Micelle-Formulated Juglone Effectively Targets Pancreatic Cancer and Remodels the Tumor Microenvironment.

Pancreatic cancer remains a formidable challenge due to limited treatment options and its aggressive nature. In recent years, the naturally occurring anticancer compound juglone has emerged as a potential therapeutic candidate, showing promising results in inhibiting tumor growth and inducing cancer cell apoptosis. However, concerns over its toxicity have hampered juglone's clinical application. To address this issue, we have explored the use of polymeric micelles as a delivery system for juglone in pancreatic cancer treatment. These micelles, formulated using Poloxamer 407 and D-α-Tocopherol polyethylene glycol 1000 succinate, offer an innovative solution to enhance juglone's therapeutic potential while minimizing toxicity. In-vitro studies have demonstrated that micelle-formulated juglone (JM) effectively decreases proliferation and migration and increases apoptosis in pancreatic cancer cell lines. Importantly, in-vivo, JM exhibited no toxicity, allowing for increased dosing frequency compared to free drug administration. In mice, JM significantly reduced tumor growth in subcutaneous xenograft and orthotopic pancreatic cancer models. Beyond its direct antitumor effects, JM treatment also influenced the tumor microenvironment. In immunocompetent mice, JM increased immune cell infiltration and decreased stromal deposition and activation markers, suggesting an immunomodulatory role. To understand JM's mechanism of action, we conducted RNA sequencing and subsequent differential expression analysis on tumors that were treated with JM. The administration of JM treatment reduced the expression levels of the oncogenic protein MYC, thereby emphasizing its potential as a focused, therapeutic intervention. In conclusion, the polymeric micelles-mediated delivery of juglone holds excellent promise in pancreatic cancer therapy. This approach offers improved drug delivery, reduced toxicity, and enhanced therapeutic efficacy.

MYC Deregulation and PTEN Loss Model Tumor and Stromal Heterogeneity of Aggressive Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) patients have a poor prognosis and few treatment options. Mouse models of TNBC are important for development of new therapies, however, few mouse models represent the complexity of TNBC. Here, we develop a female TNBC murine model by mimicking two common TNBC mutations with high co-occurrence: amplification of the oncogene MYC and deletion of the tumor suppressor PTEN. This Myc;Ptenfl model develops heterogeneous triple-negative mammary tumors that display histological and molecular features commonly found in human TNBC. Our research involves deep molecular and spatial analyses on Myc;Ptenfl tumors including bulk and single-cell RNA-sequencing, and multiplex tissue-imaging. Through comparison with human TNBC, we demonstrate that this genetic mouse model develops mammary tumors with differential survival and therapeutic responses that closely resemble the inter- and intra-tumoral and microenvironmental heterogeneity of human TNBC, providing a pre-clinical tool for assessing the spectrum of patient TNBC biology and drug response.

Robust biomarker discovery through multiplatform multiplex image analysis of breast cancer clinical cohorts.

Spatial profiling of tissues promises to elucidate tumor-microenvironment interactions and enable development of spatial biomarkers to predict patient response to immunotherapy and other therapeutics. However, spatial biomarker discovery is often carried out on a single patient cohort or imaging technology, limiting statistical power and increasing the likelihood of technical artifacts. In order to analyze multiple patient cohorts profiled on different platforms, we developed methods for comparative data analysis from three disparate multiplex imaging technologies: 1) cyclic immunofluorescence data we generated from 102 breast cancer patients with clinical follow-up, in addition to publicly available 2) imaging mass cytometry and 3) multiplex ion-beam imaging data. We demonstrate similar single-cell phenotyping results across breast cancer patient cohorts imaged with these three technologies and identify cellular abundance and proximity-based biomarkers with prognostic value across platforms. In multiple platforms, we identified lymphocyte infiltration as independently associated with longer survival in triple negative and high-proliferation breast tumors. Then, a comparison of nine spatial analysis methods revealed robust spatial biomarkers. In estrogen receptor-positive disease, quiescent stromal cells close to tumor were more abundant in good prognosis tumors while tumor neighborhoods of mixed fibroblast phenotypes were enriched in poor prognosis tumors. In triple-negative breast cancer (TNBC), macrophage proximity to tumor and B cell proximity to T cells were greater in good prognosis tumors, while tumor neighborhoods of vimentin-positive fibroblasts were enriched in poor prognosis tumors. We also tested previously published spatial biomarkers in our ensemble cohort, reproducing the positive prognostic value of isolated lymphocytes and lymphocyte occupancy and failing to reproduce the prognostic value of tumor-immune mixing score in TNBC. In conclusion, we demonstrate assembly of larger clinical cohorts from diverse platforms to aid in prognostic spatial biomarker identification and validation.

