Molecular analysis of HER2 signaling in human breast cancer by functional protein pathway activation mapping

Harnessing the potential of reverse-phase protein array technology: Advancing precision oncology strategies

The last few decades have seen remarkable strides in the field of cancer therapy. Precision oncology coupled with comprehensive genomic profiling has become routine clinical practice for solid tumors, the advent of immune checkpoint inhibitors has transformed the landscape of oncology treatment, and the number of cancer drug approvals has continued to increase. Nevertheless, the application of genomics-driven precision oncology has thus far benefited only 10%-20% of cancer patients, leaving the majority without matched treatment options. This limitation underscores the need to explore alternative avenues with regard to selecting patients for targeted therapies. In contrast with genomics-based approaches, proteomics-based strategies offer a more precise understanding of the intricate biological processes driving cancer pathogenesis. This perspective underscores the importance of integrating complementary proteomic analyses into the next phase of precision oncology to establish robust biomarker-drug associations and surmount challenges related to drug resistance. One promising technology in this regard is the reverse-phase protein array (RPPA), which excels in quantitatively detecting protein modifications, even with limited amounts of sample. Its cost-effectiveness and rapid turnaround time further bolster its appeal for application in clinical settings. Here, we review the current status of genomics-driven precision oncology, as well as its limitations, with an emphasis on drug resistance. Subsequently, we explore the application of RPPA technology as a catalyst for advancing precision oncology. Through illustrative examples drawn from clinical trials, we demonstrate its utility for unraveling the molecular mechanisms underlying drug responses and resistance.

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.

Protein signaling and drug target activation signatures to guide therapy prioritization: Therapeutic resistance and sensitivity in the I-SPY 2 Trial

Molecular subtyping of breast cancer is based mostly on HR/HER2 and gene expression-based immune, DNA repair deficiency, and luminal signatures. We extend this description via functional protein pathway activation mapping using pre-treatment, quantitative expression data from 139 proteins/phosphoproteins from 736 patients across 8 treatment arms of the I-SPY 2 Trial (ClinicalTrials.gov: NCT01042379). We identify predictive fit-for-purpose, mechanism-of-action-based signatures and individual predictive protein biomarker candidates by evaluating associations with pathologic complete response. Elevated levels of cyclin D1, estrogen receptor alpha, and androgen receptor S650 associate with non-response and are biomarkers for global resistance. We uncover protein/phosphoprotein-based signatures that can be utilized both for molecularly rationalized therapeutic selection and for response prediction. We introduce a dichotomous HER2 activation response predictive signature for stratifying triple-negative breast cancer patients to either HER2 or immune checkpoint therapy response as a model for how protein activation signatures provide a different lens to view the molecular landscape of breast cancer and synergize with transcriptomic-defined signatures.

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.

Mass spectrometry-based phosphoproteomics in clinical applications

Protein phosphorylation is an essential post-translational modification that regulates many aspects of cellular physiology, and dysregulation of pivotal phosphorylation events is often responsible for disease onset and progression. Clinical analysis on disease-relevant phosphoproteins, while quite challenging, provides unique information for precision medicine and targeted therapy. Among various approaches, mass spectrometry (MS)-centered characterization features discovery-driven, high-throughput and in-depth identification of phosphorylation events. This review highlights advances in sample preparation and instrument in MS-based phosphoproteomics and recent clinical applications. We emphasize the preeminent data-independent acquisition method in MS as one of the most promising future directions and biofluid-derived extracellular vesicles as an intriguing source of the phosphoproteome for liquid biopsy.

Quantitative proteomics and phosphoproteomics of urinary extracellular vesicles define putative diagnostic biosignatures for Parkinson's disease

BACKGROUND

Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene have been recognized as genetic risk factors for Parkinson's disease (PD). However, compared to cancer, fewer genetic mutations contribute to the cause of PD, propelling the search for protein biomarkers for early detection of the disease.

METHODS

Utilizing 138 urine samples from four groups, healthy individuals (control), healthy individuals with G2019S mutation in the LRRK2 gene (non-manifesting carrier/NMC), PD individuals without G2019S mutation (idiopathic PD/iPD), and PD individuals with G2019S mutation (LRRK2 PD), we applied a proteomics strategy to determine potential diagnostic biomarkers for PD from urinary extracellular vesicles (EVs).

RESULTS

After efficient isolation of urinary EVs through chemical affinity followed by mass spectrometric analyses of EV peptides and enriched phosphopeptides, we identify and quantify 4476 unique proteins and 2680 unique phosphoproteins. We detect multiple proteins and phosphoproteins elevated in PD EVs that are known to be involved in important PD pathways, in particular the autophagy pathway, as well as neuronal cell death, neuroinflammation, and formation of amyloid fibrils. We establish a panel of proteins and phosphoproteins as novel candidates for disease biomarkers and substantiate the biomarkers using machine learning, ROC, clinical correlation, and in-depth network analysis. Several putative disease biomarkers are further partially validated in patients with PD using parallel reaction monitoring (PRM) and immunoassay for targeted quantitation.

CONCLUSIONS

These findings demonstrate a general strategy of utilizing biofluid EV proteome/phosphoproteome as an outstanding and non-invasive source for a wide range of disease exploration.

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.

A reverse phase protein array based phospho-antibody characterization approach and its applicability for clinical derived tissue specimens

Systematic quantification of phosphoprotein within cell signaling networks in solid tissues remains challenging and precise quantification in large scale samples has great potential for biomarker identification and validation. We developed a reverse phase protein array (RPPA) based phosphor-antibody characterization approach by taking advantage of the lysis buffer compatible with alkaline phosphatase (AP) treatment that differs from the conventional RPPA antibody validation procedure and applied it onto fresh frozen (FF) and formalin-fixed and paraffin-embedded tissue (FFPE) to test its applicability. By screening 106 phospho-antibodies using RPPA, we demonstrated that AP treatment could serve as an independent factor to be adopted for rapid phospho-antibody selection. We also showed desirable reproducibility and specificity in clincical specimens indicating its potential for tissue-based phospho-protein profiling. Of further clinical significance, using the same approach, based on melanoma and lung cancer FFPE samples, we showed great interexperimental reproducibility and significant correlation with pathological markers in both tissues generating meaningful data that match clinical features. Our findings set a benchmark of an efficient workflow for phospho-antibody characterization that is compatible with high-plex clinical proteomics in precison oncology.

Characterization of anticancer drug resistance by reverse-phase protein array: new targets and strategies

INTRODUCTION

Drug resistance is the main barrier to achieving cancer cures with medical therapy. Cancer drug resistance occurs, in part, due to adaptation of the tumor and microenvironment to therapeutic stress at a proteomic level. Reverse-phase protein arrays (RPPA) are well suited to proteomic analysis of drug resistance due to high sample throughput, sensitive detection of phosphoproteins, and validation for a large number of critical cellular pathways.

