Nanoprinted Diffractive Layer Integrated Vertical-Cavity Surface-Emitting Vortex Lasers with Scalable Topological Charge.

Vertical-cavity surface-emitting lasers (VCSELs) represent an attractive light source to integrate with OAM structures to realize chip-scale vortex lasers. Although pioneering endeavors of VCSEL-based vortex lasers have been reported, they cannot achieve large topological charges (less than l = 5) due to the insufficient space-bandwidth product (SBP) caused by the inherent limited device size. Here, by integrating a nanoprinted OAM phase structure on the VCSELs, we demonstrate a vortex microlaser with a low threshold and simple structure. A monolithic microlaser array with addressable control of vortex beams with different topological charges (l = 1 to l = 5) was achieved. Nanoprinting offers high degrees of freedom for the manipulation of spatial structures. To address the challenge of insufficient SBP, two-layer cascaded spiral phase plates were designed. Thereby, a vortex beam with l = 15 and mode purity of 83.7% was obtained. Our work paves the way for future chip-scale OAM-based information multiplexing with more channels.

Orbital angular momentum holographic multicasting for switchable and secure wireless optical communication links.

The physical dimension of orbital angular momentum (OAM) states of light has been successfully implemented as information carrier in wireless optical communication (WOC) links. However, the current OAM data coding strategies in WOC are mainly limited to the temporal domain, rarely involving the degree of freedom of spatial domain to transmit an image directly. Here, we apply OAM holographic multiplexing technology for spatial information encoding in WOC links. Further, we demonstrate the new concept of OAM holographic multicasting, wherein a beam-steering grating has been utilized for information decoding. To distribute the OAM multiplexing information appropriately in the receiving terminal, the beam-steering grating with controllable topological charges and amplitude weighting coefficients of each diffraction order in the spatial frequency domain has been designed. An iterative algorithm has been introduced to obtain the intensity uniformity >98% at target diffraction orders. As such, this scheme experimentally allows four separate users to receive independent images, which can be switched by modulating the topological charges of the beam-steering gratings at each diffraction order. In addition, this leads to a beam-steering grating-encrypted WOC links, wherein the information can only be decoded by the grating phase with 7 pre-set spatial frequency components. Our results mark a new parallel decoding paradigm of OAM multiplexing holography, which opens up the door for future high-capacity and high-security all-optical holographic communications.

Multiscale diffractive U-Net: a robust all-optical deep learning framework modeled with sampling and skip connections.

As an all-optical learning framework, diffractive deep neural networks (D2NNs) have great potential in running speed, data throughput, and energy consumption. The depth of networks and the misalignment of layers are two problems to limit its further development. In this work, a robust all-optical network framework (multiscale diffractive U-Net, MDUNet) based on multi-scale features fusion has been proposed. The depth expansion and alignment robustness of the network can be significantly improved by introducing sampling and skip connections. Compared with common all-optical learning frameworks, MDUNet achieves the highest accuracy of 98.81% and 89.11% on MNIST and Fashion-MNIST respectively. The testing accuracy of MNIST and Fashion-MNIST can be further improved to 99.06% and 89.86% respectively by using the ensemble learning method to construct the optoelectronic hybrid neural network.

Perspective of fibre-optical microendoscopy with microlenses.

Fibre-optical microendoscopy is based on fibre-optical confocal scanning microscopy, where optical fibres are introduced for delivery of the source and collection of the signal. Fibre-optical microendoscopy has led to innovations in imaging of freely moving animals, long-term imaging, minimally invasive diagnostics, and microsurgery. The lens system in fibre-optical microendoscopy is significant because of the imaging resolution and miniaturisation possibility. State-of-the-art fibre-optical microendoscopy based on various types of lens systems is introduced and compared. The lens system contains an objective lens, a gradient index microlens, and other novel lens systems fabricated by electric arc discharge or two-photon lithography.

Optical fibres are introduced in confocal scanning microscopy, inspiring the development of fibre-optical microendoscopy. Fibre-optical microendoscopy takes advantages in imaging of freely moving animals, long-term imaging, minimally invasive diagnostics, and microsurgery. The lens system helps resolving small details of samples and reducing the size in a fibre-optical microendoscope. Various types of lens systems applied in the fibre-optical microendoscopes are introduced and compared, including an objective lens, a gradient index microlens, and other nanofabricated microlens systems.

