The INPP4B Tumor Suppressor Modulates EGFR Trafficking and Promotes Triple-Negative Breast Cancer

The PI3K pathway is one of the most frequently altered signaling pathways in human cancer, and genetic gain of oncogenes or loss of tumor suppressors that regulate or transduce the PI3K signal leads to tumorigenesis (1). In growth factor signaling, activation of class I PI3K results in production of the second messenger PI(3,4,5)P₃ (PIP₃), which recruits effector proteins such as the protein kinase AKT to promote cell growth, survival, migration, and metabolic reprogramming (2). Termination of PI3K signaling is achieved by dephosphorylation of PIP₃ by PTEN. Alternatively, PIP₃ can be removed by the sequential action of the SH2-domain containing inositol phosphatases 1 and 2 (SHIP1/2), to generate PI(3,4)P₂, followed by inositol polyphosphate 4-phosphatases A and B (INPP4A/B) and PTEN, ultimately generating the precursor phosphoinositides PI(3)P and PI(4)P (3–5).

Gain-of-function, oncogenic mutations in PIK3CA, the gene that encodes the p110α catalytic subunit of class Ia PI3K, occur with high frequency in estrogen receptor–positive (ER⁺) breast cancers (6). Triple-negative breast cancer (TNBC) is a subtype of breast cancer that lacks targeted therapy options due to lack of expression of ER or HER2, and exhibits a high degree of molecular heterogeneity (7). In contrast to ER⁺ breast cancers, PIK3CA is not frequently altered in TNBC; instead, inactivating mutations or deletion of PTEN and heterozygous deletion of INPP4B are frequent (8–10). Although PTEN has been established as a bona fide tumor suppressor in many cancer types and loss of PTEN sensitizes tumors to PI3K inhibitors (11), the function and mechanistic basis of INPP4B as a tumor suppressor is less clear. INPP4B was originally identified as a tumor suppressor in a genetic RNAi screen (12), and in cell-based and xenograft experiments, INPP4B inactivation leads to elevated PI(3,4)P₂ levels, AKT activation, and increased tumor growth (13, 14). In contrast, in ER⁺ cells and tumors, INPP4B can actually function as an oncogene through activation of the serum and glucocorticoid-regulated kinase 3 (SGK3) pathway (15, 16). Although loss of INPP4B protein expression is observed in 70% to 80% of TNBC patient samples (13, 17), to the extent that INPP4B negativity is identified as the most specific biomarker in basal-like breast cancer (18, 19), whether INPP4B loss functionally mediates TNBC development has not been evaluated in vivo.

The substrate of INPP4B, PI(3,4)P₂, belongs to the family of phosphoinositides where the head group of the inositol ring can be reversibly phosphorylated and dephosphorylated to generate seven distinct species, with preferential localization on distinct subcellular membrane compartments (20, 21). By binding and recruiting effector proteins, phosphoinositides regulate a multitude of cellular functions including endocytosis and intracellular vesicle trafficking, cytoskeletal remodeling, and signal transduction (20–22). Importantly, the mechanisms that regulate endocytosis, degradation, or recycling of receptor tyrosine kinases (RTK), including EGFR, MET, and FGFR, profoundly affect the amplitude and duration of signaling output and tumorigenesis (23–28). PI(3,4)P₂ recruits specific effector proteins such as lamellipodin (29) and TAPP1/2 (30), as well as effectors with more promiscuous phosphoinositide binding such as AKT (31), BAM32 (32), and sorting nexins (33–35). In addition to promoting AKT signaling, regulating actin cytoskeletal rearrangements, and facilitating clathrin-mediated endocytosis (36, 37), localized production of PI(3,4)P₂ at late endosome/lysosomes can suppress mTORC1 activation under specific nutrient-deprived conditions (38, 39). However, the precise mechanism by which INPP4B loss contributes to TNBCs has not been determined. Here, we have generated a mouse model of Inpp4b deletion in the context of TNBC, and have used it to decipher the role of PI(3,4)P₂ and RTK trafficking in tumorigenesis.

