Integrative Proteomic Characterization of Human Lung Adenocarcinoma.

Genomic studies of lung adenocarcinoma (LUAD) have advanced our understanding of the disease's biology and accelerated targeted therapy. However, the proteomic characteristics of LUAD remain poorly understood. We carried out a comprehensive proteomics analysis of 103 cases of LUAD in Chinese patients. Integrative analysis of proteome, phosphoproteome, transcriptome, and whole-exome sequencing data revealed cancer-associated characteristics, such as tumor-associated protein variants, distinct proteomics features, and clinical outcomes in patients at an early stage or with EGFR and TP53 mutations. Proteome-based stratification of LUAD revealed three subtypes (S-I, S-II, and S-III) related to different clinical and molecular features. Further, we nominated potential drug targets and validated the plasma protein level of HSP 90ß as a potential prognostic biomarker for LUAD in an independent cohort. Our integrative proteomics analysis enables a more comprehensive understanding of the molecular landscape of LUAD and offers an opportunity for more precise diagnosis and treatment.

ATR inhibition potentiates ionizing radiation-induced interferon response via cytosolic nucleic acid-sensing pathways.

Mechanistic understanding of how ionizing radiation induces type I interferon signaling and how to amplify this signaling module should help to maximize the efficacy of radiotherapy. In the current study, we report that inhibitors of the DNA damage response kinase ATR can significantly potentiate ionizing radiation-induced innate immune responses. Using a series of mammalian knockout cell lines, we demonstrate that, surprisingly, both the cGAS/STING-dependent DNA-sensing pathway and the MAVS-dependent RNA-sensing pathway are responsible for type I interferon signaling induced by ionizing radiation in the presence or absence of ATR inhibitors. The relative contributions of these two pathways in type I interferon signaling depend on cell type and/or genetic background. We propose that DNA damage-elicited double-strand DNA breaks releases DNA fragments, which may either activate the cGAS/STING-dependent pathway or-especially in the case of AT-rich DNA sequences-be transcribed and initiate MAVS-dependent RNA sensing and signaling. Together, our results suggest the involvement of two distinct pathways in type I interferon signaling upon DNA damage. Moreover, radiation plus ATR inhibition may be a promising new combination therapy against cancer.

Refining chimeric antigen receptors via barcoded protein domain combination pooled screening.

Chimeric antigen receptor (CAR)-T cells represent a promising frontier in cancer immunotherapy. However, the current process for developing new CAR constructs is time consuming and inefficient. To address this challenge and expedite the evaluation and comparison of full-length CAR designs, we have devised a novel cloning strategy. This strategy involves the sequential assembly of individual CAR domains using blunt ligation, with each domain being assigned a unique DNA barcode. Applying this method, we successfully generated 360 CAR constructs that specifically target clinically validated tumor antigens CD19 and GD2. By quantifying changes in barcode frequencies through next-generation sequencing, we characterize CARs that best mediate proliferation and expansion of transduced T cells. The screening revealed a crucial role for the hinge domain in CAR functionality, with CD8a and IgG4 hinges having opposite effects in the surface expression, cytokine production, and antitumor activity in CD19- versus GD2-based CARs. Importantly, we discovered two novel CD19-CAR architectures containing the IgG4 hinge domain that mediate superior in vivo antitumor activity compared with the construct used in Kymriah, a U.S. Food and Drug Administration (FDA)-approved therapy. This novel screening approach represents a major advance in CAR engineering, enabling accelerated development of cell-based cancer immunotherapies.

A time-resolved multi-omic atlas of the developing mouse liver.