AREAS COVERED

This review summarizes contributions of RPPA to understanding and combating drug resistance. In particular, contributions of RPPA to understanding resistance to PARP inhibitors, BRAF inhibitors, immune checkpoint inhibitors, and breast cancer investigational therapies are discussed. Articles reviewed were identified by MEDLINE, Scopus, and Cochrane search for keywords 'proteomics,' 'reverse-phase protein array,' 'drug resistance,' 'PARP inhibitor,' 'BRAF inhibitor,' 'immune checkpoint inhibitor,' and 'I-SPY' spanning October 1, 1960 - October 1, 2021.

EXPERT OPINION

Precision oncology has thus far failed to convert the armament of targeted therapies into durable responses for most patients, highlighting that genetic sequencing alone is insufficient to guide therapy selection and overcome drug resistance. Combined genomic and proteomic analyses paired with creative drug combinations and dosing strategies hold promise for maturing precision oncology into an era of improved patient outcomes.

A radiologist’s guide to novel anticancer therapies in the era of precision medicine

Novel anticancer agents have replaced conventional chemotherapy as first line agents for many cancers, with continued new and expanding indications. Small molecule inhibitors act on cell surface or intracellular targets and prevent the downstream signaling that would otherwise permit tumor growth and spread. Anticancer antibodies can be directed against growth factors or may be immunotherapeutic agents. The latter act by inhibiting mechanisms that cancer cells use to evade the immune system. Hormonal agents act by decreasing levels of hormones that are necessary for the growth of certain cancer cells. Cancer therapy protocols often include novel anticancer agents and conventional chemotherapy used successively or in combination, in order to maximize survival and minimize morbidity. A working knowledge of anti-cancer drug classification will aid the radiologist in assessing response on imaging.

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Novel anticancer agents include small molecule inhibitors, antibodies and hormones.

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These agents are predominantly cytostatic and inhibit factors that provide a survival advantage to tumor cells.

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Modern cancer therapy employs a combination of novel anticancer agents and conventional chemotherapy.

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It is essential for radiologists to have a broad understanding of these agents and their mechanisms of action.

Purification and Phosphoproteomic Analysis of Plasma-Derived Extracellular Vesicles

A successful phosphoproteomics analysis of extracellular vesicles (EVs) requires a unique approach, fine-tuned to address the challenges that have plagued plasma-based biomarker discovery. Here, I detail a procedure, which combines EVtrap-based high-recovery EV isolation, phase-transfer surfactant method for protein extraction, and PolyMAC-based enrichment of phosphopeptides. The combination of these methods provides a highly effective strategy for EV-based phosphoproteome analysis and leads to the discovery of novel phospho-markers previously undetectable.

Can Systems Biology Advance Clinical Precision Oncology?

Precision oncology is perceived as a way forward to treat individual cancer patients. However, knowing particular cancer mutations is not enough for optimal therapeutic treatment, because cancer genotype-phenotype relationships are nonlinear and dynamic. Systems biology studies the biological processes at the systems' level, using an array of techniques, ranging from statistical methods to network reconstruction and analysis, to mathematical modeling. Its goal is to reconstruct the complex and often counterintuitive dynamic behavior of biological systems and quantitatively predict their responses to environmental perturbations. In this paper, we review the impact of systems biology on precision oncology. We show examples of how the analysis of signal transduction networks allows to dissect resistance to targeted therapies and inform the choice of combinations of targeted drugs based on tumor molecular alterations. Patient-specific biomarkers based on dynamical models of signaling networks can have a greater prognostic value than conventional biomarkers. These examples support systems biology models as valuable tools to advance clinical and translational oncological research.

PD-L1 quantification across tumor types using the reverse phase protein microarray: implications for precision medicine

BACKGROUND

Anti-programmed cell death protein 1 and programmed cell death ligand 1 (PD-L1) agents are broadly used in first-line and second-line treatment across different tumor types. While immunohistochemistry-based assays are routinely used to assess PD-L1 expression, their clinical utility remains controversial due to the partial predictive value and lack of standardized cut-offs across antibody clones. Using a high throughput immunoassay, the reverse phase protein microarray (RPPA), coupled with a fluorescence-based detection system, this study compared the performance of six anti-PD-L1 antibody clones on 666 tumor samples.

METHODS

PD-L1 expression was measured using five antibody clones (22C3, 28-8, CAL10, E1L3N and SP142) and the therapeutic antibody atezolizumab on 222 lung, 71 ovarian, 52 prostate and 267 breast cancers, and 54 metastatic lesions. To capture clinically relevant variables, our cohort included frozen and formalin-fixed paraffin-embedded samples, surgical specimens and core needle biopsies. Pure tumor epithelia were isolated using laser capture microdissection from 602 samples. Correlation coefficients were calculated to assess concordance between antibody clones. For two independent cohorts of patients with lung cancer treated with nivolumab, RPPA-based PD-L1 measurements were examined along with response to treatment.

RESULTS

Median-center PD-L1 dynamic ranged from 0.01 to 39.37 across antibody clones. Correlation coefficients between the six antibody clones were heterogeneous (range: -0.48 to 0.95) and below 0.50 in 61% of the comparisons. In nivolumab-treated patients, RPPA-based measurement identified a subgroup of tumors, where low PD-L1 expression equated to lack of response.

CONCLUSIONS

Continuous RPPA-based measurements capture a broad dynamic range of PD-L1 expression in human specimens and heterogeneous concordance levels between antibody clones. This high throughput immunoassay can potentially identify subgroups of tumors in which low expression of PD-L1 equates to lack of response to treatment.

Proteomic Analysis of Cardioembolic and Large Artery Atherosclerotic Clots Using Reverse Phase Protein Array Technology Reveals Key Cellular Interactions Within Clot Microenvironments

Thrombus characteristics are dependent on clot composition, but identification of the etiology based on histological analysis has proved inconclusive. Identification of proteomic signatures may help to differentiate between clots of different etiologies such as cardioembolic, large artery atherosclerotic, and other known etiologies, information that could enhance an individualized medicine approach to secondary stroke prevention. In this study, total protein extracts from cardioembolic (n=25) and large artery atherosclerotic (n=23) thrombus specimens were arrayed in quadruplicate on nitrocellulose slides and immunostained for 31 proteins using a Dako Autostainer (Agilent Technologies, Inc., Santa Clara, USA). We quantified 31 proteins involved in platelet and/or endothelial function, inflammation, oxidative stress, and metabolism. Pathway analysis showed more heterogeneity and protein network interactions in the cardioembolic clots but no specific correlations with clot etiology. Reverse-phase protein arrays are a powerful tool for assessing cellular interactions within the clot microenvironment and may enhance understanding of clot formation and origination. This tool could be further explored to help in identifying stroke etiology in large vessel occlusion patients with embolic stroke of an undetermined source.

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.