A framework for multiplex imaging optimization and reproducible analysis.

Multiplex imaging technologies are increasingly used for single-cell phenotyping and spatial characterization of tissues; however, transparent methods are needed for comparing the performance of platforms, protocols and analytical pipelines. We developed a python software, mplexable, for reproducible image processing and utilize Jupyter notebooks to share our optimization of signal removal, antibody specificity, background correction and batch normalization of the multiplex imaging with a focus on cyclic immunofluorescence (CyCIF). Our work both improves the CyCIF methodology and provides a framework for multiplexed image analytics that can be easily shared and reproduced.

An omic and multidimensional spatial atlas from serial biopsies of an evolving metastatic breast cancer.

Mechanisms of therapeutic resistance and vulnerability evolve in metastatic cancers as tumor cells and extrinsic microenvironmental influences change during treatment. To support the development of methods for identifying these mechanisms in individual people, here we present an omic and multidimensional spatial (OMS) atlas generated from four serial biopsies of an individual with metastatic breast cancer during 3.5 years of therapy. This resource links detailed, longitudinal clinical metadata that includes treatment times and doses, anatomic imaging, and blood-based response measurements to clinical and exploratory analyses, which includes comprehensive DNA, RNA, and protein profiles; images of multiplexed immunostaining; and 2- and 3-dimensional scanning electron micrographs. These data report aspects of heterogeneity and evolution of the cancer genome, signaling pathways, immune microenvironment, cellular composition and organization, and ultrastructure. We present illustrative examples of how integrative analyses of these data reveal potential mechanisms of response and resistance and suggest novel therapeutic vulnerabilities.

Oligonucleotide conjugated antibody strategies for cyclic immunostaining.

A number of highly multiplexed immunostaining and imaging methods have advanced spatial proteomics of cancer for improved treatment strategies. While a variety of methods have been developed, the most widely used methods are limited by harmful signal removal techniques, difficulties with reagent production and antigen sensitivity. Multiplexed immunostaining employing oligonucleotide (oligos)-barcoded antibodies is an alternative approach that is growing in popularity. However, challenges remain in consistent conjugation of oligos to antibodies with maintained antigenicity as well as non-destructive, robust and cost-effective signal removal methods. Herein, a variety of oligo conjugation and signal removal methods were evaluated in the development of a robust oligo conjugated antibody cyclic immunofluorescence (Ab-oligo cyCIF) methodology. Both non- and site-specific conjugation strategies were assessed to label antibodies, where site-specific conjugation resulted in higher retained binding affinity and antigen-specific staining. A variety of fluorescence signal removal methods were also evaluated, where incorporation of a photocleavable link (PCL) resulted in full fluorescence signal removal with minimal tissue disruption. In summary, this work resulted in an optimized Ab-oligo cyCIF platform capable of generating high dimensional images to characterize the spatial proteomics of the hallmarks of cancer.

Multiomics analysis of serial PARP inhibitor treated metastatic TNBC inform on rational combination therapies.