768-ary Laguerre-Gaussian-mode shift keying free-space optical communication based on convolutional neural networks.

Beyond orbital angular momentum of Laguerre-Gaussian (LG) modes, the radial index can also be exploited as information channel in free-space optical (FSO) communication to extend the communication capacity, resulting in the LG- shift keying (LG-SK) FSO communications. However, the recognition of radial index is critical and tough when the superposed high-order LG modes are disturbed by the atmospheric turbulences (ATs). In this paper, the convolutional neural network (CNN) is utilized to recognize both the azimuthal and radial index of superposed LG modes. We experimentally demonstrate the application of CNN model in a 10-meter 768-ary LG-SK FSO communication system at the AT of Cn2 = 1e-14 m-2/3. Based on the high recognition accuracy of the CNN model (>95%) in the scheme, a colorful image can be transmitted and the peak signal-to-noise ratio of the received image can exceed 35 dB. We anticipate that our results can stimulate further researches on the utilization of the potential applications of LG modes with non-zero radial index based on the artificial-intelligence-enhanced optoelectronic systems.

Structural Determinants of the Gain-of-Function Phenotype of Human Leukemia-associated Mutant CBL Oncogene.

Mutations of the tyrosine kinase-directed ubiquitin ligase CBL cause myeloid leukemias, but the molecular determinants of the dominant leukemogenic activity of mutant CBL oncogenes are unclear. Here, we first define a gain-of-function attribute of the most common leukemia-associated CBL mutant, Y371H, by demonstrating its ability to increase proliferation of hematopoietic stem/progenitor cells (HSPCs) derived from CBL-null and CBL/CBL-B-null mice. Next, we express second-site point/deletion mutants of CBL-Y371H in CBL/CBL-B-null HSPCs or the cytokine-dependent human leukemic cell line TF-1 to show that individual or combined Tyr → Phe mutations of established phosphotyrosine residues (Tyr-700, Tyr-731, and Tyr-774) had little impact on the activity of the CBL-Y371H mutant in HSPCs, and the triple Tyr → Phe mutant was only modestly impaired in TF-1 cells. In contrast, intact tyrosine kinase-binding (TKB) domain and proline-rich region (PRR) were critical in both cell models. PRR deletion reduced the stem cell factor (SCF)-induced hyper-phosphorylation of the CBL-Y371H mutant and the c-KIT receptor and eliminated the sustained p-ERK1/2 and p-AKT induction by SCF. GST fusion protein pulldowns followed by phospho-specific antibody array analysis identified distinct CBL TKB domains or PRR-binding proteins that are phosphorylated in CBL-Y371H-expressing TF-1 cells. Our results support a model of mutant CBL gain-of-function in which mutant CBL proteins effectively compete with the remaining wild type CBL-B and juxtapose TKB domain-associated PTKs with PRR-associated signaling proteins to hyper-activate signaling downstream of hematopoietic growth factor receptors. Elucidation of mutant CBL domains required for leukemogenesis should facilitate targeted therapy approaches for patients with mutant CBL-driven leukemias.

A kinase inhibitor screen reveals protein kinase C-dependent endocytic recycling of ErbB2 in breast cancer cells.

ErbB2 overexpression drives oncogenesis in 20-30% cases of breast cancer. Oncogenic potential of ErbB2 is linked to inefficient endocytic traffic into lysosomes and preferential recycling. However, regulation of ErbB2 recycling is incompletely understood. We used a high-content immunofluorescence imaging-based kinase inhibitor screen on SKBR-3 breast cancer cells to identify kinases whose inhibition alters the clearance of cell surface ErbB2 induced by Hsp90 inhibitor 17-AAG. Less ErbB2 clearance was observed with broad-spectrum PKC inhibitor Ro 31-8220. A similar effect was observed with Go 6976, a selective inhibitor of classical Ca(2+)-dependent PKCs (α, ß1, ßII, and γ). PKC activation by PMA promoted surface ErbB2 clearance but without degradation, and ErbB2 was observed to move into a juxtanuclear compartment where it colocalized with PKC-α and PKC-δ together with the endocytic recycling regulator Arf6. PKC-α knockdown impaired the juxtanuclear localization of ErbB2. ErbB2 transit to the recycling compartment was also impaired upon PKC-δ knockdown. PMA-induced Erk phosphorylation was reduced by ErbB2 inhibitor lapatinib, as well as by knockdown of PKC-δ but not that of PKC-α. Our results suggest that activation of PKC-α and -δ mediates a novel positive feedback loop by promoting ErbB2 entry into the endocytic recycling compartment, consistent with reported positive roles for these PKCs in ErbB2-mediated tumorigenesis. As the endocytic recycling compartment/pericentrion has emerged as a PKC-dependent signaling hub for G-protein-coupled receptors, our findings raise the possibility that oncogenesis by ErbB2 involves previously unexplored PKC-dependent endosomal signaling.