Liver organogenesis and development are composed of a series of complex, well-orchestrated events. Identifying key factors and pathways governing liver development will help elucidate the physiological and pathological processes including those of cancer. We conducted multidimensional omics measurements including protein, mRNA, and transcription factor (TF) DNA-binding activity for mouse liver tissues collected from embryonic day 12.5 (E12.5) to postnatal week 8 (W8), encompassing major developmental stages. These data sets reveal dynamic changes of core liver functions and canonical signaling pathways governing development at both mRNA and protein levels. The TF DNA-binding activity data set highlights the importance of TF activity in early embryonic development. A comparison between mouse liver development and human hepatocellular carcinoma (HCC) proteomic profiles reveal that more aggressive tumors are characterized with the activation of early embryonic development pathways, whereas less aggressive ones maintain liver function-related pathways that are elevated in the mature liver. This work offers a panoramic view of mouse liver development and provides a rich resource to explore in-depth functional characterization.

Impaired replication elongation in Tetrahymena mutants deficient in histone H3 Lys 27 monomethylation.

Replication of nuclear DNA occurs in the context of chromatin and is influenced by histone modifications. In the ciliate Tetrahymena thermophila, we identified TXR1, encoding a histone methyltransferase. TXR1 deletion resulted in severe DNA replication stress, manifested by the accumulation of ssDNA, production of aberrant replication intermediates, and activation of robust DNA damage responses. Paired-end Illumina sequencing of ssDNA revealed intergenic regions, including replication origins, as hot spots for replication stress in ΔTXR1 cells. ΔTXR1 cells showed a deficiency in histone H3 Lys 27 monomethylation (H3K27me1), while ΔEZL2 cells, deleting a Drosophila E(z) homolog, were deficient in H3K27 di- and trimethylation, with no detectable replication stress. A point mutation in histone H3 at Lys 27 (H3 K27Q) mirrored the phenotype of ΔTXR1, corroborating H3K27me1 as a key player in DNA replication. Additionally, we demonstrated interactions between TXR1 and proliferating cell nuclear antigen (PCNA). These findings support a conserved pathway through which H3K27me1 facilitates replication elongation.

A Cross-Linking-Aided Immunoprecipitation/Mass Spectrometry Workflow Reveals Extensive Intracellular Trafficking in Time-Resolved, Signal-Dependent Epidermal Growth Factor Receptor Proteome.

Ligand binding to the cell surface receptors initiates signaling cascades that are commonly transduced through a protein-protein interaction (PPI) network to activate a plethora of response pathways. However, tools to capture the membrane PPI network are lacking. Here, we describe a cross-linking-aided mass spectrometry workflow for isolation and identification of signal-dependent epidermal growth factor receptor (EGFR) proteome. We performed protein cross-linking in cell culture at various time points following EGF treatment, followed by immunoprecipitation of endogenous EGFR and analysis of the associated proteins by quantitative mass spectrometry. We identified 140 proteins with high confidence during a 2 h time course by data-dependent acquisition and further validated the results by parallel reaction monitoring. A large proportion of proteins in the EGFR proteome function in endocytosis and intracellular protein transport. The EGFR proteome was highly dynamic with distinct temporal behavior; 10 proteins that appeared in all time points constitute the core proteome. Functional characterization showed that loss of the FYVE domain-containing proteins altered the EGFR intracellular distribution but had a minor effect on EGFR proteome or signaling. Thus, our results suggest that the EGFR proteome include functional regulators that influence EGFR signaling and bystanders that are captured as the components of endocytic vesicles. The high-resolution spatiotemporal information of these molecules facilitates the delineation of many pathways that could determine the strength and duration of the signaling, as well as the location and destination of the receptor.

A Bioinformatic Algorithm for Analyzing Cell Signaling Using Temporal Proteomic Data.