In a pilot study, we evaluated the feasibility of real-time deep analysis of serial tumor samples from triple negative breast cancer patients to identify mechanisms of resistance and treatment opportunities as they emerge under therapeutic stress engendered by poly-ADP-ribose polymerase (PARP) inhibitors (PARPi). In a BRCA-mutant basal breast cancer exceptional long-term survivor, a striking tumor destruction was accompanied by a marked infiltration of immune cells containing CD8 effector cells, consistent with pre-clinical evidence for association between STING mediated immune activation and benefit from PARPi and immunotherapy. Tumor cells in the exceptional responder underwent extensive protein network rewiring in response to PARP inhibition. In contrast, there were minimal changes in the ecosystem of a luminal androgen receptor rapid progressor, likely due to indifference to the effects of PARP inhibition. Together, identification of PARPi-induced emergent changes could be used to select patient specific combination therapies, based on tumor and immune state changes.

Toward reproducible, scalable, and robust data analysis across multiplex tissue imaging platforms.

The emergence of megascale single-cell multiplex tissue imaging (MTI) datasets necessitates reproducible, scalable, and robust tools for cell phenotyping and spatial analysis. We developed open-source, graphics processing unit (GPU)-accelerated tools for intensity normalization, phenotyping, and microenvironment characterization. We deploy the toolkit on a human breast cancer (BC) tissue microarray stained by cyclic immunofluorescence and present the first cross-validation of breast cancer cell phenotypes derived by using two different MTI platforms. Finally, we demonstrate an integrative phenotypic and spatial analysis revealing BC subtype-specific features.

Sensitivity to targeted therapy differs between HER2-amplified breast cancer cells harboring kinase and helical domain mutations in PIK3CA.

BACKGROUND: HER2-amplified breast cancer is a clinically defined subtype of breast cancer for which there are multiple viable targeted therapies. Resistance to these targeted therapies is a common problem, but the mechanisms by which resistance occurs remain incompletely defined. One mechanism that has been proposed is through mutation of genes in the PI3-kinase pathway. Intracellular signaling from the HER2 pathway can occur through PI3-kinase, and mutations of the encoding gene PIK3CA are known to be oncogenic. Mutations in PIK3CA co-occur with HER2-amplification in ~ 20% of cases within the HER2-amplified subtype. METHODS: We generated isogenic knockin mutants of each PIK3CA hotspot mutation in HER2-amplified breast cancer cells using adeno-associated virus-mediated gene targeting. Isogenic clones were analyzed using a combinatorial drug screen to determine differential responses to HER2-targeted therapy. Western blot analysis and immunofluorescence uncovered unique intracellular signaling dynamics in cells resistant to HER2-targeted therapy. Subsequent combinatorial drug screens were used to explore neuregulin-1-mediated resistance to HER2-targeted therapy. Finally, results from in vitro experiments were extrapolated to publicly available datasets. RESULTS: Treatment with HER2-targeted therapy reveals that mutations in the kinase domain (H1047R) but not the helical domain (E545K) increase resistance to lapatinib. Mechanistically, sustained AKT signaling drives lapatinib resistance in cells with the kinase domain mutation, as demonstrated by staining for the intracellular product of PI3-kinase, PIP3. This resistance can be overcome by co-treatment with an inhibitor to the downstream kinase AKT. Additionally, knockout of the PIP3 phosphatase, PTEN, phenocopies this result. We also show that neuregulin-1, a ligand for HER-family receptors, confers resistance to cells harboring either hotspot mutation and modulates response to combinatorial therapy. Finally, we show clinical evidence that the hotspot mutations have distinct expression profiles related to therapeutic resistance through analysis of TCGA and METABRIC data cohorts. CONCLUSION: Our results demonstrate unique intracellular signaling differences depending on which mutation in PIK3CA the cell harbors. Only mutations in the kinase domain fully activate the PI3-kinase signaling pathway and maintain downstream signaling in the presence of HER2 inhibition. Moreover, we show there is potentially clinical importance in understanding both the PIK3CA mutational status and levels of neuregulin-1 expression in patients with HER2-amplified breast cancer treated with targeted therapy and that these problems warrant further pre-clinical and clinical testing.

Relevance of circulating hybrid cells as a non-invasive biomarker for myriad solid tumors.