Multimodal Artificial Synapses for Neuromorphic Application.

The rapid development of neuromorphic computing has led to widespread investigation of artificial synapses. These synapses can perform parallel in-memory computing functions while transmitting signals, enabling low-energy and fast artificial intelligence. Robots are the most ideal endpoint for the application of artificial intelligence. In the human nervous system, there are different types of synapses for sensory input, allowing for signal preprocessing at the receiving end. Therefore, the development of anthropomorphic intelligent robots requires not only an artificial intelligence system as the brain but also the combination of multimodal artificial synapses for multisensory sensing, including visual, tactile, olfactory, auditory, and taste. This article reviews the working mechanisms of artificial synapses with different stimulation and response modalities, and presents their use in various neuromorphic tasks. We aim to provide researchers in this frontier field with a comprehensive understanding of multimodal artificial synapses.

Memory-less scattering imaging with ultrafast convolutional optical neural networks.

The optical memory effect in complex scattering media including turbid tissue and speckle layers has been a critical foundation for macroscopic and microscopic imaging methods. However, image reconstruction from strong scattering media without the optical memory effect has not been achieved. Here, we demonstrate image reconstruction through scattering layers where no optical memory effect exists, by developing a multistage convolutional optical neural network (ONN) integrated with multiple parallel kernels operating at the speed of light. Training this Fourier optics-based, parallel, one-step convolutional ONN with the strong scattering process for direct feature extraction, we achieve memory-less image reconstruction with a field of view enlarged by a factor up to 271. This device is dynamically reconfigurable for ultrafast multitask image reconstruction with a computational power of 1.57 peta-operations per second (POPS). Our achievement establishes an ultrafast and high energy-efficient optical machine learning platform for graphic processing.

Orbital angular momentum-mediated machine learning for high-accuracy mode-feature encoding.

Machine learning with optical neural networks has featured unique advantages of the information processing including high speed, ultrawide bandwidths and low energy consumption because the optical dimensions (time, space, wavelength, and polarization) could be utilized to increase the degree of freedom. However, due to the lack of the capability to extract the information features in the orbital angular momentum (OAM) domain, the theoretically unlimited OAM states have never been exploited to represent the signal of the input/output nodes in the neural network model. Here, we demonstrate OAM-mediated machine learning with an all-optical convolutional neural network (CNN) based on Laguerre-Gaussian (LG) beam modes with diverse diffraction losses. The proposed CNN architecture is composed of a trainable OAM mode-dispersion impulse as a convolutional kernel for feature extraction, and deep-learning diffractive layers as a classifier. The resultant OAM mode-dispersion selectivity can be applied in information mode-feature encoding, leading to an accuracy as high as 97.2% for MNIST database through detecting the energy weighting coefficients of the encoded OAM modes, as well as a resistance to eavesdropping in point-to-point free-space transmission. Moreover, through extending the target encoded modes into multiplexed OAM states, we realize all-optical dimension reduction for anomaly detection with an accuracy of 85%. Our work provides a deep insight to the mechanism of machine learning with spatial modes basis, which can be further utilized to improve the performances of various machine-vision tasks by constructing the unsupervised learning-based auto-encoder.

GD2 and its biosynthetic enzyme GD3 synthase promote tumorigenesis in prostate cancer by regulating cancer stem cell behavior.

