Multiplexed cell signaling analysis of human breast cancer applications for personalized therapy

Quantitative proteomic analysis of HER2 protein expression in PDAC tumors

Metastatic pancreatic adenocarcinoma (PDAC) is the third leading cause of cancer-related death in the United States, with a 5-year survival rate of only 11%, necessitating identification of novel treatment paradigms. Tumor tissue specimens from patients with PDAC, breast cancer, and other solid tumor malignancies were collected and tumor cells were enriched using laser microdissection (LMD). Reverse phase protein array (RPPA) analysis was performed on enriched tumor cell lysates to quantify a 32-protein/phosphoprotein biomarker panel comprising known anticancer drug targets and/or cancer-related total and phosphorylated proteins, including HER2Total, HER2Y1248, and HER3Y1289. RPPA analysis revealed significant levels of HER2Total in PDAC patients at abundances comparable to HER2-positive (IHC 3+) and HER2-low (IHC 1+ /2+ , FISH-) breast cancer tissues, for which HER2 screening is routinely performed. These data support a critical unmet need for routine clinical evaluation of HER2 expression in PDAC patients and examination of the utility of HER2-directed antibody-drug conjugates in these patients.

Establishment and characterization of patient-derived xenograft of a rare pediatric anaplastic pleomorphic xanthoastrocytoma (PXA) bearing a CDC42SE2-BRAF fusion

Pleomorphic xanthoastrocytoma (PXA) is a rare subset of primary pediatric glioma with 70% 5-year disease free survival. However, up to 20% of cases present with local recurrence and malignant transformation into more aggressive type anaplastic PXA (AXPA) or glioblastoma. The understanding of disease etiology and mechanisms driving PXA and APXA are limited, and there is no standard of care. Therefore, development of relevant preclinical models to investigate molecular underpinnings of disease and to guide novel therapeutic approaches are of interest. Here, for the first time we established, and characterized a patient-derived xenograft (PDX) from a leptomeningeal spread of a patient with recurrent APXA bearing a novel CDC42SE2-BRAF fusion. An integrated -omics analysis was conducted to assess model fidelity of the genomic, transcriptomic, and proteomic/phosphoproteomic landscapes. A stable xenoline was derived directly from the patient recurrent tumor and maintained in 2D and 3D culture systems. Conserved histology features between the PDX and matched APXA specimen were maintained through serial passages. Whole exome sequencing (WES) demonstrated a high degree of conservation in the genomic landscape between PDX and matched human tumor, including small variants (Pearson's r = 0.794-0.839) and tumor mutational burden (~ 3 mutations/MB). Large chromosomal variations including chromosomal gains and losses were preserved in PDX. Notably, chromosomal gain in chromosomes 4-9, 17 and 18 and loss in the short arm of chromosome 9 associated with homozygous 9p21.3 deletion involving CDKN2A/B locus were identified in both patient tumor and PDX sample. Moreover, chromosomal rearrangement involving 7q34 fusion; CDC42SE-BRAF t (5;7) (q31.1, q34) (5:130,721,239, 7:140,482,820) was identified in the PDX tumor, xenoline and matched human tumor. Transcriptomic profile of the patient's tumor was retained in PDX (Pearson r = 0.88) and in xenoline (Pearson r = 0.63) as well as preservation of enriched signaling pathways (FDR Adjusted P < 0.05) including MAPK, EGFR and PI3K/AKT pathways. The multi-omics data of (WES, transcriptome, and reverse phase protein array (RPPA) was integrated to deduce potential actionable pathways for treatment (FDR < 0.05) including KEGG01521, KEGG05202, and KEGG05200. Both xenoline and PDX were resistant to the MEK inhibitors trametinib or mirdametinib at clinically relevant doses, recapitulating the patient's resistance to such treatment in the clinic. This set of APXA models will serve as a preclinical resource for developing novel therapeutic regimens for rare anaplastic PXAs and pediatric high-grade gliomas bearing BRAF fusions.

Integrative Multi-OMICs Identifies Therapeutic Response Biomarkers and Confirms Fidelity of Clinically Annotated, Serially Passaged Patient-Derived Xenografts Established from Primary and Metastatic Pediatric and AYA Solid Tumors

Establishment of clinically annotated, molecularly characterized, patient-derived xenografts (PDXs) from treatment-naïve and pretreated patients provides a platform to test precision genomics-guided therapies. An integrated multi-OMICS pipeline was developed to identify cancer-associated pathways and evaluate stability of molecular signatures in a panel of pediatric and AYA PDXs following serial passaging in mice. Original solid tumor samples and their corresponding PDXs were evaluated by whole-genome sequencing, RNA-seq, immunoblotting, pathway enrichment analyses, and the drug−gene interaction database to identify as well as cross-validate actionable targets in patients with sarcomas or Wilms tumors. While some divergence between original tumor and the respective PDX was evident, majority of alterations were not functionally impactful, and oncogenic pathway activation was maintained following serial passaging. CDK4/6 and BETs were prioritized as biomarkers of therapeutic response in osteosarcoma PDXs with pertinent molecular signatures. Inhibition of CDK4/6 or BETs decreased osteosarcoma PDX growth (two-way ANOVA, p < 0.05) confirming mechanistic involvement in growth. Linking patient treatment history with molecular and efficacy data in PDX will provide a strong rationale for targeted therapy and improve our understanding of which therapy is most beneficial in patients at diagnosis and in those already exposed to therapy.

Applications of Proteomics in Ovarian Cancer: Dawn of a New Era

The ability to identify ovarian cancer (OC) at its earliest stages remains a challenge. The patients present an advanced stage at diagnosis. This heterogeneous disease has distinguishable etiology and molecular biology. Next-generation sequencing changed clinical diagnostic testing, allowing assessment of multiple genes, simultaneously, in a faster and cheaper manner than sequential single gene analysis. Technologies of proteomics, such as mass spectrometry (MS) and protein array analysis, have advanced the dissection of the underlying molecular signaling events and the proteomic characterization of OC. Proteomics analysis of OC, as well as their adaptive responses to therapy, can uncover new therapeutic choices, which can reduce the emergence of drug resistance and potentially improve patient outcomes. There is an urgent need to better understand how the genomic and epigenomic heterogeneity intrinsic to OC is reflected at the protein level, and how this information could potentially lead to prolonged survival.

A Positive Feedback Loop Between TGFβ and Androgen Receptor Supports Triple-negative Breast Cancer Anoikis Resistance

Triple-negative breast cancer (TNBC) is an aggressive subtype with peak recurrence as metastatic disease within the first few years of diagnosis. Androgen receptor (AR) expression is increased in anchorage-independent cells in TNBC preclinical models. Both AR knockdown and inhibition lead to reduced TNBC invasion in vitro, reduced tumorigenicity, and less recurrence in vivo in preclinical models. Transforming growth factor β (TGFβ) pathway gene signatures also increased during anchorage-independent survival both in vitro and in vivo in preclinical models and in circulating tumor cells (CTCs) from patients during emergence of chemo resistant disease. We hypothesized that a positive loop between AR and TGFβ signaling facilitates TNBC anchorage-independent survival. We find that multiple components of the TGFβ pathway, including TGFβ1 and 3, as well as pathway activity measured by nuclear localization and transcriptional activity of phosphorylated Smad3, are enhanced in anchorage-independent conditions. Further, exogenous TGFβ increased AR protein while TGFβ inhibition decreased AR and TNBC viability, particularly under anchorage-independent culture conditions. ChIP-seq experiments revealed AR binding to TGFB1 and SMAD3 regulatory regions in MDA-MB-453 cells. In clinical datasets, TGFB3 and AR positively correlate and high expression of both genes together corresponded to significantly worse recurrence-free and overall survival in both ER-negative and basal-like breast cancer. Finally, inhibiting both AR and TGFβ decreased cell survival, particularly under anchorage-independent conditions. These findings warrant further investigations into whether combined inhibition of AR and TGFβ pathways might decrease metastatic recurrence rates and mortality from TNBC.