Metastatic progression defines the final stages of tumor evolution and underlies the majority of cancer-related deaths. The heterogeneity in disseminated tumor cell populations capable of seeding and growing in distant organ sites contributes to the development of treatment resistant disease. We recently reported the identification of a novel tumor-derived cell population, circulating hybrid cells (CHCs), harboring attributes from both macrophages and neoplastic cells, including functional characteristics important to metastatic spread. These disseminated hybrids outnumber conventionally defined circulating tumor cells (CTCs) in cancer patients. It is unknown if CHCs represent a generalized cancer mechanism for cell dissemination, or if this population is relevant to the metastatic cascade. Herein, we detect CHCs in the peripheral blood of patients with cancer in myriad disease sites encompassing epithelial and non-epithelial malignancies. Further, we demonstrate that in vivo-derived hybrid cells harbor tumor-initiating capacity in murine cancer models and that CHCs from human breast cancer patients express stem cell antigens, features consistent with the potential to seed and grow at metastatic sites. Finally, we reveal heterogeneity of CHC phenotypes reflect key tumor features, including oncogenic mutations and functional protein expression. Importantly, this novel population of disseminated neoplastic cells opens a new area in cancer biology and renewed opportunity for battling metastatic disease.

The impact of tumor epithelial and microenvironmental heterogeneity on treatment responses in HER2+ breast cancer.

Despite the availability of multiple human epidermal growth factor receptor 2-targeted (HER2-targeted) treatments, therapeutic resistance in HER2+ breast cancer remains a clinical challenge. Intratumor heterogeneity for HER2 and resistance-conferring mutations in the PIK3CA gene (encoding PI3K catalytic subunit α) have been investigated in response and resistance to HER2-targeting agents, while the role of divergent cellular phenotypes and tumor epithelial-stromal cell interactions is less well understood. Here, we assessed the effect of intratumor cellular genetic heterogeneity for ERBB2 (encoding HER2) copy number and PIK3CA mutation on different types of neoadjuvant HER2-targeting therapies and clinical outcome in HER2+ breast cancer. We found that the frequency of cells lacking HER2 was a better predictor of response to HER2-targeted treatment than intratumor heterogeneity. We also compared the efficacy of different therapies in the same tumor using patient-derived xenograft models of heterogeneous HER2+ breast cancer and single-cell approaches. Stromal determinants were better predictors of response than tumor epithelial cells, and we identified alveolar epithelial and fibroblastic reticular cells as well as lymphatic vessel endothelial hyaluronan receptor 1-positive (Lyve1+) macrophages as putative drivers of therapeutic resistance. Our results demonstrate that both preexisting and acquired resistance to HER2-targeting agents involve multiple mechanisms including the tumor microenvironment. Furthermore, our data suggest that intratumor heterogeneity for HER2 should be incorporated into treatment design.

Genomic Alterations during the In Situ to Invasive Ductal Breast Carcinoma Transition Shaped by the Immune System.

The drivers of ductal carcinoma in situ (DCIS) to invasive ductal carcinoma (IDC) transition are poorly understood. Here, we conducted an integrated genomic, transcriptomic, and whole-slide image analysis to evaluate changes in copy-number profiles, mutational profiles, expression, neoantigen load, and topology in 6 cases of matched pure DCIS and recurrent IDC. We demonstrate through combined copy-number and mutational analysis that recurrent IDC can be genetically related to its pure DCIS despite long latency periods and therapeutic interventions. Immune "hot" and "cold" tumors can arise as early as DCIS and are subtype-specific. Topologic analysis showed a similar degree of pan-leukocyte-tumor mixing in both DCIS and IDC but differ when assessing specific immune subpopulations such as CD4 T cells and CD68 macrophages. Tumor-specific copy-number aberrations in MHC-I presentation machinery and losses in 3p, 4q, and 5p are associated with differences in immune signaling in estrogen receptor (ER)-negative IDC. Common oncogenic hotspot mutations in genes including TP53 and PIK3CA are predicted to be neoantigens yet are paradoxically conserved during the DCIS-to-IDC transition, and are associated with differences in immune signaling. We highlight both tumor and immune-specific changes in the transition of pure DCIS to IDC, including genetic changes in tumor cells that may have a role in modulating immune function and assist in immune escape, driving the transition to IDC. IMPLICATIONS: We demonstrate that the in situ to IDC evolutionary bottleneck is shaped by both tumor and immune cells.

