VDAC1 and SERCA3 Mediate Progesterone-Triggered Ca2+

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VDAC1 and SERCA3 mediates Progesterone triggerd Ca2+ signaling in breast cancer cells Juberiya M. Azeez, Vini Ravindran, Viji Remadevi, Arun Surendran, Abdul Jaleel, T.R. Santhosh Kumar, and Sreeja Sreeharshan J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.7b00754 • Publication Date (Web): 29 Nov 2017 Downloaded from http://pubs.acs.org on December 3, 2017

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Journal of Proteome Research

VDAC1 and SERCA3 mediates Progesterone triggerd Ca2+ signaling in breast cancer cells Juberiya M Azeez#1 , Vini Ravindran# 1,Viji Remadevi#1, Arun Surendran2,Abdul Jaleel2 T.R. Santhosh kumar1, and S.Sreeja1* 1

Cancer Research Program 2Proteomics Core Facility,

Rajiv Gandhi Centre for Biotechnology, Thiruvananthapuram, India # Equal Authorship * Corresponding Author Email ID: [email protected] Juberiya M Azeez Cancer Research Program, Rajiv Gandhi Centre for Biotechnology, Thycaud P.O, Thiruvananthapuram, Kerala, India-695014 [email protected]

Vini Ravindran Cancer Research Program, Rajiv Gandhi Centre for Biotechnology, Thycaud P.O, Thiruvananthapuram, Kerala, India-695014 [email protected]

Viji Remadevi Cancer Research Program, Rajiv Gandhi Centre for Biotechnology, Thycaud P.O, Thiruvananthapuram, Kerala, India-695014 [email protected]

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Abdul Jaleel Mass Spectrometry and Proteomic Core Facility, Rajiv Gandhi Centre for Biotechnology, Thycaud P.O., Thiruvananthapuram 695014, India [email protected]

Arun Surendran Mass Spectrometry and Proteomic Core Facility, Rajiv Gandhi Centre for Biotechnology, Thycaud P.O., Thiruvananthapuram 695014, India [email protected]

TR. Santhosh Kumar Cancer Research Program, Rajiv Gandhi Centre for Biotechnology, Thycaud P.O, Thiruvananthapuram, Kerala, India-695014 [email protected]

Sreeja Sreeharshan, Cancer Research Program, Rajiv Gandhi Centre for Biotechnology, Thycaud P.O, Thiruvananthapuram, Kerala, India-695014 [email protected]

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Corresponding author: * Sreeja Sreeharshan, Cancer Research Program, Rajiv Gandhi Centre for Biotechnology, Thycaud P.O, Thiruvananthapuram, Kerala, India-695014. Tel:+91-0471-2529474; Fax +91-0471-2348096; E-mail address: [email protected]

Acknowledgement This study was funded by the Department of Biotechnology, Government of India. Vini Ravindran appreciates the support and grants from Kerala State Council for Science, Technology & Environment. We would like to express our thanks to Prof.M.R.Pillai, Director of Rajiv Gandhi Centre for Biotechnology for his directions and support. The views and opinions expressed in this article are those of the authors.

Abbreviations LC/MS/MS: Tandem mass spectrometry coupled to liquid chromatography GO : Gene Ontology FRET : Fluorescence Resonance Energy Transfer BCLAF-1: Bcl-2-associated transcription factor 1 SERCA: Sarco/Endoplasmic Reticulum Calcium transport ATPases ROS: Reactive Oxygen Species VDAC : Voltage-dependent anion channels Running Title : Calcium regulation by progesterone in breast cancer cells . Key Words: Progesterone, Breast cancer, Proteomics, Calcium Regulation 3



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Abstract Progesterone, a biphasic hormone whose confounding role in breast cancer cells involves an initial proliferative surge, followed by sustained growth arrest. Recently we reported that progesterone induces a time and concentration dependent release of reactive oxygen species and thus regulates the anti-proliferative activity in breast cancer cell line. Furthermore the expression of p27,crucial cell cycle control protein, was regulated by binding of progesterone on progesterone receptor B thus

leads to anti proliferative signaling via multiple signaling

pathways including p53, PTEN and antioxidant systems.