The impact of ultraviolet- and infrared-based laser microdissection technology on phosphoprotein detection in the laser microdissection-reverse phase protein array workflow

Reversible protein phosphorylation represents a key mechanism by which signals are transduced in eukaryotic cells. Dysregulated phosphorylation is also a hallmark of carcinogenesis and represents key drug targets in the precision medicine space. Thus, methods that preserve phosphoprotein integrity in the context of clinical tissue analyses are crucially important in cancer research. Here we investigated the impact of UV laser microdissection (UV LMD) and IR laser capture microdissection (IR LCM) on phosphoprotein abundance of key cancer signaling protein targets assessed by reverse-phase protein microarray (RPPA). Tumor epithelial cells from consecutive thin sections obtained from four high-grade serous ovarian cancers were harvested using either UV LMD or IR LCM methods. Phosphoprotein abundances for ten phosphoproteins that represent important drug targets were assessed by RPPA and revealed no significant differences in phosphoprotein integrity from those obtained using higher-energy UV versus the lower-energy IR laser methods.

RPPA: Origins, Transition to a Validated Clinical Research Tool, and Next Generations of the Technology

RPPA technology has graduated from a research tool to an essential component of clinical drug discovery research and personalized medicine. Next generations of RPPA technology will be a single clinical instrument that integrates all the steps of the workflow.

Development of RBC Membrane Antigen Arrays for Validating Blood Grouping Reagents

Antibody reagents have been remained as a standard approach to characterize blood group (BG) antigens in clinic. The specificity and cross-reactivity of these BG antibodies are routine detected using the gel microcolumn assay (GMA). However, the GMA is neither specific nor sensitive, thus increasing the risk of improperly matched RBC transfusions. In this work, we describe a bead-based RBC membrane antigen array to detect BG antibody-antigen binding with ∼700-fold higher sensitivity and dynamic range than the GMA. RBC membrane antigen arrays were fabricated using fragmented RBC membranes highly enriched in BG panel antigens. The arrays were then used to screen the interactions of 15 BG reagents to three antigen panels. The majority of the antibody reactions (i.e., 86.7%; 39/45) aligned with those obtained with the GMA. The six cross-reactive, nonspecific antibody reactions identified only by our arrays (i.e., 13.3%; 6/45) were confirmed by agglutination inhibition and genotyping assays. These results demonstrate that our RBC membrane antigen array has great potential in screening BG antibodies and improving the safety of RBC transfusions.

Quantitative screening of serum protein biomarkers by reverse phase protein arrays

Screening biomarkers in serum samples for different diseases has always been of great interest because it presents an early, reliable, and, most importantly, noninvasive means of diagnosis and prognosis. Reverse phase protein arrays (RPPAs) are a high-throughput platform that can measure single or limited sets of proteins from thousands of patients' samples in parallel. They have been widely used for detection of signaling molecules involved in diseases, especially cancers, and related regulation pathways in cell lysates. However, this approach has been difficult to adapt to serum samples. Previously, we developed a sensitive method called the enhanced protein array to quantitatively measure serum protein levels from large numbers of patient samples. Here, we further refine the technology on several fronts: 1. simplifying the experimental procedure; 2. optimizing multiple parameters to make the assay more robust, including the support matrix, signal reporting method, background control, and antibody validation; and 3. establishing a method for more accurate quantification. Using this technology, we quantitatively measured the expression levels of 10 proteins: alpha-fetoprotein (AFP), beta 2 microglobulin (B2M), Carcinoma Antigen 15-3(CA15-3), Carcinoembryonic antigen (CEA), golgi protein 73 (GP73), Growth differentiation factor 15 (GDF15), Human Epididymis Protein 4 (HE4), Insulin Like Growth Factor Binding Protein 2 (IGFBP2), osteopontin (OPN) and Beta-type platelet-derived growth factor receptor (PDGFRB) from serum samples of 132 hepatocellular carcinoma (HCC) patients and 78 healthy volunteers. We found that 6 protein expression levels are significantly increased in HCC patients. Statistical and bioinformatical analysis has revealed decent accuracy rates of individual proteins, ranging from 0.617 (B2M) to 0.908 (AFP) as diagnostic biomarkers to distinguish HCC from healthy controls. The combination of these 6 proteins as a specific HCC signature yielded a higher accuracy of 0.923 using linear discriminant analysis (LDA), logistic regression (LR), random forest (RF) and support vector machine (SVM) predictive model analyses. Our work reveals promise for using reverse phase protein arrays for biomarker discovery and validation in serum samples.

Dual-Color, Multiplex Analysis of Protein Microarrays for Precision Medicine

Generating molecular information in a clinically relevant time frame is the first hurdle to truly integrating precision medicine in health care. Reverse phase protein microarrays are being utilized in clinical trials for quantifying posttranslationally modified signal transduction proteins and cellular signaling pathways, allowing direct comparison of the activation state of proteins from multiple specimens, or individual patient specimens, within the same array. This technology provides diagnostic and therapeutic information critical to precision medicine. To enhance accessibility of this technology, two hurdles must be overcome: data normalization and data acquisition. Herein we describe an unamplified, dual-color signal detection methodology for reverse phase protein microarrays that allows multiplex, within spot data normalization, reduces data acquisition time, simplifies automated spot detection, and provides a stable signal output. This method utilizes Quantum Nanocrystal fluorophore labels (Qdot) substituted for organic fluorophores coupled with an imager (ArrayCAM) that captures images of the microarray rather than sequentially scanning the array. Streamlining and standardizing the data analysis steps with ArrayCAM high-resolution, dual mode chromogenic/fluorescent array imaging overcomes the data acquisition hurdle. The spot location and analysis algorithm provides certain parameter settings that can be tailored to the particular microarray type (fluorescent vs. colorimetric), resulting in greater than 99 % spot location sensitivity. The described method demonstrates equivalent sensitivity for a non-amplified Qdot immunoassay when using automated vs. manual immunostaining procedures.

Protein biomarkers for subtyping breast cancer and implications for future research

INTRODUCTION

Breast cancer subtypes are currently defined by a combination of morphologic, genomic, and proteomic characteristics. These subtypes provide a molecular portrait of the tumor that aids diagnosis, prognosis, and treatment escalation/de-escalation options. Gene expression signatures describing intrinsic breast cancer subtypes for predicting risk of recurrence have been rapidly adopted in the clinic. Despite the use of subtype classifications, many patients develop drug resistance, breast cancer recurrence, or therapy failure. Areas covered: This review provides a summary of immunohistochemistry, reverse phase protein array, mass spectrometry, and integrative studies that are revealing differences in biological functions within and between breast cancer subtypes. We conclude with a discussion of rigor and reproducibility for proteomic-based biomarker discovery. Expert commentary: Innovations in proteomics, including implementation of assay guidelines and standards, are facilitating refinement of breast cancer subtypes. Proteomic and phosphoproteomic information distinguish biologically functional subtypes, are predictive of recurrence, and indicate likelihood of drug resistance. Actionable, activated signal transduction pathways can now be quantified and characterized. Proteomic biomarker validation in large, well-designed studies should become a public health priority to capitalize on the wealth of information gleaned from the proteome.

