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

BAG2, MAD2L1, and MDK are cancer-driver genes and candidate targets for novel therapies in malignant pleural mesothelioma

Malignant pleural mesothelioma (MPM) is an aggressive cancer with a poor prognosis and the identification of novel druggable targets is urgently needed. In previous work, we identified 15 deregulated genes highly expressed in MPM tissues and correlated with a poor prognosis. Here, we validated these findings on an independent dataset of 211 MPM patients (EGA, EGAD00001001915) and on a panel of MPM cell lines. Furthermore, we carried out in vitro gene silencing followed by proliferation, cytotoxicity, caspase, and migration assays to define whether these targets could be cancer-driver genes. We ended up with three novel candidates (i.e., BAG2, MAD2L1, and MDK), whose encoded proteins could be exploited as druggable targets. Moreover, of novelty, immunohistochemistry analysis on tissues revealed that the overexpression of BAG2 and MAD2L1 could differentiate MPM from RMP patients. Furthermore, when we tested Neratinib (an inhibitor of MAD2L1) and iMDK (an inhibitor of MDK) we found that they are effective on MPM cells, in part phenocopying the effects of MAD2L1 and MDK gene silencing. In summary, in the present work, we report that BAG2, MAD2L1, and MDK are bona fide cancer-driver genes for MPM worth of further studies.

Proteomics based selection achieves complete response to HER2 therapy in HER2 IHC 0 breast cancer

Recent trials have shown the efficacy of trastuzumab deruxtecan (T-DXd) in HER2-negative patients, but there is not yet a way to identify which patients will best respond, especially with the inability of current HER2 IHC and FISH assays to accurately determine HER2 expression in the unamplified setting. Here, we present a heavily pre-treated patient with triple-negative breast cancer (HER2 IHC 0 who had a complete response to T-DXd. In this case, we used a CLIA-certified reverse-phase protein array-based proteomic assay (RPPA) to determine that the patient had moderate HER2 protein expression (HER2Total 2+, 42%) and activation (HER2Y1248 1+, 23%). Using these results, we determined that the patient may benefit from T-Dxd despite being traditionally qualified as HER2 IHC 0. These findings highlight the potential for proteomics-based assays that may more accurately quantitate HER2 and (its activation) in the HER2 unamplified/IHC 0 setting to better select patients whose tumors are classically molecularly defined as HER2 IHC 0, but still could respond to HER2-directed therapy, and give patients access to therapies which for which they otherwise would not be eligible.

Protein biomarkers for subtyping breast cancer and implications for future research: a 2024 update

INTRODUCTION

Breast cancer subtyping is used clinically for diagnosis, prognosis, and treatment decisions. Subtypes are categorized by cell of origin, histomorphology, gene expression signatures, hormone receptor status, and/or protein levels. Categorizing breast cancer based on gene expression signatures aids in assessing a patient's recurrence risk. Protein biomarkers, on the other hand, provide functional data for selecting therapies for primary and recurrent tumors. We provide an update on protein biomarkers in breast cancer subtypes and their application in prognosis and therapy selection.

AREAS COVERED

Protein pathways in breast cancer subtypes are reviewed in the context of current protein-targeted treatment options. PubMed, Science Direct, Scopus, and Cochrane Library were searched for relevant studies between 2017 and 17 August 2024.

EXPERT OPINION

Post-translationally modified proteins and their unmodified counterparts have become clinically useful biomarkers for defining breast cancer subtypes from a therapy perspective. Tissue heterogeneity influences treatment outcomes and disease recurrence. Spatial profiling has revealed complex cellular subpopulations within the breast tumor microenvironment. Deciphering the functional relationships between and within tumor clonal cell populations will further aid in defining breast cancer subtypes and create new treatment paradigms for recurrent, drug resistant, and metastatic disease.

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.

Targeting HER2/HER3 co-mutations in metastatic breast cancer: Case reports of exceptional responders to trastuzumab and pertuzumab therapy

BACKGROUND

Overexpression of HER2 plays an important role in cancer progression and is the target of multiple therapies in HER2-positive breast cancer. Recent studies have also highlighted the presence of activating mutations in HER2, and HER3 that are predicted to enhance HER2 downstream pathway activation in a HER2-dependent manner.

METHODS

In this report, we present two exceptional responses in hormone receptor-positive, HER2-nonamplified, HER2/HER3 co-mutated metastatic breast cancer patients who were treated with the anti-HER2-directed monoclonal antibodies, trastuzumab and pertuzumab.