While better management of loco-regional prostate cancer (PC) has greatly improved survival, advanced PC remains a major cause of cancer deaths. Identification of novel targetable pathways that contribute to tumor progression in PC could open new therapeutic options. The di-ganglioside GD2 is a target of FDA-approved antibody therapies in neuroblastoma, but the role of GD2 in PC is unexplored. Here, we show that GD2 is expressed in a small subpopulation of PC cells in a subset of patients and a higher proportion of metastatic tumors. Variable levels of cell surface GD2 expression were seen on many PC cell lines, and the expression was highly upregulated by experimental induction of lineage progression or enzalutamide resistance in CRPC cell models. GD2high cell fraction was enriched upon growth of PC cells as tumorspheres and GD2high fraction was enriched in tumorsphere-forming ability. CRISPR-Cas9 knockout (KO) of the rate-limiting GD2 biosynthetic enzyme GD3 Synthase (GD3S) in GD2high CRPC cell models markedly impaired the in vitro oncogenic traits and growth as bone-implanted xenograft tumors and reduced the cancer stem cell and epithelial-mesenchymal transition marker expression. Our results support the potential role of GD3S and its product GD2 in promoting PC tumorigenesis by maintaining cancer stem cells and suggest the potential for GD2 targeting in advanced PC.

EHD2 overexpression promotes tumorigenesis and metastasis in triple-negative breast cancer by regulating store-operated calcium entry.

With nearly all cancer deaths a result of metastasis, elucidating novel pro-metastatic cellular adaptations could provide new therapeutic targets. Here, we show that overexpression of the EPS15-Homology Domain-containing 2 (EHD2) protein in a large subset of breast cancers (BCs), especially the triple-negative (TNBC) and HER2+ subtypes, correlates with shorter patient survival. The mRNAs for EHD2 and Caveolin-1/2, structural components of caveolae, show co-overexpression across breast tumors, predicting shorter survival in basal-like BC. EHD2 shRNA knockdown and CRISPR-Cas9 knockout with mouse Ehd2 rescue, in TNBC cell line models demonstrate a major positive role of EHD2 in promoting tumorigenesis and metastasis. Mechanistically, we link these roles of EHD2 to store-operated calcium entry (SOCE), with EHD2-dependent stabilization of plasma membrane caveolae ensuring high cell surface expression of the SOCE-linked calcium channel Orai1. The novel EHD2-SOCE oncogenic axis represents a potential therapeutic target in EHD2- and CAV1/2-overexpressing BC.

EHD1-dependent traffic of IGF-1 receptor to the cell surface is essential for Ewing sarcoma tumorigenesis and metastasis.

Overexpression of EPS15 Homology Domain containing 1 (EHD1) has been linked to tumorigenesis but whether its core function as a regulator of intracellular traffic of cell surface receptors plays a role in oncogenesis remains unknown. We establish that EHD1 is overexpressed in Ewing sarcoma (EWS), with high EHD mRNA expression specifying shorter patient survival. ShRNA and CRISPR-knockout with mouse Ehd1 rescue established a requirement of EHD1 for tumorigenesis and metastasis. RTK antibody arrays identified the IGF-1R as a target of EHD1 regulation in EWS. Mechanistically, we demonstrate a requirement of EHD1 for endocytic recycling and Golgi to plasma membrane traffic of IGF-1R to maintain its surface expression and downstream signaling. Conversely, EHD1 overexpression-dependent exaggerated oncogenic traits require IGF-1R expression and kinase activity. Our findings define the RTK traffic regulation as a proximal mechanism of EHD1 overexpression-dependent oncogenesis that impinges on IGF-1R in EWS, supporting the potential of IGF-1R and EHD1 co-targeting.

EHD1-dependent traffic of IGF-1 receptor to the cell surface is essential for Ewing sarcoma tumorigenesis and metastasis.

Overexpression of the EPS15 Homology Domain containing 1 (EHD1) protein has been linked to tumorigenesis but whether its core function as a regulator of intracellular traffic of cell surface receptors plays a role in oncogenesis remains unknown. We establish that EHD1 is overexpressed in Ewing sarcoma (EWS), with high EHD1 mRNA expression specifying shorter patient survival. ShRNA-knockdown and CRISPR-knockout with mouse Ehd1 rescue established a requirement of EHD1 for tumorigenesis and metastasis. RTK antibody arrays identified IGF-1R as a target of EHD1 regulation in EWS. Mechanistically, we demonstrate a requirement of EHD1 for endocytic recycling and Golgi to plasma membrane traffic of IGF-1R to maintain its surface expression and downstream signaling. Conversely, EHD1 overexpression-dependent exaggerated oncogenic traits require IGF-1R expression and kinase activity. Our findings define the RTK traffic regulation as a proximal mechanism of EHD1 overexpression-dependent oncogenesis that impinges on IGF-1R in EWS, supporting the potential of IGF-1R and EHD1 co-targeting.

Role of GD2 and its biosynthetic enzyme GD3 synthase in prostate cancer tumorigenesis.

