Activation of mTOR is implicated in the development and progression of breast cancer. mTOR inhibition exhibited promising antitumor effects in breast cancer; however, its effect is compromised by several feedback mechanisms. One of such mechanisms is the upregulation of mTOR pathway in breast cancer cells. Despite the established role of mTOR activation in breast cancer, the status of total mTOR protein and its impact on the tumor behavior and response to treatment are poorly understood. Besides, the mechanisms underlying mTOR protein degradation in normal and cancer breast cells are still largely unknown. We and others found that total mTOR protein level is elevated in breast cancer cells compared to their nonmalignant counterparts. We have detected defective proteolysis of mTOR protein in breast cancer cells, which could, at least in part, explain the high level of mTOR protein in these cells. We show that metformin treatment in MCF-7 breast cancer cells induced degradation of mTOR and sequestration of this protein in a perinuclear region. The decrease in mTOR protein level in these cells correlated positively with a concomitant inhibition of proliferation and migration potentials of these cells. These findings provided a novel mechanism for the metformin action in breast cancer treatment. Understanding the proteolytic mechanism responsible for mTOR level in breast cancer may pave the way for improving the efficacy of breast cancer treatment regimens and mitigating drug resistance as well as providing a basis for potential novel therapeutic modalities for breast cancer.
Activation of mTOR is implicated in the development and progression of breast cancer. mTOR inhibition exhibited promising antitumor effects in breast cancer; however, its effect is compromised by several feedback mechanisms. One of such mechanisms is the upregulation of mTOR pathway in breast cancer cells. Despite the established role of mTOR activation in breast cancer, the status of total mTOR protein and its impact on the tumor behavior and response to treatment are poorly understood. Besides, the mechanisms underlying mTOR protein degradation in normal and cancer breast cells are still largely unknown. We and others found that total mTOR protein level is elevated in breast cancer cells compared to their nonmalignant counterparts. We have detected defective proteolysis of mTOR protein in breast cancer cells, which could, at least in part, explain the high level of mTOR protein in these cells. We show that metformin treatment in MCF-7 breast cancer cells induced degradation of mTOR and sequestration of this protein in a perinuclear region. The decrease in mTOR protein level in these cells correlated positively with a concomitant inhibition of proliferation and migration potentials of these cells. These findings provided a novel mechanism for the metformin action in breast cancer treatment. Understanding the proteolytic mechanism responsible for mTOR level in breast cancer may pave the way for improving the efficacy of breast cancer treatment regimens and mitigating drug resistance as well as providing a basis for potential novel therapeutic modalities for breast cancer.
Mammalian target of rapamycin, mTOR, is a highly conserved serine/threonine kinase, which is ubiquitously expressed in cells to control growth and metabolism 1, 2, 3. This protein is essential for normal development and viability 4 as knockout of mTOR results in embryonic lethality 5, and its ablation in some somatic cells leads to increased apoptosis 6. As a key intermediate in the transmembrane signaling pathway, mTOR integrates various intracellular and extracellular stimuli to regulate many vital cellular processes. Thus, the dysregulation of mTOR pathway is implicated in an increasing number of diseases, including cancer, type 2 diabetes, and neurodegeneration (reviewed in7). Hyperactivation of mTOR signaling has been associated with aggressive tumor growth in many cancers 8, including breast cancer 9. The mTOR pathway is implicated not only in tumorigenesis of breast cancer but also in tumor sensitivity to chemotherapy and hormonal treatment. 10. Activated mTOR pathway is known to promote numerous cellular functions consistent with tumor invasiveness such as proliferation, migration, and survival 11.mTOR is activated in response to nutrients, growth factors, and cellular energy (reviewed in 2, 12). Active mTOR exists in two complexes, mTORC1 and mTORC2, which consist of distinct sets of binding proteins 13. Active mTOR phosphorylates different substrates to regulate distinct cellular functions 14 including protein synthesis, organization of the actin cytoskeleton, membrane traffic, and protein degradation (reviewed in 15). Protein synthesis is a key feature of cancer cells 16 and mTOR regulates protein synthesis through its downstream targets, p70 S6 kinase and eIF4E‐BP 17, 18. Another essential cellular function regulated by mTOR is autophagy 19, which is an intracellular degradation system that delivers cytoplasmic proteins to lysosomes 20.Involvement of active mTOR pathway in the progression of breast cancer is well established 21, 22. Its inhibition has been shown to sensitize breast cancer cells to the cytotoxic effects of chemotherapy in vitro 23. Rapamycin and its analogs (rapalogs) are highly specific inhibitors of mTOR, and currently, they are being evaluated as anticancer agents in clinical trials. However, toxicity is a limiting factor that precludes the use of high doses of mTOR inhibitors, particularly rapalogs, in combinatorial treatment for breast cancer 24. Moreover, evidence indicates that many humancancers have intrinsic resistance to treatment and the tumors initially sensitive to rapamycin demonstrate acquired resistance and become refractory to the treatment 25. One of the potential mechanisms of the ensuing drug resistance in breast cancer is the upregulation of mTOR pathway, which may involve increased activity or increased levels of total proteins in the mTOR pathway. An earlier report showed that metformin, an antidiabetic agent, exerts antitumor effects via inhibition of mTOR activity 26. Nonetheless, the molecular basis of the beneficial effects of metformin in breast cancer is far from being fully unraveled. Although metformin action on peripheral tissues requires high concentrations, its use is generally tolerable if avoided in patients with contraindications 27. The relatively safe profile of metformin makes it a promising agent for mTOR inhibition in breast cancer, particularly that mTOR inhibitors are usually required in high doses to achieve better antitumor effects.Total mTOR protein level is high in some cancers, such as colorectal cancer, and it correlates positively with the tumor stage 28, but the status of total mTOR protein and its impact in breast cancer cells are not well delineated. Although several mTOR inhibitors have shown promising antitumor effects 21, there is risk of emergence of drug resistance 29. Notably, feedback upregulation of the mTOR pathway is one of the potential mechanisms of drug resistance in breast cancer. One of the possible mechanisms underlying the upregulation of mTOR pathway is the increased level of total mTOR protein itself. The mechanisms controlling mTOR protein expression and degradation in breast cancer cells are still poorly understood. Autophagy and the ubiquitin‐proteasome system (UPS) are the main intracellular protein degradation pathways in eukaryotes 30. In the UPS, proteins are degraded by the 26S proteasome complex 31. In autophagy, protein degradation is induced by a specific autophagy inducer 32 such as starvation, oxidative stress 33, or proteasome inhibition. In normal cells, constitutive autophagy and the UPS pathways act in parallel to prevent the accumulation of proteins to prevent cells damage, however, the effect of these events in cancer cells are less understood 34. In rapidly proliferating tumor cells, the endoplasmic reticulum sustains stress exceeding the degradative capacity of the proteasome and autophagy systems. As a result, misfolded proteins accumulate in perinuclear aggresomes, which are associated with induction of nonapoptotic cell death 35.To understand possible mechanisms underlying elevated level of mTOR protein accumulation in breast cancer, we have undertaken this work. Our finding of defective proteolysis of mTOR protein could be potentially exploited for improving the efficacy of breast cancer treatment regimens and mitigating drug resistance as well as providing a basis for potential novel therapeutic modalities for breast cancer.
Materials and Methods
Cell lines and reagents
MCF‐10A, MCF‐7, and MDA‐MB‐231 breast cell lines obtained from the ATCC cultured and stored following ATCC protocol of authentication by short terminal repeat analysis. The cells were grown in Dulbecco's modified Eagle's medium (DMEM) containing high glucose (4.5 g/L) (Gibco/Life Technologies , Carlsbad, CA, USA) and supplemented with 7% fetal bovine serum (Harlan Bioproducts for Science, Inc., Indianapolis, IN, USA). Insulin, verapamil, MG132, chymostatin, leupeptin, pepstatin A, metformin, rapamycin, and PP242 purchased from Sigma Chemical Co. (St. Louis, MO, USA).