In this study, we performed a

LC/MS/MS analysis of three different breast cancer cell lines. Bioinformatics data analysis and functional classification of proteins revealed a role of progesterone in calcium signaling in MCF-7 cells and the major differentially expressed calcium regulators were S100A11, S100A10, calreticulin, VDAC1, SERCA3 and SERCA1. Later on we confirmed it by a cell line based system having a calcium cameleon sensor targeted at endoplasmic reticulum and found moderate calcium efflux from endoplasmic reticulum upon progesterone treatment. Real time PCR, western blot and TMRM staining with silenced cells confirmed the role of calcium signaling regulators VDAC1 and SERCA3 in progesterone response. Taken together all these results with our earlier studies, we suggest, that progesterone by regulating important proteins involved in calcium signaling and transport, can modulate cell proliferation and cell death. Furthermore our research may open new avenues for the hypothesis that surgery conducted during the luteal phase of the menstrual cycle might facilitate improved patient survival.

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Introduction Progesterone is an important steroid hormone, reported to either stimulate breast tumor growth, or suppress proliferation [1,2]. In breast cancer cell lines it opposes estrogen stimulated growth of ERα+ PR+ patient-derived xenograft [3]. Progesterone receptors (PR) exist in three isoforms: full-length PR-B, N-terminally truncated PR-A and the non-functional PR-C [4]. Earlier studies have shown Tob-1 as a target for progesterone signaling, mediated through progesterone receptor B in breast cancer cell line. Moreover this signaling significantly influence p53, PTEN and p27 expression and down-regulates anti-oxidant enzymes. This noteworthy cascade of signaling identified appears to result in breast cancer growth inhibition [1]. To explore the detailed molecular response of breast cancer cells to progesterone, we analyzed the proteome profile of progesterone treated MCF-7 cells. Strikingly, the proteome profile indicates a differential regulation of diverse proteins which encompassed those involved in calcium and redox regulation as well as in apoptosis, along with other biological processes. For appropriate cellular functioning, tightly controlled regulation of calcium signal is essential. Cellular processes such as cell proliferation, gene transcription and cell death has been evidenced by the changes in cytosolic free Ca2 +[5,6]. Many studies suggested the importance of p53 and PTEN in calcium signaling and its associations with endoplasmic reticulum and mitochondria associated membrane (MAMs), which is concurrent with our earlier results [7]. Ca2+ homeostasis in the endoplasmic reticulum(ER) is mainly regulated by a calcium pump Sarco/Endoplasmic Reticulum ATPase (SERCA), which resides in the endoplasmic reticulum (ER).It imports calcium ions from the cytoplasm into the main intracellular calcium storage organelle endoplasmic reticulum to regulate cytoplasmic

Ca2+ levels [8]. SERCA enzymes

are encoded by three different genes (ATP2A1-3), whose expression pattern depends on tissue and developmental stage-specific manner. When the SERCA pumps Ca2+ , ER resident Ca2+ , released in to the cytosol by specific receptors such as inositol-1,4,5-phosphat-receptor (IP3R) and ryanodine receptor ,

which subsequently leads to mitochondrial Ca2+ uptake. 5



Increased mitochondrial calcium leading to apoptosis by permeabilizing the mitochondrial outer membrane . On the other hand ER Ca2+ release causes an increase in cytosolic Ca2+ levels that activates calcineurin which inturn dephosphorylates/activates BAD. Activation of BAD inhibits anti-apoptotic Bcl-2family proteins, leading to similar outer mitochondrial membrane permeabilization followed by apoptosis. Along with apoptosis, increased cytosolic calcium triggers other forms of cell death [8,9] . Recent studies has reported alterations in the expression of SERCA2 and SERCA3 pumps in different types of cancer like: oral, lung, colon, stomach, central nervous system, thyroid, breast, and prostate has been reported [10]

Another calcium signaling regulator, located on the outer membrane of mitochondria, Mitochondrial voltage-dependent anion channels (VDACs) are a class of porin ion channels. Three VDAC isoforms have been identified in mammals VDAC1, VDAC2, and VDAC3. VDACs have been reported to play a key role in mitochondria-mediated apoptosis and are the major permeability pathways through the outer mitochondrial membrane. Increased permeability of VDAC1 allows the release of apoptogenic proteins to the cytoplasm during apoptosis, which is strongly associated with cell death [11,12]. VDAC1 is being explored as an emerging

target for cancer therapy as it is now well accepted as an important player in

apoptosis .

