312

76.07±6.457

28.85±4.271

78.69±9.147

21.30±4.217

12.2715±4.275

8.1673±1.547

387±19.548

152±11.235

235±16.483

14.67±3.124

85.33±7.157

242.464±8.317

69.925±8.127

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Table 1: Distance of comets travelled with Peruvoside treatment for 24 hrs with IC50

lP

re

-p

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concentrations.

na

MCF7control MCF7Treated A549control A549Treated HepG2control HepG2Treated

Total Length of Comet 128.68±6.315

Jo ur

Cells

Journal Pre-proof

Bcl2

89.565

3.

3VVH

MEK1

137.534

4.

1NMS

Caspase-3

101.086

5.

1OVE

p38 alpha

90.3457

6.

1WOK

PARP

150.457

7.

1X02

CDK6

91.3536

8.

2E9P

Chk1

106.248

9

2WTJ

Chk2

105.75

10

Cyclin D1

Cyclin D1

109.867

11

4JT6

mTOR

130.991

12.

2W3L

Bcl-XL

106.151

H bonds: TYR35. Interacting residues: VAL30, GLY31, SER32, VAL38, ALA51, LEU108, GLY110, ALA111, ASP112, ASN115, SER154, ASN155, LEU156, ALA157, LEU167. H bonds: ASP766, LEU769, ASP770, GLY894, ILE895, TYR896, SER904. Interacting residues: TRP861, HIS862, GLY863, SER864, ILE872, GLN875, GLY876, LEU877, ARG878, ILE879, ALA880, PRO881, TYR889, PHE897, ALA898, LYS903, TYR907. H bonds: ASP32, ARG78, LYS160. Interacting residues: GLN12, TYR13, LYS34, ASN35, ARG38, VAL40, GLU68, GLU72, HIS73, PRO74, VAL76, PHE80, ASP81, VAL97. H bonds: ILE52. Interacting residues: ALA19, TYR20, LYS38, VAL40, MET42, LYS43, ASN51, GLU55, GLU91, ASP130, LYS132, GLU134, ASN135, ASP148, GLY150, LEU151 H bonds: GLY227, CYS231, LYS249, MET304, ASP368. Interacting residues: LYS224, LEU226, SER228, GLY232, GLU233, VAL234, LEU236, ALA247, ILE250, ILE251, LEU301, LEU303, GLU305, GLY306, GLY307, GLU308, GLU351, ASN352, LEU354, ASP368 H bonds: ASP158. Interacting residues: ILE12, VAL20, ALA33, LEU34, LYS35, GLU56, VAL72, LEU91, PHE93, HIS95, GLN98, ASP99, ARG101, THR102, LEU147, ALA157. H bonds: TYR2144, ARG2224. Interacting residues: LEU1900, LEU1936, GLN1937, ILE1939, PRO1940, GLN1970, ALA1971, LEU1972, ILE1973, TYR1974, PRO1975, LEU2138, ALA2139, VAL2140, PRO2141, GLY2142, THR2143, GLU2196. MET2199, GLN2200, GLY2203, LEU2204, THR2207, ALA226, VAL2227, ILE2228. H bonds: SER64, SER75, SER76, HIS79, GLU119, ARG123. Interacting residues: ARG26, ARG68, PHE71, ALA72, GLY77, LEU78, LEU80, VAL115, VAL118, ASN122.

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2O21

ro

2

H bonds: SER372, ASP374, ASN420, HIS437. Interacting residues: ASP369, GLY373, VAL375, ALA377, LUE378, ARG379, GLY380, SER381, ARG382, LYS383, GLY421, LEU436. H bonds: ARG143, PHE150. Interacting residues: PHE101, TYR105, ASP108, PHE109, MET112, VAL130, GLU133, LEU134, ALA146, GLU149, VAL153. H bonds: ASP208. Interacting residues: LYS97, ILE99, LEU115, LEU118, VAL127, PHE129, ILE141, MET143, ARG189, ASP190, ASN195, CYS207, PHE209, GLY210, VAL211, SER212, LEU215, ILE216, MET219, ALA220, SER222, PHE223, ARG234, H bonds: GLY60, MET61, ARG64, SER120, TYR204, SER205, ARG207. Interacting residues: THR62, ASP70, HIS121, GLY122, GLN161, ALA162, CYS163, SER198, TRP206, SER213

-p

1BG1

Interacting residues

re

LibDock score 109.855

lP

1

Protein Name STAT3

na

PDB ID

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SI No.

Table 2: Ligand interactions of Peruvoside with various cell-signaling proteins from different pathways and the residues, which are forming Hydrogen bonds along with amino acids at 4 Å region.