Western blot analysis
Cell lysates from both control and treated breast cells were prepared by three rounds of freeze‐thawing and vortexing of cell suspensions in a lysis buffer containing 10 mmol/L 4‐(2‐hydroxyethyl)‐1‐piperazineethanesulfonic acid (HEPES), pH 7.9, 1.5 mmol/L MgCl2, 10 mmol/L KCl, 0.5 mmol/L dithiothreitol (DTT), 0.5 mmol/L phenylmethylsulfonyl fluoride (PMSF), 0.5 mg/mL each of leupeptin, antipain, and pepstatin, 0.1 μg/mL chymostatin, 0.3 TIU/mL aprotinin, and 0.5 mg/mL benzamidine. Equal protein amount was fractionated by electrophoresis in sodiumdodecyl sulfate‐polyacrylamide gel (SDS‐PAGE), transferred to PVDF transfer membrane (PerkinElmer, Waltham, MA, USA), stained with Ponceau S solution (Sigma Chemical Co., St. Louis, MO, USA), destained, and immunoblotted with the designated antibodies including β‐actin to ensure equal loading. Anti‐mTOR, anti‐pmTOR (Ser‐2448), anti‐pP70S6K (T‐389), anti‐LC3B I, anti‐LC3B II, anti‐β‐Actin were purchased from Cell Signaling Technology (Danvers, MA, USA). Anti‐P70‐S6K antibody was purchased from EMD Millipore Corporation(Billerica, MA, USA). Blots were developed with enhanced chemiluminescece reagent (Pierce ECL, Thermo Scientific, Waltham, MA, USA). Band densitometry was measured by AlphaView imaging software, FluorChem Q system, ProteinSimple, and semiquantitative data were normalized for β‐actin.
Protein stability assays
Cycloheximide (CHX) assay was performed by treating the cells with CHX (Sigma Chemical Co.) at 200 μg/mL concentration for various time points, as indicated in Figure legend and the stability of mTOR protein was assessed by western blot (WB).
Immunocytochemistry
MCF‐7 cells were plated on tissue culture chambers (Lab‐Tek Chamber Slide; Nunc, Inc., St. Louis, MO, USA). Cells were stained with 1 μg/mL Acridine Orange (AO, Hartman‐Leddon Co., Philadelphia, PA, USA), followed by formalin fixation, methanol antigen retrieval, 2% (W/V) fetal bovine serum (FBS) blocking, and anti‐mTOR immunostaining.
MTT cell proliferation assay
Cells were grown in 24‐well plates to 50–70% confluence and proliferation rate of the cells were determined using a live cell assay kit (CellTiter 96 Non‐Radioactive Cell Proliferation Assay) and following the manufacture's protocol (Promega Corp., Madison, WI, USA). The cells were stained with 3‐(4,5‐dimethylthiazol‐2‐1)‐2,5‐diphenyltetrazolium bromide (MTT, 0.05 mg/mL). Absorbance was recorded at 562 nm using a NanoDrop spectrophotometer (Wilmington, DE, USA).
Wound healing migration assay
Breast cells were seeded on a flat bottom 24‐well plate, incubated overnight to allow the cells to resume growth. The medium was changed with fresh growth media in 70–80% confluent monolayers and supplemented with insulin and mTOR inhibitors, as described in the Figure legend. Wound was initiated by scratching with a sterile 20‐μL plastic pipette tip. Cell migration, indicated by wound closure, was evaluated by comparing the width of the clear line of cell‐free zone with that of the initial wound using a bright field microscopy. The size of wound was measured at various time points 0, 6, 12, 24, and 48 h.
Autophagy assay
Cell lysates were fractionated in 4%/8% SDS‐PAGE and immunoblotted for microtubule associated protein 1 light chain 3 isoforms LC3B I and II using antibodies obtained from Cell Signaling Technology. Autophagy was assessed by the relative ratio of LC3BII to LC3BI proteins.
Statistical analysis
Differences between study groups were analyzed by an one‐way analysis of variance (ANOVA) with a post‐hoc Holm–Sidak method. Results represent the average of three independent experiments (n = 3; mean ± SD, and *P < 0.05 was considered statistically significant), analyzed by Sigmplot software program 12.3 (Systat Software, Inc., San Jose, CA, www.sigmaplot.com).
Results
Level of total mTOR protein is higher in breast cancer cells compared to the noncancerous cells
To assess the status of total mTOR protein in breast cells, the WB analysis was performed on cancerous and noncancerous breast cell lines. As seen in Figure 1A, total mTOR protein is significantly higher in MCF‐7 and MDA‐MB‐231 breast cancer cells compared to the noncancerous MCF‐10A breast cells. The WB analysis also revealed high levels of phosphorylated mTOR (pmTOR) as well as phosphorylated P70‐S6K (pP70‐S6K), a downstream target of mTOR, in MCF‐7 cells (Fig. 1B). Immunoblotting for pP70‐S6K in the MCF‐7 cells revealed an increase in another band consistent in molecular weight with the total nonphosphorylated form of P70‐S6K protein as shown by the large dark arrow (Fig. 1B). Treatment of MCF‐7 cells with mTOR inhibitor PP242 (Fig. 1C) resulted in an inhibition of mTOR phosphorylation activity in a dose‐dependent manner as evident by the presence of lower levels of pmTOR and pP70‐S6K. However, it also resulted in a concomitant increase in the levels of both mTOR and P70‐S6K, as indicated by the small and large dark arrows, respectively (Fig. 1C). The dose‐dependent effect of PP242 is also represented as line graph (bottom panel, Fig. 1C), which further elucidates above findings. Together, our data suggest that total mTOR protein level is high in breast cancer cells, particularly in the MCF‐7 cells, which correlates with mTOR activity in these cells.
Figure 1
Total mTOR protein level is significantly higher in the breast cancer cells compared to their noncancerous counterparts. (A) Western blot (WB) of 100
μg of cell lysate protein from MCF‐10A, MCF‐7, and MDA‐MB‐231 cells was performed by immunoblotting with anti‐mTOR and anti‐β‐actin antibodies. A densitometric analysis of total mTOR level in the breast cancer cells MCF‐7 and MDA‐MB‐231 was compared to MCF‐10A nontumor cells (n = 3, mean ± SD, one‐way analysis of variance (ANOVA) and post‐hoc Holm–Sidak test *P < 0.05). (B) mTOR activity in MCF‐10A, MCF‐7, and MDA‐MB‐231 cells was determined by the WB analysis of mTOR target proteins using anti‐mTOR, anti‐phospho mTOR, anti‐phospho P70 S6K, anti P70 S6K, and anti‐β‐actin antibodies, respectively. (C) MCF‐7 cells treated with insulin (1 μmol/L) for 1 h and different concentrations of mTOR inhibitor PP242 (3, 9, 12, and 15 μmol/L) for 4 h. Cell lysates (100 μg) was immunoblotted for mTOR activity using antibodies as indicated in Panel B. A densitometric analysis of the indicated proteins is shown as a line graph.
Total mTOR protein level is significantly higher in the breast cancer cells compared to their noncancerous counterparts. (A) Western blot (WB) of 100
μg of cell lysate protein from MCF‐10A, MCF‐7, and MDA‐MB‐231 cells was performed by immunoblotting with anti‐mTOR and anti‐β‐actin antibodies. A densitometric analysis of total mTOR level in the breast cancer cells MCF‐7 and MDA‐MB‐231 was compared to MCF‐10A nontumor cells (n = 3, mean ± SD, one‐way analysis of variance (ANOVA) and post‐hoc Holm–Sidak test *P < 0.05). (B) mTOR activity in MCF‐10A, MCF‐7, and MDA‐MB‐231 cells was determined by the WB analysis of mTOR target proteins using anti‐mTOR, anti‐phospho mTOR, anti‐phospho P70 S6K, anti P70 S6K, and anti‐β‐actin antibodies, respectively. (C) MCF‐7 cells treated with insulin (1 μmol/L) for 1 h and different concentrations of mTOR inhibitor PP242 (3, 9, 12, and 15 μmol/L) for 4 h. Cell lysates (100 μg) was immunoblotted for mTOR activity using antibodies as indicated in Panel B. A densitometric analysis of the indicated proteins is shown as a line graph.
mTOR protein is more stable in breast cancer cells compared to noncancerous breast cells
The high level of total mTOR protein in the breast cancer cells could be attributed to increased expression and/or reduced degradation of mTOR protein. To investigate the possibility of reduced degradation of mTOR protein in the breast cancer cells, we compared the stability of mTOR protein using CHX) treatment and immunoblotted for mTOR protein (Fig. 2). Our data show that mTOR protein is more stable in MCF‐7 and MD‐MB‐231 breast cancer cells compared to the noncancerous MCF‐10A cells. In MCF‐10A cells, total mTOR protein level declined progressively following CHX treatment (Fig. 2A lanes 2 through 6). However, the level of this protein in both MCF‐7 and MDA‐MB‐231 cells remained relatively unchanged (Fig. 2B and C). These findings (Fig. 2D) suggest that proteolysis of mTOR protein most likely contributes to the lowering the level of this protein in the noncancerous breast cells, but this degradation process is, most likely, less effective in the breast cancer cells.