Disparities in the normal Ca2+ levels represent a disease state due to chemical or signal transduction changes [12]. Recent studies equipped us with more insights into the regulation of free Ca2+ in cancer cells [13]. Currently the role of progesterone in attenuating calcium signaling and endoplasmic reticulum stress in several tissue types are known but such a regulation in breast cancer remains elusive. Hence the current study emphasizes the role of steroid hormone progesterone in regulating the calcium signaling. Furthermore, this data gives strong evidence suggesting the role of progesterone in regulating calcium homeostasis, ER stress, oxidative stress, eventually leading to apoptosis in breast cancer cell line.

Materials and Methods Materials 6


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Charcoal stripped FBS (CTS) and Lipofectamine LTX was obtained from Invitrogen CA, USA, Endoplasmic reticulum (ER) -targeted Cameleon (D1ER) probe was a kind gift from Prof.Roger Chen, Rapigest (Waters) and sequencing grade modified trypsin purchased from Sigma Aldrich (St. Louis, MO). Antibodies were purchased from the following sources; SERCA3 from Santacruz Biotechnology, (Santa Cruz, CA), VDAC1, GRP74 and PDI from Cell Signaling Technology (Danvers, MA) and anti actin from Sigma-Aldrich Cell culture MCF-7, MDAMB-231 and SKBR3 cell lines were purchased from ATCC and maintained in DMEM (Sigma) medium (10% Fetal bovine serum, PAN Biotech, Germany). All experiments were done with cells, starved in 5% charcoal-stripped FBS [CTS] (Invitrogen,CA,USA) containing Dulbecco's Modified Eagle's medium.

Expression Vector and Transfection The expression vector for calcium cameleon probe targeted at ER (D1ER), a kind gift from Prof.Roger Chen, was used to study calcium efflux. MCF-7 cells were transfected with calcium cameleon probe targeted at endoplasmic reticulum using lipofectamine LTX (Invitrogen) as per instruction of the manufacturer. The cells expressing the calcium probe were selected by continuous maintenance of transfected cells in 800 µg/ml G418 (Invitrogen) containing medium for three weeks.

Intracellular calcium efflux imaging We performed ratio imaging using confocal microscopy to analyse the calcium release from ER using stable cells expressing ER-targeted Cameleon (D1ER) probe containing an ER (endoplasmic reticulum)-retention motif. When calcium binds to the calmodulin motif (D1), it causes an intramolecular rearrangement of the probe that leads to energy transfer between the donor and acceptor molecules, resulting in Fluorescence Resonance Energy Transfer (FRET) signal output. For imaging ER calcium, the cells were seeded on glass bottom chambered cover glass and allowed to grow for 48H. The cells were treated with different concentration of progesterone in calcium and magnesium free Hanks Balanced Salt Solution (HBSS). The imaging of cameleon was carried out using Laser Scanning confocal microscope A1R (Nikon) 7



using Plan Apo 60x 0.95 objective exciting with 456 nm laser line. Both Enhanced cyan fluorescent protein (ECFP) and enhanced yellow fluorescent protein (EYFP) emission were collected using NIS element software. Images were further analyzed in ratio mode after background subtraction. Real time PCR Total RNA was extracted by TRIzol (sigma) method and quantified. Using retro- transcription kit (Takara No.RR037Q), 500 ng of each sample was reverse transcribed as per the manufacturer’s instruction. The cDNA Amplification of specific genes SERCA3 and VDAC1 were performed by DyNAmo HS SYBR Green qPCR Kit (F-410L) as per the instruction and the following universal thermal cycling conditions: 15 min at 95°C (enzyme activation) followed by 40 cycles of 94°C for 10 s (denaturation) and 60°C (annealing) for 30 s and extension at 72°C for 30s. Data were analyzed and the relative level of expression of each sample (2−∆∆CT) was obtained. siRNA transfection Cells were transfected with SERCA3 and VDAC1 (Santa Cruz, CA, USA) siRNA using Lipofectamine2000 transfection reagent (Invitrogen, CA, USA), according to manufacturer’s protocol. After transfection,cells were subjected to TMRM staining and Chromatin condensation assay. TMRM Staining Progesterone treated and untreated cells were trypsinised and washed in 1XPBS and the cells were further re suspended and incubated in phenol red free DMEM containing 50nM TMRM for 10 minutes at 37°C. The cells were further filtered and analyzed by flow cytometry (Becton Dickinson, San Jose, CA). The fluorescence intensity difference was calculated by gating on live cells. Chromatin condensation assay