Simultaneous Detection of RNAs and Proteins with Subcellular Resolution.

We describe the detailed methods of "immunoFISH" to analyze the expression level and the spatial localization of RNA transcripts and proteins on cultured cells and formal-fixed, paraffin-embedded (FFPE) tissue sections. On cultured cells, we detect specific transcripts using the Stellaris fluorescence in situ hybridization (FISH) probes labeled with fluorophores that target multiple regions along the desired transcripts and proteins combining the immunofluorescent staining. On FFPE tissue sections, we use the RNAscope FISH probes, modified branched DNA (bDNA) probes to amplify the RNA signals, followed by immunofluorescent staining for protein detection. The abundance, composition, and spatial distribution are determined by signals from fluorescently labeled proteins and individual transcripts of images acquired using high-resolution fluorescence microscopy.

Oligonucleotide conjugated antibodies permit highly multiplexed immunofluorescence for future use in clinical histopathology.

SIGNIFICANCE: Advanced genetic characterization has informed cancer heterogeneity and the challenge it poses to effective therapy; however, current methods lack spatial context, which is vital to successful cancer therapy. Conventional immunolabeling, commonplace in the clinic, can provide spatial context to protein expression. However, these techniques are spectrally limited, resulting in inadequate capacity to resolve the heterogenous cell subpopulations within a tumor. AIM: We developed and optimized oligonucleotide conjugated antibodies (Ab-oligo) to facilitate cyclic immunofluorescence (cyCIF), resulting in high-dimensional immunostaining. APPROACH: We employed a site-specific conjugation strategy to label antibodies with unique oligonucleotide sequences, which were hybridized in situ with their complementary oligonucleotide sequence tagged with a conventional fluorophore. Antibody concentration, imaging strand concentration, and configuration as well as signal removal strategies were optimized to generate maximal staining intensity using our Ab-oligo cyCIF strategy. RESULTS: We successfully generated 14 Ab-oligo conjugates and validated their antigen specificity, which was maintained in single color staining studies. With the validated antibodies, we generated up to 14-color imaging data sets of human breast cancer tissues. CONCLUSIONS: Herein, we demonstrated the utility of Ab-oligo cyCIF as a platform for highly multiplexed imaging, its utility to measure tumor heterogeneity, and its potential for future use in clinical histopathology.

Fluorescent Imaging for In Situ Measurement of Drug Target Engagement and Cell Signaling Pathways.

Successful cancer treatment continues to elude modern medicine and its arsenal of therapeutic strategies. Therapy resistance is driven by significant tumor heterogeneity, complex interactions between malignant, microenvironmental and immune cells and cross talk between signaling pathways. Advances in molecular characterization technologies such as next generation sequencing have helped unravel this network of interactions and identify druggable therapeutic targets. Tyrosine kinase inhibitors (TKI) are a class of drugs seeking to inhibit signaling pathways critical to sustaining proliferative signaling, resisting cell death, and the other hallmarks of cancer. While tumors may initially respond to TKI therapy, disease progression is near universal due to mechanisms of acquired resistance largely involving cellular signaling pathway reprogramming. With the ultimate goal of improved TKI therapeutic efficacy our group has developed intracellular paired agent imaging (iPAI) to quantify drug target interactions and oligonucleotide conjugated antibody (Ab-oligo) cyclic immunofluorescence (cycIF) imaging to characterize perturbed signaling pathways in response to therapy. iPAI uses spectrally distinct, fluorescently labeled targeted and untargeted drug derivatives, correcting for non-specific drug distribution and facilitating quantitative assessment of the drug binding before and after therapy. Ab-oligo cycIF exploits in situ hybridization of complementary oligonucleotides for biomarker labeling while oligonucleotide modifications facilitate signal removal for sequential rounds of fluorescent tagging and imaging. Ab-oligo CycIF is capable of generating extreme multi-parametric images for quantifying total and phosphorylated protein expression to quantify protein activation, expression, and spatial distribution. Together iPAI and Ab-oligo cycIF can be applied to interrogate drug uptake and target binding as well as changes to heterogenous cell populations within tumors that drive variable therapeutic responses in patients.