Figure 2
mTOR protein is more stable in breast cancer cells as compared to the noncancerous breast cells. MCF‐10A, MCF‐7, and MDA‐MB‐231 cells were harvested at 0.5, 1.5, 4, 8, and 12 h post 200 μg/mL cycloheximide (CHX) treatment. Total cell lysate of MCF‐10A (100 μg in panel A), MCF‐7 (50 μg in panel B), and MDA‐MB‐231(50 μg in panel C) was immunoblotted for mTOR and β‐actin. (D) A densitometric analysis of the mTOR protein band in the treatment groups relative to the untreated control groups with a pertinent trend line representation. In a separate experiment, MCF‐10A, MCF‐7, and MDA‐MB‐231 cells were treated with 2 μmol/L of MG132 for several time points (0, 12, 24 h). Total cell lysate of MCF‐10A (100 μg in panels E and H), MCF‐7 (50 μg in panels F and I) and MDA‐MB‐231(50 μg in panels G and J) was immunoblotted for mTOR, LC3B I, LC3B II and β‐actin.
mTOR protein is more stable in breast cancer cells as compared to the noncancerous breast cells. MCF‐10A, MCF‐7, and MDA‐MB‐231 cells were harvested at 0.5, 1.5, 4, 8, and 12 h post 200 μg/mL cycloheximide (CHX) treatment. Total cell lysate of MCF‐10A (100 μg in panel A), MCF‐7 (50 μg in panel B), and MDA‐MB‐231(50 μg in panel C) was immunoblotted for mTOR and β‐actin. (D) A densitometric analysis of the mTOR protein band in the treatment groups relative to the untreated control groups with a pertinent trend line representation. In a separate experiment, MCF‐10A, MCF‐7, and MDA‐MB‐231 cells were treated with 2 μmol/L of MG132 for several time points (0, 12, 24 h). Total cell lysate of MCF‐10A (100 μg in panels E and H), MCF‐7 (50 μg in panels F and I) and MDA‐MB‐231(50 μg in panels G and J) was immunoblotted for mTOR, LC3B I, LC3B II and β‐actin.To assess the nature of proteolysis of mTOR in these cells, we treated the cells with proteasome inhibitor MG132. In MCF‐10A cells, proteasome inhibition resulted in a decrease in the total mTOR protein in a time‐dependent manner (Fig. 2E, lanes 1–3). In contrast, proteasome inhibition caused no significant change in mTOR protein level in both MCF‐7 and MDA‐MB‐231 cells (Fig. 2F and G, respectively). This finding suggested a possibility of proteasome‐dependent mTOR degradation in normal breast epithelial cell, MCF‐10A, but not in the breast carcinoma cells, MCF‐7 and MDA‐MB‐231. Since ubiquitin–proteasome system (UPS) and autophagy are two main proteolytic pathways in eukaryotic cells and these two pathways work in a coordinated and complementary manner so that inhibition of proteasome induces autophagy 30, we examined this possibility. To test, we analyzed the cellular level of LC3B proteins, a family of well‐known autophagy markers 36. As shown in Figure 2H, proteasome inhibition in MCF‐10A cells was associated with increased LC3B II (Fig. 2H, lane 3), which is consistent with activation of autophagy 37. However, in MCF‐7 and MDA‐MB‐231 cells, proteasome inhibition increased both LC3B isoforms with more increase in LC3B I than LC3B II isoform in a time‐dependent manner (Fig. 2I and J, lanes 2 and 3). The accumulation of early intermediates of autophagy, such as LC3B I, likely represents a block in the later stages of autophagy 38. Induction of autophagy marker LC 3BII 39 in MCF‐10A cells following MG132 treatment suggests that proteasome inhibition may have caused induction of autophagy in MCF‐10A cells (Fig. 2H). This event most likely leads to the degradation of mTOR protein in these cells. However, proteasome inhibition in the breast cancer cells did not induce autophagy pathway in breast cancer cells, which had resulted in an increased level of mTOR protein in the cancer cells.
Metformin treatment of MCF‐7 breast cancer cells decreases the level of total mTOR protein
We next assessed whether inhibition of mTOR activity in breast cancer cells impacts mTOR degradation. Treatment of breast cancer cells with metformin and rapamycin, two known mTOR inhibitors, resulted in a significant decrease in the total level of mTOR protein in MCF‐7 cells (Fig. 3A). To assess whether the reduction in mTOR protein after metformin treatment could be due to protein degradation, we measured the mTOR half‐life by CHX experiments in metformin‐treated cells. Our data show higher rate of reduction in mTOR protein in the metformin‐treated cells (Fig. 3B). To test if proteasomal activity is involved in the metformin‐induced mTOR degradation, we treated the MCF‐7 cells with proteasome inhibitor, MG132, with or without metformin treatment. Results, shown in Figure 3C, indicate that MG132 treatment is unable to rescue metformin‐induced mTOR degradation. This finding suggests that mTOR reduction in MCF‐7 is not proteasome‐dependent. Assessment of the effect of metformin and rapamycin treatment on the status of mTOR downstream targets revealed a notable decrease in phospho P70‐S6K (pP70‐S6K). The level of P70‐S6K protein, however, remains mostly unchanged (Fig. 3C).
Figure 3
Metformin treatment results in a decrease in the total mTOR protein in breast cancer cells. (A) MCF‐7 cells were treated with insulin (1 μmol/L) for 30 min and/or metformin (75 mmol/L) or rapamycin (100 nmol/L) for 8 h. A quantity of 50 μg of total cell lysate was fractionated and immunoblotted with mTOR and β‐actin antibodies. A densitometric analysis of total mTOR level in different treatment conditions, as indicated, is shown as bar graphs (n = 3, mean ± SD, one‐way analysis of variance (ANOVA) and post‐hoc Holm–Sidak test *P < 0.05). (B) MCF‐7 cells were harvested at 0.5, 1.5, 4, 8, and 12 h post 200 μg/mL cycloheximide (CHX) treatment. A quantity of 50 μg protein of the total cell lysate was fractionated and immunoblotted for mTOR and β‐actin. (C) MCF‐7 cells were treated with metformin (75 mmol/L) and some cells were also treated with MG132 (2 μmol/L) for a total time of 12 h. Total cell lysate (50 μg) was immunoblotted for mTOR and β‐actin. (D) MCF‐7 cells were treated with insulin, metformin, and rapamycin as described in panel A. A quantity of 100 μg of cell lysate was fractionated and immunoblotted for phospho‐P70‐S6K, P70‐S6K, and β‐actin.
Metformin treatment results in a decrease in the total mTOR protein in breast cancer cells. (A) MCF‐7 cells were treated with insulin (1 μmol/L) for 30 min and/or metformin (75 mmol/L) or rapamycin (100 nmol/L) for 8 h. A quantity of 50 μg of total cell lysate was fractionated and immunoblotted with mTOR and β‐actin antibodies. A densitometric analysis of total mTOR level in different treatment conditions, as indicated, is shown as bar graphs (n = 3, mean ± SD, one‐way analysis of variance (ANOVA) and post‐hoc Holm–Sidak test *P < 0.05). (B) MCF‐7 cells were harvested at 0.5, 1.5, 4, 8, and 12 h post 200 μg/mL cycloheximide (CHX) treatment. A quantity of 50 μg protein of the total cell lysate was fractionated and immunoblotted for mTOR and β‐actin. (C) MCF‐7 cells were treated with metformin (75 mmol/L) and some cells were also treated with MG132 (2 μmol/L) for a total time of 12 h. Total cell lysate (50 μg) was immunoblotted for mTOR and β‐actin. (D) MCF‐7 cells were treated with insulin, metformin, and rapamycin as described in panel A. A quantity of 100 μg of cell lysate was fractionated and immunoblotted for phospho‐P70‐S6K, P70‐S6K, and β‐actin.