Adaptation of Laser Microdissection Technique to Nanostring RNA Analysis in the Study of a Spontaneous Metastatic Mammary Carcinoma Mouse Model

The mouse model characterized by spontaneous lung metastasis from JygMC (A) cells closely resembles the human triple negative breast cancer (TNBC) subtype. The primary tumors morphologically present both epithelial and spindle-like cells, but metastases in lung parenchyma display only adenocarcinoma properties. In the study of molecular signatures, laser capture microdissection (LCM) on frozen tissue sections was used to separate the following regions of interest: the epithelial-mesenchymal transition (EMT), mesenchymal-epithelial transition (MET), carcinoma, lung metastases, normal mammary gland and normal lung parenchyma. NanoString was selected for the study of molecular signatures in LCM targets as a reliable downstream gene expression platform allowing analysis of tissue lysates without RNA extraction and amplification. This chapter provides detailed protocols for the collection of tissue, LCM sample preparation and dissection, production of lysates, extraction, and quality control of RNA for NanoString analysis, as well as the methodology of Nanostring gene expression profiling experiment.

Laser Microdissection Workflow for Isolating Nucleic Acids from Fixed and Frozen Tissue Samples

Laser Capture Microdissection has earned a permanent place among modern techniques connecting histology and molecular biology. Laser Capture Microdissection has become an invaluable tool in medical research as a means for collection of specific cell populations isolated from their environment. Such genomic sample enrichment dramatically increases the sensitivity and precision of downstream molecular assays used for biomarker discovery, monitoring disease onset and progression, and in the development of personalized medicine. The diversity of research targets (cancerous and precancerous lesions in clinical and animal research, cell pellets, rodent embryos, frozen tissues, archival repository slides, etc.) and scientific objectives present a challenge in establishing standard protocols for Laser Capture Microdissection. In the present chapter, we share our experiences in design and successful execution of numerous diverse microdissection projects, and provide considerations to be taken into account in planning a microdissection study. Our workflow and protocols are standardized for a wide range of animal and human tissues and adapted to downstream analysis platforms.

New insights into the metastatic behavior after breast cancer surgery, according to well-established clinicopathological variables and molecular subtypes

Despite advances in treatment, up to 30% of patients with early breast cancer (BC) experience distant disease relapse. However, a comprehensive understanding of tumor spread and site-specific recurrence patterns remains lacking. This retrospective case-control study included 103 consecutive patients with metastatic BC admitted to our institution (2000–2013). Cases were matched according to age, tumor biology, and clinicopathological features to 221 patients with non-metastatic BC (control group). The median follow-up period among the 324 eligible patients was 7.3 years. While relatively low values for sensitivity (71%) and specificity (56%) were found for axillary lymph node (ALN) involvement as an indicator of risk and pattern of distant relapse, nodal status remained the most powerful predictor of metastases (OR: 3.294; CL: 1.9–5.5). Rates of dissemination and metastatic efficiency differed according to molecular subtype. HER2-positive subtypes showed a stronger association with systemic spread (OR: 2.127; CL: 1.2–3.8) than other subgroups. Classification as Luminal or Non-Luminal showed an increased risk of lung and distant nodal recurrence, and a decreased risk in bone metastases in the Non-Luminal group (OR: 2.9, 3.345, and 0.2, respectively). Tumors with HER2 overexpression had a significantly high risk for distant relapse (OR: 2.127) compared with HER2-negative tumors and also showed higher central nervous system (CNS) and lung metastatic potential (OR: 5.6 and 2.65, respectively) and low risk of bone disease progression (OR: 0.294). Furthermore, we found significant associations between biological profiles and sites of recurrence. A new process of clinical/diagnostic staging, including molecular subtypes, could better predict the likelihood of distant relapses and their anatomical location. Recognition and appreciation of clinically distinct molecular subtypes may assist in evaluation of the probability of distant relapses and their sites. Our analysis provides new insights into management of metastatic disease behavior, to lead to an optimal disease-tailored approach and appropriate follow-up.

Synergy between Androgen Receptor Antagonism and Inhibition of mTOR and HER2 in Breast Cancer

The androgen receptor (AR) is widely expressed in breast cancer, and evidence suggests dependence on AR signaling for growth and survival. AR antagonists such as enzalutamide and seviteronel have shown success in preclinical models and clinical trials of prostate cancer and are currently being evaluated in breast cancer. Reciprocal regulation between AR and the HER2/PI3K/mTOR pathway may contribute to resistance to HER2- and mTOR-targeted therapies; thus, dual inhibition of these pathways may synergistically inhibit breast cancer growth. HER2+ and triple-negative breast cancer cell lines were treated with AR antagonist plus anti-HER2 mAb trastuzumab or mTOR inhibitor everolimus. Apoptosis, cell proliferation, and drug synergy were measured in vitro Pathway component genes and proteins were measured by qRT-PCR, Western blot, and reverse phase protein array. In vivo, HER2+ breast cancer xenografts were treated with enzalutamide, everolimus, trastuzumab, and combinations of these drugs. AR antagonists inhibited proliferation of both HER2+ and TNBC cell lines. Combining AR antagonist and either everolimus or trastuzumab resulted in synergistic inhibition of proliferation. Dihydrotestosterone caused increased phosphorylation of HER2 and/or HER3 that was attenuated by AR inhibition. Everolimus caused an increase in total AR, phosphorylation of HER2 and/or HER3, and these effects were abrogated by enzalutamide. Growth of trastuzumab-resistant HER2+ xenograft tumors was inhibited by enzalutamide, and combining enzalutamide with everolimus decreased tumor viability more than either single agent. AR antagonists synergize with FDA-approved breast cancer therapies such as everolimus and trastuzumab through distinct mechanisms. Treatment combinations are effective in trastuzumab-resistant HER2+ breast cancer cells in vivoMol Cancer Ther; 16(7); 1389-400. ©2017 AACR.

Protein network construction using reverse phase protein array data

In this paper, we introduce a novel computational method for constructing protein networks based on reverse phase protein array (RPPA) data to identify complex patterns in protein signaling. The method is applied to phosphoproteomic profiles of basal expression and activation/phosphorylation of 76 key signaling proteins in three breast cancer cell lines (MCF7, LCC1, and LCC9). Temporal RPPA data are acquired at 48h, 96h, and 144h after knocking down four genes in separate experiments. These genes are selected from a previous study as important determinants for breast cancer survival. Interaction networks are constructed by analyzing the expression levels of protein pairs using a multivariate analysis of variance model. A new scoring criterion is introduced to determine relevant protein pairs. Through a network topology based analysis, we search for wiring patterns to identify key proteins that are associated with significant changes in expression levels across various experimental conditions.

Signaling pathway profiling using reverse-phase protein array and its clinical applications

INTRODUCTION

Increased accessibility to next-generation sequencing within the last decade has led to a paradigm shift in cancer treatment from one-size-fits-all medicine to precision medicine providing therapeutic strategies tailored to the requirements of individual patients. However, the effect of even the most successful agent yet tested is only transient, and durable efficacy has yet to be achieved. Genome- and transcriptome-based approaches cannot fully predict the diversity of protein expression patterns or post-translational modifications that directly contribute to cancer pathogenesis and physiology. This underscores the need for concordant proteomic analysis in the next stage of precision medicine. Areas covered: This review begins with an overview of the recent advances and trends in precision medicine that currently rely on genomics, and highlights the utility of antibody-based reverse-phase protein array (RPPA) technology as a proteomic tool in this context. Expert commentary: RPPA is well suited for pharmacodynamics analysis in view of its ability to precisely map signaling status using limited amounts of clinical samples. In addition, the cost-effectiveness and rapid turn-around time of the RPPA platform offer a substantial advantage over existing molecular profiling technologies in clinical settings.