While better management of loco-regional prostate cancer (PC) has greatly improved survival, advanced PC remains a major cause of cancer deaths. Identification of novel, targetable, pathways that contribute to tumor progression of PC could open new therapeutic options. The di-ganglioside GD2 is a target of FDA-approved antibody therapies in neuroblastoma, but the role of GD2 in PC has been only little explored. Here, we show that GD2 is expressed on a small subpopulation of PC cells in a subset of patients, especially in metastatic PC. Variable levels of cell surface GD2 expression are seen in most PC cell lines, and the expression is highly upregulated by experimental induction of lineage progression or enzalutamide resistance in CRPC cell models. GD2high cell fraction is enriched upon growth of PC cells as tumorspheres and GD2high fraction is enriched in tumorsphere growth. CRISPR-Cas9 knockout (KO) of the rate-limiting GD2 biosynthetic enzyme GD3 Synthase (GD3S) in GD2-high CRPC cell models led to marked impairment of their in vitro oncogenic traits, reduced cancer stem cell (CSC) and epithelial-mesenchymal transition (EMT) marker expression and growth as bone-implanted xenograft tumors. Our results support the potential role of GD3S and its product GD2 in promoting PC tumorigenesis by maintaining cancer stem cells and suggest the potential for GD2 targeting in advanced PC.

Mechanisms of Trastuzumab resistance in ErbB2-driven breast cancer and newer opportunities to overcome therapy resistance.

The Human Epidermal Growth Factor Receptor 2 (Her2, ErbB2 or Neu) is overexpressed in about 20 - 25% of breast cancers and is causally linked to oncogenesis, providing opportunities for targeted therapy. Trastuzumab (Herceptin(™), Genentech Inc, San Francisco, CA), a humanized monoclonal antibody against ErbB2, is a successful example of this concept and has vastly improved the response to treatment and overall survival in a majority of ErbB2+ breast cancer patients. However, lack of response in some patients as well as relapse during the course of therapy in others, continue to challenge researchers and clinicians alike towards a better understanding of the fundamental mechanisms of Trastuzumab action and resistance to treatment. The exact in vivo mechanism of action of Trastuzumab remains enigmatic, given its direct effects on the ErbB2 signaling pathway as well as indirect contributions from the immune system, by virtue of the ability of Trastuzumab to elicit Antibody-Dependent Cellular Cytotoxicity. Consequently, multiple mechanisms of resistance have been proposed. We present here a comprehensive review of our current understanding of the mechanisms, both of Trastuzumab action and clinical resistance to Trastuzumab-based therapies. We also review newer strategies (based on ErbB2 receptor biology) that are being explored to overcome resistance to Trastuzumab therapy.

Continuous requirement of ErbB2 kinase activity for loss of cell polarity and lumen formation in a novel ErbB2/Neu-driven murine cell line model of metastatic breast cancer.

BACKGROUND: Well over a quarter of human breast cancers are ErbB2-driven and constitute a distinct subtype with substantially poorer prognosis. Yet, there are substantial gaps in our understanding of how ErbB2 tyrosine kinase activity unleashes a coordinated program of cellular and extracellular alterations that culminate in aggressive breast cancers. Cellular models that exhibit ErbB2 kinase dependency and can induce metastatic breast cancer in immune competent hosts are likely to help bridge this gap. MATERIALS AND METHODS: Here, we derived and characterized a cell line model obtained from a transgenic ErbB2/Neu-driven mouse mammary adenocarcinoma. RESULTS: The MPPS1 cell line produces metastatic breast cancers when implanted in the mammary fat pads of immune-compromised as well as syngeneic immune-competent hosts. MPPS1 cells maintain high ErbB2 overexpression when propagated in DFCI-1 or related media, and their growth is ErbB2-dependent, as demonstrated by concentration-dependent inhibition of proliferation with the ErbB kinase inhibitor Lapatinib. When grown in 3-dimensional (3-D) culture on Matrigel, MPPS1 cells predominantly form large irregular cystic and solid structures. Remarkably, low concentrations of Lapatinib led to a switch to regular acinar growth on Matrigel. Immunofluorescence staining of control vs. Lapatinib-treated acini for markers of epithelial polarity revealed that inhibition of ErbB2 signaling led to rapid resumption of normal mammary epithelium-like cell polarity. CONCLUSIONS: The strict dependence of the MPPS1 cell system on ErbB2 signals for proliferation and alterations in cell polarity should allow its use to dissect ErbB2 kinase-dependent signaling pathways that promote loss of cell polarity, a key component of the epithelial mesenchymal transition and aggressiveness of ErbB2-driven breast cancers.