Metformin induces a perinuclear sequestration of mTOR protein in breast cancer cells
To further verify the involvement of protein degradation in the metformin‐mediated mTOR reduction in MCF‐7 cells, immunocytochemistry for the subcellular localization of mTOR protein was performed. MCF‐7 cells were treated with metformin or verapamil, an autophagy inducer that is known to induce autophagy in vascular smooth muscle cells as well as adenocarcinoma cells 40, 41. The cells were stained with AO for localization of acidic vacuoles in the cytoplasm. Verapamil treatment induced extensive vacuole formation in the cytoplasm of MCF‐7 cells as shown by the arrow heads in Figure 4B, bottom panel, with no apparent effect on mTOR staining in the rim of condensed cytoplasm surrounding the vacuoles. In contrast to verapamil treatment, metformin treatment of MCF‐7 cells did not induce a noticeable vacuolization of the cytoplasm, but it induced accumulation of mTOR protein in the vicinity of the nucleus as shown by the arrows in Figure 4C, bottom two panels, with no focal increase in autophagic activity of AO staining. These findings indicate that metformin treatment induced aggregation of mTOR protein in a perinuclear region consistent with aggresome formation which is known to allow sequestration of misfolded abundant protein molecules and facilitates their clearance by degradation 42.
Figure 4
Metformin induced a juxtanuclear aggregation of mTOR protein in the MCF‐7 cells. Confocal immunofluorescence and phase contrast images of MCF‐7 cells (40× magnification) stained with acridine orange (AO) and immunostained for mTOR protein. (A) Untreated (Control) MCF‐7 cells show an even distribution of mTOR protein in the cytoplasm and the absence of focal autophagosomes activity. (B) Arrow heads (in bottom section: Marge) point to vacuoles surrounded by a rim of cytoplasm with relatively intense evenly distributed staining of mTOR as well as Acridine Orange (AO) following treatment with 300 μmol/L of the autophagy‐inducer, verapamil, for 14 h. (C) Metformin (50 mmol/L) treatment for 10 h resulted in a clustering of mTOR proteins in a perinuclear position as indicated by the white arrows in two bottom sections (mTOR and Marge) with no focal increase in autophagosomes in the cytoplasm of MCF‐7 cells. (D) Negative control MCF‐7 cells stained only with AO without immunostaining for mTOR as control for potential background autofluorescence of cellular proteins.
Metformin induced a juxtanuclear aggregation of mTOR protein in the MCF‐7 cells. Confocal immunofluorescence and phase contrast images of MCF‐7 cells (40× magnification) stained with acridine orange (AO) and immunostained for mTOR protein. (A) Untreated (Control) MCF‐7 cells show an even distribution of mTOR protein in the cytoplasm and the absence of focal autophagosomes activity. (B) Arrow heads (in bottom section: Marge) point to vacuoles surrounded by a rim of cytoplasm with relatively intense evenly distributed staining of mTOR as well as Acridine Orange (AO) following treatment with 300 μmol/L of the autophagy‐inducer, verapamil, for 14 h. (C) Metformin (50 mmol/L) treatment for 10 h resulted in a clustering of mTOR proteins in a perinuclear position as indicated by the white arrows in two bottom sections (mTOR and Marge) with no focal increase in autophagosomes in the cytoplasm of MCF‐7 cells. (D) Negative control MCF‐7 cells stained only with AO without immunostaining for mTOR as control for potential background autofluorescence of cellular proteins.
The metformin‐induced decrease in mTOR protein level correlates positively with a decrease in the proliferation and migration potentials of MCF‐7 breast cancer cells
To examine the impact of metformin‐induced mTOR degradation on the phenotype of breast cancer cells, we compared the effect of various mTOR inhibitors on the proliferation and migration potentials of different breast cells. Metformin treatment of MCF‐7 cells was associated with a marked decrease in the cells proliferation compared to the other mTOR inhibitors (Fig. 5A). These findings were further corroborated by the effect of mTOR inhibitors on the migration of breast cell lines. As shown in the wound healing assay (Fig. 5B), MCF‐7 cells migration decreased profoundly with mTOR inhibition. The migration of MCF‐7 cells was assessed by changes in the wound size in the treatment groups at the designated time points compared to the control groups. The wound size is indicated by the length of thick white line across the wound region (Fig. 5C), which is inversely proportional to the migration potential of the cells. The results show that metformin treatment dramatically inhibited MCF‐7 cells migration (Fig. 5C, track iv compared to the other mTOR inhibitors PP242 and rapamycin (Fig. 5C, tracks iii and v, respectively). The line graph shows that metformin treatment in particular dramatically inhibited MCF‐7 cells migration.
Figure 5
Inhibition of mTOR reduces breast cells’ proliferation and migration. MCF‐10A, MCF‐7, and MDA‐MB‐231 cells were treated with insulin (1 μmol/L) for 12 h in the presence and absence of mTOR inhibitors PP242 (3 μmol/L), metformin (50 mmol/L), and rapamycin (100 nmol/L) for 12 h. (A) A MTT cell proliferation assay for each of the treatment groups was performed as described in Materials and Methods. *P < 0.05 (B) A wound healing assay was performed following a method as described in Materials and Methods. (C) The distance between the growing edges of migrating cells to bridge the wound was measured under microscope, which is inversely proportional to cells’ potential for migration. The length of thick white lines, which was measured and plotted in the line graph representation, measures the MCF‐7 cell migration in response to mTOR inhibitors.
Inhibition of mTOR reduces breast cells’ proliferation and migration. MCF‐10A, MCF‐7, and MDA‐MB‐231 cells were treated with insulin (1 μmol/L) for 12 h in the presence and absence of mTOR inhibitors PP242 (3 μmol/L), metformin (50 mmol/L), and rapamycin (100 nmol/L) for 12 h. (A) A MTT cell proliferation assay for each of the treatment groups was performed as described in Materials and Methods. *P < 0.05 (B) A wound healing assay was performed following a method as described in Materials and Methods. (C) The distance between the growing edges of migrating cells to bridge the wound was measured under microscope, which is inversely proportional to cells’ potential for migration. The length of thick white lines, which was measured and plotted in the line graph representation, measures the MCF‐7 cell migration in response to mTOR inhibitors.
Discussion
The findings of this work emphasized results of previous research about beneficial role of mTOR inhibition in breast cancer. This study showed an evidence that metformin and rapamycin resulted in a decrease in the overall level of mTOR protein in MCF‐7 breast cancer cells in addition to the inhibition of mTOR activation. Compared to other mTOR inhibitors, such as rapamycin and PP242, metformin treatment exerted more inhibitory effect on proliferation and migration of breast cancer cells. Furthermore, metformin elicited less rebound upregulation of total proteins in the mTOR pathway (namely, P70 S6K, as seen in Fig. 3C) in breast cancer cells, which potentially imposes a lesser risk of emergence of drug resistance to mTOR inhibition in breast cancer treatment regimens.This study revealed that total mTOR protein is higher in the breast cancer cells compared to the noncancerous cells, which correlated positively with the level of mTOR activity (Fig. 1). Therefore, high mTOR protein could be potentially involved in promoting the cancerous phenotype of breast cancer cells. This hypothesis is substantiated by the relatively strong correlation between the decreased total mTOR protein induced by metformin (Fig. 3) and the resultant inhibition of proliferation and migration of breast cancer cells (Fig. 5).The decreased mTOR protein degradation is one of the potential causes underlying the high mTOR protein level in breast cancer cells. Our findings revealed that mTOR protein is degraded more rapidly in the noncancerous breast cells compared to the breast cancer cells (Fig. 2). These findings suggest that the rate of mTOR degradation in breast cancer cells is, most likely, lower compared to that in the noncancerous cells. Such a difference between normal and cancer breast cells could be exploited to open a new avenue for novel antitumor agents by targeting these mechanisms preferentially in the breast cancer cells. Our data in Figures 3 and 4 provided evidence that metformin may be able to induce mTOR degradation in breast cancer cells by triggering aggresome formation.This study revealed an increase in the LC3B I more than LC3B II isoform in breast cancer cells upon proteasome inhibition (Fig. 2), which suggests that these cells are likely to initiate autophagy, yet unable to finish the conversion process. These findings together could, at least in part, explain the high mTOR level in the breast cancer cells and low mTOR level in the noncancerous cells.Treatment of MCF‐7 cells with a known autophagy inducer, verapamil 40, 41, induced vacuolization of the cytoplasm consistent with autophagosome formation, but metformin treatment; however, did not induce such vacuolization. Instead, metformin treatment induced accumulation of mTOR protein in a perinuclear aggresome. Accumulating proteins in cells are generally transported toward the microtubule organizing center, where they are sequestered into a single large perinuclear aggresome 43. Aggresome formation allows accumulated proteins to be sequestered in aggresome and facilitates their clearance by autophage 42 Our results show that metformin induced sequestration of mTOR in perinuclear aggregation (Fig. 4). Metformin treatment also resulted in increased degradation of cytoskeletal proteins, which could explain decreased viability and proliferation of MCF‐7 cells after metformin treatment. Our finding of growth regulation of metformin‐treated breast cancer cells (Fig. 5) is consistent with a previous finding which showed metformin‐induced inhibition of MCF‐7 cell proliferation in an AMPK‐dependent manner 44. Since activation of AMPK causes inhibition of mTOR 45, 46, 47, our finding raises the possibility that AMPK–mTOR signaling event might also be involved in breast cancer cell growth inhibition. Furthermore, metformin induced degradation of mTOR (Fig. 3) plays an important role in triggering cell growth inhibition. These findings provide a novel mechanism involving the mode of action of metformin in breast cancer cells, could be utilized in improving the efficacy of breast cancer treatment, and counteracting emergence of resistance in breast cancer cells to the treatment modalities.
