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. 2018 Mar;19(3):e44767.
doi: 10.15252/embr.201744767. Epub 2018 Jan 15.

Differential roles of ERRFI1 in EGFR and AKT pathway regulation affect cancer proliferation

Junmei Cairns  1 , Brooke L Fridley  2   3 , Gregory D Jenkins  2 , Yongxian Zhuang  1 , Jia Yu  1 , Liewei Wang  4
Affiliations

Differential roles of ERRFI1 in EGFR and AKT pathway regulation affect cancer proliferation

Junmei Cairns et al. EMBO Rep. 2018 Mar.

Abstract

AKT signaling is modulated by a complex network of regulatory proteins and is commonly deregulated in cancer. Here, we present a dual mechanism of AKT regulation by the ERBB receptor feedback inhibitor 1 (ERRFI1). We show that in cells expressing high levels of EGFR, ERRF1 inhibits growth and enhances responses to chemotherapy. This is mediated in part through the negative regulation of AKT signaling by direct ERRFI1-dependent inhibition of EGFR In cells expressing low levels of EGFR, ERRFI1 positively modulates AKT signaling by interfering with the interaction of the inactivating phosphatase PHLPP with AKT, thereby promoting cell growth and chemotherapy desensitization. These observations broaden our understanding of chemotherapy response and have important implications for the selection of targeted therapies in a cell context-dependent manner. EGFR inhibition can only sensitize EGFR-high cells for chemotherapy, while AKT inhibition increases chemosensitivity in EGFR-low cells. By understanding these mechanisms, we can take advantage of the cellular context to individualize antineoplastic therapy. Finally, our data also suggest targeting of EFFRI1 in EGFR-low cancer as a promising therapeutic approach.

Keywords: AKT; AKT inhibitor; EGFR; ERRFI1; PHLPP.

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Figures

Figure 1
Figure 1. TCN cytotoxicity

  1. Representative TCN cytotoxicity dose–response curves. Two cell lines from each of the three ethnic groups were selected to illustrate a range of TCN cytotoxicity “dose–response” curves. AA (African Americans), CA (Caucasian Americans), HCA (Han Chinese Americans). The x‐axis indicates TCN dose, and the y‐axis indicates the surviving fraction after TCN exposure. Data represent mean ± SEM of three replicates.

  2. TCN IC50 among three ethnic groups. Horizontal line: median; box limits: first and third quantiles; whiskers: if no points exist reaching beyond 1.5*IQR (inter‐quartile range) of the 1st and 3rd quantiles, then it's the smallest or largest data value, otherwise it is 1st quantile – 1.5*IQR or 3rd quantile + 1.5*IQR; dots: values outside of 1.5*IQR of the 1st and 3rd quantile. Statistical analyses were performed with the F‐test from a linear regression model of gender (1 numerator df) or race (2 numerator df) vs. van der Waerdan transformed IC50.

  3. Gender effect on TCN IC50 values. Horizontal line: median; box limits: first and third quantiles; whiskers: if no points exist reaching beyond 1.5*IQR (inter‐quartile range) of the 1st and 3rd quantiles, then it's the smallest or largest data value, otherwise it is 1st quantile – 1.5*IQR or 3rd quantile + 1.5*IQR; dots: values outside of 1.5*IQR of the 1st and 3rd quantile. Statistical analyses were performed with the F‐test from a linear regression model of gender (1 numerator df) or race (2 numerator df) vs. van der Waerdan transformed IC50.

  4. Association of basal expression with TCN IC50 for 263 LCLs. The y‐axis represents the −log10 (P‐value) for the association of individual expression array probe set. Expression probe sets are plotted on the x‐axis based on the chromosomal locations. If genes had more than one probe set, the one with the lowest P‐value was plotted.

  5. Genomewide SNP association with TCN IC50 for 263 LCLs. The y‐axis represents −log10 (P‐value) for the association of each SNP with TCN IC50. SNPs are plotted on the x‐axis based on their chromosomal locations.