Journal Pre-proof Disease

Gene (s)

BRCA BRCA BRCA BRCA BRCA BRCA BRCA BRCA BRCA BRCA BRCA BRCA BRCA BRCA BRCA BRCA BRCA BRCA BRCA BRCA BRCA BRCA BRCA BRCA LUAD+LUSC LUAD+LUSC LUAD+LUSC LUAD+LUSC LUAD+LUSC LUAD+LUSC LUAD+LUSC LUAD+LUSC LUAD+LUSC LUAD+LUSC LUAD+LUSC LUAD+LUSC LUAD+LUSC LUAD+LUSC

MAPK1 MAP2K1 GSK3A CTNNB1 AKT1 MTOR MAP1LC3A SQSTM1 PIK3CA BECN1 AKT1/AKT2/AKT3|Akt AKT1/AKT2/AKT3|Akt_pS473 AKT1/AKT2/AKT3|Akt_pT308 BECN1|Beclin MAPK1|ERK2 GSK3A/GSK3B|GSK3-alpha-beta GSK3A/GSK3B|GSK3-alpha-beta_pS21_S9 GSK3A/GSK3B|GSK3_pS9 MAPK1/MAPK3|MAPK_pT202_Y204 MAP2K1|MEK1 MAP2K1|MEK1_pS217_S221 PIK3CA/|PI3K-p110-alpha CTNNB1|beta-Catenin SQSTM1|p62-LCK-ligand MAPK1 MAP2K1 GSK3A CTNNB1 AKT1 MTOR MAP1LC3A SQSTM1 PIK3CA BECN1 Akt Akt_pS473 Akt_pT308 Beclin

mRNA/Protein

OS_Cox.Reg_Coefficient

mRNA mRNA mRNA mRNA mRNA mRNA mRNA mRNA mRNA mRNA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA mRNA mRNA mRNA mRNA mRNA mRNA mRNA mRNA mRNA mRNA Protein RPPA Protein RPPA Protein RPPA Protein RPPA

0.219035475 0.176932006 0.01488892 -0.051090856 0.019438938 -0.052159717 -0.205869974 0.053864365 0.265857672 -0.02361558 0.205129225 0.084407381 0.121121525 -0.079814547 0.030224988 0.196692653 0.373845275 0.38561695 0.108144035 0.063351089 0.007742873 0.470130977 0.16297971 0.091889797 0.018844414 0.200514477 0.189428852 -0.010363747 -0.024607943 0.063130835 -0.020927629 -0.050149095 0.045152198 -0.064920534 -0.080513062 0.036641517 0.022212422 0.339363344

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OS_Cox.Reg_pvalue 0.185135578 0.338846694 0.942273408 0.700638264 0.889527814 0.757364632 0.010048863 0.637697202 0.022757482 0.870553595 0.274875304 0.423702952 0.347111205 0.809651634 0.887601127 0.435759136 0.014682541 0.011969228 0.285396006 0.792205968 0.973842395 0.204394257 0.192098797 0.426572857 0.831841994 0.062804896 0.050094056 0.897220921 0.808667888 0.491914835 0.643332812 0.396378137 0.404567462 0.613711137 0.404728402 0.662543912 0.837371407 0.276367377

0.050606747 0.0037158 0.011097446 -0.219248453 0.181347532 -0.133597756 -0.085051712 0.037136387 0.108286534 -0.189103686 -0.011624641 0.206845795 0.206467165 0.524418167 -0.144132331 0.020994676 0.258375424 0.31830772 0.14037144 -0.237515425 0.045766924 -0.434275189 0.004058246 0.065878148 -0.220199043 -0.049228275 0.069580497 0.13011601 -0.009302356 0.098625453 0.005270517 -0.018068079 -0.135315683 0.200188385 -0.062239097 -0.047097133 0.018532977 -0.183131652

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RFS_Cox.Reg_Coefficient

RFS_Cox.Reg_pvalue 0.7560971 0.984144204 0.958589788 0.104336117 0.196900453 0.433839744 0.29856165 0.772181053 0.356674797 0.197994902 0.94783069 0.044136041 0.107281359 0.147453131 0.495698376 0.934714874 0.093049457 0.039043046 0.180452856 0.332830286 0.849067572 0.291123567 0.97472311 0.579082306 0.02453842 0.668855876 0.505544321 0.120143377 0.931830199 0.311674556 0.914182857 0.773981485 0.024936762 0.140359222 0.533589989 0.592077159 0.867442344 0.568716144