Rapamycin modulation of p70 S6 kinase signaling inhibits Rift Valley fever virus pathogenesis

Despite over 60 years of research on antiviral drugs, very few are FDA approved to treat acute viral infections. Rift Valley fever virus (RVFV), an arthropod borne virus that causes hemorrhagic fever in severe cases, currently lacks effective treatments. Existing as obligate intracellular parasites, viruses have evolved to manipulate host cell signaling pathways to meet their replication needs. Specifically, translation modulation is often necessary for viruses to establish infection in their host. Here we demonstrated phosphorylation of p70 S6 kinase, S6 ribosomal protein, and eIF4G following RVFV infection in vitro through western blot analysis and in a mouse model of infection through reverse phase protein microarrays (RPPA). Inhibition of p70 S6 kinase through rapamycin treatment reduced viral titers in vitro and increased survival and mitigated clinical disease in RVFV challenged mice. Additionally, the phosphorylation of p70 S6 kinase was decreased following rapamycin treatment in vivo. Collectively these data demonstrate modulating p70 S6 kinase can be an effective antiviral strategy.

Strategies in functional proteomics: Unveiling the pathways to precision oncology

Personalised strategies in cancer care are required to overcome the therapeutic challenges posed by variability between patients and disease subsets. To this end, enhanced precision tools must be developed to describe the molecular drivers of malignant proliferation. Such tools must also identify druggable targets and biomarkers in order to provide essential information regarding drug development and therapeutic outcome. Here we discuss how proteomics-based approaches provide a set of viable methodologies capable of delivering quantitative information throughout the main stages of personalised oncology and a ratiometric platform that delivers systems-wide methods for drug evaluation.

Constitutive expression of microRNA-150 in mammary epithelium suppresses secretory activation and impairs de novo lipogenesis

Profiling of RNA from mouse mammary epithelial cells (MECs) isolated on pregnancy day (P)14 and lactation day (L)2 revealed that the majority of differentially expressed microRNA declined precipitously between late pregnancy and lactation. The decline in miR-150, which exhibited the greatest fold-decrease, was verified quantitatively and qualitatively. To test the hypothesis that the decline in miR-150 is crucial for lactation, MEC-specific constitutive miR-150 was achieved by crossing ROSA26-lox-STOP-lox-miR-150 mice with WAP-driven Cre recombinase mice. Both biological and foster pups nursed by bitransgenic dams exhibited a dramatic decrease in survival compared with offspring nursed by littermate control dams. Protein products of predicted miR-150 targets Fasn, Olah, Acaca, and Stat5B were significantly suppressed in MECs of bitransgenic mice with constitutive miR-150 expression as compared with control mice at L2. Lipid profiling revealed a significant reduction in fatty acids synthesized by the de novo pathway in L2 MECs of bitransgenic versus control mice. Collectively, these data support the hypothesis that a synchronized decrease in miRNAs, such as miR-150, at late pregnancy serves to allow translation of targets crucial for lactation.

Adaptation of Laser Microdissection Technique for the Study of a Spontaneous Metastatic Mammary Carcinoma Mouse Model by NanoString Technologies

Laser capture microdissection (LCM) of tissue is an established tool in medical research for collection of distinguished cell populations under direct microscopic visualization for molecular analysis. LCM samples have been successfully analyzed in a number of genomic and proteomic downstream molecular applications. However, LCM sample collection and preparation procedure has to be adapted to each downstream analysis platform. In this present manuscript we describe in detail the adaptation of LCM methodology for the collection and preparation of fresh frozen samples for NanoString analysis based on a study of a model of mouse mammary gland carcinoma and its lung metastasis. Our adaptation of LCM sample preparation and workflow to the requirements of the NanoString platform allowed acquiring samples with high RNA quality. The NanoString analysis of such samples provided sensitive detection of genes of interest and their associated molecular pathways. NanoString is a reliable gene expression analysis platform that can be effectively coupled with LCM.

Clinical utility of reverse phase protein array for molecular classification of breast cancer

Reverse Phase Protein Array (RPPA) represents a sensitive and high-throughput technique allowing simultaneous quantitation of protein expression levels in biological samples. This study aimed to confirm the ability of RPPA to classify archival formalin-fixed paraffin-embedded (FFPE) breast cancer tissues into molecular classes used in the Nottingham prognostic index plus (NPI+) determined by immunohistochemistry (IHC). Proteins were extracted from FFPE breast cancer tissues using three extraction protocols: the Q-proteome FFPE Tissue Kit (Qiagen, Hilden, Germany) and two in-house methods using Laemmli buffer with either incubation for 20 min or 2 h at 105 °C. Two preparation methods, full-face sections and macrodissection, were used to assess the yield and quality of protein extracts. Ten biomarkers used for the NPI+ (ER, PgR, HER2, Cytokeratins 5/6 and 7/8, EGFR, HER3, HER4, p53 and Mucin 1) were quantified using RPPA and compared to results determined by IHC. The Q-proteome FFPE Tissue Kit produced significantly higher protein concentration and signal intensities. The intra- and inter-array reproducibility assessment indicated that RPPA using FFPE lysates was a highly reproducible and robust technique. Expression of the biomarkers individually and in combination using RPPA was highly consistent with IHC results. Macrodissection of the invasive tumour component gave more reliable results with the majority of biomarkers determined by IHC, (80 % concordance) compared with full-face sections (60 % concordance). Our results provide evidence for the technical feasibility of RPPA for high-throughput protein expression profiling of FFPE breast cancer tissues. The sensitivity of the technique is related to the quality of extracted protein and purity of tumour tissue. RPPA could provide a quantitative technique alternative to IHC for the biomarkers used in the NPI+.

HE, Lucio C, Douglas CW, Vienna L, B. SM, A. LL, F. PE, Mariaelena P. Impact of upfront cellular enrichment by laser capture microdissection on protein and phosphoprotein drug target signaling activation measurements in human lung cancer: Implications for personalized medicine

PURPOSE

The aim of this study was to evaluate whether upfront cellular enrichment via laser capture microdissection (LCM) is necessary for accurately quantifying predictive biomarkers in nonsmall cell lung cancer tumors.

EXPERIMENTAL DESIGN

Fifteen snap frozen surgical biopsies were analyzed. Whole tissue lysate and matched highly enriched tumor epithelium via LCM were obtained for each patient. The expression and activation/phosphorylation levels of 26 proteins were measured by reverse phase protein microarray. Differences in signaling architecture of dissected and undissected matched pairs were visualized using unsupervised clustering analysis, bar graphs, and scatter plots.

RESULTS

Overall patient matched LCM and undissected material displayed very distinct and differing signaling architectures with 93% of the matched pairs clustering separately. These differences were seen regardless of the amount of starting tumor epithelial content present in the specimen.

CONCLUSIONS AND CLINICAL RELEVANCE

These results indicate that LCM driven upfront cellular enrichment is necessary to accurately determine the expression/activation levels of predictive protein signaling markers although results should be evaluated in larger clinical settings. Upfront cellular enrichment of the target cell appears to be an important part of the workflow needed for the accurate quantification of predictive protein signaling biomarkers. Larger independent studies are warranted.