  6. Schematic diagram of the strategy of integrated analysis used to select genes for functional validation.

Figure EV1
Figure EV1. Functional validation of candidate genes in human tumor cell lines
SU86 cells were transfected with specific siRNA and then treated with 0, 0.01, 0.1, 1, 10, 25, 50, 100, and 500 μM TCN for 72 h. Cell survival was determined. The x‐axis indicates drug dose, and the y‐axis indicates the survival fraction after TCN exposure. Each point shows the mean values for three independent experiments; error bars represent ± SEM.
Figure EV2
Figure EV2. Functional validation of candidate genes in human tumor cell lines
MDA‐MB‐231 cells were transfected with specific siRNA and then treated with 0, 0.01, 0.1, 1, 10, 25, 50, 100, and 500 μM TCN for 72 h. Cell survival was determined. Each point shows the mean values for three independent experiments; error bars represent ± SEM.
Figure EV3
Figure EV3. Functional validation of candidate genes in LCL
LCL were transfected with specific siRNA and then treated with 0, 0.01, 0.1, 1, 10, 25, 50, 100, and 500 μM TCN for 72 h. Cell survival was determined using CYQUANT assay. Knockdown efficiency was determined using qRT–PCR. Each point shows the mean values for three independent experiments; error bars represent ± SEM.
Figure 2
Figure 2. ERRFI1 differentially regulates AKT phosphorylation in EGFR‐high and EGFR‐low cells

  1. MDA‐MB‐231 and SU86 cells were transfected with negative siRNA (siNeg) or indicated siRNA. Cell lysates were then blotted with the indicated antibodies. The mRNAs were extracted from the rest of the cells and subjected to qRT–PCR to determine knockdown efficiency. Error bars represent the SEM of three independent experiments. **P < 0.01. Statistical analyses were performed with Student's t‐test.

  2. Cell lysates from 13 human cancer cell lines were blotted with anti‐EGFR antibody. Quantification of EGFR protein relative to the GAPDH was determined. Error bars represent the SEM of three independent experiments.

  3. MDA‐MB‐468, PANC1, MDA‐MB‐231, SU86, U251, and HCT116 cells were transfected with two ERRFI1 siRNAs; 48 h later, cell lysates were subjected to Western blot. The ratio of phospho‐AKT473 /total AKT signal (pAKT473/AKT) was quantified using ImageJ. pAKT473/AKT in siNeg is set to 1 within each cell line. Error bars represent ± SEM of three independent experiments. The significant difference between siNeg and siERRFI1 is indicated by: **P < 0.01. Statistical analyses were performed with Student's t‐test.

Source data are available online for this figure.
Figure EV4
Figure EV4. ERRFI1 does not directly regulate the phosphorylation of AKT at Thr308

  1. MDA‐MB‐468 and U251 cell lysates were subjected to immunoprecipitation with control IgG or anti‐ERRFI1 antibody. The immunoprecipitates were blotted with the indicated antibodies.

  2. MDA‐MB‐468, PANC1, U251, and HCT116 cells were transfected with siERRFI1. Cell lysates were subjected to immunoprecipitation with control IgG or anti‐AKT antibody. The immunoprecipitates were blotted with the indicated antibodies.

Source data are available online for this figure.
Figure 3
Figure 3. ERRFI1 regulates AKT‐PHLPP interaction

  1. MDA‐MB‐468, PANC1, U251, and HCT116 cell lysates were subjected to immunoprecipitation with control IgG or anti‐ERRFI1 antibody. The immunoprecipitates were then blotted with the indicated antibodies. Quantifications of the Western blots were analyzed by ImageJ. To quantify each interaction, the amount of AKT or EGFR was first normalized back to the input level for each protein and then corrected by the amount of IPed protein, ERRFI1. Error bars represent ± SEM of three independent experiments. The significant difference between ERRFI1‐EGFR binding and ERRFI1‐AKT binding is indicated by: **P < 0.01. Statistical analyses were performed with Student's t‐test.

  2. Purified recombinant GST, GST‐AKT, and His‐ERRFI1 were incubated in cell‐free conditions. The interaction between AKT and ERRFI1 was then examined.

  3. MDA‐MB‐468, PANC1, U251, and HCT116 cell lysates were subjected to immunoprecipitation with control IgG or anti‐PHLPP antibody. The immunoprecipitates were blotted with the indicated antibodies. The interaction was then quantified in each cell line. The amount of AKT corrected by IPed PHLPP was calculated in each of the four cancer cells transfected with siNeg or siERRFI1s. The results were then corrected by the siNeg. The interaction in siNeg is set to 1 within each cell line. Error bars represent ± SEM of three independent experiments. The significant difference between siNeg and siERRFI1 is indicated by: **P < 0.01. Statistical analyses were performed with Student's t‐test.

Source data are available online for this figure.
Figure EV5
Figure EV5. ERRFI1 regulates AKT‐PHLPP interaction

  1. MDA‐MB‐468, PANC1, U251, and HCT116 cells were serum‐starved for 36 h and then treated with EGF (100 ng/ml) for 30 min prior to cell lysis. Cells lysates were subjected to immunoprecipitation with control IgG or anti‐ERRFI1 antibody. The immunoprecipitates were blotted with the indicated antibodies. The ERRFI1‐AKT and ERRFI1‐EGFR interaction was quantified using ImageJ. The immunoprecipitated ERRFI1 levels were normalized for each interaction and then corrected for MDA‐MB‐468 no EGF treatment. The interaction in no EGF‐treated (‐EGF) MDA‐MB‐468 is set to 1. Error bars represent ± SEM of three independent experiments. The significant difference between vehicle and EGF treatment is indicated by: **P < 0.01. Statistical analyses were performed with Student's t‐test.