RESULTS

Both patients acheived exceptional responses to treatment, suggesting that combined trastuzumab, pertuzumab, and endocrine therapy could be a highly effective therapy for these patients and our observations could help prioritize trastuzumab deruxtecan as an early therapeutic choice for patients whose cancers have activating mutations in HER2.

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.

Neratinib for HER2-positive breast cancer with an overlooked option

Positive human epidermal growth factor receptor 2 (HER2) expression is associated with an increased risk of metastases especially those to the brain in patients with advanced breast cancer (BC). Neratinib as a tyrosine kinase inhibitor can prevent the transduction of HER1, HER2 and HER4 signaling pathways thus playing an anticancer effect. Moreover, neratinib has a certain efficacy to reverse drug resistance in patients with BC with previous HER2 monoclonal antibody or targeted drug resistance. Neratinib, as monotherapy and in combination with other therapies, has been tested in the neoadjuvant, adjuvant, and metastatic settings. Neratinib with high anticancer activity is indicated for the prolonged adjuvant treatment of HER2-positive early BC, or in combination with other drugs including trastuzumab, capecitabine, and paclitaxel for the treatment of advanced HER2-positive BC especially cancers with central nervous system (CNS) metastasis to reduce the risk of BC recurrence. This article reviewed the pharmacological profiles, efficacy, safety, tolerability, and current clinical trials pertaining to neratinib, with a particular focus on the use of neratinib in patients with metastatic breast cancer (MBC) involving the CNS. We further discussed the use of neratinib for HER2-negative and HER2-mutant breast cancers, and mechanisms of resistance to neratinib. The current evidence suggests that neratinib has promising efficacy in patients with BC which is at least non-inferior compared to previous therapeutic regimens. The most common AE was diarrhea, and the incidence, severity and duration of neratinib-related grade 3 diarrhea can be reduced with loperamide. Of note, neratinib has the potential to effectively control and prevent brain metastasis in patients with advanced BC, providing a therapeutic strategy for HER2-positive BC.

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.

Precision Breast Cancer Medicine: Early Stage Triple Negative Breast Cancer-A Review of Molecular Characterisation, Therapeutic Targets and Future Trends

Personalised approaches to the management of all solid tumours are increasing rapidly, along with wider accessibility for clinicians. Advances in tumour characterisation and targeted therapies have placed triple-negative breast cancers (TNBC) at the forefront of this approach. TNBC is a highly heterogeneous disease with various histopathological features and is driven by distinct molecular alterations. The ability to tailor individualised and effective treatments for each patient is of particular importance in this group due to the high risk of distant recurrence and death. The mainstay of treatment across all subtypes of TNBC has historically been cytotoxic chemotherapy, which is often associated with off-target tissue toxicity and drug resistance. Neoadjuvant chemotherapy is commonly used as it allows close monitoring of early treatment response and provides valuable prognostic information. Patients who achieve a complete pathological response after neoadjuvant chemotherapy are known to have significantly improved long-term outcomes. Conversely, poor responders face a higher risk of relapse and death. The identification of those subgroups that are more likely to benefit from breakthroughs in the personalised approach is a challenge of the current era where several targeted therapies are available. This review presents an overview of contemporary practice, and promising future trends in the management of early TNBC. Platinum chemotherapy, DNA damage response (DDR) inhibitors, immune checkpoint inhibitors, inhibitors of the PI3K-AKT-mTOR, and androgen receptor (AR) pathways are some of the increasingly studied therapies which will be reviewed. We will also discuss the growing evidence for less-developed agents and predictive biomarkers that are likely to contribute to the forthcoming advances in this field. Finally, we will propose a framework for the personalised management of TNBC based upon the integration of clinico-pathological and molecular features to ensure that long-term outcomes are optimised.

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.

RAB5A expression is a predictive biomarker for trastuzumab emtansine in breast cancer

HER2 is a predictive biomarker for HER2-targeted therapeutics. For antibody-drug conjugates (ADCs; e.g., trastuzumab emtansine (T-DM1)), HER2 is utilized as a transport gate for cytotoxic agents into the cell. ADC biomarkers may therefore be more complex, also reflecting the intracellular drug transport. Here we report on a positive correlation between the early endosome marker RAB5A and T-DM1 sensitivity in five HER2-positive cell lines. Correlation between RAB5A expression and T-DM1 sensitivity is confirmed in breast cancer patients treated with trastuzumab emtansine/pertuzumab in the I-SPY2 trial (NCT01042379), but not in the trastuzumab/paclitaxel control arm. The clinical correlation is further verified in patients from the KAMILLA trial (NCT01702571). In conclusion, our results suggest RAB5A as a predictive biomarker for T-DM1 response and outline proteins involved in endocytic trafficking as predictive biomarkers for ADCs.