Nanoprinted high-neuron-density optical linear perceptrons performing near-infrared inference on a CMOS chip.

Optical machine learning has emerged as an important research area that, by leveraging the advantages inherent to optical signals, such as parallelism and high speed, paves the way for a future where optical hardware can process data at the speed of light. In this work, we present such optical devices for data processing in the form of single-layer nanoscale holographic perceptrons trained to perform optical inference tasks. We experimentally show the functionality of these passive optical devices in the example of decryptors trained to perform optical inference of single or whole classes of keys through symmetric and asymmetric decryption. The decryptors, designed for operation in the near-infrared region, are nanoprinted on complementary metal-oxide-semiconductor chips by galvo-dithered two-photon nanolithography with axial nanostepping of 10 nm1,2, achieving a neuron density of >500 million neurons per square centimetre. This power-efficient commixture of machine learning and on-chip integration may have a transformative impact on optical decryption3, sensing4, medical diagnostics5 and computing6,7.

Neuron-Inspired Steiner Tree Networks for 3D Low-Density Metastructures.

Three-dimensional (3D) micro-and nanostructures have played an important role in topological photonics, microfluidics, acoustic, and mechanical engineering. Incorporating biomimetic geometries into the design of metastructures has created low-density metamaterials with extraordinary physical and photonic properties. However, the use of surface-based biomimetic geometries restricts the freedom to tune the relative density, mechanical strength, and topological phase. The Steiner tree method inspired by the feature of the shortest connection distance in biological neural networks is applied, to create 3D metastructures and, through two-photon nanolithography, neuron-inspired 3D structures with nanoscale features are successfully achieved. Two solutions are presented to the 3D Steiner tree problem: the Steiner tree networks (STNs) and the twisted Steiner tree networks (T-STNs). STNs and T-STNs possess a lower density than surface-based metamaterials and that T-STNs have Young's modulus enhanced by 20% than the STNs. Through the analysis of the space groups and symmetries, a topological nontrivial Dirac-like conical dispersion in the T-STNs is predicted, and the results are based on calculations with true predictive power and readily realizable from microwave to optical frequencies. The neuron-inspired 3D metastructures opens a new space for designing low-density metamaterials and topological photonics with extraordinary properties triggered by a twisting degree-of-freedom.

CHIP/STUB1 Ubiquitin Ligase Functions as a Negative Regulator of ErbB2 by Promoting Its Early Post-Biosynthesis Degradation.

Overexpression of the epidermal growth factor receptor (EGFR) family member ErbB2 (HER2) drives oncogenesis in up to 25% of invasive breast cancers. ErbB2 expression at the cell surface is required for oncogenesis but mechanisms that ensure the optimal cell surface display of overexpressed ErbB2 following its biosynthesis in the endoplasmic reticulum are poorly understood. ErbB2 is dependent on continuous association with HSP90 molecular chaperone for its stability and function as an oncogenic driver. Here, we use knockdown and overexpression studies to show that the HSP90/HSC70-interacting negative co-chaperone CHIP (C-terminus of HSC70-Interacting protein)/STUB1 (STIP1-homologous U-Box containing protein 1) targets the newly synthesized, HSP90/HSC70-associated, ErbB2 for ubiquitin/proteasome-dependent degradation in the endoplasmic reticulum and Golgi, thus identifying a novel mechanism that negatively regulates cell surface ErbB2 levels in breast cancer cells, consistent with frequent loss of CHIP expression previously reported in ErbB2-overexpressing breast cancers. ErbB2-overexpressing breast cancer cells with low CHIP expression exhibited higher endoplasmic reticulum stress inducibility. Accordingly, the endoplasmic reticulum stress-inducing anticancer drug Bortezomib combined with ErbB2-targeted humanized antibody Trastuzumab showed synergistic inhibition of ErbB2-overexpressing breast cancer cell proliferation. Our findings reveal new insights into mechanisms that control the surface expression of overexpressed ErbB2 and suggest that reduced CHIP expression may specify ErbB2-overexpressing breast cancers suitable for combined treatment with Trastuzumab and ER stress inducing agents.