  2. U251 and HCT116 cells were transfected with ERRFI1 construct. After 48 h, cells were lysed and subjected to immunoprecipitation with control IgG or anti‐PHLPP antibody. The immunoprecipitates were then blotted with the indicated antibodies.

  3. U251 and HCT116 cells from (B) were treated with increasing dose of gemcitabine (Gem) alone or in combination with 10 μM MK‐2206 2HCl (MK) for 72 h. Cell survival was then determined. Each point shows the mean values for three independent experiments; error bars represent ± SEM.

Source data are available online for this figure.
Figure 4
Figure 4. Binding of ERRFI1 to AKT2 and AKT3

  1. MDA‐MB‐468, PANC1, U251, and HCT116 cells lysates were subjected to immunoprecipitation with control IgG, anti‐AKT1, anti‐AKT2, or anti‐AKT3 antibody. The immunoprecipitates were blotted with the indicated antibodies. The supernatant of the precipitation were blotted with AKT1, AKT2, and AKT3 antibodies to ensure that the majority of the AKT isoform was precipitated with specific antibody.

  2. Quantification analysis of all three AKT isoforms. In the input sample, each AKT isoform was normalized to GAPDH, and then the normalized levels of AKT2 and AKT3 relative to AKT1 were determined within each cell line. Error bars represent ± SEM of three independent experiments.

  3. Quantifications of the interaction between ERRFI1 and three AKT isoforms using ImageJ. Antibodies against three AKT isoforms was used to pull down ERRFI1. The ERRFI1‐AKT isoform interactions were determined in a similar fashion as Fig 3C. Error bars represent ± SEM of three independent experiments. The significant difference between AKT2/or AKT3‐ERRFI1 and AKT1‐ERRFI1 interaction is indicated by: **P < 0.01. Statistical analyses were performed with Student's t‐test.

  4. Cells lysates from (A) were subjected to immunoprecipitation with control IgG or anti‐ERRFI1 antibody. The immunoprecipitates were blotted with the indicated antibodies. The interactions were quantified in a similar fashion as in (C). Error bars represent ± SEM of three independent experiments. The significant difference between AKT2/or AKT3‐ERRFI1 and AKT1‐ERRFI1 interaction is indicated by: **P < 0.01. Statistical analyses were performed with Student's t‐test.

Source data are available online for this figure.
Figure 5
Figure 5. ERRFI1 regulating AKT2/3‐PHLPP interaction depends on EGFR level
  1. A–D

    MDA‐MB‐468 (A), PANC1 (B), U251 (C), and HCT116 (D) were transfected with siNeg or siERRFI1. Cell lysates were subjected to immunoprecipitation with control IgG or anti‐PHLPP1 antibody. The immunoprecipitates were blotted with the indicated antibodies. AKT‐PHLPP interaction was quantified as described before. Error bars represent ± SEM of three independent experiments. The significant difference between siNeg and siERRFI1 is indicated by: *P < 0.05, **P < 0.01. Statistical analyses were performed with Student's t‐test.

  2. E

    U251 cells were transfected with GST‐tagged full‐length ERRFI1 (FL) or ERRFI1 truncation constructs; 48 h later, half of the cells were harvested and lysates were subjected to immunoprecipitation with control IgG or anti‐GST antibody. The immunoprecipitates were then blotted with the indicated antibodies.

  3. F

    The rest of the U251 cells from (E) were treated with increasing doses of TCN or gemcitabine for 3 days. Survival fraction was determined by CYQUANT assay. The x‐axis indicates drug dose, and the y‐axis indicates the survival fraction after drug exposure. Overexpression efficiency is shown in (E, input). Error bars represent ± SEM of three independent experiments.

Source data are available online for this figure.
Figure 6
Figure 6. EGFR level affects AKT‐ERRFI1 interaction

  1. MDA‐MB‐468 and PANC1 cells were transfected with siEGFR, and U251 and HCT116 cells were transfected with empty vector (EV) or EGFR construct; 48 h later, cell lysates were subjected to immunoprecipitation with control IgG, or anti‐AKT antibody. The immunoprecipitates were blotted with the indicated antibodies. Quantification of the binding was calculated. The interaction in cells transfected with siNeg or EV was set to 1 within each cell line. Error bars represent ± SEM of three independent experiments. The significant difference between siNeg and siEGFR, or EV and OE EGFR is indicated by: **P < 0.01. Statistical analyses were performed with Student's t‐test.