Conflicts of Interest
No potential conflicts of interest were disclosed by the authors.
Authors: Xiao J Wang; Jun Yu; Sunny H Wong; Alfred S L Cheng; Francis K L Chan; Simon S M Ng; Chi H Cho; Joseph J Y Sung; William K K Wu Journal: Autophagy Date: 2013-07-11 Impact factor: 16.016
Authors: Daniel J Klionsky; Fabio C Abdalla; Hagai Abeliovich; Robert T Abraham; Abraham Acevedo-Arozena; Khosrow Adeli; Lotta Agholme; Maria Agnello; Patrizia Agostinis; Julio A Aguirre-Ghiso; Hyung Jun Ahn; Ouardia Ait-Mohamed; Slimane Ait-Si-Ali; Takahiko Akematsu; Shizuo Akira; Hesham M Al-Younes; Munir A Al-Zeer; Matthew L Albert; Roger L Albin; Javier Alegre-Abarrategui; Maria Francesca Aleo; Mehrdad Alirezaei; Alexandru Almasan; Maylin Almonte-Becerril; Atsuo Amano; Ravi Amaravadi; Shoba Amarnath; Amal O Amer; Nathalie Andrieu-Abadie; Vellareddy Anantharam; David K Ann; Shailendra Anoopkumar-Dukie; Hiroshi Aoki; Nadezda Apostolova; Giuseppe Arancia; John P Aris; Katsuhiko Asanuma; Nana Y O Asare; Hisashi Ashida; Valerie Askanas; David S Askew; Patrick Auberger; Misuzu Baba; Steven K Backues; Eric H Baehrecke; Ben A Bahr; Xue-Yuan Bai; Yannick Bailly; Robert Baiocchi; Giulia Baldini; Walter Balduini; Andrea Ballabio; Bruce A Bamber; Edward T W Bampton; Gábor Bánhegyi; Clinton R Bartholomew; Diane C Bassham; Robert C Bast; Henri Batoko; Boon-Huat Bay; Isabelle Beau; Daniel M Béchet; Thomas J Begley; Christian Behl; Christian Behrends; Soumeya Bekri; Bryan Bellaire; Linda J Bendall; Luca Benetti; Laura Berliocchi; Henri Bernardi; Francesca Bernassola; Sébastien Besteiro; Ingrid Bhatia-Kissova; Xiaoning Bi; Martine Biard-Piechaczyk; Janice S Blum; Lawrence H Boise; Paolo Bonaldo; David L Boone; Beat C Bornhauser; Karina R Bortoluci; Ioannis Bossis; Frédéric Bost; Jean-Pierre Bourquin; Patricia Boya; Michaël Boyer-Guittaut; Peter V Bozhkov; Nathan R Brady; Claudio Brancolini; Andreas Brech; Jay E Brenman; Ana Brennand; Emery H Bresnick; Patrick Brest; Dave Bridges; Molly L Bristol; Paul S Brookes; Eric J Brown; John H Brumell; Nicola Brunetti-Pierri; Ulf T Brunk; Dennis E Bulman; Scott J Bultman; Geert Bultynck; Lena F Burbulla; Wilfried Bursch; Jonathan P Butchar; Wanda Buzgariu; Sergio P Bydlowski; Ken Cadwell; Monika Cahová; Dongsheng Cai; Jiyang Cai; Qian Cai; Bruno Calabretta; Javier Calvo-Garrido; Nadine Camougrand; Michelangelo Campanella; Jenny Campos-Salinas; Eleonora Candi; Lizhi Cao; Allan B Caplan; Simon R Carding; Sandra M Cardoso; Jennifer S Carew; Cathleen R Carlin; Virginie Carmignac; Leticia A M Carneiro; Serena Carra; Rosario A Caruso; Giorgio Casari; Caty Casas; Roberta Castino; Eduardo Cebollero; Francesco Cecconi; Jean Celli; Hassan Chaachouay; Han-Jung Chae; Chee-Yin Chai; David C Chan; Edmond Y Chan; Raymond Chuen-Chung Chang; Chi-Ming Che; Ching-Chow Chen; Guang-Chao Chen; Guo-Qiang Chen; Min Chen; Quan Chen; Steve S-L Chen; WenLi Chen; Xi Chen; Xiangmei Chen; Xiequn Chen; Ye-Guang Chen; Yingyu Chen; Yongqiang Chen; Yu-Jen Chen; Zhixiang Chen; Alan Cheng; Christopher H K Cheng; Yan Cheng; Heesun Cheong; Jae-Ho Cheong; Sara Cherry; Russ Chess-Williams; Zelda H Cheung; Eric Chevet; Hui-Ling Chiang; Roberto Chiarelli; Tomoki Chiba; Lih-Shen Chin; Shih-Hwa Chiou; Francis V Chisari; Chi Hin Cho; Dong-Hyung Cho; Augustine M K Choi; DooSeok Choi; Kyeong Sook Choi; Mary E Choi; Salem Chouaib; Divaker Choubey; Vinay Choubey; Charleen T Chu; Tsung-Hsien Chuang; Sheau-Huei Chueh; Taehoon Chun; Yong-Joon Chwae; Mee-Len Chye; Roberto Ciarcia; Maria R Ciriolo; Michael J Clague; Robert S B Clark; Peter G H Clarke; Robert Clarke; Patrice Codogno; Hilary A Coller; María I Colombo; Sergio Comincini; Maria Condello; Fabrizio Condorelli; Mark R Cookson; Graham H Coombs; Isabelle Coppens; Ramon Corbalan; Pascale Cossart; Paola Costelli; Safia Costes; Ana Coto-Montes; Eduardo Couve; Fraser P Coxon; James M Cregg; José L Crespo; Marianne J Cronjé; Ana Maria Cuervo; Joseph J Cullen; Mark J Czaja; Marcello D'Amelio; Arlette Darfeuille-Michaud; Lester M Davids; Faith E Davies; Massimo De Felici; John F de Groot; Cornelis A M de Haan; Luisa De Martino; Angelo De Milito; Vincenzo De Tata; Jayanta Debnath; Alexei Degterev; Benjamin Dehay; Lea M D Delbridge; Francesca Demarchi; Yi Zhen Deng; Jörn Dengjel; Paul Dent; Donna Denton; Vojo Deretic; Shyamal D Desai; Rodney J Devenish; Mario Di Gioacchino; Gilbert Di Paolo; Chiara Di Pietro; Guillermo Díaz-Araya; Inés Díaz-Laviada; Maria T Diaz-Meco; Javier Diaz-Nido; Ivan Dikic; Savithramma P Dinesh-Kumar; Wen-Xing Ding; Clark W Distelhorst; Abhinav Diwan; Mojgan Djavaheri-Mergny; Svetlana Dokudovskaya; Zheng Dong; Frank C Dorsey; Victor Dosenko; James J Dowling; Stephen Doxsey; Marlène Dreux; Mark E Drew; Qiuhong Duan; Michel A Duchosal; Karen Duff; Isabelle Dugail; Madeleine Durbeej; Michael Duszenko; Charles L Edelstein; Aimee L Edinger; Gustavo Egea; Ludwig Eichinger; N Tony Eissa; Suhendan Ekmekcioglu; Wafik S El-Deiry; Zvulun Elazar; Mohamed Elgendy; Lisa M Ellerby; Kai Er Eng; Anna-Mart Engelbrecht; Simone Engelender; Jekaterina Erenpreisa; Ricardo Escalante; Audrey Esclatine; Eeva-Liisa Eskelinen; Lucile Espert; Virginia Espina; Huizhou Fan; Jia Fan; Qi-Wen Fan; Zhen Fan; Shengyun Fang; Yongqi Fang; Manolis Fanto; Alessandro Fanzani; Thomas Farkas; Jean-Claude Farré; Mathias Faure; Marcus