Significance analysis of proteomic data generated by LC-MS/MS is challenging owing to great data variability originated from biological, operational, and instrumental variations. Protein quantification by LC-MS/MS either in absolute or relative scale is often highly skewed, which put limitations on model-based statistical inference. For this purpose, we have developed an alternative nonparametric statistical algorithm (named IQR algorithm) for significance analysis of temporal proteomic data and have successfully applied our strategy in finding gefitinib-targeted transcription factors and coregulators in Epidermal Growth Factor (EGF)-stimulated HeLa cells. Our strategy relies on a reference group composed of more than a dozen of datasets collected at different experimental times, thus, accurately captures biological variations measured in quartile scale. The algorithm considers six categories and calculates signal strength when performing significance analysis of proteins of different abundances. This stratified strategy allows confident identification of well-characterized EGF responders (e.g. EGR1, JUN, FOSB, BHLHE40, NR4A1, and NR4A2) and unexplored gefitinib induced transcription factors and coregulators in HeLa cells. Gene set enrichment analysis has validated ErbB signaling pathway as the major inhibitory target of gefitinib. The identification of several gefitinib-inducible transcription factors implicates alternative signaling pathways as potential druggable pathways in gefitinib-resistant or insensitive patients.

Quantitative proteomic analysis of histone modifications in decitabine sensitive and resistant leukemia cell lines.

BACKGROUND: The refractory nature of many cancers remains the main health challenge over the past century. The epigenetic drug, decitabine (DAC), represents one of the most promising therapeutic agents in cancers particularly in acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS). However, its ambiguous anti-tumor mechanism and the unpredictable drug-resistant nature in some population compromise its application in cancer therapy. In crosstalk with DNA methylation, histone post-translational modifications (PTMs) are the key players in modulating the downstream epigenetic status of tumor suppressor genes. This study targets the role of decitabine in epigenetic regulation in leukemia therapy and searches responsive predictors and therapeutic targets for pretreatment evaluation and drug development. RESULTS: A simple, fast, and robust proteomic strategy identified 15 novel PTMs and 60 PTM combinations in two leukemia cell lines (MDS-L and TF-1). Histone modification profiles have been generated and compared between DAC sensitive and resistant groups (n = 3) in response to DAC treatment. Among these histone PTMs, five of which were found differentially upon DAC treatment in drug sensitive and resistant cells: H3.3K36me3, H4K8acK12acK16ac in MDS-L cells; and H3.1K27me1, H3.1K36me1, H3.1K27me1K36me1 in TF-1 cells. They may serve as biomarkers in predicting leukemia and drug responsiveness. In addition, we also explored PTM differences in two cell lines which were developed from early and advanced stages of AML. Three PTMs (H3.1K27me3, H3.1K27me2K36me2 and H3.3K27me2K36me2) are highly abundant in TF-1 cells (advanced AML cell line), suggesting their relevance to leukemogenesis. Our method allowed deep analysis of histone proteins and elucidation of a large number of histone PTMs with high precision and sensitivity. CONCLUSION: DAC-induced DNA hypomethylation has wide impact on chromatin modifications. This study represents first effort to investigate the undefined epigenetic mechanism of decitabine in leukemia therapy. The identification of 15 novel PTMs and the discovery of several marks have relevance to epigenetic directed therapies.

Quantitative proteomics reveals histone modifications in crosstalk with H3 lysine 27 methylation.

Methylation at histone H3 lysine 27 (H3K27me) is an evolutionarily conserved epigenetic mark associated with transcriptional repression and replication elongation. We have previously shown that in Tetrahymena thermophila, a unicellular eukaryote, the histone methyltransferases (HMTs) TXR1 and EZL2 are primarily responsible for H3K27 mono-methylation (H3K27me1) and di-/tri-methylation (H3K27me2/3), respectively. Using (15)N metabolically labeled histones as the internal reference, we quantified global changes in histone post-translational modifications in ΔTXR1 and ΔEZL2 cells, to systematically identify potential crosstalk between H3K27 methylation and other PTMs across all four core histones as well as their variants. Most prominently, we observed hyper-acetylation of histones H2A, H2A.Z, and H4 in their N-terminal domains in response to decreased H3K27 methylation. We also provide additional evidence implicating hyper-acetylation in the DNA damage response pathway in replication-defective ΔTXR1 cells, in apparent contrast to the transcriptional role of hyper-acetylation in ΔEZL2 cells.