To determine whether genetic loss of INPP4B plays a functional role in the etiology of TNBC, we generated an INPP4B-deficient model by crossing Inpp4b phosphatase knockout mice (40) with a TNBC model, in which Trp53 and Brca1 were deleted upon K14-driven Cre expression in mammary epithelial cells (ref. 41; Supplementary Fig. S1A, for breeding schematics). We confirmed deletion of exon 22 by genotyping (Supplementary Fig. S1B) as described previously (42). As reported previously (40, 43), Inpp4b phosphatase deletion alone did not result in any appreciable phenotype, although we did observe age- and sex-dependent weight gain resulting in increased body weight in female mice more than 8 months of age with regular chow (Supplementary Fig. S1C). Similarly, modest alterations in glucose clearance when challenged with glucose, but not with insulin, were observed in Inpp4b heterozygous (HET) and knockout (KO) mice compared with wild-type (WT) littermates (Supplementary Fig. S1D). When crossed into the TNBC mouse model, Inpp4b phosphatase loss resulted in a dose-dependent increase in mammary tumor penetrance. Whereas mammary tumors developed in 17.2% of WT mice, 38% of Inpp4b HET mice developed mammary tumors, which increased to 53.7% in Inpp4b KO mice (Fig. 1A). This significant increase in mammary tumor penetrance was also manifested as increased mammary tumor–related death (Fig. 1B). In addition, we observed a slightly shortened life span for mammary tumor–bearing mice. The mean life span due to mammary tumor development for Inpp4b WT mice was 290.8 days, whereas that for Inpp4b HET mice was 232.9 days (P = 0.006, one-way ANOVA), and similarly 239 days for Inpp4b KO mice (P = 0.01, one-way ANOVA; Fig. 1C).

To understand the nature of mammary tumors developed from distinct Inpp4b genetic backgrounds, we analyzed tumor histology by IHC. The majority (76.19%) of tumors scored as mammary adenocarcinomas (Fig. 1D, a), although ductular carcinomas, mammary adenocarcinoma mixed with focal squamous cell carcinoma, and mammary cystic differentiated adenocarcinomas were also noted (Fig. 1D, b–d). The triple-negative nature of these mammary tumors was confirmed by ER, progesterone receptor, and HER2 IHC as previously reported using this TNBC model (42), as well as RNA-sequencing analyses using AIMS classifiers (Fig. 1E), PAM50 classifiers (Supplementary Fig. S1E), and unsupervised hierarchical clustering (Supplementary Fig. S1F).

In addition to its role in PI3K pathway signaling, loss of INPP4B elicits DNA-repair defects in ovarian cancer, which can result in chromosomal instability and increased tumor incidence (44). Therefore, we performed whole-exome sequencing and evaluated markers for genome instability, including the number of chromosome breaks (Fig. 2A), chromosomal translocations (Fig. 2B), and small insertions and deletions (Fig. 2C), but did not find any statistically significant differences in these parameters. In contrast, an increase in the number of point mutations was observed in INPP4B KO tumors compared with WT (Fig. 2D). Among the different point mutations, we observed a significant increase in C to T mutations when comparing Inpp4b HET or KO with WT tumors (Supplementary Fig. S2A and S2B), but no differences in T to other nucleotide mutations (Supplementary Fig. S2C). Overall, our data demonstrate that INPP4B loss does not affect gross chromosomal instability during tumor development in this model, although the number of single-nucleotide point mutations is increased.

We next compared the transcriptional profile of tumors developed from the INPP4B mouse models. Using gene set enrichment analysis (GSEA), we found an enhanced AKT pathway gene signature in INPP4B HET or KO mice compared with WT mice (Fig. 3A). Surprisingly, tumors developed from Inpp4b HET or KO mice also showed an increased MEK pathway gene signature (Fig. 3B). To confirm this observation in vitro, we knocked down INPP4B in breast epithelial MCF10A cells using short hairpin RNA (shRNA), and this also resulted in enhanced PI3K pathway activation, as reported by increased pAKT1, pAKT2, and pPRAS40, as well as increased ERK phosphorylation and pS6 (pS235/p236; Fig. 3C). Moreover, both the duration and magnitude of pAKT and pERK were enhanced in EGF-stimulated cells, in which INPP4B was transiently downregulated using siRNA (Fig. 3D; Supplementary Fig. S3A and S3B). The increase in pAKT/AKT and pERK/ERK was also observed in primary mammary epithelial cells stimulated with EGF over a time course (Supplementary Fig. S3C). Phenotypically, INPP4B reduction promoted MCF10A cell proliferation under serum-deprived conditions when supplemented with EGF (Fig. 3E), but not in cells grown with complete media (Supplementary Fig. S3D). Finally, overexpression of INPP4B in the TNBC cell line MDA-MB-231 resulted in significantly reduced spheroid growth in 3-D (Supplementary Fig. S3E). In summary, the in vivo and in vitro results above show INPP4B loss promotes both PI3K and ERK pathway activation, which may contribute to mammary tumor development in TNBC.