Reverse Phase Protein Arrays

Reverse phase protein arrays (RPPA) are used to quantify proteins and protein posttranslational modifications in cellular lysates and body fluids. RPPA technology is suitable for biomarker discovery, protein pathway profiling, functional phenotype analysis, and drug discovery mechanism of action. The principles of RPPA technology are (a) immobilizing protein-containing specimens on a coated slide in discrete spots, (b) antibody recognition of proteins, (c) amplification chemistries to detect the protein-antibody complex, and (d) quantifying spot intensity. Construction of a RPPA begins with the robotic liquid transfer of protein-containing specimens from microtiter plates onto nitrocellulose-coated slides. The robotic arrayer deposits each sample as discrete spots in an array format. Specimens, controls, and calibrators are printed on each array, thus providing a complete calibrated assay on a single slide. Each RPPA slide is subsequently probed with catalyzed signal amplification chemistries and a single primary antibody, a secondary antibody, and either fluorescent or colorimetric dyes. The focus of this chapter is to describe RPPA detection and imaging using a colorimetric (diaminobenzidine (DAB)) detection strategy.

Integrative analysis of multi-platform reverse-phase protein array data for the pharmacodynamic assessment of response to targeted therapies

Reverse-phase protein array (RPPA) technology uses panels of high-specificity antibodies to measure proteins and protein post-translational modifications in cells and tissues. The approach offers sensitive and precise quantification of large numbers of samples and has thus found applications in the analysis of clinical and pre-clinical samples. For effective integration into drug development and clinical practice, robust assays with consistent results are essential. Leveraging a collaborative RPPA model, we set out to assess the variability between three different RPPA platforms using distinct instrument set-ups and workflows. Employing multiple RPPA-based approaches operated across distinct laboratories, we characterised a range of human breast cancer cells and their protein-level responses to two clinically relevant cancer drugs. We integrated multi-platform RPPA data and used unsupervised learning to identify protein expression and phosphorylation signatures that were not dependent on RPPA platform and analysis workflow. Our findings indicate that proteomic analyses of cancer cell lines using different RPPA platforms can identify concordant profiles of response to pharmacological inhibition, including when using different antibodies to measure the same target antigens. These results highlight the robustness and the reproducibility of RPPA technology and its capacity to identify protein markers of disease or response to therapy.

Protein array-based companion diagnostics in precision medicine

INTRODUCTION

The development of companion diagnostics (CDx) will increase efficacy and cost-benefit markedly, compared to the currently prevailing trial-and-error approach for treatment. Recent improvements in high-throughput protein technology have resulted in large amounts of predictive biomarkers that are potentially useful components of future CDx assays. Current high multiplex protein arrays are suitable for discovery-based approaches, while low-density and more simple arrays are suitable for use in point-of-care facilities.

AREA COVERED

This review discusses the technical platforms available for protein array focused CDx, explains the technical details of the platforms and provide examples of clinical use, ranging from multiplex arrays to low-density clinically applicable arrays. We thereafter highlight recent predictive biomarkers within different disease areas, such as oncology and autoimmune diseases. Lastly, we discuss some of the challenges connected to the implementation of CDx assays as point-of-care tests.

EXPERT OPINION

Recent advances in the field of protein arrays have enabled high-density arrays permitting large biomarker discovery studies, which are beneficial for future CDx assays. The density of protein arrays range from a single protein to proteome-wide arrays, allowing the discovery of protein signatures that may correlate with drug response. Protein arrays will undoubtedly play a key role in future CDx assays.

Phosphorylation Ratio Determination in Fresh-Frozen and Formalin-Fixed Paraffin-Embedded Tissue with Targeted Mass Spectrometry

Formalin-fixed paraffin-embedded (FFPE) tissues are routinely prepared and collected for diagnostics in pathology departments. These are, therefore, the most accessible research sources in pathology archives. In this study we investigated whether we can apply a targeted and quantitative parallel reaction monitoring (PRM) method for FFPE tissue samples in a sensitive and reproducible way. The feasibility of this technical approach was demonstrated for normal brain and glioblastoma multiforme tissues. Two methods were used: PRM measurement of a tryptic digest without phosphopeptide enrichment (Direct-PRM) and after Fe-NTA phosphopeptide enrichment (Fe-NTA-PRM). With these two methods, the phosphorylation ratio could be determined for four selected peptide pairs that originate from neuroblast differentiation-associated protein (AHNAK S5448-p), calcium/calmodulin-dependent protein kinase type II subunit delta (CAMK2D T337-p), eukaryotic translation initiation factor 4B (EIF4B S93-p), and epidermal growth factor receptor (EGFR S1166-p). In normal brain FFPE tissues, the Fe-NTA-PRM method enabled the quantification of targeted phosphorylated peptides with high reproducibility (CV < 14%). Our results indicate that formalin fixation does not impede relative quantification of a phospho-site and its phosphorylation ratio in FFPE tissues. The developed workflow combining these methods opens ways to study archival FFPE tissues for phosphorylation ratio determination in proteins.

Plasma-Derived Extracellular Vesicle Phosphoproteomics through Chemical Affinity Purification

The invasive nature and the pain caused to patients inhibit the routine use of tissue biopsy-based procedures for cancer diagnosis and surveillance. The analysis of extracellular vesicles (EVs) from biofluids has recently gained significant traction in the liquid biopsy field. EVs offer an essential "snapshot" of their precursor cells in real time and contain an information-rich collection of nucleic acids, proteins, lipids, and so on. The analysis of protein phosphorylation, as a direct marker of cellular signaling and disease progression could be an important stepping stone to successful liquid biopsy applications. Here we introduce a rapid EV isolation method based on chemical affinity called EVtrap (extracellular vesicle total recovery and purification) for the EV phosphoproteomics analysis of human plasma. By incorporating EVtrap with high-performance mass spectrometry (MS), we were able to identify over 16 000 unique peptides representing 2238 unique EV proteins from just 5 μL of plasma sample, including most known EV markers, with substantially higher recovery levels compared with ultracentrifugation. Most importantly, more than 5500 unique phosphopeptides representing almost 1600 phosphoproteins in EVs were identified using only 1 mL of plasma. Finally, we carried out a quantitative EV phosphoproteomics analysis of plasma samples from patients diagnosed with chronic kidney disease or kidney cancer, identifying dozens of phosphoproteins capable of distinguishing disease states from healthy controls. The study demonstrates the potential feasibility of our robust analytical pipeline for cancer signaling monitoring by tracking plasma EV phosphorylation.

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.

New HER2-negative breast cancer subtype responsive to anti-HER2 therapy identified

Purpose

HER2 signaling functional activity may be important to measure in addition to HER2 protein quantification when identifying patients eligible for HER2 therapies. A HER2 Signaling Function (CELx HSF) Test for HER2-negative patients uses patient’s live tumor cells on a biosensor to identify patients with abnormally high HER2-related signaling (HSFs+) likely to respond to anti-HER2 therapies.