Quantitative proteomics reveals that the specific methyltransferases Txr1p and Ezl2p differentially affect the mono-, di- and trimethylation states of histone H3 lysine 27 (H3K27).

Nuclear DNA in eukaryotic cells is assembled into the hierarchical chromatin structure via a process that is dynamically affected by the combinatorial set of post-translational modifications (PTMs) of histones in a dynamic manner responsive to physiological and environmental changes. The precise quantification of these complex modifications is challenging. Here we present a robust MS-based quantitative proteomics method for studying histone PTMs using (15)N metabolically labeled histones as the internal reference. Using this approach, we identified Tetrahymena trithorax related 1 (Txr1p) as a histone methyltransferase in Tetrahymena thermophila and characterized the relationships of the Txr1p and Ezl2p methyltransferases to histone H3 modification. We identified 32 PTMs in more than 60 tryptic peptides from histone H3 of the ciliate model organism Tetrahymena thermophila, and we quantified them (average coefficient of variation: 13%). We examined perturbations to histone modification patterns in two knockout strains of SET-domain-containing histone methyltransferases (HMT). Knockout of TXR1 led to progressively decreased mono-, di-, and tri-methylation of H3K27 and apparent reduced monomethylation of H3K36 in vivo. In contrast, EZL2 knockout resulted in dramatic reductions in both di- and tri-methylation of H3K27 in vivo, whereas the levels of monomethylation of H3K27 increased significantly. This buildup of monomethyl H3K27 is consistent with its role as a substrate for Ezl2p. These results were validated via immunoblotting using modification site-specific antibodies. Taken together, our studies define Txr1p as an H3K27 monomethylation-specific HMT that facilitates the buildup of H3K27 di- and trimethylation by the canonical H3K27-specific HMT, Ezl2p. Our studies also delineate some of the interdependences between various H3 modifications, as compensatory increases in monomethylation at H3K4, H3K23, and H3K56 were also observed for both TXR1 and ELZ2 mutants.

Bioinformatic and proteomic analysis of bulk histones reveals PTM crosstalk and chromatin features.

Systems analysis of chromatin has been constrained by complex patterns and dynamics of histone post-translational modifications (PTMs), which represent major challenges for both mass spectrometry (MS) and immuno-based approaches (e.g., chromatin immuno-precipitation, ChIP). Here we present a proof-of-concept study demonstrating that crosstalk among PTMs and their functional significance can be revealed via systematic bioinformatic and proteomic analysis of steady-state histone PTM levels from cells under various perturbations. Using high resolution tandem MS, we quantified 53 modification states from all core histones and their conserved variants in the unicellular eukaryotic model organism Tetrahymena. By correlating histone PTM patterns across 15 different conditions, including various physiological states and mutations of key histone modifying enzymes, we identified 5 specific chromatin states with characteristic covarying histone PTMs and associated them with distinctive functions in replication, transcription, and DNA repair. In addition to providing a detailed picture on histone PTM crosstalk at global levels, this work has established a novel bioinformatic and proteomic approach, which can be adapted to other organisms and readily scaled up to allow increased resolution of chromatin states.

Quantification of histone modifications using ¹5N metabolic labeling.

Mass spectrometry has made major contributions to recent discoveries in the field of epigenetics, particularly in the characterization of the myriad post-translational modifications (PTMs) of histones which are technically challenging to analyze. These new developments have further aroused great interest in development of robust, new mass spectrometric methods to quantitatively study the dynamics of histone modifications. This review covers quantitative analysis of histone PTMs and discuss an ¹5N metabolic labeling procedure for quantifying histone PTMs applied to the analysis of methyltransferase knockouts in the model organism, Tetrahymena thermophila.

Influence of Geometric Characteristics on Water Flow and Solute Transport at Fracture Intersections.