We reasoned that if TNBC cells with reduced INPP4B levels become more dependent on PI3K and ERK signaling for tumor initiation and/or maintenance, then pathway inhibition may show a more pronounced effect compared with cells that retain INPP4B. We first tested this hypothesis in vitro, and generated INPP4B knockdown cells (using siRNA/shRNA and CRISPR/Cas9; Supplementary Fig. S4A) and treated cells with PI3K pathway inhibitors, including the pan class I PI3K inhibitor BKM-120 and the catalytic AKT inhibitor GDC0068. We found that in both cases INPP4B loss increased sensitivity to inhibitor treatment, resulting in statistically significant decreases in IC₅₀ to both BKM120 (Fig. 4A; Supplementary Fig. S4B and S4C, n = 3) and GDC0068 (Fig. 4B; Supplementary Fig. S4D, n = 3). We also observed a trend showing decreased IC₅₀ for the MEK inhibitor trametinib; however, this decrease was not statistically significant (Supplementary Fig. S4E). To test this hypothesis in vivo, we implanted tumors developed from Inpp4b WT, HET, or KO backgrounds into the mammary glands of recipient nude mice (45), and carried out in vivo drug treatment using predetermined doses once tumors reached 7 to 8 mm in diameter (ref. 42; Fig. 4C). We confirmed the efficacy of BKM120, the p110α-specific PI3K inhibitor BYL719, and the MEK inhibitor trametinib in pathway inhibition by immunoblotting tumor lysates for pAKT and pERK, respectively (Supplementary Fig. S4F and S4G). We found that both BKM120 and BYL719 improved overall survival (Fig. 4D), whereas trametinib delayed tumor growth (Fig. 4E) without affecting overall survival (Supplementary Fig. S4H). However, Inpp4b HET and KO tumors were more sensitive to either BKM120 or BYL719 (Fig. 4F) or trametinib (Fig. 4G) when compared with tumors developed from the INPP4B WT background. Therefore, INPP4B loss confers sensitivity to both PI3K and ERK pathway inhibition.

INPP4B is a lipid phosphatase that dephosphorylates the 4′ position of PI(3,4)P₂ to generate PI(3)P, and therefore loss or inactivation of INPP4B leads to increased pools of PI(3,4)P₂. Consistent with this model, CRISPR/Cas9-mediated INPP4B reduction in MCF10A cells resulted in increased EGF-stimulated PI(3,4)P₂ as measured by ³H-inositol labeling, whereas the levels of other phosphoinositides were unaffected (Fig. 5A; Supplementary Fig. S5A). PI(3,4)P₂ has been shown to be localized to the plasma membrane where it regulates clathrin-mediated endocytosis, as well as at intracellular vesicles where it stimulates AKT signaling (46, 47). Consistent with previous studies, immunofluorescence (IF) staining using anti-PI(3,4)P₂ antibodies in INPP4B-downregulated cells revealed an increase in PI(3,4)P₂ in intracellular vesicles following EGF stimulation (Fig. 5B and C). In contrast, the PI(3,4)P₂ plasma membrane pool only transiently increased at 3 minutes and remained largely unaffected at other timepoints upon INPP4B downregulation (Supplementary Fig. S5B and S5C). These data are consistent with the model that INPP4B contributes to the intracellular endomembrane pool of PI(3,4)P₂ biosynthesis upon growth factor stimulation, leading to downstream pathway activation.

In initial INPP4B knockdown experiments, we noticed that in addition to enhanced pAKT and pERK, total EGFR protein levels were consistently elevated compared with control cells (Figs. 3D and 6A). Increased EGFR expression was confirmed by siRNA-mediated downregulation of INPP4B, with no alterations in EGFR and slight change in MET mRNA transcript levels (Fig. 6B; Supplementary Fig. S6A–S6C). Given the established functions of phosphoinositides, including PI(3,4)P₂ in RTK trafficking (36), we investigated whether INPP4B loss affects RTK trafficking and signaling. We found that although total EGFR protein levels decreased in control siRNA–treated cells upon a time course of EGF stimulation, degradation of EGFR was delayed in INPP4B siRNA–treated cells (Fig. 6C and D). This was confirmed using INPP4B CRISPR/Cas9 cells stimulated with EGF (Fig. 6E; Supplementary Fig. S6D and S6E). However, INPP4B reduction did not alter sensitivity to the EGFR inhibitor erlotinib (Supplementary Fig. S6F). In TNBC, EGFR overexpression has been shown to play an important role during tumor development, although other RTKs including MET also contribute (48). Consistent with this, total MET protein levels are increased in response to hepatocyte growth factor (HGF) stimulation in INPP4B knockdown cells compared with control (Fig. 6F). In addition, pAKT and pERK were enhanced and prolonged in response to HGF (Fig. 6F), similar to that observed in EGF-stimulated cells.

Next, we tracked EGFR subcellular localization dynamics upon EGF stimulation using IF. At early timepoints, accumulation of EGFR in intracellular vesicles was not affected by INPP4B reduction in response to EGF (Supplementary Fig. S6G). In contrast, by 60 and 90 minutes, EGFR trafficked to a perinuclear region in control siRNA–treated cells, but remained scattered in INPP4B siRNA–treated cells. By 180 minutes, EGFR staining was significantly diminished in control cells, whereas in INPP4B knockdown cells, EGFR was still detectable with a perinuclear staining pattern (Fig. 6G; Supplementary Fig. S6H).