Methods

The CELx HSF test was employed to: (1) characterize the sensitivity and specificity of the test to detect abnormal levels of HER2 signaling; (2) evaluate the inhibitory effectiveness of five different anti-HER2 therapies; (3) assess the correlation between CELx HSF test detection of abnormal HER2 signaling and response to HER2 therapy using xenograft models; and (4) confirm the prevalence of abnormal HER2 signaling amongst HER2-negative breast cancer patients (HER2−/HSFs+).

Results

HER2−/HSFs+ breast cancer patient samples were identified and showed sensitivity to five approved anti-HER2 therapies. Xenograft studies using both HER2+ and HER2− cell lines confirmed that CELx HER2 signaling status better predicts HER2 inhibitor efficacy than HER2 receptor status. In a study of 114 HER2-negative breast tumor patient samples, 27 (23.7%; 95% CI = 17–32%) had abnormal HER2 signaling (HSFs+). A ROC curve constructed with this dataset projects the CELx HSF Test would have greater than 90% sensitivity and specificity to detect the HER2−/HSFs+ patient population.

Conclusions

The CELx HSF test is a well-characterized functional biomarker assay capable of identifying dynamic HER2-driven signaling dysfunction in tumor cells from HER2-negative breast cancer patients. This test has demonstrated efficacy of various HER2 targeted therapies in live tumor cells from the HSFs+ population and correlated the test result to HER2 drug response in mouse xenograft studies. The proportion of HER2-negative breast cancer patients found to have abnormal HER2 signaling in a 114 patient sample study, 20–25%, is significant. A clinical trial to evaluate the efficacy of anti-HER2 therapies in this patient population is warranted.

Electronic supplementary material

The online version of this article (10.1007/s00432-020-03144-7) contains supplementary material, which is available to authorized users.

Validation of HER2 Amplification as a Predictive Biomarker for Anti–Epidermal Growth Factor Receptor Antibody Therapy in Metastatic Colorectal Cancer

Purpose

HER2 amplification has been implicated in resistance to therapy with anti–epidermal growth factor receptor antibodies (anti-EGFRabs) in metastatic colorectal cancer (mCRC). The purpose of the study was to validate the predictive impact of HER2 amplification in mCRC.

Patients and Methods

We analyzed patients with RAS/BRAF wild-type mCRC across two distinct cohorts. In cohort 1 (n = 98), HER2 amplification was tested in tumor tissue using dual in situ hybridization ( HER2 amplification: HER2/CEP17 ratio, 2.0 or greater). Cohort 2 (n = 70) included 16 patients with HER2 amplification and 54 HER2 nonamplified controls identified by next-generation sequencing ( HER2 amplification: four or more copies) who had received prior anti-EGFRabs. The primary end point was progression-free survival (PFS) on treatment with anti-EGFRab therapy, which was estimated and compared using the Kaplan-Meier method and log-rank test.

Results

Median PFS in cohort 1 on anti-EGFRab–based therapy was significantly shorter in patients with HER2 amplification compared with HER2 nonamplified patients (2.8 v 8.1 months, respectively; hazard ratio [HR], 7.05; 95% CI, 3.4 to 14.9; P < .001). These findings were validated in cohort 2 (median PFS for HER2 amplified v nonamplified: 2.8 v 9.3 months, respectively; HR, 10.66; 95% CI, 4.5 to 25.1; P < .001). The median PFS on therapy without anti-EGFRabs was similar among HER2-amplified and nonamplified patients in both cohort 1 (9.7 v 11.1 months, respectively; HR, 1.01; 95% CI, 0.4 to 2.4; P = .97) and cohort 2 (9.6 v 11.3 months, respectively; HR, 1.21; 95% CI, 0.5 to 3.1; P = .66). In multivariable analyses, HER2 amplification emerged as a single independent predictor of poor PFS on anti-EGFRab therapy in both cohort 1 (HR, 6.48; 95% CI, 3.1 to 13.6; P < .001) and cohort 2 (HR, 10.1; 95% CI, 4.3 to 23.9; P < .001).

Conclusion

HER2 amplification in RAS/RAF wild-type mCRC seems to be a predictive biomarker for lack of efficacy of anti-EGFRab therapy. Screening patients with RAS/BRAF wild-type mCRC for HER2 amplification should be considered before anti-EGFRab treatment to guide therapy and to identify patients for early referral to clinical trials.

Dynamic Regulation of Caveolin-1 Phosphorylation and Caveolae Formation by Mammalian Target of Rapamycin Complex 2 in Bladder Cancer Cells

The mammalian target of rapamycin (mTOR) and associated phosphatidylinositol 3-kinase/AKT/mTOR signaling pathway is commonly up-regulated in cancer, including bladder cancer. mTOR complex 2 (mTORC2) is a major regulator of bladder cancer cell migration and invasion, but the mechanisms by which mTORC2 regulates these processes are unclear. A discovery mass spectrometry and reverse-phase protein array-based proteomics dual approach was used to identify novel mTORC2 phosphoprotein targets in actively invading cancer cells. mTORC2 targets included focal adhesion kinase, proto-oncogene tyrosine-protein kinase Src, and caveolin-1 (Cav-1), among others. Functional testing shows that mTORC2 regulates Cav-1 localization and dynamic phosphorylation of Cav-1 on Y14. Regulation of Cav-1 activity by mTORC2 also alters the abundance of caveolae, which are specialized lipid raft invaginations of the plasma membrane associated with cell signaling and membrane compartmentalization. Our results demonstrate a unique role for mTORC2-mediated regulation of caveolae formation in actively migrating cancer cells.

[Personalized oncology]

CLINICAL ISSUE

Innovative next generation sequencing (NGS) technologies and comprehensive sequencing investigations in large patient cohorts have paved the way for very promising personalized treatment strategies based on the molecular characteristics of individual tumors.

STANDARD TREATMENT

Targeted therapies, such as tyrosine kinase inhibitors, antibodies and modern immunotherapeutic approaches are well established as monotherapy and combination therapy for many hematological and oncological malignancies.

TREATMENT INNOVATIONS

A plethora of innovative therapies targeting various components of intracellular signaling cascades and effective mechanisms against oncogenes as well as the availability of NGS technologies enable personalized cancer treatment based on the molecular profiles of individual tumors and genetic stratification, within clinical trials.

DIAGNOSTIC WORK-UP

Comprehensive genetic approaches including cancer gene panel sequencing, whole exome, whole genome and transcriptome sequencing are carried out to a varying extent and particularly in the academic setting.

PERFORMANCE

Principally, a comprehensive characterization of tumors in addition to DNA and RNA sequencing that also incorporates epigenetic, metabolomic, and proteomic alterations would be desirable. A comprehensive clinical implementation of integrative, multidimensional genetic typing is, however, currently not possible.