Functional characterization of epithelial ovarian cancer histotypes by drug target based protein signaling activation mapping: implications for personalized cancer therapy

Epithelial ovarian carcinoma (EOC) is a deadly disease, with a 5-year survival of 30%. The aim of the study was to perform broad-scale protein signaling activation mapping to evaluate if EOC can be redefined based on activated protein signaling network architecture rather than histology. Tumor cells were isolated using laser capture microdissection (LCM) from 72 EOCs. Tumors were classified as serous (n = 38), endometrioid (n = 13), mixed (n = 8), clear cell (CCC; n = 7), and others (n = 6). LCM tumor cells were lysed and subjected to reverse-phase protein microarray to measure the expression/activation level of 117 protein drug targets. Unsupervised hierarchical clustering analysis was utilized to explore the overall signaling network. ANOVA was used to detect significant differences among the groups (p < 0.05). Regardless of histology, unsupervised analysis revealed five pathway-driven clusters. When the EOC histotypes were compared by ANOVA, only CCC showed a distinct signaling network, with activation of EGFR, Syk, HER2/ErbB2, and SHP2 (p = 0.0007, p = 0.0021, p < 0.0001, and p = 0.0410, respectively). The histological classification of EOC fails to adequately describe the underpinning protein signaling network. Nevertheless, CCC presents unique signaling characteristics compared to the other histotypes. EOC may need to be characterized by functional signaling activation mapping rather than pure histology.

Discovering cancer biomarkers from clinical samples by protein microarrays

Cancer biomarkers are of potential use in early cancer diagnosis, anticancer therapy development, and monitoring the responses to treatments. Protein-based cancer biomarkers are major forms in use, as they are much easier to be monitored in body fluids or tissues. For cancer biomarker discovery, high-throughput techniques such as protein microarrays hold great promises, because they are capable of global unbiased monitoring but with a miniaturized format. In doing so, novel and cancer type specific biomarkers can be systematically discovered at an affordable cost. In this review, we give a relatively complete picture on protein microarrays applied to clinical samples for cancer biomarker discovery, and conclude this review with the future perspectives.

Subtyping of breast cancer using reverse phase protein arrays

Reverse phase protein arrays (RPPAs) present a robust and sensitive high capacity platform for targeted proteomics that relies on highly specific antibodies to obtain a quantitative readout regarding phosphorylation state and abundance of proteins of interest. This review summarizes the current state of RPPA-based proteomic profiling of breast cancer in the context of existing preanalytical strategies and sample preparation protocols. RPPA-based subtypes identified so far are compared to those obtained by other approaches such as immunohistochemistry, genomics and transcriptomics. Special attention is given to discussing the potential of RPPA for biomarker discovery and biomarker validation.

Reverse phase protein arrays: mapping the path towards personalized medicine

Reverse phase protein array (RPPA) technology evolved from the advent of miniaturized immunoassays and gene microarray technology. Reverse phase protein arrays provide either a low throughput or high throughput methodology for quantifying proteins and their post-translationally modified forms in both cellular and non-cellular samples. As the demand for patient tailored therapies increases so does the need for precise and sensitive technology to accurately profile the molecular circuitry driving an individual patient's disease. RPPAs are currently utilized in clinical trials for profiling and comparing the functional state of protein signaling pathways, either temporally within tumors, between patients, or within the same patients before/after treatment. RPPAs are generally employed for quantifying large numbers of samples on one array, under identical experimental conditions. However, the goal of personalized cancer medicine is to design therapies based on the molecular portrait of a patient's tumor, which in turn result in more efficacious treatments with less toxicity. Therefore, RPPAs are also being validated for low throughput assays of individual patient samples. This review explores RPPA technology in the cancer research field, concentrating on its role as a fundamental tool for deciphering protein signaling networks and its emerging role in personalized medicine.

Reverse phase protein arrays in signaling pathways: a data integration perspective

The reverse phase protein array (RPPA) data platform provides expression data for a prespecified set of proteins, across a set of tissue or cell line samples. Being able to measure either total proteins or posttranslationally modified proteins, even ones present at lower abundances, RPPA represents an excellent way to capture the state of key signaling transduction pathways in normal or diseased cells. RPPA data can be combined with those of other molecular profiling platforms, in order to obtain a more complete molecular picture of the cell. This review offers perspective on the use of RPPA as a component of integrative molecular analysis, using recent case examples from The Cancer Genome Altas consortium, showing how RPPA may provide additional insight into cancer besides what other data platforms may provide. There also exists a clear need for effective visualization approaches to RPPA-based proteomic results; this was highlighted by the recent challenge, put forth by the HPN-DREAM consortium, to develop visualization methods for a highly complex RPPA dataset involving many cancer cell lines, stimuli, and inhibitors applied over time course. In this review, we put forth a number of general guidelines for effective visualization of complex molecular datasets, namely, showing the data, ordering data elements deliberately, enabling generalization, focusing on relevant specifics, and putting things into context. We give examples of how these principles can be utilized in visualizing the intrinsic subtypes of breast cancer and in meaningfully displaying the entire HPN-DREAM RPPA dataset within a single page.

Mechanisms involved in breast cancer liver metastasis

Liver metastasis is a frequent occurrence in patients with breast cancer; however, the available treatments are limited and ineffective. While liver-specific homing of breast cancer cells is an important feature of metastasis, the formation of liver metastases is not random. Indeed, breast cancer cell factors contribute to the liver microenvironment. Major breakthroughs have been achieved recently in understanding breast cancer liver metastasis (BCLM). The process of liver metastasis consists of multiple steps and involves various factors from breast cancer cells and the liver microenvironment. A further understanding of the roles of breast cancer cells and the liver microenvironment is crucial to guide future work in clinical treatments. In this review we discuss the contribution of breast cancer cells and the liver microenvironment to liver metastasis, with the aim to improve therapeutic efficacy for patients with BCLM.

Kinome profiling reveals breast cancer heterogeneity and identifies targeted therapeutic opportunities for triple negative breast cancer

Our understanding of breast cancer heterogeneity at the protein level is limited despite proteins being the ultimate effectors of cellular functions. We investigated the heterogeneity of breast cancer (41 primary tumors and 15 breast cancer cell lines) at the protein and phosphoprotein levels to identify activated oncogenic pathways and developing targeted therapeutic strategies. Heterogeneity was observed not only across histological subtypes, but also within subtypes. Tumors of the Triple negative breast cancer (TNBC) subtype distributed across four different clusters where one cluster (cluster ii) showed high deregulation of many proteins and phosphoproteins. The majority of TNBC cell lines, particularly mesenchymal lines, resembled the cluster ii TNBC tumors. Indeed, TNBC cell lines were more sensitive than non-TNBC cell lines when treated with targeted inhibitors selected based on upregulated pathways in cluster ii. In line with the enrichment of the upregulated pathways with onco-clients of Hsp90, we found synergy in combining Hsp90 inhibitors with several kinase inhibitors, particularly Erk5 inhibitors. The combination of Erk5 and Hsp90 inhibitors was effective in vitro and in vivo against TNBC leading to upregulation of pro-apoptotic effectors. Our studies contribute to proteomic profiling and improve our understanding of TNBC heterogeneity to provide therapeutic opportunities for this disease.

Kinomic profiling of electromagnetic navigational bronchoscopy specimens: a new approach for personalized medicine

Purpose

Researchers are currently seeking relevant lung cancer biomarkers in order to make informed decisions regarding therapeutic selection for patients in so-called “precision medicine.” However, there are challenges to obtaining adequate lung cancer tissue for molecular analyses. Furthermore, current molecular testing of tumors at the genomic or transcriptomic level are very indirect measures of biological response to a drug, particularly for small molecule inhibitors that target kinases. Kinase activity profiling is therefore theorized to be more reflective of invivo biology than many current molecular analysis techniques. As a result, this study seeks to prove the feasibility of combining a novel minimally invasive biopsy technique that expands the number of lesions amenable for biopsy with subsequent exvivo kinase activity analysis.