The prediction from the in vitro INPP4B knockdown experiments would be that in the setting of INPP4B loss in vivo, EGFR protein levels would be elevated. IHC staining of EGFR on the INPP4B mouse tumors revealed that although both tumors derived from the INPP4B WT cohort showed low levels of EGFR expression, five of six tumors from the Inpp4b HET or seven of 10 tumors from the KO backgrounds showed medium- to high-level expression of total EGFR (Fig. 6H).

To further investigate trafficking of RTKs in the context of INPP4B loss, we performed IF to measure colocalization of EGFR with endosomal markers. At all timepoints tested, the intensity of staining and vesicle size of the early endosome antigen 1 (EEA1) marker was not affected upon INPPB reduction with siRNA (Supplementary Fig. S7A and S7B). Similarly, the colocalization of EEA1 with EGFR in INPP4B siRNA–treated cells was unaffected at early timepoints, but persisted at later timepoints (60, 90, and 180 minutes; Fig. 7A; Supplementary Fig. 7C). At early timepoints (10 and 30 minutes), we also did not observe significant differences in the staining intensity of the late endosome/lysosome marker CD63 or CD63-positive vesicle size (Fig. 7B). In contrast, at later timepoints when EGFR trafficks to the late endosome/lysosome for degradation, CD63 intensity decreased with a concomitant increase in vesicle size in control cells; however, there was no increase in INPP4B knockdown cells (Fig. 7B). Consistent with this observation, the dynamics of EGFR–CD63 colocalization were significantly altered: In control cells, internalized EGFR progressively accumulated in CD63-positive late endosomes before being degraded, whereas a much less pronounced late endosomal EGFR accumulation was observed in INPP4B knockdown cells (Fig. 7C; Supplementary Fig. S7D). These data suggest a defect in EGFR trafficking from early endosomes to late endosomes/lysosomes. Furthermore, we found increased recycling of EGFR to the plasma membrane in INPP4B siRNA–treated cells (Fig. 7D), explaining its increased surface levels (Fig. 7E). Our data indicate that loss of INPP4B delays trafficking of the EGFR from early endosomes to the late endosomes/lysosomes, thus delaying receptor degradation and thereby sustaining downstream signaling.

In this study, we developed a genetically engineered mouse model (GEMM) to provide evidence that INPP4B inactivation drives TNBC. Mechanistically, we uncovered a function for INPP4B in regulating the trafficking and degradation of EGFR and MET. INPP4B reduction results in increased PI(3,4)P₂ accumulation in intracellular vesicles, delaying trafficking of EGFR from early endosomes to late endosomes/lysosomes upon EGF stimulation, while promoting recycling of EGFR to the cell surface. As a result, INPP4B loss delays EGFR degradation with a concomitant prolonged duration and amplitude of both AKT and ERK signaling, thereby promoting tumorigenesis. Consequently, INPP4B inactivation sensitizes TNBC cells to both PI3K and MEK inhibitors in vitro and in vivo.

Transcriptional profiling has revealed the extensive genetic heterogeneous nature of TNBC, with multiple distinct subgroups classified according to unique expression profiles with important clinical implications (49). Similarly, large-scale sequencing studies have detected diverse but low-frequency oncogenic mutations in numerous genes in TNBC, many of which contribute to PI3K and ERK pathway (8, 50–52). Approximately 40% of patients with ER⁺ breast cancer harbor activating PIK3CA mutations, and the p110α-specific inhibitor Piqray (alpelisib) was recently approved for the treatment of PIK3CA-mutant, ER⁺ breast cancer in combination with fulvestrant in postmenopausal women with advanced or metastatic disease (53). In contrast, less than 10% of patients with TNBC possess oncogenic PIK3CA mutations, and to date there is no approved molecular targeted therapy for TNBC. Given the frequency of PI3K pathway hyperactivation in TNBC, targeting aberrant PI3K pathway activation remains a promising option. In our GEMM, mammary tumors resulting from INPP4B HET or homozygous deletion mice were more sensitive to PI3K pathway inhibition (Fig. 4), suggesting that loss of INPP4B may be a predictive marker for sensitivity to PI3K inhibition, consistent with previous studies in cell lines (54).

Because AKT functions to modulate phenotypes associated with malignancy, including proliferation, survival, migration, and metabolism, and is frequently hyperactivated in many cancers, numerous small-molecule inhibitors have been developed for clinical use (2). As single agents, AKT inhibitors have shown minimal efficacy in clinical trials (55). In our GEMM, INPP4B loss increased sensitivity to the AKT inhibitor GDC0068 (ipatasertib) in vitro. In clinical trials, the AKT inhibitor AZD5363 did not significantly improve progression-free survival compared with paclitaxel alone in ER⁺ breast cancer harboring PIK3CA mutations (NCT01625286; ref. 56). In contrast, addition of GDC0068 to paclitaxel as neoadjuvant therapy in patients with early-stage TNBC harboring PIK3CA/AKT/PTEN alterations showed a favorable response (complete response 39% for GDC0068 + paclitaxel vs. 9% for paclitaxel alone; NCT02301988; ref. 57). Given that INPP4B loss is common in TNBC (13, 14, 18, 19) and promotes hyperactivation of AKT, it would therefore be interesting to evaluate the response of INPP4B-deficient TNBC to AKT inhibitors in vivo and in the clinic.