ACHIEVEMENTS

It remains to be demonstrated whether these approaches will translate into significantly better outcomes for patients and whether they can be increasingly implemented in the routine diagnostic work-up.

PRACTICAL RECOMMENDATIONS

The selection of diagnostic tools in individual cases and the extent of genomic analyses in the clinical context, need to take the availability of methods as well as the present clinical situation into account.

Utility of Reverse-Phase Protein Array for Refining Precision Oncology

Despite the early successes of targeted therapies and continuous improvements in next-generation sequencing technology over the last two decades, genomics-driven precision oncology has helped only a minority of cancer patients; thus treatment regimens are still not matched to the vast majority of cancer patients. It has become apparent that genomic profiling in itself is limited with respect to optimal selection of patients for targeted therapy. Proteomics-based approaches (in contrast to genomics-based and transcriptomics-based approaches) capture biological processes (e.g., diversity of protein expression patterns and post-translational modifications) directly contributing to cancer pathogenesis. This encourages incorporation of concordant proteomic analyses into the next stage of precision oncology. Reverse-phase protein array (RPPA) is well suited to pharmacodynamic analysis due to its ability to precisely map signaling status using limited amounts of clinical sample. In addition, the cost-effectiveness and rapid turnaround time of the RPPA platform offer a substantial advantage over existing molecular profiling technologies in a clinical setting. In this chapter, we begin by reviewing the current status of genomics-driven precision oncology, along with its limitations and challenges. Finally, we discuss the utility of RPPA technology as a means of improving precision oncology.

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.

Cofilin hyperactivation in HIV infection and targeting the cofilin pathway using an anti-α4β7 integrin antibody

A functional HIV cure requires immune reconstitution for lasting viremia control. A major immune dysfunction persisting in HIV infection is the impairment of T helper cell migration and homing to lymphoid tissues such as GALTs (gut-associated lymphoid tissues). ART (antiretroviral therapy) does not fully restore T cell motility for tissue repopulation. The molecular mechanism dictating this persistent T cell dysfunction is not understood. Cofilin is an actin-depolymerizing factor that regulates actin dynamics for T cell migration. Here, we demonstrate that blood CD4 T cells from HIV-infected patients (n = 193), with or without ART, exhibit significantly lower levels of cofilin phosphorylation (hyperactivation) than those from healthy controls (n = 100; ratio, 1.1:2.3; P < 0.001); cofilin hyperactivation is also associated with poor CD4 T cell recovery following ART. These results suggest an HIV-mediated systemic dysregulation of T cell motility that cannot be repaired solely by ART. We further demonstrate that stimulating blood CD4 T cells with an anti-human α₄β₇ integrin antibody can trigger signal transduction and modulate the cofilin pathway, partially restoring T cell motility in vitro. However, we also observed that severe T cell motility defect caused by high degrees of cofilin hyperactivation was not repairable by the anti-integrin antibody, demonstrating a mechanistic hindrance to restore immune functions in vivo. Our study suggests that cofilin is a key molecule that may need to be therapeutically targeted early for T cell tissue repopulation, immune reconstitution, and immune control of viremia.

Trastuzumab inhibits pituitary tumor cell growth modulating the TGFB/SMAD2/3 pathway

In pituitary adenomas, early recurrences and resistance to conventional pharmacotherapies are common, but the mechanisms involved are still not understood. The high expression of epidermal growth factor receptor 2 (HER2)/extracellular signal-regulated kinase (ERK1/2) signal observed in human pituitary adenomas, together with the low levels of the antimitogenic transforming growth factor beta receptor 2 (TBR2), encouraged us to evaluate the effect of the specific HER2 inhibition with trastuzumab on experimental pituitary tumor cell growth and its effect on the antiproliferative response to TGFB1. Trastuzumab decreased the pituitary tumor growth as well as the expression of ERK1/2 and the cell cycle regulators CCND1 and CDK4. The HER2/ERK1/2 pathway is an attractive therapeutic target, but its intricate relations with other signaling modulators still need to be unraveled. Thus, we investigated possible cross-talk with TGFB signaling, which has not yet been studied in pituitary tumors. In tumoral GH3 cells, co-incubation with trastuzumab and TGFB1 significantly decreased cell proliferation, an effect accompanied by a reduction in ERK1/2 phosphorylation, an increase of SMAD2/3 activation. In addition, through immunoprecipitation assays, a diminution of SMAD2/3-ERK1/2 and an increase SMAD2/3-TGFBR1 interactions were observed when cells were co-incubated with trastuzumab and TGFB1. These findings indicate that blocking HER2 by trastuzumab inhibited pituitary tumor growth and modulated HER2/ERK1/2 signaling and consequently the anti-mitogenic TGFB1/TBRs/SMADs cascade. The imbalance between HER2 and TGFBRs expression observed in human adenomas and the response to trastuzumab on experimental tumor growth may make the HER2/ERK1/2 pathway an attractive target for future pituitary adenoma therapy.

Highly Efficient Phosphoproteome Capture and Analysis from Urinary Extracellular Vesicles

Analysis of protein phosphorylation in extracellular vesicles (EVs) offers an unprecedented potential for understanding cancer signaling and early stage disease diagnosis. However, prior to the phosphoproteome analysis step, the isolation of EVs from biofluids remains a challenging issue to overcome due to the low yield and impurity from current isolation methods. Here, we carry out an extensive assessment of several EV isolation methods including a novel rapid isolation method EVTRAP for highly efficient capture of extracellular vesicles from human urine sample. We demonstrate that over 95% recovery yield can be consistently achieved by EVTRAP, a significant improvement over current standard techniques. We then applied EVTRAP to identify over 16 000 unique peptides representing 2000 unique EV proteins from 200 μL urine sample, including all known EV markers with substantially increased recovery levels over ultracentrifugation. Most importantly, close to 2000 unique phosphopeptides were identified from more than 860 unique phosphoproteins using 10 mL of urine. The data demonstrated that EVTRAP is a highly effective and potentially widely implementable clinical isolation method for analysis of EV protein phosphorylation.

Evaluation of the HER/PI3K/AKT Family Signaling Network as a Predictive Biomarker of Pathologic Complete Response for Patients With Breast Cancer Treated With Neratinib in the I-SPY 2 TRIAL

PURPOSE

In the I-SPY 2 TRIAL (Investigation of Serial Studies to Predict Your Therapeutic Response With Imaging and Molecular Analysis 2), the pan-erythroblastic oncogene B inhibitor neratinib was available to all hormone receptor (HR)/human epidermal growth factor receptor 2 (HER2) subtypes and graduated in the HR-negative/HER2-positive signature. We hypothesized that neratinib response may be predicted by baseline HER2 epidermal growth factor receptor (EGFR) signaling activation/phosphorylation levels independent of total levels of HER2 or EGFR proteins.