Laboratory experiments and numerical simulations were performed to explore the influence of intersection geometry on fluid flow and solute transport in fractures. Fractures were engraved and sealed into an acrylic plate and two orthogonal intersections with different geometry were constructed. The effects of curvature and relative shear displacement at intersections on preferential flow and solute transport were investigated. By solving the Navier-Stokes (NS) equation, the fluid mixing and solute distribution were predicted. The results showed that the geometric characteristics at the intersection have a significant effect on the preferential flow and solute distribution. The results agreed well with the experimental results, in terms of flow direction, preferential flow rate, and heterogeneous solute distribution. With an increase in curvature, the flow difference between the two outlets increases gradually. Increasing curvature can reduce the preferential flow and weaken the inhomogeneity of solute distribution. An increase of relative shear displacement decreases the pressure gradient and flow rate at the entrance of the two branch fractures, and thereby increases preferential flow and inhomogeneity of solute distribution. The results provide a basis and reference for further exploring the relationship between the geometric characteristics of fracture intersections and flow behaviors.

Diagnosis Framework for Probable Alzheimer's Disease and Mild Cognitive Impairment Based on Multi-Dimensional Emotion Features.

BACKGROUND: Emotion and cognition are intercorrelated. Impaired emotion is common in populations with Alzheimer's disease (AD) and mild cognitive impairment (MCI), showing promises as an early detection approach. OBJECTIVE: We aim to develop a novel automatic classification tool based on emotion features and machine learning. METHODS: Older adults aged 60 years or over were recruited among residents in the long-term care facilities and the community. Participants included healthy control participants with normal cognition (HC, n = 26), patients with MCI (n = 23), and patients with probable AD (n = 30). Participants watched emotional film clips while multi-dimensional emotion data were collected, including mental features of Self-Assessment Manikin (SAM), physiological features of electrodermal activity (EDA), and facial expressions. Emotional features of EDA and facial expression were abstracted by using continuous decomposition analysis and EomNet, respectively. Bidirectional long short-term memory (Bi-LSTM) was used to train classification model. Hybrid fusion was used, including early feature fusion and late decision fusion. Data from 79 participants were utilized into deep machine learning analysis and hybrid fusion method. RESULTS: By combining multiple emotion features, the model's performance of AUC value was highest in classification between HC and probable AD (AUC = 0.92), intermediate between MCI and probable AD (AUC = 0.88), and lowest between HC and MCI (AUC = 0.82). CONCLUSIONS: Our method demonstrated an excellent predictive power to differentiate HC/MCI/AD by fusion of multiple emotion features. The proposed model provides a cost-effective and automated method that can assist in detecting probable AD and MCI from normal aging.

FOXK2 amplification promotes breast cancer development and chemoresistance.

Oncogene activation through DNA amplification or overexpression is a crucial driver of cancer initiation and progression. The FOXK2 gene, located on chromosome 17q25, encodes a transcription factor with a forkhead DNA-binding domain. Analysis of genomic datasets reveals that FOXK2 is frequently amplified and overexpressed in breast cancer, correlating with poor patient survival. Knockdown of FOXK2 significantly inhibited breast cancer cell proliferation, migration, anchorage-independent growth, and delayed tumor growth in a xenograft mouse model. Additionally, inhibiting FOXK2 sensitized breast cancer cells to chemotherapy. Co-overexpression of FOXK2 and mutant PI3KCA transformed non-tumorigenic MCF-10A cells, suggesting a role for FOXK2 in PI3KCA-driven tumorigenesis. CCNE2, PDK1, and ESR1 were identified as transcriptional targets of FOXK2 in MCF-7 cells. Small-molecule inhibitors of CCNE2/CDK2 (dinaciclib) and PDK1 (dichloroacetate) exhibited synergistic anti-tumor effects with PI3KCA inhibitor (alpelisib) in vitro. Inhibition of FOXK2 by dinaciclib synergistically enhanced the anti-tumor effects of alpelisib in a xenograft mouse model. Collectively, these findings highlight the oncogenic function of FOXK2 and suggest that FOXK2 and its downstream genes represent potential therapeutic targets in breast cancer.