Journal Pre-proof LUAD+LUSC LUAD+LUSC LUAD+LUSC LUAD+LUSC LUAD+LUSC LUAD+LUSC LUAD+LUSC LUAD+LUSC LUAD+LUSC LUAD+LUSC LUAD+LUSC LUAD+LUSC LUAD+LUSC LUAD+LUSC LIHC LIHC LIHC LIHC LIHC LIHC LIHC LIHC LIHC LIHC LIHC LIHC LIHC LIHC LIHC LIHC LIHC LIHC LIHC LIHC LIHC LIHC LIHC LIHC LIHC LIHC

GSK3-alpha-beta GSK3-alpha-beta_pS21_S9 GSK3_pS9 MAPK_pT202_Y204 MEK1 MEK1_pS217_S221 PI3K-p110-alpha PI3K-p85 beta-Catenin mTOR mTOR_pS2448 p38_MAPK p38_pT180_Y182 p62-LCK-ligand MAPK1 MAP2K1 GSK3A CTNNB1 AKT1 MTOR MAP1LC3A SQSTM1 PIK3CA BECN1 Akt Akt_pS473 Akt_pT308 Beclin GSK3-alpha-beta GSK3-alpha-beta_pS21_S9 GSK3_pS9 MAPK_pT202_Y204 MEK1 MEK1_pS217_S221 PI3K-p110-alpha PI3K-p85 beta-Catenin mTOR mTOR_pS2448 p38_MAPK

Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA mRNA mRNA mRNA mRNA mRNA mRNA mRNA mRNA mRNA mRNA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA Protein RPPA

-0.064881225 -0.088311851 -0.038102632 -0.122911773 -0.134090176 0.008163694 -0.297927532 -0.292200526 0.018205905 0.115205706 -0.065861217 -0.419092113 -0.186945364 -0.061447049 0.212221702 -0.038152791 0.388863118 0.123525826 0.027800713 -0.027463975 -0.153798126 0.256591848 0.101608799 0.050213598 -0.682945028 -0.259063094 -0.052635929 -0.475945052 0.379649006 -0.106845512 0.309210027 -0.350159217 -0.388923545 -0.246655614 -0.680125486 0.72990962 -0.049107915 0.503292544 -0.825048298 0.219582104

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0.791099873 0.388613333 0.670677636 0.259825186 0.465858846 0.969304478 0.227814367 0.137706291 0.8199192 0.500781521 0.754757796 0.098687369 0.073233785 0.409635527 0.151360361 0.793938948 0.050987474 0.39325978 0.858056425 0.809449317 0.017639006 0.001942661 0.34865787 0.772127688 0.042855653 0.273627241 0.896193639 0.290246424 0.317003366 0.845361817 0.342993715 0.161407585 0.292425528 0.707282817 0.474148867 0.082501063 0.804630187 0.234476371 0.093854639 0.540038478

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-0.05462984 -0.099248095 -0.116502573 -0.106171012 -0.201635397 0.214387639 -0.345559486 -0.256210828 0.036040467 0.006758375 -0.152863665 -0.593237301 -0.127599106 -0.086642364 0.270694697 0.085170216 0.319359173 -0.02987134 -0.148216673 -0.051931565 -0.065267924 0.106699422 0.094667072 0.096953186 -0.403586808 0.122456461 0.386218752 0.329990007 0.287421497 0.956967747 0.605254684 -0.162153931 0.283836394 -1.794002186 0.049092717 0.680107628 0.016483533 0.008799153 -0.485527315 0.182282563

0.828437517 0.349906374 0.210015822 0.349674206 0.284678756 0.318457821 0.179463132 0.210713097 0.661875469 0.969240807 0.480443891 0.023679036 0.242436429 0.26447778 0.042389126 0.505267954 0.064691995 0.805917268 0.256995423 0.590339601 0.248146816 0.15405924 0.313512424 0.533935213 0.302791231 0.632906544 0.342231112 0.503514448 0.429562997 0.080158825 0.089114573 0.501849783 0.404957745 0.079239539 0.957157969 0.09113955 0.936907659 0.984686713 0.342104313 0.60650269

Journal Pre-proof LIHC LIHC

p38_pT180_Y182 p62-LCK-ligand

Protein RPPA Protein RPPA

-0.077862003 0.247031827

0.792175473 0.019687725

0.033938167 0.114895019

0.908036036 0.334036204

Table 3: Overall survival (OS) and recurrence-free survival (RFS) Cox regression analyses on mRNA expression and protein abundance of selected genes in the TCGA breast cancer (BRCA), liver cancer (LIHC), and lung cancer cohorts (lung adenocarcinoma and lung squamous carcinoma, LUAD+LUSC). Abbreviation: RPPA, reverse phase protein array; Cox.Reg_Coefficient, Cox regression coefficient; Cox.Reg_p-value, p-value from Cox regression analysis; OS, overall survival; RFS, recurrence-free survival. Yellow highlights = significant positive correlation while Gray highlight = significant negative correlation.

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