Hoechst 33342 (Life Technologies, Carlsbad, CA, USA) staining was used to identify apoptotic cells and performed as described previously [1]. 8


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Immunoblotting Lysates from progesterone treated and control cells were prepared [1]. Lysate proteins were resolved by 10–12% sodium dodecyl sulfate polyacrylamide gel electrophoresis and transferred onto polyvinylidene fluoride membrane. Immunoblotting was performed as described previously [1]. Extraction of proteins: Cells were grown in low glucose DMEM containing 5% charcoal-stripped FBS and then treated with progesterone for 24 hours. After washing cells twice with 1(X) phosphate buffered saline, the cells were scraped and centrifuged in pre-chilled 15 ml falcon tubes. The cellular pellets (treated samples) and their corresponding controls, were further lysed with the help of 0.1% Rapigest (Waters, Mexico) as a detergent in 50 mM ammonium bicarbonate. The samples were incubated at 80ºC for 15min to increase protein solubilization. Mass spectrometry was performed as described previously [14].Detailed protocol is given as supplementary file.

Bioinformatics and Statistical Analysis The proteins identified were subjected to Gene Ontology (GO) analysis using DAVID functional ontology analyzer [15]. Analysis was done in proteins identified in any one of the three technical replicates. Total Proteins detected in the dataset were defined by their NCBI IDs. After extracting the GO terms for the identified proteins, differentially abundant proteins were categorized according to their function. GO groups were selected based on the confidence score (p value < 0.05), and for overlapping GO groups, one representative category was selected within the dataset. The identification of gene ID and names from the protein ID was done with the

help

of

online

tool

biological

DataBase

network

[16]

(bioDBnet,

(http://biodbnet.abcc.ncifcrf.gov/). Using the the software , Venny 2.0 , differentially expressed proteins upon progesterone treatment in ER-positive cell line,MCF-7, was grouped in VennEuler diagrams. [17]. Differential fold change of overlapping proteins was represented by heat map generated using ClustVis webtool [18] . Average clustering method was employed and correlation was the parameter used as clustering distance. Further identified proteins that showed changes in their expression according to protein class were classified, with 9



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thePANTHER [19] classification system version 10 (http://pantherdb.org/). Functional interaction networks were identified with STRING [20] (Version 10, http://stringdb.org/).Active prediction methods used in our analysis were neighborhood, co-expression, gene fusions, databases, text mining, co-occurrence and experiments, using medium confidence (0.4). All the experiments were carried out in triplicate and data are expressed as means ± SEM. The level of significance was considered statistically significant when the P value was deemed 0.95) and a fold-change higher than 30% (ratio of either 1.3), as significantly altered levels of expression, was used for subsequent filtering. 212 up-regulated proteins and 191 down-regulated proteins were identified in progesterone treated samples compared to control (Fig1). The proteins identified from the proteomics data was categorized into up-regulated and down-regulated according to the criteria mentioned earlier (Fig.1.b).

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Comparison of differential fold change of proteins were done by constructing heatmap at different time points of progesterone treatment (Fig 2) by Clustvis webtool [18]. Average clustering method was employed and correlation was the parameter used for clustering. The color gradient white to blue indicates the over-expressed to sub-expressed proteins.