A robust performance evaluation method based on interval evidential reasoning approach under uncertainty.

Performance evaluation (PE) is an important part of equipment health management. If the monitoring information of the equipment is interfered, the evaluation results may be erroneous. A robust performance evaluation (RPE) method is proposed to solve this problem. The performance evaluation results are obtained by distinguishing the cases of single evidence with interference and two evidence with interference, and a robustness measurement based on interval similarity is proposed. To improve the accuracy of the evaluation results, the referential values in the IER evaluation model are optimized. The robustness thresholds of the input indexes are obtained under the satisfaction of the robustness constraints. If the interference value of the input index is within the thresholds, the deviation between the evaluation results using monitoring information with interference and those using monitoring information without interference is small. Finally, the proposed method is applied to a type of electric servo mechanism performance evaluation, and the case shows the validity of the RPE method.

Water optical properties over or around coral reefs in the coastal region: implications for coral reef remote sensing.

Coral reefs inhabit clear oceanic-type waters to turbid coastal regimes. For shallow coastal water environments, the coral reefs from remote sensing will be substantially influenced by the complexity and heterogeneity of the optical properties of water. Through a set of bio-optical and chemical measurements in July 2019 around Xidao Island, Sanya, China, we explored spatial variations of water components' concentrations (including suspended solids, phytoplankton, and dissolved organic carbon) and the optical absorptions (i.e., particulate pigments, detritus, and colored dissolved organic matter) in waters over or around coral reefs; further analysis of their influences upon the remote sensing reflectance (Rrs(λ)) of water was performed. It was observed that the bio-optical and chemical properties of the waters over or around coral reefs were spatially and vertically heterogeneous for different sampling sites. As expected, the suspended solids dominated the optical properties of coral reefs waters in areas of Xidao Island, which evidently influenced the Rrs(λ), especially for the surface waters (Pearson r > 0.60, p < 0.01). In addition, the dissolved organic carbon concentrations exhibited significant relations to the Rrs(λ) both in surface and bottom water layers, whereas the colored dissolved organic matter showed a weak negative correlation with the Rrs(λ). These findings will support the mapping and monitoring benthic habitats with remote sensing imagery in coastal regions, especially when a removal of the influence by particulate sediments was available.

A New Evidential Reasoning Rule Considering Interval Uncertainty and Perturbation.

The evidential reasoning (ER) rule has been widely applied in the multiple attribute decision making (MADM), which makes the decision-making process transparent and credible by using a belief structure. To improve the ability of the ER rule in dealing with the interval uncertainty, a new interval ER (IER) rule is proposed in this article. The interval uncertainty is described as the interval grade in the new frame of discernment (FoD) to model the local ignorance. It is proved that the IER rule is a generalization of the ER rule. To study the influence of perturbation on the IER rule, the perturbation is first introduced to the belief structure, and the perturbation analysis (PA) is conducted for the IER rule. An optimization model is established to estimate the perturbation threshold, which can measure the effectiveness of the inference result under perturbation. Two numerical examples and a case study are carried out, respectively, to show the implementation process of the proposed IER rule and validate its effectiveness in different decision-making scenarios.

Interaction between tumor cell TNFR2 and monocyte membrane-bound TNF-α triggers tumorigenic inflammation in neuroblastoma.