Methods

Eight patients with lung lesions of varying location and size were biopsied using the novel electromagnetic navigational bronchoscopy (ENB) technique. Basal kinase activity (kinomic) profiles and exvivo interrogation of samples in combination with tyrosine kinase inhibitors erlotinib, crizotinib, and lapatinib were performed by PamStation 12 microarray analysis.

Results

Kinomic profiling qualitatively identified patient specific kinase activity profiles as well as patient and drug specific changes in kinase activity profiles following exposure to inhibitor. Thus, the study has verified the feasibility of ENB as a method for obtaining tissue in adequate quantities for kinomic analysis and has demonstrated the possible use of this tissue acquisition and analysis technique as a method for future study of lung cancer biomarkers.

Conclusions

We demonstrate the feasibility of using ENB-derived biopsies to perform kinase activity assessment in lung cancer patients.

Analytical challenges translating mass spectrometry-based phosphoproteomics from discovery to clinical applications

Phosphoproteomics is the systematic study of one of the most common protein modifications in high throughput with the aim of providing detailed information of the control, response, and communication of biological systems in health and disease. Advances in analytical technologies and strategies, in particular the contributions of high-resolution mass spectrometers, efficient enrichments of phosphopeptides, and fast data acquisition and annotation, have catalyzed dramatic expansion of signaling landscapes in multiple systems during the past decade. While phosphoproteomics is an essential inquiry to map high-resolution signaling networks and to find relevant events among the apparently ubiquitous and widespread modifications of proteome, it presents tremendous challenges in separation sciences to translate it from discovery to clinical practice. In this mini-review, we summarize the analytical tools currently utilized for phosphoproteomic analysis (with focus on MS), progresses made on deciphering clinically relevant kinase-substrate networks, MS uses for biomarker discovery and validation, and the potential of phosphoproteomics for disease diagnostics and personalized medicine.

Prediction of individual response to anticancer therapy: historical and future perspectives

Since the introduction of chemotherapy for cancer treatment in the early 20th century considerable efforts have been made to maximize drug efficiency and at the same time minimize side effects. As there is a great interpatient variability in response to chemotherapy, the development of predictive biomarkers is an ambitious aim for the rapidly growing research area of personalized molecular medicine. The individual prediction of response will improve treatment and thus increase survival and life quality of patients. In the past, cell cultures were used as in vitro models to predict in vivo response to chemotherapy. Several in vitro chemosensitivity assays served as tools to measure miscellaneous endpoints such as DNA damage, apoptosis and cytotoxicity or growth inhibition. Twenty years ago, the development of high-throughput technologies, e.g. cDNA microarrays enabled a more detailed analysis of drug responses. Thousands of genes were screened and expression levels were correlated to drug responses. In addition, mutation analysis became more and more important for the prediction of therapeutic success. Today, as research enters the area of -omics technologies, identification of signaling pathways is a tool to understand molecular mechanism underlying drug resistance. Combining new tissue models, e.g. 3D organoid cultures with modern technologies for biomarker discovery will offer new opportunities to identify new drug targets and in parallel predict individual responses to anticancer therapy. In this review, we present different currently used chemosensitivity assays including 2D and 3D cell culture models and several -omics approaches for the discovery of predictive biomarkers. Furthermore, we discuss the potential of these assays and biomarkers to predict the clinical outcome of individual patients and future perspectives.

Array-based proteomic approaches to study signal transduction pathways: prospects, merits and challenges

Very often dysfunctional aspects of various signalling networks are found to be associated with human diseases and disorders. The major characteristics of signal transduction pathways are specificity, amplification of the signal, desensitisation and integration, which is accomplished not solely, but majorly by proteins. Array-based profiling of protein-protein and other biomolecular interactions is a versatile approach, which holds immense potential for multiplex interactome mapping and provides an inclusive representation of the signal transduction pathways and networks. Protein microarrays such as analytical protein microarrays (antigen-antibody interactions, autoantibody screening), RP microarrays (interaction of a particular ligand with all the possible targets in cell), functional protein microarrays (protein-protein or protein-ligand interactions) are implemented for various applications, including analysis of protein interactions and their significance in signalling cascades. Additionally, successful amalgamation of the array-based approaches with different label-free detection techniques allows real-time analysis of interaction kinetics of multiple interaction events simultaneously. This review discusses the prospects, merits and limitations of different variants of array-based techniques and their promising applications for studying the modifications and interactions of biomolecules, and highlights the studies associated with signal transduction pathways and their impact on disease pathobiology.

Novel neoadjuvant therapy paradigms for bladder cancer: results from the National Cancer Center Institute Forum

OBJECTIVE

To bridge gaps in translational science and develop the concepts for 2 novel biomarker-driven clinical trials: one in the presurgical setting and the other in the setting of bladder preservation with chemoradiation.

METHODS AND MATERIALS

The National Cancer Institute sponsored a forum, "Novel Neoadjuvant Therapy for Bladder Cancer," which brought leading clinical and laboratory-based scientists together with the advocacy community.

RESULTS

The group designed a neoadjuvant clinical trial to compare the clinical efficacy of the two frontline chemotherapy regimens (gemcitabine plus cisplatin versus MVAC) and the ability of a gene expression profiling-based algorithm (CoXEN) to predict complete pathological response. The trial was recently opened under the leadership of the Southwest Oncology Group (SWOG, S1314), receiving support for the biomarker studies from the NCI's BISQFP resource. A second clinical trial was planned that will examine the relationship between expression of the DNA repair protein MRE11 and complete response in patients treated with concurrent 5-fluorouracil/mitomycin C plus radiation.

CONCLUSION

The meeting provided a unique opportunity to launch a collective effort to establish molecular-based therapies for muscle-invasive urothelial cancer. The goal is to use this framework to develop comparable trials with immunotherapy in non-muscle invasive cancers and to exploit the neoadjuvant platform to develop targeted therapy in muscle-invasive disease.

Signaling pathway profiling by reverse-phase protein array for personalized cancer medicine

Deregulation of intracellular signaling through accumulation of genetic alterations is a hallmark of cancer. In the past few decades, concerted and systematic efforts have been made to identify key genetic alterations and to develop therapeutic agents targeting active signaling molecules. However, the efficacy of molecular therapeutics often varies among individuals, and precise mapping of active molecules in individual patients is now considered an essential for therapy optimization. Reverse-phase protein array or microarray (RPPA or RPPM) is an emerging antibody-based highly quantitative proteomic technology, especially suitable for profiling of expression and modification of signaling proteins in low abundance. Because the supply of clinical materials is often limited, RPPA technology is highly advantageous for clinical proteomics in view of its high sensitivity as well as accurate quantification. RPPA has now begun to be incorporated into various clinical trials employing molecular-targeted therapeutics. In this article we review and discuss the application of RPPA technology in the fields of basic, preclinical, and clinical research. The RPPA Global Workshop was recently launched to accelerate the exchange of rapidly expanding knowledge of this fascinating technology among academic laboratories and industries worldwide. This article is part of a Special Issue entitled: Medical Proteomics.