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Functional characterization of differentially expressed proteins The functional aspects of the identified proteins were retrieved using PANTHER classification system [19] (version10)(Fig.3).Based on molecular function 128 overexpressed proteins were analyzed

among them , we identified around 8 classes and of relevance were structural

molecule activity, binding, catalytic activity etc. When classified according to the biological process, we identified proteins involved in metabolic and cellular processes like cell cycle, cell proliferation, cell communication etc. Subsequently the down-regulated proteins were grouped according to molecular and biological functions. Of which, structural molecule activity, binding, and catalytic activity were predominant molecular functions, whereas metabolic and cellular process predominated biological functions.

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Analysis of Protein-Protein interaction networks of the differentially expressed proteins To understand the possible network of protein-protein interaction between the differentially expressed proteins upon progesterone treatment, STRING software [20] were used to create the networks (Fig. 4, Fig. 5). We also attempted to establish connection between proteins observed from our earlier studies [1] and those obtained from the present study (Fig.7).Known and predicted protein interaction were analyzed to understand any plausible connection. The interactions include direct (physical) and indirect (functional) associations and were derived from four sources were namely, neighborhood, co-expression, gene fusions, databases, text mining, co-occurrence and experiments, using medium confidence (0.4). K-Clustering was applied to enrich the up-regulated and down-regulated proteins. String database was enriched by Biological process; mainly apoptosis related and stress induced proteins. Both over expressed

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and sub-expressed proteins were enriched in proteins involved in apoptosis and stress (Fig.6).

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Progesterone induced Calcium Efflux from Endoplasmic Reticulum In a low calcium concentration environment, the cameleon molecule is unfolded and cyan fluorescent protein (CFP) fluorescence occurs when the molecule is excited with 442-nanometer light. However, when the calcium ion concentration increases, CFP fluorescence decreases and YFP fluorescence increases due to resonance energy transfer. The ratio between Enhanced Cyan Fluorescence Protein (ECFP) and Enhanced Yellow Fluorescent Protein (EYFP) is measured to estimate the change calcium levels in endoplasmic reticulum. We analyzed the steady state ratio at 24H and 48H that also showed an increased ratio change compared to control (Fig.8).

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Progesterone treatment caused upregulation of SERCA3 and VDAC1 As, we observed a differential expression of VDAC1 and SERCA3 in the mass spectrometry data, next we checked the expression pattern of SERCA3 and VDAC1 in MCF-7 cells in response to progesterone treatment. Real-time PCR expression of SERCA3 and VDAC1 was time dependent and increased in24H and 1H (Fig 9). Since progesterone is a biphasic hormone its effect on calcium channels also showed a time dependent expression. Concurrent with the real time data immunoblot also confirmed the protein expression of SERCA3 and VDAC1 in progesterone treated MCF- 7 cells (Fig 10)

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TMRM staining of Progesterone treated cells indicate loss in membrane potential Recent studies have shown that loss of mitochondrial membrane potential is directly linked to decrease in cell viability [21]. Hence TMRM staining was performed to evaluate the mitochondrial potential change upon progesterone treatment for various time duration. It was found that there was reduction in TMRM staining of cells which indicated a loss of potential in all treatments (Fig 11a). Further it was confirmed that loss in membrane potential is mediated through SERCA3 (Fig11B) and VDAC1 (Fig 11C) by silencing the cells with corresponding siRNAs.

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SERCA3 silencing inhibits chromatin condensation Earlier we have shown that progesterone induces chromatin condensation in MCF-7 cells. Silencing of SERCA3 (Fig12 A) and VDAC1 (Fig12B) effectually inhibited the chromatin condensation after progesterone treatment.

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Discussion:

A handful of reports indicate that progesterone and intracellular calcium levels are functionally linked [22, 23, 24]. One of the key trigger or regulator of cellular processes salient to tumor progression is calcium signaling and this is known to mediate proliferation, migration, and apoptosis [5, 6]. Earlier we have demonstrated that progesterone could induce mild apoptosis, oxidative stress and cell cycle arrest [1] which led us further to analyze proteome profile of progesterone treated breast cancer cells. Interestingly, our current data indicates the implication of calcium homeostasis in the death signal, stimulated by progesterone in breast cancer cells in a time dependent manner. In this study we analyzed the proteome profile of progesterone treated estrogen receptor positive MCF-7 cell lines at different time points (12h, 24h, 48h). Further to this the differential protein expression of MCF-7 cells were compared to identify overlapping as well as unique number of proteins (Fig. 1) .The fold change were quantitatively represented by heat map (Fig. 2). Since our earlier study demonstrated that the predominant action of progesterone is seen between 12h and 48h, further analysis was done for the intermediate time of 24h. Table 1 and Table 2 shows differentially expressed proteins, at 24h and their interaction pattern was then analyzed using STRING network analyzer (Fig.4, Fig.5). The major differentially expressed calcium regulators were S100A11, S100A10, calreticulin, SERCA3 and SERCA1. Several crucial cell functions are affected by calcium homeostasis. Calcium stored in ER is necessary for protein storage and transport, signal transduction pathways, and for diverse cellular activities.

Sarco/endoplasmic reticulum calcium transport ATPase (SERCA)-type

calcium pumps ensures calcium homeostasis in cells [8, 9, 10, 25]. There are three known SERCA genes ATP2A1, ATPA2 and ATP2A3 and alternative splicing generates its multiple isoforms. Expressions of these isoforms are highly tissue dependent and are regulated developmentally. SERCA3 is known to have six isoforms and is commonly co-expressed with SERCA2b in many tissues. SERCAs have often been suggested as an anti-cancer target due to its pivotal role in calcium regulation, proliferation, cell death and carcinogenesis [8, 2]. The expression levels are found to 24


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vary with tumor grade. For instance, in comparison to normal epithelium SERCA3 expression is much reduced in colon adenoma/adenocarcinoma [26]. A marked decrease in SERCA3 expression is seen in high-grade lesions, very low and barely observable in well-differentiated adenocarcinomas, and in moderately/ poorly differentiated carcinomas respectively. On the contrary, SERCA3 expression is found to be upregulated in the case of colon and gastric cancer cell differentiation, which involves a change in calcium homeostasis of the cell. Similar to colon carcinoma, normal breast acinar epithelial cells displays marked expression of SERCA3. Also, its expression is downregulated at the earliest morphologically detectable stages of lobular dysplasia and thereafter remains low at further stages of lobular tumorigenesis. When it comes to ductal carcinoma, an inverse correlation is seen with SERCA3, tumor differentiation and the degree of aggressiveness/ malignancy [26]. In this study, we found that mRNA levels of SERCA3 are upregulated in 24h progesterone treated MCF-7 cell lines and there was time dependence for the expression pattern. It can be thus speculated that one of the methods by which progesterone meditates calcium signaling via the expression of SERCA3. Later on, we observed a moderate efflux of calcium from endoplasmic reticulum to cytoplasm in progesterone treated cells, which is evident from EYFP/EGFP ratio (Fig 8). Efflux of calcium from ER and ROS produced by progesterone may lead to ER stress (Fig10). Besides, progesterone treatment activated PTEN [1], is also found in endoplasmic reticulum with an augmentation in mitochondria-associated membranes (MAMs) [27, 28]. Targeting of PTEN to the ER is found to increase calcium ion efflux from endoplasmic reticulum-to-mitochondria and also to enhance sensitivity to apoptosis. Similarly, p53, upon activation, is reported to bind the sarco/ER Ca(2+)-ATPase (SERCA) pump at the ER that alters its oxidative state and consequently increases Ca(2+) load, resulting in apoptosis [29,30]. Chromatin condensation assay clearly shows that silencing of SERCA3 prevents apoptosis, a consequence of progesterone treatment (Fig12 A). Understanding the molecular implications of SERCA3 and its expression in calcium homeostasis may open up new path in uncovering the role of progesterone regulation in cells at various levels. On progesterone treatment S100A11 and S100A10 are found to be upregulated, which are important S100 proteins relevant to calcium homeostasis. S100 proteins function both as intracellular Ca2+sensors and are overexpressed in breast cancer [31]. S100A11 is also said to 25