RESTORE: Robust intEnSiTy nORmalization mEthod for multiplexed imaging.

Recent advances in multiplexed imaging technologies promise to improve the understanding of the functional states of individual cells and the interactions between the cells in tissues. This often requires compilation of results from multiple samples. However, quantitative integration of information between samples is complicated by variations in staining intensity and background fluorescence that obscure biological variations. Failure to remove these unwanted artifacts will complicate downstream analysis and diminish the value of multiplexed imaging for clinical applications. Here, to compensate for unwanted variations, we automatically identify negative control cells for each marker within the same tissue and use their expression levels to infer background signal level. The intensity profile is normalized by the inferred level of the negative control cells to remove between-sample variation. Using a tissue microarray data and a pair of longitudinal biopsy samples, we demonstrated that the proposed approach can remove unwanted variations effectively and shows robust performance.

Deregulating MYC in a model of HER2+ breast cancer mimics human intertumoral heterogeneity.

The c-MYC (MYC) oncoprotein is often overexpressed in human breast cancer; however, its role in driving disease phenotypes is poorly understood. Here, we investigate the role of MYC in HER2+ disease, examining the relationship between HER2 expression and MYC phosphorylation in HER2+ patient tumors and characterizing the functional effects of deregulating MYC expression in the murine NeuNT model of amplified-HER2 breast cancer. Deregulated MYC alone was not tumorigenic, but coexpression with NeuNT resulted in increased MYC Ser62 phosphorylation and accelerated tumorigenesis. The resulting tumors were metastatic and associated with decreased survival compared with NeuNT alone. MYC;NeuNT tumors had increased intertumoral heterogeneity including a subtype of tumors not observed in NeuNT tumors, which showed distinct metaplastic histology and worse survival. The distinct subtypes of MYC;NeuNT tumors match existing subtypes of amplified-HER2, estrogen receptor-negative human tumors by molecular expression, identifying the preclinical utility of this murine model to interrogate subtype-specific differences in amplified-HER2 breast cancer. We show that these subtypes have differential sensitivity to clinical HER2/EGFR-targeted therapeutics, but small-molecule activators of PP2A, the phosphatase that regulates MYC Ser62 phosphorylation, circumvents these subtype-specific differences and ubiquitously suppresses tumor growth, demonstrating the therapeutic utility of this approach in targeting deregulated MYC breast cancers.

Cyclic Multiplexed-Immunofluorescence (cmIF), a Highly Multiplexed Method for Single-Cell Analysis.