Fechheimer; Carl G Feng; Jian Feng; Qili Feng; Youji Feng; László Fésüs; Ralph Feuer; Maria E Figueiredo-Pereira; Gian Maria Fimia; Diane C Fingar; Steven Finkbeiner; Toren Finkel; Kim D Finley; Filomena Fiorito; Edward A Fisher; Paul B Fisher; Marc Flajolet; Maria L Florez-McClure; Salvatore Florio; Edward A Fon; Francesco Fornai; Franco Fortunato; Rati Fotedar; Daniel H Fowler; Howard S Fox; Rodrigo Franco; Lisa B Frankel; Marc Fransen; José M Fuentes; Juan Fueyo; Jun Fujii; Kozo Fujisaki; Eriko Fujita; Mitsunori Fukuda; Ruth H Furukawa; Matthias Gaestel; Philippe Gailly; Malgorzata Gajewska; Brigitte Galliot; Vincent Galy; Subramaniam Ganesh; Barry Ganetzky; Ian G Ganley; Fen-Biao Gao; George F Gao; Jinming Gao; Lorena Garcia; Guillermo Garcia-Manero; Mikel Garcia-Marcos; Marjan Garmyn; Andrei L Gartel; Evelina Gatti; Mathias Gautel; Thomas R Gawriluk; Matthew E Gegg; Jiefei Geng; Marc Germain; Jason E Gestwicki; David A Gewirtz; Saeid Ghavami; Pradipta Ghosh; Anna M Giammarioli; Alexandra N Giatromanolaki; Spencer B Gibson; Robert W Gilkerson; Michael L Ginger; Henry N Ginsberg; Jakub Golab; Michael S Goligorsky; Pierre Golstein; Candelaria Gomez-Manzano; Ebru Goncu; Céline Gongora; Claudio D Gonzalez; Ramon Gonzalez; Cristina González-Estévez; Rosa Ana González-Polo; Elena Gonzalez-Rey; Nikolai V Gorbunov; Sharon Gorski; Sandro Goruppi; Roberta A Gottlieb; Devrim Gozuacik; Giovanna Elvira Granato; Gary D Grant; Kim N Green; Aleš Gregorc; Frédéric Gros; Charles Grose; Thomas W Grunt; Philippe Gual; Jun-Lin Guan; Kun-Liang Guan; Sylvie M Guichard; Anna S Gukovskaya; Ilya Gukovsky; Jan Gunst; Asa B Gustafsson; Andrew J Halayko; Amber N Hale; Sandra K Halonen; Maho Hamasaki; Feng Han; Ting Han; Michael K Hancock; Malene Hansen; Hisashi Harada; Masaru Harada; Stefan E Hardt; J Wade Harper; Adrian L Harris; James Harris; Steven D Harris; Makoto Hashimoto; Jeffrey A Haspel; Shin-ichiro Hayashi; Lori A Hazelhurst; Congcong He; You-Wen He; Marie-Joseé Hébert; Kim A Heidenreich; Miep H Helfrich; Gudmundur V Helgason; Elizabeth P Henske; Brian Herman; Paul K Herman; Claudio Hetz; Sabine Hilfiker; Joseph A Hill; Lynne J Hocking; Paul Hofman; Thomas G Hofmann; Jörg Höhfeld; Tessa L Holyoake; Ming-Huang Hong; David A Hood; Gökhan S Hotamisligil; Ewout J Houwerzijl; Maria Høyer-Hansen; Bingren Hu; Chien-An A Hu; Hong-Ming Hu; Ya Hua; Canhua Huang; Ju Huang; Shengbing Huang; Wei-Pang Huang; Tobias B Huber; Won-Ki Huh; Tai-Ho Hung; Ted R Hupp; Gang Min Hur; James B Hurley; Sabah N A Hussain; Patrick J Hussey; Jung Jin Hwang; Seungmin Hwang; Atsuhiro Ichihara; Shirin Ilkhanizadeh; Ken Inoki; Takeshi Into; Valentina Iovane; Juan L Iovanna; Nancy Y Ip; Yoshitaka Isaka; Hiroyuki Ishida; Ciro Isidoro; Ken-ichi Isobe; Akiko Iwasaki; Marta Izquierdo; Yotaro Izumi; Panu M Jaakkola; Marja Jäättelä; George R Jackson; William T Jackson; Bassam Janji; Marina Jendrach; Ju-Hong Jeon; Eui-Bae Jeung; Hong Jiang; Hongchi Jiang; Jean X Jiang; Ming Jiang; Qing Jiang; Xuejun Jiang; Xuejun Jiang; Alberto Jiménez; Meiyan Jin; Shengkan Jin; Cheol O Joe; Terje Johansen; Daniel E Johnson; Gail V W Johnson; Nicola L Jones; Bertrand Joseph; Suresh K Joseph; Annie M Joubert; Gábor Juhász; Lucienne Juillerat-Jeanneret; Chang Hwa Jung; Yong-Keun Jung; Kai Kaarniranta; Allen Kaasik; Tomohiro Kabuta; Motoni Kadowaki; Katarina Kagedal; Yoshiaki Kamada; Vitaliy O Kaminskyy; Harm H Kampinga; Hiromitsu Kanamori; Chanhee Kang; Khong Bee Kang; Kwang Il Kang; Rui Kang; Yoon-A Kang; Tomotake Kanki; Thirumala-Devi Kanneganti; Haruo Kanno; Anumantha G Kanthasamy; Arthi Kanthasamy; Vassiliki Karantza; Gur P Kaushal; Susmita Kaushik; Yoshinori Kawazoe; Po-Yuan Ke; John H Kehrl; Ameeta Kelekar; Claus Kerkhoff; David H Kessel; Hany Khalil; Jan A K W Kiel; Amy A Kiger; Akio Kihara; Deok Ryong Kim; Do-Hyung Kim; Dong-Hou Kim; Eun-Kyoung Kim; Hyung-Ryong Kim; Jae-Sung Kim; Jeong Hun Kim; Jin Cheon Kim; John K Kim; Peter K Kim; Seong Who Kim; Yong-Sun Kim; Yonghyun Kim; Adi Kimchi; Alec C Kimmelman; Jason S King; Timothy J Kinsella; Vladimir Kirkin; Lorrie A Kirshenbaum; Katsuhiko Kitamoto; Kaio Kitazato; Ludger Klein; Walter T Klimecki; Jochen Klucken; Erwin Knecht; Ben C B Ko; Jan C Koch; Hiroshi Koga; Jae-Young Koh; Young Ho Koh; Masato Koike; Masaaki Komatsu; Eiki Kominami; Hee Jeong Kong; Wei-Jia Kong; Viktor I Korolchuk; Yaichiro Kotake; Michael I Koukourakis; Juan B Kouri Flores; Attila L Kovács; Claudine Kraft; Dimitri Krainc; Helmut Krämer; Carole Kretz-Remy; Anna M Krichevsky; Guido Kroemer; Rejko Krüger; Oleg Krut; Nicholas T Ktistakis; Chia-Yi Kuan; Roza Kucharczyk; Ashok Kumar; Raj Kumar; Sharad Kumar; Mondira Kundu; Hsing-Jien Kung; Tino Kurz; Ho Jeong Kwon; Albert R La Spada; Frank Lafont; Trond Lamark; Jacques Landry; Jon D Lane; Pierre Lapaquette; Jocelyn F Laporte; Lajos László; Sergio Lavandero; Josée N Lavoie; Robert Layfield; Pedro A Lazo; Weidong Le; Laurent Le Cam; Daniel J Ledbetter; Alvin J X Lee; Byung-Wan Lee; Gyun Min Lee; Jongdae Lee; Ju-Hyun Lee; Michael Lee; Myung-Shik Lee; Sug Hyung Lee; Christiaan Leeuwenburgh; Patrick Legembre; Renaud Legouis; Michael Lehmann; Huan-Yao Lei; Qun-Ying Lei; David A Leib; José Leiro; John J Lemasters; Antoinette Lemoine; Maciej S Lesniak; Dina Lev; Victor V Levenson; Beth Levine; Efrat Levy; Faqiang Li; Jun-Lin Li; Lian