Compared with ER⁺ or ERBB2 (HER2)-amplified breast cancer, EGFR overexpression is a frequent event in TNBC. Depending on the patient population and IHC test used, 13% to 76% of TNBC tumors overexpress EGFR at the protein level (58). Yet, analyses of METABRIC and The Cancer Genome Atlas reveal that only approximately 5% of patients harbor ERBB1 (EGFR) gene amplification (59). This indicates that additional mechanisms must exist to account for increased EGFR protein in TNBC. Several mechanisms have been shown, including loss of PTEN (60), loss of BRCA1 (61), and increased expression of tissue transglutaminase (62). Our data are indicative of an additional mechanism whereby loss of INPP4B increases EGFR stability, contributing to enhanced EGFR downstream signaling.

EGFR overexpression in TNBC indicates that it could serve as a potential therapeutic vulnerability for this subtype of breast cancer. However, numerous anti-EGFR therapeutics used as single agents or in combination with chemotherapy in TNBC have not shown durable therapeutic responses (63–66). One can speculate that more accurate patient stratification could improve treatment outcomes, for example, by accruing patients expressing elevated levels of EGFR. In our studies, drug sensitivity assays with erlotinib administered in cells with INPP4B reduction did not appreciably shift the IC₅₀. These data are consistent with previous observations which showed that EGFR activation is required for initial endocytosis (27, 67). Because erlotinib inhibits EGFR phosphorylation, and stabilization of EGFR upon INPP4B reduction occurs after ligand-induced receptor endocytosis, EGFR inhibition would be predicted to be ineffective in INPP4B-null tumors.

The mechanism by which loss of INPP4B and increased vesicular PI(3,4)P₂ affect EGFR degradation and recycling, and as a result total EGFR expression, is presently unknown. Upon ligand-induced clathrin-mediated endocytosis, ubiquitinated EGFR and endosomal PI(3)P recruit endosomal sorting complexes required for transport (ESCRT) for sorting into intraluminal vesicles for degradation (68–70). The INPP4B interactome has not been deciphered and it is not yet clear whether INPP4B can directly affect the ubiquitin ligase activity of CBL docked onto EGFR, thereby affecting EGFR/Hrs interaction, as has been shown for SHIP₂ (71). Alternatively, INPP4B could directly or indirectly interact with ESCRT complexes, because INPP4A/B also localizes to endosomes (43, 72, 73). Our results show that INPP4B depletion results in increased PI(3,4)P₂ in intracellular vesicles, consistent with previous studies (46, 74). Although a subset of PI(3,4)P₂-positive vesicles colocalize with EEA1, our preliminary studies show that only a small percentage (1.7% to 6.1% depending on the timepoint) colocalize with internalized EGFR. In contrast, up to 50% of EGFR-positive vesicles are also positive for EEA1. Within this small subset of EGFR-positive vesicles, PI(3,4)P₂ intensities were comparable between control siRNA- and INPP4B siRNA–treated cells. Several potential mechanisms may contribute to defects in RTK degradation and enhanced recycling. First, a block in PI(3,4)P₂ degradation due to INPP4B loss may result in the reduction of a local endosomal pool of PI(3)P derived from PI(3,4)P₂ [i.e., a minor pool not separable from the total cellular PI(3)P pool in our high-performance liquid chromatography (HPLC) analysis], upstream of PI(3,5)P₂ production via PIKFYVE and EGFR degradation. In addition, failure to dephosphorylate PI(3,4)P₂ via INPP4B may promote funneling of PI(3,4)P₂ into an alternative PTEN-mediated degradation pathway toward PI(4)P (3), a lipid that promotes recycling to the cell surface (75, 76). Alternatively, PI(3,4)P₂-rich endomembranes may recruit effectors to promote recycling. One possibility is that SNX18, a PX-BAR–containing sorting nexin that belongs to the SNX9/18/30 family, may contribute to this mechanism. SNX18 binds to PI(3,4)P₂ as well as other phosphoinositides (33, 47) and colocalizes with RAB11 but not EEA1, and has been shown to promote tubulated recycling endomembranes (77–79).