Immunotherapy harnesses the power of the adaptive immune system and has revolutionized the field of oncotherapy, as novel therapeutic strategies have been introduced into clinical use. The development of immune checkpoint inhibitors has led to durable control of disease in a subset of advanced cancer patients, such as those with melanoma and non-small cell lung cancer. However, predicting patient responses to therapy remains a major challenge, due to the remarkable genomic, epigenetic, and microenvironmental heterogeneity present in each tumor. Breast cancer (BC) is the most common cancer in women, where hormone receptor-positive (HR+; estrogen receptor and/or progesterone receptor) BC comprises the majority (>50%) and has better prognosis, while a minority (<20%) are triple negative BC (TNBC), which has an aggressive phenotype. There is a clinical need to identify predictors of late recurrence in HR+ BC and predictors of immunotherapy outcomes in advanced TNBC. Tumor-infiltrating lymphocytes (TILs) have recently been shown to predict late recurrence in HR+, counter to the findings that TILs confer good prognosis in TNBC and human epidermal growth factor receptor 2 positive (HER2+) subtypes. Furthermore, the spatial arrangement of TILs also appears to have prognostic value, with dense clusters of immune cells predicting poor prognosis in HR+ and good prognosis in TNBC. Whether TIL clusters in different breast cancer subtypes represent the same or different landscapes of TILs is unknown and may have treatment implications for a significant portion of breast cancer patients. Current histopathological staining technology is not sufficient for characterizing the ensembles of TILs and their spatial patterns, in addition to tumor and microenvironmental heterogeneity. However, recent advances in cyclic immunofluorescence enable differentiation of the subsets based on TILs, tumor heterogeneity, and microenvironment composition between good and poor responders. A computational framework for understanding the importance of the spatial relationships between TILs and tumor cells in cancer tissues, which will allow for quantitative interpretation of cyclic immunostaining, is also under development. This chapter will explore the workflow for a newly developed cyclic multiplexed-immunofluorescence (cmIF) assay, which has been optimized for formalin-fixed. paraffin-embedded tissues and developed to process digital images for quantitative single-cell based spatial analysis of tumor heterogeneity and microenvironment, including immune cell composition.

Proteomics advances for precision therapy in ovarian cancer.

Introduction: Due to the relatively low mutation rate and high frequency of copy number variation, finding actionable genetic drivers of high-grade serous carcinoma (HGSC) is a challenging task. Furthermore, emerging studies show that genetic alterations are frequently poorly represented at the protein level adding a layer of complexity. With improvements in large-scale proteomic technologies, proteomics studies have the potential to provide robust analysis of the pathways driving high HGSC behavior. Areas covered: This review summarizes recent large-scale proteomics findings across adequately sized ovarian cancer sample sets. Key words combined with 'ovarian cancer' including 'proteomics', 'proteogenomic', 'reverse-phase protein array', 'mass spectrometry', and 'adaptive response', were used to search PubMed. Expert opinion: Proteomics analysis of HGSC as well as their adaptive responses to therapy can uncover new therapeutic liabilities, which can reduce the emergence of drug resistance and potentially improve patient outcomes. There is a pressing need to better understand how the genomic and epigenomic heterogeneity intrinsic to ovarian cancer is reflected at the protein level and how this information could be used to improve patient outcomes.

GRB7 dependent proliferation of basal-like, HER-2 positive human breast cancer cell lines is mediated in part by HER-1 signaling.

GRB7 gene encodes a multi-domain signal transduction molecule and is part of the core of the HER-2 amplicon. GRB7 is commonly co-amplified and overexpressed with HER-2 in human breast cancer. This study addresses the role of GRB7 in HER-2 positive human breast cancers resistant to HER-2 targeted therapy. HCC1954, 21MT1, and JIMT1 are basal like HER-2 positive breast cancer cell lines based on expression profiling. These three cell lines are resistant to trastuzumab and lapatinib treatment. Knockdown of GRB7 protein expression with siRNA transfection as well as lentiviral vector mediated shRNA over-expression decreased the growth of HCC1954, 21MT1, and JIMT1 cells in vitro and the growth of tumor xenografts these cells formed in animal models. When assayed by ki-67 staining and TUNEL assay, the mechanism of reduced tumor xenograft growth appeared to be distinct. Reduced proliferation and increased apoptosis were seen in 21MT1 cells, while reduced proliferation was seen in HCC1954 cells and increased apoptosis in JIMT1 cells. Phospho-proteome profiling found HER-1 tyrosine phosphorylation was reduced with GRB7 knock down in JIMT1 cells. Immuno-blotting and immuno-precipitation experiments found HER-1 phosphorylation was reduced with GRB7 knock down in all three cell lines. HER-1 knock down via siRNA transient transfection as well as blocking HER-1 function with panitumumab decreased proliferation of all three cell lines in vitro. Our study finds that GRB7 has an essential growth promoting function which is mediated in part by HER-1 activation. The potential of HER-1 targeting in therapy resistant HER-2 positive breast cancer merits further study.