BACKGROUND: Tumor progression and resistance to therapy in children with neuroblastoma (NB), a common childhood cancer, are often associated with infiltration of monocytes and macrophages that produce inflammatory cytokines. However, the mechanism by which tumor-supportive inflammation is initiated and propagated remains unknown. Here, we describe a novel protumorigenic circuit between NB cells and monocytes that is triggered and sustained by tumor necrosis factor alpha (TNF-α). METHODS: We used NB knockouts (KOs) of TNF-α and TNFRSF1A mRNA (TNFR1)/TNFRSF1B mRNA (TNFR2) and TNF-α protease inbitor (TAPI), a drug that modulates TNF-α isoform expression, to assess the role of each component in monocyte-associated protumorigenic inflammation. Additionally, we employed NB-monocyte cocultures and treated these with clinical-grade etanercept, an Fc-TNFR2 fusion protein, to neutralize signaling by both membrane-bound (m) and soluble (s)TNF-α isoforms. Further, we treated NOD/SCID/IL2Rγ(null) mice carrying subcutaneous NB/human monocyte xenografts with etanercept and evaluated the impact on tumor growth and angiogenesis. Gene set enrichment analysis (GSEA) was used to determine whether TNF-α signaling correlates with clinical outcomes in patients with NB. RESULTS: We found that NB expression of TNFR2 and monocyte membrane-bound tumor necrosis factor alpha is required for monocyte activation and interleukin (IL)-6 production, while NB TNFR1 and monocyte soluble TNF-α are required for NB nuclear factor kappa B subunit 1 (NF-κB) activation. Treatment of NB-monocyte cocultures with clinical-grade etanercept completely abrogated release of IL-6, granulocyte colony-stimulating factor (G-CSF), IL-1α, and IL-1ß and eliminated monocyte-induced enhancement of NB cell proliferation in vitro. Furthermore, etanercept treatment inhibited tumor growth, ablated tumor angiogenesis, and suppressed oncogenic signaling in mice with subcutaneous NB/human monocyte xenografts. Finally, GSEA revealed significant enrichment for TNF-α signaling in patients with NB that relapsed. CONCLUSIONS: We have described a novel mechanism of tumor-promoting inflammation in NB that is strongly associated with patient outcome and could be targeted with therapy.

FOXK2 amplification and overexpression promotes breast cancer development and chemoresistance.

Activation of oncogenes through DNA amplification/overexpression plays an important role in cancer initiation and progression. Chromosome 17 has many cancer-associated genetic anomalies. This cytogenetic anomaly is strongly associated with poor prognosis of breast cancer. FOXK2 gene is located on 17q25 and encodes a transcriptional factor with a forkhead DNA binding domain. By integrative analysis of public genomic datasets of breast cancers, we found that FOXK2 is frequently amplified and overexpressed in breast cancers. FOXK2 overexpression in breast cancer patients is associated with poor overall survival. FOXK2 knockdown significantly inhibits cell proliferation, invasion and metastasis, and anchorage-independent growth, as well as causes G0/G1 cell cycle arrest in breast cancer cells. Moreover, inhibition of FOXK2 expression sensitizes breast cancer cells to frontline anti-tumor chemotherapies. More importantly, co-overexpression of FOXK2 and PI3KCA with oncogenic mutations (E545K or H1047R) induces cellular transformation in non-tumorigenic MCF10A cells, suggesting that FOXK2 is an oncogene in breast cancer and is involved in PI3KCA-driven tumorigenesis. Our study identified CCNE2, PDK1, and Estrogen receptor alpha (ESR1) as direct transcriptional targets of FOXK2 in MCF-7 cells. Blocking CCNE2- and PDK1-mediated signaling by using small molecule inhibitors has synergistic anti-tumor effects in breast cancer cells. Furthermore, FOXK2 inhibition by gene knockdown or inhibitors for its transcriptional targets (CCNE2 and PDK1) in combination with PI3KCA inhibitor, Alpelisib, showed synergistic anti-tumor effects on breast cancer cells with PI3KCA oncogenic mutations. In summary, we provide compelling evidence that FOXK2 plays an oncogenic role in breast tumorigenesis and targeting FOXK2-mediated pathways may be a potential therapeutic strategy in breast cancer.