Neoadjuvant T-DM1/pertuzumab and paclitaxel/trastuzumab/pertuzumab for HER2+ breast cancer in the adaptively randomized I-SPY2 trial

HER2-targeted therapy dramatically improves outcomes in early breast cancer. Here we report the results of two HER2-targeted combinations in the neoadjuvant I-SPY2 phase 2 adaptive platform trial for early breast cancer at high risk of recurrence: ado-trastuzumab emtansine plus pertuzumab (T-DM1/P) and paclitaxel, trastuzumab and pertuzumab (THP). Eligible women have >2.5 cm clinical stage II/III HER2+ breast cancer, adaptively randomized to T-DM1/P, THP, or a common control arm of paclitaxel/trastuzumab (TH), followed by doxorubicin/cyclophosphamide, then surgery. Both T-DM1/P and THP arms 'graduate' in all subtypes: predicted pCR rates are 63%, 72% and 33% for T-DM1/P (n = 52), THP (n = 45) and TH (n = 31) respectively. Toxicity burden is similar between arms. Degree of HER2 pathway signaling and phosphorylation in pretreatment biopsy specimens are associated with response to both T-DM1/P and THP and can further identify highly responsive HER2+ tumors to HER2-directed therapy. This may help identify patients who can safely de-escalate cytotoxic chemotherapy without compromising excellent outcome.

Laser Capture Proteomics: spatial tissue molecular profiling from the bench to personalized medicine

INTRODUCTION

Laser Capture Microdissection (LCM) uses a laser to isolate, or capture, specific cells of interest in a complex heterogeneous tissue section, under direct microscopic visualization. Recently, there has been a surge of publications using LCM for tissue spatial molecular profiling relevant to a wide range of research topics.

AREAS COVERED

We summarize the many advances in tissue Laser Capture Proteomics (LCP) using mass spectrometry for discovery, and protein arrays for signal pathway network mapping. This review emphasizes: a) transition of LCM phosphoproteomics from the lab to the clinic for individualized cancer therapy, and b) the emerging frontier of LCM single cell molecular analysis combining proteomics with genomic, and transcriptomic analysis. The search strategy was based on the combination of MeSH terms with expert refinement.

EXPERT OPINION

LCM is complemented by a rich set of instruments, methodology protocols, and analytical A.I. (artificial intelligence) software for basic and translational research. Resolution is advancing to the tissue single cell level. A vision for the future evolution of LCM is presented. Emerging LCM technology is combining digital and AI guided remote imaging with automation, and telepathology, to a achieve multi-omic profiling that was not previously possible.

A protein interaction landscape of breast cancer

[Figure: see text].

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.

PI3K and MAPK Pathways as Targets for Combination with the Pan-HER Irreversible Inhibitor Neratinib in HER2-Positive Breast Cancer and TNBC by Kinome RNAi Screening

Human epidermal growth factor receptor (EGFR) 2 (HER2) is overexpressed/amplified in about 25% of all breast cancers, and EGFR is overexpressed in up to 76% and amplified in up to 24% of triple-negative breast cancers (TNBC). Here, we aimed to identify inhibitors that may enhance the anti-tumor activity of neratinib for HER2+ breast cancer and TNBC. By conducting a non-biased high-throughput RNA interference screening, we identified PI3K/AKT/mTOR and MAPK as two potential inhibitory synergistic canonical pathways. We confirmed that everolimus (mTOR inhibitor) and trametinib (MEK inhibitor) enhances combinatorial anti-proliferative effects with neratinib under anchorage-independent growth conditions (p < 0.05). Compared to single agent neratinib, the combination therapies significantly enhanced tumor growth inhibition in both SUM190 HER2+ breast cancer (neratinib plus everolimus, 77%; neratinib plus trametinib, 77%; p < 0.0001) and SUM149 TNBC (neratinib plus everolimus, 71%; neratinib plus trametinib, 81%; p < 0.0001) xenograft models. Compared to single-agent neratinib, everolimus, or trametinib, both everolimus plus neratinib and trametinib plus neratinib significantly suppressed proliferation marker Ki67 and enhanced antitumor efficacy by activating the apoptosis pathway shown by increased Bim and cleaved-PARP expression. Taken together, our data justify new neratinib-based combinations for both HER2+ breast cancer and TNBC.