A pilot study utilizing multi-omic molecular profiling to find potential targets and select individualized treatments for patients with previously treated metastatic breast cancer

The primary objective was to determine if multi-omic molecular profiling (MMP) informed selection of approved cancer treatments could change the clinical course of disease for patients with previously treated metastatic breast cancer (MBC) (i.e., produce a growth modulation index (GMI) ≥1.3). GMI was calculated as the ratio of progression free survival on MMP-selected therapy/time to progression on last prior treatment. To meet the primary objective at least 35 % of the subjects should demonstrate a GMI ≥1.3. Secondary endpoints included determining the response rate (according to RECIST 1.1), the percent of patients with non-progression at 4 months, and overall survival in patients whose therapy is selected by molecular profiling and proteomic analysis. Eligible patients had MBC, with ≥3 prior lines of therapy. A multi-omic based approach was performed incorporating multiplexed immunohistochemistry, c-DNA microarray, and phosphoprotein pathway activation mapping by reverse phase protein array. MMP was performed on fresh core biopsies; results were generated and sent to a Treatment Selection Committee (TSC) for review and treatment selection. Three sites enrolled 28 patients, of which 25 were evaluable. The median range of prior treatment was 7 (range 3-12). The MMP analysis and treatment recommendation were delivered within a median of 15.5 days from biopsy (range 12-23). The TSC selected MMP-rationalized treatment in 100 % (25/25) of cases. None of the MMP-based therapies were the same as what the clinician would have selected if the MMP had not been performed. GMI ≥1.3 was reported in 11/25 (44 %) patients. Partial responses were noted in 5/25 (20 %), stable disease in 8/25 (32 %) and 9/25 (36 %) had no progression at 4 months. This pilot study demonstrates the feasibility of finding possible treatments for patients with previously treated MBC using a multiplexed MMP-rationalized treatment recommendation. This MMP approach merits further investigation.

Realizing the promise of reverse phase protein arrays for clinical, translational, and basic research: a workshop report: the RPPA (Reverse Phase Protein Array) society

Reverse phase protein array (RPPA) technology introduced a miniaturized "antigen-down" or "dot-blot" immunoassay suitable for quantifying the relative, semi-quantitative or quantitative (if a well-accepted reference standard exists) abundance of total protein levels and post-translational modifications across a variety of biological samples including cultured cells, tissues, and body fluids. The recent evolution of RPPA combined with more sophisticated sample handling, optical detection, quality control, and better quality affinity reagents provides exquisite sensitivity and high sample throughput at a reasonable cost per sample. This facilitates large-scale multiplex analysis of multiple post-translational markers across samples from in vitro, preclinical, or clinical samples. The technical power of RPPA is stimulating the application and widespread adoption of RPPA methods within academic, clinical, and industrial research laboratories. Advances in RPPA technology now offer scientists the opportunity to quantify protein analytes with high precision, sensitivity, throughput, and robustness. As a result, adopters of RPPA technology have recognized critical success factors for useful and maximum exploitation of RPPA technologies, including the following: preservation and optimization of pre-analytical sample quality, application of validated high-affinity and specific antibody (or other protein affinity) detection reagents, dedicated informatics solutions to ensure accurate and robust quantification of protein analytes, and quality-assured procedures and data analysis workflows compatible with application within regulated clinical environments. In 2011, 2012, and 2013, the first three Global RPPA workshops were held in the United States, Europe, and Japan, respectively. These workshops provided an opportunity for RPPA laboratories, vendors, and users to share and discuss results, the latest technology platforms, best practices, and future challenges and opportunities. The outcomes of the workshops included a number of key opportunities to advance the RPPA field and provide added benefit to existing and future participants in the RPPA research community. The purpose of this report is to share and disseminate, as a community, current knowledge and future directions of the RPPA technology.

Implications of functional proteomics in breast cancer

Breast cancer is one of the major public health problems of the Western world. Recent advances in genomics and gene expression-profiling approaches have enriched our understanding of this heterogeneous disease. However, progress in functional proteomics in breast cancer research has been relatively slow. Allied with genomics, the functional proteomics approach will be important in improving diagnosis through better classification of breast cancer and in predicting prognosis and response to different therapies, including chemotherapy, hormonal therapy, and targeted therapy. In this review, we will present functional proteomic approaches with a focus on the recent clinical implications of utilizing the reverse-phase protein array platform in breast cancer research.

Application of molecular technologies for phosphoproteomic analysis of clinical samples

The integration of small kinase inhibitors and monoclonal antibodies into oncological practice has opened a new paradigm for treating cancer patients. As proteins are the direct targets of the new generations of targeted therapeutics, many of which are kinase/enzymatic inhibitors, there is an increasing interest in developing technologies capable of monitoring post-translational changes of the human proteome for the identification of new predictive, prognostic and therapeutic biomarkers. It is well known that the vast majority of the activation/deactivation of these drug targets is driven by phosphorylation. This review provides a description of the main proteomic platforms (planar and bead array, reverse phase protein microarray, phosphoflow, AQUA and mass spectrometry) that have successfully been used for measuring changes in phosphorylation level of drug targets and downstream substrates using clinical specimens. Major emphasis was given to the strengths and weaknesses of the different platforms and to the major barriers that are associated with the analysis of the phosphoproteome. Finally, a number of examples of application of the above-mentioned technologies in the clinical setting are reported.

Glioblastoma cell enrichment is critical for analysis of phosphorylated drug targets and proteomic-genomic correlations

The quality of cancer genomic and proteomic data relies upon the quality of the clinical specimens examined. Here, we show that data derived from non-microdissected glioblastoma multiforme tumor tissue is either masked or not accurate, producing correlations between genomic and proteomic data that lead to false classifications for therapeutic stratification. We analyzed the level of 133 key signaling proteins and phosphoproteins in laser capture microdissected (LCM) primary tumors from a study set of tissues used for the Cancer Genome Atlas (TCGA) profiling efforts, comparing the results to tissue-matched, nontumor cell-enriched lysates from adjacent sections. Among the analytes, 44%, including targets for clinically important inhibitors, such as phosphorylated mTOR, AKT, STAT1, VEGFR2, or BCL2, differed between matched tumor cell-enriched and nonenriched specimens (even in tumor sections with 90% tumor cell content). While total EGFR protein levels were higher in tumors with EGFR mutations, regardless of tumor cell enrichment, EGFR phosphorylation was increased only in LCM-enriched tumor specimens carrying EGFR mutations. Phosphorylated and total PTEN, which is highly expressed in normal brain, was reduced only in LCM-enriched tumor specimens with either PTEN mutation or loss in PTEN copy number, with no differences observed in non-microdissected samples. These results were confirmed in an independent, non-microdissected, publicly available protein data set from the TCGA database. Our findings highlight the necessity for careful upfront cellular enrichment in biospecimens that form the basis for targeted therapy selection and for molecular characterization efforts such as TCGA.

Advances towards the design and development of personalized non-small-cell lung cancer drug therapy

INTRODUCTION

Non-small-cell lung cancer (NSCLC) subtypes are driven by specific genetic aberrations. For reasons such as this, there is a call for treatment personalization. The ability to instigate NSCLC fragmentation poses new methodological problems, and new 'driver' molecular aberrations are being discovered at an unprecedented pace.

AREAS COVERED

This article describes the clinical development of epidermal growth factor-tyrosine kinase inhibitors (EGFR-TKIs) and crizotinib for EGFR-mutant and anaplastic lymphoma kinase (ALK)-rearranged NSCLC. Further, the authors briefly describe the emerging molecular targets in NSCLC, in terms of both rationale for therapeutic targeting and strategies, for clinical development.

EXPERT OPINION

Target identification and validation in NSCLC still requires considerable effort, as not all of the molecular alterations are clear 'drivers' nor can they be efficiently targeted with available drugs. However, 50% of the NSCLC cases are without clear-defined molecular aberrations. Clinical trial methodology will need to develop novel paradigms for targeted drug development, aiming at the validation of an ideal 'biology-to-trial' approach. Despite significant challenges, a truly 'personalized' approach to NSCLC therapy appears to be within our reach.