regulate cell apoptosis differentially depending on cell types [32, 33] and is often mediated through partial translocation of apoptosis-inducing factor (AIF) from the cytoplasm to nuclei [34]. Notably our proteomics data showed up-regulation of AIF upon progesterone treatment. AIF1 plays an important role in caspase independent cell death and also participates in the regulation of apoptotic mitochondrial membrane permeabilization [32]. In addition to this, VanDieckJ et al [35] reported that S100 proteins modulate p53 activity in a calcium-dependent manner. This correlates well with our earlier data [1] where progesterone treatment up-regulated p53 as well as induced mild apoptosis. In addition to S100 proteins, calretculin, an intracellular Ca2+ regulator was down regulated upon progesterone treatment. Notably, Palmer et al reports reduced calreticulin in endometrium of primates in progesterone-dominant phase of the menstrual cycle as well as in progesterone treated Ishikawa cells [36]. Reduced expression of calreticulin by progesterone directly points out lower capacity for Ca2+ storage according to Nakumura et al [37]. Another noteworthy observation is the differential regulation of proteins involved in oxidative stress and apoptosis. Of which VDAC1 and VDAC2, AIF and BCLAF are found to be important.

Bcl-2-associated transcription factor 1 (BCLAF-1), link transcriptional events to cell death and a P53 inducer [38], is seen up regulated according to mass spectrometry data. This correlates with our earlier studies that demonstrated the induction of P53 upon progesterone treatment [1]. Furthermore, Alkhalaf et al., [39] reported that progesterone induced apoptosis appears to be p53 mediated.

Voltage-dependent anion channel (VDAC) is involved in calcium signal delivery between the endoplasmic reticulum and mitochondria and also in mitochondria-mediated apoptosis [40]. Three VDAC isoforms have been identified in mammals, with VDAC2 and VDAC3 less abundantly expressed in most tissues compared to VDAC1. VDAC1 interacts with different proteins and factors whereby mediating the release of CytoC [11, 12]. It is also a known metabolite transporter. Numerous studies have reported that VDAC1 in the outer mitochondrial membrane can transport Calcium ion [39, 40]. The anion channel has also been suggested to have a role in mediating release of ROS from the mitochondria to the cytosol [41]. It is now 26


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recognized as an important player in apoptosis and is considered as a potential target for cancer therapy. Recent studies shown that silencing of VDAC1 inhibit cancer cell proliferation [40]. Here we observed an upregulation in the expression of VDAC1 and VDAC2 in the mass spectroscopic data. Interestingly mRNA levels of VDAC1 were found to be time dependent, which is a characteristic of progesterone action in breast cancer cells. Notably the mitochondrial potential were also altered as observed by TMRM analysis (Fig11 A) giving a stronger evidence to support the relevance of progesterone in calcium delivery between endoplasmic reticulum and mitochondria and also in mitochondria-mediated cell death. Moreover, when VDAC1 and SERCA3 were silenced, mitochondrial membrane potential loss seemed to be restored in transfected cells (Fig 11B, 11C). In VDAC1 silenced cells, this effect is enhanced on progesterone treatment, indicating that VDAC1 has a specific role in regulating mitochondrial membrane potential. This point out that lack of VDAC1 expression in progesterone treated breast cancer cells may augment the proliferative signal. In correspondence to this chromatin condensation assay clearly demonstrates the effect of progesterone on viability of cell, is highly mediated by VDAC1 (Fig12B) along with SERCA3, In summary, the synchronised effort of calcium pumps in the endoplasmic reticulum and mitochondria bring about the response of progesterone treatment in cells which supports the inhibition of growth in breast cancer cells.

Conclusion Taking together our earlier data and current study, progesterone treatment induces ROS, and a change in mitochondrial potential as well as calcium efflux from endoplasmic reticulum. Further it differentially regulates the expression of SERCAs, S100 proteins, calreticulin, peroxiredoxins and apoptosis regulating proteins like VDACs, AIF and BCLAF. To exactly derive a conclusion of the survival mechanism of progesterone in breast cancer role of PR isoforms, localization, PR-A/PR-B ratio, concentration and duration progesterone exposure [1], association of PR with ER-α [42] and mechanism of signaling i.e. classical pathway and non genomic signaling has to be taken into account. The current study provide evidence for calcium dependent signaling involving calcium pumps and calcium binding proteins probably as a trigger for cell death that may subsequently cause endoplasmic stress. These early events 27



contribute for increased ROS and may modulate cell death and cell proliferation depending on the threshold. The order of events cannot be ascertained yet, since ROS induction and calcium efflux are closely interlinked. This report is probably the first of its kind, indicating survival mechanism of progesterone in ER positive breast cancer through calcium signaling. The exact mechanism and the order of events still need further elucidation. An accurate or deep understanding may pave way to development of novel “Ca2+-signaling hormonal drugs that could augment calcium ion fluxes in cancer in hormone positive cells.