Traditionally viewed as a breakdown product of PI(3,4,5)P₃, recent studies have shown that PI(3,4)P₂ has important signaling roles in its own right (36, 80). Different enzymes contribute to the localized production of this signaling lipid, exerting seemingly different biological activities. For example, class II PI3K C2α at clathrin-coated pits is important for the synthesis of PI(3,4)P₂ to mediate constriction of late-stage clathrin-coated pits (47, 81, 82). Class II PI3K C2β at late endosomes/lysosomes during growth factor starvation suppresses mTORC1 activity (39). Alternatively, class I PI3K activation by RTKs, such as EGFR, generates PI(3,4,5)P₃, which is dephosphorylated by 5′ phosphatases to give rise to PI(3,4)P₂, contributing to endosomal PI(3,4)P₂ (5). Although the relative quantitative contribution from each of the routes during EGFR intracellular trafficking is not precisely understood, it is generally accepted that degradation from PI(3,4,5)P₃ contributes to a significant fraction of PI(3,4)P₂ in intracellular vesicles upon RTK activation (36, 37). Additional studies are required to determine whether class II PI3Ks can function in an analogous manner to INPP4B in TNBC etiology, especially given their importance in physiology and disease (83).

Recent studies have found that PTEN can also degrade PI(3,4)P₂, and that combined depletion of INPP4B and PTEN results in synergistic accumulation of PI(3,4)P₂ and AKT activation (3). Because PTEN inactivation is also a frequent event in TNBC, and combined PTEN and INPP4B loss leads to AKT hyperactivation, this provides additional rationale for preclinical and clinical studies for AKT inhibitors in this setting. At the same time, it is important to note that although INPP4B functions as a bona fide tumor suppressor in TNBC and other cancers, studies in cell lines and mice have shown that in ER⁺ breast cancer and colorectal cancer, INPP4B actually functions as an oncogene, potentially due to copy-number gain or overexpression in these tumor types (15, 84).

In summary, we have developed a mouse model of TNBC in which INPP4B functions as a tumor suppressor and regulates RTK trafficking and degradation. We propose a model whereby INPP4B inactivation results in PI(3,4)P₂ accumulation in intracellular vesicles, delaying degradation of RTKs, prolonging both PI3K and ERK signaling and tumorigenesis, and leading to sensitization to pathway inhibitors.

Animal experiments were conducted in accordance with Institutional Animal Care and Use Committee–approved protocols (# 099-2015) at Beth Israel Deaconess Medical Center (Boston, MA). K14cre; Brca1^flox/flox; Trp53^flox/flox mice were obtained from Dr. Jos Jonkers (Netherlands Cancer Institute, Amsterdam, the Netherlands), and INPP4B del/del mice were obtained from Dr. Takehiko Sasaki (Tokyo Medical and Dental University, Tokyo, Japan). Mouse breeding was carried out as shown in Supplementary Fig. S1A, and genotyping was carried out as described previously (40, 41).

Tumor pieces were cut into 2 mm in diameter and inserted into the fourth mammary fat pad of 8- to 10-week-old recipient mice via a 0.5 cm² incision in the skin. The skin was closed with VetBond.

Once tumors reached approximately 8 mm in diameter as measured by electrical caliper (Thermo Fisher Scientific), mice were treated with indicated drugs obtained from MedChemExpress, LLC (BKM120, BYL719, and trametinib). For oral gavage, 100 μL of drug suspension was administrated daily for 6 consecutive days, followed by one drug holiday. Tumor sizes were measured twice a week (length and width), and tumor volume was calculated as (3.14 × length × width × width/6).

Genomic DNA from tumor or liver samples was prepared following the protocol for Promega ReliaPrep Tissue DNA Miniprep System (A2051). SureSelect or NimbleGen Mouse Exome Capture Kits were used to generate DNA library according to the manufacturer's instructions. Sequencing was carried out using HiSeq4000 (Illumina) using paired-end clustering and 51 × 2 cycles sequencing.

See the Supplementary Methods for details. Somatic mutations were identified upon removing any mutations found in any tail, liver, or normal mammary control samples in mouse dbSNP, or with insufficient coverage in the control samples. Mutations were annotated with SnpEff. Copy-number variants were called using CNVkit after removing low-quality reads. Sample-specific thresholds were computed to call amplifications and deletions.

Total RNA was prepared following the protocol for Promega Relia-Prep RNA Tissue Miniprep System (Z6111), and RNA integrity and concentration were measured using the Agilent 2100 Bioanalyzer (Agilent Technologies). cDNA libraries were prepared from 15 to 35 ng RNA starting material (RNA integrity number values > 6.0), using the TruSeq RNA Sample Preparation Kit (Illumina) according to the manufacturer's instructions, and quality was checked on an Agilent 2100 Bioanalyzer (Agilent Technologies). Sequencing was carried out on the HiSeq 2500 (Illumina) using paired-end clustering and 51 × 2 cycles sequencing.