Li; Sheng Li; Weijie Li; Xue-Jun Li; Yan-bo Li; Yi-Ping Li; Chengyu Liang; Qiangrong Liang; Yung-Feng Liao; Pawel P Liberski; Andrew Lieberman; Hyunjung J Lim; Kah-Leong Lim; Kyu Lim; Chiou-Feng Lin; Fu-Cheng Lin; Jian Lin; Jiandie D Lin; Kui Lin; Wan-Wan Lin; Weei-Chin Lin; Yi-Ling Lin; Rafael Linden; Paul Lingor; Jennifer Lippincott-Schwartz; Michael P Lisanti; Paloma B Liton; Bo Liu; Chun-Feng Liu; Kaiyu Liu; Leyuan Liu; Qiong A Liu; Wei Liu; Young-Chau Liu; Yule Liu; Richard A Lockshin; Chun-Nam Lok; Sagar Lonial; Benjamin Loos; Gabriel Lopez-Berestein; Carlos López-Otín; Laura Lossi; Michael T Lotze; Peter Lőw; Binfeng Lu; Bingwei Lu; Bo Lu; Zhen Lu; Frédéric Luciano; Nicholas W Lukacs; Anders H Lund; Melinda A Lynch-Day; Yong Ma; Fernando Macian; Jeff P MacKeigan; Kay F Macleod; Frank Madeo; Luigi Maiuri; Maria Chiara Maiuri; Davide Malagoli; May Christine V Malicdan; Walter Malorni; Na Man; Eva-Maria Mandelkow; Stéphen Manon; Irena Manov; Kai Mao; Xiang Mao; Zixu Mao; Philippe Marambaud; Daniela Marazziti; Yves L Marcel; Katie Marchbank; Piero Marchetti; Stefan J Marciniak; Mateus Marcondes; Mohsen Mardi; Gabriella Marfe; Guillermo Mariño; Maria Markaki; Mark R Marten; Seamus J Martin; Camille Martinand-Mari; Wim Martinet; Marta Martinez-Vicente; Matilde Masini; Paola Matarrese; Saburo Matsuo; Raffaele Matteoni; Andreas Mayer; Nathalie M Mazure; David J McConkey; Melanie J McConnell; Catherine McDermott; Christine McDonald; Gerald M McInerney; Sharon L McKenna; BethAnn McLaughlin; Pamela J McLean; Christopher R McMaster; G Angus McQuibban; Alfred J Meijer; Miriam H Meisler; Alicia Meléndez; Thomas J Melia; Gerry Melino; Maria A Mena; Javier A Menendez; Rubem F S Menna-Barreto; Manoj B Menon; Fiona M Menzies; Carol A Mercer; Adalberto Merighi; Diane E Merry; Stefania Meschini; Christian G Meyer; Thomas F Meyer; Chao-Yu Miao; Jun-Ying Miao; Paul A M Michels; Carine Michiels; Dalibor Mijaljica; Ana Milojkovic; Saverio Minucci; Clelia Miracco; Cindy K Miranti; Ioannis Mitroulis; Keisuke Miyazawa; Noboru Mizushima; Baharia Mograbi; Simin Mohseni; Xavier Molero; Bertrand Mollereau; Faustino Mollinedo; Takashi Momoi; Iryna Monastyrska; Martha M Monick; Mervyn J Monteiro; Michael N Moore; Rodrigo Mora; Kevin Moreau; Paula I Moreira; Yuji Moriyasu; Jorge Moscat; Serge Mostowy; Jeremy C Mottram; Tomasz Motyl; Charbel E-H Moussa; Sylke Müller; Sylviane Muller; Karl Münger; Christian Münz; Leon O Murphy; Maureen E Murphy; Antonio Musarò; Indira Mysorekar; Eiichiro Nagata; Kazuhiro Nagata; Aimable Nahimana; Usha Nair; Toshiyuki Nakagawa; Kiichi Nakahira; Hiroyasu Nakano; Hitoshi Nakatogawa; Meera Nanjundan; Naweed I Naqvi; Derek P Narendra; Masashi Narita; Miguel Navarro; Steffan T Nawrocki; Taras Y Nazarko; Andriy Nemchenko; Mihai G Netea; Thomas P Neufeld; Paul A Ney; Ioannis P Nezis; Huu Phuc Nguyen; Daotai Nie; Ichizo Nishino; Corey Nislow; Ralph A Nixon; Takeshi Noda; Angelika A Noegel; Anna Nogalska; Satoru Noguchi; Lucia Notterpek; Ivana Novak; Tomoyoshi Nozaki; Nobuyuki Nukina; Thorsten Nürnberger; Beat Nyfeler; Keisuke Obara; Terry D Oberley; Salvatore Oddo; Michinaga Ogawa; Toya Ohashi; Koji Okamoto; Nancy L Oleinick; F Javier Oliver; Laura J Olsen; Stefan Olsson; Onya Opota; Timothy F Osborne; Gary K Ostrander; Kinya Otsu; Jing-hsiung James Ou; Mireille Ouimet; Michael Overholtzer; Bulent Ozpolat; Paolo Paganetti; Ugo Pagnini; Nicolas Pallet; Glen E Palmer; Camilla Palumbo; Tianhong Pan; Theocharis Panaretakis; Udai Bhan Pandey; Zuzana Papackova; Issidora Papassideri; Irmgard Paris; Junsoo Park; Ohkmae K Park; Jan B Parys; Katherine R Parzych; Susann Patschan; Cam Patterson; Sophie Pattingre; John M Pawelek; Jianxin Peng; David H Perlmutter; Ida Perrotta; George Perry; Shazib Pervaiz; Matthias Peter; Godefridus J Peters; Morten Petersen; Goran Petrovski; James M Phang; Mauro Piacentini; Philippe Pierre; Valérie Pierrefite-Carle; Gérard Pierron; Ronit Pinkas-Kramarski; Antonio Piras; Natik Piri; Leonidas C Platanias; Stefanie Pöggeler; Marc Poirot; Angelo Poletti; Christian Poüs; Mercedes Pozuelo-Rubio; Mette Prætorius-Ibba; Anil Prasad; Mark Prescott; Muriel Priault; Nathalie Produit-Zengaffinen; Ann Progulske-Fox; Tassula Proikas-Cezanne; Serge Przedborski; Karin Przyklenk; Rosa Puertollano; Julien Puyal; Shu-Bing Qian; Liang Qin; Zheng-Hong Qin; Susan E Quaggin; Nina Raben; Hannah Rabinowich; Simon W Rabkin; Irfan Rahman; Abdelhaq Rami; Georg Ramm; Glenn Randall; Felix Randow; V Ashutosh Rao; Jeffrey C Rathmell; Brinda Ravikumar; Swapan K Ray; Bruce H Reed; John C Reed; Fulvio Reggiori; Anne Régnier-Vigouroux; Andreas S Reichert; John J Reiners; Russel J Reiter; Jun Ren; José L Revuelta; Christopher J Rhodes; Konstantinos Ritis; Elizete Rizzo; Jeffrey Robbins; Michel Roberge; Hernan Roca; Maria C Roccheri; Stephane Rocchi; H Peter Rodemann; Santiago Rodríguez de Córdoba; Bärbel Rohrer; Igor B Roninson; Kirill Rosen; Magdalena M Rost-Roszkowska; Mustapha Rouis; Kasper M A Rouschop; Francesca Rovetta; Brian P Rubin; David C Rubinsztein; Klaus Ruckdeschel; Edmund B Rucker; Assaf Rudich; Emil Rudolf; Nelson Ruiz-Opazo; Rossella Russo; Tor Erik Rusten; Kevin M Ryan; Stefan W Ryter; David M Sabatini; Junichi Sadoshima; Tapas Saha; Tatsuya Saitoh; Hiroshi Sakagami; Yasuyoshi Sakai; Ghasem Hoseini Salekdeh; Paolo Salomoni; Paul