Source data are available online for this figure.
Figure 7
Figure 7. The effect of ERRFI1 on AKT activation and cell proliferation depends on the basal EGFR level
  1. A, B

    Knockdown of ERRFI1 increased proliferation and colony formation in MDA‐MB‐468 and PANC1, two EGFR‐high cells (A). Knockdown of ERRFI1 decreased proliferation and colony formation in U251 and HCT116 EGFR‐low cells (B). Cell proliferation was monitored every 12 h. The x‐axis indicates time post‐treatment, and the y‐axis indicates cell proliferation rate. The representative colony formation pictures from triplicate experiments are shown. Error bars represent ± SEM of three independent experiments; *P < 0.05, **P < 0.01 compared to siNeg. Statistical analyses were performed with Student's t‐test. Remaining cells were blotted with the indicated antibodies.

  2. C, D

    U251 and HCT116 cells were transfected with indicated siRNA. Cell lysates were blotted with the indicated antibodies. Cell proliferation and colony formation were assessed. Quantification of colony formation is shown. Error bars represent ± SEM of three independent experiments. **P < 0.01. Statistical analyses were performed with Student's t‐test.

Source data are available online for this figure.
Figure 8
Figure 8. The effect of ERRFI1 on response to therapy and AKT activation is cell context dependent
  1. A

    MDA‐MB‐468, PANC1, U251, and HCT116 cells transfected with siERRFI1 were treated with increasing doses of gemcitabine for 72 h, and cell survival was then determined. The x‐axis indicates drug dose, and the y‐axis indicates the survival fraction after gemcitabine exposure. Knockdown efficiency is shown in (D). Error bars represent the SEM of three independent experiments. Statistical analyses were performed with Student's t‐test.

  2. B

    MDA‐MB‐468 and PANC1 cells transfected with siERRFI1 were treated with increasing doses of gemcitabine (Gem) alone or in combination with either 10 μM gefitinib (G) or 10 μM TCN (T) for 72 h. Cell survival was then determined. Knockdown efficiency is shown in (D). Error bars represent the SEM of three independent experiments. Statistical analyses were performed with Student's t‐test.

  3. C

    U251 and HCT116 transfected with ERRFI1 plasmid were treated with Gem alone or in combination with either 10 μM T or 10 μM G for 72 h. Cell survival was then determined. Overexpression efficiency is shown in (E). Error bars represent the SEM of three independent experiments. Statistical analyses were performed with Student's t‐test.

  4. D, E

    MDA‐MB‐468 and U251 cells from (B and C) were treated with vehicle or 20 nM of Gem alone or in combination with either 10 μM of G or 10 μM of T for 12 h. Cells lysates were blotted with the indicated antibodies. The pAKT473/AKT ratio and pERK473/ERK ratio were quantified. The ratio in siNeg or EV is set to 1 within each cell line. Data represent the SEM of three independent experiments. **P < 0.01. Statistical analyses were performed with Student's t‐test.

Source data are available online for this figure.
Figure 9
Figure 9. ERRFI1 regulates organoid growth, therapy response and AKT activation depending on EGFR level
  1. A

    Organoid lysates from six human breast cancer PDX tumors were blotted with EGFR antibody. Quantification of EGFR protein relative to the GAPDH was determined. Error bars represent the SEM of three independent experiments.

  2. B, C

    EGFR‐high BJ06 and BJ16 organoids transfected with siERRFI1 were treated with vehicle (Veh) or 50 nM of gemcitabine (Gem) alone or in combination with either 10 μM gefitinib (G) or 10 μM TCN (T). Organoid growth was monitored every 3 days. Knockdown efficiency is shown in (F). Error bars represent the SEM of three independent experiments. **P < 0.01. Statistical analyses were performed with Student's t‐test.

  3. D, E

    EGFR‐low BJ43 and BJ44 organoids transfected with ERRFI1 plasmid were treated as above. Organoid growth was monitored every 3 days. Overexpression efficiency is shown in (G). Error bars represent the SEM of three independent experiments. **P < 0.01. Statistical analyses were performed with Student's t‐test.

  4. F, G

    BJ06 and BJ44 organoids were treated with vehicle or 50 nM of Gem alone or in combination with either 10 μM of G or 10 μM of T for 72 h. Organoid lysates were blotted with the indicated antibodies.

Source data are available online for this figure.
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