Tumors and cells were lysed in RIPA lysis buffer with protease inhibitors (Roche) and phosphatase inhibitors (Sigma). Equal amount of total protein lysates were used for immunoblotting. The following antibodies were from Cell Signaling Technology and were used at 1:1,000 dilution: pAKT (#3787), AKT (#4691), pERK (#4370), ERK (#4695), pMET (#3077), MET (#3127), pEGFR (#3777), EGFR (#4267), pPRAS40 (#2997), PRAS40 (#2691), and Vinculin (#13901). Other antibodies used in this article are as follows: INPP4B (Abcam, Ab81269) and b-actin (Sigma, A2228).

MCF10A and MDA-MB-231 cells were obtained from the ATCC and authenticated using short tandem repeat profiling. Primary human mammary epithelial cells (HMEC) were obtained as described previously (42). MCF10A cells and HMECs were maintained in DMEM/Ham's F12 (CellGro) supplemented with 5% equine serum (CellGro), 10 mg/mL insulin (Life Technologies), 500 ng/mL hydrocortisone (Sigma-Aldrich), 20 ng/mL EGF (R&D Systems), and 100 ng/mL cholera toxin (Sigma-Aldrich). MDA-MB-231 cells were maintained in DMEM (CellGro) supplemented with 10% FBS (Gemini). Cells were passaged for no more than 2 months and routinely assayed for Mycoplasma contamination (MycoAlert, Lonza).

Lentivirus preparation and infection were carried out as described using Lipofectamine 2000 (Thermo Fisher Scientific; ref. 42).

Cells (1,500) were plated in 96-well plates in 200 μL of cell culture medium and measured with CellTiter-Glo (Promega, G7572). For 3-D culture, each well of the 8-well chamber slides was coated with 50 μL growth factor–reduced Matrigel (Corning), followed by seeding 3,000 cells in growth medium containing 2% Matrigel.

Cells (5,000) were plated in 96-well plates and changed to medium (growth media or serum-free media/50 ng/mL EGF) containing inhibitors at different concentrations. The following inhibitors were used: BKM-120 and BYL719 (MedChemExpress, LLC), GDC0068 (Selleck), trametinib (Selleck), and erlotinib (Selleck). After 72 hours, the relative numbers of remaining cells were measured with CellTiter-Glo (Promega, G7572).

Cells were seeded on serum-precoated glass cover slips overnight, serum-starved for 16 to 18 hours, and stimulated with 50 ng/mL EGF. At indicated timepoints, cells were fixed in 4% paraformaldehyde, followed by 0.1% Triton X-100 in PBS (5 minutes, room temperature), blocked at 37°C with 10% normal goat serum in PBS for 30 minutes, and incubated with the following primary antibodies at 4°C overnight. After washing, cells were incubated with Alexa Fluor 488- or 568-conjugated secondary antibodies (Molecular Probes). Primary antibodies used are as follows: EGFR (Cell Signaling Technology #4267 for intracellular staining), EGFR-AF488 (BioLegend #352908 for surface staining), EEA1 (BD Bioscience #610457), and CD63 (BioLegend #353013). Images were acquired with Zeiss LSM 880 upright confocal system and analyzed with Volocity Imaging Software (Improvision, PerkinElmer).

For PI(3,4)P₂ staining, after fixation, cells were permeabilized and blocked with PBS containing 0.5% saponin, 1% BSA, and 10% normal goat serum for 30 minutes for plasma membrane staining, or with 20 μmol/L digitonin in buffer A (20 mmol/L Pipes, pH 6.8, 137 mmol/L NaCl, and 2.7 mmol/L KCl) followed by 30 minutes in buffer A containing 5% normal goat serum and 50 mmol/L NH₄Cl for intracellular vesicle staining. Anti-PI(3,4)P₂ antibody (Echelon Biosciences Z-P034b) was diluted 1:150 in PBS or buffer A (for plasma membrane or intracellular vesicle, respectively) containing 5% normal goat serum, incubated for 1 hour at room temperature, and washed before incubating with Alexa Fluor 568–conjugated anti-mouse secondary antibody. Images were acquired using a spinning disk Confocal Microscope (Ultraview ERS, Perkin Elmer) and analyzed with Volocity Imaging Software (Improvision, Perkin Elmer). PI(3,4)P₂ levels were quantified using custom written ImageJ macros as described previously (47).

Slides were deparaffinized and rehydrated, and antigen retrieval was performed using SignalStain Citrate Unmasking Solution (Cell Signaling Technology #14746). Slides were incubated with freshly prepared 3% H₂O₂ for 10 minutes, washed twice with ddH₂O and once with TBST, and blocked in TBST/5% normal goat serum at room temperature for 1 hour. After incubating with anti-mouse EGFR antibody (Cell Signaling Technology #71655) diluted in TBST/5% goat serum overnight at 4°C, the slides were washed 3 × TBST and incubated with goat-anti-rabbit-biotin secondary antibody at room temperature for 30 minutes. Color development was carried out following the manufacturer's instructions (Vectastain Elite ABC HRP Kit). Slides were counterstained with hematoxylin (#14166), dehydrated, and mounted.