MATERIALS AND METHODS

Complete experimental and response data were available for between 130 and 193 patients. In qualifying analyses, which used logistic regression and treatment interaction analysis, 18 protein/phosphoprotein, 10 mRNA, and 12 DNA biomarkers that related to HER family signaling were evaluated. Exploratory analyses used Wilcoxon rank sum and t tests without multiple comparison correction.

RESULTS

HER pathway DNA biomarkers were either low prevalence or nonpredictive. In expression biomarker analysis, only one gene (STMN1) was specifically associated with response to neratinib in the HER2-negative subset. In qualifying protein/phosphoprotein analyses that used reverse phase protein microarrays, six HER family markers were associated with neratinib response. After analysis was adjusted for HR/HER2 status, EGFR Y1173 (pEGFR) showed a significant biomarker-by-treatment interaction (P = .049). Exploratory analysis of HER family signaling in patients with triple-negative (TN) disease found that activation of EGFR Y1173 (P = .005) and HER2 Y1248 (pHER2) (P = .019) were positively associated with pathologic complete response. Exploratory analysis in this pEGFR/pHER2-activated TN subgroup identified elevated levels of estrogen receptor α (P < .006) in these patients.

CONCLUSION

Activation of HER family phosphoproteins associates with response to neratinib, but only EGFR Y1173 and STMN1 appear to add value to the graduating signature. Activation of HER2 and EGFR in TN tumors may identify patients whose diseases respond to neratinib and implies that there is a subset of patients with TN disease who paradoxically exhibit HER family signaling activation and may achieve clinical benefit with neratinib; this concept must be validated in future studies.

Molecular Profiling of Patients with Pancreatic Cancer: Initial Results from the Know Your Tumor Initiative

Purpose: To broaden access to and implementation of precision medicine in the care of patients with pancreatic cancer, the Know Your Tumor (KYT) program was initiated using a turn-key precision medicine system. Patients undergo commercially available multiomic profiling to determine molecularly rationalized clinical trials and off-label therapies.Experimental Design: Tumor samples were obtained for 640 patients from 287 academic and community practices covering 44 states. College of American Pathologists/Clinical Laboratory Improvement Amendments-accredited laboratories were used for genomic, proteomic, and phosphoprotein-based molecular profiling.Results: Tumor samples were adequate for next-generation sequencing in 96% and IHC in 91% of patients. A tumor board reviewed the results for every patient and found actionable genomic alterations in 50% of patients (with 27% highly actionable) and actionable proteomic alterations (excluding chemopredictive markers) in 5%. Actionable alterations commonly found were in DNA repair genes (BRCA1/2 or ATM mutations, 8.4%) and cell-cycle genes (CCND1/2/3 or CDK4/6 alterations, 8.1%). A subset of samples was assessed for actionable phosphoprotein markers. Among patients with highly actionable biomarkers, those who received matched therapy (n = 17) had a significantly longer median progression-free survival (PFS) than those who received unmatched therapy [n = 18; PFS = 4.1 vs. 1.9 months; HR, 0.47; 95% confidence interval (CI): 0.24-0.94; P _adj = 0.03].Conclusions: A comprehensive precision medicine system can be implemented in community and academic settings, with highly actionable findings observed in over 25% of pancreatic cancers. Patients whose tumors have highly actionable alterations and receive matched therapy demonstrated significantly increased PFS. Our findings support further prospective evaluation of precision oncology in pancreatic cancer. Clin Cancer Res; 24(20); 5018-27. ©2018 AACR.

Reverse Phase Protein Microarrays

While genes and RNA encode information about cellular status, proteins are considered the engine of the cellular machine, as they are the effective elements that drive all cellular functions including proliferation, migration, differentiation, and apoptosis. Consequently, investigations of the cellular protein network are considered a fundamental tool for understanding cellular functions.Alteration of the cellular homeostasis driven by elaborate intra- and extracellular interactions has become one of the most studied fields in the era of personalized medicine and targeted therapy. Increasing interest has been focused on developing and improving proteomic technologies that are suitable for analysis of clinical samples. In this context, reverse-phase protein microarrays (RPPA) is a sensitive, quantitative, high-throughput immunoassay for protein analyses of tissue samples, cells, and body fluids.RPPA is well suited for broad proteomic profiling and is capable of capturing protein activation as well as biochemical reactions such as phosphorylation, glycosylation, ubiquitination, protein cleavage, and conformational alterations across hundreds of samples using a limited amount of biological material. For these reasons, RPPA represents a valid tool for protein analyses and generates data that help elucidate the functional signaling architecture through protein-protein interaction and protein activation mapping for the identification of critical nodes for individualized or combinatorial targeted therapy.

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.

Protein activation mapping of human sun-protected epidermis after an acute dose of erythemic solar simulated light

Ultraviolet radiation is an important etiologic factor in skin cancer and a better understanding of how solar stimulated light (SSL) affects signal transduction pathways in human skin which is needed in further understanding activated networks that could be targeted for skin cancer prevention. We utilized Reverse Phase Protein Microarray Analysis (RPPA), a powerful technology that allows for broad-scale and quantitative measurement of the activation/phosphorylation state of hundreds of key signaling proteins and protein pathways in sun-protected skin after an acute dose of two minimal erythema dose (MED) of SSL. RPPA analysis was used to map the altered cell signaling networks resulting from acute doses of solar simulated radiation (SSL). To that end, we exposed sun-protected skin in volunteers to acute doses of two MED of SSL and collected biopsies pre-SSL and post-SSL irradiation. Frozen biopsies were subjected to laser capture microdissection (LCM) and then assessed by RPPA. The activation/phosphorylation or total levels of 128 key signaling proteins and drug targets were selected for statistical analysis. Coordinate network-based analysis was performed on specific signaling pathways that included the PI3k/Akt/mTOR and Ras/Raf/MEK/ERK pathways. Overall, we found early and sustained activation of the PI3K-AKT-mTOR and MAPK pathways. Cell death and apoptosis-related proteins were activated at 5 and 24 h. Ultimately, expression profile patterns of phosphorylated proteins in the epidermal growth factor receptor(EGFR), AKT, mTOR, and other relevant pathways may be used to determine pharmacodynamic activity of new and selective topical chemoprevention agents administered in a test area exposed to SSL to determine drug-induced attenuation or reversal of skin carcinogenesis pathways.

Skin exposure to ultraviolet radiation leads to the activation of proteins involved in carcinogenic pathways. Janine Einspahr and Clara Curiel-Lewandrowski of the Arizona Cancer Center and colleagues in the US exposed normally ultraviolet protected skin of 12 individuals to two times the dose of solar-simulated light needed to induce redness. Skin biopsies were taken before and after exposure and 128 proteins known to be involved in key cancer signaling pathways were examined using ‘reverse phase protein microarray analysis’. They found early and sustained activation of multiple signaling pathways, in addition to activation of cell death and apoptosis-related proteins. The study may serve as a model for investigating the pathways involved in chronic or ultraviolet-induced carcinogenesis, which may ultimately lead to the development of targeted therapies to attenuate or reverse skin cancer pathways.