Presence of anaplastic lymphoma kinase in inflammatory breast cancer

Although Inflammatory Breast Cancer (IBC) is recognized as the most metastatic variant of locally advanced breast cancer, the molecular basis for the distinct clinical presentation and accelerated program of metastasis of IBC is unknown. Reverse phase protein arrays revealed activation of the receptor tyrosine kinase, anaplastic lymphoma kinase (ALK) and biochemically-linked downstream signaling molecules including JAK1/STAT3, AKT, mTor, PDK1, and AMPKβ in pre-clinical models of IBC. To evaluate the clinical relevance of ALK in IBC, analysis of 25 IBC patient tumors using the FDA approved diagnostic test for ALK genetic abnormalities was performed. These studies revealed that 20/25 (80%) had either increased ALK copy number, low level ALK gene amplification, or ALK gene expression, with a prevalence of ALK alterations in basal-like IBC. One of 25 patients was identified as having an EML4-ALK translocation. The generality of gains in ALK copy number in basal-like breast tumors with IBC characteristics was demonstrated by analysis of 479 breast tumors using the TGCA data-base and our newly developed 79 IBC-like gene signature. The small molecule dual tyrosine kinase cMET/ALK inhibitor, Crizotinib (PF-02341066/Xalkori®, Pfizer Inc), induced both cytotoxicity (IC₅₀ = 0.89 μM) and apoptosis, with abrogation of pALK signaling in IBC tumor cells and in FC-IBC01 tumor xenograft model, a new IBC model derived from pleural effusion cells isolated from an ALK⁺ IBC patient. Based on these studies, IBC patients are currently being evaluated for the presence of ALK genetic abnormalities and when eligible, are being enrolled into clinical trials evaluating ALK targeted therapeutics.

Innovations in studying in vivo cell behavior and pharmacology in complex tissues--microvascular endothelial cells in the spotlight

Many studies on the molecular control underlying normal cell behavior and cellular responses to disease stimuli and pharmacological intervention are conducted in single-cell culture systems, while the read-out of cellular engagement in disease and responsiveness to drugs in vivo is often based on overall tissue responses. As the majority of drugs under development aim to specifically interact with molecular targets in subsets of cells in complex tissues, this approach poses a major experimental discrepancy that prevents successful development of new therapeutics. In this review, we address the shortcomings of the use of artificial (single) cell systems and of whole tissue analyses in creating a better understanding of cell engagement in disease and of the true effects of drugs. We focus on microvascular endothelial cells that actively engage in a wide range of physiological and pathological processes. We propose a new strategy in which in vivo molecular control of cells is studied directly in the diseased endothelium instead of at a (far) distance from the site where drugs have to act, thereby accounting for tissue-controlled cell responses. The strategy uses laser microdissection-based enrichment of microvascular endothelium which, when combined with transcriptome and (phospho)proteome analyses, provides a factual view on their status in their complex microenvironment. Combining this with miniaturized sample handling using microfluidic devices enables handling the minute sample input that results from this strategy. The multidisciplinary approach proposed will enable compartmentalized analysis of cell behavior and drug effects in complex tissue to become widely implemented in daily biomedical research and drug development practice.

Individualized therapy for metastatic colorectal cancer

Systemic therapeutic efficacy is central to determining the outcome of patients with metastatic colorectal cancer (CRC). In these patients, there is a critical need for predictive biomarkers to optimize efficacy whilst minimizing toxicity. The integration of a new generation of molecularly targeted drugs into the treatment of CRC, coupled with the development of sophisticated technologies for individual tumours as well as patient molecular profiling, underlines the potential for personalized medicine. In this review, we focus on the latest progress made within the genomic and proteomic fields, concerning predictive biomarkers for individualized therapy in metastatic CRC.

A pilot characterization of human lung NSCLC by protein pathway activation mapping

BACKGROUND

An understanding of the activated protein signaling architecture in non-small-cell lung cancer (NSCLC) is of critical importance to the development of new therapeutic approaches and identification of predictive and prognostic biomarkers for patient stratification.

METHODS

We used reverse-phase protein microarrays to map the activated protein signaling networks of 47 NSCLC tumors, 28 of which were node negative, which were subjected to tumor cellular enrichment using laser capture microdissection. The phosphorylation/cleavage levels of 111 key signaling proteins and total levels of 17 proteins were measured for broadscale signaling analysis.

RESULTS

Pathway activation mapping of NSCLC revealed distinct subgroups composed of epidermal growth factor receptor (ERBB1), v-erb-b2 erythroblastic leukemia viral oncogene homolog 2 (ERBB2), v-erb-b2 erythroblastic leukemia viral oncogene homolog 3 (ERBB3), v-erb-a erythroblastic leukemia viral oncogene homolog 4 (ERBB4), v-akt murine thymoma viral oncogene homolog 1- mammalian target of rapamycin (AKT-mTOR), protein kinase, AMP-activated, alpha 2 catalytic subunit (AMPK), and autophagy-related signaling, along with transforming growth factor-beta-signaling protein 1 (SMAD), insulin-line growth factor receptor (IGFR), rearranged during transfection proto-oncogene (RET), and activated CDC42-associated kinase (ACK) activation. Investigation of epidermal growth factor receptor (EGFR)-driven signaling identified a unique cohort of tumors with low EGFR protein expression yet high relative levels of phosphorylated EGFR and high EGFR total protein with low relative levels of phosphorylation. Last, mapping analysis of patients with NSCLC with N0 disease revealed a pilot pathway activation signature composed of linked epidermal growth factor receptor family (HER)-AMPK-AKT-mTOR signaling network along with focal adhesion kinase- LIM domain kinase-1 (FAK-LIMK) and janus kinase (JAK)-signal transducers and activators of transcription (STAT) pathways that correlated with short-term survival and aggressive disease.

CONCLUSIONS

Functional protein pathway activation mapping of NSCLC reveals distinct activation subgroups that are underpinned by important therapeutic targets and that patients with early-stage node negative disease and poor prognosis may be identified by activation of defined, biochemically linked protein signaling events. Such findings, if confirmed in larger study sets, could help select and stratify patients for personalized targeted therapies.

Laser capture microdissection for protein and NanoString RNA analysis

Laser capture microdissection (LCM) allows the precise procurement of enriched cell populations from a heterogeneous tissue, or live cell culture, under direct microscopic visualization. Histologically enriched cell populations can be procured by harvesting cells of interest directly or isolating specific cells by ablating unwanted cells. The basic components of laser microdissection technology are (a) visualization of cells via light microscopy, (b) transfer of laser energy to a thermolabile polymer with either the formation of a polymer-cell composite (capture method) or transfer of laser energy via an ultraviolet laser to photovolatize a region of tissue (cutting method), and (c) removal of cells of interest from the heterogeneous tissue section. The capture and cutting methods (instruments) for laser microdissection differ in the manner by which cells of interest are removed from the heterogeneous sample. Laser energy in the capture method is infrared (810 nm), while in the cutting mode the laser is ultraviolet (355 nm). Infrared lasers melt a thermolabile polymer that adheres to the cells of interest, whereas ultraviolet lasers ablate cells for either removal of unwanted cells or excision of a defined area of cells. LCM technology is applicable to an array of applications including mass spectrometry, DNA genotyping and loss-of-heterozygosity analysis, RNA transcript profiling, cDNA library generation, proteomics discovery, and signal kinase pathway profiling. This chapter describes LCM using an Arcturus(XT) instrument for downstream protein sample analysis and using an mmi CellCut Plus® instrument for RNA analysis via NanoString technology.