M Salvaterra; Guy Salvesen; Rosa Salvioli; Anthony M J Sanchez; José A Sánchez-Alcázar; Ricardo Sánchez-Prieto; Marco Sandri; Uma Sankar; Poonam Sansanwal; Laura Santambrogio; Shweta Saran; Sovan Sarkar; Minnie Sarwal; Chihiro Sasakawa; Ausra Sasnauskiene; Miklós Sass; Ken Sato; Miyuki Sato; Anthony H V Schapira; Michael Scharl; Hermann M Schätzl; Wiep Scheper; Stefano Schiaffino; Claudio Schneider; Marion E Schneider; Regine Schneider-Stock; Patricia V Schoenlein; Daniel F Schorderet; Christoph Schüller; Gary K Schwartz; Luca Scorrano; Linda Sealy; Per O Seglen; Juan Segura-Aguilar; Iban Seiliez; Oleksandr Seleverstov; Christian Sell; Jong Bok Seo; Duska Separovic; Vijayasaradhi Setaluri; Takao Setoguchi; Carmine Settembre; John J Shacka; Mala Shanmugam; Irving M Shapiro; Eitan Shaulian; Reuben J Shaw; James H Shelhamer; Han-Ming Shen; Wei-Chiang Shen; Zu-Hang Sheng; Yang Shi; Kenichi Shibuya; Yoshihiro Shidoji; Jeng-Jer Shieh; Chwen-Ming Shih; Yohta Shimada; Shigeomi Shimizu; Takahiro Shintani; Orian S Shirihai; Gordon C Shore; Andriy A Sibirny; Stan B Sidhu; Beata Sikorska; Elaine C M Silva-Zacarin; Alison Simmons; Anna Katharina Simon; Hans-Uwe Simon; Cristiano Simone; Anne Simonsen; David A Sinclair; Rajat Singh; Debasish Sinha; Frank A Sinicrope; Agnieszka Sirko; Parco M Siu; Efthimios Sivridis; Vojtech Skop; Vladimir P Skulachev; Ruth S Slack; Soraya S Smaili; Duncan R Smith; Maria S Soengas; Thierry Soldati; Xueqin Song; Anil K Sood; Tuck Wah Soong; Federica Sotgia; Stephen A Spector; Claudia D Spies; Wolfdieter Springer; Srinivasa M Srinivasula; Leonidas Stefanis; Joan S Steffan; Ruediger Stendel; Harald Stenmark; Anastasis Stephanou; Stephan T Stern; Cinthya Sternberg; Björn Stork; Peter Strålfors; Carlos S Subauste; Xinbing Sui; David Sulzer; Jiaren Sun; Shi-Yong Sun; Zhi-Jun Sun; Joseph J Y Sung; Kuninori Suzuki; Toshihiko Suzuki; Michele S Swanson; Charles Swanton; Sean T Sweeney; Lai-King Sy; Gyorgy Szabadkai; Ira Tabas; Heinrich Taegtmeyer; Marco Tafani; Krisztina Takács-Vellai; Yoshitaka Takano; Kaoru Takegawa; Genzou Takemura; Fumihiko Takeshita; Nicholas J Talbot; Kevin S W Tan; Keiji Tanaka; Kozo Tanaka; Daolin Tang; Dingzhong Tang; Isei Tanida; Bakhos A Tannous; Nektarios Tavernarakis; Graham S Taylor; Gregory A Taylor; J Paul Taylor; Lance S Terada; Alexei Terman; Gianluca Tettamanti; Karin Thevissen; Craig B Thompson; Andrew Thorburn; Michael Thumm; FengFeng Tian; Yuan Tian; Glauco Tocchini-Valentini; Aviva M Tolkovsky; Yasuhiko Tomino; Lars Tönges; Sharon A Tooze; Cathy Tournier; John Tower; Roberto Towns; Vladimir Trajkovic; Leonardo H Travassos; Ting-Fen Tsai; Mario P Tschan; Takeshi Tsubata; Allan Tsung; Boris Turk; Lorianne S Turner; Suresh C Tyagi; Yasuo Uchiyama; Takashi Ueno; Midori Umekawa; Rika Umemiya-Shirafuji; Vivek K Unni; Maria I Vaccaro; Enza Maria Valente; Greet Van den Berghe; Ida J van der Klei; Wouter van Doorn; Linda F van Dyk; Marjolein van Egmond; Leo A van Grunsven; Peter Vandenabeele; Wim P Vandenberghe; Ilse Vanhorebeek; Eva C Vaquero; Guillermo Velasco; Tibor Vellai; Jose Miguel Vicencio; Richard D Vierstra; Miquel Vila; Cécile Vindis; Giampietro Viola; Maria Teresa Viscomi; Olga V Voitsekhovskaja; Clarissa von Haefen; Marcela Votruba; Keiji Wada; Richard Wade-Martins; Cheryl L Walker; Craig M Walsh; Jochen Walter; Xiang-Bo Wan; Aimin Wang; Chenguang Wang; Dawei Wang; Fan Wang; Fen Wang; Guanghui Wang; Haichao Wang; Hong-Gang Wang; Horng-Dar Wang; Jin Wang; Ke Wang; Mei Wang; Richard C Wang; Xinglong Wang; Xuejun Wang; Ying-Jan Wang; Yipeng Wang; Zhen Wang; Zhigang Charles Wang; Zhinong Wang; Derick G Wansink; Diane M Ward; Hirotaka Watada; Sarah L Waters; Paul Webster; Lixin Wei; Conrad C Weihl; William A Weiss; Scott M Welford; Long-Ping Wen; Caroline A Whitehouse; J Lindsay Whitton; Alexander J Whitworth; Tom Wileman; John W Wiley; Simon Wilkinson; Dieter Willbold; Roger L Williams; Peter R Williamson; Bradly G Wouters; Chenghan Wu; Dao-Cheng Wu; William K K Wu; Andreas Wyttenbach; Ramnik J Xavier; Zhijun Xi; Pu Xia; Gengfu Xiao; Zhiping Xie; Zhonglin Xie; Da-zhi Xu; Jianzhen Xu; Liang Xu; Xiaolei Xu; Ai Yamamoto; Akitsugu Yamamoto; Shunhei Yamashina; Michiaki Yamashita; Xianghua Yan; Mitsuhiro Yanagida; Dun-Sheng Yang; Elizabeth Yang; Jin-Ming Yang; Shi Yu Yang; Wannian Yang; Wei Yuan Yang; Zhifen Yang; Meng-Chao Yao; Tso-Pang Yao; Behzad Yeganeh; Wei-Lien Yen; Jia-jing Yin; Xiao-Ming Yin; Ook-Joon Yoo; Gyesoon Yoon; Seung-Yong Yoon; Tomohiro Yorimitsu; Yuko Yoshikawa; Tamotsu Yoshimori; Kohki Yoshimoto; Ho Jin You; Richard J Youle; Anas Younes; Li Yu; Long Yu; Seong-Woon Yu; Wai Haung Yu; Zhi-Min Yuan; Zhenyu Yue; Cheol-Heui Yun; Michisuke Yuzaki; Olga Zabirnyk; Elaine Silva-Zacarin; David Zacks; Eldad Zacksenhaus; Nadia Zaffaroni; Zahra Zakeri; Herbert J Zeh; Scott O Zeitlin; Hong Zhang; Hui-Ling Zhang; Jianhua Zhang; Jing-Pu Zhang; Lin Zhang; Long Zhang; Ming-Yong Zhang; Xu Dong Zhang; Mantong Zhao; Yi-Fang Zhao; Ying Zhao; Zhizhuang J Zhao; Xiaoxiang Zheng; Boris Zhivotovsky; Qing Zhong; Cong-Zhao Zhou; Changlian Zhu; Wei-Guo Zhu; Xiao-Feng Zhu; Xiongwei Zhu; Yuangang Zhu; Teresa Zoladek; Wei-Xing Zong; Antonio Zorzano; Jürgen Zschocke; Brian Zuckerbraun Journal: Autophagy Date: 2012-04 Impact factor: 16.016
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5