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.

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.

Precision oncology based on omics data: The NCT Heidelberg experience

Precision oncology implies the ability to predict which patients will likely respond to specific cancer therapies based on increasingly accurate, high-resolution molecular diagnostics as well as the functional and mechanistic understanding of individual tumors. While molecular stratification of patients can be achieved through different means, a promising approach is next-generation sequencing of tumor DNA and RNA, which can reveal genomic alterations that have immediate clinical implications. Furthermore, certain genetic alterations are shared across multiple histologic entities, raising the fundamental question of whether tumors should be treated by molecular profile and not tissue of origin. We here describe MASTER (Molecularly Aided Stratification for Tumor Eradication Research), a clinically applicable platform for prospective, biology-driven stratification of younger adults with advanced-stage cancer across all histologies and patients with rare tumors. We illustrate how a standardized workflow for selection and consenting of patients, sample processing, whole-exome/genome and RNA sequencing, bioinformatic analysis, rigorous validation of potentially actionable findings, and data evaluation by a dedicated molecular tumor board enables categorization of patients into different intervention baskets and formulation of evidence-based recommendations for clinical management. Critical next steps will be to increase the number of patients that can be offered comprehensive molecular analysis through collaborations and partnering, to explore ways in which additional technologies can aid in patient stratification and individualization of treatment, to stimulate clinically guided exploratory research projects, and to gradually move away from assessing the therapeutic activity of targeted interventions on a case-by-case basis toward controlled clinical trials of genomics-guided treatments.

Increased PDGFR-beta and VEGFR-2 protein levels are associated with resistance to platinum-based chemotherapy and adverse outcome of ovarian cancer patients

Despite frequent initial response rates of epithelial ovarian cancer to platinum-based chemotherapy the majority of patients develop drug resistance. Our aim was to evaluate differential expression of signaling-pathway proteins in platinum-sensitive versus platinum-resistant primary epithelial ovarian cancer specimens to identify predictive biomarkers for treatment response.

192 patients were studied comprising of independent training (n = 89) and validation (n = 103) cohorts. Full-length proteins were extracted from paraffin-embedded samples including multiple regions per tumor to account for intratumoral heterogeneity. Quantitative reverse-phase-protein-arrays were used to analyze protein and phospho-protein levels of 41 signaling molecules including growth-factor receptors, AKT and MAPK signaling pathways as well as angiogenesis and cell-adhesion.

Platinum-resistant ovarian cancers (56/192) demonstrated significantly higher intratumoral levels of the angiogenesis-associated growth-factor receptors PDGFR-beta and VEGFR2 compared to platinum-sensitive tumors. In addition, patients with high PDGFR-beta expression had significantly shorter overall and progression-free survival (HR 3.6 and 2.4; p < 0.001). The prognostic value of PDGFR-beta and VEGFR2 was confirmed in publicly available microarray-datasets.

High intratumoral levels of the angiogenesis-related growth-factor receptors PDGFR-beta and VEGFR2 might serve as novel predictive biomarkers to identify primary resistance to platinum-based chemotherapy. Those ovarian cancer patients might particularly benefit from additional anti-vascular therapy including anti-VEGF antibody or receptor tyrosine-kinase-inhibitor therapy.

Enrichment of PI3K-AKT-mTOR Pathway Activation in Hepatic Metastases from Breast Cancer

Purpose: Little is known about the molecular signatures associated with specific metastatic sites in breast cancer. Using comprehensive multi-omic molecular profiling, we assessed whether alterations or activation of the PI3K-AKT-mTOR pathway is associated with specific sites of breast cancer metastasis.Experimental Design: Next-generation sequencing-based whole-exome sequencing was coupled with reverse-phase protein microarray (RPPA) functional signaling network analysis to explore the PI3K-AKT-mTOR axis in 32 pretreated breast cancer metastases. RPPA-based signaling data were further validated in an independent cohort of 154 metastatic lesions from breast cancer and 101 unmatched primary breast tumors. The proportion of cases with PI3K-AKT-mTOR genomic alterations or signaling network activation were compared between hepatic and nonhepatic lesions.Results:PIK3CA mutation and activation of AKT (S473) and p70S6K (T389) were detected more frequently among liver metastases than nonhepatic lesions (P < 0.01, P = 0.056, and P = 0.053, respectively). However, PIK3CA mutations alone were insufficient in predicting protein activation (P = 0.32 and P = 0.19 for activated AKT and p70S6K, respectively). RPPA analysis of an independent cohort of 154 tumors confirmed the relationship between pathway activation and hepatic metastasis [AKT (S473), mTOR (S2448), and 4EBP1 (S65); P < 0.01, P = 0.02, and P = 0.01, respectively]. Similar results were also seen between liver metastases and primary breast tumors [AKT (S473) P < 0.01, mTOR (S2448) P < 0.01, 4EBP1 (S65) P = 0.01]. This signature was lost when primary tumors were compared with all metastatic sites combined.Conclusions: Breast cancer patients with liver metastasis may represent a molecularly homogenized cohort with increased incidence of PIK3CA mutations and activation of the PI3K-AKT-mTOR signaling network. Clin Cancer Res; 23(16); 4919-28. ©2017 AACR.

A functional signal profiling test for identifying a subset of HER2-negative breast cancers with abnormally amplified HER2 signaling activity

The results of clinical trials evaluating the efficacy of HER2 inhibitors in patients with breast cancer indicate that the correlation between HER2 receptor levels and patient outcomes is as low as 50%. The relatively weak correlation between HER2 status and response to HER2-targeting drugs suggests that measurement of HER2 signaling activity, rather than absolute HER2 levels, may more accurately diagnose HER2-driven breast cancer. A new diagnostic test, the CELx HER2 Signaling Profile (CELx HSP) test, is demonstrated to measure real-time HER2 signaling function in live primary cells. In the present study, epithelial cells extracted fresh from breast cancer patient tumors classified as HER2 negative (HER2-, n = 34 of which 33 were estrogen receptor positive) and healthy subjects (n = 16) were evaluated along with reference breast cancer cell lines (n = 19). Live cell response to specific HER2 agonists (NRG1b and EGF) and antagonist (pertuzumab) was measured. Of the HER2- breast tumor cell samples tested, 7 of 34 patients (20.5%; 95% CI = 10%-37%) had HER2 signaling activity that was characterized as abnormally high. Amongst the tumor samples there was no correlation between HER2 protein status (by cell cytometry) and HER2 signaling activity (hyperactive or normal) (Regression analysis P = 0.144, R2 = 0.068). One conclusion is that measurement of HER2 signaling activity can identify a subset of breast cancers with normal HER2 receptor levels with abnormally high levels of HER2 signaling. This result constitutes a new subtype of breast cancer that should be considered for treatment with HER2 pathway inhibitors.