Conflict of Interest The views and opinions expressed in this paper are those of the authors. The authors declare that there is no conflict of interests in the publication of this paper.

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Figure Legends Figure 1: Venn-Euler diagram of differentially expressed proteins in MCF-7 cells: Cells were treated with progesterone for 12H, 24H and 48H .The protein samples were collected by cell lysis .Total proteins were further analysed by LC-MS-MS. (a) Venn Euler diagram showing the number of proteins present in the Control and progesterone treated MCF-7 at different time points (b)Shows up-regulated proteins upon progesterone treatment at different time points and (c)Shows down-regulated proteins after progesterone treatment at different time points. Figure 2: Heat map of the differentially expressed proteins represented using Clustvis webtool : By average clustering method, differentially expressed proteins found in all the three treatment duration of progesterone i.e 12H, 24H and 48 H were represented as heat map and thus fold change of these proteins were compared. The color gradient indicates differential fold change i.e. white color indicates highly up-regulated proteins while blue color indicates highly down-regulated ones.

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Figure 3:Functional and protein class analysis of differentially expressed proteins in MCF-7 cells: By panther classification system, molecular function and protein class analysis was performed in 24H progesterone treated MCF-7 cells (a1) Shows set of up-regulated proteins (a2) down-regulated proteins , according to molecular function analysis (b1) shows upregulated proteins and (b2) down-regulated proteins, according to functional protein class . Figure 4:Interactome analysis of over-expressed proteins identified by LC-MS/MS using STRING: The figure shows "action view " which explains the functional relationship between the over-expressed proteins . Different interactions are denoted by distinct colors. K-clustering has been used to group functionally related proteins. Figure 5: Interactome analysis of sub-expressed proteins identified by LC-MS/MS using STRING: The figure shows "action view " which explains the functional relationship between the sub-expressed proteins. The different colored connectors denote the relations indicated. Kclustering has been used to group functionally related proteins. Figure 6: STRING Network analysis and Enrichment by GO Biological Process: Figure (a) Shows up-regulated proteins where (a1) is enriched with cell death related protein and (a2) is enriched with Stress induced proteins (b) Shows down-regulated proteins wherein (b1) is enriched with cell death related protein (b2) enriched with stress induced proteins Figure7: Interactome of relevant proteins identified from proteomics data and previous studies analyzed using STRING interaction analysis: Figure (a)Shows interaction of proteins identified and (b) Shows interaction between proteins that are predicted to connect the identified proteins which was obtained from STRING database c) The set of proteins in b is Enriched by GO Biological Process, Response to steroid hormones . Figure 8: Progesterone induces calcium efflux in MCF-7 cells: : (A)Cells were stably transfected with ER-localized calcium probe, D1ER cameleon were treated with progesterone at different concentrations, 25nM, 50nM,100nM for 24H. The treated and untreated cells were imaged using Laser Scanning confocal microcsope A1R ( Nikon). Both Enhanced cyan fluorescent protein (ECFP) and enhanced yellow fluorescent protein (EYFP) emission were

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collected using NIS element software. (B)ECFP/EYFP ratio clearly indicated that higher concentration of progesterone (100nM) induces calcium efflux.

Figure 9: Progesterone induces expression of VDAC1 and SERCA3 : MCF-7 cells were treated with progesterone and gene expression were analyzed using real time PCR and increase in expression was indicated as the relative level of expression of each sample (2−∆∆CT).Each bar represents mean±SD of three independent experiments. Significant difference from control value was indicated by * (p

VDAC1 and SERCA3 Mediate Progesterone-Triggered Ca2+

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