Mechanism of action biomarkers predicting response to AKT inhibition in the I-SPY 2 breast cancer trial

The AKT inhibitor MK2206 (M) was evaluated in I-SPY 2 and graduated in the HER2+, HR−, and HR− HER2+ signatures. We hypothesized that AKT signaling axis proteins/genes may specifically predict response to M and tested 26 phospho-proteins and 10 genes involved in AKT-mTOR-HER signaling; in addition, we tested 9 genes from a previous study in the metastatic setting. One hundred and fifty patients had gene expression data from pretreatment biopsies available for analysis (M: 94, control: 56) and 138 had protein data (M: 87, control: 51). Logistic modeling was used to assess biomarker performance in pre-specified analysis. In general, phospho-protein biomarkers of activity in the AKT-mTOR-HER pathway appeared more predictive of response to M than gene expression or total protein biomarkers in the same pathway; however, the nature of the predictive biomarkers differed in the HER2+ and TN groups. In the HER2+ subset, patients achieving a pCR in M had higher levels of multiple AKT kinase substrate phospho-proteins (e.g., pmTOR, pTSC2). In contrast, in the TN subset responding patients had lower levels of AKT pathway phospho-proteins, such as pAKT, pmTOR, and pTSC2. Pathway mutations did not appear to account for these associations. Additional exploratory whole-transcriptome analysis revealed immune signaling as strongly associated with response to M in the HER2+ subset. While our sample size is small, these results suggest that the measurement of particular AKT kinase substrate phospho-proteins could be predictive of MK2206 efficacy in both HER2+ and TN tumors and that immune signaling may play a role in response in HER2+ patients.

Trastuzumab effects depend on HER2 phosphorylation in HER2-negative breast cancer cell lines

The breast cancer (BC) biomarker HER2 (Human Epidermal Receptor 2) is overexpressed in 25% of BC. Only patients with HER2-positive tumors receive HER2-targeting therapies, like trastuzumab (Herceptin). However, some women with a HER2-negative BC could benefit from trastuzumab. This could be explained by the activation/phosphorylation of HER2 that can be recognized by trastuzumab. The aim of this study is to examine trastuzumab effects on HER2 phosphorylation at tyrosine Y877 (pHER2Y877). HER2 and pHER2Y877 status were evaluated in a cohort of BC patients representative of molecular subtypes distribution (n = 497) and in a series of BC cell lines (n = 7). Immunohistochemistry against pHER2Y877 was performed on tissue micro arrays. Cellular proliferation assays were performed on BC cell lines presenting different combinations of HER2 and pHER2Y877 status and treated with increasing doses of trastuzumab (0-150 μg/ml). The prevalence of pHER2Y877 in this cohort was 6%. Nearly 5% of patients with HER2-negative tumors (n = 406, 82%) overexpressed pHER2Y877. Among triple negative BC patients (n = 39, 8%), 7.7% expressed pHER2Y877. Trastuzumab treatment decreased cell proliferation in HER2-/pHER2Y877+ BC cell lines, to an extent comparable to what occurs in HER2+ cell lines, but did not affect HER2-/pHER2Y877- cell lines. Trastuzumab sensitivity in HER2-/pHER2Y877+ cell line is specific to HER2 tyrosine 877 phosphorylation. Hence, with further confirmation in a bigger cohort, trastuzumab treatment could be envisaged as a treatment option to women presenting with HER2-/pHER2+ tumors, representing more than 1000 BC women in Canada in 2019.

Utilization of Proteomic Technologies for Precision Oncology Applications

Genomic analysis of tumor specimens has revealed that cancer is fundamentally a proteomic disease at the functional level: driven by genomically defined derangements, but selected for in the proteins that are encoded and the aberrant activation of signaling and biochemical networks. This activation is measured by posttranslational modifications such as phosphorylation and other modifications that modulate cellular signaling, and these events cannot be effectively measured by genomic analysis alone. Moreover, these signaling networks by and large represent the targets for many FDA-approved and experimental molecularly targeted therapeutics. Consequently, it is important that we consider new classification schemas for oncology based not on tumor site of origin or histology under the microscope but on the functional protein signaling architecture. There are numerous proteomic technologies that could be discussed from a purely technological standpoint, but this chapter will concentrate on an overview of the main proteomic technologies available for conducting protein pathway activation analysis of clinical specimens such as multiplex immunoassays, phospho-specific flow cytometry, reverse phase protein microarrays, quantitative immunohistochemistry, and mass spectrometry. This chapter will focus on the application of these technologies to cancer-based clinical studies evaluating prognostic/predictive markers or for stratifying patients to personalized treatments.

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.