How may targeted proteomics complement genomic data in breast cancer?

INTRODUCTION

Breast cancer (BC) is the most common female cancer in the world and was recently deconstructed in different molecular entities. Although most of the recent assays to characterize tumors at the molecular level are genomic-based, proteins are the actual executors of cellular functions and represent the vast majority of targets for anticancer drugs. Accumulated data has demonstrated an important level of quantitative and qualitative discrepancies between genomic/transcriptomic alterations and their protein counterparts, mostly related to the large number of post-translational modifications. Areas covered: This review will present novel proteomics technologies such as Reverse Phase Protein Array (RPPA) or mass-spectrometry (MS) based approaches that have emerged and that could progressively replace old-fashioned methods (e.g. immunohistochemistry, ELISA, etc.) to validate proteins as diagnostic, prognostic or predictive biomarkers, and eventually monitor them in the routine practice. Expert commentary: These different targeted proteomic approaches, able to complement genomic data in BC and characterize tumors more precisely, will permit to go through a more personalized treatment for each patient and tumor.

A pilot study exploring the molecular architecture of the tumor microenvironment in human prostate cancer using laser capture microdissection and reverse phase protein microarray

The cross-talk between tumor epithelium and surrounding stromal/immune microenvironment is essential to sustain tumor growth and progression and provides new opportunities for the development of targeted treatments focused on disrupting the tumor ecology. Identification of novel approaches to study these interactions is of primary importance. Using laser capture microdissection (LCM) coupled with reverse phase protein microarray (RPPA) based protein signaling activation mapping we explored the molecular interconnection between tumor epithelium and surrounding stromal microenvironment in 18 prostate cancer (PCa) specimens. Four specimen-matched cellular compartments (normal-appearing epithelium and its adjacent stroma, and malignant epithelium and its adjacent stroma) were isolated for each case. The signaling network analysis of the four compartments unraveled a number of molecular mechanisms underlying the communication between tumor cells and stroma in the context of the tumor microenvironment. In particular, differential expression of inflammatory mediators like IL-8 and IL-10 by the stroma cells appeared to modulate specific cross-talks between the tumor cells and surrounding microenvironment.

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.

Using reverse-phase protein arrays as pharmacodynamic assays for functional proteomics, biomarker discovery, and drug development in cancer

The majority of the targeted therapeutic agents in clinical use target proteins and protein function. Although DNA and RNA analyses have been used extensively to identify novel targets and patients likely to benefit from targeted therapies, these are indirect measures of the levels and functions of most therapeutic targets. More importantly, DNA and RNA analysis is ill-suited for determining the pharmacodynamic effects of target inhibition. Assessing changes in protein levels and function is the most efficient way to evaluate the mechanisms underlying sensitivity and resistance to targeted agents. Understanding these mechanisms is necessary to identify patients likely to benefit from treatment and to develop rational drug combinations to prevent or bypass therapeutic resistance. There is an urgent need for a robust approach to assess protein levels and protein function in model systems and across patient samples. While "shot gun" mass spectrometry can provide in-depth analysis of proteins across a limited number of samples, and emerging approaches such as multiple reaction monitoring have the potential to analyze candidate markers, mass spectrometry has not entered into general use because of the high cost, requirement of extensive analysis and support, and relatively large amount of material needed for analysis. Rather, antibody-based technologies, including immunohistochemistry, radioimmunoassays, enzyme-linked immunosorbent assays (ELISAs), and more recently protein arrays, remain the most common approaches for multiplexed protein analysis. Reverse-phase protein array (RPPA) technology has emerged as a robust, sensitive, cost-effective approach to the analysis of large numbers of samples for quantitative assessment of key members of functional pathways that are affected by tumor-targeting therapeutics. The RPPA platform is a powerful approach for identifying and validating targets, classifying tumor subsets, assessing pharmacodynamics, and identifying prognostic and predictive markers, adaptive responses and rational drug combinations in model systems and patient samples. Its greatest utility has been realized through integration with other analytic platforms such as DNA sequencing, transcriptional profiling, epigenomics, mass spectrometry, and metabolomics. The power of the technology is becoming apparent through its use in pathology laboratories and integration into trial design and implementation.

The Obama Administration's Cancer Moonshot: A Call for Proteomics

The Cancer Moonshot Program has been launched and represents a potentially paradigm-shifting initiative with the goal to implement a focused national effort to double the rate of progress against cancer. The placement of precision medicine, immunotherapy, genomics, and combination therapies was placed at the central nexus of this initiative. Although we are extremely enthusiastic about the goals of the program, it is time we meet this revolutionary project with equally bold and cutting-edge ideas: it is time we move firmly into the postgenome era and provide the necessary resources to propel and seize on innovative recent gains in the field of proteomics required for it to stand on equal footing in this narrative as a combined, synergistic engine for molecular profiling. After all, although the genome is the information archive, it is the proteins that actually do the work of the cell and represent the structural cellular machinery. It is the proteins that comprise most of the biomarkers that are measured to detect cancers, constitute the antigens that drive immune response and inter- and intracellular communications, and it is the proteins that are the drug targets for nearly every targeted therapy that is being evaluated in cancer trials today. We believe that a combined systems biology view of the tumor microenvironment that orients cancer studies back to the functional proteome, phosphoproteome, and biochemistry of the cell will be essential to deliver on the promise of the Cancer Moonshot Program. Clin Cancer Res; 22(18); 4556-8. ©2016 AACR.

Emerging anti-cancer antibodies and combination therapies targeting HER3/ERBB3

Cancer progression depends on stepwise accumulation of oncogenic mutations and a select group of growth factors essential for tumor growth, metastasis and angiogenesis. Agents blocking the epidermal growth factor receptor (EGFR, also called HER1 and ERBB1) and the co-receptor called HER2/ERBB2 have been approved over the last decade as anti-cancer drugs. Because the catalytically defective member of the family, HER3/ERBB3, plays critical roles in emergence of resistance of carcinomas to various drugs, current efforts focus on antibodies and other anti-HER3/ERBB3 agents, which we review herein with an emphasis on drug combinations and some unique biochemical features of HER3/ERBB3.

Deciphering the complexity of the cancer proteome for diagnostic applications

The proteome is the most functional component encoded in the genome, yet most features of the proteome that are deregulated in cancer cannot be predicted from genomic analysis alone. These include post-translational modifications (PTMs), sub-cellular localization, networks and circuitry, formation of complexes, and functional activity, all of which could play a role or be affected as part of tumorigenesis. Thus, there is a substantial opportunity to elucidate protein alterations in cancer and to translate knowledge into diagnostics and therapeutics. The progress made in mining the cancer proteome for diagnostic applications and the path forward are herein reviewed.