Phosphoinositide measurements were performed as reported previously (73). Briefly, cells were labeled for 48 hours in inositol-free DMEM with glutamine, 10% dialyzed FBS, and 20 mCi/mL ³H myo-inositol. At the indicated times, cells were washed and harvested by scraping in 1.5 mL ice-cold aqueous solution (1 mol/L HCl, 5 mmol/L tetrabutylammonium bisulfate, and 25 mmol/L EDTA) before adding 2 mL of MeOH and 4 mL of CHCl₃, vortexed, and centrifuged. The aqueous layer was extracted three times using theoretical lower reagent (CHCl₃:MeOH:aqueous solution in 8:4:3 v/v), and organic phase was collected and dried, deacylated at 55°C for 1 hour, and dried. To the dried vials, 1 mL of theoretical upper and 1.5 mL of theoretical lower were added, vortexed, centrifuged, and the aqueous phase was collected and dried. Samples were resuspended in 150 μL buffer A (1 mmol/L EDTA), injected in anion-exchange HPLC using Partisphere SAX column, eluted with buffer B (1 mmol/L EDTA, 1 mol/L NaH₂PO₄), and detected using an on-line continuous flow scintillation detector (detailed gradient is provided in the Supplementary Methods).

M.N. Paddock reports her contribution to this work was completed at Weill Cornell Medical College, and reports employment with Calico Life Sciences. G.M. Wulf reports grants from the Breast Cancer Research Foundation and NIH 1R01CA226776 during the conduct of the study, as well as grants from Merck & Co, Ludwig BIDMC Wulf FY18, 9617011 KI-DFHCC Bridge Project, and 5P30CA006516-54 outside the submitted work. O. Elemento reports personal fees and equity from Volastra Therapeutics and equity from OneThree Biotech outside the submitted work, and is a scientific advisor and equity holder in Owkin and Freenome. L.C. Cantley reports grants from the NCI, Breast Cancer Research Foundation, and Gray Family Foundation during the conduct of the study, as well as personal fees from Agios Pharmaceuticals (founder and SAB), Petra Pharmaceuticals (founder and SAB and support for his laboratory), and Volastra Pharmaceuticals (founder and SAB) outside the submitted work. A. Toker reports personal fees from Bertis, Inc and Oncologie, Inc outside the submitted work. No potential conflicts of interest were disclosed by the other authors.

One of the Editors-in-Chief is an author on this article. In keeping with the AACR's editorial policy, the peer review of this submission was managed by a senior member of Cancer Discovery's editorial team; a member of the AACR Publications Committee rendered the final decision concerning acceptability.

H. Liu: Conceptualization, data curation, formal analysis, supervision, funding acquisition, investigation, methodology, writing-original draft, project administration, writing-review and editing. M.N. Paddock: Investigation, methodology, writing-review and editing. H. Wang: Investigation, methodology, writing-review and editing. C.J. Murphy: Data curation, formal analysis, methodology, writing-review and editing. R.C. Geck: Investigation, methodology, writing-review and editing. A.J. Navarro: Investigation, methodology, writing-review and editing. G.M. Wulf: Conceptualization, supervision, funding acquisition, investigation, writing-review and editing. O. Elemento: Data curation, formal analysis, supervision, validation, investigation, writing-review and editing. V. Haucke: Conceptualization, supervision, funding acquisition, investigation, project administration, writing-review and editing. L.C. Cantley: Conceptualization, supervision, funding acquisition, writing-review and editing. A. Toker: Conceptualization, supervision, funding acquisition, writing-original draft, project administration, writing-review and editing.

We thank Drs. Jos Jonkers and Takehiko Sasaki for providing mouse strains, Junyan Zhang and Kangkang Yang for technical support, members of the Toker and Cantley laboratories for advice and discussion, Roderick Bronson at the DH/FCC Rodent Histopathology Core, Lay-Hong Ang and Aniket Gad at BIDMC Confocal Image Core, Suzanne L. White and Lena Liu for histology work, Eva Csizmadia for IHC, and Luke Dow for plasmid constructs. This work was supported by a Susan G. Komen postdoctoral fellowship (to H. Liu); the Ludwig Center at Harvard (to A. Toker); the Breast Cancer Alliance (to A. Toker); the Deutsche Forschungsgemeinschaft TRR186/A08 (to V. Haucke); NIH R35 CA197588 (to L.C. Cantley); NIH R01 CA226776 (to G.M. Wulf); Breast Cancer Research Foundation (to L.C. Cantley and G.M. Wulf); a gift from the Jon and Mindy Gray Foundation (to L.C. Cantley); and NIH U54CA210184 (to L.C. Cantley) and NCI F31 CA213460 (to R.C. Geck).